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Expanding toolkits of EPA/DHA enrichment from natural sources is essential for better satisfying increasing demands for them. Lipase K80, from Proteus vulgaris K80, showed an application potential in EPA/DHA enrichment, whereas no desired heterologous expression in generally regarded as safe (GRAS) hosts restricted its relevant applications. In this study, expression of lipase K80 in a well-reputed GRAS host, Pichia pastoris, was achieved and further enhanced via combining disruption of its C-terminal KKL motif with co-expression of N-Acetyltransferase Mpr1, with a cumulative increment of nearly 200% in the secretion level and the volumetric activity. Its application in EPA/DHA enrichment from fish oil was thereafter obtained with merits of low temperature and much less time, yielding an increase of ~31% in their total percentage. To gain mechanistic insights into its substrate chain-length specificity, we performed molecular dynamics simulation and revealed the substrate-dependent significant yet divergent conformational shifts of predominantly distal surface-exposed regions, suggesting a predominant long-range modulation mechanism. Together, this work provided in-depth insights into substrate specificity of lipase K80 and an alternate engineering site, the C-terminal KKL motif, for its expression optimization in P. pastoris, as well as extended toolboxes of EPA/DHA enrichment and application scopes of lipase K80., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier B.V.)

Immune checkpoint inhibitors (ICIs) have revolutionized lung cancer treatment, yet resistance remains a challenge. Co-inhibition of PD-1/PD-L1 and TGF-β shows promise but faces limited efficacy and systemic toxicity. We developed gelatinase-responsive nanoparticles (GPNPs) delivering anti-PD-1 antibody (αPD-1) and TGF-β receptor I inhibitor galunisertib (Gal). GPNPs effectively inhibit tumor progression without observed side effects. Immune profiling by cytometry assay reveals robust recruitment of both activated and exhausted tumor-infiltrating lymphocytes (TILs) and macrophages. Transcriptomic analysis indicates extracellular matrix modulation, supported by reduced collagen deposition and αSMA expression. Fate mapping demonstrates attenuation of Pdgfrα + fibroblast transition to αSMA myofibroblasts, potentially reversing "immune-exclusive" status. This study validates GPNPs as a promising lung cancer immunotherapy platform, offering mechanistic insights for clinical translation and therapeutic enhancement., Competing Interests: Declarations. Ethics approval and consent to participate: All experimental procedures have been approved by the Medical Ethics Committee of the Affiliated Drum Tower Hospital of Nanjing University Medicine School (2021-027-02). All animal experiments were performed in accordance with guidelines set by the Animal Care Committee at Drum Tower Hospital (Nanjing, China). Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

The extensive use of tetracyclines in livestock poses health risks due to their residues in animal-derived food; therefore, developing simple detection methods to replace complex traditional approaches is of paramount importance. Here, we developed a dual-ligand zinc-based metal-organic framework material, Zn-BTC-BDC-NH 2 (denoted as ZTD), for the detection of tetracyclines. The intrinsic blue fluorescence of ZTD was quenched upon the introduction of tetracyclines due to electron transfer from -NH 2 of ZTD to -CO- and -OH groups of tetracycline molecules; meanwhile, the new green fluorescence emission was generated through π-π stacking between aromatic rings and the formation of complexes between Zn 2+ and C-O/C═O groups. In real food samples, ZTD exhibited recovery rates ranging from 93.62 to 110.66%, with detection limits as low as 0.011 μmol·L -1 . Additionally, a ZTD fluorescence test paper was developed for portable detection. This study presents a novel tetracycline detection method, offering insights into multiligand metal-organic framework preparation and future sensing method design.

The levels of 37 pesticides in dandelion were analyzed using gas chromatography-tandem mass spectrometry (GC-MS/MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The dandelion samples were treated with different irradiation doses, pH levels, moisture contents, and initial concentrations. Additionally, the respective contents of chicoric, chlorogenic, and caffeic acids in the dandelion samples were determined using high-performance liquid chromatography (HPLC) with DAD detector. The results showed that the pesticide degradation rate was positively correlated with the irradiation dose and negatively correlated with pesticide concentration. The degradation of most pesticides followed first-order kinetics. The pesticide degradation rate initially decreased and subsequently increased with an increase in the pH. Irradiation below 8 kGy had an insignificant effect on the three active ingredients of dandelion. The chicoric acid content decreased with an increase in water content and pH, whereas the caffeic acid content increased., Competing Interests: Declaration of competing interest The authors declare that they have no competing financial interests or personal relationships that may have influenced the work reported in this study., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The present study aim to investigate the effects of three drying processes on the flavor-related compounds and sensory quality of summer black tea. A total of 234 flavonoids and 1200 volatile compounds were identified in tea samples by using UPLC-MS/MS and HS-SPME-GC-MS, respectively. It was found that the combining hot-air and roasting drying process increased the level of epigallocatechin, epicatechin, gallic acid, theaflavins, and umami and sweet amino acids in tea samples. Conversely, the contents of epigallocatechin gallate, caffeine, kaempferol and acylated kaempferol glycosides, and quercetin and acylated quercetin glycosides were found to decrease. Analysis of the volatile compounds revealed that combined drying process enhanced the contents of volatile substances with sweet, nutty, and floral properties while reducing those with green attributes. Sensory evaluation results showed that the combined drying process improved the mellow taste and pure aroma, decreased the bitterness and astringency, and weakened the unpleasant flavor of summer black tea. Overall result indicated that the combined drying process could improve the flavor quality of summer black tea. This study may provide data support and feasible strategies for improving summer congou black tea quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

As China's aging population deepens and its pace accelerates, it is particularly crucial to rely on technological innovation to drive industrial differentiation. Is there a connection between population aging, technological innovation, and industrial differentiation? Does technological innovation have a moderating effect? Based on the panel data of 31 provinces in China from 2006 to 2022, this paper constructs the entropy index to measure the overall industrial differentiation and tertiary industrial differentiation in China, and subsequently investigates the relationship among the three using the two-way fixed effect model. The results indicate that population aging has a significant positive impact on the overall industrial differentiation in China, with a regression coefficient of 1.1025. Technological innovation plays a positive moderating role, with an interaction coefficient of 0.3489. The effects of population aging on the differentiation of the three industries differ: the regression coefficient for the primary industry is -0.6437, which is significantly negative; for the secondary industry, the regression coefficient is 0.9252, which is statistically insignificant; and for the tertiary industry, the regression coefficient is 0.1539, which is significantly positive. The government should encourage enterprises to invest in technology research and development through tax cuts and subsidies, and enterprises should absorb high-quality talents, carry out intelligent transformation of traditional industries of enterprises, and improve their competitiveness., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Li, Chen, Wu, Gao and Zou.)

Background: It has been reported the therapeutic effects of mesenchymal stem cells (MSCs) on hearing loss. This study explored the therapeutic effects of growth differentiation factor 6 (GDF6) overexpression-induced MSCs (MSCs-GDF6) on age-related hearing loss (ARHL) and its underlying mechanisms., Methods: Reverse transcription-quantitative PCR and western blotting were used to evaluate gene expression. Flow cytometry and immunofluorescence assays were performed for the detection of apoptosis and autophagy, respectively. Hearing function and loss of outer hair cells (HCs) in ARHL rats were measured using the auditory brainstem response and cochlear silver nitrate staining, respectively. MSC proliferation was evaluated with the Cell Counting Kit-8 assay., Results: Growth differentiation factor 15 (GDF15) and sirtuin 1 (SIRT1) expression was significantly decreased in hydrogen peroxide (H 2 O 2 )-induced House Ear Institute-Organ of Corti 1 (HEI-OC1) cells and the cochlea of ARHL rats. Elevated apoptosis and blocked autophagic flux were uncovered in H 2 O 2 -induced HEI-OC1 cells and ARHL rats. GDF15 overexpression inhibited apoptosis and restored autophagic flux in vitro and in vivo . Meanwhile, GDF15 positively regulated SIRT1 protein expression. MSCs-GDF6 not only upregulated GDF15 and SIRT1 expression but also suppressed apoptosis and restored autophagic flux to reduce loss of HCs and hearing loss in ARHL rats., Conclusions: MSCs-GDF6 prevented loss of HCs to relieve ARHL by inhibiting apoptosis and restoring autophagic flux, likely in association with upregulation of the GDF15/SIRT1 axis., (© 2025 The Author(s). Published by IMR Press.)

Perillae Folium (PF), the leaf of Perilla frutescens (L.) Britt is extensively used as a culinary vegetable and medicinal herb in many countries. Purple PF (P. frutescens var. arguta) and green PF (P. frutescens var. frutescens) are two of the main varieties. In this study, UHPLC-Q-TOF/MS assisted with feature-based molecular networking (FBMN) was applied for chemical characterization. In total, 82 metabolites, mainly phenolic acid derivatives were identified from PF. With the help of FBMN, five organic acid glucosides together with three N-phenylpropenoyl-L-amino acids (NPAs) were identified in PF for the first time. Multivariate statistical methods were utilized for comprehensive comparison of purple and green PF profiles. 12 compounds with their relative contents varied significantly between purple and green PF were screened out. Overall, the present study offers valuable insights for chemical elucidation of PF which would be helpful for comprehensive utilization of PF resource., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Personalized tourism has recently become an increasingly popular mode of travel. Effective personalized route recommendations must consider numerous complex factors, including the vast historical trajectory of tourism, individual traveler preferences, and real-time environmental conditions. However, the large temporal and spatial spans of trajectory data pose significant challenges to achieving high relevance and accuracy in personalized route recommendation systems. This study addresses these challenges by proposing a personalized tourism route recommendation model, the Temporal Multilayer Sequential Neural Network (TMS-Net). The fixed-length trajectory segmentation method designed in TMS-Net can adaptively adjust the segmentation length of tourist trajectories, effectively addressing the issue of large spatiotemporal spans by integrating tourist behavior characteristics and route complexity. The self-attention mechanism incorporating relative positional information enhances the model's ability to capture the relationships between different paths within a tourism route by merging position encoding and distance information. Additionally, the multilayer Long Short-Term Memory neural network module, built through hierarchical time series modeling, deeply captures the complex temporal dependencies in travel routes, improving the relevance of the recommendation results and the ability to recognize long-duration travel behaviors. The TMS-Net model was trained on over six million trajectory data points from Chengdu City, Sichuan Province, spanning January 2016 to December 2022. The experimental results indicated that the optimal trajectory segmentation interval ranged from 0.8 to 1.2 h. The model achieved a recommendation accuracy of 88.6% and a Haversine distance error of 1.23, demonstrating its ability to accurately identify tourist points of interest and provide highly relevant recommendations. This study demonstrates the potential of TMS-Net to improve personalized tourism experiences significantly and offers new methodological insights for personalized travel recommendations., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Text embedding plays a crucial role in natural language processing (NLP). Among various approaches, nonnegative matrix factorization (NMF) is an effective method for this purpose. However, the standard NMF approach, fundamentally based on the bag-of-words model, fails to utilize the contextual information of documents and may result in a significant loss of semantics. To address this issue, we propose a new NMF scheme incorporating a regularization term based on the Wasserstein metric, which quantifies an approximation of a word-context matrix to leverage semantic information. Since the word-context matrix is typically symmetric and positive definite (SPD), the Wasserstein metric used in the regularization is related to a natural SPD manifold structure. We then build upon this manifold structure to integrate an explicit expression of the Wasserstein metric into the NMF framework. Additionally, we introduce modifications to the gradient computation to adapt three fundamental classes of numerical algorithms from ordinary NMF to tackle the Wasserstein-regularized NMF (NMF-WR) problem. To demonstrate the effectiveness of the NMF-WR model and the proposed algorithms, we conduct experiments on popular datasets, focusing on topic modeling and document clustering. The results indicate that the NMF-WR model exhibits superior performance compared to other conventional NMF models in processing text embeddings. These findings suggest that this novel NMF-WR framework not only enhances semantic representation but also underscores a commitment to the model's reliability and interpretability., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Worldwide, tea is a popular beverage; within the realm of Chinese tea, Sichuan tea holds particular significance for its role in the origin and composition of Chinese tea cultivars. Sichuan tea is noted for its rich content of free amino acids (FAAs) and tea polyphenols (TPs), which has made it an important subject for studying genetic diversity and the genes regulating these compounds. In this study, 139 varieties of tea were collected from areas in Sichuan Province, China, with similar geographical and climatic conditions. The FAA content was approximately 3% and the TP content was approximately 17%. Using RAD sequencing, 5,656,224 variant loci were identified, primarily comprising SNPs (94.17%) and indels (5.83%). Evolutionary analysis revealed that genetic divergence was not closely linked to the collection location. Population structure analysis confirmed a division into two main populations having a similar composition to the phylogenetic clusters. Screening for FAA-related SNPs identified significant loci associated with 33 genes that potentially regulate FAA content. Similarly, TP-related analysis pinpointed 8 SNPs significantly linked to 20 candidate genes. Notably, genetic associations hinted at the genes involved in the stress response and the accumulation of phenolic compounds, enhancing the understanding of determinants of tea quality. This research underscores the potential for molecular breeding based on genetic insights, suggesting pathways to improve the FAA and TP contents in tea. These findings not only provide a solid foundation for exploring gene-chemical interactions but also offer practical strategies for improving the nutritional and sensory attributes of tea cultivars through informed breeding practices., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The misuse of tetracyclines in livestock production poses significant health risks. Thus, establishing convenient detection methods to replace complex laboratory tests for food safety is crucial. In this study, a heterostructure Zn-BTC/IRMOF-3 (denoted as ZBI) asynchronous response fluorescence sensor was developed for the qualitative and quantitative detection of tetracyclines in foods. The ZBI solution exhibited blue fluorescence under UV excitation; upon the introduction of tetracyclines, ZBI selectively recognized the tetracycline molecules through electron transfer, π-π stacking, and chelation, resulting in blue fluorescence quenching and green fluorescence enhancement. The ZBI sensor for tetracycline detection achieved recovery rates ranging from 93.91 to 111.91% in food samples, with a detection limit of as low as 0.086 μmol/L. Lastly, a portable sensing device using support vector classifier was constructed for detecting tetracyclines in real-life scenarios. Our findings introduce a new approach for fabricating fluorescence sensors and offer a novel method for detecting tetracyclines., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Protein-protein/peptide interactions play crucial roles in various biological processes. Exploring their interactions attracts wide attention. However, accurately predicting their binding sites remains a challenging task. Here, we develop an effective model GraphPBSP based on Graph Attention Network with Convolutional Neural Network and Multilayer Perceptron for protein-protein/peptide binding site prediction, which utilizes various feature types derived from protein sequence and structure including interface residue pairwise propensity developed by us and sequence embeddings obtained from a new pre-trained model ProstT5, alongside physicochemical properties and structural features. To our best knowledge, ProstT5 sequence embeddings and residue pairwise propensity are first introduced for protein-protein/peptide binding site prediction. Additionally, we propose a spatial neighbor-based feature statistic method for effectively considering key spatially neighboring information that significantly improves the model's prediction ability. For model training, a multi-scale objective function is constructed, which enhances the learning capability across samples of the same or different classes. On multiple protein-protein/peptide binding site test sets, GraphPBSP outperforms the currently available state-of-the-art methods with an excellent performance. Additionally, its performances on protein-DNA/RNA binding site test sets also demonstrate its good generalization ability. In conclusion, GraphPBSP is a promising method, which can offer valuable information for protein engineering and drug design., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Chunhua Li reports financial support was provided by National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Acupuncture has been demonstrated to be a safe and effective treatment for insomnia in patients without cancer. A lack of evidence, however, supports its application in the treatment of cancer-related insomnia (CRI)., Objective: To conduct a systematic review and meta-analysis to assess the efficacy as well as safety of acupuncture for alleviating insomnia in patients with cancer., Methods: A systematic search was conducted using four electronic databases (PubMed, EMBASE, Scopus and the Cochrane Library) to select publications published in peer-reviewed journals written in English. The OR was calculated, along with their 95% CIs. We assessed heterogeneity using Cochrane Q, I 2 statistics and the appropriate p value. The analysis used RevMan V.5.3., Findings: The present meta-analysis comprised 561 individuals from 10 randomised controlled trials (RCTs) across age cohorts. Acupuncture intervention improves Pittsburgh Sleep Quality Index (PSQI) scores and CRI more than control, with a pooled OR of 1.66 (95% CI 1.12 to 2.46), OR of 5.90 (95% CI 2.64 to 13.23) for electroacupuncture, OR of 2.30 (95% CI 1.48 to 3.58) for auricular-acupuncture and 2.72. Acupuncture improved the Insomnia Severity Index (ISI) and CRI more than control approaches, with ORs of 1.31 (95% CI 0.69 to 2.48), 5.29 (95% CI 2.18 to 12.84), 3.17 (95% CI 1.35 to 7.44) and 1.64 (95% CI 1.00 to 2.68)., Conclusion: The change in PSQI and ISI scores showed that acupuncture moderately improved insomnia in patients with cancer. Acupuncture is safe and effective, enabling subsequent clinical treatments., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Due to the growing focus on daily hygiene practices, sodium dodecyl sulfate (SDS), a widely used surfactant, is increasingly found in domestic sewage and rainfall runoff. Upon entering the lake-terrestrial ecotone, SDS affects the composition, abundance, and functional capacity of soil bacterial communities due to its bacteriostatic properties. To investigate the effects of long-term discharge of sewage containing low concentrations of SDS on microorganisms in the lake-terrestrial ecotone, alterations in bacterial community structure, functional genes, and biomass were examined using a simulated continuous pollutant input. The results indicated the following: (1) The degradation rate of sodium dodecyl sulfate (SDS) by soil microorganisms in the lake-terrestrial ecotone under long-term and low concentrations of SDS stress ranged from 11 to 16 mg/kg·d. (2) The effects of low concentrations and long-term SDS stress on bacterial community structure and gene function in the lake-terrestrial ecotone differed significantly from those of short-term pollution. The damage to microbial-promoted material cycling in the lake-terrestrial ecotone was more severe; however, the proliferation of pathogenic bacteria remained continuously suppressed. (3) Soil bacteria in the lake-terrestrial ecotone responded to the stress of long-term and low concentrations of SDS primarily by enhancing chemotaxis and tolerance.

Objective: Iatrogenic skin injury is a common neonatal skin problem that can have a severe impact on the health and life of newborns. The purpose of this study was to explore the factors influencing iatrogenic skin injury in neonates, identify and correct nursing behaviors that may lead to skin damage, thereby reduce the occurrence of skin damage and protect the health of newborns., Methods: The clinical data of 87 neonates with iatrogenic skin injury admitted to the Department of Neonatology of Shangrao People's Hospital, China, between January and June 2022, were retrospectively collected as a research group. The causes of iatrogenic skin injury were statistically analyzed. 50 neonates without iatrogenic skin injury in the same department during the same period were selected as the control group. The general data of the two groups were contracted, and the independent risk factors affecting iatrogenic skin injury in neonates were explored using multivariate Logistic regression. The corresponding nursing strategies were analyzed., Result: (1) Among the 87 neonates with iatrogenic skin injury, the causes included adhesive dressing stripping (41.38%, 36/87), skin scratch during blue light phototherapy (25.29%, 22/87), diaper dermatitis (20.69%, 18/87), and skin pressure redness related to ventilator and continuous positive airway pressure (CPAP) (12.64%, 11/87). (2) The gestational age, birth weight, length of stay, use of noninvasive mechanical ventilation, orotracheal intubation, gastric tube, PICC catheterization, and skin allergy history of the two groups had statistically significant differences (P < .05). (3) The results of multivariate Logistic regression analysis indicated that the length of stay (OR=2.994, 95% CI=1.341~6.686), orotracheal intubation use (OR=0.015, 95% CI=0.004~0.060), and gastric tube use (OR=17.132, 95% CI=5.231~56.108) were independent risk factors of iatrogenic skin injury in neonates (P < .05)., Conclusion: Length of stay, orotracheal intubation use, and gastric tube use are independent risk factors for iatrogenic skin injury in neonates. Hospital stays and unnecessary use of orotracheal intubation and gastric tube should be reduced in future clinical management. Attention should be paid to strengthening skin observation and care, keeping skin dry and clean, and preventing iatrogenic skin injury.

A lytic Proteus mirabilis phage, PmP19, was isolated from sewage on a farm. PmP19 has an icosahedral head (60 ± 3 nm in diameter) and a short tail (15 ± 2 nm long). Its genome, a linear, double-stranded DNA molecule 44,305 bp in length with an average GC content of 51.93%, has 52 putative open reading frames (ORFs). BLASTn comparisons and phylogenetic analysis revealed a close relationship between Pmp19 and Klebsiella phage vB&#95;KpnP&#95;ZK1. Bioinformatic analysis revealed that PmP19 belongs to the phage subfamily Molineuxvirinae., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

The dynamics of RNAs are related intimately to their functions. Molecular flexibility, as a starting point for understanding their dynamics, has been utilized to predict many characteristics associated with their functions. Since the experimental measurement methods are time-consuming and labor-intensive, it is urgently needed to develop reliable theoretical methods to predict RNA flexibility. In this work, we develop an effective machine learning method, RNAfcg, to predict RNA flexibility, where the Random Forest (RF) is trained by features including the topological centralities, flexibility-rigidity index, and global characteristics first introduced by us, as well as some traditional sequence and structural features. The analyses show that the three types of features introduced first have significant contributions to RNA flexibility prediction, among which the topological type contributes the most, which indicates the importance of structural topology in determining RNA flexibility. The performance comparison indicates that RNAfcg outperforms the state-of-the-art machine learning methods and the commonly used Gaussian Network Model (GNM) models, achieving a much higher Pearson correlation coefficient (PCC) of 0.6619 on the test data set. This work is helpful for understanding RNA dynamics and can be used to predict RNA function information. The source code is available at https://github.com/ChunhuaLab/RNAfcg/.

Graded activation contributes to the precise regulation of GPCR activity, presenting new opportunities for drug design. In this work, a total of 10 μs enhanced-sampling simulations are performed to provide molecular insights into the binding dynamics differences of the neurotensin receptor 1 (NTSR1) to the full agonist SRI-9829, partial agonist RTI-3a and inverse agonist SR48692. The possible graded activation mechanism of NTSR1 is revealed by an integrated analysis utilizing the reweighted potential of mean force (PMF), deep learning (DL) and transfer entropy (TE). Specifically, the orthosteric pocket is observed to undergo expansion and contraction, with the G-protein-binding site experiencing interconversions among the inactive, intermediate and active-like states. Detailed structural comparisons capture subtle conformational differences arising from ligand binding in allosteric signaling, which can well explain the graded activation. Critical microswitches that contribute to graded activation are efficiently identified with the DL model. TE calculations enable the visualization of allosteric communication networks within the receptor, elucidating the driver-responder relationships associated with signal transduction. Fortunately, the dissociation of the full agonist from the orthosteric pocket is observed. The current findings systematically reveal the mechanism of NTSR1 graded activation, and also provide implications for structure-based drug design., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Chunhua Li reports financial support was provided by the National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Ginsenoside Rh2 (G-Rh2) is a vital bioactive compound in Traditional Chinese Medicine, celebrated for its strong pharmacological properties, particularly its potent antitumor effects. However, its poor water solubility and limited bioavailability have necessitated the development of a novel drug delivery method. In this study, we utilized an indocyanine green carboxylic acid-hydroxypropyl cellulose-abietic acid-bovine serum albumin hydrogel (ICG-HPC-AA/BSA hydrogel) as a tumor in situ vaccine to enhance the permeability, retention, and tumor-targeted therapeutic efficacy of G-Rh2. We examined the therapeutic impact of a G-Rh2-loaded hydrogel combined with systemic PD-1 antibody treatment in murine models of H22 liver cancer and CT26 colon cancer. Additionally, we explored the immune microenvironment of the tumors influenced by this in situ vaccination strategy., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Introduction: Psychologists are particularly interested in how people operate in stressful settings. The sporting arena is a "natural laboratory" for studying how people behave and perform in high-pressure situations. This study explores the gender differences in archers' ability to cope with adversity, highlighting the significant cold-hand effect observed in both male and female archers, with notable differences in the last arrow performance under pressure., Methods: Our method is a Poisson general linear model -based test for the cold hand that examines how the performance of the last arrow per set depends on the performance of the previous two shots. We also interact the player's gender with performance on the previous two arrows and game status to test for gender differences in response to past performance and intermediate game status., Results: The Poisson regression analysis reveals that male and female archers' performance dropped significantly after experiencing two consecutive missing bullseyes, which means a cold-hand effect exists. However, although there was no significant difference in the performance of male and female archers on the third arrow, female archers have significantly lower last arrow per set scores than male archers after near poor performance or being in a situation where losing can only be avoided by winning the current set., Discussion: This finding suggests that female archers are more vulnerable to the potentially negative effects of adversity caused by trailing or recent failures than their male counterparts. We attempt to explain the reasons behind the results above from both psychological and physiological perspectives., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li and Zhao.)

Peptides are pivotal in numerous biological activities by engaging in up to 40 % of protein-protein interactions in many cellular processes. Due to their exceptional specificity and effectiveness, peptides have emerged as promising candidates for drug design. However, accurately predicting protein-peptide binding affinity remains a challenging. Aiming at the problem, we develop a prediction model PepPAP based on convolutional neural network and multi-head attention, which relies solely on sequence features. These features include physicochemical properties, intrinsic disorder, sequence encoding, and especially interface propensity which is extracted from 16,689 non-redundant protein-peptide complexes. Notably, the adopted regression stratification cross-validation scheme proposed in our previous work is beneficial to improve the prediction for the cases with extreme binding affinity values. On three benchmark test datasets: T100, a series of peptides targeting to PDZ domain and CXCR4, PepPAP shows excellent performance, outperforming the existing methods and demonstrating its good generalization ability. Furthermore, PepPAP has good results in binary interaction prediction, and the analysis of the feature space distribution visualization highlights PepPAP's effectiveness. To the best of our knowledge, PepPAP is the first sequence-based deep attention model for wide-genome protein-peptide binding affinity prediction, and holds the potential to offer valuable insights for the peptide-based drug design., Competing Interests: Declaration of competing interest The authors have declared that no competing interests exist., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Allostery is one of the most direct and efficient ways to regulate protein functions. The diverse allosteric sites make it possible to design allosteric modulators of differential selectivity and improved safety compared with those of orthosteric drugs targeting conserved orthosteric sites. Here, we develop an ensemble machine learning method AllosES to predict protein allosteric sites in which the new and effective features are utilized, including the entropy transfer-based dynamic property, secondary structure features, and our previously proposed spatial neighbor-based evolutionary information besides the traditional physicochemical properties. To overcome the class imbalance problem, the multiple grouping strategy is proposed, which is applied to feature selection and model construction. The ensemble model is constructed where multiple submodels are trained on multiple training subsets, respectively, and their results are then integrated to be the final output. AllosES achieves a prediction performance of 0.556 MCC on the independent test set D24, and additionally, AllosES can rank the real allosteric sites in the top three for 83.3/89.3% of allosteric proteins from the test set D24/D28, outperforming the state-of-the-art peer methods. The comprehensive results demonstrate that AllosES is a promising method for protein allosteric site prediction. The source code is available at https://github.com/ChunhuaLab/AllosES.

Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

Nucleotide-binding and oligomerization structural domain (NOD)-like receptors (NLRs) play an important role in innate immunity as cytoplasmic pattern recognition receptors (PRRs). Over the past decade, considerable progress has been made in understanding the mechanisms by which NLR family members regulate immune system function, particularly the formation of inflammasome and downstream inflammatory signals. However, recent studies have shown that some members of the NLRs, including Nlrp12, NLRX1, and NLRC3, are important in the negative regulation of inflammatory signaling and are involved in the development of various diseases, including inflammatory diseases and cancer. Based on this, in this review, we first summarize the interactions between canonical and non-canonical nuclear factor-κB (NF-κB) signaling pathways that are mainly involved in NLRs, then highlight the mechanisms by which the above NLRs negatively regulate inflammatory signaling responses as well as their roles in tumor progression, and finally summarize the synthetic and natural derivatives with therapeutic effects on these NLRs, which are considered as potential therapeutic agents for overcoming inflammatory diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Spider mite infestation has a severe impact on tea growth and quality. In this study, we conducted a deep exploration of the functions and regulations of the CsPIP5K gene family using chromosomal localization and collinearity analysis. Additionally, we carefully examined the cis elements within these genes. To fully understand the metabolic response of CsPIP5K under spider mite infection, we integrated previously published metabolomic and transcriptomic data. Our analysis revealed that multiple CsPIP5K genes are associated with phospholipid metabolism, with CsPIP5K06 showing the strongest correlation. Therefore, we employed qPCR and subcellular localization techniques to determine the expression pattern of this gene and its functional location within the cell. Overall, this study not only comprehensively elucidated the characteristics, structure, and evolution of the CsPIP5K gene family but also identified several candidate CsPIP5K genes related to phospholipid biosynthesis and associated with spider mites based on previously published data. This research makes a significant contribution to enhancing the resistance of tea to spider mite and maintaining optimal tea quality.

Excess use of tetracyclines poses significant health risks arising from animal-derived foods, meaning simple and sensitive methods to detect tetracyclines would be beneficial given current laboratory methods are complex and expensive. Herein, we describe an asynchronous response fluorescence sensor constructed based on Zn-based metal-organic framework and Ru(bpy) 3 2+ (denoted as Ru@Zn-BTEC) for the qualitative and quantitative detection of tetracyclines in foods. Under excitation at 365 nm, the sensor emitted red fluorescence at 609 nm. When tetracyclines were present, these molecules aggregated in the Ru@Zn-BTEC framework, causing green fluorescence emission at 528 nm. The developed sensing system accurately distinguished the different categories of tetracyclines with a classifier accuracy of 94 %. The Ru@Zn-BTEC sensor demonstrated a detection limit of 0.012 μM and satisfactory recovery (87.81 %-113.84 %) for tetracyclines in food samples. This work provides a pathway for constructing asynchronous response fluorescence sensors for food analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Effectively tackling extreme climate change requires sound knowledge about carbon emissions and their driving forces. Currently, agricultural carbon emission assessment often deals with its inventory, efficiency, determinants, and response independently, which will leave out the complex interactions among its various components, thus there is a lack of comprehensive, scalable, comparable explanations for agricultural carbon emissions. Herein, we introduce an integrated agricultural carbon emission assessment framework (IEDR): Inventory (I) × Efficiency (E) × Determinants (D) × Response (R), which was then applied to an illustration for the county-level agricultural carbon emissions in Hunan Province, China. Results show that: (1) Agricultural carbon emission inventory (ACEI) increased from 20.06 × 10 6 tC in 2006 to 21.99 × 10 6 tC in 2014 and decreased to 19.07 × 10 6 tC by 2020, depicting a fluctuating trend. Meanwhile, there was remarkable spatial heterogeneity, with higher ACEI in the North and South than in the East and West. (2) Agricultural carbon emission efficiency (ACEE) increased from 0.8520 in 2006 to 0.8992 in 2020, depicting a growing trend driven by technological progress. Spatially distributed in contrast to ACEI, regions with higher ACEE were located in the eastern and western areas. (3) ACEI was negatively correlated with ACEE (-0.657), indicating that increasing ACEE is a key strategy for reducing emissions. (4) The natural environment, rural development level, and policy support had critical impacts on ACEE and ACEI. In particular, the cultivated area and rural water affairs development were significant influences on ACEE and ACEI. Given the externalities of carbon emissions and its important public goods characteristics of the atmosphere, local carbon issues are also global concerns. Therefore, the case study of the IEDR model not only validates this theoretical paradigm and realizes regional responsibility for global carbon reduction but also supports and expands the theoretical and empirical corpus in the field of agricultural carbon emissions and efficiency, providing insights and references for other global regions facing similar challenges., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Globally, metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD), is one of the most common liver disorders and is strongly associated with copper deficiency. To explore the potential effects and mechanisms of Lactiplantibacillus plantarum LPJZ-658, copper deficiency combined with a high-sugar diet-induced MASLD mouse model was utilized in this study. We fed 40-week-old (middle-aged) male C57BL/6 mice a copper-deficient and high-sugar diet for 16 weeks (CuDS), with supplementary LPJZ-658 for the last 6 weeks (CuDS + LPJZ-658). In this study, we measured body weight, liver weight, and serum biochemical markers. Lipid accumulation, histology, lipidomics, and sphingolipid metabolism-related enzyme expression were investigated to analyze liver function. Untargeted metabolomics was used to analyze the serum and the composition and abundance of intestinal flora. In addition, the correlation between differential liver lipid profiles, serum metabolites, and gut flora at the genus level was measured. The results show that LPJZ-658 significantly improves abnormal liver function and hepatic steatosis. The lipidomics analyses and metabolic pathway analysis identified sphingolipid, retinol, and glycerophospholipid metabolism as the most relevant metabolic pathways that characterized liver lipid dysregulation in the CuDS group. Consistently, RT-qPCR analyses revealed that the enzymes catalyzing sphingolipid metabolism that were significantly upregulated in the CuDS group were downregulated by the LPJZ-658 treatment. In addition, the serum metabolomics results indicated that the linoleic acid, taurine and hypotaurine, and ascorbate and aldarate metabolism pathways were associated with CuDS-induced MASLD. Notably, we found that treatment with LPJZ-658 partially reversed the changes in the differential serum metabolites. Finally, LPJZ-658 effectively regulated intestinal flora abnormalities and was significantly correlated with differential hepatic lipid species and serum metabolites. In conclusion, we elucidated the function and potential mechanisms of LPJZ-658 in alleviating copper deficiency combined with sugar-induced middle-aged MASLD and hope this will provide possible treatment strategies for improving MASLD.

To analyze the metabolites (blood, urine and feces) in normal rats after intragastric administration of the decoction of Phellodendri Amurensis Cortex (PAC) and to map the metabolic profile of PAC in vivo of rat; meanwhile, to evaluate the anti-rheumatoid arthritis (RA) effect of PAC by blood metabolomics technique and to explore its mechanism. Performing on UPLC-Q-TOF-MS technology with a Waters ACQUITY UPLC BEH-C 18 column (100 mm × 2.1 mm, 1.7 μm), the mobile phase was acetonitrile-0.1% formic acid aqueous solution (gradient elution). Prior to and following the administration of the decoction of PAC, the samples of blood, urine, and fecal were collected from the rats, in the positive ion mode, pharmacogenic metabolites in each biological sample were identified according to the accurate mass, fragment ions, retention time, metabolic reaction type, comparison of reference substance and retrieval of Pub Med database; The adjuvant-type arthritis (AA) rat model was established, and blood metabonomics method was used to study the improvement effect of rheumatoid arthritis after drug intervention with PAC, and its mechanism was preliminarily explored through analysis of metabolic pathway. A total of 72 exogenous components were identified, including 17 prototype components and 55 metabolites; 14 biomarkers were screened by blood metabolomics techniques combined with multivariate statistical analysis, and PAC significantly improved symptoms of rheumatoid arthritis in rats, and the metabolic pathway analysis mainly involves 5 metabolic pathways. The components in the aqueous decoction of PAC mainly undergo phase I metabolic reactions in rats, such as oxidation, reduction, dehydrogenation, demethylation, and phase II metabolic reactions, such as acetylation, glucuronidation, methylation; PAC has anti-rheumatoid arthritis effects, and its mechanism of action may be related to biosynthesis of aminoacyl-tRNA, metabolism of phenylalanine, metabolism of tryptophan, degradation of valine, leucine and isoleucine and biosynthesis of pantothenic acid and coenzyme A, providing a scientific basis for the study of the pharmacodynamic substances and the action mechanism of PAC against RA., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interest or personal relationship that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Protein missense mutations and resulting protein stability changes are important causes for many human genetic diseases. However, the accurate prediction of stability changes due to mutations remains a challenging problem. To address this problem, we have developed an unbiased effective model: PMSPcnn that is based on a convolutional neural network. We have included an anti-symmetry property to build a balanced training dataset, which improves the prediction, in particular for stabilizing mutations. Persistent homology, which is an effective approach for characterizing protein structures, is used to obtain topological features. Additionally, a regression stratification cross-validation scheme has been proposed to improve the prediction for mutations with extreme ΔΔG. For three test datasets: S sym , p53, and myoglobin, PMSPcnn achieves a better performance than currently existing predictors. PMSPcnn also outperforms currently available methods for membrane proteins. Overall, PMSPcnn is a promising method for the prediction of protein stability changes caused by single point mutations., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Gambogic acid is a natural compound with anticancer properties and is effective for many tumors. But its low water solubility and dose-dependent side effects limit its clinical application. This study aims to develop a novel drug delivery system for intratumoral delivery of gambogic acid. In our experimental study, we propose a new method for encapsulating gambogic acid nanoparticles using a manganese composite hyaluronic acid hydrogel as a carrier, designed for targeted drug delivery to tumors. The hydrogel delivery system is synthesized through the coordination of hyaluronic acid-dopamine (HA-DOPA) and manganese ions. The incorporation of manganese ions serves three purposes:1.To form cross-linked hydrogels, thereby improving the mechanical properties of HA-DOPA.2.To monitor the retention of hydrogels in vivo in real-time using magnetic resonance imaging (MRI).3.To activate the body's immune response. The experimental results show that the designed hydrogel has good biosafety, in vivo sustained release effect and imaging tracking ability. In the mouse CT26 model, the hydrogel drug-loaded group can better inhibit tumor growth. Further immunological analysis shows that the drug-loaded hydrogel group can stimulate the body's immune response, thereby better achieving anti-tumor effects. These findings indicate the potential of the developed manganese composite hyaluronic acid hydrogel as an effective and safe platform for intratumoral drug delivery. The amalgamation of biocompatibility, controlled drug release, and imaging prowess positions this system as a promising candidate for tumor treatment., Competing Interests: Declaration of competing interest All authors disclosed no relevant relationships., (Copyright © 2024. Published by Elsevier B.V.)

Degradation of bond strength due to corrosion of steel strands is of great importance for serviceability of prestressed concrete structures. An analytical model is proposed to demonstrate the effect of corrosion of steel strand on reduction of bond strength. Corrosion expansion force generated by steel strand corrosion before and after corrosion cracking is firstly estimated. Then, the reduced gripping effect of the concrete, change of friction coefficient between the corroded strand and reduction force on the bearing face are considered in calculating the pre-rib extrusion force. Finally, the enhancement of bond strength due to transverse confinement of stirrups is considered and the ultimate bond strength of corroded steel strand is calculated. Comparison of results between the prediction and experimental result shows the proposed model can be used to reasonably evaluate the bond strength. The prediction result of the bond strength model is affected by the degree of strand corrosion, but almost not by the drawing method., (© 2024. The Author(s).)

Porcine epidemic diarrhea virus (PEDV) is the etiology of porcine epidemic diarrhea (PED), a highly contagious digestive disease in pigs and especially in neonatal piglets, in which a mortality rate of up to 100% will be induced. Immunizing pregnant sows remains the most promising and effective strategy for protecting their neonatal offspring from PEDV. Although half a century has passed since its first report in Europe and several prophylactic vaccines (inactivated or live attenuated) have been developed, PED still poses a significant economic concern to the swine industry worldwide. Hence, there is an urgent need for novel vaccines in clinical practice, especially live attenuated vaccines (LAVs) that can induce a strong protective lactogenic immune response in pregnant sows. Reverse genetic techniques provide a robust tool for virological research from the function of viral proteins to the generation of rationally designed vaccines. In this review, after systematically summarizing the research progress on virulence-related viral proteins, we reviewed reverse genetics techniques for PEDV and their application in the development of PED LAVs. Then, we probed into the potential methods for generating safe, effective, and genetically stable PED LAV candidates, aiming to provide new ideas for the rational design of PED LAVs.

Alzheimer's disease (AD), a primary cause of dementia, is rapidly emerging as one of the most financially taxing, lethal, and burdensome diseases of the 21st century. Increasing evidence suggests that microglia-mediated neuroinflammation plays a key role in both the initiation and progression of AD. Recently, emerging evidence has demonstrated mitochondrial dysfunction, particular in microglia where precedes neuroinflammation in AD. Multiple signaling pathways are implicated in this process and pharmaceutical interventions are potentially involved in AD treatment. In this review, advance over the last five years in the signaling pathways and pharmaceutical interventions are summarized and it is proposed that targeting the signaling pathways in microglia with mitochondrial dysfunction could represent a novel direction for AD treatment., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s). Published by IMR Press.)

Protein-DNA interactions are pivotal to various cellular processes. Precise identification of the hotspot residues for protein-DNA interactions holds great significance for revealing the intricate mechanisms in protein-DNA recognition and for providing essential guidance for protein engineering. Aiming at protein-DNA interaction hotspots, this work introduces an effective prediction method, ESPDHot based on a stacked ensemble machine learning framework. Here, the interface residue whose mutation leads to a binding free energy change (ΔΔ G ) exceeding 2 kcal/mol is defined as a hotspot. To tackle the imbalanced data set issue, the adaptive synthetic sampling (ADASYN), an oversampling technique, is adopted to synthetically generate new minority samples, thereby rectifying data imbalance. As for molecular characteristics, besides traditional features, we introduce three new characteristic types including residue interface preference proposed by us, residue fluctuation dynamics characteristics, and coevolutionary features. Combining the Boruta method with our previously developed Random Grouping strategy, we obtained an optimal set of features. Finally, a stacking classifier is constructed to output prediction results, which integrates three classical predictors, Support Vector Machine (SVM), XGBoost, and Artificial Neural Network (ANN) as the first layer, and Logistic Regression (LR) algorithm as the second one. Notably, ESPDHot outperforms the current state-of-the-art predictors, achieving superior performance on the independent test data set, with F1, MCC, and AUC reaching 0.571, 0.516, and 0.870, respectively.

The gingiva is a key oral barrier that protects oral tissues from various stimuli. A loss of gingival tissue homeostasis causes periodontitis, one of the most prevalent inflammatory diseases in humans. The human gingiva exists as a complex cell network comprising specialized structures. To understand the tissue-specific pathophysiology of the gingiva, we applied a recently developed spatial enhanced resolution omics-sequencing (Stereo-seq) technique to obtain a spatial transcriptome (ST) atlas of the gingiva in healthy individuals and periodontitis patients. By utilizing Stereo-seq, we identified the major cell types present in the gingiva, which included epithelial cells, fibroblasts, endothelial cells, and immune cells, as well as subgroups of epithelial cells and immune cells. We further observed that inflammation-related signalling pathways, such as the JAK-STAT and NF-κB signalling pathways, were significantly upregulated in the endothelial cells of the gingiva of periodontitis patients compared with those of healthy individuals. Additionally, we characterized the spatial distribution of periodontitis risk genes in the gingiva and found that the expression of IFI16 was significantly increased in endothelial cells of inflamed gingiva. In conclusion, our Stereo-seq findings may facilitate the development of innovative therapeutic strategies for periodontitis by mapping periodontitis-relevant genes and pathways and effector cells., (© 2023. Science China Press.)

Coronaviruses (CoVs) are a large class of positively stranded RNA viruses that pose a significant threat to public health, livestock farming, and wild animals. These viruses have the ability to cross species barriers and cause devastating epidemics. Animals are considered to be intermediate hosts for many coronaviruses, and many animal coronaviruses also have the potential for cross-species transmission to humans. Therefore, controlling the epidemic transmission of animal coronaviruses is of great importance to human health. Vaccination programs have proven to be effective in controlling coronaviruses infections, offering a cost-effective approach to reducing morbidity and mortality, so the re-emergence of lethal coronaviruses emphasizes the urgent need for the development of effective vaccines. In this regard, we explore the progress in animal coronavirus vaccine development, covering the latest taxonomy of the main animal coronaviruses, spillover events, diverse vaccine development platforms, potential main targets for animal coronavirus vaccine development, and primary challenges facing animal coronavirus vaccines. We emphasize the urgent need to create a "dual-effect" vaccine capable of eliciting both cellular and humoral immune responses. The goal is to highlight the contributions of veterinary scientists in this field and emphasize the importance of interdisciplinary collaboration between the veterinary and medical communities. By promoting communication and cooperation, we can enhance the development of novel and super vaccines to combat human and animal coronavirus infections in the future.

The inwardly rectifying potassium channel Kir3.2, a member of the inward rectifier potassium (Kir) channel family, exerts important biological functions through transporting potassium ions outside of the cell, during which a large-scale synergistic movement occurs among its different domains. Currently, it is not fully understood how the binding of the ligand to the Kir3.2 channel leads to the structural changes and which key residues are responsible for the channel gating and allosteric dynamics. Here, we construct the Gaussian network model (GNM) of the Kir3.2 channel with the secondary structure and covalent interaction information considered (sscGNM), which shows a better performance in reproducing the channel's flexibility compared with the traditional GNM. In addition, the sscANM-based perturbation method is used to simulate the channel's conformational transition caused by the activator PIP2's binding. By applying certain forces to the PIP2 binding pocket, the coarse-grained calculations generate the similar conformational changes to the experimental observation, suggesting that the topology structure as well as PIP2 binding are crucial to the allosteric activation of the Kir3.2 channel. We also utilize the sscGNM-based thermodynamic cycle method developed by us to identify the key residues whose mutations significantly alter the channel's binding free energy with PIP2. We identify not only the residues important for the specific binding but also the ones critical for the allosteric transition coupled with PIP2 binding. This study is helpful for understanding the working mechanism of Kir3.2 channels and can provide important information for related drug design.

Prevention of Clostridium difficile infection is challenging worldwide owing to its high morbidity and mortality rates. C. difficile is currently being classified as an urgent threat by the CDC. Devising a new therapeutic strategy become indispensable against C. difficile infection due to its high rates of reinfection and increasing antimicrobial resistance. The current study is based on core proteome data of C. difficile to identify promising vaccine and drug candidates. Immunoinformatics and vaccinomics approaches were employed to construct multi-epitope-based chimeric vaccine constructs from top-ranked T- and B-cell epitopes. The efficacy of the designed vaccine was assessed by immunological analysis, immune receptor binding potential and immune simulation analyses. Additionally, subtractive proteomics and druggability analyses prioritized several promising and alternative drug targets against C. difficile. These include FMN-dependent nitroreductase which was prioritized for pharmacophore-based virtual screening of druggable molecule databases to predict potent inhibitors. A MolPort-001-785-965 druggable molecule was found to exhibit significant binding affinity with the conserved residues of FMN-dependent nitroreductase. The experimental validation of the therapeutic targets prioritized in the current study may worthy to identify new strategies to combat the drug-resistant C. difficile infection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Aiman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Six-spotted spider mite (Eotetranychus sexmaculatus) is one of the most damaging pests of tea (Camellia sinensis). E. sexmaculatus causes great economic loss and affects tea quality adversely. In response to pests, such as spider mites, tea plants have evolved resistance mechanisms, such as expression of defense-related genes and defense-related metabolites., Results: To evaluate the biochemical and molecular mechanisms of resistance in C. sinensis against spider mites, "Tianfu-5" (resistant to E. sexmaculatus) and "Fuding Dabai" (susceptible to E. sexmaculatus) were inoculated with spider mites. Transcriptomics and metabolomics based on RNA-Seq and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) technology were used to analyze changes in gene expression and metabolite content, respectively. RNA-Seq data analysis revealed that 246 to 3,986 differentially expressed genes (DEGs) were identified in multiple compared groups, and these DEGs were significantly enriched in various pathways, such as phenylpropanoid and flavonoid biosynthesis, plant-pathogen interactions, MAPK signaling, and plant hormone signaling. Additionally, the metabolome data detected 2,220 metabolites, with 194 to 260 differentially abundant metabolites (DAMs) identified in multiple compared groups, including phenylalanine, lignin, salicylic acid, and jasmonic acid. The combined analysis of RNA-Seq and metabolomic data indicated that phenylpropanoid and flavonoid biosynthesis, MAPK signaling, and Ca2+-mediated PR-1 signaling pathways may contribute to spider mite resistance., Conclusions: Our findings provide insights for identifying insect-induced genes and metabolites and form a basis for studies on mechanisms of host defense against spider mites in C. sinensis. The candidate genes and metabolites identified will be a valuable resource for tea breeding in response to biotic stress., (© 2023. The Author(s).)

Shigella sonnei is a gram-negative bacterium and is the primary cause of shigellosis in advanced countries. An exceptional rise in the prevalence of the disease has been reported in Asia, the Middle East, and Latin America. To date, no preventive vaccine is available against S. sonnei infections. This pathogen has shown resistances towards both first- and second-line antibiotics. Therefore, an effective broad spectrum vaccine development against shigellosis is indispensable. In the present study, vaccinomics-aided immunoinformatics strategies were pursued to identify potential vaccine candidates from the S. sonnei whole proteome data. Pathogen essential proteins that are non-homologous to human and human gut microbiome proteome set, are feasible candidates for this purpose. Three antigenic outer membrane proteins were prioritized to predict lead epitopes based on reverse vaccinology approach. Multi-epitope-based chimeric vaccines was designed using lead B- and T-cell epitopes combined with suitable linker and adjuvant peptide sequences to enhance immune responses against the designed vaccine. The SS-MEVC construct was prioritized based on multiple physicochemical, immunological properties, and immune-receptors docking scores. Immune simulation analysis predicted strong immunogenic response capability of the designed vaccine construct. The Molecular dynamic simulations analysis ensured stable molecular interactions of lead vaccine construct with the host receptors. In silico restriction and cloning analysis predicted feasible cloning capability of the SS-MEVC construct within the E. coli expression system. The proposed vaccine construct is predicted to be more safe, effective and capable of inducing robust immune responses against S. sonnei infections and may be worthy of examination via in vitro/in vivo assays., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Aiman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

We aim to study the inhibitory effect of alkaline serine protease (ASPNJ) on lymphocytic leukemia Jurkat cells and its related mechanism through examining the expression of membrane proteins or membrane-associated proteins. MTT assay and trypan blue staining were used to detect the inhibitory effect of ASPNJ on the proliferation and growth of Jurkat cells. Wright-Giemsa staining was used to observe the effect of ASPNJ on the morphology of Jurkat cells. The effect of ASPNJ on Jurkat cell apoptosis was detected by flow cytometry. Two-dimensional electrophoresis-mass spectrometry (2-DE-MS) was used to detect and identify the differentially expressed proteins of Jurkat cells treated with ASPNJ (4 μg/mL, 3 h), of which three were selected and verified by Western blot. ASPNJ significantly inhibited the proliferation of leukemia cells (Raji, U937, and Jurkat), caused obvious morphological changes, and induced apoptosis of Jurkat cells. ASPNJ also increased the sensitivity of Jurkat cells to vincristine (VCR). Seven differentially expressed proteins were obtained through 2DE-MS, of which Peroxiredoxin-6 (PRDX6), Calcium-binding protein (CHP1), and 40S ribosomal protein SA (RPSA) were validated. ASPNJ can cause significant toxic effects on Jurkat cells and enhance the effects of VCR. The mechanism of action of ASPNJ on Jurkat cells may be related to differentially expressed proteins such as PRDX6. This study provides a new experimental basis and direction for antileukemia research., (© 2023 Wiley Periodicals LLC.)

Tetracycline residues in animal-derived food pose serious harm to human health, making it demanded to develop simple and sensitive method for detecting tetracycline. Herein, a dual-emission synchronous response fluorescence probe is reported based on amino-functionalized Al-MOF modulated TpTt-COF (donate as NMT). NMT exhibits excellent dual-emission at 455 and 575 nm under single excitation. Tetracycline is sensitively detected through quenching the dual-emission of NMT. NMT specifically recognizes tetracycline through intermolecular hydrogen bonding between -OH/-NH 2 of tetracycline and deprotonated O - /-NH-/CN of NMT. A calibration curve is built between the fluorescence ratio and the tetracycline concentration with a detection limit of 0.014 μmol/L. NMT is employed to detect tetracycline in milk, pork and chicken, and displays satisfactory recoveries of 94.39-105.67%, respectively. The optosmart sensor based on NMT and smartphone has been constructed for visually detecting tetracycline. This method provides routes to construct MOF-COF fluorescence probes and has good prospects in food analysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The objective of this investigation was to understand the epidemiology of fascioliasis in yaks in the alpine pastoral areas of the Qinghai-Tibet Plateau, China. The prevalence of Fasciola hepatica infection was estimated by examining eggs in the feces of yaks and by autopsy after the slaughter. Yaks were sampled from a total of 16 representative counties in Qinghai province, and risk factors were assessed based on regional and age characteristics. Fecal samples were obtained from 1542 yaks aged 0-1 (<1 year old), 1-2 (≥1 year old and <3 years old), and over 3 years (≥3 years old). In addition, 242 yaks over 3 years old who had not undergone fecal examinations were randomly selected for autopsy. A total of 267 fecal samples were positive for Fasciola spp. eggs. The average infection rate was 17.32% (0-60.61%), and the average infection intensity was 51.9 eggs per gram (epg) of feces, with intensities ranging from 18 to 112 epg. In Maduo, Dari, Zhiduo, Chengduo, and Datong counties, the Fasciola spp. eggs infection rate was zero. Fasciola spp. adult flukes were detected in 66 out of 242 yaks at autopsy, with a total infection rate of 27.27% and an average infection intensity of 21.2 (adult worms), with intensities ranging from 3 to 46 worms. Logistic regression model analysis showed that age was a significant risk factor for yak infection with Fasciola spp. In addition, the risk varied between regions: Haiyan, Gangcha, Duran, and Wulan were all high-risk areas for yak infection with Fasciola spp. The spatial distribution of the Fasciola spp. infection rate in each region showed a very weak negative correlation (Moran's I = -0.062), Duran formed a spatial distribution of high-low clusters with surrounding areas, and Datong formed a low-high clustering distribution characteristic with the surrounding areas. This investigation revealed that the infection rate of Fasciola spp. in yaks was higher on the Qinghai-Tibet Plateau. Increasing age was a risk factor for infection with Fasciola spp.; different regions also have a different risk of Fasciola spp. infection. Only two regions showed clustering characteristics in the spatial distribution of infection rates. These findings extend the epidemiological information on Fasciola spp. infection in yaks and provide baseline data for the execution of control measures against Fasciola spp. infection.

Porous organic polymers (POPs) are a novel class of polymeric materials with high flexibility and designability for building structures. Herein, a phthalocyanine-based porous organic polymer (PcPOP) was constructed in situ on copper foil from H 2 Pc(ethynyl) 4 [Pc(ethynyl) 4 = 2(3),9(10),16(17),23(24)-tetra(ethynyl)phthalocyanine] by the coupling reaction. Benefiting from the uniformly distributed electron-rich nitrogen atoms in the Pc structure and the sp-hybridized carbons in the acetylenic linkage, Li intercalation in the porous organic polymer would be improved and stabilized. As a result, PcPOP showed remarkable electrochemical performance in lithium-ion batteries as the anode, including high specific capacity (a charge capacity of 1172 mA h g -1 at a current density of 150 mA g -1 ) and long cycling stability (a reversible capacity of 960.1 mA h g -1 can be achieved even after 600 cycles at a current density of 1500 mA g -1 ). The result indicates that the intrinsic doping of electron-rich sites of the building molecules is beneficial for the electrochemical performance of the porous organic polymer.

Characiformes is a diverse and evolutionarily significant order of freshwater fish encompassing over 2,300 species. Despite its diversity, our understanding of Characiformes' evolutionary relationships and adaptive mechanisms is limited due to insufficient genome sequences. In this study, we sequenced and assembled the genomes of four Characiformes species, three of which were chromosome-level assemblies. Our analyses revealed dynamic changes in gene family evolution, repeat sequences and variations in chromosomal collinearity within these genomes. With the assembled genomes, we were not only able to elucidate the evolutionary relationship of the four main orders in Otophysi but also indicated Characiformes as the paraphyletic group. Comparative genomic analysis with other available fish genomes shed light on the evolution of genes related to tooth development in Characiformes. Notably, variations in the copy number of secretory calcium-binding phosphoproteins (SCPP) genes were observed among different orders of Otophysi, indicating their potential contribution to the diversity of tooth types. Our study offers invaluable genome sequences and novel insights into Characiformes' evolution, paving the way for further genomic and evolutionary research in fish., (© The Author(s) 2023. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.)

Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5'-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 μs Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor.

Background: The chimeric antigen receptor (CAR)-T therapy has a limited therapeutic effect on solid tumors owing to the limited CAR-T cell infiltration into solid tumors and the inactivation of CAR-T cells by the immunosuppressive tumor microenvironment. Macrophage is an important component of the innate and adaptive immunity, and its unique phagocytic function has been explored to construct CAR macrophages (CAR-Ms) against solid tumors. This study aimed to investigate the therapeutic application of CAR-Ms in ovarian cancer., Methods: In this study, we constructed novel CAR structures, which consisted of humanized anti-HER2 or CD47 scFv, CD8 hinge region and transmembrane domains, as well as the 4-1BB and CD3ζ intracellular domains. We examined the phagocytosis of HER2 CAR-M and CD47 CAR-M on ovarian cancer cells and the promotion of adaptive immunity. Two syngeneic tumor models were used to estimate the in vivo antitumor activity of HER2 CAR-M and CD47 CAR-M., Results: We constructed CAR-Ms targeting HER2 and CD47 and verified their phagocytic ability to ovarian cancer cells in vivo and in vitro. The constructed CAR-Ms showed antigen-specific phagocytosis of ovarian cancer cells in vitro and could activate CD8 + cytotoxic T lymphocyte (CTL) to secrete various anti-tumor factors. For the in vivo model, mice with human-like immune systems were used. We found that CAR-Ms enhanced CD8 + T cell activation, affected tumor-associated macrophage (TAM) phenotype, and led to tumor regression., Conclusions: We demonstrated the inhibition effect of our constructed novel HER2 CAR-M and CD47 CAR-M on target antigen-positive ovarian cancer in vitro and in vivo, and preliminarily verified that this inhibitory effect is due to phagocytosis, promotion of adaptive immunity and effect on tumor microenvironment., (© 2023. BioMed Central Ltd., part of Springer Nature.)