Aspirin Use and Common Cancer Risk:A Meta-Analysis of Cohort Studies and Randomized Controlled Trials

BackgroundWhether aspirin use can decrease or increase cancer risk remains controversial. In this study, a meta-analysis of cohort studies and randomized controlled trials (RCTs) were conducted to evaluate the effect of aspirin use on common cancer risk.MethodMedline and Embase databases were searched to identify relevant studies. Meta-analyses of cohort studies and RCTs were performed to assess the effect of aspirin use on the risk of colorectal, gastric, breast, prostate and lung cancer. Cochran Q test and the I square metric were calculated to detect potential heterogeneity among studies. Subgroup meta-analyses according to exposure categories (frequency and duration) and timing of aspirin use (whether aspirin was used before and after cancer diagnosis) were also performed. A dose-response analysis was carried out to evaluate and quantify the association between aspirin dose and cancer risk.ResultsA total of 88 cohort studies and seven RCTs were included in the final analysis. Meta-analyses of cohort studies revealed that regular aspirin use reduced the risk of colorectal cancer (CRC) (RR=0.85, 95%CI: 0.78-0.92), gastric cancer (RR=0.67, 95%CI: 0.52-0.87), breast cancer (RR=0.93, 95%CI: 0.87-0.99) and prostate cancer (RR=0.92, 95%CI: 0.86-0.98), but showed no association with lung cancer risk. Additionally, meta-analyses of RCTs showed that aspirin use had a protective effect on CRC risk (OR=0.74, 95%CI: 0.56-0.97). When combining evidence from meta-analyses of cohorts and RCTs, consistent evidence was found for the protective effect of aspirin use on CRC risk. Subgroup analysis showed that high frequency aspirin use was associated with increased lung cancer risk (RR=1.05, 95%CI: 1.01-1.09). Dose-response analysis revealed that high-dose aspirin use may increase prostate cancer risk.ConclusionsThis study provides evidence for low-dose aspirin use for the prevention of CRC, but not other common cancers. High frequency or high dose use of aspirin should be prescribed with caution because of their associations with increased lung and prostate cancer risk, respectively. Further studies are warranted to validate these findings and to find the minimum effective dose required for cancer prevention

Visual Representation Learning with Transformer: A Sequence-to-Sequence Perspective

Visual representation learning is the key of solving various vision problems. Relying on the seminal grid structure priors, convolutional neural networks (CNNs) have been the de facto standard architectures of most deep vision models. For instance, classical semantic segmentation methods often adopt a fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution and learns more abstract visual concepts with larger receptive fields. Since context modeling is critical for segmentation, the latest efforts have been focused on increasing the receptive field, through either dilated (i.e., atrous) convolutions or inserting attention modules. However, the FCN-based architecture remains unchanged. In this paper, we aim to provide an alternative perspective by treating visual representation learning generally as a sequence-to-sequence prediction task. Specifically, we deploy a pure Transformer to encode an image as a sequence of patches, without local convolution and resolution reduction. With the global context modeled in every layer of the Transformer, stronger visual representation can be learned for better tackling vision tasks. In particular, our segmentation model, termed as SEgmentation TRansformer (SETR), excels on ADE20K (50.28% mIoU, the first position in the test leaderboard on the day of submission), Pascal Context (55.83% mIoU) and reaches competitive results on Cityscapes. Further, we formulate a family of Hierarchical Local-Global (HLG) Transformers characterized by local attention within windows and global-attention across windows in a hierarchical and pyramidal architecture. Extensive experiments show that our method achieves appealing performance on a variety of visual recognition tasks (e.g., image classification, object detection and instance segmentation and semantic segmentation).Comment: Extended version of CVPR 2021 paper arXiv:2012.1584

Therapeutic potential of Ganoderma lucidum polysaccharide peptide in Doxorubicin-induced nephropathy: modulation of renin-angiotensin system and proteinuria

Introduction: In the Doxorubicin (DOX)-induced nephropathy model, proteinuria is a manifestation of progressive kidney injury. The pathophysiology of renal illness is heavily influenced by the renin-angiotensin system (RAS). To reduce renal RAS activation and proteinuria caused by DOX, this study evaluated the effectiveness of Ganoderma lucidum polysaccharide peptide (GL-PP), a new glycopeptide produced from Ganoderma lucidum grown on grass.Methods: Three groups of BALB/c male mice were created: control, DOX, and DOX + GL-PP. GL-PP (100 mg/kg) was administered to mice by intraperitoneal injection for 4 weeks following a single intravenous injection of DOX (10 mg/kg via the tail vein).Results: After 4 weeks, full-length and soluble pro(renin) receptor (fPRR/sPRR) overexpression in DOX mouse kidneys, which is crucial for the RAS pathway, was dramatically inhibited by GL-PP therapy. Additionally, GL-PP successfully reduced elevation of urinary renin activity and angiotensin II levels, supporting the idea that GL-PP inhibits RAS activation. Moreover, GL-PP showed a considerable downregulation of nicotinamide adenine nucleotide phosphate oxidase 4 (NOX4) expression and a decrease in hydrogen peroxide (H2O2) levels. GL-PP treatment effectively reduced glomerular and tubular injury induced by DOX, as evidenced by decreased proteinuria, podocyte damage, inflammation, oxidative stress, apoptosis, and fibrosis.Discussion: GL-PP inhibits intrarenal PRR/sPRR-RAS activation and upregulation of NOX4 and H2O2, suggesting potential therapeutic approaches against DOX-induced nephropathy

A systematic review of microbial markers for risk prediction of colorectal neoplasia

BACKGROUND: Substantial evidence indicates that dysbiosis of the gut microbial community is associated with colorectal neoplasia. This review aims to systematically summarise the microbial markers associated with colorectal neoplasia and to assess their predictive performance. METHODS: A comprehensive literature search of MEDLINE and EMBASE databases was performed to identify eligible studies. Observational studies exploring the associations between microbial biomarkers and colorectal neoplasia were included. We also included prediction studies that constructed models using microbial markers to predict CRC and adenomas. Risk of bias for included observational and prediction studies was assessed. RESULTS: Forty-five studies were included to assess the associations between microbial markers and colorectal neoplasia. Nine faecal microbiotas (i.e., Fusobacterium, Enterococcus, Porphyromonas, Salmonella, Pseudomonas, Peptostreptococcus, Actinomyces, Bifidobacterium and Roseburia), two oral pathogens (i.e., Treponema denticola and Prevotella intermedia) and serum antibody levels response to Streptococcus gallolyticus subspecies gallolyticus were found to be consistently associated with colorectal neoplasia. Thirty studies reported prediction models using microbial markers, and 83.3% of these models had acceptable-to-good discrimination (AUROC > 0.75). The results of predictive performance were promising, but most of the studies were limited to small number of cases (range: 9–485 cases) and lack of independent external validation (76.7%). CONCLUSIONS: This review provides insight into the evidence supporting the association between different types of microbial species and their predictive value for colorectal neoplasia. Prediction models developed from case-control studies require further external validation in high-quality prospective studies. Further studies should assess the feasibility and impact of incorporating microbial biomarkers in CRC screening programme

Genetically predicted high IGF-1 levels showed protective effects on COVID-19 susceptibility and hospitalization:a Mendelian randomisation study with data from 60 studies across 25 countries

Background: Epidemiological studies observed gender differences in COVID-19 outcomes, however, whether sex hormone plays a causal in COVID-19 risk remains unclear. This study aimed to examine associations of sex hormone, sex hormones-binding globulin (SHBG), insulin-like growth factor-1 (IGF-1), and COVID-19 risk. Methods: Two-sample Mendelian randomization (TSMR) study was performed to explore the causal associations between testosterone, estrogen, SHBG, IGF-1, and the risk of COVID-19 (susceptibility, hospitalization, and severity) using genome-wide association study (GWAS) summary level data from the COVID-19 Host Genetics Initiative (N=1,348,701). Random-effects inverse variance weighted (IVW) MR approach was used as the primary MR method and the weighted median, MR-Egger, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test were conducted as sensitivity analyses. Results: Higher genetically predicted IGF-1 levels have nominally significant association with reduced risk of COVID-19 susceptibility and hospitalization. For one standard deviation increase in genetically predicted IGF-1 levels, the odds ratio was 0.77 (95% confidence interval [CI], 0.61-0.97, p=0.027) for COVID-19 susceptibility, 0.62 (95% CI: 0.25-0.51, p=0.018) for COVID-19 hospitalization, and 0.85 (95% CI: 0.52-1.38, p=0.513) for COVID-19 severity. There was no evidence that testosterone, estrogen, and SHBG are associated with the risk of COVID-19 susceptibility, hospitalization, and severity in either overall or sex-stratified TSMR analysis. Conclusions: Our study indicated that genetically predicted high IGF-1 levels were associated with decrease the risk of COVID-19 susceptibility and hospitalization, but these associations did not survive the Bonferroni correction of multiple testing. Further studies are needed to validate the findings and explore whether IGF-1 could be a potential intervention target to reduce COVID-19 risk

Adopting big data to accelerate discovery of 2D TMDCs materials via CVR method for the potential application in urban airborne Hg0 sensor

Airborne Hg0 has significant negative effect on cities and urban systems. The development of effect airborne Hg0 sensor is rather important for both urban atmospheric Hg0 detection and the evaluation of Hg0 capture materials. Previous research showed MoS2 as a typical TMDCs materials had excellent performance to capture Hg0. In this study, the other 2D TMDCs materials via CVR method in big data was initially studied for the potential urban airborne Hg0 sensor application. The combinations of Pymatgen initial screening, Factsage thermochemical screening and Aflow structural screening were developed for accelerating discovery of the 2D TMDCs in big data. The results from Pymatgen showed that except elements Cd, Sc, Y, Zn, and the other elements have the potential to form TMDC. Furthermore, elements such as Co, Ni, Mo, Ru, W and Ir have the ability forming pure TMDC and Ti, Mn, Zr and Pd can only form partial TMDC. However, other elements such as Sc, V, Cr, Fe, Cu, Zn, Y, Rh and Cd have no possibility to form TMDC. Finally, TiS2, NiS2, ZrS2, MoS2, PdS2 and WS2 were found with 2D structure, which are possible to be prepared by the S-CVR method as the airborne Hg0 sensor materials

Can a Manufacturer Get Better off When Providing Product Sharing Services?

The emerging product sharing trend poses challenges for manufacturers. Although the cost of purchasing products is decreased by adopting product sharing, consumers must accept that their demand cannot be responded to instantly and must use unfamiliar shared products. There are unavoidable inconveniences that are inherent in product sharing that directly affect consumers’ choices and further affect manufacturers’ decisions about providing sharing services. However, few papers have focused on the impact of such factors. In this paper, we aim to study how the unavoidable inconvenience costs and operational costs affect the manufacturer’s decision on whether to provide sharing services. First, low inconvenience cost and operational cost encourage the manufacturer to provide sharing services. High product quality weakens the influence of these two factors, while strengthening the influence of the pooling effect on the manufacturer’s provision decision. Second, the sharing market cannibalizes the sales demand when inconvenience cost is low and product quality is high. Third, the provision of sharing services is a win-win situation for consumers and the manufacturers of low-quality products

(Pro)Renin Receptor Decoy Peptide PRO20 Protects against Oxidative Renal Damage Induced by Advanced Oxidation Protein Products

Chronic kidney disease (CKD) is associated with advanced oxidation protein products (AOPPs). A recent study has shown that AOPP-induced renal tubular injury is mediated by the (pro)renin receptor (PRR). However, it is unclear whether the PRR decoy inhibitor PRO20 can protect against renal damage related to AOPPs in vivo. In this study, we examined the role of the PRR in rats with AOPP-induced renal oxidative damage. Male SD rats were subjected to unilateral nephrectomy, and after a four-day recuperation period, they were randomly divided into four groups (n = 6/group) for four weeks: control (CTR), unmodified rat serum albumin (RSA, 50 mg/kg/day via tail-vein injection), AOPPs-RSA (50 mg/kg/day via tail-vein injection), and AOPPs-RSA + PRO20 (50 mg/kg/day via tail-vein injection + 500 μg/kg/day via subcutaneous injection) groups. PRO20 was administered 3 days before AOPPs-RSA injection. Renal histopathology evaluation was performed by periodic acid–Schiff (PAS) staining, and biochemical parameters related to renal injury and oxidative stress biomarkers were evaluated. The expression of related indicators was quantified by RT-qPCR and immunoblotting analysis. In the results, rats in the AOPPs-RSA group exhibited higher levels of albuminuria, inflammatory cell infiltration, and tubular dilation, along with upregulation of oxidative stress, profibrotic and proinflammatory factors, and elevation of AOPP levels. Meanwhile, in the PRO20 group, these were significantly reduced. Moreover, the levels of almost all components of the renin-angiotensin system (RAS) and Nox4-dependent H2O2 production in urine and the kidneys were elevated by AOPPs-RSA, while they were suppressed by PRO20. Furthermore, AOPPs-RSA rats showed elevated kidney expression of the PRR and soluble PRR (sPRR) and increased renal excretion of sPRR. In summary, these findings suggest that PRR inhibition may serve as a protective mechanism against AOPP-induced nephropathy by inhibiting the intrarenal RAS and Nox4-derived H2O2 mechanisms