Engineering Versatile Bacteria-Derived Outer Membrane Vesicles: An Adaptable Platform for Advancing Cancer Immunotherapy.

In recent years, cancer immunotherapy has undergone a transformative shift toward personalized and targeted therapeutic strategies. Bacteria-derived outer membrane vesicles (OMVs) have emerged as a promising and adaptable platform for cancer immunotherapy due to their unique properties, including natural immunogenicity and the ability to be engineered for specific therapeutic purposes. In this review, a comprehensive overview is provided of state-of-the-art techniques and methodologies employed in the engineering of versatile OMVs for cancer immunotherapy. Beginning by exploring the biogenesis and composition of OMVs, unveiling their intrinsic immunogenic properties for therapeutic appeal. Subsequently, innovative approaches employed to engineer OMVs are delved into, ranging from the genetic engineering of parent bacteria to the incorporation of functional molecules. The importance of rational design strategies is highlighted to enhance the immunogenicity and specificity of OMVs, allowing tailoring for diverse cancer types. Furthermore, insights into clinical studies and potential challenges utilizing OMVs as cancer vaccines or adjuvants are also provided, offering a comprehensive assessment of the current landscape and future prospects. Overall, this review provides valuable insights for researchers involved in the rapidly evolving field of cancer immunotherapy, offering a roadmap for harnessing the full potential of OMVs as a versatile and adaptable platform for cancer treatment.

iProps: A comprehensive software tool for protein classification and analysis with automatic machine learning capabilities and model interpretation capabilities.

Protein classification is a crucial field in bioinformatics. The development of a comprehensive tool that can perform feature evaluation, visualization, automated machine learning, and model interpretation would significantly advance research in protein classification. However, there is a significant gap in the literature regarding tools that integrate all these essential functionalities. This paper presents iProps, a novel Python-based software package, meticulously crafted to fulfill these multifaceted requirements. iProps is distinguished by its proficiency in feature extraction, evaluation, automated machine learning, and interpretation of classification models. Firstly, iProps fully leverages evolutionary information and amino acid reduction information to propose or extend several numerical protein features that are independent of sequence length, including SC-PSSM, ORDip, TRC, CTDC-E, CKSAAGP-E, and so forth; at the same time, it also implements the calculation of 17 other numerical features within the software. iProps also provides feature combination operations for the aforementioned features to generate more hybrid features, and has added data balancing sampling processing as well as built-in classifier settings, among other functionalities. Thus, It can discern the most effective protein class recognition feature from a multitude of candidates, utilizing three automated machine learning algorithms to identify the most optimal classifiers and parameter settings. Furthermore, iProps generates a detailed explanatory report that includes 23 informative graphs derived from three interpretable models. To assess the performance of iProps, a series of numerical experiments were conducted using two well-established datasets. The results demonstrated that our software achieved superior recognition performance in every case. Beyond its contributions to bioinformatics, iProps broadens its applicability by offering robust data analysis tools that are beneficial across various disciplines, capitalizing on its automated machine learning and model interpretation capabilities. As an open-source platform, iProps is readily accessible and features an intuitive user interface, ensuring ease of use for individuals, even those without a background in programming. The source code of the software is available for download at the following website: https://github.com/LigosQ/iProps and https://gitee.com/LigosQ/iProps.

Multifunctional Nanomesh Enables Cellular-Resolution, Elastic Neuroelectronics.

Silicone-based devices have the potential to achieve an ideal interface with nervous tissue but suffer from scalability, primarily due to the mechanical mismatch between established electronic materials and soft elastomer substrates. This study presents a novel approach using conventional electrode materials through multifunctional nanomesh to achieve reliable elastic microelectrodes directly on polydimethylsiloxane (PDMS) silicone with an unprecedented cellular resolution. This engineered nanomesh features an in-plane nanoscale mesh pattern, physically embodied by a stack of three thin-film materials by design, namely Parylene-C for mechanical buffering, gold (Au) for electrical conduction, and Poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) for improved electrochemical interfacing. Nanomesh elastic neuroelectronics are validated using single-unit recording from the small and curvilinear epidural surface of mouse dorsal root ganglia (DRG) with device self-conformed and superior recording quality compared to plastic control devices requiring manual pressing is demonstrated. Electrode scaling studies from in vivo epidural recording further revealed the need for cellular resolution for high-fidelity recording of single-unit activities and compound action potentials. In addition to creating a minimally invasive device to effectively interface with DRG sensory afferents at a single-cell resolution, this study establishes nanomeshing as a practical pathway to leverage traditional electrode materials for a new class of elastic neuroelectronics.

Cyrtomiumadenotrichum (Dryopteridaceae), a new species from Guangxi, China.

Cyrtomiumadenotrichum Y. Nong & R.H. Jiang (Dryopteridaceae), a new species from Guangxi, China, is described and illustrated. This new species is similar to C.nephrolepioides (Christ) Copel., C.obliquum Ching & K. H. Shing ex K. H. Shing, C.sinningense Ching & K. H. Shing ex K. H. Shing and C.calcis Liang Zhang, N.T.Lu & Li Bing Zhang in having erect rhizomes, dense, leathery lamina and rounded sori, but it can be easily distinguishable by its stipe sparsely glandular, base obvious oblique, basiscopic base truncate, acroscopic base auriculate or ovate.

Probiotic Lactobacillus rhamnosus GG improves insulin sensitivity and offspring survival via modulation of gut microbiota and serum metabolite in a sow model.

BACKGROUND: Sows commonly experience insulin resistance in late gestation and lactation, causing lower feed intake and milk production, which can lead to higher mortality rates in newborn piglets. The probiotic Lactobacillus rhamnosus GG (LGG) is known to improve insulin resistance. However, whether supplementing LGG can improve insulin sensitivity in sows and enhance lactation performance, particularly the early survival of offspring remains unclear. Hence, we explored the effects and mechanisms of supplementing LGG during late gestation and lactation on sow insulin sensitivity, lactation performance, and offspring survival. In total, 20 sows were randomly allocated to an LGG (n = 10) and control group (n = 10). RESULTS: In sows, LGG supplementation significantly improved insulin sensitivity during late gestation and lactation, increased feed intake, milk production and colostrum lactose levels in early lactation, and enhanced newborn piglet survival. Moreover, LGG treatment significantly reshaped the gut microbiota in sows, notably increasing microbiota diversity and enriching the relative abundance of insulin sensitivity-associated probiotics such as Lactobacillus, Bifidobacterium, and Bacteroides. Serum metabolite and amino acid profiling in late-gestation sows also revealed decreased branched-chain amino acid and kynurenine serum levels following LGG supplementation. Further analyses highlighted a correlation between mitigated insulin resistance in late pregnancy and lactation by LGG and gut microbiota reshaping and changes in serum amino acid metabolism. Furthermore, maternal LGG enhanced immunity in newborn piglets, reduced inflammation, and facilitated the establishment of a gut microbiota. CONCLUSIONS: We provide the first evidence that LGG mitigates insulin resistance in sows and enhances offspring survival by modulating the gut microbiota and amino acid metabolism.

Genome-wide analysis of TOPLESS/TOPLESS-RELATED co-repressors and functional characterization of BnaA9.TPL regulating the embryogenesis and leaf morphology in rapeseed.

TOPLESS/TOPLESS-RELATED (TPL/TPR) proteins belong to the Groucho (Gro)/Tup1 family co-repressors and act as broad co-repressors that modulate multiple phytohormone signalling pathways and various developmental processes in plant. However, TPL/TPR co-repressors so far are poorly understood in the rapeseed, one of the world-wide important oilseed crops. In this study, we comprehensively characterized eighteen TPL/TPR genes into five groups in the rapeseed genome. Members of TPL/TPR1/TPR4 and TPR2/TPR3 had close evolutionary relationship, respectively. All TPL/TPRs had similar expression patterns and encode conserved protein domain. In addition, we demonstrated that BnaA9.TPL interacted with all known plant repression domain (RD) sequences, which were distributed in non-redundant 24,238 (22.6 %) genes and significantly enriched in transcription factors in the rapeseed genome. These transcription factors were largely co-expressed with the TPL/TPR genes and involved in diverse pathway, including phytohormone signal transduction, protein kinases and circadian rhythm. Furthermore, BnaA9.TPL was revealed to regulate apical embryonic fate by interaction with Bna.IAA12 and suppression of PLETHORA1/2. BnaA9.TPL was also identified to regulate leaf morphology by interaction with Bna.AS1 (Asymmetric leaves 1) and suppression of KNOTTED-like homeobox genes and YABBY5. These data not only suggest the rapeseed TPL/TPRs play broad roles in different processes, but also provide useful information to uncover more TPL/TPR-mediated control of plant development in rapeseed.

Effects of climate warming on soil nitrogen cycles and bamboo growth in core giant panda habitat.

Climate change can pose a significant threat to terrestrial ecosystems by disrupting the circulation of soil nitrogen. However, experimental analyses on the effect of climate change on soil nitrogen cycles and the implications for the conservation of key wildlife species (i.e., the giant panda, Ailuropoda melanoleuca) remain understudied. We investigated the effects of a 1.5 °C, 3 °C, and 4.5 °C temperature increase on nitrogen distribution in different soil layers of bamboo forest via an in-situ experiment and assessed the implications for the growth and survival of arrow bamboo (Bashania faberi), a critical food resource for giant pandas. Our results showed that warming treatments generally increased soil N content, while effects differed between surface soil and subsurface soil and at different warming treatments. Particularly an increase of 1.5 °C raised the subsurface soil NO3-N content, as well as the content of N in bamboo leaves. We found a significant positive correlation between the subsurface soil NO3-N content and the N content of arrow bamboo. An increase of 3-4.5 °C raised the content of total N and NO3-N in the surface soil and led to a reduction in the total aboveground biomass and survival rate of arrow bamboo. Limited warming (e.g., the increase of 0-1.5 °C) may promote the soil N cycle, raise the N-acetylglucosaminidase (NAG) enzyme activity, increase NO3-N in subsurface soil, increase the N content of bamboo, and boost the biomass of bamboo - all of which could be beneficial to giant panda survival. However, higher warming (e.g., an increase of 3-4.5 °C) resulted in mass death of bamboo and a large reduction in aboveground biomass. Our findings provide a cautiously optimistic scenario for bamboo forest ecosystems under low levels of warming over a short period of time, but risks from higher levels of warming may be serious, especially considering the unpredictability of global climatic change.

Incidence and treatment-related risk factors of inhibitor development after intensive FVIII replacement for major orthopaedic surgery in previous treated haemophilia A.

INTRODUCTION: Haemophilia A (HA) is an X-linked recessive bleeding disorder caused by lack or deficiency of coagulation factor VIII. AIM: The aim of this study is to determine the incidence and treatment-related risk factors of inhibitor development after intensive FVIII replacement for major orthopaedic surgery in previous treated persons with HA. METHODS: A total of 151 HA who underwent 221 major orthopaedic surgical procedures after intensive FVIII treatment were reviewed. The results of inhibitor tests were collected. Potential clinical risk factors for inhibitor development were analyzed. RESULTS: 111 people were diagnosed with severe HA. Thirty-seven persons (24.5%) had history of previous intensive FVIII treatment for surgical procedure. They received a mean perioperative cumulative FVIII of 498 iu/kg within first week after surgery. Seven cases (4.6%) developed an inhibitor post-operatively in our study. Surgical procedure for pseudotumor and the group of persons who experienced postoperative complications had the higher incidence of inhibitor development (9.5%, 13.3% respectively). Only previous history for intensive FVIII exposure was considered as a significant predictor for postoperative inhibitor development after multivariate logistic regression analysis (OR: 29.5, P = 0.002). CONCLUSION: The incidence of inhibitor development in previously treated persons with HA undergoing major orthopaedic surgery was 4.6% and the history of previous intensive FVIII treatment for surgery was associated with higher risk of inhibitor development.

Improvement of insulin sensitivity by dietary fiber consumption during late pregnant sows is associated with gut microbiota regulation of tryptophan metabolism.

BACKGROUND: Dietary fiber (DF) consumption was reported to improve insulin sensitivity, change the tryptophan metabolism, and alter the gut microbiota. Herein, this study aimed to investigate the effects of DF consumption on insulin sensitivity, tryptophan metabolism, and gut microbiota composition in sows during late pregnancy, and explore the relationship between tryptophan metabolites and insulin sensitivity regulated by DF supplementation. RESULTS: Twelve sows were randomly assigned to two dietary treatment groups (six/group): the low-fiber (LF) group, which was fed a basal diet, and the high-fiber (HF) group, which was fed the basal diet supplemented with 22.60 g/kg inulin and 181.60 g/kg cellulose. During late pregnancy, meal test, glucose tolerance test, and insulin challenge test were used to investigate the insulin sensitivity of sows, using the percutaneous brachiocephalic vein catheterization technique. High DF consumption resulted in improved insulin sensitivity, especially during the second and third trimesters, and promoted serotonin production from tryptophan. Additionally, plasma serotonin concentration was positively correlated with the insulin sensitivity index during late pregnancy. Moreover, DF consumption elevated fecal short-chain fatty acid (SCFA) concentrations, altered fecal microbial diversity, and increased the abundances of Rikenellaceae_RC9_gut_group, Alloprevotella, Parabacteroides, Roseburia, and Sphaerochaeta, which were positively correlated to plasma serotonin concentration. CONCLUSIONS: DF consumption improved insulin sensitivity during late pregnancy in sows, which improved microbial diversity in fecal samples and increased fecal SCFA concentrations, resulting in a positive correlation with plasma serotonin level.

The impact of PM2.5 on lung function and chronic respiratory diseases: insights from genetic evidence.

BACKGROUND: PM2.5 has been associated with various adverse health effects, particularly affecting lung function and chronic respiratory diseases. However, the genetic causality relationship between PM2.5 exposure and lung function as well as chronic respiratory diseases remains poorly understood. METHOD: We conducted a two-sample Mendelian randomization analysis to investigate the causal impact of PM2.5 on lung function and chronic respiratory diseases. Instrumental variables were carefully selected, with significance thresholds (P < 5 × 10- 8), and linkage disequilibrium with an r2 value below 0.001. Additionally, SNPs with an F-statistic exceeding 10 were included to mitigate potential bias stemming from weak instrumental variables. The primary analytical approach employed the Inverse Variance Weighted method, supplemented by the Weighted Median, MR-Egger, Simple Model, and Weighted Model. Furthermore, pleiotropy and heterogeneity were evaluated through the MR-Egger intercept test and Cochrane's Q test, with a sensitivity analysis conducted using the leave-one-out method. RESULTS: Eight SNPs significantly associated with PM2.5 exposure were identified as Instrumental variables. Mendelian randomization analysis revealed a significant causal association between PM2.5 exposure and lung function (FEV), with an OR of 0.7284 (95% CI: 0.5799-0.9150). Similarly, PM2.5 exposure demonstrated a substantial causal effect on asthma, with an OR of 1.5280 (95% CI: 1.0470-2.2299). However, no causal association was observed between PM2.5 exposure and chronic obstructive pulmonary disease, with an OR of 1.5176 (95% CI: 0.8294-2.7768). CONCLUSION: These findings emphasize the necessity for continued research efforts in environmental health to develop effective strategies for the prevention and management of chronic respiratory diseases.

A Gestational Pectin Diet Could Improve the Health of Multiparous Sows by Modulating the Gut Microbiota and Cytokine Level during Late Pregnancy.

This study aimed to investigate the effects of the dietary fiber pectin on the gut microbiota and health of parturient sows. A total of 30 parity 5-7, multiparous gestation sows (Large White × Landrace) were randomly assigned to two treatment groups after mating: Con (control, basic diet) and Pec (pectin, 3%). The sows received the two diets during gestation, and all sows were fed the same standard basic diet during lactation. The results of ß-diversity showed that the composition of the gut microbiota was different in the Con and Pec groups. Compared with the sows in the Con group, the Pec sows showed a higher abundance of the gut bacteria Clostridium and Romboutsia and a lower abundance of harmful bacteria (Micrococcaceae, Coriobacteriaceae, Dorea, Actinomyces). On the other hand, the SCFA plasma concentration was increased in the Pec group, while pro-inflammatory cytokine (IL-6, IL-1ß, and TNF-α) concentrations were decreased. In conclusion, the soluble dietary fiber pectin could improve the reproductive performance and health of sows by increasing the abundance of some commensal bacteria enhancing the metabolite SCFA levels and reducing the pro-inflammatory cytokine plasma levels.

Benefits of maternal pectin supplementation in gestation diet on vaginal microbiota of sows and intestinal health of newborn piglets.

Pectin is a proven prebiotic and widely used in human health products. This study aims to assess the impact of dietary pectin supplementation during gestation on sow vaginal microbiota and the offspring's intestinal composition. Thirty sows were randomly allocated to two groups and fed a standard diet (CON) or a standard diet supplemented with 3 g/kg pectin (PEC). Blood, feces, and vaginal swab samples from the sows and blood, intestines issue, and colonic content samples from the offspring were collected and analyzed. The results indicate that the relative abundance of vaginal Lactobacillus was notably enhanced in the PEC group and fecal ß-glucuronidase (ß-G) activity and plasma 17ß-estradiol (E2) concentration were also significantly increased in the PEC group. Newborn piglets were found to host different microbial communities as well. At the phylum level, Proteobacteria dominated in the CON group, and Firmicutes was predominant in the PEC group. Newborn piglets in the PEC group had a lower interleukin-6 (IL-6) concentration in their plasma. The expression of intestinal cytokines of offspring was improved as well. Villus height and villus height/crypt depth (V/C) in the PEC group were extremely higher than those in the CON group. In conclusion, dietary pectin supplementation can be of benefit to both sows and newborn piglets.

4-Octyl itaconate inhibits inflammation via the NLRP3 pathway in neuromyelitis optica spectrum disorders.

OBJECTIVE: Neuromyelitis optica spectrum disorders (NMOSD) are rare inflammatory astrocytic diseases of the central nervous system (CNS). The roles of immune response gene-1 (IRG1) and the IRG1-itaconic acid-NLRP3 inflammatory pathway in the pathogenesis of NMOSD and the effects of 4-octyl itaconate (4-OI) on the NLRP3 inflammatory pathway in NMOSD are unclear. This study aimed to determine the role of IRG1 and the activation status of the NLRP3 inflammatory pathway in acute-onset NMOSD and to investigate the inhibitory effects of 4-OI on NLRP3 inflammasome activation via the IRG1-itaconic acid-NLRP3 pathway in monocytes and macrophages by using in vitro models. METHODS: Peripheral blood mononuclear cells (PBMCs) and serum were collected from patients with acute NMOSDs and healthy controls (HC), followed by monocyte typing and detection of the expression of NLRP3-related inflammatory factors. Subsequently, the effects of 4-OI on the IRG1-itaconic acid-NLRP3 pathway were investigated in peripheral monocytes from patients with NMOSD and in macrophages induced by human myeloid leukemia mononuclear cells (THP-1 cells) via in vitro experiments. RESULTS: Patients with acute NMOSD exhibited upregulated IRG1 expression. In particular, the upregulation of the expression of the NLRP3 inflammasome and proinflammatory factors was notable in monocytes in acute NMOSD patients. 4-OI inhibited the activation of the IRG1-itaconic acid-NLRP3 inflammatory pathway in the PBMCs of patients with NMOSD. INTERPRETATION: 4-OI could effectively inhibit NLRP3 signaling, leading to the inhibition of proinflammatory cytokine production in patients with NMOSD-derived PBMCs and in a human macrophage model. Thus, 4-OI and itaconate could have important therapeutic value for the treatment of NMOSD in the future.

Identification of Arginine-Vasopressin Receptor 1a (Avpr1a/Avpr1a) as a Novel Candidate Gene for Chronic Visceral Pain Sheds Light on the Potential Role of Enteric Neurons in the Development of Visceral Hypersensitivity.

Chronic abdominal pain in the absence of ongoing disease is the hallmark of disorders of gut-brain interaction (DGBIs), including irritable bowel syndrome (IBS). While the etiology of DGBIs remains poorly understood, there is evidence that both genetic and environmental factors play a role. In this study, we report the identification and validation of arginine-vasopressin receptor 1A (Avpr1a) as a novel candidate gene for visceral hypersensitivity (VH), a primary peripheral mechanism underlying abdominal pain in DGBI/IBS. Comparing 2 C57BL/6 (BL/6) substrains (C57BL/6NTac and C57BL/6J) revealed differential susceptibility to the development of chronic VH following intrarectal zymosan instillation, a validated preclinical model for postinflammatory IBS. Using whole-genome sequencing, we identified a single-nucleotide polymorphism differentiating the 2 strains in the 5' intergenic region upstream of Avpr1a, encoding the protein Avpr1a. We used behavioral, histological, and molecular approaches to identify distal colon-specific gene expression and neuronal hyperresponsiveness covarying with Avpr1a genotype and VH susceptibility. While the 2 BL/6 substrains did not differ across other gastrointestinal phenotypes (eg, fecal water retention), VH-susceptible BL/6NTac mice had higher colonic Avpr1a mRNA and protein expression. These results parallel findings that patients' colonic Avpr1a mRNA expression corresponded to higher pain ratings. Moreover, neurons of the enteric nervous system were hyperresponsive to the Avpr1a agonist arginine-vasopressin, suggesting a role for enteric neurons in the pathology underlying VH. Taken together, these findings implicate differential regulation of Avpr1a as a novel mechanism of VH susceptibility as well as a potential therapeutic target specific to VH. PERSPECTIVE: This article presents evidence of Avpr1a as a novel candidate gene for VH in a mouse model of IBS. Avpr1a genotype and/or tissue-specific expression represents a potential biomarker for chronic abdominal pain susceptibility.

Extraction, characterization and intestinal anti-inflammatory and anti-oxidative activities of polysaccharide from stems and leaves of Chuanminshen violaceum M. L. Sheh & R. H. Shan.

ETHNOPHARMACOLOGICAL RELEVANCE: Chuanminshen violaceum M. L. Sheh & R. H. Shan (CV) is used as a medicine with roots, which have the effects of benefiting the lungs, harmonizing the stomach, resolving phlegm and detoxifying. Polysaccharide is one of its main active components and has various pharmacological activities, but the structural characterization and pharmacological activities of polysaccharide from the stems and leaves parts of CV are still unclear. AIM OF THE STUDY: The aim of this study was to investigate the optimal extraction conditions for ultrasound-assisted extraction of polysaccharide from CV stems and leaves, and to carry out preliminary structural analyses, anti-inflammatory and antioxidant effects of the obtained polysaccharide and to elucidate the underlying mechanisms. MATERIALS AND METHODS: The ultrasonic-assisted extraction of CV stems and leaves polysaccharides was carried out, and the response surface methodology (RSM) was used to optimize the extraction process to obtain CV polysaccharides (CVP) under the optimal conditions. Subsequently, we isolated and purified CVP to obtain the homogeneous polysaccharide CVP-AP-I, and evaluated the composition, molecular weight, and structural features of CVP-AP-I using a variety of technical methods. Finally, we tested the pharmacological activity of CVP-AP-Ⅰ in an LPS-induced model of oxidative stress and inflammation in intestinal porcine epithelial cells (IPEC-J2) and explored its possible mechanism of action. RESULTS: The crude polysaccharide was obtained under optimal extraction conditions and subsequently isolated and purified to obtain CVP-AP-Ⅰ (35.34 kDa), and the structural characterization indicated that CVP-AP-Ⅰ was mainly composed of galactose, galactose, rhamnose and glucose, which was a typical pectic polysaccharide. In addition, CVP-AP-Ⅰ attenuates LPS-induced inflammation and oxidative stress by inhibiting the expression of pro-inflammatory factor genes and proteins and up-regulating the expression of antioxidant enzyme-related genes and proteins in IPEC-J2, by a mechanism related to the activation of the Nrf2/Keap1 signaling pathway. CONCLUSION: The results of this study suggest that the polysaccharide isolated from CV stems and leaves was a pectic polysaccharide with similar pharmacological activities as CV roots, exhibiting strong anti-inflammatory and antioxidant activities, suggesting that CV stems and leaves could possess the same traditional efficacy as CV roots, which is expected to be used in the treatment of intestinal diseases.

High-fidelity imaging of a tumour-associated lysosomal enzyme with an acceptor engineering-boosted near-infrared fluorescent probe.

To facilitate the understanding of the dynamic distribution and activity of lysosomal enzymes, it is highly desirable to develop high-fidelity near-infrared (NIR) activatable fluorescent probes. Here, we propose a general acceptor engineering strategy to construct NIR probes with lysosome-targeting capability. Upon isosteric replacement and additional functionalization, the ß-gal-activatable probe OELyso-Gal exhibited excellent lysosome-targeting capability and favorable responsive performance to the enzyme of interest. Notably, the steric hindrance effect from acceptor engineering is modest, which renders the probe unprecedented affinity to enzymes. Upon the introduction of acceptor engineering, the lysosome-targeting probe became more sensitive to ß-gal in cells and tissues, boosting the discrimination of high ß-gal-expressing ovarian cancer tumours from low ß-gal-expressing tissues. Furthermore, the superiority of OELyso-Gal was validated in real-time visualization of ovarian cancer in tumour-bearing mice. This elegant acceptor engineering strategy provides inspirational insights into the development of customized fluorescent probes for monitoring disease-associated biomarkers within subcellular organelles.

Research on improved YOLOv8n based potato seedling detection in UAV remote sensing images.

Introduction: Accurate detection of potato seedlings is crucial for obtaining information on potato seedlings and ultimately increasing potato yield. This study aims to enhance the detection of potato seedlings in drone-captured images through a novel lightweight model. Methods: We established a dataset of drone-captured images of potato seedlings and proposed the VBGS-YOLOv8n model, an improved version of YOLOv8n. This model employs a lighter VanillaNet as the backbone network in-stead of the original YOLOv8n model. To address the small target features of potato seedlings, we introduced a weighted bidirectional feature pyramid network to replace the path aggregation network, reducing information loss between network layers, facilitating rapid multi-scale feature fusion, and enhancing detection performance. Additionally, we incorporated GSConv and Slim-neck designs at the Neck section to balance accuracy while reducing model complexity. Results: The VBGS-YOLOv8n model, with 1,524,943 parameters and 4.2 billion FLOPs, achieves a precision of 97.1%, a mean average precision of 98.4%, and an inference time of 2.0ms. Comparative tests reveal that VBGS-YOLOv8n strikes a balance between detection accuracy, speed, and model efficiency compared to YOLOv8 and other mainstream networks. Specifically, compared to YOLOv8, the model parameters and FLOPs are reduced by 51.7% and 52.8% respectively, while precision and a mean average precision are improved by 1.4% and 0.8% respectively, and the inference time is reduced by 31.0%. Discussion: Comparative tests with mainstream models, including YOLOv7, YOLOv5, RetinaNet, and QueryDet, demonstrate that VBGS-YOLOv8n outperforms these models in terms of detection accuracy, speed, and efficiency. The research highlights the effectiveness of VBGS-YOLOv8n in the efficient detection of potato seedlings in drone remote sensing images, providing a valuable reference for subsequent identification and deployment on mobile devices.

Separation and Detection of Catechins and Epicatechins in Shanxi Aged Vinegar Using Solid-Phase Extraction and Hydrophobic Deep Eutectic Solvents Combined with HPLC.

This research presents a new, eco-friendly, and swift method combining solid-phase extraction and hydrophobic deep eutectic solvents (DES) with high-performance liquid chromatography (SPE-DES-HPLC) for extracting and quantifying catechin and epicatechin in Shanxi aged vinegar (SAV). The parameters, such as the elution solvent type, the XAD-2 macroporous resin dosage, the DES ratio, the DES volume, the adsorption time, and the desorption time, were optimized via a one-way experiment. A central composite design using the Box-Behnken methodology was employed to investigate the effects of various factors, including 17 experimental runs and the construction of three-dimensional response surface plots to identify the optimal conditions. The results show that the optimal conditions were an HDES (tetraethylammonium chloride and octanoic acid) ratio of 1:3, an XAD-2 macroporous resin dosage of 188 mg, and an adsorption time of 11 min. Under these optimal conditions, the coefficients of determination of the method were greater than or equal to 0.9917, the precision was less than 5%, and the recoveries ranged from 98.8% to 118.8%. The environmentally friendly nature of the analytical process and sample preparation was assessed via the Analytical Eco-Scale and AGREE, demonstrating that this method is a practical and eco-friendly alternative to conventional determination techniques. In summary, this innovative approach offers a solid foundation for the assessment of flavanol compounds present in SAV samples.

A stacking-based algorithm for antifreeze protein identification using combined physicochemical, pseudo amino acid composition, and reduction property features.

Antifreeze proteins have wide applications in the medical and food industries. In this study, we propose a stacking-based classifier that can effectively identify antifreeze proteins. Initially, feature extraction was performed in three aspects: reduction properties, scalable pseudo amino acid composition, and physicochemical properties. A hybrid feature set comprised of the combined information from these three categories was obtained. Subsequently, we trained the training set based on LightGBM, XGBoost, and RandomForest algorithms, and the training outcomes were passed to the Logistic algorithm for matching, thereby establishing a stacking algorithm. The proposed algorithm was tested on the test set and an independent validation set. Experimental data indicates that the algorithm achieved a recognition accuracy of 98.3 %, and an accuracy of 98.5 % on the validation set. Lastly, we analyzed the reasons why numerical features achieved high recognition capabilities from multiple aspects. Data dimensionality reduction and the analysis from two-dimensional and three-dimensional views revealed separability between positive and negative samples, and the protein three-dimensional structure further demonstrated significant differences in related features between the two samples. Analysis of the classifier revealed that Hr*Hr, HrHr, and Sc-PseAAC_1, 188D(152,116,57,183) were among the seven most important numerical features affecting algorithm recognition. For Hr*Hr and HrHr, supportive sequence level evidence for the reduction dictionary was found in terms of conservation area analysis, multiple sequence alignment, and amino acid conservative substitution. Moreover, the importance of the reduction dictionary was recognized through a comparative analysis of importance before and after the reduction, realizing the effectiveness of the dictionary in improving feature importance. A decision tree model has been utilized to discern the distinctions between dipeptides associated with the physical and chemical properties of His(H), Iso(I), Leu(L), and Lys(K) and other dipeptides. We finally analyzed the other seven features of importance, and data analysis confirmed that hydrophobicity, secondary structure, charge properties, van der Waals forces, and solvent accessibility are also factors affecting the antifreeze capability of proteins.

Exploring the Link Between Autophagy-Lysosomal Dysfunction and Early Heterotopic Ossification in Tendons.

Heterotopic ossification (HO), the pathological formation of bone within soft tissues such as tendon and muscle, is a notable complication resulting from severe injury. While soft tissue injury is necessary for HO development, the specific molecular pathology responsible for trauma-induced HO remains a mystery. The previous study detected abnormal autophagy function in the early stages of tendon HO. Nevertheless, it remains to be determined whether autophagy governs the process of HO generation. Here, trauma-induced tendon HO model is used to investigate the relationship between autophagy and tendon calcification. In the early stages of tenotomy, it is observed that autophagic flux is significantly impaired and that blocking autophagic flux promoted the development of more rampant calcification. Moreover, Gt(ROSA)26sor transgenic mouse model experiments disclosed lysosomal acid dysfunction as chief reason behind impaired autophagic flux. Stimulating V-ATPase activity reinstated both lysosomal acid functioning and autophagic flux, thereby reversing tendon HO. This present study demonstrates that autophagy-lysosomal dysfunction triggers HO in the stages of tendon injury, with potential therapeutic targeting implications for HO.