CoGANPPIS: Coevolution-enhanced Global Attention Neural Network for Protein-Protein Interaction Site Prediction

Protein-protein interactions are essential in biochemical processes. Accurate prediction of the protein-protein interaction sites (PPIs) deepens our understanding of biological mechanism and is crucial for new drug design. However, conventional experimental methods for PPIs prediction are costly and time-consuming so that many computational approaches, especially ML-based methods, have been developed recently. Although these approaches have achieved gratifying results, there are still two limitations: (1) Most models have excavated some useful input features, but failed to take coevolutionary features into account, which could provide clues for inter-residue relationships; (2) The attention-based models only allocate attention weights for neighboring residues, instead of doing it globally, neglecting that some residues being far away from the target residues might also matter. We propose a coevolution-enhanced global attention neural network, a sequence-based deep learning model for PPIs prediction, called CoGANPPIS. It utilizes three layers in parallel for feature extraction: (1) Local-level representation aggregation layer, which aggregates the neighboring residues' features; (2) Global-level representation learning layer, which employs a novel coevolution-enhanced global attention mechanism to allocate attention weights to all the residues on the same protein sequences; (3) Coevolutionary information learning layer, which applies CNN & pooling to coevolutionary information to obtain the coevolutionary profile representation. Then, the three outputs are concatenated and passed into several fully connected layers for the final prediction. Application on two benchmark datasets demonstrated a state-of-the-art performance of our model. The source code is publicly available at https://github.com/Slam1423/CoGANPPIS_source_code

Examining the Association between Location-Specific Chronic Pain and Objectively Measured Physical Activity

Background: Chronic pain (CP) is an important public health problem because of its high prevalence and its effects on the physical and psychological well-being of individuals. The association between CP and physical activity (PA) has been discussed in previous literature. However, in most studies, the assessments of PA is done via self report, which can be affected by substantial bias and measurement error. In recent years, the use of wearable technology allowed the objective quantification of the frequency, duration, and intensity of PA. The current study is focused on assessing the associations between objectively measured PA chronic upper limb pain, chronic spinal pain, and chronic lower limb pain in U.S. adults. Methods: The sample was comprised of U.S. adults aged between 25 and 85 years from the 2003-2004 National Health and Nutritional Examination Survey data (NHANES, N = 2, 516), and was stratified into age- and gender-specific groups. PA data obtained via hip-worn accelerometry were summarized into 6 objective measures of volume and 2 measures of fragmentation. Survey-weighted regression models were conducted which regressed each PA measure on location-specific pain indicator, with and without adjustment for potential confounders, including age, race/ethnicity, behaviors, and medical conditions. Results: Chronic upper limb pain, chronic spinal pain, and chronic lower limb pain showed higher prevalence among females and middle-aged study participants. All three types of CP were strongly associated with lower levels of physical activity in 45-65 years old females. Males aged 25-45 or 65-85 years old with either CP in spine or leg also engaged in less physical activity than those without pain. The statistical significance of the associations remained, even after adjusting for relevant covariates. Conclusion: This study identified statistically significant associations between objectively measured PA and self-reported CP. The magnitude of the signal varies with the reported location of CP, gender, and age category. These findings may inform that clinical management could be targeted by the CP location. Moreover, results emphasized the importance of wearable technology for providing objective and reproducible measurements in health-related research

Testing loan loss provisioning hypotheses for banks in China

The purpose of this paper is to test four hypotheses which are related to bank loan loss provision: income smoothing, capital management, business cycle and bank efficiency. Data is collected for Chinese banks in 2011 to 2016, and Stochastic frontier analysis and Generalized method of moments are taken for analysis. The results support bank efficiency hypothesis in Chinese non state-owned banks, and indicate the countercyclicality of loan loss provision in both state-owned banks and non state-owned banks. However, there is no evidence for income-smoothing behaviour and capital management hypothesis

NCACO-score: An effective main-chain dependent scoring function for structure modeling

<p>Abstract</p> <p>Background</p> <p>Development of effective scoring functions is a critical component to the success of protein structure modeling. Previously, many efforts have been dedicated to the development of scoring functions. Despite these efforts, development of an effective scoring function that can achieve both good accuracy and fast speed still presents a grand challenge.</p> <p>Results</p> <p>Based on a coarse-grained representation of a protein structure by using only four main-chain atoms: N, Cα, C and O, we develop a knowledge-based scoring function, called NCACO-score, that integrates different structural information to rapidly model protein structure from sequence. In testing on the Decoys'R'Us sets, we found that NCACO-score can effectively recognize native conformers from their decoys. Furthermore, we demonstrate that NCACO-score can effectively guide fragment assembly for protein structure prediction, which has achieved a good performance in building the structure models for hard targets from CASP8 in terms of both accuracy and speed.</p> <p>Conclusions</p> <p>Although NCACO-score is developed based on a coarse-grained model, it is able to discriminate native conformers from decoy conformers with high accuracy. NCACO is a very effective scoring function for structure modeling.</p

Root biomass in cereals, catch crops and weeds can be reliably estimated without considering aboveground biomass

Reliable information on belowground plant biomass is essential to estimate belowground carbon inputs to soils. Estimations of belowground plant biomass are often based on a fixed allometric relationship of plant biomass between aboveground and belowground parts. However, environmental and management factors may affect this allometric relationship making such estimates uncertain and biased. Therefore, we aimed to explore how root biomass for typical cereal crops, catch crops and weeds could most reliably be estimated. Published and unpublished data on aboveground and root biomass (corrected to 0–25 cm depth) of cereal crops (wheat and barley), catch crops and weeds were collected from studies in Denmark. Leave one out cross validation was used to determine the model that could best estimate root biomass. Root biomass varied with year, farming system (organic versus conventional) and cereal species. Shoot and root biomass of catch crops were higher than for weeds (sampled in late autumn), and farming system significantly affected root biomass of catch crops and weeds. The use of fixed root biomass based on the most influential factors (farming system and species) provided the lowest error of prediction for estimation of root biomass, compared with the use of fixed allometric relations, such as root/shoot ratio. For cereal crops, the average root dry matter in organic farming systems was 218 g m−2 (243 and 193 g m−2 for wheat and barley, respectively), but in conventional systems only 139 g m−2 (142 and 129 g m−2 for wheat and barley, respectively). For catch crops and weeds, the root dry matter in organic farming systems were around 127 and 35 g m−2, and in conventional farming systems 75 and 28 g m−2, respectively. In conclusion, the present analysis indicates that root biomass in cereals, catch crops and weeds can be reliably estimated without considering aboveground biomass, and it may be better estimated using fixed values based on species and farming systems than using fixed allometric ratios

2 μm soliton lasers in a bidirectional nonlinear polarization evolution Tm3+-doped fiber oscillator

Funding Information: This work is financially supported by National Natural Science Foundation of China ( 61905150 ; 61805281 ); Fundamental Research Funds for the Central Universities, China (Grant No. 3072022CFJ2501 ; 3072022CF2506 ); Natural Science Foundation of Guangdong Province, China ( 2019A1515010732 ).Peer reviewedPublisher PD

Lack of spontaneous ocular neovascularization and attenuated laser-induced choroidal neovascularization in IGF-I overexpression transgenic mice

Robust IGF-I overexpression induces ocular angiogenesis in mice. To investigate the effect of subtle IGF-I overexpression, we examined the ocular phenotype of IGF-II promoter-driven IGF-I transgenic mice. Despite 2.5-fold elevation of IGF-I mRNA in the retina and 29 and 52% increase of IGF-I protein in the retina and aqueous humor, respectively, no ocular abnormality was observed in these transgenics. This was correlated with unaltered VEGF mRNA levels in the transgenic retina. The transgene was also associated with an attenuated laser-induced choroidal neovascularization. Differential expression levels and pattern of IGF-I gene may underlie the different retinal phenotypes in different transgenic lines

Functional inks and printing of two-dimensional materials.

Graphene and related two-dimensional materials provide an ideal platform for next generation disruptive technologies and applications. Exploiting these solution-processed two-dimensional materials in printing can accelerate this development by allowing additive patterning on both rigid and conformable substrates for flexible device design and large-scale, high-speed, cost-effective manufacturing. In this review, we summarise the current progress on ink formulation of two-dimensional materials and the printable applications enabled by them. We also present our perspectives on their research and technological future prospects

Inkjet-printed CMOS-integrated graphene–metal oxide sensors for breath analysis

Abstract: Early diagnosis in exhaled breath is a key technology for next-generation personal healthcare monitoring. Current chemiresistive sensors, primarily based on metal oxide (MOx) thin films, have limited applicability in such portable systems due to their high power consumption, long recovery time, poor device-to-device consistency, and baseline drifts. To address these challenges for ammonia (NH3) detection in exhaled breath, a critical biomarker for a variety of kidney and liver problems, we present a formulation of a graphene–MOx functional ink-based sensing platform. We integrate our sensing layer directly onto miniaturized CMOS microhotplates (μHP) via inkjet printing, potentially enabling scalability and device-to-device performance repeatability. Using stage-by-stage temporal analysis, and a temperature-pulsed modulation (TM) strategy, we achieve ultrahigh responsivity (1500% at 10 ppm pure NH3), fast response and recovery time (28 and 43 s), ultralow power consumption (~6 mW), negligible baseline drift (<0.67%), excellent cross-device and cross-cycle consistency (<0.5% and <0.41% variation in responsivity) and long-term stability (<1% variation) in our graphene–zinc oxide (ZnO) formulation, outperforming conventional MOx chemiresistive sensors. We further mitigate the effect of humidity through our measurement protocols, while interference from acetone is compensated through the parallel deployment of an additional inkjet printed graphene–tungsten oxide (WO3) device as part of the sensor array. Our dual graphene–MOx formulations and their integration with ultralow power CMOS through inkjet printing represent a significant step towards reliable and portable multi-analyte breath diagnostics