ObjectiveTo explore the possible mechanism of Jianpi Huazhuo Tiaozhi Granule （健脾化浊调脂颗粒， JHTG） in treating atherosclerosis （AS） based on the regulation of perivascular adipose tissue （PVAT） browning via the phosphoinositide 3-kinase/protein kinase B （PI3K/AKT） signaling pathway. MethodsFifteen SPF male C57BL/6J mice served as control group， while 76 ApoE^-/- mice were first fed a high-fat diet for 16 weeks to establish AS model. After successful modeling， they were randomly divided into model group （n=16）， as well as the browning group， the low-， medium- and high-dose JHTG group， with 15 mice in each group. The browning group was intraperitoneally injected with β3-adrenergic receptor agonist CL 316243 at 1 mg/（kg·d） once daily. The low-， medium- and high-dose JHTG groups were treated with 4.3 g/（kg·d）， 8.6 g/（kg·d）， and 17.2 g/（kg·d） of JHTG by gavage， respectively， while the control group and the model group were given normal saline at 10 ml/（kg·d） by intragastric administration， once daily. All groups received continuous intervention for 4 weeks. The aorta was collected to assess the plaque ratio by gross oil red O staining. HE staining was used to measure the plaque area in cross-sections. Masson staining was employed to detect the proportion of collagen fibers in plaque. Transmission electron microscopy was used to observe the quantity and morphological changes of mitochondria and lipid droplets in adipocytes. The levels of serum triglycerides （TG）， total cholesterol （TC）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） were detected， as well as tumor necrosis factor α （TNF-α） and interleukin 6 （IL-6） levels in the PVAT and aorta. The protein levels of adiponectin and leptin in PVAT， and protein expression levels of phosphoinositide 3-kinase （PI3K）， phosphorylated phosphoinositide 3-kinase （p-PI3K）， protein kinase B （AKT）， phosphorylated protein kinase B （p-AKT）， uncoupling protein 1 （UCP1）， peroxisome proliferator-activated receptor γ coactivator 1α （PGC-1α）， and PR domain containing 16 （PRDM16） were measured. The mRNA expression levels of UCP1， PGC-1α and PRDM16 in PVAT were detected. ResultsCompared to the control group， the model group showed increased serum TG， TC， and LDL-C levels and decreased HDL-C level， elevated TNF-α and IL-6 levels in PVAT and aorta， decreased average fluorescence intensity of adiponectin， increased average fluorescence intensity of leptin， reduced p-PI3K/PI3K and p-AKT/AKT values as well as protein levels and mRNA expression levels of UCP1， PGC-1α and PRDM16 （P＜0.01）. The pathological results showed that no significant plaque formation was observed in the aortas of mice in the control group. In the model group， multiple plaques were observed in the aortas， with large numbers of foam cells， cholesterol crystals， and inflammatory cell aggregation in the plaques. Compared to the model group， the browning group and the high-dose JHTG group significantly improved the above indicators and aortic pathological changes （P＜0.05 or P＜0.01）. Three JHTG groups showed a dose-dependent effect in reducing LDL-C level and plaque ratio by gross oil red O staining， elevating the average fluorescence intensity of adiponectin， the p-AKT/AKT value， the protein level of PGC-1α， and the mRNA expression levels of UCP1 and PRDM16 （P＜0.05）. The high-dose JHTG group and the browning group showed similar efficacy in improving the pathology of the aorta. ConclusionJHTG may promote PVAT browning in AS model mice through the PI3K/AKT pathway， improve the endocrine function of PVAT， inhibit aortic inflammation， and thereby ameliorate the formation of AS plaques.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

Abuse of amphetamine-based stimulants is a primary public health concern. Recent studies have underscored a troubling escalation in the inappropriate use of prescription amphetamine-based stimulants. However, the neurophysiological mechanisms underlying the impact of acute methamphetamine exposure (AME) on sleep homeostasis remain to be explored. This study employed non-human primates and electroencephalogram (EEG) sleep staging to evaluate the influence of AME on neural oscillations. The primary focus was on alterations in spindles, delta oscillations, and slow oscillations (SOs) and their interactions as conduits through which AME influences sleep stability. AME predominantly diminishes sleep-spindle waves in the non-rapid eye movement 2 (NREM2) stage, and impacts SOs and delta waves differentially. Furthermore, the competitive relationships between SO/delta waves nesting with sleep spindles were selectively strengthened by methamphetamine. Complexity analysis also revealed that the SO-nested spindles had lost their ability to maintain sleep depth and stability. In summary, this finding could be one of the intrinsic electrophysiological mechanisms by which AME disrupted sleep homeostasis.
Animals ; Methamphetamine ; Electroencephalography ; Male ; Sleep/drug effects* ; Central Nervous System Stimulants ; Delta Rhythm/drug effects* ; Sleep Stages/drug effects*

Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.

Filamenting temperature-sensitive mutant Z (FtsZ), a protein essential for bacterial cell division, is highly conserved across bacterial species but absent in humans, positioning it as a strategic target for the development of antibiotics. Significant efforts to identify FtsZ inhibitors-via biochemical assays (e.g., GTPase activity) and cellular approaches (e.g., immunofluorescence)-have yielded over 100 natural products and synthetic compounds, whose cheminformatics clustering underscores a limited chemical diversity among the current scaffolds. Structural studies, including X-ray crystallography and cryo-electron microscopy, have resolved 97 FtsZ structures revealing conserved polymerization mechanisms and conformational plasticity, as exemplified by extremophile adaptations (e.g., Shewanella benthica from the high-pressure environment of the Mariana Trench's Challenger Deep). However, clinical translation is hindered by weak binding affinities, inhibitory inefficacy, dynamic conformational flexibility, and evolving drug resistance linked to FtsZ's functional plasticity. To address these challenges, future efforts should be directed to resolve transient assembly intermediates, leveraging machine learning with high-throughput screening, and integrating structural biology with pharmacokinetic optimization. Multidisciplinary strategies combining these approaches hold promise for translating FtsZ-focused research into clinically viable therapies, addressing the critical unmet need posed by antibiotics resistance.

The translation of genetic findings from genome-wide association studies into actionable therapeutics persists as a critical challenge in Alzheimer's disease (AD) research. Here, we present PI4AD, a computational medicine framework that integrates multi-omics data, systems biology, and artificial neural networks for therapeutic discovery. This framework leverages multi-omic and network evidence to deliver three core functionalities: clinical target prioritisation; self-organising prioritisation map construction, distinguishing AD-specific targets from those linked to neuropsychiatric disorders; and pathway crosstalk-informed therapeutic discovery. PI4AD successfully recovers clinically validated targets like APP and ESR1, confirming its prioritisation efficacy. Its artificial neural network component identifies disease-specific molecular signatures, while pathway crosstalk analysis reveals critical nodal genes (e.g., HRAS and MAPK1), drug repurposing candidates, and clinically relevant network modules. By validating targets, elucidating disease-specific therapeutic potentials, and exploring crosstalk mechanisms, PI4AD bridges genetic insights with pathway-level biology, establishing a systems genetics foundation for rational therapeutic development. Importantly, its emphasis on Ras-centred pathways-implicated in synaptic dysfunction and neuroinflammation-provides a strategy to disrupt AD progression, complementing conventional amyloid/tau-focused paradigms, with the future potential to redefine treatment strategies in conjunction with mRNA therapeutics and thereby advance translational medicine in neurodegeneration.

Bombesin receptor subtype-3 (BRS3) is an orphan G protein-coupled receptor (GPCR) that plays critical roles in energy homeostasis, glucose metabolism, and insulin secretion. Recent structural studies have elucidated BRS3 signaling mechanisms using synthetic ligands, including BA1 and MK-5046. However, the molecular basis of BRS3 activation by bioactive natural compounds and their derivatives, particularly those derived from traditional Chinese medicine, remains unclear. Here, we present high-resolution cryogenic electron microscopy (cryo-EM) structures of the human BRS3-G_q complex in both unliganded and active states bound by two herb-derived compounds (DSO-5a and oridonin), at resolutions of 2.9, 2.8, and 2.9 Å, respectively. These structures display distinct ligand recognition patterns between DSO-5a and oridonin. Although both compounds bind to the orthosteric pocket, they differentially engage the interaction network of BRS3, as demonstrated by mutagenesis studies assessing calcium mobilization and inositol phosphate 1 (IP1) accumulation. These findings enhance our understanding of BRS3 activation and provide valuable insights into the development of small-molecule BRS3 modulators with therapeutic potential.

The cooccurrence of NPM1, FLT3-ITD, and DNMT3A mutations (i.e., triple mutation) is related to dismal prognosis in patients with acute myeloid leukemia (AML) receiving chemotherapy alone. In this multicenter retrospective cohort study, we aimed to identify whether allogeneic hematopoietic stem cell transplantation (allo-HSCT) could overcome the poor prognosis of DNMT3A^mutNPM1^mutFLT3-ITD^mut AML across four transplant centers in China. Fifty-three patients with triple-mutated AML receiving allo-HSCT in complete remission were enrolled. The 1.5-year probabilities of relapse, leukemia-free survival, and overall survival after allo-HSCT were 11.9%, 80.3%, and 81.8%, respectively. Multivariate analysis revealed that more than one course of induction chemotherapy and allo-HSCT beyond CR1 were associated with poor survival. To our knowledge, this work is the largest study to explore the up-to-date undefined role of allo-HSCT in patients with triple-mutated AML. Our real-world data suggest that allo-HSCT could overcome the poor prognosis of DNMT3A^mutNPM1^mutFLT3-ITD^mut in AML.
Humans ; Nucleophosmin ; Leukemia, Myeloid, Acute/mortality* ; Hematopoietic Stem Cell Transplantation/methods* ; Male ; Female ; DNA Methyltransferase 3A ; Adult ; China ; Retrospective Studies ; DNA (Cytosine-5-)-Methyltransferases/genetics* ; Middle Aged ; Prognosis ; fms-Like Tyrosine Kinase 3/genetics* ; Mutation ; Young Adult ; Transplantation, Homologous ; Nuclear Proteins/genetics* ; Adolescent ; Aged