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Abstract Background Root nodule symbiosis (RNS) is a fascinating evolutionary event. Given that limited genes conferring the evolution of RNS in Leguminosae have been functionally validated, the genetic basis of the evolution of RNS remains largely unknown. Identifying the genes involved in the evolution of RNS will help to reveal the mystery. Results Here, we investigate the gene loss event during the evolution of RNS in Leguminosae through phylogenomic and synteny analyses in 48 species including 16 Leguminosae species. We reveal that loss of the Lateral suppressor gene, a member of the GRAS-domain protein family, is associated with the evolution of RNS in Leguminosae. Ectopic expression of the Lateral suppressor (Ls) gene from tomato and its homolog MONOCULM 1 (MOC1) and Os7 from rice in soybean and Medicago truncatula result in almost completely lost nodulation capability. Further investigation shows that Lateral suppressor protein, Ls, MOC1, and Os7 might function through an interaction with NODULATION SIGNALING PATHWAY 2 (NSP2) and CYCLOPS to repress the transcription of NODULE INCEPTION (NIN) to inhibit the nodulation in Leguminosae. Additionally, we find that the cathepsin H (CTSH), a conserved protein, could interact with Lateral suppressor protein, Ls, MOC1, and Os7 and affect the nodulation. Conclusions This study sheds light on uncovering the genetic basis of the evolution of RNS in Leguminosae and suggests that gene loss plays an essential role.

Abstract Background The tumor microenvironment (TME) plays a key role in lung cancer initiation, proliferation, invasion, and metastasis. Artificial intelligence (AI) methods could potentially accelerate TME analysis. The aims of this study were to (1) assess the feasibility of using hematoxylin and eosin (H&E)-stained whole slide images (WSI) to develop an AI model for evaluating the TME and (2) to characterize the TME of adenocarcinoma (ADCA) and squamous cell carcinoma (SCCA) in fibrotic and non-fibrotic lung. Methods The cohort was derived from chest CT scans of patients presenting with lung neoplasms, with and without background fibrosis. WSI images were generated from slides of all 76 available pathology cases with ADCA (n = 53) or SCCA (n = 23) in fibrotic (n = 47) or non-fibrotic (n = 29) lung. Detailed ground-truth annotations, including of stroma (i.e., fibrosis, vessels, inflammation), necrosis and background, were performed on WSI and optimized via an expert-in-the-loop (EITL) iterative procedure using a lightweight [random forest (RF)] classifier. A convolution neural network (CNN)-based model was used to achieve tissue-level multiclass segmentation. The model was trained on 25 annotated WSI from 13 cases of ADCA and SCCA within and without fibrosis and then applied to the 76-case cohort. The TME analysis included tumor stroma ratio (TSR), tumor fibrosis ratio (TFR), tumor inflammation ratio (TIR), tumor vessel ratio (TVR), tumor necrosis ratio (TNR), and tumor background ratio (TBR). Results The model’s overall classification for precision, sensitivity, and F1-score were 94%, 90%, and 91%, respectively. Statistically significant differences were noted in TSR (p = 0.041) and TFR (p = 0.001) between fibrotic and non-fibrotic ADCA. Within fibrotic lung, statistically significant differences were present in TFR (p = 0.039), TIR (p = 0.003), TVR (p = 0.041), TNR (p = 0.0003), and TBR (p = 0.020) between ADCA and SCCA. Conclusion The combined EITL—RF CNN model using only H&E WSI can facilitate multiclass evaluation and quantification of the TME. There are significant differences in the TME of ADCA and SCCA present within or without background fibrosis. Future studies are needed to determine the significance of TME on prognosis and treatment.

Abstract Purpose Evaluate the behavior of lung nodules occurring in areas of pulmonary fibrosis and compare them to pulmonary nodules occurring in the non-fibrotic lung parenchyma. Methods This retrospective review of chest CT scans and electronic medical records received expedited IRB approval and a waiver of informed consent. 4500 consecutive patients with a chest CT scan report containing the word fibrosis or a specific type of fibrosis were identified using the system M*Model Catalyst (Maplewood, Minnesota, U.S.). The largest nodule was measured in the longest dimension and re-evaluated, in the same way, on the follow-up exam if multiple time points were available. The nodule doubling time was calculated. If the patient developed cancer, the histologic diagnosis was documented. Results Six hundred and nine patients were found to have at least one pulmonary nodule on either the first or the second CT scan. 274 of the largest pulmonary nodules were in the fibrotic tissue and 335 were in the non-fibrotic lung parenchyma. Pathology proven cancer was more common in nodules occurring in areas of pulmonary fibrosis compared to nodules occurring in areas of non-fibrotic lung (34% vs 15%, p

Abstract Background Chest Computed tomography (CT) scans detect lung nodules and assess pulmonary fibrosis. While pulmonary fibrosis indicates increased lung cancer risk, current clinical practice characterizes nodule risk of malignancy based on nodule size and smoking history; little consideration is given to the fibrotic microenvironment. Purpose To evaluate the effect of incorporating fibrotic microenvironment into classifying malignancy of lung nodules in chest CT images using deep learning techniques. Materials and methods We developed a visualizable 3D classification model trained with in-house CT dataset for the nodule malignancy classification task. Three slightly-modified datasets were created: (1) nodule alone (microenvironment removed); (2) nodule with surrounding lung microenvironment; and (3) nodule in microenvironment with semantic fibrosis metadata. For each of the models, tenfold cross-validation was performed. Results were evaluated using quantitative measures, such as accuracy, sensitivity, specificity, and area-under-curve (AUC), as well as qualitative assessments, such as attention maps and class activation maps (CAM). Results The classification model trained with nodule alone achieved 75.61% accuracy, 50.00% sensitivity, 88.46% specificity, and 0.78 AUC; the model trained with nodule and microenvironment achieved 79.03% accuracy, 65.46% sensitivity, 85.86% specificity, and 0.84 AUC. The model trained with additional semantic fibrosis metadata achieved 80.84% accuracy, 74.67% sensitivity, 84.95% specificity, and 0.89 AUC. Our visual evaluation of attention maps and CAM suggested that both the nodules and the microenvironment contributed to the task. Conclusion The nodule malignancy classification performance was found to be improving with microenvironment data. Further improvement was found when incorporating semantic fibrosis information.

The inherent complexity of cellulose, hemicellulose, and lignin contributes to the recalcitrance of lignocellulosic biomass, resulting in a low conversion efficiency and high cost of bioethanol conversion. Pretreatment methods that disrupt the plant cell structure of lignocellulose, such as straw, can significantly enhance the conversion efficiency. In this study, we utilized an acid-assisted mechanocatalytic depolymerization technique to pretreat rice straw, and the results demonstrated a significant disruption of the cellulose structure of the straw. Compared to the untreated straw, the particle size of pretreated straw reduced from 279 μm to 11.8 μm, the crystallinity of cellulose decreased from 43.05% to 22.71%, the specific surface area increased by 177%, and the surface oxygen-to-carbon ratio (O/C) ratio was enhanced by 75%. The changes in microstructure enabled the pretreated straw to achieve a total sugar yield of over 95% within 12 h of enzymatic hydrolysis, significantly superior to the 36.24% yield from untreated straw, the 45.20% yield from acid impregnated straw, and the 73.25% yield from ball milled straw. Consequently, acid-assisted mechanocatalytic depolymerization emerges as a highly effective pretreatment strategy to enhance both the enzymatic hydrolysis and the overall conversion efficiency of rice straw.

This study aims to investigate the coupling and harmonization between land ecological security (LES) and high-quality agricultural development (HAD) in the Han River Basin (HRB), China, with the objective of promoting harmonious coexistence between agriculture and ecosystems. Using 17 cities in the HRB as the research objects, an evaluation index system of two systems, LES and HAD, was constructed, analyzed, and evaluated via projective tracer modeling for multiple intelligent genetic algorithms (MIGA-PTM). The degree of coupling coordination (DCC) was used to quantitatively evaluate the coupling coordination development status of the two systems, the obstacle model (OM) was used to identify the main influencing factors, and the gray predictive model first-order univariate model (GM (1, 1)) was used to predict the DCC of the LES and HAD from 2025 to 2040. The results show the following: (1) the LES and HAD levels of the 17 cities in the HRB tended to increase during the study period, and there was a large gap between cities; (2) the spatial distributions of the DCCs of the LES and HAD in the HRB were uneven, with high values in the southern and low values in the central and northern parts, and the overall degree of coupling tended to fluctuate. The overall DCC showed a fluctuating upward trend; (3) the degree of obstacles, per capita water resources, greening coverage, and rate of return on financial expenditure are the main influencing factors; and (4) the prediction results of GM (1, 1) indicate that the LES and HAD of the HRB will be close to reaching the intermediate stage of coupling in 2035. This research offers critical insights into sustainable development practices that facilitate the alignment of agricultural growth with ecological preservation.

To address the challenges of missed and false detections in citrus fruit detection caused by environmental factors such as leaf occlusion, fruit overlap, and variations in natural light in hilly and mountainous orchards, this paper proposes a citrus detection model based on an improved YOLOv5 algorithm. By introducing receptive field convolutions with full 3D weights (RFCF), the model overcomes the issue of parameter sharing in convolution operations, enhancing detection accuracy. A focused linear attention (FLA) module is incorporated to improve the expressive power of the self-attention mechanism while maintaining computational efficiency. Additionally, anchor boxes were re-clustered based on the shape characteristics of target objects, and the boundary box loss function was improved to Foal-EIoU, boosting the model’s localization ability. Experiments conducted on a citrus fruit dataset labeled using LabelImg, collected from hilly and mountainous areas, showed a detection precision of 95.83% and a mean average precision (mAP) of 79.68%. This research not only significantly improves detection performance in complex environments but also provides crucial data support for precision tasks such as orchard localization and intelligent picking, demonstrating strong potential for practical applications in smart agriculture.

Large Language Models (LLMs), based on their highly developed ability to comprehend and generate human-like text, promise to revolutionize all aspects of society. These LLMs facilitate complex language understanding, translation, content generation, and problem-solving, enabled by vast historical data processing and fine-tuning. Throughout the past year, with the initial release of ChatGPT to the public, many papers have appeared on how to exploit LLMs for the ways we operate and interact with intelligent transportation systems. In this study, we review more than 130 papers on the subject and group them according to their major contributions into the following five categories: autonomous driving, safety, tourism, traffic, and others. Based on the aggregated proposals and findings in the extant literature, this paper concludes with a set of challenges and research recommendations, hopefully contributing to guide research in this young, yet extremely active research domain.

Although nitrogen deficiency and sucrose are linked to anthocyanin synthesis, the potential role of sucrose in regulating anthocyanin biosynthesis under low nitrogen conditions (LN) in purple lettuce (Lactuca sativa L.) remains unclear. We found that adding exogenous sucrose enhanced anthocyanin biosynthesis but significantly inhibited lettuce growth at high concentrations. Optimal results were obtained using 1 mmol/L sucrose in a low-nitrogen nutrient solution (LN + T1). Chlorophyll fluorescence imaging indicated that the addition of exogenous sucrose induced mild stress. Meanwhile, the activities of antioxidant enzymes (SOD, CAT, and POD) and antioxidant capacity were both enhanced. The mild stress activated the antioxidant system, thereby promoting the accumulation of anthocyanins induced by exogenous sucrose. LN + T1 (low nitrogen nutrient solution supplemented with 1 mmol/L sucrose) up-regulated enzyme genes in the biosynthetic pathway of anthocyanins, including phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), dihydroflavonol reductase (DFR), flavanone 3-hydroxylase (F3H), flavonoid 3′-hydroxylase (F3′H), flavone synthase II (FNSII), and anthocyanidin synthase (ANS). Additionally, various transcription factors such as AP2/ERF, MYB, bHLH, C2H2, NAC, C2C2, HB, MADS, bZIP, and WRKY were found to be up-regulated. This study elucidates the regulatory mechanism of anthocyanin metabolism in response to the addition of exogenous sucrose under low nitrogen conditions and provides a nutrient solution formula to enhance anthocyanin content in modern, high-quality agricultural cultivation.

Irreversible cryogenic damage caused by oocyte vitrification limits its widespread use in female fertility preservation. In recent years, nanoparticles (NPs) have gained great attention as potential alternatives in protecting oocytes against cryoinjuries. In this paper, a novel composite nanoparticle, poly (lactic-co-glycolic acid)-resveratrol (PLGA-RES) was designed to improve the biocompatibility and sustained release properties by encapsulating natural antioxidant RES into PLGA NPs. Firstly, biotoxicity and oxidation resistance of PLGA-RES were determined, and the results showed that PLGA-RES had nontoxic effect on oocyte survival during in vitro maturation (IVM) (97.08% ± 0.24% vs. 98.89% ± 1.11%, p > 0.05). Notably, PLGA-RES even increased maturation (65.10% ± 4.11% vs. 52.85% ± 2.87%, p < 0.05) and blastocyst rate (56.13% ± 1.36% vs. 40.91% ± 5.85%, p < 0.05). Moreover, the reduced reactive oxygen species (ROS) level (13.49 ± 2.30 vs. 34.07 ± 3.30, p < 0.01), increased glutathione (GSH) (44.13 ± 1.57 vs. 37.62 ± 1.79, p < 0.01) and elevated mitochondrial membrane potential (MMP) levels (43.10 ± 1.81 vs. 28.52 ± 1.25, p < 0.01) were observed in oocytes treated with PLGA-RES when compared with that of the control group. Subsequently, the role of PLGA-RES played in oocytes during vitrification was systematically evaluated. The results showed that the addition of PLGA-RES during vitrification and thawing significantly improved the survival rate (80.42% ± 1.97% vs. 75.37% ± 1.3%, p < 0.05). Meanwhile, increased GSH (15.09 ± 0.86 vs. 14.51 ± 0.78, p < 0.01) and mitochondrial membrane potential (22.56 ± 3.15 vs. 6.79 ± 0.60, p < 0.01), decreased reactive oxygen species levels (52.11 ± 2.95 vs. 75.41 ± 7.23, p < 0.05) and reduced mitochondrial abnormality distribution rate (25.00% ± 0.29% vs. 33.33% ± 1.15%, p < 0.01) were assessed in vitrified MII oocytes treated with PLGA-RES. Furthermore, transcriptomic analyses demonstrated that PLGA-RES participated in endocytosis and PI3K/AKT/mTOR pathway regulation, which was verified by the rescued expression of ARRB2 and ULK3 protein after PLGA-RES treatment. In conclusion, PLGA-RES exhibited potent antioxidant activity, and could be used as an efficacious strategy to improve the quality of vitrified oocytes.

Abstract Objective This cross-sectional study aimed to investigate the association between periodontitis and osteoporosis among US adults as well as the subgroup of menopausal women. Background Periodontitis and osteoporosis are both chronic inflammatory diseases characterized by local or systemic bone resorption. Since they share many risk factors, and the significant decrease in estrogen along with menopause is unfavorable for both diseases, it’s reasonable to assume that there exists some links between the two diseases, especially during the menopause. Methods We analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2009–2010 and 2013–2014. Periodontitis (defined according to the CDC/AAP definition) and osteoporosis (assessed by the dual-energy radiation absorptiometry) data were available for 5736 participants, and 519 subjects were enrolled in the subgroup of menopausal women aged 45–60 years old. We used binary logistic regression analysis to examine the association between the two diseases both in crude and fully adjusted model. Results In the fully adjusted model, osteoporosis was significantly associated with an increased risk of periodontal disease (OR:1.66, 95% CI: 1.00–2.77) in the whole population. As to the subgroup of menopausal women, osteoporosis group had an adjusted OR of 9.66 (95% CI: 1.13–82.38) for developing severe periodontitis in the fully adjusted model. Conclusions Osteoporosis is significantly associated with periodontitis and the association is even more pronounced in menopausal women with severe periodontitis.

Efficient acquisition of crop leaf moisture information holds significant importance for agricultural production. This information provides farmers with accurate data foundations, enabling them to implement timely and effective irrigation management strategies, thereby maximizing crop growth efficiency and yield. In this study, unmanned aerial vehicle (UAV) multispectral technology was employed. Through two consecutive years of field experiments (2021–2022), soybean (Glycine max L.) leaf moisture data and corresponding UAV multispectral images were collected. Vegetation indices, canopy texture features, and randomly extracted texture indices in combination, which exhibited strong correlations with previous studies and crop parameters, were established. By analyzing the correlation between these parameters and soybean leaf moisture, parameters with significantly correlated coefficients (p < 0.05) were selected as input variables for the model (combination 1: vegetation indices; combination 2: texture features; combination 3: randomly extracted texture indices in combination; combination 4: combination of vegetation indices, texture features, and randomly extracted texture indices). Subsequently, extreme learning machine (ELM), extreme gradient boosting (XGBoost), and back propagation neural network (BPNN) were utilized to model the leaf moisture content. The results indicated that most vegetation indices exhibited higher correlation coefficients with soybean leaf moisture compared with texture features, while randomly extracted texture indices could enhance the correlation with soybean leaf moisture to some extent. RDTI, the random combination texture index, showed the highest correlation coefficient with leaf moisture at 0.683, with the texture combination being Variance1 and Correlation5. When combination 4 (combination of vegetation indices, texture features, and randomly extracted texture indices) was utilized as the input and the XGBoost model was employed for soybean leaf moisture monitoring, the highest level was achieved in this study. The coefficient of determination (R2) of the estimation model validation set reached 0.816, with a root-mean-square error (RMSE) of 1.404 and a mean relative error (MRE) of 1.934%. This study provides a foundation for UAV multispectral monitoring of soybean leaf moisture, offering valuable insights for rapid assessment of crop growth.

Abstract The defects within perovskite films are the fatal roadblock limiting the performance of perovskite solar cells (PSCs). Herein, we develop a patching strategy to obtain high‐quality perovskite film using bifunctional trifluorophenylacetic acid (TFPA). Theoretical calculation and experiments reveal that the –COOH groups in TFPA effectively passivate the deep‐energy‐level defects of perovskite by combining with Pb clusters on the perovskite grain surfaces to enhance the efficiency of PSCs, and hydrophobic benzene groups containing fluorine in TFPA are exposed to improve the stability of PSCs. The power conversion efficiency (PCE) of PSCs with TFPA is enhanced from 22.95% to 24.56%. Most importantly, we successfully fabricated flexible PSCs using TFPA with the high PCE of 22.65%. The devices with TFPA maintain 93.22% of the initial efficiency MPP under continuous irradiation for 10.5 h, while the devices without TFPA only retain 82.22% of the initial efficiency under the same conditions for just 5 h. Meanwhile, the unsealed devices with TFPA hold 93.59% of the initial efficiency when stored in air for 3912 h.

Nitric oxide (NO), as an important gaseous medium, plays a pivotal role in the human body, such as maintaining vascular homeostasis, regulating immune-inflammatory responses, inhibiting platelet aggregation, and inhibiting leukocyte adhesion. In recent years, the rapid prevalence of coronavirus disease 2019 (COVID-19) has greatly affected the daily lives and physical and mental health of people all over the world, and the therapeutic efficacy and resuscitation strategies for critically ill patients need to be further improved and perfected. Inhaled nitric oxide (iNO) is a selective pulmonary vasodilator, and some studies have demonstrated its potential therapeutic use for COVID-19, severe respiratory distress syndrome, pulmonary infections, and pulmonary hypertension. In this article, we describe the biochemistry and basic characteristics of NO and discuss whether iNO can act as a “savior” for COVID-19 and related respiratory and cardiovascular disorders to exert a potent clinical protective effect.

This study attempted to explore the adaptability of gut microbiota in grass carp to diets with different carbohydrate-to-protein ratios in order to better understand the immunological and metabolic changes in the organism. Three different ratios of carbohydrate and protein diets (12.5%-carbohydrate 46.3%-protein (LCHP), 27.5%-carbohydrate 33.7%-protein (MCMP), and 42.5%-carbohydrate 16.9%-protein (HCLP)) were satiety-fed to grass carp. After feeding, the growth performance, gut microbial community composition and function were analyzed. Growth performance results showed that LCHP group exhibited the significantly lower specific growth ratio than MCMP group, and HCLP group displayed the significantly higher feed coefficient and lower survival rate. The community composition results showed that the abundance of the beneficial genus Cetobacterium was the highest in MCMP group, and the abundance of the harmful genera Ruminiclostridium_9 and Phreatobacter was the highest in the LCHP and HCLP groups, respectively. Furthermore, the ratio of Firmicutes to Bacteroidetes considered as an indicator of gut microbiota dysfunction, was significantly higher in the LCHP and HCLP groups than that in the MCMP group. The community functional analysis showed that the abundance levels of cofactors and vitamin metabolism were significantly lower and the abundance levels of neurodegenerative diseases were significantly higher in the LCHP and HCLP groups than those in the MCMP group. The abundance levels of energy metabolism and a range of biomolecules metabolism were significantly decreased in the HCLP group. These results suggested that high-carbohydrate diets have a greater negative impact on the gut microbiota than high-protein diets. The gut microbiota results echoed the growth performance parameters, reflecting that gut microbiota may play an important role in the influence of different carbohydrate-to-protein ratios diets on host. Bacterial genera such as Ruminiclostridium_9 and Phreatobacter may play key roles in the effects of high-protein and high-carbohydrate diets on host health and metabolism, respectively.

This experiment investigated the impact of taurine supplementation in low fishmeal diets on growth, antioxidant capacity, immunity and intestinal health of Litopenaeus vannamei. In this experiment, five diets were formulated, of which the high fishmeal diet contained 25% fishmeal (HF) and the remaining four diets were a mixture of soybean protein concentrate and Clostridium autoethanogenum protein (CAP) replacing 15% fishmeal and supplemented with 0%, 0.2%, 0.4% and 0.6% taurine (LF, T1, T2, T3). A total of 800 healthy shrimp (0.32 ± 0.00 g) were randomly allocated into 5 groups, with each group consisting of 4 replicates and 40 shrimp per replicate. The shrimp were fed four times a day for 51 days. The results showed that there was no significant difference in weight gain rate and survival (P＞0.05). Dietary taurine supplementation significantly improved the antioxidant capacity of shrimp. Compared with LF group, the mRNA expression of alf (anti-lipopolysaccharide factor) and cru (crustins) in HF group were significantly up-regulated (P＜0.05). Compared with the HF and LF groups, the mRNA expression of pen3 (penaeidins 3) in T1, T2 and T3 groups was significantly up-regulated, and the mRNA expression of dorsal in T2 group was significantly up-regulated (P＜0.05). The mRNA expression of bcl-2 (B-cell lymphoma-2) in T2 group was significantly up-regulated than that in other groups (P＜0.05). The mRNA expression of cyt-c (cytochrome c) in LF group was significantly up-regulated than that in other groups (P＜0.05). Compared with LF group, the mRNA expression of tnf-a (tumor necrosis factor-alpha) in HF, T2 and T3 groups was significantly down-regulated (P＜0.05). The mRNA expression of caspase8 in HF and T2 group was significantly down-regulated than that in other groups (P＜0.05). Compared with LF group, the mRNA expression of caspase3 in T1 groups was significantly down-regulated (P＜0.05). Intestinal H&E stained sections showed that dietary taurine supplementation improved intestinal mucosal folds height, width and muscle layer thickness. In general, dietary taurine supplementation can improve the antioxidant capacity, immunity and intestinal health of Litopenaeus vannamei, and the optimal supplemental level is 0.4%.

Abstract Background High-order chromatin structure plays important roles in gene regulation. However, the diversity of the three-dimensional (3D) genome across plant accessions are seldom reported. Results Here, we perform the pan-3D genome analysis using Hi-C sequencing data from 27 soybean accessions and comprehensively investigate the relationships between 3D genomic variations and structural variations (SVs) as well as gene expression. We find that intersection regions between A/B compartments largely contribute to compartment divergence. Topologically associating domain (TAD) boundaries in A compartments exhibit significantly higher density compared to those in B compartments. Pan-3D genome analysis shows that core TAD boundaries have the highest transcription start site (TSS) density and lowest GC content and repeat percentage. Further investigation shows that non-long terminal repeat (non-LTR) retrotransposons play important roles in maintaining TAD boundaries, while Gypsy elements and satellite repeats are associated with private TAD boundaries. Moreover, presence and absence variation (PAV) is found to be the major contributor to 3D genome variations. Nevertheless, approximately 55% of 3D genome variations are not associated with obvious genetic variations, and half of them affect the flanking gene expression. In addition, we find that the 3D genome may also undergo selection during soybean domestication. Conclusion Our study sheds light on the role of 3D genomes in plant genetic diversity and provides a valuable resource for studying gene regulation and genome evolution.

This work aims to evaluate the effect of stacking sequence on impact properties of polymer hybrid composites comprising randomly oriented Phoenix pusilla leaf fibers (PPFs), woven E-glass, and carbon fabrics. The PPFs were treated with 6% (w/v) NaOH solution for a period of 45 min. The composite laminates are produced through manual hand lay-up method by arranging treated PPFs, E-glass, and carbon fabrics in different layering sequences and impact and interlaminar shear strength properties were evaluated. The results showed that hybrid composites with carbon as outer layers exhibit an improved impact and an interlaminar strength property as compared to remaining hybrid laminates. Scanning electron microscopy investigation was also carried out on the fractured specimens in this work. This work is a part of exploring the use of hybrid composite prepared for some potential engineering applications.

ObjectiveThis study aims to solve the problems of poor tracking stability and low rapidity of traditional maximum power tracking algorithms in shipborne wind power generation systems.MethodsOn the basis of systematically analyzing the characteristics of the synthetic wind field of ship motion, an optimal mechanical angular velocity tracking control strategy based on single neuron proportional integral (SNPI) is proposed to improve the tracking speed of wind turbine restart. At the same time, the power sliding mode extremum seeking (PSMES) algorithm is used to replace the tip speed ratio (TSR) method which relies on accurate wind speed measurement to achieve the rapid optimization of mechanical angular velocity and cope with the maximum power search under frequent restarts of the power generation system. ResultsThe simulation results show that using the maximum power tracking strategy of mechanical angular velocity PSMES optimization and SNPI control, compared with the traditional algorithm, improves rapidity performance by more than 50% while also enhancing stability performance. ConclusionThe proposed maximum power tracking algorithm has obvious advantages in both rapidity and stability.

Due to the increasing concern with the environmental safety and recyclability, natural fiber-reinforced composites have attracted more and more attention. In the present work, braking composite samples with and without wet granulation were fabricated and their physical, mechanical, and environmental properties were investigated systematically. The experimental results showed that the use of the wet granulation technology did not improve significantly the water absorption and impact strength properties of the braking composite samples but considerably improved their density and environmental performance in comparison to the braking composite sample without wet granulation, especially the environmental performance. Among the braking composite samples with wet granulation, with the decreasing of the resin contents, the density was decreased gradually, the water absorption was decreased and then increased, and the impact strength was increased. Samples FG-13 and FG-11 had a relatively low dust capacity, and sample FG-5 was the highest. The method of the braking composite preparation in the present work may serve as a useful guide to produce a strong low-resin environmental-friendly composite for automotive components.

Shoot branching is critical in determining soybean yield. Here, the authors report natural variation of Dt2 in controlling soybean branching number and the interaction of Dt2 with GmAgl22 and GmSoc1a to activate transcription of GmAp1a and GmAp1d.

Semen cryopreservation is a promising technology employed in preserving high-quality varieties in animal husbandry and is also widely applied in the human sperm bank. However, the compromised qualities, such as decreased sperm motility, damaged membrane structure, and reduced fertilization competency, have significantly hampered the efficient application of this technique. Therefore, it is imperative to depict various molecular changes found in cryopreserved sperm and identify the regulatory network in response to the cryopreservation stress. In this study, semen was collected from three Chinese Merino rams and divided into untreated (fresh semen, FS) and programmed freezing (programmed freezing semen, PS) groups. After measuring different quality parameters, the ultra-low RNA-seq and tandem mass tag-based (TMT) proteome were conducted in both the groups. The results indicated that the motility (82.63% ± 3.55% vs. 34.10% ± 2.90%, p < 0.05) and viability (89.46% ± 2.53% vs. 44.78% ± 2.29%, p < 0.05) of the sperm in the FS group were significantly higher compared to those in the PS group. In addition, 45 upregulated and 291 downregulated genes, as well as 30 upregulated and 48 downregulated proteins, were found in transcriptomics and proteomics data separately. Moreover, three integrated methods, namely, functional annotation and enrichment analysis, Pearson’s correlation analysis, and two-way orthogonal partial least squares (O2PLS) analysis, were used for further analysis. The results suggested that various differentially expressed genes and proteins (DEGs and DEPs) were mainly enriched in leishmaniasis and hematopoietic cell lineage, and Fc gamma receptor Ia (FCGR1A) was significantly downregulated in cryopreserved sperm both at mRNA and protein levels in comparison with the fresh counterpart. In addition, top five genes (FCGR1A, HCK, SLX4, ITGA3, and BET1) and 22 proteins could form a distinct network in which genes and proteins were significantly correlated (p < 0.05). Interestingly, FCGR1A also appeared in the top 25 correlation list based on O2PLS analysis. Hence, FCGR1A was selected as the most potential differentially expressed candidate for screening by the three integrated multi-omics analysis methods. In addition, Pearson’s correlation analysis indicated that the expression level of FCGR1A was positively correlated with sperm motility and viability. A subsequent experiment was conducted to identify the biological role of FCGR1A in sperm function. The results showed that both the sperm viability (fresh group: 87.65% ± 4.17% vs. 75.8% ± 1.15%, cryopreserved group: 48.15% ± 0.63% vs. 42.45% ± 2.61%, p < 0.05) and motility (fresh group: 83.27% ± 4.15% vs. 70.41% ± 1.07%, cryopreserved group: 45.31% ± 3.28% vs. 35.13% ± 2.82%, p < 0.05) were significantly reduced in fresh and frozen sperm when FCGR1A was blocked. Moreover, the cleavage rate of embryos fertilized by FCGR1A-blocked sperm was noted to be significantly lower in both fresh (95.28% ± 1.16% vs. 90.44% ± 1.56%, p < 0.05) and frozen groups (89.8% ± 1.50% vs. 82.53% ± 1.53%, p < 0.05). In conclusion, our results revealed that the downregulated membrane protein FCGR1A can potentially contribute to the reduced sperm fertility competency in the cryopreserved sheep sperm.

Brevibacillus laterosporus (B. laterosporus) is widely distributed in nature and demonstrates significant potential for applications in biological control, environmental protection, agricultural production, and clinical medicine. This review provides a comprehensive overview of the applications of B. laterosporus in crop cultivation and animal feeding, as well as an examination of the antimicrobial peptides produced by B. laterosporus and their antibacterial mechanisms. B. laterosporus enhances crop cultivation by secreting hydrolases to improve nutrient absorption capabilities, synthesizing hormones to promote crop growth, and producing proteins to inhibit the reproduction of harmful organisms. B. laterosporus has been used to improve animal production by regulating the structure of the intestinal microbiota and inhibiting the growth of pathogenic bacteria through the secretion of various antimicrobial peptides. The bactericidal activity of Brevilaterins secreted by B. laterosporus is attributed to their ability to bind to lipopolysaccharide/lipid II molecules on the cell membrane, thereby altering permeability. Brevilaterins also inhibit bacterial reproduction by affecting relevant gene pathways in the cell membranes of pathogenic bacteria. These pathways include ATP synthesis, peptidoglycan biosynthesis, membrane transport, and cellular metabolism. In conclusion, B. laterosporus exhibits substantial potential as a probiotic activity in crop and animal production. However, applications of B. laterosporus in animal production could be improved, necessitating further research to elucidate the underlying probiotic mechanisms.

Perovskite solar cells have aroused a worldwide research upsurge in recent years due to their soaring photovoltaic performance, ease of solution processing, and low cost. The power conversion efficiency record is constantly being broken and has recently reached 26.1% in the lab, which is comparable to the established photovoltaic technologies such as crystalline silicon, copper indium gallium selenide and cadmium telluride (CdTe) solar cells. Currently, perovskite solar cells are standing at the entrance of industrialization, where huge opportunities and risks coexist. However, towards commercialization, challenges of up-scaling, stability and lead toxicity still remain, the proper handling of which could potentially lead to the widespread adoption of perovskite solar cells as a low-cost and efficient source of renewable energy. This review gives a holistic analysis of the path towards commercialization for perovskite solar cells. A comprehensive overview of the current state-of-the-art level for perovskite solar cells and modules will be introduced first, with respect to the module efficiency, stability and current status of industrialization. We will then discuss the challenges that get in the way of commercialization and the corresponding strategies to address them, involving the upscaling, the stability and the lead toxicity issue. Insights into the future direction of commercialization of perovskite photovoltaics was also provided, including the flexible perovskite cells and modules and perovskite indoor photovoltaics. Finally, the future perspectives towards commercialization are put forward.

Tong et al. describe a super pangenome assembled from long-read sequences of 545 wild and domesticated silkworms. Naturally selected (diapause, aposemantic coloration) or artificially selected (silk yield and fineness) sets of genes are delineated.

In this article, mechanical and tribological characterization of Cissus quadrangularis stem fiber (CQSF)/epoxy resin particulate with and without coconut shell ash (CSA) powder was carried out. The materials were fabricated by the hand lay-up method. Epoxy and 30 wt.% CQSF with 40 mm fiber length were taken to fabricate the base material, and CSA was separately added at 2.5, 5, 7.5, and 10 wt.%. In this way, five materials were fabricated for mechanical and tribological investigation. The tribological characterization was analyzed by Response Surface Methodology (RSM) using Design-Expert software, and pin-on-disc wear testing machine was used to calculate the specific wear rate of the materials under different experimental conditions. A design table was created for four factors and three levels using full factorial central composite design. The maximum tensile (110.31 MPa) and flexural (136.11 MPa) strength obtained at 5 wt.% CSA addition and after that reduced. The maximum hardness (98 HRRW) and impact strength (20.03 J/cm2) were obtained at 10 wt.% CSA particulate-filled CQSF/epoxy composite. CQSF/epoxy with 5.9 wt.% CSA filler yielded better specific wear rate (6.67 × 10−5 mm3/Nm) compared with other compositions, which was found in the RSM technique. Scanning electron microscopy (SEM) images were taken to identify failure mechanisms for the specimen.

Co3O4 spinel oxides have manifested promising activity toward the oxygen evolution reaction (OER) through effective modifications. For them to become top electrocatalysts, however, accurate accounts of the catalytic kinetics are essential to gain a deep understanding of the activity promotion mechanisms. Herein, we use a newly proposed kinetic model based on energetic span as the rate-determining term for the electrocatalytic reaction to throw light on the promotion mechanism of Co3O4 interfaced with nickel hydroxides (NiOxHy) for the OER. We find that depending on the electrode potential, the OER kinetics at the designed interface between Co3O4 and NiOxHy are boosted in entirely different ways. As a result, the OER can occur at a lower onset potential as well as a low Tafel slope. This work emphasizes the benefit of using rational theoretical models for electrocatalyst design.