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The invasive golden apple snail Pomacea canaliculata has a strong reproductive capacity and has rapidly spread in Asian countries. Current control methods include physical, chemical, and biological approaches, but there has been limited research on the control of P. canaliculata in its different life stages. This study assessed the effectiveness of using giant river prawns Macrobrachium rosenbergii in controlling juveniles of P. canaliculata through a controlled indoor experiment. The density, size, and dispersal range of recently hatched juvenile snails were significantly lower among those kept with prawns than those kept without prawns, indicating a control effect of M. rosenbergii at least on P. canaliculata juveniles. Furthermore, the study speculates on the potential application of M. rosenbergii in the context of a rice–prawn symbiotic system of ecological farming to control invasive P. canaliculata. In terms of effectiveness and safety, its application might lead to a win-win situation for both rice-farm profits and the ecological benefits of invasive species control. [ABSTRACT FROM AUTHOR]

Quality-related prediction in the continuous-casting process is important for the quality and process control of casting slabs. As intelligent manufacturing technologies continue to evolve, numerous data-driven techniques have been available for industrial applications. This case study was aimed at developing a machine-learning algorithm, capable of predicting slag inclusion defects in continuous-casting slabs, based on process condition sensor data. A large dataset consisting of sensor data from nearly 7300 casting samples has been analyzed, with the empirical mode decomposition (EMD) algorithm utilized to process the multi-modal time series. The following machine-learning algorithms have been examined: K-Nearest neighbors, support vector classifier (linear and nonlinear kernels), decision trees, random forests, AdaBoost, and Artificial Neural Networks. Four over-sampling or under-sampling algorithms have been adopted to solve imbalanced data distribution. In the experiment, the optimized random forest outperformed other machine-learning algorithms in terms of recall and ROC AUC, which could provide valuable insights for quality control. [ABSTRACT FROM AUTHOR]

With the change of climate issues and the needs of economic development, the idea of practicing green and low-carbon behaviors sinks deeper and deeper into people's hearts. This paper based on the social cost of carbon (SCC) model, this paper constructs a new carbon social cost model by adding the impact of green low-carbon behavior. Classify climate states, based on Bayesian statistical knowledge, study the posterior probability distribution of climate state transitions, and discuss the optimal carbon policy for different climate states by balancing emission utility costs and utility weighted carbon marginal products. This article also discusses the damage caused by rising temperatures and explores their impact on carbon price policies. then, the paper calculates SCC under four kinds of climate states, which will be visually displayed with graphs. Finally, we compare SCC obtained in this paper with that in other researches. The results show that: (1) Climate status has a significant impact on carbon policy, and carbon price predictions will dynamically change with climate status. (2) Green low-carbon behavior has a positive impact on climate status. (3) There are differences in the impact of the three types of damage caused by rising temperatures on carbon price policies. (4) Green development is conducive to stabilizing the value of SCC. (5) Close monitoring of the climate state helps to update the probability of damage in time so that we can precisely adjust the corresponding policies on SCC. This study provides theoretical and empirical reference for the government to formulate carbon price policies and promote the development of social green behavior. [ABSTRACT FROM AUTHOR]

Highlights: The I3− additive promoted in situ formation of zincophilic Cu nanoclusters on commercial Cu foil, which achieves uniform Zn deposition with ultralow nucleation overpotential and high reversibility. The Zn-rich ZnI2 cathode confined by graphene/polyvinyl pyrrolidone heterostructure shows enhanced conductivity and shuttle effect suppression, providing sufficient Zn2+ for the anode stably. The assembled anode-free Zn-iodine battery exhibits attractive features for commercialization: low cost, fast production, significantly increased energy density and durable cycle stability under practical application conditions.The anode-free design is a promising strategy to increase the energy density of aqueous Zn metal batteries (AZMBs). However, the scarcity of Zn-rich cathodes and the rapid loss of limited Zn greatly hinder their commercial applications. To address these issues, a novel anode-free Zn-iodine battery (AFZIB) was designed via a simple, low-cost and scalable approach. Iodine plays bifunctional roles in improving the AFZIB overall performance: enabling high-performance Zn-rich cathode and modulating Zn deposition behavior. On the cathode side, the ZnI2 serves as Zn-rich cathode material. The graphene/polyvinyl pyrrolidone heterostructure was employed as an efficient host for ZnI2 to enhance electron conductivity and suppress the shuttle effect of iodine species. On the anode side, trace I3− additive in the electrolyte creates surface reconstruction on the commercial Cu foil. The in situ formed zincophilic Cu nanocluster allows ultralow-overpotential and uniform Zn deposition and superior reversibility (average coulombic efficiency > 99.91% over 7,000 cycles). Based on such a configuration, AFZIB exhibits significantly increased energy density (162 Wh kg−1) and durable cycle stability (63.8% capacity retention after 200 cycles) under practical application conditions. Considering the low cost and simple preparation methods of the electrode materials, this work paves the way for the practical application of AZMBs. [ABSTRACT FROM AUTHOR]

Background: Influenza A viruses (IAV) exhibit vast genetic mutability and have great zoonotic potential to infect avian and mammalian hosts and are known to be responsible for a number of pandemics. A key computational issue in influenza prevention and control is the identification of molecular signatures with cross-species transmission potential. We propose an adjusted entropy-based host-specific signature identification method that uses a similarity coefficient to incorporate the amino acid substitution information and improve the identification performance. Mutations in the polymerase genes (e.g., PB2) are known to play a major role in avian influenza virus adaptation to mammalian hosts. We thus focus on the analysis of PB2 protein sequences and identify host specific PB2 amino acid signatures. Results: Validation with a set of H5N1 PB2 sequences from 1996 to 2006 results in adjusted entropy having a 40% false negative discovery rate compared to a 60% false negative rate using unadjusted entropy. Simulations across different levels of sequence divergence show a false negative rate of no higher than 10% while unadjusted entropy ranged from 9 to 100%. In addition, under all levels of divergence adjusted entropy never had a false positive rate higher than 9%. Adjusted entropy also identifies important mutations in H1N1pdm PB2 previously identified in the literature that explain changes in divergence between 2008 and 2009 which unadjusted entropy could not identify. Conclusions: Based on these results, adjusted entropy provides a reliable and widely applicable host signature identification approach useful for IAV monitoring and vaccine development. [ABSTRACT FROM AUTHOR]

• Coal ash and AAEMs have a significant promoting effect on the NH 3 oxidation. • AAEMs promote the decomposition of N 2 O at 800 °C. • Alkali metals (K and Na) only promote the reduction of NO at 600–800 °C. • AAEMs enhance the adsorption capacity of NH 3 on the active site of the coal ash. • A appropriate O 2 concentration should be selected for the power plant. Ammonia as an eco-friendly and carbon-free energy has been greatly concerned at home and abroad. It has been utilized in the ammonia and coal co-firing process, demonstrating robust market viability. Nonetheless, due to the element N within ammonia causing the production of NO x , the catalytic effect and reaction mechanics of AAEMs in coal ash on the NH 3 oxidation remain elusive. In this study, the catalytic effects of AAEMs (K, Ca, Na and Mg) on NH 3 oxidation were investigated through experiments, and the reaction mechanism was elucidated from a microscopic perspective by density functional theory (DFT). The experimental results show that the addition of AAEMs does enhance the oxidation potential of NH 3 during coal and ammonia co-firing process, and promote the transformation of NH 3 to NO, N 2 O and N 2. However, the promotion effect of different AAEMs is different, consequently influencing the selectivity of NH 3 oxidation pathway. At 600–800 °C, alkaline earth metals (Ca and Mg) facilitate the oxidation of NH 3 while alkali metals (K and Na) have the opposite effect. Mg has the highest promoting effect on the conversion of NH 3 to NO at 600–800 °C, but the catalytic effect of K and Na is more dominant from 800 °C to 900 °C. The transformation from NH 3 to N 2 O remains the same, but the catalytic impact of Ca is mostly pronounced. AAEMs can reduce thermal decomposition activation energy of N 2 O, and the decomposition of N 2 O can be promoted at 800 °C. The DFT results indicate that AAEMs can enhance the adsorption capacity of NH 3 on the active site of the coal ash surface, and reduce the activation energy of NH 3 oxidation, thereby accelerating the transformation of NH 3 to other nitrogen-containing species. This study provides new insight into the evidence for the enhanced catalytic effect of AAEMs on NH 3 oxidation during ammonia and coal co-firing process. [ABSTRACT FROM AUTHOR]

Background: Intensive aquaculture farming has caused significant degradation of coastal wetlands and has been proposed as a reservoir for pathogenic Vibrio spp. Results: Gut pathogens including Vibrio spp., Salmonella spp., and Klebsiella spp. were isolated from bird feces, shrimp and wetland water in two typical coastal regions of China in 2015 and 2017 and were subsequently subjected to whole-genome sequencing. Meanwhile, local patient isolates were also selected to confirm the epidemiological links. Bacterial community composition analyses of the sediments that were sampled in 2015 and 2017 were conducted by the hypervariable region 4 of the 16S rRNA gene. Together with the local clinical isolates, we observed highly related Vibrio isolates from waterbirds, wetlands and shrimp. Phylogenetic genome comparisons also demonstrated that sequence types ST3 and ST2414 Vibrio parahaemolyticus isolates obtained from aquatic animals were clonally related to patient isolates. Likewise, three Salmonella typhimurium isolates were also genomically related to one clinical strain. The results showed that farming activities significantly altered the community composition and resulted in the emergence of several pathogens, including Acinetobacter, Mycobacterium and Legionella. Conclusions: In conclusion, our results demonstrated that intensive shrimp farming in wetlands has two devastating impacts: pathogen dissemination from aquatic animals into migratory birds and transmission of foodborne pathogens into local communities. [ABSTRACT FROM AUTHOR]

• The co-agglomeration accentuates haze pollution. • Co-agglomeration has obvious spatial effects on haze pollution. • The pollution effect of co-agglomeration is weakened with the improvement of the economic level. • Technological innovation has an inhibitory effect on the pollution effect of co-agglomeration. The issue of haze in the middle reaches of the Yangtze River urban agglomeration has significant implications for China. Concurrently, co-agglomeration and technological innovation are key factors influencing haze pollution. Using the panel data composed of PM2.5 concentration and other data from 27cities in the middle reaches of the Yangtze River urban agglomeration between 2010 and 2020, this paper empirically investigates the impact of co-agglomeration and technological innovation on haze pollution. From this rigorous analysis, several conclusions crystallize: (1)the co-agglomeration of productive services and manufacturing accentuates haze pollution, showcasing notable regional variances;(2)the haze pollution has a significant positive correlation with the co-agglomeration levels in local and neighboring regions;(3)the negative consequences of co-agglomeration on environments reduce as the agglomeration of productive services and economic development increases;(4)technological innovation significantly moderates the pollution effects of co-agglomeration. [ABSTRACT FROM AUTHOR]

Assessing the presence of waterborne pathogens and antibiotic resistance genes (ARGs) is crucial for managing the environmental quality of drinking water sources. However, detecting low abundance pathogens in such settings is challenging. In this study, a workflow was developed to enrich for broad spectrum pathogens from drinking water samples. A mock community was used to evaluate the effectiveness of various enrichment broths in detecting low-abundance pathogens. Monthly metagenomic surveillance was conducted in a drinking water source from May to September 2021, and water samples were subjected to five enrichment procedures for 6 h to recover the majority of waterborne bacterial pathogens. Oxford Nanopore Technology (ONT) was used for metagenomic sequencing of enriched samples to obtain high-quality pathogen genomes. The results showed that selective enrichment significantly increased the proportions of targeted bacterial pathogens. Compared to direct metagenomic sequencing of untreated water samples, targeted enrichment followed by ONT sequencing significantly improved the detection of waterborne pathogens and the quality of metagenome-assembled genomes (MAGs). Eighty-six high-quality MAGs, including 70 pathogen MAGs, were obtained from ONT sequencing, while only 12 MAGs representing 10 species were obtained from direct metagenomic sequencing of untreated water samples. In addition, ONT sequencing improved the recovery of mobile genetic elements and the accuracy of phylogenetic analysis. This study highlights the urgent need for efficient methodologies to detect and manage microbial risks in drinking water sources. The developed workflow provides a cost-effective approach for environmental management of drinking water sources with microbial risks. The study also uncovered pathogens that were not detected by traditional methods, thereby advancing microbial risk management of drinking water sources. [Display omitted] • An enrichment workflow targeted on enteric pathogens was developewd for uncovering pathogen genomes from drinking water. • Targeted enrichment followed ONT sequencing significantly improved the detection of waterborne pathogens. • This workflow also improved the recovery of mobile genetic elements and assessed the transferability of majority of ARGs. [ABSTRACT FROM AUTHOR]

The degradable protective articles made of thermoplastic polyvinyl alcohol (TPVA) are widely used in nuclear power plants, and they are thermally decomposed after use to reduce solid waste. However, in the real decomposition of TPVA, the temperature in the oxidation reactor is not self-sustaining; as a result, the degradation products contain a lot of CO, resulting in more pollution and energy waste. In this paper, jet stirred reactor (JSR) and Chemkin software were used to study the reaction kinetics characteristics of the oxidation process of degradation products from TPVA in the range of 550 °C–700 °C. Both experiments and kinetic simulation show that a higher average temperature of the oxidation reactor is needed to achieve lower CO emissions. When using 5% or 10% TPVA degradation solution, the average temperature should not befall below 625 °C or 675 °C. The corresponding residence time should be greater than 6 s and 5 s respectively. The combination of research findings and engineering practice provides great help to the optimization of the actual work process. • The temperature and residence time required for the complete degradation of thermoplastic polyvinyl alcohol after preliminary oxidation with the Fenton method were studied in a jet stirred reactor. • Ketones, the main products of TPVA initial degradation, are used as combustible materials after solution gasification to simulate the oxidation process simulation. • The simulated data are in good agreement with the experimental data. • This article produces cloud maps of operating conditions corresponding to different CO and CH 4 emission standards to guide similar engineering applications. [ABSTRACT FROM AUTHOR]

Introduction: It is clinically challenging to infer the phylogenetic relationship between different tumor lesions of patients with multiple synchronous lung cancers (MSLC), whether these lesions are the result of independently evolved tumor or intrapulmonary metastases. Methods: We used the Illumina X10 platform to sequence 128 stage I lung cancer samples collected from 64 patients with MSLC. All samples were analyzed for mutation spectra and phylogenetic inference. Results: We detected genetic aberrations within genes previously reported to be recurrently altered in lung adenocarcinoma including, EGFR, ERBB2, TP53, BRAF, and KRAS. Other putative driver mutations identified were enriched in RTK‐RAS signaling, TP53 signaling, and cell cycle. Also, we found some interesting cases, two cases that carried EGFR L858R and T790M co‐mutation in one tumor and another tumor with only EGFR 19del, and 1 case with two KRAS hotspots in the same tumor. Due to the short follow‐up time and early stage, further investigation is needed to determine whether this unique mutation profile will affect their progression‐free survival (PFS) and overall survival (OS). Regarding genetic evolution analysis among 64 tumor samples, 50 of them display distinct mutational profiles, suggesting these are independently evolved tumors, which is consistent with histopathological assessment. On the other hand, six patients were identified to be intrapulmonary metastasis as the mutations harbored in different lesions are clonally related. Conclusion: In summary, unlike intrapulmonary metastases, patients with MSLC harbor distinct genomic profiles in different tumor lesions, and we could distinguish MSLC from intrapulmonary metastases via clonality estimation. [ABSTRACT FROM AUTHOR]

Federated learning has attracted much attention in fault diagnosis since it can effectively protect data privacy. However, efficient fault diagnosis performance relies on the uninterrupted training of model parameters with massive amounts of perfect data. To solve the problems of model training difficulty and parameter negative transfer caused by data corruption, a novel cross-device fault diagnosis method based on repaired data is proposed. Specifically, the local model training link in each source client performs random forest regression fitting on the fault samples with missing fragments, and then the repaired data is used for network training. To avoid inpainting fragments to produce the wrong characteristics of faulty samples, joint domain discrepancy loss is introduced to correct the phenomenon of parameter bias during local model training. Considering the randomness of the overall performance change brought about by the local model update, an adaptive update is proposed for each round of global model download and local model update. Finally, the experimental verification was carried out in various industrial scenarios established by three sets of bearing data sets, and the effectiveness of the proposed method in terms of fault diagnosis performance and data privacy protection was verified by comparison with various currently popular federated transfer learning methods. [ABSTRACT FROM AUTHOR]

Since China's speedy economic development, the problems of energy consumption and environmental pollution have become increasingly prominent. A question worth in-depth study is whether ecological civilization (EC) construction, one of the main policies to solve China's severe environmental and ecological problems, affects carbon dioxide emissions (CDE). In this study, we use a novel method proposed by Hsiao et al. (2012) to estimate the average treatment effect by using panel data to study the impact of establishing the EC pilot zones of China on CDE. The results show that, although EC construction is effective in reducing CDE, the impact varies from region to region. The study findings can provide a scientific basis to promote the experience of EC construction better and improve its CDE effect. • Impact of ecological civilization pilot zones on carbon emissions is studied. • An empirical analysis is conducted based on the HCW method. • Effects of ecological civilization on reducing carbon emissions vary by area. [ABSTRACT FROM AUTHOR]

Does energy-saving have a positive effect on the long-term development of enterprises? To answer this question, this study uses the propensity score matching (PSM) method to determine the impact of enterprises completing energy-saving objectives on their financial performance based on data from an industrial enterprise database in China. The results show that industrial enterprises that have completed the energy-saving target have advantages in profitability, operational and financial indicators but have deficiencies in debt indicators, and there is no significant difference in the ratio of profits to cost and expense. The research results of high energy-consuming industry are the same as the overall sample of industrial enterprises in terms of operational and financial indicators, and debt ratio indicators. Nevertheless, energy saving has no significant impact on profit and ratio of profits to cost of high energy-consuming industry. • Impact of energy saving on financial performance of industrial enterprises in China was studied. • An empirical analysis was conducted based on propensity score matching method. • Energy saving positively influences profitability, operational and financial indicators. [ABSTRACT FROM AUTHOR]

Motivation Quantitative determination of protein thermodynamic stability is a critical step in protein and drug design. Reliable prediction of protein stability changes caused by point variations contributes to developing-related fields. Over the past decades, dozens of structure-based and sequence-based methods have been proposed, showing good prediction performance. Despite the impressive progress, it is necessary to explore wild-type and variant protein representations to address the problem of how to represent the protein stability change in view of global sequence. With the development of structure prediction using learning-based methods, protein language models (PLMs) have shown accurate and high-quality predictions of protein structure. Because PLM captures the atomic-level structural information, it can help to understand how single-point variations cause functional changes. Results Here, we proposed THPLM, a sequence-based deep learning model for stability change prediction using Meta's ESM-2. With ESM-2 and a simple convolutional neural network, THPLM achieved comparable or even better performance than most methods, including sequence-based and structure-based methods. Furthermore, the experimental results indicate that the PLM's ability to generate representations of sequence can effectively improve the ability of protein function prediction. Availability and implementation The source code of THPLM and the testing data can be accessible through the following links: https://github.com/FPPGroup/THPLM. [ABSTRACT FROM AUTHOR]

Members of the spotted fever group rickettsia express four large, surface-exposed autotransporters, at least one of which is a known virulence determinant. Autotransporter translocation to the bacterial outer surface, also known as type V secretion, involves formation of a β-barrel autotransporter domain in the periplasm that inserts into the outer membrane to form a pore through which the N-terminal passenger domain is passed and exposed on the outer surface. Two major surface antigens of Rickettsia rickettsii, are known to be surface exposed and the passenger domain cleaved from the autotransporter domain. A highly passaged strain of R. rickettsii, Iowa, fails to cleave these autotransporters and is avirulent. We have identified a putative peptidase, truncated in the Iowa strain, that when reconstituted into Iowa restores appropriate processing of the autotransporters as well as restoring a modest degree of virulence. Author summary: Strains of R. rickettsii, the agent of Rocky Mountain spotted fever, differ greatly in the severity of the disease caused. The genetic differences responsible for this disparity are only now being uncovered. An avirulent, laboratory adapted strain of R. rickettsii fails to proteolytically process several large surface protein antigens. We have identified a protease that cleaves the protein precursors to their mature form. The gene encoding this protease is mutated in the avirulent strain. Complementation of the active form of the gene identifies proteolytic processing of surface antigens as important to virulence. [ABSTRACT FROM AUTHOR]

This study proposes an approach to minimize the maximum makespan of the integrated scheduling problem in flexible job-shop environments, taking into account conflict-free routing problems. A hybrid genetic algorithm is developed for production scheduling, and the optimal ranges of crossover and mutation probabilities are also discussed. The study applies the proposed algorithm to 82 test problems and demonstrates its superior performance over the Sliding Time Window (STW) heuristic proposed by Bilge and the Genetic Algorithm proposed by Ulusoy (UGA). For conflict-free routing problems of Automated Guided Vehicles (AGVs), the genetic algorithm based on AGV coding is used to study the AGV scheduling problem, and specific solutions are proposed to solve different conflicts. In addition, sensors on the AGVs provide real-time data to ensure that the AGVs can navigate through the environment safely and efficiently without causing any conflicts or collisions with other AGVs or objects in the environment. The Dijkstra algorithm based on a time window is used to calculate the shortest paths for all AGVs. Empirical evidence on the feasibility of the proposed approach is presented in a study of a real flexible job-shop. This approach can provide a highly efficient and accurate scheduling method for manufacturing enterprises. [ABSTRACT FROM AUTHOR]

The occurrence and removal of 38 antibiotics from nine classes in two drinking water treatment plants (WTPs) were monitored monthly over one year to evaluate the efficiency of typical treatment processes, track the source of antibiotics in tap water and assess their potential risks to ecosystem and human health. In both source waters, 18 antibiotics were detected at least once, with average total antibiotic concentrations of 538.5 ng/L in WTP1 and 569.3 ng/L in WTP2. The coagulation/flocculation and sedimentation, sand filtration and granular activated carbon processes demonstrated limited removal efficiencies. Chlorination, on the other hand, effectively eliminated antibiotics by 48.7 ± 11.9%. Interestingly, negative removal was observed along the distribution system, resulting in a significant antibiotic presence in tap water, with average concentrations of 131.5 ng/L in WTP1 and 362.8 ng/L in WTP2. Source tracking analysis indicates that most antibiotics in tap water may originate from distribution system. The presence of antibiotics in raw water and tap water posed risks to the aquatic ecosystem. Untreated or partially treated raw water could pose a medium risk to infants under six months. Water parameters, for example, temperature, total nitrogen and total organic carbon, can serve as indicators to estimate antibiotic occurrence and associated risks. Furthermore, machine learning models were developed that successfully predicted risk levels using water quality parameters. Our study provides valuable insights into the occurrence, removal and risk of antibiotics in urban WTPs, contributing to the broader understanding of antibiotic pollution in water treatment systems. [Display omitted] • 18 antibiotics were detected in raw water from two drinking water systems. • Temperature, TN and TOC could be used to estimate antibiotic occurrence. • A majority of antibiotics in tap water could originate from the distribution systems. • Antibiotics in raw water and tap water posed medium to high level of risks. • Machine learning models were developed successfully to predict the antibiotics risk levels. [ABSTRACT FROM AUTHOR]

The Xinjiazui gold deposit, a newly discovered deposit, is situated in the northwestern margin of the Yangtze Block, China. The source and genesis of gold mineralization are poorly understood. It is urgent to use the H–O isotopic composition of quartz and geochemistry of pyrite to evaluate the origins of the Au and ore-forming fluids of this deposit. Three types of pyrite were identified, including synsedimentary framboidal pyrites (Py0), the directional arrangement of pyrites in pre-mineralization stage (Py1), and euhedral coarse-grain pyrites in the quartz–sulfide veins of the mineralization stage (Py2). The As content in Py2 is relatively higher than Py0 and Py1, indicating that the ore-forming fluids are strongly enriched in As. The δ34S values of Py2 (+5.50–+13.34‰) overlap with the S1–2M phyllite (+7.25‰–+8.70‰). This result is consistent with the Pb isotopic composition of Py2, showing that the source of ore-forming materials was derived from the S1–2M phyllite. Meanwhile, the variations in quartz's H and O isotopic composition suggest that the ore-forming fluids were derived originally from metamorphic fluid. Additionally, the Au mineralization is strictly controlled by the shear zone. Above all, we would like to classify the Xinjiazui deposit as an orogenic gold deposit. [ABSTRACT FROM AUTHOR]

Programmed cell death 1 ligand 1 (PD-L1) has been approved as predictive biomarker for non-small-cell lung cancer (NSCLC) patients treated with PD-(L)1 blockade therapy. The clinical/genomic features associated with PD-L1 are not well studied. Genomic profiling of tumor biopsies from 883 Chinese NSCLC patients was performed by targeted next-generation sequencing. Immunohistochemical analysis was conducted to evaluate PD-L1 expression levels using antibodies Dako 22C3 and 28-8, respectively. Our study showed distinct correlation between PD-L1 expression and clinical/genomic characteristics when using different PD-L1 antibodies and in different histological subtypes including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively. PD-L1 high expression (22C3) was associated with male and lymph node metastasis only in ADC patients. Furthermore, mutations of TP53 and KRAS, KIF5B-RET fusion, copy number gains of PD-L1 and PD-L2, and arm-level amplifications of chr.12p were significantly associated with PD-L1 positive status in ADC patients. For SCC patients, the gain of EGFR and MDM2 and loss of PTPRD were negatively associated with PD-L1 expression. We also compared our results with other studies and found conflicting results presumably because of the multiplicity of antibody clones and platforms, the difference of cutoffs for assigning PD-L1 expression levels, and the variation in study populations. Our study can help to understand the utility and validity of PD-L1 as biomarker of response to immune checkpoint inhibitors. [ABSTRACT FROM AUTHOR]

Transcription initiation has long been considered a primary regulatory step in gene expression. Recent work, however, shows that downstream events, such as transcription elongation, can also play important roles. 1–3 A well-characterized example from animals is promoter-proximal pausing, where transcriptionally engaged Pol II accumulates 30–50 bp downstream of the transcription start site (TSS) and is thought to enable rapid gene activation. 2 Plants do not make widespread use of promoter-proximal pausing; however, in a phenomenon known as 3′ pausing, a significant increase in Pol II is observed near the transcript end site (TES) of many genes. 4–6 Previous work has shown that 3′ pausing is promoted by the BORDER (BDR) family of negative transcription elongation factors. Here we show that BDR proteins play key roles in gene repression. Consistent with BDR proteins acting to slow or pause elongating Pol II, BDR-repressed genes are characterized by high levels of Pol II occupancy, yet low levels of mRNA. The BDR proteins physically interact with FPA, 7 one of approximately two dozen genes collectively referred to as the autonomous floral-promotion pathway, 8 which are necessary for the repression of the flowering time gene FLOWERING LOCUS C (FLC). 9–11 In early-flowering strains, FLC expression is repressed by repressive histone modifications, such as histone H3 lysine 27 trimethylation (H3K27me3), thereby allowing the plants to flower early. These results suggest that the repression of transcription elongation by BDR proteins may allow for the temporary pausing of transcription or facilitate the long-term repression of genes by repressive histone modifications. • BDR proteins repress expression of the floral repressor, FLC • BDR proteins physically interact with the autonomous pathway protein FPA • BDR-repressed genes have high levels of Pol II occupancy, despite low mRNA levels • Gene repression by BDR may involve the inhibition of transcription elongation Yu et al. show that genes repressed by the BDR family of negative transcription elongation factors have high levels of Pol II occupancy, despite relatively low steady-state RNA levels. In this way, BDR proteins may allow for the later resumption of transcription or facilitate the long-term repression of genes by repressive histone modifications. [ABSTRACT FROM AUTHOR]

A submerged combustion vaporizer (SCV) is a popular vaporizer that is utilized for the peak regulation of liquefied natural gas (LNG) in cities or as the main vaporizer in cold regions. Due to the different genesis of reservoirs, LNGs from different production places have different components and ratios, leading to a different gasification state in the heating tube, difficultly in predicting the SCV thermal performance, and difficulty in controlling the water bath temperature and gas consumption to combust during SCV operation. Therefore, in this study, a numerical model of the heating tube in SCV is established and the flow and heat transfer features of three types of LNGs with different components are compared with those of pure methane. Moreover, the heat transfer and thermal performances of supercritical LNG in a serpentine tube are analyzed under various operating pressures and thermophysical properties. The results indicate that higher the ratio of methane, larger the heat transfer capacity, closer the comprehensive pseudo-critical temperature of LNG is to that of pure methane, and the more similar is the thermal performance. Furthermore, the SCV thermal performance decreases with the ratio of pure methane. The smallest Euler number is observed for LNG from ChangYi (C.Y.) because of its smallest dynamic viscosity and highest specific heat among the observed LNGs; thus, its Nu / Eu and η are better than those of pure methane and it has a higher outlet temperature for the gasification rate. • The thermophysical properties of S-LNG from various production places are compared. • The effect of component of S-LNGs on flow and heat transfer is studied numerically. • The effect of operation pressure of S-LNGs on flow and heat transfer is explored. • The thermal performance of SCV is studied under effect of pressure and component. [ABSTRACT FROM AUTHOR]

Hydrogen blending into natural gas is a feasible approach to realize the low-carbon energy structure. The impact of the hydrogen blending ratio on the leakage characteristics of buried gas pipelines determines the safety of pipeline operations. In this study, we investigated the influence of the hydrogen blending ratio on the soil temperature field after the buried gas pipeline leak and the detection range of fiber optic sensors through a field test and numerical simulation. A critical flow model based on the Peng-Robinson (PR) equation and a soil diffusion model based on simplified throttling were established for the microleakage and diffusion stages of the buried pipeline. Furthermore, the soil temperature variation after the buried pipeline leak and the prediction model of cooling capacity caused by gas leakage were obtained. In addition, the leakage experiments were performed to evaluate the impact of hydrogen blending ratio, pipeline operation pressure, and leak direction, as well as to achieve the soil temperature field distribution near the leak point. The following conclusions can be drawn: (1) Soil temperature decreases as the hydrogen blending ratio increases; (2) The detection range of the fiber optic sensors increases as the hydrogen blending ratio increases, ensuring the applicability of the existing fiber optic detection system for detecting hydrogen blending pipeline leaks. The findings provide a valuable research topic for hydrogen pipeline leak detection. • An experiment on the leakage of hydrogen - doped natural gas from buried pipeline is carried out. • A flow model based on PR equation of state is established for leakage prediction. • Calculation method of cooling capacity caused by gas injection based on soil temperature distribution. • The distribution of soil temperature and temperature change rate near the leakage. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbonized biomass as a self-standing electrode promotes electro-demulsification. • Carbonized biomass as self-standing electrode also promotes oil removal. • Electrode capacity reached 1180 mg g−1 (97.97 %) toluene removal at 5.0 V for 3.4 h. • The electric field compressed and ruptured emulsion droplets in porous electrodes. • Electrostatic adsorption caused small molecule adherence to graphitic pore walls. Emulsion wastewater contain substantial amounts of oil and various additives, which pose threats to the environment and human health. Demulsification is a crucial pretreatment stage for wastewater. This study aims to identify a novel electro-demulsification method with high oil removal efficiency and low energy consumption. Modified carbonized birch wood with a unique isotropic multiscale pore structure is used as a self-standing electrode to treat a toluene oil-in-water (O/W) emulsion. The electrode must have a highly porous structure to facilitate efficient water diffusion and oil adsorption. It must also have high electronic conductivity to expedite polarized molecular electrophoresis to realize penetration into the pores and, subsequently, demulsification. Guided by an applied electric field force, polarized O/W droplets are drawn toward the electrode, revealing electrical characteristics distinct from those of polarized organic molecules. This electric field force augments the capture and adhesion of droplets by the electric double layer at the electrode interface. Consequently, adsorbed droplets in close proximity to the electrode rupture due to the combined influence of the electric field force and the electrostatic effects stemming from the electrode's multiscale porous structure. This synergistic action enables demulsification to occur efficiently at low energy consumption levels. This study has revealed that electro-demulsification can effectively treat toluene emulsions stabilized by various surfactants and microemulsion containing toluene. Therefore, this electro-demulsification technology can be further developed for various types of water pollution. [ABSTRACT FROM AUTHOR]

The morbidity and mortality rates of endometrial cancer (EC) are increasing yearly. Early-stage EC can be effectively treated through surgery or surgery combined with radiotherapy and chemotherapy. Advanced and recurrent EC is treated with chemotherapy and comprehensive treatment; however, the prognosis for patients at this disease stage is poor. Consequently, novel and effective treatment strategies are urgently required for these patients. Breakthrough progress has been made with the use of immunosuppressants in the treatment of EC, which have been included in treatment guidelines. In the present review, the etiology and classification of EC was outlined and the relevant scientific basis for the application of immunosuppressants in advanced and recurrent EC was discussed. The relevant published and ongoing clinical trials are also summarized. As such, the present review aimed to provide a scientific summary of immunotherapy of EC. [ABSTRACT FROM AUTHOR]

Spinal muscular atrophy (SMA) is one of the most common and severe genetic diseases. SMA carrier screening is an effective way to identify couples at risk of having affected children. Next-generation sequencing (NGS)-based expanded carrier screening could detect SMN1 gene copy number without extra experiment and with high cost performance. However, its performance has not been fully evaluated. Here we conducted a systematic comparative study to evaluate the performance of three common methods. 478 samples were analyzed with multiplex ligation probe amplification (MLPA), real-time quantitative polymerase chain reaction (qPCR) and NGS, simultaneously. Taking MLPA-based results as the reference, for 0 copy, 1 copy and ≥ 2 copy SMN1 analysis with NGS, the sensitivity, specificity and precision were all 100%. Using qPCR method, the sensitivity was 100%, 97.52% and 94.30%, respectively; 98.63%, 95.48% and 100% for specificity; and 72.72%, 88.72% and 100% for precision. NGS repeatability was higher than that of qPCR. Moreover, among three methods, NGS had the lowest retest rate. Thus, NGS is a relatively more reliable method for SMN1 gene copy number detection. In expanded carrier screening, compared with the combination of multiple methods, NGS method could reduce the test cost and simplify the screening process. [ABSTRACT FROM AUTHOR]

[Display omitted] • Chemically expanded graphite and Zn foil are co-rolled at room temperature. • Ultrathin Zn-carbon composite anodes (down to 6 μm) are constructed. • These anodes exhibit an island distribution and a 3D-interpenetrating structure. • The unique structure inhibits dendrites and shields the internal Zn from corrosion. • Long cycle life of the symmetric cell is achieved at high discharge depth of 23.3% Zinc (Zn) anodes in aqueous zinc ion batteries (AZIBs) suffer from severe dendritic growth and corrosion reactions, and the resulting Zn loss prevents the batteries from stable cycling during the deep discharging process. Satisfactory performance can be achieved using over-thick Zn foils (>100 μm), but at the expense of full-cell energy density. Here, a facile strategy of co-rolling Zn foil and chemically expanded graphite (CEG) at room temperature is proposed to prepare an ultrathin Zn-carbon composite anode (Zn@CEG) with an adjustable thickness (6–40 μm). In Zn@CEG, Zn is uniformly embedded into the laterally arranged graphite spacing, forming a unique three-dimensional (3D) interpenetrating structure. The hydrophobic microregions of CEG accelerate the desolvation and conduction of Zn2+, promote uniform current density distribution, and suppress dendrites. Moreover, the transverse graphite sheets restrict the deep corrosion caused by electrolyte penetration. Thus, the symmetric cell assembled with ultrathin Zn@CEG stably cycles over 350 h at a discharge depth of 23.3%. When the Zn@CEG is matched with the high-loading MnO 2 cathode (16 mg cm−2), the full cells achieve 500 and 800 cycles at low negative/positive capacity ratios of 6.9 and 10.7, respectively. This scalable strategy for constructing ultrathin Zn anodes provides new ideas for commercializing AZIBs. [ABSTRACT FROM AUTHOR]