Deep Intraspecific Divergence in the Endemic Herb Lancea tibetica (Mazaceae) Distributed Over the Qinghai-Tibetan Plateau

Qinghai-Tibetan Plateau (QTP) is an important biodiversity hub, which is very sensitive to climate change. Here in this study, we investigated genetic diversity and past population dynamics of Lancea tibetica (Mazaceae), an endemic herb to QTP and adjacent highlands. We sequenced chloroplast and nuclear ribosomal DNA fragments for 429 individuals, collected from 29 localities, covering their major distribution range at the QTP. A total of 19 chloroplast haplotypes and 13 nuclear genotypes in two well-differentiated lineages, corresponding to populations into two groups isolated by Tanggula and Bayangela Mountains. Meanwhile, significant phylogeographical structure was detected among sampling range of L. tibetica, and 61.50% of genetic variations was partitioned between groups. Gene flow across the whole region appears to be restricted by high mountains, suggesting a significant role of geography in the genetic differences between the two groups. Divergence time between the two lineages dated to 8.63 million years ago, which corresponded to the uplifting of QTP during the late Miocene and Pliocene. Ecological differences were found between both the lineages represent species-specific characteristics, sufficient to keep the lineages separated to a high degree. The simulated distribution from the last interglacial period to the current period showed that the distribution of L. tibetica experienced shrinkage and expansion. Climate changes during the Pleistocene glacial-interglacial cycles had a dramatic effect on L. tibetica distribution ranges. Multiple refugia of L. tibetica might have remained during the species history, to south of the Tanggula and north of Bayangela Mountains, both appeared as topological barrier and contributed to restricting gene flow between the two lineages. Together, geographic isolation and climatic factors have played a fundamental role in promoting diversification and evolution of L. tibetica

A data-driven mathematical model of multi-drug resistant Acinetobacter baumannii transmission in an intensive care unit

Major challenges remain when attempting to quantify and evaluate the impacts of contaminated environments and heterogeneity in the cohorting of health care workers (HCWs) on hospital infections. Data on the detection rate of multidrug-resistant Acinetobacter baumannii (MRAB) in a Chinese intensive care unit (ICU) were obtained to accurately evaluate the level of environmental contamination and also to simplify existing models. Data-driven mathematical models, including mean-field and pair approximation models, were proposed to examine the comprehensive effect of integrated measures including cohorting, increasing nurse-patient ratios and improvement of environmental sanitation on MRAB infection. Our results indicate that for clean environments and with strict cohorting, increasing the nurse-patient ratio results in an initial increase and then a decline in MRAB colonization. In contrast, in contaminated environments, increasing the nurse-patient ratio may lead to either a consistent increase or an initial increase followed by a decline of MRAB colonization, depending on the level of environmental contamination and the cohorting rate. For developing more effective control strategies, the findings suggest that increasing the cohorting rate and nurse-patient ratio are effective interventions for relatively clean environments, while cleaning the environment more frequently and increasing hand washing rate are suitable measures in contaminated environments

Association of maternal lipid levels with birth weight and cord blood insulin: a Bayesian network analysis

Objective: To assess the independent association of maternal lipid levels with birth weight and cord blood insulin (CBI) level. Setting: The Born in Guangzhou Cohort Study, Guangzhou, China. Participants: Women who delivered between January 2015 and June 2016 and with umbilical cord blood retained were eligible for this study. Those with prepregnancy health conditions, without an available fasting blood sample in the second trimester, or without demographic and glycaemic information were excluded. After random selection, data from 1522 mother–child pairs were used in this study. Exposures and outcome measures: Additive Bayesian network analysis was used to investigate the interdependency of lipid profiles with other metabolic risk factors (prepregnancy body mass index (BMI), fasting glucose and early gestational weight gain) in association with birth weight and CBI, along with multivariable linear regression models. Results: In multivariable linear regressions, maternal triglyceride was associated with increased birth weight (adjusted β=67.46, 95% CI 41.85 to 93.06 g per mmol/L) and CBI (adjusted β=0.89, 95% CI 0.06 to 1.72 μU/mL per mmol/L increase), while high-density lipoprotein cholesterol was associated with decreased birth weight (adjusted β=−45.29, 95% CI −85.49 to −5.09 g per mmol/L). After considering the interdependency of maternal metabolic risk factors in the Network analysis, none of the maternal lipid profiles was independently associated with birth weight and CBI. Instead, prepregnancy BMI was the global strongest factor for birth weight and CBI directly and indirectly. Conclusions: Gestational dyslipidaemia appears to be secondary to metabolic dysfunction with no clear association with metabolic adverse outcomes in neonates. Maternal prepregnancy overweight/obesity appears the most influential upstream metabolic risk factor for both maternal and neonatal metabolic health; these data imply weight management may need to be addressed from the preconception period and during early pregnancy

Exosomal miR-27a Derived from Gastric Cancer Cells Regulates the Transformation of Fibroblasts into Cancer-Associated Fibroblasts

Background/Aims: The malignant biological behavior of gastric cancer(GC) is not only determined by cancer cells alone, but also closely regulated by the microenvironment. Fibroblasts represent a large proportion of the components in the tumor microenvironment, and they promote the development of disease. Currently, accumulating evidence suggests that exosomes can function as intercellular transport systems to relay their contents, especially microRNAs(miRNAs). Methods: First, we detected the highly-expressed level of miR-27a in exosomes isolated from gastric cancer cells by qRT-PCR. MiR-27a –over-expressed models in vitro and in vivo were established to investigate the transformation of cancer-associated fibroblasts observed by Western blotting, and the malignant behavior of gastric cancer cells using the methods CCK8 and Transwell. Moreover, the downregulation of CSRP2 in fibroblasts was used to evaluate the promotion of malignancy of gastric cancer using the methods CCK8 and Transwell. Results: In this study, we found a marked high level of miR-27a in exosomes derived from GC cells. miR-27a was found to function an oncogene that not only induced the reprogramming of fibroblasts into cancer-associated fibroblasts(CAFs), but also promoted the proliferation, motility and metastasis of cancer cells in vitro and in vivo. Conversely, CAFs with over-expression of miR-27a could pleiotropically increase the malignant behavior of the GC cells. For the first time, we revealed that CSRP2 is a downstream target of miR-27a. CSRP2 downregulation could increase the proliferation and motility of GC cells. Conclusion: Thus, this report indicates that miR-27a in exosomes derived from GC cells has a crucial impact on the microenvironment and may be used as a potential therapeutic target in the treatment of G

Whole exome sequencing identifies frequent somatic mutations in cell-cell adhesion genes in chinese patients with lung squamous cell carcinoma

Lung squamous cell carcinoma (SQCC) accounts for about 30% of all lung cancer cases. Understanding of mutational landscape for this subtype of lung cancer in Chinese patients is currently limited. We performed whole exome sequencing in samples from 100 patients with lung SQCCs to search for somatic mutations and the subsequent target capture sequencing in another 98 samples for validation. We identified 20 significantly mutated genes, including TP53, CDH10, NFE2L2 and PTEN. Pathways with frequently mutated genes included those of cell-cell adhesion/Wnt/Hippo in 76%, oxidative stress response in 21%, and phosphatidylinositol-3-OH kinase in 36% of the tested tumor samples. Mutations of Chromatin regulatory factor genes were identified at a lower frequency. In functional assays, we observed that knockdown of CDH10 promoted cell proliferation, soft-agar colony formation, cell migration and cell invasion, and overexpression of CDH10 inhibited cell proliferation. This mutational landscape of lung SQCC in Chinese patients improves our current understanding of lung carcinogenesis, early diagnosis and personalized therapy

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

The complete chloroplast genome sequence of Neopallasia pectinata (Asteraceae)

The complete chloroplast (cp) genome of Neopallasia pectinata was sequenced and analyzed in this study. It was 150,766 bp in length and has a typical circular structure, including a large single copy (LSC) with 82,605 bp, two inverted repeats (IRs) with 24,944 bp, and a small single copy (SSC) with 18,273 bp. The phylogenetic analysis of N. pectinata and its related taxa was conducted depended on the complete cp-genome sequences. The maximum likelihood tree indicates a close relationship between Chrysanthemum and Neopallasia. The cp-genome of N. pectinata is useful for future phylogenetic studies of Asteraceae

Comparative Plastome Analyses of Ephedra przewalskii and E. monosperma (Ephedraceae)

Ephedra species were erect, branching shrubs found in desert or arid regions worldwide as the source of ephedrine alkaloids. In this study, the complete chloroplast genome of Ephedra przewalskii and E. monosperma on the Qinghai-Tibet Plateau were sequenced, assembled, and annotated. Compared with the other four published Ephedra species, the chloroplast genomes of Ephedra species were highly conservative, with a quadripartite structure. The length of the chloroplast genome was 109,569 bp in E. przewalskii with 36.6% GC and 109,604 bp in E. monosperma with 36.6% GC. We detected 118 genes in both Ephedra species, including 73 PCGs, 37 tRNA genes, and eight rRNA genes. Among them, the ndh family genes were lost, which could be used to study the phylogeny and genetic diversity of the genus Ephedra, combined with multiple highly variable intergenic spacer (IGS) regions. Codon usage preference of Ephedra species was weak. The ratio of non-synonymous substitutions and synonymous substitutions was low, showing that the PCGs of Ephedra may be under the pressure of purifying selection. ML and BI analysis showed similar phylogenetic topologies. Ephedra species clustered together in a well-supported monophyletic clade. E. przewalskii and E. monosperma were not gathered in one clade, consistent with the classification system by Flora of China. This study reveals differences in the chloroplast genomes of Ephedra, providing valuable and abundant data for the phylogenetic analysis and species identification of Ephedra

Fungal Endophytic Community and Diversity Associated with Desert Shrubs Driven by Plant Identity and Organ Differentiation in Extremely Arid Desert Ecosystem

Despite desert ecosystem being crucial to our understanding of natural geography, species evolution and global climate change, there is limited information on the dynamics of their composition and the diversity of endophytic fungi communities driven by plant identity and organ differentiation. Here, an extensive investigation of endophytic fungal microbiome in root, stem, and leaf organs associated with five xerophyte shrubs in an extremely arid desert, Northwest China, were examined. The fungal community dominated by Dothideomycetes and Pleosporales. Shrub species strongly drive the niche-based processes of endophytic fungi across the root, stem and leaf compartments. The diversity and composition of endophytic fungi in stem showed higher variability among plant species than leaf and root. The fungal communities in root libraries were more diverse and exhibited a remarkable differentiation of community composition. We further demonstrated the significant host preferences and tissue specificity of desert endophytic fungi, and unique specific taxa were also observed. The co-occurrence network revealed the coexistence of fungal endophytes in arid desert, and the root fungal network harbored the highest interspecies connectivity. Members of Pleosporales were the most common keystone species in the root fungal network. This is the first report of mycobiota in both plant species and organ differentiation in an extremely arid desert ecosystem

Setting-Specific and Symptom-Specific Association between Secondhand Smoke Exposure and Depressive Symptoms

Few studies have focused on the potential relationship between secondhand smoke (SHS) exposure and depressive symptoms. This study aimed to explore the potential association between SHS exposure and depressive symptoms and differentiate this association in setting-specific exposure and symptom-specific outcomes. A cross-sectional study was conducted in Guangdong province of China from September to December 2010 using a multistage sampling method to randomly sample adults aged 18 years and older. SHS exposure was defined as inhalation by non-smokers of the smoke exhaled from smokers for at least 1 day a week in the past 30 days. Depressive symptoms were measured using the nine-item Patient Health Questionnaire. The zero-inflate negative binomial regression models were used to explore the associations between SHS exposure and depressive symptoms. A total of 2771 non-smokers were included in this study, with mean age of 49.6 ± 14.0 years and 70.3% of females. The prevalence of depressive symptoms was significantly higher in participants with SHS exposure than in those without exposure (incidence rate ratio (IRR) = 1.32, 95% confidence interval (CI) 1.16–1.51), and there were similar positive associations for SHS exposure in medical facilities (IRR = 1.37, 95% CI 1.17–1.61) and in schools (IRR = 1.46, 95% CI 1.20–1.77). Notably, there was a monotonically increasing dose-response relationship between frequency of SHS exposure and depressive symptoms. When differentiating this relationship by the dimensions of depressive symptoms, there were similar dose-response relationships for cognitive-affective and somatic symptoms. When differentiating this relationship by sex, only females showed a significant dose-response relationship. Our findings suggest dose-response relationships between SHS exposure and depressive symptoms in sex-specific and symptom-specific manners. Future longitudinal studies are needed to establish the biological mechanisms of the impact of SHS exposure