Bosnian Journal of Basic Medical Sciences
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Correction: Glioblastoma induces CAF-like astrocyte activation via the AKT/mTOR–SERPINH1/COL5A1 axis
Full text linkCorrection to: Glioblastoma induces CAF-like astrocyte activation via the AKT/mTOR–SERPINH1/COL5A1 axis
This corrigendum corrects the authors’ affiliations to:
Jingxian Zhang¹,²#, Yajia Chen¹,²#, and Hongwu Xu¹,²*.
¹Department of Neurosurgery, Tenth Affiliated Hospital, Southern Medical University, Dongguan, Guangdong, China.²Department of Human Anatomy, Shantou University Medical College, Jinping District, Shantou, Guangdong, China.
The authors sincerely apologize for this error and confirm that this correction does not affect the scientific content or conclusions of the article
Gut microbiota-derived extracellular vesicles in Alzheimer’s disease – Immunomodulatory mechanisms, biomarkers, and therapeutic opportunities: A review
Full text linkAlzheimer\u27s disease (AD) is a progressive neurodegenerative disorder that poses a growing global health challenge. Beyond traditional hallmarks such as amyloid-β (Aβ) deposition, tau hyperphosphorylation, and neuroinflammation, the gut–brain axis (GBA) has emerged as a significant modulator of AD pathogenesis. Among gut-derived mediators, microbiota-derived extracellular vesicles (mEVs) transport bioactive cargo across epithelial and vascular barriers, thereby linking intestinal dysbiosis to neurodegeneration. This narrative review synthesizes experimental, translational, and early clinical evidence regarding the immunomodulatory roles of gut mEVs in AD. We examine how mEVs may traverse compromised intestinal and blood–brain barriers, activate microglia and astrocytes, and influence Aβ and tau metabolism, thereby integrating peripheral and central immune interactions. Based on this evidence, we propose the "microbiota–EV–immune–neuro axis" as a conceptual framework that connects gut dysbiosis with AD-related neurodegeneration. The review also highlights emerging data on mEV signatures as minimally invasive biomarkers and explores their potential as therapeutic targets or delivery vectors. While current evidence is preliminary and methodologically heterogeneous, mEVs are increasingly recognized as both indicators and potential modulators of AD pathophysiology, emphasizing the need for standardized, longitudinal, and interventional studies
S-palmitoylation-related genes in Crohn\u27s disease: Bioinformatic identification and validation
Full text linkCrohn\u27s disease (CD) is a complex chronic inflammatory bowel disorder characterized by the absence of reliable biomarkers and effective targeted treatments. Recent evidence has suggested a role for S-palmitoylation, a reversible post-translational modification, in immune regulation and intestinal inflammation. However, a systematic, gene-centric investigation explicitly linking S-palmitoylation to the pathogenesis and diagnosis of CD has not been conducted. To address this gap, our study employs a comprehensive bioinformatic analysis to identify and validate key genes associated with both CD and S-palmitoylation, assessing their potential as diagnostic biomarkers and therapeutic targets. Utilizing data from the Gene Expression Omnibus (GEO, GSE83448) and GeneCards, we identified 23 S-palmitoylation-associated differentially expressed genes (SP-DEGs) in CD. Functional enrichment analysis indicated their significant roles in cysteine-specific S-palmitoylation and immunometabolic regulation. We applied machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) regression and support vector machine–recursive feature elimination (SVM-RFE), to select nine hub genes. Validation in two independent cohorts (GSE16879 and GSE59071) and ROC analysis confirmed ZDHHC23 and IFITM1 as biomarkers with high diagnostic value. These genes also exhibited correlations with immune infiltration patterns, as determined by cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), MCPcounter, and QuanTIseq. In vitro experiments corroborated consistent changes in mRNA and protein expression for both ZDHHC23 and IFITM1, reinforcing their involvement in CD. This study offers systematic insights into the functional roles of S-palmitoylation-related genes in CD, providing a novel theoretical foundation for the development of diagnostic and targeted therapeutic strategies
Plasma serotonin precursors and metabolites as diagnostic and therapeutic biomarkers for osteoporosis in postmenopausal women
Full text linkThis study aims to evaluate the diagnostic and therapeutic potential of plasma 5-hydroxytryptamine (5-HT) precursors and metabolites in postmenopausal osteoporosis (PMOP). A total of 287 consecutive postmenopausal women were retrospectively enrolled. Data including age, body mass index (BMI), serum calcium, serum phosphorus, menopausal duration, and bone mineral density (BMD) of the lumbar spine and femoral neck, as well as serum and plasma samples were collected. Based on BMD measurements, participants were categorized into normal, osteopenia, and osteoporosis (OP) groups. Serum β-CTX and PINP, along with plasma levels of 5-HT precursors and metabolites, were measured using ELISA. Receiver operating characteristic (ROC) curve analysis, multivariate analysis, and Kaplan-Meier curves were employed to assess the predictive value of 5-HT precursors and metabolites in PMOP and to evaluate the association between their expression levels and PMOP risk. Plasma levels of 5-hydroxytryptophan (5-HTP), 5-HT, and 5-hydroxyindoleacetic acid (5-HIAA) were elevated in PMOP patients and showed correlations with bone turnover markers and BMD. These biomarkers were identified as independent risk factors for PMOP. Combined analysis of the three biomarkers demonstrated greater predictive value than individual markers. Elevated levels were particularly pronounced in women with ≥ 12 years since menopause (YSM), and were associated with a higher risk of developing PMOP. In summary, 5-HT precursors and metabolites are significantly associated with bone turnover and BMD in postmenopausal women. They serve as independent risk factors and show strong predictive value for PMOP, suggesting their potential as plasma biomarkers for diagnosis and treatment. Furthermore, their relationship with YSM highlights their promise as therapeutic targets to delay the onset of osteoporosis in postmenopausal women.
Artificial intelligence driven innovations in biochemistry: A review of emerging research frontiers
Full text linkArtificial intelligence (AI) has become a powerful tool in biochemistry, greatly enhancing research capabilities by enabling the analysis of complex datasets, predicting molecular interactions, and accelerating drug discovery. As AI continues to evolve, its applications in biochemistry are poised to expand, revolutionizing both theoretical and applied research. This review explores current and potential AI applications in biochemistry, with a focus on data analysis, molecular modeling, enzyme engineering, and metabolic pathway studies. Key AI techniques—such as machine learning algorithms, natural language processing, and AI-based molecular modeling—are discussed. The review also highlights emerging research areas benefiting from AI, including personalized medicine and synthetic biology. The methodology involves an extensive analysis of existing literature, particularly peer-reviewed studies on AI applications in biochemistry. AI-driven tools like AlphaFold, which have significantly advanced protein structure prediction, are evaluated alongside AI’s role in expediting drug discovery. The review also addresses challenges such as data quality, model interpretability, and ethical considerations. Results indicate that AI has expanded the scope of biochemical research by facilitating large-scale data analysis, enhancing molecular simulations, and opening new avenues of inquiry. However, challenges remain, particularly in data handling and ethical concerns. In conclusion, AI is transforming biochemistry by driving innovation and expanding research possibilities. Future advancements in AI algorithms, interdisciplinary collaboration, and integration with automated techniques will be crucial to fully unlocking AI’s potential in advancing biochemical research
Diagnostic accuracy of two-dimensional shear wave elastography and point shear wave elastography in identifying different stages of liver fibrosis in patients with metabolic dysfunction-associated steatotic liver disease: A meta-analysis
Full text linkTo assess the diagnostic accuracy of two-dimensional shear wave elastography (2-D SWE) and point shear wave elastography (pSWE) in detecting liver fibrosis stages in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), a comprehensive search was conducted across four databases up to February 9, 2024. A bivariate random-effects model was used to analyze the diagnostic accuracy of the methods. After screening, 13 studies involving pSWE included 1527 patients, while nine studies involving 2-D SWE included 1088 patients. The areas under the summary receiver operating characteristic (SROC) curves for diagnosing significant fibrosis (F ≥ 2), advanced fibrosis (F ≥ 3), and cirrhosis (F = 4) using pSWE and 2-D SWE were as follows: 0.84 (95% CI 0.80–0.87), 0.91 (95% CI 0.88–0.93), and 0.94 (95% CI 0.91–0.95) for pSWE; 0.83 (95% CI 0.79–0.86) 0.85 (95% CI 0.82–0.88), and 0.89 (95% CI 0.86–0.91) for 2-D SWE, respectively. The pooled sensitivity for pSWE and 2-D SWE for stages F ≥ 2, F ≥ 3, and F = 4 were 0.71 (95% CI 0.63–0.78), 0.81 (95% CI 0.72–0.88), and 0.81 (95% CI 0.63–0.91) for pSWE, and 0.77 (95% CI 0.68–0.84), 0.80 (95% CI 0.72–0.87), and 0.92 (95% CI 0.75–0.98) for 2-D SWE, respectively. The pooled specificity of pSWE and 2-D SWE for these stages were 0.83 (95% CI 0.76–0.88), 0.87 (95% Cl: 0.81–0.92), and 0.91 (95% CI 0.86–0.94) for pSWE, and 0.76 (95% CI 0.66–0.84), 0.76 (95% CI 0.69–0.82), and 0.83 (95% CI 0.78–0.85) for 2-D SWE, respectively. In conclusion, both 2-D SWE and pSWE demonstrated high diagnostic performance in identifying various stages of liver fibrosis in MASLD patients
Predictors of implant failure: A comprehensive analysis of risk factors in oral implant restoration for patients with partial defects of dentition
Full text linkImplant failure remains a significant challenge in oral implantology, necessitating a deeper understanding of its risk factors to improve treatment outcomes. This study aimed to enhance the clinical outcomes of oral implant restoration by investigating the factors contributing to implant failure in patients with partial dentition defects within two years of treatment. Additionally, the study sought to develop an early risk prediction model for implant failure. A retrospective analysis was conducted on 300 patients with partial dentition defects, dividing them into two groups: a failed implant group and a successful implant group, based on the occurrence of implant failure within two years. General clinical data and condition-specific clinical information were compared between the groups. Multivariate binary logistic regression analysis was used to identify influencing factors, while the predictive effectiveness of the model was assessed using a receiver operating characteristic (ROC) curve. The analysis revealed that factors, such as gender, post-implant smoking, oral hygiene status at the second-year follow-up, tooth position, number of implants, timing of loading, width of keratinized mucosa, and bone quantity significantly influenced the likelihood of implant failure (P < 0.05). Among these, post-implant smoking and tooth position were identified as independent risk factors. The area under the curve (AUC) for tooth position was 0.695, indicating low predictive performance. Although tooth position was determined to be an independent risk factor for implant failure within two years, its predictive performance was limited
Neoadjuvant immunochemotherapy for resectable esophageal cancer: A study on efficacy and safety
Full text linkThe combination of immunosuppressants and chemotherapy has reshaped the treatment landscape for esophageal cancer (EC). This study aimed to evaluate the effectiveness and safety of a neoadjuvant immunochemotherapy (nICT) regimen in patients with resectable EC. A total of 99 eligible patients were included. Data on patient characteristics, nICT regimens, surgical approaches, postoperative outcomes, adverse events (AEs) related to neoadjuvant therapy and surgery, overall survival (OS), and disease-free survival (DFS) were collected. OS, DFS, and safety were the primary endpoints. Cox regression analysis was used to identify prognostic factors in the overall population. Additionally, exploratory research was conducted to assess the clinical value of blood immune indicators in predicting tumor regression. Following surgery, 99.0% of patients achieved complete resection (R0). After neoadjuvant therapy, the number of patients with stage T0N0 increased, with complete or moderate responses being the most common outcomes according to American Joint Committee on Cancer (AJCC)/ College of American Pathologists (CAP)-tumor regression grading (TRG) evaluations (64.7%). The one-year OS and DFS rates were 91.6% and 49.3%, respectively. Grade ≥3 AEs related to neoadjuvant therapy occurred in 21.2% of patients, with gastrointestinal reactions being the most frequent (16 cases, 16.2%). No treatment-related deaths were reported. Grade ≥3 surgery-related AEs occurred in 10.1% of patients, with anastomotic leakage being the most common (six cases, 6.1%). Several factors were associated with significantly improved OS, including chemotherapy regimens combining paclitaxel with platinum, surgical approaches using laparoscopy or thoracotomy (left or right), an interval of ≤34 days between the last treatment and surgery, and the absence of positive lymph node detection. Higher cT staging was significantly associated with worse DFS. Blood immune markers, such as the neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were found to predict tumor regression in EC patients. In summary, nICT demonstrated favorable effectiveness and safety in resectable EC. The choice of platinum-based chemotherapy agents, rather than the type of immunosuppressant, was associated with prognosis. Moreover, a shorter interval (≤34 days) between the final nICT administration and surgery was linked to improved outcomes
Cutaneous inflammation alters nociceptor electrophysiology in guinea pigs but not rats
Full text linkInflammatory pain hypersensitivity is believed to result, in part, from increased excitability of nociceptive dorsal root ganglion (DRG) neurons. We previously demonstrated in guinea pigs that hindlimb inflammation induces electrophysiological changes in these neurons, including faster action potential (AP) and afterhyperpolarization (AHP) kinetics. Given that rats and guinea pigs are distinct species with notable differences in genetic composition and physiology, we hypothesized that cutaneous inflammation would have different effects on the electrophysiological properties of nociceptive DRG neurons in rats—the predominant rodent model for pain research. To test this hypothesis, we performed intracellular voltage recordings from DRG neurons (n = 430) in deeply anesthetized, untreated (control) and complete Freund’s adjuvant (CFA)-treated rats and guinea pigs. C-, Aδ-, and Aβ-nociceptors were identified based on their dorsal root conduction velocities (CVs) and responses to natural noxious stimuli. Consistent with our hypothesis, we observed no significant changes in any electrophysiological variables in rat nociceptive neurons four days after CFA-induced hindlimb inflammation. In contrast, guinea pig nociceptors exhibited a significant increase in CV and significant decreases in both AP and AHP durations. The inflammation-induced shortening of absolute and relative refractory periods likely contributes to increased firing frequency in nociceptive nerve fibers, thereby promoting inflammatory pain hypersensitivity. These findings suggest species-specific differences in peripheral neuronal mechanisms underlying inflammatory pain, potentially due to variation in ion channel expression and/or function in DRG neurons between rats and guinea pigs. Given the genetic and metabolic similarities between guinea pigs and humans, further research is warranted to determine whether guinea pigs may serve as a more accurate model of chronic inflammatory pain than rats
Impact of thyroid immune-related adverse events on clinical outcomes in non-small cell lung cancer (NSCLC) patients treated with checkpoint inhibitor therapy: A single center study
Full text linkImmune checkpoint inhibitors (ICIs) have transformed the treatment landscape for non-small cell lung carcinoma (NSCLC) but are associated with immune-related adverse events (irAEs), including thyroid dysfunction. This study examines the incidence and clinical impact of thyroid dysfunction in NSCLC patients receiving ICIs at the Clinic of Oncology, Clinical Center University of Sarajevo. In this retrospective cohort study of 50 patients with metastatic NSCLC treated with ICIs—either in combination with chemotherapy or as monotherapy for those with programmed death-ligand 1 (PD-L1) expression ≥ 50%—we collected data on demographics, treatment regimens, thyroid function tests, and survival outcomes. Thyroid dysfunction occurred in 24 patients (48%), with 12 (24%) developing hypothyroidism, 4 (8%) developing hyperthyroidism, and 8 (16%) experiencing a transition from hyperthyroidism to hypothyroidism. The incidence of thyroid dysfunction was significantly higher in patients treated with atezolizumab compared to pembrolizumab (P = 0.04), with 87.5% of affected patients receiving atezolizumab. The median time to onset of thyroid dysfunction was 10 cycles (interquartile range [IQR]: 5) for hypothyroidism and six cycles (IQR: 19) for hyperthyroidism. Progression-free survival (PFS) was significantly longer in patients who developed thyroid dysfunction, with the median PFS not reached, compared to a median PFS of 14 months (95% CI: 9.68–18.32) in patients without thyroid dysfunction (P = 0.038). No significant associations were found between thyroid dysfunction and patient age or gender. These findings suggest that thyroid dysfunction is a common irAE in patients with metastatic NSCLC receiving ICIs, particularly atezolizumab, and its development may be associated with improved PFS. Regular monitoring of thyroid function is recommended to promptly identify and manage thyroid abnormalities during ICI therapy, potentially improving patient outcomes