Determinants of carbon emission: A multiple scale decomposition of Gansu Province.

China, being the largest contributor to total carbon emissions, still has a long way to go in energy conservation and emission reduction. Employing the structural decomposition analysis (SDA) method and using input-output table data, this study examines the evolution of carbon emissions resulting from energy consumption in Gansu Province in China over the period 2007 to 2017. By exploring carbon emission driving factors and identifying key final demand and sectors for carbon emissions, Gansu province can formulate more effective emission reduction policies that can balance economic development and carbon emission control.

Influence of Light Irradiation on the Degradation of Dezocine in Injections.

Dezocine, which is well-known as an analgesic, had about 45% share of the Chinese opioid analgesic market. Since drug products containing impurities could bring serious health consequences, it was important to control the generation of impurities and degradation products in the dezocine product. In this study, two kinds of photodegradation products (i.

MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-modal features using deep learning algorithms. These features include 3D structural properties at the nucleotide base level of the RNA molecule, relational graphs based on overall RNA structure, and rich RNA semantic information.

RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding.

Motivation: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the development of cancer therapeutic vaccines. While recent deep learning-based methods have achieved significant performance in predicting MHC-peptide binding affinity, most of them separately encode MHC molecules and peptides as inputs, potentially overlooking critical interaction information between the two.

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of protein phosphorylation sites. However, most existing methods rely on simple protein sequence features that provide limited contextual information.

CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism.

Motivation: Accurate and rapid prediction of protein-ligand binding affinity is a great challenge currently encountered in drug discovery. Recent advances have manifested a promising alternative in applying deep learning-based computational approaches for accurately quantifying binding affinity. The structure complementarity between protein-binding pocket and ligand has a great effect on the binding strength between a protein and a ligand, but most of existing deep learning approaches usually extracted the features of pocket and ligand by these two detached modules.

Multisource Attention-Mechanism-Based Encoder-Decoder Model for Predicting Drug-Drug Interaction Events.

Many computational methods have been proposed to predict drug-drug interactions (DDIs), which can occur when combining drugs to treat various diseases, but most mainly utilize single-source features of drugs, which is inadequate for drug representation. To fill this gap, we propose two attention-mechanism-based encoder-decoder models that incorporate multisource information: one is MAEDDI, which can predict DDIs, and the other is MAEDDIE, which can make further DDI-associated event predictions for drug pairs with DDIs. To better express the drug feature, we used three encoding methods to encode the drugs, integrating the self-attention mechanism, cross-attention mechanism, and graph attention network to construct a multisource feature fusion network.

Facile fabrication of graphene encapsulating 3d transition metal nanoparticles as highly active and anti-poisoning catalysts for selective hydrogenation of nitroaromatics.

Graphene encapsulating 3d transition metal nanoparticles (Ni, Co, Fe@G) are successfully fabricated through pyrolysis of complexes which are simply prepared via "acid-base reactions" between metal hydroxides and carboxylic acid such as citric acid. In particular, the Ni@G catalyst exhibits outstanding catalytic activity and selectivity (>99%) toward the reduction of various nitroaromatics under mild conditions (1 MPa H, 60 °C), even in the presence of poisons (CO and thiophene etc.).

Occupational Mercury Exposure at a Thermometer Facility - Jiangsu Province, 2019.

What Is Already Known About This Topic?: Mercury is still used in the manufacture of some thermometers in China. This may pose health risks if exposure is not properly prevented and controlled.

What Is Added By This Report?: An onsite investigation of a workplace at a thermometer facility in Jiangsu Province in 2019 found heavily elevated airborne and urinary mercury levels among a massive number of workers exposed to mercury.

Induced pluripotent stem cells attenuate chronic allogeneic vasculopathy in an integrin beta-1-dependent manner.

This study aimed to determine the mechanism of isogeneic-induced pluripotent stem cells (iPSCs) homing to vascular transplants and their therapeutic effect on chronic allogeneic vasculopathy. We found that integrin β1 (Intgβ1) was the dominant integrin β unit in iPSCs that mediates the adhesion of circulatory and endothelial cells (ECs). Intgβ1 knockout or Intgβ1-siRNAs inhibit iPSC adhesion and migration across activated endothelial monolayers.

In situ evolution of the active phase on stainless steel mesh toward a cost-effective bifunctional electrode for energy storage and conversion.

Developing low-cost, efficient and stable electrode materials is a major challenge of energy storage and conversion. Here, we report a facile, cost-effective and scaled-up self-sacrificing strategy for transforming commercial stainless steel into highly active and ultrastable electrodes for supercapacitors and the hydrogen evolution reaction. The modified stainless steel displays superior electrochemical activity as well as excellent cycling durability.

An Efficient Metal-Free Catalyst for Oxidative Dehydrogenation Reaction: Activated Carbon Decorated with Few-Layer Graphene.

Activated carbon (AC) has been widely used in the catalysis field because of its low cost, scalable production, high specific surface area, and abundant exposed edge. Because of the amorphous structure, traditional AC is unstable in presence of O at high temperature, which hinders the application of AC catalysts in oxidative dehydrogenation (ODH) of alkanes. Here, partially graphitic AC decorated with few-layer graphene is facilely fabricated by simple high-temperature calcination.

Relationship between JAK2V617F mutation, allele burden and coagulation function in Ph-negative myeloproliferative neoplasms.

Objectives: Our aim was to explore the relationship between JAK2V617F mutation allele burden and hematological parameters especially in coagulation function in Chinese population.

Methods: This study included 133 Ph-negative myeloproliferative neoplasms (MPNs) patients between 2013 and 2016. All the clinical and experimental data of patients were collected at the time of the diagnosis without any prior treatment, including blood parameters, coagulation function, splenomegaly, vascular events and chromosome karyotype.

Prognostic value of RDW in cancers: a systematic review and meta-analysis.

Red blood cell distribution width (RDW), a parameter that used to differentiate the type of anemia for several decades, recent studies suggest it was a prognostic factor in various types of cancer patients. However, the prognostic value of RDW in cancer patients remains controversial. Here, we performed a meta-analysis and systematic review to evaluate the prognostic value of RDW in cancer patients.

Neutrophil CD64 Index as a superior biomarker for early diagnosis of infection in febrile patients in the hematology department.

Background: In the hematology department, the availability of biomarkers for early detection of infection is difficult to obtain. The present study aimed to compare the diagnostic values of neutrophil CD64 Index, procalcitonin (PCT), interleukin-6 (IL-6) and C-reactive protein (CRP) and to determine whether the combined analysis of these biomarkers offer stronger predictive power in the diagnosis for the infection of febrile patients.

Methods: Neutrophil CD64 Index, PCT, IL-6 and CRP levels were determined in 356 febrile patients in the hematology ward from May 2013 to May 2015.

Transduction of interleukin-10 through renal artery attenuates vascular neointimal proliferation and infiltration of immune cells in rat renal allograft.

Renal transplantation is the treatment of choice for end-stage renal failure. Although acute rejection is not a major issue anymore, chronic rejection, especially vascular rejection, is still a major factor that might lead to allograft dysfunction on the long term. The role of the local immune-regulating cytokine interleukin-10 (IL-10) in chronic renal allograft is unclear.

Weighted bootstrapping: a correction method for assessing the robustness of phylogenetic trees.

Background: Non-parametric bootstrapping is a widely-used statistical procedure for assessing confidence of model parameters based on the empirical distribution of the observed data 1 and, as such, it has become a common method for assessing tree confidence in phylogenetics 2. Traditional non-parametric bootstrapping does not weigh each tree inferred from resampled (i.e.

[Preparation of a reversed-phase capillary monolithic column and its application in the separation of polypeptide mixtures].

Capillary monolithic columns (75 microm i.d.) were prepared by the copolymerization of lauryl methacrylate as the basic monomer, ethylene dimethacrylate as the cross-linking agent and 1-dodecyl alcohol, 1,4-butanediol and dimethyl sulfoxide as the porogenic mixture.