Predicting siRNA potency with random forests and support vector machines

Abstract Background Short interfering RNAs (siRNAs) can be used to knockdown gene expression in functional genomics. For a target gene of interest, many siRNA molecules may be designed, whereas their efficiency of expression inhibition often varies. Results To facilitate gene functional studies, we have developed a new machine learning method to predict siRNA potency based on random forests and support vector machines. Since there were many potential sequence features, random forests were used to select the most relevant features affecting gene expression inhibition. Support vector machine classifiers were then constructed using the selected sequence features for predicting siRNA potency. Interestingly, gene expression inhibition is significantly affected by nucleotide dimer and trimer compositions of siRNA sequence. Conclusions The findings in this study should help design potent siRNAs for functional genomics, and might also provide further insights into the molecular mechanism of RNA interference

Estimating the Cooling Effect of Pocket Green Space in High Density Urban Areas in Shanghai, China

Recently, pocket green spaces (PGS), i.e., small green spaces, have attracted growing attention for their various ecological and social services. As a crucial part of urban green spaces in high-density urban areas, PGS facilitates recreation and relaxation for neighborhoods and thus improves the livability of cities at the local scale. However, whether and how the PGS cools the urban heat island effect is still unclear. This research was performed in the highly developed areas of the city of Shanghai during hot summer daytime. We applied a set of cooling effect indicators to estimate the cooling extent, cooling intensity, and cooling efficiency of PGS. We further examined whether and how landscape features within and surrounding the PGS influence its cooling effects. The results showed that 90% of PGS are cooler than their surroundings. Among the landscape features, the land surface temperature of PGS logarithmically decreased with its area, and the maximum local cool island intensity and maximum cooling area logarithmically increased with the area of PGS. The vegetation types and their composition within the PGS also influenced their surface temperature and the cooling effect. The PGS dominated by tree-shrub-grass showed the highest cooling efficiency. The surrounding landscape patterns, especially the patch density and the landscape shape index, influence the cooling effect of PGS at both class and landscape levels. These findings add new knowledge on factors influencing the cooling effect of PGS, and provide the biophysical theoretical basis for developing nature-based cooling strategies for urban landscape designers and planners.Peer Reviewe

Synergistic effects of neck circumference and metabolic risk factors on insulin resistance: the Cardiometabolic Risk in Chinese (CRC) study

Objectives: Recent studies have associated neck circumference (NC) with insulin resistance (IR). We examined whether such relation was modified by other metabolic risk factors. Methods: The study samples were from a community-based health examination survey in central China. A total of 2588 apparently healthy Chinese men and women were included. Results: Plasma levels of total cholesterol (TC), HDL-C, uric acid (UA) and diastolic blood pressure (DBP) were independently associated with NC after adjusted for age, sex, body mass index (BMI), waist circumference (WC) and hip circumference (HC) (P = 0.009, 0.001, 0.015 and 0.015, respectively). We observed significant interactions of NC with triglyceride (TG) and UA (all the p for interaction = 0.001) in relation to HOMA-IR. It appeared that the associations between NC and HOMA-IR were more evident in those with higher UA or TG level. Conclusions: Our data indicate that in apparently healthy Chinese adults, there were synergistic effects of UA, TG and neck circumference on insulin resistance

TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection

Thanks to recent advancements in end-to-end speech modeling technology, it has become increasingly feasible to imitate and clone a user`s voice. This leads to a significant challenge in differentiating between authentic and fabricated audio segments. To address the issue of user voice abuse and misuse, the second Audio Deepfake Detection Challenge (ADD 2023) aims to detect and analyze deepfake speech utterances. Specifically, Track 2, named the Manipulation Region Location (RL), aims to pinpoint the location of manipulated regions in audio, which can be present in both real and generated audio segments. We propose our novel TranssionADD system as a solution to the challenging problem of model robustness and audio segment outliers in the trace competition. Our system provides three unique contributions: 1) we adapt sequence tagging task for audio deepfake detection; 2) we improve model generalization by various data augmentation techniques; 3) we incorporate multi-frame detection (MFD) module to overcome limited representation provided by a single frame and use isolated-frame penalty (IFP) loss to handle outliers in segments. Our best submission achieved 2nd place in Track 2, demonstrating the effectiveness and robustness of our proposed system

Proteomic analysis reveals proteins and pathways associated with declined testosterone production in male obese mice after chronic high-altitude exposure

ObjectiveObesity is common in highland areas owing to lifestyle alterations. There are pieces of evidence to suggest that both obesity and hypoxia may promote oxidative stress, leading to hypogonadism in males. These findings indicate an increased risk of hypogonadism in obese males following hypoxia exposure. However, the mechanisms underlying the disease process remain unclear. The current study aims to explore the mechanism of testosterone production dysfunction in obese male mice exposed to a chronic high-altitude hypoxia environment.MethodsAn obese male mouse model was generated by inducing obesity in mice via a high-fat diet for 14 weeks, and the obese mice were then exposed to a high-altitude hypoxia environment for 24 days. Sera and testicular tissues were collected to detect serum lipids, sex hormone level, and testicular oxidative stress indicators. Morphological examination was performed to assess pathological alterations in testicular tissues and suborganelles in leydig cells. Proteomic alterations in testicular tissues were investigated using quantitative proteomics in Obese/Control and Obese-Hypoxia/Obese groups.ResultsThe results showed that chronic high-altitude hypoxia exposure aggravated low testosterone production in obese male mice accompanied by increased testicular oxidative stress and histological damages. In total, 363 and 242 differentially expressed proteins (DEPs) were identified in the two comparison groups, Obese/Control and Obese-Hypoxia/Obese, respectively. Functional enrichment analysis demonstrated that several significant functional terms and pathways related to testosterone production were altered in the two comparison groups. These included cholesterol metabolism, steroid hormone biosynthesis, peroxisome proliferator-activated receptor (PPAR) signaling pathway, oxidative stress responses, as well as retinol metabolism. Finally, 10 representative DEPs were selected for parallel reaction monitoring verification. Among them, StAR, DHCR7, NSDHL, CYP51A1, FDPS, FDX1, CYP11A1, ALDH1A1, and GPX3 were confirmed to be downregulated in the two groups.ConclusionsChronic hypoxia exposure could exacerbate low testosterone production in obese male mice by influencing the expression of key proteins involved in steroid hormone biosynthesis, cholesterol biosynthesis, oxidative stress responses and retinol metabolism

Malat1 regulates PMN-MDSC expansion and immunosuppression through p-STAT3 ubiquitination in sepsis

Myeloid-derived suppressor cells (MDSCs) expand during sepsis and contribute to the development of persistent inflammation-immunosuppression-catabolism syndrome. However, the underlying mechanism remains unclear. Exploring the mechanisms of MDSCs generation may provide therapeutic targets for improving immune status in sepsis. Here, a sepsis mouse model is established by cecal ligation and perforation. Bone marrow cells at different sepsis time points are harvested to detect the proportion of MDSCs and search for differentially expressed genes by RNA-sequence. In lethal models of sepsis, polymorphonuclear-MDSCs (PMN-MDSCs) decrease in early but increase and become activated in late sepsis, which is contrary to the expression of metastasis-associated lung adenocarcinoma transcript 1 (Malat1). In vivo, Malat1 inhibitor significantly increases the mortality in mice with late sepsis. And in vitro, Malat1 down-regulation increases the proportion of PMN-MDSCs and enhanced its immunosuppressive ability. Mechanistically, Malat1 limits the differentiation of PMN-MDSCs by accelerating the degradation of phosphorylated STAT3. Furthermore, Stattic, an inhibitor of STAT3 phosphorylation, improves the survival of septic mice by inhibiting PMN-MDSCs. Overall, the study identifies a novel insight into the mechanism of sepsis-induced MDSCs and provides more evidence for targeting MDSCs in the treatment of sepsis

Rapid and Simple Detection of Viable Foodborne Pathogen Staphylococcus aureus

Staphylococcus aureus (S. aureus) contamination in food safety has become a worldwide health problem. In this work, we utilized RNA one-step detection of denaturation bubble-mediated Strand Exchange Amplification (SEA) method to realize the detection of viable foodborne pathogen S. aureus. A pair of S. aureus specific primers were designed for the SEA reaction by targeting hypervariable V2 region of 16S rDNA and the amplification reaction was finished about 1 h. The results of amplification reaction could be observed by the naked eyes with a significant color change from light yellow to red to realize the colorimetric detection of S. aureus. Therefore, there only required an isothermal water bath, which was very popular for areas with limited resources. In real sample testing, although the SEA detection was so time-saving compared with the traditional plating method, the SEA method showed great consistency with the traditional plating method. In view of the above-described advantages, we provided a simple, rapid and equipment-free detection method, which had a great potential on ponit-of-care testing (POCT) application. Our method reported here will also provide a POCT detection platform for other food-borne pathogens in food, even pathogenic bacteria from other fields