Background China faces a growing burden of chronic non-communicable diseases (NCDs), particularly in resource-limited rural areas with extreme climatic conditions. To address this challenge, the National Chronic Disease Prevention and Control Initiative, implemented at the provincial level in Heilongjiang Province (2017–2025). However, evidence on the effectiveness of subnational prevention strategies in such settings remains scarce. This study aimed to evaluate the impact of this policy on chronic disease prevalence trends in a cold rural region. Methods We conducted a longitudinal interrupted time series analysis using data from a natural population cohort in Mingshui County (n = 10694 participants, mean age of 57·98 ± 8·80 years, 61·75% female) from 2015 to 2025. Annual prevalence, proportional distribution, and year-over-year growth rates for eight major categories of chronic diseases were calculated. Segmented regression models assessed policy effects on prevalence trends, while network analysis visualized multimorbidity patterns. Results The overall prevalence of chronic diseases increased from 2015 to 2025, but policy implementation in 2019 significant slowed the growth trajectory (slope change = -0·542% per year, p < 0·05). Disease-specific trends were heterogeneous: cardiovascular disease maintained the highest prevalence (2015: 23·1%; 2025: 67·0%), its annual growth rate demonstrated the most significant deceleration post-policy (difference = -5·536%), while respiratory diseases showed accelerated growth (difference = + 0·499%). Multimorbidity prevalence increased persistently, with a core cluster of cardiovascular, endocrine/metabolic, digestive, and respiratory diseases forming the central pattern of disease co-occurrence. Conclusions The provincial chronic disease prevention initiative effectively curbed the growth of certain diseases like cardiovascular conditions, but its impact on respiratory diseases and multimorbidity remains limited. These findings underscore the necessity for more targeted interventions addressing region-specific risk factors and multimorbidity patterns in cold rural settings. This study provides critical evidence for optimizing chronic disease control strategies in similar high-risk environments globally.

Background:Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), as a common chronic liver condition globally, is experiencing an increasing incidence rate which poses significant health risks. Despite this, the detailed mechanisms underlying the disease's onset and progression remain poorly understood. In this study, we aim to identify effective diagnostic biomarkers for MASLD using microarray data combined with machine learning techniques, which will aid in further understanding the pathogenesis of MASLD. Methods:We collected six datasets from the Gene Expression Omnibus (GEO) database, using five of them as training sets and one as a validation set. We employed three machine learning methods-LASSO, SVM, and Random Forest (RF)-to identify hub genes associated with MASLD. These genes were further validated using the external dataset GSE164760. Additionally, functional enrichment analysis, immune infiltration analysis, and immune function analysis were conducted. A TF-miRNA-mRNA network was constructed, and single-cell RNA sequencing was used to determine the distribution of key genes within key cell clusters. Finally, the expression of the key genes was further validated using the palmitic acid-induced AML-12 cell line and the MCD mouse model. Results:In this study, through differential gene expression (DEGs) analysis and machine learning techniques, we successfully identified 10 hub genes. Among these, the key gene EGR1 was validated and screened using an external dataset, with an area under the curve (AUC) of 0.882. Enrichment analyses and immune infiltration assessments revealed multiple pathways involving EGR1 in the pathogenesis and progression of MASLD, showing significant correlations with various immune cells. Furthermore, additional cellular experiments and animal model validations confirmed that the expression trends of EGR1 are highly consistent with our analytical findings. Conclusion:Our research has confirmed EGR1 as a key gene in MASLD, providing novel insights into the disease's pathogenesis and identifying new therapeutic targets for its treatment.

Changes in myocardial fat in addition to changes in cardiac structure and function have not been accurately evaluated in obese patients following surgery. Forty-four obese patients who underwent sleeve gastrectomy and completed preoperative and postoperative cardiac magnetic resonance imaging (CMR) before surgery and at 1, 3, and 6 months after surgery were enrolled, and their clinical and laboratory data were collected. The differences and correlations between clinical, laboratory, and CMR parameters between the preoperative and postoperative groups were analysed. The left ventricular mass (LVM), left ventricle cardiac output (LVCO), pericardial adipose tissue volume (PATV), and myocardial proton density fat fraction (M-PDFF) decreased after surgery (all P < 0.05). The left ventricle global longitudinal strain increased at 6 months after surgery (P = 0.004). A decrease in BMI was positively correlated with the LVCO (r = 0.58, P < 0.001) at 3 months after surgery and was positively correlated with the LVM and PATV (r = 0.54, P < 0.05) at 6 months after surgery. Six months after surgery, the changes in PATV were positively correlated with the changes in triglycerides (r = 0.61, P < 0.01). There was a moderately positive correlation between the decrease in the LVM and PATV (r = 0.54 0.71, P < 0.02) after surgery. After surgery, the cardiac structure and function of obese patients significantly improved, the PATV and M-PDFF decreased, and there was a correlation between the structure and function of the heart and several clinical and laboratory indicators.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease, influenced by both environmental and genetic factors. Single nucleotide polymorphism (SNP) in the human genome may influence the risk of developing COPD and the response to treatment. We assessed the effects of gene polymorphism of inflammatory and immune-active factors and gene-environment interaction on risk of COPD in middle-aged and older Chinese individuals. In this community-based case–control study, 471 patients with COPD and 485 controls aged 40–76 years in Heilongjiang Province, China were included. Face-to-face interviews, lung function tests, and multiplex polymerase chain reaction were used to obtain data. Logistic regression model, generalized multifactor dimensionality reduction and crossover analysis were used to analyse the effects of SNPs, gene–gene interactions, and gene-environment interactions on COPD. CRP gene[rs1130864-A allele (OR, 1.77; 95

Parkinson's disease (PD) is a neurodegenerative disease, and inflammation is a key factor in the progression of PD. S100A9 mediates pyroptosis and implicates in various diseases including PD. Pyroptosis, an emerging form of programmed cell death, usually causes cell rupture and death via an inflammatory response. α-Lipoic acid (α-ALA), a cellular coenzyme, participates in anti-inflammatory and antioxidant processes. Although its role in PD has been confirmed, but the exact mechanism of its anti-inflammatory effect remains unclear. In our research, we examined the potential mechanisms of pyroptosis mediated by S100A9 in PD and the neuroprotective effects of α-ALA. We used 6-hydroxydopamine (6-OHDA) to induce SH-SY5Y cells in vitro and in C57BL/6 mice in vivo. The cell viability of SH-SY5Y cells confirmed the neuroprotective effect of α-ALA. Proteomics analysis indicated that S100A9 was involved in 6-OHDA-mediated neuronal injury, while α-ALA could inhibit. We found that α-ALA ameliorated PD symptoms induced by 6-OHDA and decreased the levels of NLRP3 inflammasome, Gasdermin D, and IL-1β, which are major hallmarks of pyroptosis. Furthermore, our research demonstrated that α-ALA mitigated cell injury by suppressing NLRP3-dependent pyroptosis mediated by S100A9. In brief, pyroptosis is pivotal in PD, while α-ALA protects dopaminergic neurons by suppressing pyroptosis mediated through the NLRP3 inflammasome, directly reducing S100A9, and subsequently inhibiting the NLRP3/Gasdermin D signaling pathways. Our results collectively suggest that suppressing S100A9-mediated pyroptosis and administering α-ALA may represent a novel approach in treating of PD.

Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease worldwide. Cuproptosis has recently been reported as a form of cell death that appears to drive the progression of a variety of diseases. This study aimed to explore cuproptosis-related molecular clusters and construct a prediction model. The gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The associations between molecular clusters of cuproptosis-related genes and immune cell infiltration were investigated using 50 NAFLD samples. Furthermore, cluster-specific differentially expressed genes were identified by the WGCNA algorithm. External datasets were used to verify and screen feature genes, and nomograms, calibration curves and decision curve analysis (DCA) were performed to verify the performance of the prediction model. Finally, a NAFLD-diet mouse model was constructed to further verify the predictive analysis, thus providing new insights into the prediction of NAFLD clusters and risks. The role of cuproptosis in the development of non-alcoholic fatty liver disease and immune cell infiltration was explored. Non-alcoholic fatty liver disease was divided into two cuproptosis-related molecular clusters by unsupervised clustering. Three characteristic genes (ENO3, SLC16A1 and LEPR) were selected by machine learning and external data set validation. In addition, the accuracy of the nomogram, calibration curve and decision curve analysis in predicting NAFLD clusters was also verified. Further animal and cell experiments confirmed the difference in their expression in the NAFLD mouse model and Mouse hepatocyte cell line. The present study explored the relationship between non-alcoholic fatty liver disease and cuproptosis, providing new ideas and targets for individual treatment of the disease.

There is a correlation between IBD and breast cancer according to previous observational studies. However, so far there is no evidence to support if there is a causal relationship between these 2 diseases. We acquired comprehensive Genome-Wide Association Study (GWAS) summary data on IBD (including ulcerative colitis [UC] and Crohn disease [CD]) as well as breast cancer of completely European descent from the IEU GWAS database. The estimation of bidirectional causality between IBD (including UC and CD) and breast cancer was achieved through the utilization of 2-sample Mendelian randomization (MR). The MR results were also assessed for any potential bias caused by heterogeneity and pleiotropy through sensitivity analyses. Our study found a bidirectional causal effect between IBD and breast cancer. Genetic susceptibility to IBD was associated with an increased risk of breast cancer (OR = 1.053, 95% CI: 1.016-1.090, P = .004). Similarly, the presence of breast cancer may increase the risk of IBD (OR = 1.111, 95% CI: 1.035-1.194, P = .004). Moreover, the bidirectional causal effect between IBD and breast cancer can be confirmed by another GWAS of IBD. Subtype analysis showed that CD was associated with breast cancer (OR = 1.050, 95% CI: 1.020-1.080, P < .001), but not UC and breast cancer. There was a suggestive association between breast cancer and UC (OR = 1.106, 95% CI: 1.011-1.209, P = .028), but not with CD. This study supports a bidirectional causal effect between IBD and breast cancer. There appear to be considerable differences in the specific associations of UC and CD with AD. Understanding that IBD including its specific subtypes and breast cancer constitute common risk factors can contribute to the clinical management of both diseases.

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disease worldwide. Chronic activation of endoplasmic reticulum stress (ERS) in hepatocytes may promote the development of NAFLD, yet endoplasmic reticulum stress-related genes (ERSGs) have not been studied in NAFLD. Our aim is to study the relationship between ERSGs and the immune microenvironment of NAFLD patients and to construct predictive models. We screened 48 endoplasmic reticulum stress-related differentially expressed genes (ERSR-DEGs) using data from two GEO datasets and the GeneCards database. Enrichment analysis revealed that ERSR-DEGs are closely associated with immune-related pathways and functions. The immune infiltration profile of NAFLD was obtained by single sample gene set enrichment analysis (ssGSEA). There were significant differences in immune cell infiltration and immune function between NAFLD group and control group. Using 113 NAFLD samples, we explored two molecular clusters based on ERSR-DEGs. A five-gene SVM model was selected as the best machine learning model, and a nomogram based on five-gene SVM model showed good predictive efficiency. The mRNA expression levels of POR, PPP1R15A, FOS and FAS were significantly different between NAFLD mice and healthy mice. In conclusion, ERS is closely associated with the development of NAFLD. We established a promising and SVM-based predictive model to assess the risk of disease in patients with ERS subtypes and NAFLD.

While the TyG index has been studied in relation to stroke risk, there is a lack of research integrating fat distribution indicators like Body Roundness Index (BRI) and Fat Mass Index (FMI). Additionally, comparative studies across multiple regions are scarce. This study investigates the association between obesity-related parameters and stroke incidence, examining the mediation effects of multimorbidity, using data from rural areas in China and the United Kingdom. This cohort study included 60,685 participants (6,980 from China and 53,705 from UK). The obesity-related parameters were calculated using established formulas. The TyG index was determined as ln [TG (mg/dL) × GLU (mg/dL) / 2]. Additionally, composite indices were created by multiplying the TyG index by BMI, WC, FMI, and RBI to assess obesity-related risks. Cox regression analyses were employed on the relationship between Triglyceride Glucose index related parameters and stroke risk. Multiple mediation analysis was applied to assess the contributions of multimorbidity to obesity indicators in stroke occurrence. After excluding those who developed stroke within two years of enrollment, the Chinese cohort (6,638 subjects, median follow-up 4.33 years) had 237 ischemic and 21 hemorrhagic strokes. The UK cohort (53,631 subjects, median follow-up 13.85 years) had 742 ischemic and 316 hemorrhagic strokes. Chinese residents had lower BMI but higher visceral obesity (BRI), higher prevalence of multimorbidity, and higher stroke incidence compared to UK residents. Cox analyses demonstrated significant associations between BMI/TyG indices and ischemic stroke in both Chinese and UK populations, which diminished after adjusting for multimorbidity. In the Chinese rural cohort, only TyG-BRI (HR:1.13, 95

Objective The factors related to the changes in the liver and abdominal adipose tissue during the rapid weight loss after bariatric surgery remain uncertain. Methods This study included 44 participants who had undergone sleeve gastrectomy. The study aimed to analyze changes and correlations of body weight (BW), laboratory tests, and magnetic resonance imaging (MRI) indicators of the liver and abdominal adipose tissue conducted before and after bariatric surgery at 1, 3, and 6 months. Results Following a rapid weight loss within 6 months of surgery, there was a concurrent decrease in blood glucose, blood lipids, and fat content of the liver and abdomen and the changes showed a correlation. The change of BW (ΔBW) was positively correlated with the change of hepatic proton density fat fraction (ΔPDFF) in one and three months after surgery and was positively correlated with the change of abdominal visceral fat area (ΔAVFA) in six months after surgery, (P<0.05). In one month after surgery, ΔPDFF was positively correlated with the change of aspartate aminotransferase (ΔAST), change of alanine aminotransferase (ΔALT), and change of triglyceride glucose (ΔTYG) index (P<0.05). ΔPDFF was positively correlated with the change of hepatic native T1 values (P<0.001) and was moderately negatively correlated with the change of hepatic apparent diffusion coefficient (ΔADC) values in three months after surgery (P<0.05). Conclusion ΔBW can serve as an indirect indicator for evaluating changes in liver fat fraction at 1 and 3 months after bariatric surgery and indicative of changes in visceral fat 6 months after surgery. ΔPDFF was positively correlated with ΔAST, ΔALT and ΔTYG index in 1 months after surgery.

Abstract Non-alcoholic Fatty Liver Disease (NAFLD), prevalent among adults, has become a dominant chronic liver condition worldwide, with a rising incidence of liver cirrhosis. The progression of NAFLD is critically influenced by Neutrophil Extracellular Traps (NETs), which play a key role in its pathogenesis. However, the specific functions of NETs-related genes within NAFLD necessitate further in-depth research. Our team utilized advanced methodologies including AddModuleScore, ssGSEA, and WGCNA for gene screening, identifying NETs-linked genes in single-cell and bulk transcriptomic data. Through algorithms such as Random Forest, Support Vector Machine, Least Absolute Shrinkage and Selection Operator, and Selector Operator, we identified ZFP36L2 and PHLDA1 as significant hub genes. Their role in NAFLD diagnosis was validated using the training dataset GSE164760 and further confirmed in an animal model. The study pinpointed 116 NET-associated genes, predominantly involved in immune and metabolic pathways. Notably, PHLDA1 and ZFP36L2 were determined as hub genes via machine learning techniques, contributing to a predictive model. These genes are involved in inflammatory and metabolic processes, with single-cell RNA sequencing (scRNA-seq) revealing distinct cellular communication patterns based on their expression. In conclusion, this research elucidates the molecular characteristics of NET-associated genes in NAFLD, identifying PHLDA1 and ZFP36L2 as potential biomarkers. By exploring their roles in the hepatic microenvironment, our findings offer significant insights for diagnosing and managing NAFLD, ultimately aiming to enhance patient outcomes.

Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes.

Aims: Non-alcoholic fatty liver disease (NAFLD) has risen as a significant global public health issue, for which vertical sleeve gastrectomy (VSG) has become an effective treatment method. The study sought to elucidate the processes through which PIM1 mitigates the advancement of NAFLD. The Pro -viral integration site for Moloney murine leukemia virus 1 (PIM1) functions as a serine/threonine kinase. Bioinformatics analysis revealed that reduced PIM1 expression in NAFLD. Methods: To further prove the role of PIM1 in NAFLD, an in-depth in vivo experiment was performed, in which male C57BL/6 mice were randomly grouped to receive a normal or high -fat diet for 24 weeks. They were operated or delivered the loaded adeno-associated virus which the PIM1 was overexpressed (AAV-PIM1). In an in vitro experiment, AML12 cells were treated with palmitic acid to induce hepatic steatosis. Key findings: The results revealed that the VSG surgery and virus delivery of mice alleviated oxidative stress, and apoptosis in vivo. For AML12 cells, the levels of oxidative stress, apoptosis, and lipid metabolism were reduced via PIM1 upregulation. Moreover, ML385 treatment resulted in the downregulation of the NRF2/HO-1/NQO1 signaling cascade, indicating that PIM1 mitigates NAFLD by targeting this pathway. Significance: PIM1 alleviated mice liver oxidative stress and NAFLD induced by high -fat diet by regulating the NRF2/HO-1/NQO1 signaling Pathway.

Ferroptosis plays a crucial role in the development of non-alcoholic fatty liver disease (NAFLD). In this study, we aimed to use a comprehensive bioinformatics approach and experimental validation to identify and verify potential ferroptosis-related genes in NAFLD. We downloaded the microarray datasets for screening differentially expressed genes (DEGs) and identified the intersection of these datasets with ferroptosis-related DEGs from the Ferroptosis database. Subsequently, ferroptosis-related DEGs were obtained using SVM analysis; the LASSO algorithm was then used to identify six marker genes. Furthermore, the CIBERSORT algorithm was used to estimate the proportion of different types of immune cells. Subsequently, we constructed drug regulatory networks and ceRNA regulatory networks. We identified six genes as marker genes for NAFLD, demonstrating their robust diagnostic abilities. Subsequent functional enrichment analysis results revealed that these marker genes were associated with multiple diseases and play a key role in NAFLD via the regulation of immune response and amino acid metabolism, among other pathways. The expression of hepatic EGR1, IL-6, SOCS1, and NR4A1 was significantly downregulated in the NAFLD model. Our findings provide new insights and molecular clues for understanding and treating NAFLD. Further studies are needed to assess the diagnostic potential of these markers for NAFLD.

成人巨结肠虽然临床少见,但可严重威胁患者的身心健康和生命安全,其最常见的临床表现是腹胀和便秘.成人巨结肠按照病因可分为成人先天性巨结肠、神经节细胞缺乏症、特发性巨结肠、中毒性巨结肠、医源性巨结肠以及急性假性结肠梗阻综合征等类型.由于早期临床症状不典型以及人们对该病认识的不足,部分患者在确诊时已错失最佳治疗时机.手术是成人巨结肠最有效的治疗措施,本文结合国内外文献对成人巨结肠的外科诊疗现状进行总结,以期为本病的临床诊疗提供参考.

Background: Afatinib is an irreversible epidermal growth factor receptor tyrosine kinase inhibitor, and it plays a role in hepatocellular carcinoma (LIHC). This study aimed to screen a key gene associated with afatinib and identify its potential candidate drugs. Methods: We screened afatinib-associated differential expressed genes based on transcriptomic data of LIHC patients from The Cancer Genome Atlas, Gene Expression Omnibus, and the Hepatocellular Carcinoma Database (HCCDB). By using the Genomics of Drug Sensitivity in Cancer 2 database, we determined candidate genes using analysis of the correlation between differential genes and half-maximal inhibitory concentration. Survival analysis of candidate genes was performed in the TCGA dataset and validated in HCCDB18 and GSE14520 datasets. Immune characteristic analysis identified a key gene, and we found potential candidate drugs using CellMiner. We also evaluated the correlation between the expression of ADH1B and its methylation level. Furthermore, Western blot analysis was performed to validate the expression of ADH1B in normal hepatocytes LO2 and LIHC cell line HepG2. Results: We screened eight potential candidate genes (ASPM, CDK4, PTMA, TAT, ADH1B, ANXA10, OGDHL, and PON1) associated with afatinib. Patients with higher ASPM, CDK4, PTMA, and TAT exhibited poor prognosis, while those with lower ADH1B, ANXA10, OGDHL, and PON1 had unfavorable prognosis. Next, ADH1B was identified as a key gene negatively correlated with the immune score. The expression of ADH1B was distinctly downregulated in tumor tissues of pan-cancer. The expression of ADH1B was negatively correlated with ADH1B methylation. Small-molecule drugs panobinostat, oxaliplatin, ixabepilone, and seliciclib were significantly associated with ADH1B. The protein level of ADH1B was significantly downregulated in HepG2 cells compared with LO2 cells. Conclusion: Our study provides ADH1B as a key afatinib-related gene, which is associated with the immune microenvironment and can be used to predict the prognosis of LIHC. It is also a potential target of candidate drugs, sharing a promising approach to the development of novel drugs for the treatment of LIHC.

Objective: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disease in the world, and its pathogenesis is not fully understood. Disulfidptosis is the most recently reported form of cell death and may be associated with NAFLD progression. Our study aimed to explore the molecular clusters associated with disulfidptosis in NAFLD and to construct a predictive model.Methods: First, we analyzed the expression profile of the disulfidptosis regulators and immune characteristics in NAFLD. Using 104 NAFLD samples, we investigated molecular clusters based on differentially expressed disulfidptosis-related genes, along with the related immune cell infiltration. Cluster-specific differentially expressed genes were then identified by using the WGCNA method. We also evaluated the performance of four machine learning models before choosing the optimal machine model for diagnosis. Nomogram, calibration curves, decision curve analysis, and external datasets were used to confirm the prediction effectiveness. Finally, the expression levels of the biomarkers were assessed in a mouse model of a high-fat diet.Results: Two differentially expressed DRGs were identified between healthy and NAFLD patients. We revealed the expression profile of DRGs in NAFLD and the correlation with 22 immune cells. In NAFLD, two clusters of molecules connected to disulfidptosis were defined. Significant immunological heterogeneity was shown by immune infiltration analysis among the various clusters. A significant amount of immunological infiltration was seen in Cluster 1. Functional analysis revealed that Cluster 1 differentially expressed genes were strongly linked to energy metabolism and immune control. The highest discriminatory performance was demonstrated by the SVM model, which had a higher area under the curve, relatively small residual and root mean square errors. Nomograms, calibration curves, and decision curve analyses were used to show how accurate the prediction of NAFLD was. Further analysis revealed that the expression of three model-related genes was significantly associated with the level of multiple immune cells. In animal experiments, the expression trends of DDO, FRK and TMEM19 were consistent with the results of bioinformatics analysis.Conclusion: This study systematically elucidated the complex relationship between disulfidptosis and NAFLD and developed a promising predictive model to assess the risk of disease in patients with disulfidptosis subtypes and NAFLD.

Gynecological cancer poses a serious threat to women's health. Chemotherapy-based systemic therapy plays a crucial role in the treatment of gynecological cancers. Many systemic therapeutic drugs are metabolized in the kidneys. Therefore, normal renal function is a prerequisite for gynecological tumor patients to complete the full course of systematic treatment and provide a guarantee for achieving an ideal prognosis. Chronic kidney disease often places restrictions on systematic treatment to different extents, such as influencing drug pharmacokinetics, increasing drug toxicity, and the risk of adverse drug reactions. Unfortunately, women undergoing renal replacement have a higher risk of developing gynecological cancers. This article summarizes the current knowledge on systemic treatment drugs for patients with gynecological cancer undergoing dialysis. We discuss the optimal choice of the systematic therapeutic protocol, administration of form and dosage, and window of chemotherapy during hemodialysis sessions to ensure both effectiveness and safety in gynecological cancer patients.

Objective:To recognize the spatial and temporal characteristics of iodine deficiency disorders (IDD), China national IDD surveillance data for the years of 1995-2018 were analyzed.Methods:Time series analysis was used to describe and predict the IDD related indicators, and spatial analysis was used to analyze the spatial distribution of salt iodine levels.Results:In China, the median urinary iodine concentration increased in 1995-1997, then decreased to adequate levels, and are expected to remain appropriate in 2019-2022. The goiter rate continually decreased and is expected to be maintained at a low level. Since 2002, the coverage rates of iodized salt and the consumption rates of qualified iodized salt (the percentage of qualified iodized salt in all tested salt) increased and began to decline in 2012; they are expected to continue to decrease. Spatial epidemiological analysis indicated a positive spatial correlation in 2016-2018 and revealed feature regarding the spatial distribution of salt related indicators in coastal areas and areas near iodine-excess areas.Conclusions:Iodine nutrition in China showed gradual improvements. However, a recent decline has been observed in some areas following changes in the iodized salt supply in China. In the future, more regulations regarding salt management should be issued to strengthen IDD control and prevention measures, and avoid the recurrence of IDD.