BACKGROUND: Severe stroke has high rates of mortality and morbidity. This study aimed to investigate the clinical course, causes of worsening, and outcomes of severe ischemic stroke. METHODS: This prospective, multicenter cohort study enrolled adult patients admitted ≤30 days after ischemic stroke from nine hospitals in China between September 2017 and December 2019. Severe stroke was defined as a score of ≥15 on the National Institutes of Health Stroke Scale (NIHSS). Clinical worsening was defined as an increase of 4 in the NIHSS score from baseline. Unfavorable functional outcome was defined as a modified Rankin scale score ≥3 at 3 months and 1 year after stroke onset, respectively. We performed Logistic regression to explore baseline features and reperfusion therapies associated with clinical worsening and functional outcomes. RESULTS: Among 4201 patients enrolled, 854 patients (20.33%) had severe stroke on admission. Of 3347 patients without severe stroke on admission, 142 (4.24%) patients developed severe stroke in hospital. Of 854 patients with severe stroke on admission, 33.95% (290/854) experienced clinical worsening (median time from stroke onset: 43 h, Q1-Q3: 20-88 h), with brain edema (54.83% [159/290]) as the leading cause; 24.59% (210/854) of these patients died by 30 days, and 81.47% (677/831) and 78.44% (633/807) had unfavorable functional outcomes at 3 months and 1 year respectively. Reperfusion reduced the risk of worsening (adjusted odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.12-0.49, P  <0.01), 30-day death (adjusted OR: 0.22, 95% CI: 0.11-0.41, P  <0.01), and unfavorable functional outcomes at 3 months (adjusted OR: 0.24, 95% CI: 0.08-0.68, P <0.01) and 1 year (adjusted OR: 0.17, 95% CI: 0.06-0.50, P  <0.01). CONCLUSIONS: Approximately one-fifth of patients with ischemic stroke had severe neurological deficits on admission. Clinical worsening mainly occurred in the first 3 to 4 days after stroke onset, with brain edema as the leading cause of worsening. Reperfusion reduced the risk of clinical worsening and improved functional outcomes. REGISTRATION ClinicalTrials.gov , NCT03222024.
Humans ; Male ; Female ; Prospective Studies ; Ischemic Stroke/mortality* ; Aged ; Middle Aged ; Aged, 80 and over ; Stroke ; Brain Ischemia

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

This study investigated the protective effect of arbutin(Arb) in yam on lipopolysaccharide(LPS)-induced acute lung injury(ALI) in a mouse model and revealed its possible mechanism of action by metabolomics technology, providing a theoretical basis for clinical treatment of ALI. SPF BALB/c mice were randomly divided into normal control group, model group, resveratrol(Rv)-positive control group, Arb low-dose(15 mg·kg~(-1)) group, and Arb high-dose(30 mg·kg~(-1)) group. The LPS-induced ALI model was established in all groups except the normal control group. Hematoxylin-eosin(HE) staining, TUNEL staining, and WBP whole-body non-invasive pulmonary function testing were used to evaluate the degree of lung tissue damage and lung function changes. Enzyme-linked immunosorbent assay(ELISA) was used to detect the level of inflammatory factors in lung tissue. Flow cytometry was used to analyze the M1/M2 polarization status of macrophages in lung tissue. Western blot was used to detect the expression levels of the TLR4 signaling pathway and related apoptotic proteins. Liquid chromatograph-mass spectrometer(LC-MS) metabolomics was used to analyze the changes in serum metabolic profile after Arb intervention. The results showed that Arb pretreatment significantly alleviated LPS-induced lung tissue injury, improved lung function, reduced the levels of pro-inflammatory factors(IL-6, TNF-α, IL-18, and IL-1β), and regulated the polarization status of M1/M2 macrophages. In addition, Arb inhibited the activation of the TLR4 signaling pathway, reduced the expression of pro-apoptotic proteins such as Bax, caspase-3, and caspase-9, up-regulated the level of Bcl-2 protein, and inhibited apoptosis of lung cells. Metabolomic analysis showed that Arb significantly improved LPS-induced metabolic abnormalities, mainly involving key pathways such as galactose metabolism, phenylalanine metabolism, and lipid metabolism. In summary, Arb can significantly reduce LPS-induced ALI by regulating the release of inflammatory factors, inhibiting the activation of the TLR4 signaling pathway, improving metabolic disorders, and regulating macrophage polarization, indicating that Arb has potential clinical application value.
Animals ; Acute Lung Injury/chemically induced* ; Mice ; Mice, Inbred BALB C ; Arbutin/administration & dosage* ; Male ; Toll-Like Receptor 4/immunology* ; Apoptosis/drug effects* ; Lung/metabolism* ; Signal Transduction/drug effects* ; Protective Agents/administration & dosage* ; Humans ; Macrophages/immunology* ; Drugs, Chinese Herbal/administration & dosage*

Baihuasheshecao(Hedyotis diffusa) is a commonly used traditional Chinese medicine derived from the whole herb of H. diffusa and has been widely utilized in folk medicine. It possesses anti-tumor, antibacterial, and anti-inflammatory properties, making it one of the frequently used herbs in TCM clinical practice. However, Shuixiancao(H. corymbosa) and Xianhuaercao(H. tenelliflora), species of the same genus, are often used as substitutes for Baihuasheshecao. To substantiate the medicinal basis of Baihuasheshecao, this study systematically reviewed classical herbal texts and modern literature, examining its nomenclature, botanical origin, harvesting, processing, properties, meridian tropism, pharmacological effects, and clinical applications. The results indicate that Baihuasheshecao was initially recorded as "Shuixiancao" in Preface to the Indexes to the Great Chinese Botany(Zhi Wu Ming Shi Tu Kao). Based on its morphological characteristics and habitat description, it was identified as H. diffusa in the Rubiaceae family. Subsequent records predominantly refer to it as Baihuasheshecao as its official name. In most regions, Baihuasheshecao is recognized as the authentic medicinal material, distinct from Shuixiancao and Xianhuaercao. Baihuasheshecao is harvested in late summer and early autumn, and the dried whole plant, including its roots, is used medicinally. The standard processing method involves cutting. It is known for its effects in clearing heat, removing toxins, reducing swelling and pain, and promoting diuresis to resolve abscesses. Initially, it was mainly used for treating appendicitis, intestinal abscesses, and venomous snake bites, and later, it became a treatment for cancer. The excavation of its clinical value followed a process in which overseas Chinese introduced the herb from Chinese folk medicine to other countries. After its unique anti-cancer effects were recognized abroad, it was reintroduced to China and gradually became a crucial TCM for cancer treatment. The findings of this study help clarify the historical and contemporary uses of Baihuasheshecao, providing literature support and a scientific basis for its rational development and precise clinical application.
Humans ; China ; Drugs, Chinese Herbal/chemistry* ; Hedyotis/classification* ; Medicine, Chinese Traditional/history*

OBJECTIVE: Acupuncture therapies are known for their effectiveness in treating a variety of gastric diseases, although the mechanisms underlying these effects are not fully understood. This study tested the effectiveness of electroacupuncture (EA) at acupoints Zhongwan (RN12) and Weishu (BL21) for managing gastric motility disorder (GMD) and investigated the underlying mechanisms involved. METHODS: A GMD model was used to evaluate the impact of EA on various aspects of gastric function including the amplitude of gastric motility, electrogastrogram, food intake, and the rate of gastric emptying. Immunofluorescence techniques were used to explore the activation of spinal neurons by EA, specifically examining the presence of cholera toxin B subunit (CTB)-positive neurons and fibers emanating from acupoints RN12 and BL21. The stimulation of γ-aminobutyric acid (GABA)-ergic neurons in the spinal dorsal horn, the inhibition of sympathetic preganglionic neurons in the spinal lateral horn, and their collective effects on the activity of sympathetic nerves were examined. RESULTS: EA at RN12 and BL21 significantly improved gastric motility compromised by GMD. Notably, EA activated spinal neurons, with CTB-positive neurons and fibers from RN12 and BL21 being detectable in both the dorsal root ganglia and the spinal dorsal horn. Further analysis revealed that EA at these acupoints not only stimulated GABAergic neurons in the spinal dorsal horn but also suppressed sympathetic preganglionic neurons in the spinal lateral horn, effectively reducing excessive activity of sympathetic nerves triggered by GMD. CONCLUSION EA treatment at RN12 and BL21 effectively enhances gastric motility in a GMD model. The therapeutic efficacy of this approach is attributed to the activation of spinal neurons and the modulation of the spinal GABAergic-sympathetic pathway, providing a neurobiological foundation for the role of acupuncture in treating gastric disorders. Please cite this article as: Zhang MT, Liang YF, Dai Q, Gao HR, Wang H, Chen L, Huang S, Wang XY, Shen GM. A spinal neural circuit for electroacupuncture that regulates gastric functional disorders. J Integr Med. 2025; 23(1): 56-65.
Electroacupuncture ; Animals ; Male ; Acupuncture Points ; Stomach Diseases/physiopathology* ; Rats, Sprague-Dawley ; Gastrointestinal Motility ; Rats ; Gastric Emptying ; Neurons ; Spinal Cord ; Stomach/physiopathology*

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Objective:Melanoma is highly malignant and heterogeneous.It is essential to develop a specific prognostic model for improving the patients'survival and treatment strategies.Recent studies have shown that ferroptosis results from the overproduction of lipid peroxidation and is an iron-dependent form of programmed cell death.Despite this,ferroptosis-related genes(FRGs)and their clinical significances remain unknown in malignant melanoma.This study aims to assess the role of FRGs in melanoma,with the goal of developing a novel prognostic model that provides new insights into personalized treatment and improvement of therapeutic outcomes for melanoma. Methods:We systematically characterized the genetic alterations and mRNA expression of 73 FRGs in The Cancer Genome Atlas(TCGA)-skin cutaneous melanoma(SKCM)dataset in this study.The results were validated with real-time RT-PCR and Western blotting.Subsequently,a multi-gene feature model was constructed using the TCGA-SKCM cohort.Melanoma patients were classified into a high-risk group and a low-risk group based on the feature model.As a final step,correlations between ferroptosis-related signatures and immune features,immunotherapy efficacy,or drug response were analyzed. Results:By analyzing melanoma samples from TCGA-SKCM dataset,FRGs exhibited a high frequency of genetic mutations and copy number variations(CNVs),significantly impacting gene expression.Additionally,compared with normal skin tissue,30 genes with significantly differential expression were identified in melanoma tissues.A prognostic model related to FRGs,constructed using the LASSO Cox regression method,identified 13 FRGs associated with overall survival prognosis in patients and was validated with external datasets.Finally,functional enrichment and immune response analysis further indicated significant differences in immune cell infiltration,mutation burden,and hypoxia status between the high-risk group and the low-risk group,and the model was effective in predicting responses to immunotherapy and drug sensitivity. Conclusion:This study develops a strong ferroptosis-related prognostic signature model which could put forward new insights into target therapy and immunotherapy for patients with melanoma.

The rare-earth-elements-doped upconversion nanoparticles NaYF4:Yb3+,Er3+were synthesized by solvothermal method,and NaYF4:Yb3+,Er3+@SiO2 were prepared by coating SiO2 on the surface of NaYF4:Yb3+,Er3+by inverse microemulsion method in this work.Based on the fluorescence quenching principle between NaYF4∶Yb3+,Er3+@SiO2 and SQA-Fe3+,a NaYF4∶Yb3+,Er3+@SiO2-SQA-Fe3+fluorescence nanosensor was constructed for detection of trace hydrogen peroxide(H2O2).Under optimal conditions,the linear range of this method for detecting H2O2 was 1.8?84.0 μmol/L,with detection limit(3σ)of 0.47 μmol/L.The recoveries of H2O2 spiked in milk were 98.4%?99.7%.This method could be used for detection of H2O2 residue in milk samples,with advantages such as low detection limit,good stability and strong anti-interference ability.

Objective To investigate the application value of combining the Demirjian's method with ma-chine learning algorithms for dental age estimation in northern Chinese Han children and adolescents.Methods Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected.The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian's method.Various machine learning algorithms,including support vector re-gression(SVR),gradient boosting regression(GBR),linear regression(LR),random forest regression(RFR),and decision tree regression(DTR)were employed.Age estimation models were constructed based on total,female,and male samples respectively using these algorithms.The fitting performance of different machine learning algorithms in these three groups was evaluated.Results SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples,while GBR showed the best performance in male samples.The mean absolute error(MAE)of the op-timal age estimation model was 1.246 3,1.281 8 and 1.153 8 years in the total,female and male samples,respectively.The optimal age estimation model exhibited varying levels of accuracy across dif-ferent age ranges,which provided relatively accurate age estimations in individuals under 18 years old.Conclusion The machine learning model developed in this study exhibits good age estimation effi-ciency in northern Chinese Han children and adolescents.However,its performance is not ideal when applied to adult population.To improve the accuracy in age estimation,the other variables can be con-sidered.