Search Results (2,662)

Sudden tailings dam breaches trigger large-scale heavy metal compound pollution in coupled surface water–groundwater systems, requiring systematic full-cycle ecological damage quantification tools applicable to diverse contamination types. This study constructs an integrated full-cycle ecological damage assessment framework for sudden water pollution accidents, integrating three core modules: multi-model pollutant migration prediction, multi-scale aquatic biological damage diagnosis, and three-dimensional ecological-economic loss accounting. The framework adopts a modular design that can potentially accommodate heavy metals (Cd, Cr, As, Pb) and organic pollutants such as polycyclic aromatic hydrocarbons (PAHs), with standardized molecular, individual, and population-level biological endpoints and corresponding pollutant dose–response templates reserved as reference calculation modules. However, applicability beyond this case has not been validated and requires case-specific calibration. To verify the operability and accuracy of the proposed integrated system, a typical tailings dam leakage incident dominated by hexavalent chromium (Cr(VI)) and arsenic (As) pollution was selected as the practical validation case; all field monitoring, pollutant simulation, and final economic loss quantification in this case exclusively rely on on-site measured Cr(VI) and As data, while Cd and PAH-related biological response curves and remediation cost formulas retained in the manuscript only serve as illustrative universal template components of the framework rather than case-measured results. For the Cr(VI)/As pollution case, the advection–diffusion model simulation revealed that the Cr(VI) contamination plume horizontally spread 250 m within 48 h and extended to 560 m after seven days, and anaerobic groundwater environments drove the transformation of toxic mobile trivalent arsenic (As(III)) from primary pentavalent arsenic. The calibrated SWAT model achieved Nash–Sutcliffe efficiency (NSE) coefficients of 0.75 for dissolved Cr(VI) and 0.68 for particulate As. The graph theory-based rapid prediction model cut computation duration down to minutes; when validated against independent field monitoring data, it yielded an average relative error of 14.2%, and its consistency with the SWAT model reached 10.5% relative deviation, satisfying the accuracy requirement for emergency early warning. Field biological monitoring demonstrated substantial ecological impairment: metallothionein (MT) expression in fish tissues was markedly elevated (the reported 6.2-fold induction value derives from standard Cd exposure template tests within the framework, with analogous MT upregulation also observed for field Cr(VI)/As co-stress), and benthic community Shannon diversity declined by over 50% in polluted river reaches. The standardized Ecological Damage Index (EDI) of the case was calculated as 480.2, indicating severe aquatic ecosystem damage, with total comprehensive ecological and economic losses reaching 17.25 million CNY. This study innovatively couples high-precision physical transport models with fast emergency prediction algorithms and establishes a complete multi-tier biological indicator chain linking molecular biomarkers to community integrity metrics; the three-dimensional loss accounting system integrating ecosystem service impairment, restoration expenditure, and post-pollution recovery loss realizes closed-loop full-cycle damage evaluation. The proposed framework, demonstrated for Cr(VI) and As pollution, has a modular design that may potentially be extended to other pollutants such as Cd and PAHs by adjusting model parameters, providing a quantitative reference for emergency disposal, pollution remediation, and ecological compensation of water contamination accidents, although further validation across different pollutants and hydrological settings is required. Full article

Background/Objectives: Transcranial magnetic stimulation (TMS) initiates a cascade from intracranial electric-field exposure through neural recruitment and plasticity to distributed network responses. Neuronavigation improves the geometric reproducibility of delivery but does not guarantee equivalent cortical exposure or target engagement. This narrative review integrates these levels within an operational framework for precision TMS. Methods: Six domain-specific PubMed searches covering 1 January 1985 to 31 July 2026 were supplemented by Google Scholar and citation tracking. A documented rerun on 17 August 2026 yielded 6430 records (5617 unique after cross-query deduplication). Evidence was synthesized narratively; no quantitative synthesis or formal risk-of-bias assessment was performed. Results: Neuronavigation improves geometric precision by stabilizing target definition and coil pose, whereas individualized electric-field models estimate intracranial exposure. Neither establishes biological precision, which also depends on neuronal orientation, brain state, circuit architecture, medication, and behavior. Motor-system measures are not validated as universal biomarkers for nonmotor cortex, and no single validated biomarker captures TMS-induced plasticity. Convergent, controlled multimodal evidence may strengthen inference about target engagement; adaptive and closed-loop approaches remain experimental. Conclusions: Geometric delivery, modeled exposure, biological engagement, and durable functional or clinical benefit require separate validation. Spatial accuracy alone does not establish clinical value. Full article

Quantitative EEG features such as frontal alpha asymmetry, spectral ratios and signal-complexity measures are often presented as interpretable biomarkers of emotion. Such claims require the markers to generalize across individuals, yet common evaluation protocols allow overlapping epochs and recordings from the same participants to appear in both training and test sets. We re-evaluated qEEG-based valence and arousal recognition on DEAP and DREAMER under trial-grouped, participant-independent, within-participant and cross-dataset protocols. Epoch-pooled evaluation on DEAP gave ROC-AUC values of 0.689 for valence and 0.711 for arousal, whereas participant-independent evaluation of the same features and model returned 0.493 and 0.447. Grouping epochs by trial accounted for about 0.06 of that difference and separating participants for a further 0.13 to 0.17. The same features identified participants with accuracy of 0.998 on DEAP and 0.891 on DREAMER, and a predictor that used no EEG, assigning each trial its participant’s training-set positive rate, accounted for 42 to 84 percent of the above-chance discrimination of the epoch-pooled model. Emotion-related effects were reproducible within participants on DEAP but close to zero on DREAMER, and their direction reversed for about 40 percent of features across participants. In a matched participant-level comparison using a single fixed estimator in both arms, training on a participant’s own data improved DEAP valence by 0.092 AUC (95% CI 0.029 to 0.157, Holm-adjusted $p=0.042$) and gave no reliable benefit for DEAP arousal or for either DREAMER target. Across the channels shared by the two datasets, per-feature arousal effect sizes correlated moderately, although no individual feature reached false-discovery-rate significance in both datasets. Pooled qEEG emotion-recognition scores can therefore reflect participant-specific recording structure rather than transferable affective information. Population-level claims require participant-independent evaluation, while personalization should be considered only where stable within-person effects are demonstrated. Full article

Cancer, the second leading cause of death worldwide, is a significant global challenge, and widespread, accessible, and early diagnostics are recognized as the most cost-effective strategies for reducing cancer burdens. Point-of-care (POC) systems offer an attractive alternative by enabling rapid and cost-effective diagnoses. We introduce a novel POC strategy for cancer biomarker identification based on monitoring the isothermal amplification of relevant cancer markers using a portable Arduino-based loop-mediated isothermal amplification (LAMP) system. The trajectory of the LAMP reaction during the first 3 min of the reaction is used as an indicator of the rate of amplification (defined as the m_P3 value). We obtained sets of m_P3 values that showed statistically significant differences in the genetic expression of four genes (ESR 1, PGR, Her2, and Ki67) within and between tissue spheroids derived from the MCF7, MDA-MB-231, Du145, and BJ fibroblast cell lines. We then used principal component analysis and clustering techniques to demonstrate that the m_P3 value sets derived from the expression of the four selected genes are sufficient to distinguish tissue spheroids derived from four different commercial cell lines. Further qPCR and immunostaining assays confirmed the quantitative LAMP (qLAMP) experimental trends. The immunostaining results were consistent with previous literature reports and with our qLAMP and qPCR results. We present a proof-of-concept demonstration of the use of a LAMP-based POC platform for the identification or discrimination of cancer tissues. Our strategy can be extended to other diseases associated with altered gene expression in body tissues or fluids. Full article

Background: Diagnostic evaluation of suspected neuromyelitis optica spectrum disorder (NMOSD) integrates AQP4-IgG testing, clinical assessment, neuroimaging, and exclusion of alternative inflammatory demyelinating disorders; nevertheless, some patients remain diagnostically unresolved or may be misclassified as multiple sclerosis (MS) or other disorders. Methods: This single-center retrospective exploratory study analyzed quantitative serum proteomics from 20 patients with MS and 20 with NMOSD. Proteins meeting nominal p < 0.05 together with prespecified fold-change criteria were considered exploratory candidates. VWF, PPBP, and SERPINA3 were subsequently assessed by ELISA in a separate, non-overlapping cohort from the same center, together with routine hematological variables. Results: Among 261 protein entries, 34 met the exploratory nominal threshold and fold-change criteria, but none remained significant after Benjamini–Hochberg correction (lowest q = 0.0734). VWF and PPBP showed no significant differences across the four validation groups. SERPINA3 differed across groups (Kruskal–Wallis H = 44.982, p = 9.34 × 10⁻¹⁰) and was higher in NMOSD than in MS, TBI, and HCs after Holm adjustment (adjusted p = 0.036, 1.49 × 10⁻⁹, and 1.13 × 10⁻⁵, respectively). In the full ELISA cohort, the AUC was 0.928 for NMOSD versus HC and 0.800 for NMOSD versus MS. In a post hoc sensitivity analysis excluding participants with preceding infection, the NMOSD–MS separation was attenuated. In smaller complete-case analyses, adding an additional laboratory variable to SERPINA3 did not significantly improve apparent discrimination. Conclusions: SERPINA3 is therefore an exploratory adjunctive serum biomarker candidate rather than a stand-alone diagnostic test; prospective external validation in clinically representative cohorts is required. Full article

The role of adamalysins (ADAMs) has been widely described in many processes related to carcinogenesis, angiogenesis, inflammation, metastasis, and metabolic disorders. Despite numerous studies, their role in colorectal cancer (CRC) remains unclear. The aim of this study was to evaluate the expression of selected ADAM genes in colorectal cancer tissue and corresponding surgical margins. In addition, for a subgroup of patients, the expression of selected proteins from the ADAM family was assessed. The final study group consisted of 67 patients who underwent elective surgery for colorectal cancer. The relative expression of the ADAM10, 12, 17, and 28 genes was expressed as relative quantification (RQ) and determined by real-time quantitative PCR (RT-qPCR) in tumor tissue and surgical margins. In addition, for a subgroup of 45 patients, the expression of ADAM10, 12, and 17 proteins was assessed by ELISA. Associations between ADAM expression and clinicopathological parameters were analyzed statistically. ADAM12 gene expression was significantly higher in tumor than in margin tissue (median RQ: 0.995 vs. 0.251; p = 0.003), whereas ADAM28 RQ was significantly higher in the margin (median RQ: 0.400 vs. 0.204; p = 0.021). No significant differences were observed in the expression of the ADAM10, ADAM12, ADAM17, or ADAM28 genes based on tumor stage, sex, substance use, BMI, or age, except for nominally higher ADAM12 gene expression in patients over 65 years of age (p = 0.033). Among patients under 65 years of age with cardiovascular disease (CVD), ADAM28 RQ in tumor tissue was significantly higher than in those without CVD (p < 0.05). In obese patients with CVD, a markedly increased expression of ADAM28 in tumor tissue was observed, regardless of age (1.469 vs. 0.132; p < 0.005). Significant positive correlations were observed between the ADAM10 and ADAM17 RQ, and between the ADAM10 and ADAM28 RQ, in both tumor and marginal tissues (all adjusted p < 0.01). No significant correlations were found between gene expression and corresponding protein levels for ADAM10, ADAM12, or ADAM17. ADAM10, 12, 17, and 28 are poor biomarkers for colorectal cancer, but their significance may increase in patients with comorbid metabolic disorders. The lack of correlation between protein expression and gene expression suggests the contribution of post-transcriptional and post-translational regulatory mechanisms, which justifies further research. Full article

Background: Optical coherence tomography angiography (OCTA) provides quantitative metrics of the retinal microvasculature, most prominently vessel density (VD), that are increasingly used as biomarkers in ocular, systemic, and cerebrovascular disease. Because OCTA relies on the detection of flow-related motion contrast, image quality has emerged as a pervasive determinant of these metrics, yet its effect has been reported in fragmentary and non-comparable ways across the literature. Methods: We identified OCTA studies indexed in PubMed that examined the relationship between image quality and quantitative OCTA parameters, and we summarised their methods and findings across the macular, foveal avascular zone, and peripapillary regions and across vascular layers. We integrated directly comparable per-unit scan-quality effects using random-effects meta-analysis and separately synthesized direct cross-sectional Pearson correlations between manufacturer-reported image quality and macular vessel-density outcomes from independent healthy cohorts. Results: Higher image quality was associated with higher measured vessel density in every contributing dataset. On the Optovue scan-quality (SQ, 0–10) scale, superficial macular VD increased by 3.46% (95% CI 1.85–5.07) per SQ unit in controlled signal-attenuation experiments and by covariate-adjusted observational estimates ranging from 0.90% to 2.16% per SQ unit; a combined order-of-magnitude estimate across both estimator types was 1.64% (95% CI 1.15–2.12). Peripapillary estimates were heterogeneous and derived from only two independent cohorts; they were therefore summarised descriptively rather than pooled. Across three independent externally authored healthy cohorts reporting direct cross-sectional Pearson correlations, higher image quality was strongly associated with higher macular vessel-density outcomes (random-effects pooled r = 0.64, 95% CI 0.50–0.75; I² = 49%). Conclusions: Image quality is an important, directional confounder of VD-based OCTA metrics whose magnitude can rival the biological or physiological signal of interest. Platform-appropriate standardisation, transparent reporting, and consideration of image quality in acquisition and analysis are therefore important for the valid interpretation of vessel-density measurements, particularly in functional and longitudinal studies. Full article

Background: In recent decades, the incidence of colorectal cancer (CRC) has been rising worldwide. CRC ranks second in cancer-related mortality. The identification of reliable biomarkers for early diagnosis and prognosis prediction, along with a deeper understanding of the underlying molecular events, holds substantial promise for improving patient outcomes. The tissue inhibitor of the metalloproteinase 1 (TIMP1) gene is overexpressed in various gastrointestinal malignancies and contributes to tumor progression. However, its role in regulating the CRC tumor immune microenvironment (TIME) and its potential as a clinically actionable prognostic biomarker remain unclear. Methods: To probe how TIMP1 acts as a prognosis-related candidate biomarker in colorectal carcinoma, TCGA-derived datasets were adopted to conduct Kaplan–Meier survival assessment. We also investigated the connection between the expression abundance of TIMP1 and the infiltration of immune populations and intratumoral lymphocytes; furthermore, immune checkpoint-related genes were systematically assessed across multiple tumor types via the TISIDB and TIMER2.0 platforms, with particular emphasis on CRC. We adopted the ESTIMATE scoring system to figure out how TIMP1 gene expression correlates with the phenotypic properties of the colorectal-cancer TIME. We relied on the limma toolkit for the screening of differential transcripts from high-TIMP1 and low-TIMP1 cohorts. Enrichment assessments covering Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes entries were then carried out to predict the potential biological pathways associated with TIMP1. We constructed the protein–protein interaction map for TIMP1-interacting partners via the STRING repository. To further explore TIMP1-correlated genes, we performed Venn diagram intersection analysis combined with Spearman’s correlation test. Finally, quantitative reverse-transcription PCR was then implemented to detect TIMP1 messenger-RNA abundance inside the RKO colorectal carcinoma cell line as well as normal colonic epithelial CCD-18Co cells, which offered in vitro experimental verification for our bioinformatic outcomes. Results: According to outcome data, TIMP1 transcripts were markedly up-regulated in CRC specimens and cell lines relative to normal samples. Elevated TIMP1 expression served as a poor-prognosis indicator for overall survival (hazard ratio [HR] = 0.43, 95% confidence interval [CI] = 0.29–0.64, p < 0.001) and disease-specific survival (HR = 0.39, 95% CI = 0.22–0.68, p = 0.001) among colorectal-carcinoma patients. TIMP1-high and TIMP1-low groups exhibited notable differences in immune cell infiltration (CD8⁺ T, macrophage, mast, neutrophil, B, monocyte, dendritic, and CD4⁺ T cells). TIMP1 expression was also significantly correlated with tumor-infiltrating lymphocytes, key immune checkpoint genes (e.g., CD274 [PD-L1] and CTLA4), and immunomodulatory chemokines (e.g., CCL3 and CCL5). Twelve TIMP1-interacting DEGs were selected: COL5A1, FN1, PRG4, and a cluster of nine MMPs (MMP1/2/3/7/8/9/11/13/14), all of which showed significant positive correlations with TIMP1 (r = 0.31–0.63, all p < 0.001). Conclusions: TIMP1 expression correlates with features of the tumor immune microenvironment and extracellular matrix remodeling in CRC, suggesting that TIMP1 shows potential as a candidate biomarker. However, its potential as a therapeutic target warrants further experimental investigation. Full article

Preclinical models play a critical role in the development of PSMA-targeted radiopharmaceuticals for prostate cancer. However, many existing models have practical limitations, including slow tumor growth, low engraftment rates, and restricted availability, and all human PSMA-positive lines are confined to immunodeficient hosts. We developed and characterized a novel PSMA-expressing transgenic cell line, CT26-PSMA, as a practical tool for preclinical screening of PSMA-targeting agents. The CT26-PSMA cell line was established by stable transfection of the murine colon carcinoma CT26 cell line with human PSMA using the Sleeping Beauty transposon system. PSMA expression was confirmed by RT-qPCR (reverse transcription quantitative polymerase chain reaction), flow cytometry, and radioligand saturation binding on intact cells. Two [⁶⁸Ga]Ga-labeled radioconjugates—the well-established PSMA-617 and a newly synthesized conjugate (Conjugate-1)—were used to validate the functionality of the model through in vitro binding, uptake and internalization studies, and through ex vivo biodistribution in CT26-PSMA tumor-bearing athymic male nu/nu mice. The CT26-PSMA cell line demonstrated high and stable PSMA expression, with approximately 95% of cells expressing the biomarker and no measurable loss over 16 passages in antibiotic-free medium. Saturation binding gave a receptor density of ∼3.5 × 10⁶ sites per cell, approximately four-fold higher than that of LNCaP cells (∼0.8 × 10⁶), with dissociation constants that were indistinguishable between the two radioconjugates and between the two cell lines (K_d 9.0–11.6 nM). Subcutaneous tumors reached ~300 mm³ within 8–10 days of inoculation, with a take rate of 10/10 versus 1/10 for LNCaP (Fisher’s exact test, p = 1.2 × 10⁻⁴). Both radiotracers showed saturable, 2-PMPA-blockable binding and uptake in CT26-PSMA cells, confirming the functional activity of the recombinant receptor. Biodistribution studies revealed accumulation of both conjugates in CT26-PSMA tumors, with generally comparable tumor-to-background profiles. The CT26-PSMA cell line represents a robust, rapid, and reproducible platform for preclinical evaluation of PSMA-targeting radiopharmaceuticals, and its murine BALB/c origin permits engraftment in immunocompetent or minimally immunosuppressed hosts, whereas existing human PSMA-positive lines do not. It is intended as a screening platform rather than as a model of prostate cancer biology. The validation data obtained with [⁶⁸Ga]Ga-labelled conjugates confirm the suitability of this cell line for future studies of PSMA-directed compounds. Full article

Platelet-rich plasma (PRP) has emerged as one of the most extensively investigated orthobiologic therapies for tendon disorders because of its potential to modulate inflammation, enhance extracellular matrix remodeling, and promote tissue regeneration through the delivery of concentrated platelets and bioactive molecules. However, despite compelling biological rationale and encouraging preclinical evidence, clinical outcomes remain inconsistent across different tendon pathologies. This narrative review critically examines the principal biological and methodological factors underlying this variability, including differences in cellular composition, growth factor and cytokine profiles, activation strategies, and current PRP classification systems. We further synthesize the available clinical evidence across major tendon disorders, highlighting the influence of disease-specific biology, product heterogeneity, and procedural variability on treatment response. In addition, the emerging role of quantitative imaging biomarkers in objectively evaluating tendon regeneration is discussed as a complementary tool for biological outcome assessment. Based on the evidence reviewed, we propose the quantifiable platelet-rich plasma (Q-PRP) framework, a practical reporting model that integrates cellular, molecular, procedural, and clinical variables into a standardized approach for biologically meaningful PRP characterization. Rather than replacing existing classification systems, the proposed framework aims to improve reproducibility, facilitate cross-study comparison, and support the transition toward precision regenerative medicine. Standardized biological characterization, combined with objective outcome assessment, may represent a critical step toward optimizing PRP research and clinical application in tendon healing. Full article

Diffusion-weighted imaging (DWI) has evolved from a niche research sequence into an increasingly valuable adjunct to conventional magnetic resonance imaging (MRI) in musculoskeletal (MSK) radiology. By providing qualitative and quantitative information on tissue microstructure through assessment of water diffusion and apparent diffusion coefficient (ADC) mapping, DWI offers functional insights beyond conventional morphological imaging. We aim to present the current evidence for DWI in MSK imaging organised around established applications and emerging applications, with particular emphasis on composition-related interpretive pitfalls relevant to differentiating tumours and other pathologies, and to review the technique’s evolving role in routine practice. This narrative review synthesises the current literature on the clinical utility of DWI in MSK imaging. It is structured in four parts: foundations and the tissue composition signal framework, including the basis of qualitative and quantitative assessment; established applications; emerging applications; and assessment of tissue composition-related interpretive as well as technical pitfalls, including those arising due to myxoid matrix, chondroid matrix, blood degradation products, organising thrombus, crystalline or mineralised material, keratinaceous debris, purulent content, cellular haematopoietic marrow, by using original cases from the authors’ institution, which have been confirmed either histologically or surgically. Applications are stratified by strength of evidence. Established applications of DWI include soft tissue abscess detection, differentiation of malignant from benign soft tissue tumours, differentiation of malignant from benign vertebral compression fractures, and myeloma staging and response assessment, as well as treatment response in soft tissue and bone sarcomas. Whole-body MRI with DWI for staging and response assessment in multiple myeloma is guideline-endorsed and supported by prospective multicentre data. Soft tissue abscess detection, soft tissue and bone tumour characterisation, and characterisation of vertebral compression fractures are supported by consistent evidence from multiple independent cohorts, although no universally transferable ADC threshold exists. The emerging applications, which are promising adjuncts supported by small, single-centre or heterogeneous studies with thresholds that have not been externally validated, include ADC ghost sign in osteomyelitis (high specificity but sensitivity of only 20%), peripheral nerve sheath tumour characterisation and surveillance in NF1 patients, peripheral neuropathy and plexopathy, predisposing conditions such as Li Fraumeni syndrome in paediatric cancers, inflammatory myopathy, and postsurgical assessment of residual disease, as well as opportunistic detection of venous thrombosis. Radiomics and machine learning approaches remain experimental. Recent technical advances, including reduced field-of-view imaging, multi-shot acquisition and improved fat suppression, have mitigated but not eliminated historical limitations of susceptibility artefacts and limited spatial resolution. DWI has become an important functional imaging technique that complements conventional MRI across a broad range of musculoskeletal disorders. Understanding the relationship between tissue composition and the diffusion signal is central to both interpreting DWI correctly and avoiding its characteristic pitfalls. DWI is best regarded not as a stand-alone technique but as one component of a multiparametric assessment, in which its functional information is integrated with conventional morphological imaging. Ongoing technical improvement and expanding clinical evidence are expected to further support its integration into routine MSK imaging and its development as a quantitative biomarker for diagnosis, prognostication, and treatment monitoring. Full article

Background/Objectives: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Conventional computed tomography (CT) is the preferred imaging modality for evaluating pulmonary nodules because of its high spatial resolution; however, it primarily provides morphological information, including lesion size, shape, and density. Dual-energy CT (DECT), a more recent imaging technique, uses two different energy levels to enable material decomposition and quantitative parameter assessment. These parameters may provide additional information regarding tumor perfusion, vascularization, and tissue composition. This rapid review aimed to evaluate the current evidence regarding the clinical utility of DECT in the detection, characterization, and staging of lung tumors. Methods: This rapid review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A literature search was performed in the PubMed and Cochrane Library databases for studies published between 2005 and 2026. Studies were included if they evaluated the detection, characterization, or staging of lung tumors using quantitative DECT parameters. Case reports, editorials, duplicate studies, and studies without quantitative DECT data were excluded. Descriptive data analysis was performed using Microsoft Excel. Results: A total of 24 studies were included, comprising 18 retrospective (75%) and 6 prospective studies (25%). Only one study evaluated the role of DECT in lung tumor detection, demonstrating improved detection of mixed ground-glass nodules and invasive adenocarcinoma. Significant correlations were found between iodine uptake and tumor perfusion, highlighting the potential of DECT to improve differentiation between benign and malignant lesions. Several studies also demonstrated associations between DECT parameters and tumor biomarkers, including Ki-67 Proliferation Index (Ki-67) expression, Epidermal Growth Factor Receptor (EGFR) mutation status, Programmed Death-Ligand 1 (PD-L1) expression, and treatment response in non-small cell lung cancer. In addition, DECT provided complementary metabolic information regarding tumor malignancy and showed correlations between iodine uptake and fluorodeoxyglucose (FDG) parameters. Associations between iodine volume and tumor differentiation grade were also reported. One study demonstrated the potential role of DECT in tumor staging by predicting mediastinal lymph node metastasis. Across all included studies, iodine-based parameters (50%), radiomics and material decomposition parameters (16.67% each), and spectral attenuation parameters (12.50%) were the most frequently investigated DECT metrics. Conclusions: DECT appears to be a promising complementary imaging technique that provides quantitative perfusion-related and compositional surrogate information beyond the morphological assessment offered by conventional CT. However, the current evidence remains heterogeneous and is largely based on retrospective studies with relatively small patient cohorts. Larger prospective studies with standardized imaging protocols are necessary to further establish the clinical utility of DECT in lung tumors. Full article

Objectives: We sought to evaluate the early efficacy of faricimab (Vabysmo^®) in treating diabetic macular edema (DME) and to explore the predictive value of multi-slice optical coherence tomography (OCT) biomarkers for anatomical and visual outcomes. Methods: In this retrospective cohort study, 26 anti-VEGF-naive DME patients (36 eyes) treated with intravitreal faricimab were analyzed from baseline through 6 months of follow-up. Best-corrected visual acuity (BCVA) was recorded, while central subfield thickness (CST) and various OCT biomarkers were evaluated using multi-slice OCT quantitative analysis. Logistic and linear regression models were utilized to examine predictive factors, and scatter plots were employed to assess the correlation between anatomical improvement and functional visual gain. Results: Changes in CST and BCVA, along with the evolution and predictive power of OCT biomarkers—including vitreomacular interface (VMI), epiretinal membrane (ERM), disorganization of the retinal inner layers (DRIL), intraretinal cysts (IRCs), hyperreflective foci (HRF), hard exudates (HEs), large outer-nuclear-layer cavities (LONLCs), ellipsoid zone disruption (EZD), and subretinal fluid (SRF)—were assessed. Post-treatment CST demonstrated rapid and significant reduction, decreasing from 377.7 μm (95% CI: 347.0–408.4) at baseline to 312.8 μm (95% CI: 287.5–338.2; p < 0.0001) at month 3 and 291.5 μm (95% CI: 275.6–307.4; p < 0.0001) at month 6, with an approximately 48 μm reduction post-first injection. Overall intraocular pressure (IOP) and BCVA showed no statistically significant improvement. Baseline analysis indicated that EZD was significantly associated with older age (p = 0.029), worse initial BCVA (p = 0.005), and thicker CST (p = 0.002). After adjusting for initial CST in the linear regression model, we identified the presence of baseline HEs as the sole independent predictor of substantial anatomical improvement (B = 45.9, p = 0.002). Conclusions: Faricimab demonstrated rapid and significant early anatomical improvements. Baseline HEs independently predicted the extent of CST reduction, potentially reflecting the greater fluid burden of eyes with more severe barrier breakdown. Baseline EZD was observed exclusively among eyes that did not achieve complete anatomical remission, although the small number of EZD-positive eyes (n = 7) precludes firm conclusions. Full article

Background/Objectives: Distinguishing parathyroid carcinoma from parathyroid adenoma remains a major diagnostic challenge because these tumors frequently share similar clinical, biochemical, radiological, and histopathological features. Accurate diagnosis is essential for appropriate surgical management, highlighting the need for reliable adjunctive biomarkers. This study evaluated the diagnostic value of tumor angiogenesis, quantified by microvessel density (MVD), for differentiating parathyroid carcinoma from parathyroid adenoma and its association with clinicopathological characteristics. Methods: This retrospective study included 50 patients with primary hyperparathyroidism who underwent surgery at a tertiary endocrine surgery center, including 10 parathyroid carcinomas and 40 parathyroid adenomas. Tumor angiogenesis was assessed by immunohistochemical staining, and MVD was quantified in vascular hot spots using standardized methods. Receiver operating characteristic (ROC) analysis evaluated the diagnostic performance of MVD, while correlations with clinicopathological parameters were analyzed. Results: Parathyroid carcinoma demonstrated significantly higher MVD than parathyroid adenoma (median 901.14 vs. 431.24; p < 0.001). ROC analysis showed excellent diagnostic performance, with an area under the curve of 0.917. Higher MVD was positively associated with Ki-67 expression, preoperative parathyroid hormone and calcium levels, and tumor weight, indicating a close relationship between angiogenesis, tumor proliferation, biochemical disease severity, and tumor burden. No significant associations were observed with age or preoperative phosphate levels. Conclusions: Quantitative assessment of MVD is a promising adjunctive immunohistochemical biomarker for distinguishing parathyroid carcinoma from parathyroid adenoma. Incorporating MVD into conventional histopathological evaluation may improve diagnostic confidence, particularly in morphologically challenging cases. Larger multicenter studies are warranted to validate these findings and further establish the clinical utility of MVD. Full article

Obesity and type 2 diabetes (T2D) are multifactorial metabolic disorders characterized by progressive dysfunction of multiple organs and biological systems. Although mitochondrial dysfunction is a hallmark of disease progression, the mechanisms linking metabolic stress to coordinated tissue dysfunction remain incompletely understood. Comparative proteomic studies have consistently identified coordinated remodeling of oxidative phosphorylation, fatty acid oxidation, tricarboxylic acid cycle activity, redox regulation, mitochondrial proteostasis, and adaptive signaling across metabolically affected organs, revealing conserved organizational principles underlying mitochondrial adaptation. However, these findings have largely been interpreted within reductionist, pathway-centered frameworks. Here, we integrate evidence from comparative proteomics, mitochondrial biology, bioenergetics, redox biology, signaling, and systems biology to propose the concept of mitochondrial-centered biological networks (MCBNs), in which mitochondria function as dynamic regulatory hubs coordinating interconnected processes that collectively determine metabolic adaptation and tissue resilience. Building on this framework, we introduce the Mitochondrial Homeostasis Hypothesis, which proposes that preservation or restoration of mitochondrial homeostasis depends on coordinated regulation of MCBNs and constitutes a fundamental systems-level mechanism underlying resistance to obesity, T2D, and hypercaloric diet-induced metabolic dysfunction. Curcumin represents a well-studied network-modulating intervention that coordinately influences mitochondrial bioenergetics, metabolic flexibility, redox homeostasis, proteostasis, inflammatory signaling, and adaptive stress responses, supporting the concept that mitochondrial homeostasis is preserved through coordinated network regulation rather than isolated modulation of individual molecular pathways. Finally, we discuss how emerging technologies, including functional proteomics, redox proteomics, spatial and single-cell proteomics, acetylomics, integrated multi-omics, and artificial intelligence-assisted network analysis, provide unprecedented opportunities to quantitatively characterize MCBNs, validate the proposed hypothesis, identify network-based biomarkers, and accelerate the development of network-guided precision mitochondrial medicine. Full article