Exploring Cohesin-Related Multiomics Information in the Web Browser.

Cohesin is a protein complex that plays a key role in regulating chromosome structure and gene expression. While next-generation sequencing technologies have provided extensive information on various aspects of cohesin, integrating and exploring the vast datasets associated with cohesin are not straightforward. CohesinDB ( https://cohesindb.iqb.u-tokyo.ac.jp ) offers a web-based interface for browsing, searching, analyzing, visualizing, and downloading comprehensive multiomics cohesin information in human cells. In this protocol, we introduce how to utilize CohesinDB to facilitate research on transcriptional regulation and chromatin organization.

The Impact of Gender and Race on Outcomes for Hospitalized Hepatitis A Patients Stratified by Liver Disease Severity.

Background: The incidence of hepatitis A virus (HAV) infection is on the rise, with a minority of patients at risk for poor outcomes. This study investigates the prognostic impacts of race and gender on hospital outcomes among admitted HAV-infected patients. Methods: Using the National Inpatient Sample from 2012 to 2017, patients admitted with HAV were selected and stratified by gender (male and female) and race (White, Black, Hispanic, Asian-Pacific Islander, Other). Propensity score-matching and statistical analysis were implemented with comparison to the controls ("Female" and "White"). Primary endpoints included mortality, length of stay (LOS), and hospitalization costs, while secondary endpoints consisted of hepatic-related medical complications such as ascites, hepatic encephalopathy, varices, and acute liver failure. Results: Females with compensated cirrhosis had increased odds of mortality (aOR 2.59, 95% CI: 1.14-5.91, P = 0.02). Otherwise, no other differences in mortality were detected between genders and races. Females had a shorter hospital LOS (aOR 0.97, 95% CI: 0.96-0.98, P < 0.001), lower adjusted cost ($12,241 vs. $13,510, aOR 0.92, 95% CI: 0.92-0.92, P < 0.001), lower odds of esophageal varices (aOR 0.74, 95% CI: 0.57-0.97, P = 0.03) and hepatic encephalopathy (aOR 0.67, 95% CI: 0.53-0.84, P < 0.001) compared to males. Black patients exhibited higher LOS (aOR 1.06, 95% CI: 1.04-1.08, P < 0.001) and adjusted costs ($13,392 vs $12,592, aOR 1.02, 95% CI: 1.02-1.03, P < 0.001). Hispanic patients exhibited higher rates of esophageal varices (aOR 2.19, 95% CI: 1.28-3.76, P = 0.005) and adjusted costs ($14,202 vs. $12,381, aOR 1.07, 95% CI: 1.07-1.07, P < 0.001), and Asian patients experienced higher adjusted costs ($18,426 vs. $13,137, aOR 1.10, 95% CI: 1.10-1.10, P < 0.001) compared to White patients. Conclusion: Various nuanced impacts of gender and race on hospitalization outcomes in HAV infection were observed, with only one subgroup analysis demonstrating a higher rate of mortality. Further research is warranted to better understand these findings and their implications.

Infection and infestation-related adverse events of biologics in psoriasis: insights from the Food and Drug Administration Adverse Event Reporting System (FAERS).

OBJECTIVE: The study aims to thoroughly assess the adverse events related to infections and infestations associated with biological agents used for psoriasis using the U.S. Food and Drug Administration's Adverse Event Reporting System (FAERS) database. METHODS: We analyzed FAERS data from the first quarter of 2004 to the fourth quarter of 2023. The study included TNF-α inhibitors (etanercept, infliximab, adalimumab), IL-12/23 inhibitors (ustekinumab), IL-23p19 inhibitors (guselkumab), and IL-17 inhibitors (secukinumab, ixekizumab). We used disproportionality analysis and Bayesian methods to quantify the related adverse event (AE) signals. RESULTS: Most AEs related to infections and infestations are already listed on the drug packaging labels. Notably, TNF-α inhibitors are associated with a significantly higher incidence of tuberculosis-related diseases compared to other biological agents. In contrast, IL-17 inhibitors show a greater variety and number of fungal infection-related AEs than their counterparts. Furthermore, our study has identified new potential AEs that require the attention of clinicians. CONCLUSION: In clinical practice, it is advisable to monitor the risks of infections and infestations in patients receiving biological agents for psoriasis to enable early detection and intervention. Our findings highlight the need for further epidemiological investigations to establish causality and guide clinical practice in managing these risks effectively.

Emergency department utilization among children with Long COVID symptoms: a COVID-19 research consortium study.

BACKGROUND AND OBJECTIVES: Long COVID, characterized by persistent symptoms beyond the acute infection phase, remains poorly characterized in children. Our study aim is to determine if children who exhibit any symptoms/conditions associated with Long COVID after acute COVID-19 infection have higher Emergency Department (ED) utilization compared to those who do not exhibit these symptoms. METHODS: Data from the HealthJump ambulatory database from the COVID-19 Research Database Consortium was utilized to identify pediatric COVID-19 cases from March 2020 to May 2023. Long COVID cases were defined based on symptoms/conditions occurring 30-180 days after initial COVID diagnosis. Descriptive statistics and multivariable logistic regression models were used to model the relationship between Long COVID and child ED utilization. RESULTS: Out of 130,010 children diagnosed with COVID-19, 43,645 (33.6%) exhibited at least one Long COVID symptom/condition. Children with Long COVID symptoms/conditions had 152% higher odds (OR: 2.52, CI: 2.32-2.73) of ED visits, while those with specific symptoms including "chest pain" had 255% higher odds (AOR: 3.55, CI: 2.73-4.54) and "fluid and electrolyte disturbances" had 229% higher odds (AOR: 3.29, CI: 2.23-4.73) compared to those without those symptoms/conditions. CONCLUSION: This study reveals that children with Long COVID symptoms had notably higher odds of ED visits, with chest pain, fluid imbalances, and generalized pain being most closely linked to such visits. This study highlights the burden of Long COVID on ED providers and underscores the importance of improved guidance for managing Long COVID symptoms in children.

Exploring the association of disease-modifying therapies for multiple sclerosis and BTK inhibitors with epilepsy.

Background: Multiple lines of evidence suggest a role of inflammation in epilepsy. Seizure incidence in patients with multiple sclerosis (MS) is twofold to threefold higher than the age-matched general population. Objectives: To explore the association of MS disease-modifying therapies (DMTs) and FDA-approved Bruton tyrosine kinase inhibitors (for lymphocytic malignancies) with the occurrence of epilepsy using the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Design: Secondary analysis of the FAERS database. Methods: We conducted a disproportionality analysis of FAERS between 2003-Q4 and 2023-Q3. MS DMTs and the Bruton tyrosine kinase inhibitor, ibrutinib, were included in the analysis. An inverse association was defined by a 95% confidence interval (CI) upper limit of reporting odds ratio (ROR) <1. Results: We found an inverse association of ibrutinib, ocrelizumab, ofatumumab, rituximab, and teriflunomide with epilepsy. The strongest inverse association was seen with ibrutinib (ROR: 0.338; 95% CI: 0.218-0.524). Conclusion: Our findings suggest the possibility of considering these medications for repurposing opportunities in epilepsy and support a potential pathogenic role of leukocyte subsets in seizure perpetuation.

How multiple sclerosis treatments and Bruton tyrosine kinase inhibitors may be linked to epilepsy The research presented in this manuscript attempts to elucidate the potential relationship between inflammation and epilepsy. Multiple sclerosis (MS) is the most common inflammatory disorder of the brain and spinal cord in humans. There are over 20 FDA-approved disease-modifying therapies (DMTs) for MS. Other anti-inflammatory agents called Bruton tyrosine kinase (BTK) inhibitors are in clinical development. We show that the use of some DMTs and a BTK inhibitor appear to be associated with a lower chance of epilepsy.

Elevated Triglyceride-Glucose (TyG) Index Predicts Poor Clinical Outcomes in Critically Ill AECOPD Patients: A Retrospective Study.

Purpose: The triglyceride-glucose (TyG) index is a surrogate biomarker of insulin resistance which has been widely used in intensive care unit (ICU) to predict prognosis. However, its role in critically ill acute exacerbation of COPD (AECOPD) patients remains largely unknown. Material and methods: A total of 645 AECOPD patients were induced in this retrospective cohort study, which extracted data from the eICU Collaborative Research Database (eICU-CRD). The TyG index was calculated as Ln (fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2). The primary endpoint includes in-hospital mortality and ICU mortality. The secondary endpoint was sepsis, acute kidney injury (AKI), and acute respiratory failure (ARF). Results: Multivariable Cox regression analysis revealed that the TyG index was independently associated with an increased risk of in-hospital mortality (hazard ratio, HR: 1.45, 95% CI: 1.04-2.01, P = 0.028) and ICU mortality (HR: 2.13, 95% CI: 1.28-3.54, P = 0.004). Moreover, the TyG index was independently associated with an increased risk of sepsis (odds ratio, OR: 1.54, 95% CI: 1.24-1.93, P < 0.001), AKI (OR: 1.57, 95% CI: 1.26-2.02, P < 0.001) and ARF (OR: 1.50, 95% CI: 1.20-1.87, P < 0.001). Kaplan-Meier survival analysis revealed that higher TyG indexes were also related to increased in-hospital mortality and ICU mortality. In addition, the restricted cubic splines regression model demonstrated that the in-hospital mortality and ICU mortality increased linearly with increasing TyG index (P for non-linearity = 0.897, P for non-linearity = 0.897, respectively). Conclusion: Elevated TyG index was independently associated with an increased risk of poor clinical outcomes in critically ill AECOPD patients. A prospective study to define TyG as a biomarker for prognosis prediction in critically ill AECOPD patients is warranted.

Enhancing dietary analysis: Using machine learning for food caloric and health risk assessment.

In the wake of growing concerns regarding diet-related health issues, this study investigates the application of machine learning methods to estimate the energy content and classify the health risks of foods based on the USDA National Nutrient Database. The caloric content of foods was estimated using the nutritional composition (i.e., carbohydrates, protein, total lipid, and total sugar content) and classified based on their weighted health risks, considering their carbohydrate, lipid, and glycemic index levels. The algorithms used for modeling include multiple linear regression (MLR), K-nearest neighbors, support vector machine, random forest regression (RFR), gradient-boosted regression, decision trees (DT), and deep neural networks. The MLR model demonstrated high accuracy on the training dataset (R2 = 0.99, mean absolute error [MAE] = 7.71 kcal, and root mean squared error [RMSE] = 17.89 kcal) and testing dataset (R2 = 0.99, MAE = 7.75 kcal, and RMSE = 18 kcal) in energy estimation, indicating its effectiveness in dietary assessment. The RFR and DT models were useful in categorizing foods into low-health-risk foods, but their performance was reduced in medium and high-health-risk groups. This research contributes to developing tools that could aid in personalized dietary planning and public health interventions to mitigate diet-related health risks. PRACTICAL APPLICATION: This study applies machine learning to estimate how many calories are in food and to understand the health risks different foods might have. By investigating the fats, cholesterol, and sugars in food items listed in a public database, we can better plan diets or develop apps that help people make healthier eating choices. This work aims to improve public access to nutritional information, supporting efforts to combat diet-related diseases through educational materials and applications that guide dietary choices in various settings.

Real-World Assessment of Psychotropic and Antiepileptic Drug Use During Pregnancy in Belgium: Trends, Predictors, and Comparative Risk of Congenital Anomalies (2010-2016).

PURPOSE: To analyze the prescription patterns and sociodemographic factors associated with the use of antipsychotic, antidepressant, and antiepileptic drugs during pregnancy in Belgium, and to investigate their potential association with congenital anomalies. METHODS: Using a nationwide linked database, we identified antidepressants, antipsychotics, and antiepileptics via the Anatomical Therapeutic and Chemical Classification (ATC) codes. For each medication group, we calculated the overall prevalence and prevalence for the three most used medications at the fifth ATC level. Sociodemographic factors influencing medication use during pregnancy were analyzed, and potential associations with congenital anomalies were investigated through logistic regression models based on generalized estimating equations. RESULTS: Overall, 828 016 live births pregnancies associated with 611 094 mothers were identified. We found that the use of antidepressants, antipsychotics, and antiepileptics was decreasing with the arrival of pregnancy. Mothers with a less favorable sociodemographic status were more likely to be exposed to these medications. Antiepileptics used in the first trimester were associated with an increased risk of congenital anomalies (aOR = 1.65, 95% CI 1.11-2.45) compared with unexposed women. The three most used antiepileptics were lamotrigine, valproate, and levetiracetam, among them, we found an association with congenital anomalies only for valproate (aOR = 3.92, 95% CI 2.30-6.67). CONCLUSIONS: Psychotropic and antiepileptic drug use decreased during pregnancy. Pregnant women with a less favorable sociodemographic status were more likely to be exposed to psychotropics and antiepileptics during pregnancy. The elevated risk of congenital anomalies associated with antiepileptics use, particularly valproate, underscores the need for targeted interventions and increased awareness to improve maternal and fetal health outcomes.

Novel linkage of the Society of Thoracic Surgeons database and hospital electronic health records.

BACKGROUND: Society of Thoracic Surgeons Congenital Heart Surgery Database is the largest congenital heart surgery database worldwide but does not provide information beyond primary episode of care. Linkage to hospital electronic health records would capture complications and comorbidities along with long-term outcomes for patients with CHD surgeries. The current study explores linkage success between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health record data in North Carolina and Georgia. METHODS: The Society of Thoracic Surgeons Congenital Heart Surgery Database was linked to hospital electronic health records from four North Carolina congenital heart surgery using indirect identifiers like date of birth, sex, admission, and discharge dates, from 2008 to 2013. Indirect linkage was performed at the admissions level and compared to two other linkages using a "direct identifier," medical record number: (1) linkage between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health records from a subset of patients from one North Carolina institution and (2) linkage between Society of Thoracic Surgeons data from two Georgia facilities and Georgia's CHD repository, which also uses direct identifiers for linkage. RESULTS: Indirect identifiers successfully linked 79% (3692/4685) of Society of Thoracic Surgeons Congenital Heart Surgery Database admissions across four North Carolina hospitals. Direct linkage techniques successfully matched Society of Thoracic Surgeons Congenital Heart Surgery Database to 90.2% of electronic health records from the North Carolina subsample. Linkage between Society of Thoracic Surgeons and Georgia's CHD repository was 99.5% (7,544/7,585). CONCLUSIONS: Linkage methodology was successfully demonstrated between surgical data and hospital-based electronic health records in North Carolina and Georgia, uniting granular procedural details with clinical, developmental, and economic data. Indirect identifiers linked most patients, consistent with similar linkages in adult populations. Future directions include applying these linkage techniques with other data sources and exploring long-term outcomes in linked populations.

Missed Adjuvant Therapy in Human Papillomavirus Positive Oropharyngeal Squamous Cell Carcinoma.

OBJECTIVE: Investigate missed adjuvant therapy and associated disparities in overall survival (OS) for human papillomavirus-associated (HPV+) oropharyngeal squamous cell carcinoma (OPSCC). METHODS: The 2010-2017 National Cancer Database was queried for patients with surgically resected HPV+ OPSCC. Indications for adjuvant radiotherapy (aRT) included pT3-4 classification, pN2-3 classification, lymphovascular invasion, pathologic extranodal extension (pENE), and/or positive surgical margins (PSM). Indication(s) for adjuvant chemoradiotherapy (aCRT) included pENE and/or PSM. Multivariable logistic and Cox regression models were implemented. RESULTS: Of 5297 patients satisfying inclusion criteria, 4288 had indication(s) for aRT; 775 did not receive any adjuvant therapy and were considered as missing aRT. A total of 2234 patients had indication(s) for aCRT. Of these, 1383 (61.9%) received aCRT, 555 (24.8%) patients received aRT alone and were considered as having missed aCRT, and 296 (13.2%) did not receive any adjuvant therapy. Missed aRT and missed aCRT were each associated with age, treatment facility type, pN classification, and surgical margin status (p < 0.015). Among patients with indication(s) for aRT alone, OS of those receiving no adjuvant therapy, aRT alone, and aCRT was 90.0%, 94.8%, and 93.4%, respectively (p = 0.080). Among patients with indication(s) for aCRT, those receiving aRT alone and aCRT had similar OS (89.0% vs. 86.6%, p = 0.357) which was superior to receiving no adjuvant therapy (74.9%, p < 0.001). These patterns in OS persisted on multivariable Cox regression. CONCLUSION: Among patients with HPV+ OPSCC and indication(s) for aRT, missed aRT was not associated with worse OS. For patients with indication(s) for aCRT, aRT alone was associated with similar OS as aCRT. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Differences in safety profiles of anti-herpesvirus medications: a real-world pharmacovigilance study based on the FAERS database.

BACKGROUND: Anti-herpesvirus drug safety profiles have not been systematically compared. Understanding variations in adverse events (AEs) could provide reference for rational clinical use. METHODS: We collected data on acyclovir, ganciclovir, valaciclovir, and foscarnet from the FDA Adverse Event Reporting System (FAERS) database from Q1 2004 to Q3 2023. Disproportionality analyses were conducted to evaluate risk of AEs. RESULTS: All drugs exhibited significant associations with hematotoxicity, with ganciclovir and foscarnet being more myelosuppressive. The correlation with renal impairment ranked as follows: foscarnet, ganciclovir, valaciclovir, and acyclovir (ROR = 16.72, 7.06, 3.51, and 2.02, respectively). Regarding hepatotoxicity, ganciclovir was associated with acute-on-chronic liver failure (ROR = 52.83), and foscarnet was associated with fulminant hepatitis (ROR = 49.91). In nervous system, acyclovir showed the highest intensity of neurotoxicity (ROR = 14.95). Valaciclovir ranked first in toxic encephalopathy (ROR = 64.70). Foscarnet showed the highest intensity of status epilepticus (ROR = 6.45). Besides, acyclovir showed the strongest association with severe cutaneous adverse reactions (SCARs). CONCLUSIONS: Our study revealed differences in safety profiles of four anti-herpesvirus medications. Ganciclovir exhibited the highest risk of hematotoxicity but appeared relatively safe in seizures and SCARs. Foscarnet was more likely to induce nephrotoxicity, seizures, and electrolyte imbalances than others. Acyclovir and valaciclovir were strongly associated with plasmacytosis, neurotoxicity, and SCARs.

T-CLEARE: a pilot community-driven tissue clearing protocol repository.

Selecting and implementing a tissue clearing protocol is challenging. Established more than 100 years ago, tissue clearing is still a rapidly evolving field of research. There are currently many published protocols to choose from, and each performs better or worse across a range of key evaluation factors (e.g., speed, cost, tissue stability, fluorescence quenching). Additionally, tissue clearing protocols are often optimized for specific experimental contexts, and applying an existing protocol to a new problem can require a lengthy period of adaptation by trial and error. Although the primary literature and review articles provide a useful starting point for optimization, there is growing recognition that results can vary dramatically with changes to tissue type or antibody used. To help address this issue, we have developed a novel, freely available repository of tissue clearing protocols named T-CLEARE (Tissue CLEAring protocol REpository; https://doryworkspace.org/doryviz). T-CLEARE incorporates community responses to an open survey designed to capture details not commonly found in the scientific literature, including modifications to published protocols required for specific use cases and instances when tissue clearing protocols did not perform well (negative results). The goal of T-CLEARE is to help the community share evaluations and modifications of tissue clearing protocols for various tissue types and potentially identify best-in-class methods for a given application.

Traditional Chinese Medicine Herbs for Breast Cancer Prevention and Survival: A Narrative Review of Epidemiological Studies from Taiwan.

PURPOSE OF REVIEW: This review aims to describe the association of integrating traditional Chinese medicine (TCM) herbs into conventional medicine (CM) in preventing breast cancer and improving survival rates among breast cancer patients of Taiwan. RECENT FINDINGS: Of 7 relevant studies, spanning 2014-2023, 4 investigated breast cancer risk in women with menopausal symptoms and other comorbidities. All 4 reported that TCM herbal use was associated with lower risks of developing breast cancer. Three studies investigated survival in newly-diagnosed breast cancer patients receiving CM. All reported that adjunctive TCM users had lower mortality rates than CM-only patients. However, the heterogeneity of study designs, populations, and interventions may limit the generalizability and robustness of the findings. TCM herbs may promote breast cancer prevention and survival when used alongside CM. More rigorous observational research and clinical trials in specific patient populations are needed to guide clinical decision-making.

Impact of waitlist weight change on outcomes in heart transplant recipients: a UNOS database analysis.

BACKGROUND: While the effect of pre-transplant weight on patient outcomes following heart transplantation (HTx) has previously been studied, data regarding the impact of dynamic weight change prior to HTx are extremely limited. OBJECTIVES: We sought to elucidate the interaction between HTx listing weight and weight change while waitlisted, and explore how that interaction impacts post-HTx survival in a continuous manner. METHODS: Adult patients listed for HTx from 1987 to 2020 were identified from UNOS database. Three-dimensional restricted cubic spline analysis explored post-HTx survival relative to both changes in BMI/weight and BMI at time of HTx listing. Continuous predictor variables were analyzed with Cox proportional hazards method. RESULTS: 9,628 included patients underwent HTx. Median recipient age was 55 [IQR 46-62] years, and 21% were females. 53% of patients lost while 47% gained weight on the waitlist. Median BMI (27.6 kg/m2 [24.3-31.3] vs. 27.4 kg/m2 [24.2-30.9], paired p < 0.001) and weight (84.8 kg [73.0-98.0] kg vs. 84.4 kg [72.6-96.6], p < 0.001) were similar at listing and transplant. One-year survival was 89.3%. Weight loss over 3 BMI points or 10 kg was associated with higher hazard of death irrespective of listing BMI. In non-obese patients, some weight gain (1-4 BMI points or 5-15 kg) was associated with improved survival. In cachectic patients (BMI < 18.5), failure to gain weight was associated with worse survival. CONCLUSIONS: Impact of weight change varies depending on listing BMI. While a survival benefit is seen in non-obese patients who gain some weight, significant weight loss is associated with poorer survival.

Understanding disparities in cardiovascular death rates among older adults with sick sinus syndrome in the US.

Background: Sick sinus syndrome (SSS) increases with age, and approximately one in 600 patients above 65 develop this condition. In this study, the authors assessed trends in mortality related to SSS among older adults ≥65 years of age in the United States from 1999 to 2019. Methods: Trends in cardiovascular mortality related to SSS were identified by analyzing the data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database, where cardiovascular deaths were listed as the underlying cause of death and SSS was listed as the contributing cause of death between 1999 and 2019. Age-adjusted mortality rates (AAMR) per 1,000,000 population were determined. Results: Between 1999 and 2019, a total of 41,615 SSS-related deaths occurred in older adults. Of these, 17,466 (41.9%) were men and 24,149 (58.1%) were women. Although a decline in cardiovascular mortality related to SSS was apparent from 1999 to 2014, a steep rise was noted from 2014 to 2019 [Annual Percentage Change (APC): 2.9%; 95% CI, 1.5-5.7]. Overall AAMRs were highest among White men (AAMR: 55.8; 95% CI, 54.9-56.6), followed by Black men (AAMR: 44.8; 95% CI, 42-47.6), White women (AAMR: 43.3; 95% CI, 42.8-43.9), and Black women (AAMR: 39.4; 95% CI, 37.6-41.2). Rural dwellers had higher AAMRs compared to urban dwellers. Notably, rural dwellers had a period of stability between 2014 and 2019, while an increase in mortality was apparent among urban dwellers during this period. Lastly, states in the 90th percentile displayed approximately two fold higher AAMR compared to those in the bottom 10th percentile. Conclusion: Sick sinus syndrome-related mortality trends have shown a steady rise from 2014 to 2019. Moreover, NH White adults, rural dwellers, and individuals residing in the states among the 90th percentile demonstrated significantly higher AAMRs. Thus, further investigations and actions are required to reverse these rising trends.

Development and validation of a prognostic nomogram for predicting liver metastasis in thyroid cancer: a study based on the surveillance, epidemiology, and end results database.

This study aimed to create a prognostic nomogram to predict the risk of liver metastasis (LM) in thyroid cancer (TC) patients and assess survival outcomes for those with LM. Data were collected from the SEER database, covering TC patients from 2010 to 2020, totaling 110,039 individuals, including 142 with LM. Logistic regression and stepwise regression based on the Akaike information criterion (AIC) identified significant factors influencing LM occurrence: age, histological type, tumor size, bone metastasis, lung metastasis, and T stage (p < 0.05). A nomogram was constructed using these factors, achieving a Cindex of 0.977, with ROC curve analysis showing an area under the curve (AUC) of 0.977. For patients with TCLM, follicular TC, medullary TC, papillary TC, and examined regional nodes were associated with better prognosis (p < 0.001, HR < 1), while concurrent brain metastasis indicated poorer outcomes (HR = 2.747, p = 0.037). In conclusion, this nomogram effectively predicts LM risk and evaluates prognosis for TCLM patients, aiding clinicians in personalized treatment decisions.

Parathyroid carcinoma and atypical parathyroid tumor: Analysis of an Italian database.

OBJECTIVE: Atypical parathyroid tumor (aPT) and parathyroid carcinoma (PC) are extremely rare parathyroid neoplasms, accounting together for less than 2% of all parathyroid tumors. They often present an overlapping clinical phenotype, sharing clinical, biochemical, and some histological features. They are distinguished only by the presence of local invasion, and lymph nodes or distant metastasis, which are all absent in aPTs. To date, only few studies have compared clinical presentation and features between aPTs and PCs.Our purpose was to conduct a retrospective study on a multicenter Italian database of aPT and PC patients. DESIGN AND METHODS: We comparatively analyzed main features of aPT (n=57) and PC (n=74) patients collected at 15 major endocrinology and endocrine surgery centers in Italy. RESULTS AND CONCLUSIONS: aPTs and PCs showed no significant differences in many clinical features, and presented similar values of elevated parathyroid hormone and total serum calcium. Renal complications, namely nephrolithiasis and nephrocalcinosis, appeared to be more common in PC, with a significantly higher rate of renal colic, regardless of total serum calcium levels and 24-hour calciuria. PCs showed significantly higher post-operative disease persistence and recurrence rates, presumably due to an uncomplete resection of the primary tumor in 23.5% of cases and/or presence of unremoved active metastasis, but they had similar disease-free mean time after surgery than aPT.To deepen the study of malignant parathyroid tumors, the institution of a novel Italian retro-prospective multicenter registry of aPTs and PCs is currently ongoing, and a dedicated PC European registry has been recently activated.

A clinical prediction model for distant metastases of pediatric neuroblastoma: an analysis based on the SEER database.

Background: Patients with distant metastases from neuroblastoma (NB) usually have a poorer prognosis, and early diagnosis is essential to prevent distant metastases. The aim was to develop a machine-learning model for predicting the risk of distant metastasis in patients with neuroblastoma to aid clinical diagnosis and treatment decisions. Methods: We built a predictive model using data from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2018 on 1,542 patients with neuroblastoma. Seven machine-learning methods were employed to forecast the likelihood of neuroblastoma distant metastases. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for building machine learning models. Secondly, the subject operating characteristic area under the curve (AUC), Precision-Recall (PR) curves, decision curve analysis (DCA), and calibration curves were used to assess model performance. To further explain the optimal model, the Shapley summation interpretation method (SHAP) was applied. Ultimately, the best model was used to create an online calculator that estimates the likelihood of neuroblastoma distant metastases. Results: The study included 1,542 patients with neuroblastoma, multifactorial logistic regression analysis showed that age, histology, tumor size, tumor grade, primary site, surgery, chemotherapy, and radiotherapy were independent risk factors for distant metastasis of neuroblastoma (P < 0.05). Logistic regression (LR) was found to be the optimal algorithm among the seven constructed, with the highest AUC values of 0.835 and 0.850 in the training and validation sets, respectively. Finally, we used the logistic regression model to build a network calculator for distant metastasis of neuroblastoma. Conclusion: The study developed and validated a machine learning model based on clinical and pathological information for predicting the risk of distant metastasis in patients with neuroblastoma, which may help physicians make clinical decisions.

Development of a comprehensive open access "molecules with androgenic activity resource (MAAR)" to facilitate risk assessment of chemicals.

The increasing prevalence of endocrine-disrupting chemicals (EDCs) and their potential adverse effects on human health underscore the necessity for robust tools to assess and manage associated risks. The androgen receptor (AR) is a critical component of the endocrine system, playing a pivotal role in mediating the biological effects of androgens, which are male sex hormones. Exposure to androgen-disrupting chemicals during critical periods of development, such as fetal development or puberty, may result in adverse effects on reproductive health, including altered sexual differentiation, impaired fertility, and an increased risk of reproductive disorders. Therefore, androgenic activity data is critical for chemical risk assessment. A large amount of androgenic data has been generated using various experimental protocols. Moreover, the data are reported in different formats and in diverse sources. To facilitate utilization of androgenic activity data in chemical risk assessment, the Molecules with Androgenic Activity Resource (MAAR) was developed. MAAR is the first open-access platform designed to streamline and enhance the risk assessment of chemicals with androgenic activity. MAAR's development involved the integration of diverse data sources, including data from public databases and mining literature, to establish a reliable and versatile repository. The platform employs a user-friendly interface, enabling efficient navigation and extraction of pertinent information. MAAR is poised to advance chemical risk assessment by offering unprecedented access to information crucial for evaluating the androgenic potential of a wide array of chemicals. The open-access nature of MAAR promotes transparency and collaboration, fostering a collective effort to address the challenges posed by androgenic EDCs.