Biomedicines最新文献

Introduction/Object: Gastrointestinal cancers are among the most common types of neoplasms and are often associated with malnutrition, which affects physical performance, treatment tolerance and prognosis. This paper aims to synthesize, through a systematic search, the evidence on the impact of nutritional interventions on nutritional status in patients with digestive cancers prone to malnutrition. Methods: A systematic search was performed in PubMed, MDPI, Web of Science and ScienceDirect, for articles published between 2009 and 2025. Overall, 14,503 records were identified, and after screening of titles, abstracts and full-text evaluation, 80 studies (cross-sectional and cohort) were included. Data extraction was performed by a single researcher, using pre-established criteria and a standardized table, and the assessment of study quality was performed qualitatively, taking into account study design, sample size, nutritional assessment methods and clarity of reporting of results. Results: Evidence suggests that individualized and early applied nutritional interventions contribute to maintaining weight and protein status, improve tolerance to oncological treatments and may positively influence patient survival. Conclusions: Nutritional therapy plays a crucial role in preventing complications and supporting the body during oncological treatment, optimizing patients' quality of life. This review provides a clear synthesis of the current evidence and recognizes methodological limitations related to the qualitative assessment of the included studies.

Objectives: Respiratory motion degrades the quantitative accuracy and test-retest (TRT) reliability of fluorine-18 fluorodeoxyglucose ([¹⁸F] FDG) positron emission tomography (PET)/computed tomography (CT) in lung cancer. This study investigated whether a deep-learning-based respiratory motion correction (RMC) method improves the TRT reliability and image quality of [¹⁸F] FDG PET tumor quantification compared with non-motion-corrected (NMC) reconstructions. Methods: Thirty-one patients with primary lung cancer underwent three PET acquisitions: whole body free breathing (Scan1), thoracic free breathing (Scan2), and thoracic controlled breathing (ScanCB). Each dataset was reconstructed with and without RMC. Visual assessments of liver motion artifacts, lesion clarity, and PET-CT co-registration were scored. Lung tumors were segmented to derive standardized uptake value max (SUVmax), SUVmean, metabolic tumor volume (MTV), PET-derived lesion length (PLL), and total lesion glycolysis (TLG). Visual image scores and TRT reliability of tumor quantification were compared using Kruskal-Wallis one-way analysis of variance and intraclass correlation coefficients (ICCs). Results: RMC reconstructions achieved higher visual scores of lesion clarity and PET-CT co-registration across all lung lobes and significantly reduced liver motion artifacts compared with NMC reconstructions. Differences in SUVmax, SUVmean, PLL, MTV, and TLG between Scan2 and ScanCB were significantly smaller with RMC than with NMC. ICCs for SUVmax, SUVmean, MTV, and TLG were higher between scans with RMC than NMC reconstructions, indicating improved TRT reliability. Conclusions: The deep-learning-based RMC method improved the image quality and TRT reproducibility of [¹⁸F] FDG PET/CT quantification in lung cancer, supporting its potential for routine adoption in therapy-response assessments.

Background/Objectives: Ulcerative colitis (UC) is an inflammatory bowel disease and a major cause of ulcers and chronic inflammation in the colon and rectum. Recurring symptoms include abdominal pain, rectal bleeding, and diarrhoea, and patients with UC are at a higher risk of developing comorbidities such as colorectal cancer and poor mental health. In UC, the decreased diversity and changed metabolic profile of gut microbiota, along with a diminished mucus layer, leads to disruption of the underlying epithelial barrier, with an ensuing excessive and detrimental inflammatory response. Treatment options currently rely on drugs that reduce the inflammation, but less emphasis has been placed on improving the resilience of the epithelial barrier. Macrolide antibiotics exhibit epithelial barrier-enhancing capacities unrelated to their antibacterial properties. Methods: We investigated two novel barriolides, macrolides with reduced antibacterial effects in common bacterial strains. Gut epithelial cell barrier resistance in the Caco-2 cell line, with and without co-culture with mucus-producing HT-29 cells, was increased when treated with barriolides. Using ^AXGut-on-Chip technology with inflammatory cytokine-stimulated Caco-2/HT-29 co-cultures, the effectiveness of the barriolides was confirmed. Lastly, we reveal the barrier-enhancing and inflammation-reducing effects of the barriolides in a dextran-sulphate sodium (DSS)-induced colitis mouse model. Results: We show the predictive power of the novel ^AXGut-on-Chip system and the effectiveness of the novel barriolides. Indications include reduced inflammatory response, increased epithelial barrier and decreased overall clinical score. Conclusions: The results of this study indicate the notion that barriolides could be used as a treatment option for UC.

Background: Chronic urticaria (CU) is a complex skin condition, frequently challenging both patients and clinicians and requiring wise individualized management. While allergy, autoimmunity, and depression are recognized comorbidities, evidence linking CU and malignancy remains underexplored. Screening for malignancy is not a routine standard of care for CU patients. Methods: A literature review was conducted to explore the potential risk or associations, including immune mechanisms, between CU and malignancy, based on searches in the PubMed and Google Scholar databases. Results: Scientific evidence on the malignancy risk in CU and its causal relationship is limited to a few population-based studies and case reports. A higher incidence of hematologic malignancy in CU patients has been reported in several publications, but the overall risk of malignancy in the CU population remains controversial. Antihistamine resistance, ultra-low IgE, and older age at the time of CU diagnosis may be related to a higher risk of malignancy, especially shortly after CU diagnosis. Immunological pathways linking CU and cancer are not clear. Immune system dysregulation, including alterations in immune checkpoints, is a feature of both cancer and CU. Such dysregulation may promote immunotolerance, abnormal immune responses, and mast cell activation through novel autoantigens and autoantibodies involved in the tumor microenvironment. Conclusions: There is growing, although limited, evidence suggesting a possible link between CU and malignancy, especially hematologic cancers. Large multicenter cohort studies are warranted to determine whether CU may act as a clinical harbinger of malignancy and to identify patient subsets that may benefit from targeted cancer screening.

Introduction: The global prevalence of chronic kidney disease (CKD) is increasing and it is associated with higher mortality rates. Transforming growth factor-beta (TGF-β) can serve as a novel biomarker for early prediction of chronic kidney disease (CKD) progression. Methods: This was a prospective longitudinal study among black patients with CKD who attended the Charlotte Maxeke Johannesburg Academic Hospital between September 2019 and March 2022. Patients provided urine and blood samples for laboratory investigations at study entry (0) and at 24 months follow up. Baseline serum and urine TGF-β1, TGF-β2 and TGF-β3 levels were measured using ELISAs. Multivariable logistic regression analysis was utilized to determine if TGF-β isoforms could predict CKD progression. Results: A total of 312 patients were enrolled at baseline, of whom 275 (88.1%) had early-stage CKD (Stage 1-3). A majority, 95.2% (297/312), of the patients completed the study after 2 years follow up. The prevalence of CKD progression was 47.8% when measured by a sustained decline in eGFR of >4 mL/min/1.73 m²/year or more and 51.9% when measured by a change in uPCR > 30%. The patients with CKD progression had significantly lower eGFR and increased urine protein-creatinine ratios compared to non-progressors. Furthermore, comparing progressors with non-progressors, the median serum TGF-β1 was 21210 (15915-25745) ng/L vs. 24200 (17570-29560) ng/L and the median urine TGF-β3 was 17.5 (5.4-76.2) ng/L vs. 2.8 (1.8-15.3) ng/L, respectively. Baseline serum and urine TGF-β isoforms were unable to discriminate between CKD progressors and non-progressors after multivariable logistic regression analysis. Conclusions: Despite the multiple roles of TGF-β isoforms in kidney disease, baseline levels were not predictive of chronic kidney disease progression.

Background: Diagnosing CNS tumors through MRI is limited by significant variability in scanner hardware, acquisition protocols, and intensity characteristics at clinical centers, resulting in substantial domain shifts that lead to diminished reliability for automated models. Methods: We present a Domain-Adaptive MRI Learning Model (DA-MLM) consisting of an adversarially aligned hybrid 3D CNN-transformer encoder with contrastive regularization and covariance-based feature harmonization. Varying sequence MRI inputs (T1, T1ce, T2, and FLAIR) were inputted to multi-scale convolutional layers followed by global self-attention to effectively capture localized tumor structure and long-range spatial context, with domain adaptation that harmonizes feature distribution across datasets. Results: On the BraTS 2020 dataset, we found DA-MLM achieved 94.8% accuracy, 93.6% macro-F1, and 96.2% AUC, improving upon previously established benchmarks by 2-4%. DA-MLM also attained Dice score segmentation of 93.1% (WT), 91.4% (TC), and 89.5% (ET), improving upon 2-3.5% for CNN and transformer methods. On the REMBRANDT dataset, DA-MLM achieved 92.3% accuracy with segmentation improvements of 3-7% over existing U-Net and expert annotations. Robustness testing indicated 40-60% less degradation under noise, contrast shift, and motion artifacts, and synthetic shifts in scanner location showed negligible performance impairment (<0.06). Cross-domain evaluation also demonstrated 5-11% less degradation than existing methods. Conclusions: In summary, DA-MLM demonstrates improved accuracy, segmentation fidelity, and robustness to perturbations, as well as strong cross-domain generalization indicating the suitability for deployment in multicenter MRI applications where variation in imaging performance is unavoidable.

Background: Although Duchenne muscular dystrophy (DMD) is primarily characterized as a skeletal muscle-wasting disorder, the resulting pathophysiological changes extend to multiple non-muscle tissues and organ systems. Among these, renal and urinary tract dysfunctions have been reported, albeit in relatively few studies, as potential complications in DMD patients, sometimes occurring from an early age. Importantly, as life expectancy improves, the incidence of renal impairment is also expected to increase. This narrative review summarizes the available evidence on kidney involvement in DMD and discusses the associated biomarkers of renal dysfunction within the context of multisystem disease progression. Methods: The review draws on data from both human and animal studies and analyzes published evidence to explore kidney involvement in DMD, with a focus on clinical manifestations, biomarkers of renal dysfunction, and potential pathogenic mechanisms. Results: Available data indicate a close association between cardiac and renal dysfunction, particularly in patients with advanced-stage DMD. The review explores potential underlying mechanisms of renal impairment, including intrinsic dystrophin deficiency in the kidney, secondary effects of cardiovascular complications, and the nephrotoxic impact of drug therapies, highlighting renal function as an active determinant of clinical risk. Conclusions: While cardiac function monitoring is already a cornerstone of multidisciplinary care for this multisystem disease, systematic assessment of renal function should also be implemented, with implications for clinical management and drug safety. Moreover, the risk of drug-induced nephrotoxicity warrants attention in both clinical management and the development of novel therapeutic strategies for DMD.

The extracellular matrix (ECM) is a dynamic, tissue-specific network that integrates biochemical and mechanical cues to regulate cell behavior and organ homeostasis. Increasing evidence indicates that dysregulated ECM remodeling is an upstream driver of chronic human diseases rather than a passive consequence of injury. This review summarizes principles of ECM organization, mechanotransduction, and pathological remodeling and highlights translational opportunities for ECM-targeted therapies, biomaterial platforms, and precision diagnostics. We conducted a narrative synthesis of foundational and recent literature covering ECM composition and turnover, stiffness-dependent signaling, and disease-associated remodeling across fibrosis/cardiovascular disease, cancer, and metabolic disorders, together with advances in ECM-based biomaterials, drug delivery, and ECMderived biomarkers and imaging. Across organs, a self-reinforcing cycle of altered matrix composition, excessive crosslinking, and stiffness-dependent mechanotransduction (including integrin-FAK and YAP/TAZ pathways) sustains fibroinflammation, myofibroblast persistence, and progressive tissue dysfunction. In tumors, aligned and crosslinked ECM promotes invasion, immune evasion, and therapy resistance while also shaping perfusion and drug penetration. Translational strategies increasingly focus on modulating ECM synthesis and crosslinking, normalizing rather than ablating matrix architecture, and targeting ECM-cell signaling axes in combination with anti-fibrotic, cytotoxic, or immunotherapeutic regimens. ECM biology provides a unifying framework linking pathogenesis, therapy, and precision diagnostics across chronic diseases. Clinical translation will benefit from standardized quantitative measures of matrix remodeling, mechanism-based biomarkers of ECM turnover, and integrative imaging-omics approaches for patient stratification and treatment monitoring.

Background/Objectives: Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorders. Despite its multifactorial etiology, PD pathophysiology shared specific features such as cytoplasmic α-synuclein inclusions, oxidative stress, mitochondrial dysfunction, and impaired autophagy. Bromodomain and Extra-Terminal domain (BET) proteins, functioning as epigenetic readers, have recently emerged as promising therapeutic targets due to their regulatory role in redox homeostasis, neuroinflammation, and autophagy. However, their potential involvement in PD pathophysiology remains largely unexplored. Therefore, we aimed at evaluating whether BET modulation could ameliorate the parkinsonian phenotype in two cellular models. Methods: Differentiated SH-SY5Y and N1E-115 neuronal cells were exposed to rotenone toxin to mimic PD phenotype and co-treated with the small BET inhibitor JQ1. Results: BET inhibition significantly counteracted rotenone-induced cell death, neuromorphological alterations, and α-synuclein accumulation. These protective effects were accompanied by restoration of redox balance, as indicated by enhanced activation of the antioxidant system and suppression of the pro-oxidant NADPH oxidase complex. Moreover, JQ1 treatment alleviated mitochondrial dysfunction and corrected autophagy impairments triggered by rotenone. Conclusions: These data highlight a novel role for BET proteins in neurodegeneration, suggesting that their modulation may represent a promising approach to counteract PD neuropathology.

Disulfidptosis is a recently identified form of regulatory cell death (RCD), Which has emerged as a research hotspot due to its distinctive feature of accumulating protein disulfide bonds, setting it apart from other RCD mechanisms. This discovery may offer new therapeutic strategies for cancer and various chronic diseases. This review aims to summarize the molecular mechanisms, inhibitors, regulatory networks, distinctions and connections between disulfidptosis and other regulatory death pathways, and the application of disulfidptosis in tumors and other chronic diseases. It also identifies unresolved issues and provides an outlook on future prospects.