BACKGROUND:Magnetic resonance imaging is the gold standard for the diagnosis of osteonecrosis of femoral head,and previous methods of predicting osteonecrosis of femoral head collapse based on magnetic resonance images mostly require the combined assessment of coronal and sagittal images.However,osteonecrosis of femoral head tends to occur bilaterally,most hospitals perform bilateral hip magnetic resonance imaging scans during clinical examinations,but the bilateral hip scans can only view coronal and cross-sectional images,and it is difficult to obtain sagittal images,which affects the assessment of the risk of collapse.Therefore,it is of clinical value to establish a method to assess the risk of early osteonecrosis of femoral head collapse by applying the images that can be obtained after bilateral hip magnetic resonance scanning. OBJECTIVE:To establish a method of applying coronal and cross-sectional images of bilateral hip magnetic resonance imaging to assess the risk of osteonecrosis of femoral head collapse. METHODS:The medical records of 111 patients(181 hips)with early-stage osteonecrosis of femoral head diagnosed at the outpatient clinic of Honghui Hospital Affiliated to Xi'an Jiaotong University from October 2017 to October 2019 were retrospectively analyzed.They were categorized into collapsed and non-collapsed groups according to the femoral head collapse at the final follow-up,with 69 hips in the collapsed group and 112 hips in the non-collapsed group.The angle of necrotic range on the images of median coronal plane,transverse plane or one level above and below it was measured on the magnetic resonance imaging system.The sum of the two angles of necrotic angle on the coronal and transverse planes was used as the combined necrotic angle.The average of the three combined necrotic angles of each hip was taken to get the average combined necrotic angle of each hip.Finally,the correlation between the three combined necrotic angles and the average combined necrotic angle with the collapse of osteonecrosis of femoral head was analyzed,and the specificity and sensitivity of the four combined necrotic angles in predicting collapse were evaluated by using receiver operating characteristic curves. RESULTS AND CONCLUSION:(1)Totally 69 hips(38.1%)had femoral head collapse at the last follow-up and were included in the collapsed group;112 hips(61.9%)did not have progression of collapse and were included in the non-collapsed group.(2)The difference between the collapsed group and the non-collapsed group in terms of Association Research Circulation Osseous(ARCO)stage was significant(P<0.001).The difference in age,body mass index,follow-up time,gender distribution,side of onset,and causative factors was not significant(P>0.05).(3)The results of independent samples t-test suggested that all four combined necrotic angles were significantly correlated with collapse(P<0.000 1);and the differences in combined necrotic angles between the collapsed group and the non-collapsed group of ARCO stage I and the two groups of ARCO stage II were all significant(P<0.000 1).(4)In the analysis of the receiver operating characteristic,the area under the curve of the average combined necrotic angle was greater than that of the combined necrotic angle on the lower level of the median,the middle level,and the upper level of the median.(5)The average combined necrotic angle had a higher accuracy in the prediction of collapse than the lower level of the median,the middle level,and the upper level of the combined necrotic angle.(6)It is concluded that the accuracy of the average combined necrotic angle in predicting the risk of osteonecrosis of femoral head collapse is higher,and the clinical practicability is stronger,so we can consider using this method to predict the risk of osteonecrosis of femoral head collapse.

Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.

OBJECTIVES: To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software. RESULTS: Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05). CONCLUSIONS PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans ; Attention Deficit Disorder with Hyperactivity/genetics* ; Child ; Male ; Female ; Cross-Sectional Studies ; Neuropsychological Tests ; Multifactorial Inheritance ; Adolescent ; Mental Disorders/etiology* ; Executive Function ; Genetic Risk Score

OBJECTIVE: To explore the effect of acupuncture therapy on dysphagia in patients with Parkinson's disease. METHODS: This randomized controlled study lasted 42 days and included 112 patients with Parkinson's disease and dysphagia. Participants were randomly assigned to the experimental and control groups (56 cases each group) using the completely randomized design, all under routine treatment. The experimental group was given acupuncture therapy. The primary outcome was Penetration-Aspiration Scale (PAS). The secondary outcomes were (1) Standardized Swallowing Assessment (SSA), and (2) nutritional status including body mass index (BMI), serum albumin, prealbumin, and hemoglobin. Adverse events were recorded as safety indicators. RESULTS: One participant quitted the study midway. There were no significant differences in baseline assessment (P>0.05). After treatment, both groups showed significant improvement in PAS, SSA and nutritional status except for BMI of the control group. There were significant differences between the two groups in the PAS for both paste and liquid, SSA (25.18±8.25 vs. 20.84±6.92), BMI (19.97±3.34 kg/m²vs. 21.26 ±2.38 kg/m²), serum albumin (35.16 ±5.29 g/L vs. 37.24 ±3.98 g/L), prealbumin (248.33 ±27.72 mg/L vs. 261.39 ±22.10 mg/L), hemoglobin (119.09±12.53 g/L vs. 126.67±13.97 g/L) (P<0.05). There were no severe adverse events during the study. CONCLUSION: The combination of routine treatment and acupuncture therapy can better improve dysphagia and nutritional status in patients with Parkinson's disease, than routine treatment solely. (registration No. CLINICALTRIAL gov NCT06199323).
Humans ; Parkinson Disease/therapy* ; Deglutition Disorders/physiopathology* ; Acupuncture Therapy/adverse effects* ; Male ; Female ; Aged ; Middle Aged ; Treatment Outcome ; Nutritional Status ; Body Mass Index

Hypertrophic scar is a fibrous hyperplastic disorder that arises from skin injuries. The current therapeutic modalities are constrained by the dense and rigid scar tissue which impedes effective drug delivery. Additionally, insufficient autophagic activity in fibroblasts hinders their apoptosis, leading to excessive matrix deposition. Here, we developed an active microneedle (MN) system to overcome these challenges by integrating micromotor-driven drug delivery with autophagy regulation to remodel the scar microenvironment. Specifically, sodium bicarbonate and citric acid were introduced into the MNs as a built-in engine to generate CO₂ bubbles, thereby enabling enhanced lateral and vertical drug diffusion into dense scar tissue. The system concurrently encapsulated curcumin (Cur), an autophagy activator, and triamcinolone acetonide (TA), synergistically inducing fibroblast apoptosis by upregulating autophagic activity. In vitro studies demonstrated that active MNs achieved efficient drug penetration within isolated scar tissue. The rabbit hypertrophic scar model revealed that TA-Cur MNs significantly reduced the scar elevation index, suppressed collagen I and transforming growth factor-β1 (TGF-β1) expression, and elevated LC3 protein levels. These findings highlight the potential of the active MN system as an efficacious platform for autonomous augmented drug delivery and autophagy-targeted therapy in fibrotic disorder treatments.

Pyroptosis is an identified programmed cell death that has been highly linked to endoplasmic reticulum (ER) dynamics. However, the crucial proteins for modulating dynamic ER membrane curvature change that trigger pyroptosis are currently not well understood. In this study, a biotin-labeled chemical probe of potent pyroptosis inducer α-mangostin (α-MG) was synthesized. Through protein microarray analysis, reticulon-4 (RTN4/Nogo), a crucial regulator of ER membrane curvature, was identified as a target of α-MG. We observed that chemically induced proteasome degradation of RTN4 by α-MG through recruiting E3 ligase UBR5 significantly enhances the pyroptosis phenotype in cancer cells. Interestingly, the downregulation of RTN4 expression significantly facilitated a dynamic remodeling of ER membrane curvature through a transition from tubules to sheets, consequently leading to rapid fusion of the ER with the cell plasma membrane. In particular, the ER-to-plasma membrane fusion process is supported by the observed translocation of several crucial ER markers to the "bubble" structures of pyroptotic cells. Furthermore, α-MG-induced RTN4 knockdown leads to pyruvate kinase M2 (PKM2)-dependent conventional caspase-3/gasdermin E (GSDME) cleavages for pyroptosis progression. In vivo, we observed that chemical or genetic RTN4 knockdown significantly inhibited cancer cells growth, which further exhibited an antitumor immune response with anti-programmed death-1 (anti-PD-1). In translational research, RTN4 high expression was closely correlated with the tumor metastasis and death of patients. Taken together, RTN4 plays a fundamental role in inducing pyroptosis through the modulation of ER membrane curvature remodeling, thus representing a prospective druggable target for anticancer immunotherapy.
Pyroptosis/immunology* ; Humans ; Endoplasmic Reticulum/immunology* ; Animals ; Nogo Proteins/antagonists & inhibitors* ; Mice ; Cell Line, Tumor ; Xanthones/pharmacology* ; Neoplasms/pathology* ; Mice, Nude

The Healthy China 2030 Plan set the goal of reducing premature deaths from diabetes by 30% by 2030. However, there has been a lack of assessment of premature mortality for diabetes since the action plan was issued. This study used data from the Global Burden of Disease Study 2021, calculated the premature deaths for diabetes by sex, provinces, and subtypes from 1990 to 2021. We explored the temporal trend of premature mortality using the average annual percent change (AAPC) for different sexes, provinces, and subtypes from 1990 to 2021. Furthermore, we predicted premature mortality for diabetes through 2030 for China and its provinces according to the average annual change rate from 2010 to 2021. There was a first slow upward trend in premature mortality for diabetes from 0.5% in 1990 to 0.6% in 2004, and then a decline until 2021 with premature mortality of 0.4%. By 2030, only Fujian (30.3%) will achieve the desired level of reduction, with only seven provinces meeting the target for females and none for males. There is a large range in the degree of decline between inland and coastal regions, showing obvious geographic differences, and there should be a focus on balancing medical resources.
Humans ; China/epidemiology* ; Female ; Male ; Mortality, Premature/trends* ; Diabetes Mellitus/mortality* ; Goals ; Middle Aged ; Adult

Objective To understand the incidence and characteristics of adverse drug reactions(ADRs)of carbapenems,explore the relevant risk signals,and provide a reference for clinically safe drug use.Methods All spontaneous reports of carbapenem drug-related ADRs from January 2008 to October 2022 in the Adverse Drug Reaction Monitoring Center,PLA General Hospital's ADR database were retrieved,and information such as patients'general conditions,involved systems and organs damage,and the names of ADRs involved were retrospectively analysed.Using the reporting odd ratio method,the proportional reporting ratio method,the Medicines and Healthcare Products Regulatory Agency method,and information component method to obtain risk signals of carbapenem antimicrobial drug-related ADR.Results A total of 2 642 ADR reports of carbapenems were reported,of which 410 serious ADR reports(15.52％)were serious ADR reports,five cabapenem antimirobial drug species were mainly involved.In descending order of composition were imipenem cilastatin(51.28％),meropenem(32.13％),biapenem(8.10％),ertapenem(7.68％),and panipenem(0.79％).The male to female ratio of patients was 1.74:1,with the most age＞60 years(59.69％).A total of 14"drug-ADR name"combinations generated risk signals in all four data mining methods,with meropenem being the most signals,and imipenem cilastatin and ertapenem had a high number of reported ADR in nervous system.Conclusion The results of risk signal mining are basically consistent with the known carbapenem ADR information,during the use of carbapenem antimicrobial drugs in the clinic,it is recommended to monitor patients'liver and kidney functions as well as blood biochemical indexes,so as to strengthen the awareness of vigilance in the clinical use of carbapenem antimicrobial drugs,and timely recognize and deal with ADRs in a timely manner,and to avoid the occurrence of serious ADRs.

Objective To construct a module for drug-induced central nervous system adverse reactions(CNS-ADR)within the Clinical Adverse Drug Event Active Monitoring and Intelligent Assessment Alert System-Ⅱ(ADE-ASAS-Ⅱ),and to conduct a large-scale,real-world active monitoring and evaluation of CNS-ADR specifically related to imipenem/cilastatin.Methods Based on literature review,spontaneous report evaluation,and initial word set of CNS-ADR related descriptions in electronic medical records,text recognition technology was used to construct and optimize the condition settings of the CNS-ADR automatic monitoring module.Hospitalized patients using imipenem/cilastatin were retrospectively monitored from 2017 to 2021,and the positive patients which had CNS-ADR were statistically described in terms of the demographic characteristics,CNS symptoms,and hospital departments.Results Based on a repeated testing optimization using 1 185 manually monitored results,the best setting for the determined module includes 62 sets of keywords,with a positive predictive value(PPV)of 13.63％and a recall rate of 100％.Expanding the monitoring to 8 222 medication users using this module,281 cases of positive causality were identified,with an incidence rate of 3.42％.Among them,patients over 60 years old accounted for 50.17％,and the main manifestations of CNS-ADR were epileptic seizures,headaches,mania,and delirium.Conclusion The CNS-ADR automatic monitoring module established based on ADE-ASAS-Ⅱ provides fast and reliable text data mining support for conducting real-world research on CNS-ADR.