Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the ...experimental investigation of all drug combinations to become costly and time-consuming. Computational techniques can improve the efficiency of drug combination screening. Despite recent advances in applying machine learning to synergistic drug combination prediction, several challenges remain. First, the performance of existing methods is suboptimal. There is still much space for improvement. Second, biological knowledge has not been fully incorporated into the model. Finally, many models are lack interpretability, limiting their clinical applications. To address these challenges, we have developed a knowledge-enabled and self-attention transformer boosted deep learning model, TranSynergy, which improves the performance and interpretability of synergistic drug combination prediction. TranSynergy is designed so that the cellular effect of drug actions can be explicitly modeled through cell-line gene dependency, gene-gene interaction, and genome-wide drug-target interaction. A novel Shapley Additive Gene Set Enrichment Analysis (SA-GSEA) method has been developed to deconvolute genes that contribute to the synergistic drug combination and improve model interpretability. Extensive benchmark studies demonstrate that TranSynergy outperforms the state-of-the-art method, suggesting the potential of mechanism-driven machine learning. Novel pathways that are associated with the synergistic combinations are revealed and supported by experimental evidences. They may provide new insights into identifying biomarkers for precision medicine and discovering new anti-cancer therapies. Several new synergistic drug combinations have been predicted with high confidence for ovarian cancer which has few treatment options. The code is available at https://github.com/qiaoliuhub/drug_combination.
Background To date, coronavirus disease 2019 (COVID-19) becomes increasingly fierce due to the emergence of variants. Rapid herd immunity through vaccination is needed to block the mutation and ...prevent the emergence of variants that can completely escape the immune surveillance. We aimed to systematically evaluate the effectiveness and safety of COVID-19 vaccines in the real world and to establish a reliable evidence-based basis for the actual protective effect of the COVID-19 vaccines, especially in the ensuing waves of infections dominated by variants. Methods We searched PubMed, Embase and Web of Science from inception to July 22, 2021. Observational studies that examined the effectiveness and safety of SARS-CoV-2 vaccines among people vaccinated were included. Random-effects or fixed-effects models were used to estimate the pooled vaccine effectiveness (VE) and incidence rate of adverse events after vaccination, and their 95% confidence intervals (CI). Results A total of 58 studies (32 studies for vaccine effectiveness and 26 studies for vaccine safety) were included. A single dose of vaccines was 41% (95% CI: 28-54%) effective at preventing SARS-CoV-2 infections, 52% (31-73%) for symptomatic COVID-19, 66% (50-81%) for hospitalization, 45% (42-49%) for Intensive Care Unit (ICU) admissions, and 53% (15-91%) for COVID-19-related death; and two doses were 85% (81-89%) effective at preventing SARS-CoV-2 infections, 97% (97-98%) for symptomatic COVID-19, 93% (89-96%) for hospitalization, 96% (93-98%) for ICU admissions, and 95% (92-98%) effective for COVID-19-related death, respectively. The pooled VE was 85% (80-91%) for the prevention of Alpha variant of SARS-CoV-2 infections, 75% (71-79%) for the Beta variant, 54% (35-74%) for the Gamma variant, and 74% (62-85%) for the Delta variant. The overall pooled incidence rate was 1.5% (1.4-1.6%) for adverse events, 0.4 (0.2-0.5) per 10 000 for severe adverse events, and 0.1 (0.1-0.2) per 10 000 for death after vaccination. Conclusions SARS-CoV-2 vaccines have reassuring safety and could effectively reduce the death, severe cases, symptomatic cases, and infections resulting from SARS-CoV-2 across the world. In the context of global pandemic and the continuous emergence of SARS-CoV-2 variants, accelerating vaccination and improving vaccination coverage is still the most important and urgent matter, and it is also the final means to end the pandemic. Graphical Keywords: SARS-CoV-2, Vaccine, Effectiveness, Safety, Meta-analysis
Graphitic carbon nitride (g-C3N4) polymer was doped with cobalt species and supported on a similar sp2 structure graphene, to form a novel nitrogen–metal macrocyclic catalyst for the oxygen reduction ...reaction (ORR) in alkaline fuel cells. The structural characterizations confirmed the formation of Co–N bonds and the close electron coupling between Co-g-C3N4 and graphene sheets. The electrocatalytic measurements demonstrated Co-g-C3N4-catalyzed reduction of oxygen mainly in a four electron pathway. The improvement of ORR activity is closely related to the abundant accessible Co–N x active sites and fast charge transfer at the interfaces of Co-g-C3N4/graphene. Also, Co-g-C3N4@graphene exhibited comparable ORR activity, better durability, and methanol tolerance ability in comparison to Pt/C, and bodes well for a promising non-noble cathode catalyst for the application of direct methanol fuel cells. The chemical doping strategy in this work would be helpful to improve other present catalysts for fuel cell applications.
Due to its practicality, hybrid flowshop scheduling problem (HFSP) with productivity objective has been extensively explored. However, studies on HFSP considering green objective in distributed ...production environment are quite limited. Moreover, the current manufacturing mode is gradually evolving toward distributed co-production mode. Thus, this paper investigated a distributed hybrid flowshop scheduling problem (DHFSP) with objectives of minimization the makespan and total energy consumption (TEC). To address this problem, this paper designed a Pareto-based multi-objective hybrid iterated greedy algorithm (MOHIG) by integrating the merits of genetic operator and iterated greedy heuristic. In this MOHIG, firstly, one cooperative initialization strategy is proposed to boost initial solutions’ quality based on the previous experience and rules. Secondly, one knowledge-based multi-objective local search method is invented to enhance the exploitation capability according to characteristics of problem. Thirdly, an energy-saving technique is developed to decrease the idle energy consumption of machine tools. Furthermore, the effectiveness of each improvement component of MOHIG is assessed by three common indicators. Finally, the proposed MOHIG algorithm is compared with other multi-objective optimization algorithms, including SPEA2, MOEA/D, and NSGAII. Experimental results indicate that the proposed MOHIG outperforms its compared algorithms in solving this problem. In addition, this research can better guide practical production in some certain environments.
•Considering green scheduling in distributed hybrid flowshop environment.•Designing a new energy-saving strategy into this problem.•Proposing a Pareto-based multi-objective hybrid iterated greedy algorithm (MOHIG).•Evaluating performance of the proposed MOHIG by conducting comparison experiments.
Here, the hybrid of NiCo2S4 nanoparticles grown on graphene in situ is first described as an effective bifunctional nonprecious electrocatalyst for oxygen reduction reaction (ORR) and oxygen ...evolution reaction (OER) in the alkaline medium. NiCo2S4@N/S-rGO was synthesized by a one-pot solvothermal strategy using Co(OAc)2, Ni(OAc)2, thiourea, and graphene oxide as precursors and ethylene glycol as the dispersing agent; simultaneously, traces of nitrogen and sulfur were double-doped into the reduced graphene oxide (rGO) in the forms of pyrrolic-N, pyridinic-N, and thiophenic-S, which are often desirable for metal-free ORR catalysts. In comparison with commercial Pt/C catalyst, NiCo2S4@N/S-rGO shows less reduction activity, much better durability, and superior methanol tolerance toward ORR in 0.1 M KOH; it reveals higher activity toward OER in both KOH electrolyte and phosphate buffer at pH 7.0. NiCo2S4@graphene demonstrated excellent overall bicatalytic performance, and importantly, it suggests a novel kind of promising nonprecious bifunctional catalyst in the related renewable energy devices.
Multiple sclerosis is characterized by inflammatory activity that results in destruction of the myelin sheaths that enwrap axons. The currently available medications for multiple sclerosis are ...predominantly immune-modulating and do not directly promote repair. White matter regeneration, or remyelination, is a new and exciting potential approach to treating multiple sclerosis, as remyelination repairs the damaged regions of the central nervous system. A wealth of new strategies in animal models that promote remyelination, including the repopulation of oligodendrocytes that produce myelin, has led to several clinical trials to test new reparative therapies. In this Review, we highlight the biology of, and obstacles to, remyelination. We address new strategies to improve remyelination in preclinical models, highlight the therapies that are currently undergoing clinical trials and discuss the challenges of objectively measuring remyelination in trials of repair in multiple sclerosis.
Identification of grain shape determining genes can facilitate breeding of rice cultivars with optimal grain shape and appearance quality. Here, we identify GS9 (Grain Shape Gene on Chromosome 9) ...gene by map-based cloning. The gs9 null mutant has slender grains, while overexpression GS9 results in round grains. GS9 encodes a protein without known conserved functional domain. It regulates grain shape by altering cell division. The interaction of GS9 and ovate family proteins OsOFP14 and OsOFP8 is modulated by OsGSK2 kinase, a key regulator of the brassinosteroids signaling pathway. Genetic interaction analysis reveals that GS9 functions independently from other previously identified grain size genes. Introducing the gs9 allele into elite rice cultivars significantly improves grain shape and appearance quality. It suggests potential application of gs9, alone or in combination with other grain size determining genes, in breeding of rice varieties with optimized grain shape.
The Himalaya, the world's highest mountain ranges, are home to a large group of glaciers and glacial lakes. Glacial lake outburst floods (GLOFs) in this region have resulted in catastrophic damages ...and fatalities in the past decades. The recent warming has caused dramatic glacial lake changes and increased potential GLOF risk in the Himalaya. However, our knowledge on the current state and change of glacial lakes in the entire Himalaya is limited. This study maps the current (2015) distribution of glacial lakes across the entire Himalaya and monitors the spatially-explicit evolution of glacial lakes over five time periods from 1990 to 2015 using a total of 348 Landsat images at 30m resolution. The results show that 4950 glacial lakes in 2015 cover a total area of 455.3±72.7km2, mainly located between 4000m and 5700m above sea level. Himalayan glacial lakes expanded by approximately 14.1% from 1990 to 2015. The changing patterns of supraglacial lakes and proglacial lakes are rather complex, involving both lake disappearance and emergence. Many emergent glacial lakes are found at higher elevations, especially the new proglacial lakes, which have formed as a result of glacier retreat. Spatially heterogeneous changes of Himalayan glacial lakes are observed, with the most significant expansion occurring in the southern slopes of the central Himalaya. Increasing glacier meltwater induced by the Himalayan atmospheric warming is a primary cause for the observed lake expansion. This study provides primary data for future GLOF risk assessments. A total of 118 rapidly expanded glacial lakes are identified as potential vulnerable lakes for the priority of risk assessment.
•Revealing the distribution of Himalayan glacial lakes using Landsat 8 images in 2015•Demonstrating the evolution and regional heterogeneity of Himalayan glacial lakes•Detecting the rapidly expanding glacial lakes with potential outburst risk
This article investigates whether market competition enhances the incentives of Chinese industrial firms to avoid corporate income tax. We estimate the effects of competition on the relationship ...between firms' reported accounting profits and their imputed profits based on the national income account. To cope with measurement errors and potential endogeneity, we use instrumental variables, exogenous policy shocks and other robustness analysis. We find robust and consistent evidence that firms in more competitive environments engage in more tax avoidance activities. Moreover, all else equal, firms in relatively disadvantageous positions demonstrate stronger incentives to avoid corporate income tax.
Glacial lake outburst flood (GLOF) is a serious hazard in high, mountainous regions. In the Himalayas, catastrophic risks of GLOFs have increased in recent years because most Himalayan glaciers have ...experienced remarkable downwasting under a warming climate. However, current knowledge about the distribution and recent changes in glacial lakes within the central Himalaya mountain range is still limited. Here, we conducted a systematic investigation of the glacial lakes within the entire central Himalaya range by using an object-oriented image processing method based on the Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper (ETM) images from 1990 to 2010. We extracted the lake boundaries for four time points (1990, 2000, 2005 and 2010) and used a time series inspection method combined with a consistent spatial resolution of Landsat images that consistently revealed lake expansion. Our results show that the glacial lakes expanded rapidly by 17.11% from 1990 to 2010. The pre-existing, larger glacial lakes, rather than the newly formed lakes, contributed most to the areal expansion. The greatest expansions occurred at the altitudinal zones between 4800 m and 5600 m at the north side of the main Himalayan range and between 4500 m and 5600 m at the south side, respectively. Based on the expansion rate, area and type of glacial lakes, we identified 67 rapidly expanding glacial lakes in the central Himalayan region that need to be closely monitored in the future. The warming and increasing amounts of light-absorbing constituents of snow and ice could have accelerated the melting that directly affected the glacial lake expansion. Across the main central Himalayas, glacial lakes at the north side show more remarkable expansion than those at the south side. An effective monitoring and warning system for critical glacial lakes is urgently needed.
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