Objective To quantitatively assess the exposure-response association between exposure to heatwave and sudden death, estimate the attributable excess deaths, and identify potential vulnerable subgroups. Methods A time-stratified case-crossover study was conducted among residents who died from sudden death in Jiangsu Province, China between 2015 and 2021. Heatwave events in Jiangsu Province, defined using varying relative temperature thresholds and durations, were identified using temperature data from the China Meteorological Administration Land Data Assimilation System (CLDAS V2.0). Individual heatwave exposure was assessed based on each subject's residential address. The exposure-response association between heatwave and sudden death was evaluated using conditional logistic regression model combined with a Distributed Lag Nonlinear Model(DLNM). Heatwave-attributable excess deaths were estimated. Stratified analyses by sex and age were performed to assess potential effect modifications. Results Under all definitions, exposure to heatwave was significantly associated with an increased risk of sudden death, and the risk increased with the intensity of heatwave. Using the P95_3d definition (temperature exceeding the 95th percentile for ≥3 consecutive days), heatwave was significantlyassociated with a 56% increased risk of sudden death (95% CI: 31%, 86%). The population-attributable fraction of sudden death due to heatwave exposure was 1.45% (95% CI: 0.97%, 1.90%). Stratified analyses indicated no statistically significant differences in the association between heatwave exposure and sudden death across age or sex subgroups. Conclusion Heatwave exposure was associated with an increased risk of sudden death. Reducing heatwave exposure during summer may help lower the occurrence of sudden death.

ObjectiveTo improve the therapeutic effect of Buyang Huanwutang（BYHW） on diabetic kidney disease （DKD） and explore new methods for developing new Chinese medicine decoctions，we utilized 5-hydroxymethylcytosine （5hmC）-Seal sequencing technology and network pharmacology to modify BYHW. MethodsWe selected 14 diabetes mellitus （DM） patients and 15 DKD patients hospitalized in the Department of Endocrinology of Peking University Third Hospital in 2021. Circulating free DNA （cfDNA） in the patients’ plasma was sequenced. After data processing and screening， we performed temporal clustering analysis to select a DKD 5hmC gene set， which was then cross-validated with a DKD database gene set to obtain the DKD gene set. We retrieved target genes of the seven herbal components of BYHW from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP） and the Encyclopedia of Traditional Chinese Medicine （ETCM）， and performed cross-analysis with the DKD gene set to identify common genes shared by the disease and the Chinese medicines. A protein-protein interaction （PPI） network was constructed for the common genes to screen out the key genes. Chinese medicines targeting these key genes were searched against ETCM to identify removable Chinese medicines. Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis was performed on non-common DKD genes， and key genes in DKD-related pathways were selected based on machine learning. The GSE30529 dataset was used to verify the expression trends of 5hmC-modified genes and the feasibility of target genes as drug targets. TCMBank was used to search for target genes and obtain compounds targeting these genes and the corresponding Chinese medicines to construct a "key target-compound-Chinese medicine" network. Molecular docking was employed to verify the binding affinity of compounds with key targets. TCMSP and ETCM were used to search and count the candidate Chinese medicines targeting DKD-related genes， and a new decoction was formed by adding the selected Chinese medicines. A mouse model of DKD was established to examine the efficacy of the new decoction based on the mouse body mass， random blood glucose， urinary microalbumin （mALB）， serum creatinine （Scr）， and blood urea nitrogen （BUN） and by hematoxylin-eosin staining， periodic acid-Schiff staining， Masson staining， immunofluorescence assay， and Real-time PCR. ResultsThe cross-analysis results showed that the DKD gene set included 507 genes， of which 30 were target genes of BYHW. The PPI analysis indicated that the top 15% target genes regarding the degree were interleukin-6 （IL-6）， Toll-like receptor 4 （TLR4）， lactotransferrin （LTF）， lipoprotein lipase （LPL）， and sterol regulatory element-binding transcription factor 1 （SREBF1）. Persicae Semen and Pheretima in BYHW were unrelated to key genes and removed. Machine learning identified 10 potential target genes， among which TBC1 domain family member 5 （TBC1D5）， RAD51 paralog B （RAD51B）， and proteasome 20S subunit alpha 6 （PSMA6） had expression trends consistent with the GSE30529 dataset and could serve as drug targets. The "key target-compound-Chinese medicine" network and molecular docking results indicated that the compounds with good binding affinity to target proteins were arginine， glycine， myristicin， serine， and tyrosine， corresponding to 121 Chinese medicines. The top 10 Chinese medicines targeting DKD-related genes were Lycii Fructus， Ginseng Radix et Rhizoma， Dioscoreae Rhizoma， Rehmanniae Radix Praeparata， Isatidis Radix， Glehniae Radix， Ophiopogonis Radix， Allii Sativi Bulbus， Isatidis Folium， and Bolbostemmatis Rhizoma. Based on traditional Chinese medicine theory， the new decoction was obtained after removal of Persicae Semen and Pheretima and addition of Rehmanniae Radix Praeparata and Dioscoreae Rhizoma. Animal experiment results indicated that the modified BYHW improved the kidney function and inhibited renal fibrosis in DKD mice， with better effects than the original decoction. ConclusionThe BYHW modified based on 5hmC-Seal sequencing demonstrates better performance in inhibiting fibrosis and ameliorating DKD than the original decoction. This elucidates the biomedical theory behind the epigenetic modification of traditional Chinese medicine prescriptions， potentially offering new perspectives for the exploration of these prescriptions

ObjectiveTo improve the therapeutic effect of Buyang Huanwutang（BYHW） on diabetic kidney disease （DKD） and explore new methods for developing new Chinese medicine decoctions，we utilized 5-hydroxymethylcytosine （5hmC）-Seal sequencing technology and network pharmacology to modify BYHW. MethodsWe selected 14 diabetes mellitus （DM） patients and 15 DKD patients hospitalized in the Department of Endocrinology of Peking University Third Hospital in 2021. Circulating free DNA （cfDNA） in the patients’ plasma was sequenced. After data processing and screening， we performed temporal clustering analysis to select a DKD 5hmC gene set， which was then cross-validated with a DKD database gene set to obtain the DKD gene set. We retrieved target genes of the seven herbal components of BYHW from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP） and the Encyclopedia of Traditional Chinese Medicine （ETCM）， and performed cross-analysis with the DKD gene set to identify common genes shared by the disease and the Chinese medicines. A protein-protein interaction （PPI） network was constructed for the common genes to screen out the key genes. Chinese medicines targeting these key genes were searched against ETCM to identify removable Chinese medicines. Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis was performed on non-common DKD genes， and key genes in DKD-related pathways were selected based on machine learning. The GSE30529 dataset was used to verify the expression trends of 5hmC-modified genes and the feasibility of target genes as drug targets. TCMBank was used to search for target genes and obtain compounds targeting these genes and the corresponding Chinese medicines to construct a "key target-compound-Chinese medicine" network. Molecular docking was employed to verify the binding affinity of compounds with key targets. TCMSP and ETCM were used to search and count the candidate Chinese medicines targeting DKD-related genes， and a new decoction was formed by adding the selected Chinese medicines. A mouse model of DKD was established to examine the efficacy of the new decoction based on the mouse body mass， random blood glucose， urinary microalbumin （mALB）， serum creatinine （Scr）， and blood urea nitrogen （BUN） and by hematoxylin-eosin staining， periodic acid-Schiff staining， Masson staining， immunofluorescence assay， and Real-time PCR. ResultsThe cross-analysis results showed that the DKD gene set included 507 genes， of which 30 were target genes of BYHW. The PPI analysis indicated that the top 15% target genes regarding the degree were interleukin-6 （IL-6）， Toll-like receptor 4 （TLR4）， lactotransferrin （LTF）， lipoprotein lipase （LPL）， and sterol regulatory element-binding transcription factor 1 （SREBF1）. Persicae Semen and Pheretima in BYHW were unrelated to key genes and removed. Machine learning identified 10 potential target genes， among which TBC1 domain family member 5 （TBC1D5）， RAD51 paralog B （RAD51B）， and proteasome 20S subunit alpha 6 （PSMA6） had expression trends consistent with the GSE30529 dataset and could serve as drug targets. The "key target-compound-Chinese medicine" network and molecular docking results indicated that the compounds with good binding affinity to target proteins were arginine， glycine， myristicin， serine， and tyrosine， corresponding to 121 Chinese medicines. The top 10 Chinese medicines targeting DKD-related genes were Lycii Fructus， Ginseng Radix et Rhizoma， Dioscoreae Rhizoma， Rehmanniae Radix Praeparata， Isatidis Radix， Glehniae Radix， Ophiopogonis Radix， Allii Sativi Bulbus， Isatidis Folium， and Bolbostemmatis Rhizoma. Based on traditional Chinese medicine theory， the new decoction was obtained after removal of Persicae Semen and Pheretima and addition of Rehmanniae Radix Praeparata and Dioscoreae Rhizoma. Animal experiment results indicated that the modified BYHW improved the kidney function and inhibited renal fibrosis in DKD mice， with better effects than the original decoction. ConclusionThe BYHW modified based on 5hmC-Seal sequencing demonstrates better performance in inhibiting fibrosis and ameliorating DKD than the original decoction. This elucidates the biomedical theory behind the epigenetic modification of traditional Chinese medicine prescriptions， potentially offering new perspectives for the exploration of these prescriptions

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

OBJECTIVE To investigate the improvement effect and potential mechanism of Qingxue xiaozhi jiangtang formula on insulin resistance （IR） in type 2 diabetes mellitus （T2DM） rats. METHODS T2DM rat model was established by intraperitoneal injection of 30 mg/kg streptozotocin combined with high-fat and high-sugar diet. The rats were randomly divided into normal control group， model group， Qingxue xiaozhi jiangtang formula low-dose and high-dose groups （6.525， 13.05 g/kg， calculated by raw material） and metformin group （positive control， 0.18 g/kg）， with 8 rats in each group. Administration groups were given relevant medicine intragastrically； normal control group and model group were given constant volume of normal saline intragastrically， once a day， for consecutive 6 weeks. Body mass and fasting blood glucose （FBG） were determined， and oral glucose tolerance test was conducted. Serum fasting insulin （FINS） level was measured to calculate the insulin resistance index （HOMA-IR） and insulin sensitivity index （ISI）. Additionally， the level of serum lipids， liver function， oxidative stress indicators and inflammatory factors were assessed. The phosphorylation levels of kinase R-like endoplasmic reticulum kinase （PERK） and forkhead box O1 （FOXO1） protein in liver tissue of rats were determined. RESULTS Compared with model group， the body weight， ISI， the levels of high-density lipoprotein cholesterol and superoxide dismutase were increased significantly in Qingxue xiaozhi jiangtang formula high-dose group and metformin group （P＜0.05）； FBG， blood glucose level at 120 minutes of glucose loading， area under the curve of glucose， FINS， HOMA-IR， low-density lipoprotein cholesterol， total cholesterol， triglyceride， alanine transaminase， aspartate transaminase， alkaline phosphatase， malondialdehyde， interleukin-6， tumor necrosis factor-α， and C-reactive protein levels were significantly reduced （P＜ Δ0.05）； the pathological damage of liver tissue had significantlyimproved， and the phosphorylation levels of PERK and FOXO1 proteins in liver tissue were significantly decreased （P＜0.05）. CONCLUSIONS Qingxue xiaozhi jiangtang formula can regulate glucose and lipid metabolism， inflammation factor and oxidative stress levels， and alleviate insulin resistance in T2DM rats. Its mechanism of action may be related to the inhibition of the PERK/FOXO1 signaling pathway.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

Objective: To analyze the status and trends of the disease burden of periodontal disease among women of reproductive age (15-49 years) in China from 1990 to 2021, and to provide a reference for the development of periodontal disease prevention and control strategies for women of reproductive age. Methods: Using the global burden of disease (GBD) data from 1990 to 2021, this study investigated the periodontal disease burden among women of reproductive age, including prevalence, incidence, disability-adjusted life years (DALYs), DALY rates, and their corresponding standardized indicators. Joinpoint 5.2.0.0 software was used for time trend analysis of DALYs, age-specific DALY rates, and annual average percentage change (AAPC) values. A log-linear regression model was used to test trends for DALYs and DALY rates. Results: Compared with 1990, the prevalence and incidence of periodontal disease among Chinese women in 2021 increased by 45.67% (per 100,000 people) and 29.29% (per 100,000 people), respectively. The distribution of periodontal disease among women (15-49 years) showed a continuous and rapid upward trend, with the growth rate increasing rapidly with age. The number of cases increased the fastest in the 45-49 age group, and the prevalence increased the fastest in the 35-44 age group. The incidence of periodontal disease continued to rise with age, with the fastest increase in the 35-44 age group among women of reproductive age. The Joinpoint regression model results showed that periodontal disease led to an expanding trend in the disease burden among women of reproductive age in China, with an AAPC of DALYs = 1.20% and an AAPC of DALY rate = 1.25% (P<0.001). Conclusion The periodontal disease burden among Chinese women aged 15-49 years showed a gradually increasing trend from 1990 to 2021.

Direct compression is an ideal method for tablet preparation, but it requires the powder's high functional properties. The functional properties of the powder during compression directly affect the quality of the tablet. 15 parameters such as Py, FES-8KN, FES-12KN, FES-16KN, CR-8KN, CR-12KN, and CR-16KN were used as the characteristic variables in this paper. Unsupervised learning methods like principal component analysis, cluster analysis, and factor analysis were applied to analyze and classify the compression behavior data of 36 traditional Chinese medicine powders. The results showed that both different dimensionality reduction classification methods could effectively differentiate the compression behavior characteristics of 36 traditional Chinese medicine compound powders. The hierarchical cluster analysis results showed a better agreement with the actual compression phenomena of the powders, where group 1 was high elasticity and low compressibility, group 2 was easily compressed and hard to break, group 3 was excellent compressibility and compactibility. This study is expected to provide references and ideas for predicting the behavior of traditional Chinese medicine powders and the screening of tablet formulations.