Source and level of dietary iron influence semen quality by affecting inflammation, oxidative stress and iron utilization levels in boars.

BACKGROUND: Boars fed a mixed form of inorganic and organic iron in excess of the NRC recommended levels still develop anemia, which suggested that the current level and form of iron supplementation in boar diets may be inappropriate. Therefore, 56 healthy Topeka E line boars aged 15-21 months were randomly divided into 5 groups: basal diet supplemented with 96 mg/kg ferrous sulfate (FeSO4) and 54 mg/kg glycine chelated iron (Gly-Fe, control); 80 mg/kg or 115 mg/kg Gly-Fe; 80 mg/kg or 115 mg/kg methionine hydroxyl analogue chelated iron (MHA-Fe, from Calimet-Fe) for 16 weeks. The effects of dietary iron supplementation with different sources and levels on semen quality in boars were investigated. RESULTS: 1) Serum Fe and hemoglobin concentrations were not affected by reduced dietary iron levels in the 80 mg/kg or 115 mg/kg Gly-Fe and MHA-Fe groups compared with the control group (P > 0.05). 2) Serum interleukin-6 (IL-6) and sperm malondialdehyde (MDA) levels in the 80 mg/kg or 115 mg/kg MHA-Fe groups were lower than those in the control group (P < 0.05), and higher serum superoxide dismutase levels and lower MDA levels in the 115 mg/kg MHA-Fe group (P < 0.05). 3) Boars in the 80 mg/kg or 115 mg/kg Gly-Fe and MHA-Fe groups had lower serum hepcidin (P < 0.01), ferritin (P < 0.05), and transferrin receptor (P < 0.01) concentrations, and boars in the 115 mg/kg MHA-Fe group had higher seminal plasma Fe concentrations compared with the control group. 4) Boars in the 80 mg/kg and 115 mg/kg MHA-Fe groups had lower abnormal sperm rate and in situ oscillating sperm ratio compared to the control group at weeks 12 and/or 16 of the trial. However, the effect of Gly-Fe on improving semen quality in boars was not evident. 5) Serum IL-6 level was positively correlated with hepcidin concentration (P < 0.05), which in turn was significantly positively correlated with abnormal sperm rate (P < 0.05). Furthermore, significant correlations were also found between indicators of iron status and oxidative stress and semen quality parameters. CONCLUSIONS: Dietary supplementation with 80 mg/kg or 115 mg/kg MHA-Fe did not induce iron deficiency, but rather reduced serum inflammatory levels and hepcidin concentration, alleviated oxidative stress, increased body iron utilization, and improved semen quality in adult boars.

Few-shot RUL prediction for engines based on CNN-GRU model.

In the realm of prognosticating the remaining useful life (RUL) of pivotal components, such as aircraft engines, a prevalent challenge persists where the available historical life data often proves insufficient. This insufficiency engenders obstacles such as impediments in performance degradation feature extraction, inadequacies in capturing temporal relationships comprehensively, and diminished predictive accuracy. To address this issue, a 1D CNN-GRU prediction model for few-shot conditions is proposed in this paper. In pursuit of more comprehensive data feature extraction and enhanced RUL prognostication precision, the Convolutional Neural Network (CNN) is selected for its capacity to discern high-dimensional features amid the intricate dynamics of the data. Concurrently, the Gated Recurrent Unit (GRU) network is leveraged for its robust capability in extracting temporal features inherent within the data. We combine the two to construct a CNN-GRU hybrid network. Moreover, the integration of data distribution alongside correlation and monotonicity indices is employed to winnow the input of multi-sensor monitoring parameters into the CNN-GRU network. Finally, the engine RULs are predicted by the trained model. In this paper, experiments are conducted on a sub-dataset of the National Aeronautics and Space Administration (NASA) C-MAPSS multi-constraint dataset to validate the effectiveness of the method. Experimental results have demonstrated that this method has high accuracy in RUL prediction tasks, which can powerfully demonstrate its effectiveness.

Modification of Microstructure and Mechanical Properties of Extruded AZ91-0.4Ce Magnesium Alloy through Addition of Ca.

The effect of the addition of alkali earth element Ca on the microstructure and mechanical properties of extruded AZ91-0.4Ce-xCa (x = 0, 0.4, 0.8, 1.2 wt.%) alloys was studied by using scanning electron microscopy, transmission electron microscopy, and tensile tests. The results showed that the addition of Ca could significantly refine the second phase and grain size of the extruded AZ91-0.4Ce alloy. The refinement effect was most obvious when 0.8 wt.% of Ca was added, and the recrystallized grain size was 4.75 µm after extrusion. The addition of Ca resulted in the formation of a spherical Al2Ca phase, which effectively suppressed the precipitation of the ß-Mg17Al12 phase, promoted dynamic recrystallization and grain refinement, impeded dislocation motion, and exerted a positive influence on the mechanical properties of the alloy. The yield strength (YS), ultimate tensile strength (UTS), and elongation (EL) of the AZ91-0.4Ce-0.8Ca alloy were 238.7 MPa, 338.3 MPa, and 10.8%, respectively.

Exposure of water purification deficit network in response to nitrogen application intensity.

Ecosystem services are strongly responsive to changes in land use intensity, especially for the service of water purification, which is highly sensitive to water pollutant emission. Increased nitrogen (N) application to cropland has potential impacts on the supply and demand for water purification through changes in land use intensity. However, there has been a lack of research focusing on the impacts of cropland N application on population exposure to water purification deficit and their cross-regional delivery network. Taking the Dongting Lake (DTL) Basin as an example, this study explored the spatial pattern of N exposure in the DTL Basin from 1990 to 2015 by integrating water purification deficit and population density. Changes in potential N exposure in 2050 were simulated based on population projection data from the Shared Socioeconomic Pathways (SSP1-5). N delivery pathways in the DTL Basin were clarified by constructing the N delivery network. The results showed that N exposure increased significantly with increasing N application in DTL Basin. The DTL surrounding area and lower reaches of the Xiangjiang River Basin had high increases of N exposure (50.2 % and 71.6 %) and high increases in N exposure due to increases in N application per unit (N influence coefficients exceeding 0.5). The lower reaches of the Xiangjiang River Basin with the highest population density had the smallest decrease in N exposure (1.4 %-11.1 %) in the SSP1-5 scenarios. During 1990-2015, the increase of N export to the DTL surrounding area was higher in the lower reach sub-basins of DTL Basin. N application had a stronger impact on N delivery processes in the lower reaches of DTL Basin. Managers should distribute N applications to basins with high N retention and low N export to the DTL surrounding area. This study confirmed the strong response of water purification deficit and its population exposure to N application, and provided decision-making guidelines for water quality enhancement in DTL Basin from a spatial planning perspective.

Cross-talk of MLST and transcriptome unveiling antibiotic resistance mechanism of carbapenem resistance Acinetobacter baumannii clinical strains isolated in Guiyang, China.

Introduction: Acinetobacter baumannii (A. baumannii) is an important opportunistic pathogen causing nosocomial infection in the clinic. The occurrence rate of antibiotic resistance is increasing year by year, resulting in a highly serious situation of bacterial resistance. Methods: To better understand the local epidemiology of multidrug-resistant A. baumannii, an investigation was conducted on the antibiotic resistance of different types of A. baumannii and its relationship with the genes of A. baumannii. Furthermore, the molecular mechanism underlying antibiotic resistance in A. baumannii was investigated through transcriptome analysis. Results: These results showed that a total of 9 STs were detected. It was found that 99% of the strains isolated in the hospital belonged to the same STs, and the clone complex CC208 was widely distributed in various departments and all kinds of samples. Furthermore, these A. baumannii strains showed high resistance to ertapenem, biapenem, meropenem, and imipenem, among which the resistance to ertapenem was the strongest. The detection rate of bla OXA-51 gene in these carbapenem resistance A. baumannii (CRAB) reached 100%; Additionally, the transcriptome results showed that the resistance genes were up-regulated in resistance strains, and these genes involved in biofilm formation, efflux pumps, peptidoglycan biosynthesis, and chaperonin synthesis. Discussion: These results suggest that the CC208 STs were the main clonal complex, and showed high carbapenem antibiotic resistance. All these resistant strains were distributed in various departments, but most of them were distributed in intensive care units (ICU). The bla OXA-23 was the main antibiotic resistance genotype; In summary, the epidemic trend of clinical A. baumannii in Guiyang, China was analyzed from the molecular level, and the resistance mechanism of A. baumannii to carbapenem antibiotics was analyzed with transcriptome, which provided a theoretical basis for better control of A. baumannii.

Structural Engineering of Prussian Blue Analogues Enabling All-Climate and Ultralong Cycling Sodium-Ion Batteries.

The development of cost-efficient, long-lifespan, and all-climate sodium-ion batteries is of great importance for advancing large-scale energy storage but is plagued by the lack of suitable cathode materials. Here, we report low-cost Na-rich Mn-based Prussian blue analogues with superior rate capability and ultralong cycling stability over 10,000 cycles via structural optimization with electrochemically inert Ni atoms. Their thermal stability, all-climate properties, and potential in full cells are investigated in detail. Multiple in situ characterizations reveal that the outstanding performances benefit from their highly reversible three-phase transformations and trimetal (Mn-Ni-Fe) synergistic effects. In addition, a high sodium diffusion coefficient and a low volume distortion of 2.3% are observed through in situ transmission electron microscopy and first-principles calculations. Our results provide insights into the structural engineering of Prussian blue analogues for advanced sodium-ion batteries in large-scale energy storage applications.

Aggregation-Induced Emission Photosensitizer with Ag(I)-π Interaction-Enhanced Reactive Oxygen Species for Eliminating Multidrug Resistant Bacteria.

Multidrug-resistant (MDR) bacteria pose serious threats to public health due to the lack of effective and biocompatible drugs to kill MDR bacteria. Photodynamic antibacterial therapy has been widely studied due to its low induction of resistance. However, photosensitizers that can efficiently generate reactive oxygen species (ROS) through both type I and type II mechanisms and that have the capability of multiple modes of action are rarely reported. Addressing this issue, we developed a near-infrared-emitting triphenylamine indole iodoethane (TTII) and its silver(I) self-assembled (TTIIS) aggregation-induced emission (AIE) photosensitizer for multimode bacterial infection therapy. TTII can efficiently produce both Type I ROS •OH and Type II ROS 1O2. Interestingly, the Ag(I)-π interaction contributed in TTIIS efficiency promotion of the generation of 1O2. Moreover, by releasing Ag+, TTIIS enabled photodynamic-Ag(I) dual-mode sterilization. As a result, TTIIS achieved an effective enhancement of antibacterial activity, with a 1-2-fold boost against multidrug-resistant Escherichia coli (MDR E. coli). Both TTII and TTIIS at a concentration as low as 0.55 µg mL-1 can kill more than 98% of methicillin resistant Staphylococcus aureus (MRSA) on MRSA-infected full-thickness defect wounds of a mouse, and both TTII and TTIIS were effective in eliminating the bacteria and promoting wound healing.

Gut microbiota from B-cell-specific TLR9-deficient NOD mice promote IL-10+ Breg cells and protect against T1D.

Introduction: Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of insulin-producing ß cells. Toll-like receptor 9 (TLR9) plays a role in autoimmune diseases, and B cell-specific TLR9 deficiency delays T1D development. Gut microbiota are implicated in T1D, although the relationship is complex. However, the impact of B cell-specific deficiency of TLR9 on intestinal microbiota and the impact of altered intestinal microbiota on the development of T1D are unclear. Objectives: This study investigated how gut microbiota and the intestinal barrier contribute to T1D development in B cell-specific TLR9-deficient NOD mice. Additionally, this study explored the role of microbiota in immune regulation and T1D onset. Methods: The study assessed gut permeability, gene expression related to gut barrier integrity, and gut microbiota composition. Antibiotics depleted gut microbiota, and fecal samples were transferred to germ-free mice. The study also examined IL-10 production, Breg cell differentiation, and their impact on T1D development. Results: B cell-specific TLR9-deficient NOD mice exhibited increased gut permeability and downregulated gut barrier-related gene expression. Antibiotics restored gut permeability, suggesting microbiota influence. Altered microbiota were enriched in Lachnospiraceae, known for mucin degradation. Transferring this microbiota to germ-free mice increased gut permeability and promoted IL-10-expressing Breg cells. Rag-/- mice transplanted with fecal samples from Tlr9 fl/fl Cd19-Cre+ mice showed delayed diabetes onset, indicating microbiota's impact. Conclusion: B cell-specific TLR9 deficiency alters gut microbiota, increasing gut permeability and promoting IL-10-expressing Breg cells, which delay T1D. This study uncovers a link between TLR9, gut microbiota, and immune regulation in T1D, with implications for microbiota-targeted T1D therapies.

Regulation of Interface Ion Transport by Electron Ionic Conductor Construction toward High-Voltage and High-Rate LiNi0.5Co0.2Mn0.3O2 Cathodes in Lithium Ion Battery.

Simultaneously achieving high-energy-density and high-power-density is a crucial yet challenging objective in the pursuit of commercialized power batteries. In this study, atomic layer deposition (ALD) is employed combined with a coordinated thermal treatment strategy to construct a densely packed, electron-ion dual conductor (EIC) protective coating on the surface of commercial LiNi0.5Co0.2Mn0.3O2 (NCM523) cathode material, further enhanced by gradient Al doping (Al@EIC-NCM523). The ultra-thin EIC effectively suppresses side reactions, thereby enhancing the stability of the cathode-electrolyte interphase (CEI) at high-voltages. The EIC's dual conduction capability provides a potent driving force for Li+ transport at the interface, promoting the formation of rapid ion deintercalation pathways within the Al@EIC-NCM523 bulk phase. Moreover, the strategic gradient doping of Al serves to anchor the atomic spacing of Ni and O within the structure of Al@EIC-NCM523, curbing irreversible phase transitions at high-voltages and preserving the integrity of its layered structure. Remarkably, Al@EIC-NCM523 displays an unprecedented rate capability (114.7 mAh g-1 at 20 C), and a sustained cycling performance (capacity retention of 74.72% after 800 cycles at 10 C) at 4.6 V. These findings demonstrate that the proposed EIC and doping strategy holds a significant promise for developing high-energy-density and high-power-density lithium-ion batteries (LIBs).

Analyzing Large-Scale Single-Cell RNA-Seq Data Using Coreset.

The recent boom in single-cell sequencing technologies provides valuable insights into the transcriptomes of individual cells. Through single-cell data analyses, a number of biological discoveries, such as novel cell types, developmental cell lineage trajectories, and gene regulatory networks, have been uncovered. However, the massive and increasingly accumulated single-cell datasets have also posed a seriously computational and analytical challenge for researchers. To address this issue, one typically applies dimensionality reduction approaches to reduce the large-scale datasets. However, these approaches are generally computationally infeasible for tall matrices. In addition, the downstream data analysis tasks such as clustering still take a large time complexity even on the dimension-reduced datasets. We present single-cell Coreset (scCoreset), a data summarization framework that extracts a small weighted subset of cells from a huge sparse single-cell RNA-seq data to facilitate the downstream data analysis tasks. Single-cell data analyses run on the extracted subset yield similar results to those derived from the original uncompressed data. Tests on various single-cell datasets show that scCoreset outperforms the existing data summarization approaches for common downstream tasks such as visualization and clustering. We believe that scCoreset can serve as a useful plug-in tool to improve the efficiency of current single-cell RNA-seq data analyses.

Dissecting the binding effect of Crocetin glucosyltransferase 2 in crocetin biotransformation in saffron (Crocus sativus L.) from different origins.

Crocus sativus L. is a both medicinal and food bulbous flower whose qualities are geographically characterized. However, identification involving different places of origin of such substances is currently limited to single-omics mediated content analysis. Integrated metabolomics and proteomics, 840 saffron samples from six countries (Spain, Greece, Iran, China, Japan, and India) were analyzed using the QuEChERS extraction method. A total of 77 differential metabolites and 14 differential proteins were identified. The limits of detection of the method were 1.33 to 8.33 µg kg-1, and the recoveries were 85.56% to 105.18%. Using homology modeling and molecular docking, the Gln84, Lys195, Val182 and Pro184 sites of Crocetin glucosyltransferase 2 were found to be the targets of crocetin binding. By multivariate statistical analysis (PCA and PLS-DA), different saffron samples were clearly distinguished. The results provided the basis for the selection and identification of high quality saffron from different producing areas.

Treatment of manganese and lead poisoning with sodium para-aminosalicylic acid: A contemporary update.

Sodium para-aminosalicylic acid (PAS-Na) treatment for manganese (Mn) intoxication has shown efficacy in experimental and clinical studies, giving rise to additional studies on its efficacy for lead (Pb) neurotoxicity and its associated mechanisms of neuroprotection. The difference between PAS-Na and other metal complexing agents, such as edetate calcium sodium (CaNa2-EDTA), is firstly that PAS-Na can readily pass through the blood-brain barrier (BBB), and complex and facilitate the excretion of manganese and lead. Secondly, PAS-Na has anti-inflammatory effects. Recent studies have broadened the understanding on the mechanisms associated with efficacy of PAS-Na. The latter has been shown to modulate multifarious manganese- and lead- induced neurotoxicity, via its anti-apoptotic and anti-inflammatory effects, as well as its ability to inhibit pyroptosis, and regulate abnormal autophagic processes. These observations provide novel scientific bases and new concepts for the treatment of lead, mercury, copper, thallium, as well as other toxic encephalopathies, and implicate PAS-Na as a compound with greater prospects for clinical medical application.

A Cullin 5-based complex serves as an essential modulator of ORF9b stability in SARS-CoV-2 replication.

The ORF9b protein, derived from the nucleocapsid's open-reading frame in both SARS-CoV and SARS-CoV-2, serves as an accessory protein crucial for viral immune evasion by inhibiting the innate immune response. Despite its significance, the precise regulatory mechanisms underlying its function remain elusive. In the present study, we unveil that the ORF9b protein of SARS-CoV-2, including emerging mutant strains like Delta and Omicron, can undergo ubiquitination at the K67 site and subsequent degradation via the proteasome pathway, despite certain mutations present among these strains. Moreover, our investigation further uncovers the pivotal role of the translocase of the outer mitochondrial membrane 70 (TOM70) as a substrate receptor, bridging ORF9b with heat shock protein 90 alpha (HSP90α) and Cullin 5 (CUL5) to form a complex. Within this complex, CUL5 triggers the ubiquitination and degradation of ORF9b, acting as a host antiviral factor, while HSP90α functions to stabilize it. Notably, treatment with HSP90 inhibitors such as GA or 17-AAG accelerates the degradation of ORF9b, leading to a pronounced inhibition of SARS-CoV-2 replication. Single-cell sequencing data revealed an up-regulation of HSP90α in lung epithelial cells from COVID-19 patients, suggesting a potential mechanism by which SARS-CoV-2 may exploit HSP90α to evade the host immunity. Our study identifies the CUL5-TOM70-HSP90α complex as a critical regulator of ORF9b protein stability, shedding light on the intricate host-virus immune response dynamics and offering promising avenues for drug development against SARS-CoV-2 in clinical settings.

Ten key issues for ecological restoration of territorial space.

This study innovatively puts forward the three-stage restoration goals and cutting-edge key scientific issues of ecological restoration, as well as their relationships.

Dendrite-Free All-Solid-State Lithium Metal Batteries by In Situ Phase Transformation of the Soft Carbon-Li3N Interface Layer.

The accelerated formation of lithium dendrites has considerably impeded the advancement and practical deployment of all-solid-state lithium metal batteries (ASSLMBs). In this study, a soft carbon (SC)-Li3N interface layer was developed with both ionic and electronic conductivity, for which the in situ lithiation reaction not only lithiated SC into LiC6 with good electronic/ionic conductivity but also successfully transformed the mixed-phase Li3N into pure-phase ß-Li3N with a high ionic conductivity/ion diffusion coefficient and stability to lithium metal. The mixed conductive interface layer facilitates fast Li+ transport at the interface and induces the homogeneous deposition of lithium metal inside it. This effectively inhibits the formation of lithium dendrites and greatly improves the performance of the ASSLMB. The ASSLMB assembled with the SC-Li3N interface layer exhibits high areal capacity (15 mA h cm-2), high current density (7.5 mA cm-2), and long cycle life (6000 cycles). These results indicate that this interface layer has great potential for practical applications in high-energy-density ASSLMBs.

Lightweight helmet target detection algorithm combined with Effici-Bi-Level Routing Attention.

Wearing helmets is essential in two-wheeler traffic to reduce the incidence of injuries caused by accidents. We present FB-YOLOv7, an improved detection network based on the YOLOv7-tiny model. The objective of this network is to tackle the problems of both missed detection and false detection that result from the difficulties in identifying small targets and the constraints in equipment performance during helmet detection. By applying an enhanced Bi-Level Routing Attention, the network can improve its capacity to extract global characteristics and reduce information distortion. Furthermore, we deploy the AFPN framework and effectively resolve information conflict using asymptotic adaptive feature fusion technology. Incorporating the EfficiCIoU loss significantly improves the prediction box's accuracy. Experimental trials done on specific datasets reveal that FB-YOLOv7 attains an accuracy of 87.2% and 94.6% on the mean average precision (mAP@.5). Additionally, it maintains a high level of efficiency with frame rates of 129 and 126 frames per second (FPS). FB-YOLOv7 surpasses the other six widely-used detection networks in terms of detection accuracy, network implementation requirements, sensitivity in detecting small targets, and potential for practical applications.

Facing the challenge of NDVI dataset consistency for improved characterization of vegetation response to climate variability.

Non-linear trend detection in Earth observation time series has become a standard method to characterize changes in terrestrial ecosystems. However, results are largely dependent on the quality and consistency of the input data, and only few studies have addressed the impact of data artifacts on the interpretation of detected abrupt changes. Here we study non-linear dynamics and turning points (TPs) of temperate grasslands in East Eurasia using two independent state-of-the-art satellite NDVI datasets (CGLS v3 and MODIS C6) and explore the impact of water availability on observed vegetation changes during 2001-2019. By applying the Break For Additive Season and Trend (BFAST01) method, we conducted a classification typology based on vegetation dynamics which was spatially consistent between the datasets for 40.86 % (459,669 km2) of the study area. When considering also the timing of the TPs, 27.09 % of the pixels showed consistent results between datasets, suggesting that careful interpretation was needed for most of the areas of detected vegetation dynamics when applying BFAST to a single dataset. Notably, for these areas showing identical typology we found that interrupted decreases in vegetation productivity were dominant in the transition zone between desert and steppes. Here, a strong link with changes in water availability was found for >80 % of the area, indicating that increasing drought stress had regulated vegetation productivity in recent years. This study shows the necessity of a cautious interpretation of the results when conducting advanced characterization of vegetation response to climate variability, but at the same time also the opportunities of going beyond the use of single dataset in advanced time-series approaches to better understanding dryland vegetation dynamics for improved anthropogenic interventions to combat vegetation productivity decrease.

Scalable Precise Nanofilm Coating and Gradient Al Doping Enable Stable Battery Cycling of LiCoO2 at 4.7†V.

The quest for smart electronics with higher energy densities has intensified the development of high-voltage LiCoO2 (LCO). Despite their potential, LCO materials operating at 4.7 V faces critical challenges, including interface degradation and structural collapse. Herein, we propose a collective surface architecture through precise nanofilm coating and doping that combines an ultra-thin LiAlO2 coating layer and gradient doping of Al. This architecture not only mitigates side reactions, but also improves the Li+ migration kinetics on the LCO surface. Meanwhile, gradient doping of Al inhibited the severe lattice distortion caused by the irreversible phase transition of O3-H1-3-O1, thereby enhanced the electrochemical stability of LCO during 4.7 V cycling. DFT calculations further revealed that our approach significantly boosts the electronic conductivity. As a result, the modified LCO exhibited an outstanding reversible capacity of 230 mAh g-1 at 4.7 V, which is approximately 28 % higher than the conventional capacity at 4.5 V. To demonstrate their practical application, our cathode structure shows improved stability in full pouch cell configuration under high operating voltage. LCO exhibited an excellent cycling stability, retaining 82.33 % after 1000 cycles at 4.5 V. This multifunctional surface modification strategy offers a viable pathway for the practical application of LCO materials, setting a new standard for the development of high-energy-density and long-lasting electrode materials.