Study on the combination of virtual machine tools and wearable vibration devices for operators experiencing cutting forces in the milling process.

The primary goal of this study is to develop a wearable system for providing CNC machine operators with visual and tactile perception of triaxial cutting forces, thereby assisting operators in industrial environments to enhance work efficiency and prevent mechanical failures. To achieve this goal, we successfully integrated a virtual machining tool simulator with the remote-control wearable system (RCWS). Using the 'King Path' milling parameters, we employed the simulation software developed by the AIM-HI team to calculate static and dynamic cutting forces, converting this data into vibrational commands for the RCWS to generate corresponding tactile feedback. Furthermore, we conducted extensive experiments, testing various data conversion methods, including three sampling techniques and two data compression strategies, aiming to provide accurate tactile feedback related to cutting forces under different operating conditions.

Activation of Wnt signaling mitigates blood-brain barrier disruption by inhibiting vesicular transcytosis after traumatic brain injury in mice.

Elevated transport of Caveolin-1 (CAV-1) vesicles within vascular endothelial cells constitutes a significant secondary pathogenic event contributing to the compromise of the blood-brain barrier (BBB) post-traumatic brain injury (TBI). While Wnt/ß-catenin signaling is recognized for its critical involvement in angiogenesis and the maintenance of BBB integrity, its influence on vascular endothelial transcytosis in the aftermath of TBI is not well-defined. This study aims to elucidate the impact of Wnt/ß-catenin signaling on cerebrovascular vesicular transcytosis following TBI. In this experiment, adult male wild-type (WT) C57BL/6 mice underwent various interventions. TBI was induced utilizing the controlled cortical impact technique. Post-TBI, mice were administered either an inhibitor or an agonist of Wnt signaling via intraperitoneal injection. Recombinant adeno-associated virus (rAAV) was administered intracerebroventricularly to modulate the expression of the CAV-1 inhibitory protein, Major facilitator superfamily domain-containing 2a (Mfsd2a). This research utilized Evans blue assay, Western blot analysis, immunofluorescence, transmission electron microscopy, and neurobehavioral assessments. Post-TBI observations revealed substantial increases in macromolecule (Evans blue and albumin) leakage, CAV-1 transport vesicle count, astrocyte end-feet edema, and augmented aquaporin-4 (AQP4) expression, culminating in BBB disruption. The findings indicate that Wnt signaling pathway inhibition escalates CAV-1 transport vesicle activity and aggravates BBB compromise. Conversely, activating this pathway could alleviate BBB damage by curtailing CAV-1 vesicle presence. Post-TBI, there is a diminution in Mfsd2a expression, which is directly influenced by the modulation of WNT signals. Employing a viral approach to regulate Mfsd2a, we established that its down-regulation undermines the protective benefits derived from reducing CAV-1 transport vesicles through WNT signal enhancement. Moreover, we verified that the WNT signaling agonist LiCl notably ameliorates neurological deficits following TBI in mice. Collectively, our data imply that Wnt/ß-catenin signaling presents a potential therapeutic target for safeguarding against BBB damage and enhancing neurological function after TBI.

Novel Pyrazole-4-Carboxamide Derivatives Containing Oxime Ether Group as Potential SDHIs to Control Rhizoctonia solani.

In the search for novel succinate dehydrogenase inhibitor (SDHI) fungicides to control Rhizoctonia solani, thirty-five novel pyrazole-4-carboxamides bearing either an oxime ether or an oxime ester group were designed and prepared based on the strategy of molecular hybridization, and their antifungal activities against five plant pathogenic fungi were also investigated. The results indicated that the majority of the compounds containing oxime ether demonstrated outstanding in vitro antifungal activity against R. solani, and some compounds also displayed pronounced antifungal activities against Sclerotinia sclerotiorum and Botrytis cinerea. Particularly, compound 5e exhibited the most promising antifungal activity against R. solani with an EC50 value of 0.039 µg/mL, which was about 20-fold better than that of boscalid (EC50 = 0.799 µg/mL) and 4-fold more potent than fluxapyroxad (EC50 = 0.131 µg/mL). Moreover, the results of the detached leaf assay showed that compound 5e could suppress the growth of R. solani in rice leaves with significant protective efficacies (86.8%) at 100 µg/mL, superior to boscalid (68.1%) and fluxapyroxad (80.6%), indicating promising application prospects. In addition, the succinate dehydrogenase (SDH) enzymatic inhibition assay revealed that compound 5e generated remarkable SDH inhibition (IC50 = 2.04 µM), which was obviously more potent than those of boscalid (IC50 = 7.92 µM) and fluxapyroxad (IC50 = 6.15 µM). Furthermore, SEM analysis showed that compound 5e caused a remarkable disruption to the characteristic structure and morphology of R. solani hyphae, resulting in significant damage. The molecular docking analysis demonstrated that compound 5e could fit into the identical binding pocket of SDH through hydrogen bond interactions as well as fluxapyroxad, indicating that they had a similar antifungal mechanism. The density functional theory and electrostatic potential calculations provided useful information regarding electron distribution and electron transfer, which contributed to understanding the structural features and antifungal mechanism of the lead compound. These findings suggested that compound 5e could be a promising candidate for SDHI fungicides to control R. solani, warranting further investigation.

STUB1 promotes the degradation of HSPB1 and induces ferroptosis in lung cancer cells.

Lung cancer is a common malignancy characterized by ferroptosis, an iron-dependent form of cell death caused by excessive lipid peroxidation. The disruption of the ubiquitination system plays a crucial role in tumor development and spread. In recent years, there has been increasing interest in utilizing ferroptosis for lung cancer treatment; however, the precise mechanism of how ubiquitination modulates ferroptosis remains unclear. We used databases to analyze STUB1 expression patterns in lung cancer tissues compared to normal tissues and performed immunohistochemistry. The functional role of STUB1 was investigated through gain-of-function and loss-of-function experiments both in vitro and in vivo. Malondialdehyde levels, Fe2+ content, and cell viability assays were employed to evaluate ferroptosis status. Downstream targets of STUB1 were identified through screening and validated using immunoprecipitation and ubiquitination assays. Our findings demonstrate that STUB1 is downregulated in lung cancer cells and functions as an inhibitor of their growth and metastasis both in vitro and in vivo while promoting ferroptosis. Mechanistically, STUB1 induces ferroptosis through E3 ligase-dependent degradation of the ferroptosis suppressor HSPB1. Furthermore, our study elucidated the specific types and sites of modification on HSPB1 mediated by STUB1. This research establishes STUB1 as a tumor suppressor influencing proliferation of lung cancer cells as well as the epithelial-mesenchymal transition process associated with it. Importantly, our work highlights the role of STUB1 in ubiquitination-mediated degradation of HSPB1, providing insights for potential treatments for lung cancer.

A novel approach has been developed to produce pure plant-based gel soy yogurt by combining soy proteins (7S/11S), high pressure homogenization, and glycation reaction.

This research sought to examine how the physicochemical characteristics of soy globulins and different processing techniques influence the gel properties of soy yogurt. The goal was to improve these gel properties and rectify any texture issues in soy yogurt, ultimately aiming to produce premium-quality plant-based soy yogurt. In this research study, the investigation focused on examining the impact of 7S/11S, homogenization pressure, and glycation modified with glucose on the gel properties of soy yogurt. A plant-based soy yogurt with superior gel and texture properties was successfully developed using a 7S/11S globulin-glucose conjugate at a 1:3 ratio and a homogenization pressure of 110 MPa. Compared to soy yogurt supplemented with pectin or gelatin, this yogurt demonstrated enhanced characteristics. These findings provide valuable insights into advancing plant protein gels and serve as a reference for cultivating new soybean varieties by soybean breeding experts.

MicroRNA-7 attenuates secondary brain injury following experimental intracerebral hemorrhage via inhibition of NLRP3.

BACKGROUND AND PURPOSE: The pathophysiological mechanisms underlying brain injury resulting from intracerebral hemorrhage (ICH) remain incompletely elucidated, and efficacious therapeutic interventions to enhance the prognosis of ICH patients are currently lacking. Previous research indicates that MicroRNA-7 (miR-7) can suppress the expression of Nod-like receptor protein 3 (NLRP3), thereby modulating neuroinflammation in Parkinson's disease pathogenesis. However, the potential regulatory effects miR-7 on NLRP3 inflammasome after ICH are yet to be established. This study aims to ascertain whether miR-7 mitigates secondary brain injury following experimental ICH by inhibiting NLRP3 and to investigate the underlying mechanisms. METHODS: An ICH model was established by stereotaxically injecting 100 µL of autologous blood into the right basal ganglia of Sprague-Dawley (SD) rats. Subsequently, these rats were allocated into three groups: sham, ICH + Vehicle, and ICH + miR-7, each comprising 18 animals. Twelve hours post-modeling, rats received intraventricular injections of 10 µL physiological saline, 10 µL phosphate, and 10 µL phosphate-buffered saline solution containing 0.5 nmol of miR-7 mimics, respectively. Neurological function was assessed on day three post-modeling, followed by euthanasia for brain tissue collection. Brain water content was determined using the dry-wet weight method. The expression of inflammatory cytokines in cerebral tissues surrounding the hematoma was analyzed through immunohistochemistry and Western blot assays. These cytokines were re-evaluated using Reverse Transcription-Polymerase Chain Reaction (RT-PCR). Moreover, bioinformatics tools were employed to predict miR-7's binding to NLRP3. A wild-type luciferase reporter gene vector and a corresponding mutant vector were constructed, followed by transfection of miR-7 mimics into HEK293T cells to assess luciferase activity. RESULTS: Our study demonstrates that the administration of miR-7 mimics markedly reduced neurological function scores and attenuated brain edema in rats following ICH. A significant upregulation of NLRP3 expression in microglia/macrophage adjacent to the hematoma was observed, substantially reduced after the treatment with miR-7 mimics. Furthermore, this intervention ameliorated neurodegenerative changes and effectively decreased the protein and mRNA levels of pro-inflammatory cytokines, namely TNF-α, IL-1ß, IL-6, and Caspase1, in the cerebral tissues proximate to the hematomas. In addition, miR-7 mimics distinctly inhibited the luciferase activity associated with the wild-type reporter gene, an effect not mirrored in its mutant variant. CONCLUSIONS: The miR-7 suppressed NLRP3 expression in microglia/macrophage to reduce the production of inflammatory cytokines, leading to conducting certain neuroprotection post-ICH in rats.

Gallic Acid Alleviates Cognitive Impairment by Promoting Neurogenesis via the GSK3ß-Nrf2 Signaling Pathway in an APP/PS1 Mouse Model.

Background: Neuronal loss occurs early and is recognized as a hallmark of Alzheimer's disease (AD). Promoting neurogenesis is an effective treatment strategy for neurodegenerative diseases. Traditional Chinese herbal medicines serve as a rich pharmaceutical source for modulating hippocampal neurogenesis. Objective: Gallic acid (GA), a phenolic acid extracted from herbs, possesses anti-inflammatory and antioxidant properties. Therefore, we aimed to explore whether GA can promote neurogenesis and alleviate AD symptoms. Methods: Memory in mice was assessed using the Morris water maze, and protein levels were examined via western blotting and immunohistochemistry. GA's binding site in the promoter region of transcription regulator nuclear factor erythroid 2-related factor 2 (Nrf2) was calculated using AutoDock Vina and confirmed by a dual luciferase reporter assay. Results: We found that GA improved spatial memory by promoting neurogenesis in the hippocampal dentate gyrus zone. It also improved synaptic plasticity, reduced tau phosphorylation and amyloid-ß concentration, and increased levels of synaptic proteins in APP/PS1 mice. Furthermore, GA inhibited the activity of glycogen synthase kinase-3ß (GSK-3ß). Bioinformatics tools revealed that GA interacts with several amino acid sites on GSK-3ß. Overexpression of GSK-3ß was observed to block the protective effects of GA against AD-like symptoms, while GA promoted neurogenesis via the GSK-3ß-Nrf2 signaling pathway in APP/PS1 mice. Conclusions: Based on our collective findings, we hypothesize that GA is a potential pharmaceutical agent for alleviating the pathological symptoms of AD.

Targeted Delivery of Gemcitabine for Precision Therapy of Cholangiocarcinoma Using Hyaluronic Acid-Modified Metal-Organic Framework Nanoparticles.

Chemotherapy is widely recognized as an important approach for the treatment of cholangiocarcinoma. Gemcitabine (GEM) has been considered a first-line drug for treating cholangiocarcinoma due to its ability to effectively inhibit the proliferation, migration, and invasion of liver cancer cells. However, the systemic toxicity, premature degradation, and lack of tumor-targeting properties of GEM limit its application in cholangiocarcinoma chemotherapy. Additionally, precise targeted delivery of GEM is necessary to align with the current concept of precision medicine. In this study, considering the overexpression of hyaluronic acid (HA) receptors (CD44) on cholangiocarcinoma cells, we designed GEM@ZIF-67-HA NPs by loading GEM onto ZIF-67 and modifying its surface with HA. The structure, size, morphology, and elemental composition of GEM@ZIF-67-HA were analyzed using transmission electron microscopy, Fourier transform infrared spectroscopy, ζ-potential, and isothermal adsorption. Cell toxicity experiments demonstrated that GEM@ZIF-67-HA NPs not only reduced cytotoxicity to normal cells but also effectively inhibited the viability of two types of cholangiocarcinoma tumor cells. In a subcutaneous tumor model, GEM@ZIF-67-HA significantly suppressed tumor growth. The tumor-targeting and controllable properties of GEM@ZIF-67-HA NPs hold promise for further development in the strategy of precise targeted therapy for cholangiocarcinoma.

Behavioral responses of cave-roosting bats to artificial light of different spectra and intensities: Implications for lighting management strategy.

Artificial light at night has become an emerging environmental pollutant, posing a serious threat to biodiversity. Cave-roosting animals are vulnerable to light pollution due to long-term adaptation to nocturnal niches, and the problem is especially severe in the context of cave tourism and limestone mining. Mitigating the adverse impacts of artificial light on cave-dwelling animals presents a challenge. This study aimed to assess the relative contributions of spectral parameters and light intensity to the emergence behavior of nine cave-roosting bat species: Rhinolophus macrotis, Rhinolophus pearsonii, Rhinolophus rex, Rhinolophus pusillus, Rhinolophus siamensis, Rhinolophus sinicus, Hipposideros armiger, Myotis davidii, and Miniopterus fuliginosus. We manipulated light spectra and intensities through light-emitting diode (LED) lighting and gel filters at the entrance of bat roost. We monitored nightly passes per species to quantify bat emergence under the dark control and ten lighting conditions (blue, green, yellow, red, and white light at high and low intensities) using ultrasonic recording. Our analyses showed that the number of bat passes tended to be reduced in the presence of white, green, and yellow light, independent of light intensity. In contrast, the number of bat passes showed no pronounced differences under the dark control, blue light, and red light. The number of bat passes was primarily affected by LED light's blue component, red component, peak wavelength, and half-width instead of light intensity. These results demonstrate that spectral parameters of LED light can significantly affect emergence behavior of cave-dwelling bats. Our findings highlight the importance of manipulating light colors to reduce the negative impacts of light pollution on cave-roosting bats as a function of their spectral sensitivity. We recommend the use of gel filters to manage existing artificial lighting systems at the entrance of bat-inhabited caves.

Using deep learning models in magnetic resonance cholangiopancreatography images to diagnose common bile duct stones.

BACKGROUNDS AND AIMS: Magnetic resonance cholangiopancreatography (MRCP) plays a significant role in diagnosing common bile duct stones (CBDS). Currently, there are no studies to detect CBDS by using the deep learning (DL) model in MRCP. This study aimed to use the DL model You Only Look Once version 5 (YOLOv5) to diagnose CBDS in MRCP images and verify its validity compared to the accuracy of radiologists. METHODS: By collecting the thick-slab MRCP images of patients diagnosed with CBDS, 4 submodels of YOLOv5 were used to train and validate the performance. Precision, recall rate, and mean average precision (mAP) were used to evaluate model performance. Analyze possible reasons that may affect detection accuracy by validating MRCP images in 63 CBDS patients and comparing them with radiologist detection accuracy. Calculate the correctness of YOLOv5 for detecting one CBDS and multiple CBDS separately. RESULTS: The precision of YOLOv5l (0.970) was higher than that of YOLOv5x (0.909), YOLOv5m (0.874), and YOLOv5s (0.939). The mAP did not differ significantly between the 4 submodels, with the following results: YOLOv5l (0.942), YOLOv5x (0.947), YOLO5s (0.927), and YOLOv5m (0.946). However, in terms of training time, YOLOv5s was the fastest (4.8 h), detecting CBDS in only 7.2 milliseconds per image. In 63 patients the YOLOv5l model detected CBDS with an accuracy of 90.5% compared to 92.1% for radiologists, analyzing the difference between the positive group successfully identified and the unidentified negative group not. The incorporated variables include common bile duct diameter > 1 cm (p = .560), combined gallbladder stones (p = .706), maximum stone diameter (p = .057), combined cholangitis (p = .846), and combined pancreatitis (p = .656), and the number of CBDS (p = .415). When only one CBDS was present, the accuracy rate reached 94%. When multiple CBDSs were present, the recognition rate dropped to 70%. CONCLUSION: YOLOv5l is the model with the best results and is almost as accurate as the radiologist's detection of CBDS and is also capable of detecting the number of CBDS. Although the accuracy of the test gradually decreases as the number of stones increases, it can still be useful for the clinician's initial diagnosis.

Artificial light affects foraging behavior of a synanthropic bat.

Artificial light at night has been considered an emerging threat to global biodiversity. However, the impacts of artificial light on foraging behavior in most wild animals remain largely unclear. Here, we aimed to assess whether artificial light affects foraging behavior in Asian parti-colored bats (Vespertilio sinensis). We manipulated the spectra of light-emitting diode (LED) lighting in a laboratory. Using video and audio recording, we monitored foraging onset, total foraging time, food consumption, freezing behavior (temporary cessation of body movement), and echolocation vocalizations in triads of bats under each lighting condition. Analyses showed that the foraging activities of experimental bats were reduced under LED light. Green, yellow, and red light had greater negative effects on bats' foraging onset, total foraging time, and food consumption than white and blue light. LED light of different spectra induced increased freezing time and echolocation vocalizations in captive bats, except for the white light. The peak wavelength of light emission correlated positively with freezing time, estimated echolocation pulse rate (the number of echolocation pulses per minute), and foraging onset, but negatively with total foraging time and food consumption. These results demonstrate that artificial light disturbs foraging behavior in Asian parti-colored bats. Our findings have implications for understanding the influencing mechanism of light pollution on bat foraging.

Cuproptosis and cuproptosis-related genes: Emerging potential therapeutic targets in breast cancer.

Breast cancer is one of the most common malignant tumors in women worldwide, and thus, it is important to enhance its treatment efficacy [1]. Copper has emerged as a critical trace element that affects various intracellular signaling pathways, gene expression, and biological metabolic processes [2], thereby playing a crucial role in the pathogenesis of breast cancer. Recent studies have identified cuproptosis, a newly discovered type of cell death, as an emerging therapeutic target for breast cancer treatment, thereby offering new hope for breast cancer patients. Tsvetkov's research has elucidated the mechanism of cuproptosis and uncovered the critical genes involved in its regulation [3]. Manipulating the expression of these genes could potentially serve as a promising therapeutic strategy for breast cancer treatment. Additionally, using copper ionophores and copper complexes combined with nanomaterials to induce cuproptosis may provide a potential approach to eliminating drug-resistant breast cancer cells, thus improving the therapeutic efficacy of chemotherapy, radiotherapy, and immunotherapy and eventually eradicating breast tumors. This review aims to highlight the practical significance of cuproptosis-related genes and the induction of cuproptosis in the clinical diagnosis and treatment of breast cancer. We examine the potential of cuproptosis as a novel therapeutic target for breast cancer, and we explore the present challenges and limitations of this approach. Our objective is to provide innovative ideas and references for the development of breast cancer treatment strategies based on cuproptosis.

Research progress of neonatal hypoxic-ischemic encephalopathy in nonhuman primate models.

Neonatal hypoxic-ischemic encephalopathy (HIE) is one of the important complications of neonatal asphyxia, which not only leads to neurological disability but also seriously threatens the life of neonates. Over the years, animal models of HIE have been a research hotspot to find ways to cope with HIE and thereby reduce the risk of neonatal death or disability in moderate-to-severe HIE. By reviewing the literature related to HIE over the years, it was found that nonhuman primates share a high degree of homology with human gross neural anatomy. The basic data on nonhuman primates are not yet complete, so it is urgent to mine and develop new nonhuman primate model data. In recent years, the research on nonhuman primate HIE models has been gradually enriched and the content is more novel. Therefore, the purpose of this review is to further summarize the methods for establishing the nonhuman primate HIE model and to better elucidate the relevance of the nonhuman primate model to humans by observing the behavioral manifestations, neuropathology, and a series of biomarkers of HIE in primates HIE. Finally, the most popular and desirable treatments studied in nonhuman primate models in the past 5 years are summarized.

Aphid cluster recognition and detection in the wild using deep learning models.

Aphid infestation poses a significant threat to crop production, rural communities, and global food security. While chemical pest control is crucial for maximizing yields, applying chemicals across entire fields is both environmentally unsustainable and costly. Hence, precise localization and management of aphids are essential for targeted pesticide application. The paper primarily focuses on using deep learning models for detecting aphid clusters. We propose a novel approach for estimating infection levels by detecting aphid clusters. To facilitate this research, we have captured a large-scale dataset from sorghum fields, manually selected 5447 images containing aphids, and annotated each individual aphid cluster within these images. To facilitate the use of machine learning models, we further process the images by cropping them into patches, resulting in a labeled dataset comprising 151,380 image patches. Then, we implemented and compared the performance of four state-of-the-art object detection models (VFNet, GFLV2, PAA, and ATSS) on the aphid dataset. Extensive experimental results show that all models yield stable similar performance in terms of average precision and recall. We then propose to merge close neighboring clusters and remove tiny clusters caused by cropping, and the performance is further boosted by around 17%. The study demonstrates the feasibility of automatically detecting and managing insects using machine learning models. The labeled dataset will be made openly available to the research community.

Effects of folic acid and folic acid plus zinc supplements on the sperm characteristics and pregnancy outcomes of infertile men: A systematic review and meta-analysis.

Background: Folic acid and zinc supplements have been used to treat male infertility, but their efficacy is still debated. Objective: To systematically evaluate the effects of folic acid and folic acid plus zinc supplements on sperm characteristics and pregnancy outcomes of infertile men. Methods: An online systematic search was performed using PubMed, Cochrane Library, and EMBASE databases from inception to August 1, 2022. The goal was to identify randomized controlled trials (RCTs) that used folic acid or folic acid plus zinc to improve sperm characteristics of infertile men. Data were extracted by two investigators who independently screened the literature and assessed for quality according to the criteria. The meta-analysis was performed using RevMan 5.4 software. Results: A total of 8 RCT studies involving 2168 patients were included. The results showed that compared with the controls, folic acid significantly increased sperm motility (MD, 3.63; 95% CI, -1.22 to 6.05; P = 0.003), but did not affect the sperm concentration (MD, 2.53; 95% CI, -1.68 to 6.73; P = 0.24) and sperm morphology (MD, -0.02; 95% CI, -0.29 to 0.24; P = 0.86) in infertile men. Folic acid plus zinc did not affect sperm concentration (MD, 1.87; 95% CI, -1.39 to 5.13; P = 0.26), motility (MD, 1.67; 95% CI, -1.29 to 4.63; P = 0.27), and morphology (MD, -0.05; 95% CI, -0.27 to 0.18; P = 0.69) in infertile men. Secondary results showed that compared with a placebo, folic acid alone had a higher rate of pregnancy in transferred embryos (35.6% vs. 20.4%, P = 0.082), but the difference was not significant. Folic acid plus zinc did not affect pregnancy outcomes. Conclusions: Based on the meta-analysis, no significant improvements in sperm characteristics with folic acid plus zinc supplements were seen. However, folic acid alone has demonstrated the potential to improve sperm motility and in vitro fertilization-intracytoplasmic sperm injection (IVF-ICSI) outcomes. This indicates that folic acid supplements alone may be a viable treatment option for male infertility.

V-shaped chiral hosts based on π-extended hematoxylin.

Hematoxylin has a V-shaped chiral geometry, but its potential in chiroptical self-assembled materials is underdeveloped. Herein, three novel V-shaped chiral hematoxylin derivatives were synthesized, and they showed extended skeletons as well as photophysical and chiroptical behaviors. Moreover, their host-guest interactions with C60 were investigated. Our findings could aid in the design and synthesis of novel chiral host molecules from natural products.

Design, Synthesis, and Antifungal Activities of Novel Carboxamides Derivatives Bearing a Chalcone Scaffold as Potential SDHIs.

In search for SDHIs fungicides, twenty-five novel carboxamides containing a chalcone scaffold were designed, synthesized, and evaluated for antifungal activities against five pathogenic fungi. The results showed that compound 5 k exhibited outstanding antifungal activity against R. solani with an EC50 value of 0.20 µg/mL, which was much better than that of commercial SDHIs Boscalid (EC50 =0.74 µg/mL). Moreover, compound 5 k also displayed promising antifungal activities against S. sclerotiorum, B. cinerea, and A. alternate (IC50 =2.53-4.06 µg/mL), indicating that 5 k had broad-spectrum antifungal activity. Additionally, in vivo antifungal activities results showed that 5 k could significantly inhibit the growth of R. solani in rice leaves with good protective efficacy (57.78 %) and curative efficacy (58.45 %) at 100 µg/mL, both of which were much better than those of Boscalid, indicating a promising application prospect. Moreover, SEM analysis showed that compound 5 k could remarkably disrupt the typical structure and morphology of R. solani hyphae. Further SDH enzyme inhibition assay and molecular docking study revealed that lead compound 5 k had a similar mechanism of action as commercial SDHI Boscalid. These results indicated that compound 5 k showed potential as a SDHIs fungicide and deserved further investigation.

Design, Synthesis, and Antifungal Activities of Novel Pyrazole-4-carboxamide Derivatives Containing an Ether Group as Potential Succinate Dehydrogenase Inhibitors.

A series of novel pyrazole-4-carboxamides bearing an ether group were designed and synthesized on the basis of the structure of commercial succinate dehydrogenase inhibitor (SDHI) fungicide flubeneteram via scaffold hopping and evaluated for their antifungal activities against five fungi. The bioassay results showed that most of the target compounds exhibited excellent in vitro antifungal activity against Rhizoctonia solani and some compounds exerted remarkable antifungal activities against Sclerotinia sclerotiorum, Botrytis cinerea, Fusarium graminearum, and Alternaria alternate. Particularly, compounds 7d and 12b displayed outstanding antifungal activity against R. solani, with an EC50 value of 0.046 µg/mL, far superior to that of boscalid (EC50 = 0.741 µg/mL) and fluxapyroxad (EC50 = 0.103 µg/mL). Meanwhile, compound 12b also presented a broader fungicidal spectrum than other compounds. Moreover, in vivo anti-R. solani results showed that compounds 7d and 12b could significantly inhibit the growth of R. solani in rice leaves with excellent protective and curative efficacies. In addition, the results of the succinate dehydrogenase (SDH) enzymatic inhibition assay showed that compound 7d generated significant SDH inhibition, with an IC50 value of 3.293 µM, which was about 2 times better than that of boscalid (IC50 = 7.507 µM) and fluxapyroxad (IC50 = 5.991 µM). Furthermore, scanning electron microscopy (SEM) analysis indicated that compounds 7d and 12b significantly destroyed the typical structure and morphology of R. solani hyphae. The molecular docking study revealed that compounds 7d and 12b could embed into the binding pocket of SDH and form hydrogen bond interactions with TRP173 and TRY58 at the activity site of SDH, which was in line with fluxapyroxad, indicating that they had a similar mechanism of action. These results demonstrated that compounds 7d and 12b could be promising candidates of SDHI fungicides, which deserved further investigation.

Gender, Smoking History, and Age Prediction from Laryngeal Images.

Flexible laryngoscopy is commonly performed by otolaryngologists to detect laryngeal diseases and to recognize potentially malignant lesions. Recently, researchers have introduced machine learning techniques to facilitate automated diagnosis using laryngeal images and achieved promising results. The diagnostic performance can be improved when patients' demographic information is incorporated into models. However, the manual entry of patient data is time-consuming for clinicians. In this study, we made the first endeavor to employ deep learning models to predict patient demographic information to improve the detector model's performance. The overall accuracy for gender, smoking history, and age was 85.5%, 65.2%, and 75.9%, respectively. We also created a new laryngoscopic image set for the machine learning study and benchmarked the performance of eight classical deep learning models based on CNNs and Transformers. The results can be integrated into current learning models to improve their performance by incorporating the patient's demographic information.