Automated BigSMILES conversion workflow and dataset for homopolymeric macromolecules.

The simplified molecular-input line-entry system (SMILES) has been utilized in a variety of artificial intelligence analyses owing to its capability of representing chemical structures using line notation. However, its ease of representation is limited, which has led to the proposal of BigSMILES as an alternative method suitable for the representation of macromolecules. Nevertheless, research on BigSMILES remains limited due to its preprocessing requirements. Thus, this study proposes a conversion workflow of BigSMILES, focusing on its automated generation from SMILES representations of homopolymers. BigSMILES representations for 4,927,181 records are provided, thereby enabling its immediate use for various research and development applications. Our study presents detailed descriptions on a validation process to ensure the accuracy, interchangeability, and robustness of the conversion. Additionally, a systematic overview of utilized codes and functions that emphasizes their relevance in the context of BigSMILES generation are produced. This advancement is anticipated to significantly aid researchers and facilitate further studies in BigSMILES representation, including potential applications in deep learning and further extension to complex structures such as copolymers.

Association of maternal thyroid disease with obesity in child.

OBJECTIVES: During pregnancy, many women develop thyroid disorders, which can result in fetal and neonatal development defects. We investigated whether maternal thyroid dysfunction would affect their children's growth and obesity. STUDY DESIGN: We conducted a nationwide population-based cohort study using a combination of data from several Korean nationwide registries to investigate the association between maternal thyroid dysfunction, offspring growth, and obesity. Childhood growth was repeatedly measured at three periods of age from 42 to 80 months, using body mass index (BMI). RESULTS: A total of 1,123,499 women were enrolled in this study; 78,902 (7.0 %) had pre-pregnancy thyroid disease. Significant association was found between maternal hyperthyroidism and obesity in all children aged 42-66 months (42-54 months, adjusted odds ratio (aOR) 0.93, 95 % confidence interval (CI) 0.89-0.98; 54-66 months, aOR 0.93, 95 % CI 0.87-0.99), but not at later ages. In the analysis by sex, maternal hyperthyroidism was associated with childhood obesity in boys, whereas it was not associated with those in girls of any age. No association was observed between maternal hypothyroidism and child BMI or obesity. CONCLUSIONS: The association between maternal thyroid function and obesity in offspring is attenuated from early to late childhood, suggesting that many other factors may be involved in developing childhood obesity.

Development of a multipotent diagnostic tool for chest X-rays by multi-object detection method.

The computer-aided diagnosis (CAD) for chest X-rays was developed more than 50 years ago. However, there are still unmet needs for its versatile use in our medical fields. We planned this study to develop a multipotent CAD model suitable for general use including in primary care areas. We planned this study to solve the problem by using computed tomography (CT) scan with its one-to-one matched chest X-ray dataset. The data was extracted and preprocessed by pulmonology experts by using the bounding boxes to locate lesions of interest. For detecting multiple lesions, multi-object detection by faster R-CNN and by RetinaNet was adopted and compared. A total of twelve diagnostic labels were defined as the followings: pleural effusion, atelectasis, pulmonary nodule, cardiomegaly, consolidation, emphysema, pneumothorax, chemo-port, bronchial wall thickening, reticular opacity, pleural thickening, and bronchiectasis. The Faster R-CNN model showed higher overall sensitivity than RetinaNet, nevertheless the values of specificity were opposite. Some values such as cardiomegaly and chemo-port showed excellent sensitivity (100.0%, both). Others showed that the unique results such as bronchial wall thickening, reticular opacity, and pleural thickening can be described in the chest area. As far as we know, this is the first study to develop an object detection model for chest X-rays based on chest area defined by CT scans in one-to-one matched manner, preprocessed and conducted by a group of experts in pulmonology. Our model can be a potential tool for detecting the whole chest area with multiple diagnoses from a simple X-ray that is routinely taken in most clinics and hospitals on daily basis.

Comparative study of deep learning algorithms for atomic force microscopy image denoising.

Atomic force microscopy (AFM) enables direct visualisation of surface topography at the nanoscale. However, post-processing is generally required to obtain accurate, precise, and reliable AFM images owing to the presence of image artefacts. In this study, we compared and analysed state-of-the-art deep learning models, namely MPRNet, HINet, Uformer, and Restormer, with respect to denoising AFM images containing four types of noise. Specifically, these algorithms' denoising performance and inference time on AFM images were compared with those of conventional methods and previous studies. Through a comparative analysis, we found that the most efficient and the most effective models were Restormer and HINet, respectively. The code, models, and data used in this work are available at https://github.com/hoichanjung/AFM_Image_Denoising.

Doubly-robust methods for differences in restricted mean lifetimes using pseudo-observations.

In clinical studies or trials comparing survival times between two treatment groups, the restricted mean lifetime (RML), defined as the expectation of the survival from time 0 to a prespecified time-point, is often the quantity of interest that is readily interpretable to clinicians without any modeling restrictions. It is well known that if the treatments are not randomized (as in observational studies), covariate adjustment is necessary to account for treatment imbalances due to confounding factors. In this article, we propose a simple doubly-robust pseudo-value approach to effectively estimate the difference in the RML between two groups (akin to a metric for estimating average causal effects), while accounting for confounders. The proposed method combines two general approaches: (a) group-specific regression models for the time-to-event and covariate information, and (b) inverse probability of treatment assignment weights, where the RMLs are replaced by the corresponding pseudo-observations for survival outcomes, thereby mitigating the estimation complexities in presence of censoring. The proposed estimator is double-robust, in the sense that it is consistent if at least one of the two working models remains correct. In addition, we explore the potential of available machine learning algorithms in causal inference to reduce possible bias of the causal estimates in presence of a complex association between the survival outcome and covariates. We conduct extensive simulation studies to assess the finite-sample performance of the pseudo-value causal effect estimators. Furthermore, we illustrate our methodology via application to a dataset from a breast cancer cohort study. The proposed method is implementable using the R package drRML, available in GitHub.

Adverse Pregnancy Outcomes and Maternal Chronic Diseases in the Future: A Cross-Sectional Study Using KoGES-HEXA Data.

Adverse pregnancy outcomes (APOs) are associated with an increased risk of chronic diseases, including cardiovascular disease (CVD) and metabolic syndrome (MS), in the future. We designed a large-scale cohort study to evaluate the influence of APOs (preeclampsia, gestational diabetes mellitus (GDM), stillbirth, macrosomia, and low birth weight) on the incidence of chronic diseases, body measurements, and serum biochemistry in the future and investigate whether combinations of APOs had additive effects on chronic diseases. We used health examinee data from the Korean Genome and Epidemiology Study (KoGES-HEXA) and extracted data of parous women (n = 30,174; mean age, 53.02 years) for the analysis. Women with APOs were more frequently diagnosed with chronic diseases and had a family history of chronic diseases compared with women without APOs. Composite APOs were associated with an increased risk of hypertension, diabetes mellitus, hyperlipidemia, angina pectoris, stroke, and MS (adjusted odds ratio: 1.093, 1.379, 1.269, 1.351, 1.414, and 1.104, respectively) after adjustment for family history and social behaviors. Preeclampsia and GDM were associated with an increased risk of some chronic diseases; however, the combination of preeclampsia and GDM did not have an additive effect on the risk. APOs moderately influenced the future development of maternal CVD and metabolic derangements, independent of family history and social behaviors.

Prior pregnancy complications and maternal cardiovascular disease in young Korean women within 10 years after pregnancy.

BACKGROUND: This study aimed to compare obstetric outcomes in Korean women with and without future cardiovascular disease (CVD) within 10 years after pregnancy, and assessed whether pregnancy complications are independent risk factors, and whether the combination of pregnancy complications has an additive function for risk factors for CVD. METHODS: This was a nationwide population-based study combining the database of the Korea National Health Insurance claims and National Health Screening Programs to assess preeclampsia, low birth weight (LBW), and preterm delivery as risk factors for CVD. Cox proportional hazards models was used to evaluate the risk of total CVD, ischemic heart disease (IHD), and stroke after the pregnancy complications, with adjustment for potential confounding variables. RESULTS: Women with CVD were likely to have a higher prevalence of pregnancy complications than women without CVD. The risk of total CVD was associated with preeclampsia (adjusted hazard ratio (HR), 1.60 [95% confidence interval (CI) 1.50-1.72]), LBW (1.20 [1.12-1.28]), and preterm delivery (1.32 [1.22-1.42]), after adjustment for confounders, including cardiovascular risk factors before pregnancy. The risk estimates of pregnancy complications for IHD were higher than those for stroke. In this study, the risk of total CVD was higher in the combined presence of preeclampsia and preterm delivery (2.23 [1.57-3.17] or all three complications (2.06 [1.76-2.40]), relative to no complications. The highest HR was noted in the risk of all pregnancy complications for IHD (2.39 [1.98-2.89]). CONCLUSION: Preeclampsia, preterm delivery, and LBW were independently associated with CVD in young Korean women. In addition, the combination of pregnancy complications had less-than-additive effects on CVD incidence.

Risk factors associated with idiopathic sudden sensorineural hearing loss in pregnant South Korean women: a nationwide population-based study.

OBJECTIVE: Sudden sensorineural hearing loss (SSNHL) is rare in pregnancy and can be attributed to pregnancy-induced changes in hormone levels that increase thrombogenic risk and alter cochlear microcirculation with consequent development of sudden deafness. The study aimed to analyze the risk factors associated with SSNHL in pregnant South Korean. METHODS: A retrospective study of the incidence and risk factors associated with SSNHL before pregnancy enrolled 401,470 Korean women who delivered between January 2010 and December 2014. All participants underwent a pre-pregnancy national health screening examination through the National Health Insurance Corporation. We investigated the risk factors in 459 pregnant women with sudden sensorineural hearing loss and in 401,011 pregnant women without SSNHL through the pre-pregnancy national health screening examination and adverse perinatal outcome. RESULTS: No statistically significant intergroup differences were observed in the maternal age, parity, method of delivery, gestational age at delivery, body mass index, blood pressure, as well as fasting blood glucose and cholesterol levels. After adjusting for maternal age, the pre-pregnancy body mass index was associated with an increased risk of sensorineural hearing loss in pregnancy (adjusted odds ratio 1.52, 95% confidence interval 1.04-2.22). The sensorineural hearing loss did not increase the risk for gestational hypertension, preterm birth (<37 weeks' gestation), small- and large-for-gestational-age infants, postpartum hemorrhage, placenta previa, and placental abruption. CONCLUSION: SSNHL can occur throughout pregnancy and is associated with maternal pre-pregnancy obesity. Notably, it does not increase risks during delivery or cause adverse perinatal outcomes.

Risk of Early Childhood Obesity in Offspring of Women with Preeclampsia: A Population-Based Study.

Preeclampsia (PE) is a major disease of pregnancy, with various short- or long-term complications for both the mother and offspring. We focused on the body mass index (BMI) of offspring and compared the incidence of obesity during early childhood between PE- and non-PE-affected pregnancies. Women with singleton births (n = 1,697,432) were identified from the Korea National Health Insurance database. The outcomes of offspring at 30-80 months of age were analyzed. The effects of PE on BMI and the incidence of obesity in the offspring were compared. The incidence of low birth weight (LBW) offspring was higher in the PE group (n = 29,710) than that in the non-PE group (n = 1,533,916) (24.70% vs. 3.33%, p < 0.01). However, BMI was significantly higher in the PE-affected offspring than that in non-PE-affected offspring. After adjusting for various factors, the risk of obesity was higher in the PE-affected offspring (odds ratio = 1.34, 95% confidence interval = 1.30-1.38). The BMI and incidence of obesity were higher during early childhood in the PE-affected offspring, even though the proportion of LBW was higher. These results may support the basic hypotheses for the occurrence of various cardiovascular and metabolic complications in PE-affected offspring. In addition, early-age incidence of obesity could influence PE management and child consultation in clinical applications.

Women with multiple gestations have an increased risk of development of hypertension in the future.

BACKGROUND: Multiple gestations are associated with an increased incidence of preeclampsia. However, there exists no evidence for an association between multiple gestations and development of hypertension(HTN) later in life. This study aimed to determine whether multiple gestations are associated with HTN beyond the peripartum period. METHODS: In this retrospective nationwide population-based study, women who delivered a baby between January 1, 2007, and December 31, 2008, and underwent a national health screening examination within one year prior to their pregnancy were included. Subsequently, we tracked the occurrence of HTN during follow-up until December 31, 2015, using International Classification of Diseases-10th Revision codes. RESULTS: Among 362,821 women who gave birth during the study period, 4,944 (1.36%) women had multiple gestations. The cumulative incidence of HTN was higher in multiple gestations group compared with singleton group (5.95% vs. 3.78%, p < 0.01, respectively). On the Cox proportional hazards models, the risk of HTN was increased in women with multiple gestations (HR 1.35, 95% CI 1.19, 1.54) compared with those with singleton after adjustment for age, primiparity, preeclampsia, atrial fibrillation, body mass index, blood pressure, diabetes mellitus, high total cholesterol, abnormal liver function test, regular exercise, and smoking status. CONCLUSIONS: Multiple gestations are associated with an increased risk of HTN later in life. Therefore, guidelines for the management of high-risk patients after delivery should be established.

Twelve-month post-treatment parameters are superior in predicting hepatocellular carcinoma in patients with chronic hepatitis B.

BACKGROUND & AIMS: There are currently several prediction models for hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) receiving oral antiviral therapy. However, most models are based on pre-treatment clinical parameters. The current study aimed to develop a novel and practical prediction model for HCC by using both pre- and post-treatment parameters in this population. METHODS: We included two treatment-naïve CHB cohorts who were initiated on oral antiviral therapies: the derivation cohort (n = 1480, Korea prospective SAINT cohort) and the validation cohort (n = 426, the US retrospective Stanford Bay cohort). We employed logistic regression, decision tree, lasso regression, support vector machine and random forest algorithms to develop the HCC prediction model and selected the most optimal method. RESULTS: We evaluated both pre-treatment and the 12-month clinical parameters on-treatment and found the 12-month on-treatment values to have superior HCC prediction performance. The lasso logistic regression algorithm using the presence of cirrhosis at baseline and alpha-foetoprotein and platelet at 12 months showed the best performance (AUROC = 0.843 in the derivation cohort. The model performed well in the external validation cohort (AUROC = 0.844) and better than other existing prediction models including the APA, PAGE-B and GAG models (AUROC = 0.769 to 0.818). CONCLUSIONS: We provided a simple-to-use HCC prediction model based on presence of cirrhosis at baseline and two objective laboratory markers (AFP and platelets) measured 12 months after antiviral initiation. The model is highly accurate with excellent validation in an external cohort from a different country (AUROC 0.844) (Clinical trial number: KCT0003487).

Similarity-Based Unsupervised Spelling Correction Using BioWordVec: Development and Usability Study of Bacterial Culture and Antimicrobial Susceptibility Reports.

BACKGROUND: Existing bacterial culture test results for infectious diseases are written in unrefined text, resulting in many problems, including typographical errors and stop words. Effective spelling correction processes are needed to ensure the accuracy and reliability of data for the study of infectious diseases, including medical terminology extraction. If a dictionary is established, spelling algorithms using edit distance are efficient. However, in the absence of a dictionary, traditional spelling correction algorithms that utilize only edit distances have limitations. OBJECTIVE: In this research, we proposed a similarity-based spelling correction algorithm using pretrained word embedding with the BioWordVec technique. This method uses a character-level N-grams-based distributed representation through unsupervised learning rather than the existing rule-based method. In other words, we propose a framework that detects and corrects typographical errors when a dictionary is not in place. METHODS: For detected typographical errors not mapped to Systematized Nomenclature of Medicine (SNOMED) clinical terms, a correction candidate group with high similarity considering the edit distance was generated using pretrained word embedding from the clinical database. From the embedding matrix in which the vocabulary is arranged in descending order according to frequency, a grid search was used to search for candidate groups of similar words. Thereafter, the correction candidate words were ranked in consideration of the frequency of the words, and the typographical errors were finally corrected according to the ranking. RESULTS: Bacterial identification words were extracted from 27,544 bacterial culture and antimicrobial susceptibility reports, and 16 types of spelling errors and 914 misspelled words were found. The similarity-based spelling correction algorithm using BioWordVec proposed in this research corrected 12 types of typographical errors and showed very high performance in correcting 97.48% (based on F1 score) of all spelling errors. CONCLUSIONS: This tool corrected spelling errors effectively in the absence of a dictionary based on bacterial identification words in bacterial culture and antimicrobial susceptibility reports. This method will help build a high-quality refined database of vast text data for electronic health records.

In utero exposure to ritodrine during pregnancy and risk of autism in their offspring until 8 years of age.

Beta-2 adrenergic receptor (B2AR) agonists, used as asthma treatments and tocolytics during pregnancy, have recently been reported to be associated with autism in their offspring. However, the particular link between autism and ritodrine, a common type of B2AR agonist used solely as tocolytics, has never been substantiated with any nationwide database. Thus, we aimed to examine the association between in utero exposure of ritodrine and the risk of autism in their offspring using a national database. This population-based cohort study was conducted by merging the Korea National Health Insurance claims database and National Health Screening Program for Infants and Children database. These databases included all women who had delivered singleton between January 2007 and December 2008 in Korea. Out of the total 770,016 mothers, 30,959 (4.02%) were exposed to ritodrine during pregnancy, and 5583 (0.73%) of their children were identified as having autism, defined until 8 years of age. According to our analysis, the overall cumulative incidence of autism up to 8 years was 1.37% in ritodrine exposure group and 0.70% in ritodrine non-exposure group (p < 0.05, log-rank test). By Cox proportional hazard analysis, use of ritodrine in preterm birth was associated with significantly higher hazard of autism [adjusted hazard ratio: 1.23, 95% CI 1.04-1.47], after adjusting for confounding variables including maternal age, parity, cesarean section, preterm labor, steroid use, birth weight, gender, and preeclampsia. Thus, in utero exposure to ritodrine was associated with an increased risk of autism in their offspring.

Pre-Pregnancy Risk Factors for Severe Hyperemesis Gravidarum: Korean Population Based Cohort Study.

Hyperemesis gravidarum is known to be associated with poor perinatal outcomes. This study aimed to identify pre-pregnancy risk factors for hospital admission in women with hyperemesis gravidarum. We enrolled women who had delivered between 1 January 2013 and 31 December 2015, and had undergone a national health screening examination through the National Health Insurance Corporation 1-2 years before their first delivery. Multiple logistic regression analysis was performed to estimate the risk factors for hospital admission due to hyperemesis gravidarum. Of the 216,373 study participants with hyperemesis gravidarum, 2210 (1.02%) pregnant women were hospitalized. These women had lower waist circumference and were underweight based on body mass index compared to pregnant women who did not require hospitalization due to hyperemesis gravidarum. On multivariate analysis, primiparity, multiple pregnancies, female fetus, alcohol consumption, and pre-pregnancy underweight status were associated with an increased risk of hospitalization due to the condition. In this population-based cohort study, we found that hospitalization due to hyperemesis gravidarum was associated with pre-pregnancy lifestyle characteristics. Early recognition and management of these pre-pregnancy factors may help control the need for hospitalization in women with the condition in subsequent pregnancies.

Paradoxical long-term impact of maternal influenza infection on neonates and infants.

BACKGROUND: Pregnant women are at high risk of influenza-related morbidity and mortality. In addition, maternal influenza infection may lead to adverse birth outcomes. However, there is insufficient data on long-term impact of maternal influenza infection. METHODS: This study was conducted to assess the impact of maternal influenza infection on birth outcomes and long-term influence on infants by merging the Korea National Health Insurance (KNHI) claims database and National Health Screening Program for Infants and Children (NHSP-IC). Mother-offspring pairs were categorized by maternal influenza infection based on the ICD-10 code. RESULTS: Multivariate analysis revealed that maternal influenza infection significantly increased the risk of preterm birth (OR 1.408) and low birth weight (OR 1.198) irrespective of gestational age. The proportion of low birth weight neonates was significantly higher in influenza-infected women compared to those without influenza. However, since the fourth health screening (30-80 months after birth), the fraction of underweight was no longer different between children from influenza-infected and non-infected mothers, whereas the rates of overweight increased paradoxically in those born to mothers with influenza infection. CONCLUSIONS: Maternal influenza infection might have long-term effects on the health of children and adolescents even after infancy.

Evaluation of maternal rhesus blood type as a risk factor in adverse pregnancy outcomes in Korea: a nationwide health insurance database study.

OBJECTIVES: The current study aimed to investigate whether pregnancy outcomes are affected by maternal rhesus (Rh) status by comparing the primigravida pregnancy outcomes of Rh-negative women with those of Rh-positive women. METHODS: The study data were collected from the Korea National Health Insurance Claims Database and the National Health Screening Program for Infants and Children. In total, 1,664,882 primigravida women who gave birth between January 1, 2007 and December 31, 2014, were enrolled in this study. As the risk and severity of sensitization response increases with each subsequent pregnancy, only primigravida women were enrolled. The patients were divided into 2 groups according to Rh status, and the pregnancy outcomes were compared. RESULTS: In total, 1,661,320 women in the Rh-positive group and 3,290 in the Rh-negative group were assessed. With regard to adverse pregnancy outcomes, there was no statistically significant difference between the 2 groups in terms of the prevalence of preeclampsia, postpartum hemorrhage, abruptio placenta, placenta previa, and uterine artery embolization. A univariate analysis revealed that none of the adverse pregnancy outcomes were significantly correlated to Rh status (preeclampsia: odds ratio [OR], 1.00, 95% confidence interval [CI], 0.81-1.23; postpartum hemorrhage: OR, 1.10, 95% CI, 0.98-1.24; abruptio placenta: OR, 0.80, 95% CI, 0.46-1.37; and placenta previa: OR, 1.08, 95% CI, 0.78-1.42). The adjusted ORs of postpartum hemorrhage and preterm birth did not significantly differ. CONCLUSION: Maternal Rh status is not associated with adverse outcomes in primigravida women.

Peripartum Blood Transfusions are Associated with Increased Risk of Cancer: A National Retrospective Cohort Study.

BACKGROUND: The effect of blood transfusions on the risk of developing primary cancer remains unclear, especially when administered in the peripartum period. MATERIALS AND METHODS: We conducted a retrospective cohort study of 270,529 pregnant women who delivered between January 1, 2007 and December 31, 2009, with data obtained from three national databases in South Korea. From this cohort, we identified 4569 patients who received peripartum blood transfusions. We calculated hazard ratios (HRs) for new diagnoses of cancer and adjusted them for relevant clinical factors using a Cox proportional hazards model. RESULTS: During follow-up, patients who received peripartum transfusions had an increased risk of developing cancer, with an adjusted HR of 1.16 (95% confidence interval [CI], 1.01-1.34). In a subgroup analysis, this risk was significant only among patients who received 3 or more units of blood, with an adjusted HR of 1.40 (95% CI, 1.10-1.79). Increased risk after transfusions were seen with brain, lung, ovarian, and gallbladder cancers. The difference in cancer risk between the transfusion and no-transfusion groups remained significant during both the first (1.29% vs 1.07%, p < 0.01) and second year (0.74% vs 0.56%, p < 0.01) after delivery. CONCLUSION: Receipt of 3 or more blood transfusions in the peripartum period was associated with a significantly increased risk of developing cancer. Prospective studies should be pursued to further understand the link between blood transfusions and long-term oncologic risks.

Pregnancy and neonatal outcomes of women with disabilities: a nationwide population-based study in South Korea.

We investigated (1) pregnancy and neonatal outcomes in women with and without disabilities, (2) time trends in deliveries, and (3) risks of pregnancy and neonatal complications among women with various disability types and severity. This was a nationwide population-based study merging the database of the Korea National Health Insurance claims, National Health Screening Program for Infants and Children, and Disability Registration System to compare perinatal outcomes in women with and without disabilities. Pregnancy and neonatal outcomes were analyzed during 2007 and 2015, as were time trends of deliveries. Multivariate logistic regression was used to evaluate risk of perinatal outcomes among women with various disability types and severities. Women with disabilities showed higher rates of cesarean section (aOR, 1.73; 95% CI, 1.69-1.77), hypertensive disorders (aOR, 1.74; 95% CI, 1.63-1.86), placenta abruption (aOR, 1.27; 95% CI, 1.12-1.45), placenta previa (aOR, 1.14; 95% CI, 1.05-1.24), stillbirths (aOR, 1.30; 95% CI, 1.17-1.45), preterm births (aOR, 1.67; 95% CI, 1.57-1.78), and LBW (aOR, 1.87; 95% CI, 1.78-1.97) than those without disabilities. From 2007 to 2015, although delivery rate in women with disabilities decreased steeply compared with that in women without disabilities, the rate of cesarean section increased in women with disabilities. Women with intellectual disability and those with vision impairment had the highest number of perinatal complications among women with various types of disabilities. Women with disability had more adverse pregnancy and neonatal outcomes than those without disabilities. Specific disability types & severities are more vulnerable to specific perinatal complications.

Gene expression network analysis of lymph node involvement in colon cancer identifies AHSA2, CDK10, and CWC22 as possible prognostic markers.

Colon cancer has been well studied using a variety of molecular techniques, including whole genome sequencing. However, genetic markers that could be used to predict lymph node (LN) involvement, which is the most important prognostic factor for colon cancer, have not been identified. In the present study, we compared LN(+) and LN(-) colon cancer patients using differential gene expression and network analysis. Colon cancer gene expression data were obtained from the Cancer Genome Atlas and divided into two groups, LN(+) and LN(-). Gene expression networks were constructed using LASSO (Least Absolute Shrinkage and Selection Operator) regression. We identified hub genes, such as APBB1, AHSA2, ZNF767, and JAK2, that were highly differentially expressed. Survival analysis using selected hub genes, such as AHSA2, CDK10, and CWC22, showed that their expression levels were significantly associated with the survival rate of colon cancer patients, which indicates their possible use as prognostic markers. In addition, protein-protein interaction network, GO enrichment, and KEGG pathway analysis were performed with selected hub genes from each group to investigate the regulatory relationships between hub genes and LN involvement in colon cancer; these analyses revealed differences between the LN(-) and LN(+) groups. Our network analysis may help narrow down the search for novel candidate genes for the treatment of colon cancer, in addition to improving our understanding of the biological processes underlying LN involvement. All R implementation codes are available at journal website as Supplementary Materials.