Search

Abstract Diabetic nephropathy (DN) is a common complication of diabetes mellitus (DM), and cell death plays an important role. Ferroptosis is a recently discovered type of iron‐dependent cell death and one that is different from other kinds of cell death including apoptosis and necrosis. However, ferroptosis has not been described in the context of DN. This study explored the role of ferroptosis in DN pathophysiology and aimed to confirm the efficacy of the ferroptosis inhibitor SRS 16‐86 on DN. Streptozotocin injection was used to establish the DM and DN animal models. To investigate the presence or occurrence of ferroptosis in DN, we assessed the concentrations of iron, reactive oxygen species and specific markers associated with ferroptosis in a rat model of DN. Additionally, we performed haematoxylin–eosin staining, blood biochemistry, urine biochemistry and kidney function analysis to evaluate the efficacy of the ferroptosis inhibitor SRS 16‐86 in ameliorating DN. We found that SRS 16‐86 could improve the recovery of renal function after DN by upregulating glutathione peroxidase 4, glutathione and system xc−light chain and by downregulating the lipid peroxidation markers and 4‐hydroxynonenal. SRS 16‐86 treatment could improve renal organization after DN. The inflammatory cytokines interleukin 1β and tumour necrosis factor α and intercellular adhesion molecule 1 were significantly decreased following SRS 16‐86 treatment after DN. The results indicate that there is a strong connection between ferroptosis and the pathological mechanism of DN. The efficacy of the ferroptosis inhibitor SRS 16‐86 in DN repair supports its use as a new therapeutic treatment for DN.

Microscopic inspection of thin-film blood smears is widely used to identify red blood cell (RBC) pathologies, including malaria parasitism and hemoglobinopathies, such as sickle cell disease and thalassemia. Emerging research indicates that non-pathologic changes in RBCs can also be detected in images, such as deformability and morphological changes resulting from the storage lesion. In transfusion medicine, cell deformability is a potential biomarker for the quality of donated RBCs. However, a major impediment to the clinical translation of this biomarker is the difficulty associated with performing this measurement. To address this challenge, we developed an approach for biophysical profiling of RBCs based on cell images in thin-film blood smears. We hypothesize that subtle cellular changes are evident in blood smear images, but this information is inaccessible to human expert labellers. To test this hypothesis, we developed a deep learning strategy to analyze Giemsa-stained blood smears to assess the subtle morphologies indicative of RBC deformability and storage-based degradation. Specifically, we prepared thin-film blood smears from 27 RBC samples (9 donors evaluated at 3 storage time points) and imaged them using high-resolution microscopy. Using this dataset, we trained a convolutional neural network to evaluate image-based morphological features related to cell deformability. The prediction of donor deformability is strongly correlated to the microfluidic scores and can be used to categorize images into specific deformability groups with high accuracy. We also used this model to evaluate differences in RBC morphology resulting from cold storage. Together, our results demonstrate that deep learning models can detect subtle cellular morphology differences resulting from deformability and cold storage. This result suggests the potential to assess donor blood quality from thin-film blood smears, which can be acquired ubiquitously in clinical workflows.

Large scale digital data, which are becoming more prevalent, offer the potential to alleviate reproducibility concerns in psychology research findings. However, large scale digital data are not sufficient in and of themselves, thus necessitating the need for the development of machine learning (ML) pipelines that are capable of handling high dimensional datasets at scale. Such ML-based methodologies enable the analysis of complex relationships, which allows for the consideration of complicated demographics, a factor that is likely to play a role in the generalizability of research. We introduce a novel ML pipeline and demonstrate its potential on a large-scale digital dataset, Sea Hero Quest, a mobile game with data from nearly 770,000 players (ages 19 to 70, men N = 404,455, women N = 367,173). We analyzed how demographics are related to self-reported navigation ability using exploratory analysis, supervised and unsupervised learning. The results suggest that gender is the most important demographic factor in predicting self-reported navigation ability, followed by daily commuting time, age, and education, such that men (compared to women), long commuters (compared to those whose commuting time is shorter than 1 h), and older people with tertiary education (compared to younger people with secondary education) tended to evaluate themselves as better navigators. The large-scale dataset and ML pipeline capture influential factors, such as daily commuting time and education level, which have often been overlooked and are difficult to investigate with in-laboratory studies that use limited samples and traditional analytical techniques.

BackgroundTrace metals have side-effect on human health. The association between trace metals exposure and hearing loss remains unclear.MethodsA total of 8,128 participants were exacted for analysis of association between trace metals and hearing loss from the database of the National Health and Nutrition Examination Survey (NHANES) (2013–2018). Multivariable logistic regression and restricted cubic spline models were used to examine the association between trace metals and hearing loss.ResultsParticipants with hearing loss had a higher level of lead, cadmium, molybdenum, tin, thallium, and tungsten (all p < 0.05). After adjusting for confounders, compared with the reference of the lowest quartile, the ORs with 95%CIs for hearing loss across quartiles were 1.14 (0.86, 1.51), 1.49 (1.12, 1.98), 1.32 (0.97, 1.80) for cobalt, and 1.35 (0.98, 1.87), 1.58 (1.15, 2.16), 1.75 (1.28, 2.40) for tin. Individuals with the level of cobalt at third quartile had 49% higher risks of hearing loss than those at lowest quartile. And participants with highest quartile of tin had 1.75-folds risks of hearing loss than those with lowest quartile of tin. There were increasing trends in risks of hearing loss with a raised level of thallium (p for trend

Abstract Background This study investigated the impact of handedness on a common spatial abilities task, the mental rotation task (MRT). The influence of a right-handed world was contrasted with people’s embodied experience with their own hands by testing both left- and right-handed people on an MRT of right- and left-hand stimuli. An additional consideration is the influence of matching the shape of the hand stimuli with the proprioception of one’s own hands. Two orthogonal hypothesis axes were crossed to yield four competing hypotheses. One axis contrasted (i) embodied experience versus (ii) world knowledge; the other axis contrasted (a) the match between the visual image of a hand on the screen and one’s own hand versus (b) the resemblance of the shape outline information from the hand stimuli with the proprioception of one’s own hands. Results Among people with mixed handedness, right-handers performed more accurately for left-hand stimuli, while left-handers had a trend for higher accuracy for right-hand stimuli. For people with extreme handedness, right-handers outperformed left-handers. Regardless of group, there was no significant variation in performance for left-hand stimuli, with only right-hand stimuli producing significant variation. Conclusions No hypothesis fully aligned with all the data. For left-hand stimuli, the consistent performance across groups does not provide support for embodied experience, while world knowledge might influence all groups similarly. Alternatively, the within-group variation for mixed-handed people supports embodied experience in the hand MRT, likely processed through visual-proprioceptive integration.

ObjectivesThis project aimed to construct an individualized PET/CT prognostic biomarker to accurately quantify the progression risk of patients with stage IIIC-IV epidermal growth factor receptor (EGFR)-mutated Non-small cell lung cancer (NSCLC) after first-line first and second generation EGFR- tyrosine kinase inhibitor (TKI) drug therapy and identify the first and second generation EGFR-TKI treatment-sensitive population.MethodsA total of 250 patients with stage IIIC-IV EGFR-mutated NSCLC underwent first-line first and second generation EGFR-TKI drug therapy were included from two institutions (140 patients in training cohort; 60 patients in internal validation cohort, and 50 patients in external validation cohort). 1037 3D radiomics features were extracted to quantify the phenotypic characteristics of the tumor region in PET and CT images, respectively. A four-step feature selection method was performed to enable derivation of stable and effective signature in the training cohort. According to the median value of radiomics signature score (Rad-score), patients were divided into low- and high-risk groups. The progression-free survival (PFS) behaviors of the two subgroups were compared by Kaplan–Meier survival analysis.ResultsOur results shown that higher Rad-scores were significantly associated with worse PFS in the training (p < 0.0001), internal validation (p = 0.0153), and external validation (p = 0.0006) cohorts. Rad-score can effectively identify patients with a high risk of rapid progression. The Kaplan–Meier survival curves of the three cohorts present significant differences in PFS between the stratified slow and rapid progression subgroups.ConclusionThe PET/CT-derived Rad-score can realize the precise quantitative stratification of progression risk after first-line first and second generation EGFR-TKI drug therapy for NSCLC and identify EGFR-mutated NSCLC populations sensitive to targeted therapy, which might help to provide precise treatment options for NSCLC.

The environmental oxygen concentration is a crucial factor affecting cell proliferation. Owing to the reversible binding property of hemoglobin to oxygen, it can be utilized to regulate the oxygen concentration in vitro, and its ability to reduce apoptosis can be evaluated. In this study, a process comprising isolation, purification, and extraction was used to obtain hemoglobin from Perinereis aibuhitensis, a polychaete invertebrate. Extracts were separated and characterized using sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Extract component identity was confirmed by matrix-assisted laser desorption time-of-flight mass spectrometry analysis, with the molecular weight determined as 412,216.6875 Da. The oxygen carrying capacity of P. aibuhitensis hemoglobin was comparable with that of human hemoglobin. P. aibuhitensis hemoglobin remarkably downregulated the apoptosis rate. Reactive oxygen species (ROS) assays confirmed the reduction in ROS production, enabling a better elucidation of the mechanism underlying the decrease in apoptosis. These results suggested that P. aibuhitensis hemoglobin is a natural oxygen carrier, that, owing to its low-cost and accessibility, can be considered a candidate for culture medium supplement to reduce the apoptosis rate.

This study employed a data fusion method to extract the high-similarity time series feature index of a dataset through the integration of MS (Multi-Spectrum) and SAR (Synthetic Aperture Radar) images. The farmlands are divided into small pieces that consider the different behaviors of farmers for their planting contents in Taiwan. Hence, the conventional image classification process cannot produce good outcomes. The crop phenological information will be a core factor to multi-period image data. Accordingly, the study intends to resolve the previous problem by using three different SPOT6 satellite images and nine Sentinel-1A synthetic aperture radar images, which were used to calculate features such as texture and indicator information, in 2019. Considering that a Dynamic Time Warping (DTW) index (i) can integrate different image data sources, (ii) can integrate data of different lengths, and (iii) can generate information with time characteristics, this type of index can resolve certain classification problems with long-term crop classification and monitoring. More specifically, this study used the time series data analysis of DTW to produce “multi-scale time series feature similarity indicators”. We used three approaches (Support Vector Machine, Neural Network, and Decision Tree) to classify paddy patches into two groups: (a) the first group did not apply a DTW index, and (b) the second group extracted conflict predicted data from (a) to apply a DTW index. The outcomes from the second group performed better than the first group in regard to overall accuracy (OA) and kappa. Among those classifiers, the Neural Network approach had the largest improvement of OA and kappa from 89.51, 0.66 to 92.63, 0.74, respectively. The rest of the two classifiers also showed progress. The best performance of classification results was obtained from the Decision Tree of 94.71, 0.81. Observing the outcomes, the interference effects of the image were resolved successfully by various image problems using the spectral image and radar image for paddy rice classification. The overall accuracy and kappa showed improvement, and the maximum kappa was enhanced by about 8%. The classification performance was improved by considering the DTW index.

Background. We performed this meta-analysis to investigate the efficacy of probiotics on prevention of infection-related complications following colorectal resection. Method. PubMed, EMBASE, Cochrane Library, and the Web of Science were searched up to January 2016. According to the results, only randomized controlled trials that compared the efficacy of probiotics on patients with colorectal resection were included for meta-analysis. Results. Nine studies including a total of 1146 patients met the criteria (556 received multistrain probiotic bacteria, 590 with non-multistrain probiotic bacteria). The combination of multistrain probiotics was beneficial in the reduction of total infections (OR = 0.30, 95%CI: 0.15–0.61, p=0.0009), including surgical site infections (SSI) (OR = 0.48, 95%CI: 0.25–0.89, p=0.02) and nonsurgical site infections (NSSI) (OR = 0.36, 95%CI: 0.23–0.56, p

BACKGROUND: The high recurrence rate of hepatocellular carcinoma (HCC) after potentially curative treatment determines the long-term prognosis.

Transarterial therapies, either alone or in conjunction with adjuvant therapies, have been demonstrated to improve survival rates in patients with hepatocellular carcinoma (HCC). Although generally well tolerated and widely used for more than two decades, transarterial procedures have been reported to be associated with several infectious complications when performed in patients with HCC. However, the question of whether antibiotic prophylaxis is necessary for patients undergoing transarterial procedures for HCC remains controversial. Accordingly, this meta-analysis examined clinical trial evidence regarding the effects of prophylactic antibiotic therapy versus no prophylactic treatment with respect to infectious complications in patients undergoing transarterial therapy for HCC.

In this study, we aimed to investigate the effect of acute and chronic exposure to HA on the aerobic and anaerobic metabolism in liver by determining the hepatic levels of ICDH and ATP. Lactate levels in liver and blood were also examined. Rats were exposed to an altitude of 4,300 m for 30 days, and those without HA exposure were used as controls. We observed an increased expression of liver ICDH following acute exposure (days 1, 3, and 7), whereas the liver ATP concentration was reduced on day 1. No changes in the hepatic expression of ICDH and ATP were found in rats chronically exposed to HA. Lactate concentrations of liver and blood did not show any significant changes following HA exposure. Thus, aerobic metabolism may be the major metabolic pathway in response to HA hypoxia in order to acclimatize themselves to the stressful environments.

Targeted delivery of diagnostics and therapeutics offers essential advantages over nontargeted systemic delivery. These include the reduction of toxicity, the ability to reach sites beyond biological barriers, and the delivery of higher cargo concentrations to diseased sites. Virus-like particles (VLPs) can efficiently be used for targeted delivery purposes. VLPs are derived from the coat proteins of viral capsids. They are self-assembled, biodegradable, and homogeneously distributed. In this study, hepatitis E virus (HEV) VLP derivatives, hepatitis E virus nanoparticles (HEVNPs), were radiolabeled with gallium-68, and consequently, the biodistribution of the labeled [68Ga]Ga-DOTA-HEVNPs was studied in mice. The results indicated that [68Ga]Ga-DOTA-HEVNPs can be considered as promising theranostic nanocarriers, especially for hepatocyte-targeting therapies.