Yersinia pseudotuberculosis Exploits CD209 Receptors for Promoting Host Dissemination and Infection

Yersinia pseudotuberculosis is a Gram-negative enteropathogen and causes gastrointestinal infections. It disseminates from gut to mesenteric lymph nodes (MLNs), spleen, and liver of infected humans and animals. Although the molecular mechanisms for dissemination and infection are unclear, many Gram-negative enteropathogens presumably invade the small intestine via Peyer's patches to initiate dissemination. In this study, we demonstrate that Y. pseudotuberculosis utilizes its lipopolysaccharide (LPS) core to interact with CD209 receptors, leading to invasion of human dendritic cells (DCs) and murine macrophages. These Y. pseudotuberculosis CD209 interactions result in bacterial dissemination to MLNs, spleens, and livers of both wild-type and Peyer's patch-deficient mice. The blocking of the Y. pseudotuberculosis CD209 interactions by expression of 0-antigen and with oligosaccharides reduces infectivity. Based on the well-documented studies in which HIV-CD209 interaction leads to viral dissemination, we therefore propose an infection route for Y. pseudotuberculosis where this pathogen, after penetrating the intestinal mucosal membrane, hijacks the Y. pseudotuberculosis CD209 interaction antigen-presenting cells to reach their target destinations, MLNs, spleens, and livers.Peer reviewe

Joint analysis of three genome-wide association studies of esophageal squamous cell carcinoma in Chinese populations

We conducted a joint (pooled) analysis of three genome-wide association studies (GWAS) 1-3 of esophageal squamous cell carcinoma (ESCC) in ethnic Chinese (5,337 ESCC cases and 5,787 controls) with 9,654 ESCC cases and 10,058 controls for follow-up. In a logistic regression model adjusted for age, sex, study, and two eigenvectors, two new loci achieved genome-wide significance, marked by rs7447927 at 5q31.2 (per-allele odds ratio (OR) = 0.85, 95% CI 0.82-0.88; P=7.72x10−20) and rs1642764 at 17p13.1 (per-allele OR= 0.88, 95% CI 0.85-0.91; P=3.10x10−13). rs7447927 is a synonymous single nucleotide polymorphism (SNP) in TMEM173 and rs1642764 is an intronic SNP in ATP1B2, near TP53. Furthermore, a locus in the HLA class II region at 6p21.32 (rs35597309) achieved genome-wide significance in the two populations at highest risk for ESSC (OR=1.33, 95% CI 1.22-1.46; P=1.99x10−10). Our joint analysis identified new ESCC susceptibility loci overall as well as a new locus unique to the ESCC high risk Taihang Mountain region

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Methylation of histone H3 lysine 27 associated with apoptosis in osteosarcoma cells induced by staurosporine

The relationship between histone methylation and apoptosis, programmed cell death, is beginning to be explored. The objective of this study was to investigate the effects of staurosporine, a PKC inhibitor on the methylation of histone H3 in osteosarcoma cells. Following stimulation by staurosporine in vitro of G292 cells, a human osteosarcoma cell line with fibroblast-like phenotype, methylation of histone H3 was evaluated by western blotting and immunocytochemistry. G292 cells revealed the expression of cleaved PARP after incubation with staurosporine for 3 hours. Monomethyl lysine (K) 27 was induced by staurosporine at a concentration of 1, but no monomethyl K4 or K9 in histone H3 was seen. Dimethyl and trimethyl histone H3 K27 were also identified. There was no expression of dimethyl or trimethyl histone H3 K4 and K9. Expression of monomethyl histone H3 K27 was dose-dependent. The morphologic changes of apoptosis induced by staurosporine were observed under microscopy. Immunocytochemistry of monomethyl histone H3 K27 showed a weak signal in controls, a strong signal in staurosporine-treated tumor cells and a denser signal in the apoptotic cells. Our studies demonstrated that monomethyl histone H3 lysine 27 is expressed in staurosporine-induced apoptotic osteosarcoma cells. The findings may provide novel bridge information between the epigenetic episodes and apoptotic proces

The clinical application of a novel method of internal fixation for femoral neck fractures—dynamic locking compression system

Abstract Background Femoral neck fractures are the commonly encountered injury in orthopedic practice and result in significant morbidity and mortality. Currently, how to treat femoral neck fractures safely and effectively is still a challenge. The objective of this study is to evaluate the efficiency of dynamic compression locking system for femoral neck fractures. Methods This is a retrospective study conducted from May 2015 to October 2016. The study included 36 patients suffering from femoral neck fractures who underwent closed reduction and were fixed using dynamic compression locking system. All surgeries were performed by the same surgeon. The study was conducted by telephone and on-site follow-up. The Garden classification and anatomical site classification were categorized for all patients. We assessed radiographic outcomes of union, femoral neck shortening, screw back-out, and femoral head avascular necrosis. We also evaluated functional outcome using the Harris hip score. Other outcomes included the length of surgery, duration of hospital stay, injury to surgery time, intraoperative hemorrhage, time to clinical bone union, and other fracture complications. Results All patients were followed up 12 to 29 months with an average of 21.58 ± 5.41 months. All cases were caused by falls including 17 males and 19 females with an average age of 65.33 ± 9.30 years old ranging from 53 to 82 years old. Among them, injury to surgery time ranged between 1 and 4 days with an average of 2.58 ± 1.05 days. Duration of hospital stay was 8 to 21 days with an average of 15.33 ± 3.71 days. Intraoperative hemorrhage was 40 to 80 ml with an average of 61.67 ± 12.31 ml. Operation time was from 35 to 80 min with average of 50.25 ± 11.77 min. According to Garden classification, 9 cases (25%) were type II and 27 cases (75%) were type III. According to the anatomical site classification, 8 cases (22.2%) were subcapital femoral neck fractures, 19 cases (52.8%) trans-cervical, and 9 cases (25%) basi-cervical. At present, the follow-up has not found the fracture complications of femoral head avascular necrosis, fracture nonunion, and re-fracture. All patients achieved solid bone union. The mean time of clinical bone union was 3 to 4 months. Among all patients, there were only 3 cases of femoral neck shortening < 5 mm and 1 case of screw back-out = 4 mm. For Harris scoring, average Harris scale at the end of the follow-up was 93.42 ± 3.95 ranging from 85 to 98. There were 32 cases of excellent function scores on the Harris scale and 4 cases of good function scores on the Harris scale. Therefore, the excellent and good rate of Harris hip scores was 100%. Conclusions Femoral neck dynamic compression locking system for femoral neck fractures in elderly patients can provide effective stability and reduce complications and revision rates

Application of Random Forest and ICON Models Combined with Weather Forecasts to Predict Soil Temperature and Water Content in a Greenhouse

Climate change might potentially cause extreme weather events to become more frequent and intense. It could also enhance water scarcity and reduce food security. More efficient water management techniques are thus required to ensure a stable food supply and quality. Maintaining proper soil water content and soil temperature is necessary for efficient water management in agricultural practices. The usage of water and fertilizers can be significantly improved with a precise water content prediction tool. In this study, we proposed a new framework that combines weather forecast data, numerical models, and machine learning methods to simulate and predict the soil temperature and volumetric water content in a greenhouse. To test the framework, we performed greenhouse experiments with cherry tomatoes. The numerical models and machine learning methods we selected were Newton’s law of cooling, HYDRUS-1D, the random forest model, and the ICON (inferring connections of networks) model. The measured air temperature, soil temperature, and volumetric water content during the cultivation period were used for model calibration and validation. We compared the performances of the models for soil temperature and volumetric water content predictions. The results showed that the random forest model performed a more accurate prediction than other methods under the limited information provided from greenhouse experiments. This approach provides a framework that can potentially learn best water management practices from experienced farmers and provide intelligent information for smart greenhouse management