Narcissism, perfectionism, and self-promoting behavior on social networking sites among university students in Pakistan / Narcisismo, perfeccionismo y comportamiento de autopromoción en sitios de redes sociales entre estudiantes universitarios en Pakistán

Existe un debate considerable en la literatura sobre cómo el narcisismo predice diversos comportamientos asociados con la utilidad de los sitios de redes sociales, pero los investigadores han prestado menos atención a explorar los mediadores potenciales de esta relación. Con base en la literatura existente, anticipamos que el narcisismo predice comportamientos de autopromoción en los sitios de redes sociales. El estudio actual también investigó el papel mediador del perfeccionismo multidimensional entre el narcisismo y el comportamiento de autopromoción. Se recopiló un total de 605 cuestionarios completos de estudiantes de universidades de Rawalpindi e Islamabad, Pakistán, mediante un muestreo conveniente. El estudio utilizó el Inventario de Personalidad Narcisista (Ames et al., 2006), un cuestionario de desarrollo propio sobre comportamiento de autopromoción en sitios de redes sociales y la Escala de Perfeccionismo Multidimensional (Hewitt et al., 1991). Los hallazgos indicaron que las mujeres en comparación con los hombres y las solteras en comparación con las casadas obtuvieron puntuaciones más altas en narcisismo. Los niveles educativos más altos se asociaron con tasas más altas de narcisismo. Los resultados también sugieren que el narcisismo se correlaciona con el perfeccionismo orientado a uno mismo y, más significativamente, con el narcisismo orientado a los demás. El perfeccionismo orientado a uno mismo y a los demás medió significativamente la relación entre el narcisismo y el comportamiento de autopromoción en los sitios de redes sociales.(AU)

There is considerable debate in the literature about how narcis-sism predicts various behaviors associated with the utility of social net-working sites, but researchers have paid less attention to exploring the po-tential mediators of this relationship.Based on the existing literature, we anticipated that narcissism predicts self-promoting behaviors on social networking sites. The current study also investigated the mediating role of multidimensional perfectionismbetween narcissism and self-promoting behavior. A total of 605 complete questionnaires weregathered fromstu-dents from universities from Rawalpindi and Islamabad, Pakistan using convenient sampling. The study used Narcissistic Personality Inventory (Ames et al., 2006), self-developed Self-promoting Behavior on social net-working sites questionnaire, and the Multidimensional Perfectionism Scale (Hewitt et al., 1991). Findings indicated that females as compared to males and single as comparedto married individuals scored higher on narcissism. Higher educational levels were associated with higher rates of narcissism. The results also suggestthat narcissism correlated with self-oriented per-fectionism, and more significantlywith others-oriented narcissism. Self-oriented and others-oriented perfectionism significantly mediated the rela-tionship between narcissism and self-promoting behavior on social net-working sites.(AU)

Harnessing the Missing Spectral Correlation for Metasurface Inverse Design.

A long-held tenet in computer science asserts that the training of deep learning is analogous to an alchemical furnace, and its "black box" signature brings forth inexplicability. For electromagnetic metasurfaces, the related intelligent applications also get stuck into such a dilemma. Although the past 5 years have witnessed a proliferation of deep learning-based works across complex photonic scenarios, they neglect the already existing but untapped physical laws. Here, the intrinsic correlation between the real and imaginary parts of the spectra are revealed using Kramers-Kronig relations, which is then mimicked by bidirectional information flow in neural network space. Such consideration harnesses the missing spectral connection to extract crucial features effectively. The bidirectional recurrent neural network is benchmarked in metasurface inverse design and compare it with a fully-connected neural network, unidirectional recurrent neural network, and attention-based transformer. Beyond the improved accuracy, the study examines the intermediate information products and physically explains why different network structures yield different performances. The work offers explicable perspectives to utilize physical information in the deep learning field and facilitates many data-intensive research endeavors.

Enhanced Thermally Activated Delayed Fluorescence by Sole Coordination: From an Organic Molecule to Its Zinc Complex.

A BPAPTPyC organic molecule containing a sandwich structural chromophore is designed and synthesized to produce blue thermally activated delayed fluorescence (TADF). The chromophore is composed of two di(4-tert-butylphenyl)amino donors and one inserted terpyridyl acceptor hitched at positions 1, 8, and 9 of a single carbazole via the p-phenylene group, in which the multiple space π-π interactions between the donor and acceptor enable the molecule to possess the TADF feature with a high energy emission at 470 nm but a low photoluminescence quantum yield (PLQY) and a small proportion of the delayed component. In contrast, the corresponding Zn(BPAPTPyC)Cl2 complex has a high PLQY and a short lifetime with a red-shifted emission due to the enhanced rigidity and electron accepting ability of the terpyridyl group from coordination. A solution-processed organic light-emitting diode (OLED) based on the complex achieves a maximum external quantum efficiency (EQE) of 17.9% with an emission peak at 585 nm, while an OLED of the organic molecule produces blue emission with a maximum EQE of 2.7%.

Proteomics analysis of deep fascia in acute compartment syndrome.

Acute compartment syndrome (ACS) is a syndrome in which local circulation is affected due to increased pressure within the compartment. We previously found in patients with calf fractures, the pressure of fascial compartment could be sharply reduced upon the appearance of tension blisters. Deep fascia, as the important structure for compartment, might play key role in this process. Therefore, the aim of the present study was to examine the differences in gene profile in deep fascia tissue in fracture patients of the calf with or without tension blisters, and to explore the role of fascia in pressure improvement in ACS. Patients with lower leg fracture were enrolled and divided into control group (CON group, n = 10) without tension blister, and tension blister group (TB group, n = 10). Deep fascia tissues were collected and LC-MS/MS label-free quantitative proteomics were performed. Genes involved in fascia structure and fibroblast function were further validated by Western blot. The differentially expressed proteins were found to be mainly enriched in pathways related to protein synthesis and processing, stress fiber assembly, cell-substrate adhesion, leukocyte mediated cytotoxicity, and cellular response to stress. Compared with the CON group, the expression of Peroxidasin homolog (PXDN), which promotes the function of fibroblasts, and Leukocyte differentiation antigen 74 (CD74), which enhances the proliferation of fibroblasts, were significantly upregulated (p all <0.05), while the expression of Matrix metalloproteinase-9 (MMP9), which is involved in collagen hydrolysis, and Neutrophil elastase (ELANE), which is involved in elastin hydrolysis, were significantly reduced in the TB group (p all <0.05), indicating fascia tissue underwent microenvironment reconstruction during ACS. In summary, the ACS accompanied by blisters is associated with the enhanced function and proliferation of fibroblasts and reduced hydrolysis of collagen and elastin. The adaptive alterations in the stiffness and elasticity of the deep fascia might be crucial for pressure release of ACS.

Effects of recreational team sports on the metabolic health, body composition and physical fitness parameters of overweight and obese populations: A systematic review.

This systematic review aims to provide a summary of the results from individual studies that specifically focused on overweight or obese populations, regardless of age or sex. The goal is to determine the effects of structured recreational team sports interventions (TSG) on metabolic health, body composition and physical fitness parameters when compared to passive or active control groups. This study adhered to the PRISMA guidelines for reporting a systematic review. A thorough examination of relevant literature was conducted on November 06, 2023, using three prominent databases: PubMed, Scopus, and the Web of Science. Inclusion criteria considered overweight (e.g., BMI 25.0-29.9 kg/m2) and obese (e.g., BMI > 30 kg/m2) populations exposed to training interventions using recreational team sports, while the comparator group consisted of the same populations not exposed to exercise (passive controls) or exposed to alternative training methods. The primary outcomes of interest were metabolic health parameters (glucose, waist circumference, blood pressure, cholesterol, triglycerides), body composition (e.g., fat mass, lean mass), as well as physical fitness parameters (e.g., aerobic fitness, muscular fitness). Only studies with two- or multi-arm designs, whether randomized or not, were eligible for inclusion. The PEDro scale was used to assess the methodological bias of the included studies. Out of the initial 275 titles retrieved, we deemed ten eligible for our study. In terms of body composition, TSG demonstrated a significant decrease in body mass index across three studies (-2.3 to -5.1%) and a significant reduction in waist circumference in four studies (-4.6% to -8.4%). Regarding blood pressure, TSG exhibited a significant decrease in systolic blood pressure in two studies (-3.9% to -8.3%), while diastolic blood pressure showed a significant decrease in only one study (-7.3%). Cholesterol levels saw a significant decrease in TSG in three studies (-7.0% to -9.7%), and triglyceride levels showed a significant reduction in four studies (-16.4% to -20.1%). In terms of aerobic fitness, TSG demonstrated within-group improvements in the field-based tests in three studies (8.1% to 79.0%), and within-group improvements in maximal oxygen uptake in four studies (6.5% to 31.0%), with significant favoring of TSG in most studies. Overall, TSG demonstrated significant benefits for overweight and obese populations compared to the control group, particularly in terms of improvements in body mass index, systolic blood pressures, cholesterol and triglyceride levels, and aerobic fitness. Future research ought to concentrate on tailoring responses to varying training volumes on an individualized basis.

Differential expression profiles and functional prediction of circular RNAs in lung cancer patients with chronic obstructive pulmonary disease: a pilot study.

Chronic obstructive pulmonary disease (COPD), characterized by clinical sub-phenotypes such as emphysema (E) and chronic bronchitis (CB), is associated with a greater risk of lung cancer (LC). This study aimed to assess the expression patterns of circRNA and their potential functional involvement in LC patients with COPD. A circRNA microarray was used to characterize differentially expressed circRNAs (DEcircRNAs) profiles. A total of 176, 240, 163, and 243 DEcircRNAs were identified in comparisons between CB vs. LC patients (Con), E vs. Con, E vs. CB, and CBE vs. Con, respectively. DEcircRNAs in all comparison groups were primarily associated with immune-related GO terms and were also enriched in immune and inflammatory pathways. In total, 49 DEcircRNAs were significantly correlated with the infiltration of multiple immune cells. Among them, hsa-MROH9_0001 and hsa-RP11-35J10_0013 were positively and negatively correlated with plasma cells and T-cell CD4 memory resting cells, respectively; these two DEcircRNA-sponged miRNAs have good diagnostic performance. WGCNA identified six key circRNAs associated with CB progression. The expression patterns of hsa-MROH9_0001 and circRNA_21729 in E and CB groups were confirmed by RT-qPCR. In conclusion, we reported circRNA profiles and the findings demonstrated that hsa-MROH9_0001 and circRNA_21729 may be potential therapeutic targets for LC with COPD.

Trace Iron-Doped Nickel-Cobalt selenide with rich heterointerfaces for efficient overall water splitting at high current densities.

Developing bifunctional electrocatalysts based on non-precious metals for overall water splitting, while maintaining high catalytic activity and stability under high current densities, remains challenging. Herein, we successfully constructred trace iron-doped nickel-cobalt selenide with abundant CoSe2 (210)-Ni3Se4 (202) heterointerfaces via a simple one-step selenization reaction. The synthesized Fe-NiCoSex/NCFF (NCFF stands for nickel-cobalt-iron foam) exhibits outstanding hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) activity with low overpotentials of 328 mV for HER and 345 mV for OER at a high current density of 1000 mA cm-2, while maintaining stability for over 20 h. Additionally, the Fe-NiCoSex/NCFF exhibits the lowest Tafel slope values for both HER (33.7 mV dec-1) and OER (55.92 mV dec-1), indicating the fastest kinetics on its surface. The Fe-NiCoSex/NCFF features uniformly distributed micrometer-sized selenide particles with dense nanowires on their surface, providing a large reactive surface area and abundant active sites. Moreover, X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) analyses reveal that the catalyst is composed of nickel, cobalt, and iron, forming micrometer-sized particles with both crystalline and amorphous phases, thereby enhancing HER and OER performance under high current density. Density functional theory (DFT) calculations demonstrate that the heterostructure CoSe2 (210)-Ni3Se4 (202), with high electron density and suitable adsorption capacity for reaction intermediates, and low energy barriers for HER (-0.384 eV) and OER (ΔG1st: 0.243 eV, ΔG2nd: 0.376 eV), serves as an active center for both HER and OER.

Study on factors influencing carbon dioxide emissions and carbon peak heterogenous pathways in Chinese provinces.

Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government.

ReMAR: a preoperative CT angiography guided metal artifact reduction framework designed for follow-up CTA of endovascular coiling.

OBJECTIVE: Follow-up CT Angiography (CTA) is necessary for ensuring occlusion effect of endovascular coiling. However, the implanted metal coil will introduce artifacts that have a negative spillover into radiologic assessment. Method. A framework named ReMAR is proposed in this paper for metal artifacts reduction (MAR) from follow-up CTA of patients with coiled aneurysms. It employs preoperative CTA to provide the prior knowledge of the aneurysm and the expected position of the coil as a guidance thus balances the metal artifacts removal performance and clinical feasibility. The ReMAR is composed of three modules: segmentation, registration and MAR module. The segmentation and registration modules obtain the metal coil knowledge via implementing aneurysms delineation on preoperative CTA and alignment of follow-up CTA. The MAR module consisting of hybrid CNN- and transformer- architectures is utilized to restore sinogram and remove the artifact from reconstructed image. Both image quality and vessel rendering effect after metal artifacts removal are assessed in order to responding clinical concerns. Main results. 137 patients undergone endovascular coiling have been enrolled in the study: 13 of them have complete diagnosis/follow-up records for end-to-end validation, while the rest lacked of follow-up records are used for model training. Quantitative metrics show ReMAR significantly reduced the metal-artifact burden in follow-up CTA. Qualitative ranks show ReMAR could preserve the morphology of blood vessels during artifact removal as desired by doctors. Significance. The ReMAR could significantly remove the artifacts caused by implanted metal coil in the follow-up CTA. It can be used to enhance the overall image quality and convince CTA an alternative to invasive follow-up in treated intracranial aneurysm (IA).

Selective N-functionalization of Arylhydrazines with Primary Alcohols and Acids under PPh3/DDQ System.

We present a PPh3/DDQ-mediated regiospecific selective N-functionalization of arylhydrazines with primary benzylic alcohols and aryl carboxylic acids for the synthesis of N1-benzyl arylhydrazines and N2-acyl arylhydrazines, respectively. This metal- and base-free approach features very short reaction times (about 10 min), broad substrate scope, good functional group tolerance, and mild reaction conditions. Furthermore, N1-benzlated products have also been successfully applied to the concise synthesis of N-substituted indoles and anticancer drug MDM2 inhibitor.

Impact of Molecular Chlorine Production from Aerosol Iron Photochemistry on Atmospheric Oxidative Capacity in North China.

Elevated levels of atmospheric molecular chlorine (Cl2) have been observed during the daytime in recent field studies in China but could not be explained by the current chlorine chemistry mechanisms in models. Here, we propose a Cl2 formation mechanism initiated by aerosol iron photochemistry to explain daytime Cl2 formation. We implement this mechanism into the GEOS-Chem chemical transport model and investigate its impacts on the atmospheric composition in wintertime North China where high levels of Cl2 as well as aerosol chloride and iron were observed. The new mechanism accounts for more than 90% of surface air Cl2 production in North China and consequently increases the surface air Cl2 abundances by an order of magnitude, improving the model's agreement with observed Cl2. The presence of high Cl2 significantly alters the oxidative capacity of the atmosphere, with a factor of 20-40 increase in the chlorine radical concentration and a 20-40% increase in the hydroxyl radical concentration in regions with high aerosol chloride and iron loadings. This results in an increase in surface air ozone by about 10%. This new Cl2 formation mechanism will improve the model simulation capability for reactive chlorine abundances in the regions with high emissions of chlorine and iron.

Combined application of myo-inositol and corn steep liquor enhances seedling growth and cold tolerance in cucumber and tomato.

Low temperatures pose a common challenge in the production of cucumbers and tomatoes, hindering plant growth and, in severe cases, leading to plant death. In our investigation, we observed a substantial improvement in the growth of cucumber and tomato seedlings through the application of corn steep liquor (CSL), myo-inositol (MI), and their combinations. When subjected to low-temperature stress, these treatments resulted in heightened levels of photosynthetic pigments, thereby fostering enhanced photosynthesis in both tomato and cucumber plants. Furthermore, it contributed to a decrease in malondialdehyde (MDA) levels and electrolyte leakage (REP). The effectiveness of the treatment was further validated through the analysis of key gene expressions (CBF1, COR, MIOX4, and MIPS1) in cucumber. Particularly, noteworthy positive outcomes were noted in the treatment involving 0.6 mL L-1 CSL combined with 72 mg L-1 MI. This study provides valuable technical insights into leveraging the synergistic effects of inositol and maize leachate to promote early crop growth and bolster resistance to low temperatures.

Mapping the distribution of Nipah virus infections: a geospatial modelling analysis.

BACKGROUND: Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia. METHODS: In this geospatial modelling analysis, we developed an integrated database containing information on the distribution of Nipah virus infections in humans and animals from 1998 to 2021. We conducted phylodynamic analysis to examine the evolution and migration pathways of the virus and meta-analyses to estimate the adjusted case-fatality rate. We used two boosted regression tree models to identify the potential ecological drivers of Nipah virus occurrences in spillover events and endemic areas, and mapped potential risk areas for Nipah virus endemicity. FINDINGS: 749 people and eight bat species across nine countries were documented as being infected with Nipah virus. On the basis of 66 complete genomes of the virus, we identified two clades-the Bangladesh clade and the Malaysia clade-with the time of the most recent common ancestor estimated to be 1863. Adjusted case-fatality rates varied widely between countries and were higher for the Bangladesh clade than for the Malaysia clade. Multivariable meta-regression analysis revealed significant relationships between case-fatality rate estimates and viral clade (p=0·0021), source country (p=0·016), proportion of male patients (p=0·036), and travel time to health-care facilities (p=0·036). Temperature-related bioclimate variables and the probability of occurrence of Pteropus medius were important contributors to both the spillover and the endemic infection models. INTERPRETATION: The suitable niches for Nipah virus are more extensive than previously reported. Future surveillance efforts should focus on high-risk areas informed by updated projections. Specifically, intensifying zoonotic surveillance efforts, enhancing laboratory testing capacity, and implementing public health education in projected high-risk areas where no human cases have been reported to date will be crucial. Additionally, strengthening wildlife surveillance and investigating potential modes of transmission in regions with documented human cases is needed. FUNDING: The Key Research and Development Program of China.

A cargo sorting receptor mediates chloroplast protein trafficking through the secretory pathway.

Nucleus-encoded chloroplast proteins can be transported via the secretory pathway. The molecular mechanisms underlying the trafficking of chloroplast proteins between the intracellular compartments are largely unclear, and a cargo sorting receptor has not previously been identified in the secretory pathway. Here we report a cargo sorting receptor that is specifically present in Viridiplantae and mediates the transport of cargo proteins to the chloroplast. Using a forward genetic analysis, we identified a gene encoding a transmembrane protein (MtTP930) in barrel medic (Medicago truncatula). Mutation of MtTP930 resulted in impaired chloroplast function and a dwarf phenotype. MtTP930 is highly expressed in the aerial parts of the plant and is localized to the ER exit sites (ERESs) and Golgi. MtTP930 contains typical cargo sorting receptor motifs, interacts with Sar1, Sec12 and Sec24, and participates in coat protein II (COPII) vesicular transport. Importantly, MtTP930 can recognize the cargo proteins plastidial N-glycosylated nucleotide pyrophosphatase/ phosphodiesterase (MtNPP) and α-carbonic anhydrase (MtCAH) in the ER, and then transport them to the chloroplast via the secretory pathway. Mutation of a homolog of MtTP930 in Arabidopsis (Arabidopsis thaliana) resulted in a similar dwarf phenotype. Furthermore, MtNPP-GFP failed to localize to chloroplasts when transgenically expressed in Attp930 protoplasts, implying that these cargo sorting receptors are conserved in plants. These findings fill a gap in our understanding of the mechanism by which chloroplast proteins are sorted and transported via the secretory pathway.

Synergistic solidification and mechanism research of electrolytic manganese residue and coal fly ash based on C-A-S-H gel material.

Electrolytic manganese residue (EMR) is known for high concentrations of Mn2+, NH4+, and heavy metals. Failure to undergo benign treatment and landfill disposal would undeniably lead to negative impacts on the quality of the surrounding ecological environment. This study sought to mitigate the latent environmental risks associated with EMR using a cooperative solidification/stabilization (S/S) method involving coal fly ash (CFA). Leveraging leaching toxicity tests, the leaching behavior of pollutants in electrolytic manganese residue-based geopolymer materials (EMRGM) was determined. At the same time, mechanistic insights into S/S processes were explored utilizing characterization techniques such as XRF, XRD, FT-IR, SEM-EDS, and XPS. Those results confirmed significant reductions in the leaching toxicities of Mn2+ and NH4+ to 4.64 µg/L and 0.99 mg/L, respectively, with all other heavy metal ions falling within the permissible limits set by relevant standards. Further analysis shows that most of NH4+ volatilizes into the air as NH3, and a small part is fixed in the EMRGM in the form of struvite; in addition to being oxidized to MnOOH and MnO2, Mn2+ will also be adsorbed and wrapped by silicon-aluminum gel together with other heavy metal elements in the form of ions or precipitation. This research undeniably provides a solid theoretical foundation for the benign treatment and resourceful utilization of EMR and CFA, two prominent industrial solid wastes.

GraphADT: Empowering interpretable predictions of acute dermal toxicity with Multi-View graph pooling and structure remapping.

MOTIVATION: Accurate prediction of acute dermal toxicity (ADT) is essential for the safe and effective development of contact drugs. Currently, graph neural networks (GNNs), a form of deep learning technology, accurately model the structure of compound molecules, enhancing predictions of their ADT. However, many existing methods emphasize atom-level information transfer and overlook crucial data conveyed by molecular bonds and their interrelationships. Additionally, these methods often generate" equal" node representations across the entire graph, failing to accentuate" important" substructures like functional groups, pharmacophores, and toxicophores, thereby reducing interpretability. RESULTS: We introduce a novel model, GraphADT, utilizing structure remapping and multi-view graph pooling technologies to accurately predict compound ADT. Initially, our model applies structure remapping to better delineate bonds, transforming" bonds" into new nodes and" bond-atom-bond" interactions into new edges, thereby reconstructing the compound molecular graph. Subsequently, we employ multi-view graph pooling to amalgamate data from various perspectives, minimizing biases inherent to single-view analyses. Following this, the model generates a robust node ranking collaboratively, emphasizing critical nodes or substructures to enhance model interpretability. Lastly, we apply a graph comparison learning strategy to train both the original and structure remapped molecular graphs, deriving the final molecular representation. Experimental results on public datasets indicate that the GraphADT model outperforms existing state-of-the-art models. The GraphADT model has been demonstrated to effectively predict compound ADT, offering potential guidance for the development of contact drugs and related treatments. AVAILABILITY AND IMPLEMENTATION: Our code and data are accessible at: https://github.com/mxqmxqmxq/GraphADT.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Development and Validation of Machine Learning-Based Models for Prediction of Intensive Care Unit Admission and In-Hospital Mortality in Patients with Acute Exacerbations of Chronic Obstructive Pulmonary Disease.

Background: This present work focused on predicting prognostic outcome of inpatients developing acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and enhancing patient monitoring and treatment by using objective clinical indicators. Methods: The present retrospective study enrolled 322 AECOPD patients. Registry data downloaded based on COPD Pay-for-Performance Program database from January 2012 to December 2018 were used to check whether the enrolled patients were eligible. Our primary and secondary outcomes were ICU admission and in-hospital mortality, respectively. The best feature subset was chosen by recursive feature elimination. Moreover, seven machine learning (ML) models were trained for forecasting ICU admission among AECOPD patients, and the model with the most excellent performance was used. Results: According to our findings, random forest (RF) model showed superb discrimination performance, and the values of area under curve (AUC) were 0.973 and 0.828 in training and test cohorts, separately. Additionally, according to decision curve analysis, the net benefit of RF model was higher when differentiating patients with a high risk of ICU admission at a <0.55 threshold probability. Moreover, the ML-based prediction model was also constructed to predict in-hospital mortality, and it showed excellent calibration and discrimination capacities. Conclusion: The ML model was highly accurate in assessing the ICU admission and in-hospital mortality risk for AECOPD cases. Maintenance of model interpretability helped effectively provide accurate and lucid risk prediction of different individuals.

Carotid revascularisation versus medical treatment for asymptomatic carotid artery stenosis.

OBJECTIVES: This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To compare the safety and efficacy of carotid revascularisation plus best medical treatment with best medical treatment alone in people with asymptomatic carotid artery stenosis.