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Abstract Hyaluronic acid is a major component of extracellular matrix which plays an important role in development, cellular response to injury and inflammation, cell migration, and cancer. The naked mole-rat (Heterocephalus glaber) contains abundant high-molecular-mass hyaluronic acid in its tissues, which contributes to this species’ cancer resistance and possibly to its longevity. Here we report that abundant high-molecular-mass hyaluronic acid is found in a wide range of subterranean mammalian species, but not in phylogenetically related aboveground species. These subterranean mammalian species accumulate abundant high-molecular-mass hyaluronic acid by regulating the expression of genes involved in hyaluronic acid degradation and synthesis and contain unique mutations in these genes. The abundant high-molecular-mass hyaluronic acid may benefit the adaptation to subterranean environment by increasing skin elasticity and protecting from oxidative stress due to hypoxic conditions. Our work suggests that high-molecular-mass hyaluronic acid has evolved with subterranean lifestyle.

Abstract Aims The primary aim of this study was to characterize the health-related quality of life (HRQoL) and identify the associated factors among children aged 2 to 18 in China diagnosed with idiopathic nephrotic syndrome (INS). Additionally, the study aimed to evaluate the HRQoL and caregiving burden of their caregivers and investigate the correlation between the HRQoL of the children and that of their caregivers. Methods This study recruited 181 children diagnosed with INS from Children’s Hospital, Zhejiang University School of Medicine in China. The proxy-reported PedsQL Generic Core Module (PedsQL™ 4.0 GCM) was used to measure the HRQoL of children, and the EuroQol five-dimensional questionnaire, five-level version (EQ-5D-5L) was applied to measure caregivers’ HRQoL. Differences in scale scores and total scores of PedsQL™ 4.0 GCM were assessed using t-tests and one-way ANOVA. Multivariate linear regression analysis was used to identify the factors associated with children’s HRQoL. Pearson correlation analysis evaluated the correlation between children’s HRQoL and caregiver’s HRQoL. Results HRQoL of Children with INS declines with increasing age, and children aged 5-18 had lower scores in physical functioning, emotional functioning, school functioning, psychosocial health summary score, and total PedsQL™ 4.0 GCM score compared to healthy children. Various factors, including the mother filling out the questionnaire, the father being unemployed, and the use of other medications except for steroids, were associated with worse HRQoL of children (p values

Abstract The development of hydrogen technologies is at the heart of a green economy. As prerequisite for implementation of hydrogen storage, active and stable catalysts for (de)hydrogenation reactions are needed. So far, the use of precious metals associated with expensive costs dominates in this area. Herein, we present a new class of lower-cost Co-based catalysts (Co-SAs/NPs@NC) in which highly distributed single-metal sites are synergistically combined with small defined nanoparticles allowing efficient formic acid dehydrogenation. The optimal material with atomically dispersed CoN2C2 units and encapsulated 7-8 nm nanoparticles achieves an excellent gas yield of 1403.8 mL·g−1·h−1 using propylene carbonate as solvent, with no activity loss after 5 cycles, which is 15 times higher than that of the commercial Pd/C. In situ analytic experiments show that Co-SAs/NPs@NC enhances the adsorption and activation of the key intermediate monodentate HCOO*, thereby facilitating the following C-H bond breaking, compared to related single metal atom and nanoparticle catalysts. Theoretical calculations show that the integration of cobalt nanoparticles elevates the d-band center of the Co single atoms as the active center, which consequently enhances the coupling of the carbonyl O of the HCOO* intermediate to the Co centers, thereby lowering the energy barrier.

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a group of chronic interstitial pulmonary diseases characterized by myofibroblast proliferation and extracellular matrix (ECM) deposition. However, current treatments are not satisfactory. Therefore, more effective therapies need to be explored. Cepharanthine (CEP) is a naturally occurring alkaloid that has recently been reported to have multiple pharmacological effects, particularly in chronic inflammation. Methods For in vivo experiments, first, a pulmonary fibrosis murine model was generated via tracheal injection of bleomycin (BLM). Second, the clinical manifestations and histopathological changes of the mice were used to verify that treatment with CEP might significantly reduce BLM-induced fibrosis. Furthermore, flow cytometric analysis was used to analyze the changes in the number of M2 macrophages in the lung tissues before and after treatment with CEP to explore the relationship between macrophage M2 polarization and pulmonary fibrosis. In vitro, we constructed two co-culture systems (THP-1 and MRC5 cells, RAW264.7 and NIH 3T3 cells), and measured the expression of fibrosis-related proteins to explore whether CEP could reduce pulmonary fibrosis by regulating macrophage M2 polarization and fibroblast activation. Results The results showed that the intranasal treatment of CEP significantly attenuated the symptoms of pulmonary fibrosis induced by BLM in a murine model. Our findings also indicated that CEP treatment markedly reduced the expression of fibrosis markers, including TGF-β1, collagen I, fibronectin and α-SMA, in the mouse lung. Furthermore, in vitro studies demonstrated that CEP attenuated pulmonary fibrosis by inhibiting fibroblast activation through modulating macrophage M2 polarization and reducing TGF-β1 expression. Conclusions This study demonstrated the potential and efficacy of CEP in the treatment of pulmonary fibrosis. In particular, this study revealed a novel mechanism of CEP in inhibiting fibroblast activation by regulating macrophage M2 polarization and reducing the expression of fibrosis-associated factors. Our findings open a new direction for future research into the treatment of pulmonary fibrosis.

Abstract Cadmium, a common metal pollutant, has been demonstrated to induce type 2 diabetes by disrupting pancreatic β cells function. In this study, transcriptome microarray was utilized to identify differential gene expression in oxidative damage to pancreatic β cells following cadmium exposure. The results indicated that a series of mRNAs, LncRNAs, and miRNAs were altered. Of the differentially expressed miRNAs, miR-29a-3p exhibited the most pronounced alteration, with an 11.62-fold increase relative to the control group. Following this, the target gene of miR-29a-3p was identified as Col3a1 through three databases (miRDB, miRTarbase and Tarbase), which demonstrated a decrease across the transcriptome microarray. The upstream target gene of miR-29a-3p was identified as NONMMUT036805, with decreased expression observed in the microarray. Finally, the expression trend of NONMMUT036805/miR-29a-3p/Col3a1 was reversed following NAC pretreatment. This was accompanied by a reduction in oxidative damage indicators, MDA/ROS/GSH-Px appeared to be negatively affected to varying degrees. In conclusion, this study has demonstrated that multiple RNAs are altered during cadmium exposure-induced oxidative damage in pancreatic β cells. The NONMMUT036805/miR-29a-3p/Col3a1 axis has been shown to be involved in this process, which provides a foundation for the identification of potential targets for cadmium toxicity intervention.

Abstract Background Madelung’s disease (MD), alternatively referred to as benign symmetric lipomatosis, multiple symmetric lipomatosis, or Launois–Bensaude syndrome, is an uncommon benign disorder marked by symmetric proliferation of adipose tissue in the head, neck, and torso regions. Case description In this case, the patient was a female with the late middle-aged demographic, diagnosed with Type I MD. Notably, she exhibited no prior history of alcohol consumption, and there was no family history of MD. Subsequent to the clinical diagnosis, the patient underwent medical imaging assessments to delineate the surgical parameters. Post-surgery, she demonstrated a favorable recovery trajectory, marked by the absence of any surgical complications. Result The patient underwent successful surgical excision of the lipomatous mass. Postoperatively, she had an uneventful recovery with no complications and no recurrence observed during the follow-up period of seven months. Conclusion Timely diagnosis and early surgical intervention play a pivotal role in enhancing the quality of life for individuals with MD. Preoperative medical imaging examinations function as highly effective tools, contributing to heightened surgical safety and a decreased probability of encountering complications during the surgical procedure.

Abstract Perovskite oxides show promise for the oxygen evolution reaction. However, numerical chemical compositions remain unexplored due to inefficient trial-and-error methods for material discovery. Here, we develop a transfer learning paradigm incorporating a pre-trained model, ensemble learning, and active learning, enabling the prediction of undiscovered perovskite oxides with enhanced generalizability for this reaction. Screening 16,050 compositions leads to the identification and synthesis of 36 new perovskite oxides, including 13 pure perovskite structures. Pr0.1Sr0.9Co0.5Fe0.5O3 and Pr0.1Sr0.9Co0.5Fe0.3Mn0.2O3 exhibit low overpotentials of 327 mV and 315 mV at 10 mA cm−2, respectively. Electrochemical measurements reveal coexistence of absorbate evolution and lattice oxygen mechanisms for O-O coupling in both materials. Pr0.1Sr0.9Co0.5Fe0.3Mn0.2O3 demonstrates enhanced OH- affinity compared to Pr0.1Sr0.9Co0.5Fe0.5O3, with the emergence of oxo-bridged Mn-Co conjugate facilitating charge redistribution and dynamic reversibility of Olattice/VO, thereby slowing down Co dissolution. This work paves the way for accelerated discovery and development of high-performance perovskite oxide electrocatalysts for this reaction.

Abstract Background Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn’t been fully investigated for the differentiation and may have the potential to improve it. Methods A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance. Results Higher ADCkurtosis (P = 0.022), frackurtosis (P

Transferring abundant, inexpensive, and nontoxic carbon dioxide (CO2) into biodegradable polymers is one of the ideal ways to promote sustainable development. Although a great deal of preeminent researches has been reported in the last decade, including well-designed organometallic complexes, Lewis pairs, etc. The moisture- and air-sensitive nature of these extensively used catalysts preclude their use in industrial applications. Herein, we report a novel stable catalyst system of commercial zinc glutarate (ZnGA) with a supported metal for the synthesis of poly­(ester-b-carbonate). The special supported microstructure facilitates efficient polymerizations via a plausible heterometal coordination mechanism. Notably, the resulted biodegradable CO2-based copolymer showed strong tensile strength (>40 MPa), improved elongation (45% versus 7%), excellent transmittance, and low water vapor permeability (WVP) (1.7 × 10–11 g m–1 s–1 Pa–1). Moreover, the supported ZnGA catalyst is recyclable, and its simple and low-cost preparation process is compatible with the manufacturing and processing methods of the existing infrastructure.

Abstract Background Neurodevelopmental disorders (NDD), such as autism spectrum disorders (ASD) and intellectual disorders (ID), are highly debilitating childhood psychiatric conditions. Genetic factors are recognized as playing a major role in NDD, with a multitude of genes and genomic regions implicated. While the functional validation of NDD-associated genes has predominantly been carried out using mouse models, the significant differences in brain structure and gene function between mice and humans have limited the effectiveness of mouse models in exploring the underlying mechanisms of NDD. Therefore, it is important to establish alternative animal models that are more evolutionarily aligned with humans. Results In this study, we employed CRISPR/Cas9 and somatic cell nuclear transplantation technologies to successfully generate a knockout miniature pig model of the MIR137 gene, which encodes the neuropsychiatric disorder-associated microRNA miR-137. The homozygous knockout of MIR137 (MIR137 –/– ) effectively suppressed the expression of mature miR-137 and led to the birth of stillborn or short-lived piglets. Transcriptomic analysis revealed significant changes in genes associated with neurodevelopment and synaptic signaling in the brains of MIR137 –/– miniature pig, mirroring findings from human ASD transcriptomic data. In comparison to miR-137-deficient mouse and human induced pluripotent stem cell (hiPSC)-derived neuron models, the miniature pig model exhibited more consistent changes in critical neuronal genes relevant to humans following the loss of miR-137. Furthermore, a comparative analysis identified differentially expressed genes associated with ASD and ID risk genes in both miniature pig and hiPSC-derived neurons. Notably, human-specific miR-137 targets, such as CAMK2A, known to be linked to cognitive impairments and NDD, exhibited dysregulation in MIR137 –/– miniature pigs. These findings suggest that the loss of miR-137 in miniature pigs affects genes crucial for neurodevelopment, potentially contributing to the development of NDD. Conclusions Our study highlights the impact of miR-137 loss on critical genes involved in neurodevelopment and related disorders in MIR137 –/– miniature pigs. It establishes the miniature pig model as a valuable tool for investigating neurodevelopmental disorders, providing valuable insights for potential applications in human research.

Abstract Background Gut bacteria are related to colorectal cancer (CRC) and its clinicopathologic characteristics. Objective To develop gut bacterial subtypes and explore potential microbial targets for CRC. Methods Stool samples from 914 volunteers (376 CRCs, 363 advanced adenomas, and 175 normal controls) were included for 16S rRNA sequencing. Unsupervised learning was used to generate gut microbial subtypes. Gut bacterial community composition and clustering effects were plotted. Differences of gut bacterial abundance were analyzed. Then, the association of CRC‐associated bacteria with subtypes and the association of gut bacteria with clinical information were assessed. The CatBoost models based on gut differential bacteria were constructed to identify the diseases including CRC and advanced adenoma (AA). Results Four gut microbial subtypes (A, B, C, D) were finally obtained via unsupervised learning. The characteristic bacteria of each subtype were Escherichia‐Shigella in subtype A, Streptococcus in subtype B, Blautia in subtype C, and Bacteroides in subtype D. Clinical information (e.g., free fatty acids and total cholesterol) and CRC pathological information (e.g., tumor depth) varied among gut microbial subtypes. Bacilli, Lactobacillales, etc., were positively correlated with subtype B. Positive correlation of Blautia, Lachnospiraceae, etc., with subtype C and negative correlation of Coriobacteriia, Coriobacteriales, etc., with subtype D were found. Finally, the predictive ability of CatBoost models for CRC identification was improved based on gut microbial subtypes. Conclusion Gut microbial subtypes provide characteristic gut bacteria and are expected to contribute to the diagnosis of CRC.

Summary: Structural features of proteins capture underlying information about protein evolution and function, which enhances the analysis of proteomic and transcriptomic data. Here, we develop Structural Analysis of Gene and protein Expression Signatures (SAGES), a method that describes expression data using features calculated from sequence-based prediction methods and 3D structural models. We used SAGES, along with machine learning, to characterize tissues from healthy individuals and those with breast cancer. We analyzed gene expression data from 23 breast cancer patients and genetic mutation data from the Catalog of Somatic Mutations In Cancer database as well as 17 breast tumor protein expression profiles. We identified prominent expression of intrinsically disordered regions in breast cancer proteins as well as relationships between drug perturbation signatures and breast cancer disease signatures. Our results suggest that SAGES is generally applicable to describe diverse biological phenomena including disease states and drug effects.

BackgroundIntervertebral disc degeneration (IDD) progression involves multiple factors, including loss of nucleus pulposus cells and extracellular matrix as the basic pathological mechanism of degeneration, and is closely related to cellular senescence and immune cell infiltration. The aim of study was to identify critical cellular senescence-related genes and immune cell infiltration characteristics in IDD.MethodsFour datasets, including GSE70362, GSE112216, GSE114169, and GSE150408, were downloaded from the Gene Expression Omnibus database. The senescence-related genes were acquired from the CellAge Database and intersected with differentially expressed genes (DEGs) between IDD and control samples for senescence-related DEGs (SRDEGs). Protein-protein interaction (PPI) network analysis was performed to obtain ten hub SRDEGs. A consensus cluster analysis based on these hub genes was performed to divide the patients into clusters. The functional enrichment, and immune infiltration statuses of the clusters were compared. Weighted gene co-expression network analysis was used to identified key gene modules. The overlapping genes from key modules, DEGs of clusters and hub SRDEGs were intersected to obtain potential biomarkers. To verify the expression of potential biomarkers, quantitative polymerase chain reaction (qPCR) and immunohistochemistry were performed by using human intervertebral disc tissues.ResultsIn the GSE70362 dataset, a total of 364 DEGs were identified, of which 150 were upregulated and 214 were downregulated, and 35 genes were selected as SRDEGs. PPI analysis revealed ten hub SRDEGs and consensus cluster analysis divided the patients into two clusters. Compared to Cluster 2, Cluster 1 was highly enriched in extracellular matrix organization and various metabolic process. The level of Follicular T helper cells in the Cluster 1 was significantly higher than that in the Cluster 2. IGFBP3 and NQO1 were identified as potential biomarkers. The remaining 3 datasets, and the result of qPCR and immunohistochemistry showed that the expression levels of NQO1 and IGFBP3 in the degenerated group were higher than those in the control or treatment groups.ConclusionSenescence-related genes play a key role in the development and occurrence of IDD. IGFBP3 and NQO1 are strongly correlated with immune infiltration in the IDD and could become novel therapeutic targets that prevent the progression of IDD.

Background Despite the high burden of diabetes and cardiovascular risk factors in American Indian communities in the United States, prospective studies of heart failure (HF) in this population group are scarce, and the generalizability of previous HF risk scales may be limited. We developed a parsimonious HF risk prediction equation that accounts for relevant risk factors affecting American Indian communities, focusing on diabetes and kidney damage. Methods and Results A total of 3059 participants from the SHS (Strong Heart Study) (56±8 years of age, 58% women) were included. Five hundred seven developed HF. Progressively adjusted Cox proportional hazards models were used to identify risk factors for HF and HF subtypes. Predictors of risk at 5 and 10 years included older age (hazard ratio [HR], 1.79 [95% CI, 1.43–2.25]; HR, 1.68 [95% CI, 1.44–1.95]), smoking (HR, 2.26 [95% CI, 1.23–4.13]; HR, 2.08 [95% CI, 1.41–3.06]), macroalbuminuria (HR, 8.38 [95% CI, 4.44–15.83]; HR, 5.20 [95% CI, 3.42–7.9]), microalbuminuria (HR, 2.72 [95% CI, 1.51–4.90]; HR, 1.92 [95% CI, 1.33, 2.78]), and previous myocardial infarction (HR, 6.58 [95% CI, 2.54–17.03]; HR, 3.87 [95% CI, 2.29–6.54]), respectively. These predictors, together with diabetes diagnosis and glycated hemoglobin were significant at 10 and 28 years. High discrimination performance was achieved (C index, 0.81 [95% CI, 0.76–0.84]; C index, 0.78 [95% CI, 0.75–0.81]; and C index, 0.77 [95% CI, 0.74–0.78] at 5, 10, and up to 28 years of follow up, respectively). Some associations varied across HF subtypes, although diabetes, albuminuria, and previous myocardial infarction were associated with all subtypes. Conclusions This prospective study of HF risk factors in American Indian communities identifies that smoking, body mass index, and indicators of diabetes control and kidney damage (glycated hemoglobin and albuminuria) are major determinants of HF. Our findings can improve HF risk assessment in populations with a high burden of diabetes.

Cadmium can lead to the death of pancreatic β cells, thus affecting the synthesis and secretion of insulin. However, the specific mechanisms underlying the cadmium-induced pancreatic β cell death have not been fully understood. In this study, roles of m6A modification in regulating protein processing in endoplasmic reticulum (PPER) pathway in cadmium-induced pancreatic β cell death were explored. Our results demonstrated that cell viability and RNA m6A modification level were decreased, while apoptosis rates increased after CdSO4 treatment in pancreatic β cells (NIT-1). In addition, expressions of Bcl-2, Xbp1, Col3a1, Bax, Chop, Dnajb1, and Hsp90aa1 were all significantly changed in CdSO4 treatment cells. The m6A agonist entacapone (Ent) can prominently reverse the cytotoxicity effects of CdSO4 and alleviate the changes of protein expression induced by CdSO4 treatment. By contrast, m6A inhibitor 3-Deazaadenosine (DAA) can synergistically enhance the cytotoxicity of CdSO4 and aggravate the disorder of protein levels caused by CdSO4 treatment. Interestingly, the results of the immunoprecipitation experiment indicate that Ythdc2, one of m6A binding proteins, may regulate the PPER pathway molecules in an m6A-dependent manner. In summary, our findings provide new directions for the prevention and treatment of the impairment of pancreatic β cell function induced by cadmium.

Abstract Occult hemorrhages after trauma can be present insidiously, and if not detected early enough can result in patient death. This study evaluated a hemorrhage model on 18 human subjects, comparing the performance of traditional vital signs to multiple off-the-shelf non-invasive biomarkers. A validated lower body negative pressure (LBNP) model was used to induce progression towards hypovolemic cardiovascular instability. Traditional vital signs included mean arterial pressure (MAP), electrocardiography (ECG), plethysmography (Pleth), and the test systems utilized electrical impedance via commercial electrical impedance tomography (EIT) and multifrequency electrical impedance spectroscopy (EIS) devices. Absolute and relative metrics were used to evaluate the performance in addition to machine learning-based modeling. Relative EIT-based metrics measured on the thorax outperformed vital sign metrics (MAP, ECG, and Pleth) achieving an area-under-the-curve (AUC) of 0.99 (CI 0.95–1.00, 100% sensitivity, 87.5% specificity) at the smallest LBNP change (0–15 mmHg). The best vital sign metric (MAP) at this LBNP change yielded an AUC of 0.6 (CI 0.38–0.79, 100% sensitivity, 25% specificity). Out-of-sample predictive performance from machine learning models were strong, especially when combining signals from multiple technologies simultaneously. EIT, alone or in machine learning-based combination, appears promising as a technology for early detection of progression toward hemodynamic instability.

The invasive fall armyworm Spodoptera frugiperda (J. E. Smith) invaded Asia in 2018, colonizing the tropical and southern subtropical regions as well as migrating with the monsoons into Northeast Asia during spring and summer. This has resulted in widespread infestations, with significant impacts on maize production in various Asian countries. Previous studies have shown that the invasion of this pest can alter the species relationships of maize pests, but the actual impact on maize pest management is still unclear. This study investigated the changes in maize pest occurrence and pesticide use in the annual breeding areas of S. frugiperda in Yunnan Province and the Guangxi Zhuang Autonomous Region of China during 2017–2021, based on surveys and interviews with small farmers in maize production. The results showed that S. frugiperda has emerged as the dominant species among maize pests after invasion and colonization, replacing traditional pests such as Ostrinia furnacalis, Spodoptera litura, Agrotis ypsilon, and Rhopalosiphum maidis. The variety of pesticides used for maize pest control has changed from chlorpyrifos, lambda-cyhalothrin, and acetamiprid to emamectin benzoate-based pesticides with high effectiveness against S. frugiperda. Furthermore, the frequency of maize pest chemical applications has increased from an average of 5.88 to 7.21 times per season, with the amounts of pesticides used in summer and autumn maize being significantly higher than in winter and spring maize, thereby increasing application costs by more than 35%. The results of this study clarified the impact of S. frugiperda invasion on maize pest community succession and chemical pesticide use in tropical and south subtropical China, thereby providing a baseline for modifying the regional control strategies for maize pests after the invasion of this relatively new pest.

Abstract CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood. In this study, we uncovered the PTM profiling of CTCF and demonstrated that CTCF can be O-GlcNAcylated and arginine methylated. Functionally, we demonstrated that O-GlcNAcylation inhibits CTCF binding to chromatin. Meanwhile, deficiency of CTCF O-GlcNAcylation results in the disruption of loop domains and the alteration of chromatin loops associated with cellular development. Furthermore, the deficiency of CTCF O-GlcNAcylation increases the expression of developmental genes and negatively regulates maintenance and establishment of stem cell pluripotency. In conclusion, these results provide key insights into the role of PTMs for the 3D chromatin structure.

Abstract When testing earthquake simulation shaking tables, it is commonly assumed that the test load, table, and actuator are integrated, which differs significantly from the actual situation and negatively impacts the accuracy of system waveform reproduction. This paper simplifies the connection between the three as a spring-damping model for simulation modeling. The effects of different load mass, different connection intrinsic frequency, different connection damping ratios, and other factors on the control performance of the system are analyzed, and based on the results of the analysis, a method to improve the effects of the connection characteristics on the performance of the system, called flexible connection reaction force compensation algorithm, is proposed. Resonance peaks caused by flexible connections reduce the effective bandwidth. To broaden the bandwidth and enhance system stability, the paper introduces a flexible connection force compensation algorithm based on a multi-parameter control algorithm to compensate for the interaction force caused by the connection characteristics. This compensation strategy expands the effective bandwidth, eliminates resonance peaks, improves the waveform correlation coefficient (CC), and reduces the root-mean-square error (RMSE).

Repairing mechanical hole out of dimension tolerance of aluminum (Al) alloy has a high potential and function in manufacturing industries. To achieve a reliably repaired hole of 2024 Al alloy, radial-additive friction stir repairing (R-AFSR) was developed, and this technology was divided into the regularizing-defect and repairing stages. Results showed that by adjusting the filling depth of pinless tool at the regularizing-defect stage and the rotating direction of tool with threaded pin at the repairing stage, the sufficient metallurgical bonding was achieved and then the kissing bond defect was eliminated due to not only the enlarged stir zone but also the heightened pressure and temperature. Under the suitable processing parameters, the maximum tensile and compressive shear strengths of the repaired hole by R-AFSR were 281.8 and 206.8 MPa, which were 89.1 % and 95.1 % of those of the standard hole. The fracture mode of repaired hole was decided by the metallurgical bonding effect of interface between filling material (FM) and base material (BM) (the FM/BM interface), and three fracture modes, including tensile fracture, tensile-plug fracture and plug fracture, were obtained. The R-AFSR provides a new approach to acquiring a high-quality repaired mechanical hole of Al alloy.

ABSTRACTIn the context of global warming and the increasing water shortage in dry areas, it is necessary to find a sustainable pathway for utilization of land resources (ULR) to solve these problems. For this purpose, using socioeconomic and environmental indicators from 2006 to 2018 and taking the Tarim Basin, China as an example, this study employed an integrated approach composed of the indicator evaluation system (IES) and the System Dynamics (SD) model to evaluate the possibility of sustainable ULR in the basin. During the simulation, three scenarios namely traditional development (TD), economic priority (EP) and harmonious development (HD) were designed, and different thresholds were set for each indicator of potential ULR in each sub-region to predict their future development status. The IES was established to derive the sustainable utilization degree (SUD) of ULR. The results show that the SUD in Tarim in 2030 is likely be 0.60 (TD), 0.62 (EP) and 0.68 (HD), indicating that only in HD scenario is it possible to find pathway to solve water scarcity problem and achieve sustainable ULR. This study provides a supportive idea for decision-making on sustainable ULR in Tarim and also an approach for similar sustainability assessment in other dry areas.

Abstract The abandoned pond‐to‐mangrove restoration project provides greater advantages than tidal flats afforestation in restoring mangrove ecosystem services and will be the primary method for mangrove restoration in the future. The existing methods for abandoned pond‐to‐mangrove restoration include artificial restoration through ‘dike‐breaking, filling with imported soil and tree planting’ and natural restoration through ‘dike‐breaking and natural succession’. However, little is known about which restoration strategy (natural or artificial restoration) provides more benefits to the biodiversity of mangrove macrobethos. Given a prevailing view suggested that artificial restoration should be the preferred approach for accelerating recovery of biodiversity and vegetation structure in tropical regions, we hypothesised higher macrobenthic biodiversity and more complex community structure in artificial restoration than in natural restoration. To test this hypothesis, macrobenthic biodiversity and ecological processes were monitored in a typical abandoned pond‐to‐mangrove area of Dongzhaigang Bay, China, where artificial and natural restoration methods were used concurrently. Differences in macrobenthic biodiversity, community structure and ecological processes were compared using diversity indices, complex network analysis and null models. Similar species composition and ecological niche overlap and width among macrobenthos were observed at artificial and natural restoration sites. The biotic heterogeneity and interaction among macrobenthos were higher at the natural restoration sites than at the artificial restoration sites. Macrobenthos community assembly at natural and artificial restoration sites was both determined by deterministic processes, with environmental filtering dominating, which explained 52% and 54% of the variations in macrobenthic community structures respectively. Although our findings did not validate the research hypothesis, higher biotic heterogeneity and species interaction among macrobenthos could support natural restoration as the primary method for abandoned pond‐to‐mangrove projects, because it is a nature‐based solution for mangrove restoration.

Municipal solid waste incineration for power generation is significant for reducing and reusing solid waste. The study conducted an integrated assessment of environment and economy on municipal solid waste incineration in China, from a “cradle to grave” perspective using 1 tonne of municipal solid waste incineration as the functional unit. The environmental impacts of each month are also calculated to analyze the dynamic change throughout one year. The results indicate that the environmental impacts are mainly concentrated in marine ecotoxicity, freshwater ecotoxicity, human carcinogenic toxicity, and human non-carcinogenic toxicity. Flue gas purification, waste incineration and transportation are the key processes, which account for 65.61 %, 18.50 %, and 11.93 % of the overall environmental impact, respectively. Urea, activated carbon, chelating agent (EDTA) and diesel fuel for transportation are key factors. The life cycle cost (LCC) is 132.26 RMB/t of waste, of which the initial capital causes the largest economic cost. When considering power generated from municipal solid waste incineration to replace electricity supply from the power grid, it achieves significant environmental benefits and the normalized environmental impact value changes from 0.85 to −12.19. The findings provide references for municipal solid waste treatment to mitigate the environmental impact and reduce the economic burden across the entire life cycle.

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

ABSTRACT: Eggshell is one of the most important indicators of egg quality, and due to low shell strength, pimple eggs (PE) are more susceptible to breakage, thus causing huge economic losses to the egg industry. At the current time, the molecular mechanisms that regulate the formation of pimple eggs are poorly understood. In this study, uterine tissues of PE-laying hens (n = 8) and normal egg (NE) -laying hens (n = 8) were analyzed by whole transcriptome sequencing, and a total of 619 differentially expressed mRNAs (DE mRNAs), 122 differentially expressed lncRNAs (DE lncRNAs) and 21 differentially expressed miRNAs (DE miRNAs) were obtained. Based on the targeting relationship among DE mRNAs, DE lncRNAs and DE miRNAs, we constructed a competitive endogenous RNA (ceRNA) network including 12 DE miRNAs, 19 DE lncRNAs, and 128 DE mRNAs. Considering the large amount of information contained in the network, we constructed a smaller ceRNA network to better understand the complex mechanisms of pimple egg formation. The smaller ceRNA network network contains 7 DE lncRNAs (LOC107056551, LOC121109367, LOC121108909, LOC121108862, LOC112530033, LOC121113165, LOC107054145), 5 DE miRNAs (gga-miR-6568-3p, gga-miR-31-5p, gga-miR-18b-3p, gga-miR-1759-3p, gga-miR-12240-3p) and 7 DE mRNAs (CABP1, DNAJC5, HCN3, HPCA, IBSP, KCNT1, OTOP3), and these differentially expressed genes may play key regulatory roles in the formation of pimpled eggs in hens. This study provides the overall expression profiles of mRNAs, lncRNAs and miRNAs in the uterine tissues of hens, which provides a theoretical basis for further research on the molecular mechanisms of pimpled egg formation, and has potential applications in improving eggshell quality.

Abstract This study investigates correlates of anti-S1 antibody response following COVID-19 vaccination in a U.S. population-based meta-cohort of adults participating in longstanding NIH-funded cohort studies. Anti-S1 antibodies were measured from dried blood spots collected between February 2021-August 2022 using Luminex-based microsphere immunoassays. Of 6245 participants, mean age was 73 years (range, 21-100), 58% were female, and 76% were non-Hispanic White. Nearly 52% of participants received the BNT162b2 vaccine and 48% received the mRNA-1273 vaccine. Lower anti-S1 antibody levels are associated with age of 65 years or older, male sex, higher body mass index, smoking, diabetes, COPD and receipt of BNT16b2 vaccine (vs mRNA-1273). Participants with a prior infection, particularly those with a history of hospitalized illness, have higher anti-S1 antibody levels. These results suggest that adults with certain socio-demographic and clinical characteristics may have less robust antibody responses to COVID-19 vaccination and could be prioritized for more frequent re-vaccination.

Abstract Electrochemical carbon dioxide reduction reaction using sustainable energy is a promising approach of synthesizing chemicals and fuels, yet is highly energy intensive. The oxygen evolution reaction is particularly problematic, which is kinetically sluggish and causes anodic carbon loss. In this context, we couple CO2 electrolysis with hydrogen oxidation reaction in a single electrochemical cell. A Ni(OH)2/NiOOH mediator is used to fully suppress the anodic carbon loss and hydrogen oxidation catalyst poisoning by migrated reaction products. This cell is highly flexible in producing either gaseous (CO) or soluble (formate) products with high selectivity (up to 95.3%) and stability (>100 h) at voltages below 0.9 V (50 mA cm−2). Importantly, thanks to the “transferred” oxygen evolution reaction to a water electrolyzer with thermodynamically and kinetically favored reaction conditions, the total polarization loss and energy consumption of our H2-integrated CO2 reduction reaction, including those for hydrogen generation, are reduced up to 22% and 42%, respectively. This work demonstrates the opportunity of combining CO2 electrolysis with the hydrogen economy, paving the way to the possible integration of various emerging energy conversion and storage approaches for improved energy/cost effectiveness.

Abstract Background Sodium-Glucose cotransporter 1 and 2 (SGLT1/2) belong to the family of glucose transporters, encoded by SLC5A1 and SLC5A2, respectively. SGLT2 is almost exclusively expressed in the renal proximal convoluted tubule cells. SGLT1 is expressed in the kidneys but also in other organs throughout the body. Many SGLT inhibitor drugs have been developed based on the mechanism of blocking glucose (re)absorption mediated by SGLT1/2, and several have gained major regulatory agencies’ approval for treating diabetes. Intriguingly these drugs are also effective in treating diseases beyond diabetes, for example heart failure and chronic kidney disease. We recently discovered that SGLT1 is upregulated in the airway epithelial cells derived from patients of cystic fibrosis (CF), a devastating genetic disease affecting greater than 70,000 worldwide. Results In the present work, we show that the SGLT1 upregulation is coupled with elevated endoplasmic reticulum (ER) stress response, indicated by activation of the primary ER stress senor inositol-requiring protein 1α (IRE1α) and the ER stress-induced transcription factor X-box binding protein 1 (XBP1), in CF epithelial cells, and in epithelial cells of other stress conditions. Through biochemistry experiments, we demonstrated that the spliced form of XBP1 (XBP1s) acts as a transcription factor for SLC5A1 by directly binding to its promoter region. Targeting this ER stress → SLC5A1 axis by either the ER stress inhibitor Rapamycin or the SGLT1 inhibitor Sotagliflozin was effective in attenuating the ER stress response and reducing the SGLT1 level in these cellular model systems. Conclusions The present work establishes a causal relationship between ER stress and SGLT1 upregulation and provides a mechanistic explanation why SGLT inhibitor drugs benefit diseases beyond diabetes.

Abstract Although previous studies have made some clear leap in learning latent dynamics from high‐dimensional representations, the performances in terms of accuracy and inference time of long‐term model prediction still need to be improved. In this study, a deep convolutional network based on the Koopman operator (CKNet) is proposed to model non‐linear systems with pixel‐level measurements for long‐term prediction. CKNet adopts an autoencoder network architecture, consisting of an encoder to generate latent states and a linear dynamical model (i.e., the Koopman operator) which evolves in the latent state space spanned by the encoder. The decoder is used to recover images from latent states. According to a multi‐step ahead prediction loss function, the system matrices for approximating the Koopman operator are trained synchronously with the autoencoder in a mini‐batch manner. In this manner, gradients can be synchronously transmitted to both the system matrices and the autoencoder to help the encoder self‐adaptively tune the latent state space in the training process, and the resulting model is time‐invariant in the latent space. Therefore, the proposed CKNet has the advantages of less inference time and high accuracy for long‐term prediction. Experiments are performed on OpenAI Gym and Mujoco environments, including two and four non‐linear forced dynamical systems with continuous action spaces. The experimental results show that CKNet has strong long‐term prediction capabilities with sufficient precision.

Surface defects on the track may lead to accidents and pose a serious threat to the safety of passengers and staff. Regarding current detection methods, there are still shortcomings: manual detection is time-consuming and labor-intensive; vibration acceleration and machine vision methods rely solely on a single sensor data type, making them vulnerable to external interference, including coupled vibrations and oil contamination, leading to errors. The article proposes a new model for identifying the surface condition of steel rails using multimodal data of vibration and images: the multi-scale feature dynamic fusion network (MFDF-Net). Features are categorized into three scales: shallow, intermediate, and deep. An attention mechanism is incorporated to emphasize features of different scales, enabling dynamic weighting during the fusion of vibration and multi-scale features. Additionally, attention is given to fundamental features such as frequency and edge characteristics, as well as abstract features like the correlation between time series and image structure. MFDF-Net utilizes data collected by service vehicles to demonstrate that, in evaluating the model’s stability, the average accuracy of the test set across multiple training sessions reaches 99.333%. This represents a 2.67% improvement over the test accuracy of a single vibration mode and a 7.8% enhancement over that of a single image mode. These results indicate that the fusion network effectively discerns rail surface states, with multi-modal fusion offering higher precision and improved robustness compared to single-mode rail surface state analysis. This network holds promise for advancing intelligent diagnosis of rail surface defects.

Abstract Background Polycystic ovarian syndrome (PCOS) is recognized as the most prevalent endocrine disorder among women of reproductive age. While the utilization of assisted reproductive technology (ART) has resulted in favorable outcomes for infertility treatment in PCOS patients, the inherent pathophysiological features of the condition give rise to complications and consequences during pregnancy and delivery for both the mother and offspring. This study was to assess the correlation between maternal PCOS and various pregnancy complications and neonatal outcomes undergone ART. Methods A systematic search was conducted on PubMed, EmBase, and the Cochrane Library to identify observational studies that investigated the association between PCOS and the risk of various pregnancy complications and neonatal outcomes, including gestational diabetes mellitus (GDM), hypertension in pregnancy (PIH), preeclampsia (PE), preterm birth, abortion, congenital malformations (CA), small for gestational age (SGA), large for gestational age (LGA), low birth weight (LBW), macrosomia, neonatal intensive care unit (NICU) admission and birth weight. Eligible studies were selected based on predetermined inclusion and exclusion criteria. The meta-analysis was conducted using Review Manager and Stata software, with odds ratios (ORs) or mean difference (MD), confidence intervals (CIs), and heterogeneity (I2) being calculated. The search was conducted up to March 2023. Results A total of 33 studies with a combined sample size of 92,810 participants were identified. The findings indicate that PCOS is significantly associated with an increased risk of GDM (OR 1.51, 95% CI:1.17–1.94), PIH (OR 1.72, 95% CI:1.25–2.39), PE (OR 2.12, 95% CI:1.49–3.02), preterm birth (OR 1.29, 95% CI:1.21–1.39), and LBW (OR 1.29, 95% CI:1.14–1.47). In subgroup analyses, the risks of GDM (OR 1.80, 95% CI:1.23–2.62) and abortion (OR 1.41, 95% CI:1.08–1.84) were elevated in fresh embryo transferred (ET) subgroup, whereas elevated risk of PE (OR 1.82, 95% CI:1.17–2.83) and preterm birth (OR 1.31, 95% CI:1.21–1.42) was identified in frozen ET subgroup. Whatever with or without hyperandrogenism, patients with PCOS had a higher risk in preterm birth (OR 1.69, 95% CI: 1.31–2.18; OR 1.24, 95% CI:1.02–1.50) and abortion (OR 1.38, 95% CI:1.12–1.71; OR 1.23, 95% CI:1.06–1.43). Conclusion Our findings suggest that individuals with PCOS undergone ART are at a notably elevated risk for experiencing pregnancy complications and unfavorable neonatal outcomes. Nevertheless, to establish a definitive association between PCOS and pregnancy-related outcomes, it is necessary to conduct extensive prospective, blinded cohort studies and effectively control for confounding variables.

With the opening of industrial networks in the information age, the characteristic of Industrial Control Protocols (ICPs) to transmit plaintext without encryption exposes serious security risks, threatening the safe and stable operation of Industrial Control Systems (ICSs). Exploring the work of mining vulnerabilities in ICPs can use fuzzing to mine potential vulnerabilities in protocols to ensure the safe operation of ICS. However, traditional fuzzing methods require the construction of test cases based on expert experience and the format syntax specification of ICPs. This process is time-consuming, labor-intensive, inefficient, and limited when facing unknown ICPs. In response to these issues, this paper proposes an automated fuzzing method for ICPs based on the Denoising Diffusion Probabilistic Model (DDPM). Specifically, DDPM achieves the conversion from noise to data samples, which can easily and quickly generate test cases. On this basis, we designed a universal fuzzing framework, DiffusionFuzz, that can be applied to most ICPs. The experimental results obtained on ICPs such as Modbus/TCP in the Industrial Attack-Defense Range of the Key Laboratory of Information Security for Petrochemical Industry in Liaoning Province demonstrate that the test cases generated by this method are diverse, and outperform other fuzzing methods in terms of acceptance rate and ability to trigger exceptions. Certainly, DiffusionFuzz can enhance the effectiveness of fuzzing, identify vulnerabilities in ICPs, and thereby reduce potential economic risks and impacts.

[INLINE:1] Neonatal hypoxic-ischemic encephalopathy is often associated with permanent cerebral palsy, neurosensory impairments, and cognitive deficits, and there is no effective treatment for complications related to hypoxic-ischemic encephalopathy. The therapeutic potential of human placental chorionic plate-derived mesenchymal stem cells for various diseases has been explored. However, the potential use of human placental chorionic plate-derived mesenchymal stem cells for the treatment of neonatal hypoxic-ischemic encephalopathy has not yet been investigated. In this study, we injected human placental chorionic plate-derived mesenchymal stem cells into the lateral ventricle of a neonatal hypoxic-ischemic encephalopathy rat model and observed significant improvements in both cognitive and motor function. Protein chip analysis showed that interleukin-3 expression was significantly elevated in neonatal hypoxic-ischemic encephalopathy model rats. Following transplantation of human placental chorionic plate-derived mesenchymal stem cells, interleukin-3 expression was downregulated. To further investigate the role of interleukin-3 in neonatal hypoxic-ischemic encephalopathy, we established an in vitro SH-SY5Y cell model of hypoxic-ischemic injury through oxygen-glucose deprivation and silenced interleukin-3 expression using small interfering RNA. We found that the activity and proliferation of SH-SY5Y cells subjected to oxygen-glucose deprivation were further suppressed by interleukin-3 knockdown. Furthermore, interleukin-3 knockout exacerbated neuronal damage and cognitive and motor function impairment in rat models of hypoxic-ischemic encephalopathy. The findings suggest that transplantation of hpcMSCs ameliorated behavioral impairments in a rat model of hypoxic-ischemic encephalopathy, and this effect was mediated by interleukin-3-dependent neurological function.

Abstract Background Recent studies demonstrated that restoring sagittal alignment to the original Roussouly type can remarkably reduce complication rates after adult spinal deformity surgery. However, there is still no data proving the benefit of maintaining ideal Roussouly shape in the lumbar degenerative diseases and its association with the development of adjacent segment disease (ASD). Thus, this study was performed to validate the usefulness of Roussouly classification to predict the occurrence of ASD after lumbar fusion surgery. Materials and Methods This study retrospectively reviewed 234 consecutive patients with lumbar degenerative diseases who underwent 1- or 2-level fusion surgery. Demographic and radiographic data were compared between ASD and non-ASD groups. The patients were classified by both “theoretical” [based on pelvic incidence (PI)] and “current” (based on sacral slope) Roussouly types. The patients were defined as “matched” if their “current” shapes matched the “theoretical” types and otherwise as “mismatched”. The logistic regression analysis was performed to identify the factors associated with ASD. Finally, clinical data and spinopelvic parameters of “theoretical” and “current” types were compared. Results With a mean follow-up duration of 70.6 months, evidence of ASD was found in the 68 cases. Postoperatively, ASD group had more “current” shapes classified as type 1 or 2 and fewer as type 3 than the non-ASD group (p

High-power linearly polarized fiber lasers are widely used in coherent beam combination, nonlinear frequency conversion, and gravitational wave detection. With the increase in output power, it is challenging for fiber lasers to maintain a high polarization extinction ratio (PER). Combined with intelligent techniques, active polarization control is a prospective method to obtain the laser output with high PER and high stability. We demonstrate a comprehensive model of an active polarization control system. The root mean square propagation (RMS-Prop) algorithm is used to control the non-polarization-maintaining (non-PM) fiber laser to generate linearly polarized laser. The parameters of the RMS-Prop algorithm are theoretically analyzed, including cost function, perturbation amplitude, and global learning rate. The simulation results show that PER is the optimal cost function. When the perturbation amplitude is 0.06 and the global learning rate is 0.6, the system can achieve the optimal control speed and accuracy. By comparison with the stochastic parallel gradient descent (SPGD) algorithm, the RMS-Prop algorithm has an advantage in obtaining higher PER.

Soil fungi play a critical role in the biogeochemical cycles of forest ecosystems. Larix gmelinii is a strong and important timber tree species, which forms close associations with a wide range of soil fungi. However, the temporal-spatial disparity effects on the assembly of soil fungal communities in L. gmelinii forests are poorly understood. To address these questions, a total of 120 samples, including 60 bulk soil and 60 root samples, were collected from Aershan and Genhe in July (summer) and October (autumn)2021. We obtained 7,788 operational taxonomic units (OTUs) after merging, filtering, and rarefying using high-throughput sequencing. The dominant phyla are Basidiomycota, Ascomycota, Mortierellomycota, and Mucoromycota. There were 13 dominant families, among which the families with average relative abundance more than 5% included Thelephoraceae, Mortierellaceae, Archaeorhizomycoaceae, and Inocybaceae. In the functional guilds, symbiotrophic fungi had a relative advantage in the identified functions, and the relative abundances of pathotrophic and saprotrophic fungi varied significantly between sites. There were 12 families differentially expressed across compartments, 10 families differentially expressed between seasons, and 69 families were differentially expressed between sites. The variation in alpha diversity in the bulk soil was greater than that in the rhizosphere soil. Among the three parts (compartment, season, and site), the site had a crucial effect on the beta diversity of the fungal community. Deterministic processes dominated fungal community assembly in Genhe, whereas stochastic processes dominated in Aershan. Soil physicochemical properties and climatic factors significantly affected fungal community structure, among which soil total nitrogen and pH had the greatest effect. This study highlights that spatial variations play a vital role in the structure and assembly of soil fungal communities in L. gmelinii forests, which is of great significance for us in maintaining the health of the forests.

Optical differential operation is an important scheme for image edge detection due to its advantages of high efficiency, real time and low consumption. In this paper, the actively manipulating optical differential operation is proposed in a quasi-PT-symmetric structure containing graphene, and applied to realize edge imaging with tunable contrast. It is found that there are abrupt changes of the in-plane shift and transverse shift in the photonic spin Hall effect at the Fermi energy of 0.4 eV, where the quasi-exceptional points exist according to the degeneracy analysis of scattering matrix eigenvalues. Based on the photonic spin Hall effect near the quasi-exceptional points, we design the optical differential operation whose spatial transfer function is actively manipulated by changing the external electric field to adjust the Fermi energy of graphene. Finally, the edge imaging with different contrast can also be achieved when the optical differential operation is applied to image processing. The actively manipulating optical differential operation opens up new possibilities in microscopic imaging and smart driving.

In high-intensity farming, swiftly and accurately adjusting the proportion of artificially reared pollinators according to the flowering phenology of crops is vital. This adjustment is essential for sustaining crop yields without disrupting the ecological niche of native pollinators. Although advancements in remote sensing provide practical means to gather data on crop coverage and extent, identifying insect-pollinated crops during their initial flowering to guide the deployment of managed pollinators is an underexamined research area. Here, we tested the capability of utilizing Sentinel-2 satellite images combined with a deep learning model to map crop fields during the initial flowering stage of insect-pollinated crops in Zhaosu County, Xinjiang, China. Specifically, we examined rapeseed fields by employing 12 neural network designs to identify images of the initial flowering stage. Different network combinations of three convolutional neural network (CNN) models (U-Net, PSPNet, and DeepLab V3) and four different backbone networks (ResNet-18, ResNet-34, ResNet-50, and ResNet-101) were explored to determine the most effective model for detecting rapeseed fields at the initial flowering stage. A comparison was conducted with Sentinel-2 images obtained at the peak stage of rapeseed flowering. Our results suggest that the use of a deep learning model in combination with Sentinel-2 image data can successfully identify rapeseed fields at the initial flowering stage, thereby offering preliminary insights for the strategic introduction of managed pollinators. The PSPNet model emerged as the superior choice for the identification of rapeseed fields, exhibiting high accuracy in both detection and boundary recognition, with F1 scores of 88.17 % and an intersection over union (IoU) of 53.11 % during initial flowering and F1 scores of 93.33 % with an IoU of 53.49 % during peak flowering. The planting area of rapeseed fields detected by the model in Zhaosu County was 122.16 km2, distributed within an area of 1068 km2. These findings can provide foundational data for informed decisions regarding artificial pollinator supplementation, helping to sustain the health and stability of agricultural ecosystems.

Summary: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The dysfunction of zinc homeostasis participates in the early and advancing malignancy of HCC. However, the prognostic ability of zinc homeostasis in HCC has not been clarified yet. Here, we showed a zinc-homeostasis related risk model in HCC. Five signature genes including ADAMTS5, PLOD2, PTDSS2, KLRB1, and UCK2 were screened out via survival analyses and regression algorithms to construct the nomogram with clinical characteristics. Experimental researches indicated that UCK2 participated in the progression of HCC. Patients with higher risk scores always had worse outcomes and were more associated with immune suppression according to the analyses of immune related-pathway activation, cell infiltration, and gene expression. Moreover, these patients were likely to exhibit more sensitivity to sorafenib and other antitumor drugs. This study highlights the significant prognostic role of zinc homeostasis and suggests potential treatment strategies in HCC.

Summary: Aging is considered a critical factor of poor prognosis in allogenic hemopoietic stem cell transplantation (allo-HSCT). To elucidate the underlying mechanisms, we comprehensively reintegrated our clinical data from patients after allo-HSCT and public single-cell transcriptomic profile from post-allo-HSCT and healthy individuals, demonstrating that old donors were more prone to acute GVHD (aGVHD) with pronounced inflammation accumulation and worse overall survival (OS). We also found the presence of inflammation-related CXCL2+ HSC subpopulation during aging with significantly enriched pro-inflammatory pathways. Shifting attention to the HSC microenvironment, we deciphered that IL-1/IL-6 and TRAIL (i.e., TNFSF10) ligand‒receptor pair serves as the crucial bridge between CD14/CD16 monocytes and hematopoietic stem/progenitor cells (HSPCs). The profound upregulation of these signaling pathways during aging finally causes HSC dysfunction and lineage-biased differentiation. Our findings provide the theoretical basis for achieving tailored GVHD management and enhancing allo-HSCT regimens efficacy for aged donors.

ABSTRACT: White striping (WS) is a common myopathy seen in fast-growing broilers. Studies have demonstrated that chitosan is effective as an antioxidant and has antiobesity and fat-absorption reduction properties. We hypothesized that the dietary supplementation of chitosan would have similar effects when fed to fast-growing broilers and would thus lower WS incidence and improve meat quality. One hundred twenty-six broilers were fed corn-soy diets. The grower and finisher diets contained either 0, 0.2, or 0.4% chitosan. After a 6 wk growth period, birds were euthanized, and then WS and gross pathology scores were assessed. Pectoralis major tissues were collected to evaluate cook loss, drip loss, histopathology scores, and the gene expression of CCR7, LECT2, CD36, PPARG, and PTGS2. There were no significant differences between the broiler weights, thus chitosan did not appear to compromise the overall growth of the broilers. Female broilers fed 0.4% chitosan had the lowest WS incidence, while male broiler fed 0.4% chitosan had the least cook loss. However, gene expression analyses did not offer insight into any grossly or histologically visualized differences in the muscles. Thus, while we can postulate that chitosan could have some positive effect in reducing WS incidence and improving meat quality, further studies are required to better scrutinize the mechanisms by which chitosan affects WS and other such myopathies in fast-growing broilers.

The increasing integration of wind power in power systems necessitates the probabilistic assessment of various uncertain factors. In operational planning, modeling short-term scale uncertainties, i.e., wind power forecast errors, plays an important role. In this paper, according to the different forecast values, the corresponding probability distributions of wind power forecast errors are developed using a data-driven manner. Then, the polynomial chaos expansion surrogate is developed to facilitate the probabilistic load margin assessment considering wind power forecast errors. The effectiveness of the forecast error model is verified using the historical data of realistic wind power plants. The results show that the probability distributions of forecast errors vary with the level of forecast values. Moreover, the performance of the polynomial chaos expansion surrogate in estimating probabilistic load margin is validated in the IEEE 30-bus system. The results demonstrate that the versatile forecast error distributions significantly impact the characteristics of load margin. Moreover, the polynomial chaos expansion surrogate can accelerate the load margin assessment compared to the Monter Carlo simulation while retaining the same accuracy.

Probabilistic power flow is one of the fundamental tools for assessing the impacts of uncertainties on the operating states of power systems. However, this analysis requires sufficient historical data to obtain precise probability distributions of input variables, which may not be met in practical engineering problems. In this paper, input variables with insufficient data are represented by parametric probability boxes (p-boxes), i.e., probability distributions with imprecise parameters. In order to facilitate the uncertain power flow calculation with p-boxes, a polynomial chaos expansion-based method is developed. Moreover, the interval-valued Borgonovo index is proposed for global sensitivity analysis and to identify the input variables that have critical impacts on systems. The simulations in IEEE 14-bus and 118-bus systems verify the accuracy and efficiency of the proposed method by comparing it with the conventional double-loop sampling method.