Shp2 in uterine stromal cells critically regulates on time embryo implantation and stromal decidualization by multiple pathways during early pregnancy.

Approximately 75% of failed pregnancies are considered to be due to embryo implantation failure or defects. Nevertheless, the explicit signaling mechanisms governing this process have not yet been elucidated. Here, we found that conditional deletion of the Shp2 gene in mouse uterine stromal cells deferred embryo implantation and inhibited the decidualization of stromal cells, which led to embryonic developmental delay and to the death of numerous embryos mid-gestation, ultimately reducing female fertility. The absence of Shp2 in stromal cells increased the proliferation of endometrial epithelial cells, thereby disturbing endometrial epithelial remodeling. However, Shp2 deletion impaired the proliferation and polyploidization of stromal cells, which are distinct characteristics of decidualization. In human endometrial stromal cells (hESCs), Shp2 expression gradually increased during the decidualization process. Knockout of Shp2 blocked the decidual differentiation of hESCs, while Shp2 overexpression had the opposite effect. Shp2 knockout inhibited the proliferation of hESCs during decidualization. Whole gene expression profiling analysis of hESCs during the decidualization process showed that Shp2 deficiency disrupted many signaling transduction pathways and gene expression. Analyses of hESCs and mouse uterine tissues confirmed that the signaling pathways extracellular regulated protein kinases (ERK), protein kinase B (AKT), signal transducer and activator of transcription 3 (STAT3) and their downstream transcription factors CCAAT/enhancer binding protein β (C/EBPβ) and Forkhead box transcription factor O1 (FOXO-1) were involved in the Shp2 regulation of decidualization. In summary, these results demonstrate that Shp2 plays a crucial role in stromal decidualization by mediating and coordinating multiple signaling pathways in uterine stromal cells. Our discovery possibly provides a novel key regulator of embryo implantation and novel therapeutic target for pregnancy failure

Distinct hyperuricemia trajectories are associated with different risks of incident diabetes: A prospective cohort study

Background and aim: Conflicting results suggest a link between serum uric acid and diabetes and previous studies ignored the effect of continuous exposure of serum uric acid on diabetes risk. This study aims to characterize hyperuricemia trajectories in middle-aged adults and to examine its potential impact on diabetes risk, considering the role of obesity, dyslipidemia, and hypertension. Methods and results: The cohort included 9192 participants who were free of diabetes before 2013. The hyperuricemia trajectories during 2009–2013 were identified by latent class growth models. Incident diabetes during 2014–2018 was used as the outcome. Modified Poisson regression models were used to assess the association of trajectories with diabetes. Furthermore, marginal structural models were used to estimate the mediating effects of the relationship between hyperuricemia trajectories and diabetes. We identified three discrete hyperuricemia trajectories: high-increasing (n = 5794), moderate-stable (n = 2049), and low-stable (n = 1349). During 5 years of follow-up, we documented 379 incident diabetes cases. Compared with the low-stable pattern, the high-increasing pattern had a higher risk of developing diabetes (RR, 1.42; 95% CI: 1.09–1.84). In addition, the percentages of total effect between the high-increasing hyperuricemia pattern and diabetes mediated by obesity, dyslipidemia, and hypertension were 24.41%, 18.26%, and 6.29%. However, the moderate-stable pattern was not associated with an increased risk of diabetes. Conclusions: These results indicate that the high-increasing hyperuricemia trajectory is significantly associated with an increased risk of diabetes. Furthermore, obesity, dyslipidemia, and hypertension play mediating roles in the relationship between the high-increasing hyperuricemia pattern and increased diabetes risk

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe

SoccerNet 2023 Challenges Results

peer reviewedThe SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast video understanding, is composed of three high-level tasks related to describing events occurring in the video broadcasts: (1) action spotting, focusing on retrieving all timestamps related to global actions in soccer, (2) ball action spotting, focusing on retrieving all timestamps related to the soccer ball change of state, and (3) dense video captioning, focusing on describing the broadcast with natural language and anchored timestamps. The second theme, field understanding, relates to the single task of (4) camera calibration, focusing on retrieving the intrinsic and extrinsic camera parameters from images. The third and last theme, player understanding, is composed of three low-level tasks related to extracting information about the players: (5) re-identification, focusing on retrieving the same players across multiple views, (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams, and (7) jersey number recognition, focusing on recognizing the jersey number of players from tracklets. Compared to the previous editions of the SoccerNet challenges, tasks (2-3-7) are novel, including new annotations and data, task (4) was enhanced with more data and annotations, and task (6) now focuses on end-to-end approaches. More information on the tasks, challenges, and leaderboards are available on https://www.soccer-net.org. Baselines and development kits can be found on https://github.com/SoccerNet

A Flexible and Highly Sensitive Pressure Sense Electrode Based on Cotton Pulp for Wearable Electronics

Flexible pressure sensors with high sensitivity have great potential applications in wearable electronics. However, it is still a great challenge to prepare sense electrodes with high flexibility, high sensitivity, and high electrochemical performance. Here, we propose a novel and simple method for carbonizing cotton fibers as excellent electrically conductive materials. Moreover, carbonized cotton fiber (CCF) and polydimethylsiloxane (PDMS) were assembled into a flexible sense electrode. The CCF/PDMS electrode shows a high sensitivity of 10.8 kPa−1, a wide response frequency from 0.2–2.0 Hz, and durability over 900 cycles. The combined CCF/PDMS sensors can monitor human movement and pulse vibration, showing the enormous potential for use in wearable device technology. Additionally, the CCF/PDMS can be used as electrodes with a specific capacitance of 332.5 mF cm−2 at a current density of 5 mA cm−2, thanks to their high electrical conductivity and hydrophilicity, demonstrating the promising prospect of flexible supercapacitors

Blood Vessel Segmentation of Retinal Image Based on Dense-U-Net Network

The accurate segmentation of retinal blood vessels in fundus is of great practical significance to help doctors diagnose fundus diseases. Aiming to solve the problems of serious segmentation errors and low accuracy in traditional retinal segmentation, a scheme based on the combination of U-Net and Dense-Net was proposed. Firstly, the vascular feature information was enhanced by fusion limited contrast histogram equalization, median filtering, data normalization and multi-scale morphological transformation, and the artifact was corrected by adaptive gamma correction. Secondly, the randomly extracted image blocks are used as training data to increase the data and improve the generalization ability. Thirdly, stochastic gradient descent was used to optimize the Dice loss function to improve the segmentation accuracy. Finally, the Dense-U-net model was used for segmentation. The specificity, accuracy, sensitivity and AUC of this algorithm are 0.9896, 0.9698, 0.7931, 0.8946 and 0.9738, respectively. The proposed method improves the segmentation accuracy of vessels and the segmentation of small vessels

A study on borrower choice and market competition in Singapore’s moneylending market

This paper uses data obtained from Onelyst, an online loan matching platform to study the Singapore moneylending market. We explored two main research questions: what offer terms are borrowers most concerned with when making an offer acceptance decision (Choice Model) and whether lenders compete to offer more favourable loan terms (Competition Model). The Choice Model utilizes the Conditional Logistic Regression Model to understand how borrowers make decisions when faced with multiple loan offers, and the results show that amongst the various offer characteristics available in our data, borrowers are most concerned with the Offer Amount-to-Request Amount Ratio (Offer-Request Ratio), Interest Rate, and Distance between them and the moneylender. The result has regulatory implications, as authorities have mainly focused on regulating the licensed moneylending market via restrictions on interest rates, and have in fact banned the geographic entry of moneylenders; however, our results show that preventing such entry could be undesirable for borrowers. The Competition Model builds on the findings of the Choice Model and examines if lenders compete by lowering Interest Rates and increasing Offer-Request Ratio. We used a Two-Stage Least Squares Regression (2SLS) to correct for omitted variable bias in the Ordinary Least Squares (OLS) Regression. The results were insignificant for Offer-Request Ratio but highly significant for Interest Rate, where the 2SLS estimates show that the marginal offer induced by market competition reduces interest rate significantly, while the marginal endogenous offer has negligible impact. This shows that competition is in fact beneficial to borrowers, and that regulators should reconsider anti-competitive measures in the future.Bachelor of Art