Pontifícia Universidade Católica do Rio Grande do Sul

Cystic fibrosis (CF) is an autosomal recessive disease that alters ionic transport in the body's secretions, including those of the lung mucosa, and is the most common hereditary respiratory disease in the Western world. One of the causes of morbidity and decreased quality of life in patients with CF is osteoporosis, which is currently assessed by bone densitometry. bi-centric, cross-sectional, retrospective study, reviewing data contained in the medical records of patients with cystic fibrosis participants who were treated at 2 CF reference centers, and reanalysis of chest tomography scans performed annually during checkup, in comparison with their bone densitometry measurements from the same period. A total of 73 CF patients were evaluated. Patients with DXA-defined osteoporosis showed significantly lower HU values. Using 215HU as the cutoff, we obtained 83% sensitivity and 68% specificity for osteoporosis. Area under the ROC curve was 0.86 using analyses of T10 to T12 vertebrae. Chest computed tomography may serve as an opportunistic screening for identifying patients with cystic fibrosis at increased risk of low bone mineral density, particularly when CT examinations are already being performed for other clinical reasons.

Este artigo, de autoria da Climbe Investimentos, analisa a tecnologia blockchain como motor da tokenização para a democratização dos investimentos. O estudo aborda como as barreiras do sistema financeiro tradicional, como altos aportes e burocracia, limitam o acesso de pequenos investidores a ativos reais. Através da fundamentação em redes descentralizadas e smart contracts, demonstra-se que a fragmentação de ativos em tokens digitais reduz custos e elimina intermediários. São discutidos os security tokens (padrão ERC 1400), que garantem conformidade regulatória e segurança jurídica. Explora-se ainda o impacto das Finanças Descentralizadas (DeFi) e das CBDCs na infraestrutura global. Os resultados indicam que a tokenização amplia a liquidez de ativos ilíquidos e promove transparência via ledger distribuído. A intenção da Climbe Holding com o presente artigo é validar a economia digital inclusiva e a superação de exclusões geográficas e financeiras no mercado global.

ABSTRACTAdvanced chronic liver disease (ACLD) remains a major cause of global morbidity and mortality. Preventing hepatic decompensation—both the first event and subsequent recurrences—has become a central therapeutic goal to prolong survival. The transition from the compensated phase (cACLD) to the decompensated phase (dACLD) is driven by clinically significant portal hypertension (CSPH) and continuous exposure to etiologic factors, and is often precipitated by systemic triggers such as infections, portal vein thrombosis, and hepatocellular carcinoma. Thus, effective prevention requires a multidisciplinary strategy combining etiologic control with hemodynamic modulation, supported by vaccination, optimized nutrition and physical activity, judicious endoscopic therapy, and a critical reassessment of antibiotic prophylaxis in the era of antimicrobial resistance. Among non‐selective beta‐blockers (NSBBs), carvedilol—through combined β1/β2 and α1 blockade—achieves a greater reduction in hepatic venous pressure gradient (HVPG) than propranolol and demonstrates superiority in preventing first decompensation. In dACLD, although the effect of NSBBs is attenuated, carvedilol still emerges as the preferred option, given that propranolol shows significantly lower efficacy at this stage. Endoscopic variceal ligation (EVL) remains an alternative for NSBB‐intolerant patients in cACLD and is essential for secondary prophylaxis. Moreover, in dACLD, the combination of EVL with carvedilol is increasingly being explored in Child‐Pugh B/C patients. We provide an overview of pathophysiological mechanisms, risk stratification using non‐invasive tests, and pragmatic prevention strategies across the different stages of disease, emphasizing recompensation, the NSBB “therapeutic window,” and the need to revisit routine antibiotic prophylaxis.

Lung cancer (LC) incidence and mortality rates are increasing in Brazil, particularly among women. Studies indicate that sex may affect incidence, survival, and treatment response. However, overlooked or unknown risk factors may also play a role in the sex disparities observed. For instance, although smoking is a major risk factor for LC, increasing rates of LC among nonsmoking women in Brazil, and elsewhere, have been observed. Also, traditional gender roles expose women to specific environmental hazards, as they are often expected to perform domestic tasks and thus are more likely to be indoors and exposed to second-hand smoke, air pollution from cooking fuels, and radon. In addition, occupational hazards such as formaldehyde, particularly in hairdressing, disproportionately affect women. This narrative review highlights the disparities associated with LC and female sex in Brazil, and calls for more research on these overlooked risk factors.

168 Background: In the phase 3 TALAPRO-2 study, talazoparib (TALA) + enzalutamide (ENZA) significantly improved radiographic progression-free survival (rPFS) and overall survival (OS) vs placebo (PBO) + ENZA as first-line treatment (tx) in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) unselected (cohort 1) and selected for homologous recombination repair gene alterations (HRRm cohort). Here, we report post-hoc analyses of PSA kinetics from the final OS analysis cutoff date. Methods: Pts were randomized 1:1 to ENZA 160 mg + either TALA 0.5 mg or PBO once daily. The primary endpoint was rPFS; OS, a key secondary endpoint. We performed post hoc analyses of PSA flare (defined as a rise in PSA above baseline followed by a return to baseline or lower within 12 months), PSA response ≥50% (PSA50), PSA response ≥90% (PSA90), undetectable PSA (defined as PSA <0.2 ng/mL), and duration of PSA response. OS and rPFS were analyzed in PSA50 responders. Results: At data cutoff (Sep 3, 2024), PSA flare was observed in 2–3% of pts in both tx arms of the unselected and HRRm cohorts (Table). The median time for PSA to decline back to or below baseline after a rise above baseline was 57 days in both tx arms in the unselected cohort, and 60 and 117 days with TALA + ENZA and PBO + ENZA, respectively, in the HRRm cohort (Table). A greater proportion of pts taking TALA + ENZA achieved PSA50, PSA90, and undetectable PSA compared with PBO + ENZA in both cohorts (Table). In both cohorts, pts in the TALA + ENZA arm also had a longer median duration of PSA50 response, PSA90 response, and undetectable PSA vs PBO + ENZA (Table). In the unselected cohort, rPFS and OS directionally favored TALA + ENZA vs PBO + ENZA in PSA50 responders (rPFS HR: 0.72 [95% CI 0.57, 0.89], median 39.8 vs 27.6 months; OS HR: 0.90 [0.72, 1.13], median 53.3 vs 47.3 months). Similarly, in the HRRm cohort, rPFS and OS favored TALA + ENZA in PSA50 responders (rPFS HR: 0.51 [0.38, 0.70], median 36.1 vs 18.3 months; OS HR: 0.62 [0.44, 0.86], median not reached vs 38.2 months). Conclusions: In both cohorts, a greater proportion of pts in the TALA + ENZA arm achieved PSA responses with longer durations vs PBO + ENZA. Also, PSA flare was unusual (2–3%) and resolved in ~60 days (both cohorts) with TALA + ENZA vs ~60 days (unselected) and ~120 days (HRRm) with PBO + ENZA. In both cohorts, OS and rPFS numerically favored TALA + ENZA vs PBO + ENZA in PSA50 responders. Analyses of PSA responses for specific genes (e.g. BRCA2 ) are underway. Clinical trial information: NCT03395197 . Unselected Cohort HRRm Cohort TALA + ENZA (n=402) PBO + ENZA (n=403) TALA + ENZA (n=200) PBO + ENZA (n=199) PSA flare, n (%) 12 (3) 11 (3) 5 (2) 5 (3) Median time for PSA decline back to or below baseline, days 57 57 60 117 PSA50, n (%) 335 (83) 285 (71) 173 (86) 126 (63) Median duration, days 430 284 420 225 PSA90, n (%) 253 (63) 182 (45) 139 (70) 80 (40) Median duration, days 480 419 589 308 Undetectable PSA, n (%) 159 (40) 107 (27) 87 (44) 44 (22) Median duration, days 644 539 650 365

870 Background: Upper tract urothelial carcinoma (UTUC) is a rare malignancy (5–10% of urothelial cancers) with challenging diagnosis and heterogeneous outcomes. Artificial intelligence (AI)—including radiomics, machine learning (ML), deep learning (DL), and digital pathology—has emerged as a tool to improve detection, risk stratification, and treatment planning. Methods: A systematic literature review (PubMed, Scopus, Embase) to August 2025 identified original human studies using AI for UTUC diagnosis or prognosis. Extracted data included sample size, AI methodology, validation type, and key performance metrics. Results: Twenty-one studies met inclusion criteria (2018–2025): CT urography radiomics (n = 12), prognostic perirenal fat/peritumoral texture analysis (n = 2), AI-assisted urine cytology (n = 2), DL-based digital pathology (n = 2), and multimodal models integrating imaging and clinical/molecular data (n = 3). Radiomics achieved AUCs of 0.80–0.94 for grading/staging; multimodal approaches improved predictive accuracy (ΔAUC ≈ +0.06). AI-assisted cytology reached sensitivity > 85% for recurrence detection, and digital pathology predicted lymph-node status with AUC up to 0.85. Most studies were retrospective and single-center; only 14% reported external validation. Conclusions: AI shows strong promise for UTUC diagnosis and prognostication, particularly via CT radiomics and multimodal integration. However, clinical adoption requires multicenter prospective validation, standardized imaging/pathology workflows, regulatory approval, and cost-effectiveness evaluation.