Portable multimodal platform with carbon nano-onions as colorimetric and fluorescent signal output for trypsin detection.

Multimodal biosensors with independent signaling pathways can self-calibrate and improve the reliability of disease biomarker detection. Herein, a colorimetric-fluorescent dual-mode paper-based biosensor with PAN/Fe(III)-CNOs (FPCs) as core components has been developed, which information is recognized by smartphone and naked eye. Using 1-(2-pyridylazo)-2-naphthol (PAN) as a mediator, Fe(III) is enriched on the surface of carbon nano-onions (CNOs), endowing FPCs with excellent mimetic enzyme activity and photothermal conversion ability, which allows it to output amplified colorimetric signals under laser irradiation. In addition, the complexation of PAN with Fe(III) broadens its absorption spectrum, which makes FPCs more suitable to be energy acceptors to quench fluorescence of polymer dots (Pdots), resulting in the changes of output fluorescent signal. Based on the above design, a portable colorimetric-fluorescent dual-mode biosensor is proposed for trypsin detection with Pdots as fluorescence sources and FPCs as fluorescence quenchers and nanoenzymes. This work provides a convenient way for constructing portable visual multimodal biosensors, which is expected to applied in various disease diagnosis.

Anti-inflammatory effects of MerTK by inducing M2 macrophage polarization via PI3K/Akt/GSK-3ß pathway in gout.

Mer tyrosine kinase (MerTK) has been found to regulate the secretion of inflammatory factors and exert immunosuppressive effects, but its role in gout remains unclear. In this study, we aimed to clarify the immnue effects of MerTK in gout. MerTK in synovium or serum of gout patients was determined by immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), and real-time quantitative polymerase chain reaction (RT-qPCR). In monosodium urate (MSU)-induced gout mice, the effect of MerTK inhibitor (UNC2250) on inflammation and polarization was also assessed. After inhibition, knockdown or overexpression of MerTK, inflammatory response and polarization level in THP1-derived macrophages were evaluated by RT-qPCR and flow cytometry. Regulation of MerTK inhibitors on mitochondrial function and downstream pathway in THP1-derived macrophages were detected. MerTK in synovium and serum of gout patients were increased. MerTK inhibitor stimulated the inflammation and M1 polarization in MSU-induced gout mice. MerTK inhibition, knock-down, or overexpression affected inflammatory response, polarization and mitochondrial function in vitro in gout model. The PI3K/Akt/GSK-3ß pathway was identified to reduce after MerTK inhibition and the relevant results were as expected, validated by knock-down or overexpressing MerTK. In conclusion, MerTK was detected to increase in both gout patients and model. MerTK influenced inflammatory response and polarization markers through PI3K/Akt/GSK-3ß pathway. Interfering MerTK/PI3K/Akt/GSK-3ß axis may provide a new therapeutic target for gout.

An Ultrasensitive Molecularly Imprinted Point-Of-Care Electrochemical Sensor for Detection of Glial Fibrillary Acidic Protein.

Accurate assessment of neurological disease through monitoring of biomarkers has been made possible using the antibody-based assays. But these assays suffer from expensive development of antibody probes, reliance on complicated equipments, and high maintenance costs. Here, using the novel reduced graphene oxide/polydopamine-molecularly imprinted polymer (rGO/PDA-MIP) as the probe layer, a robust electrochemical sensing platform is demonstrated for the ultrasensitive detection of glial fibrillary acidic protein (GFAP), a biomarker for a range of neurological diseases. A miniaturized integrated circuit readout system is developed to interface with the electrochemical sensor, which empowers it with the potential to be used as a point-of-care (POC) diagnostic tool in primary clinical settings. This innovative platform demonstrated good sensitivity, selectivity, and stability, with imprinting factor evaluated as 2.8. A record low limit-of-detection (LoD) is down to 754.5 ag mL-1, with a wide dynamic range from 1 to 106 fg mL-1. The sensing platform is validated through the analysis of GFAP in clinical plasma samples, yielding a recovery rate range of 81.6-108.8% compared to Single Molecule Array (Simoa). This cost-effective and user-friendly sensing platform holds the potential to be deployed in primary and resource-limited clinical settings for the assessment of neurological diseases.

Research on fatigue detection of flight trainees based on face EMF feature model combination with PSO-CNN algorithm.

Even though the capability of aircraft manufacturing has improved, human factors still play a pivotal role in flight accidents. For example, fatigue-related accidents are a common factor in human-led accidents. Hence, pilots' precise fatigue detections could help increase the flight safety of airplanes. The article suggests a model to recognize fatigue by implementing the convolutional neural network (CNN) by implementing flight trainees' face attributions. First, the flight trainees' face attributions are derived by a method called the land-air call process when the flight simulation is run. Then, sixty-eight points of face attributions are detected by employing the Dlib package. Fatigue attribution points were derived based on the face attribution points to construct a model called EMF to detect face fatigue. Finally, the proposed PSO-CNN algorithm is implemented to learn and train the dataset, and the network algorithm achieves a recognition ratio of 93.9% on the test set, which can efficiently pinpoint the flight trainees' fatigue level. Also, the reliability of the proposed algorithm is validated by comparing two machine learning models.

Fe─S Bond-Mediated Efficient Electron Transfer in Quantum Dots/Metal-Organic Frameworks for Boosting Photoelectrocatalytic Nitrogen Fixation.

Effective electron supply to produce ammonia in photoelectrochemical nitrogen reduction reaction (PEC NRR) remains challenging due to the sluggish multiple proton-coupled electron transfer and unfavorable carrier recombination. Herein, InP quantum dots decorated with sulfur ligands (InP QDs-S2-) bound to MIL-100(Fe) as a benchmark catalyst for PEC NRR is reported. It is found that MIL-100(Fe) can combined with InP QDs-S2- via Fe─S bonds as bridge to facilitate the electron transfer by experimental results. The formation of Fe─S bonds can facilitate electron transfer from inorganic S2- ligands of InP QDs to the Fe metal sites of MIL-100(Fe) within 52 ps, ensuring a more efficient electron transfer and electron-hole separation confirmed by the time-resolved spectroscopy. More importantly, the process of photo-induced carrier transfer can be traced by in situ attenuated total reflection surface-enhanced infrared tests, certifying that the effective electron transfer can promote N≡N dissociation and N2 hydrogenation. As a result, InP QDs-S2-/MIL-100(Fe) exhibits prominent performance with an outstanding NH3 yield of 0.58 µmol cm-2 h-1 (3.09 times higher than that of MIL-100(Fe)). This work reveals an important ultrafast dynamic mechanism for PEC NRR in QDs modified metal-organic frameworks, providing a new guideline for the rational design of efficient MOFs photocathodes.

One becomes three: An integrative morphological and molecular analysis of the windowpane oyster Placuna (Bivalvia: Pectinida) reveals new species.

For decades, many marine animals have been considered to exhibit cosmopolitan or transoceanic distribution. This situation is prevalent in Asia, where many species were collected and named by American or European experts in the 1700s to early 1900s. Using the windowpane oysters Placuna-a small genus of bivalves with five recognized species-we show that careful analysis is required to reassess the validity of these species. Currently, only two species of Placuna (P. placenta and P. ephippium) widely reported in the Indo-Pacific region have been recorded from Chinese coastal waters. Here, we described two new species of Placuna from China. Placuna vitream sp. nov. can be distinguished from P. placenta by its larger ridge angle. Phylogenetic analysis using five gene fragments fully supported that P. vitream sp. nov. is a sister to the specimen from Singapore identified as P. placenta and more distant from other Placuna species with available molecular data. Besides, based on subfossil shells, we describe Placuna aestuaria sp. nov. that differs from its congeneric species by its broad hinge, medium ridge angle, and nearly straight ridges. Finally, we suggest a combination of hinge structure and ridge angle that can be used for identifying Placuna species and preparing a key to this genus. Our findings of two new species expand the diversity of Placuna and prompt reassessment of the many presumably widely distributed marine species in Asia.

The Antidiabetic Potential of Probiotics: A Review.

Diabetes has become one of the most prevalent global epidemics, significantly impacting both the economy and the health of individuals. Diabetes is associated with numerous complications, such as obesity; hyperglycemia; hypercholesterolemia; dyslipidemia; metabolic endotoxemia; intestinal barrier damage; insulin-secretion defects; increased oxidative stress; and low-grade, systemic, and chronic inflammation. Diabetes cannot be completely cured; therefore, current research has focused on developing various methods to control diabetes. A promising strategy is the use of probiotics for diabetes intervention. Probiotics are a class of live, non-toxic microorganisms that can colonize the human intestine and help improve the balance of intestinal microbiota. In this review, we summarize the current clinical studies on using probiotics to control diabetes in humans, along with mechanistic studies conducted in animal models. The primary mechanism by which probiotics regulate diabetes is improved intestinal barrier integrity, alleviated oxidative stress, enhanced immune response, increased short-chain fatty acid production, etc. Therefore, probiotic supplementation holds great potential for the prevention and management of diabetes.

Sarcopenia is a prognostic factor in lymphoma patients: a systematic review and meta-analysis.

Findings regarding the relationship between sarcopenia and lymphoma have been inconsistent across studies. This study investigated the association between sarcopenia and lymphoma. We systematically searched the Embase, Science Direct, Cochrane Library, and PubMed databases from inception to 31 March 2024 to identify relevant studies. Two researchers independently extracted and evaluated studies that met inclusion and exclusion criteria. Twenty-six studies with 3659 participants were included. Sarcopenic lymphoma patients had poor overall survival (OS) (HR = 1.88; 95% CI: 1.47-2.41; p < 0.001). The heterogeneity was high (I2=80%). However, the result of the Egger test indicated a significant publication bias (p < 0.001). After employing the trim and fill method to adjust for this bias, the HR of OS became non-significant (p > 0.05). The progression-free survival (PFS) was worse in sarcopenic patients (HR = 1.77; 95% CI: 1.37-2.29; p < 0.001; I2=70%). There was no significant publication bias (p > 0.05). In the subgroup analyses, sarcopenia was a negative predictor of OS in lymphoma patients who undergo hematopoietic cell transplantation (HCT) (HR  = 1.61;95% CI: 1.19-2.18; I2=30%). Male lymphoma patients with sarcopenia had a significantly worse OS (HR = 2.29; 95% CI:1.24-4.24; p = 0.009). Among patients with primary central nervous system lymphoma (PCNSL), those with sarcopenia defined by temporal muscle thickness (TMT) exhibited significantly worse OS (HR = 2.20; 95% CI:1.04-4.65; p = 0.039; I2=68%). Sarcopenia is associated with worse PFS in lymphoma patients. Subgroup analyses indicate that sarcopenia is a negative predictor of OS after HCT, and male lymphoma patients who suffer from sarcopenia have higher mortality. Sarcopenia defined by TMT is also a negative predictor of OS for patients with PCNSL.

A future directions of renal cell carcinoma treatment: combination of immune checkpoint inhibition and carbon ion radiotherapy.

Renal cell carcinoma (RCC) is considered radio- and chemo-resistant. Immune checkpoint inhibitors (ICIs) have demonstrated significant clinical efficacy in advanced RCC. However, the overall response rate of RCC to monotherapy remains limited. Given its immunomodulatory effects, a combination of radiotherapy (RT) with immunotherapy is increasingly used for cancer treatment. Heavy ion radiotherapy, specifically the carbon ion radiotherapy (CIRT), represents an innovative approach to cancer treatment, offering superior physical and biological effectiveness compared to conventional photon radiotherapy and exhibiting obvious advantages in cancer treatment. The combination of CIRT and immunotherapy showed robust effectiveness in preclinical studies of various tumors, thus holds promise for overcoming radiation resistance of RCC and enhancing therapeutic outcomes. Here, we provide a comprehensive review on the biophysical effects of CIRT, the efficacy of combination treatment and the underlying mechanisms involved in, as well as its therapeutic potential specifically within RCC.

Heat-killed Bifidobacterium longum BBMN68 and inulin protect against high-fat diet-induced obesity by modulating gut microbiota.

Introduction: Obesity, a pervasive global epidemic, has heightened susceptibility to chronic ailments and diminished the overall life expectancy on a global scale. Probiotics and inulin (IN) have been documented to mitigate obesity by exerting an influence on the composition of the gut microbiota. Whether heat-killed Bifidobacterium longum BBMN68 (MN68) and IN have an anti-obesity effect remains to be investigated. Methods: In this study, Wistar rats were fed a high-fat diet (HFD), and orally administered heat-killed MN68 (2 × 1011 CFU/kg) and/or inulin (0.25 kg/kg) for 12 weeks. Histological analysis, serology analysis and 16S rRNA gene sequencing were performed. Results: Heat-killed MN68 + IN treatment showed an enhanced effect on preventing weight gain, diminishing fat accumulation, and regulating lipid metabolism, compared to either heat-killed MN68 treatment or inulin treatment. Gut microbiota results showed that heat-killed MN68 + IN treatment significantly increased the relative abundance of Bacteroidota, Oscillospira, Intestinimonas, Christensenella, and Candidatus_Stoquefichus, and reduced the relative abundance of Enterococcus. Furthermore, heat-killed MN68 + IN significantly increased the SCFA levels, which were correlated with changes in the gut microbiota. Discussion: This research provides support for the application of heat-killed MN68 and IN in the treatment of obesity, and highlights the combination of heat-killed BBMN68 and IN as functional food ingredients.

Diversity and Pathogenicity of Six Diaporthe Species from Juglans regia in China.

Walnut (Juglans regia L.) is cultivated extensively in China for its substantial economic potential as a woody oil species. However, many diseases caused by Diaporthe greatly affect the health of Juglans regia trees. The present study revealed the presence of Diaporthe species from Juglans regia. A total of six species of Diaporthe were isolated from twigs of Juglans regia in three provinces in China, including two known species (Diaporthe gammata and D. tibetensis) and four novel species (D. chaotianensis, D. olivacea, D. shangluoensis and D. shangrilaensis). Phylogenetic relationships of the new species were determined by multilocus phylogenetic analyses based on partial sequences of the internal transcribed spacer (ITS) region, calmodulin (cal) gene, histone H3 (his3) gene, translation elongation factor 1-α (tef1-α) gene and ß-tubulin (tub2) gene. Pathogenicity tests indicated that all Diaporthe species obtained in this study were confirmed as pathogens of Juglans regia. This study deepens the understanding of species associated with several disease symptoms in Juglans regia and provides useful information for effective disease control.

Machine learning-based prognostic model for in-hospital mortality of aortic dissection: Insights from an intensive care medicine perspective.

Objective: Aortic dissection (AD) is a severe emergency with high morbidity and mortality, necessitating strict monitoring and management. This retrospective study aimed to identify prognostic factors and establish predictive models for in-hospital mortality among AD patients in the intensive care unit (ICU). Methods: We retrieved ICU admission records of AD patients from the Medical Information Mart for Intensive Care (MIMIC)-IV critical care data set and the eICU Collaborative Research Database. Functional data analysis was further applied to estimate continuous vital sign processes, and variables associated with in-hospital mortality were identified through univariate analyses. Subsequently, we employed multivariable logistic regression and machine learning techniques, including simple decision tree, random forest (RF), and eXtreme Gradient Boosting (XGBoost) to develop prognostic models for in-hospital mortality. Results: Given 643 ICU admissions from MIMIC-IV and 501 admissions from eICU, 29 and 28 prognostic factors were identified from each database through univariate analyses, respectively. For prognostic model construction, 507 MIMIC-IV admissions were divided into 406 (80%) for training and 101 (20%) for internal validation, and 87 eICU admissions were included as an external validation group. Of the four models tested, the RF consistently exhibited the best performance among different variable subsets, boasting area under the receiver operating characteristic curves of 0.870 and 0.850. The models highlighted the mean 24-h fluid intake as the most potent prognostic factor. Conclusions: The current prognostic models effectively forecasted in-hospital mortality among AD patients, and they pinpointed noteworthy prognostic factors, including initial blood pressure upon ICU admission and mean 24-h fluid intake.

Comprehensive analysis of lncRNA-mediated ceRNA network in renal cell carcinoma based on GEO database.

Renal cell carcinoma (RCC) ranks among the leading causes of cancer-related mortality. Despite extensive research, the precise etiology and progression of RCC remain incompletely elucidated. Long noncoding RNA (lncRNA) has been identified as competitive endogenous RNA (ceRNA) capable of binding to microRNA (miRNA) sites, thereby modulating the expression of messenger RNAs (mRNA) and target genes. This regulatory network is known to exert a pivotal influence on cancer initiation and progression. However, the specific role and functional significance of the lncRNA-miRNA-mRNA ceRNA network in RCC remain poorly understood. The RCC transcriptome data was obtained from the gene expression omnibus database. The identification of differentially expressed long noncoding RNAs (DElncRNAs), differentially expressed miRNAs, and differentially expressed mRNAs (DEmRNAs) between RCC and corresponding paracancer tissues was performed using the "Limma" package in R 4.3.1 software. We employed a weighted gene co-expression network analysis to identify the key DElncRNAs that are most relevant to RCC. Subsequently, we utilized the encyclopedia of RNA interactomes database to predict the interactions between these DElncRNAs and miRNAs, and the miRDB database to predict the interactions between miRNAs and mRNAs. Therefore, key DElncRNAs were obtained to verify the expression of their related genes in the The Cancer Genome Atlas database and to analyze the prognosis. The construction of RCC-specific lncRNA-miRNA-mRNA ceRNA network was carried out using Cytoscape 3.7.0. A total of 286 DElncRNAs, 56 differentially expressed miRNAs, and 2065 DEmRNAs were identified in RCC. Seven key DElncRNAs (GAS6 antisense RNA 1, myocardial infarction associated transcript, long intergenic nonprotein coding RNA 921, MMP25 antisense RNA 1, Chromosome 22 Open Reading Frame 34, MIR34A host gene, MIR4435-2 host gene) were identified using weighted gene co-expression network analysis and encyclopedia of RNA interactomes databases. Subsequently, a network diagram comprising 217 nodes and 463 edges was constructed based on these key DElncRNAs. The functional analysis of DEmRNAs in the ceRNA network was conducted using Kyoto Encyclopedia of Genes and Genomes and gene ontology. We constructed RCC-specific ceRNA networks and identified the crucial lncRNAs associated with RCC using bioinformatics analysis, which will help us further understand the pathogenesis of this disease.

A case report and literature review on TP53 gene mutation in a bladder rhabdomyosarcoma patient.

Background: Rhabdomyosarcoma of the bladder is an infrequent neoplastic condition characterized by a pronounced malignant situation with challenges in treatment due to the lack of standardized guidelines and large-scale of clinical studies. The patient in this case is tested TP53 mutation that may provide new diagnostic and therapeutic options. Case presentation: Here, we reported a 34-year-old male who received bladder tumor resection, and diagnosed as bladder rhabdomyosarcoma with TP53 mutation after the pathology test. This patient underwent 6 rounds of chemotherapy. However, the pelvic tumor recurred 11 months after the first surgery. So, the patient accepted the pelvic tumor resection. Only 3 months after the surgical intervention, the patient underwent abdominal massive metastasis and ultimately succumbed to the illness six months following the second surgery. The course of the illness was 22 months. Conclusion: Bladder rhabdomyosarcoma is a disease with an extremely poor prognosis. Genetic testing holds significant value in the diagnosis and treatment. Perhaps targeted therapy against TP53 is potential valuable for such rare diseases.

Prevalence and influencing factors of subjects at high risk for cardiovascular disease in different regions of Gansu province, China: a cross-sectional study of 100,725 residents from 2017 to 2022.

Background: To investigate the prevalence rate of subjects at high risk for cardiovascular disease (CVD) and to analyze the influencing factors in different regions of Gansu Province. Methods: We used data from the China Patient-centered Evaluative Assessment of Cardiac Events (PEACE) Million Persons Project (MPP), which screened 100,725 residents aged 35-75 years from 10 project sites in Gansu Province, China, from 2017 to 2022. In addition, a questionnaire survey, anthropometric measurements, and collection of biological samples were carried out. Results: Of the 100,082 residents included, 21,059 were identified as subjects at high-risk for CVD. The overall prevalence rate of subjects at high risk for CVD was 19.7%, and the prevalence rate in the HeXi region was greater than that in the LongZhong and LongDong regions. The prevalence rates were 14.0%, 58.2%, 34.9%, and 5.7% for cardiovascular history, hypertension, dyslipidemia, and WHO-assessed risk ≥20%, respectively. The prevalence rate of cardiovascular history type was the highest in the HeXi region, hypertension and dyslipidemia types were the highest in the LongZhong region, and WHO-assessed risk ≥20% type was the highest in the LongDong region. Male, higher education level, smoking status, snoring status, overweight and obesity status, central obesity status, and disease history were more likely to be risk factors for subjects at high risk for CVD. There were some differences among different regions in age, annual household income, farming status, rural/urban status, and drinking status. Conclusion: The prevalence rate of subjects at high risk for CVD in Gansu Province is relatively high. Individualized intervention measures as well as comprehensive prevention and control strategies should be adopted, focusing on the distribution characteristics of risk factors among high-risk subjects in different regions.

Ethical requirements of instructions for authors of complementary and alternative medicine journals: a cross-sectional study.

BACKGROUND: Medical research in complementary and alternative medicine (CAM) has increased recently, raising ethical concerns about the moral status of CAM. Medical academic journals are responsible for conducting ethical review (ER) of manuscripts to protect the interests of human subjects and to make ethical results available before deciding to publish. However, there has been no systematic analysis of the ER in CAM journals. This study is aim to evaluate the current status of ethical requirements and compliance in CAM journals. METHODS: This is a cross-sectional study. We reviewed instructions for authors (IFAs) of CAM journals included in the Journal Citation Reports (2021) ( https://jcr.clarivate.com ) for general information and requirements for ER. We also browsed the manuscripts regarding randomized controlled trials published by CAM journals in Q1 and Q2 section from January to June, 2023, to check the actual situation of ethical requirement. Descriptive statistics and Fisher's exact test were used for statistical analysis. RESULTS: 27 journals and 68 manuscripts were ultimately included. 92.6% (25/27) IFAs included keywords of ER, indicating the presence of ethical considerations. However, no specific ER was required for CAM (n = 0). We categorized journals by Geographic origin, JCR section, Year of electronic JCR, Types of studies, % of OA Gold to explore the factors that could influence CAM journals to have certain ethical review policies. The results showed there was no statistical significance in certain ethical review policy in any classification of journals (p > 0.05). All RCT manuscripts included in the study generally met the requirements of the published journals for ethical review. CONCLUSIONS: All IFAs discussed ER, but the content was scattered, unfocused, and there were no specific ER requirements regarding CAM. Although the manuscripts basically met the requirements of the journal, it was not possible to get closer to the process of ER in the manuscript. To ensure full implementation of these policies in the future, CAM journals should require authors to provide more details, or to form a list of items necessary for CAM ethical review.

Research on identification of flight cadets' cognitive load based on multi-source physiological data and CGAN-DBN model.

Modern aircraft cockpit system is highly information-intensive. Pilots often need to receive a large amount of information and make correct judgments and decisions in a short time. However, cognitive load can affect their ability to perceive, judge and make decisions accurately. Furthermore, the excessive cognitive load will induce incorrect operations and even lead to flight accidents. Accordingly, the research on cognitive load is crucial to reduce errors and even accidents caused by human factors. By using physiological acquisition systems such as eye movement, ECG, and respiration, multi-source physiological signals of flight cadets performing different flight tasks during the flight simulation experiment are obtained. Based on the characteristic indexes extracted from multi-source physiological data, the CGAN-DBN model is established by combining the conditional generative adversarial networks (CGAN) model with the deep belief network (DBN) model to identify the flight cadets' cognitive load. The research results show that the flight cadets' cognitive load identification based on the CGAN-DBN model established has high accuracy. And it can effectively identify the cognitive load of flight cadets. The research paper has important practical significance to reduce the flight accidents caused by the high cognitive load of pilots.

In our study, a highly accurate cognitive load identification model for flight cadets was established by using multi-source physiological data. Moreover, it provides a theoretical basis for identifying the cognitive load of pilots through wearable physiological devices. Our intent is to catalyse further research and technological development.

Uncertainty quantification via localized gradients for deep learning-based medical image assessments.

Objective.Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep learning models have been shown to be highly accurate across a variety of tasks, measures that indicate the reliability of these models are less established. Increasingly, uncertainty quantification (UQ) methods are being introduced to inform users on the reliability of model outputs. However, most existing methods cannot be augmented to previously validated models because they are not post hoc, and they change a model's output. In this work, we overcome these limitations by introducing a novel post hoc UQ method, termedLocal Gradients UQ, and demonstrate its utility for deep learning-based metastatic disease delineation.Approach.This method leverages a trained model's localized gradient space to assess sensitivities to trained model parameters. We compared the Local Gradients UQ method to non-gradient measures defined using model probability outputs. The performance of each uncertainty measure was assessed in four clinically relevant experiments: (1) response to artificially degraded image quality, (2) comparison between matched high- and low-quality clinical images, (3) false positive (FP) filtering, and (4) correspondence with physician-rated disease likelihood.Main results.(1) Response to artificially degraded image quality was enhanced by the Local Gradients UQ method, where the median percent difference between matching lesions in non-degraded and most degraded images was consistently higher for the Local Gradients uncertainty measure than the non-gradient uncertainty measures (e.g. 62.35% vs. 2.16% for additive Gaussian noise). (2) The Local Gradients UQ measure responded better to high- and low-quality clinical images (p< 0.05 vsp> 0.1 for both non-gradient uncertainty measures). (3) FP filtering performance was enhanced by the Local Gradients UQ method when compared to the non-gradient methods, increasing the area under the receiver operating characteristic curve (ROC AUC) by 20.1% and decreasing the false positive rate by 26%. (4) The Local Gradients UQ method also showed more favorable correspondence with physician-rated likelihood for malignant lesions by increasing ROC AUC for correspondence with physician-rated disease likelihood by 16.2%.Significance. In summary, this work introduces and validates a novel gradient-based UQ method for deep learning-based medical image assessments to enhance user trust when using deployed clinical models.

Updating the Species Diversity of Pestalotioid Fungi: Four New Species of Neopestalotiopsis and Pestalotiopsis.

Pestalotioid fungi are associated with a wide variety of plants around the world as pathogens, endophytes, and saprobes. In this study, diseased leaves and branches of plants were collected from Guizhou and Sichuan in China. Here, the fungal isolates were identified based on a phylogenetic analysis of the internal transcribed spacer region (ITS), the translation elongation factor 1-alpha (tef1-α) and the beta-tubulin (tub2) of ribosomal DNA, and the morphological characteristics. Ten Neopestalotiopsis isolates and two Pestalotiopsis isolates were obtained, and these isolates were further confirmed as four novel species (N. acericola, N. cercidicola, N. phoenicis, and P. guiyangensis) and one known species, N. concentrica.

Bifidobacterium lactis and Lactobacillus plantarum Enhance Immune Function and Antioxidant Capacity in Cats through Modulation of the Gut Microbiota.

Gastrointestinal (GI) afflictions are prevalent among the feline population, wherein the intricacies of the gut microbiome exert a profound influence on their overall health. Alterations within this microbial consortium can precipitate a cascade of physiological changes, notably in immune function and antioxidant capacity. This research investigated the impact of Bifidobacterium lactis (B. lactis) and Lactobacillus plantarum (L. plantarum) on cats' GI health, exploring the effects of probiotic supplementation on the intestinal ecosystem using 16S rRNA gene sequencing. The findings demonstrated a significant improvement in gut barrier function by reducing plasma concentrations of D-lactate (D-LA) by 30.38% and diamine oxidase (DAO) by 22.68%, while increasing the population of beneficial bacteria such as Lactobacillus. There was a notable 25% increase in immunoglobulin A (IgA) levels, evidenced by increases of 19.13% in catalase (CAT), 23.94% in superoxide dismutase (SOD), and 21.81% in glutathione peroxidase (GSH-Px). Further analysis revealed positive correlations between Lactobacillus abundance and IgA, CAT, and total antioxidant capacity (T-AOC) levels. These correlations indicate that B. lactis and L. plantarum enhance feline immune and antioxidant functions by increasing the abundance of beneficial Lactobacillus in the GI tract. These findings provide a foundation for probiotic interventions aimed at enhancing health and disease resistance in feline populations.