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Abstract Objectives To examine the spatiotemporal trends in pancreatic cancer (PC) disability-adjusted life years (DALYs) and mortality attributable to high body-mass index (BMI) by age, gender, and countries from 1990 to 2019. Methods Data were extracted from the Global Burden of Disease Study 2019 results. We presented the annual number of PC DALYs and mortality, and corresponding age-standardized rates (ASDR and ASMR), which were further stratified by age, gender, and countries. The estimated annual percentage change (EAPC) was computed to assess the longitudinal trends in ASRs. Results In 2019, 0.7 million DALYs and 31.9 thousand deaths worldwide were caused by PC attributable to high BMI, with the largest amount reported in high-income North America, Western Europe, and East Asia. The corresponding ASDR and ASMR were highest in females and in high SDI regions, while quite varied across countries. The global EAPC in ASDR and ASMR was 1.45 (95% uncertainty interval [UI]: 1.40, 1.50) and 1.44 (95% UI: 1.39, 1.49), respectively. Almost all involved countries demonstrated significant uptrends in ASRs from 1990 to 2019. Conclusions More productive efforts to reduce the impact of modifiable risk factors, such as overweight, should be undertaken, and thus effectively curb the rise of PC burden.

Abstract Background The spread of antibiotic resistance genes (ARGs) has been of global concern as one of the greatest environmental threats. The gut microbiome of animals has been found to be a large reservoir of ARGs, which is also an indicator of the environmental antibiotic spectrum. The conserved microbiota makes the honeybee a tractable and confined ecosystem for studying the maintenance and transfer of ARGs across gut bacteria. Although it has been found that honeybee gut bacteria harbor diverse sets of ARGs, the influences of environmental variables and the mechanism driving their distribution remain unclear. Results We characterized the gut resistome of two closely related honeybee species, Apis cerana and Apis mellifera, domesticated in 14 geographic locations across China. The composition of the ARGs was more associated with host species rather than with geographical distribution, and A. mellifera had a higher content of ARGs in the gut. There was a moderate geographic pattern of resistome distribution, and several core ARG groups were found to be prevalent among A. cerana samples. These shared genes were mainly carried by the honeybee-specific gut members Gilliamella and Snodgrassella. Transferrable ARGs were frequently detected in honeybee guts, and the load was much higher in A. mellifera samples. Genomic loci of the bee gut symbionts containing a streptomycin resistance gene cluster were nearly identical to those of the broad-host-range IncQ plasmid, a proficient DNA delivery system in the environment. By in vitro conjugation experiments, we confirmed that the mobilizable plasmids could be transferred between honeybee gut symbionts by conjugation. Moreover, “satellite plasmids” with fragmented genes were identified in the integrated regions of different symbionts from multiple areas. Conclusions Our study illustrates that the gut microbiota of different honeybee hosts varied in their antibiotic resistance structure, highlighting the role of the bee microbiome as a potential bioindicator and disseminator of antibiotic resistance. The difference in domestication history is highly influential in the structuring of the bee gut resistome. Notably, the evolution of plasmid-mediated antibiotic resistance is likely to promote the probability of its persistence and dissemination. Video Abstract

The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes.

Dementia has become a major global public health challenge with a heavy economic burden. It is urgently necessary to understand dementia pathogenesis and to identify biomarkers predicting risk of dementia in the preclinical stage for prevention, monitoring, and treatment. Metabolomics provides a novel approach for the identification of biomarkers of dementia. This systematic review aimed to examine and summarize recent retrospective cohort human studies assessing circulating metabolite markers, detected using high-throughput metabolomics, in the context of disease progression to dementia, including incident mild cognitive impairment, all-cause dementia, and cognitive decline. We systematically searched the PubMed, Embase, and Cochrane databases for retrospective cohort human studies assessing associations between blood (plasma or serum) metabolomics profile and cognitive decline and risk of dementia from inception through October 15, 2018. We identified 16 studies reporting circulating metabolites and risk of dementia, and six regarding cognitive performance change. Concentrations of several blood metabolites, including lipids (higher phosphatidylcholines, sphingomyelins, and lysophophatidylcholine, and lower docosahexaenoic acid and high-density lipoprotein subfractions), amino acids (lower branched-chain amino acids, creatinine, and taurine, and higher glutamate, glutamine, and anthranilic acid), and steroids were associated with cognitive decline and the incidence or progression of dementia. Circulating metabolites appear to be associated with the risk of dementia. Metabolomics could be a promising tool in dementia biomarker discovery. However, standardization and consensus guidelines for study design and analytical techniques require future development.

Background: Cerebral microbleeds (CMBs) are considered to be risk factors for cognitive dysfunction. The specific pathology and clinical manifestations of CMBs are different based on their locations. We investigated the association between CMBs at different locations and cognitive dysfunction and explored the potential underlying pathways in a rural Han Chinese population. Methods: We used baseline data from 562 community-dwelling adults (55–65 years old) in the Taizhou Imaging Study between 2013 and 2015. All individuals underwent multimodal brain magnetic resonance imaging (MRI) and 444 subjects completed neuropsychological tests: the Mini-Mental Status Examination and the Montreal Cognitive Assessment. Multinomial logistic regression was used to estimate the association between CMBs and cognitive dysfunction. The volume of brain regions and white matter microstructure were analyzed using Freesurfer and tract-based spatial statistics, respectively. Results: CMBs were detected in 104 individuals (18.5%) in our study. Multinomial logistic regression found deep/mixed CMBs were associated with global cognitive dysfunction (OR 3.52; 95% CI 1.21 to 10.26), whereas lobar CMBs (OR 1.76; 95% CI 0.56 to 5.53) were not. Quantification of multimodal brain MRI showed that deep/mixed CMBs were accompanied by decreased thalamic volume and loss of fractional anisotropy of bilateral anterior thalamic radiations. Conclusion: Deep/mixed CMBs were associated with cognitive dysfunction in this Chinese cross-sectional study. Disruption of thalamocortical connectivity might be a potential pathway underlying this relationship. Keywords: Cerebral microbleeds, Cognitive impairment, Multimodal imaging

Introduction: Metabolomics provide a promising tool to understand the pathogenesis and to identify novel biomarkers of dementia. This study aimed to determine circulating metabolites associated with incident dementia in a Chinese cohort, and whether a selectedmetabolite panel could predict dementia. Methods: Thirty-eight metabolites in baseline serum were profiled by nuclearmagnetic resonance in 1440 dementia-free participants followed 5 years in the Shanghai Aging Study. Results: Higher serum levels of glutamine and O-acetyl-glycoproteins were associated with increased risk of dementia, whereas glutamate, tyrosine, acetate, glycine, and phenylalanine were negatively related to incident dementia. A panel of five metabolites selected by least absolute shrinkage and selection operatorwithin cross-validation regression analysis could predict incident dementia with an area under the receiveroperating characteristic curve of 0.72. Discussion:We identified seven candidate serum metabolic biomarkers for dementia. These findings and the underlying biological mechanisms need to be further replicated and elucidated in future studies. [ABSTRACT FROM AUTHOR]

Background: The incidence of cancer was determined by genetic and environmental factors and varied across the world. The discrepancies in cancer profile among Chinese people living in different regions remained obscure. Methods: Chinese people living in urban Shanghai, Hong Kong, Taiwan, Macau, Singapore, and Los Angeles were included in this study. The cancer case data and population data were collected from either the Cancer Incidence in Five Continents Plus database or the regional cancer registry. A rate model was applied to examine the regional differences in cancer risk with Shanghai set as the reference. Results: From 1983 to 2013, the cancer profiles in most regions were changed. Significant differences in cancer incidence, by sex, period, and age, were detected across regions. The most pronounced disparities were found between Shanghai people and American Chinese in Los Angeles. For cancer site, the most significant differences were detected in prostate, gastrointestinal, gynecologic, oral cavity and pharynx, and brain and central nervous system (CNS) cancers. Specifically, Shanghai was significantly higher in stomach, liver, esophageal, pancreatic, and brain and CNS cancers, while lower in colon, prostate, breast, cervical, and oral cavity and pharynx cancers compared with the other five populations. Conclusions: Cancer profile was distinct across Chinese populations, which shared a similar genetic background but lived in different regions. The disparities indicate that cancer development was majorly determined by environmental factors, and suggests that region-tailored cancer prevention strategies were warranted. Impact: The cancer patterns in populations sharing the same genetic background were significantly influenced by different living conditions. [ABSTRACT FROM AUTHOR]