ASSOCIATION OF TESSELLATION DENSITY WITH PROGRESSION OF AXIAL LENGTH AND REFRACTION IN CHILDREN: An Artificial Intelligence-Assisted 4-Year Study.

PURPOSE: To investigate fundus tessellation density (TD) and its association with axial length (AL) elongation and spherical equivalent (SE) progression in children. METHODS: The school-based prospective cohort study enrolled 1,997 individuals aged 7 to 9 years in 11 elementary schools in Mojiang, China. Cycloplegic refraction and biometry were performed at baseline and 4-year visits. The baseline fundus photographs were taken, and TD, defined as the percentage of exposed choroidal vessel area in the photographs, was quantified using an artificial intelligence-assisted semiautomatic labeling approach. After the exclusion of 330 ineligible participants because of loss to follow-up or ineligible fundus photographs, logistic models were used to assess the association of TD with rapid AL elongation (>0.36 mm/year) and SE progression (>1.00 D/year). RESULTS: The prevalence of tessellation was 477 of 1,667 (28.6%) and mean TD was 0.008 ± 0.019. The mean AL elongation and SE progression in 4 years were 0.90 ± 0.58 mm and -1.09 ± 1.25 D. Higher TD was associated with longer baseline AL (ß, 0.030; 95% confidence interval: 0.015-0.046; P < 0.001) and more myopic baseline SE (ß, -0.017; 95% confidence interval: -0.032 to -0.002; P = 0.029). Higher TD was associated with rapid AL elongation (odds ratio, 1.128; 95% confidence interval: 1.055-1.207; P < 0.001) and SE progression (odds ratio, 1.123; 95% confidence interval: 1.020-1.237; P = 0.018). CONCLUSION: Tessellation density is a potential indicator of rapid AL elongation and refractive progression in children. TD measurement could be a routine to monitor AL elongation.

Diagnosis of a Rabbit Hemorrhagic Disease Virus 2 (RHDV2) and the Humoral Immune Protection Effect of VP60 Vaccine.

Rabbit hemorrhagic disease (RHD) is known as rabbit plague and hemorrhagic pneumonia. It is an acute, septic, and highly fatal infectious disease caused by the Lagovirus rabbit hemorrhagic disease virus (RHDV) in the family Caliciviridae that infects wild and domestic rabbits and hares (lagomorphs). At present, RHDV2 has caused huge economic losses to the commercial rabbit trade and led to a decline in the number of wild lagomorphs worldwide. We performed a necropsy and pathological observations on five dead rabbits on a rabbit farm in Tai'an, China. The results were highly similar to the clinical and pathological changes of typical RHD. RHDV2 strain was isolated and identified by RT-PCR, and partial gene sequencing and genetic evolution analysis were carried out. There were significant differences in genetic characteristics and antigenicity between RHDV2 and classical RHDV strain, and the vaccine prepared with the RHDV strain cannot effectively prevent rabbit infection with RHDV2. Therefore, we evaluated the protective efficacy of a novel rabbit hemorrhagic virus baculovirus vector inactivated vaccine (VP60) in clinical application by animal regression experiment. The result showed that VP60 could effectively induce humoral immunity in rabbits. The vaccine itself had no significant effect on the health status of rabbits. This study suggested that the clinical application of VP60 may provide new ideas for preventing the spread of RHD2.

Regulation of Parkin in Cr (VI)-induced mitophagy in chicken hepatocytes.

The large amount of heavy metal chromium emissions from industrial production, ore smelting and sewage treatment plants have made chromium one of the most widespread heavy metal pollutants, with Cr (VI) being the most toxic. In recent years, people have gradually recognized the great harm of heavy metal chromium pollution, but the research on its pathogenic mechanism is still not deep enough. In this study, we treated the Primary cells of chicken liver with Cr (VI) to establish a model of toxicity. The optimal treatment time and Cr (VI) concentration were screened using the CCK-8 test. The intracellular mitochondrial membrane potential (MMP) and reactive oxygen species (ROS) were measured qualitatively and quantitatively by laser confocal and flow cytometry, respectively. This result was confirmed by the fact that Cr (VI) could cause mitophagy by causing damage to mitochondria. Subsequently, this study used LMH cells to construct a Parkin silencing model to further investigate that Parkin exerts the function on the Cr (VI)-induced mitophagy in chicken hepatocytes. The results showed that the knockdown of Parkin effectively blocked p62 degradation and LC3 lipidation and that PINK1 expression was significantly inhibited in LMH cells, further suggesting that the knockdown of Parkin effectively inhibited mitophagy. Mitochondrial morphology, MMP, and ROS were observed using laser confocal. The results showed that Parkin knockdown resulted in mitochondrial fission and increased levels of reactive oxygen species, together with increased depolarization of the mitochondrial membrane potential. These changes led to increased mitochondrial damage. In conclusion, this study showed that Cr (VI) could cause the occurrence of mitophagy by damaging mitochondria, and Parkin played a crucial role in Cr (VI)-induced mitophagy in chicken hepatocytes.

Streptococcus agalactiae-induced autophagy of bovine mammary epithelial cell via PI3K/AKT/mTOR pathway.

Streptococcus agalactiae (S. agalactiae) infection is a significant cause of mastitis, resulting in loss of cellular homeostasis and tissue damage. Autophagy plays an essential function in cell survival, defense, and the preservation of cellular homeostasis, and is often part of the response to pathogenic challenge. However, the effect of autophagy induced by S. agalactiae in bovine mammary epithelial cells (bMECs) is mainly unknown. So in this study, an intracellular S. agalactiae infection model was established. Through evaluating the autophagy-related indicators, we observed that after S. agalactiae infection, a significant quantity of LC3-I was converted to LC3-II, p62 was degraded, and levels of Beclin1 and Bcl2 increased significantly in bMECs, indicating that S. agalactiae induced autophagy. The increase in levels of LAMP2 and LysoTracker Deep Red fluorescent spots indicated that lysosomes had participated in the degradation of autophagic contents. After autophagy was activated by rapamycin (Rapa), the amount of p-Akt and p-mTOR decreased significantly, whilst the amount of intracellular S. agalactiae increased significantly. Whereas the autophagy was inhibited by 3-methyladenine (3MA), the number of intracellular pathogens decreased. In conclusion, the results demonstrated that S. agalactiae could induce autophagy through PI3K/Akt/mTOR pathway and utilize autophagy to survive in bMECs.

Role of PERK-Mediated Endoplasmic Reticulum Stress in Ferroptosis Caused by Hexavalent Chromium in Chicken Hepatocytes.

This study aimed to investigate whether Cr(VI) can induce ferroptosis in chicken hepatocytes and determine the role of PERK-mediated endoplasmic reticulum stress (ERS). First, a model of Cr(VI) poisoning was established by exposing chicken hepatocytes to Cr(VI). The levels of ferroptosis-related proteins, meanwhile, GSH, SOD, MDA, and lipid ROS, were measured. Furthermore, the expression of GRP78 and PERK proteins was examined. Changes in ERS and ferroptosis were evaluated by silencing the PERK gene. Results showed that Cr(VI) led to the accumulation of lipid ROS, decreased expression of GPX4 and HSP27, increased expression of COX2, and induced ferroptosis in chicken hepatocytes. Exposure to Cr(VI) increased the protein expression of GRP78 and PERK, and silencing of PERK worsened Cr(VI)-induced ferroptosis. In conclusion, Cr(VI) can induce ferroptosis in chicken hepatocytes, and PERK plays an important role as a negative regulator.

Research on Bacterial Diversity and Antibiotic Resistance in the Dairy Farm Environment in a Part of Shandong Province.

Antimicrobials are extensively utilized in dairy farms to prevent and control diseases in cattle. However, their use contributes to the emergence of antimicrobial-resistant bacteria (ARB) and antimicrobial-resistant genes (ARG), and these can be transmitted to the environment. Regular monitoring of antimicrobial resistance (AMR) is crucial for implementing effective mitigation strategies. This research aimed to assess the environmental microbial species present on dairy farms in Shandong Province and characterize the antimicrobial resistance profiles of the isolates. Five dairy farms located in Shandong Province were selected, representing the prevalent large-scale farming patterns in the area. Sampling took place from April to June 2022, with a total of 223 isolates collected from various environmental locations within each farm (bedding, sports field, and milking parlor). Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) was employed to identify the species of the clinical isolates. The main pathogens isolated were Aerococcus viridans (5.38%, n = 12), Corynebacterium xerosis (4.93%, n = 11), and Acinetobacter lwoffii (4.03%, n = 9). Among the bacterial isolates, resistance to lincomycin was highest at 91%, and 88% were resistant to sulfadiazine. Antimicrobial resistance genes were detected in only a small proportion of the isolates, the most common of which was sul1. These findings highlight the necessity for careful evaluation of antimicrobial usage in maintaining their effectiveness in human medicine. Understanding the microbial species present and their antimicrobial resistance profiles aids in focusing efforts toward sustainable antimicrobial use and safeguarding human health.

Development and validation of a deep learning model to predict axial length from ultra-wide field images.

BACKGROUND: To validate the feasibility of building a deep learning model to predict axial length (AL) for moderate to high myopic patients from ultra-wide field (UWF) images. METHODS: This study included 6174 UWF images from 3134 myopic patients during 2014 to 2020 in Eye and ENT Hospital of Fudan University. Of 6174 images, 4939 were used for training, 617 for validation, and 618 for testing. The coefficient of determination (R2), mean absolute error (MAE), and mean squared error (MSE) were used for model performance evaluation. RESULTS: The model predicted AL with high accuracy. Evaluating performance of R2, MSE and MAE were 0.579, 1.419 and 0.9043, respectively. Prediction bias of 64.88% of the tests was under 1-mm error, 76.90% of tests was within the range of 5% error and 97.57% within 10% error. The prediction bias had a strong negative correlation with true AL values and showed significant difference between male and female (P < 0.001). Generated heatmaps demonstrated that the model focused on posterior atrophy changes in pathological fundus and peri-optic zone in normal fundus. In sex-specific models, R2, MSE, and MAE results of the female AL model were 0.411, 1.357, and 0.911 in female dataset and 0.343, 2.428, and 1.264 in male dataset. The corresponding metrics of male AL models were 0.216, 2.900, and 1.352 in male dataset and 0.083, 2.112, and 1.154 in female dataset. CONCLUSIONS: It is feasible to utilize deep learning models to predict AL for moderate to high myopic patients with UWF images.

Cr(VI) induces ferroptosis in DF-1 cells by simultaneously perturbing iron homeostasis of ferritinophagy and mitophagy.

Hexavalent chromium [Cr(VI)] is an environmental pollutant known for its strong oxidizing and carcinogenic effects. However, its potential to induce ferroptosis in poultry remains poorly understood. This study aims to investigate the induction of ferroptosis by Cr(VI) in DF-1 cells and elucidate the underlying mechanisms. DF-1 cells exposed to Cr(VI) showed increased lipid reactive oxygen species and changes in ferroptosis marker genes (decreased expression of GPX4 and increased expression of COX2). Notably, the addition of the ferroptosis-specific inhibitor ferrostatin-1 (Fer-1) can reverse this effect. During the cell death process, Cr(VI) induced ferritinophagy, disrupting iron homeostasis and releasing labile iron ions. We predicted by docking that these iron ions would bind to mitochondrial membrane proteins through virtual docking. This binding was validated through colocalization analysis. In addition, Cr(VI) caused mitophagy, which releases additional ferrous ions. Therefore, Cr(VI) can induce the simultaneous release of ferrous ions through these pathways, thereby exacerbating lipid peroxidation and ultimately triggering ferroptosis in DF-1 cells. This study demonstrates that Cr(VI) can induce ferroptosis in DF-1 cells by disrupting intracellular iron homeostasis and providing valuable insights into the toxic effects of Cr(VI) in poultry and potentially other organisms.

A simple-to-use score system for predicting HBsAg clearance to peginterferon alfa-2b in nucleoside analogs-experienced chronic hepatitis B patients.

Objective: Patients with chronic hepatitis B (CHB) often fail to achieve clearance of the hepatitis B surface antigen (HBsAg) with peginterferon treatment. Our study aimed to develop a simple-to-use scoring system to predict the likelihood of HBsAg clearance following treatment with peginterferon alfa-2b(PEG-IFN-α2b) in patients with CHB. Methods: A total of 231 patients were enrolled and divided into HBsAg clearance (n = 37) and non-HBsAg clearance (n = 194) groups. Multifactor logistic models were constructed using univariate and multiple logistic regression analyses. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis were used to evaluate the discrimination, calibration, and clinical applicability of the predictive scoring system. Results: Four clinical variables (age, baseline HBsAg level, HBsAg level decline at week 12, and alanine aminotransferase ratio at week 12) were independently associated with HBsAg clearance after PEG-IFN-α2b treatment and, therefore, were used to develop a predictive scoring system ranging from 0 to 13. The optimal cut-off value was >4, with a sensitivity of 86.49%, specificity of 72.16%, positive predictive value of 37.2%, negative predictive value of 96.6%, and an AUC of 0.872. This model exhibited good discrimination, calibration, and clinical applicability. Among patients with scores <4, 4, or > 4 HBsAg clearance was achieved in 0.85, 14.29, and 37.21% of the patients, respectively. Conclusion: The scoring system could effectively predict the predominance of HBsAg clearance after PEG-IFN-α2b treatment in the early stage. This may be helpful when making clinical decisions for the treatment of patients with CHB.

Medical matting: Medical image segmentation with uncertainty from the matting perspective.

High-quality manual labeling of ambiguous and complex-shaped targets with binary masks can be challenging. The weakness of insufficient expression of binary masks is prominent in segmentation, especially in medical scenarios where blurring is prevalent. Thus, reaching a consensus among clinicians through binary masks is more difficult in multi-person labeling cases. These inconsistent or uncertain areas are related to the lesions' structure and may contain anatomical information conducive to providing an accurate diagnosis. However, recent research focuses on uncertainties of model training and data labeling. None of them has investigated the influence of the ambiguous nature of the lesion itself. Inspired by image matting, this paper introduces a soft mask called alpha matte to medical scenes. It can describe the lesions with more details better than a binary mask. Moreover, it can also be used as a new uncertainty quantification method to represent uncertain areas, filling the gap in research on the uncertainty of lesion structure. In this work, we introduce a multi-task framework to generate binary masks and alpha mattes, which outperforms all state-of-the-art matting algorithms compared. The uncertainty map is proposed to imitate the trimap in matting methods, which can highlight fuzzy areas and improve matting performance. We have created three medical datasets with alpha mattes to address the lack of available matting datasets in medical fields and evaluated the effectiveness of our proposed method on them comprehensively. Furthermore, experiments demonstrate that the alpha matte is a more effective labeling method than the binary mask from both qualitative and quantitative aspects.

Combination therapy of ursodeoxycholic acid and glucocorticoid and (or) immunosuppressant in patients with primary biliary cholangitis: A meta-analysis.

BACKGROUND/OBJECTIVES: Primary biliary cholangitis (PBC) is a chronic inflammatory autoimmune cholestasis liver disease. There were many studies comparing a combination of glucocorticoids and/or immunosuppressants to a single UDCA therapy in PBC patients, while the literature demonstrated divergent finds. To evaluate the effectiveness of ursodeoxycholic acid (UDCA) combined with glucocorticoids and (or) immunosuppressants on biochemistry, immunology, histology, clinical symptoms, and adverse reactions of PBC from the perspective of evidence-based medicine. MATERIALS AND METHODS: PubMed, web of science, the Cochrane Library, EMBASE databases were searched to collect clinical randomized trials and self-control studies of UDCA combined with glucocorticoids and (or) immunosuppressants and UDCA monotherapy in the treatment of PBC. The retrieval time is from the establishment of the database to August 2020. Two reviewers independently screened literature, extracted data and evaluated the bias of included studies. Revman 5.3 software was used for meta-analysis. RESULTS: Six studies including 201 patients were included. The meta-analysis found that the combination therapy can improve some biochemical indexes, immunological indexes, and clinical symptoms of patients with PBC. However, combination therapy has no significant improvement in other biochemical indicators which respond to liver and bile duct damage, such as ALT, GGT, and ALB. Besides, the improvement of liver histology is limited, and the incidence of adverse events is higher. CONCLUSION: Overall, the combination therapy showed no improvement in key biochemical parameters and limited improvement in liver pathology. Besides, the side effects were more serious. Therefore, in the current treatment regimen, it is not recommended for PBC patients.

Changes in the bacterial communities in chromium-contaminated soils.

Introduction: Hexavalent chromium or Cr(VI) is essential to various industries, such as leather manufacturing and stainless steel production. Given that inevitable leakage from industries pollutes the soil and thereby affects the soil environment. Microbial communities could improve the quality of the soil. Abundant bacterial communities would significantly enhance the soil richness and resist external pressure, benefiting agriculture. But the pollution of heavy metal broke the balance and decrease the abundance of bacterial communities, which weak the self-adjust ability of soil. This study aimed to explore changes in the diversity of soil bacterial communities and to identify the influences of soil bacterial communities on enzymes in soil polluted by Cr(VI). Methods: The target soils were sampled quickly and aseptically. Their chromium content was detected through inductively coupled plasma-mass spectrometry, and bacterial microbiome communities were explored through MiSeq high-throughput sequencing. Then, the content of nitrite reductase and catalases were investigated through enzyme-linked immunosorbent assay (ELISA). Results: Chromium content in polluted soils was higher than that in the control soils at all depths. Sobs, Chao1, Ace, and Shannon diversity estimators in the control were higher, whereas Simpson's diversity estimators in the control soils were lower than those of contaminated samples at all depths. Contaminants affected the composition of the bacterial community. The soil microbial species were relatively single and inhomogeneous in the polluted soils. The bacterial phyla in polluted and controlled soils include Proteobacteria, Actinobacteria, Chloroflexi, and Acidobacteria, which differ markedly in abundance. Discussion: The results of these observations provide insights into the ecotoxicological effects of Cr(VI) exposure to soil microorganisms. To sum up these results are critical for evaluating the stabilized state of microbial community structures, contributing to the assessment of the potential risk of metal accumulation in soils.

3D matting: A benchmark study on soft segmentation method for pulmonary nodules applied in computed tomography.

Usually, lesions are not isolated but are associated with the surrounding tissues. For example, the growth of a tumour can depend on or infiltrate into the surrounding tissues. Due to the pathological nature of the lesions, it is challenging to distinguish their boundaries in medical imaging. However, these uncertain regions may contain diagnostic information. Therefore, the simple binarization of lesions by traditional binary segmentation can result in the loss of diagnostic information. In this work, we introduce the image matting into the 3D scenes and use the alpha matte, i.e., a soft mask, to describe lesions in a 3D medical image. The traditional soft mask acted as a training trick to compensate for the easily mislabelled or under-labelled ambiguous regions. In contrast, 3D matting uses soft segmentation to characterize the uncertain regions more finely, which means that it retains more structural information for subsequent diagnosis and treatment. The current study of image matting methods in 3D is limited. To address this issue, we conduct a comprehensive study of 3D matting, including both traditional and deep-learning-based methods. We adapt four state-of-the-art 2D image matting algorithms to 3D scenes and further customize the methods for CT images to calibrate the alpha matte with the radiodensity. Moreover, we propose the first end-to-end deep 3D matting network and implement a solid 3D medical image matting benchmark. Its efficient counterparts are also proposed to achieve a good performance-computation balance. Furthermore, there is no high-quality annotated dataset related to 3D matting, slowing down the development of data-driven deep-learning-based methods. To address this issue, we construct the first 3D medical matting dataset. The validity of the dataset was verified through clinicians' assessments and downstream experiments. The dataset and codes will be released to encourage further research.1.