Search Results (7,221)

Carbonic anhydrases (CAs) are a class of zinc-containing metalloenzymes widely present in the biological world, catalyzing the reversible hydration of CO₂ to form HCO₃⁻ and H⁺. These enzymes play essential roles in pH homeostasis, gas exchange, metabolic regulation, and virulence expression in pathogens. In fungi, CAs mainly belong to the α- and β-classes and have undergone extensive diversification during evolution. In plant pathogenic fungi, the functions of CAs have extended beyond traditional metabolic roles, evolving into key “environmental adaptation and virulence regulatory factors.” This review takes Magnaporthe oryzae as a model organism and integrates recent advances in CA research across various microorganisms. It systematically summarizes the classification diversity, structural features, subcellular localization, and biological functions of fungal CAs. Particular emphasis is placed on the molecular profile, mitochondrial localization, physical interaction network, and multiple functional roles of the MoCA family members in conidial development, appressorium formation, oxidative stress response, HCO₃⁻ homeostasis, nitrogen metabolism, and mitochondrial energy metabolism. Based on these findings, this study proposes a multi-layered analytical framework integrating CA molecular characteristics, mitochondrial functional regulation, and fungal pathogenicity. It explores the potential of targeting fungal CAs for the development of novel selective fungicides and highlights key research directions, aiming to provide theoretical insights into plant-fungal interactions and innovative strategies for disease control. Full article

Vitamin D comprises a group of fat-soluble secosteroids traditionally associated with animal physiology, calcium-phosphate homeostasis, and skeletal metabolism. However, vitamin D and related compounds have also been reported in taxonomically distinct non-animal systems, including fungi, microalgae, other algae, phytoplankton, and higher plants, although the strength of evidence differs substantially among these groups. This review synthesizes current knowledge on the occurrence, structural chemistry, UV-B-driven photochemical mechanisms, environmental determinants, analytical challenges, and biofortification potential of vitamin D formation in photosynthetic organisms and fungi. Vitamin D synthesis is initiated by UV-B radiation, primarily within the 290–315 nm range, which converts sterol precursors such as 7-dehydrocholesterol and ergosterol into previtamin D intermediates and is followed by thermal isomerization to the corresponding vitamin D forms. Continued irradiation may additionally generate lumisterol, tachysterol, and other photoproducts, thereby limiting net vitamin D accumulation. This non-enzymatic mechanism supports the interpretation that vitamin D formation can occur outside vertebrates when an appropriate 5,7-diene sterol precursor is accessible to a sufficient UV-B dose. In photosynthetic organisms and fungal matrices, net vitamin D accumulation is constrained by the spectral dose of UV-B, environmental exposure, tissue architecture, sterol localization, oxygen availability, antioxidant capacity, and ROS-mediated degradation. Studies of microalgae and phytoplankton, including reports concerning Emiliania huxleyi, suggest the occurrence or UV-B-dependent formation of both vitamin D₂ and vitamin D₃. However, these findings require evaluation according to the analytical method, use of authentic standards, experimental conditions, and confidence of compound identification. In fungi, the UV-B-induced conversion of abundant ergosterol to vitamin D₂ is well established. Microalgae represent a developing source of vitamin D₂ and vitamin D₃, whereas evidence for nutritionally relevant vitamin D accumulation in higher plants remains limited and heterogeneous. Although higher plants contain diverse phytosterols, the formation of vitamin D₄, vitamin D₅, or related analogues requires appropriate photoreactive 5,7-diene precursors and should not be inferred directly from the presence of common phytosterols such as β-sitosterol. Analytical detection remains challenging because of low concentrations, complex lipophilic matrices, and structural similarity among secosteroids and photoproducts; therefore, reliable identification requires validated analytical procedures. LC-MS/MS provides high sensitivity and selectivity but should be supported by authentic standards, preferably isotope-labelled internal standards, retention-time agreement, quantitative and qualifying ions, matrix-recovery assessment, limits of detection and quantification, and evaluation of ion suppression. Structurally similar analogues and photoproducts may additionally require orthogonal confirmation. Nutritionally, post-harvest UV-B enrichment of edible mushrooms is currently the best-validated strategy for increasing non-animal vitamin D₂ content. Microalgae constitute a developing platform for vitamin D₂ and vitamin D₃ production, whereas biofortification of higher plants remains experimental. Full article

Against the backdrop of China’s “Carbon Peaking and Carbon Neutrality” goal, the steel industry faces mounting pressure to improve its environmental accounting information disclosure as part of its green and low-carbon transition. This study evaluates the quality of environmental accounting disclosure among 30 listed Chinese steel companies from 2019 to 2023, using the analytic hierarchy process (AHP) and content analysis across disclosure channels and content dimensions. Three key findings are revealed: (1) Annual reports remain the dominant disclosure channel, while the share of standalone environmental reports rises from 3.33% to 53.33% but remains low and inconsistent. (2) Disclosure exhibits a pattern of “strong hard indicators but weak soft indicators and excessive positive information but scarce negative information”; environmental liability carries the highest weight (0.3083); and the quantitative disclosure of industrial solid waste and other specific metrics remains below 30%. (3) A weight-driven stratification pattern exists: high-weight hard indicators have improved under policy and market pressure, whereas low-weight soft indicators and negative information remain largely neglected. Based on these findings, this study proposes optimization paths from institutional norms, corporate governance, and external supervision. The conclusions provide practical implications for enhancing disclosure quality and supporting the green transformation of the steel industry under the “Carbon Peaking and Carbon Neutrality” strategy. Full article

Phlorotannins are the characteristic phenolic metabolites of brown seaweeds and represent one of the most chemically diverse, analytically challenging, and industrially promising classes of marine polyphenols. Unlike terrestrial phenolics, phlorotannins are formed from phloroglucinol units and occur as complex mixtures of fucols, phlorethols, fuhalols, fucophlorethols, eckols, and related oligomeric or polymeric structures whose composition varies strongly with species, tissue, season, habitat, extraction protocol, and purification strategy. This review critically examines brown seaweed phlorotannins across five major dimensions: chemical diversity and species-dependent availability; extraction, enrichment, and sustainable solvent strategies, including natural deep eutectic solvents (NADES); analytical challenges and advances in selective quantification, highlighting the non-specific nature of Folin–Ciocalteu assays and the emerging value of selective qNMR-based quantification; and biological relevance to ageing-associated processes such as oxidative stress, inflammation, glycation, metabolic dysfunction, neurodegeneration, and skin ageing. The review further evaluates translational barriers, including poor standardization, uncertain bioavailability, matrix interference, limited compound-specific standards, and insufficient in vivo and clinical validation. Finally, a phlorotannin-first brown seaweed biorefinery framework is proposed, in which the phenolic fraction is recovered early as a high-value stream before sequential valorization of polysaccharides, proteins, pigments, minerals, and residual biomass. This integrated perspective highlights the need to move from crude “total phenolic” descriptions toward chemically defined, functionally validated, and industrially scalable phlorotannin systems. Full article

Pharyngeal infection with high-risk human papillomavirus (HPV), particularly HPV16, is biologically distinct from cervical infection because it occurs within the specialized lymphoepithelial environment of Waldeyer’s ring. This review evaluates nanoparticle materials for the prevention, detection, and treatment of pharyngeal HPV, with an emphasis on structure–property–function relationships, mucosal performance, and translational feasibility. Lipid nanoparticle platforms, polymeric nanoparticle platforms, inorganic systems, and hybrid platforms are compared with respect to composition, particle size distribution, surface charge, colloidal stability, biodegradability, payload compatibility, release behavior, and manufacturing complexity. Evidence suggests that lipid and polymeric systems are the most credible near-future candidates for mucosal vaccination and localized nucleic acid delivery because they offer the best balance between controllable fabrication, analytical tractability, and biologically plausible performance in mucus-exposed tissue. By contrast, the development of inorganic theranostics and CRISPR-enabled platforms remains at an earlier stage because repeated mucosal dosing, retention in lymphoid tissue, and combined product regulation impose substantial burdens. A translational roadmap is proposed in which material selection is guided by clinically relevant quality attributes, standardized saliva- and mucus-relevant assays, human tonsil organoid testing, and early attention to manufacturability, safety, and regulatory strategy. The field is promising, but direct pharyngeal HPV data remain limited; accordingly, there is an urgent need for comparative studies that connect nanoparticle architecture to measurable outcomes such as tonsillar deposition, epithelial uptake, immune activation, and local tolerability. Full article

Background: Socioeconomic deprivation is a well-established determinant of participation in colorectal cancer (CRC) screening. However, less is known about the geographic clustering of screening adherence and whether spatial inequalities mirror regional patterns of socioeconomic disadvantage. This study investigated the association between socioeconomic deprivation and adherence to CRC screening across Italian regions and explored the presence of spatial autocorrelation using geographic analytical methods. Methods: We conducted a nationwide ecological cross-sectional study including 21 Italian regional units. Pearson correlation analysis was performed to explore associations between colorectal cancer (CRC) screening adherence, primary care physician (PCP) workload and socioeconomic deprivation. Multivariable linear regression was used after assessment of multicollinearity using variance inflation factors (VIFs). Sensitivity analyses included alternative deprivation indicators and leave-one-region-out analyses. Spatial dependence was evaluated using Global Moran’s I and Local Indicators of Spatial Association (LISA). Results: CRC screening adherence showed substantial geographic variability across Italy, with higher participation in northern regions and lower participation in southern areas. Screening adherence was inversely associated with socioeconomic deprivation. Sensitivity analyses confirmed the robustness of the association across alternative deprivation measures and sequential exclusion of each regional unit. Spatial analysis demonstrated significant positive spatial autocorrelation (Moran’s I = 0.275; p = 0.039), indicating that neighbouring regions tended to exhibit similar screening behaviours. LISA analysis identified significant High–High clusters in northern Italy, Low–Low clusters in southern and insular regions, and isolated spatial outliers, highlighting persistent territorial inequalities in preventive healthcare utilisation. Conclusions: Regional disparities in CRC screening participation were associated with socioeconomic deprivation and modest but significant spatial clustering. These findings provide a regional-level description of inequalities in screening participation and may help inform future public health strategies aimed at reducing disparities in organised colorectal cancer screening. Full article

Progressive Familial Intrahepatic Cholestasis (PFIC) is a rare liver disorder that, although typically present in childhood, can also occur in adulthood. Early diagnosis is crucial for appropriate clinical management, prognostic assessment, and therapeutic decision-making; however, it remains challenging due to phenotypic variability and the frequent identification of genetic variants of uncertain significance (VUS). Advances in next-generation sequencing (NGS) and whole-exome sequencing (WES) have improved the detection of disease-associated variants, revealing that the same genetic variants—often in a heterozygous state—may lead to adult-onset cholestatic disease, with milder or atypical presentations, while still conferring a significant risk of progressive liver injury and related complications. To assess the diagnostic yield and clinical utility of NGS panels and WES in adults with suspected PFIC or unexplained cholestatic liver disease, focusing on variant interpretation, emerging disease-associated genes, and clinical significance of VUS. A literature review was conducted to assess molecular diagnostics in adult cryptogenic cholestasis, with a focus on studies employing targeted NGS panels and WES. Selected studies were examined for diagnostic yield, variant classification, interpretive challenges, including VUS, and integration with clinical data. Data on patient demographics, sequencing techniques, and variant interpretation strategies were extracted to evaluate the current capabilities and limitations of genomic testing. From an initial search of 211 publications, 15 studies met the inclusion criteria, comprising five large adult cohorts and ten single-patient or trio-based reports. Across 72 patients, sequencing technologies identified 75 pathogenic or likely pathogenic variants, predominantly missense mutations, demonstrating high genetic heterogeneity. The most implicated genes included ABCB4, ABCB11, ATP8B1, TJP2, and USP53, with diagnostic yields ranging from 13.2% in large heterogeneous cohorts to substantially higher rates in carefully selected individual cases. VUS were identified in up to 67% of cases, highlighting the need for multidisciplinary interpretation integrating clinical, biochemical, and genetic data. Emerging evidence also implicated ciliopathy-associated genes such as DCDC2, NPHP3, PKHD1, TULP3, and TTC21B, expanding the genetic spectrum of adult cholestasis. Clinically, presentations ranged from mild biochemical abnormalities to progressive cholestasis, with pruritus being a common feature across studies. Comprehensive genetic testing significantly enhances diagnostic accuracy, informs prognosis, and guides individualized management in adults with cryptogenic cholestasis. Emerging evidence suggests that ciliopathy-associated genes may contribute to the genetic architecture of adult cholestatic disorders, further expanding the spectrum of disease-associated genes. However, the high prevalence of VUS remains a major challenge, highlighting the need for functional studies, longitudinal follow-up, and improved variant interpretation frameworks. As genomic technologies and analytical approaches continue to evolve, genetic testing is expected to play an increasingly central role in precision hepatology. Full article

Aqueous two-phase systems (ATPSs) provide a versatile, fully aqueous platform for probing solute–water interactions and protein structure. This review first surveys the diversity and phase behavior of biphasic aqueous systems formed by polymers and salts. We describe how phase diagrams characterize ATPS formation and composition and how both polymer chemistry and salt identity, rather than molecular size alone, govern phase separation by modulating the solvent properties of water. Building on a modified binodal model, we show that phase separation and solute partitioning can be understood in terms of changes in aqueous solvent dipolarity/polarizability, hydrogen-bond donor/acceptor properties, hydrophobicity, and electrostatics, quantified via solvatochromic probes and homologous solute series. These measurements underpin solvent interaction analysis (SIA), in which the partition coefficients of small molecules and proteins across panels of ATPSs are used to generate “structural signatures” that sensitively report on amino acid substitutions, conformational changes, aggregation, ligand binding, osmolyte effects, and post-translational modifications, independent of protein size. We discuss how SIA can be implemented in vial-, plate-, and microfluidic formats and combined with diverse analytical readouts (HPLC, MS, colorimetric assays, and immunoassays), and we contrast this structure-focused approach with conventional concentration-only proteomic and biomarker strategies. Particular emphasis is placed on structure-based biomarker discovery, where disease-relevant shifts in proteoform distributions—especially glycosylation changes—are often more informative than bulk protein levels and where SIA can complement or simplify complex glycomics and top-down proteomics workflows. As a case study, we describe the recently FDA-approved IsoPSA assay, which applies SIA principles to prostate-specific antigen by measuring cancer-associated structural alterations in circulating PSA via its partition behavior in a proprietary ATPS. IsoPSA generates a single index that discriminates between high-grade prostate cancer and benign and low-grade conditions. Prospective, longitudinal, and MRI-integrated clinical studies demonstrate that IsoPSA improves pre-biopsy risk stratification, reduces unnecessary biopsies, and provides robust negative and positive predictive values within the PSA “gray zone.” Collectively, the data support aqueous solvent interaction analysis as a broadly applicable, mechanistically grounded technology for protein characterization, drug–protein interaction studies, and structure-centric biomarker development, exemplified by the clinical translation of IsoPSA. Full article

Rapid detection and quantification of epidemiologically important Salmonella enterica serovars are critical for poultry surveillance, food safety monitoring, and risk-based intervention strategies. This study performed comprehensive analytical validation together with a preliminary field-based diagnostic performance evaluation of GenoPATHX™, a multiplex probe-based qPCR platform designed for the simultaneous detection and quantification of priority Salmonella serovars in poultry-associated matrices. The platform consists of two multiplex panels, designated the Chicken Key Performance Indicator (CKPI) and Turkey Key Performance Indicator (TKPI), each designed to detect priority poultry-associated Salmonella serovars together with a genus-level S. enterica marker. Analytical performance was evaluated for amplification efficiency, linearity, limit of detection (LoD₉₅), limit of quantification (LoQ), repeatability, intermediate precision, analytical specificity (inclusivity/exclusivity), robustness, matrix effects, and performance in artificially inoculated matrices. Diagnostic performance was further assessed using naturally contaminated poultry environmental samples. The assay demonstrated robust amplification performance in both singleplex and multiplex formats, with high linearity (R² = 0.987–0.999) and LoD₉₅ values ranging from 60 to 545 genome equivalents per reaction. Complete analytical inclusivity and high exclusivity were achieved for the evaluated isolate panel. In field samples, the direct GenoPATHX™ workflow demonstrated 81.0% sensitivity, 91.3% specificity, and substantial agreement with the USDA-FSIS reference culture method (κ = 0.73). Overall, GenoPATHX™ exhibited robust analytical performance and enabled rapid, same-day quantitative detection of priority Salmonella serovars in poultry-associated matrices, supporting its application for poultry surveillance and food safety monitoring. Full article

Diabetic retinopathy (DR) and glaucoma, globally leading causes of irreversible blindness, can be detected and managed early with timely screening. In low-resource settings, access to ophthalmological examination is limited by a variety of constraints, including scarcity of specialists, equipment costs, geographic distance from care centers, and limited patient awareness. This narrative review examines the principal barriers to early detection of glaucoma and DR and evaluates evidence-based strategies to overcome them, including low-cost portable ophthalmic testing tools, artificial intelligence (AI) analytics, risk-based resource allocation, teleophthalmology, and targeted patient education. In different populations, these strategies have been shown to meaningfully increase access to ophthalmologic screening and follow-up at a significantly lower cost. We describe these approaches, demonstrate previously successful initiatives, and propose various combined approaches adapted to the specific needs of the various low-resource settings. Full article

Background: Drilling slurry, a waste material generated during natural gas extraction, requires careful chemical characterization to determine its environmental hazard classification and inform appropriate management strategies. Methods: This study characterizes the drilling fluid used as raw material and the resulting drilling slurry waste, using a case study sample from the Buzău extraction area (Well 1 Florica, S.N.G.N. Romgaz S.A.), including total composition analysis, three-stage leaching tests, linear regression of leaching kinetics, and standardized geoaccumulation indices (Igeo, CF, PLI). Results: Total composition analysis confirmed low heavy metal concentrations (Cd = 0.02, Cr = 0.05, Pb = 0.64, Zn = 2.82 mg/kg dry matter). All leachate parameters remained below non-hazardous waste thresholds (Order No. 95/2005), with safety factors of 20–100× for regulated metals and 1.2–2.7× for chlorides, sulphates, and dissolved organic carbon. Standardized pollution indices confirmed Class 0 (unpolluted) status for all five metals, with a composite Pollution Load Index of 0.0124. Leaching regression analysis revealed dissolution-controlled release for chlorides, sulphates, and zinc (R² > 0.93) versus matrix-retention behavior for copper, nickel, cadmium, and chromium. Comparative analysis showed horizontal drilling generates approximately 146% more waste volume than conventional vertical drilling (170 m³ versus 69 m³ at 2100 m depth). Conclusions: The analyzed drilling slurry meets non-hazardous waste classification with substantial safety margins, corroborated by three independent analytical frameworks. Waste minimization strategies and biodegradable fluid substitution offer practical pathways to reduce the environmental footprint of natural gas drilling operations. Full article

Chimeric antigen receptor (CAR) T-cell therapies have demonstrated remarkable clinical efficacy in hematological malignancies, yet their broader application is constrained by manufacturing complexity and variability, particularly in autologous settings. The development of allogeneic CAR T-cell therapies offers a promising alternative by enabling scalable, “off-the-shelf” production; however, these approaches introduce additional challenges related to donor variability, genome editing, and product consistency. Robust analytical strategies are therefore required to ensure safety, efficacy, and batch-to-batch reproducibility. Conventional analytical methods, such as flow cytometry and enzyme-linked immunosorbent assays, provide targeted, high-confidence measurements of predefined cellular and soluble markers but are inherently limited in their ability to capture the full molecular and functional complexity of CAR T-cell products. In current manufacturing paradigms, these assays are typically deployed as isolated quality control readouts rather than as components of an integrated control strategy that links donor variability, gene-editing material quality, in-process metabolic state, final product critical quality attributes, and clinical biomarker responses. In this context, mass spectrometry (MS) has emerged as a powerful platform for high-dimensional molecular characterization, enabling analysis of gene-editing reagents, proteins, metabolites, lipids, and both culture and spent-media composition across the CAR T-cell manufacturing workflow. In this review, we examine the various applications and tools of MS across key stages of the allogeneic CAR T-cell workflow, including donor characterization, analysis of gene-editing materials, in-process culture monitoring, drug product quality assessment, and post-infusion biomarker evaluation. Collectively, these approaches demonstrate the potential of MS-driven analytics to address current limitations in CAR T-cell manufacturing by improving process understanding, enabling comprehensive quality assessment, and supporting regulatory decision-making. The integration of MS into CAR T-cell workflows may ultimately facilitate the development of more consistent, scalable, and effective cell therapies. Full article

Introduction: Proper analysis of high-throughput lipidomic data requires specialized tools for data processing, normalization, visualization, and statistical and bioinformatic analysis. However, limitations in lipid parsing, data processing, and visualization capabilities in existing software packages create challenges for comprehensive lipidomic data analysis. To address these limitations, we developed LipidAnalyst (v 1.0.3), a user-friendly tool designed to facilitate efficient lipid parsing and processing, visualization, and analysis of lipidomic datasets. Methods: LipidAnalyst was developed using the R Shiny framework. It is hosted on MiServer for online work but can also be downloaded from GitHub. Results: LipidAnalyst provides functionalities in three major areas: data processing, visualization, and statistical analysis. Data processing features include quality control filtering, normalization, internal standard-based quantification, and unique capabilities for missing-value imputation, lipid parsing, and aggregation. Visualization tools include box and violin plots for data distribution assessment, principal component analysis (PCA) plots, hierarchical clustering and differential abundance heatmaps, volcano plots, correlation plots, and Debiased Sparse Partial Correlation (DSPC) clustering plots. Statistical analysis modules include t-test, analysis of variance (ANOVA), Partial Least Squares Differential Analysis (PLS-DA), Orthogonal Partial Least Squares Differential Analysis (OPLS-DA), and Random Forest (RF) modeling. Conclusions: LipidAnalyst is a comprehensive platform for optimal processing, visualization, and analysis of lipidomic data. By integrating advanced data processing workflows with extensive visualization and statistical analysis capabilities, LipidAnalyst enables researchers to explore lipidomic datasets more effectively and develop informed analytical strategies. Full article

Recent advances in artificial intelligence have transformed recipes from static textual artifacts into computational objects that support design, generation, and personalized recommendation. However, existing studies remain fragmented, typically addressing these tasks in isolation and lacking a unified analytical framework. This paper presents a comprehensive survey of recipe intelligence by systematically integrating recipe design, recipe generation, and recipe recommendation within a coherent computational framework. We review representative methods across these three tasks, including knowledge-based design systems, statistical and neural sequence generation models, cross-modal vision-language generation methods, pretraining- and retrieval-augmented generation approaches, and behavior-, context-, semantic-, and goal-driven recommendation methods. Particular attention is given to how these methods represent culinary knowledge, model user preferences, handle constraints, and support personalization. We further summarize commonly used datasets, data acquisition and processing strategies, and evaluation protocols, thereby clarifying the empirical foundations of current recipe intelligence research. Finally, we discuss key challenges and outline future directions toward unified, controllable, and interactive recipe intelligence systems. Full article

The chemical composition of chocolate is influenced by multiple factors, including cocoa genotype, fermentation, roasting, and formulation, which complicate the identification of reliable compositional descriptors. In this study, amino acid and biogenic amine profiles were determined by LC–MS/MS in 91 commercial dark chocolates (56–100% cocoa content) to assess their potential for product characterization. Because the analytical sequence extended over several days, different signal-correction strategies (including internal standard normalization and quality-control-based drift correction) were evaluated to compensate for instrumental variability prior to chemometric analysis. Signal reductions of up to 91% were observed, and the selected correction procedures improved measurement precision by up to 18-fold. A total of 19 amino acids and 8 amines were detected, with tyrosine, hydroxyproline, proline, leucine, phenylalanine, and valine being the most abundant compounds. Principal Component Analysis revealed a compositional gradient primarily associated with cocoa content, whereas classifications based on cocoa variety, geographical origin, and certification status showed limited discrimination. In contrast, Partial Least Squares-Discriminant Analysis achieved a balanced classification accuracy of 75.2% under repeated M-fold cross-validation when classifying samples according to manufacturer. Furthermore, permutation tests were carried out, confirming that the observed classification performance was highly unlikely to arise by chance. These findings indicate that amino acid and biogenic amine profiles in commercial dark chocolates are influenced mainly by cocoa content and manufacturer-related factors, whereas the effects of cocoa origin and variety appear less evident within the products evaluated. Full article