EasyNAT MTC Assay: a Rapid Method to Detect Mycobacterium Tuberculosis in Respiratory Specimens.

BACKGROUND: This study aimed to effectively evaluate the diagnostic performance of the EasyNAT Mycobacterium tuberculosis complex (MTC) assay for tuberculosis (TB) detection from sputum. METHODS: The retrospectively analyzed data was collected from September 1, 2021, to November 1, 2023, in our hospital. RESULTS: Forty EasyNAT-positive sputum specimens were simultaneously detected using the GeneXpert MTB/ rifampicin (RIF) assay. The concordance rate between the EasyNAT and GeneXpert MTB/RIF assays was 100%. CONCLUSIONS: Because of the complexity of detecting RIF resistance data information, the rapid EasyNAT system used in conjunction with GeneXpert might be a better choice for the detection of TB in hospitals.

Advanced nanomedicines and immunotherapeutics to treat respiratory diseases especially COVID-19 induced thrombosis.

Immunotherapy and associated immune regulation strategies gained huge attraction in order to be utilized for treatment and prevention of respiratory diseases. Engineering specifically nanomedicines can be used to regulate host immunity in lungs in the case of respiratory diseases including coronavirus disease 2019 (COVID-19) infection. COVID-19 causes pulmonary embolisms, thus new therapeutic options are required to target thrombosis, as conventional treatment options are either not effective due to the complexity of the immune-thrombosis pathophysiology. In this review, we discuss regulation of immune response in respiratory diseases especially COVID-19. We further discuss thrombosis and provide an overview of some antithrombotic nanoparticles, which can be used to develop nanomedicine against thrombo-inflammation induced by COVID-19 and other respiratory infectious diseases. We also elaborate the importance of immunomodulatory nanomedicines that can block pro-inflammatory signalling pathways, and thus can be recommended to treat respiratory infectious diseases.

Association between extremely high prognostic nutritional index and all-cause mortality in patients with coronary artery disease: secondary analysis of a prospective cohort study in China.

OBJECTIVES: Decreased prognostic nutritional index (PNI) was associated with adverse outcomes in many clinical diseases. This study aimed to evaluate the relationship between baseline PNI value and adverse clinical outcomes in patients with coronary artery disease (CAD). DESIGN: The Personalized Antiplatelet Therapy According to CYP2C19 Genotype in Coronary Artery Disease (PRACTICE) study, a prospective cohort study of 15 250 patients with CAD, was performed from December 2016 to October 2021. The longest follow-up period was 5 years. This study was a secondary analysis of the PRACTICE study. SETTING: The study setting was Xinjiang Medical University Affiliated First Hospital in China. PARTICIPANTS: Using the 50th and 90th percentiles of the PNI in the total cohort as two cut-off limits, we divided all participants into three groups: Q1 (PNI <51.35, n = 7515), Q2 (51.35 ≤ PNI < 59.80, n = 5958) and Q3 (PNI ≥ 59.80, n = 1510). The PNI value was calculated as 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (per mm3). PRIMARY OUTCOME: The primary outcome measure was mortality, including all-cause mortality (ACM) and cardiac mortality (CM). RESULTS: In 14 983 participants followed for a median of 24 months, a total of 448 ACM, 333 CM, 1162 major adverse cardiovascular events (MACE) and 1276 major adverse cardiovascular and cerebrovascular events (MACCE) were recorded. The incidence of adverse outcomes was significantly different among the three groups (p <0.001). There were 338 (4.5%), 77 (1.3%) and 33 (2.2%) ACM events in the three groups, respectively. A restricted cubic spline displayed a J-shaped relationship between the PNI and worse 5-year outcomes, including ACM, CM, MACE and MACCE. After adjusting for traditional cardiovascular risk factors, we found that only patients with extremely high PNI values in the Q3 subgroup or low PNI values in the Q1 subgroup had a greater risk of ACM (Q3 vs Q2, HR: 1.617, 95% CI 1.012 to 2.585, p=0.045; Q1 vs Q2, HR=1.995, 95% CI 1.532 to 2.598, p <0.001). CONCLUSION: This study revealed a J-shaped relationship between the baseline PNI and ACM in patients with CAD, with a greater risk of ACM at extremely high PNI values. TRIAL REGISTRATION NUMBER: NCT05174143.

Feasibility and limitations of combined treatment for lateral pelvic lymph node metastases in rectal cancer.

Colorectal cancer ranks among the most commonly diagnosed cancers globally, and is associated with a high rate of pelvic recurrence after surgery. In efforts to mitigate recurrence, pelvic lymph node dissection (PLND) is commonly advocated as an adjunct to radical surgery. Neoadjuvant chemoradiotherapy (NACRT) is a therapeutic approach employed in managing locally advanced rectal cancer, and has been found to increase the survival rates. Chua et al have proposed a combination of NACRT with selective PLND for addressing lateral pelvic lymph node metastases in rectal cancer patients, with the aim of reducing recurrence and improving survival outcomes. Nevertheless, certain studies have indicated that the addition of PLND to NACRT and total mesorectal excision did not yield a significant reduction in local recurrence rates or improvement in survival. Consequently, meticulous patient selection and perioperative chemotherapy may prove indispensable in ensuring the efficacy of PLND.

Machine learning model for cardiovascular disease prediction in patients with chronic kidney disease.

Introduction: Cardiovascular disease (CVD) is the leading cause of death in patients with chronic kidney disease (CKD). This study aimed to develop CVD risk prediction models using machine learning to support clinical decision making and improve patient prognosis. Methods: Electronic medical records from patients with CKD at a single center from 2015 to 2020 were used to develop machine learning models for the prediction of CVD. Least absolute shrinkage and selection operator (LASSO) regression was used to select important features predicting the risk of developing CVD. Seven machine learning classification algorithms were used to build models, which were evaluated by receiver operating characteristic curves, accuracy, sensitivity, specificity, and F1-score, and Shapley Additive explanations was used to interpret the model results. CVD was defined as composite cardiovascular events including coronary heart disease (coronary artery disease, myocardial infarction, angina pectoris, and coronary artery revascularization), cerebrovascular disease (hemorrhagic stroke and ischemic stroke), deaths from all causes (cardiovascular deaths, non-cardiovascular deaths, unknown cause of death), congestive heart failure, and peripheral artery disease (aortic aneurysm, aortic or other peripheral arterial revascularization). A cardiovascular event was a composite outcome of multiple cardiovascular events, as determined by reviewing medical records. Results: This study included 8,894 patients with CKD, with a composite CVD event incidence of 25.9%; a total of 2,304 patients reached this outcome. LASSO regression identified eight important features for predicting the risk of CKD developing into CVD: age, history of hypertension, sex, antiplatelet drugs, high-density lipoprotein, sodium ions, 24-h urinary protein, and estimated glomerular filtration rate. The model developed using Extreme Gradient Boosting in the test set had an area under the curve of 0.89, outperforming the other models, indicating that it had the best CVD predictive performance. Conclusion: This study established a CVD risk prediction model for patients with CKD, based on routine clinical diagnostic and treatment data, with good predictive accuracy. This model is expected to provide a scientific basis for the management and treatment of patients with CKD.

Under pressure: integrated endothelial cell response to hydrostatic and shear stresses.

Blood flow within the vasculature is a critical determinant of endothelial cell (EC) identity and functionality, yet the intricate interplay of various hemodynamic forces and their collective impact on endothelial and vascular responses are not fully understood. Specifically, the role of hydrostatic pressure in the EC flow response is understudied, despite its known significance in vascular development and disease. To address this gap, we developed in vitro models to investigate how pressure influences EC responses to flow. Our study demonstrates that elevated pressure conditions significantly modify shear-induced flow alignment and increase endothelial cell density. Bulk and single-cell RNA sequencing analyses revealed that, while shear stress remains the primary driver of flow-induced transcriptional changes, pressure modulates shear-induced signaling in a dose-dependent manner. These pressure-responsive transcriptional signatures identified in human ECs were conserved during the onset of circulation in early mouse embryonic vascular development, where pressure was notably associated with transcriptional programs essential to arterial and hemogenic EC fates. Our findings suggest that pressure plays a synergistic role with shear stress on ECs and emphasizes the need for an integrative approach to endothelial cell mechanotransduction, one that encompasses the effects induced by pressure alongside other hemodynamic forces.

Plasma from older children in Malawi inhibits Plasmodium falciparum binding in 3D brain microvessels.

A hallmark of cerebral malaria is sequestration of Plasmodium falciparum-infected erythrocytes (IEs) in the brain microcirculation. Antibodies contribute to malaria immunity, but it remains unclear whether functional antibodies targeting parasite-expressed ligand can block cytoadhesion in the brain. Here, we screened the plasma of older children and young adults in Malawi to characterize the antibody response against the P. falciparum-IE surface and used a bioengineered 3D human brain microvessel model incorporating variable flow dynamics to measure adhesion blocking responses. We found a strong correlation between surface antibody reactivity by flow cytometry and reduced P. falciparum-IE binding in 3D microvessels. Moreover, there was a threshold of surface antibody reactivity necessary to achieve robust inhibitory activity. Our findings provide evidence of the acquisition of adhesion blocking antibodies against cerebral binding variants in people exposed to stable P. falciparum transmission and suggest the quality of the inhibitory response can be influenced by flow dynamics.

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies.

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.

Identified γ-glutamyl cyclotransferase (GGCT) as a novel regulator in the progression and immunotherapy of pancreatic ductal adenocarcinoma through multi-omics analysis and experiments.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its challenging early diagnosis, high malignancy, and resistance to chemotherapy drugs, the treatment of pancreatic cancer has long been exceedingly difficult in the realm of oncology. γ-Glutamyl cyclotransferase (GGCT), a vital enzyme in glutathione metabolism, has been implicated in the proliferation and progression of several tumor types, while the biological function of GGCT in pancreatic ductal adenocarcinoma remains unknown. METHODS: The expression profile of GGCT was validated through western blotting, immunohistochemistry, and RT-qPCR in both pancreatic cancer tissue samples and cell lines. Functional enrichment analyses including GSVA, ssGSEA, GO, and KEGG were conducted to explore the biological role of GGCT. Additionally, CCK8, Edu, colony formation, migration, and invasion assays were employed to evaluate the impact of GGCT on the proliferation and migration abilities of pancreatic cancer cells. Furthermore, the LASSO machine learning algorithm was utilized to develop a prognostic model associated with GGCT. RESULTS: Our study revealed heightened expression of GGCT in pancreatic cancer tissues and cells, suggesting an association with poorer patient prognosis. Additionally, we explored the immunomodulatory effects of GGCT in both pan-cancer and pancreatic cancer contexts, found that GGCT may be associated with immunosuppressive regulation in various types of tumors. Specifically, in patients with high expression of GGCT in pancreatic cancer, there is a reduction in the infiltration of various immune cells, leading to poorer responsiveness to immunotherapy and worse survival rates. In vivo and in vitro assays indicate that downregulation of GGCT markedly suppresses the proliferation and metastasis of pancreatic cancer cells. Moreover, this inhibitory effect appears to be linked to the regulation of GGCT on c-Myc. A prognostic model was constructed based on genes derived from GGCT, demonstrating robust predictive ability for favorable survival prognosis and response to immunotherapy.

Interferon-γ induces combined pyroptotic angiopathy and APOL1 expression in human kidney disease.

Elevated interferon (IFN) signaling is associated with kidney diseases including COVID-19, HIV, and apolipoprotein-L1 (APOL1) nephropathy, but whether IFNs directly contribute to nephrotoxicity remains unclear. Using human kidney organoids, primary endothelial cells, and patient samples, we demonstrate that IFN-γ induces pyroptotic angiopathy in combination with APOL1 expression. Single-cell RNA sequencing, immunoblotting, and quantitative fluorescence-based assays reveal that IFN-γ-mediated expression of APOL1 is accompanied by pyroptotic endothelial network degradation in organoids. Pharmacological blockade of IFN-γ signaling inhibits APOL1 expression, prevents upregulation of pyroptosis-associated genes, and rescues vascular networks. Multiomic analyses in patients with COVID-19, proteinuric kidney disease, and collapsing glomerulopathy similarly demonstrate increased IFN signaling and pyroptosis-associated gene expression correlating with accelerated renal disease progression. Our results reveal that IFN-γ signaling simultaneously induces endothelial injury and primes renal cells for pyroptosis, suggesting a combinatorial mechanism for APOL1-mediated collapsing glomerulopathy, which can be targeted therapeutically.

Establishment of a SUMO pathway related gene signature for predicting prognosis, chemotherapy response and investigating the role of EGR2 in bladder cancer.

Background: Bladder cancer is a prevalent malignancy with significant clinical implications. Small Ubiquitin-like Modifier (SUMO) pathway related genes (SPRG) have been implicated in the development and progression of cancer. Methods: In this study, we conducted a comprehensive analysis of SPRG in bladder cancer. We analyzed gene expression and prognostic value of SPRG and developed a SPRG signature (SPRGS) prognostic model based on four genes (HDAC4, TRIM27, EGR2, and UBE2I) in bladder cancer. Furthermore, we investigated the relationship between SPRGS and genomic alterations, tumor microenvironment, chemotherapy response, and immunotherapy. Additionally, we identified EGR2 as a key SPRG in bladder cancer. The expression of EGR2 in bladder cancer was detected by immunohistochemistry, and the cell function experiment clarified the effect of knocking down EGR2 on the proliferation, invasion, and migration of bladder cancer cells. Results: Our findings suggest that SPRGS hold promise as prognostic markers and predictive biomarkers for chemotherapy response and immunotherapy efficacy in bladder cancer. The SPRGS prognostic model exhibited high predictive accuracy for bladder cancer patient survival. We also observed correlations between SPRG and genomic alterations, tumor microenvironment, and response to chemotherapy. Immunohistochemical results showed that EGR2 was highly expressed in bladder cancer tissues, and its overexpression was associated with poor prognosis. Knockdown of EGR2 inhibited bladder cancer cell proliferation, invasion, and migration. Conclusion: This study provides valuable insights into the landscape of SPRGS in bladder cancer and their potential implications for personalized treatment strategies. The identification of EGR2 as a key SPRG and its functional impact on bladder cancer cells further highlights its significance in bladder cancer development and progression. Overall, SPRGS may serve as important prognostic markers and predictive biomarkers for bladder cancer patients, guiding treatment decisions and improving patient outcomes.

Photo-uncaging Triggers on Self-Blinking to Control Single-Molecule Fluorescence Kinetics for Super-resolution Imaging.

Super-resolution imaging, especially a single-molecule localization approach, has raised a fluorophore engineering revolution chasing sparse single-molecule dark-bright blinking transforms. Yet, it is a challenge to structurally devise fluorophores manipulating the single-molecule blinking kinetics. In this pursuit, we have developed a triggering strategy by innovatively integrating the photoactivatable nitroso-caging strategy into self-blinking sulfonamide to form a nitroso-caged sulfonamide rhodamine (NOSR). Our fluorophore demonstrated controllable self-blinking events upon phototriggered caging unit release. This exceptional blink kinetics improved the super-resolution imaging integrity on microtubules compared to self-blinking analogues. With the aid of paramount single-molecule fluorescence kinetics, we successfully reconstructed the ring structure of nuclear pores and the axial morphology of mitochondrial outer membranes. We foresee that our synthetic approach of photoactivation and self-blinking would facilitate rhodamine devising for super-resolution imaging.

Icariin Ameliorates D-galactose-induced Cell Injury in Neuron-like PC12 Cells by Inhibiting MPTP Opening.

OBJECTIVE: Icariin (ICA) has a good neuroprotective effect and can upregulate neuronal basal autophagy in naturally aging rats. Mitochondrial dysfunction is associated with brain aging-related neurodegenerative diseases. Abnormal opening of the mitochondrial permeability transition pore (mPTP) is a crucial factor in mitochondrial dysfunction and is associated with excessive autophagy. This study aimed to explore that ICA protects against neuronal injury by blocking the mPTP opening and down-regulating autophagy levels in a D-galactose (D-gal)-induced cell injury model. METHODS: A cell model of neuronal injury was established in rat pheochromocytoma cells (PC12 cells) treated with 200 mmol/L D-gal for 48 h. In this cell model, PC12 cells were pre-treated with different concentrations of ICA for 24 h. MTT was used to detect cell viability. Senescence associated ß-galactosidase (SA-ß-Gal) staining was used to observe cell senescence. Western blot analysis was performed to detect the expression levels of a senescence-related protein (p21), autophagy markers (LC3B, p62, Atg7, Atg5 and Beclin 1), mitochondrial fission and fusion-related proteins (Drp1, Mfn2 and Opa1), and mitophagy markers (Pink1 and Parkin). The changes of autophagic flow were detected by using mRFP-GFP-LC3 adenovirus. The intracellular ultrastructure was observed by transmission electron microscopy. Immunofluorescence was used to detect mPTP, mitochondrial membrane potential (MMP), mitochondrial reactive oxygen species (mtROS) and ROS levels. ROS and apoptosis levels were detected by flow cytometry. RESULTS: D-gal treatment significantly decreased the viability of PC12 cells, and markedly increased the SA-ß-Gal positive cells as compared to the control group. With the D-gal stimulation, the expression of p21 was significantly up-regulated. Furthermore, D-gal stimulation resulted in an elevated LC3B II/I ratio and decreased p62 expression. Meanwhile, autophagosomes and autolysosomes were significantly increased, indicating abnormal activation of autophagy levels. In addition, in this D-gal-induced model of cell injury, the mPTP was abnormally open, the ROS generation was continuously increased, the MMP was gradually decreased, and the apoptosis was increased. ICA effectively improved mitochondrial dysfunction to protect against D-gal-induced cell injury and apoptosis. It strongly inhibited excessive autophagy by blocking the opening of the mPTP. Cotreatment with ICA and an mPTP inhibitor (cyclosporin A) did not ameliorate mitochondrial dysfunction. However, the protective effects were attenuated by cotreatment with ICA and an mPTP activator (lonidamine). CONCLUSION: ICA inhibits the activation of excessive autophagy and thus improves mitochondrial dysfunction by blocking the mPTP opening.

Insight into saffron associated microbiota from different origins and explore the endophytes for enhancement of bioactive compounds.

Crocus sativus L. is a perennial crop for its valuable active compounds. Plant-associated microbes impact on the quality and efficacy of medicinal herbs by promoting bioactive components accumulation. However, how microbes influence the accumulation of bioactive components in saffron have not been well studied. Here, the microbiome in C. sativus derived from 3 core production areas were deciphered by 16S rDNA sequencing and the relationship between endophytes and bioactive ingredients were further investigated. The main results are as follows: (1) Both Comamonadaceae and Burkholderiaceae were positively correlated with the content of bioactive components in the stigmas. (2) The synthesis of crocin was positively correlated with Xanthomonadaceae, negatively correlated with Lachnospiraceae and Prevotellaceae. Therefore, further investigation is required to determine whether Xanthomonadaceae plays an unknown function in the synthesis of crocin. These findings provide guidelines for disentangling the function of endophytes in the production of bioactive ingredients and thus for microbe-mediated breeding.

Lefamulin Overcomes Acquired Drug Resistance via Regulating Mitochondrial Homeostasis by Targeting ILF3 in Hepatocellular Carcinoma.

Acquired resistance represents a critical clinical challenge to molecular targeted therapies such as tyrosine kinase inhibitors (TKIs) treatment in hepatocellular carcinoma (HCC). Therefore, it is urgent to explore new mechanisms and therapeutics that can overcome or delay resistance. Here, a US Food and Drug Administration (FDA)-approved pleuromutilin antibiotic is identified that overcomes sorafenib resistance in HCC cell lines, cell line-derived xenograft (CDX) and hydrodynamic injection mouse models. It is demonstrated that lefamulin targets interleukin enhancer-binding factor 3 (ILF3) to increase the sorafenib susceptibility of HCC via impairing mitochondrial function. Mechanistically, lefamulin directly binds to the Alanine-99 site of ILF3 protein and interferes with acetyltransferase general control non-depressible 5 (GCN5) and CREB binding protein (CBP) mediated acetylation of Lysine-100 site, which disrupts the ILF3-mediated transcription of mitochondrial ribosomal protein L12 (MRPL12) and subsequent mitochondrial biogenesis. Clinical data further confirm that high ILF3 or MRPL12 expression is associated with poor survival and targeted therapy efficacy in HCC. Conclusively, this findings suggest that ILF3 is a potential therapeutic target for overcoming resistance to TKIs, and lefamulin may be a novel combination therapy strategy for HCC treatment with sorafenib and regorafenib.

The role of exosome derived miRNAs in inter-cell crosstalk among insulin-related organs in type 2 diabetes mellitus.

Exosomes are small extracellular vesicles secreted by almost all cell types, and carry diverse cargo including RNA, and other substances. Recent studies have focused exosomal microRNAs (miRNAs) on various human diseases, including type 2 diabetes mellitus (T2DM) and metabolic syndrome (METS) which accompany the occurrence of insulin resistance. The regulation of insulin signaling has connected with some miRNA expression which play a significant regulatory character in insulin targeted cells or organs, such as fat, muscle, and liver. The miRNAs carried by exosomes, through the circulation in the body fluids, mediate all kinds of physiological and pathological process involved in the human body. Studies have found that exosome derived miRNAs are abnormally expressed and cross-talked with insulin targeted cells or organs to affect insulin pathways. Further investigations of the mechanisms of exosomal miRNAs in T2DM will be valuable for the diagnostic biomarkers and therapeutic targets of T2DM. This review will summarize the molecular mechanism of action of the miRNAs carried by exosomes which are secreted from insulin signaling related cells, and elucidate the pathogenesis of insulin resistance to provide a new strategy for the potential diagnostic biomarkers and therapeutic targets for the type 2 diabetes.

Association of levonorgestrel-releasing intrauterine device with gynecologic and breast cancers: a national cohort study in Sweden.

BACKGROUND: The levonorgestrel-releasing intrauterine device (LNG-IUD) is widely used for the treatment of menorrhagia, dysmenorrhea, and for contraception. However, the association between the use of LNG-IUD and the risk of site-specific gynecologic and breast cancers remains inconclusive. OBJECTIVE: We aim to address this knowledge gap by investigating whether the use of LNG-IUD is associated with a significant risk of site-specific gynecologic and breast cancers. This will be achieved by accessing the nationwide Swedish Registers, with consideration given to the influence and potential interaction of family history of cancer. STUDY DESIGN: A total of 514,719 women aged 18 to 50 years who have used LNG-IUD between July 2005 and December 2018 were identified from the Swedish Prescribed Drug Register and randomly matched with 1,544,157 comparisons who did not use LNG-IUD at a ratio of 1:3. The propensity score was calculated and matched among women who used LNG-IUD and the matched comparisons. The follow-up period started from the date of the first prescription of LNG-IUD for users as well as for their matched comparisons and ended at the date of diagnosis of gynecologic and breast cancers, date of death from any cause, and the end of the study period, whichever came first. The Cox proportional hazard model with a competing risk analysis was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Additive interaction was calculated as the relative excess risk for interaction, while multiplicative interaction was calculated by including a product term in the regression model. RESULTS: The use of LNG-IUD was associated with a 13% higher risk of breast cancer (adjusted HR, 1.13; 95% CI, 1.10-1.17), a 33% lower risk of endometrial cancer (adjusted HR, 0.67; 95% CI, 0.56-0.80), a 14% lower risk of ovarian cancer (adjusted HR, 0.86; 95% CI, 0.75-0.99), and a 9% reduced risk of cervical cancer (adjusted HR, 0.91; 95% CI, 0.84-0.99) compared to women who did not use LNG-IUD. A significant additive interaction between LNG-IUD use and family history of cancer was observed in breast cancer, indicating a relative 19% excess risk for interaction (P<.002), and 1.63 additional cases per 10,000 person-years. CONCLUSION: The risk of gynecologic and breast cancers exhibits a site-specific effect among LNG-IUD users. It is important to note that the observed effect is small for breast cancer and the results are limited by the observational study design. Clinical recommendations regarding the use of LNG-IUD should carefully weigh its potential benefits and risks. Close monitoring is advisable for the potential development of breast cancer, particularly among women with a family history of breast cancer.

Salvianolic acid A alleviates H2O2-induced endothelial oxidative injury via miR-204-5p.

Oxidative stress induced endothelial dysfunction plays a particularly important role in promoting the development of cardiovascular diseases (CVDs). Salvianolic acid A (SalA) is a water-soluble component of traditional Chinese medicine Salvia miltiorrhiza Bunge with anti-oxidant potency. This study aims to explore the regulatory effect of SalA on oxidative injury using an in vitro model of H2O2-induced injury in human umbilical vein endothelial cells (HUVECs). In the study, we determined cell viability, the activities of Lactate dehydrogenase (LDH) and Superoxide dismutase (SOD), cell proliferation rate and intracellular reactive oxygen species (ROS). Flow cytometry was used to detect cell apoptosis. Western-blotting was used to evaluate the expression of cell senescence, apoptosis, autophagy and pyroptosis protein factors. The expression level of miRNA was determined by qRT-PCR. Compared with H2O2-induced HUVECs, SalA promoted cell viability and cell proliferation rate; decreased LDH and ROS levels; and increased SOD activity. SalA also significantly attenuated endothelial senescence, inhibited cell apoptosis, reversed the increase of LC3 II/I ratio and NLRP3 accumulation. Furthermore, miR-204-5p was regulated by SalA. Importantly, miR-204-5p inhibitor had similar effect to that of SalA on H2O2-induced HUVECs. Our results indicated that SalA could alleviate H2O2-induced oxidative injury by downregulating miR-204-5p in HUVECs.

Risk prediction models of depression in older adults with chronic diseases.

BACKGROUND: Detecting potential depression and identifying the critical predictors of depression among older adults with chronic diseases are essential for timely intervention and management of depression. Therefore, risk prediction models (RPMs) of depression in elderly people should be further explored. METHODS: A total of 3959 respondents aged 60 years or over from the wave four survey of the China Health and Retired Longitudinal Study (CHARLS) were included in this study. We used five machine learning (ML) algorithms and three data balancing techniques to construct RPMs of depression and calculated feature importance scores to determine which features are essential to depression. RESULTS: The prevalence of depression was 19.2 % among older Chinese adults with chronic diseases in the wave four survey. The random forest (RF) model was more accurate than the other models after balancing the data using the Synthetic Minority Oversampling Technique (SMOTE) algorithm, with an area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) of 0.957 and 0.920, respectively, a balanced accuracy of 0.891 and a sensitivity of 0.875. Furthermore, we further identified several important predictors between male and female patients via constructed sex-stratified models. LIMITATIONS: Further research on the clinical impact studies of our models and external validation are needed. CONCLUSIONS: After several techniques were used to address class imbalance issues, most RPMs achieved satisfactory accuracy in predicting depression among elderly people with chronic diseases. RPMs may thus become valuable screening tools for both older individuals and healthcare practitioners to assess the risk of depression.