Objective To optimize the extraction process of Xuetong capsules and establish its quality control method. Methods The extraction process was optimized by orthogonal experiment using ethanol reflux method to investigate the effects of different factors on diphenylstilbene, aloin and extraction yield. The content of 5 anthraquinone compounds in Xuetong capsule was determined by HPLC. Results The optimal extraction process was to add 10 times ethanol, with an ethanol concentration of 70%, and extract 3 times, each time for 1 h; 5 components had a good linear relationship with peak area within a certain concentration range, r>0.999 7; The range of sample recovery rate was 93.66%-96.85%, RSD range of 1.48%-1.66%. The content determination results of the 5 components in three batches of Xuetong capsules were （0.632-0.641）, （0.660-0.681）, （1.968-1.991）, （2.547-2.580）, and （1.076-1.101） mg/g. Conclusion The method was accurate, reproducible, and highly feasible, which could be references for producing and improving the quality control standards of Xuetong capsules.

ObjectiveTo investigate the incidence of stroke in patients with type 2 diabetes mellitus (T2DM) in the community of Shanghai, and to explore its influencing factors. MethodsA two-way cohort study was used to observe the incidence of stroke in a dynamic cohort of14 743 community-based T2DM patients who were enrolled for management from January 2016 to December 2018 in Hongkou District, Shanghai. All the research subjects were followed up for 3 years to observe the stroke occurrence. Outcome events were retrospectively collected from the Shanghai Stroke and Acute Myocardial Infarction Registry Reporting Information System and the Cause of Death Registry System, and information on stroke onset and verification of past medical history were collected by family physicians through clinic follow-up, home follow-up, and telephone follow-up. Cox proportional hazards model was used to identify the risk factors of stroke in TDM2 patients, and the hazard ratio (HR) and its 95% confidence interval (CI) were calculated. ResultsAfter a mean follow up of 3.5 years, the standardized incidence of stroke in patients with T2DM was 8.65‰, and the risk of standardized incidence was 3.50 (95%CI: 3.26‒3.77) compared with that of the total national population. Cox proportional hazards regression analysis showed that age (HR=1.18, 95%CI: 1.13‒1.23), being female (HR=1.14, 95%CI: 1.01‒1.29), physical activity <600 metabolic equivalent (MET)·min·week^-1 (HR=1.24, 95%CI: 1.06‒1.44), substandard of HbA1c control (HR=1.16, 95%CI: 1.03‒1.30), occasional smoker(HR=1.23, 95%CI: 1.04‒1.45), and those who took insulin therapy (HR=1.36, 95%CI: 1.11‒1.66) were associated with an increased risk of stroke, while those received contracted services from family doctors were associated with a decreased risk of stroke(HR=0.78, 95%CI: 0.71‒0.88). ConclusionCommunity T2DM population in Shanghai has a high risk of stroke. It is necessary to continue to explore the positive role of family doctor contract service management model, strengthen individualized exercise, smoking cessation and other lifestyle interventions, and strictly control blood glucose as soon as one can to delay or avoid the occurrence of complications.

In this paper， by consulting the ancient and modern literature， the name， origin， quality evaluation， harvesting and processing， and others of the original animal and medicinal materials of Moschus were systematically sorted out and verified， in order to provide the basis for the development and utilization of the famous classical formulas containing Moschus. According to the textual research， musk deer was first recorded in Shanhaijing. Shennong Bencaojing was recorded as Moschus and all generations were used as the correct name， but there were also aliases such as Shefu， Xiangzhang and Xiangqizi. In ancient times， Moschus berezovskii， M. sifanicus and M. moschiferus were the main sources of Moschus， and the quality of Moschus produced in northwest China was better than that produced in the Yangtze River basin. In modern times， Moschus of M. moschiferus produced in northeast China， M. sifanicus produced in Gansu， Sichuan and other places， and M. berezovskii produced in Ningxia， Shaanxi and other places are regarded as genuine. In ancient times， gunshots， lassoes， arrow shots and other methods were generally used to hunt live musk deer， and the sachets were immediately cut off. Those with high quality were called Xiangshanhuo， and dried in the shade after harvesting， which was known as Maoke Shexiang. Cut open the sachet， remove the shell and dry preservation， commonly known as Moschus kernel. In modern times， the method of taking Moschus from the living body of cultured musk deer is adopted， that is， Moschus kernel is directly taken from its sachet， dried in the shade or dried in a closed dryer. This method realizes the sustainable utilization of Chinese herbal medicine resources， but attention should be paid to the frequency and quality of Moschus. The harvesting time is mostly after the autumnal equinox every year， and before the next summer， it is better to gather sachet in winter. In recent times， it is believed that the shell Moschus is dry， full， thin， elastic， loose inside， many particles， strong and persistent aroma for the best， while the Moschus kernel is particle purple-black， powder yellow-brown， soft and oily texture， strong and persistent aroma for the best. The ancient processing method of Moschus was extracting kernels from the shell. After removing impurities， it is ground and used as medicine. Because its composition is not suitable for heating， the processing method is most common in preparations such as grinding into powder and putting into pills or powders， which has the effect of opening up the orifices and refreshing the mind， and it has continued to this day. Based on the research conclusions， it is suggested that the development of famous classical formulas containing Moschus， M. sifanicus， M. moschiferus and M. berezovskii should be used as the origins. According to the processing requirements specified in the original formula， it should be processed and used as medicine， while those without processing requirements should be used as raw products.

Objective The study aims to investigate the immunological functions of the nucleocapsid (N) protein of the novel coronavirus Omicron (BA.1, BA.2) and evaluate the differences among different N proteins of mutant strains in immunogenicity. Methods By aligning sequences, the mutation sites of the Omicron (BA.1, BA.2) N protein relative to prototype strain of the novel coronavirus (Wuhan-Hu-1) were determined. The pET-28a-N-Wuhan-Hu-1 plasmid was used as template to construct pET-28a-BA.1/BA.2-N through single point mutation or homologous recombination. The three kinds of N protein were expressed in prokaryotic system, purified through Ni-NTA affinity chromatography, and then immunized into mice. The titer and reactivity of the polyclonal antibody, as well as the expression level of IL-1β and IFN-γ in mouse spleen cells, were detected using indirect ELISA and Western blot assay. Results The constructed prokaryotic expression plasmids were successfully used to express the Wuhan-Hu-1 N, BA.1 N, and BA.2 N proteins in E.coli BL21(DE3) at 37 DegreesCelsius for 4 hours. The indirect ELISA test showed that the titers of polyclonal antibody prepared by three N proteins were all 1:51 200. All three N proteins can increase the expression of IFN-γ and IL-1β cytokines, but the effect of Omicron N protein in activing two cytokines was more obvious than that of Wuhan-Hu-1 N protein. Conclusion The study obtained three new coronavirus N proteins and polyclonal antibodies, and confirmed that mutations in the amino acid sites of the N protein can affect its immunogenicity. This provides a basis for developing rapid diagnostic methods targeting N protein of different novel coronavirus variants.
Animals ; Mice ; SARS-CoV-2/genetics* ; Coronavirus Nucleocapsid Proteins/immunology* ; Nucleocapsid Proteins/isolation & purification* ; COVID-19/immunology* ; Antibodies, Viral/immunology* ; Mice, Inbred BALB C ; Interferon-gamma/metabolism* ; Interleukin-1beta/metabolism* ; Female ; Escherichia coli/metabolism* ; Mutation ; Humans

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

The persistent high prevalence and poor survival outcomes of lung cancer underscore the urgent need for innovative therapeutic modalities. Here, we present a novel multifunctional delivery platform for the synergistic treatment of lung malignancies, combining in situ-triggerable photodynamic therapy (PDT) with radiotherapy. The new platform CLL was developed by loading a new reactive oxygen species (ROS)-triggerable photosensitizer, luminol-conjugated chlorin e6 (Ce6), into liposomes. CLL can be activated through the bioluminescence resonance energy transfer effect under oxidative stress, thereby producing singlet oxygen for targeted tumor treatment without external irradiation. In vitro studies showed significant cytotoxic effects of CLL in both 4T1 and A549 tumor cells. Furthermore, a PDT-radiopharmaceutical combination nanotherapy CLL-¹⁷⁷Lu was engineered by incorporating the radionuclide ¹⁷⁷Lu into CLL. CLL-¹⁷⁷Lu demonstrated synergistic antitumor effects in 4T1 and A549 tumor cells, as well as in mouse models of 4T1 breast cancer lung metastasis or A549 tumor xenografts. Mechanistically, CLL-¹⁷⁷Lu can induce singlet oxygen/ROS generation, enhance tumor cell apoptosis, and promote M1 macrophage-mediated immunotherapy. Preliminary assessments showed a favorable profile for CLL-¹⁷⁷Lu, highlighting its potential as a promising nanotherapy for cancer treatment. Additionally, CLL can serve as a versatile platform for delivering a range of therapies to achieve synergistic antitumor effects.

OBJECTIVES: To evaluate the therapeutic effect of gastrodin against hypoxic-ischemic brain damage (HIBD) in neonatal mice and explore the role of GPX4/SLC7A11/FTH1 signaling in mediating its effect. METHODS: Twenty-four 9- to 11-day-old C57BL/6J mice were randomized equally into 4 groups for sham operation, HIBD modeling by right common carotid artery ligation and subsequent exposure to hypoxia for 1 h, or gastrodin treatment at 100 or 200 mg/kg before and at 1 and 2 days after modeling. The mice then underwent neurological assessment (Zea-Longa scores), and the cerebral cortical penumbra tissue were collected for HE and Nissl staining, detection of ferroptosis biomarkers and protein expressions of GPX4, SLC7A11, and FTH1 with Western blotting and immunofluorescence co-localization, and observation of mitochondrial ultrastructure with electron microscopy. In cultured HT22 neuronal cells with oxygen-glucose deprivation (OGD) for 2 h, the effects of pretreatments with 0.5 mmol/L gastrodin, 10 μmol/L RSL3 (a GPX4 inhibitor), alone or in combination, were analyzed on expressions of ferroptosis-related proteins, cellular Fe²⁺, ROS, lipid peroxidation, MDA, and GSH levels, mitochondrial membrane potential (JC-1), and cell viability. RESULTS: Gastrodin treatment at the two doses both significantly ameliorated HIBD and neurological deficits of the mice, reduced mitochondrial damage and Fe²⁺, MDA and ROS levels, increased GSH level, and upregulated GPX4, SLC7A11, and FTH1 protein expressions. In HT22 cells, gastrodin pretreatment obviously attenuated OGD-induced ferroptosis and improved cell viability and mitochondrial function. Co-treatment with RSL3 potently abrogated the inhibitory effects of gastrodin on Fe²⁺, ROS, BODIPY-C11, and MDA levels and attenuated its protective effects on GSH level, cell viability, and mitochondrial membrane potential. CONCLUSIONS Gastrodin provides neuroprotective effects in neonatal mice with HIBD by suppressing neuronal ferroptosis via upregulating the GPX4/SLC7A11/FTH1 signaling pathway.
Animals ; Ferroptosis/drug effects* ; Hypoxia-Ischemia, Brain/drug therapy* ; Mice ; Mice, Inbred C57BL ; Signal Transduction/drug effects* ; Phospholipid Hydroperoxide Glutathione Peroxidase ; Glucosides/pharmacology* ; Animals, Newborn ; Benzyl Alcohols/pharmacology* ; Amino Acid Transport System y+/metabolism*

OBJECTIVE: To develop a method for identifying high-risk patients among septic populations requiring mechanical ventilation, and to conduct phenotypic analysis based on this method. METHODS: Data from four sources were utilized: the Medical Information Mart for Intensive Care (MIMIC-IV 2.0, MIMIC-III 1.4), the Philips eICU-Collaborative Research Database 2.0 (eICU-CRD 2.0), and the Anhui Medical University Second Affiliated Hospital dataset. The adult patients in intensive care unit (ICU) who met Sepsis-3 and received invasive mechanical ventilation (IMV) on the first day of first admission were enrolled. The MIMIC-IV dataset with the highest data integrity was divided into a training set and a test set at a 6:1 ratio, while the remaining datasets were served as validation sets. The demographic information, comorbidities, laboratory indicators, commonly used ICU scores, and treatment measures of patients were extracted. Clinical data collected within first day of ICU admission were used to calculate the sequential organ failure assessment (SOFA) score. K-means clustering was applied to cluster SOFA score components, and the sum of squared errors (SSE) and Davies-Bouldin index (DBI) were used to determine the optimal number of disease subtypes. For clustering results, normalized methods were employed to compare baseline characteristics by visualization, and Kaplan-Meier curves were used to analyze clinical outcomes across phenotypes. RESULTS: This study enrolled patients from MIMIC-IV dataset (n = 11 166), MIMIC-III dataset (n = 4 821), eICU-CRD dataset (n = 6 624), and a local dataset (n = 110), with the four datasets showing similar median ages and male proportions exceeding 50%; using 85% of the MIMIC-IV dataset as the training set, 15% as the test set, and the rest dataset as the validation set. K-means clustering based on the six-item SOFA score was performed to determine the optimal number of clusters as 3, and patients were finally classified into three phenotypes. In the training set, compared with the patients with phenotype II and phenotype III, those with phenotype I had the more severe circulatory and respiratory dysfunction, a higher proportion of vasoactive drug usage, more obvious metabolic acidosis and hypoxia, and a higher incidence of congestive heart failure. The patients with phenotype II was dominated by respiratory dysfunction with higher visceral injury. The patients with phenotype III had relatively stable organ function. The above characteristics were consistent in both the test and validation sets. Analysis of infection-related indicators showed that the patients with phenotype I had the highest SOFA score within 7 days after ICU admission, initial decreases and later increases in platelet count (PLT), and higher counts of neutrophils, lymphocytes, and monocytes as compared with those with phenotype II and phenotype III, their blood cultures had a higher positivity rates for Gram-positive bacteria, Gram-negative bacteria and fungi as compared with those with phenotype II and phenotype III. The Kaplan-Meier curve indicated that in the training, test, and validation sets, the 28-day cumulative mortality of patients with phenotype I was significantly higher than that of patients with phenotypes II and phenotype III. CONCLUSIONS Three distinct phenotypes in septic patients receiving IMV based on unsupervised machine learning is derived, among which phenotype I, characterized by cardiorespiratory failure, can be used for the early identification of high-risk patients in this population. Moreover, this population is more prone to bloodstream infections, posing a high risk and having a poor prognosis.
Humans ; Machine Learning ; Sepsis/therapy* ; Respiration, Artificial ; Intensive Care Units ; Organ Dysfunction Scores ; Male ; Female ; Middle Aged ; Adult

Cancer is a serious global health problem and a major cause of human death. Conventional cancer treatments often run the risk of impairing vital organ functions. Anticancer peptides (ACPs) are considered to be one of the most promising therapeutic agents against common human cancers due to their small sizes, high specificity, and low toxicity. Since ACP recognition is highly limited to the laboratory, expensive, and time-consuming, we proposed pLM4ACP, a model for predicting ACPs based on machine learning and protein language models. In this model, the protein language model ProtT5 was used to extract the features of ACPs, and the extracted features were input into the support vector machine (SVM) classification algorithm for optimization and performance evaluation. The model showcased significantly higher accuracy than other methods, with the overall accuracy of 0.763, F1-score of 0.767, Matthews correlation coefficient of 0.527, and area under the curve of 0.827 on the independent test set. This study constructs an efficient anticancer peptide prediction model based on protein language models, further advancing the application of artificial intelligence in the biomedical field and promoting the development of precision medicine and computational biology.
Machine Learning ; Antineoplastic Agents/chemistry* ; Humans ; Peptides/chemistry* ; Support Vector Machine ; Algorithms ; Computational Biology/methods* ; Neoplasms/drug therapy*

Objective:To investigate the association of serum uric acid (SUA) with the outcome in patients with acute ischemic stroke (AIS) at one year after onset.Methods:Patients with AIS admitted to the Department of Neurology, Dagang Hospital, Tianjin Binhai New Area were included retrospectively. According to the modified Rankin Scale (mRS) score at 1 year after onset, patients were divided into a good outcome group (0-2) and a poor outcome group (>2). They were also divided into a survival group and a death group based on their survival status at 1 year after onset. The clinical baseline data and laboratory tests were compared. Multivariate logistic regression analysis was used to determine the associations of SUA with poor outcome and death in patients with AIS. Results:A total of 651 patients were enrolled, including 430 males (66.1%) aged 67.5±11.7 years. Four hundred and fourteen patients (63.6%) were in the good outcome group, and 237 (36.4%) were in the poor outcome group. There were 568 patients (87.3%) in the survival group and 43 (16.7%) in the death group. Univariate analysis showed that there were differences in age, atrial fibrillation, history of stroke or transient ischemic attack, baseline National Institutes of Health Stroke Scale (NIHSS) score, and pre-admission mRS score between the poor outcome group and the good outcome group. The homocysteine, SUA, white blood cell count, and creatinine in the poor outcome group were higher than those in the good outcome group, while the red blood cell count and hemoglobin were lower than those in the good outcome group (all P<0.05). There were differences in age, history of ischemic heart disease, atrial fibrillation, history of stroke or transient ischemic attack, baseline NIHSS score, pre-admission mRS score, and stroke etiology classification between the survival group and the death group. Hemoglobin and triglycerides in the survival group were higher than those in the death group, while the white blood cell count and creatinine were lower than those in the death group (all P<0.05). Multivariate logistic regression analysis showed that SUA was an independent risk factor for poor outcome in patients with AIS (odds ratio 1.004, 95% confidence interval 1.001-1.006; P<0.01), but there was no independent correlation with death. Conclusion:Higher SUA is an independent risk factor for poor outcome at one year after onset in patients with AIS.