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Introduction: Reverse genetic studies conducted in the plant with a complex or polyploidy genome enriched with large gene families (like wheat) often meet challenges in identifying the key candidate genes related to important traits and prioritizing the genes for functional experiments. Objective: To overcome the above-mentioned challenges of reverse genetics, this work aims to establish an efficient multi-species strategy for genome-wide gene identification and prioritization of the key candidate genes. Methods: We established the integrative gene duplication and genome-wide analysis (iGG analysis) as a strategy for pinpointing key candidate genes deserving functional research. The iGG captures the evolution, and the expansion/contraction of large gene families across phylogeny-related species and integrates spatial–temporal expression information for gene function inference. Transgenic approaches were also employed to functional validation. Results: As a proof-of-concept for the iGG analysis, we took the wheat calcineurin B-like protein-interacting protein kinases (CIPKs) family as an example. We identified CIPKs from seven monocot species, established the orthologous relationship of CIPKs between rice and wheat, and characterized Triticeae-specific CIPK duplicates (e.g., CIPK4 and CIPK17). Integrated with our analysis of CBLs and CBL-CIPK interaction, we revealed that divergent expressions of TaCBLs and TaCIPKs could play an important role in keeping the stoichiometric balance of CBL-CIPK. Furthermore, we validated the function of TaCIPK17-A2 in the regulation of drought tolerance by using transgenic approaches. Overexpression of TaCIPK17 enhanced antioxidant capacity and improved drought tolerance in wheat. Conclusion: The iGG analysis leverages evolutionary and comparative genomics of crops with large genomes to rapidly highlight the duplicated genes potentially associated with speciation, domestication and/or particular traits that deserve reverse-genetic functional studies. Through the identification of Triticeae-specific TaCIPK17 duplicates and functional validation, we demonstrated the effectiveness of the iGG analysis and provided a new target gene for improving drought tolerance in wheat.

Abstract Surface modification is frequently used to solve the problems of low combustion properties and agglomeration for aluminum‐based fuels. However, due to the intrinsic incompatibility between the aluminum powder and the organic modifiers, the surface coating is usually uneven and disordered, which significantly deteriorates the uniformity and performances of the Al‐based fuels. Herein, a new approach of monolayer nano‐vesicular self‐assembly is proposed to prepare high‐performance Al fuels. Triblock copolymer G‐F‐G is produced by glycidyl azide polymer (GAP) and 2,2′‐(2,2,3,3,4,5,5‐Octafluorohexane‐1,6‐diyl) bis (oxirane) (fluoride) ring‐open addition reaction. By utilizing G‐F‐G vesicular self‐assembly in a special solvent, the nano‐sized vesicles are firmly adhered to the surface of Al powder through the long‐range attraction between the fluorine segments and Al. Meanwhile, the electrostatic repulsion between vesicles ensures an extremely thin coating thickness (≈15 nm), maintaining the monolayer coating structure. Nice ignition, combustion, anti‐agglomeration, and water‐proof properties of Al@G‐F‐G(DMF) are achieved, which are superior among the existing Al‐based fuels. The derived Al‐based fuel has excellent comprehensive properties, which can not only inspire the development of new‐generation energetic materials but also provide facile but exquisite strategies for exquisite surface nanostructure construction via ordered self‐assembly for many other applications.

Abstract As the first point of contact for patients, General Practitioners (GPs) play a crucial role in the National Health Service (NHS). An accurate primary diagnosis from the GP can alleviate the burden on specialists and reduce the time needed to re-confirm the patient’s condition, allowing for more efficient further examinations. However, GPs have broad but less specialized knowledge, which limits the accuracy of their diagnosis. Therefore, it is imperative to introduce an intelligent system to assist GPs in making decisions. This paper introduces two data augmentation methods, the Complaint Symptoms Integration Method and Symptom Dot Separating Method, to integrate essential information into the Integration dataset. Additionally, it proposes a hybrid architecture that fuses the features of words from different representation spaces. Experiments demonstrate that, compared to commonly used pre-trained attention-based models, our hybrid architecture delivers the best classification performance for four common neurological diseases on the enhanced Integration dataset. For example, the classification accuracy of the BERT+CNN hybrid architecture is 0.897, which is a 5.1% improvement over both BERT and CNN with 0.846. Finally, this paper develops an AI diagnosis assistant web application that leverages the superior performance of this architecture to help GPs complete primary diagnosis efficiently and accurately.

Introduction: Antifreeze peptides regulate the physiological functions of frozen cells and even their apoptosis; however, the mechanisms by which antifreeze peptides regulate these processes remain unclear, although the interactions between cell membranes and ice are well known to be important in this process. Objectives: Our study aims to investigate how antifreeze peptides regulate cell physiological functions during the freezing process. Methods: We investigated the cryoprotective effect of rsfAFP on the physiological functions of S. thermophilus under freezing stress by measuring cellular metabolism activity, intracellular enzyme activity, cell membrane characterization, and cell apoptosis. The mechanism by which rsfAFP impacts S. thermophilus physiological functions under freezing stress was investigated using multispectral techniques and cryo-TEM. Results: We show that a recombinant antifreeze peptide (rsfAFP) interacts with the extracellular capsular polysaccharides and peptidoglycan of Streptococcus thermophilus and ice to cover the outer layer of the membrane, forming a dense protective layer that regulates the molecular structure of extracellular ice crystals, which results in reduced extracellular membrane damage, depressed apoptosis and increased intracellular metabolic activity. This interaction mechanism was indicated by the fact that S. thermophilus better maintained its permeability barrier, membrane fluidity, membrane structural integrity, and cytoplasmic membrane potential during freezing stress with rsfAFP treatment. Conclusion: These results provide new insights into the mechanism by which rsfAFP regulates frozen cell physiological functions and apoptosis under freezing stress.

Emission factors serve as a valuable tool for quantifying the release of pollutants from road vehicles and predicting emissions within a specific time or area. In order to overcome the limitation of the computer program to calculate emissions from the road transport (COPERT) model in directly obtaining precise emission factors from on-board diagnostic (OBD) data, we propose a novel two-stream network that combines time-series features and time-frequency features to enhance the accuracy of the COPERT model. Firstly, for the instantaneous emission factors of NOx from multiple driving segments provided by heavy-duty diesel vehicles in actual driving, we select the monitored attributes with a high correlation to the emission factor of NOx considering the data scale and employing Spearman rank correlation analysis to obtain the final dataset composed of them and emission factors. Subsequently, we construct an information matrix to capture the impact of past data on emission factors. Each attribute of the time series is then converted into a time-frequency matrix using the continuous wavelet transform. These individual time-frequency matrices are combined to create a multi-channel time-frequency matrix, which represents the historical information. Finally, the historical information matrix and the time-frequency matrix are inputted into a two-stream parallel model that consists of ResNet50 and a convolutional block attention module. This model effectively integrates time-series features and time-frequency features, thereby enhancing the representation of emission characteristics. The reliability and accuracy of the proposed method were validated through a comparative analysis with existing mainstream models.

Abstract Background Mesenchymal stem cells (MSCs) are promising candidates for tissue regeneration and disease treatment. However, long-term in vitro passaging leads to stemness loss of MSCs, resulting in failure of MSC therapy. This study investigated whether the combination of melatonin and human umbilical cord mesenchymal stem cells (hUC-MSCs) was superior to hUC-MSCs alone in ameliorating high-fat diet and streptozocin (STZ)-induced type II diabetes mellitus (T2DM) in a mouse model. Methods Mice were divided into four groups: normal control (NC) group; T2DM group; hUC-MSCs treatment alone (UCMSC) group and pretreatment of hUC-MSCs with melatonin (UCMSC/Mel) group. Results RNA sequence analysis showed that certain pathways, including the signaling pathway involved in the regulation of cell proliferation signaling pathway, were regulated by melatonin. The blood glucose levels of the mice in the UCMSC and UCMSC/Mel treatment groups were significantly reduced compared with the T2DM group without treatment (P

Abstract Background Social determinants of health (SDH), including food insecurity, are associated with depression in the general population. This study estimated the prevalence of depression and food insecurity and evaluated the impact of food insecurity and other SDH on depression in adults with rheumatoid arthritis (RA). Methods Adults (≥ 18 years) with RA were identified from the 2013–2014 and 2015–2016 National Health and Nutrition Examination Survey (NHANES). Depression was defined as a score of ≥ 5 (mild depression: 5–9; moderate-to-severe depression: 10–27) using the Patient Health Questionnaire-9 (PHQ-9). Food insecurity was assessed with the 18-item US Household Food Security Survey Module. Adults with household-level marginal-to-very-low food security were classified as experiencing food insecurity. The prevalence of depression and food insecurity among participants with RA were estimated. Weighted logistic regression was used to evaluate the association between depression and participants’ characteristics including SDH. Penalized regression was performed to select variables included in the final multivariable logistic regression. Results A total of 251 and 276 participants from the 2013–2014 and the 2015–2016 NHANES, respectively, had self-reported RA. The prevalence of depression among these participants was 37.1% in 2013–2014 and 44.1% in 2015–2016. The prevalence of food insecurity was 33.1% in 2013–2014 and 43.0% in 2015–2016. Food insecurity was associated with higher odds of having depression (OR 2.17, 95% CI 1.27, 3.72), and the association varied by depression severity. Compared with participants with full food security, the odds of having depression was particularly pronounced for those with very low food security (OR 2.96, 95% CI 1.48, 5.90) but was not significantly different for those with marginal or low food security. In the multivariable regression, being female, having fair/poor health condition, any physical disability, and ≥ 4 physical limitations were significantly associated with depression. Conclusions In adults with self-reported RA, the prevalence of depression and food insecurity remained high from 2013 to 2016. We found that depression was associated with SDH such as food insecurity, although the association was not statistically significant once adjusted for behavioral/lifestyle characteristics. These results warrant further investigation into the relationship between depression and SDH among patients with RA.

Wheat is one of the most important food crops in the world and is considered one of the top targets in crop biotechnology. With the high-quality reference genomes of wheat and its relative species and the recent burst of genomic resources in Triticeae, demands to perform gene functional studies in wheat and genetic improvement have been rapidly increasing, requiring that production of transgenic wheat should become a routine technique. While established for more than 20 years, the particle bombardment-mediated wheat transformation has not become routine yet, with only a handful of labs being proficient in this technique. This could be due to, at least partly, the low transformation efficiency and the technical difficulties. Here, we describe the current version of this method through adaptation and optimization. We report the detailed protocol of producing transgenic wheat by the particle gun, including several critical steps, from the selection of appropriate explants (i.e., immature scutella), the preparation of DNA-coated gold particles, and several established strategies of tissue culture. More importantly, with over 20 years of experience in wheat transformation in our lab, we share the many technical details and recommendations and emphasize that the particle bombardment-mediated approach has fewer limitations in genotype dependency and vector construction when compared with the Agrobacterium-mediated methods. The particle bombardment-mediated method has been successful for over 30 wheat genotypes, from the tetraploid durum wheat to the hexaploid common wheat, from modern elite varieties to landraces. In conclusion, the particle bombardment-mediated wheat transformation has demonstrated its potential and wide applications, and the full set of protocol, experience, and successful reports in many wheat genotypes described here will further its impacts, making it a routine and robust technique in crop research labs worldwide.

Arthrospira species are widely cultivated due to their high nutritional value as a food supplement. The fluctuating temperature strongly influences the cultivation system for Arthrospira mass production. To reveal the underlying mechanisms of coping with temperature stress to adopt measures of harm reduction, we analyzed changes in growth, photosynthetic pigments and the transcriptome of Arthrospira sp. TJSD091 exposed to short-term cold stress. The photosynthetic pigments decreased significantly under cold temperature stress conditions, and so as the cells` dry weight. A total of 1294 genes were expressed differentially. Pathway analysis revealed 473 differentially expressed genes were identified in 32 KEGG pathways, of which 309 genes (65.33 %) are involved in the most affected metabolic pathway. The most sensitive metabolic pathways in response to cold stress involved energy metabolism, carbohydrate metabolism and photosynthesis proteins. The key hub regulatory genes were perceived as cyaA and genes related to two-component signal transduction systems. The genes regulated diverse metabolic functions to survive and grow. The increased respiration provided essential energy for basic motility maintenance under cold stress. The down-regulation of genes involved in photosynthesis, glycolysis, Calvin cycle and citrate cycle supported the low biomass production of the blue-green algae. The results provide a basis for revealing the survival mechanism of the blue-green algae to withstand cold stress at the gene transcription level.

Hexagonal boron nitride (h-BN) is an excellent thermally conductive and electrically insulative material. However, the formation of heat transfer pathways of h-BN in thermal interface materials is restricted due to its poor aqueous dispersity. Herein, water-soluble lignosulfonate (LS) is used to promote the dispersion of h-BN, the phenolic hydroxyl and three-dimensional structure of LS could form hydrogen bonding or steric hindrance with h-BN under ultrasound treatment. After mixing with cellulose nanofiber (CNF), the three-dimensional thermally conductive pathways are built in LS-BN/CNF aerogel through freeze-drying. The results show that the through-plane thermal conductivity of LS-BN/CNF/PVA composite with 0.2 wt% LS (LS0.2-BN/CNF/PVA) exceeds 1.22 W/mK when the h-BN/CNF ratio is 3:1 (w/w), which is 6.1-fold of that of PVA film (0.20 W/mK). The initial decomposition temperature and tensile strength of LS0.2-BN/CNF/PVA composite are 205 °C and 38.5 MPa, respectively, demonstrating acceptable thermal stability and mechanical properties for electronics as thermal interface and packing material. Overall, this work put forwards an effective approach to disperse h-BN and paves the way in developing high-performance thermal interface materials.

Background: Epigenetic aging is accelerated in tissues of persons living with HIV (PLWH) and may underlie the early onset of age-related illnesses. This study examines the rate-of-change in epigenetic age in PLWH following HIV infection but before HAART, using archived longitudinal samples from the Multicenter AIDS Cohort Study.Methods: DNA was isolated from cryopreserved peripheral blood mononuclear cells from 101 men living with HIV, with baseline visit

Abstract Background Glutathione transferases (GSTs), the ancient, ubiquitous and multi-functional proteins, play significant roles in development, metabolism as well as abiotic and biotic stress responses in plants. Wheat is one of the most important crops, but the functions of GST genes in wheat were less studied. Results A total of 330 TaGST genes were identified from the wheat genome and named according to the nomenclature of rice and Arabidopsis GST genes. They were classified into eight classes based on the phylogenetic relationship among wheat, rice, and Arabidopsis, and their gene structure and conserved motif were similar in the same phylogenetic class. The 43 and 171 gene pairs were identified as tandem and segmental duplication genes respectively, and the Ka/Ks ratios of tandem and segmental duplication TaGST genes were less than 1 except segmental duplication gene pair TaGSTU24/TaGSTU154. The 59 TaGST genes were identified to have syntenic relationships with 28 OsGST genes. The expression profiling involved in 15 tissues and biotic and abiotic stresses suggested the different expression and response patterns of the TaGST genes. Furthermore, the qRT-PCR data showed that GST could response to abiotic stresses and hormones extensively in wheat. Conclusions In this study, a large GST family with 330 members was identified from the wheat genome. Duplication events containing tandem and segmental duplication contributed to the expansion of TaGST family, and duplication genes might undergo extensive purifying selection. The expression profiling and cis-elements in promoter region of 330 TaGST genes implied their roles in growth and development as well as adaption to stressful environments. The qRT-PCR data of 14 TaGST genes revealed that they could respond to different abiotic stresses and hormones, especially salt stress and abscisic acid. In conclusion, this study contributed to the further functional analysis of GST genes family in wheat.

Gas injection into a slab continuous casting mold is a common practice as it enables long casting sequences by reducing SEN clogging. However, too much gas injection can generate lots of bubbles, and bubbles formed inside the mold are also responsible for the occurrence of various quality defects such as deterioration of steel cleanliness, reoxidation of liquid steel, and occurrence of sliver and blister defects, etc. Mean bubble size is a key parameter and controlling it can resolve/reduce these quality issues. Operating parameters such as gas flow rate and liquid flow rate are the major factors affecting the mean bubble size. Two-phase water modeling​ experiments were performed to generate bubbles in the mold, and the mean bubble diameter was captured using various gas and liquid flow rates. Clear images of bubbles were recorded using a high-speed high-resolution camera along with the application of shadowgraphy. Bubble images were processed using an image processing software, ImageJ to obtain bubble characteristics, and Sauter mean diameter was calculated for each operating condition. Advance machine learning techniques such as Multilinear Regression (MLR), Decision Tree (DT), Support Vector Machine (SVM), and Artificial Neural Network (ANN) were used on the experimental data to predict the combined effect of these operating parameters on the mean bubble diameter. All four ML techniques were compared considering the values of cross-validated adjusted R2, and a performance metric is presented to compare the suitability of ML techniques in this case.

Background: Since the outbreak of COVID-19 in 2020, routine CT examination was recommended to hospitalized patients at some hospitals and discovered lung cancer patients at an early stage. This study aimed to investigate the detection efficacy of routine CT examination on early diagnosis of lung cancer, especially on pathological characteristics. Methods: The epidemic of COVID-19 outbreak in January 2020 in China, and routine CT examination was recommended to hospitalized patients in June 2020 and ended in July 2021. Based on the time points, we compared the diagnosis efficacy between three periods: pre-period, peri-period, and the period of routine CT examination. Results: During the period of routine CT examination, more early stages of lung cancer were detected and the tumor size was reduced to 2.14 cm from 3.21 cm at pre-period (p = 0.03). The proportion of lung adenocarcinoma and early stage adenocarcinoma was increased by 12% and 30% in the period of routine CT examination, with referral to the pre-period of CT examination (p < 0.05). A total of 61% of diagnosed patients had the wild type of TP53 gene during the period of routine CT examination, compared to 45% of patients at the pre-period of CT examination (p = 0.001). The median Ki-67 index was 15% among patients diagnosed at the period of routine CT examination and increased to 35% at the pre-period of CT examination (p < 0.001). The period of routine CT examination was associated with a 78% higher probability of detecting an early stage of adenocarcinoma (OR = 1.78, 95%CI 1.03, 3.08) but no significant association was observed for squamous cell carcinoma. From the pre-period to the period of routine CT examination, the proportion of female patients and non-smoking patients increased by 57% and 44%, respectively (p < 0.001). Conclusion: Routine CT examination could detect more lung cancer at an early stage, especially for adenocarcinoma, and detect patients with less aggressive features. Further studies were warranted to confirm the findings.

Due to its unique physical and chemical properties, MXene has recently attracted much attention as a promising candidate for wastewater treatment. However, the low water permeation flux of MXene membrane remains a challenge that has not been fully solved. In this study, attapulgite was used to increase the flux of MXene membrane through a facile one-pot method, during which the MXene nanosheets were self-assembled while being intercalated by the attapulgite nanorods to finally form the composite membranes. Under optimal conditions, an increase of water permeation flux of 97.31% could be observed, which was attributed to the broadened nano-channel upon the adequate intercalation of attapulgite nanorods. Its permeation flux and rejection rate for methylene blue (MB) were further studied for diverse applications. In contrast to bare MXene, the permeation flux increased by 61.72% with a still high rejection rate of 90.67%, owing to the size rejection. Overcoming a key technique barrier, this work successfully improved the water permeability of MXene by inserting attapulgite nanorods, heralding the exciting prospects of MXene-based lamellar membrane in dye wastewater treatment.

Dietary phenolic compounds must be released from the food matrix in the gastrointestinal tract to play a bioactive role, the release of which is interfered with by food structure. The release of phenolics (unbound and bound) of cold and hot extruded noodles enriched with phenolics (2.0%) during simulated in vitro gastrointestinal digestion was investigated. Bound phenolic content and X-ray diffraction (XRD) analysis were utilized to characterize the intensity and manner of starch-phenolic complexation during the preparation of extruded noodles. Hot extrusion induced the formation of more complexes, especially the V-type inclusion complexes, with a higher proportion of bound phenolics than cold extrusion, contributing to a more controlled release of phenolics along with slower starch digestion. For instance, during simulated small intestinal digestion, less unbound phenolics (59.4%) were released from hot extruded phenolic-enhanced noodles than from the corresponding cold extruded noodles (68.2%). This is similar to the release behavior of bound phenolics, that cold extruded noodles released more bound phenolics (56.5%) than hot extruded noodles (41.9%). For noodles extruded with rutin, the release of unbound rutin from hot extruded noodles and cold extruded noodles was 63.6% and 79.0%, respectively, in the small intestine phase, and bound rutin was released at a much lower amount from the hot extruded noodles (55.8%) than from the cold extruded noodles (89.7%). Hot extrusion may allow more potential bioaccessible phenolics (such as rutin), further improving the development of starchy foods enriched with controlled phenolics.

This retrospective cohort analysis leveraged vaccination data for BNT162b2, mRNA-1273, and Ad26.COV2.S in the United States from the Komodo Healthcare Map database, the TriNetX Dataworks USA Network, and Cerner Real-World EHR (electronic health record) Data to evaluate rates of adherence to and completion of COVID-19 vaccination series (November 2020 through June 2021). Individuals were indexed on the date they received the first dose of a COVID-19 vaccine, with an adherence follow-up window of 42 days. Adherence/completion rates were calculated in the overall cohort of each database and by month of initiation and stratified by age, race/ethnicity, and urban/rural status. Overall adherence and completion to 2-dose COVID-19 mRNA vaccine schedules ranged from 79.4% to 87.4% and 81.0% to 89.2%, respectively. In TriNetX and Cerner, mRNA-1273 recipients were generally less adherent compared with BNT162b2 across sociodemographic groups. In Komodo, rates of adherence/completion between mRNA-1273 and BNT162b2 were similar. Adherence/completion were generally lower in younger (

Abstract Background HIV-positive persons bear an excess burden of chronic kidney disease (CKD); however, conventional methods to assess kidney health are insensitive and non-specific for detecting early kidney injury. Urinary biomarkers can detect early kidney injury, and may help mitigate the risk of overt CKD. Methods Cross-sectional study of HIV-positive persons in the Multicenter AIDS Cohort Study and the Women’s Interagency HIV Study. We measured levels of 14 biomarkers, capturing multiple dimensions of kidney injury. We then evaluated associations of known CKD risk factors with urine biomarkers using separate multivariable adjusted models for each biomarker. Results Of the 198 participants, one third were on HAART and virally suppressed. The vast majority (95%) had preserved kidney function as assessed by serum creatinine, with a median eGFR of 103 ml/min/1.73 m2 (interquartile range (IQR): 88, 116). In our multivariable analyses, the associations of each CKD risk factor with urinary biomarker levels varied in magnitude. For example, HIV viral load was predominantly associated with elevations in interleukin(IL)-18, and albuminuria, while higher CD4 levels were associated with lower monocyte chemoattractant protein-1 (MCP-1) and β2-microglobulin. In contrast, older age was significantly associated with elevations in α1-microglobulin, kidney injury marker-1, clusterin, MCP-1, and chitinase-3-like protein-1 levels, as well as lower epidermal growth factor, and uromodulin levels. Conclusions Among HIV-positive persons, CKD risk factors are associated with unique and heterogeneous patterns of changes in urine biomarkers levels. Additional work is needed to develop parsimonious algorithms that integrate multiple biomarkers and clinical data to discern the risk of overt CKD and its progression.

Tellurium (Te), the most metallic semiconductor, has been widely explored in recent decades owing to its fantastic properties such as a tunable bandgap, high carrier mobility, high thermal conductivity, and in-plane anisotropy. Many references have witnessed the rapid development of synthesizing diverse Te geometries with controllable shapes, sizes, and structures in different strategies. In all types of Te nanostructures, Te with one-dimensional (1D) hollow internal structures, especially nanotubes (NTs), have attracted extensive attention and been utilized in various fields of applications. Motivated by the structure-determined nature of Te NTs, we prepared a minor review about the emerging synthesis and nanostructure control of Te NTs, and the recent progress of research into Te NTs was summarized. Finally, we highlighted the challenges and further development for future applications of Te NTs.

Strict monitoring and prediction of endpoints in a Basic Oxygen Furnace (BOF) are essential for end-product quality and overall process efficiency. Existing control models are mostly developed based on thermodynamic principles or by deploying advanced sensors. This article aims to propose a novel hybrid algorithm for endpoint temperature, carbon, and phosphorus, based on heat and mass balance and a data-driven technique. Three types of static models were established in this study: firstly, theoretical models, based on user-specified inputs, were formulated based on mass and energy balance; secondly, artificial neural networks (ANN) were developed for endpoints predictions; finally, the proposed hybrid model was established, based upon exchanging outputs among theoretical models and ANNs. Data of steelmaking production details collected from 28,000 heats from Tata Steel India were used for this article. Machine learning model validation was carried out with five-fold cross-validation to ensure generalizations in model predictions. ANNs are found to achieve better predictive accuracies than theoretical models in all three endpoints. However, they cannot be directly applied in any steelmaking plants, due to possible variations in the production setting. After applying the hybrid algorithm, normalized root mean squared errors are reduced for endpoint carbon and phosphorus by 3.7% and 9.77%.

By installing on-board diagnostics (OBD) on tested vehicles, the after-treatment exhaust emissions can be monitored in real time to construct driving cycle-based emission models, which can provide data support for the construction of dynamic emission inventories of mobile source emission. However, in actual vehicle emission detection systems, due to the equipment installation costs and differences in vehicle driving conditions, engine operating conditions, and driving behavior patterns, it is impossible to ensure that the emission monitoring data of different vehicles always follow the same distribution. The traditional machine learning emission model usually assumes that the training set and test set of emission test data are derived from the same data distribution, and a unified emission model is used for estimation of different types of vehicles, ignoring the difference in monitoring data distribution. In this study, we attempt to build a diesel vehicle NOx emission prediction model based on the deep transfer learning framework with a few emission monitoring data. The proposed model firstly uses Spearman correlation analysis and Lasso feature selection to accomplish the selection of factors with high correlation with NOx emission from multiple sources of external factors. Then, the stacked sparse AutoEncoder is used to map different vehicle working condition emission data into the same feature space, and then, the distribution alignment of different vehicle working condition emission data features is achieved by minimizing maximum mean discrepancy (MMD) in the feature space. Finally, we validated the proposed method with the diesel vehicle OBD data that were collected by the Hefei Environmental Protection Bureau. The comprehensive experiment results show that our method can achieve the feature distribution alignment of emission data under different vehicle working conditions and improve the prediction performance of the NOx inversion model given a little amount of NOx emission monitoring data.

Abstract All‐solid‐sate Al‐air batteries with features of high theoretical energy density, low cost, and environmental‐friendliness are promising as power sources for next‐generation flexible and wearable electronics. However, the sluggish oxygen reduction reaction (ORR) and poor interfacial contact in air cathodes cause unsatisfied performance. Herein, a free‐standing Co3Fe7 nanoalloy and Co5.47N encapsulated in 3D nitrogen‐doped carbon foam (Co3Fe7@Co5.47N/NCF) is prepared as an additive‐free and integrated air cathode for flexible Al‐air batteries in both alkaline and neutral electrolytes. The Co3Fe7@Co5.47N/NCF outperforms commercial platinum/carbon (Pt/C) toward ORR with an onset potential of 1.02 V and a positive half‐wave potential of 0.92 V in an alkaline electrolyte (0.59 V in sodium chloride solution), which is ascribed to the unique interfacial structure between Co3Fe7 and Co5.47N supported by 3D N‐doped carbon foam to facilitate fast electron and mass transfer. The high ORR performance is also supported by in‐situ electrochemical Raman spectra and density functional theory calculation. Furthermore, the fabricated Al‐air battery displays good flexibility and delivers a power density of 199.6 mW cm−2, and the binder‐free and integrated cathode shows better discharge performance than the traditionally slurry casting cathode. This work demonstrates a facile and efficient approach to develop integrated air cathode for metal‐air batteries.

Objective Breast cancer has become the most common cancer in women in China, and the clinicopathological features differ from those in Western patients. This study was performed to investigate the distribution of programmed cell death protein 1 (PD-1) + /PD-1 − tumor-infiltrating lymphocytes (TILs) and its association with clinicopathological features among Chinese patients with breast cancer. Methods In total, 133 consecutive patients with primary breast cancer were recruited into this cross-sectional study from 2012 to 2013. TILs were measured by cell counts under high-power fields (HPFs). Immunohistochemistry was used to detect PD-1 expression on tumor-infiltrating lymphocytes in the microenvironment. Results The median cell counts of the overall TILs, PD-1 + TILs, and PD-1 − TILs were 80, 18, and 55/HPF, respectively. The number of PD-1 − TILs was significantly lower in older than younger patients (50 vs. 60/HPF). Patients with positive E-cadherin expression had more PD-1 − TILs than patients with negative E-cadherin expression (57 vs. 27/HPF). The Ki-67 index was positively correlated with the cell counts of PD-1 + TILs, and the correlation coefficient was 0.29. Conclusions PD-1 expression on TILs had different clinicopathological features in Chinese patients with breast cancer. E-Cadherin expression was associated with PD-1 − TILs; however, Ki-67 expression was associated with PD-1 + TILs.

Buckwheat noodles are mainly sold in the form of fresh and dried noodles in China. Among the noodles with varied proportions of extruded buckwheat flour (20% to 80%), the cooking or textural qualities of fresh and dried buckwheat noodles (FBN and DBN, respectively) were significantly different, and FBN showed a lower cooking loss and breakage ratio and were more elastic than DBN. FBN-20% showed the highest sensory score, followed by DBN-50%. The mechanisms causing the quality differences were investigated using water mobility and the internal structures of the noodles were investigated with low-field nuclear magnetic resonance and scanning electron microscopy, respectively. Compared with FBN, DBN showed a denser internal structure, which explained its higher hardness. The water within FBN and DBN was mainly in the form of softly bound water and tightly bound water, respectively. FBN with highly mobile softly bound water (longer T22) and a more uniform internal structure had a lower breakage ratio, whereas the trends of water relation with texture properties were different for FBN and DBN. The drying process and added extruded buckwheat flour together contributed to the varied cooking and textural properties.

MYB transcription factors play important roles in plant responses to biotic and abiotic stress. In this study, TaODORANT1, a R2R3-MYB gene, was cloned from wheat (Triticum aestivum L.). TaODORANT1 was localized in the nucleus and functioned as a transcriptional activator. TaODORANT1 was up-regulated in wheat under PEG6000, NaCl, ABA, and H2O2 treatments. TaODORANT1-overexpressing transgenic tobacco plants exhibited higher relative water content and lower water loss rate under drought stress, as well as lower Na+ accumulation in leaves under salt stress. The transgenic plants showed higher CAT activity but lower ion leakage, H2O2 and malondialdehyde contents under drought and salt stresses. Besides, the transgenic plants also exhibited higher SOD activity under drought stress. Our results also revealed that TaODORANT1 overexpression up-regulated the expression of several ROS- and stress-related genes in response to both drought and salt stresses, thus enhancing transgenic tobacco plants tolerance. Our studies demonstrate that TaODORANT1 positively regulates plant tolerance to drought and salt stresses.

Calcineurin B-like protein interacting protein kinases (CIPKs) are vital elements in plant abiotic stress signaling pathways. However, the functional mechanism of CIPKs has not been understood clearly, especially in Brachypodium distachyon, a new monocot model plant. In this study, BdCIPK31, a CIPK gene from B. distachyon was characterized. BdCIPK31 was downregulated by polyethylene glycol, NaCl, H2O2, and abscisic acid (ABA) treatments. Transgenic tobacco plants overexpressing BdCIPK31 presented improved drought and salt tolerance, and displayed hypersensitive response to exogenous ABA. Further investigations revealed that BdCIPK31 functioned positively in ABA-mediated stomatal closure, and transgenic tobacco exhibited reduced water loss under dehydration conditions compared with the controls. BdCIPK31 also affected Na+/K+ homeostasis and root K+ loss, which contributed to maintain intracellular ion homeostasis under salt conditions. Moreover, the reactive oxygen species scavenging system and osmolyte accumulation were enhanced by BdCIPK31 overexpression, which were conducive for alleviating oxidative and osmotic damages. Additionally, overexpression of BdCIPK31 could elevate several stress-associated gene expressions under stress conditions. In conclusion, BdCIPK31 functions positively to drought and salt stress through ABA signaling pathway. Overexpressing BdCIPK31 functions in stomatal closure, ion homeostasis, ROS scavenging, osmolyte biosynthesis, and transcriptional regulation of stress-related genes.

CO2 has been regarded as one of the most promising blowing agents for polystyrene (PS) foam due to its non-flammability, low price, nontoxicity, and eco-friendliness. However, the low solubility and fast diffusivity of CO2 in PS hinder its potential applications. In this study, an attapulgite (ATP)/polypyrrole (PPy) nanocomposite was developed using the in situ polymerization method to generate the hierarchical cell texture for the PS foam based on the supercritical CO2 foaming. The results demonstrated that the nanocomposite could act as an efficient CO2 capturer enabling the random release of it during the foaming process. In contrast to the pure PS foam, the ATP/PPy nanocomposite reinforced PS foam is endowed with high cell density (up to 1.9 × 106) and similar thermal conductivity as the neat PS foam, as well as high compression modulus. Therefore, the in situ polymerized ATP/PPy nanocomposite makes supercritical CO2 foaming desired candidate to replace the widely used fluorocarbons and chlorofluorocarbons as PS blowing agents.

Solid acids have been proposed as a hydrolytic agent for wood biomass dissolution. In this work, we presented an environmentally friendly physicochemical treatment to leave behind cellulose, dissolve hemicellulose, and remove lignin from poplar wood. Several pretreatments, such as autohydrolysis and disk refining, were compared to optimize and modify the process. The p-toluenesulfonic acid could extract lignin from wood with a small amount of cellulose degradation. Disk refining with subsequent acid hydrolysis (so-called physicochemical treatment) doubled the delignification efficiency. A comprehensive morphology and overall chemical composition were provided. The crystallinity index (CrI) of treated poplar was increased and the chemical structure was changed after physicochemical treatment. Optical microscopy and scanning electron microscopy analysis demonstrated physicochemical treatment affected the morphology of poplar wood by removing lignin and generating fiberization. In general, this work demonstrated this physicochemical method could be a promising fractionation technology for lignocellulosic biomass due to its advantages, such as good selectivity, in removing lignin while preserving cellulose.

High electrolyte wettability, thermal dimensional stability, and tensile strength are prerequisites for implementing separators in practical applications. In this study, we report on the discovery of nanofibril membranes derived from various plant fibers commonly used in the papermaking industry, for low cost and higher performances than the commercially available Celgard2325 in regard to the application of separators for lithium-ion batteries. Nanofibril membranes showed water contact angles as low as 18°, negligible size change at a heating temperature of 160 °C for 120 min, and tensile strength up to 137.6 MPa. The homogenization was found to strongly contribute to these improved performances. These findings suggest that the plant fiber-derived nanofibril membranes are anticipated to be promising candidates as separators for lithium-ion batteries.