A Competition for the Diagnosis of Myopic Maculopathy by Artificial Intelligence Algorithms.

Importance: Myopic maculopathy (MM) is a major cause of vision impairment globally. Artificial intelligence (AI) and deep learning (DL) algorithms for detecting MM from fundus images could potentially improve diagnosis and assist screening in a variety of health care settings.

Objectives: To evaluate DL algorithms for MM classification and segmentation and compare their performance with that of ophthalmologists.

Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.

Background And Objectives: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate treatment and potential side effects of rescue medications. To address this issue, this study aimed to use multimodality deep learning models combining chest X-ray (CXR) and electronic health record (EHR) data to screen patients with abnormal N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in emergency departments.

Methods: Using the open-source dataset MIMIC-IV and MIMICCXR, the study population consisted of 1,432 patients and 1,833 pairs of CXRs and EHRs.

Vitamin D alleviation of oxidative stress in human retinal pigment epithelial cells.

Background: Oxidative stress-induced retinal pigment epithelium (RPE) cell damage is a major factor in age-related macular degeneration (AMD). Vitamin D (VD) is a powerful antioxidant and it has been suggested to have anti-aging properties and potential for treating AMD. This study aimed to investigate the effect of VD on RPE cell oxidative apoptosis of RPE cells in order to provide experimental evidence for the treatment of AMD.

Unraveling implicit human behavioral effects on dynamic characteristics of Covid-19 daily infection rates in Taiwan.

We investigate the dynamic characteristics of Covid-19 daily infection rates in Taiwan during its initial surge period, focusing on 79 districts within the seven largest cities. By employing computational techniques, we extract 18 features from each district-specific curve, transforming unstructured data into structured data. Our analysis reveals distinct patterns of asymmetric growth and decline among the curves.

A deep learning system for predicting time to progression of diabetic retinopathy.

Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images.

Sex-specific association between carotid atherosclerosis and fundus arteriosclerosis in a Chinese population: a retrospective cross-sectional study.

Objectives: Vascular stiffening is highly predictive of major adverse cardiovascular events. It is not clear whether microangiopathy, such as fundus arteriosclerosis, is related to carotid atherosclerosis. Hence, this study was designed to investigate the relationship between carotid atherosclerosis and fundus arteriosclerosis among individuals of different sexes in the Chinese health-examination population.

Few-shot transfer learning for personalized atrial fibrillation detection using patient-based siamese network with single-lead ECG records.

The proliferation of wearable devices has allowed the collection of electrocardiogram (ECG) recordings daily to monitor heart rhythm and rate. For example, 24-hour Holter monitors, cardiac patches, and smartwatches are widely used for ECG gathering and application. An automatic atrial fibrillation (AF) detector is required for timely ECG interpretation.

Learned Practical Guidelines for Evaluating Conditional Entropy and Mutual Information in Discovering Major Factors of Response-vs.-Covariate Dynamics.

We reformulate and reframe a series of increasingly complex parametric statistical topics into a framework of response-vs.-covariate (Re-Co) dynamics that is described without any explicit functional structures. Then we resolve these topics' data analysis tasks by discovering major factors underlying such Re-Co dynamics by only making use of data's categorical nature.

Case report: A novel c.1842_1845dup mutation of in two Chinese siblings with multiple acyl-CoA dehydrogenase deficiency.

This article reports the characterization of two siblings diagnosed with late-onset multiple Acyl-CoA dehydrogenase deficiency (MADD) caused by mutations in electron transfer flavoprotein(ETF)-ubiquinone oxidoreductase (ETF-QO) () gene. Whole exome sequencing (WES) was performed in the proband's pedigree. Clinical phenotypes of Proband 1 (acidosis, hypoglycemia, hypotonia, muscle weakness, vomiting, hypoglycemia, hepatomegaly, glutaric acidemia, and glutaric aciduria) were consistent with symptoms of MADD caused by the mutation.

Retinal vascular fractal dimension measurements in patients with obstructive sleep apnea syndrome: a retrospective case-control study.

Study Objectives: We performed a case-control study to investigate the correlation between the apnea-hypopnea index (AHI) and the retinal vascular fractal dimension (FD).

Methods: We selected 527 individuals who underwent polysomnography during health checkups at the Huadong Sanatorium from January to December 2021 as the study population, of whom 468 were included and 59 were excluded. All participants underwent a detailed health examination, including medical history assessment, physical examination, assessment of lifestyle factors, fundus photography, and laboratory examinations.

Spontaneous immunomodulation and regulation of angiogenesis and osteogenesis by Sr/Cu-borosilicate glass (BSG) bone cement to repair critical bone defects.

Injectable bone biomaterials like bone cement should be designed and fabricated with certain biological criteria, which include: 1) recruitment and polarization of the macrophages from M1 (pro-inflammatory) to M2 (anti-inflammatory) phenotype, 2) enhance vascularization, and 3) activate osteogenic differentiation of bone marrow-derived stem cells to promote bone healing. So far, no injectable biomaterials could spontaneously regulate the entire bone healing process that involves inflammation, angiogenesis, and osteogenesis. Therefore, in this study, we designed bone cement comprised of strontium and copper-incorporated borosilicate glass (Sr/Cu-BSG) in the liquid phase of chitosan to modulate bone healing.

Chinese familial central precocious puberty with hyperuricemia due to recurrent DLK1 mutation: Case report and review of the literature.

Background: Central precocious puberty (CPP) is a precocious puberty due to premature activation of the hypothalamic-pituitary-gonadal axis (HPG). MKRN3 defects are well-known causes of CPP, while DLK1 mutations were recently identified in a few patients with CPP.

Methods: The study was approved by the Institutional Review and the scientific committee of the hospital.

Changes in retinal vascular bifurcation in eyes with myopia.

Objective: To evaluate the effect of myopia on retinal vascular bifurcation.

Methods: A cross-sectional study that retrospectively analyzed the fundus photographs and clinical data of 493 people who participated in routine physical examinations in Huadong Sanatorium. One eye of each subject was included in the analysis.

Manipulating Bacterial Biofilms Using Materiobiology and Synthetic Biology Approaches.

Bacteria form biofilms on material surfaces within hours. Biofilms are often considered problematic substances in the fields such as biomedical devices and the food industry; however, they are beneficial in other fields such as fermentation, water remediation, and civil engineering. Biofilm properties depend on their genome and the extracellular environment, including pH, shear stress, and matrices topography, stiffness, wettability, and charges during biofilm formation.

Unraveling Hidden Major Factors by Breaking Heterogeneity into Homogeneous Parts within Many-System Problems.

For a large ensemble of complex systems, a Many-System Problem (MSP) studies how heterogeneity constrains and hides structural mechanisms, and how to uncover and reveal hidden major factors from homogeneous parts. All member systems in an MSP share common governing principles of dynamics, but differ in idiosyncratic characteristics. A typical dynamic is found underlying response features with respect to covariate features of quantitative or qualitative data types.

Gender-Specific Impact of Metabolic Obesity Phenotypes on the Risk of Hashimoto's Thyroiditis: A Retrospective Data Analysis Using a Health Check-Up Database.

Background: Hashimoto's thyroiditis (HT) is recognized as the most common autoimmune thyroid disease, often accompanied by the diffuse enlargement of thyroid with abundant blood flow and elevated level of thyroid autoantibodies. As obesity had a positive association with the risk of HT. Thus, this retrospective study was established to further explore the gender relationship between metabolic obesity phenotypes and the risk of Hashimoto's thyroiditis (HT).

Categorical Nature of Major Factor Selection via Information Theoretic Measurements.

Without assuming any functional or distributional structure, we select collections of major factors embedded within response-versus-covariate (Re-Co) dynamics via selection criteria [C1: confirmable] and [C2: irrepaceable], which are based on information theoretic measurements. The two criteria are constructed based on the computing paradigm called Categorical Exploratory Data Analysis (CEDA) and linked to Wiener-Granger causality. All the information theoretical measurements, including conditional mutual information and entropy, are evaluated through the contingency table platform, which primarily rests on the categorical nature within all involved features of any data types: quantitative or qualitative.

Mimicking Complexity of Structured Data Matrix's Information Content: Categorical Exploratory Data Analysis.

We develop Categorical Exploratory Data Analysis (CEDA) with mimicking to explore and exhibit the complexity of information content that is contained within any data matrix: categorical, discrete, or continuous. Such complexity is shown through visible and explainable serial multiscale structural dependency with heterogeneity. CEDA is developed upon all features' categorical nature via histogram and it is guided by all features' associative patterns (order-2 dependence) in a mutual conditional entropy matrix.

Radiomic analysis of magnetic resonance imaging predicts brain metastases velocity and clinical outcome after upfront radiosurgery.

Background: Brain metastasis velocity (BMV) predicts outcomes after initial distant brain failure (DBF) following upfront stereotactic radiosurgery (SRS). We developed an integrated model of clinical predictors and pre-SRS MRI-derived radiomic scores (R-scores) to identify high-BMV (BMV-H) patients upon initial identification of brain metastases (BMs).

Methods: In total, 256 patients with BMs treated with upfront SRS alone were retrospectively included.

Increased RNA production in Saccharomyces cerevisiae by simultaneously overexpressing FHL1, IFH1, and SSF2 and deleting HRP1.

Ribonucleic acid (RNA) and its degradation products are widely used in the food industry. In this study, we constructed Saccharomyces cerevisiae mutants with FHL1, IFH1, SSF1, and SSF2 overexpression and HRP1 deletion, individually to evaluate the effect on RNA production. The RNA content of recombinant strains W303-1a-FHL1, W303-1a-SSF2, and W303-1a-ΔHRP1 was increased by 14.

Use of a cytogenetic whole-genome comparison to resolve phylogenetic relationships among three species: implications for mammalian systematics and conservation biology.

The objective was to apply a novel modification of a genome-wide, comparative cytogenetic technique (comparative genomic hybridization, comparative genomic hybridization (CGH)), to study species belonging to the myrmecophagous (ant/termite eating) mammalian orders/superorders (Pholidota, Tubulidentata, Carnivora, and Xenarthra), as a model for other applications in mammalian systematics and conservation biology. In this study, CGH was applied to high-quality metaphase spreads of pangolin (Pholidota), using probes of sloth and canine (Xenarthra and Carnivora, respectively) genomic DNA labeled with different fluorophores, thereby facilitating analysis of the visible color spectrum on pangolin karyotypes. Our results posited that pholidotes are closer to carnivores than to xenarthrans, which confirmed the current consensus that myrmecophagy in these mammalian lineages was more likely because of homoplasy (convergent evolution) than being an ancestral character.

Spike count reliability and the Poisson hypothesis.

The variability of cortical activity in response to repeated presentations of a stimulus has been an area of controversy in the ongoing debate regarding the evidence for fine temporal structure in nervous system activity. We present a new statistical technique for assessing the significance of observed variability in the neural spike counts with respect to a minimal Poisson hypothesis, which avoids the conventional but troubling assumption that the spiking process is identically distributed across trials. We apply the method to recordings of inferotemporal cortical neurons of primates presented with complex visual stimuli.