Background Kinesin family member 20A (KIF20A), a microtubule-dependent motor protein of the Kinesin superfamily, is involved in cell division and organelle transport. Its expression is dysregulated in various cancers and is closely related to tumor metastasis and patient prognosis. However, its specific functions in different tumor types and the potential as an anticancer target have not been fully elucidated, and a systematic pan-cancer analysis is lacking. Methods This study integrated multiple cancer database resources and systematically analyzed the multi-omics alterations of KIF20A in different cancers using R software, including gene expression, genomic variation, methylation status, biological pathways, and clinical value. In addition, we evaluated the regulatory role and immunotherapy potential of KIF20A in the tumor microenvironment through various bioinformatics algorithms. Finally, we explored the impact of KIF20A on the biological behaviors of Kidney Renal Clear Cell Carcinoma (KIRC) cells through in vitro and in vivo experiments. Results KIF20A is localized in the nucleus and participates in the cell cycle process, serving as a core gene for tumor cell growth. It undergoes copy number alterations in various tumors, and its high expression is closely associated with clinical progression, poor prognosis, and activation of classical oncogenic pathways in multiple cancers. Mechanistically, aberrant epigenetic modifications and mutations in hallmark pathways are significant reasons for the dysregulated expression of KIF20A. Furthermore, the expression of KIF20A correlates with immune cell infiltration and the expression of immune checkpoint molecules, impacting the efficacy of immunotherapy in various cancers. In vitro experiments have confirmed that interfering with KIF20A expression can effectively inhibit the proliferation, migration, and invasion of KIRC cells. Furthermore, in vivo experimental results indicate that interfering with KIF20A can inhibit tumor growth in nude mice. Conclusion To our knowledge, this is the first study to reveal the role of KIF20A in tumorigenesis and development from a pan-cancer multi-omics perspective, providing solid theoretical and experimental evidence for KIF20A as a potential anti-cancer therapeutic target.

Background Our work aims to develop and evaluate a combined model that integrates clinical features, conventional computed tomography angiography (CTA) features, and radiomics features of perivascular adipose tissue (PVAT) to identify asymptomatic carotid stenosis (ACS) patients at high risk for short-term stroke. Methods We enrolled 582 ACS patients confirmed by CTA from three medical centers and divided them into a training set ( n = 188), an internal validation set ( n = 85), and two independent external validation sets (set 1, n = 157; set 2, n = 152). Radiomics features of PVAT were extracted from CTA images, and dimensionality reduction was performed to identify predictive features. Five machine learning classifiers were employed to construct radiomics models, and the model with the highest AUC was selected to generate the radiomics score (Rad-score). Clinical factors associated with stroke were determined using univariate and multivariate logistic regression analyses to construct a clinical model. A combined model integrating clinical factors and the Rad-score was subsequently developed, and a nomogram was created to provide a visual tool for stroke risk prediction. We assessed model performance comprehensively through calibration curves, discrimination analysis, reclassification, and clinical application. Results A total of nine optimal radiomics features were ultimately selected from the CTA images. Across the four datasets, the AUC values of the five classifier models ranged from 0.643 to 0.869, 0.716 to 0.826, 0.651 to 0.858, and 0.638 to 0.848, respectively, with the XGBoost model demonstrating the best performance. The combined model, incorporating hypertension, soft plaque, and the Rad-score as variables, achieved AUCs of 0.911, 0.868, 0.882, and 0.871, respectively, across the four datasets. Conclusions A combined model based on PVAT imaging features around carotid plaques can effectively predict the short-term stroke risk in ACS patients. This model may be expected to provide an important auxiliary tool for clinical prognosis assessment and treatment decisions, with potential clinical application value.

To investigate the patterns of recurrence/metastasis and the clinical value of radiotherapy in local control for pediatric pancreatoblastoma. A retrospective analysis was conducted on 14 pediatric patients with pathologically confirmed pancreatoblastoma treated at our institution from June 2017 to June 2024. Clinical data, including baseline characteristics, surgical approaches, pathological staging, adjuvant therapies (chemotherapy/radiotherapy), recurrence/metastasis patterns, and subsequent interventions, were systematically collected. The impact of radiotherapy on local control was evaluated, with survival analysis performed using Kaplan-Meier methods, and prognostic factors analyzed via log-rank tests and Cox regression models. The median age of the entire cohort was 7 years (range, 3-13 years), with 4 cases of pancreatic head tumors and 10 cases of pancreatic body/tail tumors. At initial diagnosis, 57.1% (8/14) presented with regional lymph node metastasis, and 57.1% (8/14) had distant metastasis. The R0 resection rate during the first surgery was 57.1% (8/14), while R1/R2 resections accounted for 28.6% (4/14); 2 did not undergo surgery. With a median follow-up of 31 months, the overall survival rate was 78.6% (11/14). The recurrence/metastasis rate was 64.2% (9/14), with predominant patterns including tumor bed recurrence (3/9, 33.3%), regional lymph node metastasis (3/9, 66.7%), and liver metastasis (5/9, 55.6%). Multimodal therapies encompassed chemotherapy, secondary surgery, liver transplantation, and radiotherapy for metastatic lesions. In the radiotherapy group, the 1-year and 2-year local control rates were 100% and 88%, respectively. Log-rank test and Cox analysis identified failure to achieve R0 resection and regional lymph node metastasis as independent prognostic factors for inferior overall survival (P < 0.05). Other factors-including age, gender, presence of initial metastasis, initial liver/lung metastasis, number of recurrence/metastasis events, and radiotherapy-showed no significant correlation with overall survival. Regional lymph node metastasis and failure to achieve R0 resection are critical prognostic factors affecting long-term survival in pancreatoblastoma patients. Adjuvant radiotherapy significantly improves local control rates and may enhance survival outcomes in patients with positive margins or lymph node metastasis by strengthening local disease control, warranting further validation in prospective studies.

Purpose Vitamin B1 (VB1), an essential coenzyme in cellular energy metabolism, is postulated to modulate clinical outcomes in sepsis. However, the relationship between VB1 and sepsis remains inadequately explored both domestically and internationally, and its potential clinical value remains unclear. Therefore, this study aims to investigate the association between VB1 deficiency and the severity of sepsis, and to evaluate the potential clinical utility of VB1 in ameliorating sepsis-induced organ injury and coagulation dysfunction. Methods A total of 67 patients from Inner Mongolia Baogang Hospital were enrolled in this study. Among them, 41 were assigned to the sepsis group (clinically diagnosed with sepsis), and the remaining 26 comprised the control group (patients with ordinary pneumonia who did not meet the clinical diagnostic criteria for sepsis). Serum VB1 levels were measured using ultra-high-performance liquid chromatography–tandem mass spectrometry from peripheral blood samples. Clinical and laboratory data were obtained from electronic medical records. Multivariate logistic regression analysis was employed to assess the potential of VB1 as an independent biomarker for sepsis. All statistical analyses were performed using SPSS version 27.0. Results The sepsis group exhibited significantly lower VB1 levels than the control group ( p &amp;lt; 0.001). Further analysis revealed a significantly higher proportion of sepsis patients in the VB1 deficiency group compared to the control group, whereas the VB1 sufficiency group showed a significantly lower proportion of sepsis patients ( p &amp;lt; 0.001). Correlation analysis demonstrated significant negative correlations between VB1 levels and sequential organ failure assessment scores, procalcitonin, D-dimer, creatinine, and cardiac troponin I, and positively correlated with albumin. Multivariable logistic regression analysis revealed that when VB1 was analyzed as a continuous variable, a high VB1 level was independently associated with a low prevalence of sepsis (OR = 0.127, 95% CI: 0.022–0.744, p = 0.022). Conclusion VB1 levels exhibit an inverse association with key inflammatory biomarkers in patients with sepsis, and reduced VB1 concentration is independently associated with a higher prevalence of sepsis.

Hyperlipidemia is a major risk factor for coronary atherosclerotic heart disease (CAHD). However, conventional lipid profiling fails to fully reflect the complexity of lipid metabolism. Furthermore, while lipidomics has identified numerous complex lipids as biomarkers, the role of their fundamental constituents-serum fatty acids-remains less explored in CAHD. In this study, we performed detailed profiling of serum fatty acid species to explore their utility in improving the identification and management of lipid disorders specifically within the CAHD population, an approach whose clinical value in this context remains underexplored. The study analyzed serum fatty acid profiles in three CAHD cohorts: a training cohort (n = 432) and two external validation cohorts (n = 1302 and n = 1458). Serum samples were collected during initial and subsequent hospitalizations. A total of 39 fatty acids were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Multivariate analyses were conducted to identify fatty acids with diagnostic relevance, followed by model development and external validation. In CAHD patients, several fatty acids were significantly correlated with total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (Apo B). Among these, esterified linoleic acid demonstrated a strong correlation with lipid biomarker (r > 0.69, p < 0.001). Logistic regression analysis identified esterified oleic acid (OR = 37.80, p < 0.001) and linoleic acid (OR = 10.74, p < 0.001) as independent significant risk factors for hyperlipidemia. The combined model incorporating these fatty acids demonstrated an AUC exceeding 0.94 (95% CI: 0.93-0.95) in both training and validation cohorts, with sensitivity and specificity exceeding 85.6% and 81.0%, respectively. Notably, during statin therapy, linoleic acid decreased significantly and was associated with favorable lipid-lowering effects, comparable to the rate of change in TC, with no significant difference. Esterified linoleic acid (C18:2 n6) and oleic acid (C18:1 n9) were identified as key serum biomarkers for hyperlipidemia in CAHD patients, and their combination yielded the best diagnostic performance. Moreover, C18:2 n6 decreased during statin therapy and may serve as a useful marker for monitoring treatment response.

Objective . This study aimed to systematize and analyze contemporary data on the evolution of cephalosporin antibiotics from the first to the fifth generation, with a focus on changes in their antimicrobial spectrum, pharmacokinetic properties, and safety profile in the context of rising antibiotic resistance. Materials and methods . A review of the scientific literature was conducted, sourcing data from PubMed, Google Scholar, CyberLeninka, elibrary.ru, and library resources using keywords such as "cephalosporins", "antibiotic resistance", "MRSA", "Gram-negative bacteria", and "cefiderocol". The analysis included systematic reviews, randomized clinical trials, cohort studies, and meta-analyses published over the last two decades, as well as foundational historical works. Results . The review demonstrates a clear evolutionary trajectory in the development of cephalosporin. First- and second- generation agents remain relevant for treating infections caused by Gram-positive cocci and some communities of Gram-negative microorganisms. Third- and fourth-generation cephalosporins have become the cornerstone of empirical therapy for nosocomial infections because of their expanded spectrum of activity against Gram-negative flora, including Pseudomonas aeruginosa. Fifth-generation drugs (ceftobiprole and ceftaroline) were developed to overcome MRSA resistance. A separate analysis was dedicated to the innovative agent, cefiderocol — the first siderophore cephalosporin, which possesses a unique transport mechanism into the bacterial cell and demonstrates activity against carbapenem-resistant strains of Enterobacterales, P. aeruginosa, and A. baumannii. Despite its unique properties, cefiderocol resistance is already emerging. The specific pharmacokinetic profiles (administration routes, half-life, and blood-brain barrier penetration) and spectrum of adverse reactions (allergic, hematological, and neurological) of different generations were analyzed. Conclusion . Cephalosporins remain a cornerstone of modern antimicrobial therapy because of their favorable efficacy and safety profile. The introduction of new generations, particularly cefiderocol, represents a direct response to the global challenge of antibiotic resistance. However, the rapid emergence of resistance mechanisms even to the most advanced agents underscores the critical importance of antimicrobial stewardship programs and strict adherence to the principles of rational antibiotic therapy to preserve the future clinical value of this drug class.

Blood-brain barrier (BBB) disruption is a recognized contributor to neurodegenerative diseases. However, its specific role in cognitive decline in diabetes has not been sufficiently explored. This study aimed to evaluate the association between BBB integrity and cognitive function and to investigate the discriminative ability of BBB-related biomarkers for cognitive impairment in individuals with type 2 diabetes mellitus (T2DM). In this case-control study, participants were recruited from the Second Affiliated Hospital of Nanchang University. All subjects underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We compared quantitative brain imaging (Ktrans and Ve) and serum platelet-derived growth factor receptor β (PDGFRβ) between diabetic individuals with and without cognitive impairment. The relationships between these biomarkers and cognitive performance were assessed using linear regression analyses. The discriminative capacity of each biomarker for distinguishing groups was evaluated using receiver operating characteristic (ROC) curve analysis. T2DM individuals with cognitive impairment exhibited significantly elevated Ktrans and Ve levels compared to those without, which correlated inversely with MoCA scores in key brain regions. Serum PDGFRβ was also independently associated with impaired cognition. Every biomarker individually demonstrated high discriminative power for evaluating cognitive status, with AUC values of 0.908 (95% CI: 0.842 to 0.973) for Ktrans, 0.923 (95% CI: 0.86 to 0.986) for Ve, and 0.839 (95% CI: 0.751 to 0.928) for PDGFRβ. Our results confirm the critical role of BBB dysfunction in diabetic cognitive impairment. The biomarkers serum PDGFRβ, Ktrans, and Ve showed potential associations with this condition, suggesting their clinical value for future clinical application in risk stratification and therapeutic monitoring in T2DM population. TRN: ChiCTR2400085417, 2024.06.06, retrospectively registered.

Objectives To develop a diagnostic prediction model for rapidly progressive central precocious puberty (RP-CPP) and evaluate the contribution of osteocalcin(OC) to the model. Methods For a total of 411 girls who met the criteria for central precocious puberty were selected. Of these, 219 were included in the training set, 87 in the internal validation set, and 105 in the external validation set. Binary logistic regression was used to construct the model. The model fit and diagnostic accuracy were assessed using the Akaike Information Criterion (AIC), calibration curves, and the area under the receiver operating characteristic curve(AUC). The model was presented in the form of a nomogram. Internal and external validations of the model were performed. Results Diagnostic models for RP-CPP were developed both with and without the inclusion of OC. Among all models, those that included OC consistently demonstrated smaller AIC values, higher AUC values, and lower prediction error rates. A model incorporating the duration of breast development, serum OC levels, mean ovarian volume, endometrial presence/absence, and breast Tanner staging demonstrated superior performance. The AUC for diagnosing RP-CPP was 0.973, with a sensitivity of 91.6% and specificity of 92.5%. The model performed well in the internal and external validation sets, demonstrating good clinical application value. Conclusion The inclusion of OC helps improve the predictive performance of the model. For the diagnosis of RP-CPP in girls, a model can be chosen that includes the duration of breast development, serum OC levels, mean ovarian volume, endometrial presence/absence, and breast Tanner staging. However, all samples were from a single center, and multicenter validation is still needed.

University-hospital conventions within the Italian Servizio Sanitario Nazionale, regulated by D.Lgs. 517/1999, allow academic clinicians to serve as clinical directors in public hospitals. While the educational and scientific benefits are well described, systematic economic evaluation of these arrangements is lacking. A 12-month Budget Impact Analysis was conducted comparing two staffing models: (i) a hospital-employed clinical director fully remunerated by the regional health service, and (ii) a university-affiliated professor whose base salary is funded by the university under national conventions. Direct personnel costs were calculated using CCNL Dirigenza Medica salary tables, statutory allowances, employer contributions, and institutional payroll data. Analyses were performed from both the hospital perspective and the system-wide public-sector perspective, with deterministic sensitivity analyses assessing robustness. Academic integration reduced hospital personnel expenditures by 66.6%, with average annual savings of €145,100 (95% CI: €141,900-€148,600) per department. Savings remained above 50% across all sensitivity analyses. When university-funded salary components were included, total public-sector expenditure for the academic-integrated model approximated that of the conventional model, indicating cost redistribution rather than system-wide savings. University-affiliated clinical directors provide substantial and reliable hospital-level cost savings for Italian public hospitals through redistribution of salary obligations across the public sector. However, this economic advantage does not imply demonstrated improvements in clinical productivity, research output, or educational value, which were not evaluated in this study and require dedicated empirical investigation. Clear distinction between economic and non-economic dimensions is essential when interpreting the role of university-hospital conventions.

BACKGROUNDPost-stroke depression (PSD) is associated with hypothalamic-pituitary-adrenal (HPA) axis dysfunction and neurotransmitter deficits. Selective serotonin reuptake inhibitors (SSRIs) are commonly used, but their efficacy is limited. This study investigated whether combining SSRIs with traditional Chinese medicine (TCM) Free San could enhance their therapeutic effects.AIMTo evaluate the clinical efficacy and safety of combining SSRIs with Free San in treating PSD, and to assess its impact on HPA axis function.METHODSNinety-two patients with PSD were enrolled and randomly divided into control groups (n = 46) and study groups (n = 46). The control group received the SSRI paroxetine alone, whereas the study group received paroxetine combined with Free San for 4 weeks. Hamilton Depression Scale and TCM syndrome scores were assessed before and after treatment. Serum serotonin, norepinephrine, cortisol, corticotropin-releasing hormone, and adrenocorticotropic hormone were measured. The treatment responses and adverse reactions were recorded.RESULTSAfter treatment, the Hamilton Depression Scale and TCM syndrome scores were significantly lower in the study group than in the control group (P < 0.05). Serum serotonin and norepinephrine levels were significantly higher in the study group than in the control group, whereas cortisol, corticotropin-releasing hormone, and adrenocorticotropic hormone levels were significantly lower (P < 0.05). The total efficacy rates were 84.78% and 65.22% in the study and control groups, respectively (P < 0.05). No significant differences in adverse reactions were observed between the two groups (P > 0.05).CONCLUSIONCombining SSRIs with Free San can enhance therapeutic efficacy, improve depressive symptoms, and regulate HPA axis function in patients with PSD with good safety and clinical application value.

Insomnia is a prevalent sleep disorder characterized by difficulty initiating or maintaining sleep and is associated with substantial health and economic burdens. Although cognitive behavioral therapy (CBT) is recommended as the first-line treatment, pharmacotherapy remains widely used despite adverse effects and significant indirect costs related to impaired productivity and workplace safety. Digital therapeutics delivering CBT through mobile platforms have emerged as scalable alternatives to improve access and outcomes. Somzz is a commercially available, domestically developed digital therapeutic that delivers CBT-based interventions for insomnia via a mobile app. This study evaluated the cost-effectiveness of Somzz compared with conventional insomnia treatment combining CBT and pharmacotherapy from both health care system and societal perspectives in South Korea. A decision-analytic model integrating a short-term decision tree with a Markov model was developed to compare costs and outcomes of digital CBT via Somzz versus conventional care in 2023. The model simulated a 27-week time horizon (three treatment cycles) and applied an annual discount rate of 4.5%. Clinical inputs, including remission probabilities and health utility values, were derived from a published randomized clinical trial comparing digital CBT delivered via Somzz with sleep hygiene education. Additional inputs, including health care resource use and unit costs, were obtained from published literature and national sources. Health outcomes were measured in quality-adjusted life years (QALYs). The cost analysis included direct medical costs and indirect costs related to absenteeism, productivity loss, and workplace accidents attributable to insomnia. Incremental cost-effectiveness ratios (ICERs) were estimated in 2023 South Korean Won (KRW). Deterministic one-way and probabilistic sensitivity analyses were conducted to assess uncertainty. From a health care system perspective, digital CBT via Somzz resulted in modestly higher costs and improved health outcomes compared with standard care. Over approximately 6.5 months, Somzz generated an additional 0.0092 QALYs per patient at an incremental cost of KRW 79,691 (US $61.87), yielding an ICER of KRW 8,719,727 (US $990,883) per QALY gained. This estimate was well below the Korean willingness-to-pay threshold of KRW 30,000,000 (US $23,192.91) per QALY. From a societal perspective, digital CBT was cost-saving, producing a negative ICER due to reductions in health care utilization, workplace accidents, and productivity losses associated with higher remission rates. Sensitivity analyses identified intervention costs and remission probabilities as key drivers; however, digital CBT remained cost-effective across all scenarios under willingness-to-pay thresholds of KRW 30,000,000 and KRW 15,000,000 per QALY. Digital CBT for insomnia offers favorable clinical and economic value in South Korea. Using Korean clinical trial data and locally relevant societal cost inputs, this study provides policy-relevant evidence supporting early integration of digital CBT into routine insomnia care, employer health strategies, and national digital health policy. World Health Organization International Clinical Trials Registry Platform KCT0007292; https://trialsearch.who.int/Trial2.aspx?TrialID=KCT0007292.

The lymphatic system is widely distributed in skeletal muscles, joints, and skeletal tissues and plays a key role in maintaining immune homeostasis, regulating inflammatory responses, and tissue repair. In recent years, an increasing number of studies have shown that morphological and functional changes in lymphatic vessels are closely associated with the onset and progression of a variety of musculoskeletal disorders (MSDs), such as osteoarthritis (OA), fractures, and muscular dystrophy. However, the specific mechanisms of the lymphatic system's role in these diseases have not been fully elucidated, and their potential clinical value remains to be thoroughly explored. In this review, we review the recent research progress on the structure, function, and pathophysiological role of the lymphatic system in the musculoskeletal system, and we focus on the association between lymphangiogenesis, dysfunction, and MSDs, and systematically summarize the therapeutic strategies targeting the lymphatic system. In addition, we summarize the limitations of current studies and propose key directions for future research, with a view to providing new ideas for basic research and clinical intervention in MSDs.

Cardiometabolic multimorbidity (CMM) is the simultaneous manifestation of multiple cardiovascular and metabolic diseases, and it has arisen as a substantial worldwide healthcare issue. The stress-hyperglycemia ratio (SHR) represents a novel biomarker that is strongly associated with the prognosis of various diseases; however, its role in CMM remains insufficiently understood. This research aims to examine the association between SHR and CMM risk and assess its clinical utility in risk assessment. This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES), with a total of 12,279 participants meeting the inclusion criteria. A weighted logistic regression model was used to examine the correlation between SHR and CMM. Furthermore, machine learning (ML) techniques were applied to develop a CMM prediction model, and the validity of the findings was confirmed by several sensitivity analysis, including external validation using the China Health and Retirement Longitudinal Survey (CHARLS). In addition, mediation analysis was performed to investigate the potential mediating roles of body mass index (BMI) and waist circumference (WC). A substantial positive relationship was identified between SHR and CMM risk. For 1-unit rise in SHR, the risk of CMM rose by 21.131 (OR = 22.131 [10.688, 45.823]). Smooth curve fitting analysis indicated a U-shaped correlation between SHR and CMM risk. When SHR is below 0.841, CMM risk decreases as SHR increases (OR = 0.001 [0.000, 0.004]); however, when SHR exceeds 0.841, CMM risk increases sharply as SHR rises (OR = 116.890 [70.086, 194.951]). The findings of the mediation study demonstrated that BMI and WC moderated the association between SHR and CMM risk. Furthermore, the gradient boosting machine (GBM) model demonstrated robust predictive performance with an Area Under the Curve (AUC) of 0.880 (95% CI 0.866-0.894), while shapley additive explanations identified age, SHR, and WC as the top three predictors with the most significant impact on the model outcomes. Sensitivity analyses consistently validated the findings, with the external validation in the CHARLS cohort confirming a significant positive association (OR = 1.389, [1.026, 1.880]. This study identified a U-shaped non-linear relationship between SHR and CMM risk, underscoring the potential clinical value of SHR in the early diagnosis and risk assessment of CMM. The predictive model developed using machine learning methods can significantly aid clinicians in conducting personalized risk assessments for CMM.

To develop and validate a clinical prediction model for differentiating non-small cell lung cancer (NSCLC) from benign pulmonary diseases (BPD). The retrospective study included 226 participants in the training set (134 with NSCLC and 92 with BPD) and 98 participants in the validation set (62 with NSCLC and 36 with BPD). A logistic regression model was constructed using variables such as sex, hemoptysis, serum biomarkers (carcinoembryonic antigen [CEA] and total protein [TP]), and CT features (volume ratio of solid density region [VR_2A], volume of calcified density area [VR_3], total volume [TV], CT variance [CTV], and maximum surface area [MSA]). The model was validated on an independent cohort, and its performance was evaluated using area under the curve (AUC), accuracy, calibration curves, and decision curves. Additionally, a nomogram was developed for clinical application, and its acceptance and convenience among clinicians were assessed. The prediction model achieved an AUC-ROC of 0.95 in the training set and 0.82 in the validation set. Calibration and decision curves demonstrated that the model had reliable diagnostic performance and good clinical application value. The integrated prediction model combining clinical features, laboratory biomarkers, and CT features shows promise for improving the accuracy of differentiating NSCLC from BPD. Further studies are warranted to explore its potential in clinical practice.

Identification of blood-based inflammatory biomarkers for vestibular neuritis using a proximity extension assay.

Methylated septin9 (septin9-mC) is a well-validated biomarker for colorectal cancer screening, and accurate detection of such site-specific methylated DNA holds significant clinical value for early disease diagnosis. However, conventional methods suffer from cumbersome pretreatment, DNA degradation risks, and poor performance in low-abundance samples. Herein, we report a synergistic iontronic sensing platform integrating methylation-sensitive restriction enzyme (AciI), CRISPR/Cas12a, Ag-DNAzyme, and Au/Pt heterometallic nanozyme for highly sensitive and specific detection of septin9-mC. AciI selectively cleaves unmethylated septin9 (septin9-C) while sparing septin9-mC, and intact septin9-mC activates Cas12a trans-cleavage activity to trigger catalytic hairpin assembly (CHA), generating Ag-DNAzyme. Activated Ag-DNAzyme induces detachment of Au/Pt nanoparticles from anodic aluminum oxide membranes, reducing the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to positively charged oxTMB and altering ion transport fluxes in nanochannels, which is read out via current-voltage characteristics. The linear range is 100 aM to 10 nM with a detection limit of 34.0 aM. This method effectively distinguishing colorectal cancer cells from human colonic epithelial cells and colorectal cancer patients from healthy individuals, showing excellent performance in real sample analysis. The proposed method provides a dependable tool for site-specific methylation detection with promising applications in biological research and clinical diagnosis.

[Objective] To explore the clinical value of serum Intestinal Trefoil Factor (ITF), Ionized Calcium-Binding Adapter Molecule 1 (IBA-1), and Calgranulin B levels in the early auxiliary diagnosis and prognostic evaluation of cervical cancer. [Methods] The cervical cancer group consisted of 256 patients who received a cervical cancer diagnosis at this hospital between January 2023 and June 2024. 150 people who were diagnosed with cervical intraepithelial neoplasia (CIN) at this hospital within the same time period made up the CIN group. 90 women who underwent health checks at this facility throughout the same time period made up the healthy control group. The diagnostic effectiveness of serum ITF, IBA-1, and Calgranulin B levels in patients with cervical cancer, as well as their correlations with clinical indicators and prognosis, were examined, as were changes in these levels in each group. [Results] The cervical cancer group's blood ITF, IBA-1, and Calgranulin B levels were noticeably higher than those of the CIN group and the healthy control group. Compared to the healthy control group, the CIN group's serum ITF, IBA-1, and Calgranulin B levels were considerably higher (P&lt;0.05). When diagnosing cervical cancer, serum ITF, IBA-1, and Calgranulin B levels are highly valuable. When all three signs were detected together, the sensitivity was 89.4% and the specificity was 97.6%, and 0.961 was the receiver operating characteristic curve's area under the curve, which was significantly greater than that of ITF (Z=4.620, P&lt;0.05), IBA-1 (Z=4.167, P&lt;0.05), and Calgranulin B (Z=5.210, P&lt;0.05) alone in independent testing. Serum ITF, IBA-1, and Calgranulin B levels were significantly higher in patients with poorly differentiated, clinical stage II, HPV-positive cervical cancer with lymph node metastases than in patients with moderately differentiated, clinical stage I, HPV-negative cervical cancer without lymph node metastases. These differences were statistically significant (P&lt;0.05). However, there were no statistically significant differences in the levels of serum ITF, IBA-1 or Calgranulin B among cervical cancer patients of different ages, pathological types, maximum tumor diameters, depths of myometrial invasion, vascular invasion and nerve invasion (P&gt;0.05). Serum ITF, IBA-1, and Calgranulin B levels in the nonsurviving group were substantially higher than those in the surviving group at the 1-year follow-up (P&lt;0.05). [Conclusion] The levels of serum ITF, IBA-1 and Calgranulin B have high clinical value in the diagnosis and prognostic evaluation of cervical cancer. The combined detection of these three indicators is helpful for improving the auxiliary diagnostic efficacy of cervical cancer.

Early and rapid diagnosis of non-puerperal mastitis (NPM), as well as elucidation of its specific pathological features, is of important clinical and scientific value. Peripheral blood mononuclear cells (PBMCs), which are key mediators in the inflammatory response, contribute substantially to disease onset, progression, and therapeutic effect, making them promising biomarkers for the early identification and management of inflammatory processes. Nevertheless, novel approaches for the detection and analysis of PBMCs remain urgently needed to facilitate the development of liquid biopsy strategies. In this study, we employed Raman spectroscopy to characterize molecular alterations in PBMCs derived from two distinct groups of NPM patients and healthy controls. Additionally, several machine learning algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), and support vector machine (SVM), were applied to establish diagnostic prediction models for NPM, yielding area under the curve (AUC) values exceeding 0.93. Our findings indicate that PBMC-based liquid biopsy coupled with Raman spectroscopy and machine learning provides novel opportunities for the diagnosis of NPM.

Background: Vancomycin is a core drug for the treatment of methicillin-resistant Staphylococcus aureus , but its neurologic adverse effects are rarely reported. This case is the first to report a possible association between intravenous vancomycin and episodic migraine. Rapid identification of drug-induced migraine can avoid unnecessary invasive testing and medication delays and has direct clinical value. Objective: To report and document a case of episodic migraine that was highly correlated with the timing of intravenous vancomycin administration, assessing causality and its general clinical significance. Methods: This narrative case report is accompanied by an assessment of drug causality and supplemented by a review of pharmacovigilance databases. A systematic search using keywords was conducted. Inclusion criteria included case, cohort, or pharmacovigilance data related to headache/migraine use with glycopeptide drugs. Primary headaches unrelated to the drug were excluded. Case: A 54-year-old woman was admitted to the hospital with traumatic injuries resulting in bilateral lower extremity pain and a 1-hour bleeding episode on the left leg. The injuries included multiple fractures and traumatic injuries, and a postoperative wound infection developed. Results: Based on wound culture results, the patient was treated with intravenous vancomycin. During intravenous vancomycin treatment, the patient developed episodic migraines, and a causal relationship to vancomycin was confirmed using the Naranjo score. After discontinuation of vancomycin, the patient’s episodic migraines gradually resolved. The patient’s episodic migraines resolved completely within 3 days, and the same symptoms did not recur during subsequent treatment. The patient remained headache-free for 3 months after discharge. Conclusion: Pharmacovigilance data indicate that headaches associated with intravenous administration are rare but do occur with glycopeptide drugs. This review suggests that vancomycin may induce episodic migraines, a rare adverse effect that should be included in the differential diagnosis of acute headaches associated with intravenous glycopeptide drugs. Pharmacovigilance combined with therapeutic drug monitoring may serve as a low-cost, reproducible clinical identification tool. This case suggests a possible association between vancomycin and episodic migraines but does not directly prove causation, and further research is needed.

Precision in assessing neurological function after stroke is key to optimizing the efficacy of rehabilitation. Functional near-infrared spectroscopy (fNIRS) provides a highly ecologically valid assessment of cortical activation and functional reorganization after stroke by monitoring cortical hemodynamic changes during different tasks. However, the current fNIRS task paradigm lacks systematic integration for standardized design and clinical translation strategies, and fragmented evidence is difficult to converge into actionable practice guidelines. To fill this gap, this paper systematically reviews the application of fNIRS in motor, cognitive, language, and dual-task paradigms in stroke rehabilitation research. It reveals the clinical value of different paradigms for neurological function assessment and proposes adaptive task designs that fit the functional characteristics of patients with stroke. This study emphasizes the importance of personalized and ecological paradigms, providing a theoretical basis and practical reference for subsequent standardized research on fNIRS task paradigms and developing clinical application standards.