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The success of deep supervised learning in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) relies on a large number of labeled samples. However, label noise often exists in large-scale datasets, which highly influence network training. This study proposes loss curve fitting-based label noise uncertainty modeling and a noise uncertainty-based correction method. The loss curve is a discriminative feature to model label noise uncertainty using an unsupervised fuzzy clustering algorithm. Then, according to this uncertainty, the sample set is divided into different subsets: the noisy-label set, clean-label set, and fuzzy-label set, which are further used in training loss with different weights to correct label noise. Experiments on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset prove that our method can deal with varying ratios of label noise during network training and correct label noise effectively. When the training dataset contains a small ratio of label noise (40%), the proposed method corrects 98.6% of these labels and trains the network with 98.7% classification accuracy. Even when the proportion of label noise is large (80%), the proposed method corrects 87.8% of label noise and trains the network with 82.3% classification accuracy.

The Ricci curvature in Finsler geometry naturally generalizes the Ricci curvature in Riemannian geometry. In this paper, we study the -th root metric with weakly isotropic scalar curvature and obtain that its scalar curvature must vanish. Further, we prove that a locally conformally flat cubic Finsler metric with weakly isotropic scalar curvature must be locally Minkowskian.

Abstract The mismanagement of waste is jeopardizing urban sustainability. Although polycentric waste governance (PWG) has been introduced, characterizing the PWG remains challenging. This paper employs game theory to illustrate polycentricity by investigating the equilibrium state from the stakeholders’ perspective. Shanghai, Tokyo, and Hong Kong are selected as target cities for comparative analysis. The findings reveal the heterogeneous characteristics in three megacities’ PWG—the collaboration by principal stakeholders (formal recyclers, informal recyclers, households) in Shanghai, the exclusion of informal recyclers in Tokyo, and the limited contribution provided by the formal recyclers in Hong Kong. The divergent PWG characteristics can be attributed to variations in governance patterns, socioeconomic factors, and policy formulation. Regarding urban sustainability, Tokyo and Shanghai’s PWG contribute to the circular economy’s expansion, while Hong Kong’ potential, in this regard, is undervalued. Despite Tokyo’s improved social recognition to practitioners, this PWG mode, primarily driven by formal recyclers and households, presents limited inclusion of low-income groups. Additionally, it is crucial for the authorities in Shanghai and Hong Kong to acknowledge the potential pollution of informal recyclers’ non-environmental behavior. This paper offers a valuable model for characterizing and analyzing PWG across different cities, facilitating knowledge aggregation and the implementation of PWG practice.

Chimeric antigen receptor (CAR‐T) cell therapy is a newly developed immunotherapy strategy and has achieved satisfactory outcomes in the treatment of hematological malignancies. However, some adverse effects related to CAR‐T cell therapy have to be resolved before it is widely used in clinics as a cancer treatment. Furthermore, the application of CAR‐T cell therapy in the treatment of solid tumors has been hampered by numerous limitations. Therefore, it is essential to explore novel strategies to improve the therapeutic effect of CAR‐T cell therapy. In this review, we summarized the recently developed strategies aimed at optimizing the generation of CAR‐T cells and improving the anti‐tumor efficiency of CAR‐T cell therapy. Furthermore, the discovery of new targets for CAR‐T cell therapy and the combined treatment strategies of CAR‐T cell therapy with chemotherapy, radiotherapy, cancer vaccines and nanomaterials are highlighted.

Abstract China prioritizes a coordinated and sustainable shift from rural to urban areas, termed rural-urban transformation. This involves land, population, and industry urbanization. Here we explore the spatiotemporal dynamics of rural-urban transformation patterns in China, focusing on the degree of integrated transformation and the coupling between the three tracks. To conduct our investigation, we utilized the urbanization cube theory, satellite-derived gridded datasets, and the self-organizing map. Our findings show that eastern China has higher levels of integrated transformation and coupling compared to western China. There has been an overall increase in the coupling of China’s three rural-urban transformation tracks. We identified six typical rural-urban transformation patterns across China. Over time, 53.58% of prefectures improved in rural-urban transformation patterns, 3.44% degraded, and 42.98% (mainly in western China) remained unchanged. More importantly, we highlight that the increasing and coupling rural-urban transformation in China has reduced inequities in urban and rural well-being.

To address the current inefficiencies and subjective nature of manual observation in maize cultivation, with the aim of achieving high efficiency and productivity, this study focused on the DeMaya D3 maize variety. It proposes a maize growth stage recognition method based on the MobileNet model, which is a lightweight convolutional neural network architecture. The method was tested and achieved recognition accuracies of 0.98, 0.96, 0.92, 0.85, and 0.97 for different growth stages, respectively. Additionally, a maize growth prediction model was developed. Based on data collected from experimental plots regarding maize plant height and stem diameter, the Prophet model and an optimized version of the Prophet model were used to forecast maize growth trends. The Prophet model is an open-source tool for time series forecasting. Comparative analysis was conducted between the predictions of the original Prophet model and the optimized version. The relative errors of the Prophet model predictions were 0.85%, 2.11%, and 0.79%, while those of the optimized Prophet model were 0.76%, 0.47%, and 0.71%. Compared to the Prophet model, the optimized model reduced errors by 0.09%, 1.64%, and 0.08%, respectively. The maize plant growth control system was designed to obtain the information through the collection layer. The decision-making layer judged the soil nutrient absorption and growth status. Finally, the management layer controlled water and fertilizer.

Abstract 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.

Abstract Background The global aging population presents challenges that are particularly acute in China. Older Chinese adults’ attitudes towards death significantly impact their quality of life. Death education is crucial for promoting positive perspectives on life and death. Narrative education offers a promising approach to facilitating death education. Integrating the Knowledge-Attitude-Practice (KAP) model into death education will enhance the feasibility and acceptability of death education programs. Methods This mixed-methods feasibility study included a quasi-experimental trial and semi-structured interviews. Older adults in the intervention group (N = 27) received a 6-week KAP-based narrative life education program in addition to standard community health education; participants in the control group (N = 20) received only the normal community health education. In both groups, attitudes toward death and the meaning of life were assessed at baseline and immediately after the intervention. A post-intervention semi-structured interview and satisfaction survey were also conducted for the intervention group. Results Forty out of 47 older adults completed the program for an 85.1% retention rate. All of the older adults in the experiment were very satisfied and satisfied with the life education program, and no adverse events were reported. Compared to the control group, participants in the intervention group had a significant decrease in the fear of death (P = 0.028), and substantial improvement in their value of life (P = 0.031), goal of life (P = 0.035), freedom of life (P = 0.003), and the total score for purpose in life (P = 0.017). The qualitative results yielded four themes: profound recognition of life and death, contradiction between thoughts and action, conflict between one’s acceptance and others’ avoidance, and evaluation of the life education program. Conclusions The KAP-based narrative life education program is feasible and acceptable for older Chinese community-dwelling adults. It is also potentially effective in improving attitudes toward death attitudes and the meaning of life in this cohort. Trial registration This study was retrospectively registered at China Clinical Trial Registry as ChiCTR2300069551 on 2023-03-20. URL of registration: https://www.chictr.org.cn/showproj.html?proj=183176 .

Abstract Bacteria utilize intercellular communication to orchestrate essential cellular processes, adapt to environmental changes, develop antibiotic tolerance, and enhance virulence. This communication, known as quorum sensing (QS), is mediated by the exchange of small signalling molecules called autoinducers. AI-2 QS, regulated by the metabolic enzyme LuxS (S-ribosylhomocysteine lyase), acts as a universal intercellular communication mechanism across gram-positive and gram-negative bacteria and is crucial for diverse bacterial processes. In this study, we demonstrated that in Streptococcus suis (S. suis), a notable zoonotic pathogen, AI-2 QS enhances galactose utilization, upregulates the Leloir pathway for capsular polysaccharide (CPS) precursor production, and boosts CPS synthesis, leading to increased resistance to macrophage phagocytosis. Additionally, our molecular docking and dynamics simulations suggest that, similar to S. pneumoniae, FruA, a fructose-specific phosphoenolpyruvate phosphotransferase system prevalent in gram-positive pathogens, may also function as an AI-2 membrane surface receptor in S. suis. In conclusion, our study demonstrated the significance of AI-2 in the synthesis of galactose metabolism-dependent CPS in S. suis. Additionally, we conducted a preliminary analysis of the potential role of FruA as a membrane surface receptor for S. suis AI-2.

Abstract The purpose of this study was to develop and validate a physiologically based pharmacokinetic (PBPK) model combined with an EGFR occupancy (EO) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and the intracranial time-course of EGFR (T790M and L858R mutants) engagement in patient populations. The PBPK model was also used to investigate the key factors affecting OSI pharmacokinetics (PK) and intracranial EGFR engagement, analyze resistance to the target mutation C797S, and determine optimal dosing regimens when used alone and in drug-drug interactions (DDIs). A population PBPK-EO model of OSI was developed using physicochemical, biochemical, binding kinetic, and physiological properties, and then validated using nine clinical PK studies, observed EO study, and two clinical DDI studies. The PBPK-EO model demonstrated good consistency with observed data, with most prediction-to-observation ratios falling within the range of 0.7 to 1.3 for plasma AUC, Cmax, Ctrough and intracranial free concentration. The simulated time-course of C797S occupancy by the PBPK model was much lower than T790M and L858R occupancy, providing an explanation for OSI on-target resistance to the C797S mutation. The PBPK model identified ABCB1 CLint,u, albumin level, and EGFR expression as key factors affecting plasma Ctrough and intracranial EO for OSI. Additionally, PBPK-EO simulations indicated that the optimal dosing regimen for OSI in patients with brain metastases is either 80 mg once daily (OD) or 160 mg OD, or 40 mg or 80 mg twice daily (BID). When used concomitantly with CYP enzyme perpetrators, the PBPK-EO model suggested appropriate dosing regimens of 80 mg OD with fluvoxamine (FLUV) itraconazole (ITR) or fluvoxamine (FLUC) for co-administration and an increase to 160 mg OD with rifampicin (RIF) or efavirenz (EFA). In conclusion, the PBPK-EO model has been shown to be capable of simulating the pharmacokinetic concentration–time profiles and the time-course of EGFR engagement for OSI, as well as determining the optimum dosing in various clinical situations.

Given a graph G, an [Formula: see text]-labeling of G is an assignment f of non-negative integers (labels) to the vertices of G such that [Formula: see text] if [Formula: see text] (i = 1, 2, 3). For a non-negative integer k, a k-[Formula: see text]-labeling is an [Formula: see text]-labeling such that no label is greater than k. The [Formula: see text]-labeling number of G, denoted by [Formula: see text], is the smallest number k such that G has a k-[Formula: see text]-labeling. Chia proved that the [Formula: see text]-labeling number of a tree T with maximum degree Δ can have one of three values: [Formula: see text] and [Formula: see text]. This paper gives some sufficient conditions for [Formula: see text] and [Formula: see text], respectively. As a result, the [Formula: see text]-labeling numbers of complete m-ary trees, spiders and banana trees are completely determined.

Abstract Background An accurate perception of death risk is a prerequisite for advanced cancer patients to make informed end-of-life care decisions. However, there is to date no suitable scale to measure death risk perception. This study was to develop and psychometrically test the death risk perception scale (DRPS) for advanced cancer patients. Methods Process of instrument development and psychometric evaluation were used. First, qualitative research, a literature review, brainstorming, a Delphi study, and cognitive interviews were conducted to construct a pretest scale of death risk perception. Second, a scale-based survey was administered to 479 advanced cancer patients. Item, exploratory factor, and confirmatory factor analyses were employed to optimize the scale. The Cronbach’s alpha was calculated as a reliability analysis. The validity analysis included construct, convergent, discriminant, and content validity values. Results A three-dimension, 12-item scale was developed, including deliberative, affective, and experiential risk perception. The confirmatory factor analysis supported the three-factor model with satisfactory convergent and discriminant validity levels. The Cronbach's alpha coefficient for internal consistency was 0.807 and scale-level content validity index was 0.98. Conclusions The 12-item DRPS is a reliable and valid instrument for assessing the level of death risk perception in advanced cancer patients. More studies are needed to examine its structure and robustness prior to use.

Post-stroke depression (POSD) is a common difficulty and most predominant emotional syndrome after stroke often consequences in poor outcomes. In the present investigation, we have designed and studied the neurologically active celastrol/minocycline encapsulated with macrophages-derived exosomes functionalized PLGA nanoformulations (CMC-EXPL) to achieve enhanced anti-inflammatory behaviour and anti-depressant like activity in a Rat model of POSD. The animal model of POSD was established through stimulating process with chronic unpredictable mild stress (CUM) stimulations after procedure of middle cerebral artery occlusion (MCAO). Neuronal functions and Anti-inflammation behaviours were observed by histopathological (H&E) examination and Elisa analyses, respectively. The anti-depressive activity of the nanoformulations treated Rat models were evaluated by open-field and sucrose preference test methods. Microglial polarization was evaluated via flow-cytometry and qRT-PCR observations. The observed results exhibited that prepared nanoformulations reduced the POSD-stimulated depressive-like activities in rat models as well alleviated the neuronal damages and inflammatory responses in the cerebral hippocampus. Importantly, prepared CMC-EXPL nanoformulation effectively prevented the M1 pro-inflammatory polarization and indorsed M2 anti-inflammatory polarization, which indicates iNOS and CD86 levels significantly decreased and upsurged Arg-1 and CD206 levels. CMC-EXPL nanoformulation suggestively augmented anti-depressive activities and functional capability and also alleviated brain inflammation in POSD rats, demonstrating its therapeutic potential for POSD therapy.

The terpene synthase (TPS) plays a pivotal roles in plant growth, development, and enhancing resilience against environmental stresses. Despite this, the bioinformatics analysis of the TPS family gene in soybean (Glycine max) is lacking. In this study, we investigated 36 GmTPS members in soybean, exhibiting a diverse range of protein lengths, spanning from 144 to 835 amino acids. A phylogenetic tree was constructed from these GmTPS genes revealed a classification into five distinct subgroups: Group1, Group2, Group3, Group4 and Group5. Notably, within each subgroup, we identified the motifs of GmTPS proteins were similar, although variations existed among different subfamilies. Gene duplication events analysis demonstrated that TPS genes expand differently in G. max, A. thaliana and O. sativa. Among, both tandem duplication and Whole genome duplication contributive to the expansion of TPS genes in G. max, and Whole genome duplication played a major role. Moreover, the cis-element analysis suggested that TPS is related to hormone signals, plant growth and development and environmental stress. Yeast two-hybrid (Y2H) assay results indicated TPS protein may form heterodimer to function, or may form complex with P450 proteins to function. RNA-seq results revealed a higher expression of most GmTPS genes in flowers, suggesting their potential contribution to flower development. Collectively, these findings offer a provide a holistic knowledge of the TPS gene family in soybean and will facilitate further characterization of TPSs effectively.

IntroductionPaclitaxel, a widely used chemotherapeutic agent for various cancers, induces peripheral neuropathy (PIPN) in approximately 80% of patients, severely affecting their quality of life. The role of vitamin D in pain perception has gained attention, but its correlation with PIPN remains unclear.MethodsThis study included 129 cancer patients who received adjuvant paclitaxel chemotherapy from January to June 2023. Neuropathic pain was assessed using the Douleur Neuropathique 4 Questions (DN4) questionnaire, and serum levels of vitamin D and glutathione (GSH) were measured to explore the correlation between vitamin D levels and neuropathic pain induced by paclitaxel chemotherapy.ResultsThe results showed a negative correlation between vitamin D deficiency and the occurrence of neuropathic pain (Spearman correlation coefficient of −0.324, P < 0.001). The receiver operating characteristic (ROC) curve analysis revealed that the area under the vitamin D curve for neuropathic pain was 0.681. Furthermore, after paclitaxel chemotherapy, there was a significant decrease in GSH levels in the serum of patients, with a more pronounced decline in the vitamin D-deficient group.DiscussionThe findings of this study indicate that higher levels of vitamin D are negatively associated with the occurrence of paclitaxel-induced neuropathic pain, suggesting that vitamin D might protect against oxidative stress. This discovery is significant for clinical treatment as it may help physicians better understand the mechanisms of pain during paclitaxel therapy and provide new strategies for the prevention and treatment of such pain. It also suggests that modulating vitamin D levels could reduce the neurotoxicity of paclitaxel, thereby improving patients’ quality of life and treatment compliance.

PurposeTo investigate the value of multiparameter MRI of early cervical cancer (ECC) combined with pre-treatment serum squamous cell carcinoma antigen (SCC-Ag) in predicting its pelvic lymph node metastasis (PLNM).Material and methods115 patients with pathologically confirmed FIGO IB1~IIA2 cervical cancer were retrospectively included and divided into the PLNM group and the non-PLNM group according to pathological results. Quantitative parameters of the primary tumor include Ktrans, Kep, Ve from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), ADCmean, ADCmin, ADCmax, D, D* and f from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were measured. Pre-treatment serum SCC-Ag was obtained. The difference of the above parameters between the two groups were compared using the student t-test or Mann-Whitney U test. Multivariate Logistic regression analysis was performed to determine independent risk factors. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic efficacy of individual parameters and their combination in predicting PLNM from ECC.ResultsThe PLNM group presented higher SCC-Ag [14.25 (6.74,36.75) ng/ml vs.2.13 (1.32,6.00) ng/ml, P

Crayfish (Procambarus clarkii) are economically important freshwater crustaceans. With the growth of the crayfish industry, the associated food-safety risks should be seriously considered. Although Vibrio parahaemolyticus is commonly recognized as a halophilic foodborne pathogen associated with seafood, it has been found to be a major pathogen in crayfish-associated food poisoning cases. In this study, the V. parahaemolyticus contamination level in crayfish production-sale chain was investigated using crayfish and environmental samples collected from crayfish farms and markets. Serious V. parahaemolyticus contamination (detection rate of 66%) was found in the entire crayfish production-sale chain, while the V. parahaemolyticus contamination level of the market samples was extremely high (detection rate of 92%). The V. parahaemolyticus detection rate of crayfish surface was similar to that of whole crayfish, indicating that crayfish surface was important for V. parahaemolyticus contamination. The simulation experiments of crayfish for sale being contaminated by different V. parahaemolyticus sources were performed. All the contamination sources, containing V. parahaemolyticus-positive tank, water, and crayfish, were found to be efficient to contaminate crayfish. The crayfish tank displayed the most significant contaminating role, while the water seemed to inhibit the V. parahaemolyticus contamination. The contamination extent of the crayfish increased with the number of V. parahaemolyticus cells the tank carried and the contact time of the crayfish and the tank, but decreased with the time that the crayfish were maintained in the water. It was also confirmed that the crayfish surface was more susceptible to V. parahaemolyticus contamination than the crayfish intestine. Furthermore, the adsorption of V. parahaemolyticus onto the crayfish shell was analyzed. Over 90% of the V. parahaemolyticus cells were adsorbed onto the crayfish shell in 6 h, indicating a significant adsorption effect between V. parahaemolyticus and the crayfish shell. In conclusion, within a water-free sale style, the fresh crayfish for sale in aquatic products markets uses its shell to capture V. parahaemolyticus cells from the V. parahaemolyticus-abundant environments. The V. parahaemolyticus contamination in crayfish for sale exacerbates the crayfish-associated food-safety risk. This study sheds light on V. parahaemolyticus control and prevention in crayfish industry.

Purpose: Accurate identification of primary breast cancer and axillary positive-node response to neoadjuvant chemotherapy (NAC) is important for determining appropriate surgery strategies. We aimed to develop combining models based on breast multi-parametric magnetic resonance imaging and clinicopathologic characteristics for predicting therapeutic response of primary tumor and axillary positive-node prior to treatment. Materials and methods: A total of 268 breast cancer patients who completed NAC and underwent surgery were enrolled. Radiomics features and clinicopathologic characteristics were analyzed through the analysis of variance and the least absolute shrinkage and selection operator algorithm. Finally, 24 and 28 optimal features were selected to construct machine learning models based on 6 algorithms for predicting each clinical outcome, respectively. The diagnostic performances of models were evaluated in the testing set by the area under the curve (AUC), sensitivity, specificity, and accuracy. Results: Of the 268 patients, 94 (35.1 %) achieved breast cancer pathological complete response (bpCR) and of the 240 patients with clinical positive-node, 120 (50.0 %) achieved axillary lymph node pathological complete response (apCR). The multi-layer perception (MLP) algorithm yielded the best diagnostic performances in predicting apCR with an AUC of 0.825 (95 % CI, 0.764–0.886) and an accuracy of 77.1 %. And MLP also outperformed other models in predicting bpCR with an AUC of 0.852 (95 % CI, 0.798–0.906) and an accuracy of 81.3 %. Conclusions: Our study established non-invasive combining models to predict the therapeutic response of primary breast cancer and axillary positive-node prior to NAC, which may help to modify preoperative treatment and determine post-NAC surgery strategy.

Aim: Endothelial dysfunction has been associated with both cerebrovascular pathology and Alzheimer’s disease (AD). However, the connection between circulating endothelial cells and the risk of AD remains uncertain. The objective was to leverage data from the Framingham Heart Study to investigate various circulating endothelial subtypes and their potential correlations with the risk of AD. Methods: The study conducted data analyses using Cox proportional hazard regression and linear regression methods. Additionally, genome-wide association study (GWAS) was carried out to further explore the data. Results: Among the eleven distinct circulating endothelial subtypes, only circulating endothelial progenitor cells (EPCs) expressing CD34+CD133+ were found to be negatively and dose-dependently associated with reduced AD risk. This association persisted even after adjusting for age, sex, years of education, apolipoprotein E (APOE) ε4 status, and various vascular diseases. Particularly noteworthy was the significant association observed in individuals with hypertension and cerebral microbleeds. Consistently, positive associations were identified between CD34+CD133+ EPCs and specific brain regions, such as higher proportions of circulating CD34+CD133+ cells correlating with increased volumes of white matter and the hippocampus. Additionally, a GWAS study unveiled that CD34+CD133+ cells influenced AD risk specifically in individuals with homozygous genotypes for variants in two stem cell-related genes: kirre like nephrin family adhesion molecule 3 (KIRREL3, rs580382 CC and rs4144611 TT) and exocyst complex component 6B (EXOC6B, rs61619102 CC). Conclusions: The findings suggest that circulating CD34+CD133+ EPCs possess a protective effect and may offer a new therapeutic avenue for AD, especially in individuals with vascular pathology and those carrying specific genotypes of KIRREL3 and EXOC6B genes.

Abstract Background The number of patients with type 1 diabetes rises rapidly around the world in recent years. Maternal diabetes has a detrimental effect on reproductive outcomes due to decreased oocyte quality. However, the strategies to improve the oocyte quality and artificial reproductive technology (ART) efficiency of infertile females suffering from diabetes have not been fully studied. In this study, we aimed to examine the effects of nicotinamide mononucleotide (NMN) on oocyte maturation of mouse with type 1 diabetes mouse and explore the underlying mechanisms of NMN’s effect. Methods Streptozotocin (STZ) was used to establish the mouse models with type 1 diabetes. The successful establishment of the models was confirmed by the results of body weight test, fasting blood glucose test and haematoxylin and eosin (H&E) staining. The in vitro maturation (IVM) rate of oocytes from diabetic mice was examined. Immunofluorescence staining (IF) was performed to examine the reactive oxygen species (ROS) level, spindle/chromosome structure, mitochondrial function, actin dynamics, DNA damage and histone modification of oocytes, which are potential factors affecting the oocyte quality. The quantitative reverse transcription PCR (RT-qPCR) was used to detect the mRNA levels of Sod1, Opa1, Mfn2, Drp1, Sirt1 and Sirt3 in oocytes. Results The NMN supplementation increased the oocyte maturation rate of the mice with diabetes. Furthermore, NMN supplementation improved the oocyte quality by rescuing the actin dynamics, reversing meiotic defects, improving the mitochondrial function, reducing ROS level, suppressing DNA damage and restoring changes in histone modifications of oocytes collected from the mice with diabetes. Conclusion NMN could improve the maturation rate and quality of oocytes in STZ-induced diabetic mice, which provides a significant clue for the treatment of infertility of the patients with diabetes.

Objectives The current clinical pulse lavage technique for flushing fresh osteochondral allografts (OCAs) to remove immunogenic elements from the subchondral bone is ineffective. This study aimed to identify the optimal method for removing immunogenic elements from OCAs. Methods We examined five methods for the physical removal of immunogenic elements from OCAs from the femoral condyle of porcine knees. We distributed the OCAs randomly into the following seven groups: (1) control, (2) saline, (3) ultrasound, (4) vortex vibration (VV), (5) low‐pulse lavage (LPL), (6) high‐pulse lavage (HPL), and (7) high‐speed centrifugation (HSC). OCAs were evaluated using weight measurement, micro‐computed tomography (micro‐CT), macroscopic and histological evaluation, DNA quantification, and chondrocyte activity testing. Additionally, the subchondral bone was zoned to assess the bone marrow and nucleated cell contents. One‐way ANOVA and paired two‐tailed Student's t‐test are used for statistical analysis. Results Histological evaluation and DNA quantification showed no significant reduction in marrow elements compared to the control group after the OCAs were treated with saline, ultrasound, or VV treatments; however, there was a significant reduction in marrow elements after LPL, HPL, and HSC treatments. Furthermore, HSC more effectively reduced the marrow elements of OCAs in the middle and deep zones compared with LPL (p

Abstract Osteoarthritis (OA) is a common degenerative disease worldwide and new therapeutics that target inflammation and the crosstalk between immunocytes and chondrocytes are being developed to prevent and treat OA. These attempts involve repolarizing pro-inflammatory M1 macrophages into the anti-inflammatory M2 phenotype in synovium. In this study, we found that phosphoglycerate mutase 5 (PGAM5) significantly increased in macrophages in OA synovium compared to controls based on histology of human samples and single-cell RNA sequencing results of mice models. To address the role of PGAM5 in macrophages in OA, we found conditional knockout of PGAM5 in macrophages greatly alleviated OA symptoms and promoted anabolic metabolism of chondrocytes in vitro and in vivo. Mechanistically, we found that PGAM5 enhanced M1 polarization via AKT-mTOR/p38/ERK pathways, whereas inhibited M2 polarization via STAT6-PPARγ pathway in murine bone marrow-derived macrophages. Furthermore, we found that PGAM5 directly dephosphorylated Dishevelled Segment Polarity Protein 2 (DVL2) which resulted in the inhibition of β-catenin and repolarization of M2 macrophages into M1 macrophages. Conditional knockout of both PGAM5 and β-catenin in macrophages significantly exacerbated osteoarthritis compared to PGAM5-deficient mice. Motivated by these findings, we successfully designed mannose modified fluoropolymers combined with siPGAM5 to inhibit PGAM5 specifically in synovial macrophages via intra-articular injection, which possessed desired targeting abilities of synovial macrophages and greatly attenuated murine osteoarthritis. Collectively, these findings defined a key role for PGAM5 in orchestrating macrophage polarization and provides insights into novel macrophage-targeted strategy for treating OA.

Aim: In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics. Methods: Transcriptome data, pathological images, and clinical data from 443 cases were retrieved from TCGA (The Cancer Genome Atlas Program) for survival analysis. The images were segmented using the Otsu algorithm, and features were extracted using the PyRadiomics package. Subsequently, the cases were randomly divided into a training cohort of 165 cases and a validation cohort of 69 cases. Features selected via minimum Redundancy - Maximum Relevance (mRMR)- recursive feature elimination (RFE) screening were used to train a model using the Gradient Boosting Machine (GBM) algorithm. The model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curves. Additionally, the correlation between the Pathomics score (PS) and immune genes was examined. Results: In the multivariate analysis, heightened infiltration of activated CD4 memory T cells was strongly associated with improved overall survival (HR = 0.505, 95 % CI = 0.342–0.745, P

Immune-related adverse events (irAEs) impact outcomes, with most research focusing on early prediction (baseline data), rather than near-term prediction (one cycle before the occurrence of irAEs and the current cycle). We aimed to explore the near-term predictive value of neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), absolute eosinophil count (AEC) for severe irAEs induced by PD-1 inhibitors. Data were collected from tumor patients treated with PD-1 inhibitors. NLR, PLR, and AEC data were obtained from both the previous and the current cycles of irAEs occurrence. A predictive model was developed using elastic net logistic regression Cutoff values were determined using Youden’s Index. The predicted results were compared with actual data using Bayesian survival analysis. A total of 138 patients were included, of whom 47 experienced grade 1–2 irAEs and 18 experienced grade 3–5 irAEs. The predictive model identified optimal α and λ through 10-fold cross-validation. The Shapiro-Wilk test, Kruskal-Wallis test and logistic regression showed that only current cycle data were meaningful. The NLR was statistically significant in predicting irAEs in the previous cycle. Both NLR and AEC were significant predictors of irAEs in the current cycle. The model achieved an area under the ROC curve (AUC) of 0.783, with a sensitivity of 77.8% and a specificity of 80.8%. A probability ≥ 0.1345 predicted severe irAEs. The model comprising NLR, AEC, and sex may predict the irAEs classification in the current cycle, offering a near-term predictive advantage over baseline models and potentially extending the duration of immunotherapy for patients.

Abstract Objective The purpose of the study is to construct meaningful nomogram models according to the independent prognostic factor for metastatic pancreatic cancer receiving chemotherapy. Methods This study is retrospective and consecutively included 143 patients from January 2013 to June 2021. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) is utilized to determine the optimal cut‐off value. The Kaplan–Meier survival analysis, univariate and multivariable Cox regression analysis are exploited to identify the correlation of inflammatory biomarkers and clinicopathological features with survival. R software are run to construct nomograms based on independent risk factors to visualize survival. Nomogram model is examined using calibration curve and decision curve analysis (DCA). Results The best cut‐off values of 966.71, 0.257, and 2.54 for the systemic immunological inflammation index (SII), monocyte‐to‐lymphocyte ratio (MLR), and neutrophil‐to‐lymphocyte ratio (NLR) were obtained by ROC analysis. Cox proportional‐hazards model revealed that baseline SII, history of drinking and metastasis sites were independent prognostic indices for survival. We established prognostic nomograms for primary endpoints of this study. The nomograms' predictive potential and clinical efficacy have been evaluated by calibration curves and DCA. Conclusion We constructed nomograms based on independent prognostic factors, these models have promising applications in clinical practice to assist clinicians in personalizing the management of patients.

Cell electrofusion is a key process in many research fields, such as genetics, immunology, and cross-breeding. The electrofusion efficiency is highly dependent on the buffer osmotic pressure properties. However, the mechanism by which the buffer osmotic pressure affects cell electrofusion has not been theoretically or numerically understood. In order to explore the mechanism, the microfluidic structure with paired arc micro-cavities was first evaluated based on the numerical analysis of the transmembrane potential and the electroporation induced on biological cells when the electrofusion was performed on this structure. Then, the numerical model was used to analyze the effect of three buffer osmotic pressures on the on-chip electrofusion in terms of membrane tension and cell size. Compared to hypertonic and isotonic buffers, hypotonic buffer not only increased the reversible electroporation area in the cell-cell contact zone by 1.7 times by inducing a higher membrane tension, but also significantly reduced the applied voltage required for cell electroporation by increasing the cell size. Finally, the microfluidic chip with arc micro-cavities was fabricated and tested for electrofusion of SP2/0 cells. The results showed that no cell fusion occurred in the hypertonic buffer. The fusion efficiency in the isotonic buffer was about 7%. In the hypotonic buffer, the fusion efficiency was about 60%, which was significantly higher compared to hypertonic and isotonic buffers. The experimental results were in good agreement with the numerical analysis results.

Abstract Chloroplasts play a vital role in plant growth and development, which are the main sites of photosynthesis and the production of hormones and metabolites. Despite their significance, the regulatory mechanisms governing chloroplast development remain unclear. In our investigation, we identified a rice mutant with defective chloroplasts in rice (Oryza sativa L.), named albino lethal 13 (osal13), which displayed a distinct albino phenotype in leaves, ultimately resulting in seedling lethality. Molecular cloning revealed that OsAL13 encodes a novel rice protein with no homologous gene or known conserved domain. This gene was located in the chloroplast and exhibited constitutive expression in various tissues, particularly in green tissues and regions of active cell growth. Our study's findings reveal that RNAi‐mediated knockdown of OsAL13 led to a pronounced albino phenotype, reduced chlorophyll and carotenoid contents, a vesicle chloroplast structure, and a decrease in the expression of chloroplast‐associated genes. Consequently, the pollen fertility and seed setting rate were lower compared with the wild type. In contrast, the overexpression of OsAL13 resulted in an increased photosynthetic rate, a higher total grain number per panicle, and enhanced levels of indole‐3‐acetic acid (IAA) in the roots and gibberellin A3 (GA3) in the shoot. These outcomes provide new insights on the role of OsAL13 in regulating chloroplast development in rice.

Effective ship detection in synthetic aperture radar (SAR) imagery is crucial for maritime safety and surveillance. Despite the advancements in deep learning for SAR ship detection, significant challenges remain, particularly in large scenes. These challenges are twofold: the detection of extremely small ships is often hindered by inadequate feature extraction, and the presence of inshore ships is obscured by pronounced land-based interference, both of which lead to reduced detection accuracy. To address these issues, we present a novel deep learning framework that integrates constant false alarm rate (CFAR) processing with dual-polarization data, termed the CFAR-guided dual-polarization fusion framework (CFAR-DP-FW). The integration is designed to enhance the detection sensitivity for small-scale maritime targets by utilizing dual-polarization's rich feature representation, and CFAR's strength in suppressing background noise, highlighting potential targets. The proposed CFAR-DP-FW consists of three core components: the CFAR dual-polarization detector provides initial target indication; the CFAR field generator constructs a probabilistic ship presence map, reducing reliance on CFAR's hard thresholds; and the CFAR guidance dual-polarization network incorporates a novel feature extractor and enhancement module, tailored to amplify relevant features, and suppress noise. This strategic fusion within our framework markedly improves the detection of small and inshore ships. Evaluated on the large-scale SAR ship detection dataset-v1.0, our framework demonstrates superior performance, surpassing 20 state-of-the-art models. It achieves a 3.28% increase in mean average precision for inshore ships over the next best-performing model, validating its efficacy in tackling the intricate challenges of large-scale SAR ship detection.

Abstract Background Immunotherapy targeting PD-1/PD-L1 has revolutionized the treatment of extensive-stage small cell lung cancer (ES-SCLC). However, clinical trials suggest differential efficacy of anti-PD-1 agents and anti-PD-L1 agents in first-line treatment of ES-SCLC. This retrospective multicenter study aimed to compare the efficacy and safety of anti-PD-1 agents versus anti-PD-L1 agents in first-line treatment of ES-SCLC in real-world practice. Methods Patients with pathologically or cytologically confirmed ES-SCLC treated with platinum plus etoposide combined with anti-PD-1 or PD-L1 agents as first-line treatment in different centers of PLA General Hospital between January 2017 and October 2021 were included for this study. Survival outcomes and safety were compared between patients receiving anti-PD-1 and PD-L1 agents. Results Of the total 154 included patients, 68 received anti-PD-1 agents plus chemotherapy (PD-1 group), and 86 received anti-PD-L1 agents plus chemotherapy (PD-L1 group). Progression-free survival (PFS) and overall survival (OS) in the entire cohort were 7.6 months (95% confidence interval [CI]: 6.5–8.2 months) and 17.4 months (95% CI: 15.3–19.3 months), respectively. Median PFS and OS were comparable between the PD-1 group and PD-L1 group (PFS: 7.6 months vs. 8.3 months, HR = 1.13, 95% CI: 0.79–1.62, p = 0.415; OS: 26.9 months vs. 25.6 months, HR = 0.96, 95% CI: 0.63–1.47, p = 0.859. The objective response rate and disease control rate were comparable between the two groups: 79.4% vs. 79.1% and 92.6% vs. 94.2%, respectively. The 6-month, 12-month, and 18-month PFS and OS rates were slightly higher in the PD-L1 group than in the PD-1 group, while the 24-month PFS rate was slightly higher in the PD-1 group than in the PD-L1 group. Stratified analysis showed that locoregional thoracic radiotherapy and normal lactate dehydrogenase level were independent predictors of better OS in ES-SCLC patients treated with first-line chemotherapy plus ICI. Adverse events were not significantly different between the two groups. Conclusions Anti-PD-1 agents and anti-PD-L1 agents combined with chemotherapy as first-line treatment for ES-SCLC are comparably effective and well tolerated.

Superwetting materials have drawn unprecedented attention in the treatment of oily wastewater due to their preferable anti-fouling property and selective oil/water separation. However, it is still a challenge to fabricate multifunctional and environmentally friendly materials, which can be stably applied to purify the actual complicated wastewater. Here, a Ag/α-Fe2O3 heterostructure anchored copper mesh was intentionally synthesized using a facile two-step hydrothermal method. The resultant mesh with superhydrophilicity and underwater superoleophobicity was capable of separating various oil/water mixtures with superior separation efficiency and high permeation flux driven by gravity. Benefiting from the joint effects of the smaller band gap of Ag/α-Fe2O3 heterojunction, inherent antibacterial capacity of α-Fe2O3 and Ag nanoparticles, favorable conductive substrate, as well as the hierarchical structure with superwettability, such mesh presented remarkably enhanced degradation capability toward organic dyes under visible light irradiation and antibacterial activity against both Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) compared with the pure α-Fe2O3 coated mesh. Impressively, the mesh exhibited bifunctional water purification performance, in which organic dyes were eliminated simultaneously from water during oil/water separation in one filtration process. More importantly, this mesh behaved exceptional chemical resistance, mechanical stability and long-term reusability. Therefore, this material with multifunctional integration may hold promising potential for steady water purification in practice.

Changes in olfactory function are considered to be early biomarkers of Parkinson’s disease. Olfactory dysfunction is one of the earliest non-motor features of Parkinson’s disease, appearing in about 90% of patients with early-stage Parkinson’s disease, and can often predate the diagnosis by years. Therefore, olfactory dysfunction should be considered a reliable marker of the disease. However, the mechanisms responsible for olfactory dysfunction are currently unknown. In this article, we clearly explain the pathology and medical definition of olfactory function as a biomarker for early-stage Parkinson’s disease. On the basis of the findings of clinical olfactory function tests and animal model experiments as well as neurotransmitter expression levels, we further characterize the relationship between olfactory dysfunction and neurodegenerative diseases as well as the molecular mechanisms underlying olfactory dysfunction in the pathology of early-stage Parkinson’s disease. The findings highlighted in this review suggest that olfactory dysfunction is an important biomarker for preclinical-stage Parkinson’s disease. Therefore, therapeutic drugs targeting non-motor symptoms such as olfactory dysfunction in the early stage of Parkinson’s disease may prevent or delay dopaminergic neurodegeneration and reduce motor symptoms, highlighting the potential of identifying effective targets for treating Parkinson’s disease by inhibiting the deterioration of olfactory dysfunction.

Abstract Objective We aimed to reveal the role of structural and functional alterations of cingulate gyrus in early cognitive impairment in Type 2 diabetes mellitus (T2DM) patients. Methods Fifty‐six T2DM patients and 60 healthy controls (HCs) underwent a neuropsychological assessment and sagittal three‐dimensional T1‐weighted and resting‐state functional MRI. Differences in the cortical thickness of the cingulate cortex and the functional connectivity (FC) of the nine subregions of the cingulate gyrus and the whole brain were compared between T2DM patients and HCs. Correlation analysis was performed between cortex thickness and FC and the participants' clinical/cognitive variables. Results The cortical thickness of the cingulate gyrus was not significantly different between T2DM patients and HCs. However, the T2DM patients showed significantly lower FC between the pregenual ACC (pACC) and the bilateral hippocampus, significantly higher FC between the pACC and bilateral lateral prefrontal cortex (LPFC) and left precentral gyrus, and significantly lower FC between the retrosplenial cortex (RSC) and right cerebellar Crus I. The FC between the pACC and the left hippocampus was negatively correlated with the FC between the pACC and LPFC (r = −0.306, p = 0.022). Interpretation The pACC and the RSC show dysfunctional connectivity before the appearance of structural abnormalities in T2DM patients. Abnormal FC of the pACC with the bilateral hippocampus and LPFC may imply a neural compensatory mechanism for memory function. These findings provide valuable information and new directions for possible interventions for the T2DM‐related cognitive impairment.

Abstract Previous research on global urban land expansion has primarily focused on accommodating the growing population without adequately considering the trade-offs between urban land and ecological services. Consequently, it is important to investigate the effect of this expansion on the ecological service system, while also examining the potential trade-offs between population growth and available urban land. Here, we quantify how different global land expansion options contribute to reconciling global population changes and to compliance with the UN Sustainable Development Goal 11 on sustainable cities and human settlements. Using an integrated framework for projecting global land consumption with the trade-off strategy between global land expansion and population under shared socioeconomic pathways (SSPs), we aim to bridge the knowledge gap in this area. The results of our study suggest that implementing a trade-off strategy between global land expansion and population growth can successfully reduce the levels of global land consumption in the future. Under the SSP1 scenario, for instance, our findings indicate that implementing trade-off policies can significantly reduce land consumption while increasing carbon sinks and protecting the global ecological service system. Specifically, converting land to forest or grassland can help decrease land consumption by 8.07% by the end of the 21st century. These insights can be valuable in designing land use policies that incorporate data-based solutions and address the challenges of sustainable urban development while also accommodating population growth.

Abstract Background Runt-related transcription factor-1 (RUNX1), a key member of the core-binding factor family of transcription factors, has emerged as a novel therapeutic target for cardiovascular disease. There is an urgent need to fully understand the expression pattern of Runx1 in the heart and the mechanisms by which it is controlled under normal conditions and in response to disease. The expression of Runx1 is regulated at the transcriptional level by two promoters designated P1 and P2. Alternative usage of these two promoters creates differential mRNA transcripts diversified in distribution and translational potential. While the significance of P1/P2 promoter-switch in the transcriptional control of Runx1 has been highlighted in the embryogenic process, very little is known about the level of P1- and P2-specific transcripts in adult hearts, and the underlying mechanisms controlling the promoter-switch. Methods To amplify P1/P2 specific sequences in the heart, we used two different sense primers complementary to either P1 or P2 5'-regions to monitor the expression of P1/P2 transcripts. DNA methylation levels were assessed at the Runx1 promoter regions. Rats were grouped by age. Results The expression levels of both P1- and P2-derived Runx1 transcripts were decreased in older rats when compared with that in young adults, paralleled with an age-dependent decline in Runx1 protein level. Furthermore, older rats demonstrated a higher degree of DNA methylation at Runx1 promoter regions. Alternative promoter usage was observed in hearts with increased age, as reflected by altered P1:P2 mRNA ratio. Conclusion Our data demonstrate that the expression of Runx1 in the heart is age-dependent and underscore the importance of gene methylation in the promoter-mediated transcriptional control of Runx1, thereby providing new insights to the role of epigenetic regulation in the heart.

Abstract Xylo-oligosaccharides (XOS) are considered as a promising type of prebiotics that can be used in foods, feeds, and healthcare products. Xylanases play a key role in the production of XOS from xylan. In this study, we conducted a metagenomic analysis of the fecal microbiota from dairy cows fed with different types of fodders. Despite the diversity in their diets, the main phyla observed in all fecal microbiota were Firmicutes and Bacteroidetes. At the genus level, one group of dairy cows that were fed probiotic fermented herbal mixture-containing fodders displayed decreased abundance of Methanobrevibacter and increased growth of beneficial Akkermansia bacteria. Additionally, this group exhibited a high microbial richness and diversity. Through our analysis, we obtained a comprehensive dataset comprising over 280,000 carbohydrate-active enzyme genes. Among these, we identified a total of 163 potential xylanase genes and subsequently expressed 34 of them in Escherichia coli. Out of the 34 expressed genes, two alkaline xylanases with excellent temperature stability and pH tolerance were obtained. Notably, CDW-xyl-8 exhibited xylanase activity of 96.1 ± 7.5 U/mg protein, with an optimal working temperature of 55 ℃ and optimal pH of 8.0. CDW-xyl-16 displayed an activity of 427.3 ± 9.1 U/mg protein with an optimal pH of 8.5 and an optimal temperature at 40 ℃. Bioinformatic analyses and structural modeling suggest that CDW-xyl-8 belongs to GH10 family xylanase, and CDW-xyl-16 is a GH11 family xylanase. Both enzymes have the ability to hydrolyze beechwood xylan and produce XOS. In conclusion, this metagenomic study provides valuable insights into the fecal microbiota composition of dairy cows fed different fodder types, revealing main microbial groups and demonstrating the abundance of xylanases. Furthermore, the characterization of two novel xylanases highlights their potential application in XOS production.

This study presents a theoretical investigation into the voltammetric behavior of bipolar interfacial nanopores due to the effect of potential scan rate (1–1000 V/s). Finite element method (FEM) is utilized to explore the current–voltage (I–V) properties of bipolar interfacial nanopores at different bulk salt concentrations. The results demonstrate a strong impact of the scan rate on the I–V response of bipolar interfacial nanopores, particularly at relatively low concentrations. Hysteresis loops are observed in bipolar interfacial nanopores under specific scan rates and potential ranges and divided by a cross-point potential that remains unaffected by the scan rate employed. This indicates that the current in bipolar interfacial nanopores is not just reliant on the bias potential that is imposed but also on the previous conditions within the nanopore, exhibiting history-dependent or memory effects. This scan-rate-dependent current–voltage response is found to be significantly influenced by the length of the nanopore (membrane thickness). Thicker membranes exhibit a more pronounced scan-rate-dependent phenomenon, as the mass transfer of ionic species is slower relative to the potential scan rate. Additionally, unlike conventional bipolar nanopores, the ion current passing through bipolar interfacial nanopores is minimally affected by the membrane thickness, making it easier to detect.

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of liver disease worldwide. Nonalcoholic steatohepatitis (NASH) is an advanced form of NAFLD. The livers of patients with NASH are more likely to develop fibrosis. Xiaoyao San (XYS) is a classic traditional Chinese medicine (TCM) formula that has been widely used in treating liver diseases. In this study, we elucidated the effects and mechanism of XYS in treating NASH-related liver fibrosis by combining high-throughput sequencing-based high-throughput screening with network pharmacology analysis. Our work revealed that XYS may play a role in preventing NASH-related liver fibrosis by regulating biological functions related to the extracellular matrix (ECM), inflammation, and metabolism. Additionally, Bupleuri Radix, Poria, Zingiberis Rhizoma Recens, and Paeoniae Radix Alba are the key herbs of XYS that could partially represent the functions of XYS. These regulatory effects are mediated by targeting signal transducer and activator of transcription 3 (STAT3), nuclear factor kappa B (NFκB), and peroxisome proliferator-activated receptor gamma (PPARγ) signaling. Narcissin, casuarictin, and γ-sitosterol were identified as representative active compounds in XYS targeting STAT3, NFκB, and PPARγ, respectively. Taken together, our findings provide a novel strategy for investigating the pharmacological effects and biological mechanisms of a TCM formula.

This study focused on improving the flavor quality of seasonings, and enzymatic hydrolysis of soybean protein isolate (SPI) seasoning via traditional technology may lead to undesirable flavors. Herein, we aimed to develop a new type of SPI seasoning through microbial fermentation to improve its flavor quality. The effect of Corynebacterium glutamicum fermentation on the flavoring compounds of seasonings in SPI enzymatic hydrolysate was examined. Sensory evaluation showed that the SPI seasoning had mainly aromatic and roasted flavor, and the response signals of S18 (aromatic compounds), S24 (alcohols and aldehydes), and S25 (esters and ketones) sensors of the electronic nose differed significantly. Overall, 91 volatile compounds were identified via gas chromatography–mass spectrometry. SPI seasonings contained a higher number of alcohols, ketones, aromatics, and heterocyclic compounds than traditional seasonings, which had stronger cheese, fatty, and roasted aromas. According to the relative odor activity value (ROAV) analysis, n-pentylpyrzine, 2,6-dimethylpyrazine, and tetramethylpyrazine are the key flavoring compounds (ROAV ≥ 1) of SPI seasoning, which may impart a unique roasted and meaty aroma. Therefore, the fermentation of SPI enzymatic hydrolysate with C. glutamicum may improve the flavor quality of its products, providing a new method for the development and production of new seasoning products.

Defatted cottonseed meal (DCSM), a byproduct of the cotton industry, is highly regarded for its high protein content, making it a source of nutrients in animal feed. Traditional physical and chemical treatments of DCSM can lead to a reduction in nutrient content and the presence of residual organic solvents. Probiotic fermentation of DCSM offers several advantages, including degradation of anti-nutritional factors, an increase in nutrient content, and production of beneficial metabolites. This study employed probiotic fermentation of DCSM using a probiotic microbe collection composed of Saccharomyces cerevisiae, Enterococcus faecium, and Lactiplantibacillus plantarum. This fermentation process significantly enhanced the nutritional quality of DCSM. Specifically, the contents of crude protein, free amino acid, total phosphorus, and moisture increased by 1.14-fold, 1.14-fold, 1.24-fold, and 3-fold, respectively. In the meanwhile, there was a substantial reduction in the content of dry matter, crude ash, and crude fat, with decreases of 27.83%, 25.74%, and 88.23%, respectively. Probiotic fermentation of DCSM resulted in an overall enhancement of the palatability of DCSM. This study provides valuable insights into the potential of mixed probiotic fermentation as a promising approach for improving the nutritional quality of DCSM.

In mammals, 17-beta hydroxysteroid dehydrogenase 2 (Hsd17b2) enzyme specifically catalyzes the oxidation of the C17 hydroxyl group and efficiently regulates the activities of estrogens and androgens to prevent diseases induced by hormone disorders. However, the functions of the hsd17b2 gene involved in animal sex differentiation are still largely unclear. The ricefield eel (Monopterus albus), a protogynous hermaphroditic fish with a small genome size (2n = 24), is usually used as an ideal model to study the mechanism of sex differentiation in vertebrates. Therefore, in this study, hsd17b2 gene cDNA was cloned and its mRNA expression profiles were determined in the ricefield eel. The cloned cDNA fragment of hsd17b2 was 1230 bp, including an open reading frame of 1107 bp, encoding 368 amino acid residues with conserved catalytic subunits. Moreover, real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) analysis showed that hsd17b2 mRNA expressed strongly in the ovaries at early developmental stages, weakly in liver and intestine, and barely in testis and other tissues. In particular, hsd17b2 mRNA expression was found to peak in ovaries of young fish and ovotestis at the early stage, and eventually declined in gonads from the late ovotestis to testis. Likewise, chemical in situ hybridization results indicated that the hsd17b2 mRNA signals were primarily detected in the cytoplasm of oogonia and oocytes at stage I–II, subsequently concentrated in the granulosa cells around the oocytes at stage Ⅲ–Ⅳ, but undetectable in mature oocytes and male germ cells. Intriguingly, in ricefield eel ovaries, hsd17b2 mRNA expression could be significantly reduced by 17β-estradiol (E2) or tamoxifen (17β-estradiol inhibitor, E2I) induction at a low concentration (10 ng/mL) and increased by E2I induction at a high concentration (100 ng/mL). On the other hand, both the melatonin (MT) and flutamide (androgen inhibitor, AI) induction could significantly decrease hsd17b2 mRNA expression in the ovary of ricefield eel. This study provides a clue for demonstrating the mechanism of sexual differentiation in fish. The findings of our study imply that the hsd17b2 gene could be a key regulator in sexual differentiation and modulate sex reversal in the ricefield eel and other hermaphroditic fishes.

IntroductionLife’s Essential 8 (LE8) is prompted by the American Heart Association (AHA) to assess cardiovascular health. The association between LE8 and cognitive function in America is unknown. Our study was to investigate the association of LE8 with cognitive function in general adults.Materials and methodsA total of 2,301 participants were enrolled in the National Health and Nutrition Examination Surveys (NHANES). LE8 scores (range 0–100) were obtained from measurements based on American Heart Association definitions, divided into health behavior and health factor scores. Cognitive function was assessed by three tests including the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), Animal fluency test (AFT), and Digit Symbol Substitution test (DSST). The multivariable linear regression analysis explored the associations between LE8 and cognitive function. Smooth curve fitting was explored using restricted cubic splines. The inflection point was determined by the two-piecewise linear regression.ResultsIn the multivariable linear regression model with full adjustment for confounding variables, AFT scores were 1.2 points higher in participants with LE8 scores >80 than in those with LE8 scores

ABSTRACTStaphylococcus aureus (S. aureus) is a leading cause of bacteremia and blood stream infections. Methicillin-resistant S. aureus (MRSA) that first appeared in 1961 often caused hospital-acquired infections (HAIs) and community-acquired infections (CAIs) and was associated with high mortality rate. Accurate and rapid point-of-care testing (POCT) of MRSA is crucial for clinical management and treatment of MRSA infections, as well as the prevention and control of HAIs and CAIs. Here, we reported a novel extraction-free dual HiFi-LAMP assay for discriminative detection of methicillin-susceptible S. aureus and MRSA. The dual HiFi-LAMP assay can detect 30 copies/reaction of nuc and mecA genes with detection limits of 147 and 158 copies per 25 µL reaction, respectively. A retrospective clinical evaluation with 107 clinical S. aureus isolates showed both sensitivity and specificity of 100%. A prospective clinical evaluation with 35 clinical samples revealed a specificity of 100% and a sensitivity of 92.3%. The dual HiFi-LAMP assay can detect almost all S. aureus samples (141/142; 99.3%) within 20 min, implying that the entire HiFi-LAMP assay (including sample process) can be completed within 40 min, extremely significantly shorter than 3–5 days by the traditional clinical microbial culture and antibiotic susceptibility testing. The novel extraction-free dual HiFi-LAMP assay can be used as a robust POCT tool to promote precise diagnosis and treatment of MRSA infections in hospitals and to facilitate surveillance of MRSA at hospital and community settings.IMPORTANCEMethicillin-resistant Staphylococcus aureus (MRSA) was associated with high mortality rate and listed as a “priority pathogen” by the World Health Organization. Accurate and rapid point-of-care testing (POCT) of MRSA is critically required for clinical management and treatment of MRSA infections. Some previous LAMP-based POCT assays for MRSA might be questionable due to their low specificity and the lack of appropriate evaluation directly using clinical samples. Furthermore, they are relatively tedious and time-consuming because they require DNA extraction and lack multiplex detection capacity. Here, we reported a novel extraction-free dual HiFi-LAMP assay for discriminative detection of MRSA and methicillin-susceptible S. aureus. The assay has high specificity and sensitivity and can be completed within 40 min. Clinical evaluation with real clinical samples and clinical isolates showed excellent performance with 100% specificity and 92.3%–100% sensitivity. The novel extraction-free assay may be a robust POCT tool to promote precise diagnosis of MRSA infections and facilitate surveillance of MRSA at hospital and community settings.

Electrocatalytic CO2 reduction (ECR) to high-value fuels and chemicals offers a promising conversion technology for achieving sustainable carbon cycles. In recent years, although great efforts have been made to develop high-efficiency ECR catalysts, challenges remain in achieving high activity and long durability simultaneously. Taking advantage of the adjustable structure, tunable component, and the M–Ch (M ​= ​Sn, In, Bi, etc., Ch ​= ​S, Se, Te) covalent bonds stabilized metal centers, the p-block metal chalcogenides (PMC) based electrocatalysts have shown great potential in converting CO2 into CO or formates. In addition, the unique p-block electron structure can suppress the competitive hydrogen evolution reaction and enhance the adsorption of ECR intermediates. Seeking to systematically understand the structure–activity relationship of PMC-based ECR catalysts, this review summarizes the recent advances in designing PMC electrocatalysts for CO2 reduction based on the fundamental aspects of heterogeneous ECR process, including advanced strategies for optimizing the intrinsic activity and improving the loading density of catalytic sites, constructing highly stable catalysts, and tuning product selectivities. Subsequently, we outline the challenges and perspectives on developing high-performance PMC ECR catalysts for practical applications.

PurposeThe objective of this study was to conduct a meta-analysis comparing the diagnostic efficacy of models based on diffusion-weighted imaging (DWI)-MRI, dynamic contrast enhancement (DCE)-MRI, and combination models (DCE and DWI) in distinguishing benign from malignant non-mass enhancement (NME) breast lesions.Materials and methodsPubMed, Embase, and Cochrane Library were searched, from inception to January 30, 2023, for studies that used DCE or DWI-MRI for the prediction of NME breast cancer patients. A bivariate random-effects model was used to calculate the meta-analytic sensitivity, specificity, and area under the curve (AUC) of the DCE, DWI, and combination models. Subgroup analysis and meta-regression analysis were performed to find the source of heterogeneity.ResultsOf the 838 articles screened, 18 were eligible for analysis (13 on DCE, five on DWI, and four studies reporting the diagnostic accuracy of both DCE and DWI). The funnel plot showed no publication bias (p > 0.5). The pooled sensitivity and specificity and the AUC of the DCE, DWI, and combination models were 0.58, 0.72, and 0.70, respectively; 0.84, 0.69, and 0.84, respectively; and 0.88, 0.79, 0.90, respectively. The meta-analysis found no evidence of a threshold effect and significant heterogeneity among trials in terms of DCE sensitivity and specificity, as well as DWI specificity alone (I2 > 75%). The meta-regression revealed that different diagnostic criteria contributed to the DCE study’s heterogeneity (p < 0.05). Different reference criteria significantly influenced the heterogeneity of the DWI model (p < 0.05). Subgroup analysis revealed that clustered ring enhancement (CRE) had the highest pooled specificity (0.92) among other DCE features. The apparent diffusion coefficient (ADC) with a mean threshold

Summary: The interactions between human and natural systems and their effects have unforeseen results, particularly in the management of water resources. Using water stress mitigation as an example, a water resources management effect index (WRMEI) was created to quantitatively evaluate the trends of water management effects. This revealed that the WRMEI was decreasing due to the impact of the water resources management process. The findings demonstrate that water resources management has unintended effects: there was a gap between the expectation of water stress to be mitigated and the actual results of water stress increasing. That is caused by human activities in water utilization: (1) increasing available water resources from water transfer was not utilized sparingly in the receiving cities—increased water transfers from external sources increase domestic water consumption per capita; (2) improving water efficiency has a positive effect on mitigating water stress, but the population growth decreased the efficiency. It was concluded that much greater attention needs to be paid to water conservation in residential and living use to counter these unintended water management effects.

BackgroundThis study aimed to identify disruptions in white matter integrity in type 2 diabetes mellitus (T2DM) patients by utilizing the white matter tract integrity (WMTI) model, which describes compartment-specific diffusivities in the intra- and extra-axonal spaces, and to investigate the relationship between WMTI metrics and clinical and cognitive measurements.MethodsA total of 73 patients with T2DM and 57 healthy controls (HCs) matched for age, sex, and education level were enrolled and underwent diffusional kurtosis imaging and cognitive assessments. Tract-based spatial statistics (TBSS) and atlas-based region of interest (ROI) analysis were performed to compare group differences in diffusional metrics, including fractional anisotropy (FA), mean diffusivity (MD), axonal water fraction (AWF), intra-axonal diffusivity (Daxon), axial extra-axonal space diffusivity (De,//), and radial extra-axonal space diffusivity (De,⊥) in multiple white matter (WM) regions. Relationships between diffusional metrics and clinical and cognitive functions were characterized.ResultsIn the TBSS analysis, the T2DM group exhibited decreased FA and AWF and increased MD, De,∥, and De,⊥ in widespread WM regions in comparison with the HC group, which involved 56.28%, 32.07%, 73.77%, 50.47%, and 75.96% of the mean WM skeleton, respectively (P < 0.05, TFCE-corrected). De,⊥ detected most of the WM changes, which were mainly located in the corpus callosum, internal capsule, external capsule, corona radiata, posterior thalamic radiations, sagittal stratum, cingulum (cingulate gyrus), fornix (stria terminalis), superior longitudinal fasciculus, and uniform fasciculus. Additionally, De,⊥ in the genu of the corpus callosum was significantly correlated with worse performance in TMT-A (β = 0.433, P < 0.001) and a longer disease duration (β = 0.438, P < 0.001).ConclusionsWMTI is more sensitive than diffusion tensor imaging in detecting T2DM-related WM microstructure abnormalities and can provide novel insights into the possible pathological changes underlying WM degeneration in T2DM. De,⊥ could be a potential imaging marker in monitoring disease progression in the brain and early intervention treatment for the cognitive impairment in T2DM.

Objective: Our preliminary research indicates that acacetin modulates the nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain containing 3 (NLRP3) inflammasome, providing protection against Alzheimer’s Disease (AD) and cerebral ischemic reperfusion injury. The mechanisms of acacetin to inhibit the activation of the NLRP3 inflammasome remain fully elucidated. This study aims to investigate the effects and potential mechanisms of acacetin on various agonists induced NLRP3 inflammasome activation.Methods: A model for the NLRP3 inflammasome activation was established in mouse bone marrow-derived macrophages (BMDMs) using Monosodium Urate (MSU), Nigericin, Adenosine Triphosphate (ATP), and Pam3CSK4, separately. Western blot analysis (WB) was employed to detect Pro-caspase-1, Pro-Interleukin-1β (Pro-IL-1β) in cell lysates, and caspase-1, IL-1β in supernatants. Enzyme-Linked Immunosorbent Assay (ELISA) was used to measured the release of IL-1β, IL-18, and Tumor Necrosis Factor-alpha (TNF-α) in cell supernatants to assess the impact of acacetin on NLRP3 inflammasome activation. The lactate dehydrogenase (LDH) release was also assessed. The Nuclear Factor Kappa B (NF-κB) and Mitogen-Activated Protein Kinase (MAPK) signaling pathways related proteins were evaluated by WB, and NF-κB nuclear translocation was observed via laser scanning confocal microscopy (LSCM). Disuccinimidyl Suberate (DSS) cross-linking was employed to detect oligomerization of Apoptosis-associated Speck-like protein containing a Caspase Recruitment Domain (ASC), and LSCM was also used to observe Reactive Oxygen Species (ROS) production. Inductively Coupled Plasma (ICP) and N-(6-methoxyquinolyl) acetoethyl ester (MQAE) assays were utilized to determined the effects of acacetin on the efflux of potassium (K+) and chloride (Cl-) ions.Results: Acacetin inhibited NLRP3 inflammasome activation induced by various agonists, reducing the release of TNF-α, IL-1β, IL-18, and LDH. It suppressed the expression of Lipopolysaccharides (LPS)-activated Phosphorylated ERK (p-ERK), p-JNK, and p-p38, inhibited NF-κB p65 phosphorylation and nuclear translocation. Acacetin also reduced ROS production and inhibited ASC aggregation, thus suppressing NLRP3 inflammasome activation. Notably, acacetin did not affect K+ and Cl-ions efflux during the activation process.Conclusion: Acacetin shows inhibitory effects on both the priming and assembly processes of the NLRP3 inflammasome, positioning it as a promising new candidate for the treatment of NLRP3 inflammasome-related diseases.

This study aims to address the unreasonable assignment of positive and negative samples and poor localization quality in ship detection in complex scenes. Therefore, in this study, a Synthetic Aperture Radar (SAR) ship detection network (A3-IOUS-Net) based on adaptive anchor assignment and Intersection over Union (IOU) supervise in complex scenes is proposed. First, an adaptive anchor assignment mechanism is proposed, where a probability distribution model is established to adaptively assign anchors as positive and negative samples to enhance the ship samples’ learning ability in complex scenes. Then, an IOU supervise mechanism is proposed, which adds an IOU prediction branch in the prediction head to supervise the localization quality of detection boxes, allowing the network to accurately locate the SAR ship targets in complex scenes. Furthermore, a coordinate attention module is introduced into the prediction branch to suppress the background clutter interference and improve the SAR ship detection accuracy. The experimental results on the open SAR Ship Detection Dataset (SSDD) show that the Average Precision (AP) of A3-IOUS-Net in complex scenes is 82.04%, superior to the other 15 comparison models.

Abstract Background Quantifying cell-type abundance in bulk tissue RNA-sequencing enables researchers to better understand complex systems. Newer deconvolution methodologies, such as MuSiC, use cell-type signatures derived from single-cell RNA-sequencing (scRNA-seq) data to make these calculations. Single-nuclei RNA-sequencing (snRNA-seq) reference data can be used instead of scRNA-seq data for tissues such as human brain where single-cell data are difficult to obtain, but accuracy suffers due to sequencing differences between the technologies. Results We propose a modification to MuSiC entitled ‘DeTREM’ which compensates for sequencing differences between the cell-type signature and bulk RNA-seq datasets in order to better predict cell-type fractions. We show DeTREM to be more accurate than MuSiC in simulated and real human brain bulk RNA-sequencing datasets with various cell-type abundance estimates. We also compare DeTREM to SCDC and CIBERSORTx, two recent deconvolution methods that use scRNA-seq cell-type signatures. We find that they perform well in simulated data but produce less accurate results than DeTREM when used to deconvolute human brain data. Conclusion DeTREM improves the deconvolution accuracy of MuSiC and outperforms other deconvolution methods when applied to snRNA-seq data. DeTREM enables accurate cell-type deconvolution in situations where scRNA-seq data are not available. This modification improves characterization cell-type specific effects in brain tissue and identification of cell-type abundance differences under various conditions.