MDPI - Publisher of Open Access Journals

20 pages, 7017 KB

Open AccessArticle

Boron-Functionalised exo-Norbornene Monomers for ROMP: Toward Coordination-Active Poly(norbornene-B-arylene-dioxaborepine)s

by Jerzy Garbarek, Mariusz Majchrzak and Maciej Kubicki

Molecules 2026, 31(18), 3151; https://doi.org/10.3390/molecules31183151 (registering DOI) - 8 Sep 2026

Abstract

A series of boron-functionalised exo-norbornene monomers bearing boronic ester groups were synthesised via a condensation reaction and subsequently polymerised through ring-opening metathesis polymerisation (ROMP) to afford well-defined poly(norbornene-B-arylene-dioxaborepine)s. The incorporation of Lewis acidic boron centres into the norbornene-derived polymer backbone enables access [...] Read more.

A series of boron-functionalised exo-norbornene monomers bearing boronic ester groups were synthesised via a condensation reaction and subsequently polymerised through ring-opening metathesis polymerisation (ROMP) to afford well-defined poly(norbornene-B-arylene-dioxaborepine)s. The incorporation of Lewis acidic boron centres into the norbornene-derived polymer backbone enables access to coordination-active macromolecular systems with tuneable interactions towards nucleophilic species. The resulting polymers demonstrate enhanced structural definition and stability, thereby confirming the robustness of the synthetic approach and the successful incorporation of boron functionalities into ROMP-derived architectures. This work establishes a general and efficient strategy for the preparation of boron-containing ROMP polymers, providing a versatile platform for the development of coordination-responsive polymeric materials. Full article

(This article belongs to the Special Issue Latest Review on Cyclizations and Ring-Opening Reactions in Organic Chemistry)

► Show Figures

Figure 1

28 pages, 1475 KB

Open AccessReview

Artificial Intelligence for Early Prediction and Diagnosis of Neonatal Sepsis: Current Evidence, Challenges, and Future Directions

by Aikaterini I. Nikolaou, Niki Dermitzaki, Nikitas Chatzigiannis, Maria Baltogianni, Nikolaos G. Papanikolaou, Sevastianos Geitonas, Georgia Christiana Grantzi and Vasileios Giapros

Appl. Sci. 2026, 16(18), 8912; https://doi.org/10.3390/app16188912 (registering DOI) - 8 Sep 2026

Abstract

Neonatal sepsis remains a major cause of morbidity and mortality worldwide, while timely diagnosis continues to be challenging because of nonspecific clinical manifestations and limitations of conventional diagnostic methods. Recent advances in artificial intelligence (AI) have created new opportunities for the early prediction [...] Read more.

Neonatal sepsis remains a major cause of morbidity and mortality worldwide, while timely diagnosis continues to be challenging because of nonspecific clinical manifestations and limitations of conventional diagnostic methods. Recent advances in artificial intelligence (AI) have created new opportunities for the early prediction and diagnosis of neonatal sepsis through the analysis of large and complex clinical datasets. This structured narrative review summarizes current evidence regarding AI-based approaches for neonatal sepsis prediction and diagnosis. A literature search of PubMed, Scopus, and Google Scholar identified studies evaluating machine learning, deep learning, and advanced predictive analytics using clinical, laboratory, physiological, electronic health record, and multi-omics data. Current evidence suggests that AI models, particularly ensemble learning, gradient boosting, and deep learning approaches, can achieve promising predictive performance and identify infants at increased risk of sepsis hours before conventional clinical recognition. Continuous physiological monitoring and multimodal data integration appear particularly promising for real-time prediction. However, important challenges remain, including limited external validation, small and heterogeneous datasets, concerns regarding interpretability, and unresolved ethical and regulatory issues. Future progress will depend on multicenter collaboration, explainable AI frameworks, federated learning, and multimodal predictive models. Although current evidence supports the predictive potential of AI-based models, prospective multicenter validation and clinical impact studies are required before improvements in neonatal clinical outcomes can be established. Artificial intelligence has the potential to become a valuable clinical decision support tool to support early sepsis recognition and precision neonatal care. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

► Show Figures

Figure 1

19 pages, 806 KB

Open AccessArticle

Low Serum C-Peptide and Albuminuria Severity in Type 2 Diabetes Mellitus: A Cross-Sectional Study

by Bektas Isik and Bekir Tamer Tetiker

J. Clin. Med. 2026, 15(18), 6950; https://doi.org/10.3390/jcm15186950 (registering DOI) - 8 Sep 2026

Abstract

Background/Objectives: Lower serum C-peptide, reflecting reduced beta-cell reserve, has been linked to diabetic complications, but whether these associations are independent of diabetes duration and glycaemic control is unclear. The objective of this study was to determine which microvascular and macrovascular complications of type [...] Read more.

Background/Objectives: Lower serum C-peptide, reflecting reduced beta-cell reserve, has been linked to diabetic complications, but whether these associations are independent of diabetes duration and glycaemic control is unclear. The objective of this study was to determine which microvascular and macrovascular complications of type 2 diabetes mellitus (T2DM) remain associated with fasting C-peptide after adjustment for these factors. Methods: In this single-centre, cross-sectional study with consecutive prospective enrolment, non-pregnant adults with an established diagnosis of T2DM attending routine outpatient follow-up were eligible; those with pancreatic malignancy or exocrine pancreatic insufficiency, monogenic or autoimmune diabetes, or acute hyperglycaemic crises were excluded. A total of 590 patients were stratified by fasting C-peptide into insufficient (<1.0 ng/mL; n = 35), borderline (1.0–1.8 ng/mL; n = 212) and normal/high (≥1.8 ng/mL; n = 343) groups. Logistic regression adjusted for age, sex, diabetes duration, HbA1c and body mass index assessed each complication. Receiver operating characteristic analysis using DeLong’s test assessed incremental discrimination. Results: In the unadjusted analyses, every complication was more frequent at lower C-peptide. After adjustment, C-peptide was not associated with the presence of albuminuria (insufficient versus normal/high, odds ratio 1.60, 95% CI 0.16–15.86) but was strongly associated with its severity: for severely increased or nephrotic-range albuminuria, the adjusted odds ratios were 13.47 (5.33–34.07) and 6.90 (3.83–12.44) in the insufficient and borderline groups (both p < 0.001). Adding C-peptide to a model of diabetes duration, HbA1c and fasting glucose was associated with a statistically significant, but modest, improvement in discrimination for severe albuminuria (area under the curve of 0.748 to 0.783; ΔAUC = 0.035, p = 0.027). Associations with macrovascular complications were present in the unadjusted analyses but were substantially attenuated after adjustment and no longer statistically significant, except for peripheral arterial disease and foot ulcer, which remained associated with insufficient C-peptide in models based on small numbers of events and should be regarded as exploratory. Conclusions: Low C-peptide was independently associated with the severity of albuminuria rather than its presence and was associated with a modest incremental improvement in discrimination. These exploratory findings suggest that C-peptide, an inexpensive and widely available measurement, may provide information associated with advanced diabetic kidney disease; prospective, externally validated studies are needed before clinical application. Full article

(This article belongs to the Special Issue Diabetes and Its Complications: New Perspectives and Clinical Updates)

► Show Figures

Figure 1

14 pages, 1795 KB

Open AccessArticle

News Fluorescence-Based Polarization Immunoassays as a Frontline Test for the Rapid Detection of Acute and Late Phase Lyme-Borreliosis Disease

by Joao P. R. S. Carvalho, Monica E. T. Alcón-Chino, Paloma Napoleão-Pêgo, Guilherme C. Lechuga, Isis C. Prado, Mariana S. Freitas, Jessica A. Waterman, Karyne Rangel and Salvatore G. De-Simone

Molecules 2026, 31(18), 3152; https://doi.org/10.3390/molecules31183152 (registering DOI) - 8 Sep 2026

Abstract

Lyme borreliosis (LB) is a tick-borne disease caused by a diverse and expanding group of spirochetes characterized by complex biology and advanced immune evasion mechanisms. It presents a wide range of clinical symptoms affecting multiple organ systems and can lead to persistent complications. [...] Read more.

Lyme borreliosis (LB) is a tick-borne disease caused by a diverse and expanding group of spirochetes characterized by complex biology and advanced immune evasion mechanisms. It presents a wide range of clinical symptoms affecting multiple organ systems and can lead to persistent complications. The pathogenesis of LB remains incompletely understood, and diagnosis typically relies on serologic assays to detect antibodies against LB. However, the standard two-tiered testing (STTT) algorithm is limited by cross-reactivity, low sensitivity, and delayed results, hindering timely and accurate diagnosis. Although molecular tests are considered the gold standard, their reliance on centralized laboratories can delay critical treatment decisions. This underscores the urgent need for rapid, reliable diagnostic tools, particularly for use at the point of hospital admission. Point-of-care serological and direct antigen testing can provide actionable information, supporting decentralized healthcare systems in diagnosing complex diseases, such as LB. In this study, we developed two fluorescent polarization immunoassays (FPIAs) using IgM and IgG LB-specific synthetic epitopes/peptides to evaluate their diagnostic potential. These FPIAs showed high sensitivity and specificity in detecting IgM or IgG anti-LB antibodies in patient sera within minutes. The fluorescently labeled synthetic peptides produced significant polarization differences between infected and healthy samples, allowing clear discrimination. The FPIA-LB functions as a one-step assay, eliminating the need for secondary antibodies or complex protocols. This work highlights the FPIA technique as a robust, rapid, and efficient tool for LB diagnosis, offering a promising advance in improving early detection and patient outcomes, which could save lives and reduce long-term health complications. Full article

(This article belongs to the Special Issue Electrochemical Biosensors: From Design to Application, 2nd Edition)

► Show Figures

Graphical abstract

19 pages, 3444 KB

Open AccessArticle

Genome-Wide Identification of SNF7 Gene Family in Maize and Potential Roles in Response to Abiotic and Biotic Stress

by Dan Wang, Wei Hu, Cuiping Xin, Xinyan Sun, Wenbo Yang, Meichen Zhu, Huimin Li, Yanping Fan and Yanyong Cao

Int. J. Mol. Sci. 2026, 27(18), 7985; https://doi.org/10.3390/ijms27187985 (registering DOI) - 8 Sep 2026

Abstract

Sucrose non-fermenting protein 7 (SNF7) is a core operator of the endosomal sorting complex required for transport III (ESCRT-III) component mediating protein sorting and degradation. To date, the SNF7 gene family remains poorly characterized in plants, particularly in maize (Zea mays L.). [...] Read more.

Sucrose non-fermenting protein 7 (SNF7) is a core operator of the endosomal sorting complex required for transport III (ESCRT-III) component mediating protein sorting and degradation. To date, the SNF7 gene family remains poorly characterized in plants, particularly in maize (Zea mays L.). Here, we integrated bioinformatic and transcriptomic analyses to systematically characterize the ZmSNF7 gene family and its regulatory potential in stress responses. In total, 20 ZmSNF7 genes were identified genome-wide and classified into three phylogenetic clades, with conserved motifs and similar tertiary structures within the same clade. Abundant hormone- and stress-responsive cis-elements were detected in their promoters. Protein interaction prediction indicated ZmSNF7 proteins interact with intra-family members and other ESCRT components. Gene Ontology (GO) enrichment analysis suggested ZmSNF7s are primarily involved in endomembrane system organization and vesicular trafficking. Transcriptomic data revealed divergent ZmSNF7 expression patterns under drought, Rice black-streaked dwarf virus (RBSDV) infection, Colletotrichum graminicola (C. graminicola) inoculation and Asian corn borer (ACB) infestation. Collectively, this study comprehensively characterized the ZmSNF7 gene family and broadened our functional understanding of ZmSNF7 in mediating plant responses to biotic and abiotic stresses. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

► Show Figures

Figure 1

19 pages, 9168 KB

Open AccessArticle

An Intelligent Temporal Framework for Interval Prediction of Concrete Dam Deformation

by Feng Han, Chongshi Gu, Pei Liu and Xinran Cui

Informatics 2026, 13(9), 148; https://doi.org/10.3390/informatics13090148 (registering DOI) - 8 Sep 2026

Abstract

The inherent uncertainty of concrete dam systems, together with the complex influence of environmental loads and measurement noise, makes it difficult for traditional deterministic point prediction models to provide reliable deformation forecasts. In particular, the prediction performance of conventional models is highly dependent [...] Read more.

The inherent uncertainty of concrete dam systems, together with the complex influence of environmental loads and measurement noise, makes it difficult for traditional deterministic point prediction models to provide reliable deformation forecasts. In particular, the prediction performance of conventional models is highly dependent on parameter settings, while the uncertainty and potential deviation of future displacement responses are often not fully quantified. To address these limitations, this study proposes an intelligent data-driven prediction framework for dam displacement based on the integration of convolutional neural networks and long short-term memory networks. In the proposed framework, convolutional neural networks are used to extract local feature information from monitoring data, while long short-term memory networks are employed to capture temporal dependencies in displacement sequences. The Black-winged Kite Algorithm is introduced to optimize the key parameters of the integrated multi-level network, thereby improving the accuracy and robustness of point prediction. Furthermore, quantile regression is embedded into the optimized learning framework to construct an interval prediction model for dam deformation, enabling the conditional predictive uncertainty associated with displacement evolution to be quantitatively characterized. The engineering case study and comparative analyses with other models demonstrate that the proposed model achieves improved prediction performance for the investigated monitoring point. The interval prediction results further show that, for the investigated dam and monitoring point, the proposed framework can effectively characterize conditional predictive uncertainty and provide additional information for deformation interpretation and safety assessment. Further studies involving additional monitoring points and dams are required to assess its broader applicability. Full article

(This article belongs to the Section Machine Learning)

► Show Figures

Figure 1

16 pages, 37065 KB

Open AccessArticle

Small-Target Traffic Sign Detection Method Based on Multi-Path Feature Aggregation and Attention Enhancement

by Yinyin Li, Lei Liu, Yeguo Sun and Qingyu Liu

Technologies 2026, 14(9), 562; https://doi.org/10.3390/technologies14090562 (registering DOI) - 8 Sep 2026

Abstract

Detecting traffic signs in real-world roadway scenes remains a demanding task due to extensive category diversity, the prevalence of diminutive targets, and interference from cluttered surroundings. To overcome these obstacles, we present YOLO-PPA, a YOLOv11n-based detector strengthened through multi-path feature aggregation and attention-enhanced [...] Read more.

Detecting traffic signs in real-world roadway scenes remains a demanding task due to extensive category diversity, the prevalence of diminutive targets, and interference from cluttered surroundings. To overcome these obstacles, we present YOLO-PPA, a YOLOv11n-based detector strengthened through multi-path feature aggregation and attention-enhanced representation learning. First, a Parallelized Patch-Aware Attention (PPA) mechanism is embedded in place of the standard C3K2 block, simultaneously capturing fine-grained local textures and broad contextual semantics while adaptively amplifying informative spatial regions critical for small objects. Second, a high-resolution P2 detection head is appended to the feature pyramid, recovering fine spatial cues that would otherwise be attenuated across successive downsampling stages, and this design is particularly beneficial for recognizing signage occupying only a handful of pixels. Third, the Normalized Gaussian Wasserstein Distance (NWD) replaces the conventional CIoU metric as the regression loss, offering a smoother optimization landscape for tiny instances where even single-pixel displacements can destabilize standard IoU-based objectives. Evaluated on the TT100K benchmark, YOLO-PPA surpasses the YOLOv11n baseline by 2.1% in precision, 3.7% in recall, 4.3% in mAP@50, and 3.0% in mAP@50:95, confirming its effectiveness for small-scale traffic sign recognition in complex driving environments. Full article

(This article belongs to the Topic Challenges and Opportunities of Integrating Service Science with Data Science and Artificial Intelligence)

► Show Figures

Figure 1

23 pages, 1834 KB

Open AccessArticle

Sustainable AI Request Scheduling with Joint Compute, Network, and Power Optimization

by Bo Ding, Caining Wang, Kaifei Tang, Shuai Wei, Ke Song and Yu Wang

Sustainability 2026, 18(18), 9220; https://doi.org/10.3390/su18189220 (registering DOI) - 8 Sep 2026

Abstract

The rapid growth in artificial intelligence (AI) demand has significantly increased the electricity consumption and carbon emissions of computing centers. How to schedule AI requests across computing centers to reduce carbon emissions and electricity costs while maintaining low latency is an essential research [...] Read more.

The rapid growth in artificial intelligence (AI) demand has significantly increased the electricity consumption and carbon emissions of computing centers. How to schedule AI requests across computing centers to reduce carbon emissions and electricity costs while maintaining low latency is an essential research problem. Existing schedulers reduce emissions by shifting workloads or balancing resources but usually simplify power system modeling, ignore transmission-side costs and carbon emissions, or make local decisions without batch-level coordination. To better address these problems, we first develop an ILP-based scheduler to get optimized results, but it faces scalability limitations. Then, we propose RAPID, a region-aware and power-informed scheduling framework that integrates static and online heuristic schedulers for large-scale AI request scheduling. Experiments based on real-world GenAI traces and Chinese regional power profiles show that RAPID significantly reduces carbon emissions, electricity costs, and total energy consumption compared to methods from previous works while maintaining zero Service Level Agreement (SLA) violations. Full article

► Show Figures

Figure 1

23 pages, 1187 KB

Open AccessArticle

Calibrating LLM-Derived Trust Scores for News Outlets When Public Factuality Scorecards Disappear

by Pieter Claassen, Gary van Vuuren and Tanja Verster

Information 2026, 17(9), 867; https://doi.org/10.3390/info17090867 (registering DOI) - 8 Sep 2026

Abstract

Third-party news-source factuality scorecards are valuable but increasingly fragile. Web pages change, access conditions shift and underlying datasets may disappear. The challenge is therefore not only benchmark imperfection but also benchmark sustainability as credibility datasets, search interfaces and platform reputation signals become harder [...] Read more.

Third-party news-source factuality scorecards are valuable but increasingly fragile. Web pages change, access conditions shift and underlying datasets may disappear. The challenge is therefore not only benchmark imperfection but also benchmark sustainability as credibility datasets, search interfaces and platform reputation signals become harder to access reproducibly. This study investigates whether a fixed large language model (LLM) scoring procedure can generate durable, replayable outlet-level trust scores that align with a frozen external factuality benchmark rather than objective ground truth. Fifty-two English-language news outlets were assessed across nine predefined trust dimensions and compared with a frozen Media Bias Fact Check (MBFC) factuality snapshot. Raw LLM scores were rank-aware but compressed (Pearson’s

r = 0.801

, Spearman’s

ρ = 0.843

, full-cohort mean GAP

= 0.221

). An affine calibration fitted on 42 training outlets increased full-cohort Pearson alignment to

r = 0.828

and reduced mean GAP to

0.090

; on the fixed ten-outlet validation fold, mean GAP fell from

0.162

to

0.063

. Across 1000 additional stratified 42/10 splits, median validation GAP was

0.078

(central 95% split range

0.048

–

0.110

). Wikipedia lead and source-weighted web enrichment did not outperform the calibrated archival path in the retained data. The Step 4 unweighted web-search meter improved on the Wikipedia-lead meter (Pearson’s

r = 0.697

, Spearman’s

ρ = 0.576

, full-cohort mean GAP

= 0.200

; fixed-validation GAP

= 0.146

) but remained below the calibrated archival path. RSS monitoring is reported separately as an asymmetric, bounded adverse-event signal rather than a second factuality benchmark. These findings support calibrated LLM trust vectors as a potentially useful archival proxy while highlighting benchmark dependence, sampling constraints, model sensitivity and the importance of reproducible data provenance. Full article

(This article belongs to the Topic AI-Driven Information Governance for Sustainable Decision Making and Innovation)

► Show Figures

Figure 1

27 pages, 712 KB

Open AccessArticle

A Steady-State Thermodynamic Framework for Preliminary Assessment of a Nuclear–Solar–Data-Center Integrated Power-and-Cooling System

by Erich Martinez-Martin and Alta Knizley

Energies 2026, 19(18), 4235; https://doi.org/10.3390/en19184235 (registering DOI) - 8 Sep 2026

Abstract

Small modular reactors (SMRs) offer firm low-carbon heat and power, and data centers concentrate large, continuous electrical and cooling loads. Transparent tools for screening their thermal integration are scarce. To the authors’ knowledge, this paper develops the first steady-state thermodynamic framework that couples [...] Read more.

Small modular reactors (SMRs) offer firm low-carbon heat and power, and data centers concentrate large, continuous electrical and cooling loads. Transparent tools for screening their thermal integration are scarce. To the authors’ knowledge, this paper develops the first steady-state thermodynamic framework that couples SMR steam extraction, solar thermal input, and recovered data-center liquid-cooling heat through a single mixing-tank thermal bus serving both an absorption chiller and an organic Rankine cycle (ORC). The framework’s novelty is in its focus on the structural level rather than the component level. Two consistency requirements are built into its equations. First, the data-center control volume closes exactly, so that recovered heat reduces the residual cooling demand and heat removal equals IT dissipation. Second, delivered cooling is credited identically in every configuration compared, so that apparent gains cannot arise from asymmetric accounting. The framework identifies the governing mechanism of the architecture: a small 120 °C extraction stream (1.01% of core thermal power at the activation bound) unlocks the larger 70 °C recovered stream, which cannot drive the chiller alone. At the margin-constrained design point (2.93% extraction), direct liquid recovery removes 20.9 MW_th, absorption cooling serves the remaining 16.2 MW_th, and net electricity is 5.8 MW_e above the all-electric reference. An itemized estimate places the integration-specific parasitic loads at 0.6–1.5 MW_e (central value 1.0 MW_e), which reduces the increment over the liquid-cooled non-integrated reference from

+ 0.5

MW_e (gross) to approximately

- 0.5

MW_e (net). A 20,000-sample Monte Carlo analysis across seven uncertain parameters shows the net-of-parasitics gain over the all-electric reference is positive with 92% probability (median

+ 4.1

MW_e), while the increment over the non-integrated reference is positive with only 29% probability. A compact exergy inventory attributes 7.1 MW of destruction to the recovery train (process heat exchanger 2.0, mixing 1.2, ORC 2.0, chiller 2.0). The architecture’s robust value therefore lies in thermally driven cooling and the productive use of recovered heat, not in net energy. The framework is a screening tool rather than a validated plant model; a companion study populates it with published plant, climate, and equipment data. Full article

(This article belongs to the Special Issue Advances in Integrated Multi-Energy Systems and Sector Coupling)

► Show Figures

Figure 1

32 pages, 415 KB

Open AccessArticle

Development and Psychometric Validation of the Museum Quality and Museum Perceived Value Scales

by Nika Rakuša, Aleksandra Pisnik, Domen Malc and Borut Milfelner

Tour. Hosp. 2026, 7(9), 289; https://doi.org/10.3390/tourhosp7090289 (registering DOI) - 8 Sep 2026

Abstract

Reliable and culturally appropriate measurement instruments are essential for advancing museum research and enabling meaningful comparisons across studies. However, evidence regarding the psychometric performance of existing scales outside their original cultural settings remains limited. This study aimed to develop and psychometrically validate integrated [...] Read more.

Reliable and culturally appropriate measurement instruments are essential for advancing museum research and enabling meaningful comparisons across studies. However, evidence regarding the psychometric performance of existing scales outside their original cultural settings remains limited. This study aimed to develop and psychometrically validate integrated measures of museum quality and museum perceived value in the Slovenian museum context by combining newly developed items with items adapted from established measurement instruments. Scale development followed a multi-study design. First, measurement items were developed and evaluated through expert assessment to establish content validity. The scales were then refined using exploratory factor analysis and subsequently validated through confirmatory factor analysis to assess their factorial structure, reliability, convergent validity, and discriminant validity using an independent sample of museum visitors. Finally, nomological validity was examined by testing the relationships between museum quality, perceived value, and visitor satisfaction. The findings supported the proposed multidimensional structure of both scales and demonstrated satisfactory psychometric properties. The validated instruments provide reliable measures for assessing museum quality and perceived value in the Slovenian museum context and offer a methodological foundation for future research and further validation of these constructs in other cultural settings. Replication with larger samples is recommended to obtain more robust estimates of latent factor correlations. Full article

17 pages, 2661 KB

Open AccessArticle

ADCK1 Regulates Mitochondrial Bioenergetics in Hepatocellular Carcinoma In Vitro

by Noel Jacquet and Yunfeng Zhao

Int. J. Mol. Sci. 2026, 27(18), 7984; https://doi.org/10.3390/ijms27187984 (registering DOI) - 8 Sep 2026

Abstract

Hepatocellular carcinoma (HCC) is characterized by profound metabolic reprogramming and mitochondrial dysfunction, yet the molecular regulators underlying these alterations remain incompletely understood. AarF domain-containing kinase 1 (ADCK1) is an evolutionarily conserved protein associated with mitochondrial function, but its role in HCC bioenergetics has [...] Read more.

Hepatocellular carcinoma (HCC) is characterized by profound metabolic reprogramming and mitochondrial dysfunction, yet the molecular regulators underlying these alterations remain incompletely understood. AarF domain-containing kinase 1 (ADCK1) is an evolutionarily conserved protein associated with mitochondrial function, but its role in HCC bioenergetics has not been defined. In this study, we investigated the effects of ADCK1 on mitochondrial metabolism using CRISPR/Cas9-mediated ADCK1 knockout in HepG2 and SNU-449 HCC cells. Mitochondrial respiration, glycolytic activity, ATP production, lactate generation, mitochondrial membrane potential, and superoxide production were assessed following ADCK1 KO. ADCK1 KO resulted in marked reductions in basal and maximal mitochondrial respiration, ATP-linked respiration, glycolytic activity, intracellular ATP, and lactate production in both HCC cell models. ADCK1 KO also reduced mitochondrial membrane potential in a clone-dependent manner. Despite these profound bioenergetic defects, mitochondrial superoxide production was not consistently altered across the knockout clones. These findings indicate that ADCK1 supports both oxidative phosphorylation and glycolytic metabolism and is required for maintenance of bioenergetic homeostasis in HCC cells. Collectively, our results identify ADCK1 as a previously unrecognized regulator of HCC mitochondrial metabolism. Full article

(This article belongs to the Special Issue Mitochondria: Molecular Targeting in Cancer, Neurodegenerative Diseases, and Aging)

► Show Figures

Figure 1

16 pages, 1987 KB

Open AccessArticle

Situational Analysis of Offensive Strategies in Baseball: A Comparative Study on Batting Performance Across 0–5 Pitch Counts

by Chien-Lin Chen, Po-Hsiang Huang, Tzu-Chien Lo and Tsung-Yu Hsieh

Appl. Sci. 2026, 16(18), 8910; https://doi.org/10.3390/app16188910 (registering DOI) - 8 Sep 2026

Abstract

The ball–strike count resets at each plate appearance, continuously shifting strategic advantage between pitcher and batter. Prior research has focused on total count effects, leaving a gap regarding whether different sequential orders of balls and strikes within equivalent count situations produce meaningful performance [...] Read more.

The ball–strike count resets at each plate appearance, continuously shifting strategic advantage between pitcher and batter. Prior research has focused on total count effects, leaving a gap regarding whether different sequential orders of balls and strikes within equivalent count situations produce meaningful performance differences. Purpose: This study investigated whether ball–strike progression sequences significantly affect collegiate batting performance. Methods: T Drawing on 9454 plate appearances from 120 University Baseball League games, one-way ANOVA with Bonferroni post hoc comparisons assessed sequential order effects across AVG, OBP, SLG, and OPS. Results: The results indicate that sequential order produced statistically significant differences across all four indicators at the 2nd, 3rd, and 4th pitch situations (ps < 0.05), while no significant differences emerged at the 1st pitch or full count. Practical Implications: These findings demonstrate that the path through which a count develops systematically influences batting performance, with sequence effects significant at the 2nd, 3rd, and 4th pitch situations but absent at the initial pitch and full count—consistent with the strategic constraints inherent to these boundary situations. Future research should incorporate pitch type, pitch location, and game-context variables to further clarify the dynamic interaction between pitchers and batters. Full article

(This article belongs to the Collection Computer Science in Sport)

► Show Figures

Figure 1

23 pages, 6922 KB

Open AccessArticle

Enhanced GNSS Tomography Using Synthetic Ray Augmentation Constrained by Observed Tropospheric Gradients

by Pedro Mateus and Pedro M. A. Miranda

Remote Sens. 2026, 18(18), 3070; https://doi.org/10.3390/rs18183070 (registering DOI) - 8 Sep 2026

Abstract

Ground-based GNSS tomography reconstructs three-dimensional tropospheric water-vapor fields from slant observations. However, unconstrained solutions rely heavily on station and satellite geometry. This study introduces a GNSS-only approach that uses precise SP3 orbit products to create pseudo-slant observations in satellite directions not tracked by [...] Read more.

Ground-based GNSS tomography reconstructs three-dimensional tropospheric water-vapor fields from slant observations. However, unconstrained solutions rely heavily on station and satellite geometry. This study introduces a GNSS-only approach that uses precise SP3 orbit products to create pseudo-slant observations in satellite directions not tracked by individual receivers. These directions combine with existing IWV and horizontal-gradient estimates. This completes the ray distribution without adding external atmospheric constraints or independent water-vapor information. The method is tested in Hong Kong and Iceland with GPS-only, GLONASS-only, observed multi-constellation, and SP3-completed setups. GPS-derived gradients were generally in line with the full multi-GNSS solution, but GLONASS-only gradients showed larger differences. Overall, the mapped directions improved or maintained the inversion’s effective rank and numerical stability. They did not systematically degrade the retrieved water-vapor profiles, although the advantages decreased when the additional rays were geometrically redundant. Full article

(This article belongs to the Special Issue Remote Sensing Data Refinement and Utilization for Advanced Atmospheric Observations)

► Show Figures

Figure 1

16 pages, 25398 KB

Open AccessArticle

Simulations on Scintillator Thicknesses for Bone Mineral Density Measurement Based on Dual-Layer Flat-Panel Detectors

by Jongin Kim, Dong Sik Kim and Eunae Lee

Diagnostics 2026, 16(18), 2891; https://doi.org/10.3390/diagnostics16182891 (registering DOI) - 8 Sep 2026

Abstract

Background/Objectives: A dual-layer flat-panel detector (DFD), in which two flat-panel detectors are stacked vertically, enables single-shot dual-energy imaging without a fan-beam scanning and switching mechanism in conventional dual-energy X-ray absorptiometry (DXA), the clinical standard for bone mineral density (BMD). However, because single-shot BMD [...] Read more.

Background/Objectives: A dual-layer flat-panel detector (DFD), in which two flat-panel detectors are stacked vertically, enables single-shot dual-energy imaging without a fan-beam scanning and switching mechanism in conventional dual-energy X-ray absorptiometry (DXA), the clinical standard for bone mineral density (BMD). However, because single-shot BMD measurement systems using DFDs show substantial spectral overlap, their BMD measurement performance is inherently inferior to that of dual-shot systems. In this paper, we optimize the tube voltage, metal filter thickness, and CsI(Tl)-scintillator thickness so that the BMD estimation error of the single-shot method is similar to that of the double-shot method. Here, we also optimize the dual-shot approach to serve as a meaningful reference in the comparison. Methods: BMD measurement simulations were performed using a polynomial estimator based on second-order polynomial fitting of dual-energy logarithmic intensities. Performance comparison was based on noise sensitivity, quantified by the condition number and mean square error under a multiplicative noise model, and was further assessed using the equivalent energies and the bone-tissue attenuation ratios. Results: The simulation results indicate that, in the dual-shot approach, decreasing the low tube voltage is the most effective strategy for improving BMD measurement performance, whereas in the single-shot approach, reducing the upper scintillator thickness has the largest impact. Conclusions: When both approaches are evaluated under their respective optimized configurations based on synthetic simulations, the single-shot approach demonstrates that the BMD estimation error is sufficiently similar to that of the dual-shot approach, supporting its potential as a hardware-efficient alternative for BMD measurement. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

► Show Figures

Figure 1

17 pages, 1621 KB

Open AccessArticle

Influence of Different Saline and Alkali Aquaculture on the Nutritional Composition, Physicochemical Properties, and Flavor Profile of Grass Carp (Ctenopharyngodon idellus)

by Pengcheng Gao, Duanduan Yu, Peng Liu, Xinghe Chen, Long Li, Yanqing Huang, Qifang Lai and Hai Chi

Foods 2026, 15(18), 3172; https://doi.org/10.3390/foods15183172 (registering DOI) - 8 Sep 2026

Abstract

Saline and alkali aquaculture offers a sustainable strategy to alleviate pressure on freshwater resources and ecologically ameliorate saline and alkali environments; however, information regarding the quality of aquatic products from such conditions remains scarce. This study evaluated the nutritional components, color, texture, and [...] Read more.

Saline and alkali aquaculture offers a sustainable strategy to alleviate pressure on freshwater resources and ecologically ameliorate saline and alkali environments; however, information regarding the quality of aquatic products from such conditions remains scarce. This study evaluated the nutritional components, color, texture, and flavor profiles of grass carp cultured under three representative saline and alkali conditions in China: carbonate (CB), chloride (CR), and sulfate (SF), with a freshwater-cultured grass carp (Ctenopharyngodon idellus) serving as a control (CK). The results obtained in our study showed that the CB group exhibited the lowest muscle water content (68.96 ± 0.04%). Crude fat and sodium levels were significantly elevated in all treatment groups compared to the CK group (p < 0.05). Conversely, the CK group displayed superior springiness and higher concentrations of geosmin, adenine, and uracil. Notably, the CR group exhibited the highest L* and whiteness values, whereas the CB and SF groups possessed significantly higher collagen content and enriched EPA and DHA levels. These findings demonstrate that saline and alkali conditions distinctly modulate the nutritional and flavor profiles of grass carp, highlighting their potential for producing value-added aquatic products under saline and alkali conditions. Full article

(This article belongs to the Special Issue From Sea to Fork: Seafood Processing, Preservation and Effects on Human Health)

► Show Figures

Figure 1

23 pages, 5409 KB

Open AccessArticle

Mineral Accumulation and Physiological Responses of Two Halophytes, Caroxylon vermiculatum and Mesembryanthemum nodiflorum: Implications for Phytoremediation in Contaminated Coastal Environments

by Dhouha Belhadj Sghaier, Hasna Ellouzi, Houyem Abderrazak, Fourat Akrout, Mohsen Hanana and Monia EL Bour

Plants 2026, 15(18), 2743; https://doi.org/10.3390/plants15182743 (registering DOI) - 8 Sep 2026

Abstract

Halophytes are recognized for their adaptive capacity and potential applications in phytomanagement and ecosystem restoration. This study investigates the comparative physiology and antioxidant responses of two native halophytes, Caroxylon vermiculatum (L.) and Mesembryanthemum nodiflorum L., growing naturally in saline and metal-affected coastal environments. [...] Read more.

Halophytes are recognized for their adaptive capacity and potential applications in phytomanagement and ecosystem restoration. This study investigates the comparative physiology and antioxidant responses of two native halophytes, Caroxylon vermiculatum (L.) and Mesembryanthemum nodiflorum L., growing naturally in saline and metal-affected coastal environments. A comprehensive set of physiological and biochemical parameters was assessed, including macro- and microelements (Na, K, Ca, Fe, Zn, Cd), photosynthetic pigments (chlorophyll a, chlorophyll b, and carotenoids), soluble sugars, and proteins. In addition, oxidative stress markers (hydrogen peroxide, H₂O₂, and malondialdehyde, MDA), enzymatic antioxidants (superoxide dismutase, SOD, catalase, CAT, and guaiacol peroxidase, GPX), and non-enzymatic antioxidants (total phenolics, flavonoids, and proanthocyanidins) were evaluated. Antioxidant activities, including DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging and reducing power, were also measured. The results revealed clear species-specific adaptive strategies. Mesembryanthemum nodiflorum exhibited higher accumulation of Na and K, together with elevated levels of carotenoids and oxidative stress markers. This species showed translocation factors (TF > 1) for Na (~1.60) and K (~1.90), indicating efficient ion transport to aerial parts, while displaying low bioconcentration (BCF < 0.5 for most trace elements) and biological accumulation factors (BAF < 1), suggesting limited capacity for heavy metal accumulation. In contrast, Caroxylon vermiculatum showed higher concentrations of chlorophylls, carotenoids, phenolic compounds, flavonoids, and proteins, along with stronger superoxide dismutase activity. It also exhibited lower translocation of trace elements (TF < 1) and higher root retention of metals (BCF up to ~0.5), indicating a more effective exclusion and detoxification strategy. Overall, these findings demonstrate that M. nodiflorum relies on ion accumulation and translocation, whereas C. vermiculatum exhibits stronger ion regulation and antioxidant protection. Given the moderate BAF and BCF values observed, both species are more likely to contribute to phytomanagement through ion regulation and phytostabilization rather than efficient phytoextraction. Full article

(This article belongs to the Special Issue Oxidative Stress and Antioxidant Responses in Plants: Hormonal Regulation and Multi-Omics Insights Under Abiotic and Biotic Stresses)

► Show Figures

Figure 1

15 pages, 2420 KB

Open AccessArticle

Thermal Stress and Temperature Analysis of Integrated Protection-Thermal Control Multilayer Films Under Laser Irradiation in Alternating High and Low Temperatures

by Chao Zhou, Rui Zhu, Shengzhu Cao, Jun Yang and Binhua Gui

Materials 2026, 19(18), 3817; https://doi.org/10.3390/ma19183817 (registering DOI) - 8 Sep 2026

Abstract

With the rapid advancement of space-based laser weapon technologies, on-orbit safety of spacecraft such as satellites is confronted with severe laser threats. To meet the demands for film system optimization and reliability improvement of thin films integrating space laser protection and thermal control [...] Read more.

With the rapid advancement of space-based laser weapon technologies, on-orbit safety of spacecraft such as satellites is confronted with severe laser threats. To meet the demands for film system optimization and reliability improvement of thin films integrating space laser protection and thermal control functions, this study takes the Graphene/Ag/Al₂O₃/SiO₂/ITO multilayer thin film structure as the research object. Combined with the space alternating high-low temperature environment and the action of ultra-high-density transient directional heat flux, systematic simulation research on the evolution laws of temperature and stress fields inside the multilayer thin films under laser irradiation in alternating space high-low temperature environments is carried out via COMSOL Multiphysics, and the influencing mechanisms of ambient temperature and laser operating parameters on thermal stress and temperature distribution are revealed. The simulation results demonstrate that the thin film structure reaches thermal equilibrium within several seconds under a given transient directional heat flux. As laser power rises, the peak temperature of each layer increases nonlinearly and the time required to reach thermal equilibrium shortens. The laser heat flux density acts as the dominant factor governing the temperature and thermal stress distribution. Under alternating space high-low temperature conditions, the thermal stress of the thin film varies approximately linearly with temperature while the overall stress magnitude remains low, and thermal stress is mainly concentrated in the Al₂O₃ layers. Laser loading exerts a remarkable impact on film thermal stress: the amplitude of thermal stress in all film layers rises synchronously with increasing laser power, and interlayer temperature gradients as well as stress concentration are further intensified. The stress growth of Ag and Al₂O₃ layers is the most significant, which can be attributed to the synergistic effect of interlayer thermal expansion coefficient mismatch and temperature gradients. The alternating high-low temperature and laser irradiation experiments indicate that the maximum temperature and maximum stress borne by the muti-layer film under alternating temperatures ranging from −150 °C to 150 °C and laser irradiation of 200 W/cm² will not lead to macroscopic failure behaviors and degradation of thermal control performance. Full article

(This article belongs to the Special Issue Advanced Laser and Optical Methods for Material Analysis, Surface Engineering, and Performance Enhancement)

► Show Figures

Figure 1

33 pages, 25603 KB

Open AccessArticle

Configuration over Transition Temperature: A Climate-Adaptive Strategy for Sustainable Office Building Energy Efficiency with Thermochromic Glazing

by Haibin Zhang, Shiyi Shen, Shou Yuan, Julian Wang, Xiao Ma, Xuanyi Wang and Han Zhang

Sustainability 2026, 18(18), 9218; https://doi.org/10.3390/su18189218 (registering DOI) - 8 Sep 2026

Abstract

Buildings account for a substantial share of global energy use and carbon emissions, making climate-adaptive building envelopes critical for sustainable urban development. Thermochromic glazing dynamically modulates solar transmittance with temperature, offering a promising pathway toward sustainable buildings; however, guidance on transition temperatures and [...] Read more.

Buildings account for a substantial share of global energy use and carbon emissions, making climate-adaptive building envelopes critical for sustainable urban development. Thermochromic glazing dynamically modulates solar transmittance with temperature, offering a promising pathway toward sustainable buildings; however, guidance on transition temperatures and composite configurations across China’s five climate zones remains limited. This study therefore derives an evidence-based, climate-adaptive design strategy for thermochromic hydrogel-based insulating glass units in office buildings across these climate zones. To achieve this aim, an EnergyPlus model validated against summer field measurements in Chongqing quantified heating and cooling loads for 220 simulated cases and identified suitable glazing configurations and transition temperature, while RF-SHAP ranked factor importance. The results provide climate- and orientation-specific guidance for office-glazing selection: a 25 °C transition temperature delivers 2.76–4.04% total load savings in the two warm zones, and surface-2/3 Low-E composite TSG achieves up to 12.93%. In cold and severe cold zones, south-facing use can raise loads, whereas west-, east-, and north-facing applications retain saving potential; in temperate climates, single-silver Low-E glass is generally preferable. The RF-SHAP analysis ranks the factors influencing the total energy saving rate as glazing configuration > climate zone > orientation > transition temperature. These findings translate into a practical climate zone-based selection framework that supports sustainable building envelope design and retrofitting, helping to reduce operational energy consumption and carbon emissions while maintaining indoor thermal comfort. Full article

► Show Figures

Figure 1

19 pages, 2489 KB

Open AccessArticle

Machine Learning and Explainable AI for Breast Cancer Patient Prioritization: An Intelligent Decision-Support Framework

by Fabián Silva-Aravena, Jenny Morales, Hugo Núñez Delafuente and César González-Zúñiga

Bioengineering 2026, 13(9), 1044; https://doi.org/10.3390/bioengineering13091044 (registering DOI) - 8 Sep 2026

Abstract

Breast cancer continues to represent a major global health burden, highlighting the need for effective approaches to risk stratification and clinical decision support. Conventional methods, including the Breast Imaging Reporting and Data System (BI-RADS) and histopathological classifications, primarily rely on clinical assessments and [...] Read more.

Breast cancer continues to represent a major global health burden, highlighting the need for effective approaches to risk stratification and clinical decision support. Conventional methods, including the Breast Imaging Reporting and Data System (BI-RADS) and histopathological classifications, primarily rely on clinical assessments and may not fully account for relevant demographic and behavioral characteristics. To overcome these limitations, we present an integrated framework combining K-Means clustering, Random Forest classification, and Explainable Artificial Intelligence (XAI) to support breast cancer risk stratification and patient prioritization. The proposed methodology uses clustering to stratify patients into low-, medium-, and high-risk groups, followed by supervised machine learning to reproduce the cluster-derived risk categories, achieving an accuracy of 98%. To enhance interpretability, Local Interpretable Model-Agnostic Explanations (LIME) are incorporated to identify the variables that most strongly influence individual classifications, including body mass index (BMI), breastfeeding practices, and maternal age. By integrating multiple dimensions of patient information, the framework provides a more comprehensive characterization of risk while increasing the transparency of the decision-making process. Its relatively simple and scalable architecture also facilitates potential implementation in healthcare environments with limited resources. Simulation experiments further provide a proof-of-concept evaluation of the proposed prioritization approach. Compared with random patient selection, the strategy achieved a substantially higher average severity score (1.66 vs. 0.92) and prioritized 4.3 times more high-risk patients. These findings suggest that the proposed framework can serve as an intelligent decision-support tool for prioritizing breast cancer patients and improving resource allocation when healthcare capacity is constrained. Full article

(This article belongs to the Special Issue AI for Healthcare)

► Show Figures

Figure 1

14 pages, 894 KB

Open AccessArticle

ABO and RhD Blood Groups in Epilepsy: A Comprehensive Case–Control Analysis

by Okan Sokmen and Osman Korucu

J. Clin. Med. 2026, 15(18), 6949; https://doi.org/10.3390/jcm15186949 (registering DOI) - 8 Sep 2026

Abstract

Background: Although ABO blood groups have been implicated in several vascular and neurological disorders, evidence regarding their association with epilepsy remains limited and inconclusive. We performed the largest and most comprehensive case–control evaluation to date to determine whether ABO/RhD blood groups are associated [...] Read more.

Background: Although ABO blood groups have been implicated in several vascular and neurological disorders, evidence regarding their association with epilepsy remains limited and inconclusive. We performed the largest and most comprehensive case–control evaluation to date to determine whether ABO/RhD blood groups are associated with epilepsy. Methods: We conducted a retrospective hospital-based case–control study including 806 adults with epilepsy and 14,032 controls from the same institutional population between January 2015 and January 2026. Epilepsy diagnoses were confirmed independently by two neurologists according to International League Against Epilepsy criteria. Associations between epilepsy and ABO/RhD blood groups were evaluated using a comprehensive analytical framework incorporating multivariable-adjusted logistic regression, binary blood group comparisons, age- and sex-matched sensitivity analyses, and epilepsy subtype-specific analyses. Results: No significant association was identified between epilepsy and ABO/RhD blood groups across any analytical approach. Overall ABO blood group (p = 0.777) and RhD status (p = 0.611) distributions were comparable between patients with epilepsy and controls. Binary analyses showed no significant associations for non-O versus O (OR 1.05, 95% CI 0.90–1.22; p = 0.535), non-A versus A (OR 0.93, 95% CI 0.80–1.06; p = 0.297), non-B versus B (OR 1.03, 95% CI 0.85–1.25; p = 0.748), non-AB versus AB (OR 1.05, 95% CI 0.81–1.34; p = 0.723), or RhD-negative versus RhD-positive status (OR 1.06, 95% CI 0.85–1.31; p = 0.611). These findings remained unchanged after multivariable-adjusted logistic regression, 1:4 age- and sex-matched sensitivity analyses (806 patients with epilepsy and 3224 matched controls; ABO p = 0.774, RhD p = 0.740), and comparisons between focal and generalized epilepsy subtypes (ABO p = 0.531; RhD p = 0.995). Conclusions: In this large hospital-based case–control study, no significant association was identified between epilepsy and ABO/RhD blood groups. However, the hospital-based control population and the availability of blood group data should be considered when interpreting these findings. Full article

(This article belongs to the Section Clinical Neurology)

► Show Figures

Figure 1

41 pages, 1682 KB

Open AccessArticle

Emotion Analysis in Public Transport

by Zilvinas Abaravicius, Arturas Kaklauskas and Evelina Achilli

Appl. Sci. 2026, 16(18), 8911; https://doi.org/10.3390/app16188911 (registering DOI) - 8 Sep 2026

Abstract

Global studies indicate that urban public transport systems are facing critical challenges concerning capacity, speed, punctuality, comfort, and network integration, particularly on main transit axes and in central urban areas. At the same time, previous international research in transport planning has demonstrated that [...] Read more.

Global studies indicate that urban public transport systems are facing critical challenges concerning capacity, speed, punctuality, comfort, and network integration, particularly on main transit axes and in central urban areas. At the same time, previous international research in transport planning has demonstrated that urban development scenarios and transport solutions can be evaluated using multiple-criteria analysis. This research argues that such analysis should be supplemented with a system of emotional criteria that would allow for a holistic evaluation of public emotional responses to different public transport scenarios using a public transport multimodal analysis (PAMA) system. The proposed approach assumes that traditional technical, economic, environmental, social, governance, cultural, accessibility, and quality indicators do not sufficiently reflect the needs and requirements of public transport stakeholders. Public transport emotional analysis can add new shades to the above indicators by providing practical insights into stakeholders’ experiences and opinions, leading to more holistic, effective, and passenger-centered improvements. The developed PAMA system performs a multiple-criteria analysis of public transport options, calculates customer-perceived value, and provides numerical recommendations for project enhancement. Full article

► Show Figures

Figure 1

26 pages, 5415 KB

Open AccessArticle

Metric Deformation and Topological Persistence of Molecular Configuration Spaces

by Dairo José Hernández, Carlos Alberto Cadavid, Julio De Luque, David Fernández Bueno, Rafael Ramiro Vega and Álvaro Rafael Herrera

Math. Comput. Appl. 2026, 31(5), 185; https://doi.org/10.3390/mca31050185 (registering DOI) - 8 Sep 2026

Abstract

Conformational analysis is commonly centered on potential energy surfaces, whereas changes in the intrinsic metric and topological organization of molecular configuration spaces have received less attention. Here, we introduce a correspondence-preserving framework that directly compares ideal geometric samples with their constrained MMFF94-relaxed realizations. [...] Read more.

Conformational analysis is commonly centered on potential energy surfaces, whereas changes in the intrinsic metric and topological organization of molecular configuration spaces have received less attention. Here, we introduce a correspondence-preserving framework that directly compares ideal geometric samples with their constrained MMFF94-relaxed realizations. Unlike energy-based conformational analysis, the proposed approach separates changes in pairwise structural geometry from changes in global topological organization. Configuration spaces were constructed for ethane, butane, butadiene, biphenyl, and n-pentane using one- and two-dimensional torsional domains. Pairwise root-mean-square deviation (RMSD) matrices after optimal rigid-body superposition were used to quantify metric deformation, while Vietoris–Rips persistent homology was used to compare the corresponding topological signatures. MMFF94 relaxation produced structured, conformation-dependent patterns of metric expansion and contraction rather than a uniform rescaling of the configuration spaces. Nevertheless, the dominant homological organization was preserved: the one-torsional systems retained

(β_{0}, β_{1}) = (1, 1)

, compatible with

S^{1}

, whereas n-pentane retained

(β_{0}, β_{1}, β_{2}) = (1, 2, 1)

, compatible with

T^{2}

. Persistence-diagram distances further showed that preservation of these dominant classes does not imply equality of the complete persistence representations. For the molecular systems, sampling schemes, and force-field model considered, the results demonstrate that molecular relaxation can systematically reorganize RMSD geometry without altering the dominant global topological features. The framework therefore provides a quantitative means of distinguishing metric deformation from topological change in corresponding molecular configuration spaces. Full article

(This article belongs to the Topic Mathematical, Computational and Data-Driven Methods in Mechanics, Engineering and Applied Sciences)

► Show Figures

Figure 1

17 pages, 1023 KB

Open AccessArticle

Physicochemical and Functional Characterization of a Novel Extremophilic Exopolysaccharide Produced by Janibacter limosus

by Chaima Farhat, Patrícia Concórdio Reis, Besma Ettoumi, Kleyde Ramos, Ameur Cherif, Filomena Freitas and Habib Chouchane

Microorganisms 2026, 14(9), 1983; https://doi.org/10.3390/microorganisms14091983 (registering DOI) - 8 Sep 2026

Abstract

Extremophilic exopolysaccharides (EPSs) from extreme-environment microorganisms exhibit multifunctional and specific properties relevant to food, pharmaceutical, and environmental applications. This study reports the physicochemical characteristics of a novel EPS secreted by the marine actinobacterium Janibacter limosus (JlEPS) isolated from the Tyrrhenian Sea. The biopolymer [...] Read more.

Extremophilic exopolysaccharides (EPSs) from extreme-environment microorganisms exhibit multifunctional and specific properties relevant to food, pharmaceutical, and environmental applications. This study reports the physicochemical characteristics of a novel EPS secreted by the marine actinobacterium Janibacter limosus (JlEPS) isolated from the Tyrrhenian Sea. The biopolymer was characterized for its molecular mass, monosaccharide composition, functional groups, rheological, and thermal behavior. JlEPS was found as an acidic heteropolysaccharide composed of eight sugar monomers. Neutral and acidic sugars predominate, with glucose (36.60 ± 0.46 mol%), rhamnose (23.62 ± 0.15 mol%), and galacturonic acid (16.54 ± 0.18 mol%). Amino sugars were also detected, including galactosamine (8.70 ± 0.01 mol%) and glucosamine (4.00 ± 0.10 mol%). Arabinose (7.8 ± 0.76 mol%), galactose (1.35 ± 0.01 mol%), and fucose (1.42 ± 0.06 mol%) were present in minor amounts. The average molecular weight (M_w) of the biopolymer was 1.60 × 10⁶ Da, with a polydispersity index of 1.022, indicating a relatively homogeneous population. FT-IR indicated uronic acids and glycosidic linkages, while TGA demonstrated stability up to 250 °C. JlEPS solutions behaved as pseudoplastic fluids, and the flow curves were fitted with the Carreau model (R² = 0.96–0.99). The zero-shear viscosity increased from 0.542 ± 0.187 Pa·s (0.5%) to (5.01 ± 0.91) × 10⁴ Pa·s, while the flow index decreased from 0.368 ± 0.032 to 0.100 ± 0.028, confirming strong pseudoplasticity and extensive molecular entanglements. JlEPS is a complex with a defined composition and high viscosity, supporting its potential for multiple applications. Full article

(This article belongs to the Special Issue Microbiota Dynamics in Environmental and Host Systems: From Ecology to Applications)

► Show Figures

Figure 1

27 pages, 1827 KB

Open AccessReview

Thermal Management and Reliability Engineering of Advanced HBM Packages: Materials, Interfaces, and Integrated Design Strategies

by Hye Rin Do, Jun Ha Wee, Hwa Rim Lee, Young Chae Lee, Yunna Song and Sung Gyu Pyo

Micromachines 2026, 17(9), 1065; https://doi.org/10.3390/mi17091065 (registering DOI) - 8 Sep 2026

Abstract

Advances in artificial intelligence, high-performance computing, and generative AI technologies have driven a rapid increase in the memory bandwidth and data throughput required of semiconductor systems, establishing High Bandwidth Memory (HBM)—which vertically stacks multiple DRAM dies—as a key enabling memory technology. However, increasing [...] Read more.

Advances in artificial intelligence, high-performance computing, and generative AI technologies have driven a rapid increase in the memory bandwidth and data throughput required of semiconductor systems, establishing High Bandwidth Memory (HBM)—which vertically stacks multiple DRAM dies—as a key enabling memory technology. However, increasing the stack count and shrinking the interconnect pitch in HBM not only intensify vertical heat accumulation and hotspot formation but also give rise to complex reliability issues, including thermo-mechanical stress arising from coefficient-of-thermal-expansion (CTE) mismatch, package warpage, interfacial delamination, Cu protrusion, void formation, and joint degradation. This review analyzes the heat-generation and heat-transfer mechanisms of HBM packages and examines package-level thermal management strategies based on thermal interface materials, underfill, non-conductive film, epoxy molding compound, heat spreaders, and high-thermal-conductivity composites. It further summarizes the current crowding, electromigration, Cu–dielectric interfacial defects, and thermo-mechanical failure mechanisms that arise at fine-pitch interconnects and hybrid-bonding interfaces, together with the material and process design strategies developed to mitigate them. In addition, structure-based thermal management technologies—thermal TSVs, embedded cooling, and hybrid bonding—are compared. This review emphasizes that the thermal bottlenecks and reliability degradation of HBM are interconnected through interfacial thermal resistance, interfacial adhesion, residual stress, and interfacial defects, and proposes that next-generation, highly stacked HBM requires a multi-scale thermal-reliability co-design that integrally controls the heat-, stress-, and current-transfer pathways across the entire package and interconnect domain, rather than relying on the improvement of individual material properties alone. Full article

(This article belongs to the Special Issue Semiconductor Materials and Processing Technology)

► Show Figures

Figure 1

20 pages, 5591 KB

Open AccessArticle

Long-Term Labeling and Differentiation Monitoring of Mouse Spermatogonial Stem Cells Using CellREADR

by Shuaitao Hu, Lin Yan, Gulistan Khan, Xiaowei Liu and Chunsheng Han

BioTech 2026, 15(4), 77; https://doi.org/10.3390/biotech15040077 (registering DOI) - 8 Sep 2026

Abstract

Cellular identity determination and lineage tracing is a pivotal technique in modern biological research. Conceptually simple yet efficient cell labeling techniques offering broader applicability are warranted despite many methods requiring intricate construction procedures. One such technique is ADAR (adenosine deaminase acting on RNA)-mediated [...] Read more.

Cellular identity determination and lineage tracing is a pivotal technique in modern biological research. Conceptually simple yet efficient cell labeling techniques offering broader applicability are warranted despite many methods requiring intricate construction procedures. One such technique is ADAR (adenosine deaminase acting on RNA)-mediated RNA sensing, a live cell labeling technique that is based on the expression and abundance of cell-type-specific RNAs. Here, we utilized the optimized version, CellREADR (Cell access through RNA sensing by Endogenous ADAR), to establish a feasible tracing system for mouse spermatogonial stem cells (mSSCs) which are refractory to CRISPR-based reporter gene knock-in. We identified several previously unreported features of CellREADR, including RNA interference induced by double-strand RNA formation that is obligatorily generated during the normal operation of the CellREADR system. More importantly, we established its application for long-term labeling of mSSCs and monitoring mSSC differentiation induced by retinoic acid (RA) treatment in vitro. This work offers a practical solution for dynamic monitoring of mSSC self-renewal and differentiation and supports that CellREADR can be developed into more versatile and efficient tools in stem cell research. Full article

(This article belongs to the Section Biotechnology Regulation)

► Show Figures

Graphical abstract

23 pages, 1093 KB

Open AccessReview

Mesenteric Panniculitis and the Gut–Mesentery–Metabolic Axis: A Hypothesis-Generating Narrative Review

by Sorina Ispas, Viviana Maggio, Syed Arman Rabbani, Adil Farooq Wali, Bhoomendra A. Bhongade, Sirajunisa Talath, Imran Rashid Rangraze, Shakta Mani Satyam, Ashot Avagimyan, Karolina Hoffmann, Ioannis Ilias, Anna Paczkowska, Mohamed El-Tanani and Manfredi Rizzo

Biomedicines 2026, 14(9), 2017; https://doi.org/10.3390/biomedicines14092017 (registering DOI) - 8 Sep 2026

Abstract

Mesenteric panniculitis (MP) is an uncommon inflammatory disorder of mesenteric adipose tissue. Its pathophysiology remains unclear. Gut dysbiosis, intestinal barrier dysfunction, metabolic endotoxemia, glycemic variability (GV), and vascular dysfunction have been implicated in inflammatory and metabolic disorders, but their specific involvement in MP [...] Read more.

Mesenteric panniculitis (MP) is an uncommon inflammatory disorder of mesenteric adipose tissue. Its pathophysiology remains unclear. Gut dysbiosis, intestinal barrier dysfunction, metabolic endotoxemia, glycemic variability (GV), and vascular dysfunction have been implicated in inflammatory and metabolic disorders, but their specific involvement in MP has not been established. This narrative review integrates MP-specific clinical evidence with indirect mechanistic evidence from related metabolic, inflammatory, and experimental settings to examine the possible relationships between these mechanisms and MP and their integration within a proposed gut–mesentery–metabolic axis. The literature was reviewed through structured searches of PubMed, Scopus, and Web of Science for relevant publications from 2018 to 2026, supplemented by earlier foundational studies identified through reference-list screening and targeted searches. Current data suggest that dysbiosis and impaired intestinal barrier function may facilitate microbial-product translocation and lipopolysaccharide-mediated inflammatory signaling, while GV may contribute to oxidative stress, endothelial dysfunction, and pro-inflammatory responses. Mesenteric vascular anatomy and impaired regional perfusion may represent additional factors influencing local tissue susceptibility. Recent randomized controlled trials of microbiome-targeted interventions in metabolic disorders have shown heterogeneous effects on glycemic, inflammatory, and microbiota-related outcomes, indicating a need for further investigation of individualized microbiome-directed strategies. Direct evidence that microbial, metabolic, or vascular mechanisms initiate or sustain MP is currently limited. Accordingly, the proposed gut–mesentery–metabolic axis should be interpreted as a hypothesis-generating framework rather than an established causal model. Prospective MP-specific studies integrating microbiome profiling, validated measures of intestinal barrier function, metabolic phenotyping, GV, vascular assessment, and imaging are required to test the proposed relationships. Full article

(This article belongs to the Special Issue Precision Microbiome Modulation for Metabolic and Inflammatory Diseases)

► Show Figures

Figure 1

Recent Articles

Open Access Journals

Highly Accessed Articles

Latest Books

News

Blog Posts

Topics

Selected Special Issues

Selected Collections

Journals by Subject

Further Information

Guidelines

MDPI Initiatives

Follow MDPI