Summary Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified...

Background and Objectives: The COVID-19 pandemic has led to significant changes globally, which has also affected patients with type 1 diabetes mellitus (T1DM). This study aimed to determine the incidence of T1DM and the characteristics of diabetic ketoacidosis (DKA) during the pandemic comparing it to pre-pandemic period. Materials and Methods: Data from patients <19 years with newly diagnosed T1DM between 1st January 2017 and 31st December 2021 from four regional centers in Vojvodina were retrospectively collected and analyzed. Results: In 2021, the highest incidence of T1DM in the last five years was recorded, 17.3/100,000. During the pandemic period (2020–2021), there were 99 new-onset T1DM, of which 42.4% presented in DKA, which is significantly higher than in the pre-pandemic period (34.1%). During the pandemic, symptom duration of T1DM lasted significantly longer than before the COVID-19 period. At the age of 10–14 years, the highest incidence of T1DM and COVID-19, the highest frequency rate of DKA, and severe DKA were observed. Conclusions: The pandemic is associated with a high incidence rate of T1DM, longer duration of symptoms of T1DM, a high frequency of DKA, and a severe DKA at diagnosis. Patients aged 10–14 years are a risk group for the occurrence of T1DM with severe clinical presentation. Additional studies are needed with a longer study period and in a wider geographical area, with data on exposure to COVID-19 infection, the permanence of new-onset T1DM, and the psychosocial impact of the pandemic.

Pulse low-intensity electromagnetic field therapy could help as prophylaxis of HO in patients with traumatic SCI.

Pycnogenol® (PYC) has already being used as a food supplement and herbal medicine due to its potent antioxidant properties. The aim of the present study was to examine the protective effect of PYC on acetaminophen‐induced acute liver injury in rats. The effect of PYC on acetaminophen‐induced hepatotoxicity in rats was examined by determining biochemical parameters, in vitro antioxidant activity, histological assessment, and oxidative status in liver homogenates. The best antioxidant properties were demonstrated in methanolic extracts. Seven‐day pretreatment with PYC suppressed elevation of CYP2E1 protein expression induced by administration of toxic dose of acetaminophen. PYC at 50 mg/kg showed the ability to significantly decrease malondialdehyde (MDA) level compared with the group received acetaminophen. Xanthine oxidase (XOD) enzyme activity was significantly elevated in acetaminophen‐treated group compared with control, whereas concomitant administration of PYC in a dose of 50 mg/kg significantly reduced activity of this enzyme. Significant decrease of glutathione (GSH) hepatic content in acetaminophen‐intoxicated rats compared with the control rats was improved by concomitant administration of PYC at 50 mg/kg. Protective effect of PYC on acetaminophen‐induced acute liver injury in rats has showed the best in vitro antioxidant potential expressed in methanolic extract and consequent histological assessment and oxidative status in liver homogenates.

Controlled changes in mitochondrial biogenesis and morphology are required for cell survival and homeostasis, but the molecular mechanisms are largely unknown. Here, male and female prepubertal mice (P21) with insulin and IGF1 receptors deletions in steroidogenic tissues (Insr/Igf1r-DKO) were used to investigate transcription of the key regulators of mitochondrial biogenesis (Ppargc1a, Ppargc1b, Pparg, Nrf1, Tfam) and architecture (Opa1, Mfn1, Mfn2) in Leydig cells, ovaries and adrenals. Results showed that the expression of PGC1, a master regulator of mitochondrial biogenesis and integrator of environmental signals, and its downstream target Tfam, significantly decreased in androgen-producing Leydig cells. This is followed by reduction of Mtnd1, an mtDNA encoded transcript whose core subunit belongs to the minimal assembly required for catalysis. The same markers remained unchanged in ovaries. In contrast, in adrenals, the pattern of transcripts for mitochondrial biogenesis markers was the same in both sexes, but opposite from that observed in Leydig cells. The level of transcripts for markers of mitochondrial architecture (Mfn1, Mfn2) significantly increased in Leydig cells from Insr/Igf1r-DKO, but not in ovaries. This was followed by mitochondrial morphology disturbance, suggesting that the mitochondrial phase of steroidogenesis could be affected. Indeed, basal and pregnenolone stimulated progesterone productions in the mitochondria of Leydig cells from Insr/Igf1r-DKO decreased more than androgen production, and were barely detectable. Our results are the first to show that INSR and IGF1R are important for mitochondrial biogenesis in gonadal steroidogenic cells of prepubertal males, but not females and they serve as important regulators of mitochondrial architecture and biogenesis markers in Leydig cells.