The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

This paper summarizes Professor HAN Mingxiang's clinical experience in treating chronic obstructive pulmonary disease （COPD）. He believes that the key pathomechanism of COPD in the acute exacerbation stage is the invasion of external pathogens triggering latent illness， while lung qi deficiency is the primary mechanism in the stable stage. The core pathological factors throughout disease progression are deficiency， phlegm， and blood stasis. Treatment emphasizes a staged and syndrome-based approach. During the acute exacerbation stage， for wind-cold invading the lung syndrome， the self-formulated Sanzi Wenfei Decoction （三子温肺汤） is used to relieve the exterior， dispel cold， warm the lung， and resolve phlegm. For phlegm-dampness obstructing the lung syndrome， Huatan Jiangqi Fomulation （化痰降气方） is prescribed to warm the lung， transform phlegm， descend qi， and calm wheezing. For phlegm-heat obstructing the lung syndrome， Qingfei Huatan Fomulation （清肺化痰方） is applied to clear heat， resolve phlegm， moisten the lung， and stop coughing. For phlegm and blood stasis interlocking syndrome， Qibai Pingfei Fomulation （芪白平肺方） is used to tonify qi， resolve phlegm， and activate blood circulation to remove stasis. During the stable stage， for lung qi deficiency syndrome， Shenqi Wenfei Decoction （参芪温肺汤） is employed to warm the lung， tonify qi， resolve phlegm， and eliminate turbidity. For lung-spleen qi deficiency syndrome， Shenqi Buzhong Decoction （参芪补中汤） is utilized to strengthen the spleen， tonify qi， and reinforce metal （lung） from earth （spleen）. For lung-kidney deficiency syndrome， Shenqi Tiaoshen Fomulation （参芪调肾方） is prescribed to tonify the lung， warm yang， and regulate kidney function to calm wheezing. These strategies provide insights into the traditional Chinese medicine treatment of COPD.

OBJECTIVE To explore the effects of Polygala tenuifolia compatibility on toxicity， anti-inflammatory and analgesic efficacy of sand-ironing Strychnos nux-vomica （SS）. METHODS The preparation of SS single decoction， SS-P. tenuifolia core-removed （PC） （1∶2.5） or （1∶5） combined decoction， and SS-PC （1∶5） mixture were carried out to investigate their median lethal dose （LD50）. Using aspirin as positive control， the number of writhing movements， analgesic rate， pain latency， ear swelling degree and inflammation inhibition rate induced by the above-mentioned medicinal liquids in mice were compared. The contents of the active and toxic components， strychnine and brucine， in the above-mentioned medicinal liquids were also determined. RESULTS The LD50 values of SS single decoction， SS-PC （1∶2.5） combined decoction， SS-PC （1∶5） combined decoction and SS- PC （1∶5） mixture were 302.00， 614.47， 1 445.44 and 1 778.28 mg/kg， respectively. Compared with control group， the number of writhing movements and ear swelling degree in the mice of the above-mentioned medicinal liquid groups were reduced or decreased significantly （P＜0.05 or P＜0.01）； pain latency [at 90 and 120 minutes in the SS single decoction group， at 60 and 90 minutes in the SS-PC （1∶2.5） combined decoction group， and at 60，90， 120 minutes in the SS-PC （1∶5） combined decoction group and SS-PC （1∶5） mixture group] was significantly prolonged （P＜0.05 or P＜0.01）； analgesic rates of the respective medicinal liquids were 39.30%， 70.87%， 80.00% and 82.46%， and inflammation inhibition rates were 38.08%，TD 57.89%， 76.47% and 50.46%； analgesic and anti-inflammatory effects of combined decoction and mixture were generally better than those of the single decoction （P＜0.05 or P＜0.01）. In the above-mentioned four medicinal liquids， the total contents of strychnine were 0.71%， 0.42%， 0.47% and 0.64%， and the total contents of brucine were 0.88%， 0.63%， 0.57% and 0.88%， respectively. CONCLUSIONS The combination of P. tenuifolia can reduce the toxicity of SS and enhance its anti-inflammatory and analgesic effects. Moreover， there is a tendency for the toxicity-reducing and efficacy-enhancing effects to increase with the increasing dosage of P. tenuifolia. Additionally， the combined decoction of SS and P. tenuifolia can reduce the contents of the active and toxic components， strychnine and brucine， in SS.

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective: Data on syncopal donation-related vasovagal reaction (DRVR) collected from 74 blood centers between 2020 and 2023 was statistically analyzed to provide a reference for developing preventive strategies against syncopal DRVR. Methods: Data on blood donation adverse reactions and basic information of donors from 2020 to 2023 were collected through the information management system at monitoring sentinel sites. Statistical analysis was performed on the following aspects of syncopal DRVR: characteristics of donors who experienced syncope, reported incidence, triggers, duration, presence and occurrence time of syncope-related trauma, clinical management including outpatient and inpatient treatment, and severity grading. Results: From 2020 to 2023, 45 966 donation-related adverse reactions were recorded. Of these, 1 665 (3.72%) cases were syncopal DRVR. The incidence of syncopal DRVR decreased with age, being the highest in the 18-22 age group. Incidence was significantly higher in female donors than male donors, in first-time donors than repeat donors, and in university and individual donors than group donors (all P<0.05). There was no statistically significant difference among different blood donation locations (P>0.05). The top three triggers were tension, fatigue, and needle phobia or fear of blood. Among syncopal DRVR cases, 60.36% occurred during blood collection, 87.63% lasted for less than 60 seconds, and 5.05% were accompanied by trauma. Notably, 57.14% of these traumas occurred after donor had left the blood collection site. Syncope severity was graded based on required treatment: grade 1 (fully recovered without treatment, 95.50%); grade 2 (recovered after outpatient treatment, 4.02%); and grade 3 (recovered after inpatient treatment, 0.48%). Conclusion: By analyzing the data of syncopal DRVR cases, it is possible to provide a reference for formulating blood donor safety policies.

[摘 要] 目的：探究芒柄花素调节JAK2/STAT3信号通路对胆囊癌细胞GBC-SD恶性生物学行为及血管生成的影响。方法：常规培养GBC-SD细胞并构建其移植瘤裸鼠，将GBC-SD细胞和其移植瘤裸鼠分为对照组、芒柄花素组、colivelin（JAK2/STAT3激活剂）组、芒柄花素 + colivelin组。用MTT法、Transwell实验和流式细胞术分别检测各组细胞的增殖、迁移和侵袭能力，以及凋亡，用ELISA法检测各组细胞血管内皮生长因子（VEGF）分泌水平，血管生成拟态（VM）形成实验检测各组细胞的成管腔能力，移植瘤实验检测芒柄花素对移植瘤生长的影响，免疫组化法检测各组移植瘤组织中CD31和VEGF表达，WB法检测各组细胞和移植瘤组织中JAK2/STAT3通路的磷酸化水平。结果：芒柄花素可明显抑制GBC-SD细胞的增殖、迁移和侵袭能力，促进其凋亡（均P < 0.05），抑制GBC-SD细胞分泌VEGF和VM形成（均P < 0.05），抑制GBC-SD细胞移植瘤的生长及血管生成（均P < 0.05），抑制移植瘤组织中VEGF表达，抑制GBC-SD细胞和其移植瘤组织中JAK2/STAT3通路的磷酸化，colivelin均可逆转芒柄花素的上述作用（均P < 0.05）。结论：芒柄花素通过抑制JAK2/STAT3信号通路抑制GBC-SD细胞增殖、迁移、侵袭、血管形成，促进其凋亡，JAK2/STAT3信号通路是胆囊癌临床治疗的潜在靶点。