Detection of sarcopenia using deep learning-based artificial intelligence body part measure system (AIBMS)

Background: Sarcopenia is an aging syndrome that increases the risks of various adverse outcomes, including falls, fractures, physical disability, and death. Sarcopenia can be diagnosed through medical images-based body part analysis, which requires laborious and time-consuming outlining of irregular contours of abdominal body parts. Therefore, it is critical to develop an efficient computational method for automatically segmenting body parts and predicting diseases.Methods: In this study, we designed an Artificial Intelligence Body Part Measure System (AIBMS) based on deep learning to automate body parts segmentation from abdominal CT scans and quantification of body part areas and volumes. The system was developed using three network models, including SEG-NET, U-NET, and Attention U-NET, and trained on abdominal CT plain scan data.Results: This segmentation model was evaluated using multi-device developmental and independent test datasets and demonstrated a high level of accuracy with over 0.9 DSC score in segment body parts. Based on the characteristics of the three network models, we gave recommendations for the appropriate model selection in various clinical scenarios. We constructed a sarcopenia classification model based on cutoff values (Auto SMI model), which demonstrated high accuracy in predicting sarcopenia with an AUC of 0.874. We used Youden index to optimize the Auto SMI model and found a better threshold of 40.69.Conclusion: We developed an AI system to segment body parts in abdominal CT images and constructed a model based on cutoff value to achieve the prediction of sarcopenia with high accuracy

Evidence of gene-environment interaction for two genes on chromosome 4 and environmental tobacco smoke in controlling the risk of nonsyndromic cleft palate

Nonsyndromic cleft palate (CP) is one of the most common human birth defects and both genetic and environmental risk factors contribute to its etiology. We conducted a genome-wide association study (GWAS) using 550 CP case-parent trios ascertained in an international consortium. Stratified analysis among trios with different ancestries was performed to test for GxE interactions with common maternal exposures using conditional logistic regression models. While no single nucleotide polymorphism (SNP) achieved genome-wide significance when considered alone, markers in SLC2A9 and the neighboring WDR1 on chromosome 4p16.1 gave suggestive evidence of gene-environment interaction with environmental tobacco smoke (ETS) among 259 Asian trios when the models included a term for GxE interaction. Multiple SNPs in these two genes were associated with increased risk of nonsyndromic CP if the mother was exposed to ETS during the peri-conceptual period (3 months prior to conception through the first trimester). When maternal ETS was considered, fifteen of 135 SNPs mapping to SLC2A9 and 9 of 59 SNPs in WDR1 gave P values approaching genome-wide significance (10-6<P<10-4) in a test for GxETS interaction. SNPs rs3733585 and rs12508991 in SLC2A9 yielded P = 2.26×10-7 in a test for GxETS interaction. SNPs rs6820756 and rs7699512 in WDR1 also yielded P = 1.79×10-7 and P = 1.98×10-7 in a 1 df test for GxE interaction. Although further replication studies are critical to confirming these findings, these results illustrate how genetic associations for nonsyndromic CP can be missed if potential GxE interaction is not taken into account, and this study suggest SLC2A9 and WDR1 should be considered as candidate genes for CP. © 2014 Wu et al

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Design and Experiment of Low-Pressure Gas Supply System for Dual Fuel Engine

A low-pressure gas supply system for dual fuel engines was designed to transport liquid natural gas from a storage tank to a dual fuel engine and gasify it during transportation. The heat exchange area and pressure drop in the spiral- wound heat exchanger, the volume of the buffer tank and the pressure drop in the pipeline of the gas supply system were calculated by programming using Python. Experiments were carried out during the proces of starting and running the dual fuel engine using this gas supply system. Experimental data show that the gas supply system can supply gas stably during the process and ensure the stable operation of the dual fuel engine. The effects of the parameters of natural gas and ethylene glycol solution on the heat exchange area of the spiralwound heat exchanger and the volume of the buffer tank in the gas supply system were studied. The results show that the heat exchange area calculated according to pure methane can adapt to the case of non-pure methane. The temperature difference between natural gas and ethylene glycol solution should be increased in order to reduce the heat exchange area. The heat exchange area selected according to the high pressure of natural gas can adapt to the low pressure of natural gas. The volume of the buffer tank should be selected according to the situation of the minimum methane content to adapt to the situation of high methane content. The main influencing factor in selecting the volume of the buffer tank is the natural gas flow. The results can provide guidance for the design of the gas supply system for dual fuel engines

Design and Experiment of Low-Pressure Gas Supply System for Dual Fuel Engine

A low-pressure gas supply system for dual fuel engines was designed to transport liquid natural gas from a storage tank to a dual fuel engine and gasify it during transportation. The heat exchange area and pressure drop in the spiral- wound heat exchanger, the volume of the buffer tank and the pressure drop in the pipeline of the gas supply system were calculated by programming using Python. Experiments were carried out during the process of starting and running the dual fuel engine using this gas supply system. Experimental data show that the gas supply system can supply gas stably during the process and ensure the stable operation of the dual fuel engine. The effects of the parameters of natural gas and ethylene glycol solution on the heat exchange area of the spiral-wound heat exchanger and the volume of the buffer tank in the gas supply system were studied. The results show that the heat exchange area calculated according to pure methane can adapt to the case of non-pure methane. The temperature difference between natural gas and ethylene glycol solution should be increased in order to reduce the heat exchange area. The heat exchange area selected according to the high pressure of natural gas can adapt to the low pressure of natural gas. The volume of the buffer tank should be selected according to the situation of the minimum methane content to adapt to the situation of high methane content. The main influencing factor in selecting the volume of the buffer tank is the natural gas flow. The results can provide guidance for the design of the gas supply system for dual fuel engines