Precise individual muscle segmentation in whole thigh CT scans for sarcopenia assessment using U-net transformer.

The study aims to develop a deep learning based automatic segmentation approach using the UNETR(U-net Transformer) architecture to quantify the volume of individual thigh muscles(27 muscles in 5 groups) for Sarcopenia assessment. By automating the segmentation process, this approach improves the efficiency and accuracy of muscle volume calculation, facilitating a comprehensive understanding of muscle composition and its relationship to Sarcopenia. The study utilized a dataset of 72 whole thigh CT scans from hip fracture patients, annotated by two radiologists. The UNETR model was trained to perform precise voxel-level segmentation and various metrics such as dice score, average symmetric surface distance, volume correlation, relative absolute volume difference and Hausdorff distance were employed to evaluate the model's performance. Additionally, the correlation between Sarcopenia and individual thigh muscle volumes was examined. The proposed model demonstrated superior segmentation performance compared to the baseline model, achieving higher dice scores (DC = 0.84) and lower average symmetric surface distances (ASSD = 1.4191 ± 0.91). The volume correlation between Sarcopenia and individual thigh muscles in the male group. Furthermore, the correlation analysis of grouped thigh muscles also showed negative associations with Sarcopenia in the male participants. This thesis presents a deep learning based automatic segmentation approach for quantifying individual thigh muscle volume in sarcopenia assessment. The results highlights the associations between Sarcopenia and specific individual muscles as well as grouped thigh muscle regions, particularly in males. The proposed method improves the efficiency and accuracy of muscle volume calculation, contributing to a comprehensive evaluation of Sarcopenia. This research enhances our understanding of muscle composition and performance, providing valuable insights for effective interventions in Sarcopenia management.

Gaps in U.S. Public Health Monitoring and Surveillance Systems in Puerto Rico.

INTRODUCTION: Puerto Rico (PR) has an ambiguous status within Centers for Disease Control and Prevention (CDC) public health monitoring and surveillance systems. However, as a U.S. territory, PR relies on federal health resource allocation processes that are informed by these data sources. This study sought to quantify the coverage of PR within CDC-supported systems compared with the 50 states, describe coverage across critical system-types, and assess the availability of data collection instruments in Spanish. METHODS: This cross-sectional observational study employed the method of data curation by identifying, collecting, and categorizing data primarily from web-based sources maintained by the CDC. Data were originally collected and coded from August 2021 to March 2022 and reviewed by two additional coders from October 2022 to March 2023. Each curated system was assessed to determine coverage of PR across five system-types (probability-based, case-based, administrative, registry, and multiple-source) compared with the 50 states. The availability of data collection instruments in Spanish was also assessed. RESULTS: Of 93 active CDC-supported systems assessed, results revealed that PR was not covered in 54% of CDC-supported systems. Comparatively, inclusive coverage of all 50 states was only lacking in 33% of CDC-supported systems. Of the 32 CDC-supported systems in PR that could be coded for language, only 53% had data collection instruments in Spanish. CONCLUSIONS: There are significant gaps in the coverage of PR within CDC-supported systems. Future efforts must be made to identify the reasons for this exclusion and increase the territory's representation within these essential public health data systems.

Analysis of microplastics in various foods and assessment of aggregate human exposure via food consumption in korea.

Evidence of microplastics in humans has recently been demonstrated. The primary route of human exposure to microplastics is consumption of contaminated food and water. However, quantitative estimations of exposure to microplastics are limited, which hinders human health risk assessments. In this study, abundances of microplastics were measured in eight food types, comprising 90 products of table salts, soy sauces, fish sauces, salted seafood, seaweed, honey, beer, and beverage. Aggregate human exposure to microplastics via food consumption was assessed based on the number and mass of microplastics, using deterministic calculations and Monte Carlo simulations. The determinations revealed that average adult Koreans likely ingest 1.4 × 10-4 and 3.1 × 10-4 g of microplastics per week, respectively. These results are orders of magnitude smaller than earlier estimates of 0.1-5 g of microplastics per week that likely chose experimental outliers. Therefore, careful selection of literature data and estimation methods is needed to provide more realistic exposure estimations from microplastic counts. This study extends our understanding of MP occurrence in food and provides a more thorough estimate of aggregate microplastic exposure via food consumption.

Factors Affecting Emergency Medical Utilization After Self-harm and Effectiveness of Community-Based Suicide Prevention Provisions in Preventing Self-harm: A Nationwide Registry-Based Study in Korea.

In order to formulate and implement a community-based suicide prevention program, as well as evaluate the effectiveness of these programs, it is necessary to understand the epidemiological characteristics of self-harm. Clinical data were collected from the National Emergency Department Information System (NEDIS) data panel in Korea for patients seen after self-harm episodes. Socioeconomic factors were collected from Statistics Korea. Variables representing SP provisions (SPPs) were collected from the Korea Foundation for Suicide Prevention. Increasing the number of mental health providers resulted in lower annual emergency department visit rate after self-harm (VRSH) in the entire population, as well as in both the young and elderly populations. An increase in the mental health budget led to a significant reduction in VRSHs. However, the number of suicide prevention centers did not have any significant association with the VRSH. This study also provides substantial evidence that community-based SPPs are effective in preventing self-harm.

PEGylated Gold Nanoparticle Toxicity in Cardiomyocytes: Assessment of Size, Concentration, and Time Dependency.

Gold Nanoparticles (GNPs) have shown promising capabilities for use in many in-vivo applications such as gene and drug delivery, photothermal ablation of tumors, and tracking in many imaging modalities. Yet GNPs have thus far had limited use in cardiovascular medicine. Polyethylene glycol functionalized (PEGylated) GNPs have been extensively studied in a wide array of in vitro and in vivo models with results showing no apparent toxicity, but to our knowledge an investigation has never been performed to determine direct cardiomyocyte toxicity. In this study, we assessed if PEGylated GNPs exhibited direct toxicity to a primary culture of neonatal rat cardiomyocytes in order to establish PEGylated GNPs for potential future use in cardiovascular medicine applications. We present novel results that demonstrate both a particle size and concentration dependent relationship on cell viability. Cell viability was found to be significantly enhanced for many concentrations and sizes as compared to the control and increased linearly as a function of particle diameter. Additionally, viability increased in a parabolically dependent manner as a function of decreasing particle concentration. These new results could advance understanding of nanoparticle-cell interactions and lead to the development of new applications involving the use of gold nanoparticles in cardiovascular medicine.

A NOVEL METHOD FOR ESTIMATING PATIENT-SPECIFIC PRIMARY DOSE IN CONE-BEAM COMPUTED TOMOGRAPHY.

For the purpose of real-time scan-protocol optimisation and patient-specific dose management in cone-beam computed tomography, we introduce a numerical algorithm that estimates the primary dose distributions in reconstructed images. The proposed algorithm is based on the ray-tracing technique and utilises reconstructed voxel data and scanning protocol. The algorithm is validated with the Monte Carlo (MC) and conventional model-based dose reconstruction methods for the simple cylindrical water and anthropomorphic head phantoms. The algorithm shows good agreement with both methods in terms of the zeroth-order x-ray interactions, which exclude the higher-order x-ray interactions at sites distant from the first interactions, and it consumes a significantly lower computational cost compared with the MC method. The differences between the proposed algorithm and the model-based dose reconstruction method as well as the improvement strategies of the algorithm are discussed in detail.

MONTE CARLO DOSE ASSESSMENT IN DENTAL CONE-BEAM COMPUTED TOMOGRAPHY.

Most dental cone-beam computed tomography (CBCT) uses an x-ray beam field covering the maxillomandibular region and the width-truncated detector geometry. The spatial dose distribution in dental CBCT is analyzed in terms of local primary and remote secondary doses by using a list-mode analysis of x-ray interactions obtained from the Monte Carlo simulations. The patient-dose benefit due to the width-truncated detector geometry is also investigated for a wide range of detector offsets. The developed dose estimation agrees with the measurement in a relative error of 7.7%. The secondary dose outside of the irradiation field becomes larger with increasing tube voltage. The dose benefit with the width-truncated geometry linearly increases as the detector-offset width is decreased. Leaving the CT image quality out of the account, the MC results reveal that the operation of dental CBCT with a lower tube voltage and a smaller detector-offset width is beneficial to the patient dose.

Simple and economical biosensors for distinguishing Agrobacterium-mediated plant galls from nematode-mediated root knots.

Agrobacterium-mediated plant galls are often misdiagnosed as nematode-mediated knots, even by experts, because the gall symptoms in both conditions are very similar. In the present study, we developed biosensor strains based on agrobacterial opine metabolism that easily and simply diagnoses Agrobacterium-induced root galls. Our biosensor consists of Agrobacterium mannitol (ABM) agar medium, X-gal, and a biosensor. The working principle of the biosensor is that exogenous nopaline produced by plant root galls binds to NocR, resulting in NocR/nopaline complexes that bind to the promoter of the nopaline oxidase gene (nox) operon and activate the transcription of noxB-lacZY, resulting in readily visualized blue pigmentation on ABM agar medium supplemented with X-gal (ABMX-gal). Similarly, exogenous octopine binds to OccR, resulting in OoxR/octopine complexes that bind to the promoter of the octopine oxidase gene (oox) operon and activate the transcription of ooxB-lacZY, resulting in blue pigmentation in the presence of X-gal. Our biosensor is successfully senses opines produced by Agrobacterium-infected plant galls, and can be applied to easily distinguish Agrobacterium crown gall disease from nematode disease.

A simple and sensitive biosensor strain for detecting toxoflavin using ß-galactosidase activity.

In this study, we developed a simple and sensitive biosensor for the determination of toxoflavin (which is toxic to various plants, fungi, animals, and bacteria) in natural samples based on ß-galactosidase activity. The proposed toxoflavin detection method for toxin-producing bacteria or toxin-contaminated foods is simple and cost effective. Burkholderia glumae, a species known to cause rice grain rot and wilt in various field crops, produces toxoflavin under the control of a LysR-type transcriptional regulator ToxR and its ligand toxoflavin. As the expression of toxoflavin biosynthetic genes requires toxoflavin as a co-activator of ToxR, a novel biosensor stain was constructed based on lacZ reporter gene integration into the first gene of the toxoflavin biosynthesis operon, toxABCDE of B. glumae. The biosensor was composed of a sensor strain (COK71), substrates (X-gal or ONPG), and culture medium, without any complex preparation process. We demonstrated that the biosensor strain is highly specific to toxoflavin, and can quantify relative amounts of toxoflavin compared with known concentrations of toxoflavin. The proposed method was reliable and simple; samples containing 50-500 nM of toxoflavin could be analyzed. More importantly, the proposed biosensor strain could identify toxoflavin-producing bacteria in real samples. The excellent performance of this biosensor is useful for diagnostic purposes, such as detecting toxoflavin-contaminated foods and environmental samples.