Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Objective: Miniscrews are commonly utilized as temporary anchorage devices (TADs) in cases of maxillary protrusion and premolar extraction. This study aimed to investigate the effects and potential side effects of two conventional miniscrew configurations on the maxillary incisors. Methods: Eighty-two adult patients with maxillary dentoalveolar protrusion who had undergone bilateral first premolar extraction were retrospectively divided into three groups: non-TAD, two posterior miniscrews only (P-TADs), and two anterior and two posterior miniscrews combined (AP-TADs). Cone-beam computed tomography was used to evaluate the maxillary central incisors (U1). Results: The APTADs group had significantly greater U1 intrusion (1.99 ± 2.37 mm, n = 50) and less retroclination (1.70° ± 8.80°) compared to the P-TADs (–0.07 ± 1.65 mm and 9.45° ± 10.68°, n = 60) and non-TAD group (0.30 ± 1.61 mm and 1.91° ± 9.39°, n = 54).However, the AP-TADs group suffered from significantly greater apical root resorption (ARR) of U1 (2.69 ± 1.38 mm) than the P-TADs (1.63 ± 1.46 mm) and non-TAD group (0.89 ± 0.97 mm). Notably, the incidence of grade IV ARR was 16.6% in the AP-TADs group, significantly higher than the rates observed in the P-TADs (6.7%) and non-TAD (1.9%) groups. Multiple regression analysis revealed that after excluding tooth movement factors, the AP-TADs configuration resulted in an additional 0.5 mm of ARR compared with the P-TADs group. Conclusions In cases of maxillary protrusion and premolar extraction, the use of combined anterior and posterior miniscrews enhances incisor intrusion and minimizes torque loss of the maxillary incisors. However, this approach results in more severe ARR, likely due to the increased apical movement and composite force exerted.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To investigate the effect of triglyceride-glucose index(TyG)on the short-term prognosis of patients with initial acute ischemic stroke.Methods A total of 391 patients with initial acute ischemic stroke who were hospitalized in Kunshan Second People's Hospital and The Affiliated Suzhou Hospital of Nanjing Medical University from Jun.2020 to Jun.2023 were retrospectively included.According to the modified Rankin scale(mRS)scores at 90 d follow-up,they were assigned to good prognosis group(286 cases)or poor prognosis group(105 cases).Logistic regression and receiver operating characteristic(ROC)curve were used to evaluate the effect of TyG on the short-term prognosis of patients with initial acute ischemic stroke.Results Compared with the good prognosis group,the patients of poor prognosis group had older age,higher proportion of atrial fibrillation,higher levels of homocysteine,triglyceride,total cholesterol,low-density lipoprotein,and TyG,and higher National Institutes of Health stroke scale(NIHSS)score(all P＜0.05).Multivariate logistic regression analysis showed that age,homocysteine,TyG and NIHSS score were independent risk factors for poor prognosis in patients with initial acute ischemic stroke(all P＜0.05).ROC curve analysis showed that TyG combined with NIHSS score had good predictive value for poor prognosis of patients with initial acute ischemic stroke,and the area under curve value was 0.795.Conclusion The combination of TyG and NIHSS score is an independent influencing factor for poor short-term prognosis in patients with initial acute ischemic stroke.

Monoamine neurotransmitters mainly include serotonin,dopamine,epinephrine,and norepinephrine.They play an indispensable regulatory role in key physiological activities such as emotion,sleep,and memory within the central nervous system.Precise detection of these neurotransmitters holds great significance in the field of neuroscience research.Detection methods for monoamine neurotransmitters encompass high-performance liquid chromatography,mass spectrometry,capillary electrophoresis,fluorescence spectroscopy,and electrochemical methods,etc.Compared with other methods,electrochemical methods offer advantages such as high sensitivity,good selectivity,low cost,strong portability,convenient operation,and capability for in vivo real-time detection.This article reviewed recent research progress in electrochemical detection of monoamine neurotransmitters,focusing on a retrospective and summary from three aspects:sensor electrode materials,detection of various monoamine neurotransmitters,and in vivo real-time analysis.Furthermore,the future development of electrochemical sensors for monoamine neurotransmitters was prospected.

BACKGROUND: The purpose of this study was to evaluate the safety and efficacy of subsequent radiotherapy (RT) following first-line treatment with durvalumab plus chemotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC). METHODS: A total of 122 patients with ES-SCLC from three hospitals during July 2019 to December 2021 were retrospectively analyzed. Inverse probability of treatment weighting (IPTW) analysis was performed to address potential confounding factors. The primary focus of our evaluation was to assess the impact of RT on progression-free survival (PFS) and overall survival (OS). RESULTS: After IPTW analysis, 49 patients received durvalumab plus platinum-etoposide (EP) chemotherapy followed by RT (Durva + EP + RT) and 72 patients received immunochemotherapy (Durva + EP). The median OS was 17.2 months vs . 12.3 months (hazard ratio [HR]: 0.38, 95% confidence interval [CI]: 0.17-0.85, P = 0.020), and the median PFS was 8.9 months vs . 5.9 months (HR: 0.56, 95% CI: 0.32-0.97, P = 0.030) in Durva + EP + RT and Durva + EP groups, respectively. Thoracic radiation therapy (TRT) resulted in longer OS (17.2 months vs . 14.7 months) and PFS (9.1 months vs . 7.2 months) compared to RT directed to other metastatic sites. Among patients with oligo-metastasis, RT also showed significant benefits, with a median OS of 17.4 months vs . 13.7 months and median PFS of 9.8 months vs . 5.9 months compared to no RT. Continuous durvalumab treatment beyond progression (TBP) prolonged OS compared to patients without TBP, in both the Durva + EP + RT (NA vs . 15.8 months, HR: 0.48, 95% CI: 0.14-1.63, P = 0.238) and Durva + EP groups (12.3 months vs . 4.3 months, HR: 0.29, 95% CI: 0.10-0.81, P = 0.018). Grade 3 or 4 adverse events occurred in 13 (26.5%) and 13 (18.1%) patients, respectively, in the two groups; pneumonitis was mostly low-grade. CONCLUSION Addition of RT after first-line immunochemotherapy significantly improved survival outcomes with manageable toxicity in ES-SCLC.
Humans ; Small Cell Lung Carcinoma/therapy* ; Retrospective Studies ; Male ; Female ; Middle Aged ; Lung Neoplasms/therapy* ; Aged ; Antibodies, Monoclonal/therapeutic use* ; Adult ; Immunotherapy/methods* ; Aged, 80 and over

BACKGROUND: Chronic kidney disease (CKD)-associated anemia (CKD-anemia) is associated with poor survival, and hemoglobin targets are often not achieved with current therapies. Phase 3 trials have demonstrated the treatment efficacy of roxadustat for CKD-anemia. This phase 4 study aims to evaluate the long-term (52-week) safety and effectiveness of roxadustat in a broad real-world patient population with CKD-anemia with and without dialysis in China. METHODS: This Phase 4 multicenter, open-label, prospective study, conducted from 24 November 2020 to 11 November 2022, evaluated the long-term safety and effectiveness of roxadustat for CKD-anemia in China. Patients aged ≥18 years with CKD-anemia with or without dialysis were included. The initial oral dose was 70-120 mg (weight-based followed by dose adjustment) over 52 weeks. The primary endpoint was safety based on adverse events (AEs). The secondary endpoints were hemoglobin changes from baseline and the proportion of patients who achieved mean hemoglobin ≥100 g/L. Effectiveness evaluable populations 1 (EE1) and EE2 included roxadustat-naïve and previously roxadustat-treated patients, respectively. The safety analysis set (SAF) included all patients who received ≥1 occasion. RESULTS: The EE1, EE2, and SAF populations included 1804, 193, and 2021 patients, respectively. In the SAF, the mean age was 50 ± 14 years, and 1087 patients (53.8%) were male. Mean baseline hemoglobin was 96.9 ± 14.0 g/L in EE1 and 100.3 ± 12.9 g/L in EE2. In EE1, the mean (95% confidence interval) hemoglobin changes from baseline over weeks 24-36 and 36-52 were 14.2 (13.5-14.9) g/L and 14.3 (13.5-15.0) g/L, respectively. Over weeks 24-36 and 36-52, 83.3% and 86.1% of patients in EE1 and 82.7% and 84.7% in EE2 achieved mean hemoglobin ≥100 g/L, respectively. In the SAF, 1643 (81.3%) patients experienced treatment-emergent AEs (TEAEs). Overall, 219 (10.8%) patients experienced drug-related TEAEs. Thirty-eight (1.9%) patients died of TEAEs (unrelated to the study drug). Vascular access thrombosis was uncommon. CONCLUSIONS: Roxadustat (52 weeks) increased hemoglobin and maintained the treatment target in Chinese patients with CKD-anemia with acceptable safety, supporting its use in real-world settings. REGISTRATION Chinese Clinical Trial Registry ( www.chictr.org.cn ) ChiCTR2100046322; CDE ( www.chinadrugtrials.org.cn ) CTR20201568.
Humans ; Male ; Female ; Anemia/etiology* ; Middle Aged ; Renal Insufficiency, Chronic/complications* ; Glycine/adverse effects* ; Isoquinolines/adverse effects* ; Aged ; Prospective Studies ; Adult ; Hemoglobins/metabolism* ; Treatment Outcome ; China ; Registries ; East Asian People

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs