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Imidocarb (IMD) is commonly used for treatment of eperythrozoon, babesia, piroplasma and trypanosoma in animals, but there are few studies on its pharmacokinetics in cattle. The purpose of this study was to obtain pharmacokinetic parameters and assess the bioequivalence of subcutaneous injections of two IMD formulations in cattle. Forty-eight healthy cattle, 24 males and 24 females, were randomLy divided into two groups (test group and reference group) with 12 males and 12 females per group. The generic IMD was injected subcutaneously with a single dose of 3.0 mg/kg in the test group. Reference group animals were given one injection of the marketed IMD at the same dosage. The limit of detection (LOD) and limit of quantification (LOQ) for IMD in cattle plasma were 0.05 ng/mL and 0.1 ng/mL, respectively. The recoveries ranged from 88.50% to 92.42%, and the equation of this calibration curve was Y = 13672.1X+187.43. The pharmacokinetics parameters of the test group showed that the maximum concentration of 2257.5±273.62 ng/mL was obtained at 2.14±0.67 h, AUC0-t 14553.95±1946.85 ng·h/mL, AUC∞ 15077.88±1952.19 ng·h/mL, T1/2 31.77±25.75 h, CL/F 0.14±0.02 mL/h/g, and Vz/F 6.53±5.34 mL/g. There was no significant difference in AUC0-t, AUC∞ and Cmax between the test group and the reference group (P>0.05). The 90% confidence interval of AUC0-t, AUC0-∞ and Cmax in the test group was included in 80%-125% AUC0-t, AUC0-∞ and 70%-143% Cmax in the reference group, respectively. Based on these results, the two preparations were found to be bioequivalent.

Abstract Proximity barcoding assay, a high-throughput method for single-exosome analysis, was employed to profile surface proteins on individual exosomes of SCZ patients. This analysis identified five differentially expressed proteins (DEPs) between SCZ patients and healthy controls (HC) and six DEPs between antipsychotic responders and non-responders. Furthermore, two exosome clusters were found to be associated with SCZ, and certain DEPs were correlated with cognitive functions.

IntroductionPeritoneal dialysis-related peritonitis (PDRP) caused by Microbacterium spp. is very rare, with only 9 cases reported to date. In this study, we report the treatment experiences of 7 patients at our peritoneal dialysis center.MethodsWe retrospectively collected clinical characteristics and antibiotic management of all 7 episodes of PDRP caused by Microbacterium spp. in 7 patients from at our center over 4 years, and reviewed the documented Microbacterium spp. PDRP in the literature.ResultsEmpiric antibiotic therapy was initiated as soon as possible, and consisted of intraperitoneal (IP) gentamicin in combination with vancomycin. After up to 5 days, gentamicin was changed to meropenem if the treatment was not effective. The intended course of antibiotic treatment was 21-day. Totally, 6 episodes were cured (85.7%), which was higher than reported.ConclusionThe 21-day antibiotic therapy program by combining vancomycin and meropenem may benefit the management of Microbacterium spp. PDRP.

Fruit object detection is crucial for automatic harvesting systems, serving applications such as orchard yield measurement and fruit harvesting. In order to achieve fast recognition and localization of green apples and meet the real-time working requirements of the vision system of harvesting robots, a fast optimized Foveabox detection model (Fast-FDM) is proposed. Fast-FDM uses an optimized form of anchor-free Foveabox to accurately and efficiently detect green apples in harvesting environments. Specifically, the EfficientNetV2-S with fast training and small size is used as the backbone network, a weighted bi-directional feature pyramid network (BiFPN) is employed as the feature extraction network to fuse multi-scale features easily and fast, and then the fused features are fed to the fovea head prediction network for the classification and bounding box prediction. Furthermore, an adaptive training sample selection (ATSS) method is adopted to directly select positive and negative samples, allowing green fruits of different scales to obtain higher recall and achieve more accurate green apple detection. Experimental results show that the proposed Fast-FDM realizes a mean average precision (mAP) of 62.3% for green apple detection using fewer parameters and floating point of operations (FLOPs), achieving better trade-offs between accuracy and detection efficiency.

Abstract The evolution of the contact scheme has driven the technology revolution of crystalline silicon (c‐Si) solar cells. The state‐of‐the‐art high‐efficiency c‐Si solar cells such as silicon heterojunction (SHJ) and tunnel oxide passivated contact (TOPCon) solar cells are featured with passivating contacts based on doped Si thin films, which induce parasitic optical absorption loss and require capital‐intensive deposition processes involving flammable and toxic gasses. A promising solution to tackle this problem is to employ dopant‐free passivating contact, involving the use of transparent and cost‐effective wide band gap materials. In this review, we first introduce the dopant‐free passivating contact, from carrier transport mechanisms, material classification to evaluation methods. Then we focus on the advances in different strategies to improve cell performance, including material property optimization, structural and interfacial engineering, as well as various post‐treatments. At the end, the challenge and perspective of dopant‐free passivating contact c‐Si solar cells are discussed.

Patients received kidney transplantation (KTR) have a low seroconversion rate after vaccination. Our objective was to compare the seroconversion rates and adverse effects of additional different vaccinations in KTR patients in existing studies. Databases such as PubMed, Cochrane Library, Web of Science, Embase, ClinicalTrials.gov and others. Three high-quality RCT were included and showed no statistical difference in seroconversion rates between the two vaccines (RR = 0.93[0.76,1.13]). There was no statistical difference in seroconversion rates between the sexes, for men (RR = 0.93[0.69,1.25]) and women (RR = 0.91[0.62,1.33]). Among the adverse effects there was no statistically significant difference in fever (RR = 1.06[0.44,2.57]), while for injection site pain there was a statistically significant difference (RR = 1.14[1.18,1.84]). There was no significant difference in seroconversion rates in patients with KTR who received the two additional vaccines. Patients injected with the viral vector vaccine were less painful than those injected with the mRNA vaccine.

IntroductionBreast cancer is a heterogeneous tumor. Tumor microenvironment (TME) has an important effect on the proliferation, metastasis, treatment, and prognosis of breast cancer.MethodsIn this study, we calculated the relative proportion of tumor infiltrating immune cells (TIICs) in the breast cancer TME, and used the consensus clustering algorithm to cluster the breast cancer subtypes. We also developed a multi-layer perceptron (MLP) classifier based on a deep learning framework to detect breast cancer subtypes, which 70% of the breast cancer research cohort was used for the model training and 30% for validation.ResultsBy performing the K-means clustering algorithm, the research cohort was clustered into two subtypes. The Kaplan-Meier survival estimate analysis showed significant differences in the overall survival (OS) between the two identified subtypes. Estimating the difference in the relative proportion of TIICs showed that the two subtypes had significant differences in multiple immune cells, such as CD8, CD4, and regulatory T cells. Further, the expression level of immune checkpoint molecules (PDL1, CTLA4, LAG3, TIGIT, CD27, IDO1, ICOS) and tumor mutational burden (TMB) also showed significant differences between the two subtypes, indicating the clinical value of the two subtypes. Finally, we identified a 38-gene signature and developed a multilayer perceptron (MLP) classifier that combined multi-gene signature to identify breast cancer subtypes. The results showed that the classifier had an accuracy rate of 93.56% and can be robustly used for the breast cancer subtype diagnosis.ConclusionIdentification of breast cancer subtypes based on the immune signature in the tumor microenvironment can assist clinicians to effectively and accurately assess the progression of breast cancer and formulate different treatment strategies for different subtypes.

Background Localized ablative immunotherapies hold great promise in stimulating antitumor immunity to treat metastatic and poorly immunogenic tumors. Tumor ablation is well known to release tumor antigens and danger-associated molecular patterns to stimulate T-cell immunity, but its immune stimulating effect is limited, particularly against metastatic tumors.Methods In this study, we combined photothermal therapy with a potent immune stimulant, N-dihydrogalactochitosan, to create a local ablative immunotherapy which we refer to as laser immunotherapy (LIT). Mice bearing B16-F10 tumors were treated with LIT when the tumors reached 0.5 cm3 and were monitored for survival, T-cell activation, and the ability to resist tumor rechallenge.Results We found that LIT stimulated a stronger and more consistent antitumor T-cell response to the immunologically ‘cold’ B16-F10 melanoma tumors and conferred a long-term antitumor memory on tumor rechallenge. Furthermore, we discovered that LIT generated de novo CD8+ T-cell responses that strongly correlated with animal survival and tumor rejection.Conclusion In summary, our findings demonstrate that LIT enhances the activation of T cells and drives de novo antitumor T-cell responses. The data presented herein suggests that localized ablative immunotherapies have great potential to synergize with immune checkpoint therapies to enhance its efficacy, resulting in improved antitumor immunity.

The novel coronavirus disease (COVID-19) caused by SARS-CoV-2 virus spreads rapidly to become a global pandemic. Researchers have been working to develop specific drugs to treat COVID-19. The main protease (Mpro) of SARS-CoV-2 virus plays a pivotal role in mediating viral replication and transcription, which makes it a potential therapeutic drug target against COVID-19. In this study, a virtual drug screening method based on the Mpro structure (Protein Data Bank ID: 6LU7) was proposed, and 8,820 compounds collected from the DrugBank database were used for molecular docking and virtual screening. A data set containing 1,545 drug molecules, derived from compounds with a low binding free energy score in the docking experiment, was established. N-1H-Indazol-5-yl-2-(6-methylpyridin-2-yl)quinazolin-4-amine, ergotamine, antrafenine, dihydroergotamine, and phthalocyanine outperformed the other compounds in binding conformation and binding free energy over the N3 inhibitor in the crystal structure. The bioactivity and ADMET properties of these five compounds were further investigated. These experimental results for five compounds suggested that they were potential therapeutics to be developed for clinical trials. To further verify the results of molecular docking, we also carried out molecular dynamics (MD) simulations on the complexes formed by the five compounds and Mpro. The five complexes showed stable affinity in terms of root mean square distance (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and hydrogen bond. It was further confirmed that the five compounds had potential inhibitory effects on SARS-CoV-2 Mpro.

As an important component of energetic materials, high-energy oxidant is one of the key materials to improve their energy. The oxidizability of oxidant directly determines the intensity of combustion or explosion reaction. It is generally believed that when the nature of reductant is certain, the stronger the oxidizability, the more intense the reaction. Dioxygenyl cation (O2+) and pentazenium cation (N5+) are two kinds of super oxidizing ions, which oxidizability are comparable to that of fluorine. A series of high energetic ionic salts with O2+, N5+ and various anions as active components are designed, and the results show that: 1) Most ionic salts have appropriate thermodynamic stability, high density (up to 2.201 g/cm3), high enthalpy of formation (up to 1863.234 kJ/mol) and excellent detonation properties (up to 10.83 km/s, 45.9 GPa); 2) The detonation velocity value of O2 (nitrotetrazole-N-oxides) and O2B(N3)4 exceed 10.0 km/s, and the detonation pressure exceed 45.0 GPa because of the O2+ salts have higher crystal density (g/cm3) and oxygen balance than that of N5+salts; 3) With a higher nitrogen content than O2+, the N5+ salts have higher enthalpy of formation, which exceed 330 kJ/mol than that of O2+ salts; 4) The linear spatial structure of N5+ leads the salts to reduce their density. Encouragingly, this study proves that these super oxidizing ions have the potential to become high-energy oxidants, which could be a theoretical reference for the design of new high energetic materials.

Abstract The development of high‐performance dopant‐free silicon solar cells is severely bottlenecked by opaque electron selective contact. In this paper, high transmittance (80.5% on glass) and low work function (2.92 eV) lithium fluoride (LiFx)/MgFxOy electron contact stack by tailoring the composition of MgFxOy hybrid film is reported. This hybrid structure exhibits a high conductivity (2978.4 S cm−1) and a low contact resistivity (2.0 mΩ cm2). The element profile of LiFx/MgFxOy contact is measured and the reaction kinetics is analyzed. As a proof‐of‐concept, this electron selective contact is applied for dopant‐free silicon solar cells. An impressive efficiency of 21.3% is achieved on dopant‐free monofacial solar cell with molybdenum oxide (MoOx)/zinc‐doped indium oxide (IZO) hole contact. An efficiency bifaciality of 71% is obtained for dopant‐free bifacial solar cell with full‐area LiFx/MgFxOy/ITO (tin‐doped indium oxide) transparent electron contact. It is the highest efficiency bifaciality so far for dopant‐free bifacial solar cells to the best knowledge. Both cell configurations with LiFx/MgFxOy contacts show excellent environment stability. The cell efficiency maintains more than 95% of its initial value after keeping in air for 1500 h. This work provides a new idea to achieve transparent electron contact, showing a great potential for high‐efficiency and low‐cost optoelectronic devices.

Accurate detection and segmentation of the object fruit is the key part of orchard production measurement and automated picking. Affected by light, weather, and operating angle, it brings new challenges to the efficient and accurate detection and segmentation of the green object fruit under complex orchard backgrounds. For the green fruit segmentation, an efficient YOLOF-snake segmentation model is proposed. First, the ResNet101 structure is adopted as the backbone network to achieve feature extraction of the green object fruit. Then, the C5 feature maps are expanded with receptive fields and the decoder is used for classification and regression. Besides, the center point in the regression box is employed to get a diamond-shaped structure and fed into an additional Deep-snake network, which is adjusted to the contours of the target fruit to achieve fast and accurate segmentation of green fruit. The experimental results show that YOLOF-snake is sensitive to the green fruit, and the segmentation accuracy and efficiency are significantly improved. The proposed model can effectively extend the application of agricultural equipment and provide theoretical references for other fruits and vegetable segmentation.

Abstract High work function vanadium oxide (V2OX, X

Because of the unstructured characteristics of natural orchards, the efficient detection and segmentation applications of green fruits remain an essential challenge for intelligent agriculture. Therefore, an innovative fruit segmentation method based on deep learning, termed SE-COTR (segmentation based on coordinate transformer), is proposed to achieve accurate and real-time segmentation of green apples. The lightweight network MobileNetV2 is used as the backbone, combined with the constructed coordinate attention-based coordinate transformer module to enhance the focus on effective features. In addition, joint pyramid upsampling module is optimized for integrating multiscale features, making the model suitable for the detection and segmentation of target fruits with different sizes. Finally, in combination with the outputs of the function heads, the dynamic convolution operation is applied to predict the instance mask. In complex orchard environment with variable conditions, SE-COTR achieves a mean average precision of 61.6% with low complexity for green apple fruit segmentation at severe occlusion and different fruit scales. Especially, the segmentation accuracy for small target fruits reaches 43.3%, which is obviously better than other advanced segmentation models and realizes good recognition results. The proposed method effectively solves the problem of low accuracy and overly complex fruit segmentation models with the same color as the background and can be built in portable mobile devices to undertake accurate and efficient agricultural works in complex orchard.

Slot‐die coating is highly promising for scaled deposition of metal halide perovskite thin films. However, the power conversion efficiencies (PCEs) of slot‐die‐prepared perovskite solar cells (PSCs) still lag behind their spin‐casted counterparts. To resolve this issue, the crystal size and quality of slot‐die‐coated methylammonium lead triiodide (MAPbI3) perovskite films are dramatically improved via additive engineering using potassium thiocyanate (KSCN). The modified micrometer‐thick films have an average grain size of ≈11 μm and charge‐carrier parameters that are comparable with single‐crystal perovskites, such as a 1.89 μs lifetime, 136.65 ± 31.52 cm2 V−1 s−1 mobility, and 25.15 ± 3.55 μm diffusion length. Exploiting these enhanced properties, planar inverted PSCs with negligible hysteresis are fabricated and an average and a maximum PCE of 20.14% and 21.38%, respectively, are achieved which are among the highest reported values for slot‐die‐coated PSCs. Notably, our devices have a narrow PCE distribution along the slot‐die coating axis, highlighting slot‐die coating's promise to fabricate large‐scale, high‐performance PSCs.

T regulatory (Treg) cells play vital roles in modulating immunity and tissue homeostasis. Their actions depend on TCR recognition of peptide-MHC molecules; yet the degree of peptide specificity of Treg-cell function, and whether Treg ligands can be used to manipulate Treg cell biology are unknown. Here, we developed an Ab-peptide library that enabled unbiased screening of peptides recognized by a bona fide murine Treg cell clone isolated from the visceral adipose tissue (VAT), and identified surrogate agonist peptides, with differing affinities and signaling potencies. The VAT-Treg cells expanded in vivo by one of the surrogate agonists preserved the typical VAT-Treg transcriptional programs. Immunization with this surrogate, especially when coupled with blockade of TNFα signaling, expanded VAT-Treg cells, resulting in protection from inflammation and improved metabolic indices, including promotion of insulin sensitivity. These studies suggest that antigen-specific targeting of VAT-localized Treg cells could eventually be a strategy for improving metabolic disease.

Summary: A diverse T cell receptor (TCR) repertoire is essential for controlling viral infections. However, information about TCR repertoires to defined viral antigens is limited. We performed a comprehensive analysis of CD8+ TCR repertoires for two dominant viral epitopes: pp65495–503 (NLV) of cytomegalovirus and M158–66 (GIL) of influenza A virus. The highly individualized repertoires (87–5,533 α or β clonotypes per subject) comprised thousands of unique TCRα and TCRβ sequences and dozens of distinct complementary determining region (CDR)3α and CDR3β motifs. However, diversity is effectively restricted by preferential V-J combinations, CDR3 lengths, and CDR3α/CDR3β pairings. Structures of two GIL-specific TCRs bound to GIL–HLA-A2 provided a potential explanation for the lower diversity of GIL-specific versus NLV-specific repertoires. These anti-viral TCRs occupied up to 3.4% of the CD8+ TCRβ repertoire, ensuring broad T cell responses to single epitopes. Our portrait of two anti-viral TCR repertoires may inform the development of predictors of immune protection. : CD8+ T cells are essential for controlling viral infections. Chen et al. analyzed human TCR repertoires specific for two viral epitopes. Repertoire diversity was much greater than previously appreciated for both public and private TCRs. Such diversity assures protection from virus escape and the provision of T cell functional heterogeneity. Keywords: αβ TCRs for IAV-GIL, αβ TCRs for CMV-NLV, TCR repertoire, TCR-pMHC structure, CD8 T cells, human

Bastnaesite, monazite and xenotime are rare earth minerals (REMs) that are typical sources for rare earth elements (REEs). To advance the understanding of their leaching and precipitation behavior in different hydrometallurgical processes, Eh-pH diagrams were constructed and modified using the HSC 9.9 software. The aqueous stability of rare earth elements in H2O and acid leaching systems, i.e., the REE-Ligands-H2O systems, were depicted and studied based on the Eh-pH diagrams. This study considers the most relevant lixiviants, their resulting equilibrium states and the importance in the hydrometallurgical recovery of rare earth elements (REMs). A literature review was performed summarizing relevant Eh-pH diagrams and associated thermodynamic data. Shifting stability regions for REEs were discovered with additions of acid ligands and a narrow stability region for soluble REE-(SO4/Cl/NO3) complexes under highly acidic conditions. As such, the recovery of REEs can be enhanced by adjusting pH and Eh values. In addition, the Eh-pH diagrams of the major contaminants (i.e., Fe, Ca and Al) in leaching systems were studied. The resulting Eh-pH diagrams provide possible insights into potential passivation on the particle surfaces due to the formation of an insoluble product layer.