Prostate Cancer Epigenetic Mechanism Study and Biomarker Discovery Using Bioinformatics Approaches

Most screening-detected prostate cancer (PCa) is indolent and not lethal. Biomarkers that can predict aggressive diseases independent of clinical features are needed to improve risk stratification of localized PCa patients and reduce overtreatment. Epigenetic, especially methylation biomarkers have better stability in biofluids or samples with a below-average quality. We aimed to identify DNA methylation differences in leukocytes between clinically defined aggressive and non-aggressive PCa to identify potential biomarkers for PCa diagnosis. To accomplish this aim, we performed DNA methylation profiling in leukocyte DNA samples obtained from 287 PCa patients with Gleason Score (GS) 6 and ≥8 using Illumina 450k methylation arrays, and 8 PCa patients using whole genome bisulfite sequencing. We observed the DNA methylation level in the core promoters and the first exon region were significantly higher in GS≥8 patients than GS=6 PCa. We then performed a 5-fold cross validated random forest model on 1,459 differentially methylated CpG Probes (DMPs) between the GS=6 and GS≥8 groups to identify PCa aggressiveness biomarkers. The power of the predictive model was further reinforced by ranking the DMPs with Decreased Gini and re-train the model with the top 97 DMPs (Testing AUC=0.920, predict accuracy=0.847). Similar approaches were performed to detect methylation differences between normal and PCa patient leukocyte DNA. Moreover, we analyzed 8 whole genome bisulfite sequencing (WGBS) patient leukocyte DNA specimens from the patient pool with Model based Analysis of Bisulfite Sequencing data (MOABS), an integrated tool for bisulfite sequencing analysis. DNA microarray and WGBS results were highly correlated (r=0.946) and mutual biomarkers were identified. To make MOABS analysis widely accessible, we also utilized bioinformatics methods to implement MOABS to the galaxy platform and validated the power of MOABS-Galaxy with quick test and public bisulfite sequencing datasets. In summary, we identified a CpG methylation signature in leukocyte DNA that is associated with PCa aggressiveness and biochemical recurrence and developed the MOABS-Galaxy web service for DNA methylation analysis using bisulfite sequencing data. Our epigenetic mechanism study may provide an alternative option for PCa screening from epigenetic biomarkers, and implementation of MOABS could benefit biologists from non-computational background on bisulfite sequencing data analysis

Free-ATM: Exploring Unsupervised Learning on Diffusion-Generated Images with Free Attention Masks

Despite the rapid advancement of unsupervised learning in visual representation, it requires training on large-scale datasets that demand costly data collection, and pose additional challenges due to concerns regarding data privacy. Recently, synthetic images generated by text-to-image diffusion models, have shown great potential for benefiting image recognition. Although promising, there has been inadequate exploration dedicated to unsupervised learning on diffusion-generated images. To address this, we start by uncovering that diffusion models' cross-attention layers inherently provide annotation-free attention masks aligned with corresponding text inputs on generated images. We then investigate the problems of three prevalent unsupervised learning techniques ( i.e., contrastive learning, masked modeling, and vision-language pretraining) and introduce customized solutions by fully exploiting the aforementioned free attention masks. Our approach is validated through extensive experiments that show consistent improvements in baseline models across various downstream tasks, including image classification, detection, segmentation, and image-text retrieval. By utilizing our method, it is possible to close the performance gap between unsupervised pretraining on synthetic data and real-world scenarios

PVP surfactant-modified flower-like BiOBr with tunable bandgap structure for efficient photocatalytic decontamination of pollutants

Designing semiconductor catalysts with superior charge carrier transfer and adequately exposed reactive sites is crucial for acquiring remarkable photocatalytic activity. Herein, a series of BiOBr catalysts with PVP as “organic armor” were synthesized via a facile precipitation strategy. As expected, the BiOBr-PVP hybrids exhibited superior catalytic oxidation toward the removal of organic dyes and tetracycline, but also catalytic reduction of Cr (VI). By virtue of tunable bandgap structure, sufficient abundance of reactive sites and decreased work function, the BiOBr-PVP composites could effectively expedite the charge carrier separation and transfer via enhanced transport pathways. Simultaneously, the reduced particle size and enlarged specific surface area achieved by loading PVP on the BiOBr catalyst could provide greater contact area and channels for intimate interaction between reactive sites and pollutants. Moreover, a photodegradation pathway for tetracycline was proposed based on LC-MS measurements and the intrinsic mechanism between BiOBr and PVP was discussed by first-principles calculation. The constructed BiOBr-PVP composites extend the scope and comprehension of photocatalysts via surface structural engineering and sufficient interfacial coupling for use in several environmental purification applications

The Influence of Perceived Social Presence on the Willingness to Communicate in Mobile Medical Consultations: Experimental Study

BackgroundWith the rise of online health care service, there is growing discussion on the relationship between physicians and patients online, yet few researchers have paid attention to patients’ perception of social presence, especially its influence on their willingness to communicate (WTC). ObjectiveThe goal of the research is to investigate the influence of perceived social presence (PSP) on WTC in mobile medical consultations. MethodsParticipants living in Yunnan province during the period of middle to high risk of COVID-19 infection were recruited via the internet. They were assigned randomly into 2 groups interacting with a virtual physician presenting high and low levels of social presence and then asked to complete a questionnaire. Based on the theoretical framework, the study puts forward a model evaluating the relationships among participants’ PSP, communication apprehension (CA), self-perceived communication competence (SPCC), and willingness to communicate about health (WTCH) in the computer-mediated communication between virtual physicians and patients. ResultsIn total 206 (106 in group 1 and 100 in group 2) valid samples were gathered (from 276 log-ins) and 88.8% (183/206) of them were aged 18 to 44 years, which approximately resembles the age distribution of the main population engaging in online medical consultation in China. Independent t test shows that there is significant difference between the PSP of the 2 groups (P=.04), indicating a successful manipulation of social presence. The total effect of PSP on WTCH is 0.56 (P<.001), among which 74.4% is direct effect (P<.001). Among the indirect effects between PSP and WTCH, the mediating effect of SPCC accounts for 68.8% (P<.001) and the sequential mediating effect of CA→SPCC accounts for 19.2% (P<.001), while the mediating effect of CA alone is not significant (P=.08). ConclusionsThis study provides a comprehensible model, demonstrating that PSP is an important antecedent of WTCH, and the sequential mediating effect of CA and SPCC found in this study also proves that in the environment of online mobile medical services, CA cannot affect communication directly. The findings will provide some practical inspiration for the popularization of online medical service, especially for the promotion of online physician-patient communication

An experimental validation method on GNSS signal attenuation model in soil

The attenuation of GNSS signals in soil is of great significance for the related research of using GNSS signals to measure soil moisture. In this paper, for the first time, the attenuation of BDS (BeiDou navigation satellite system) and GPS (global positioning system) signals in the soil was studied through experiments. In the experimental design, the GNSS antenna was placed into the soil, then the soil thickness and moisture above the antenna were continuously changed to collect the power attenuation data of the GNSS signal. Finally, these data were used to retrieve soil moisture in order to validate the GNSS signal attenuation model. Experimental results show that soil can significantly attenuate GNSS signals. The greater the soil moisture value and thickness value is, the more severe the attenuation is. In the case of clay type soil and soil moisture of 0.15~0.30 cm3/cm3, the GNSS signal power has been attenuated to be undetectable by the GNSS receiver when the soil thickness reaches 21 cm. Further retrieval of soil moisture based on the GNSS signal attenuation model was carried out, the results show that the attenuation model is more accurate when the soil thickness is larger than or equal to 10 cm and when the satellite elevation angle is larger than 50&#176;. And under this situation, the root mean square error of soil moisture retrieval using BeiDou B1 signal and GPS L1 signal is less than 0.04 cm3/cm3 and 0.09 cm3/cm3, respectively

BiOBr/MoS2 catalyst as heterogenous peroxymonosulfate activator toward organic pollutant removal: Energy band alignment and mechanism insight

Utilization of heterogenous catalysts to trigger peroxymonosulfate (PMS) activation is considered an efficient strategy for environmental decontamination. Herein, a tightly bonded flake-like 2D/2D BiOBr/MoS2 heterojunction was successfully designed through co-precipitation process. By virtue of matched energy levels and intimate interfacial coupling, the Type-II BiOBr/MoS2 heterojunction significantly expedited charge carrier transfer and thereby promoted the catalytic performance for organic dye oxidation and Cr(VI) reduction. The specially designed BiOBr/MoS2 heterojunction is also conducive to split PMS and continuously generated highly active species (SO4∙-, ∙OH and ∙O2-) in a photo-Fenton system, achieving extraordinary catalytic capacity for various emerging organic pollutants (including phenol, bisphenol A and carbamazepine). The photoexcited electron with prolonged lifetime and exposed Mo sites with multivalence and multiphase nature can effectively activate PMS, which further promotes the oxidation efficiency of holes, as confirmed by scavenging experiments. The excellent stability and oxidative properties could justify scale up using BiOBr/MoS2 to a small pilot test, implementing the potential value in practical applications. This study would provide novel insight and cognition of PMS activation via a superior heterojunction for complex polluted wastewater treatment

Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud

In 2D image processing, some attempts decompose images into high and low frequency components for describing edge and smooth parts respectively. Similarly, the contour and flat area of 3D objects, such as the boundary and seat area of a chair, describe different but also complementary geometries. However, such investigation is lost in previous deep networks that understand point clouds by directly treating all points or local patches equally. To solve this problem, we propose Geometry-Disentangled Attention Network (GDANet). GDANet introduces Geometry-Disentangle Module to dynamically disentangle point clouds into the contour and flat part of 3D objects, respectively denoted by sharp and gentle variation components. Then GDANet exploits Sharp-Gentle Complementary Attention Module that regards the features from sharp and gentle variation components as two holistic representations, and pays different attentions to them while fusing them respectively with original point cloud features. In this way, our method captures and refines the holistic and complementary 3D geometric semantics from two distinct disentangled components to supplement the local information. Extensive experiments on 3D object classification and segmentation benchmarks demonstrate that GDANet achieves the state-of-the-arts with fewer parameters. Code is released on https://github.com/mutianxu/GDANet.Comment: Accepted by AAAI202