BackgroundChronic subdural hematoma (CSDH) is a common condition affecting patients undergoing neurosurgical treatment for which burr-hole drainage remains the standard treatment. Postoperative fungal infections following this procedure are extremely rare, but can lead to severe consequences.Case DescriptionA 66-year-old male with a history of hypertension and schizophrenia underwent bilateral burr-hole drainage for bilateral frontotemporoparietal CSDH at another hospital 2 years prior to presentation. In the intervening years following this procedure, he experienced recurrent headaches, developed involuntary tongue protrusion and limb shaking, and suffered one episode of seizure 10 days before admission. Imaging suggested recurrence and possible organization of the bilateral CSDH. Bilateral craniotomy for hematoma evacuation was performed. Intraoperative examination revealed the organization and thickening of the subdural hematoma membrane, with a maximum thickness of approximately 1 cm. Postoperative pathological examination unexpectedly revealed structures suggestive of fungal hyphae. Subsequent cerebrospinal fluid culture confirmed the presence of Candida parapsilosis infection, establishing the definitive etiological diagnosis. The patient was successfully cured through surgical evacuation, antifungal therapy consisting of sequential voriconazole and fluconazole treatment, temporary lumbar drainage, and comprehensive management of complications, although the course of hospitalization was further complicated by intestinal obstruction, pneumonia, and bacteremia.ConclusionThis report describes a rare case of intracranial C. parapsilosis infection occurring 2 years after burr-hole drainage for the management of a CSDH. This case highlights the diagnostic challenges associated with delayed postoperative fungal infections and emphasizes the importance of pathological examination when encountering atypical surgical findings. A multidisciplinary approach combining aggressive surgical debridement with targeted antifungal therapy is crucial for achieving a favorable outcome.
BackgroundGlobal and Chinese efforts still face significant gaps in achieving the first 95% of the “95-95-95” target, with persistently high and rising rates of late HIV diagnosis. This study evaluates RNA/DNA quantification, RNA qualitative, and ELISA assays to optimize HIV testing strategies.MethodsA prospective cross-sectional study evaluated 215 first-time HIV testers from June 2024 to May 2025. Using clinical diagnosis as the reference standard, we assessed four methods' sensitivity, specificity, and subgroup performance, with tandem testing strategies simulation for optimal detection.ResultsDNA quantitative detection demonstrated optimal performance with 100% sensitivity and specificity. RNA quantitative assay showed 99.02% sensitivity and 100% specificity, while ELISA achieved 99.02% sensitivity and 98.23% specificity. RNA qualitative testing exhibited 99.02% sensitivity but lower specificity (75.22%). ROC revealed superior diagnostic performance for DNA quantitative (AUC = 1.000) and RNA quantitative (AUC = 0.995) compared to RNA qualitative (AUC = 0.871). All methods maintained consistent sensitivity across CD4+ T cell levels. Simulation of tandem strategies identified ELISA combined with DNA quantitative testing as optimal (net sensitivity: 99.02%, net specificity: 100%, total tests: 318). For 18 WB-indeterminate samples, DNA/RNA quantitative methods achieved 100% diagnostic accuracy, outperforming RNA qualitative (94.44%) and ELISA (83.33%).ConclusionDNA quantitative detection shows high diagnostic value in initial HIV testing, overcoming challenges from undisclosed ART-induced RNA suppression and resolving WB-indeterminate misclassifications to reduce late diagnosis risks. This study supports Nucleic acid tests into diagnostic algorithms and validates the superior performance of ELISA screening followed by DNA confirmation, offering actionable strategies to shorten diagnostic delays and advance national AIDS control objectives.
IntroductionLaboratory medicine is evolving at a rapid rate, not only in terms of the repertoire of tests available and automation of the laboratory and procedures, but also in how laboratory data is used within “calculated tests,” algorithms and guidelines. The goal is diagnostic and treatment improvements for the patient; however, there are real patient safety concerns if the limitations of what is often described as the “simple blood test” are not sufficiently understood and appreciated. The aim of this study was to investigate how laboratories take into consideration variation in cortisol assays when managing potential cases of adrenal insufficiency when they had a single cortisol measurement. For English laboratories also assessed compliance to NICE Guidance NG243 — “Adrenal insufficiency: identification and management,” published in 2024.Materials and methodsThe UK NEQAS for Steroid Hormones Scheme provides an External Quality Assessment (EQA) service for Cortisol. In December 2025, three serum specimens were distributed for cortisol analysis and interpretation based on a provided scenario — each specimen taken from a 25-year-old female at 08:30, clinical details — ?Adrenal insufficiency. Participants were required to interpret results into three categories — (1) Person may have adrenal insufficiency, (2) Probability of adrenal insufficiency uncertain or (3) Adrenal insufficiency very unlikely. Data has been evaluated based on the reported cortisol result and corresponding interpretation, broken down by manufacturer and location of laboratory.ResultsCortisol results were returned by ∼370 Participants with ∼300 interpretating their result. Specimen 536A had a cortisol of 122 nmol/L (SD 9 nmol/L, %CV 7.5%), 536B — 307 nmol/L (SD 24 nmol/L, %CV 7.8%) and 536C — 260 nmol/L (SD 19 nmol/L, %CV 7.2%) based on a mass spectrometry method mean (validated by a candidate reference method). According to NG243, these cortisol results should correspond to Codes (1), (3) and (2) respectively. As expected, there was variation in the cortisol result reported and the subsequent interpretation.DiscussionThis study utilises EQA to look at the variation in cortisol measurement specifically in the context of identifying adrenal insufficiency. By linking post-analytical interpretation to the analytical measurement we have identified variation in both cortisol assays and interpretation of results.
BackgroundLong COVID is frequently characterized by persistent fatigue and impaired quality of life. Increasing evidence suggests that gut microbiota dysbiosis and immune dysregulation may contribute to symptom persistence. We evaluated the effects of the probiotic formulation VSL#3® in patients with long COVID.MethodsIn this randomized, double-blind, placebo-controlled trial (ClinicalTrials.gov identifier: NCT05874089), patients with long COVID and clinically relevant fatigue received VSL#3® or placebo for 4 weeks. The primary endpoint was fatigue improvement assessed by the Chalder Fatigue Scale (CFS). Secondary and exploratory analyses included patient-reported outcomes, gut microbiota profiling, immune phenotyping, cytokine analyses, and targeted metabolomics.ResultsForty-eight patients completed the study (placebo n = 25; VSL#3® n = 23). VSL#3® supplementation significantly improved fatigue compared with placebo, with a greater reduction in CFS score (24.24% vs. 6.06%; p = 0.037) and a higher proportion of responders (68% vs. 35.7%; p = 0.019). Clinical benefit persisted after treatment discontinuation and was accompanied by improvements in selected quality-of-life and gastrointestinal symptom domains. VSL#3® supplementation was associated with selective enrichment of health-associated bacterial taxa, including Bifidobacterium, Lactobacillus, Ruminococcus, and Coprococcus, together with modulation of inflammatory and immune-related pathways. Exploratory multi-omic analyses identified coordinated associations among microbiota-derived metabolites, immune markers, and clinical outcomes.ConclusionVSL#3® supplementation improved fatigue and selected clinical outcomes in patients with long COVID and was associated with coordinated microbiota and immune changes. These findings support further investigation of microbiota-targeted interventions in long COVID.
Growth differentiation factor 15 (GDF-15), a stressful cytokine of the transforming growth factor-β (TGF-β) superfamily, plays pivotal roles in diverse physiological and pathological processes. Most recently, its pleiotropic effects regarding energy metabolism and nutritional modulation are of intense scrutiny. Its physiological functions involve signaling pathways such as GDF-15/glial cell-derived neurotrophic factor family receptor α-like protein (GFRAL)/rearranged during transfection (RET), phosphatidylinositol 3-kinase (PI3K)/Protein kinase B (Akt)/mammalian target of rapamycin (mTOR), nuclear factor kappa B (NF-κB), and reactive oxygen species (ROS). The mechanism of action involves regulation of energy metabolism, inflammation, oxidative stress, and muscle-fat-bone metabolism, and it holds important prognostic value and potential therapeutic significance. Mounting evidence has suggested that GDF-15 levels are significantly increased in the context of cancer cachexia, metabolic syndrome (MetS), and amongst older patients, paralleling multiple indicators of nutrition. Notably, this association appears to be gender- and age-specific, therefore serving as a good biomarker alongside a therapeutic target to mitigate or even reverse disease-related nutritional deficiency and aggravation. However, the precise contribution of GDF-15 to evaluate nutritional status and its mechanistic basis across varying disorders is not fully elucidated. In light of these knowledge gaps, we sought to delve into basic research, clinical information and translational evidence, aiming to analyze the molecular regulatory network of GDF-15 and clarify its clinical implications as a novel diagnostic tool and assessment metric, and in turn provide a theoretical basis for early intervention and personalized treatment. Future research should focus on elucidating GDF-15’s neuroanatomical basis and signaling pathways, validating gender-disparity mechanisms, establishing clinical diagnostic thresholds, optimizing targeted therapeutic strategies, and developing dynamic monitoring approaches, so as to bridge the gap from biomarker discovery to precision intervention.
Background:CD117 (c-KIT) is a tyrosine kinase receptor protein, mutations in which are important in the tumourigenesis of gastrointestinal stromal tumour (GIST). Immunohistochemical detection of CD117 is the primary identifying feature in its diagnosis. Introduction:UK NEQAS ICC & ISH conducts an EQA programme for CD117 expression in GIST. Between May-2020 and May-2025, 20 runs of this EQA were undertaken. The archived data was analysed to look for evidence regarding the quality of testing and associations between primary antibodies and stain quality. Discussion:Total submissions were 2,656 (mean per run = 132.8; range = 125-140). The number of submissions awarded a quality score indicating at least acceptable stain quality was 2,642 (99.5%). The total number of submissions that failed was 14 (mean proportion per run = 0.5%; range = 0.0%-2.4%); those obtaining a borderline score totalled 158 (mean proportion = 5.9%; range = 0.7%-10.9%); those obtaining an acceptable score totalled 394 (mean proportion = 14.8%; range = 4.3-24.4%); and those obtaining a good/excellent score totalled 2,090 (mean proportion = 78.7%; range = 57.7%-94.2%). There was a strong trend for the proportion of submissions obtaining a good/excellent quality score to increase over time. Four primary antibodies were used: Clone 9.7 (102 submissions, 3.9%), YR145 (263 submissions, 10.0%), EP10 supplied by Leica Biosystems (EP10(LB), 415 submissions, 15.8%), EP10 supplied by Roche Diagnostics (EP10(RD), 505 submissions, 19.2%), and a polyclonal antiserum supplied by Agilent Dako (1,263 submissions, 48.1%). A total of 76 submissions (2.9%) that used other primaries or suppliers were excluded from analysis. Conclusion:Demonstration of CD117 overexpression in GIST was undertaken to a very high quality standard in the majority of laboratories. For users of Dako Agilent supplied automation the highest quality staining was produced by using the polyclonal antiserum from the same supplier. Among users of Leica Biosystems and Roche Diagnostics automation the best staining was produced by using primary sourced from the same supplier that provided their automation. It is recommended that Clone 9.7 (Roche Diagnostics) should not be used as the results it produced were statistically significantly inferior to those of all other antibodies.
ObjectivesMultiple allergen simultaneous tests (MAST) increasingly incorporate both crude extract and molecular component allergens for specific IgE testing. However, systematic data on the diagnostic concordance between these two approaches remain limited. We evaluated the agreement between crude extract and corresponding component allergen results using a MAST panel in a large clinical laboratory cohort.MethodsWe retrospectively analysed deduplicated MAST results from a high-volume referral laboratory over a two-month period. For 29 crude extract allergens paired with 48 corresponding component allergens, positivity rates were assessed using a cutoff of class 2 or higher (≥0.70 IU/mL). Concordance was defined as both crude extract and at least one component allergen being positive, or both being negative. Agreement was evaluated using percent agreement and Cohen’s kappa coefficient.ResultsA total of 19,949 patients were included. The highest positivity rates were observed for Dermatophagoides farinae (31.8%), D. pteronyssinus (29.9%), rDer f 2 (24.2%), and cat epithelium (12.2%). Overall percent agreement exceeded 90% for most allergen pairs, primarily driven by high negative agreement. Cohen’s kappa revealed substantial agreement (κ ≥ 0.6) for ten allergens including D. farinae, cat dander, and birch pollen, whereas eight allergens including D. pteronyssinus and milk showed poor agreement (κ < 0.1) due to low component allergen positivity despite positive crude extract results.ConclusionDiagnostic concordance between crude extract and component allergen testing in MAST varies substantially across allergen sources. These findings underscore the need for allergen-specific interpretation guidelines when reporting MAST results incorporating component allergens in clinical laboratories.
Introduction:The measurement of the angiogenic biomarkers placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) are increasingly used to support the prediction and diagnosis of preeclampsia (PE) in routine clinical practice. There are an increasing number of methods available for the analysis of these markers but data showing their analytical comparability is limited. Materials and methods:The assays for PlGF and sFlt-1 from Revvity were evaluated and compared against Roche methods that are used in current clinical practice in Oxford. Imprecision and paired analytical comparisons studies were undertaken and data evaluated for numeric agreement and concordance relative to manufacturer recommended rule-in and rule-out thresholds for PE. Results:Imprecision estimates for the Revvity PlGF and sFlt-1 methods calculated from quality control material analysed during the evaluation were between 3.2 and 9.0 CV%. Revvity method precision profiles derived from 581 clinical specimens analysed in duplicate had a median CV% for PlGF of 1.8%, IQR 2.3% and for sFlt-1 a median CV% of 1.1%, IQR 1.5%. Comparison against the Roche PlGF and sFlt-1 methods in 437 clinical specimens showed an overall Passing-Bablok regression relationship for PlGF of y = -23.4 + 0.73x (r = 0.983) and for sFlt-1, y = -87.7 + 0.40x (r = 0.971). However, there was statistically significant (p < 0.0001) concentration dependant relative bias for both methods and the calculated ratio. Concordance of the sFlt-1:PlGF ratio relative to manufacturer specific rule-in and rule-out thresholds was 95.2%. Discussion:The Revvity methods for PlGF and sFlt-1 are precise and correlate with the Roche methods. However, numeric agreement precludes result interchangeability and the use of common rule-in and rule-out thresholds. The manufacturer specific thresholds should be applied in clinical practice. Further work is required to understand how method differences impact clinical outcomes and their causes.
IntroductionThe growing diversity of university student populations highlights the critical need for inclusive support strategies. Student outcomes often remain linked to socio-economic factors and Level 3 qualifications, challenging universities to create equitable learning environments, particularly for foundational skills like quantitative analysis. This study investigated the impact of widening participation (WP) characteristics on student engagement with, and perceptions of, novel asynchronous digital Smart Worksheets developed by LearnSci in collaboration with the Institute of Biomedical Science.MethodsStudents (N = 779) enrolled on Biomedical Science modules in Level 3 to 6 at Northumbria University UK, were surveyed to gauge perceived calculation confidence, extracurricular commitments and intent to use the Smart Worksheets. Following deployment of the Smart Worksheets, students were surveyed again to correlate intention versus actual usage, explore the influence of WP characteristics and elucidate other factors that affected engagement.ResultsSurprisingly, perceived course engagement and initial calculation confidence was generally high. Students with multiple WP characteristics, however, reported significantly lower calculation confidence (p = 0.002). While 93.9% of students expressed strong intent to use the resources, only 20% engaged. Further exploration revealed the primary barriers were resource awareness and time availability, with extracurricular commitments increasing from Level 3 to 6, culminating in 86.1% of Level 6 students having work or caring responsibilities. Regardless of initial confidence, students consistently rated the Smart Worksheet content as appropriate and their content as highly valuable.DiscussionThese findings suggest that students’ extracurricular commitments are escalating throughout their university careers, challenging traditional assumptions about final year students being more autonomous and needing less support. Flexible, high-value resources are crucial for time-poor students, addressing engagement barriers that are primarily time and capacity-related. This study underscores the increasing need for comprehensive and clearly communicated support mechanisms for all students navigating an increasingly complex academic, financial and personal landscape.
Biological age (BA) prediction has emerged as a critical research frontier for evaluating individual health status and aging trajectories beyond chronological age (CA). Recent advances in artificial intelligence (AI) have substantially accelerated this field by enabling the integration and interpretation of complex, multimodal biological data. This review provides a systematic overview of AI-driven approaches to BA prediction, covering key components including biomarker selection, feature engineering, model development, bias correction, and performance evaluation. We further highlight the growing recognition of asynchronous aging, a phenomenon in which different organs or physiological systems age at distinct rates, and discuss how AI—particularly deep learning and multimodal fusion—offers powerful tools for capturing such system-specific aging patterns. We summarize current methodologies ranging from traditional machine learning algorithms to advanced neural architectures capable of modeling nonlinear and heterogeneous aging processes. The expanding applications of AI-based BA models in disease risk assessment, geriatric evaluation, and population health monitoring are also examined. Despite rapid methodological progress, significant challenges persist, including data heterogeneity, limited model generalizability, insufficient interpretability, and barriers to clinical translation. Addressing these issues will require standardized methodological practices, robust validation across diverse populations, and the development of interpretable and equitable AI systems. Future research should prioritize the integration of multi-omics and longitudinal datasets with AI-driven analytical frameworks to establish reliable, system-level, and clinically actionable BA prediction models that account for asynchronous aging.
BackgroundThis study aims to assess the effectiveness of non-invasive preimplantation genetic testing (niPGT) for detecting aneuploidy at two different time points, 48- and 54-hour following the cleavage stage of embryo development.MethodsA cohort of 15 infertile women was enrolled, involving a total of 58 embryos. All embryos underwent sequential culture media procedures and received assisted hatching during the cleavage stage on Day 3. After biopsy examination, conducted either 48 or 54 hours post cleavage, spent culture media (SCM) were gathered and processed for the amplification and quantification of cell-free DNA. This was followed by low-pass whole genome sequencing.ResultsThe cell-free DNA content within SCM remained consistent across both time points post cleavage. The accuracy of niPGT in ploidy detection, in comparison to trophectoderm biopsy, was 53.71%. No significant distinction in ploidy detection accuracy was observed between SCM collected from embryos at 48 hours versus those at 54 hours post cleavage. The overall accuracy for sex determination reached 79.63%.ConclusionsThe concentration of cell-free DNA within SCM was found to be consistent at both 48- and 54-hours after embryo cleavage. However, the accuracy of ploidy determination, when contrasted with the conventional trophectoderm biopsy, did not yield satisfactory outcomes.
Genomic imprinting is the phenomenon in which only a single allele of a gene is expressed based on its parental origin, thereby deviating from the typical biallelic expression of autosomal genes. It is meticulously controlled by epigenetic mechanisms, particularly DNA methylation. Imprinted loci are crucial for regulating growth during early development, and anomalies in imprinting can lead to congenital syndromes such as Beckwith-Wiedemann’s and Prader-Willi’s. Similarly, many cancers exhibit dysregulated imprinting patterns, putatively contributing to tumour growth. Yet, the assessment of imprinting in cancer is complex due to technical challenges, impeding clinical research and the translation of novel insight to the clinic. This review starts with a general introduction to imprinting, its (dys)regulation and key clinical findings in cancer and beyond. Then, we summarize common methods used to characterize normal imprinting and aberrations in cancer. Subsequently, we discuss how the interpretation of such findings is complicated by technical challenges, such as tumour impurity, the requirement for heterozygosity to distinguish between maternal and paternal alleles and the presence of tissue- and transcript-specific imprinting patterns. We further delve into state-of-the-art methods able to mitigate these challenges. Finally, we discuss how future methodological innovations, particularly by integrating single-cell and single-molecule based methods, may further facilitate a straightforward characterization of imprinting dysregulation and its underlying causes, and guide the development of clinical tests. Thus, by integrating recent advances and proposing innovative approaches, our review aims to provide a comprehensive overview for cancer researchers and clinicians to facilitate cancer imprinting research and its translation to the clinic.
Semi-quantitative scoring of PD-L1 expression on tumor cells (TCs) and/or infiltrating immune cells (ICs) is complex and requires expert pathologist training to reduce inter- and intra-reader variability. We conducted a 1- or 2-day training of 751 pathologists world-wide from 63 countries over a period of 2 years (2016 and 2017). Pathologists read microscopic slides or fully digitized slides stained with PD-L1 immunohistochemistry 22C3 pharmDx assay with expression levels enriched around the clinically relevant cutoffs of 1% and 50% in non-small cell lung cancer (NSCLC). The overall inter-reader agreement (OPA) for PD-L1-stained NSCLC was 95.6% for TPS ≥1% and 87.3% for TPS ≥50% cut-off. The corresponding intra-reader agreement was 95.9% for the ≥1% and 91.4% for the ≥50% cut-off. The inter-reader negative percent agreement (NPA) for TPS ≥1% was 85.6% and 91.9% for the TPS ≥50% cut-off, and the positive percent agreement (PPA) was 97.6% (TPS ≥1%) and 81.0% (TPS ≥50%). The observed high inter- and intra-reader agreements are promising given the difficulty of reproducible scoring tumor cells with heterogeneous distribution of PD-L1 staining combined with the varied professional training, expertise, and experience of the participants. The results may reflect the utility of the expert led standardized protocol used to train pathologists for scoring PD-L1 staining in NSCLC specimens. The digital image-led training approach has the additional advantage of providing a computer-assisted scoring system and allows for remote training of pathologists worldwide.
IntroductionEnsuring the reliability, standardization, and international comparability of antimicrobial resistance (AMR) surveillance data critically depends on the implementation of robust quality assurance frameworks. South Korea established the Korea Global Antimicrobial Resistance Surveillance System (Kor-GLASS), supported by a centralized quality control center (QCC). As Kor-GLASS transitioned from Phase II to Phase III, new bacterial species and antimicrobial agents were incorporated, underscoring the need to evaluate whether quality assurance performance could be sustained during system expansion.Materials and MethodsWe analyzed interlaboratory proficiency testing (IPT) and external quality assessment (EQA) outcomes generated by the QCC between 2020 and 2024, covering Phases II and III of Kor-GLASS. Clinical isolates were collected at participating hospitals and transferred to organism-specialized analysis centers for standardized antimicrobial susceptibility testing (AST), while the QCC independently oversees data quality through IPT and EQA. IPT was conducted by comparing AST results between analysis centers and the QCC using subsets of routine clinical isolates, with acceptance criteria defined as categorical agreement (CA) ≥90% and major error rates <3%. EQA involved quarterly distribution of pre-characterized strains to participating centers. Additional evaluations addressed the performance of newly introduced ceftazidime-avibactam susceptibility testing and interlaboratory validation for Haemophilus spp.ResultsAcross the study period, overall CA consistently exceeded 97% in IPT, and no EQA failures observed among participating centers. While major errors during Phase II were primarily attributable to AST reading and near-breakpoint discrepancies, their frequency markedly decreased in Phase III following targeted corrective actions and educational interventions. Susceptibility testing for ceftazidime-avibactam showed high concordance between centers, with rare discrepancies limited to near-breakpoint measurements. Interlaboratory validation confirmed acceptable performance for AST of Haemophilus spp., supporting its formal inclusion in Phase III.DiscussionThese findings demonstrate that a centralized, QCC-led quality assurance framework can maintain stable and reliable AMR surveillance performance during periods of system expansion. Beyond routine oversight, coordinated quality assurance activities function as an evidence-based evaluation of how standardized laboratory data are generated and validated, reinforcing their essential role in sustaining the credibility and future development of AMR surveillance systems.
In almost all aspects of biomedical science, molecular pathology has brought unprecedented value in the diagnosis and management of human disease. Numerous commentators cite haematological disease as the leading genetic cause of global mortality and morbidity, and of these, those of the red blood cells are the most frequent. This narrative review, with a historical perspective, will discuss the role of genetics in these conditions, the leading pathology of red blood cells being the haemoglobinopathies, principally sickle cell disease and thalassaemia, with their many variants, and with potential roles for non-coding RNAs. The impact of genetics into conditions of the red cell cytoplasm will consider the enzymopathies, led by glucose-6-phosphate dehydrogenase deficiency, and extend to those of the cell membrane, causing disease such as hereditary elliptocytosis. Mutations in genes coding almost all the coagulation factors, and several platelet abnormalities, are discussed, as are those linked to conditions of iron overload. Previous, current and evolving technologies for diagnostic testing and their link with potential targeted therapeutic options for patient management are considered.
IntroductionAortic valve sclerosis (AVSc) is an active pathological process driven by extracellular matrix remodeling, consistent with a potentially reversible early stage of aortic valve disease.MethodsIn this cross-sectional study of 168 participants (29, normal aortic valve [NAV]; 98, AVSc; 41, aortic stenosis [AS]), serum levels of matrix metalloproteinase (MMP)-1, -2, -3, and -9, tissue inhibitor of metalloproteinases-1 (TIMP-1), tumor necrosis factor (TNF), interleukin-6 (IL-6), and transforming growth factor-beta (TGF-β) were measured. Multivariable adjustments were performed.ResultsCompared with AS, AVSc was associated with higher circulating MMP-9 levels, with MMP-9 also increased relative to NAV. TIMP-1 concentrations were reduced in AVSc compared with both AS and NAV. TNF levels were higher in AVSc than in AS, while IL-6 and TGF-β did not differ among groups. Notably, MMP-9/TIMP-1 ratio was markedly increased in AVSc.DiscussionOur findings suggest that AVSc may exhibit an active proteolytic and inflammatory profile amenable to targeted anti-inflammatory and anti-proteolytic interventions.
IntroductionSarcopenia, characterised by age-associated decline in skeletal muscle mass and function, is driven by multifactorial mechanisms including oxidative stress, chronic inflammation, and genomic instability. The imbalance between reactive oxygen species (ROS) and antioxidant defence contributes to mitochondrial dysfunction and DNA damage, thereby affecting cellular metabolism and promoting muscle degeneration. Tocotrienol-rich fraction (TRF), a potent antioxidant form of vitamin E, has shown potential in modulating oxidative and inflammatory pathways. However, in vivo evidence exploring TRF’s multifaceted role in ageing muscle remains limited. This study investigates the correlation between oxidative stress and inflammation with the metabolomics profile in ageing skeletal muscle in a rat model and its modulation by tocotrienols.MethodsYoung (3 months) and old (21 months) male Sprague-Dawley rats were divided into control and TRF-supplemented groups (n = 10). TRF was administered orally (60 mg/kg/day) for 3 months. Antioxidant enzymes, lipid peroxidation products: malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE); and inflammatory markers: C-reactive protein (CRP), Interleukin-6 (IL-6), and tumour necrosis factor alpha (TNF-α) were quantified, alongside DNA damage, using the comet assay. Muscle histology was assessed using hematoxylin and eosin (H&E) staining. Pearson correlation analysis was performed between selected metabolites and biological markers.ResultsAgeing significantly increased oxidative damage, pro-inflammatory markers, and DNA fragmentation, while reducing antioxidant enzyme activities and disrupting metabolic profiles. Although TRF supplementation did not significantly restore muscle mass or overall body composition, it effectively enhanced antioxidant defence by increasing Superoxide dismutase (SOD) and catalase (CAT) activities, reducing lipid peroxidation (MDA and 4-HNE), attenuating inflammatory responses, preserving DNA integrity, and improving muscle histological features. Importantly, correlation analyses revealed that ageing is associated with a coordinated metabolic shift linking amino acid and carnitine metabolism with antioxidant defence, inflammation, and genomic stability. TRF supplementation weakened these maladaptive biomarker and metabolite associations while strengthening correlations between protective metabolites (e.g., taurine, histidine, pantothenic acid) and antioxidant enzymes, alongside inverse relationships between lipid peroxidation and inflammatory markers (e.g., MDA, prostaglandin factor 2-alpha, PGF2α) and redox-supportive metabolites.DiscussionCollectively, these findings indicate that TRF acts primarily as a preventive intervention by restoring redox balance, dampening inflammatory signalling, and stabilising metabolic and inflammatory coupling, highlighting its potential as a nutritional strategy for preserving muscle health and genomic integrity during ageing.
Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype characterized by marked molecular heterogeneity and limited targeted therapeutic options. Its incidence is rising in many low- and middle-income countries, where genetic profiling of affected patients remains largely unexplored despite evident clinical disparities. This study aimed to characterize, for the first time in a Tunisian cohort, the spectrum of germline and somatic mutations in TNBC patients and to assess their potential impact on therapeutic response. Targeted next-generation sequencing (NGS) of hotspot regions across 50 cancer-related genes was performed in twelve patients using the AmpliSeq for Illumina Cancer Hotspot Panel v2, applied to both tumor tissues and matched adjacent non-tumoral tissues. Bioinformatics analysis revealed recurrent germline variants present in all samples, notably in TP53 (rs1042522), CSF1R (rs2066933), FGFR3 (rs7688609), RET (rs1800861), KDR (rs7692791), and PDGFRA (rs1873778). In tumor tissues, 32 deleterious somatic variants were detected across 20 oncogenes, with TP53 emerging as the most frequently mutated gene (58%). Distinct mutational patterns were observed in relation to treatment response. Notably, the co-occurrence of AKT1 (rs121434592) and TP53 (rs876660754) was observed in a patient with treatment resistance, whereas an in-frame deletion in NOTCH1 (p.Val1578del) was uniquely detected in patients who subsequently experienced disease recurrence. These findings provide the first comprehensive characterization of germline and somatic alterations in Tunisian TNBC patients, representing a North African cohort. They reveal the heterogeneity of mutation patterns linked to treatment response, and emphasize the importance of genomic profiling into clinical practice and guide personalized therapeutic strategies.
BackgroundLong COVID (LC) presents persistent symptoms that pose a major clinical challenge. Identification of reliable biomarkers to evaluate LC pathophysiology is needed.ObjectivesTo investigate whether serum S- and N-antibody titers against SARS-CoV-2 spike and nucleocapsid proteins reflect the clinical features of LC.MethodsThis retrospective observational study included patients diagnosed with Omicron variant-related LC who attended a post-COVID-19 outpatient clinic between July 2023 and November 2024 and provided informed consent for antibody testing.ResultsAmong 275 patients (129 men and 146 women), 57 (21%) were unvaccinated. Median S- and N-antibody titers in vaccinated versus unvaccinated patients were 20,963 U/mL and 24.8 cut-off index (COI) versus 24 U/mL and 44.5 COI, respectively. S-antibody titers were associated with the number of vaccine doses received, whereas N-antibody titers correlated with disease severity during the acute phase of COVID-19 infection, with females having higher titers by multivariable analysis. N-antibody titers in unvaccinated patients with LC were negatively correlated with time interval from infection to clinic visit, with an estimated daily decline of 0.34% in measured N-antibody levels. Patients with LC having memory impairment had low S-antibody titers by multivariable logistic regression analysis, and low S-antibody levels were associated with reduced quality of life (QOL). Additionally, N-antibody titers positively correlated with lymphocyte counts and immunoglobulin levels.ConclusionSerum N-antibody titers reflect immune responses to COVID-19, although they are affected by gender differences and interval between infection and evaluation. Lower S-antibody titers were associated with brain fog symptoms and reduced QOL in patients with LC.
