Estimating Uncertainty of Geographic Atrophy Segmentations with Bayesian Deep Learning.

Purpose: To apply methods for quantifying uncertainty of deep learning segmentation of geographic atrophy (GA). Design: Retrospective analysis of OCT images and model comparison. Participants: One hundred twenty-six eyes from 87 participants with GA in the SWAGGER cohort of the Nonexudative Age-Related Macular Degeneration Imaged with Swept-Source OCT (SS-OCT) study. Methods: The manual segmentations of GA lesions were conducted on structural subretinal pigment epithelium en face images from the SS-OCT images. Models were developed for 2 approximate Bayesian deep learning techniques, Monte Carlo dropout and ensemble, to assess the uncertainty of GA semantic segmentation and compared to a traditional deep learning model. Main Outcome Measures: Model performance (Dice score) was compared. Uncertainty was calculated using the formula for Shannon Entropy. Results: The output of both Bayesian technique models showed a greater number of pixels with high entropy than the standard model. Dice scores for the Monte Carlo dropout method (0.90, 95% confidence interval 0.87-0.93) and the ensemble method (0.88, 95% confidence interval 0.85-0.91) were significantly higher (P < 0.001) than for the traditional model (0.82, 95% confidence interval 0.78-0.86). Conclusions: Quantifying the uncertainty in a prediction of GA may improve trustworthiness of the models and aid clinicians in decision-making. The Bayesian deep learning techniques generated pixel-wise estimates of model uncertainty for segmentation, while also improving model performance compared with traditionally trained deep learning models. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Retinal vascular changes after Silicon Oil removal in the Eye with Rhegmatogenous Retinal detachment.

BACKGROUND: This study aims to examine vessel density changes in the optic nerve and macula following silicone oil removal (SOR) surgery in eyes with rhegmatogenous retinal detachment (RRD) at different time points by Optical Coherence Tomography Angiography (OCTA) in compared to the contralateral eye. METHODS: A total of 43 eyes from 43 patients with silicone oil in their eyes for 3-9 months underwent OCT-A using AngioVue and optic disc-associated vessel density (VD) and thickness, macular-associated VD and thickness, Foveal avascular zone (FAZ) area, FAZ perimeter (PERIM), Acircularity index (AI), vessel density within a 300 µm wide region of the FAZ were compared between eyes. OCTA scans were performed one week before SOR and one month and three months after SOR. RESULTS: The mean age of participants was 52.8 years (SD = 15.85) and a median visual acuity was 0.8 (range: 0.5-1.0). Notably, male participants constituted 67.4% of the sample. The preoperative mean value BCVA (logMAR) of patients was 0.73, and 3 months post-oil removal was 0.7727. Regarding optic disc parameters, RNFL thickness and vessel density (VD) measurements Peripapillary, whole disc, inside disc, and Disc Angio (superior, Nasal, inferior, temporal) did not change. In analyzing macular thickness parameters, all of them (Whole and Fovea, parafoveal, and Perifovea) remained unchanged. Examining macular vessel density parameters revealed no significant changes across superficial and deep retinal layers. Finally, the comparison of the foveal avascular zone (FAZ) area and flow density (FD) parameters demonstrated consistent measurements with non-significant alterations observed in FAZ size (p = 0.6) and FD values (p = 0.49) over the monitored duration. CONCLUSION: There was no change in peripapillary VD and macular vessel density of the superficial capillary plexus (SCP) and deep capillary plexus (DCP) after silicone oil removal. FAZ and full retinal thickness  remained stable 3 month after SOR.  Clinical trial number: Not applicable.

The Interplay between Mitochondrial Metabolism and Nasal Mucociliary Function as a Surrogate Method to Diagnose Thyroid Dysfunction: Insights from a Population-Based Study.

Aim and Background. This study aims to explore alternative diagnostic methods to assess thyroid function in patients unable to undergo blood tests for thyroid-stimulating hormones (TSH) and thyroxine (T4), such as individuals with trypanophobia, severe medical conditions, or coagulopathy. Considering the impact of thyroid dysfunction on mitochondrial metabolism and the essential role of proper mitochondrial function in ciliary motility, we postulate that assessing nasal ciliary function could serve as a surrogate diagnostic approach for thyroid dysfunction. Methods. This cross-sectional study was performed on individuals with no history of thyroid diseases. The primary endpoint was the diagnostic value of the nasal mucociliary (NMC) test using Iranica Picris (Asteraceae) aqueous extract in differentiating hypo- or hyperthyroidism cases from euthyroid cases. Results. 232 individuals were recruited (71% females, 86% euthyroid). Receiver operating characteristic (ROC) analysis showed a good diagnostic value for the NMC test in differentiating overt hypothyroidism (area under the ROC curve [AUROC] = 0.82, p = 0.004) and its fair value in diagnosing subclinical hyperthyroidism (AUROC = 0.78, p = 0.01) from the euthyroid condition. The NMC test had a significant positive correlation with TSH (r = 0.47, p < 0.001) and a significant negative correlation with T4 (r = -0.32, p < 0.001). The NMC rate was significantly different in distinct thyroid function groups (p < 0.001). Compared with euthyroid cases, the post-hoc analysis showed that the NMC test is significantly higher in overt hypothyroidism (15.06 vs. 21.07 min, p = 0.003) and significantly lower in subclinical hyperthyroidism (15.05 vs. 10.9 min, p = 0.02). Conclusions. The Iranica Picris-based NMC test might serve as a diagnostic method to distinguish overt hypothyroidism and subclinical hyperthyroidism.

Structure-aware deep learning model for peptide toxicity prediction.

Antimicrobial resistance is a critical public health concern, necessitating the exploration of alternative treatments. While antimicrobial peptides (AMPs) show promise, assessing their toxicity using traditional wet lab methods is both time-consuming and costly. We introduce tAMPer, a novel multi-modal deep learning model designed to predict peptide toxicity by integrating the underlying amino acid sequence composition and the three-dimensional structure of peptides. tAMPer adopts a graph-based representation for peptides, encoding ColabFold-predicted structures, where nodes represent amino acids and edges represent spatial interactions. Structural features are extracted using graph neural networks, and recurrent neural networks capture sequential dependencies. tAMPer's performance was assessed on a publicly available protein toxicity benchmark and an AMP hemolysis data we generated. On the latter, tAMPer achieves an F1-score of 68.7%, outperforming the second-best method by 23.4%. On the protein benchmark, tAMPer exhibited an improvement of over 3.0% in the F1-score compared to current state-of-the-art methods. We anticipate tAMPer to accelerate AMP discovery and development by reducing the reliance on laborious toxicity screening experiments.

Simple and rapid determination of tartrazine in fake saffron using the metal organic framework (Fe SA MOF@CNF) by HPLC/PDA.

The present study of a novel metal-organic framework containing Fe single atoms doped on electrospun carbon nanofibers (Fe SA-MOF@CNF) based on dispersive micro solid phase extraction (D-µ-SPE) using HPLC-PDA for detection tartrazine in fake saffron samples was designed. The Fe SA-MOF@CNF sorbent was extensively characterized through various techniques including N2 adsorption-desorption isotherms, X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy. The specific area of surface of the sorbent was 577.384 m2/g. The study variables were optimized via the central composite design (CCD), which included a sorbent mass of 15 mg, a contact time of 6 min, a pH of 7.56, and a tartrazine concentration of 300 ng/ml. Under the optimum condition, the calibration curve of this method was linear in the range of 5-1000 ng/mL, with a correlation coefficient of 0.992. The LOD and LOQ values were ranged 0.38-0.74 and 1.34-2.42 ng/ml, respectively. This approach revealed significant improvements, including high extraction recovery (98.64), recovery rates (98.43-102.72%), and accuracy (RSDs < 0.75 to 3.6%). the enrichment factors were obtained in the range of 80.6-86.4 with preconcentration factor of 22.3. Consequently, the D-µ-SPE method based on synthesized Fe SA-MOF@CNF could be recommended as a sustainable sorbent for detecting tartrazine in saffron samples.

An imprint-based approach to replicate nano- to microscale roughness on gelatin hydrogel scaffolds: surface characterization and effect on endothelialization.

Biologization of biomaterials with endothelial cells (ECs) is an important step in vascular tissue engineering, aiming at improving hemocompatibility and diminishing the thrombo-inflammatory response of implants. Since subcellular topography in the scale of nano to micrometers can influence cellular adhesion, proliferation, and differentiation, we here investigate the effect of surface roughness on the endothelialization of gelatin hydrogel scaffolds. Considering the micron and sub-micron features of the different native tissues underlying the endothelium in the body, we carried out a biomimetic approach to replicate the surface roughness of tissues and analyzed how this impacted the adhesion and proliferation of human umbilical endothelial cells (HUVECs). Using an imprinting technique, nano and micro-roughness ranging from Sa= 402 nm to Sa= 8 µm were replicated on the surface of gelatin hydrogels. Fluorescent imaging of HUVECs on consecutive days after seeding revealed that microscale topographies negatively affect cell spreading and proliferation. By contrast, nanoscale roughnesses of Sa= 402 and Sa= 538 nm promoted endothelialization as evidenced by the formation of confluent cell monolayers with prominent VE-cadherin surface expression. Collectively, we present an affordable and flexible imprinting method to replicate surface characteristics of tissues on hydrogels and demonstrate how nanoscale roughness positively supports their endothelialization.

A novel therapeutic strategy: the significance of exosomal miRNAs in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a fast-growing blood cancer that interferes with the normal growth of blood cells in the bone marrow and blood. It is characterized by its unpredictable outlook and high death rate. The main treatment for AML is chemotherapy, but this often results in drug resistance and the possibility of the disease returning. For this reason, new biomarkers are necessary to diagnose, predict, and treat this disease. Research has demonstrated that cells responsible for AML release exosomes that interact with the disease's microenvironment. These exosomes have significant roles in promoting leukemia growth, suppressing normal hematopoiesis, facilitating angiogenesis, and contributing to drug resistance in AML. Further investigations have shown that these exosomes contain miRNAs, which are transferred to target cells and have functional roles. Biomarkers are utilized to assess various aspects of tumor cell behavior, including proliferation, apoptosis, angiogenesis, changes in the microenvironment, transfer of drug resistance, and stability in serum and blood plasma. In this research, we showed that exosomal miRNAs and exosomes have the potential to be used as indicators for detecting various phases of AML and can aid in its medical treatment. Furthermore, they can be specifically targeted for therapeutic purposes in addressing this condition.

Understanding the lncRNA/miRNA-NFκB regulatory network in diabetes mellitus: From function to clinical translation.

Diabetes mellitus (DM) and its significant ramifications make out one of the primary reasons behind morbidity worldwide. Noncoding RNAs (ncRNAs), such as microRNAs and long noncoding RNAs, are involved in regulating manifold biological processes, including diabetes initiation and progression. One of the established pathways attributed to DM development is NF-κB signaling. Neurons, ß cells, adipocytes, and hepatocytes are among the metabolic tissues where NF-κB is known to produce a range of inflammatory chemokines and cytokines. The direct or indirect role of ncRNAs such as lncRNAs and miRNAs on the NF-κB signaling pathway and DM development has been supported by many studies. As a result, effective diabetes treatment and preventive methods will benefit from a comprehensive examination of the interplay between NF-κB and ncRNAs. Herein, we provide a concise overview of the role of NF-κB-mediated signaling pathways in diabetes mellitus and its consequences. The reciprocal regulation of ncRNAs and the NF-κB signaling pathway in diabetes is then discussed, shedding light on the pathogenesis of the illness and its possible therapeutic interventions.

Investigation into the effects of hydrophobicity on thermohydraulic characteristics and entropy generation of hybrid nanofluid with the magnetic property in a micro-heat sink under a magnetic field.

The cooling of devices is a big challenge in the electronics industry, and most process units (graphical are central process units) experience defects under harsh temperature conditions, so dissipating generated heat under various working conditions should be studied seriously. This study investigates the magnetohydrodynamics of hybrid ferro-nanofluids in the presence of hydrophobic surfaces in a micro-heat sink. To scrutinize this study, a finite volume method (FVM) is applied. The ferro-nanofluid includes water as a base fluid and multiwall carbon nanotubes (MWCNTs) and Fe3O4as nanoadditives, which are used in three concentrations (0, 1, and 3%). Other parameters such as the Reynolds number (5-120), Hartmann number (magnitude of the magnetic field from 0 to 6), and hydrophobicity of surfaces are scrutinized for their impacts on heat transfer and hydraulic variables as well as entropy generation variables. The outcomes indicate that increasing the level of hydrophobicity in surfaces leads simultaneously to improved heat exchange and reduced pressure drop. Likewise, it decreases the frictional and thermal types of entropy generation. Intensifying the magnitude of the magnetic field enhances the heat exchange as much as the pressure drop. It can also decrease the thermal term in entropy generation equations for the fluid, but increase the frictional entropy generation and adds a new term, magnetic entropy generation. Incrementing the Reynolds number improves the convection heat transfer parameters, although it intensifies the pressure drop in the length of the channel. Also, the thermal entropy generation and frictional entropy generation decrease and increase with an increasing flow rate (Reynolds number).

Recent advances in pre-conditioned mesenchymal stem/stromal cell (MSCs) therapy in organ failure; a comprehensive review of preclinical studies.

Mesenchymal stem/stromal cells (MSCs)-based therapy brings the reassuring capability to regenerative medicine through their self-renewal and multilineage potency. Also, they secret a diversity of mediators, which are complicated in moderation of deregulated immune responses, and yielding angiogenesis in vivo. Nonetheless, MSCs may lose biological performance after procurement and prolonged expansion in vitro. Also, following transplantation and migration to target tissue, they encounter a harsh milieu accompanied by death signals because of the lack of proper tensegrity structure between the cells and matrix. Accordingly, pre-conditioning of MSCs is strongly suggested to upgrade their performances in vivo, leading to more favored transplantation efficacy in regenerative medicine. Indeed, MSCs ex vivo pre-conditioning by hypoxia, inflammatory stimulus, or other factors/conditions may stimulate their survival, proliferation, migration, exosome secretion, and pro-angiogenic and anti-inflammatory characteristics in vivo. In this review, we deliver an overview of the pre-conditioning methods that are considered a strategy for improving the therapeutic efficacy of MSCs in organ failures, in particular, renal, heart, lung, and liver.

DDCNet: Deep Dilated Convolutional Neural Network for Dense Prediction.

Dense pixel matching problems such as optical flow and disparity estimation are among the most challenging tasks in computer vision. Recently, several deep learning methods designed for these problems have been successful. A sufficiently larger effective receptive field (ERF) and a higher resolution of spatial features within a network are essential for providing higher-resolution dense estimates. In this work, we present a systemic approach to design network architectures that can provide a larger receptive field while maintaining a higher spatial feature resolution. To achieve a larger ERF, we utilized dilated convolutional layers. By aggressively increasing dilation rates in the deeper layers, we were able to achieve a sufficiently larger ERF with a significantly fewer number of trainable parameters. We used optical flow estimation problem as the primary benchmark to illustrate our network design strategy. The benchmark results (Sintel, KITTI, and Middlebury) indicate that our compact networks can achieve comparable performance in the class of lightweight networks.

Dense optic nerve head deformation estimated using CNN as a structural biomarker of glaucoma progression.

PURPOSE: To present a new structural biomarker for detecting glaucoma progression based on structural transformation of the optic nerve head (ONH) region over time. METHODS: Dense ONH deformation was estimated using deep learning methods namely DDCNet-Multires, FlowNet2, and FlowNetCorrelation, and legacy computational methods namely the topographic change analysis (TCA) and proper orthogonal decomposition (POD) methods. A candidate biomarker was estimated as the average magnitude of deformation of the ONH and evaluated using longitudinal confocal scans of 12 laser treated and 12 contralateral normal eyes of 12 primates from the LSU Experimental Glaucoma Study (LEGS); and 36 progressing eyes and 21 longitudinal normal eyes from the UCSD Diagnostic Innovations in Glaucoma Study (DIGS). Area under the ROC curve (AUC) was used to assess the diagnostic accuracy of the biomarker. RESULTS: AUROC (95% CI) for LEGS were: 0.83 (0.79, 0.88) for DDCNet-Multires; 0.83 (0.78, 0.88) for FlowNet2; 0.83 (0.78, 0.88) for FlowNet-Correlation; 0.94 (0.91, 0.97) for POD; and 0.86 (0.82, 0.91) for TCA methods. For DIGS: 0.89 (0.80, 0.97) for DDCNet-Multires; 0.82 (0.71, 0.93) for FlowNet2; 0.93 (0.86, 0.99) for FlowNet-Correlation; 0.86 (0.76, 0.96) for POD; and 0.86 (0.77, 0.95) for TCA methods. Lower diagnostic accuracy of the learning-based methods for LEG study eyes were due to image alignment errors in confocal sequences. CONCLUSION: Deep learning methods trained to estimate generic deformation were able to estimate ONH deformation from image sequences and provided a higher diagnostic accuracy. Our validation of the biomarker using ONH sequences from controlled experimental conditions confirms the diagnostic accuracy of the biomarkers observed in the clinical population. Performance can be further improved by fine-tuning these networks using ONH sequences.

Effect of gravity on the spreading of a droplet deposited by liquid needle deposition technique.

This study represents an experimental investigation, complemented with a mathematical model, to decipher the effect of gravity on the spreading dynamics of a water droplet. For the theoretical discussion, an overall energy balance approach is adopted to explain the droplet spreading under both microgravity (µg) and terrestrial gravity condition. Besides explaining the mechanism of the droplet spreading under microgravity condition achieved during the parabolic flight, a technique with a detailed experimental set-up has also been developed for the successful deposition of droplet. A rational understanding is formulated through experimental investigation and theoretical analysis, which allows us to distinguish the transient variation of the spreading of a droplet, between microgravity and terrestrial gravity condition. The spreading of the droplet is predicted by the non-linear overall energy balance equation, which accounts for the operating parameters in the form of non-dimensional groups like Reynolds number ([Formula: see text]), Weber number (We) and Bond number (Bo). To distinctly identify the difference in the drop spreading at terrestrial and microgravity conditions, the Bo with transient gravitational field obtained through the on-board accelerometer is considered. The obtained theoretical results are further corroborated by experimental results which are obtained from the parabolic flight.

Evaluation of the periodontal disease on oral microorganisms during pregnancy: A systematic review and meta-analysis.

Background and Aim: In the present study, the potential changes of oral microbes during pregnancy were investigated by examining the findings of the previous studies and comprehensively examining their results. The relationship between oral microorganisms and birth outcomes and adverse labor outcomes was investigated; to provide sufficient evidence. The purpose of the present study was to evaluate periodontal disease in oral microorganisms during pregnancy. Materials and Methods: All articles were published between January 2011 and January 2023 in international databases, including PubMed, Scopus, Science Direct, and Embase. To answer the research questions, the Google Scholar search engine employed the PECO strategy. STATA.V17 software was used to analyze the data. Results: Two hundred and eighteen studies were found in the initial search; 63 full texts were reviewed; and finally, 14 articles were included in the analysis. The mean differences in salivary S. mutans carriage before and after prenatal dental treatment were 0.92 (MD; 95 CI [0.57, 1.27], P > 0.05). The odds ratio of association between perinatal mortality and periodontal treatment was -0.88 (OR; 95 CI [-2.53, 0.76], P > 0.05) and the odds ratio of association between pre-term birth and periodontal treatment was -0.31 (OR; 95 CI [-0.70, 0.09], P > 0.05). There was a statistically significant relationship between birth weight and periodontal treatment during pregnancy. Conclusion: According to the present meta-analysis, periodontal treatment can reduce the odds ratio of perinatal mortality and pre-term birth by 88% and 31%, respectively. High association of microorganisms between pregnancy and postpartum requires further study. Relevance for Patients: In the findings of the present study, it is observed that during pregnancy, there is a direct relationship between periodontal disease with low birth weight, perinatal mortality, and pre-term delivery; however, the high association of microorganisms between pregnancy and postpartum requires further study. Oral microforms are reported to be affected in pregnant women, and they should take extra care of their mouth and teeth. Sufficient and strong evidence can help to improve the health outcomes of mothers and children.

Early Vitrectomy: An Effective Treatment for Acute Postcataract Surgery Endophthalmitis.

Background: Endophthalmitis is a rare but a high morbid complication after cataract surgery, and a gold standard treatment is not recommended yet. In this study, we aim to evaluate the effect of early vitrectomy on the visual acuity of patients with postcataract endophthalmitis. Materials and Methods: This study was a single-arm clinical trial on 27 patients with postcataract surgery endophthalmitis. Early vitrectomy was the intervention. Visual acuity as the primary outcome was evaluated and compared at baseline, at discharge, and 1 and 3 months after the intervention. Results: From 27 patients who included in our study, six patients gain favorable visual acuity of 5/10 and above (success rate = 22%), and four of them have no improvement in their visual acuity. Retinal detachment was reported as a complication in just one case. Negative culture was a predictor for success in terms of visual acuity after the surgery. All patients who gain favorable results, presented in the first 15 days after the cataract surgery. Conclusion: The result of our study showed that, considering complete, early vitrectomy for the treatment of postcataract surgery endophthalmitis, especially for those who presented in the first 15 days of cataract surgery and for those who have negative culture is promising.

Fabrication of a microfluidic device for probiotic drug's dosage screening: Precision Medicine for Breast Cancer Treatment.

Breast cancer is the most common cancer in women; it has been affecting the lives of millions each year globally and microfluidic devices seem to be a promising method for the future advancements in this field. This research uses a dynamic cell culture condition in a microfluidic concentration gradient device, helping us to assess breast anticancer activities of probiotic strains against MCF-7 cells. It has been shown that MCF-7 cells could grow and proliferate for at least 24 h; however, a specific concentration of probiotic supernatant could induce more cell death signaling population after 48 h. One of our key findings was that our evaluated optimum dose (7.8 mg/L) was less than the conventional static cell culture treatment dose (12 mg/L). To determine the most effective dose over time and the percentage of apoptosis versus necrosis, flowcytometric assessment was performed. Exposing the MCF-7 cells to probiotic supernatant after 6, 24 and 48 h, confirmed that the apoptotic and necrotic cell death signaling were concentration and time dependent. We have shown a case that these types of microfluidics platforms performing dynamic cell culture could be beneficial in personalized medicine and cancer therapy.

Digital evaluation of dental bleaching using a new methodology: an in vivo study.

OBJECTIVE: The objective of the present study was to assess the progress and efficiency of at-home bleaching protocols with 10% carbamide peroxide using a new methodology based on dental photography. MATERIALS AND METHODS: A 4-week overnight at-home bleaching protocol using whitening trays and 10% carbamide peroxide was performed on 52 patients. The tooth color was analyzed using standardized photographs taken every week for 4 weeks and at 4 months posttreatment. The values of the color evolution (ΔE00), L*, a*, and b* were also measured and used to assess the evolution of the chroma, luminosity, and hue using the CIEDE2000 formula. The statistical analyses were conducted at a significance level of P < 0.05 by means of a repeated measures analysis of variance (ANOVA). RESULTS: The tooth color changed the most, and thus the highest ΔE00 was observed, after the first week of treatment. The color continued to change but to a lesser degree during the following weeks. After 4 weeks, the treatment proved to be very effective. Four months after the end of treatment, a color relapse was observed, though it was hardly perceptible to the human eye. The luminosity (L') changed significantly between the beginning and the end of treatment, affecting the maxilla to a greater extent. The chroma evolution showed a high variance and a low relapse for both jaws. The hue was not affected significantly during the treatment and the stabilization. CONCLUSIONS: Within the limitations of the present study, the authors were able to assess the progress and efficiency of at-home bleaching with 10% carbamide peroxide in terms of chroma, luminosity, and hue using a new methodology based on dental photography. CLINICAL SIGNIFICANCE: This new method is effective and enables a reliable analysis of the evolution of a dental bleaching treatment, turning dental photo-graphy into an even more powerful tool for analysis and communication. It can also be used as a proof-of-concept, paving the way for further research on objective monitoring and evaluation of dental treatments using dental photography.

MicroRNA-125a-3p, -4530, and -92a as a Potential Circulating MicroRNA Panel for Noninvasive Pancreatic Cancer Diagnosis.

MicroRNA (miRNA) expression dysregulations in pancreatic ductal adenocarcinoma (PDAC) have been studied widely for their diagnostic and prognostic utility. By the use of bioinformatics-based methods, in our previous study, we identified some potential miRNA panels for diagnosis of pancreatic cancer patients from noncancerous controls (the screening stage). In this report, we used 142 plasma samples from people with and without pancreatic cancer (PC) to conduct RT-qPCR differential expression analysis to assess the strength of the first previously proposed diagnostic panel (consisting of miR-125a-3p, miR-4530, and miR-92a-2-5p). As the result, we identified significant upregulation for all the three considered miRNAs in the serum of PC patients. After that, a three-miRNA panel in serum was developed. The area under the receiver operating characteristic curves (AUC) for the panel were 0.850, 0.910, and 0.86, respectively, indicating that it had a higher diagnostic value than individual miRNAs. Therefore, we detected a promising three-miRNA panel in the plasma for noninvasive PC diagnosis (miR-125a-3p, miR-4530, and miR-92a-2-5p).

SARS-CoV-2-associated gut microbiome alteration; A new contributor to colorectal cancer pathogenesis.

The emergence of a novel coronavirus, COVID-19, in December 2019 led to a global pandemic with more than 170 million confirmed infections and more than 6 million deaths (by July 2022). Studies have shown that infection with SARS-CoV-2 in cancer patients has a higher mortality rate than in people without cancer. Here, we have reviewed the evidence showing that gut microbiota plays an important role in health and is linked to colorectal cancer development. Studies have shown that SARS-CoV-2 infection leads to a change in gut microbiota, which modify intestinal inflammation and barrier permeability and affects tumor-suppressor or oncogene genes, proposing SARS-CoV-2 as a potential contributor to CRC pathogenesis.

Quantitative Echocardiography Improves Resident Assessment of Left Ventricular Systolic Function.

Background: The use of echocardiography to assess left ventricular ejection fraction (LVEF) is an important component of anesthesiology resident education; however, there is no consensus on the most effective method for teaching this skill set. This study investigates the impact and feasibility of teaching a quantitative LVEF assessment method to anesthesiology residents, compared with teaching visual estimation techniques. Methods: We included all anesthesiology residents rotating through cardiac anesthesia at our institution from August 2020 through March 2021. Participants completed a pretest to assess baseline ability to accurately estimate LVEF. All tests consisted of transthoracic echocardiography images with standard views from 10 patients. Participants were assigned to either a control group that received teaching on visual estimation of LVEF or an intervention group that was taught quantitative LVEF assessment with the Simpson biplane method of discs. After 4 weeks, all participants were administered a postteaching exam. A retention exam was administered an additional 4 weeks later. LVEF accuracy was measured as the absolute difference between their LVEF estimation and the reference value. Results: Control and intervention groups performed similarly on the preteaching exam of LVEF estimation accuracy. Intervention-group residents demonstrated significantly improved accuracy in LVEF assessment on the postteaching exam (3.6% improvement in accuracy, confidence interval [CI], 1.23-5.97; P = .03) compared with the control group (0.60% improvement inaccuracy, CI, -1.77-2.97; P = .62). The observed improvement was not maintained through the retention exam.Conclusions: Addition of quantitative LVEF assessment to traditional teaching of visual LVEF estimation methods significantly improved the diagnostic accuracy of anesthesiology residents' left ventricular systolic function assessment.