Noisy weak-lensing convergence peak statistics near clusters of galaxies and beyond

Taking into account noise from intrinsic ellipticities of source galaxies, in this paper, we study the peak statistics in weak-lensing convergence maps around clusters of galaxies and beyond. We emphasize how the noise peak statistics is affected by the density distribution of nearby clusters, and also how cluster-peak signals are changed by the existence of noise. These are the important aspects to be understood thoroughly in weak-lensing analyses for individual clusters as well as in cosmological applications of weak-lensing cluster statistics. We adopt Gaussian smoothing with the smoothing scale $\theta_G=0.5\hbox{ arcmin}$ in our analyses. It is found that the noise peak distribution near a cluster of galaxies depends sensitively on the density profile of the cluster. For a cored isothermal cluster with the core radius $R_c$, the inner region with $R\le R_c$ appears noisy containing on average $\sim 2.4$ peaks with $\nu\ge 5$ for $R_c= 1.7\hbox{ arcmin}$ and the true peak height of the cluster $\nu=5.6$, where $\nu$ denotes the convergence signal to noise ratio. For a NFW cluster of the same mass and the same central $\nu$, the average number of peaks with $\nu\ge 5$ within $R\le R_c$ is $\sim 1.6$. Thus a high peak corresponding to the main cluster can be identified more cleanly in the NFW case. In the outer region with $R_c<R\le 5R_c$, the number of high noise peaks is considerably enhanced in comparison with that of the pure noise case without the nearby cluster. (abridged)Comment: 10 figures, ApJ in pres

COVID-19 vaccination and the risk of autoimmune diseases: a Mendelian randomization study

BackgroundIn recent times, reports have emerged suggesting that a variety of autoimmune disorders may arise after the coronavirus disease 2019 (COVID-19) vaccination. However, causality and underlying mechanisms remain unclear.MethodsWe collected summary statistics of COVID-19 vaccination and 31 autoimmune diseases from genome-wide association studies (GWAS) as exposure and outcome, respectively. Random-effects inverse variance weighting (IVW), MR Egger, weighted median, simple mode, and weighted mode were used as analytical methods through Mendelian randomization (MR), and heterogeneity and sensitivity analysis were performed.ResultsWe selected 72 instrumental variables for exposure (p &lt; 5 × 10−6; r2 &lt; 0.001, genetic distance = 10,000 kb), and MR analyses showed that COVID-19 vaccination was causally associated with an increased risk of multiple sclerosis (MS) (IVW, OR: 1.53, 95% CI: 1.065–2.197, p = 0.026) and ulcerative colitis (UC) (IVW, OR: 1.00, 95% CI: 1.000–1.003, p = 0.039). If exposure was refined (p &lt; 5 × 10−8; r2 &lt; 0.001, genetic distance = 10,000 kb), the associations became negative. No causality was found for the remaining outcomes. These results were robust to sensitivity and heterogeneity analyses.ConclusionOur study provided potential evidence for the impact of COVID-19 vaccination on the risk of MS and UC occurrence, but it lacks sufficient robustness, which could provide a new idea for public health policy

UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy

In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up objects in high-quality and diverse ways and generalize across hundreds of categories and even the unseen. Inspired by successful pipelines used in parallel gripper grasping, we split the task into two stages: 1) grasp proposal (pose) generation and 2) goal-conditioned grasp execution. For the first stage, we propose a novel probabilistic model of grasp pose conditioned on the point cloud observation that factorizes rotation from translation and articulation. Trained on our synthesized large-scale dexterous grasp dataset, this model enables us to sample diverse and high-quality dexterous grasp poses for the object point cloud.For the second stage, we propose to replace the motion planning used in parallel gripper grasping with a goal-conditioned grasp policy, due to the complexity involved in dexterous grasping execution. Note that it is very challenging to learn this highly generalizable grasp policy that only takes realistic inputs without oracle states. We thus propose several important innovations, including state canonicalization, object curriculum, and teacher-student distillation. Integrating the two stages, our final pipeline becomes the first to achieve universal generalization for dexterous grasping, demonstrating an average success rate of more than 60\% on thousands of object instances, which significantly outperforms all baselines, meanwhile showing only a minimal generalization gap.Comment: Accepted to CVPR 202

Optimizing adjuvant treatment options for patients with glioblastoma

BackgroundThis study focused on minimizing the costs and toxic effects associated with unnecessary chemotherapy. We sought to optimize the adjuvant therapy strategy, choosing between radiotherapy (RT) and chemoradiotherapy (CRT), for patients based on their specific characteristics. This selection process utilized an innovative deep learning method.MethodsWe trained six machine learning (ML) models to advise on the most suitable treatment for glioblastoma (GBM) patients. To assess the protective efficacy of these ML models, we employed various metrics: hazards ratio (HR), inverse probability treatment weighting (IPTW)-adjusted HR (HRa), the difference in restricted mean survival time (dRMST), and the number needed to treat (NNT).ResultsThe Balanced Individual Treatment Effect for Survival data (BITES) model emerged as the most effective, demonstrating significant protective benefits (HR: 0.53, 95% CI, 0.48–0.60; IPTW-adjusted HR: 0.65, 95% CI, 0.55–0.78; dRMST: 7.92, 95% CI, 7.81–8.15; NNT: 1.67, 95% CI, 1.24–2.41). Patients whose treatment aligned with BITES recommendations exhibited notably better survival rates compared to those who received different treatments, both before and after IPTW adjustment. In the CRT-recommended group, a significant survival advantage was observed when choosing CRT over RT (p &lt; 0.001). However, this was not the case in the RT-recommended group (p = 0.06). Males, older patients, and those whose tumor invasion is confined to the ventricular system were more frequently advised to undergo RT.ConclusionOur study suggests that BITES can effectively identify GBM patients likely to benefit from CRT. These ML models show promise in transforming the complex heterogeneity of real-world clinical practice into precise, personalized treatment recommendations

Loss of circSRY reduces γH2AX level in germ cells and impairs mouse spermatogenesis.

Sry on the Y chromosome is the master switch of sex determination in mammals. It has been well established that Sry encodes a transcription factor that is transiently expressed in somatic cells of the male gonad, leading to the formation of testes. In the testis of adult mice, Sry is expressed as a circular RNA (circRNA) transcript. However, the physiological function of Sry circRNA (circSRY) remains unknown since its discovery in 1993. Here we show that circSRY is mainly expressed in the spermatocytes, but not in mature sperm or somatic cells of the testis. Loss of circSRY led to germ cell apoptosis and the reduction of sperm count in the epididymis. The level of γH2AX was decreased, and failure of XY body formation was noted in circSRY KO germ cells. Further study demonstrated that circSRY directly bound to miR-138-5p in spermatocytes, and in vitro assay suggested that circSRY regulates H2AX mRNA through sponging miR-138-5p. Our study demonstrates that, besides determining sex, Sry also plays an important role in spermatogenesis as a circRNA

Individualized survival prediction and surgery recommendation for patients with glioblastoma

BackgroundThere is a lack of individualized evidence on surgical choices for glioblastoma (GBM) patients.AimThis study aimed to make individualized treatment recommendations for patients with GBM and to determine the importance of demographic and tumor characteristic variables in the selection of extent of resection.MethodsWe proposed Balanced Decision Ensembles (BDE) to make survival predictions and individualized treatment recommendations. We developed several DL models to counterfactually predict the individual treatment effect (ITE) of patients with GBM. We divided the patients into the recommended (Rec.) and anti-recommended groups based on whether their actual treatment was consistent with the model recommendation.ResultsThe BDE achieved the best recommendation effects (difference in restricted mean survival time (dRMST): 5.90; 95% confidence interval (CI), 4.40–7.39; hazard ratio (HR): 0.71; 95% CI, 0.65–0.77), followed by BITES and DeepSurv. Inverse probability treatment weighting (IPTW)-adjusted HR, IPTW-adjusted OR, natural direct effect, and control direct effect demonstrated better survival outcomes of the Rec. group.ConclusionThe ITE calculation method is crucial, as it may result in better or worse recommendations. Furthermore, the significant protective effects of machine recommendations on survival time and mortality indicate the superiority of the model for application in patients with GBM. Overall, the model identifies patients with tumors located in the right and left frontal and middle temporal lobes, as well as those with larger tumor sizes, as optimal candidates for SpTR

Advanced lung cancer inflammation index is associated with long-term cardiovascular death in hypertensive patients: national health and nutrition examination study, 1999–2018

Background: Hypertension is one of the main causes of cardiovascular death. Inflammation was considered influential factors of cardiovascular (CVD) death in patients with hypertension. Advanced lung cancer inflammation index (ALI) is an index to assess inflammation, few studies have investigated the relationship between advanced lung cancer inflammation index and cardiovascular death in hypertensive patients.Objective: The aim of this study was to investigate the association between advanced lung cancer inflammation index and long-term cardiovascular death in hypertensive patients.Method: Data from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 with mortality follow-up through 31 December 2019 were analyzed. Advanced lung cancer inflammation index was calculated as BMI (kg/㎡) × serum albumin level (g/dL)/neutrophil to lymphocyte ratio (NLR). A total of 20,517 participants were evaluated. Patients were divided into three groups based on tertiles of advanced lung cancer inflammation index as follows: T1 (n = 6,839), T2 (n = 6,839), and T3 (n = 6,839) groups. The relationship between advanced lung cancer inflammation index and long-term cardiovascular death was assessed by survival curves and Cox regression analysis based on the NHANES recommended weights.Results: The median advanced lung cancer inflammation index value in this study was 61.9 [44.4, 84.6]. After full adjustment, the T2 group (hazard ratio [HR]: 0.59, 95% confidence interval [CI]: 0.50–0.69; p &lt; 0.001) and T3 group (HR: 0.48, 95% CI: 0.39–0.58; p &lt; 0.001) were found to have a significantly lower risk of cardiovascular death compared to the T1 group.Conclusion: High levels of advanced lung cancer inflammation index were associated with reduced risk of cardiovascular death in hypertensive patients

Effect of storage time on the silage quality and microbial community of mixed maize and faba bean in the Qinghai-Tibet Plateau

Tibetan Plateau is facing serious shortage of forage in winter and spring season due to its special geographical location. Utilization of forages is useful to alleviate the forage shortage in winter and spring season. Consequently, the current study was aimed to evaluate the influence of storage time on the silage quality and microbial community of the maize (Zea mays L.) and faba bean (Vicia faba L.) mixed silage at Qinghai-Tibet Plateau. Maize and faba bean were ensiled with a fresh weight ratio of 7:3, followed by 30, 60, 90, and 120 days of ensiling. The results showed the pH value of mixed silage was below 4.2 at all fermentation days. The LA (lactic acid) content slightly fluctuated with the extension of fermentation time, with 33.76 g/kg DM at 90 days of ensiling. The AA (acetic acid) and NH3-N/TN (ammonium nitrogen/total nitrogen) contents increased with the extension of fermentation time and no significantly different between 90 and 120 days. The CP (crude protein) and WSC (water soluble carbohydrate) contents of mixed silage decreased significantly (P &lt; 0.05) with ensiling time, but the WSC content remained stable at 90 days. The Proteobacteria was the predominant phyla in fresh maize and faba bean, and Pseudomonas and Sphingomonas were the predominant genera. After ensiling, Lactobacillus was the prevalent genus at all ensiling days. The relative abundance of Lactococcus increased rapidly at 90 days of ensiling until 120 days of fermentation. Overall, the storage time significant influenced the silage fermentation quality, nutrient content, and microbial environment, and it remained stable for 90 days of ensiling at Qinghai-Tibet Plateau. Therefore, the recommended storage time of forage is 90 days in Qinghai-Tibet Plateau and other cool areas

The ABC130 barrel module prototyping programme for the ATLAS strip tracker

For the Phase-II Upgrade of the ATLAS Detector, its Inner Detector, consisting of silicon pixel, silicon strip and transition radiation sub-detectors, will be replaced with an all new 100 % silicon tracker, composed of a pixel tracker at inner radii and a strip tracker at outer radii. The future ATLAS strip tracker will include 11,000 silicon sensor modules in the central region (barrel) and 7,000 modules in the forward region (end-caps), which are foreseen to be constructed over a period of 3.5 years. The construction of each module consists of a series of assembly and quality control steps, which were engineered to be identical for all production sites. In order to develop the tooling and procedures for assembly and testing of these modules, two series of major prototyping programs were conducted: an early program using readout chips designed using a 250 nm fabrication process (ABCN-25) and a subsequent program using a follow-up chip set made using 130 nm processing (ABC130 and HCC130 chips). This second generation of readout chips was used for an extensive prototyping program that produced around 100 barrel-type modules and contributed significantly to the development of the final module layout. This paper gives an overview of the components used in ABC130 barrel modules, their assembly procedure and findings resulting from their tests.Comment: 82 pages, 66 figure