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Based on the oil and gas exploration in western depression of the Qaidam Basin, NW China, combined with the geochemical, seismic, logging and drilling data, the basic geological conditions, oil and gas distribution characteristics, reservoir-forming dynamics, and hydrocarbon accumulation model of the Paleogene whole petroleum system (WPS) in the western depression of the Qaidam Basin are systematically studied. A globally unique ultra-thick mountain-style WPS is found in the western depression of the Qaidam Basin. Around the source rocks of the upper member of the Paleogene Lower Ganchaigou Formation, the structural reservoir, lithological reservoir, shale oil and shale gas are laterally distributed in an orderly manner and vertically overlapped from the edge to the central part of the lake basin. The Paleogene WPS in the western depression of the Qaidam Basin is believed unique in three aspects. First, the source rocks with low organic matter abundance are characterized by low carbon and rich hydrogen, showing a strong hydrocarbon generating capacity per unit mass of organic carbon. Second, the saline lake basinal deposits are ultra-thick, with mixed deposits dominating the center of the depression, and strong vertical and lateral heterogeneity of lithofacies and storage spaces. Third, the strong transformation induced by strike-slip compression during the Himalayan resulted in the heterogeneous enrichment of oil and gas in the mountain-style WPS. As a result of the coordinated evolution of source-reservoir-caprock assemblage and conducting system, the Paleogene WPS has the characteristics of “whole process” hydrocarbon generation of source rocks which are low-carbon and hydrogen-rich, “whole depression” ultra-thick reservoir sedimentation, “all direction” hydrocarbon adjustment by strike-slip compressional fault, and “whole succession” distribution of conventional and unconventional oil and gas. Due to the severe Himalayan tectonic movement, the western depression of the Qaidam Basin evolved from depression to uplift. Shale oil is widely distributed in the central lacustrine basin. In the sedimentary system deeper than 2 000 m, oil and gas are continuous in the laminated limy-dolomites within the source rocks and the alga limestones neighboring the source kitchen, with intercrystalline pores, lamina fractures in dolomites and fault-dissolution bodies serving as the effective storage space. All these findings are helpful to supplement and expand the WPS theory in the continental lake basins in China, and provide theoretical guidance and technical support for oil and gas exploration in the Qaidam Basin.

Abstract Bitter gourd wilt, a severe vascular disease triggered by the soilborne pathogen Fusarium oxysporum f. sp. momordicae (FOM), markedly constrains bitter gourd yield. In this study, a novel strain BF19 of Brevibacillus brevis was isolated and identified, exhibiting strong antimicrobial activity against FOM through in vivo and in vitro experiments. To comprehensively assess the biocontrol potential of strain BF19, we conducted phenotypic, phylogenetic, and comparative genomics analyses. Phenotypic analysis revealed that BF19 exhibited 53.33% biocontrol efficacy and significantly increased the average plant height, root fresh weight, and dry weight. Whole-genome sequencing and comparative genomic analysis revealed numerous potential genes associated with biocontrol mechanisms in BF19. Importantly, the integration of metabolic cluster prediction with liquid chromatography‒tandem mass spectrometry (LC‒MS/MS) revealed the presence of a macrobrevin antibiotic, a product of polyketide synthases (PKSs), predominantly in BF19 fermentation products. The effectiveness of the Br. brevis strain BF19 and its crude extract against bitter gourd wilt has also been confirmed. This study provides a genetic framework for future investigations on PKSs and establishes a scientific basis for optimizing field applications of microbial biopesticides derived from Br. brevis BF19.

Abstract Psoriasis is a chronic inflammatory skin disorder with multiple causes, including genetic and environmental factors. Despite advances in treatment, there remains a need to identify novel therapeutic targets. A Mendelian randomization (MR) analysis was conducted to identify therapeutic targets for psoriasis. Data on cis-expression quantitative trait loci were obtained from the eQTLGen Consortium (n = 31,684). Summary statistics for psoriasis (outcome) were sourced from the GWAS Catalog with a sample size of 484,598, including 5,427 cases and 479,171 controls. Colocalization analysis was used to assess whether psoriasis risk and gene expression were driven by shared single nucleotide polymorphisms. Drug prediction and molecular docking were utilized to validate the pharmacological value of the drug targets. The MR analysis found that 81 drug targets were significantly associated, and two (TYK2 and PRSS36) were supported by colocalization analysis (PP.H4 > 0.80). Phenome-wide association studies did not show any associations with other traits at the gene level. Biologically, these genes were closely related to immune function. Molecular docking revealed strong binding with drugs and proteins, as supported by available structural data. This study validated TYK2 as a drug target for psoriasis, in line with its existing clinical use, including the development of decucravacitinib. PRSS36 is a potential novel target requiring further investigation.

Abstract Rain is a common weather phenomenon, and the challenge of removing rain streaks from a single image is crucial due to its detrimental impact on image quality and the extraction of valuable background information. Existing methods commonly rely on specific assumptions regarding rain models, which restricts their ability to accommodate a wide range of real-world scenarios. To overcome this limitation, these methods often require complex optimization techniques or stepwise refinement strategies. In this paper, we propose a novel wide rectangular regional block and dual attention complementary enhancement deraining kernel prediction subnet to meet the challenge. The network called WRRDANet consists of a kernel prediction subnet and pixel-wise dilation filtering. In the kernel prediction subnet, we capture more specific contextual background information and complex pixel-wise kernels. Afterward, the learned pixel-wise multi-scale kernels from the kernel prediction subnet are used to perform dilation filtering on the original rainy image, effectively restoring richer background details by expanding the scope of deraining to a larger extent. We conducted a comprehensive evaluation using synthetic and real rainfall datasets to demonstrate the effectiveness of our approach. The results, both qualitatively and quantitatively, indicate that our approach outperforms other popular rain removal methods.

Abstract Teratoma, due to its remarkable ability to differentiate into multiple cell lineages, is a valuable model for studying human embryonic development. The similarity of the gene expression and chromatin accessibility patterns in these cells to those observed in vivo further underscores its potential as a research tool. Notably, teratomas derived from human naïve (pre-implantation epiblast-like) pluripotent stem cells (PSCs) have larger embryonic cell diversity and contain extraembryonic lineages, making them more suitable to study developmental processes. However, the cell type-specific epigenetic profiles of naïve PSC teratomas have not been yet characterized. Using single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), we analyzed 66,384 cell profiles from five teratomas derived from human naïve PSCs and their post-implantation epiblast-like (primed) counterparts. We observed 17 distinct cell types from both embryonic and extraembryonic lineages, resembling the corresponding cell types in human fetal tissues. Additionally, we identified key transcription factors specific to different cell types. Our dataset provides a resource for investigating gene regulatory programs in a relevant model of human embryonic development.

Catenary optics enables metasurfaces with higher efficiency and wider bandwidth, and is highly anticipated in the imaging system, super-resolution lithography, and broadband absorbers. However, the periodic boundary approximation without considering aperiodic electromagnetic crosstalk poses challenges for catenary optical devices to reach their performance limits. Here, perfect control of both local geometric and propagation phases is realized through field-driven optimization, in which the field distribution is calculated under real boundary conditions. Different from other optimization methods requiring a mass of iterations, the proposed design method requires less than ten iterations to get the efficiency close to the optimal value. Based on the library of shape-optimized catenary structures, centimeter-scale devices can be designed in ten seconds, with the performance improved by ~15%. Furthermore, this method has the ability to extend catenary-like continuous structures to arbitrary polarization, including both linear and elliptical polarizations, which is difficult to achieve with traditional design methods. It provides a way for the development of catenary optics and serves as a potent tool for constructing high-performance optical devices.

Abstract Repeated and widespread use of single chemical pesticides raises concerns about efficiency and safety, developing multi-component synergistic pesticides provides a new route for efficient control of diseases. Most commercial compound formulations are open systems with non-adjustable released rates, resulting in a high frequency of applications. Meanwhile, although nano pesticide delivery systems constructed with different carrier materials have been extensively studied, realizing their actual scale-up production still has important practical significance due to the large-scale field application. In this study, a boscalid and pyraclostrobin dual-loaded nano pesticide system (BPDN) was constructed with industrial-grade carrier materials to facilitate the realization of large-scale production. The optimal industrial-scale preparation mechanism of BPDN was studied with surfactants as key factors. When agricultural emulsifier No.600 and polycarboxylate are used as the ratio of 1:2 in the preparation process, the BPDN has a spherical structure with an average size of 270 nm and exhibits superior physical stability. Compared with commercial formulation, BPDN maintains rate-stabilized release up to 5 times longer, exhibits better dispersion and spreading performance on foliar, has more than 20% higher deposition amounts, and reduces loss. A single application of BPDN could efficiently control tomato gray mold during the growing period of tomatoes due to extended duration and combinatory effectiveness, reducing two application times and labor costs. Toxicology tests on various objects systematically demonstrated that BPDN has improved safety for HepG2 cells, and nontarget organism earthworms. This research provides insight into creating safe, efficient, and environmentally friendly pesticide production to reduce manual operation times and labor costs. Accompanied by production strategies that can be easily scaled up industrially, this contributes to the efficient use of resources for sustainable agriculture.

ABSTRACT Acanthamoeba species are among the most common free-living amoeba and ubiquitous protozoa, mainly distributed in water and soil, and cause Acanthamoeba keratitis (AK) and severe visual impairment in patients. Although several studies have reported genomic characteristics of Acanthamoeba, limited sample sizes and sources have resulted in an incomplete understanding of the genetic diversity of Acanthamoeba from different sources. While endosymbionts exert a significant influence on the phenotypes of Acanthamoeba, including pathogenicity, virulence, and drug resistance, the species diversity and functional characterization remain largely unexplored. Herein, our study sequenced and analyzed the whole genomes of 19 Acanthamoeba pathogenic strains that cause AK, and by integrating publicly available genomes, we sampled 29 Acanthamoeba strains from ocular, environmental, and other sources. Combined pan-genomic and comparative functional analyses revealed genetic differences and evolutionary relationships among the different sources of Acanthamoeba, as well as classification into multiple functional groups, with ocular isolates in particular showing significant differences that may account for differences in pathogenicity. Phylogenetic and rhizome gene mosaic analyses of ocular Acanthamoeba strains suggested that genomic exchanges between Acanthamoeba and endosymbionts, particularly potential antimicrobial resistance genes trafficking including the adeF, amrA, and amrB genes exchange events, potentially contribute to Acanthamoeba drug resistance. In conclusion, this study elucidated the adaptation of Acanthamoeba to different ecological niches and the influence of gene exchange on the evolution of ocular Acanthamoeba genome, guiding the clinical diagnosis and treatment of AK and laying a theoretical groundwork for developing novel therapeutic approaches.IMPORTANCEAcanthamoeba causes a serious blinding keratopathy, Acanthamoeba keratitis, which is currently under-recognized by clinicians. In this study, we analyzed 48 strains of Acanthamoeba using a whole-genome approach, revealing differences in pathogenicity and function between strains of different origins. Horizontal transfer events of antimicrobial resistance genes can help provide guidance as potential biomarkers for the treatment of specific Acanthamoeba keratitis cases.

We study dual AGN host galaxy morphologies at $z=2$ using the ASTRID simulation, selecting black hole (BH) pairs with small separation ($\Delta r10^7M_\odot$), and luminosity ($L_{\text{bol,12}}>10^{43}\rm{erg/s}$). We kinematically decompose (using MORDOR) $\sim1000$ dual AGN hosts into standard components - a 'disk' (thin and thick disk, pseudo-bulge) and 'bulge' (bulge and halo) and define disk-dominated galaxies by the disk-to-total $D/T\geq0.5$. In ASTRID, $60.9\pm2.1\%$ of dual AGN hosts (independent of separation) are disk-dominated, with the $D/T$ distribution peaking at $\sim0.7$. In dual-AGN hosts, the $D/T$ increases from $\sim17\% $ at $M_{\rm *}\sim 10^{9} M_{\odot}$ to $ 64\% $ for $M_{\rm *} \sim 10^{11.5} M_{\odot}$, and the pseudo-bulge is the dominant component of the disk fraction at the high mass end. Moreover, dual AGN hosts exhibit a higher fraction of disk/large pseudo-bulge than single-AGN hosts. The Disk-to-Total ratio is approximately constant with BH mass or AGN luminosity. We also create mock images of dual AGN host galaxies, employing morphological fitting software Statmorph to calculate morphological parameters and compare them with our kinematic decomposition results. Around $83.3\pm2.4\%$ of galaxies display disk-like profiles, of which $\sim60.7\pm2.2\%$ are kinematically confirmed as disks. Se\'rsic indices and half-mass radii of dual AGN host galaxies align with observational measurements from HST at $z\sim2$. Around $34\%$ are identified as mergers from the $\text{Gini}-M_{20}$ relation. We find two dual AGN hosted by galaxies that exhibit disk-like se\'rsic index $n_{12}0.5$, which are in remarkable agreement with properties of recently discovered dual quasars in disk galaxies at $z\sim 2$.

ObjectiveTo explore the association between representative insulin resistance (IR) indices and the risk of kidney stone disease in an American adult population. The representative IR indices referred to metabolic score for IR (METS-IR), triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, triglyceride glucose-body mass index (TyG-BMI), visceral adiposity index (VAI), and homeostatic model assessment of IR (HOMA-IR).MethodsWe investigated adult participants who joined the 2015–2018 National Health and Nutrition Examination Survey (NHANES) and reported kidney stone histories. Weighted proportions, multivariable regression analysis, and restricted cubic splines were used to evaluate the associations between IR indices and kidney stones after their adjustment for gender, age, race, education, smoking status, alcohol drinking frequency, hypertension and diabetes status, physical activity level, water intake, and levels of calcium, cholesterol, and uric acid.ResultsA total of 19,225 participants were included. The weighted prevalence of kidney stone was 11.1%. A multivariable logistic regression model showed a dose–response relationship between the METS-IR and kidney stone [odds ratio (OR) = 1.02, 95% confidence interval (CI) (1.01, 1.04), p

Mepiquat chloride (1,1-dimethyl piperidinium chloride, DPC) is a representative plant growth regulator which can regulate the source-sink relationship for yield increase and shape ideal plant type for mechanical cultivation. Here we show a DPC adsorbed layered double hydroxide (DPC-LDH) architecture with enhanced controlled release property and soil distribution. By drip irrigation on cotton, it makes total dosage of DPC reduced from 270 to 90 g/ha, while the frequency decreased from 5 to 2 times. The unique supramolecular interaction is confirmed as the basis of controlled release behavior. Moreover, except for the physical resistance to the sedimentation brought by the lamellar LDH, the enhanced electrostatic interaction makes DPC-LDH the dominant distribution in soil. It improves the efficiency of DPC molecules absorbed by cotton plants and greatly saves the inputs in labor and chemicals. This method is expected to achieve the yield increase and agricultural sustainability by energy saving and emission reduction.

Purpose: To evaluate the diagnosis performance of digital mammography (DM) and digital breast tomosynthesis (DBT), DM combined DBT with AI-based strategies for breast mass ≤ 2 cm. Materials and methods: DM and DBT images in 483 patients including 512 breast masses were acquired from November 2018 to November 2019. Malignant and benign tumours were determined by biopsies using histological analysis and follow-up within 24 months. The radiomics and deep learning methods were employed to extract the breast mass features in images and finally for benign and malignant classification. The DM, DBT and DM combined DBT (DM + DBT) images were fed into radiomics and deep learning models to construct corresponding models, respectively. The area under the receiver operating characteristic curve (AUC) was employed to estimate model performance. An external dataset of 146 patients from March 2021 to December 2022 from another center was enrolled for external validation. Results: In the internal testing dataset, compared with the DM model and the DBT model, the DM + DBT models based on radiomics and deep learning both showed statistically significant higher AUCs [0.810 (RA-DM), 0.823 (RA-DBT) and 0.869 (RA-DM + DBT), P ≤ 0.001; 0.867 (DL-DM), 0.871 (DL-DBT) and 0.908 (DL-DM + DBT), P = 0.001]. The deep learning models present superior to the radiomics models in the experiments with only DM (0.867 vs 0.810, P = 0.001), only DBT (0.871 vs 0.823, P = 0.001) and DM + DBT (0.908 vs 0.869, P = 0.003). Conclusions: DBT has a clear additional value for diagnosing breast mass less than 2 cm compared with only DM. AI-based methods, especially deep learning, can help achieve excellent performance.

ABSTRACTIn this study, we used high-throughput sequencing technology to analyze the diversity and predict gene function of intestinal bacteria from captive black-capped capuchin in two wildlife parks. The results showed that the composition of intestinal gut bacterial diversity was significantly higher in black-capped capuchins monkeys from ES than HT. Moreover, high similarity of intestinal bacteria of black-capped capuchins at the same site was found by sample stratum clustering. Black-capped capuchins intestinal bacteria can be clustered into 2296 ASVs, belonging to 16 phyla, 99 families and 210 genera, respectively. The dominant phyla were Bacteroidota and Firmicutes in the intestinal bacteria of black-capped capuchins, but there were differences in the dominant bacterial families and dominant bacterial genera between ES and HT, and the bacterial families with significant differences had correspondence with bacterial genera. The results provide a basis for the study of intestinal bacteria in black-capped capuchins and the isolation and purification of dominant bacteria. The results of this study fill the gap in the study of intestinal bacterial diversity and its gene functions in black-capped capuchins, and provide a reference for the isolation of dominant bacteria in black-capped capuchins’ intestinal microbes and the discovery and study of novel functional genes.

Patients with chronic lymphocytic leukemia (CLL) respond well to initial treatment with the Bcell lymphoma 2 (BCL2) inhibitor venetoclax. Upon relapse, they often retain sensitivity to BCL2 targeting, but durability of response remains a concern. We hypothesize that targeting both BCL2 and B-cell lymphoma-extra large (BCLXL) will be a successful strategy to treat CLL, including for patients who relapse on venetoclax. To test this hypothesis, we conducted a pre-clinical investigation of LP-118, a highly potent inhibitor of BCL2 with moderate BCLXL inhibition to minimize platelet toxicity. This study demonstrated that LP-118 induces efficient BAK activation, cytochrome C release, and apoptosis in both venetoclax naïve and resistant CLL cells. Significantly, LP-118 is effective in cell lines expressing the BCL2 G101V mutation and in cells expressing BCLXL but lacking BCL2 dependence. Using an immunocompetent mouse model, Eμ-TCL1, LP-118 demonstrates low platelet toxicity, which hampered earlier BCLXL inhibitors. Finally, LP-118 in the RS4;11 and OSU-CLL xenograft models results in decreases in tumor burden and survival advantage, respectively. These results provide a mechanistic rationale for the evaluation of LP-118 for the treatment of venetoclax responsive and relapsed CLL.

The advent of general anesthesia (GA) has significant implications for clinical practice. However, the exact mechanisms underlying GA-induced transitions in consciousness remain elusive. Given some similarities between GA and sleep, the sleep-arousal neural nuclei and circuits involved in sleep-arousal, including the 5-HTergic system, could be implicated in GA. Herein, we utilized pharmacology, optogenetics, chemogenetics, fiber photometry, and retrograde tracing to demonstrate that both endogenous and exogenous activation of the 5-HTergic neural circuit between the dorsal raphe nucleus (DR) and basolateral amygdala (BLA) promotes arousal and facilitates recovery of consciousness from sevoflurane anesthesia. Notably, the 5-HT1A receptor within this pathway holds a pivotal role. Our findings will be conducive to substantially expanding our comprehension of the neural circuit mechanisms underlying sevoflurane anesthesia and provide a potential target for modulating consciousness, ultimately leading to a reduction in anesthetic dose requirements and side effects.

Abstract The development of highly active, reusable catalysts for aqueous‐phase reactions is challenging. Herein, metallic nickel is encapsulated in a nitrogen‐doped carbon–silica composite (SiO2@Ni@NC) as a catalyst for the selective hydrogenation of vanillin in aqueous media. The constructed catalyst achieved 99.8% vanillin conversion and 100% 4‐hydroxymethyl‐2‐methoxyphenol selectivity at room temperature. Based on combined scanning transmission electron microscopy, X‐ray photoelectron spectroscopy, and Raman analyses, the satisfactory catalytic performance is attributed to the composite structure consisting of an active metal, carbon, and silica. The hydrophilic silica core promoted dispersion of the catalyst in aqueous media. Moreover, the external hydrophobic NC layer has multiple functions, including preventing oxidation or leaching of the internal metal, acting as a reducing agent to reduce the internal metal, regulating the active‐site microenvironment by enriching the concentrations of H2 and organic reactants, and modifying the electronic structure of the active metal via metal–support interactions. Density functional theory calculations indicated that NC facilitates vanillin adsorption and hydrogen dissociation to promote aqueous‐phase hydrogenation. This study provides an efficient strategy for constructing encapsulated Ni‐based amphiphilic catalysts to upgrade biomass‐derived compounds.

2,4-dichlorophenol (2,4-DCP), 2,5-DCP, 2,4,5-trichlorophenol (2,4,5-TCP), 2,4,6-TCP, and ortho-phenylphenol (OPP) are widely present in the environment. However, their associations with risk and prognosis of diabetes and prediabetes remains unclear. We investigated the associations of these five phenols with the risk of diabetes and prediabetes, and with all-cause and cardiovascular disease (CVD) mortality, in adults with diabetes or prediabetes (n=6419). Information on diabetes and prediabetes indicators, and mortality data was collected from the National Health and Nutrition Examination Survey. Logistic and Cox regression models were used to explore the associations of the five phenols with risk and prognosis of diabetes and prediabetes. Participants in the highest urinary 2,4-DCP and 2,5-DCP tertiles had higher odds of diabetes [adjusted odds ratio (aOR), 1.34, 95 % confidence interval (CI): 1.10, 1.62; aOR, 1.29, 95 % CI: 1.07, 1.56, respectively] than those in the lowest tertiles. Participants with urinary OPP concentrations above the limit of detection (LOD), but below median had an aOR of 1.25 (95 % CI: 1.08, 1.46) for prediabetes compared to those with concentrations below the LOD. In adults with diabetes, the highest 2,4-DCP and 2,5-DCP tertiles were associated with all-cause mortality [adjusted hazard ratio (aHR), 1.49; 95 % CI: 1.08, 2.06; aHR, 1.49; 95 % CI: 1.08, 2.05, respectively] and CVD mortality (aHR, 2.58; 95 % CI: 1.33, 4.97; aHR, 1.96; 95 % CI: 1.06, 3.60, respectively) compared with the lowest tertiles. Compared with 2,4,5-TCP concentrations below the LOD, those above median were associated with all-cause mortality (aHR: 1.75; 95 % CI: 1.24, 2.48) and CVD mortality (aHR: 2.34; 95 % CI: 1.19, 4.63) in adults with prediabetes. Furthermore, the associations between these phenols and mortality were strengthened in some subgroups. Environmental exposure to 2,4-DCP, 2,5-DCP, 2,4,5-TCP, and OPP increases the risk or adverse prognosis of diabetes or prediabetes in adults in the US. Further studies are required to confirm these findings.

Abstract Skin diseases pose significant challenges in China. Internet health forums offer a platform for millions of users to discuss skin diseases and share images for early intervention, leaving large amount of valuable dermatology images. However, data quality and annotation challenges limit the potential of these resources for developing diagnostic models. In this study, we proposed a deep-learning model that utilized unannotated dermatology images from diverse online sources. We adopted a contrastive learning approach to learn general representations from unlabeled images and fine-tuned the model on coarsely annotated images from Internet forums. Our model classified 22 common skin diseases. To improve annotation quality, we used a clustering method with a small set of standardized validation images. We tested the model on images collected by 33 experienced dermatologists from 15 tertiary hospitals and achieved a 45.05% top-1 accuracy, outperforming the published baseline model by 3%. Accuracy increased with additional validation images, reaching 49.64% with 50 images per category. Our model also demonstrated transferability to new tasks, such as detecting monkeypox, with a 61.76% top-1 accuracy using only 50 additional images in the training process. We also tested our model on benchmark datasets to show the generalization ability. Our findings highlight the potential of unannotated images from online forums for future dermatology applications and demonstrate the effectiveness of our model for early diagnosis and potential outbreak mitigation.

As an emerging distributed machine learning technology, federated learning has gained widespread attention due to its critical privacy protection mechanism. However, it also faces challenges such as high communication costs and heterogeneous client data.In order to address the above issues. This paper proposes a federated learning approach based on the dung beetle optimizer, named FedDBO. In this method, the model parameters uploaded from clients to the server are transformed into model scores. In each round of training, only some of the clients with high model scores need to be selected to upload their parameters to the server, thus reducing communication costs; Simultaneously, a model retraining strategy is introduced. After aggregating the model parameters sent by clients, the server performs a second iterative training on the aggregated model using its own metadata, thereby reducing data heterogeneity and improving model performance. In addition, a proof of convergence is provided, demonstrating that the model aggregated by FedDBO converges to the aggregated model of FedAvg after each training round. Finally, experiments indicate that when simulating various data heterogeneous environments on datasets, FedDBO exhibits higher accuracy and better stability compared to three other algorithms: FedAvg, FedShare, and FedPSO.

Abstract To evaluate the midterm efficacy of the Castor stent (CS) versus in situ fenestration (ISF) for reconstructing the left subclavian artery (LSA) in patients with type B aortic dissection (TBAD). Between July 2017 and July 2022, a total of 247 patients with TBAD were enrolled. One hundred thirty‐seven patients were treated using CSs (group A), while the remaining 110 patients received ISFs (group B). Data of the two groups were retrospectively analyzed. The success rates of surgery were 99.3% and 95.5% in groups A and B (p = .053), There were no deaths during hospitalization. During surgery, group B showed a longer surgical duration [68.0 (66.0, 77.0) vs. 62.0 (59.0, 66.0) min, p

Abstract Coupling high-capacity cathode and Li-anode with solid-state electrolyte has been demonstrated as an effective strategy for increasing the energy densities and safety of rechargeable batteries. However, the limited ion conductivity, the large interfacial resistance, and unconstrained Li-dendrite growth hinder the application of solid-state Li-metal batteries. Here, a poly(ether-urethane)-based solid-state polymer electrolyte with self-healing capability is designed to reduce the interfacial resistance and provides a high-performance solid-state Li-metal battery. With its dynamic covalent disulfide bonds and hydrogen bonds, the proposed solid-state polymer electrolyte exhibits excellent interfacial self-healing ability and maintains good interfacial contact. Full cells are assembled with the two integrated electrodes/electrolytes. As a result, the Li||Li symmetric cells exhibit stable long-term cycling for more than 6000 h, and the solid-state Li-S battery shows a prolonged cycling life of 700 cycles at 0.3 C. The use of ultrasound imaging technology shows that the interfacial contact of the integrated structure is much better than those of traditional laminated structure. This work provides an interesting interfacial dual-integrated strategy for designing high-performance solid-state Li-metal batteries.

Abstract Microbial production of monoterpenoid indole alkaloids (MIAs) provides a sustainable and eco‐friendly means to obtain compounds with high pharmaceutical values. However, efficient biosynthesis of MIAs in heterologous microorganisms is hindered due to low supply of key precursors such as geraniol and its derivative 8‐hydroxygeraniol catalyzed by geraniol 8‐hydroxylase (G8H). In this study, we developed a facile evolution platform to screen strains with improved yield of geraniol by using the SCRaMbLE system embedded in the Sc2.0 synthetic yeast and confirmed the causal role of relevant genomic targets. Through genome mining, we identified several G8H enzymes that perform much better than the commonly used CrG8H for 8‐hydroxygeraniol production in vivo. We further showed that the N‐terminus of these G8H enzymes plays an important role in cellular activity by swapping experiments. Finally, the combination of the engineered chassis, optimized biosynthesis pathway, and utilization of G8H led to the final strain with more than 30‐fold improvement in producing 8‐hydroxygeraniol compared with the starting strain. Overall, this study will provide insights into the construction and optimization of yeast cells for efficient biosynthesis of 8‐hydroxygeraniol and its derivatives.

Abstract To investigate the influence of different grasping postures on the hand’s skin deformation, a handheld 3D EVA SCANNER was used to obtain 3D models of 111 women in five postures, including a straight posture and grasping cylinders with various diameters (4/6/8/10 cm). Skin relaxation strain ratio ( $${\lambda }_{p}$$ λ p ) and surface area skin relaxation strain ratio ( $${\lambda }_{m}$$ λ m ) were used as measures of skin deformation between two landmarks and multiple landmarks, respectively. The effects of grasping posture on skin deformation in different directions were analyzed. The results revealed significant variations in skin deformation among different grasping postures, except for the width of middle finger metacarpal and the length of middle finger’s proximal phalanx. The $${\lambda }_{p}$$ λ p increased with decreasing grasping object diameter, ranging from 5 to 18% on the coronal axis, and from 4 to 20% on the vertical axis. The overall variation of $${\lambda }_{m}$$ λ m ranged from 5 to 37.5%, following the same trend as $${\lambda }_{p}$$ λ p except for the surface area of tiger’s mouth, which exhibited a maximum difference of 10.9% with significant differences. These findings have potential applications in improving the design of hand equipment and understanding hand movement characteristics.

Remote sensing technology has found extensive application in agriculture, providing critical data for analysis. The advancement of semantic segmentation models significantly enhances the utilization of point cloud data, offering innovative technical support for modern horticulture in nursery environments, particularly in the area of plant cultivation. Semantic segmentation results aid in obtaining tree components, like canopies and trunks, and detailed data on tree growth environments. However, obtaining precise semantic segmentation results from large-scale areas can be challenging due to the vast number of points involved. Therefore, this paper introduces an improved model aimed at achieving superior performance for large-scale points. The model incorporates direction angles between points to improve local feature extraction and ensure rotational invariance. It also uses geometric and relative distance information for better adjustment of different neighboring point features. An external attention module extracts global spatial features, and an upsampling feature adjustment strategy integrates features from the encoder and decoder. A specialized dataset was created from real nursery environments for experiments. Results show that the improved model surpasses several point-based models, achieving a Mean Intersection over Union (mIoU) of 87.18%. This enhances the precision of nursery environment analysis and supports the advancement of autonomous nursery managements.

The complex structure of monoclonal antibodies (mAbs) expressed in Chinese hamster ovary (CHO) cells may result in the accumulation of unfolded proteins, triggering endoplasmic reticulum (ER) stress and an unfolded protein response (UPR). If the protein folding ability cannot maintain ER homeostasis, the cell will shut down protein translation and ultimately induce apoptosis. We co-overexpressed HsQSOX1b and survivin proteins in the antibody-producing cell line CHO-PAb to obtain a new cell line, CHO-PAb-QS. Compared with CHO-PAb cells, the survival time of CHO-PAb-QS cells in batch culture was extended by 2 days, and the antibody accumulation and productivity were increased by 52% and 45%, respectively. The proportion of (HC-LC)2 was approximately doubled in the CHO-PAb-QS cells, which adapted to the accelerated disulfide bond folding capacity by upregulating the UPR’s strength and increasing the ER content. The results of the apoptosis assays indicated that the CHO-PAb-QS cell line exhibited more excellent resistance to apoptosis induced by ER stress. Finally, CHO-PAb-QS cells exhibited mild oxidative stress but did not significantly alter the redox status. This study demonstrated that strategies based on HsQSOX1b and survivin co-overexpression could facilitate protein disulfide bond folding and anti-apoptosis ability, enhancing antibody production efficiency in CHO cell lines.

Background Nonylphenol (NP) is widely recognized as a crucial environmental endocrine-disrupting chemical and persistent toxic substance. The remediation of NP-contaminated sites primarily relies on biological degradation. Compound microbial products, as opposed to pure strains, possess a greater variety of metabolic pathways and can thrive in a wider range of environmental conditions. This characteristic is believed to facilitate the synergistic degradation of pollutants. Limited research has been conducted to thoroughly examine the potential compatibility of compound microbial agents with indigenous microflora, their ability to function effectively in practical environments, their capacity to enhance the dissipation of NP, and their potential to improve soil physicochemical and biological characteristics. Methods In order to efficiently eliminate NP in contaminated soil in an eco-friendly manner, a simulation study was conducted to investigate the impact of bioaugmentation using the functional compound microbial agent NP-M2 at varying concentrations (50 and 200 mg/L) on the dynamics of the soil microbial community. The treatments were set as follows: sterilized soil with 50 mg/kg NP (CK50) or 200 mg/kg NP (CK200); non-sterilized soil with 50 mg/kg NP (TU50) or 200 mg/kg NP (TU200); non-sterilized soil with the compound microbial agent NP-M2 at 50 mg/kg NP (J50) or 200 mg/kg NP (J200). Full-length 16S rRNA analysis was performed using the PacBio Sequel II platform. Results Both the indigenous microbes (TU50 and TU200 treatments) and the application of NP-M2 (J50 and J200 treatments) exhibited rapid NP removal, with removal rates ranging from 93% to 99%. The application of NP-M2 further accelerated the degradation rate of NP for a subtle lag period. Although the different treatments had minimal impacts on the soil bacterial α-diversity, they significantly altered the β-diversity and composition of the bacterial community. The dominant phyla were Proteobacteria (35.54%–44.14%), Acidobacteria (13.55%–17.07%), Planctomycetes (10.78%–11.42%), Bacteroidetes (5.60%–10.74%), and Actinobacteria (6.44%–8.68%). The core species were Luteitalea_pratensis, Pyrinomonas_methylaliphatogenes, Fimbriiglobus_ruber, Longimicrobium_terrae, and Massilia_sp003590855. The bacterial community structure and taxon distribution in polluted soils were significantly influenced by the activities of soil catalase, sucrase, and polyphenol oxidase, which were identified as the major environmental factors. Notably, the concentration of NP and, to a lesser extent, the compound microbial agent NP-M2 were found to cause major shifts in the bacterial community. This study highlights the importance of conducting bioremediation experiments in conjunction with microbiome assessment to better understand the impact of bioaugmentation/biostimulation on the potential functions of complex microbial communities present in contaminated soils, which is essential for bioremediation success.

Potato soft rot caused by Pectobacterium spp. are devastating diseases of potato which cause severe economic losses worldwide. Pectobacterium brasiliense is considered as one of the most virulent species. However, the virulence mechanisms and pathogenicity factors of this strain have not been fully elucidated. Here, through pathogenicity screening, we identified two Pectobacterium brasiliense isolates, SM and DQ, with distinct pathogenicity levels. SM exhibits higher virulence compared to DQ in inducing aerial stem rot, blackleg and tuber soft rot. Our genomic and transcriptomic analyses revealed that SM encodes strain specific genes with regard to plant cell wall degradation and express higher level of genes associated with bacterial motility and secretion systems. Our plate assays verified higher pectinase, cellulase, and protease activities, as well as fast swimming and swarming motility in SM. Importantly, a unique endoglucanase S specific to SM was identified. Expression of this cellulase in DQ greatly enhances its virulence compared to wild type strain. Our study sheds light on possible determinants causing different pathogenicity of Pectobacterium brasiliense species with close evolutionary distance and provides new insight into the direction of genome evolution in response to host variation and environmental stimuli.

BackgroundChronic kidney disease (CKD) is a common public health problem, which is characterized as impairment of renal function. The associations between blood metabolites and renal function remained unclear. This study aimed to assess the causal effect of various circulation metabolites on renal function based on metabolomics.MethodsWe performed a two-sample Mendelian randomization (MR) analysis to estimate the causality of genetically determined metabolites on renal function. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, while summary-level data for creatinine-based estimated glomerular filtration rate (eGFR) or CKD occurrence were set the outcomes. Inverse variance weighted (IVW) was used for primary causality analysis and other methods including weight median, MR-egger, and MR-PRESSO were applied as complementary analysis. Cochran Q test, MR-Egger intercept test, MR-PRESSO global test and leave-one-out analysis were used for sensitivity analysis. For the identified metabolites, reverse MR analysis, linkage disequilibrium score (LDSC) regression and multivariable MR (MVMR) analysis were performed for further evaluation. The causality of the identified metabolites on renal function was further validated using GWAS data for cystatin-C-based eGFR. All statistical analyses were performed in R software.ResultsIn this MR analysis, a total of 44 suggestive associations corresponding to 34 known metabolites were observed. After complementary analysis and sensitivity analysis, robust causative associations between two metabolites (betaine and N-acetylornithine) and renal function were identified. Reverse MR analysis showed no causal effects of renal function on betaine and N-acetylornithine. MVMR analysis revealed that genetically predicted betaine and N-acetylornithine could directly influence independently of each other. The causal effects of betaine and N-acetylornithine were also found on cystatin-C-based eGFR.ConclusionOur study provided evidence to support the causal effects of betaine and N-acetylornithine on renal function. These findings required further investigations to conduct mechanism exploration and drug target selection of these identified metabolites.

IntroductionAcne detection is critical in dermatology, focusing on quality control of acne imagery, precise segmentation, and grading. Traditional research has been limited, typically concentrating on singular aspects of acne detection.MethodsWe propose a multi-task acne detection method, employing a CenterNet-based training paradigm to develop an advanced detection system. This system collects acne images via smartphones and features multi-task capabilities for detecting image quality and identifying various acne types. It differentiates between noninflammatory acne, papules, pustules, nodules, and provides detailed delineation for cysts and post-acne scars.ResultsThe implementation of this multi-task learning-based framework in clinical diagnostics demonstrated an 83% accuracy in lesion categorization, surpassing ResNet18 models by 12%. Furthermore, it achieved a 76% precision in lesion stratification, outperforming dermatologists by 16%.DiscussionOur framework represents a advancement in acne detection, offering a comprehensive tool for classification, localization, counting, and precise segmentation. It not only enhances the accuracy of remote acne lesion identification by doctors but also clarifies grading logic and criteria, facilitating easier grading judgments.

Abstract Electrospinning (ES) methods that can produce piezoelectricity in polymer nanofibers have attracted tremendous research attention. These electrospun polymer nanofibers can be employed for sensors, energy harvesting, tissue engineering, and filtration applications. This paper reviews the performance of a variety of electrospun piezoelectric polymer nanofibers produced by different ES methods, including near‐field electrospinning and conventional far‐field electrospinning methods. Herein, it is described how the ES method can affect the piezoelectric properties of various polymer nanofibers, including poly(vinylidene difluorine), poly(vinylidene fluoride‐trifluoroethylene), nylon 11, poly(l‐lactic acid), and poly(α‐benzyl‐l‐glutamate). Due to the varied matrix structures of piezoelectric polymer nanofibers, the ES method may conduct variable effects on the piezoelectric properties of polymer nanofibers. After characterizations by X‐ray diffraction, Fourier transform infrared spectrum, dielectric spectra, and piezoelectric coefficient measurements, it is found that the piezoelectric properties of the polymer nanofibers can be significantly affected by the ES parameters. Most of previous review articles focus on the output performance of electrospun polymer nanofibers. A detailed description of how different ES methods affect the piezoelectricity of polymer nanofibers is still lacking. In this review paper, the basic principle behind ES methods and the way in which different ES methods affect the properties of polymer nanofibers are examined.

BackgroundProne position has been well recognized for the treatment of adult acute respiratory distress syndrome (ARDS). We aimed to evaluate the role of prone position in the mechanical ventilation in children with ARDS, to provide evidence to the treatment and care of children with ARDS.MethodsWe searched the Pubmed et al. databases by computer until January 23, 2024 for randomized controlled trials (RCTs) on the role of prone position in the mechanical ventilation in children with ARDS. We evaluated the quality of included studies according to the quality evaluation criteria recommended by the Cochrane library. RevMan 5.3 software was used for meta-analysis.Results7 RCTs involving 433 children with ARDS were included. Meta-analysis indicated that prone position is beneficial to improve the arterial oxygenation pressure [MD = 4.27 mmHg, 95% CI (3.49, 5.06)], PaO2/FiO2 [MD = 26.97, 95% CI (19.17, 34.77)], reduced the oxygenation index [MD = −3.52, 95% CI (−5.41, −1.64)], mean airway pressure [MD = −1.91 cmH2O, 95% CI (−2.27, −1.55)] and mortality [OR = 0.33, 95% CI (0.15, 0.73), all P 0.05).ConclusionsProne position ventilation has obvious advantages in improving oxygenation, but there is no significant improvement in the time of mechanical ventilation in the treatment of children with ARDS. In the future, more large-sample, high-quality RCTs are still needed to further analyze the role of prone position in the mechanical ventilation in children with ARDS.

Abstract Background Medical costs have been rising rapidly in recent years, and China is controlling medical costs from the perspective of health insurance payments. Objectives To explore the impact of the capitation prepayment method on medical expenses and health service utilization of coronary heart disease (CHD) patients, which provides a scientific basis for further improvement of the payment approach. Methods The diagnosis records of visits for CHD in the database from 2014 to 2016 (April to December each year) were selected, and two townships were randomly selected as the pilot and control groups. Propensity score matching (PSM) and difference-in-difference (DID) model were used to assess changes in outpatient and inpatient expenses and health service utilization among CHD patients after the implementation of the capitation prepayment policy. Results There were eventually 3,900 outpatients and 664 inpatients enrolled in this study after PSM. The DID model showed that in the first year of implementing the reform, total outpatient expenses decreased by CNY 13.953, drug expenses decreased by CNY 11.289, as well as Medicare payments decreased by CNY 8.707 in the pilot group compared to the control group. In the second year of implementing the reform, compared with the control group, the pilot group had a reduction of CNY 3.123 in other expenses, and a reduction of CNY 6.841 in Medicare payments. There was no significant change in inpatient expenses in the pilot group compared to the control group, but there was an increase of 0.829 visits to rural medical institutions, and an increase of 0.750 visits within the county for inpatients. Conclusions The capitation prepayment method has been effective in controlling the outpatient expenses of CHD patients, as well as improving the medical service capacity of medical institutions within the Medical Community, and increasing the rate of inside county visits for inpatients.

Abstract Synthetic auxotrophy in which cell viability depends on the presence of an unnatural amino acid (unAA) provides a powerful strategy to restrict unwanted propagation of genetically modified organisms (GMOs) in open environments and potentially prevent industrial espionage. Here, we describe a generic approach for robust biocontainment of budding yeast dependent on unAA. By understanding escape mechanisms, we specifically optimize our strategies by introducing designed “immunity” to the generation of amber-suppressor tRNAs and developing the transcriptional- and translational-based biocontainment switch. We further develop a fitness-oriented screening method to easily obtain multiplex safeguard strains that exhibit robust growth and undetectable escape frequency (

Carbon neutrality has become a global common goal. CCUS, as one of the technologies to achieve carbon neutrality, has received widespread attention from academia and industry. After CO2 enters the formation, under the conditions of formation temperature and pressure, supercritical CO2, formation water, and rock components interact, which directly affects the oil and gas recovery and carbon sequestration efficiency. In this paper, the recent progress on CO2 water–rock interaction was reviewed from three aspects, including (i) the investigation methods of CO2 water–rock interaction; (ii) the variable changes of key minerals, pore structure, and physical properties; and (iii) the nomination of suitable reservoirs for CO2 geological sequestration. The review obtains the following three understandings: (1) Physical simulation and cross-time scale numerical simulation based on formation temperature and pressure conditions are important research methods for CO2 water–rock interaction. High-precision mineral-pore in situ comparison and physical property evolution evaluation are important development directions. (2) Sensitive minerals in CO2 water–rock interaction mainly include dolomite, calcite, anhydrite, feldspar, kaolinite, and chlorite. Due to the differences in simulated formation conditions or geological backgrounds, these minerals generally show the pattern of dissolution or precipitation or dissolution before precipitation. This differential evolution leads to complex changes in pore structure and physical properties. (3) To select the suitable reservoir for sequestration, it is necessary to confirm the sequestration potential of the reservoir and the later sequestration capacity, and then select the appropriate layer and well location to start CO2 injection. At the same time, these processes can be optimized by CO2 water–rock interaction research. This review aims to provide scientific guidance and technical support for shale oil recovery and carbon sequestration by introducing the mechanism of CO2 water–rock interaction, expounding the changes of key minerals, pore structure, and physical properties, and summarizing the sequestration scheme.

Prochlorococcus, a cyanobacteria genus of the smallest and most abundant oceanic phototrophs, encompasses ecotype strains adapted to high-light (HL) and low-light (LL) niches. To elucidate the adaptive evolution of this genus, we analyzed 40 Prochlorococcus marinus ORFeomes, including two cornerstone strains, MED4 and NATL1A. Employing deep learning with robust statistical methods, we detected new protein family distributions in the strains and identified key genes differentiating the HL and LL strains. The HL strains harbor genes (ABC-2 transporters) related to stress resistance, such as DNA repair and RNA processing, while the LL strains exhibit unique chlorophyll adaptations (ion transport proteins, HEAT repeats). Additionally, we report the finding of variable, depth-dependent endogenous viral elements in the 40 strains. To generate biological resources to experimentally study the HL and LL adaptations, we constructed the ORFeomes of two representative strains, MED4 and NATL1A synthetically, covering 99% of the annotated protein-coding sequences of the two species, totaling 3976 cloned, sequence-verified open reading frames (ORFs). These comparative genomic analyses, paired with MED4 and NATL1A ORFeomes, will facilitate future genotype-to-phenotype mappings and the systems biology exploration of Prochlorococcus ecology.

Abstract Retrospective studies have identified an increased risk of ankylosing spondylitis (AS) in endometriosis patients. The purpose of this study was to investigate the causal relationship between clinical phenotypes of endometriosis and AS using mendelian randomized analysis (MR). MR was performed using data from genome-wide association studies (GWASs). Heterogeneity, pleiotropy and sensitivity analyses were performed to evaluate the robustness of the results by MR Egger and inverse variance weighted (IVW), leave-one-out analysis. IVW, IVW-MRE (inverse variance weighted multiplicative random effects), weighted median and MR Egger were used to explore the relationship between endometriosis and AS. The IVW analysis showed a causal relationship between infertile endometriosis and AS (OR = 0.8334, P = 0.02191), and the same result was observed with IVW-MRE (OR = 0.8334, P = 0.0007933). However, further stratified analysis showed that no matter which statistical method was used, ovarian endometriosis (IVW: OR = 0.1662, P = 0.4986; IVW-MRE: OR = 0.1662, P = 0.4986; MR Egger: OR = − 0.9577, P = 0.2798; Weighted median: OR = 0.2628, P = 0.3452), pelvic peritoneum endometriosis (IVW: OR = 0.4363, P = 0.225; IVW-MRE: OR = 0.4363, P = 0.225, MR Egger: OR = 4.159, P = 0.1705; Weighted median: OR = 0.4112, P = 0.2714), rectovaginal endometriosis (IVW: OR = 0.1365, P = 0.805; IVW-MRE: OR = 0.1365, P = 0.805) there was no causal relationship between endometriosis and AS. This study suggested that patients with infertility endometriosis are at increased risk for AS. This study supports clinicians to pay more attention to the occurrence of AS in endometriosis patients with infertility.

When a reservoir is damaged, it will bring destruction to people's lives and the regional economy. Flood simulation and risk assessment are two effective ways to mitigate flood risk. Flood risk is assessed by using flood hazard and vulnerability indices. However, one of the key concerns is how to quantify hazards and vulnerabilities more rationally. To this end, this study introduces a new quantitative method for flood risk assessment. Three schemes – full dam breach (S1), 1/2 dam breach (S2), and 1/3 dam breach (S3) – were proposed for flood simulation. HEC-RAS 2D was used to simulate the evolution process of dam-break floods. This study used a new quantification approach to calculate flood risk based on simulation results. The results show the following: (1) The inundation process is similar under the three schemes, but the degree differs. The greater the degree of dam break, the greater the inundation depth, maximum flow velocity, and inundation duration. (2) High-risk areas decrease with decreased dam break degree. Under the three schemes, the flood risk areas of Longjing Street account for 65.37, 71.41, and 66.22% of the total risk areas, respectively, which are the areas most affected by dam-break floods. HIGHLIGHTS HEC-RAS is used to simulate the dam-break flood process.; Flood risk is assessed by hazard and vulnerability.; The hazard and vulnerability are quantified by a conversion-assignment method.; Flood risk maps can be used to develop downstream flood control measures.;

Long non-coding RNAs (lncRNAs) participate in acute lung injury (ALI). However, their latent biological function and molecular mechanism have not been fully understood. In the present study, the global expression profiles of lncRNAs and mRNAs between the control and lipopolysaccharide (LPS)-stimulated groups of human normal lung epithelial cells (BEAS-2B) were determined using high-throughput sequencing. Overall, a total of 433 lncRNAs and 183 mRNAs were differentially expressed. A lncRNA–mRNA co-expression network was established, and then the top 10 lncRNAs were screened using topological methods. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis results showed that the key lncRNAs targeting mRNAs were mostly enriched in the inflammatory-related biological processes. Gene set variation analysis and Pearson’s correlation coefficients confirmed the close correlation for the top 10 lncRNAs with inflammatory responses. A protein–protein interaction network analysis was conducted based on the key lncRNAs targeting mRNAs, where IL-1β, IL-6, and CXCL8 were regarded as the hub genes. A competing endogenous RNA (ceRNA) modulatory network was created with five lncRNAs, thirteen microRNAs, and twelve mRNAs. Finally, real-time quantitative reverse transcription-polymerase chain reaction was employed to verify the expression levels of several key lncRNAs in BEAS-2B cells and human serum samples.

Abstract The objective of this study was to synthesize and characterize pharmaceutical characteristics of florfenicol sustained-release granules (FSRGs) in vitro and in vivo. FSRGs were synthesized using monostearate, polyethylene glycol 4000 and starch. In vitro dissolution profiles were studied using the rotating basket method in pH 1.2 HCl solution and pH 4.3 acetate buffer. Twenty-four male healthy Landrace×Yorkshire pigs were equally divided into three groups and administered a 20 mg/kg i.v bolus of florfenicol solution and dosed orally with FSRGs in the fasting and fed states. The Higuchi model was the best fit for the drug release profile in pH 1.2 and pH 4.3 media, and the mechanism of drug dissolution was governed by both diffusion and dissolution. We established a level A in vitro - in vivo correlation for FSRGs and the in vivo profile of the FSRGs can be estimated by the in vitro drug release.

Soybeans are an important oil and protein supply crop, but the utilization of by-products from its processing products has never been effectively resolved, while a large number of nutritional resources have been wasted and environmental pollution is serious, restricting the sustainable development of the industry. The critical problem of soybean processing by-products includes excessive levels of microorganisms, residual proteins, metal ions, and other substances. Because the screw extrusion process has potentially advantageous processing characteristics, it appears that it’s just the right solution to the above problem of soybean processing by-products. We propose that this technology may be a potentially scalable technology for the immediate processing of soybean by-products. This paper reviews the theoretical foundations in existing research, briefly discusses the technological advantages, feasibility, and potential risks of this process, and hopes that researchers may pay attention to this technique and conduct feasibility studies.

Today, the utilization of Information Technology tools is considered an inevitable path in the education system. In this regard, assessing the effective integration of Information Technology tools in the educational system holds significant importance. This process can be automated using artificial intelligence techniques, which are the subject of the current study. In this research, initially, a set of 14 indicators related to levels of Education Informatization (EI) in higher education is introduced. Subsequently, a clustering-based strategy is proposed to rank the indicators and determine an optimal subset of these features. Based on this framework, it is demonstrated that using 11 indicators related to educational behaviors can achieve the highest accuracy in evaluating EI levels. The proposed approach employs a group of Support Vector Machines (SVMs) for EI level assessment, where classifier hyperparameters are tuned using reinforcement learning strategy. The performance of the proposed method is evaluated on real-world data and compared with previous works. The results indicate that the proposed method can assess EI levels in universities with an average accuracy of 93.64 %, outperforming compared methods by at least 4.09 %.

Summary: In eukaryotic genomes, rDNA generally resides as a highly repetitive and dynamic structure, making it difficult to study. Here, a synthetic rDNA array on chromosome III in budding yeast was constructed to serve as the sole source of rRNA. Utilizing the loxPsym site within each rDNA repeat and the Cre recombinase, we were able to reduce the copy number to as few as eight copies. Additionally, we constructed strains with two or three rDNA arrays and found that the presence of multiple arrays did not affect the formation of a single nucleolus. Although alteration of the position and number of rDNA arrays did impact the three-dimensional genome structure, the additional rDNA arrays had no deleterious influence on cell growth or transcriptomes. Overall, this study sheds light on the high plasticity of rDNA organization and opens up opportunities for future rDNA engineering.

Mineral scaling caused by multivalent metal ions can significantly hinder the long-term operation of nanofiltration membranes. In this study, in-situ interfacial polymerization including a posttreatment by using a citric acid solution was employed in order to mitigate scaling on the membrane surface. Under the optimal conditions (15 ​min of posttreatment with a 2 ​M citric acid solution), the membrane water permeance increased from 5.76 ​± ​0.2 to 15.1 ​± ​1.8 ​L⋅m−2⋅h−1·bar−1 for the pristine and the optimal membrane, respectively. The molecular weight cut-off of the optimal membrane was 399 ​Da, which allows for the removal of organic micropollutants in groundwater. Furthermore, the resulting membrane showed a Na2SO4 and CaCl2 rejection of 92.5 ​± ​1.9 and 11.4 ​± ​1.3%, respectively. During the anti-scaling tests, the membrane fabricated with this strategy exhibited a minor decline of the water permeance of 33.5% when subjected to the same water recovery process, opposed to 65.8% for the pristine membrane. This proposed fabricating procedure thus provides an effective strategy for retarding membrane scaling in desalination applications.

This study presents a soft-rigid unified structure (SRUS) textile composed of an inorganic powder (IP) reinforced epoxy resin block (EIPB) array and a soft textile substrate via a pattern-controllable integrated molding method. The influence of IP content and alumina particle size on the cut and puncture resistance of the resulting SRUS textile was systematically investigated. Furthermore, the anti-puncture and anti-cutting mechanisms of the SRUS textile were comprehensively evaluated based on the analysis of damage morphology and process. The experimental results demonstrated a significant enhancement in the puncture and cut resistance of the SRUS textile upon the incorporation of IP. Moreover, the cut/puncture resistance of the SRUS textile increased with an increase in IP content and the size of Al2O3, and the optimal cut/puncture resistance was observed at 60 mesh-50 wt.%. Additionally, the anti-puncture mechanism of the SRUS textile was attributed to the presence of hard passivation at the EIPB, as well as friction self-locking at the gaps. The anti-cutting mechanism was ascribed to the reverse cutting action exerted by the hard particles on the blade, preventing further penetration. Overall, these findings provide valuable insights into the underlying mechanisms that contribute to its enhanced protective performance.

ABSTRACTGut dysbiosis has been reported in chronic hepatitis B (CHB) infection, however its role in CHB progression and antiviral treatment remains to be clarified. Herein, the present study aimed to characterize gut microbiota (GM) in patients with chronic hepatitis B virus infection-associated liver diseases (HBV-CLD) by combining microbiome with metabolome analyses and to evaluate their effects on peripheral immunity. Fecal samples from HBV-CLD patients (n = 64) and healthy controls (n = 17) were collected for 16s rRNA sequencing. Fecal metabolomics was measured with untargeted liquid chromatography-mass spectrometry in subgroups of 58 subjects. Lineage changes of peripheral blood mononuclear cells (PBMCs) were determined upon exposure to bacterial extracts (BE) from HBV-CLD patients. Integrated analyses of microbiome with metabolome revealed a remarkable shift of gut microbiota and metabolites in HBV-CLD patients, and disease progression and antiviral treatment were found to be two main contributing factors for the shift. Concordant decreases in Turicibacter with 4-hydroxyretinoic acid were detected to be inversely correlated with serum AST levels through host-microbiota-metabolite interaction analysis in cirrhotic patients. Moreover, depletion of E.hallii group with elevated choline was restored in patients with 5-year antiviral treatment. PBMC exposure to BE from non-cirrhotic patients enhanced expansion of T helper 17 cells; however, BE from cirrhotics attenuated T helper 1 cell count. CHB progression and antiviral treatment are two main factors contributing to the compositional shift in microbiome and metabolome of HBV-CLD patients. Peripheral immunity might be an intermediate link in gut microbe-host interplay underlying CHB pathogenesis.

Abstract Background In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. Results The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. Conclusions The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository ( https://github.com/yshen25/HLA-Clus ).

Abstract This study proposes a social-financial approach (SFA) to fill the methodological research gap in strategic policy design for managing financial transitions during social changes. The SFA seeks to characterize inclusive transitions in response to innovation and analyze financial management in social changes. Using a multilevel perspective, we combine evolutionary finance and inclusive growth analytics into this framework. We contend that the interaction between the different levels can be summarized as spontaneous adjustments and the alignment of financial elements with the indicators. Actors who attempt to achieve their goals based on past performance evaluations and other forms of bounded rationality strive to cope with adjustments and further trigger a reorientation of the existing regime. We also developed a new configuration tool called the three-axis description to describe the evolution of financial transitions at different stages. These methods allow us to analyze the evolution of financial transition and efficiency, and we argue that market efficiency evolves in stages with the financial transition. Finally, to demonstrate the capability of SFA to identify diverse financial transition pathways, we examined an example case: the establishment of the Bretton Woods System.

Abstract Background To examine the levels of exosome-derived connexin 43 (Cx43) in plasma and estimate its forecast value in patients with melanoma. Methods We measured the plasma exosome-derived Cx43 levels in the plasma of 112 melanoma patients and 50 healthy controls. Results The plasma exosome-derived Cx43 levels in patients with melanoma were substantially downregulated as opposed to the levels in healthy controls (P

DNA repair in response to DSBs in the preimplantation embryo is hard to analyze. Here the authors show that over 25% of pre-existing heterozygous loci in control single blastomere samples appeared as homozygous after whole genome amplification, therefore, they validated gene editing seen in human embryos in ESCs.