Detection of abnormal extraocular muscles in small datasets of computed tomography images using a three-dimensional variational autoencoder

We sought to establish an unsupervised algorithm with a three-dimensional (3D) variational autoencoder model (VAE) for the detection of abnormal extraocular muscles in small datasets of orbital computed tomography (CT) images. 334 CT images of normal orbits and 96 of abnormal orbits diagnosed as thyroid eye disease were used for training and validation; 24 normal and 11 abnormal orbits were used for the test. A 3D VAE was developed and trained. All images were preprocessed to emphasize extraocular muscles and to suppress background noise (e.g., high signal intensity from bones). The optimal cut-off value was identified through receiver operating characteristic (ROC) curve analysis. The ability of the model to detect muscles of abnormal size was assessed by visualization. The model achieved a sensitivity of 79.2%, specificity of 72.7%, accuracy of 77.1%, F1-score of 0.667, and AUROC of 0.801. Abnormal CT images correctly identified by the model showed differences in the reconstruction of extraocular muscles. The proposed model showed potential to detect abnormalities in extraocular muscles using a small dataset, similar to the diagnostic approach used by physicians. Unsupervised learning could serve as an alternative detection method for medical imaging studies in which annotation is difficult or impossible to perform.

Persistence or regression of prediabetes and coronary artery calcification among adults without diabetes

OBJECTIVE

The effect of changes in glycemic status on subclinical atherosclerosis is uncertain. We assessed the association of persistence, regression, or progression of prediabetes with coronary artery calcium score (CACS) as a measure of subclinical atherosclerosis.

DESIGN

A cross-sectional study, comprising 126 765 adults, and longitudinal sub-study, comprising 40 622 adults (with baseline and at least 1 follow-up computed tomography scan to assess changes in CACS), were undertaken.

METHODS

Changes in glycemic status over 1.5 years (interquartile range, 1.0-2.0) before the first CACS assessment were categorized according to 6 groups: persistent normoglycemia (reference), normoglycemia to prediabetes, normoglycemia to diabetes, prediabetes to normoglycemia, persistent prediabetes, and prediabetes to diabetes. Logistic regression was used to calculate the odds ratios (ORs) and 95% CIs for prevalent coronary artery calcification (CAC). Mixed models with random intercepts and random slopes were used to estimate 5-year CAC progression rates.

RESULTS

Mean (SD) age was 41.3 (7.0) years (74.7% male) (n = 126 765). Multivariable-adjusted OR for prevalent CAC was 1.13 (95% CI, 1.08-1.18) for persistent prediabetes, 1.05 (0.98-1.12) for regression to normoglycemia, and 1.46 (95% CI, 1.27-1.67) for progression from prediabetes to diabetes, compared with persistent normoglycemia. Coronary artery calcification progression increased significantly in all prediabetes groups. Multivariable-adjusted ratio of 5-year CAC progression rates was 1.19 (95% CI, 1.16-1.22) (persistent prediabetes), 1.11 (1.07-1.14) (regression to normoglycemia), and 1.63 (95% CI, 1.26-2.10) (progression from prediabetes to diabetes).

CONCLUSIONS

Unfavorable changes in glycemic status, including persistence of prediabetes or progression to diabetes from prediabetes, were associated with increased risk of CAC.

Initial Experience with Left Bundle Branch Area Pacing in Patients with Atrioventricular Block and Impaired LV Function

Chronic right ventricular (RV) pacing can exacerbate heart failure in patients with a low left ventricular ejection fraction (LVEF). Left bundle branch area pacing (LBBAP) has emerged as a novel physiological pacing technique; however, information remains limited on its use among patients with a low EF. This study investigated the safety and short-term clinical outcomes of LBBAP among patients with impaired left ventricular (LV) function. This retrospective analysis of pacemakers at Chosun University Hospital, South Korea, included all patients with impaired LV function (EF<50%) who underwent pacemaker implantation for atrioventricular blockage from 2019-2022. Clinical characteristics, 12-lead electrocardiography findings, echocardiography findings, and laboratory parameters were evaluated. Composite outcomes were defined as all-cause mortality, cardiac death, and hospitalization due to heart failure during the 6-month follow-up. Altogether 57 patients (25 men; mean age, 77.4±10.8 y; LVEF, 41.5±3.8%) were divided into LBBAP (n=16), biventricular pacing (BVP; n=16), and conventional RV pacing (RVP; n=25) groups. In the LBBAP group, the mean paced QRS duration (pQRSd) was narrower (119.5±14.7 vs. 140.2±14.3 vs. 163.2±13.9; p<0.001) and cardiac troponin I level was elevated post-pacing (1.14±1.29 vs. 0.20±0.29 vs. 0.24±0.51, p=0.001). Lead parameters were stable. One patient was hospitalized, and four died (one patient each from heart failure admission, myocardial infarction, unexplained death, and pneumonia in RVP vs. one from intracerebral hemorrhage in BVP) during the follow-up period. In conclusion, LBBAP is feasible in patients with impaired LV function without acute or significant complications and provides a remarkably narrower pQRSd with a stable pacing threshold.

W. Lo E, Lim H, Dias S, Wagner KR, Mao HQ, Cahan P, Lee G, Grayson WL. Engineering Skeletal Muscle Grafts with PAX7::GFP-Sorted Human Pluripotent Stem Cell-Derived Myogenic Progenitors on Fibrin Microfiber Bundles for Tissue Regeneration

Tissue engineering strategies that combine human pluripotent stem cell-derived myogenic progenitors (hPDMs) with advanced biomaterials provide promising tools for engineering 3D skeletal muscle grafts to model tissue development in vitro and promote muscle regeneration in vivo. We recently demonstrated (i) the potential for obtaining large numbers of hPDMs using a combination of two small molecules without the overexpression of transgenes and (ii) the application of electrospun fibrin microfiber bundles for functional skeletal muscle restoration following volumetric muscle loss. In this study, we aimed to demonstrate that the biophysical cues provided by the fibrin microfiber bundles induce hPDMs to form engineered human skeletal muscle grafts containing multinucleated myotubes that express desmin and myosin heavy chains and that these grafts could promote regeneration following skeletal muscle injuries. We tested a genetic PAX7 reporter line (PAX7::GFP) to sort for more homogenous populations of hPDMs. RNA sequencing and gene set enrichment analyses confirmed that PAX7::GFP-sorted hPDMs exhibited high expression of myogenic genes. We tested engineered human skeletal muscle grafts derived from PAX7::GFP-sorted hPDMs within in vivo skeletal muscle defects by assessing myogenesis, engraftment and immunogenicity using immunohistochemical staining. The PAX7::GFP-sorted groups had moderately high vascular infiltration and more implanted cell association with embryonic myosin heavy chain (eMHC) regions, suggesting they induced pro-regenerative microenvironments. These findings demonstrated the promise for the use of PAX7::GFP-sorted hPDMs on fibrin microfiber bundles and provided some insights for improving the cell-biomaterial system to stimulate more robust in vivo skeletal muscle regeneration.

Prediabetes diagnosis is associated with the progression of coronary artery calcification: The Kangbuk Samsung Health Study

AIM

To investigate the associations between prediabetes defined by different diagnostic criteria and coronary artery calcification (CAC) and its progression over time.

MATERIALS AND METHODS

This cross-sectional study included 146 436 Korean adults without diabetes who underwent CAC estimation computed tomography (CT) during health examinations from 2011 to 2019. We used multinomial logistic regression models. The longitudinal study comprised 41 100 participants with at least one follow-up cardiac CT and annual CAC progression rates and ratios were estimated. Prediabetes was categorized into three groups: isolated glucose prediabetes (fasting blood glucose [FBG] 100-125 mg/dl, HbA1c < 5.7%), isolated HbA1c prediabetes (FBG < 100 mg/dl, HbA1c 5.7%-6.4%) and prediabetes meeting both FBG and HbA1c criteria (FBG 100-125 mg/dl, HbA1c 5.7%-6.4%).

RESULTS

After adjusting for covariates, the prevalence ratios (95% CI) for CAC scores of more than 100 comparing isolated glucose prediabetes, isolated HbA1c prediabetes and prediabetes fulfilling both criteria with those of normoglycaemia were 1.12 (0.99-1.26), 1.24 (1.11-1.39) and 1.31 (1.18-1.45), respectively. The multivariable-adjusted ratio (CIs) of annual CAC progression rates comparing the corresponding groups with the normoglycaemia group were 1.031 (1.023-1.039), 1.025 (1.019-1.032) and 1.054 (1.047-1.062), respectively.

CONCLUSIONS

CAC risk and CAC progression were consistently highest in individuals meeting both glucose and HbA1c criteria, while all three prediabetes types showed a significantly increased risk of CAC progression. Atherosclerosis risk reduction management is necessary for prediabetes, especially in patients meeting both criteria.

A novel glucagon analog with an extended half-life, HM15136, normalizes glucose levels in rodent models of congenital hyperinsulinism

Congenital hyperinsulinism (CHI) is a rare genetic condition characterized by uncontrolled insulin secretion, resulting in hypoglycemia. Although glucagon has lately been regarded as a therapeutic option for CHI, its use is severely hampered by its poor solubility and stability at physiological pH, as well as its short duration of action. To address these constraints, we developed HM15136, a novel long-acting glucagon analog composed of a glucagon analog conjugated to the Fc fragment of human immunoglobulin G4 via a polyethylene glycol linker. In this study, we established that HM15136 was more soluble than natural glucagon (≥ 150 mg/mL vs 0.03 mg/mL). Next, we confirmed that HM15136 activated glucagon receptor in vitro and induced glycogenolysis and gluconeogenesis in rat primary hepatocytes. Pharmacokinetics (PK)/Pharmacodynamics (PD) analysis of HM15136 shows that HM15136 has a markedly longer half-life (36 h vs. < 5 min) and increased bioavailability (90%) compared to native glucagon in mice. Further, HM15136 could effectively reverse acute hypoglycemia induced by insulin challenge, and multiple doses of HM15136 could sustain increased blood glucose levels in CHI rats. In conclusion, our findings indicate that HM15136 promotes sustained elevation of blood glucose, demonstrating the potential for development as a once-weekly therapy for CHI.

Study of the factors influencing the use of MyData platform based on personal health record data sharing system

Background

The application of telemedicine and electronic health (eHealth) technology has grown in importance during the COVID-19 pandemic, and a new approach in personal data management and processing MyData, has emerged. Data portability and informational self-determination are fundamental concepts of MyData. This study analysed the factors that influence acceptance of the MyData platform, which, reflects the right to self-determine personal data.

Methods

The study involved participants having experience using the MyData platform, and the key factors of the unified theory of acceptance and use of technology were used in the research model (performance expectancy, effort expectancy, social influence, facilitation condition and behavioural intention to use). The questionnaire comprided 27 items, and system usage log data were used to confirm that behavioural intention to use affected actual use behaviour through structural equation modeling.

Results

In total, 1153 participants completed the survey. The goodness of fit in the structural equation model indices indicates that the data fit the research model well. Performance expectancy, social influence, and facilitating conditions had direct effects on behavioural intention to use. We used system usage log data to confirm that behavioural intention to use positively affected actual use behaviour. The impact of the main factors in the unified theory of acceptance and use of technology was not moderated by age or gender, except for performance expectancy.

Conclusions

This study is the first to examine the factors influencing the use of the MyData platform based on the personal health record data sharing system in Korea. In addition, the study confirmed the use behaviour of the MyData platform utilising the system’s actual usage log for each function and analysing the effect of the intention of use on actual use. Our study serves as a significant foundation for the acceptance of data portability and sharing concepts. It also lays the foundation for expanding the data economy and ecosystem in the pandemic era.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01929-z.

The Importance of Metabolic Syndrome Status for the Risk of Non-Viral Hepatocellular Carcinoma: A Nationwide Population-Based Study

The positive association between metabolic syndrome (MetS) and hepatocellular carcinoma (HCC) has been suggested. However, no studies have yet looked at how the risk of developing HCC varies with changes in MetS status. Therefore, we aimed to investigate the association between changes in MetS and subsequent HCC development. Data were obtained from the Korean National Health Insurance Service. In this study, 5,975,308 individuals who participated in health screenings both in 2009-2010 and 2011-2012 were included. Individuals with preexisting viral hepatitis, liver cirrhosis, or cancer diagnoses were excluded. Subjects were divided into four groups according to change in MetS status during the 2-year interval screening (from 2009 to 2011): sustained non-MetS, transition to MetS, transition to non-MetS, and sustained MetS. Cox regression analysis was used to examine the hazard ratios of HCC. The subjects were followed through December 31, 2018. During a median of 7.3 years of follow-up, 25,880 incident HCCs were identified. Compared to the sustained non-MetS group, age, sex, smoking, alcohol, regular exercise, and body mass index-adjusted hazard ratios (95% confidence interval) for HCC development were 1.01 (0.97-1.05) for the transition to MetS group, 1.05 (1.003-1.09) for the transition to non-MetS group, and 1.07 (1.03-1.10) for the sustained MetS group. Stratified analyses according to age, sex, smoking, alcohol intake, exercise, diabetes mellitus, hypertension, dyslipidemia, and chronic kidney disease showed similar results. A significantly increased HCC risk was observed in the sustained MetS and transition to non-MetS groups. The baseline status of MetS was associated with the risk of HCC development. Strategies to improve MetS, especially targeting insulin resistance, might prevent HCC development.

Transforming Thyroid Cancer Diagnosis and Staging Information from Unstructured Reports to the Observational Medical Outcome Partnership Common Data Model

BACKGROUND

Cancer staging information is an essential component of cancer research. However, the information is primarily stored as either a full or semistructured free-text clinical document which is limiting the data use. By transforming the cancer-specific data to the Observational Medical Outcome Partnership Common Data Model (OMOP CDM), the information can contribute to establish multicenter observational cancer studies. To the best of our knowledge, there have been no studies on OMOP CDM transformation and natural language processing (NLP) for thyroid cancer to date.

OBJECTIVE

We aimed to demonstrate the applicability of the OMOP CDM oncology extension module for thyroid cancer diagnosis and cancer stage information by processing free-text medical reports.

METHODS

Thyroid cancer diagnosis and stage-related modifiers were extracted with rule-based NLP from 63,795 thyroid cancer pathology reports and 56,239 Iodine whole-body scan reports from three medical institutions in the Observational Health Data Sciences and Informatics data network. The data were converted into the OMOP CDM v6.0 according to the OMOP CDM oncology extension module. The cancer staging group was derived and populated using the transformed CDM data.

RESULTS

The extracted thyroid cancer data were completely converted into the OMOP CDM. The distributions of histopathological types of thyroid cancer were approximately 95.3 to 98.8% of papillary carcinoma, 0.9 to 3.7% of follicular carcinoma, 0.04 to 0.54% of adenocarcinoma, 0.17 to 0.81% of medullary carcinoma, and 0 to 0.3% of anaplastic carcinoma. Regarding cancer staging, stage-I thyroid cancer accounted for 55 to 64% of the cases, while stage III accounted for 24 to 26% of the cases. Stage-II and -IV thyroid cancers were detected at a low rate of 2 to 6%.

CONCLUSION

As a first study on OMOP CDM transformation and NLP for thyroid cancer, this study will help other institutions to standardize thyroid cancer-specific data for retrospective observational research and participate in multicenter studies.

Plantamajoside Attenuates Neointima Formation via Upregulation of Tissue Inhibitor of Metalloproteinases in Balloon-Injured Rats

The abnormal change of vascular smooth muscle cell (VSMC) behavior is an important cellular event leading to neointimal hyperplasia in atherosclerosis and restenosis. Plantamajoside (PMS), a phenylethanoid glycoside compound of the Plantago asiatica, has been reported to have anti-inflammatory, antioxidative, and anticancer activities. In this study, the protective effects of PMS against intimal hyperplasia and the mechanisms underlying the regulation of VSMC behavior were investigated. MTT and BrdU assays were performed to evaluate the cytotoxicity and cell proliferative activity of PMS, respectively. Rat aortic VSMC migrations after treatment with the determined concentration of PMS (50 and 150 μM) were evaluated using wound healing and Boyden chamber assays. The inhibitory effects of PMS on intimal hyperplasia were evaluated in balloon-injured (BI) rat carotid artery. PMS suppressed the proliferation in platelet-derived growth factor-BB-induced VSMC, as confirmed from the decrease in cyclin-dependent kinase (CDK)-2, CDK-4, cyclin D1, and proliferating cell nuclear antigen levels. PMS also inhibited VSMC migration, consistent with the downregulated expression and zymolytic activities of matrix metalloproteinase (MMP)2, MMP9, and MMP13. PMS specifically regulated MMP expression through p38 mitogen-activated protein kinase and focal adhesion kinase pathways. Tissue inhibitor of metalloproteinase (TIMP)1 and TIMP2 levels were upregulated via Smad1. TIMPs inhibited the conversion of pro-MMPs to active MMPs. PMS significantly inhibited neointimal formation in BI rat carotid arteries. In conclusion, PMS inhibits VSMC proliferation and migration by upregulating TIMP1 and TIMP2 expression. Therefore, PMS could be a potential therapeutic agent for vascular atherosclerosis and restenosis treatment.

Human pluripotent stem cell-derived myogenic progenitors undergo maturation to quiescent satellite cells upon engraftment

Human pluripotent stem cell (hPSC)-derived myogenic progenitor cell (MPC) transplantation is a promising therapeutic approach for a variety of degenerative muscle disorders. Here, using an MPC-specific fluorescent reporter system (PAX7::GFP), we demonstrate that hPSC-derived MPCs can contribute to the regeneration of myofibers in mice following local injury and in mice deficient of dystrophin (mdx). We also demonstrate that a subset of PAX7::GFP MPCs engraft within the basal lamina of regenerated myofibers, adopt a quiescent state, and contribute to regeneration upon reinjury and in mdx mouse models. This subset of PAX7::GFP MPCs undergo a maturation process and remodel their molecular characteristics to resemble those of late-stage fetal MPCs/adult satellite cells following in vivo engraftment. These in-vivo-matured PAX7::GFP MPCs retain a cell-autonomous ability to regenerate and can repopulate in the niche of secondary recipient mice, providing a proof of principle for future hPSC-based cell therapy for muscle disorders.

Second primary malignancy risk in thyroid cancer and matched patients with and without radioiodine therapy analysis from the observational health data sciences and informatics

PURPOSE

Risk of second primary malignancy (SPM) after radioiodine (RAI) therapy has been continuously debated. The aim of this study is to identify the risk of SPM in thyroid cancer (TC) patients with RAI compared with TC patients without RAI from matched cohort.

METHODS

Retrospective propensity-matched cohorts were constructed across 4 hospitals in South Korea via the Observational Health Data Science and Informatics (OHDSI), and electrical health records were converted to data of common data model. TC patients who received RAI therapy constituted the target group, whereas TC patients without RAI therapy constituted the comparative group with 1:1 propensity score matching. Hazard ratio (HR) by Cox proportional hazard model was used to estimate the risk of SPM, and meta-analysis was performed to pool the HRs.

RESULTS

Among a total of 24,318 patients, 5,374 patients from each group were analyzed (mean age 48.9 and 49.2, women 79.4% and 79.5% for target and comparative group, respectively). All hazard ratios of SPM in TC patients with RAI therapy were ≤ 1 based on 95% confidence interval(CI) from full or subgroup analyses according to thyroid cancer stage, time-at-risk period, SPM subtype (hematologic or non-hematologic), and initial age (< 30 years or ≥ 30 years). The HR within the target group was not significantly higher (< 1) in patients who received over 3.7 GBq of I-131 compared with patients who received less than 3.7 GBq of I-131 based on 95% CI.

CONCLUSION

There was no significant difference of the SPM risk between TC patients treated with I-131 and propensity-matched TC patients without I-131 therapy.

Development and evaluation of smartphone usage management system for preventing problematic smartphone use

Objective

The increased use of smartphones has led to several problems, including excessive smartphone use and the decreased self-ability to control smartphone use. To prevent these problems, the MindsCare app was developed as a method of self-management and intervention based on an evaluation of smartphone usage. We designed the MindsCare app to manage smartphone usage and prevent problematic smartphone use by providing personalized interventions.

Methods

We recruited 342 Korean participants over the age of 20 and asked them to use MindsCare for 13 weeks. Subsequently, we evaluated the changes in average smartphone usage time and the usability of the app. We designed a usability evaluation questionnaire based on the Technology Acceptance Model and conducted factor and reliability analyses on the participants’ responses. In the eighth week of the study, participants responded to a survey on the usability of the app. We ultimately collected data from 190 participants.

Results

The average score for the usability of the system was 3.61 on a five-point Likert scale, and approximately 58% of the participants responded positively to the evaluation items. In addition, our analysis of MindsCare data revealed a significant reduction in average smartphone use time in the eighth week compared to the baseline (t = 3.47, p = 0.001). Structural equation model analysis revealed that effort expectancy and performance expectancy had a positive relation with behavior intention for the app.

Conclusions

Through this study, we confirmed the MindsCare app's smartphone usage time reduction effect and proved its good usability. As a result, MindsCare may contribute to achieving users’ goals of reducing problematic smartphone use.

Altered connectivity in the right inferior frontal gyrus associated with self-control in adolescents exhibiting problematic smartphone use: A fMRI study

BACKGROUND

With the continued spread of smartphones and development of the internet, the potential negative effects arising from problematic smartphone use (PSU) in adolescents are being reported on an increasing basis. This study aimed to investigate whether altered resting-state functional connectivity (rsFC) is related to the psychological factors underlying PSU in adolescents.

METHODS

Resting-state functional magnetic resonance images were acquired from 47 adolescents with PSU and 46 healthy control adolescents (the CON group). Seed-based functional connectivity analyses were then performed to compare the two groups with respect to rsFC in the right inferior frontal gyrus, associated with various forms of self-control, and rsFC in the left inferior frontal gyrus.

RESULTS

Compared to the CON group, the PSU group exhibited a reduction in rsFC between the right inferior frontal gyrus and limbic areas, including the bilateral parahippocampal gyrus, the left amygdala, and the right hippocampus. In addition, a reduction in fronto-limbic rsFC was associated with the severity of PSU, the degree of self-control, and the amount of time the subjects used their smartphones.

CONCLUSION

Adolescents with PSU exhibited reduced levels of fronto-limbic functional connectivity; this mechanism is involved in salience attribution and self-control, attributes that are critical to the clinical manifestation of substance and behavioral addictions. Our data provide clear evidence for alterations in brain connectivity with respect to self-control in PSU.

Asbestosis diagnosis algorithm combining the lung segmentation method and deep learning model in computed tomography image

BACKGROUND

Early detection of asbestosis is important; hence, quick and accurate diagnostic tools are essential. This study aimed to develop an algorithm that combines lung segmentation and deep learning models that can be utilized as a clinical decision support system (CDSS) for diagnosing patients with asbestosis in segmented computed tomography (CT) images.

METHODS

We accurately segmented the lungs in CT images of patients examined at Seoul St. Mary's Hospital using a threshold-based method. Lungs with asbestosis and normal lungs were classified by applying the segmented image to the long-term recurrent convolutional network deep learning model. Performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and F1 score from the test data.

RESULTS

The algorithm developed using the DenseNet201pre-trained model showed excellent performance, with a sensitivity of 0.962, specificity of 0.975, accuracy of 0.970, AUROC of 0.968, and F1 score of 0.961.

CONCLUSIONS

We developed an algorithm with significantly better diagnostic accuracy than a radiologist (0.970 vs. 0.73-0.79). Our developed algorithm is expected to be an excellent support tool if used as a CDSS to diagnose asbestosis using CT images.

Association between the use of allopurinol and risk of increased thyroid-stimulating hormone level

Allopurinol is the first-line agent for patients with gout, including those with moderate-to-severe chronic kidney disease. However, increased thyroid-stimulating hormone (TSH) levels are observed in patients with long-term allopurinol treatment. This large-scale, nested case-control, retrospective observational study analysed the association between allopurinol use and increased TSH levels. A common data model based on an electronic medical record database of 19,200,973 patients from seven hospitals between January 1997 and September 2020 was used. Individuals aged > 19 years in South Korea with at least one record of a blood TSH test were included. Data of 59,307 cases with TSH levels > 4.5 mIU/L and 236,508 controls matched for sex, age (± 5), and cohort registration date (± 30 days) were analysed. An association between the risk of increased TSH and allopurinol use in participants from five hospitals was observed. A meta-analysis (I² = 0) showed that the OR was 1.51 (95% confidence interval: 1.32-1.72) in both the fixed and random effects models. The allopurinol intake group demonstrated that increased TSH did not significantly affect free thyroxine and thyroxine levels. After the index date, some diseases were likely to occur in patients with subclinical hypothyroidism and hypothyroidism. Allopurinol administration may induce subclinical hypothyroidism.

Association between obesity and the risk of gastric cancer in premenopausal and postmenopausal women: A nationwide cohort study

BACKGROUND AND AIM

Obesity was suggested to increase the incidence of gastric cancer (GC) in women, but results from previous studies were inconsistent. We investigated the relationship between obesity and the risk of GC according to menopausal status.

METHODS

We enrolled 1 418 180 premenopausal and 4 854 187 postmenopausal women aged ≥ 40 years using the Korean National Health Insurance System Cohort (2009-2014). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for GC incidence according to body mass index (BMI) and waist circumference (WC) using the Cox proportional hazards models.

RESULTS

During the mean follow-up period of 7.2 years, 42 441 women were newly diagnosed with GC. Compared with the group with BMI 18.5-22.9 kg/m² , the adjusted HRs (95% CIs) for GC in the groups with BMI < 18.5, 23-24.9, 25-29.9, and ≥ 30 kg/m² were 1.12 (0.95-1.33), 0.96 (0.89-1.04), 1.02 (0.94-1.11), and 0.99 (0.83-1.18), respectively, for premenopausal women and 1.07 (1.00-1.14), 1.01 (0.99-1.04), 1.03 (1.00-1.05), and 1.11 (1.10-1.16), respectively, for postmenopausal women. Compared with the group with WC 65-74.9 cm, the adjusted HRs (95% CIs) for GC for the groups with WC < 65, 75-84.9, 85-94.9, and ≥ 90 cm were 1.00 (0.88-1.15), 1.03 (0.96-1.11), 1.10 (0.99-1.22), and 1.02 (0.81-1.27), respectively, for premenopausal women and 1.01 (0.94-1.09), 1.01 (0.99-1.04), 1.09 (1.06-1.13), and 1.14 (1.09-1.19), respectively, for postmenopausal women.

CONCLUSIONS

We found a positive association between the highest BMI and WC category and risk of GC in postmenopausal women; however, such an association was not evident in premenopausal women.

Machine learning prediction of dropping out of outpatients with alcohol use disorders

BACKGROUND

Alcohol use disorder (AUD) is a chronic disease with a higher recurrence rate than that of other mental illnesses. Moreover, it requires continuous outpatient treatment for the patient to maintain abstinence. However, with a low probability of these patients to continue outpatient treatment, predicting and managing patients who might discontinue treatment becomes necessary. Accordingly, we developed a machine learning (ML) algorithm to predict which the risk of patients dropping out of outpatient treatment schemes.

METHODS

A total of 839 patients were selected out of 2,206 patients admitted for AUD in three hospitals under the Catholic Central Medical Center in Korea. We implemented six ML models-logistic regression, support vector machine, k-nearest neighbor, random forest, neural network, and AdaBoost-and compared the prediction performances thereof.

RESULTS

Among the six models, AdaBoost was selected as the final model for recommended use owing to its area under the receiver operating characteristic curve (AUROC) of 0.72. The four variables affecting the prediction based on feature importance were the length of hospitalization, age, residential area, and diabetes.

CONCLUSION

An ML algorithm was developed herein to predict the risk of patients with AUD in Korea discontinuing outpatient treatment. By testing and validating various machine learning models, we determined the best performing model, AdaBoost, as the final model for recommended use. Using this model, clinicians can manage patients with high risks of discontinuing treatment and establish patient-specific treatment strategies. Therefore, our model can potentially enable patients with AUD to successfully complete their treatments by identifying them before they can drop out.

Safety Evaluation of Bifidobacterium breve IDCC4401 Isolated from Infant Feces for Use as a Commercial Probiotic

Previously, our research group isolated Bifidobacterium breve IDCC4401 from infant feces as a potential probiotic. For this study, we evaluated the safety of B. breve IDCC4401 using genomic and phenotypic analyses. Whole genome sequencing was performed to identify genomic characteristics and investigate the potential presence of genes encoding virulence, antibiotic resistance, and mobile genetic elements. Phenotypic analyses including antibiotic susceptibility, enzyme activity, production of biogenic amines (BAs), and proportion of D-/L-lactate were evaluated using E-test, API ZYM test, high-performance liquid chromatography (HPLC), and D-/L-lactic acid assay respectively. The genome of B. breve IDCC4401 consists of 2,426,499 bp with a GC content of 58.70% and 2,016 coding regions. Confirmation of the genome as B. breve was provided by its 98.93% similarity with B. breve DSM20213. Furthermore, B. breve IDCC4401 genes encoding virulence and antibiotic resistance were not identified. Although B. breve IDCC4401 showed antibiotic resistance against vancomycin, we confirmed that this was an intrinsic feature since the antibiotic resistance gene was not present. B. breve IDCC4401 showed leucine arylamidase, cystine arylamidase, α-galactosidase, β-galactosidase, and α-glucosidase activities, whereas it did not show production of harmful enzymes such as β-glucosidase and β-glucuronidase. In addition, B. breve IDCC4401 did not produce any tyramine, histamine, putrescine, cadaverine, or 2-phenethylamine, which are frequently detected BAs during fermentation. B. breve IDCC4401 produced 95.08% of L-lactate and 4.92% of Dlactate. Therefore, our findings demonstrate the safety of B. breve IDCC 4401 as a potential probiotic for use in the food industry.

Deep-learning framework and computer assisted fatty infiltration analysis for the supraspinatus muscle in MRI

Occupation ratio and fatty infiltration are important parameters for evaluating patients with rotator cuff tears. We analyzed the occupation ratio using a deep-learning framework and studied the fatty infiltration of the supraspinatus muscle using an automated region-based Otsu thresholding technique. To calculate the amount of fatty infiltration of the supraspinatus muscle using an automated region-based Otsu thresholding technique. The mean Dice similarity coefficient, accuracy, sensitivity, specificity, and relative area difference for the segmented lesion, measuring the similarity of clinician assessment and that of a deep neural network, were 0.97, 99.84, 96.89, 99.92, and 0.07, respectively, for the supraspinatus fossa and 0.94, 99.89, 93.34, 99.95, and 2.03, respectively, for the supraspinatus muscle. The fatty infiltration measure using the Otsu thresholding method significantly differed among the Goutallier grades (Grade 0; 0.06, Grade 1; 4.68, Grade 2; 20.10, Grade 3; 42.86, Grade 4; 55.79, p < 0.0001). The occupation ratio and fatty infiltration using Otsu thresholding demonstrated a moderate negative correlation (ρ = - 0.75, p < 0.0001). This study included 240 randomly selected patients who underwent shoulder magnetic resonance imaging (MRI) from January 2015 to December 2016. We used a fully convolutional deep-learning algorithm to quantitatively detect the fossa and muscle regions by measuring the occupation ratio of the supraspinatus muscle. Fatty infiltration was objectively evaluated using the Otsu thresholding method. The proposed convolutional neural network exhibited fast and accurate segmentation of the supraspinatus muscle and fossa from shoulder MRI, allowing automatic calculation of the occupation ratio. Quantitative evaluation using a modified Otsu thresholding method can be used to calculate the proportion of fatty infiltration in the supraspinatus muscle. We expect that this will improve the efficiency and objectivity of diagnoses by quantifying the index used for shoulder MRI.