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The Rhus gall aphid Schlechtendalia chinensis uses the species Rhus chinensis as its primary host plant, on which galls are produced. The galls have medicinal properties and can be used in various situations due to their high tannin content. Detoxification enzymes play significant roles in the insect lifecycle. In this study, we focused on five detoxification gene families, i.e., glutathione-S-transferase (GST), ABC transporter (ABC), Carboxylesterase (CCE), cyto-chrome P450 (CYP), and UDP-glycosyltransferase (UDP), and manually annotated 144 detoxification genes of S. chinensis using genome-wide techniques. The detoxification genes appeared mostly on chromosome 1, where a total of two pair genes were identified to show tandem duplications. There were 38 gene pairs between genomes of S. chinensis and Acyrthosiphon pisum in the detoxification gene families by collinear comparison. Ka/Ks ratios showed that detoxification genes of S. chinensis were mainly affected by purification selection during evolution. The gene expression numbers of P450s and ABCs by transcriptome sequencing data were greater, while gene expression of CCEs was the highest, suggesting they might be important in the detoxification process. Our study has firstly identified the genes of the different detoxification gene families in the S. chinensis genome, and then analyzed their general features and expression, demonstrating the importance of the detoxification genes in the aphid and providing new information for further research. [ABSTRACT FROM AUTHOR]

Residences in poor regions always depend on rain-fed agriculture, so they urgently need suitable tools to make accurate meteorological predictions. Unfortunately, meteorological observations in these regions are usually sparse and irregularly distributed. Conventional LSTM networks only handle temporal sequences and cannot utilize the links of meteorological variables among stations. GCN-LSTM networks only capture local spatial structures through the simple structures of fixed adjacency matrices, and the CNN-LSTM can only mine gridded meteorological observations for further predictions. In this study, we propose an optimization hybrid of multiple-lag LSTM networks for meteorological predictions. Our model can make full use of observed data at partner stations under different time-lag windows and strong links among the local observations of meteorological variables to produce future predictions. Numerical experiments on the meteorological predictions of Bangladesh demonstrate that our networks are superior to the classic LSTM and its variants GCN-LSTM and CNN-LSTM, as well as the SVM and DT. [ABSTRACT FROM AUTHOR]

Under global warming scenarios, extreme climate events in South Asia will occur more frequently which will seriously threaten the safety of local residents. South Asia faces dual pressures of the obligation of carbon emissions reduction globally and the demand for a better life for huge populations. Stratospheric Aerosol Injection (SAI) climate engineering provides a potential solution to this dilemma. We compared the evolution of 12 climate extreme indices under historical scenarios, two future scenarios (SSP245, SSP585) and an implementation scenario of SAI climate engineering (G6sulfur). We showed that the intensity and frequency of extreme climates under a G6sulfur scenario would be significantly higher than those under historical scenarios, and that the difference in extreme climates under three scenarios (SSP245, SSP585, and G6sulfur) would be widely varying, with some indices being considerably mitigated while others would reflect a worse set of circumstances than would be the case without SAI climate engineering. Therefore, SAI climate engineering is not an effective tool to mitigate future climate extremes in South Asia under global warming scenarios. [ABSTRACT FROM AUTHOR]

Multifractal detrended fluctuation analysis (DFA) can extract multi-scaling behavior and measure long-range correlations in climatic time series. In this study, with the help of multifractal DFA, we investigated the scaling behavior of daily minimum/maximum temperatures during the years 1989–2019 from 34 meteorological stations in Bangladesh. We revealed spatial patterns, topographic impacts and global warming impacts of long-range correlations embedded in small and large fluctuations in temperature time series. Meanwhile, we developed a multifractal DFA-based algorithm to dynamically determine thresholds to discriminate extreme and non-extreme events in climate systems and applied it to analyze the frequency and trends of temperature extremes in Bangladesh. Compared with widely-used percentile thresholds, the extreme climate events captured in our algorithm are more reliable since they are determined dynamically by the climate system itself. [ABSTRACT FROM AUTHOR]

Knowledge of factors that are important in reef resilience and integrity help us understand how reef ecosystems react following major anthropogenic and environmental disturbances. The North Jamaican fringing reefs have shown some recent resilience to acute disturbances from hurricanes and bleaching, in addition to the recurring chronic stressors of over-fishing and land development. Factors that can improve coral reef resilience are reviewed, and reef rugosity is shown to correlate with coral cover and growth, particularly for branching Acropora species. The biodiversity index for the Jamaican reefs was lowered after the 2005 mass bleaching event, as were the numbers of coral colonies, but both had recovered by 2009. The importance of coastal zone reef management strategies and the economic value of reefs are discussed, and a protocol is suggested for future management of Jamaican reefs. [ABSTRACT FROM AUTHOR]

As a developing country with an agricultural economy as a pillar, Bangladesh is highly vulnerable to adverse effects of climate change, so the generation of high-resolution temperature maps is of great value for Bangladesh to achieve agricultural sustainable development. However, Bangladesh's weak economy and sparse meteorological stations make it difficult to obtain such maps. In this study, by mining internal features and links inside observed data, we developed an efficient data-driven downscaling technique to generate high spatial-resolution temperature distribution maps of Bangladesh directly from observed temperature data at 34 meteorological stations with irregular distribution. Based on these high-resolution historical temperature maps, we further explored a data-driven forecast technique to generate high-resolution temperature maps of Bangladesh for the period 2025–2035. Since the proposed techniques are very low-cost and fully mine internal links inside irregular-distributed observations, they can support relevant departments of Bangladesh to formulate policies to mitigate and adapt to climate change in a timely manner. [ABSTRACT FROM AUTHOR]

Tumor mutational burden (TMB) is considered a potential biomarker for predicting the response and effect of immune checkpoint inhibitors (ICIs). However, there are still inconsistent standards of gene panels using next-generation sequencing and poor correlation between the TMB genes, immune cell infiltrating, and prognosis. We applied text-mining technology to construct specific TMB-associated gene panels cross various cancer types. As a case exploration, Pearson's correlation between TMB genes and immune cell infiltrating was further analyzed in colorectal cancer. We then performed LASSO Cox regression to construct a prognosis predictive model and calculated the risk score of each sample for receiver operating characteristic (ROC) analysis. The results showed that the assessment of TMB gene panels performed well with fewer than 500 genes, highly mutated genes, and the inclusion of synonymous mutations and immune regulatory and drug-target genes. Moreover, the analysis of TMB differentially expressed genes (DEGs) suggested that JAKMIP1 was strongly correlated with the gene expression level of CD8+ T cell markers in colorectal cancer. Additionally, the prognosis predictive model based on 19 TMB DEGs reached AUCs of 0.836, 0.818, and 0.787 in 1-, 3-, and 5-year OS models, respectively (C-index: 0.810). In summary, the gene panel performed well and TMB DEGs showed great potential value in immune cell infiltration and in predicting survival. [ABSTRACT FROM AUTHOR]

This study developed models to solve problems of optimisation, production, and consumption in waste management based on methods of system analysis. Mathematical models of the problems of optimisation and sustainable waste management in deterministic conditions and in a fuzzy environment were formulated. The income from production was maximised considering environmental standards that apply to the field of macroeconomics and microeconomics. The proposed approach used MANAGER software to formalise and solve the problem of revenue optimisation with production waste management to optimise the production of oil products with waste management at a specific technological facility of the Atyrau oil refinery in Kazakhstan. Based on the combined application of the principles of maximin and Pareto optimality, a formulation of the problem of production optimisation with waste management was obtained and a heuristic algorithm for solving the formulated fuzzy optimisation problem with waste management was developed. [ABSTRACT FROM AUTHOR]