Inhalable Polymeric Microparticles for Phage and Photothermal Synergistic Therapy of Methicillin-Resistant Staphylococcus aureus Pneumonia.

Acute methicillin-resistant Staphylococcus aureus (MRSA) pneumonia is a common and serious lung infection with high morbidity and mortality rates. Due to the increasing antibiotic resistance, toxicity, and pathogenicity of MRSA, there is an urgent need to explore effective antibacterial strategies. In this study, we developed a dry powder inhalable formulation which is composed of porous microspheres prepared from poly(lactic-co-glycolic acid) (PLGA), internally loaded with indocyanine green (ICG)-modified, heat-resistant phages that we screened for their high efficacy against MRSA. This formulation can deliver therapeutic doses of ICG-modified active phages to the deep lung tissue infection sites, avoiding rapid clearance by alveolar macrophages. Combined with the synergistic treatment of phage therapy and photothermal therapy, the formulation demonstrates potent bactericidal effects in acute MRSA pneumonia. With its long-term stability at room temperature and inhalable characteristics, this formulation has the potential to be a promising drug for the clinical treatment of MRSA pneumonia.

Automatic segmentation of the interscapular brown adipose tissue in rats based on deep learning using the dynamic magnetic resonance fat fraction images.

OBJECTIVE: The study aims to propose an accurate labelling method of interscapular BAT (iBAT) in rats using dynamic MR fat fraction (FF) images with noradrenaline (NE) stimulation and then develop an automatic iBAT segmentation method using a U-Net model. MATERIALS AND METHODS: Thirty-four rats fed different diets or housed at different temperatures underwent successive MR scans before and after NE injection. The iBAT were labelled automatically by identifying the regions with obvious FF change in response to the NE stimulation. Further, these FF images along with the recognized iBAT mask images were used to develop a deep learning network to accomplish the robust segmentation of iBAT in various rat models, even without NE stimulation. The trained model was then validated in rats fed with high-fat diet (HFD) in comparison with normal diet (ND). RESULT: A total of 6510 FF images were collected using a clinical 3.0 T MR scanner. The dice similarity coefficient (DSC) between the automatic and manual labelled results was 0.895 ± 0.022. For the network training, the DSC, precision rate, and recall rate were found to be 0.897 ± 0.061, 0.901 ± 0.068 and 0.899 ± 0.086, respectively. The volumes and FF values of iBAT in HFD rats were higher than ND rats, while the FF decrease was larger in ND rats after NE injection. CONCLUSION: An automatic iBAT segmentation method for rats was successfully developed using the dynamic labelled FF images of activated BAT and deep learning network.

Terrace-Like 2D Hierarchically Porous Iron/Cobalt Metal-Organic Framework: Ambient Fast Synthesis and Efficient Oxygen Evolution Reaction Application.

It is urgent to design a low-cost electrocatalyst with high activity to enhance the efficiency of oxygen evolution reaction (OER), which is limited by the slow four-electron transfer kinetics process. Nevertheless, traditional synthetic methods, including calcination and solvothermal, of the electrocatalysts are high-cost, low-yield, and energy-hogging, which limits their industrial application. Herein, an ambient fast synthetic method is developed to prepare terrace-like Fe/Co bimetal-organic framework (TFC-MOF) electrocatalyst materials in gram scale in 1 h. The method in this paper is designable based on coordination chemistry. Fe and Co ions can coordinate with the carboxyl groups on benzene-1,3,5-tricarboxylic acid (H3 BTC) to form a 2D-MOF structure. Structural characterizations, including SEM, TEM, and XRD are conducted to verify that the TFC-MOF is a terrace-like layered structure with uniform-sized mesoporous, which reduces the adsorption steric hindrance and facilitates the mass and electron transfer efficiency of OER. The TFC-MOF shows low overpotential, 255 mV at a current density of 10 mA cm-2 , and a low Tafel slope of 49.9 mV dec-1 , in an alkaline solution. This work provides a planar coordination strategy to synthesize 2D-MOF OER electrocatalyst on a large scale with low cost and low energy consumption, which will promote its practical OER applications.

Reducing the ambiguity of field inhomogeneity and chemical shift effect for fat-water separation by field factor.

PURPOSE: To reduce the ambiguity between chemical shift and field inhomogeneity with flexible TE combinations by introducing a variable (field factor). THEORY AND METHODS: The ambiguity between chemical shift and field inhomogeneity can be eliminated directly from the multiple in-phase images acquired at different TEs; however, it is only applicable to few echo combinations. In this study, we accommodated such an implementation in flexible TE combinations by introducing a new variable (field factor). The effects of the chemical shift were removed from the field inhomogeneity in the candidate solutions, thus reducing the ambiguity problem. To validate this concept, multi-echo MRI data acquired from various anatomies with different imaging parameters were tested. The derived fat and water images were compared with those of the state-of-the-art fat-water separation algorithms. RESULTS: Robust fat-water separation was achieved with the accurate solution of field inhomogeneity, and no apparent fat-water swap was observed. In addition to the good performance, the proposed method is applicable to various fat-water separation applications, including different sequence types and flexible TE choices. CONCLUSION: We propose an algorithm to reduce the ambiguity of chemical shift and field inhomogeneity and achieved robust fat-water separation in various applications.

A new deuterium-labeled compound [2,3,4,6,6'-2 H5 ]-D-glucose for deuterium magnetic resonance metabolic imaging.

Deuterium (2 H) magnetic resonance imaging is an emerging approach for noninvasively studying glucose metabolism in vivo, which is important for understanding pathogenesis and monitoring the progression of many diseases such as tumors, diabetes, and neurodegenerative diseases. However, the synthesis of 2 H-labeled glucose is costly because of the expensive raw substrates and the requirement for extreme reaction conditions, making the 2 H-labeled glucose rather expensive and unaffordable for clinic use. In this study, we present a new deuterated compound, [2,3,4,6,6'-2 H5 ]-D-glucose, with an approximate 10-fold reduction in production costs. The synthesis route uses cheaper raw substrate methyl-α-D-glucopyranoside, relies on mild reaction conditions (80°C), and has higher deuterium labeling efficiency. Magnetic resonance spectroscopy (MRS) and mass spectroscopy experiments confirmed the successful deuterium labeling in the compound. Animal studies demonstrated that the substrate could describe the glycolytic metabolism in a glioma rat model by quantifying the downstream metabolites through 2 H-MRS on an ultrahigh field system. Comparison of the glucose metabolism characteristics was carried out between [2,3,4,6,6'-2 H5 ]-D-glucose and commercial [6,6'-2 H2 ]-D-glucose in the animal studies. This cost-effective compound will help facilitate the clinical translation of deuterium magnetic resonance imaging, and enable this powerful metabolic imaging modality to be widely used in both preclinical and clinical research and applications.

Selective Reduction Leading to 3,5-cis-3-Aminosugars: Synthesis and Stereoselective Glycosylation.

Synthesis of 3,5-cis-3-amino glycals with a cis-fused cyclic sulfamidate group has been achieved by selective reduction of sulfamidate ketimine groups. The efficient access to the structurally unique glycals allowed the subsequent divergent synthesis of various naturally occurring 3-amino-2,3,6-trideoxysugars. In addition, Lewis acid-promoted glycosylation of the glycals provided a simple solution for the stereoselective installation of O- and C-linked aglycons on the amino sugar scaffolds.

Efficacy and Safety of Finerenone for Prevention of Cardiovascular Events in Type 2 Diabetes Mellitus With Chronic Kidney Disease: A Meta-analysis of Randomized Controlled Trials.

ABSTRACT: Only a few meta-analyses evaluated the effect of finerenone on cardiovascular events in type 2 diabetes mellitus with chronic kidney disease. The main aim of this meta-analysis was to gain more reliable assessments of the efficacy and safety of finerenone for prevention of cardiovascular events in diabetic kidney disease. We searched for finerenone in the treatment of diabetic kidney disease from database (PubMed, Embase, and ClinicalTrials.gov ) until December 30, 2021. Relative risks (RRs) with 95% confidence intervals (CIs) calculated by the Mantel-Haenszel random-effects model were used as summary statistics for the categorical data. We included 4 studies that met the inclusion criteria with 13,943 participants. The finerenone group demonstrated a great benefit in reducing the incidence of major adverse cardiac events (RR: 0.88; 95% CI 0.80-0.96; P = 0.003), all-cause mortality (RR: 0.89; 95% CI 0.80-0.99; P = 0.04), myocardial infarction (RR: 0.79; 95% CI 0.67-0.92; P = 0.003), and new-onset hypertension (RR: 0.71; 95% CI 0.62-0.81; P < 0.00001). No difference was found in adverse events between the finerenone and placebo groups (RR: 1.00; 95% CI [0.98-1.01], P = 0.59), whereas a higher risk of hyperkalemia was observed in the finerenone group than in the placebo group (RR = 2.04, 95% CI 1.80-2.32; P < 0.00001). Besides, cerebrovascular events and new-onset atrial fibrillation did not increase in patients taking finerenone. Overall, finerenone treatment showed a great benefit of reducing the risk of major adverse cardiac events, all-cause mortality, myocardial infarction, and new-onset hypertension events in patients with type 2 diabetes mellitus and chronic kidney disease.

Enhanced Oxidation of Organic Compounds by the Ferrihydrite-Ferrate System: The Role of Intramolecular Electron Transfer and Intermediate Iron Species.

Previous studies mostly held that the oxidation capacity of ferrate depends on the involvement of intermediate iron species (i.e., FeIV/FeV), however, the potential role of the metastable complex was disregarded in ferrate-based heterogeneous catalytic oxidation processes. Herein, we reported a complexation-mediated electron transfer mechanism in the ferrihydrite-ferrate system toward sulfamethoxazole (SMX) degradation. A synergy between intermediate FeIV/FeV oxidation and the intramolecular electron transfer step was proposed. Specifically, the conversion of phenyl methyl sulfoxide (PMSO) to methyl phenyl sulfone (PMSO2) suggested that FeIV/FeV was involved in the oxidation of SMX. Moreover, based on the in situ Raman test and chronopotentiometry analysis, the formation of the metastable complex of ferrihydrite/ferrate was found, which possesses higher oxidation potential than free ferrate and could achieve the preliminary oxidation of organics via the electron transfer step. In addition, the amino group of SMX could complex with ferrate, and the resulting metastable complex of ferrihydrite/ferrate would combine further with SMX molecules, leading to intramolecular electron transfer and SMX degradation. The ferrate loss experiments suggested that ferrihydrite could accelerate the decomposition of ferrate. Finally, the effects of pH value, anions, humic acid, and actual water on the degradation of SMX by ferrihydrite-ferrate were also revealed. Overall, ferrihydrite demonstrated high catalytic capacity, good reusability, and nontoxic performance for ferrate activation. The ferrihydrite-ferrate process may be a green and promising method for organic removal in wastewater treatment.

Genome-wide identification and analysis of the evolution and expression pattern of the SBP gene family in two Chimonanthus species.

BACKGROUND: Chimonanthus praecox and Chimonanthus salicifolius are closely related species that diverged approximately six million years ago. While both C. praecox and C. salicifolius could withstand brief periods of low temperatures of - 15 °C. Their flowering times are different, C. praecox blooms in early spring, whereas C. salicifolius blooms in autumn. The SBP-box (SQUAMOSA promoter-binding protein) is a plant-specific gene family that plays a crucial vital role in regulating plant flowering. Although extensively studied in various plants, the SBP gene family remains uncharacterized in Calycanthaceae. METHODS AND RESULTS: We conducted genome-wide identification of SBP genes in both C. praecox and C. salicifolius and comprehensively characterized the chromosomal localization, gene structure, conserved motifs, and domains of the identified SBP genes. In total, 15 and 18 SBP genes were identified in C. praecox and C. salicifolius, respectively. According to phylogenetic analysis, the SBP genes from Arabidopsis, C. praecox, and C. salicifolius were clustered into eight groups. Analysis of the gene structure and conserved protein motifs showed that SBP proteins of the same subfamily have similar motif structures. The expression patterns of SBP genes were analyzed using transcriptome data. The results revealed that more than half of the genes exhibited lower expression levels in leaves than in flowers, suggesting their potential involvement in the flower development process and may be linked to the winter and autumn flowering of C. praecox and C. salicifolius. CONCLUSION: Thirty-three SBPs were identified in C. praecox and C. salicifolius. The evolutionary characteristics and expression patterns were examined in this study. These results provide valuable information to elucidate the evolutionary relationships of the SBP family and help determine the functional characteristics of the SBP genes in subsequent studies.

Automatic segmentation of human supraclavicular adipose tissue using high-resolution T2-weighted magnetic resonance imaging.

OBJECTIVE: To achieve efficient segmentation of human supraclavicular adipose tissue (sclavAT) using high-resolution T2-weighted magnetic resonance images. METHODS: High-resolution 1.0 mm isotropic 3D T2-weighted images covering human supraclavicular area were acquired in transverse or coronary plane from 29 volunteers using a 3.0 T MRI scanner. There were typically 144/288 slices for the transverse/coronary scans for each subject, which amounts to a total of 6816 images in 29 volunteers. A U-NET network was trained to segment the supraclavicular adipose tissue (sclavAT). The performance of the automatic segmentation method was evaluated by comparing the output results with the manual labels using the quantitative indices of dice similarity coefficient (DSC), precision rate (PR), and recall rate (RR). The auto-segmented images were used to calculate the sclavAT volumes and registered to the MR fat fraction (FF) images to quantify the fat component of the sclavAT area. The relationship between body mass index (BMI), the volume and FF of sclavAT area was evaluated for all subjects. RESULTS: The DSC, PR and RR of the automatic sclavAT segmentation method on the testing datasets were 0.920 ± 0.048, 0.915 ± 0.070 and 0.930 ± 0.058. The volume and the mean FF of sclavAT were both found to be strongly correlated to BMI, with the correlation coefficient of 0.703 and 0.625 (p < 0.05), respectively. The averaged computation time of the automatic segmentation method was approximately 0.06 s per slice, compared to more than 5 min for manual labeling. CONCLUSION: The present study demonstrates that the proposed automatic segmentation method using U-Net network is able to identify human sclavAT efficiently and accurately.

Machine learning approaches to predict the apparent rate constants for aqueous organic compounds by ferrate.

The apparent second-order rate constant with hexavalent ferrate (Fe(VI)) (kFe(VI)) is a key indicator to evaluate the removal efficiency of a molecule by Fe(VI) oxidation. kFe(VI) is often determined by experiment, but such measurements can hardly catch up with the rapid growth of organic compounds (OCs). To address this issue, in this study, a total of 437 experimental second-order kFe(VI) rate constants at a range of conditions (pH and temperature) were used to train four machine learning (ML) algorithms (lasso regression (LR), ridge regression (RR), extreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM)). Using the Morgan fingerprint (MF)) of a range of organic compounds (OCs) as the input, the performance of the four algorithms was comprehensively compared with respect to the coefficient of determination (R2) and root-mean-square error (RMSE). It is shown that the RR, XGBoost, and LightGBM models displayed generally acceptable performance kFe(VI) (R2test > 0.7). In addition, the shapely additive explanation (SHAP) and feature importance methods were employed to interpret the XGBoost/LightGBM and RR models, respectively. The results showed that the XGBoost/LightGBM and RR models suggestd pH as the most important predictor and the tree-based models elucidate how electron-donating and electron-withdrawing groups influence the reactivity of the Fe(VI) species. In addition, the RR model share eight common features, including pH, with the two tree-based models. This work provides a fast and acceptable method for predicting kFe(VI) values and can help researchers better understand the degradation behavior of OCs by Fe(VI) oxidation from the perspective of molecular structure.

Fast multi-parametric imaging in abdomen by B 1 + corrected dual-flip angle sequence with interleaved echo acquisition.

PURPOSE: To achieve simultaneous T1, w /proton density fat fraction (PDFF)/ R 2 ∗ mapping in abdomen within a single breadth-hold, and validate the accuracy using state-of-art measurement. THEORY AND METHODS: An optimized multiple echo gradient echo (GRE) sequence with dual flip-angle acquisition was used to realize simultaneous water T1 (T1, w )/PDFF/ R 2 ∗ quantification. A new method, referred to as "solving the fat-water ambiguity based on their T1 difference" (SORT), was proposed to address the fat-water separation problem. This method was based on the finding that compared to the true solution, the wrong (or aliased) solution to fat-water separation problem showed extra dependency on the applied flip angle due to the T1 difference between fat and water. The B 1 + measurement sequence was applied to correct the B 1 + inhomogeneity for T1, w relaxometry. The 2D parallel imaging was incorporated to enable the acquisition within a single breath-hold in abdomen. RESULTS: The multi-parametric quantification results of the proposed method were consistent with the results of reference methods in phantom experiments (PDFF quantification: R2  = 0.993, mean error 0.73%; T1, w quantification: R2  = 0.999, mean error 4.3%; R 2 ∗ quantification: R2  = 0.949, mean error 4.07 s-1 ). For volunteer studies, robust fat-water separation was achieved without evident fat-water swaps. Based on the accurate fat-water separation, simultaneous T1, w /PDFF/ R 2 ∗ quantification was realized for whole liver within a single breath-hold. CONCLUSION: The proposed method accurately quantified T1, w /PDFF/ R 2 ∗ for the whole liver within a single breath-hold. This technique serves as a quantitative tool for disease management in patients with hepatic steatosis.

Water Specific MRI T1 Mapping for Evaluating Liver Inflammation Activity Grades in Rats With Methionine-Choline-Deficient Diet-Induced Nonalcoholic Fatty Liver Disease.

BACKGROUND: Early detection and grading of liver inflammation are important for the management of nonalcoholic fatty liver disease (NAFLD) patients. There is still lack of a noninvasive way for the inflammation characterization in NAFLD. PURPOSE: To assess liver inflammation grades by water specific T1 (wT1) in a rat model. STUDY TYPE: Prospective. ANIMAL MODEL: A total of 65 male rats with methionine-choline-deficient diet-induced NAFLD and 15 male normal rats as control. FIELD STRENGTH/SEQUENCE: A 3 T; multiecho variable flip angle gradient echo sequence. ASSESSMENT: The wT1 and proton density fat fraction were quantified. Inflammation and fibrosis were assessed histologically with H&E and Sirius red stained slices according to the nonalcoholic steatohepatitis scoring system. Inflammation grade was scored with G0/G1/G2/G3 as none/mild/moderate/severe inflammation in NALFD rats. G0 + G1 and G2 + G3 were combined as none-to-mild grade (GL) and moderate-to-severe grade (GH) inflammation groups. STATISTICAL TESTS: Analysis of variance (ANOVA), Mann-Whitney U test, Spearman's correlation, and receiver operating characteristic (ROC) analysis were performed. The areas under ROC (AUROC) was used for the diagnostic performance of wT1 in discriminating GH and GL. A P value < 0.01 was considered statistically significant. RESULTS: Seventy-six rats were included in the analysis. The numbers in G0-G3 groups were 5, 16, 13, and 27. wT1 of G0-G3 was 568.55 ± 63.93 msec, 582.53 ± 62.98 msec, 521.21 ± 67.31 msec, and 508.79 ± 60.53 msec. A moderate but significant negative correlation between wT1 and histopathological inflammation grades was observed (rs  = -0.42). The wT1 of GH (512.80 ± 62.22 msec) was significantly lower than GL (579.20 ± 61.89 msec). The AUROC of wT1 was 0.79, and the optimal cut-off of wT1 was 562.64 msec (sensitivity: 90%, specificity: 76%), for the discrimination of GL and GH. DATA CONCLUSIONS: wT1 could differentiate none-to-mild inflammation from moderate-to-severe inflammation in the early stage of the NAFLD rat model. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

STIM2 promotes the invasion and metastasis of breast cancer cells through the NFAT1/TGF-ß1 pathway.

A large amount of evidence indicates that the abnormal activation of multiple signal transduction pathways in cells is closely related to the occurrence and development of tumors. TGF-ß and NFAT1 signaling pathways can inhibit cell proliferation and promote apoptosis in the early stage of breast cancer, but with the increase of tumor malignancy, the two appear to promote tumor progression and deterioration. Therefore, the study of the relationship between STIM2 and NFAT1/TGF-ß1 is helpful for the discovery and treatment of breast cancer, which is of great significance for improving the survival rate of breast cancer patients. This article focuses on the effect of STIM2 molecules on breast cancer cell migration through the NFAT1/ TGF-ß1 pathway and discusses the regulatory mechanism of STIM2 affecting breast cancer cell migration. Experimental data shows that the positive rate of breast cancer NFAT1 is 54%, which is significantly lower than that of benign breast Tissue 85%; the positive expression rate of TGF-ß1 in benign breast tissue is 85%, and the positive expression rate in breast cancer tissue is 49%. The results show that STIM2 protein can promote the invasion and metastasis of breast cancer cells through the NFAT1 / TGF-ß1 pathway.

The effect of miR-138 on the proliferation and apoptosis of breast cancer cells through the NF-κB/VEGF signaling pathway.

The analyze the effect of miR-138 on the proliferation and apoptosis of breast cancer cells through the NF-κB/VEGF signaling pathway is the Objective of this experiment. For this aim, the endometrial stem breast cancer cell line MCF-7 was cultured in vitro, and the overexpression mimic miR-138 mimics and the inhibitor anti-miR-138 were transfected into the endometrial stem breast cancer cell line MCF-7, which was set to overexpress miR-138 group and interfere with miR-138, and set up negative control of overexpression and negative control of inhibitor. Observe the cell proliferation and apoptosis ability of each group, and the changes in tumor necrosis factor-α (TNF-α), interleukin 1ß, 6, 18 (IL-1ß, IL-6, IL-18) levels, and compare the Bax of each group, NF-κB, VEGF protein expression level. Results showed that the proliferation ability of the miR-138 overexpression group was significantly lower than that of the miR-138 overexpression control group (P<0.05); the proliferation ability of the miR-138 interference group was significantly higher than that of the miR-138 interference control group (P<0.05). The apoptosis rate, caspase-3 and caspase-9 expression levels of the miR-138 overexpression group were significantly higher than those of the miR-138 overexpression control group (P<0.05);  the apoptosis rate, caspase-3 and caspase-9 expression levels of the miR-138 interference group were significantly lower than those of the miR-138 interference control group (P<0.05). The expression levels of IL-1 ß, IL-6, IL-18 and TNF - α in the miR-138 overexpression group were significantly lower than those in the miR-138 overexpression control group (P < 0.05). The protein expression levels of Bax, NF-κB and VEGF in the miR-138 overexpression group were significantly lower than those in the miR-138 overexpression control group (P < 0.05); the protein expression levels of Bax, NF-κB and VEGF in the miR-138 interference group were significantly higher than those in the miR-138 interference control group (P <0.05). The proliferation ability of the miR-138 overexpression group was significantly lower than that of the miR-138 overexpression control group (P < 0.05); the proliferation ability of the miR-138 + NF-κB overexpression group was significantly higher than that of the miR-138 overexpression group (P<0.05). The apoptosis rate of the miR-138 + NF-κB overexpression group was significantly lower than that of the miR-138 overexpression group (P < 0.05). Then MiR-138 can significantly inhibit the proliferation of breast cancer cells, promote apoptosis, and regulate the expression of inflammatory factors in the cells. It is speculated that the related mechanism may be related to the negative regulation of the NF-κB/VEGF signaling pathway.

Automatic segmentation of whole-body adipose tissue from magnetic resonance fat fraction images based on machine learning.

OBJECTIVE: To propose a fully automated algorithm, which is implemented to segment subcutaneous adipose tissue (SAT) and internal adipose tissue (IAT) from the total adipose tissue for whole-body fat distribution analysis using proton density fat fraction (PDFF) magnetic resonance images. MATERIALS AND METHODS: Adipose tissue segmentation was implemented using the U-Net deep neural network model. All datasets were collected using a 3.0 T magnetic resonance imaging (MRI) scanner for whole-body scan of 20 volunteers covering from neck to knee with about 160 images for each volunteer. PDFF images were reconstructed based on chemical-shift-encoded fat-water imaging. After selecting the representative PDFF images (total 906 images), the manual labeling of the SAT area was used for model training (504 images), validation (168 images), and testing (234 images). RESULTS: The automatic segmentation model was validated through three indices using the validation and test sets. The dice similarity coefficient, precision rate, and recall rate were 0.976 ± 0.048, 0.978 ± 0.048, and 0.978 ± 0.050, respectively, in both validation and test sets. CONCLUSION: The proposed algorithm can reliably and automatically segment SAT and IAT from whole-body MRI PDFF images. The proposed method provides a simple and automatic tool for whole-body fat distribution analysis to explore the relationship between fat deposition and metabolic-related chronic diseases.

Equipment Identification and Localization Method Based on Improved YOLOv5s Model for Production Line.

Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the upcoming era of Industry 5.0. Currently, low recognition accuracy and low location precision of devices in intelligent monitoring remain a problem in production lines. This paper proposes a production line device recognition and localization method based on an improved YOLOv5s model. The proposed method can achieve real-time detection and localization of production line equipment such as robotic arms and AGV carts by introducing CA attention module in YOLOv5s network model architecture, GSConv lightweight convolution method and Slim-Neck method in Neck layer, add Decoupled Head structure to the Detect layer. The experimental results show that the improved method achieves 93.6% Precision, 85.6% recall, and 91.8% mAP@0.5, and the Pascal VOC2007 public dataset test shows that the improved method effectively improves the recognition accuracy. The research results can substantially improve the intelligence level of production lines and provide an important reference for manufacturing industries to realize intelligent and digital transformation.

Genome-Wide Identification of Auxin Response Factors in Peanut (Arachis hypogaea L.) and Functional Analysis in Root Morphology.

Auxin response factors (ARFs) play important roles in plant growth and development; however, research in peanut (Arachis hypogaea L.) is still lacking. Here, 63, 30, and 30 AhARF genes were identified from an allotetraploid peanut cultivar and two diploid ancestors (A. duranensis and A. ipaensis). Phylogenetic tree and gene structure analysis showed that most AhARFs were highly similar to those in the ancestors. By scanning the whole-genome for ARF-recognized cis-elements, we obtained a potential target gene pool of AhARFs, and the further cluster analysis and comparative analysis showed that numerous members were closely related to root development. Furthermore, we comprehensively analyzed the relationship between the root morphology and the expression levels of AhARFs in 11 peanut varieties. The results showed that the expression levels of AhARF14/26/45 were positively correlated with root length, root surface area, and root tip number, suggesting an important regulatory role of these genes in root architecture and potential application values in peanut breeding.

Kukhtin-Ramirez-Reaction-Inspired Deprotection of Sulfamidates for the Synthesis of Amino Sugars.

Herein, we present a mild strategy for deprotecting cyclic sulfamidates via the Kukhtin-Ramirez reaction to access amino sugars. The method features the removal of the sulfonic group of cyclic sulfamidates, which occurs through an N-H insertion reaction that implicates the Kukhtin-Ramirez adducts, followed by a base-promoted reductive N-S bond cleavage. The mild reaction conditions of the protocol enable the formation of amino alcohols including analogs that bear multiple functional groups.

Synthesis of Holmium-Oxide Nanoparticles for Near-Infrared Imaging and Dye-Photodegradation.

The development of multifunctional nanomaterials has received growing research interest, thanks to its ability to combine multiple properties for severing highly demanding purposes. In this work, holmium oxide nanoparticles are synthesized and characterized by various tools including XRD, XPS, and TEM. These nanoparticles are found to emit near-infrared fluorescence (800-1100 nm) under a 785 nm excitation source. Imaging of the animal tissues was demonstrated, and the maximum imaging depth was found to be 2.2 cm. The synthesized nanoparticles also show the capability of facilitating dye (fluorescein sodium salt and rhodamine 6G) degradation under white light irradiation. The synthesized holmium oxide nanoparticles are envisioned to be useful for near-infrared tissue imaging and dye-degradation.