Dual-Site Biomimetic Cu/Zn-MOF for Atopic Dermatitis Catalytic Therapy via Suppressing FcγR-Mediated Phagocytosis.

Atopic dermatitis (AD) is a prevalent chronic inflammatory skin disease that carries a significant global economic burden. Elevated levels of reactive oxygen species (ROS) have been recognized as contributing to AD exacerbation, making them a potential therapeutic target for AD treatment. Here, we introduce a dual-site biomimetic copper/zinc metal-organic framework (Cu/Zn-MOF) featuring four types of enzyme-like activities for AD treatment via suppressing the Fcγ receptor (FcγR)-mediated phagocytosis signal by mimicking the bimetallic sites of natural copper-zinc superoxide dismutase (CuZn-SOD). Interestingly, the neighboring Cu and Zn sites in both Cu/Zn-MOF and CuZn-SOD are at similar distances of ∼5.98 and ∼6.3 Šfrom each other, respectively, and additionally, both Cu and Zn sites are coordinated to nitrogen atoms in both structures, and the coordinating ligands to Cu and Zn are both imidazole rings. Cu/Zn-MOF exhibits remarkable SOD-like activity as well as its glutathione peroxidase (GPx)-, thiol peroxidase (TPx)-, and ascorbate peroxidase (APx)-like activities to continuously consume ROS and mitigate oxidative stress in keratinocytes. Animal experiments show that Cu/Zn-MOF outperforms halcinonide solution (a potent steroid medication) in terms of preventing mechanical injuries, reducing cutaneous water loss, and inhibiting inflammatory responses while presenting favorable biosafety. Mechanistically, Cu/Zn-MOF functions through an FcγR-mediated phagocytosis signal pathway, decreasing the continuous accumulation of ROS in AD and ultimately suppressing disease progression. These findings will provide an effective paradigm for AD therapy and contribute to the development of two-site bionics (TSB).

Detection of Helicobacter pylori Infection in Human Gastric Fluid Through Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms.

Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H. pylori diagnosis. In this study, we propose a novel technique for accurately detecting H. pylori infection through machine learning analysis of surface-enhanced Raman scattering (SERS) spectra of gastric fluid samples that were noninvasively collected from human stomachs via the string test. One hundred participants were recruited to collect gastric fluid samples noninvasively. Therefore, 12,000 SERS spectra (n = 120 spectra/participant) were generated for building machine learning models evaluated by standard metrics in model performance assessment. According to the results, the Light Gradient Boosting Machine algorithm exhibited the best prediction capacity and time efficiency (accuracy = 99.54% and time = 2.61 seconds). Moreover, the Light Gradient Boosting Machine model was blindly tested on 2,000 SERS spectra collected from 100 participants with unknown H. pylori infection status, achieving a prediction accuracy of 82.15% compared with qPCR results. This novel technique is simple and rapid in diagnosing H. pylori infection, potentially complementing current H. pylori diagnostic methods.

Low-Cost Plant-Protection Unmanned Ground Vehicle System for Variable Weeding Using Machine Vision.

This study presents a machine vision-based variable weeding system for plant- protection unmanned ground vehicles (UGVs) to address the issues of pesticide waste and environmental pollution that are readily caused by traditional spraying agricultural machinery. The system utilizes fuzzy rules to achieve adaptive modification of the Kp, Ki, and Kd adjustment parameters of the PID control algorithm and combines them with an interleaved period PWM controller to reduce the impact of nonlinear variations in water pressure on the performance of the system, and to improve the stability and control accuracy of the system. After testing various image threshold segmentation and image graying algorithms, the normalized super green algorithm (2G-R-B) and the fast iterative threshold segmentation method were adopted as the best combination. This combination effectively distinguished between the vegetation and the background, and thus improved the accuracy of the pixel extraction algorithm for vegetation distribution. The results of orthogonal testing by selected four representative spraying duty cycles-25%, 50%, 75%, and 100%-showed that the pressure variation was less than 0.05 MPa, the average spraying error was less than 2%, and the highest error was less than 5% throughout the test. Finally, the performance of the system was comprehensively evaluated through field trials. The evaluation showed that the system was able to adjust the corresponding spraying volume in real time according to the vegetation distribution under the decision-making based on machine vision algorithms, which proved the low cost and effectiveness of the designed variable weed control system.

Exosomes Derived from Adipose Mesenchymal Stem Cells Promote Regeneration of Injured Liver in Minipigs.

Hepatic ischemia/reperfusion injury (IRI) is an important factor affecting liver regeneration and functional recovery postoperatively. Many studies have suggested that mesenchymal stem cells (MSCs) contribute to hepatic tissue repair and functional recovery through paracrine mechanisms mediated by exosomes. Minipigs exhibit much more similar characteristics of the liver to those of humans than rodents. This study aimed to explore whether exosomes from adipose-derived MSCs (ADSCs-exo) could actively promote liver regeneration after hepatectomy combined with HIRI in minipigs and the role they play in the cell proliferation process. This study also compared the effects and differences in the role of ADSCs and ADSCs-exo in the inflammatory response and liver regeneration. The results showed that ADSCs-exo suppressed histopathological changes and reduced inflammatory infiltration in the liver; significantly decreased levels of ALT, TBIL, HA, and the pro-inflammatory cytokines TNF-α, IL-6, and CRP; increased levels of the anti-inflammatory cytokine IL-10 and the pro-regeneration factors Ki67, PCNA, CyclinD1, HGF, STAT3, VEGF, ANG1, ANG2; and decreased levels of the anti-regeneration factors SOCS3 and TGF-ß. These indicators above showed similar changes with the ADSCs intervention group. Indicating that ADSCs-exo can exert the same role as ADSCs in regulating inflammatory responses and promoting liver regeneration. Our findings provide experimental evidence for the possibility that ADSCs-exo could be considered a safe and effective cell-free therapy to promote regeneration of injured livers.

Key Roles of Interfacial OH- ion Distribution on Proton Coupled Electron Transfer Kinetics Toward Urea Oxidation Reaction.

Enhancing alkaline urea oxidation reaction (UOR) activity is essential to upgrade renewable electrolysis systems. As a core step of UOR, proton-coupled electron transfer (PCET) determines the overall performance, and accelerating its kinetic remains a challenge. In this work, a newly raised electrocatalyst of NiCoMoCuOx Hy with derived multi-metal co-doping (oxy)hydroxide species during electrochemical oxidation states is reported, which ensures considerable alkaline UOR activity (10/500 mA cm-2 at 1.32/1.52 V vs RHE, respectively). Impressively, comprehensive studies elucidate the correlation between the electrode-electrolyte interfacial microenvironment and the electrocatalytic urea oxidation behavior. Specifically, NiCoMoCuOx Hy featured with dendritic nanostructure creates a strengthened electric field distribution. This structural factor prompts the local OH- enrichment in electrical double layer (EDL), so that the dehydrogenative oxidation of the catalyst is directly reinforced to facilitate the subsequent PCET kinetics of nucleophilic urea, resulting in high UOR performance. In practical utilization, NiCoMoCuOx Hy -driven UOR coupled cathodic hydrogen evolution reaction (HER) and carbon dioxide reduction reaction (CO2 RR), and harvested high value-added products of H2 and C2 H4 , respectively. This work clarifies a novel mechanism to improve electrocatalytic UOR performance through structure-induced interfacial microenvironment modulation.

Development and initial validation of the psychological capital scale for nurses in Chinese local context.

BACKGROUND: Psychological capital is affected by different cultures and professional characteristics and its constituent dimensions and evaluation tools are heterogeneous. There is a lack of measurements for assessing nurses' psychological capital considering nursing professional characteristics and Chinese cultural impacts. AIMS: To develop a psychological capital scale that conforms to the Chinese cultural background and the characteristics of nursing profession, and evaluate the preliminary validation of the Nurses Psychological Capital Scale. METHODS: Nurses were conveniently recruited from two tertiary hospitals, Hebei, China. The research process included three steps: item development (Delphi survey and pilot survey), scale development (item analysis and exploratory factor analysis), scale validation (reliability and validity test). RESULTS: Exploratory factor analysis and confirmatory factor analysis showed that the 43-item scale comprised three factors (work task-oriented psychological capital, interpersonal relationship-oriented psychological capital and learning development-oriented psychological capital). Exploratory factor analysis showed the factor loadings ranging from 0.460 to 1.029. Three factors explained 68.71% of the variance. Confirmatory factor analysis showed an adequate model fit (x2/df =2.839, RMR = 0.041, RMSEA = 0.078, IFI = 0.872, TLI = 0.863, CFI = 0.871, PNFI = 0.768). The Cronbach's α for the scale was 0.975. The item-level content validity index (I-CVI) was 0.83 ~ 1.00, scale-level average content validity index (S-CVI/Ave) was 0.988. CONCLUSION: The Nurse Psychological Capital Scale had good reliability and validity, which is a reliable evaluation measure for assessing psychological capital among nurses.

Effects of Exosomes Derived from Adipose-Derived Mesenchymal Stem Cells on Pyroptosis and Regeneration of Injured Liver.

Although accumulating evidence indicates that exosomes have a positive therapeutic effect on hepatic ischemia-reperfusion injury (HIRI), studies focusing on the alleviation of liver injury by exosomes derived from adipose-derived mesenchymal stem cells (ADSCs-Exo) based on the inhibition of cell pyroptosis have not yet been reported. Exosomes contain different kinds of biologically active substances such as proteins, lipids, mRNAs, miRNAs, and signaling molecules. These molecules are widely involved in cell-cell communication, cell signal transmission, proliferation, migration, and apoptosis. Therefore, we investigated the positive effects exerted by ADSCs-Exo after hepatic ischemia-reperfusion with partial resection injury in rats. In this study, we found that the post-operative tail vein injection of ADSCs-Exo could effectively inhibit the expression of pyroptosis-related factors such as NLRP3, ASC, caspase-1, and GSDMD-N, and promote the expression of regeneration-related factors such as Cyclin D1 and VEGF. Moreover, we found that the above cellular activities were associated with the NF-κB and Wnt/ß-catenin signaling pathways. According to the results, ADSCs and ADSCs-Exo can reduce pyroptosis in the injured liver and promote the expression of those factors related to liver regeneration, while they can inhibit the NF-κB pathway and activate the Wnt/ß-catenin pathway. However, although adipose-derived mesenchymal stem cell (ADSC) transplantation can reduce liver injury, it leads to a significant increase in the pyroptosis-related protein GSDMD-N expression. In conclusion, our study shows that ADSCs-Exo has unique advantages and significance as a cell-free therapy to replace stem cells and still has a broad research prospect in the clinical diagnosis and treatment of liver injuries.

Single-Atom Catalysts for Nanocatalytic Tumor Therapy.

Recently, single-atom catalysts (SACs) have been receiving increasing attention in various catalytic fields, and meanwhile, emerging nanocatalytic medicine provides a novel tumor chemotherapy modality without using toxic chemodrugs. The distinct properties of SACs, such as well-defined and precisely located metal centers, identical coordination environment, tailorable composition and structure, and versatile functionality, make them promising candidates for catalytic tumor therapy. Herein, the most recent advances in nanocatalytic tumor therapy by using various types of SACs, especially their remarkable achievements in several nanocatalytic tumor therapy-based modalities, such as chemodynamic therapy by tumor microenvironment-responsive catalytic reactions, photodynamic therapy by photocatalytic reactions, sonodynamic therapy by sonocatalytic reactions, and parallel catalytic therapy by parallel catalytic reactions, are reviewed by focusing on the catalytic nanoplatform construction and catalytic mechanism. A concise but concentrated summary and outlook are provided finally to outline the perspectives and the remaining challenges for the future design and engineering of SACs for tumor therapy.

Primary pancreatic hydatid cyst: a case report and literature review.

BACKGROUND: Hydatid cysts are parasitic zoonoses that often occur in the liver. Pancreatic hydatid cysts are very rare and are usually misdiagnosed as pancreatic cystadenomas. At present, surgical resection combined with albendazole administration is the standard treatment for pancreatic hydatid cysts. However, making accurate preoperative diagnoses and avoiding intraoperative cystic rupture are challenges for surgeons. CASE PRESENTATION: A 28-year-old woman from the pastoral area presented to the surgical office complaining of abdominal pain and new-onset jaundice that began 9 days earlier. An enhanced computed tomography scan demonstrated a 6.0 × 5.3 cm pancreatic head cystic mass that compressed the common bile duct and induced choledochectasia. The preoperative diagnosis was pancreatic head cystadenoma, and laparotomic pancreaticoduodenectomy was initiated successfully. The intra- and postoperative diagnosis was pancreatic hydatid cyst. The patient was discharged uneventfully 7 days after the operation. A 1-year course of albendazole (15 mg/kg/day) was admitted. CONCLUSION: Pancreatic hydatid cysts are rare and often misdiagnosed as other types of cysts. History of living in an area in which the causative organism is endemic and positive anti-echinococcus IgG antibody status could help with the diagnosis. Radical resection combined with oral albendazole administration is the standard treatment for pancreatic hydatid cysts. Avoiding perioperative cystic rupture and abdominal echinococcosis implantation metastasis is crucial for the success of the operation.

Inorganic Nanoshell-Stabilized Liquid Metal for Targeted Photonanomedicine in NIR-II Biowindow.

Gallium and gallium-based alloys, typical types of liquid metals with unique physiochemical properties, are emerging as a next generation of functional materials in versatile biomedical applications. However, the exploration of their biomedical performance is currently insufficient, and their intrinsic low oxidative resistance is a key factor blocking their further clinical translation. Herein, we report on the surface engineering of liquid metal-based nanoplatforms by an inorganic silica nanoshell based on a novel but facile sonochemical synthesis for highly efficient, targeted, and near-infrared (NIR)-triggered photothermal tumor hyperthermia in the NIR-II biowindow. The inorganic silica-shell engineering of liquid metal significantly enhances the photothermal performance of the liquid metal core as reflected by enhanced NIR absorption, improved photothermal stability by oxidation protection, and abundant surface chemistry for surface-targeted engineering to achieve enhanced tumor accumulation. Systematic in vitro cell-level evaluation and in vivo tumor xenograft assessment demonstrate that (Arg-Gly-Asp) RGD-targeted and silica-coated nanoscale liquid metal substantially induces phototriggered cancer-cell death and photothermal tumor eradication, accompanied by high in vivo biocompatibility and easy excretion out of the body. This work provides the first paradigm for surface-inorganic engineering of liquid metal-based nanoplatforms for achieving multiple desirable therapeutic performances, especially for combating cancer.

Coexpression of UCA1 and ITGA2 in pancreatic cancer cells target the expression of miR-107 through focal adhesion pathway.

OBJECTIVES: Abnormal expressions of microRNAs (miRNAs) are demonstrated in pancreatic cancer (PaC), but a major part of the mechanism remains elusive. This study mainly aimed to structure a coexpressed network of long noncoding RNA (lncRNA) and messenger RNA (mRNA) in PaC, as well as to explore their direct targets. METHODS: LncRNA and mRNA microarrays were used to determine the expression profiles in PaC cells. Analysis of Kyoto Encyclopedia of Genes and Genomes pathway was performed to identify pathways associated with differentially expressed mRNAs. Coexpression profiles were identified by constructing differentially expressed lncRNA-mRNA regulatory network and further validated by quantitative real-time polymerase chain reaction assay and western blot assay. The bioinformatics computational method was applied to predict the biological target of lncRNA and mRNA, which was identified by luciferase reporter assay. Migration/invasion ability and apoptosis rate of cells were assessed by transwell assay and flow cytometry assay. RESULTS: It was identified that the level of urothelial cancer associated 1 (UCA1) was increased in PaC cells, and the inhibition of UCA1 suppressed migration and invasion ability of the cancer cells. The luciferase reporter assay recognized that miR-107 was targeted by UCA1, and integrin subunit α 2 (ITGA2) was further targeted by miR-107. This confirmed the prediction of lncRNA-miRNA-mRNA regulation mechanism. In the regulatory pathways, UCA1 and ITGA2 promoted PaC progression via focal adhesion pathway related proteins such as ITGA3, SRC protooncogene/nonreceptor tyrosine kinase, protein tyrosine kinase 2, and AKT serine/threonine kinase 1. CONCLUSION: The study revealed a regulatory network of UCA1-miR-107-ITGA2 and validated UCA1 and ITGA2 as potential prognostic factors for PaC.

An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms.

Breast cancer is becoming a leading death of women all over the world; clinical experiments demonstrate that early detection and accurate diagnosis can increase the potential of treatment. In order to improve the breast cancer diagnosis precision, this paper presents a novel automated segmentation and classification method for mammograms. We conduct the experiment on both DDSM database and MIAS database, firstly extract the region of interests (ROIs) with chain codes and using the rough set (RS) method to enhance the ROIs, secondly segment the mass region from the location ROIs with an improved vector field convolution (VFC) snake and following extract features from the mass region and its surroundings, and then establish features database with 32 dimensions; finally, these features are used as input to several classification techniques. In our work, the random forest is used and compared with support vector machine (SVM), genetic algorithm support vector machine (GA-SVM), particle swarm optimization support vector machine (PSO-SVM), and decision tree. The effectiveness of our method is evaluated by a comprehensive and objective evaluation system; also, Matthew's correlation coefficient (MCC) indicator is used. Among the state-of-the-art classifiers, our method achieves the best performance with best accuracy of 97.73%, and the MCC value reaches 0.8668 and 0.8652 in unique DDSM database and both two databases, respectively. Experimental results prove that the proposed method outperforms the other methods; it could consider applying in CAD systems to assist the physicians for breast cancer diagnosis.

MFMSNet: A Multi-frequency and Multi-scale Interactive CNN-Transformer Hybrid Network for breast ultrasound image segmentation.

Breast tumor segmentation in ultrasound images is fundamental for quantitative analysis and plays a crucial role in the diagnosis and treatment of breast cancer. Recently, existing methods have mainly focused on spatial domain implementations, with less attention to the frequency domain. In this paper, we propose a Multi-frequency and Multi-scale Interactive CNN-Transformer Hybrid Network (MFMSNet). Specifically, we utilize Octave convolutions instead of conventional convolutions to effectively separate high-frequency and low-frequency components while reducing computational complexity. Introducing the Multi-frequency Transformer block (MF-Trans) enables efficient interaction between high-frequency and low-frequency information, thereby capturing long-range dependencies. Additionally, we incorporate Multi-scale interactive fusion module (MSIF) to merge high-frequency feature maps of different sizes, enhancing the emphasis on tumor edges by integrating local contextual information. Experimental results demonstrate the superiority of our MFMSNet over seven state-of-the-art methods on two publicly available breast ultrasound datasets and one thyroid ultrasound dataset. In the evaluation of MFMSNet, tests were conducted on the BUSI, BUI, and DDTI datasets, comprising 130 images (BUSI), 47 images (BUI), and 128 images (DDTI) in the respective test sets. Employing a five-fold cross-validation approach, the obtained dice coefficients are as follows: 83.42 % (BUSI), 90.79 % (BUI), and 79.96 % (DDTI). The code is available at https://github.com/wrc990616/MFMSNet.

Impact of the thermo-alkaline pretreatment on the anaerobic digestion of poly(butylene adipate-co-terephthalate) (PBAT) and poly(lactic acid) (PLA) blended plastics.

Poly(butylene adipate-co-terephthalate) (PBAT) is a biodegradable plastic that is difficult to degrade under both mesophilic and thermophilic anaerobic conditions. In this study, the impact of the thermo-alkaline pretreatment (48 h, 70 °C, 1 % w/v NaOH) on the anaerobic degradation (AD) of PBAT, poly(lactic acid) (PLA) and PBAT/PLA blended plastics was investigated. Under mesophilic conditions, pretreatment only improved the methane yield of PBAT/PLA/starch plastic (100 days, 51 and 34 NmL/g VSadd for the treated and original plastics, respectively). Under thermophilic conditions, the pretreatment increased the methanogenic rate of PLA, PBAT and PBAT/PLA/starch plastic at the beginning stage (22 days, 35 and 79 NmL/g VSadd for original and treated PBAT, respectively), but did not change the methane yield at the end of the incubation (100 days, 91 NmL/g VSadd for original and treated PBAT). The reduction in the molecular weight and the formation of pore structures on the plastic surface accelerated the utilization of plastics by microorganisms. Furthermore, the pretreated plastics tend to form microplastics (MPs) with size predominantly below 500 µm (>90 %). The numbers of MPs dynamically changed with the degradation time. Several genera of bacteria showed specific degradation of biodegradable plastics under thermophilic conditions, including Desulfitibacter, Coprothermobacter, Tepidimicrobium, c_ D8A-2 and Thermacetogenium. The results suggest that more attention should be paid to the problem of MPs arising from the thermo-alkaline pretreatment.

Nitrogen, sulfur co-coordinated iron single-atom catalysts with the optimized electronic structure for highly efficient oxygen reduction in Zn-air battery and fuel cell.

Atomically dispersed iron-nitrogen-carbon (FesbndNsbndC) materials have been considered ideal catalysts for the oxygen reduction. Unfortunately, designing and adjusting the electronic structure of single-atom Fe sites to boost the kinetics and activity still faces grand challenges. In this work, the coordination environment engineering is developed to synthesize the FeSA/NSC catalyst with the tailored N, S co-coordinated Fe atomic site (Fe-N3S site). The structural characterizations and theoretical calculations demonstrate that the incorporation of sulfur can optimize the charge distribution of Fe atoms to weaken the adsorption of OH* and facilitate the desorption of OH*, thus leading to enhanced kinetics process and intrinsic activity. As a result, the S-modified FeSA/NSC exhibits outstanding catalytic activity with the half-wave potentials (E1/2) of 0.915 V and 0.797 V, as well as good stability, in alkaline and acidic electrolytes, respectively. Impressively, the excellent performance of FeSA/NSC is further confirmed in Zn-air batteries (ZABs) and fuel cells, with high peak power densities (146 mW cm-2 and 0.259 W cm-2).

Deep learning-based and BI-RADS guided radiomics model for automatic tumor-infiltrating lymphocytes evaluation in breast cancer.

OBJECTIVES: To investigate an interpretable radiomics model consistent with clinical decision-making process and realize automatic prediction of tumor-infiltrating lymphocytes (TILs) levels in breast cancer (BC) from ultrasound (US) images. METHODS: A total of 378 patients with invasive BC confirmed by pathological results were retrospectively enrolled in this study. Radiomics features were extracted guided by the BI-RADS lexicon from the regions of interest(ROIs) segmented with deep learning models. After features selected using the least absolute shrinkage and selection operator(LASSO) regression, four machine learning classifiers were used to establish the radiomics signature(Rad-score). Then, the integrated model was developed on the basis of the best Rad-score incorporating the independent clinical factors for TILs levels prediction. RESULTS: Tumors were segmented using the deep learning models with accuracy of 97.2%, sensitivity of 93.4%, specificity of 98.1%, and the posterior areas were also obtained. Eighteen morphology and texture related features were extracted from the ROIs and fourteen features were selected to construct the Rad-score models. Combined with independent clinical characteristics, the integrated model achieved an area under the curve (AUC) of 0.889(95% CI,0.739,0.990) in the validation cohort and outperformed the traditional radiomics model with AUC of 0.756(0.649-0862) depended on hundreds of feature items. CONCLUSIONS: This study established a promising model for TILs levels prediction with numerable interpretable features and showed great potential to help decision-making and clinical applications. ADVANCES IN KNOWLEDGE: Imaging-based biomarkers has provides non-invasive ways for TILs levels evaluation in BC. Our model combining the BI-RADS guided radiomics features and clinical data outperformed the traditional radiomics approaches.

Met-Exo attenuates mitochondrial dysfunction after hepatic ischemia-reperfusion injury in rats by modulating AMPK/SIRT1 signaling pathway.

Hepatic ischemia-reperfusion injury (IRI) results in significant postoperative liver dysfunction, and the intricate mechanism of IRI poses challenges in developing effective therapeutic drugs. Mitigating the damage caused by hepatic IRI and promoting the repair of postoperative liver injury have become focal points in recent years, holding crucial clinical significance. Adipose mesenchymal stem cell derived exosomes (ADSCs-Exo) and metformin (Met) can play a mitochondrial protective role in the treatment of hepatic IRI, but whether there is a synergistic mechanism for their intervention is not yet known. Combining the unique advantages of exosomes as drug carriers, the aim of this study was to investigate the protective effects and mechanisms of the constructed Met and ADSCs-Exo complex (Met-Exo) on the liver IRI combined with partial resection injury in rat and hypoxic reoxygenation injury of rat primary hepatocytes (HCs). In this study, firstly, we detected that mitochondrial morphology and function were severely affected in hepatic tissues after hepatic IRI combined with partial resection, and then verified by in vitro experiments that Met-Exo could promote mitochondrial biosynthesis and fusion-associated protein expression and inhibit mitochondrial fission-related protein expression by modulating the AMPK/SIRT1 signalling pathway. This indicates that ADSCs-Exo can not only play a targeting role as a drug carrier but also has a great potential to act as a vehicle to act synergistically with drugs in the treatment of tissue and organ damage, which provides a new therapeutic strategy and experimental basis for the treatment of liver injury in medical science and clinical veterinary.

Ginkgo biloba Sex Identification Methods Using Hyperspectral Imaging and Machine Learning.

Ginkgo biloba L. is a rare dioecious species that is valued for its diverse applications and is cultivated globally. This study aimed to develop a rapid and effective method for determining the sex of a Ginkgo biloba. Green and yellow leaves representing annual growth stages were scanned with a hyperspectral imager, and classification models for RGB images, spectral features, and a fusion of spectral and image features were established. Initially, a ResNet101 model classified the RGB dataset using the proportional scaling-background expansion preprocessing method, achieving an accuracy of 90.27%. Further, machine learning algorithms like support vector machine (SVM), linear discriminant analysis (LDA), and subspace discriminant analysis (SDA) were applied. Optimal results were achieved with SVM and SDA in the green leaf stage and LDA in the yellow leaf stage, with prediction accuracies of 87.35% and 98.85%, respectively. To fully utilize the optimal model, a two-stage Period-Predetermined (PP) method was proposed, and a fusion dataset was built using the spectral and image features. The overall accuracy for the prediction set was as high as 96.30%. This is the first study to establish a standard technique framework for Ginkgo sex classification using hyperspectral imaging, offering an efficient tool for industrial and ecological applications and the potential for classifying other dioecious plants.

Supramolecular assemblies of Cu(II) with a tetraphenylethene-imidazole ligand for tuning photocatalytic CO2 reduction.

Cu(II) supramolecular assemblies [Cu2(tipe)2(H2O)2](NO3)4·2.5H2O (CuN4) and [Cu2Cl4(tipe)(CH3CN)]·H2O (CuN2Cl2) (tipe = 1,1,2,2-tetrakis(4-(imidazole-1-yl)phenyl)ethene) were synthesized and utilized for photocatalytic CO2 reduction. CuN4 exhibits CO production of up to 891 µmol gcat-1 with a selectivity of 79.9%, while CuN2Cl2 gives low CO production of 206 µmol gcat-1 but with a high selectivity of >99.9% in 5 h. The experimental and DFT calculation results indicate that the coordination environment and non-covalent interactions within the assemblies have a great impact on the photocatalytic CO2 reduction behavior. This work provides useful insights on Cu(II) assembly catalyzed CO2 photoreduction.