Acute lung injury(ALI) is a critical clinical condition primarily characterized by refractory hypoxemia and infiltration of inflammatory cells in lung tissue, which can progress into a more severe form known as acute respiratory distress syndrome(ARDS). Immune cells and inflammatory cytokines play important roles in the progression of the disease. Due to its unclear pathogenesis and the lack of effective clinical treatments, ALI is associated with a high mortality rate and severely affects patients' quality of life, making the search for effective therapeutic agents particularly urgent. Ginseng Radix et Rhizoma, the dried root of the perennial herb Panax ginseng from the Araliaceae family, contains active ingredients such as saponins and polysaccharides, which possess various pharmacological effects including anti-tumor activity, immune regulation, and metabolic modulation. In recent years, studies have shown that ginsenosides exhibit notable effects in reducing inflammation, ameliorating epithelial and endothelial cell injury, and providing anticoagulant action, indicating their comprehensive role in alleviating lung injury. This review summarizes the pathogenesis of ALI and the molecular mechanisms through which ginsenosides act at different stages of ALI development. The aim is to provide a scientific reference for the development of ginsenoside-based drugs targeting ALI, as well as a theoretical basis for the clinical application of Ginseng Radix et Rhizoma in the treatment of ALI.
Ginsenosides/pharmacology* ; Humans ; Acute Lung Injury/immunology* ; Animals ; Panax/chemistry* ; Drugs, Chinese Herbal

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, overshadowing its influence on the biological effects of formulations. In this study, we reevaluated the delivery effect of CH using widely applied lipid microspheres (LM) as a model DDS. We conducted comprehensive investigations into the impact of CH on the distribution, cell uptake, and protein corona (PC) of LM at sites of cardiovascular inflammatory injury. The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage. Then, the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy. Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma (PPAR-γ) expression in vascular endothelial cells and estrogen receptor alpha (ERα) protein levels in myocardial cells, thereby enhancing LM uptake at cardiovascular inflammation sites. Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with CH metabolism-related apolipoprotein family members such as apolipoprotein A-V (Apoa5); this may be a major contributing factor to their prolonged circulation in vivo and explains why CH enhances the distribution of LM at cardiovascular inflammatory injury sites. It should be noted that changes in cell types and physiological environments can also influence the biological behavior of formulations. The findings enhance the conceptualization of CH and LM delivery, providing novel strategies for investigating prescription factors' bioactivity.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

OBJECTIVE: To compare the clinical efficacy and complication rates of staged open reduction internal fixation (ORIF) and external fixation combined with limited internal fixation (EFLIF) in the treatment of high-energy Pilon fractures. METHODS: A retrospective selection was conducted on 78 patients diagnosed with high-energy tibial Pilon fractures who received treatment between January 2021 and October 2023. These patients were categorized into the staged ORIF group and the EFLIF group according to their respective treatment protocols. The staged ORIF group comprised 48 patients, including 29 males and 19 females, aged from 33 to 53 years old with a mean age of (43.25±4.67) years old. The time from injury to treatment averaged (6.54±2.21) hours. All patients received staged ORIF treatment. The EFLIF Group consisted of 30 patients, including 18 males and 12 females, aged from 36 to 54 years old with a mean age of (43.37±3.24) years old. The time from injury to treatment averaged (6.87±1.96) hours. All patients received EFLIF treatment. The recovery of ankle joint function, fracture reduction quality, fracture healing time, and surgical-related indicators between two groups were observed and compared six months after surgery. Additionally, the postoperative complications of the two groups were recorded. RESULTS: Both groups of patients were followed up and the duration ranged from 6 to 12 months, with an average of (8.97±1.26) months. At 6-month postoperative follow-up, the American Orthopaedic Foot and Ankle Society (AOFAS) score in the ORIF group was (83.15±20.93), which did not show a statistically significant difference compared to the EFLIF group (81.88±20.67), P>0.05. The excellent and good rate of fracture reduction in the staged ORIF group was 33.33% (16/48), which did not show a statistically significant difference compared to the EFLIF group (30.00%, 9/30), P>0.05. The hospitalization duration and fracture healing time in the staged ORIF group were (16.57±1.25) days and (12.14±1.15) weeks, respectively. When compared to the EFLIF group, which demonstrated a hospitalization duration of (15.97±2.16 ) days and a fracture healing time of (12.36±1.17) weeks, no statistically significant differences were observed (P>0.05). The intraoperative blood loss in the staged ORIF group was (76.54±11.65) ml, which was significantly higher than that in the EFLIF group (70.15±10.29) ml, and the difference was statistically significant (P<0.05). The incidence of superficial tissue infection was 2.08%(1/48), which was significantly lower than that observed in the EFLIF group at 16.67% (5/30), and this difference was statistically significant (P<0.05). CONCLUSION Both staged ORIF and EFLIF were effective treatment options for high-energy closed Pilon fractures of the tibia. However, regarding the prevention of superficial tissue infection, staged ORIF demonstrates superior risk control compared to EFLIF.
Humans ; Male ; Female ; Middle Aged ; Adult ; Tibial Fractures/physiopathology* ; Fracture Fixation, Internal/methods* ; Retrospective Studies ; External Fixators ; Open Fracture Reduction/methods* ; Treatment Outcome

OBJECTIVE: To analyze the gene mutation characteristics and survival time of patients with newly diagnosed acute myeloid leukemia (AML) based on next-generation sequencing(NGS) gene detection. METHODS: A retrospective analysis was conducted on the clinical data of 92 patients with AML (non APL) admitted to our hospital from January 2018 to May 2022. AML related genes tested were using NGS, the mutation characteristics and survival time of AML patients were analyzed. RESULTS: Among the 92 patients, 41 were males and 51 were females. A total of 38 types of gene mutations were detected. Six-two patients carried at least one gere mutation, while no gene mutations were detected in 30 patients. In the group with favourable prognosis (n =14), the frequencies of higher gene mutations were NRAS, KIT (21.43%, n =3), KRAS (14.29%, n =2). In the group with intermediate prognosis (n =64), the gene mutation frequencies from high to low were DNMT3A (18.75%, n =12), NPM1 (17.19%, n =11), IDH2, FLT3-ITD, CEBPA (12.50%, n =8), TET2 (10.94%, n =7). In the poor prognosis group (n =14), ASXL1, TP53, EZH2, NRAS had higher gene mutation frequency than others(14.29 %, n =2 ). Statistical analysis revealed that KIT had a relative hotspot of mutations in the intermediate-risk group, and DNMT3A had a relative hotspot of mutations in the high-risk group (P < 0.05). The correlation analysis of genes with high mutation rates in different prognostic groups, such as NRAS, KIT, IDH2, DNMT3A, NPM1, and FLT3-ITD, with prognosis found that KIT was a factor affecting OS (P < 0.05), while no significant differences were observed for the others(P >0.05). CONCLUSION The frequency of gene mutations is high in AML patients, 67.4% of the patients carried at least one gene mutation. The mutation frequency varies among different genes in patients with different karyotypes, and there are obvious dominant mutations. KIT and DNMT3A can be used as factors for evaluating the prognosis of AML.
Humans ; Leukemia, Myeloid, Acute/genetics* ; Nucleophosmin ; Mutation ; Prognosis ; Retrospective Studies ; Male ; Female ; High-Throughput Nucleotide Sequencing ; Middle Aged ; DNA Methyltransferase 3A ; Adult ; Aged ; Survival Analysis ; Proto-Oncogene Proteins c-kit/genetics*

Aim To construct and analyze the genotype of G protein-coupled receptor kinase 2(GRK2)conditional knockout mice in synoviocytes,and to provide an animal model for stud-ying the function of GRK2 in synoviocytes.Methods Grk2flox/+mice were bred to generate Grk2flox/flox mice,Grk2flox/flox mice were bred to Col1a1-iCre+mice,Grk2flox/+Col1a1-iCre+mice were bred to Grk2flox/flox mice.Grk2flox/flox Col1a1-iCre+mice were ob-tained as target mice.DNA was extracted and amplified by PCR to identify the genotype.Western blot was used to verify the effect of Grk2 knockout in synovium,liver and kidney tissues.HE staining was used to detect the effects of Grk2 conditional knockout in synovial cells on ankle synovium,liver and kidney tissues.Multiple immunofluorescence was used to detect GRK2 expression in synovial cells.Results The results of gene iden-tification showed that Grk2flox/flox Col1a1-iCre+mice had both Flox and Col1a1-iCre genotypes.Western blot results showed that GRK2 expression decreased in synovial tissues of Grk2flox/flox Col1a1-iCre+mice,but there was no significant change in the expression of GRK2 in liver and kidney tissues.HE staining showed that Grk2flox/flox Col1a1-iCre+mice had no significant pathological changes in the ankle synovium,liver and kidney.The results of multiple immunofluorescence showed that GRK2 expression in synovial cells of Grk2flox/flox Col1a1-iCre+mice de-creased.Conclusion Grk2 conditional knockout mice in syno-viocytes are successfully constructed and identified,which pro-vides an animal model for further study of the role of GRK2 in synovial-related diseases.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Objective·To develop a graph neural network(GNN)-based auxiliary diagnostic model for gallbladder cancer on CT images,and validate its accuracy and feasibility.Methods·From January 2010 to November 2023,1 774 contrast-enhanced CT arterial-phase images were acquired from 887 patients with normal gallbladder,benign gallbladder disease,or gallbladder cancer at Xinhua Hospital and Renji Hospital,Shanghai Jiao Tong University School of Medicine.These images were randomly divided into training and testing sets at a 4∶1 ratio to develop a hybrid GNN-convolutional neural network(CNN)model,named VJK-GIN.The model constructed a pixel-level graph in which each pixel served as a node,and spatial adjacency defined the edges,enabling extraction of local texture features.In the model architecture design,VJK-GIN integrated a three-layer graph isomorphism network,augmented with virtual nodes and jump-knowledge connections;global pooling compressed node features into a graph-level representation,which was classified by a multi-layer perceptron head.Five-fold cross-validation was used to compare VJK-GIN with GNN baselines(GCN,GraphSAGE,GAT,and GIN)and CNN baselines(ViT,EfficientNetV2,and ConvNeXt)in terms of accuracy,precision,recall,F1-score,and area under the receiver operating characteristic curve(AUC).Results·The results of five-fold cross-validation showed that VJK-GIN achieved an F1-score of 0.799(95%CI 0.775?0.823),recall of 0.795(95%CI 0.773?0.817),precision of 0.799(95%CI 0.775?0.823),AUC of 0.812(95%CI 0.792?0.832),and accuracy of 0.773(95%CI 0.748?0.798),surpassing all competing models across every metric.Conclusion·The VJK-GIN model exhibits high stability and accuracy in identifying contrast-enhanced CT images of normal,benign,and malignant gallbladder conditions.