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Abstract Despite an alarming increase in the prevalence of hypertension among Chinese young adults, longitudinal studies investigating factors that affect the maintenance of normal blood pressure (BP) in this population are lacking. Our study aimed to address this knowledge gap. A total of 7100 participants from the Kailuan Study who had normal BP and were aged

Abstract Background Glioma is a lethal brain cancer and lacking effective therapies. Challenges include no effective therapeutic target, intra- and intertumoral heterogeneity, inadequate effective drugs, and an immunosuppressive microenvironment, etc. Deciphering the pathogenesis of gliomas and finding out the working mechanisms are urgent and necessary for glioma treatment. Identification of prognostic biomarkers and targeting the biomarker genes will be a promising therapy. Methods From our RNA-sequencing data of the oxidative phosphorylation (OXPHOS)-inhibition sensitive and OXPHOS-resistant cell lines, we found that the scaffolding protein caveolin 1 (CAV1) is highly expressed in the resistant group but not in the sensitive group. By comprehensive analysis of our RNA sequencing data, Whole Genome Bisulfite Sequencing (WGBS) data and public databases, we found that CAV1 is highly expressed in gliomas and its expression is positively related with pathological processes, higher CAV1 predicts shorter overall survival. Results Further analysis indicated that (1) the differentiated genes in CAV1-high groups are enriched in immune infiltration and immune response; (2) CAV1 is positively correlated with tumor metastasis markers; (3) the methylation level of CAV1 promoters in glioma group is lower in higher stage than that in lower stage; (4) CAV1 is positively correlated with glioma stemness; (5) higher expression of CAV1 renders the glioma cells’ resistant to oxidative phosphorylation inhibitors. Conclusion Therefore, we identified a key gene CAV1 and deciphered its function in glioma progression and prognosis, proposing that CAV1 may be a therapeutic target for gliomas. Graphical Abstract

Abstract The transcription factor MYCN is frequently amplified and overexpressed in a variety of cancers including high-risk neuroblastoma (NB) and promotes tumor cell proliferation, survival, and migration. Therefore, MYCN is being pursued as an attractive therapeutic target for selective inhibition of its upstream regulators because MYCN is considered a “undruggable” target. Thus, it is important to explore the upstream regulators for the transcription and post-translational modification of MYCN. Here, we report that BRCA1-associated protein-1 (BAP1) promotes deubiquitination and subsequent stabilization of MYCN by directly binding to MYCN protein. Furthermore, BAP1 knockdown inhibits NB tumor cells growth and migration in vitro and in vivo, which can be rescued partially by ectopic expression of MYCN. Importantly, depletion of BAP1 confers cellular resistance to bromodomain and extraterminal (BET) protein inhibitor JQ1 and Aurora A kinase inhibitor Alisertib. Furthermore, IHC results of NB tissue array confirmed the positive correlation between BAP1 and MYCN protein. Altogether, our work not only uncovers an oncogenic function of BAP1 by stabilizing MYCN, but also reveals a critical mechanism for the post-translational regulation of MYCN in NB. Our findings further indicate that BAP1 could be a potential therapeutic target for MYCN-amplified neuroblastoma.

Lithic artifacts are crucial for elucidation of the temporal and spatial patterns of prehistoric human occupation of the Tibetan Plateau. Core-and-flake technology is particularly noteworthy, as it is distinguished by its broad temporal span and widespread distribution across the plateau. In this study, we present the results of a reassessment of the lithic assemblage from the Su-re site in Tingri County, Shigatse City, Xizang Autonomous Region, China. Its resemblance to lithic assemblages from Southwestern China implies a close relationship between the plateau and its southeastern vicinity, contributing to the diversification of technology and prehistoric humans on the Tibetan Plateau. Moreover, gneissic pebbles transported by glacial meltwater in the Tingri Graben—the most suitable raw material available in the vicinity—explains the presence of prehistoric humans in the inhospitable Qomolangma region.

Abstract Background Cuproptosis is a regulated cell death form associated with tumor progression, clinical outcomes, and immune response. However, the role of cuproptosis in pancreatic adenocarcinoma (PAAD) remains unclear. This study aims to investigate the implications of cuproptosis-related genes (CRGs) in PAAD by integrated bioinformatic methods and clinical validation. Methods Gene expression data and clinical information were downloaded from UCSC Xena platform. We analyzed the expression, mutation, methylation, and correlations of CRGs in PAAD. Then, based on the expression profiles of CRGs, patients were divided into 3 groups by consensus clustering algorithm. Dihydrolipoamide acetyltransferase (DLAT) was chosen for further exploration, including prognostic analysis, co-expression analysis, functional enrichment analysis, and immune landscape analysis. The DLAT-based risk model was established by Cox and LASSO regression analysis in the training cohort, and then verified in the validation cohort. Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays were performed to examine the expression levels of DLAT in vitro and in vivo, respectively. Results Most CRGs were highly expressed in PAAD. Among these genes, increased DLAT could serve as an independent risk factor for survival. Co-expression network and functional enrichment analysis indicated that DLAT was engaged in multiple tumor-related pathways. Moreover, DLAT expression was positively correlated with diverse immunological characteristics, such as immune cell infiltration, cancer-immunity cycle, immunotherapy-predicted pathways, and inhibitory immune checkpoints. Submap analysis demonstrated that DLAT-high patients were more responsive to immunotherapeutic agents. Notably, the DLAT-based risk score model possessed high accuracy in predicting prognosis. Finally, the upregulated expression of DLAT was verified by RT-qPCR and IHC assays. Conclusions We developed a DLAT-based model to predict patients’ clinical outcomes and demonstrated that DLAT was a promising prognostic and immunological biomarker in PAAD, thereby providing a new possibility for tumor therapy.

High-cadence, multiwavelength observations have continuously revealed the diversity of tidal disruption events (TDEs), thus greatly advancing our knowledge and understanding of TDEs. In this work, we conducted an intensive optical-UV and X-ray follow-up campaign of TDE AT 2023lli and found a remarkable month-long bump in its UV/optical light curve nearly 2 months prior to maximum brightness. The bump represents the longest separation time from the main peak among known TDEs to date. The main UV/optical outburst declines as t ^−4.10 , making it one of the fastest-decaying optically selected TDEs. Furthermore, we detected sporadic X-ray emission 30 days after the UV/optical peak, accompanied by a reduction in the period of inactivity. It is proposed that the UV/optical bump could be caused by the self-intersection of the stream debris, whereas the primary peak is generated by the reprocessed emission of the accretion process. In addition, our results suggest that episodic X-ray radiation during the initial phase of decline may be due to the patched obscurer surrounding the accretion disk, a phenomenon associated with the inhomogeneous reprocessing process. The double TDE scenario, in which two stars are disrupted in sequence, is also a possible explanation for producing the observed early bump and main peak. We anticipate that the multicolor light curves of TDEs, especially in the very early stages, and the underlying physics can be better understood in the near future with the assistance of dedicated surveys such as the deep high-cadence survey of the 2.5 m Wide Field Survey Telescope.

Cognitive impairment is a common complication of type 2 diabetes mellitus (T2DM), and early cognitive dysfunction may be associated with abnormal changes in the cerebral cortex. This retrospective study aimed to investigate the cortical thickness-based structural topological network changes in T2DM patients without mild cognitive impairment (MCI). Fifty-six T2DM patients and 59 healthy controls underwent neuropsychological assessments and sagittal 3-dimensional T1-weighted structural magnetic resonance imaging. Then, we combined cortical thickness-based assessments with graph theoretical analysis to explore the abnormalities in structural covariance networks in T2DM patients. Correlation analyses were performed to investigate the relationship between the altered topological parameters and cognitive/clinical variables. T2DM patients exhibited significantly lower clustering coefficient (C) and local efficiency (Elocal) values and showed nodal property disorders in the occipital cortical, inferior temporal, and inferior frontal regions, the precuneus, and the precentral and insular gyri. Moreover, the structural topological network changes in multiple nodes were correlated with the findings of neuropsychological tests in T2DM patients. Thus, while T2DM patients without MCI showed a relatively normal global network, the local topological organization of the structural network was disordered. Moreover, the impaired ventral visual pathway may be involved in the neural mechanism of visual cognitive impairment in T2DM patients. This study enriched the characteristics of gray matter structure changes in early cognitive dysfunction in T2DM patients.

Ecological products and ecosystem services are essential for human survival and development. Gross Ecosystem Product (GEP) is a method to combine the value of ecosystem services and can reflect the status of ecosystem and ecological conservation and restoration performance. The conservation and restoration of desert ecosystems play an important role in expanding global cultivated land, ensuring food security, and improving human wellbeing. However, ecosystem services and the value of GEP in deserts have been neglected. Taking the Kubuqi Desert ecosystem as an example, this study evaluated the pattens, GEP value, and its change in the Kubuqi Desert ecosystem from 2000 to 2020. Our study found that 1) over the past 20 years, the areas of wetlands, forests, grasslands, and shrubs in the Kubuqi desert ecosystem had increased by 100.65%, 6.05%, 2.24%, and 2.03%, respectively, while that of desert had decreased by 10.62%; 2) the GEP of Kubuqi in 2020 was 55.48 billion CNY, among which its sandstorm prevention value was the highest (39.39%); 3) The value of ecosystem services in the Kubuqi desert ecosystem were all increased over the 20-year period and the largest increase came from sandstorm prevention (increased by 195.09%). This study emphasizes how GEP accounting can promote desert conservation and restoration, quantifies the contribution of desert ecosystems to human wellbeing, and provides future GEP accounting suggestions for desert ecosystems. This study can provide scientific information on the conservation and restoration of global desert ecosystems.

Deep neural networks (DNNs) have been effective in classifying structural magnetic resonance imaging (sMRI) images for Alzheimer's disease (AD) diagnosis. In this study, we propose a novel two-phase slice-to-volume feature representation (SVFR) framework for AD diagnosis. Specifically, we design a slice-level feature extractor to automatically select informative slice images and extract their slice-level features, by combining DNN and clustering models. Furthermore, we propose a joint volume-level feature generator and classifier to hierarchically aggregate the slice-level features into volume-level features and to classify images, by devising a spatial pyramid set pooling module and a fusion module. Experimental results demonstrate the superior performance of the proposed SVFR, surpassing the majority of the state-of-the-art methods and achieving comparable results to the best-performing approach. Experimental results also showcase the efficacy of the slice-level feature extractor in the selection of informative slice images, as well as the effectiveness of the volume-level feature generator and classifier in the integration of slice-level features for image classification. The source code for this study is publicly available at https://github.com/gll89/SVFR.

BackgroundSeveral functional magnetic resonance imaging (fMRI) investigations of patients with vestibular migraine (VM) have revealed abnormal functionality in different networks, indicating that VM is related to alterations in brain function. We sought to investigate the resting-state functional connectivity (FC) patterns during the interictal period in VM by combining data-driven voxel-wise degree centrality (DC) calculations and seed-based FC analyses, and thereby determine the associations between cerebral function and clinical symptoms.MethodsThirty-eight patients with VM and 33 matched normal controls were recruited. DC was calculated and compared between the groups, and the FC of locations showing DC alterations was further tested using a seed-based technique. The participants’ clinical indicators were correlated with the DC and FC values of the brain areas.ResultsIn contrast to the control group, the VM group showed considerably lower DC values in the bilateral medial prefrontal cortex (mPFC) and significantly higher DC values in the right occipital lobe. In the seed-based FC analyses, patients with VM demonstrated fewer connections of the bilateral mPFC with the bilateral posterior cingulate cortex, right parahippocampus, right cerebellar posterior lobe, bilateral cuneus, and left precuneus. In addition, clinical data from patients, such as pain intensity, episode frequency, and the Dizziness Handicap Inventory score, were negatively related to these FC and DC impairments.ConclusionOur findings showed changes in the default mode network and visual cortex in patients with VM, providing further insights into the complexity of the mechanisms underlying VM.

Background and objectiveQuantitative changes in retinal microvasculature are associated with subclinical cardiac alterations and clinical cardiovascular diseases (i.e., heart failure and coronary artery disease). Nonetheless, very little is known about the retinal vascular and structural changes in patients with atrial fibrillation (AF). Our study aims to characterize the microvasculature and structure of the retina in AF patients and explore their differences in different types of AF (paroxysmal and sustained AF).MethodsThis cross-sectional study was conducted at the Departments of Neurology and Cardiology in West China Hospital, Chengdu, China. Individuals aged 40 years or older with a diagnosis of AF were eligible for inclusion and underwent an evaluation and diagnosis confirmation before enrollment. Control individuals aged 40 years or older and without a history of AF, ocular abnormalities/disease, or any significant systemic illness were recruited. The retinal vascular and structural parameters were assessed using swept-source optical coherence tomography (SS-OCT)/SS-OCT angiography. Echocardiographic data of left atrium (LA) diameter were collected in patients with AF at the time of inclusion.ResultsA total of 242 eyes of 125 participants [71 men (56.8%); mean (SD) age, 61.98 (8.73) years] with AF and 219 eyes of 111 control participants [53 men (47.7%); mean (SD) age, 62.31 (6.47) years] were analyzed. In our AF cohort, 71 patients with paroxysmal AF and 54 patients with sustained AF (i.e., persistent/permanent AF) were included. Decreased retinal microvascular perfusion (β coefficient = −0.08; 95% CI, −0.14 to −0.03) and densities (β coefficient = −1.86; 95% CI, −3.11 to −0.60) in superficial vascular plexus (SVC) were found in the eyes of the participants with AF. In regard to retinal structures, thinner ganglion cell–inner plexiform layer (GCIPL; β coefficient = −2.34; 95% CI, −4.32 to −0.36) and retinal nerve fiber layer (RNFL) thicknesses (β coefficient = −0.63; 95% CI, −2.09 to −0.18) were observed in the eyes of the participants with AF. The retinal parameters did not significantly differ between paroxysmal and sustained AF (all P > 0.05). However, significant interactions were observed between LA diameter and AF subtypes with the perfusion and densities in SVC (P

Since China abandoned the zero-COVID policy at the end of 2022, a wave of severe Flu pandemic emerged in China. Rapid and accurate diagnosis of Influenza A virus (IAV) is critical for clinical management and therapeutic decision-making of patients with fever. Here, we reported a novel IAV HF-LAMP assay, which can be performed with purified RNA or directly using clinical samples. The assays with purified RNA and clinical samples have high sensitivity with limit of detection (LOD) of 9.6 copies/reaction, 9900 copies/mL, and short sample-to-answer times of 36 and 50 min, respectively. Both assays showed high specificity and significantly higher IAV detection rate than the rapid antigen detection (RAD) assays. Furthermore, we found the vast majority (91.2 %) of children with fever during the pandemic were infected by IAV, and current IAV infection has a very narrow detectable window. The novel IVA HF-LAMP assays will provide robust tools to facilitate early diagnosis of IAV infection in current and future seasonal influenza epidemics.

BackgroundIt is currently unclear whether and how the association between body composition and hypertension varies based on the presence and severity of fatty liver disease (FLD).MethodsFLD was diagnosed using ultrasonography among 6,358 participants. The association between body composition and hypertension was analyzed separately in the whole population, as well as in subgroups of non-FLD, mild FLD, and moderate/severe FLD populations, respectively. The mediation effect of FLD in their association was explored.ResultsFat-related anthropometric measurements and lipid metabolism indicators were positively associated with hypertension in both the whole population and the non-FLD subgroup. The strength of this association was slightly reduced in the mild FLD subgroup. Notably, only waist-to-hip ratio and waist-to-height ratio showed significant associations with hypertension in the moderate/severe FLD subgroup. Furthermore, FLD accounted for 17.26% to 38.90% of the association between multiple body composition indicators and the risk of hypertension.ConclusionsThe association between body composition and hypertension becomes gradually weaker as FLD becomes more severe. FLD plays a significant mediating role in their association.

Abstract Background After the COVID-19 epidemic, the state has paid more attention to the clinical teaching function of affiliated hospitals of colleges and universities. Strengthening the integration of medicine and education and improving the quality and effect of clinical practice teaching are critical challenges facing medical education. The difficulty of orthopedic teaching lies in the characteristics of a wide variety of diseases, strong professionalism, and relatively abstract characteristics, which affect the initiative, enthusiasm, and learning effect of nursing students. In this study, a flipped classroom teaching plan based on the CDIO (conceive–design–implement–operate) concept was constructed and practiced in the orthopedic nursing student training course to improve the effect of practical teaching, and it is convenient for teachers to implement more effective and targeted teaching in the flipped classroom of nursing education and even medical education in the future. Methods Fifty undergraduate nursing students who practiced in the Orthopedics Department of a tertiary hospital in June 2017 were enrolled in the control group, while 50 undergraduate nursing students who practiced in the same department in June 2018 were enrolled in the intervention group. The intervention group adopted the flipped classroom teaching mode of the CDIO concept, whereas the control group adopted the traditional teaching mode. After finishing the department practice task, the students in the two groups completed the evaluation of theory, operation skills, independent learning ability, and critical thinking ability. They completed the evaluation of clinical practice ability in eight dimensions, including four processes of nursing procedures, humanistic care ability, and evaluation of clinical teaching quality for two groups of teachers. Results After teaching, the clinical practice ability, critical thinking ability, autonomous learning ability, theoretical and operational performance, and evaluation of clinical teaching quality in the intervention group were significantly higher than those in the control group (all p

The development of 3D Synthetic Aperture Radar (SAR) imaging is currently hampered by issues such as high data dimension, high system complexity, and low imaging processing efficiency. Sparse SAR imaging has grown in importance as a research branch in SAR imaging due to the high potential of sparse signal processing techniques based on Compressed Sensing (CS) to show high potential in reducing system complexity and improving imaging quality. However, traditional sparse imaging methods are still constrained by high computational complexity, nontrivial parameter tuning, and poor adaptability to weakly sparse scenes. To address these issues, we propose a new 3D SAR imaging method based on learned sparse priors inspired by the deep unfolding concept. First, the limitations of the matrix-vector linear representation model are discussed, and an imaging operator is introduced to improve the algorithm’s imaging efficiency. Furthermore, this research focuses on algorithm network details, such as network topology design, the problem of complex-valued propagations, optimization constraints of algorithm parameters, and network training details. Finally, through simulations and measured experiments, it is proved that the proposed method can improve the imaging accuracy while reducing the running time by more than one order of magnitude compared with the conventional sparse imaging algorithms.

Systemic lupus erythematosus is characterised by the generation of antibodies targeting DNA and nuclear antigens. Here, the authors show that oxidised mitochondrial DNA induces gasdermin D oligomerization and promotes pore formation in neutrophils from patients with SLE.

The increasing use of molybdate has raised concerns about its potential toxicity in humans. However, the potential toxicity of molybdate under the current level of human exposure remains largely unknown. Endogenous metabolic alterations that are caused in humans by environmental exposure to pollutants are associated with the occurrence and progression of many diseases. This study exposed eight-week-old male C57 mice to sodium molybdate at doses relevant to humans (0.01 and 1 mg/kg/day) for eight weeks. Inductively coupled plasma mass spectrometry (ICP-MS) and ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS) were utilized to assess changes in urine element levels and serum metabolites in mice, respectively. A total of 838 subjects from the NHANES 2017–2018 population database were also included in our study to verify the associations between molybdenum and cadmium found in mice. Analysis of the metabolome in mice revealed that four metabolites in blood serum exhibited significant changes, including 5-aminolevulinic acid, glycolic acid, l-acetylcarnitine, and 2,3-dihydroxypropyl octanoate. Analysis of the elementome revealed a significant increase in urine levels of cadmium after molybdate exposure in mice. Notably, molybdenum also showed a positive correlation with cadmium in humans from the NHANES database. Further analysis identified a positive correlation between cadmium and 2,3-dihydroxypropyl octanoate in mice. In conclusion, these findings suggest that molybdate exposure disrupted amino acid and lipid metabolism, which may be partially mediated by molybdate-altered cadmium levels. The integration of elementome and metabolome data provides sensitive information on molybdate-induced metabolic disorders and associated toxicities at levels relevant to human exposure.

The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5′ UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5′ UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5′ UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5′ UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5′ UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5′ UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products.

Compared with electromagnetic compatibility (EMC) testing in anechoic rooms, open-area EMC testing takes advantage of in situ and engine running status measurement but suffers from non-negligible external electromagnetic interference. This paper proposes a novel environmental interference suppression method (named the EMC environmental interference suppression algorithm (E2ISA)) that separates signals from backgrounds via image segmentation and recognizes the near–far site signal via a group of time-varying features based on the difference in the near-site EM radiative characteristic. We find that the proposed E2ISA method, which combines the deep learning segmentation network with the classical recognition methods, is able to suppress environmental interference signals accurately. The experiment results show that the accuracy of E2ISA reaches up to 95% in the face of VHF (Very High Frequency) EMC testing tasks.

This study introduces a pioneering multimodal fusion framework to enhance near-field 3D Synthetic Aperture Radar (SAR) imaging, crucial for applications like radar cross-section measurement and concealed object detection. Traditional near-field 3D SAR imaging struggles with issues like target–background confusion due to clutter and multipath interference, shape distortion from high sidelobes, and lack of color and texture information, all of which impede effective target recognition and scattering diagnosis. The proposed approach presents the first known application of multimodal fusion in near-field 3D SAR imaging, integrating LiDAR and optical camera data to overcome its inherent limitations. The framework comprises data preprocessing, point cloud registration, and data fusion, where registration between multi-sensor data is the core of effective integration. Recognizing the inadequacy of traditional registration methods in handling varying data formats, noise, and resolution differences, particularly between near-field 3D SAR and other sensors, this work introduces a novel three-stage registration process to effectively address these challenges. First, the approach designs a structure–intensity-constrained centroid distance detector, enabling key point extraction that reduces heterogeneity and accelerates the process. Second, a sample consensus initial alignment algorithm with SHOT features and geometric relationship constraints is proposed for enhanced coarse registration. Finally, the fine registration phase employs adaptive thresholding in the iterative closest point algorithm for precise and efficient data alignment. Both visual and quantitative analyses of measured data demonstrate the effectiveness of our method. The experimental results show significant improvements in registration accuracy and efficiency, laying the groundwork for future multimodal fusion advancements in near-field 3D SAR imaging.

Through an interesting physical perspective and a certain contraction of the Ricci curvature tensor in Finsler geometry, Akbar-Zadeh introduced the concept of scalar curvature for the Finsler metric. In this paper, we show that the Kropina metric is of isotropic scalar curvature if and only if F is an Einstein metric according to the navigation data. Moreover, we obtain the three-dimensional rigidity theorem for an Einstein–Kropina metric.

Zygote arrest-1 (Zar1) and Wilms’ tumor 1 (Wt1) play an important role in oogenesis, with the latter also involved in testicular development and gender differentiation. Here, Lczar1 and Lcwt1b were identified in Asian seabass (Lates calcarifer), a hermaphrodite fish, as the valuable model for studying sex differentiation. The cloned cDNA fragments of Lczar1 were 1192 bp, encoding 336 amino acids, and contained a zinc-binding domain, while those of Lcwt1b cDNA were 1521 bp, encoding a peptide of 423 amino acids with a Zn finger domain belonging to Wt1b family. RT-qPCR analysis showed that Lczar1 mRNA was exclusively expressed in the ovary, while Lcwt1b mRNA was majorly expressed in the gonads in a higher amount in the testis than in the ovary. In situ hybridization results showed that Lczar1 mRNA was mainly concentrated in oogonia and oocytes at early stages in the ovary, but were undetectable in the testis. Lcwt1b mRNA was localized not only in gonadal somatic cells (the testis and ovary), but also in female and male germ cells in the early developmental stages, such as those of previtellogenic oocytes, spermatogonia, spermatocytes and spermatids. These results indicated that Lczar1 and Lcwt1b possibly play roles in gonadal development. Therefore, the findings of this study will provide a basis for clarifying the mechanism of Lczar1 and Lcwt1b in regulating germ cell development and the sex reversal of Asian seabass and even other hermaphroditic species.

Abstract INTRODUCTION The precise apolipoprotein E (APOE) ε4‐specific molecular pathway(s) for Alzheimer's disease (AD) risk are unclear. METHODS Plasma protein modules/cascades were analyzed using weighted gene co‐expression network analysis (WGCNA) in the Alzheimer's Disease Neuroimaging Initiative study. Multivariable regression analyses were used to examine the associations among protein modules, AD diagnoses, cerebrospinal fluid (CSF) phosphorylated tau (p‐tau), and brain glucose metabolism, stratified by APOE genotype. RESULTS The Green Module was associated with AD diagnosis in APOE ε4 homozygotes. Three proteins from this module, C‐reactive protein (CRP), complement C3, and complement factor H (CFH), had dose‐dependent associations with CSF p‐tau and cognitive impairment only in APOE ε4 homozygotes. The link among these three proteins and glucose hypometabolism was observed in brain regions of the default mode network (DMN) in APOE ε4 homozygotes. A Framingham Heart Study validation study supported the findings for AD. DISCUSSION The study identifies the APOE ε4–specific CRP–C3–CFH inflammation pathway for AD, suggesting potential drug targets for the disease. Highlights Identification of an APOE ε4 specific molecular pathway involving blood CRP, C3, and CFH for the risk of AD. CRP, C3, and CFH had dose‐dependent associations with CSF p‐Tau and brain glucose hypometabolism as well as with cognitive impairment only in APOE ε4 homozygotes. Targeting CRP, C3, and CFH may be protective and therapeutic for AD onset in APOE ε4 carriers.

Heart disease is a major health issue, and accurate diagnosis of irregular heartbeats and heart failure is crucial. Current diagnostic processes can be time-consuming, requiring significant effort from clinicians. An effective classifier, ADCGNet: Attention-based Dual Channel Gabor Network is proposed to address this challenge by accurately classifying anomalies. ADCGNet involves pre-processing every ECG beat into two-dimensional images using Analytical Morlet transform and then applying thirty-two Gabor filters and Sobel edge detection to enhance features. ADCGNet comprises three blocks, with the first block using dual channels to extract essential features in the images efficiently. The second block includes a multi-head attention mechanism to focus on relevant features, and the third block uses a SoftMax activation function to perform classification tasks. Extensive experiments with public datasets from PhysioNet, and comparison with several state-of-the-art classifiers indicate ADCGNet is superior. Specifically, ADCGNet achieved an accuracy of 99.17%, 98.98% in precision, a recall of 98.87%, an F1-score of 98.82% and AUC, 98.75% with optimal hyperparameters. Further, a GRAD-CAM visualization of activated areas on the test samples gives graphical insight into the performance of ADCGNet. The proposed ADCGNet classifier has promising potential for enhancing the diagnosis of heart disease, and we believe it will be of much interest to the medical community.

Preclinical trials play critical roles in assessing the safety and efficiency of novel therapeutic strategies for human diseases including live cancer. However, most therapeutic strategies that were proved to be effective in preclinical cancer models failed in human clinical trials due to the lack of appropriate disease animal models. Therefore, it is of importance and urgent to develop a precise animal model for preclinical cancer research. Liver cancer is one of the most frequently diagnosed cancers with low 5-year survival rate. Recently, porcine attracted increasing attentions as animal model in biomedical research. Porcine liver cancer model may provide a promising platform for biomedical research due to their similarities to human being in body size, anatomical characteristics, physiology and pathophysiology. In this review, we comprehensively summarized and discussed the advantages and disadvantages, rationale, current status and progress of pig models for liver cancer research.

Abstract After fertilization, sperm and oocyte fused and gave rise to a zygote which is the beginning of a new life. Then the embryonic development is monitored and regulated precisely from the transition of oocyte to the embryo at the early stage of embryogenesis, and this process is termed maternal‐to‐zygotic transition (MZT). MZT involves two major events that are maternal components degradation and zygotic genome activation. The epigenetic reprogramming plays crucial roles in regulating the process of MZT and supervising the normal development of early development of embryos. In recent years, benefited from the rapid development of low‐input epigenome profiling technologies, new epigenetic modifications are found to be reprogrammed dramatically and may play different roles during MZT whose dysregulation will cause an abnormal development of embryos even abortion at various stages. In this review, we summarized and discussed the important novel findings on epigenetic reprogramming and the underlying molecular mechanisms regulating MZT in mammalian embryos. Our work provided comprehensive and detailed references for the in deep understanding of epigenetic regulatory network in this key biological process and also shed light on the critical roles for epigenetic reprogramming on embryonic failure during artificial reproductive technology and nature fertilization.

Abstract Radiochemotherapy (RCT) is a powerful treatment for cervical cancer, which affects not only malignant cells but also the immune and stromal compartments of the tumor. Understanding the remodeling of the local ecosystem induced by RCT would provide valuable insights into improving treatment strategies for cervical cancer. In this study, we applied single-cell RNA-sequencing to paired pre- and post-RCT tumor biopsies from patients with cervical cancer and adjacent normal cervical tissues. We found that the residual population of epithelial cells post-RCT showed upregulated expression of MHC class II genes. Moreover, RCT led to the accumulation of monocytic myeloid-derived suppressor cells with increased pro-inflammatory features and CD16+ NK cells with a higher cytotoxic gene expression signature. However, subclusters of T cells showed no significant increase in the expression of cytotoxic features post-RCT. These results reveal the complex responses of the tumor ecosystem to RCT, providing evidence of activation of innate immunity and MHC-II upregulation in cervical cancer.

The regeneration of articular cartilage remains a great challenge due to the difficulty in effectively enhancing spontaneous healing. Recently, the combination of implanted stem cells, suitable biomaterials and bioactive molecules has attracted attention for tissue regeneration. In this study, a novel injectable nanocomposite was rationally designed as a sustained release platform for enhanced cartilage regeneration through integration of a chitosan-based hydrogel, articular cartilage stem cells (ACSCs) and mesoporous SiO2 nanoparticles loaded with anhydroicaritin (AHI). The biocompatible engineered nanocomposite acting as a novel 3D biomimetic extracellular matrix exhibited a remarkable sustained release effect due to the synergistic regulation of the organic hydrogel framework and mesopore channels of inorganic mSiO2 nanoparticles (mSiO2 NPs). Histological assessment and biomechanical tests showed that the nanocomposites exhibited superior performance in inducing ACSCs proliferation and differentiation in vitro and promoting extracellular matrix (ECM) production and cartilage regeneration in vivo. Such a novel multifunctional biocompatible platform was demonstrated to significantly enhance cartilage regeneration based on the sustained release of AHI, an efficient bioactive natural small molecule for ACSCs chondrogenesis, within the hybrid matrix of hydrogel and mSiO2 NPs. Hence, the injectable nanocomposite holds great promise for use as a 3D biomimetic extracellular matrix for tissue regeneration in clinical diagnostics.

Abstract Background The early life gut microbiome is crucial in maintaining host metabolic and immune homeostasis. Though neonates with critical congenital heart disease (CCHD) are at substantial risks of malnutrition and immune imbalance, the microbial links to CCHD pathophysiology remain poorly understood. In this study, we aimed to investigate the gut microbiome in neonates with CCHD in association with metabolomic traits. Moreover, we explored the clinical implications of the host-microbe interactions in CCHD. Methods Deep metagenomic sequencing and metabolomic profiling of paired fecal samples from 45 neonates with CCHD and 50 healthy controls were performed. The characteristics of gut microbiome were investigated in three dimensions (microbial abundance, functionality, and genetic variation). An in-depth analysis of gut virome was conducted to elucidate the ecological interaction between gut viral and bacterial communities. Correlations between multilevel microbial features and fecal metabolites were determined using integrated association analysis. Finally, we conducted a subgroup analysis to examine whether the interactions between gut microbiota and metabolites could mediate inflammatory responses and poor surgical prognosis. Results Gut microbiota dysbiosis was observed in neonates with CCHD, characterized by the depletion of Bifidobacterium and overgrowth of Enterococcus, which was highly correlated with metabolomic perturbations. Genetic variations of Bifidobacterium and Enterococcus orchestrate the metabolomic perturbations in CCHD. A temperate core virome represented by Siphoviridae was identified to be implicated in shaping the gut bacterial composition by modifying microbial adaptation. The overgrowth of Enterococcus was correlated with systemic inflammation and poor surgical prognosis in subgroup analysis. Mediation analysis indicated that the overgrowth of Enterococcus could mediate gut barrier impairment and inflammatory responses in CCHD. Conclusions We demonstrate for the first time that an aberrant gut microbiome associated with metabolomic perturbations is implicated in immune imbalance and adverse clinical outcomes in neonates with CCHD. Our data support the importance of reconstituting optimal gut microbiome in maintaining host metabolic and immunological homeostasis in CCHD. Video Abstract

Abstract Apolipoprotein ε4 (APOE ε4) is the most significant genetic risk factor for late-onset Alzheimer’s disease (AD). Elevated blood C-reactive protein (CRP) further increases the risk of AD for people carrying the APOE ε4 allele. We hypothesized that CRP, as a key inflammatory element, could modulate the impact of other genetic variants on AD risk. We selected ten single nucleotide polymorphisms (SNPs) in reported AD risk loci encoding proteins related to inflammation. We then tested the interaction effects between these SNPs and blood CRP levels on AD incidence using the Cox proportional hazards model in UK Biobank (n = 279,176 white participants with 803 incident AD cases). The five top SNPs were tested for their interaction with different CRP cutoffs for AD incidence in the Framingham Heart Study (FHS) Generation 2 cohort (n = 3009, incident AD = 156). We found that for higher concentrations of serum CRP, the AD risk increased for SNP genotypes in 3 AD-associated genes (SPI1, CD33, and CLU). Using the Cox model in stratified genotype analysis, the hazard ratios (HRs) for the association between a higher CRP level (≥10 vs.

Abstract Background 2-Phenylethanol (2-PE), a higher alcohol with a rose-like odor, inhibits growth of the producer strains. However, the limited knowledge regarding 2-PE tolerance mechanisms renders our current knowledge base insufficient to inform rational design. Results To improve the growth phenotype of Saccharomyces cerevisiae under a high 2-PE concentration, adaptive laboratory evolution (ALE) was used to generate an evolved 19–2 strain. Under 2-PE stress, its OD600 and growth rate increased by 86% and 22% than that of the parental strain, respectively. Through whole genome sequencing and reverse engineering, transcription factor Pdr1p mutation (C862R) was revealed as one of the main causes for increased 2-PE tolerance. Under 2-PE stress condition, Pdr1p mutation increased unsaturated fatty acid/saturated fatty acid ratio by 42%, and decreased cell membrane damage by 81%. Using STRING website, we identified Pdr1p interacted with some proteins, which were associated with intracellular ergosterol content, reactive oxygen species (ROS), and the ATP-binding cassette transporter. Also, the results of transcriptional analysis of genes encoded these proteins confirmed that Pdr1p mutation induced the expression of these genes. Compared with those of the reference strain, the ergosterol content of the PDR1_862 strain increased by 72%–101%, and the intracellular ROS concentration decreased by 38% under 2-PE stress. Furthermore, the Pdr1p mutation also increased the production of 2-PE (11% higher). Conclusions In the present work, we have demonstrated the use of ALE as a powerful tool to improve yeast tolerance to 2-PE. Based on the reverse engineering, transcriptional and physiological analysis, we concluded that Pdr1p mutation significantly enhanced the 2-PE tolerance of yeast by regulating the fatty acid proportion, intracellular ergosterol and ROS. It provides new insights on Pdr1p mediated 2-PE tolerance, which could help in the design of more robust yeasts for natural 2-PE synthesis.

Abstract Background The T helper 17 (Th17)/T regulatory (Treg) cell imbalance is involved in the course of obesity and type 2 diabetes mellitus (T2DM). In the current study, the exact role of glucagon-like peptide-1 receptor agonist (GLP-1RA) exenatide on regulating the Th17/Treg balance and the underlying molecular mechanisms are investigated in obese diabetic mice model. Methods Metabolic parameters were monitored in db/db mice treated with/without exenatide during 8-week study period. The frequencies of Th17 and Treg cells from peripheral blood and pancreas in db/db mice were assessed. The phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/Forkhead box O1 (FoxO1) pathway in Th17 and Treg cells from the spleens of male C57BL/6J mice was detected by western blotting. In addition, the expression of glucagon-like peptide-1 receptor (GLP-1R) in peripheral blood mononuclear cells (PBMCs) of male C57BL/6J mice was analyzed. Results Exenatide treatment improved β-cell function and insulitis in addition to glucose, insulin sensitivity and weight. Increased Th17 and decreased Treg cells in peripheral blood were present as diabetes progressed while exenatide corrected this imbalance. Progressive IL-17 + T cell infiltration of pancreatic islets was alleviated by exenatide intervention. In vitro study showed no significant difference in the level of GLP-1R expression in PBMCs between control and palmitate (PA) groups. In addition, PA could promote Th17 but suppress Treg differentiation along with down-regulating the phosphorylation of PI3K/Akt/FoxO1, which was reversed by exenatide intervention. FoxO1 inhibitor AS1842856 could abrogate all these effects of exenatide against lipid stress. Conclusions Exenatide could restore systemic Th17/Treg balance via regulating FoxO1 pathway with the progression of diabetes in db/db mice. The protection of pancreatic β-cell function may be partially mediated by inhibiting Th17 cell infiltration into pancreatic islets, and the resultant alleviation of islet inflammation.

According to the completed large-scale shaking table test of the liquefied lateral extension site-pile group foundation-superstructure system, the finite element model of the shaking table test of the liquefiable inclined site is established in the finite element software OpenSees. The reliability of the numerical model is verified by comparing with the experimental results. Based on this, numerical models of typical horizontal and inclined liquefaction site-pile foundation-bridge structural systems are established, and the difference in seismic response of horizontal and inclined site under bidirectional seismic excitation is discussed. The water pressure fluctuates more at the peak stage, and the lateral displacement of the soil increases significantly, especially in the middle of the saturated sand. The damage degree of the pile foundation in the inclined field is greater, and the maximum curvature of the pile foundation in the middle of the liquefiable layer can be increased by about approximately 13 times. The horizontal displacement of the pile body increases significantly. However, the curvature of the pier in the horizontal site is larger than that in the inclined site. It is suggested that the influence of the site inclination should be considered in the pile foundation design of the liquefaction site.

Abstract Recently, the global incidence of gastric/gastroesophageal junction (G/GEJ) cancer has remained high. China is also a large country with a high gastric cancer (GC) incidence rate, where the cases of GC account for 40% of all cases worldwide. More than 90% of GEJ cancers are the adenocarcinoma pathological type. Patients with early-stage G/GEJ adenocarcinoma may have a better prognosis after surgery. In contrast, patients with advanced metastatic G/GEJ adenocarcinoma usually choose comprehensive treatment based on systemic pharmacotherapy, but the subsequent long-term survival is not optimistic. The discovery of various biomarkers, especially microsatellite instability (MSI), programmed cell death-ligand 1 (PD-L1), human epidermal growth factor receptor 2 (HER2), tumor mutational burden (TMB) and Epstein–Barr virus (EBV), has led to the identification of an increasing number of targeted populations and has greatly improved the clinical efficacy of treatments for G/GEJ adenocarcinoma. The ToGA trial added trastuzumab to standard chemotherapy, showed improved survival of patients with HER2-positive advanced G/GEJ adenocarcinoma and brought these patients into a new era of HER2-targeted therapy. Moreover, many HER2-targeted agents have been developed and studied in patients with advanced HER2-positive G/GEJ adenocarcinoma who have demonstrated excellent clinical outcomes. However, many patients experience disease progression with HER2-targeted therapy; hence, new anti-HER2 drugs keep being developed, significantly reducing HER2 resistance. This paper reviews HER2-targeted drugs for advanced metastatic G/GEJ adenocarcinoma, potential resistance mechanisms and future directions.

Abstract Glucoraphanin (GRA) is present in the seeds and nutrient organs of broccoli and is the precursor of the anti-cancer compound sulforaphane (SF). The hairy roots obtained by infecting broccoli (Brassica oleracea L. var. Italic Planch) leaves with Agrobacterium rhizogenes (ATCC15834) are phytohormonally autonomous, genetically stable, and can produce large amounts of the anti-cancer substance SF. Melatonin (MT) is a natural hormone widely found in plants. Studies have shown that melatonin can regulate the synthesis of secondary metabolites of downstream targets by mediating the synthesis of signal molecules. However, whether MT regulates the synthesis of NO and H2O2 and mediates the synthesis mechanism of secondary metabolites, GRA and SF, is not yet clear. In this study, the hairy roots of broccoli were treated with 500 μmol/L MT, and the genome of broccoli (Brassica oleracea L. var. botrytis L) was used as the reference genome for transcriptome analysis. By this approach, we found that MT regulates the synthesis of NO and H2O2 and mediates the synthesis of secondary metabolites GRA and SF. GO annotations indicated that DEGs involved in the MT treatment of broccoli hairy roots were mainly related to catalytic activity, cells, and metabolic processes; the KEGG pathway analysis indicated that MT treatment likely affects the hormone signal transduction process in broccoli hairy roots; broccoli hairy roots were treated with 500 μmol/L MT for 0, 6, 12, 20, and 32 h, respectively; compared with 0 h, the yield of GRA and SF increased under the other treatments. The highest yields of GRA and SF occurred at 12 h. The NO content was the highest at 12 h, and the H2O2 content was positively correlated with MT concentration. The content of NO and H2O2 were regulated, and the content of GRA and SF was increased under MT treatment. NO synthase inhibitor (L-NAME and TUN) could effectively inhibit the content of NO in broccoli hairy roots and reduce GRA and SF yield; MT could regulate NO levels by regulating NO synthesis-related enzymes and could alleviate the reduction of NO content in tissue cells caused by NO synthase inhibitor and promote NO synthesis. These results have important theoretical implications for understanding the regulation of GRA and SF synthesis events by NO and H2O2.

Currently, anti-PD-1/PD-L1 immunotherapy using immune checkpoint inhibitors is widely used in the treatment of multiple cancer types including lung cancer, which is a leading cause of cancer death in the world. However, only a limited proportion of lung cancer patients will benefit from anti-PD-1/PD-L1 therapy. Therefore, it is of importance to predict the response to immunotherapy for the precision treatment of patients. Although the expression of PD-L1 and tumor mutation burden (TMB) are commonly used to predict the clinical response of anti-PD-1/PD-L1 therapy, other factors such as tumor-specific genes, dMMR/MSI, and gut microbiome are also promising predictors for immunotherapy in lung cancer. Furthermore, invasive peripheral blood biomarkers including blood DNA-related biomarkers (e.g., ctDNA and bTMB), blood cell-related biomarkers (e.g., immune cells and TCR), and other blood-related biomarkers (e.g., soluble PD-L1 and cytokines) were utilized to predict the immunotherapeutic response. In this review, the current achievements of anti-PD-1/PD-L1 therapy and the potential biomarkers for the prediction of anti-PD-1/PD-L1 immunotherapy in lung cancer treatment were summarized and discussed.

IntroductionColorectal cancer (CRC) is a highly prevalent digestive system malignancy. Aspirin is currently one of the most promising chemopreventive agents for CRC, and the combination of aspirin and natural compounds helps to enhance the anticancer activity of aspirin. Natural flavonoids like vitexin have an anticancer activity focusing on colorectal carcinoma.MethodsThis study investigated the potential mechanism of action of the novel combination of vitexin and aspirin against colorectal cancer through network pharmacology, molecular docking, molecular dynamics simulation, and in vitro experiments.ResultsThe results of network pharmacology suggested that vitexin and aspirin regulate multiple signaling pathways through various target proteins such as NFKB1, PTGS2 (COX-2), MAPK1, MAPK3, and TP53. Cellular experiments revealed that the combined effect of vitexin and aspirin significantly inhibited HT-29 cell growth. Vitexin dose-dependently inhibited COX-2 expression in cells and enhanced the down-regulation of COX-2 and NF-κB expression in colorectal cancer cells by aspirin.DiscussionThis study provides a pharmacodynamic material and theoretical basis for applying agents against colorectal cancer to delay the development of drug resistance and improve the prognosis of cancer patients.

Objective Recent therapeutic advances have greatly enhanced the survival rates of patients with neuroblastoma (NB). However, the outcomes of neuroblastoma patients in China, particularly those with high-risk (HR) NB, remain limited. Method We retrospectively analyzed the clinical data and outcomes of NB patients who were treated at a tertiary pediatric cancer facility in China between January 2013 and October 2021. Results A total of 117 NB patients were recruited. Patients with very low-risk (VLR), low-risk (LR), intermediate-risk (IR), and HR-NB patients made up 4%, 27%, 15%, and 54% of total patient population, respectively. Patients diagnosed between 2013 and 2018 were treated according to the protocol of Sun Yat-Sen University Cancer Center and those diagnosed between 2019 and 2021 were treated according to the COG ANBL0531 or ANBL0532 protocol with or without autologous stem cell transplantation (ASCT). The 5-year EFS and OS of all risk groups of patients were 67.29% and 77.90%, respectively. EFS and OS were significantly decreased in patients with higher risk classifications (EFS: VLR/LR vs IR vs HR: 97.22% vs 67.28% vs 51.83%; ***P = .001; OS: VLR/LR vs IR vs HR: 97.06% vs 94.12% vs 64.38%; *P = .046). In HR-NB patients treated according to the COG protocol between 2019 and 2021, the 3-year OS of patients who received tandem ASCT was significantly greater than those who did not receive ASCT (93.33% % vs 47.41%; *P = .046; log-rank test). EFS was not significantly different between patients with and without ASCT (72.16% vs 60.32%). Conclusion Our findings show that patients with lower risk classification have a positive prognosis for survival. The prognosis of patients with HR-NB remains in need of improvement. ASCT may enhance OS in HR-NB patients; however, protocol adjustment may be necessary to increase EFS in these patients.

Breast cancer (BC) is the most frequently occurring cancer type seriously threatening the lives of women worldwide. Clinically, the high frequency of diverse resistance to current therapeutic strategies advocates a demand to develop novel and effective approaches for the efficient treatment of BC. The chimeric antigen receptor T (CAR-T) cells therapy, one of the immunotherapies, has displayed powerful capacity to specifically kill and eliminate tumors. Due to the success of CAR-T therapy achieved in treating hematological malignancy, the effect of CAR-T cells therapy has been tested in various human diseases including breast cancer. This review summarized and discussed the landscape of the CAR-T therapy for breast cancer, including the advances, challenge and countermeasure of CAR-T therapy in research and clinical application. The roles of potential antigen targets, tumor microenvironment, immune escape in regulating CAR-T therapy, the combination of CAR-T therapy with other therapeutic strategies to further enhance therapeutic efficacy of CAR-T treatment were also highlighted. Therefore, our review provided a comprehensive understanding of CAR-T cell therapy in breast cancer which will awake huge interests for future in-depth investigation of CAR-T based therapy in cancer treatment.

Abstract Chinese herbal medicines (CHM) have been used to cure diseases for thousands of years. However, the bioactive ingredients of CHM are complex, and some CHM natural products cannot be directly absorbed by humans and animals. Moreover, the contents of most bioactive ingredients in CHM are low, and some natural products are toxic to humans and animals. Fermentation of CHM could enhance CHM bioactivities and decrease the potential toxicities. The compositions and functions of the microorganisms play essential roles in CHM fermentation, which can affect the fermentation metabolites and pharmaceutical activities of the final fermentation products. During CHM fermentation, probiotics not only increase the contents of bioactive natural products, but also are beneficial for the host gut microbiota and immune system. This review summarizes the advantages of fermentation of CHM using probiotics, fermentation techniques, probiotic strains, and future development for CHM fermentation. Cutting‐edge microbiome and synthetic biology tools would harness microbial cell factories to produce large amounts of bioactive natural products derived from CHM with low‐cost, which would help speed up modern CHM biomanufacturing.

Wheat stripe rust, triggered by Puccinia striiformis f. sp. tritici, is among the most widespread and damaging wheat (Triticum L.) diseases. The development of cultivars harboring adult plant resistance (APR) to stripe rust is a better approach to control the disease. The current study aimed to map APR to stripe rust via the QTL mapping of 165 F2–6 recombinant inbred lines (RILs), derivatives of Weimai 8/Zhengzhou 5389. The collection of phenotypic data for the stripe-rust resistance of both parents and all 165 RILs were conducted at Baoding, Hebei Province, during the 2016–2017 cropping seasons, and at Mianyang, Sichuan Province, during the 2017–2018 and 2018–2019 sowing seasons. The RIL populations and parents were also genotyped with 860 pairs of simple-sequence-repeat (SSR) primers to map APR QTLs to stripe-rust resistant. Moreover, a 55K SNP chip was used for small group bulk segregant analysis conducted to locate the genetic map location and concentration of the SNP markers on the wheat genome. Inclusive composite interval mapping (IciMapping 3.2) software identified four QTLs of stripe-rust resistance on chromosomes 1B, 2AS, 2BS, and 7DS, named QYr.wmy-1B, QYr.wmy-2AS, QYr.wmy-2BS, and QYr.wmy-7DS, which significantly explained 11.56–16.64%, 9.35–12.70%, 7.27–9.95%, and 11.49–15.07% of the phenotypic variation, respectively. All these QTLs were found from the resistant parent, Weimai 8. Meanwhile, the QTLs located on chromosomes 1B and 2AS were found close to Yr18 and Yr9, respectively. Furthermore, the results indicated that QYr.wmy-1B is possibly Yr9 and QYr.wmy-2AS is similar to Yr18 or might be a new QTL, whilst QYr.wmy-2BS and QYr.wmy-7DS were found to be different from previously reported stripe-rust-resistance QTLs and are possibly new QTLs. Overall, the QTLs and their closely associated molecular markers detected in this study could be a great source of input for marker-assisted selection to adult plant stripe-rust resistance in wheat-breeding programs.

Phycosphere niches host rich microbial consortia that harbor dynamic algae–bacteria interactions with fundamental significance in varied natural ecosystems. Hence, culturing the uncultured microbial majority of the phycosphere microbiota is vital for deep understanding of the intricate mechanisms governing the dynamic interactions, and also to provide novel and rich microbial resources, and to discover new natural bioactive metabolites. Synechococcus elongatus PCC 7942 is a robust model cyanobacterium widely used in environment, synthesis biology, and biotechnology research. To expand the number of novel phycosphere species that were brought into culture and to discover the natural bioactivities, we presented a new yellow-pigmented bacterium named ABI-127-1, which was recovered from the phycosphere of PCC 7942, using an optimized bacterial isolation procedure. Combined polyphasic taxonomic and phylogenomic characterization was performed to confidently identify the new isolate as a potential novel species belonging to the genus Qipengyuania. The observed bioactivity of strain ABI-127-1 with promoting potential towards the growth and CO2 fixation efficiency of the host microalgae was measured. Additionally, the bacterial production of active bioflocculant exopolysaccharides was evaluated after culture optimization. Thus, these findings revealed the potential environmental and biotechnological implications of this new microalgae growth-promoting bacterium isolated from the phycosphere microenvironment.

For practical maritime SAR image classification tasks with special imaging platforms, scenes to be classified are often different from those in the training sets. The quantity and diversity of the available training data can also be extremely limited. This problem of out-of-distribution (OOD) generalization with limited training samples leads to a sharp drop in the performance of conventional deep learning algorithms. In this paper, a knowledge-guided neural network (KGNN) model is proposed to overcome these challenges. By analyzing the saliency features of various maritime SAR scenes, universal knowledge in descriptive sentences is summarized. A feature integration strategy is designed to assign the descriptive knowledge to the ResNet-18 backbone. Both the individual semantic information and the inherent relations of the entities in SAR images are addressed. The experimental results show that our KGNN method outperforms conventional deep learning models in OOD scenarios with varying training sample sizes and achieves higher robustness in handling distributional shifts caused by weather conditions, terrain type, and sensor characteristics. In addition, the KGNN model converges within many fewer epochs during training. The performance improvement indicates that the KGNN model learns representations guided by beneficial properties for ODD generalization with limited training samples.

Bacterioplankton communities are critical components of varied ecosystems in the oceans. Their occurrences represent a variety of connections between environmental and ecological elements. However, our current knowledge about the shaping factors of surface bacterioplankton communities in the eastern East China Sea (ECS) is still limited. In this study, we reveal the spatial patterns of the taxonomic and functional profiles of the surface bacterioplankton communitiesies in the nearshore and offshore areas in the eastern ECS, based on 16S rRNA gene pyrosequencing and functional annotation analysis. The obtained results show that the surface bacterioplankton communities in the nearshore areas are mainly dominated by the firmicutes (85.9%), actinobacteria (8.1%), and proteobacteria (5.4%), which are mainly involved in organic compound metabolism. Meanwhile, different bacteria predominate the composition of the offshore group, namely proteobacteria (71.1%) and bacteroidetes (22.0%) responsible for nitrogen and sulfur metabolism. Furthermore, their distribution pattern is shown to be spatially determined, along with a modest finding of functional diversity when comparing the bacterial species. The primary two shaping factors of bacterioplankton diversity are found to be the offshore distance and temperature. Overall, these findings add to those previously published on bacterial species and offer up functional information on the surface bacterioplankton communities in the eastern ECS. To extend our research, we propose that, in the future, it may be beneficial to monitor the dynamics of the ecosystem in this sea area.

Metabolism underlies the pathogenesis of acute myeloid leukemia (AML) and can be influenced by gut microbiota. However, the specific metabolic changes in different tissues and the role of gut microbiota in AML remain unclear. In this study, we analyzed the metabolome differences in blood samples from patients with AML and healthy controls using UPLC-Q-Exactive. Additionally, we examined the serum, liver, and fecal metabolome of AML model mice and control mice using UPLC-Q-Exactive. The gut microbiota of the mice were analyzed using 16S rRNA sequencing. Our UPLC-MS analysis revealed significant differences in metabolites between the AML and control groups in multiple tissue samples. Through cross-species validation in humans and animals, as well as reverse validation of Celastrol, we discovered that the Carnosine–Histidine metabolic pathway may play a potential role in the occurrence and progression of AML. Furthermore, our analysis of gut microbiota showed no significant diversity changes, but we observed a significant negative correlation between the key metabolite Carnosine and Peptococcaceae and Campylobacteraceae. In conclusion, the Carnosine–Histidine metabolic pathway influences the occurrence and progression of AML, while the gut microbiota might play a role in this process.

The potential medicinal value of Ma bamboo (Dendrocalamus latiflorus), one of the most popular and economically important bamboo species in China, has been underestimated. In the present study, we found that D. latiflorus leaf extract (DLE) reduced fasting blood glucose levels, body weight, and low-density lipoprotein cholesterol with low liver toxicity in db/db mice. In addition, gene expression profiling was performed and pathway enrichment analysis showed that DLE affected metabolic pathways. Importantly, DLE activated the AKT signaling pathway and reduced glucose production by downregulating glucose-6-phosphatase (G6PC) and phosphoenolpyruvate carboxykinase 1 (PCK1) expression. Moreover, network pharmacology analysis identified rutin as an active component in DLE through targeting insulin growth factor 1 receptor (IGF1R), an upstream signaling transducer of AKT. Due to its hypoglycemic effects and low toxicity, DLE may be considered an adjuvant treatment option for type 2 diabetes patients.

Abstract The first Sustainable Development Goal (SDG) is intended to eradicate multi-dimensional poverty globally. The same multidimensional poverty indices for India and the Middle East/Africa in 2020 indicate that 10–14 years are still required to reach the level of China’s poverty eradication. Using machine learning, spatial statistics, and a scenario analysis, we demonstrate how a Monte Carlo simulation of poverty alleviation funds-guided shared socioeconomic pathways (PAFs-SSPs) in China reveals the necessity to adopt an integrated poverty alleviation strategy. This approach employs multi-dimensional development indicators to reduce wide regional differences. We developed the data-driven model framework of a PAFs-SSPs to analyze the multifaceted and long-term planning needs of poverty alleviation policies, which can be applied to the formulation of poverty alleviation policies in different developing countries. Our findings point to the importance of implementing multidimensional development policies in China to achieve the first SDG worldwide.

Traffic congestion has been widely perceived as an inevitable byproduct in the process of global urbanization, leading to significant negative economic and environmental impacts. Existing studies have attached significant importance to revealing the interaction between traffic congestion patterns and built environment features in many metropolises with little attention, if any, paid to their counterparts of satellite cities (SC). For being aware that developing SCs has been a main trend to address many urban issues of metropolises in the rapid urbanization process of emerging economies, this study makes one of the first research attempts to investigate how traffic congestion temporally and spatially evolves with the built environment characterized by land use and transportation network features in Foshan, a typical SC of Guangzhou in China by using valuable hyperlocal travel data. The results show that while weekdays experience traffic peaks in both morning and evening, weekends or holidays generally only have the evening peak. The traffic congestion in Foshan during the pre-weekend is found much heavier compared with normal weekdays and weekends with a long-lasting effect possibly due to Foshan's role as a SC of Guangzhou. Additionally, the rising traffic congestion in a SC associated with company land use during the peak hours can be partly offset by the increasing supply of public transit, suggesting urban planners increase the density of public transit where there is a denser distribution of companies. This study provides new knowledge on travel behaviors in SCs in emerging economies, supplying urban governors with new insights for improving their traffic conditions generally.