The geometric median, which is applicable to high-dimensional data, can be viewed as a generalization of the univariate median used in 1-dimensional data. It can be used as a robust estimator for identifying the location of multi-dimensional data and has a wide range of applications in real-world scenarios. This paper explores the problem of high-dimensional multivariate analysis of variance (MANOVA) using the geometric median. A maximum-type statistic that relies on the differences between the geometric medians among various groups is introduced. The distribution of the new test statistic is derived under the null hypothesis using Gaussian approximations, and its consistency under the alternative hypothesis is established. To approximate the distribution of the new statistic in high dimensions, a wild bootstrap algorithm is proposed and theoretically justified. Through simulation studies conducted across a variety of dimensions, sample sizes, and data-generating models, we demonstrate the finite-sample performance of our geometric median-based MANOVA method. Additionally, we implement the proposed approach to analyze a breast cancer gene expression dataset.

UNASSIGNED: Fasting blood glucose (FBG) is a recognized risk factor for Ischemic Stroke, but little research has examined the interaction among FBG, Platelet Distribution Width (PDW) and the severity of neuronal damage. Thus, the present study constructs a moderated mediation model aimed to elucidate the relationships among FBG, PDW, and NIHSS scores in patients with acute ischemic stroke (AIS).
UNASSIGNED: We conducted a cross-sectional study on 431 AIS patients. Upon hospital admission, we assessed the patients\' NIHSS scores and collected blood samples to measure FBG and PDW levels. The relationship between FBG and NIHSS scores moderated by PDW was analyzed by linear curve fitting analysis, multiple linear regression analysis, and moderated mediation analysis respectively.
UNASSIGNED: In the tertile grouping based on FBG, both PDW and NIHSS scores of AIS patients demonstrated an increase corresponding with rising levels of FBG (p<0.001 for both). Multiple linear regression analysis revealed that, the β coefficients (95% CI) for the relationship between FBG and NIHSS scores were 1.49 (1.27-1.71, p<0.01) post-adjustment for potential confounders. The β coefficients (95% CI) for the relationship between FBG and PDW were 0.02 (0.01-0.04, p<0.01) post-adjustment. Likewise, for the relationship between PDW and NIHSS scores, the β coefficients (95% CI) were 4.33 (3.07-5.59, p<0.01) after adjustment. These positive association remained consistent in sensitivity analysis and hierarchical analysis. Smoothed plots suggested that there are linear relationships between FBG and PDW and NIHSS scores respectively. Further mediation analysis indicated that increased PDW significantly (p<0.01) mediated 5.91% of FBG-associated increased NIHSS scores.
UNASSIGNED: This study suggested that FBG levels were associated with NIHSS scores, and the FBG-associated neurological impairment may be partially mediated by PDW. These findings underscore the importance of monitoring FBG and PDW levels in AIS patients, potentially guiding risk intervention strategies.

In this paper, we introduce an innovative multivariable data fusion strategy for adaptive steady-state detection, specifically tailored for the alumina evaporation process. This approach is designed to counteract the production instabilities that often arise from frequent alterations in production conditions. At the core of our strategy is the application of an adaptive denoising algorithm based on the Gaussian filter, which adeptly eliminates erroneous data from selected variables without compromising the fidelity of the original signal. Subsequently, we implement a multivariable R-test methodology, integrated with the adaptive Gaussian filter, to conduct a thorough and precise steady-state detection via data fusion. The efficiency of this method is rigorously validated using actual data from industrial processes.Our findings reveal that this strategy markedly enhances the stability and efficiency (by 10%) of the alumina evaporation process, thereby offering a substantial contribution to the field. Moreover, the versatility of this approach suggests its potential applicability in a wide range of industrial settings, where similar production challenges prevail. This study not only advances the domain of process control but also underscores the significance of adaptive strategies in managing complex, variable-driven industrial operations.

Early childhood marks a pivotal period in the maturation of executive function, the cognitive ability to consciously regulate actions and thoughts. Mindfulness-based interventions have shown promise in bolstering executive function in children. This study used the functional near-infrared spectroscopy technique to explore the impact of mindfulness-based training on young children. Brain imaging data were collected from 68 children (41 boys, aged 61.8 ± 10.7 months) who were randomly assigned to either an intervention group (N = 37, aged 60.03 ± 11.14 months) or a control group (N = 31, aged 59.99 ± 10.89 months). Multivariate and multiscale sample entropy analyses were used. The results showed that: (1) brain complexity was reduced in the intervention group after receiving the mindfulness-based intervention in all three executive function tasks (ps < 0.05), indicating a more efficient neural processing mechanism after the intervention; (2) difference comparisons between the intervention and control groups showed significant differences in relevant brain regions during cognitive shifting (left dorsolateral prefrontal cortex and medial prefrontal cortex) and working memory tasks (left dorsolateral prefrontal cortex), which corroborates with improved behavioral results in the intervention group (Z = -3.674, P < 0.001 for cognitive shifting; Z = 2.594, P < 0.01 for working memory). These findings improve our understanding of early brain development in young children and highlight the neural mechanisms by which mindfulness-based interventions affect executive function. Implications for early intervention to promote young children\'s brain development are also addressed.

This study comprehensively investigated the effects of high-temperature cooking (HT), complex enzyme hydrolysis (CE), and high-temperature cooking combined enzymatic hydrolysis (HE) on the chemical composition, microstructure, and functional attributes of soluble dietary fiber (SDF) extracted from corn bran. The results demonstrated that HE-SDF yielded the highest output at 13.80 ± 0.20 g/100 g, with enhancements in thermal stability, viscosity, hydration properties, adsorption capacity, and antioxidant activity. Cluster analysis revealed three distinct categories of SDF\'s physicochemical properties. Principal component analysis (PCA) confirmed the superior functional properties of HE-SDF. Correlation analysis showed positive relationships between the monosaccharide composition, purity, and viscosity of SDF and most of its functional attributes, whereas particle size and zeta potential were inversely correlated. Furthermore, a highly significant positive correlation was observed between crystallinity and thermal properties. These findings suggest that the HE method constitutes a viable strategy for enhancing the quality of SDF sourced from corn bran.

Objective: To understand the occupational stress and mental health status of hospital infection prevention and control practitioner (HIPCPs) in medical institutions, and analyze their main influencing factors. Methods: In November 2021, 550 nosocomial infection managers in Tianjin were randomly selected to conduct a questionnaire survey using the Concise Occupational Stress Questionnaire, Depression Screening Scale (PHQ-9) and Self-Rating Anxiety Scale (SAS). 497 valid questionnaires were obtained, and the total recovery efficiency was 90.36%. Single factor analysis and multivariate logistic regression method were used to analyze the main influencing factors of occupational stress and mental health status of psychiatric managers. Results: The detection rate of anxiety and depression among 497 HIPCPs was 22.73% (113/497) and 58.95% (293/497), respectively. Gender and major were the influencing factors of depression (P=0.000, 0.001). Average working hours>52 hours per week and night shift days>1 days per week were the influencing factors of anxiety (P=0.035, 0.014). Average working hours>52 h per week, night shift days >1 d per week and different majors were the influencing factors of occupational stress (P=0.000, 0.025, 0.010). Multivariate logistic regression results showed that the risk of anxiety in those who worked more than 52 hours per week was 1.753 times that of those who worked less than 52 hours per week (P=0.038), and the risk of depression in women was 3.071 times that of men (P=0.006) . Conclusion: Working hours are an important influencing factor for occupational stress and anxiety among HIPCPs. In order to reduce the occurrence of occupational stress and mental health problems, it is necessary to strengthen psychological counseling for HIPCPs and balance work and rest.
目的： 了解医疗机构医院感染管理人员的职业应激和心理健康状况，并分析其主要影响因素。 方法： 于2021年11月，随机选择天津市550名医院感染管理人员，使用《简明职业紧张问卷》《抑郁筛查量表》（PHQ-9）和《焦虑自评量表》（SAS）开展问卷调查。回收有效问卷497份，总回收有效率为90.36%。使用单因素分析和多因素非条件logistic回归方法分析院感管理人员职业应激和焦虑及抑郁的主要影响因素。 结果： 497名医院感染管理人员焦虑和抑郁检出率分别为22.73%（113/497）和58.95%（293/497）。性别、不同专业是抑郁的影响因素（P=0.000、0.001）；平均每周工作时长>52 h和每周夜班天数>1 d是焦虑的影响因素（P=0.035、0.014）；平均每周工作时长>52 h、每周夜班天数>1 d、不同专业是职业应激的影响因素（P=0.000、0.025、0.010）。多因素logistic回归结果显示，平均每周工作时长>52 h者发生焦虑的风险是平均每周工作时长≤52 h者的1.753倍（P=0.038），女性发生抑郁的风险是男性的3.071倍（P=0.006）。 结论： 工作时长是医院感染管理人员产生职业应激和焦虑的重要影响因素，应加强对医院感染管理人员的心理疏导，注意劳逸结合，以减少职业应激和心理健康问题的发生。.

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OBJECTIVE: To establish a model to predict the overall survival (OS) rate of patients with diffuse large B-cell lymphoma (DLBCL) based on systemic inflammatory indicators, and study whether the new model combined with inflammatory related parameters is more effective than the conventional model using only clinical factors to predict the OS of patients with DLBCL.
METHODS: The clinical data of 213 patients with DLBCL were analyzed retrospectively. Backward stepwise Cox regression analysis was used to screen independent prognostic factors related to OS, and a nomogram for predicting OS was constructed based on these factors. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to evaluate the fitting of the model, the consistency index (C-index), area under receiver operating characteristic (ROC) curve (AUC) and calibration curve were used to evaluate the prediction accuracy of nomogram, and decision curve analysis (DCA) and Kaplan Meier curve were used to evaluate the clinical practicability of nomogram.
RESULTS: Multivariate analysis confirmed that age, ECOG PS score, serum lactate dehydrogenase (LDH) level, systemic immune inflammatory index (SII), and prognostic nutritional index (PNI) were used to construct the nomogram. The AIC and BIC of the nomogram were lower than the International Prognostic Index (IPI) and the National Comprehensive Cancer Network (NCCN)-IPI, indicating that the nomogram had better goodness of fit. The C-index and AUC of the nomogram were higher than IPI and NCCN-IPI, indicating that the prediction accuracy of the nomogram had been significantly improved, and the calibration curve showed that the prediction results were in good agreement with the actual survival results. DCA showed that the nomogram had better clinical net income. Kaplan Meier curve showed that patients could be well divided into low-risk, medium-risk and high-risk groups according to the nomogram score (P < 0.001).
CONCLUSIONS: The nomogram combined with inflammatory indicators can accurately predict the individual survival probability of DLBCL patients.
UNASSIGNED: 系统性炎症指标可以改善弥漫大B细胞淋巴瘤患者的生存预测：模型的开发和评价.
UNASSIGNED: 基于全身炎症指标建立一个用于预测弥漫大B细胞淋巴瘤(DLBCL)患者总生存(OS)率的模型，并研究结合炎症相关参数的新模型是否比仅使用临床因素的常规模型能更有效地预测DLBCL患者的OS。.
UNASSIGNED: 回顾性分析了213例DLBCL患者的临床数据，向后逐步Cox回归分析筛选与OS相关的独立预后因素，基于这些因素构建预测OS的列线图。使用Akaike信息准则(AIC)和Bayesian信息准则(BIC)评估模型的拟合情况，一致性指数、受试者工作特征曲线下面积(AUC)和校准曲线评估列线图的预测准确性，使用决策曲线分析和Kaplan-Meier曲线评估列线图的临床实用性。.
UNASSIGNED: 多变量分析确定年龄、美国东部合作组体能状态评分、血清乳酸脱氢酶水平、全身免疫炎症指数、预后营养指数用于构建列线图。列线图的AIC和BIC低于国际预后指数(IPI)和美国国家综合癌症网络(NCCN)-IPI，表明列线图具有更好的拟合优度。列线图的一致性指数和AUC高于IPI和NCCN-IPI，表明列线图的预测准确性明显改善，校准曲线显示出预测结果和实际生存结果具有良好的一致性。决策曲线分析显示列线图具有更好的临床净收益。Kaplan-Meier曲线显示，根据列线图评分可以很好地将患者分为低危、中危、高危三个风险组(P < 0.001)。.
UNASSIGNED: 结合炎症指标的列线图可以准确地预测DLBCL患者个体化的生存概率。.

BACKGROUND: Alactic base excess (ABE) is a novel biomarker to evaluate the renal capability of handling acid-base disturbances, which has been found to be associated with adverse prognosis of sepsis and shock patients. This study aimed to evaluate the association between ABE and the risk of in-hospital mortality in patients with acute myocardial infarction (AMI).
METHODS: This retrospective cohort study collected AMI patients\' clinical data from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The outcome was in-hospital mortality after intensive care unit (ICU) admission. Univariate and multivariate Cox proportional hazards models were performed to assess the association of ABE with in-hospital mortality in AMI patients, with hazard ratios (HRs) and 95% confidence intervals (CI). To further explore the association, subgroup analyses were performed based on age, AKI, eGFR, sepsis, and AMI subtypes.
RESULTS: Of the total 2779 AMI patients, 502 died in hospital. Negative ABE (HR = 1.26, 95%CI: 1.02-1.56) (neutral ABE as reference) was associated with a higher risk of in-hospital mortality in AMI patients, but not in positive ABE (P = 0.378). Subgroup analyses showed that negative ABE was significantly associated with a higher risk of in-hospital mortality in AMI patients aged>65 years (HR = 1.46, 95%CI: 1.13-1.89), with eGFR<60 (HR = 1.35, 95%CI: 1.05-1.74), with AKI (HR = 1.32, 95%CI: 1.06-1.64), with ST-segment elevation acute myocardial infarction (STEMI) subtype (HR = 1.79, 95%CI: 1.18-2.72), and without sepsis (HR = 1.29, 95%CI: 1.01-1.64).
CONCLUSIONS: Negative ABE was significantly associated with in-hospital mortality in patients with AMI.

BACKGROUND: Patients in the intensive care unit (ICU) are highly susceptible to malnutrition, and while enteral nutrition via nasogastric tube is the preferred method, there is a risk of inadvertent reflux and aspiration. Therefore, clinicians have turned to nasointestinal tubes (NET) for enteral nutrition as an alternative option. But the precise localization of NET presents an ongoing challenge. We proposed an innovative approach to provide a valuable reference for clinicians involved in NET placement.
METHODS: Data were obtained retrospectively from the medical records of adult patients with a high risk of aspiration or gastric feeding intolerance who had a NET placed in the ICU of Zhejiang Provincial People\'s Hospital between October 1, 2017, and October 1, 2023. The collected data were subjected to statistical analysis using SPSS and R software.
RESULTS: There were 494 patients who met the inclusion and exclusion criteria. The first-pass success rate was 81.4% (n = 402). The success of a patient\'s initial NET placement was found to be associated with Angle SPC and Distance CP, as determined by univariate analysis (25.6 ± 16.7° vs. 41.9 ± 18.0°, P < 0.001; 40.0 ± 26.2 mm vs. 62.0 ± 31.8 mm, P < 0.001, respectively). By conducting a multivariate regression analysis, we identified a significant association between pyloric types and the success rate of placing NET (OR 29.559, 95%CI 14.084-62.038, P < 0.001).
CONCLUSIONS: Angle SPC, Distance CP, and the type of pylorus are independently associated with successful initial placement of NET. Besides, patients with the outside type of pylorus (OP-type) exhibit a higher rate of initial placement success.