Introduction: Obesity is a heterogeneous metabolic disease in which individuals with similar body weight may exhibit markedly different physiological risk profiles. Conventional monitoring using weight alone may fail to capture underlying metabolic and cellular changes during lifestyle intervention. Integrating body composition and biochemical markers may improve risk stratification in clinical practice. Methodology: A prospective observational analysis was conducted among participants enrolled in a structured lifestyle programme. Baseline and follow-up assessments included biochemical markers (fasting glucose, renal function, lipid profile, and liver enzymes) alongside body composition parameters derived from bioelectrical impedance analysis, including percent body fat, visceral fat area, skeletal muscle index (SMI), and phase angle (PhA). Changes over time and associations between metabolic and body composition variables were analyzed. Results: Metabolic responses varied substantially despite similar anthropometric profiles. Renal function improved significantly, with increased estimated glomerular filtration rate (eGFR) observed over time (p = 0.01), and was inversely associated with fasting glucose (r = −0.41, p <0.01). Lipid abnormalities persisted, although reductions in lowdensity lipoprotein cholesterol were noted (p = 0.04). Total cholesterol remained elevated and correlated positively with fasting glucose (r = 0.36, p = 0.02). Improvements in aspartate aminotransferase were observed (p = 0.03), while other liver markers remained stable. Notably, body composition parameters, including PhA and SMI, demonstrated variability independent of weight change, reflecting heterogeneous physiological adaptation. Conclusion Metabolic and physiological responses to lifestyle intervention are heterogeneous and not fully captured by changes in body weight alone. The integration of bioimpedance-derived parameters with biochemical markers provides a more comprehensive approach to metabolic risk stratification and may support more personalized clinical management in obesity care.
Biomarkers ; Risk Assessment ; Body Composition

Introduction: Childhood obesity is associated with significant metabolic morbidity, particularly insulin resistance (IR) and metabolic syndrome. Acanthosis nigricans (AN) is frequently observed in children with obesity and may represent a practical clinical marker of IR. This study evaluated the association between AN, IR, and metabolic complications in paediatric obesity. Methodology: A retrospective review was performed of 148 children (88 males, 60 females; median age 12 years) attending the Paediatric Obesity Clinic at Universiti Malaya Medical Centre. Data included anthropometry, AN grading, family history, HOMA-IR, and metabolic screening. Outcomes assessed were dyslipidemia, metabolic-associated fatty liver disease (MAFLD), hypertension, obstructive sleep apnea syndrome (OSAS), and glucose dysregulation. Comparisons were made between children with and without AN at baseline and over follow-up (median 2.4 years). Results: AN was present in 81.8% of patients, and 82.4% had central obesity. Increasing AN grade was significantly associated with higher BMI SDS and American Academy of Paediatrics obesity class (p <0.05). AN was more prevalent among Malay and Indian children and was associated with a family history of obesity (p <0.05). Baseline metabolic abnormalities were common, including dyslipidemia (high triglycerides 31.8%, low HDL 30.4%, high LDL 29.7%), MAFLD (23.6%), OSAS (31.1%), and glucose dysregulation (27.7%), with no significant difference between groups. During follow-up, children with AN and more severe obesity developed significantly more metabolic complications, particularly MAFLD and OSAS, with increased requirement for non-invasive ventilation (p <0.05). Higher HOMA-IR was associated with glucose dysregulation but was not independently associated with AN. Conclusion AN is strongly associated with greater adiposity and predicts the progression of metabolic complications in children with obesity. Routine assessment of AN may help identify high-risk patients who would benefit from early, intensive intervention to reduce long-term cardiometabolic morbidity
Child ; Acanthosis Nigricans ; Biomarkers ; Obesity

Stroke-associated sarcopenia is a serious post-stroke complication that can have a significant impact on patient’s functional recovery. However， currently available assessment tools for sarcopenia require specialized equipment and personnel， which are difficult to access in resource-limited settings. This article presents the role of biomarkers as an objective method in the pathogenesis， prevention， diagnosis， and prognostic assessment of stroke-associated sarcopenia， with the focus on neuromuscular， inflammatory， metabolic， and nutritional indicators.
Stroke ; Sarcopenia ; Biomarkers

Cognition is the intelligent processing of the brain， which affects the acquisition and realization of knowledge in the body， including learning， memory， thinking， language， emotion， spirit， and other psychological and social activities. Cognitive impairment refers to abnormalities in the processing of higher-order intellectual activities in the brain， such as learning， memory， thinking， and judgment， which leads to severe learning and memory difficulties， and it is often accompanied by pathological developments including aphasia and apraxia， which is mainly caused by Alzheimer disease， cerebrovascular diseases， and traumatic brain injury. At present， the etiology of cognitive impairment remains unclear. Nowadays， with the continuous development of modern science and technology， proteomics technology has been widely used in the field of clinical medical research and can provide a scientific basis for the diagnosis and treatment of diseases and the development of new drugs. This article reviews the research advances in proteomics technologies， humoral proteomics of cognitive disorders， brain tissue proteomics， and proteomics research in cognitive disorders at high altitude， in order to further reveal the application and development of proteomics in cognitive disorders.
Biomarkers

OBJECTIVE: To investigate the clinical utility of novel of new hematological markers in the preoperative diagnosis of periprosthetic joint infection (PJI). METHODS: A retrospective analysis was conducted on a total of 149 patients who underwent revision of total hip arthroplasty (THA) or total knee arthroplasty (TKA) at a single center between January 2016 and June 2022, including 63 males and 86 females, aged from 47 to 93 years old with an average of (69.5±11.8) years old. Of them, 46 were diagnosed as PJI(PJI group), including 22 males and 24 females. The mean age was (71.3±12.5) years old. The body mass index (BMI) was (26.4±3.1) kg·m^-2. And 103 patients were diagnosed as aseptic prosthesis loosening (aseptic group), including 41 males and 62 females. The mean age was (68.7±11.4) years old. The BMI was (25.8±3.5) kg·m^-2. Preoperatively analyzed clinical parameters included C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), albumin, globulin, albumin-to-globulin ratio (AGR), plasma D-dimer, and plasma fibrinogen. The receiver operating characteristic curve (ROC), sensitivity, and specificity analysis were employed to compare the diagnostic value of each blood marker in preoperative PJI diagnosis. RESULTS: In the PJI group, the levels of CRP were 16.6 (7.6, 4.5) mg·L^-1, ESR was 17.0 (12.8, 35.5) mm·h^-1, plasma D-dimer was 1.0 (0.5, 3.1) μg·L^-1, and plasma fibrinogen was 4.2 (3.2, 3.1) mg·L^-1;all of which were higher compared to the aseptic group with CRP at 4.2 (2.6, 7.8) mg·L^-1, ESR at 12.0(8.0, 20.0 )mm·h^-l, D-dimer at 0.4(0.2, 0.7)μg·L^-1, and fibrinogen at 2.8(2.4, 3.3 ) g·L^-1(P<0.05). However, the albumin level of 35.3 (32.3, 37.5) g·L^-1 and the WBC ratio of 1.0(0.9, 1.1) in the PJI group were significantly lower compared to the aseptic group with levels of 39.8 (36.1, 41.8) g·L^-1 and 1.4 (1.3, 1.5), respectively (P<0.05). Only the area under the curve (AUC) of AGR and plasma fibrinogen were greater than 0.8. The optimal predictive cut-1off, AUC, sensitivity and specificity were 3.4 g·L-1, 0.820, 69.57% and 84.47% for plasma fibrinogen; 1.18, 0.813, 82.61% and 78.64% for AGR, respectively. CONCLUSION AGR and plasma fibrinogen are promising blood markers for improving the diagnosis of PJI.
Humans ; Female ; Fibrinogen/metabolism* ; Male ; Middle Aged ; Aged ; Prosthesis-Related Infections/blood* ; Retrospective Studies ; Biomarkers/blood* ; Aged, 80 and over ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthroplasty, Replacement, Hip/adverse effects* ; Leukocyte Count

OBJECTIVE: To investigate the variability of bone metabolism levels among different populations and its association with knee osteoarthritis (KOA) pain. METHODS: A total of 50 people (control group) who participated in physical examination from January 2023 to June 2023 were selected, including 26 males and 24 females, wtih a mean aged of (52.14±9.04) years old ranging 41 to 65 years old. The other 50 patients with knee osteoarthritis(case group) who attended the outpatient clinic of the Orthopedics and Traumatology Department in the same time period, including 19 males and 31 females, with a mean age of (53.60±7.76) years old ranging 40 to 65 years. The two groups of Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC) and bone metabolism markers, such as 25-hydroxy-cholecalciferol[25(OH)D], β-isomerized typeⅠcollagen C-telopeptide breakdown products (β-CTX), total typeⅠprocollagen N-terminal propeptide (t-PINP), osteocalcin (OC), parathormone (PTH) levels were compared. Pearson correlation analysis was used to compare the correlation between two groups of bone metabolism related markers and WOMAC. RESULTS: The WOMAC score of the case group (39.90±2.34) was higher than that of the control group (3.60±0.57), with significant difference (P<0.05). There was no significant difference between the two groups of 25 (OH)D, β-CTX and PTH (P>0.05). The t-PINP and OC of the case group were (62.90±52.40) and (19.88±10.15) ng·ml-1, respectively, and those of the control group were (38.86±10.82) and (14.90±3.62) ng·ml^-1, respectively;the t-PINP and OC of the case group were higher than those of the control group, with significant difference (P<0.05). Pearson correlation analysis showed that t-PINP was positively correlated with WOMAC pain score in the case group (r²=0.045, P<0.01). CONCLUSION Bone metabolism levels in the serum of patients with knee osteoarthritis are different from those of healthy people, and the difference between OC and t-PINP is the most obvious, and the concentration of t-PINP levels is positively correlated with pain symptoms in patients with KOA. However, the specific mechanism of correlation between the bone metabolism levels of patients with KOA and their pain symptoms needs to be further elucidated by basic experimental research as well as by enlarging the samples.
Humans ; Female ; Male ; Middle Aged ; Osteoarthritis, Knee/metabolism* ; Aged ; Adult ; Bone and Bones/metabolism* ; Pain/etiology* ; Biomarkers/metabolism*

Objective To explore the clinical and immunological significance of CCDC97 in hepatocellular carcinoma (HCC). Methods Clinical data and RNA sequencing results from HCC patients were retrieved from TCGA and ICGC databases. Bioinformatics analysis and in vitro experiments were performed to investigate the role of CCDC97 in HCC. Results The expression level of CCDC97 was elevated in HCC patients and HCC cells, closely associated with pathological features and prognosis. CCDC97 was identified as a novel prognostic biomarker. It is linked to the spliceosome pathway, which is significantly active in tumors and potentially promotes carcinogenesis. CCDC97 is also highly expressed in various immune cells and is associated with microenvironment. Furthermore, knocking down CCDC97 in vitro suppressed cell migration, invasion, and proliferation. Conclusion CCDC97 plays a critical role in HCC progression and the immune microenvironment, making it a potential target for prognosis and therapeutic intervention.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Tumor Microenvironment/genetics* ; Cell Movement/genetics* ; Cell Proliferation ; Prognosis ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Male

Objective To investigate the clinical relevance and diagnostic or prognostic value of ST3β-galactoside α-2, 3-sialyltransferase 1 (ST3GAL1) in glioma and to confirm its role in promoting malignant phenotypes. Methods Using data from The Cancer Genome Atlas (TCGA) database, we analyzed the correlation between ST3GAL1 expression levels in glioma and clinical parameters to evaluate its diagnostic and prognostic value. The impact of ST3GAL1 on malignant phenotypes of glioma cells-including proliferation, cell cycle progression, apoptosis, and invasion was further validated through ST3GAL1 knockdown experiments. Results The expression level of ST3GAL1 was significantly higher in glioma tissues compared to healthy brain tissues and showed a strong correlation with clinical characteristics of glioma patients. Survival analysis and receiver operating characteristic (ROC) curve demonstrated that ST3GAL1 could serve as a potential diagnostic and prognostic biomarker for glioma. Knockdown of ST3GAL1 suppressed proliferation, invasion, and migration capabilities of glioma cell lines, and induced G1-phase cell cycle arrest. Conclusion ST3GAL1 promotes malignant phenotypes in glioma and plays a critical role in its malignant progression, suggesting its potential as a biomarker for glioma diagnosis and prognosis.
Humans ; Sialyltransferases/metabolism* ; Glioma/diagnosis* ; Cell Proliferation/genetics* ; Cell Line, Tumor ; Brain Neoplasms/enzymology* ; beta-Galactoside alpha-2,3-Sialyltransferase ; Disease Progression ; Prognosis ; Cell Movement/genetics* ; Apoptosis/genetics* ; Male ; Female ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/metabolism* ; Middle Aged

Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning

The early diagnosis and precise treatment of esophageal squamous cell carcinoma (ESCC) hold significant clinical value in improving patient survival rate. Current diagnostic methods for early-stage ESCC primarily rely on invasive procedures and endoscopy, which can cause discomfort and financial burden for patients. Therefore, non-invasive biomarkers with high sensitivity and specificity present a more suitable alternative for early tumor diagnosis. Tumor associated autoantibodies (TAAb), identified as potential biomarkers, have considerable clinical implications for the early diagnosis, treatment monitoring, and prognosis assessment of ESCC. Here in we aim to summarize recent research on ESCC-related autoantibodies, including their background, types and development, analyze the potential of those autoantibodies in clinical diagnosis, treatment monitoring, and prognosis assessment, and also discuss the limitations of existing research and future directions. The goal is to provide a theoretical foundation for the early diagnosis and personalized treatment of ESCC.
Humans ; Autoantibodies/immunology* ; Esophageal Neoplasms/therapy* ; Esophageal Squamous Cell Carcinoma/immunology* ; Biomarkers, Tumor/immunology* ; Prognosis ; Carcinoma, Squamous Cell/diagnosis* ; Animals