tbuckley/cabot-search huggingface dataset:
Study of the dosimetry, safety, and potential benefit of 177Lu-PSMA-617 radionuclide therapy prior to radical prostatectomy in men with high-risk localized prostate cancer (LuTectomy study).
Authors: Omar Alghazo, Renu Eapen, Nattakorn Dhiantravan, John A. Violet, Price Jackson, Mark Scalzo, Simon P. Keam, Catherine Mitchell, Paul J. Neeson, Shahneen Kaur Sandhu, Scott Williams, Daniel Moon, Nathan Lawrentschuk, Arun Azad, Michael S Hofman, Declan G. Murphy
Journal: Journal of Clinical Oncology (2021)

TPS264 Background: High-risk localised prostate cancer (HRCaP) is treated by radical prostatectomy (RP) or radiotherapy. Despite curative intent, a significant number of men will progress with metastatic disease or local recurrence. Lutetium-177 radiolabelled to the small molecule PSMA-617 targeting prostate-specific membrane antigen (Lu-PSMA) has proven efficacious in men with metastatic castration-resistant prostate cancer who have progressed after standard-of-care. The LuTectomy trial evaluates whether administration of Lu-PSMA before radical prostatectomy in men with HRCaP will deliver high doses of radiation to the prostate and involved lymph nodes. It also aims to assess the feasibility, safety profile and oncological efficacy of Lu-PSMA. Methods: Lutectomy is an open-label, phase I/II non-randomised clinical trial. 20 men with HRCaP defined by European Association of Urology who are scheduled for RP and pelvic lymph node dissection (PLND) will be recruited. All men will have high PSMA-avidity with a standardised uptake value (SUVmax) of ≥ 20 on 68 Ga-PSMA PET/CT. The initial 10 participants will receive one cycle of 5GBq Lu-PSMA intravenously and the latter 10 men will receive two cycles of 5GBq Lu-PSMA per cycle six weeks apart. RP with PLND will be performed six weeks later. Participants will be followed up for three years. The primary outcome is to determine the radiation absorbed dose in the prostate and involved lymph nodes. Three-time point quantitative single-photon emission computed tomography (SPECT/CT) will be used to estimate radiation dosimetry using a voxelated technique incorporating partial volume correction. Marrow absorbed dose will also be evaluated using serial blood measures to model pharmacokinetic clearance with a multi-phase exponential model. Translational research samples will include the original biopsy, prostatectomy specimen and plasma/whole blood samples. Secondary objectives include evaluation of the PSMA PET/CT imaging response (defined by SUVmax decline &gt;30%), PSA response, pathological response following Lu-PSMA, adverse effects of Lu-PSMA, surgical safety, and health-related quality of life. Post estimates for time-to-event endpoints will be estimated using the Kaplan-Meier method. The first patient was recruited in July 2020 and recruitment is expected to take up to two years. ClinicalTrials.gov Identifier: NCT04430192. Funding: Movember and Medical Research Future Fund (MRFF), Endocyte Inc., a Novartis Company, E.J. Whitten Foundation. Clinical trial information: NCT04430192.
Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis
Authors: Aaron Leong, Joanne B. Cole, Laura N. Brenner, James B. Meigs, Jose C. Florez, Josep M. Mercader
Journal: PLoS Medicine (2021)

Background Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses. Methods and findings We selected genetic variants associated with each exposure, including body mass index (BMI), at p &lt; 5 × 10 −8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p &lt; 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m 2 ; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10 −5 ; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m 2 , p = 2.1 × 10 −5 ). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null. Conclusions In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.
Association Between Preterm-Birth Phenotypes and Differential Morbidity, Growth, and Neurodevelopment at Age 2 Years
Authors: Jose Villar, María C. Restrepo-Méndez, Rose McGready, Fernando C. Barros, Cesar G. Victora, Shama Munim, Aris T. Papageorghiou, Roseline Ochieng, Rachel Craik, Hellen C. Barsosio, James A. Berkley, Maria Carvalho, Michelle Fernandes, Leila Cheikh Ismail, Ann Lambert, Shane A. Norris, Eric O. Ohuma, Alan Stein, Chrystelle O. O. Tshivuila-Matala, Krina T. Zondervan, Adele Winsey, Francois Nosten, Ricardo Uauy, Zulfiqar A. Bhutta, Stephen H. Kennedy
Journal: JAMA Pediatrics (2021)

The etiologic complexities of preterm birth remain inadequately understood, which may impede the development of better preventative and treatment measures.To examine the association between specific preterm-birth phenotypes and clinical, growth, and neurodevelopmental differences among preterm newborns compared with term newborns up to age 2 years.The INTERBIO-21st study included a cohort of preterm and term newborn singletons enrolled between March 2012 and June 2018 from maternity hospitals in 6 countries worldwide who were followed up from birth to age 2 years. All pregnancies were dated by ultrasonography. Data were analyzed from November 2019 to October 2020.Preterm-birth phenotypes.Infant size, health, nutrition, and World Health Organization motor development milestones assessed at ages 1 and 2 years; neurodevelopment evaluated at age 2 years using the INTERGROWTH-21st Neurodevelopment Assessment (INTER-NDA) tool.A total of 6529 infants (3312 boys [50.7%]) were included in the analysis. Of those, 1381 were preterm births (mean [SD] gestational age at birth, 34.4 [0.1] weeks; 5148 were term births (mean [SD] gestational age at birth, 39.4 [0] weeks). Among 1381 preterm newborns, 8 phenotypes were identified: no main maternal, fetal, or placental condition detected (485 infants [35.1%]); infections (289 infants [20.9%]); preeclampsia (162 infants [11.7%]); fetal distress (131 infants [9.5%]); intrauterine growth restriction (110 infants [8.0%]); severe maternal disease (85 infants [6.2%]); bleeding (71 infants [5.1%]); and congenital anomaly (48 infants [3.5%]). For all phenotypes, a previous preterm birth was a risk factor for recurrence. Each phenotype displayed differences in neonatal morbidity and infant outcomes. For example, infants with the no main condition detected phenotype had low neonatal morbidity but increased morbidity and hospitalization incidence at age 1 year (odds ratio [OR], 2.2; 95% CI, 1.8-2.7). Compared with term newborns, the highest risk of scoring lower than the 10th centile of INTER-NDA normative values was observed in the fine motor development domain among newborns with the fetal distress (OR, 10.6; 95% CI, 5.1-22.2) phenotype.Results of this study suggest that phenotypic classification may provide a better understanding of the etiologic factors and mechanisms associated with preterm birth than continuing to consider it an exclusively time-based entity.
Perspectives on COVID-19 and cancer immunotherapy: a review series
Authors: Jason D Goldman, Paolo Antonio Ascierto
Journal: Journal for ImmunoTherapy of Cancer (2021)

Practically every aspect of modern life has been upended by the ongoing COVID-19 pandemic caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) that emerged in 2019. Yet, despite substantial disruptions to the day-to-day practices of caring for patients and performing
The impact of the first three months of the COVID-19 pandemic on the Australian trans community
Authors: Sav Zwickl, Lachlan M. Angus, Alex Wong Fang Qi, Ariel Ginger, Kalen Eshin, Teddy Cook, Shalem Y. Leemaqz, Eden Dowers, Jeffrey D. Zajac, Ada S. Cheung
Journal: International Journal of Transgender Health (2021)

Trans and gender diverse individuals (people who identify with a gender different to what was presumed for them at birth) are one of the most medically and socially marginalized groups in our community. The COVID-19 pandemic may compound preexisting depression and thoughts of self-harm or suicide.We aimed to explore the impact of the COVID-19 pandemic on the Australian trans community.An online cross-sectional survey was conducted between 1st May 2020 and 30th June 2020, amidst strict Australia-wide social restrictions. Australian trans people aged ≥16 years were eligible to participate. Survey questions explored the impact of the COVID-19 pandemic on living situation, employment, financial situation, and healthcare. Logistic regression to assess negative impacts due to COVID-19 on depression and thoughts of self-harm or suicide (measured by Patient Health Questionnaire-9 (PHQ-9) are presented as odds ratios (95% confidence interval)).Of 1019 participants, 49.6% reported experiencing financial strain, 22% had reduced working hours, and 22.4% were unemployed (three times the national rate). Concerningly, 61.1% experienced clinically significant symptoms of depression (Patient Health Questionnaire-9 score ≥10), considerably higher than pre-COVID rates for the trans community and over twice the national rate. Moreover, 49% reported thoughts of self-harm or suicide (over three times the national rate) which was more likely if a person experienced cancelation or postponement of gender-affirming surgery (OR 1.56 (1.04, 2.35)), financial strain (OR 1.80 (1.36, 2.38)), or felt unsafe or afraid in their household (OR 1.96 (1.23, 3.08)).Given rates of clinically significant depression and thoughts of self-harm or suicide are far higher in trans people than the general population, specific strategies to improve mental health in the trans community during the COVID-19 pandemic must be made a priority for policymakers, researchers, and health service providers to prevent suicide.Supplemental data for this article is available online at https://doi.org/10.1080/26895269.2021.1890659.
Redefining Attribution From Patient to Health System—How the Notion of “Mistrust” Places Blame on Black Patients—Reply
Authors: Nicole Senft, Mark A. Manning, Susan Eggly
Journal: JAMA Oncology (2021)

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Association of Antihypertensive Drug Target Genes With Psychiatric Disorders
Authors: Solal Chauquet, Zhihong Zhu, Michael C. O’Donovan, James T. R. Walters, Naomi R. Wray, Sonia Shah
Journal: JAMA Psychiatry (2021)

Observational studies have reported associations between antihypertensive medication and psychiatric disorders, although the reported direction of association appears to be dependent on drug class.To estimate the potential effect of different antihypertensive drug classes on schizophrenia, bipolar disorder, and major depressive disorder.This 2-sample mendelian randomization study assessed the association between a single-nucleotide variant (SNV) and drug target gene expression derived from existing expression quantitative trait loci (eQTL) data in blood (sample 1) and the SNV-disease association from published case-control genome-wide association studies (sample 2). Significant associations were corroborated using published brain eQTL and protein QTL data. Participants included 40 675 patients with schizophrenia and 64 643 controls, 20 352 patients with bipolar disorder and 31 358 controls, and 135 458 patients with major depressive disorder and 344 901 controls. Blood eQTL levels were measured in 31 684 individuals from 37 cohorts (eQTLGen consortium); prefrontal cortex eQTLs were measured from the PsychENCODE resource in 1387 individuals; and protein QTLs were measured in cerebral spinal fluid from 544 individuals and plasma from 818 individuals. Data were collected from October 4, 2019, to June 1, 2020, and analyzed from October 14, 2019, to June 6, 2020.Expression levels of antihypertensive drug target genes as proxies for drug exposure, and genetic variants robustly associated with the expression of these genes as mendelian randomization instruments.Risk for schizophrenia, bipolar disorder, and major depressive disorder.A 1-SD lower expression of the angiotensin-converting enzyme (ACE) gene in blood was associated with lower systolic blood pressure of 4.0 (95% CI, 2.7-5.3) mm Hg, but increased risk of schizophrenia (odds ratio [OR], 1.75; 95% CI, 1.28-2.38; P = 3.95 × 10-4). A concordant direction of association was also observed between ACE expression in prefrontal cortex (OR, 1.33; 95% CI, 1.13-1.56) and ACE protein levels in cerebral spinal fluid (OR per 1-SD decrease, 1.12; 95% CI, 1.05-1.19) and plasma (OR per 1-SD decrease, 1.04; 95% CI, 1.01-1.07). We found no evidence for an association between genetically estimated SBP and schizophrenia risk.Findings suggest an adverse association of lower ACE messenger RNA and protein levels with schizophrenia risk. These findings warrant greater pharmacovigilance and further investigation into the effect of ACE inhibitors, particularly those that are centrally acting, on psychiatric symptoms in patients with schizophrenia, as well as the role of ACE inhibitor use in late-onset schizophrenia.
Glycemic Trajectories and Treatment Outcomes of Patients with Newly Diagnosed Tuberculosis: A Prospective Study in Eastern China
Authors: Qiao Liu, Nannan You, Hongqiu Pan, Ye Shen, Peng Lu, Jianming Wang, Wei Lu, Limei Zhu, Leonardo Martinez
Journal: American Journal of Respiratory and Critical Care Medicine (2021)

Rationale: Patients with newly diagnosed tuberculosis often have inconsistent glycemic measurements during and after treatment. Distinct glycemic trajectories after the diagnosis of tuberculosis are not well characterized, and whether patients with stress hyperglycemia have poor treatment outcomes is not known.Objectives: To identify distinct glycemic trajectories from the point of tuberculosis diagnosis to the posttreatment period and to assess the relationship between glycemic trajectories and tuberculosis treatment outcomes.Methods: Patients with newly diagnosed, drug-susceptible tuberculosis and with at least three fasting plasma glucose tests at tuberculosis diagnosis and during the third and sixth month of treatment were identified and included from Jiangsu Province, China. Patients were also given an additional fasting plasma glucose test at 2 and 4 months after treatment.Measurements and Main Results: Several distinct glycemic trajectories from the point of tuberculosis diagnosis to the posttreatment period were found, including consistently normal glycemic testing results (43%), transient hyperglycemia (24%), erratic glycemic instability (12%), diabetes (16%), and consistent hyperglycemia without diabetes (6%). Compared with participants with a consistently normal glycemic trajectory, patients with transient hyperglycemia were more likely to experience treatment failure (adjusted odds ratio [AOR], 4.20; 95% confidence interval [CI], 1.57–11.25; P = 0.004) or erratic glycemic instability (AOR, 5.98; 95% CI, 2.00–17.87; P = 0.001). Patients living with diabetes also had a higher risk of experiencing treatment failure (AOR, 6.56; 95% CI, 2.22–19.35; P = 0.001), and this was modified by glycemic control and metformin use.Conclusions: Among patients with tuberculosis without diabetes, glycemic changes were common and may represent an important marker for patient response to tuberculosis treatment.
Protective effects of VMY-2-95 on corticosterone-induced injuries in mice and cellular models
Authors: Ziru Yu, Dewen Kong, Yu Liang, Xiaoyue Zhao, Guanhua Du
Journal: Acta Pharmaceutica Sinica B (2021)

Nicotinic α4β2 receptor antagonists have drawn increasing attention in the development of new antidepressants. In this study, we aimed to investigate the protective effect of VMY-2-95, the new selective antagonist of α4β2 nicotinic acetylcholine receptor (nAChR) on corticosterone (CORT) injured mice and cellular models. Fluoxetine was applied as a positive control, and the effects of VMY-2-95 were investigated with three different doses or concentrations (1, 3, 10 mg/kg in mice, and 0.003, 0.03, 0.1 μmol/L in cells). As a result, VMY-2-95 showed significant antidepressant-like effects in the CORT injured mice by improving neuromorphic function, promoting hippocampal nerve proliferation, and regulating the contents of monoamine transmitters. Meanwhile, VMY-2-95 exhibited protective effects on cell viability, cell oxidant, cell apoptosis, and mitochondrial energy metabolism on corticosterone-impaired SH-SY5Y cells. Also, the PKA–CREB–BDNF signaling pathway was up-regulated by VMY-2-95 both in vitro and in vivo, and pathway blockers were also combined with VMY-2-95 to verify the effects furtherly. Therefore, we preliminarily proved that VMY-2-95 had protective effects in depressed mice and SH-SY5Y cells against injuries induced by corticosterone. This work indicated that the application of VMY-2-95 is a potential pharmacological solution for depression. This study also supported the development of α4β2 nAChR antagonists towards neuropsychiatric dysfunctions.
Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction
Authors: Rohan Khera, Julian Haimovich, Nathan C. Hurley, Robert McNamara, John A. Spertus, Nihar Desai, John S. Rumsfeld, Frederick A. Masoudi, Chenxi Huang, Sharon-Lise Normand, Bobak J. Mortazavi, Harlan M. Krumholz
Journal: JAMA Cardiology (2021)

Accurate prediction of adverse outcomes after acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making, and novel methods hold promise for using existing data to generate additional insights.To evaluate whether contemporary machine learning methods can facilitate risk prediction by including a larger number of variables and identifying complex relationships between predictors and outcomes.This cohort study used the American College of Cardiology Chest Pain-MI Registry to identify all AMI hospitalizations between January 1, 2011, and December 31, 2016. Data analysis was performed from February 1, 2018, to October 22, 2020.Three machine learning models were developed and validated to predict in-hospital mortality based on patient comorbidities, medical history, presentation characteristics, and initial laboratory values. Models were developed based on extreme gradient descent boosting (XGBoost, an interpretable model), a neural network, and a meta-classifier model. Their accuracy was compared against the current standard developed using a logistic regression model in a validation sample.A total of 755 402 patients (mean [SD] age, 65 [13] years; 495 202 [65.5%] male) were identified during the study period. In independent validation, 2 machine learning models, gradient descent boosting and meta-classifier (combination including inputs from gradient descent boosting and a neural network), marginally improved discrimination compared with logistic regression (C statistic, 0.90 for best performing machine learning model vs 0.89 for logistic regression). Nearly perfect calibration in independent validation data was found in the XGBoost (slope of predicted to observed events, 1.01; 95% CI, 0.99-1.04) and the meta-classifier model (slope of predicted-to-observed events, 1.01; 95% CI, 0.99-1.02), with more precise classification across the risk spectrum. The XGBoost model reclassified 32 393 of 121 839 individuals (27%) and the meta-classifier model reclassified 30 836 of 121 839 individuals (25%) deemed at moderate to high risk for death in logistic regression as low risk, which were more consistent with the observed event rates.In this cohort study using a large national registry, none of the tested machine learning models were associated with substantive improvement in the discrimination of in-hospital mortality after AMI, limiting their clinical utility. However, compared with logistic regression, XGBoost and meta-classifier models, but not the neural network, offered improved resolution of risk for high-risk individuals.