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Deep-learning-based methods play an important role in pansharpening that uses panchromatic images to enhance the spatial resolution of multispectral images while maintaining spectral features. However, most existing methods mainly consider only one fixed degradation in the training process. Therefore, their performance may drop significantly when the degradation of testing data is unknown (blind) and different from the training data, which is common in real-world applications. To address this issue, we proposed a deep variational network for blind pansharpening, named VBPN, which integrates degradation estimation and image fusion into a whole Bayesian framework. First, by taking the noise and blurring parameters of the multispectral image with the noise parameters of the panchromatic image as hidden variables, we parameterize the approximate posterior distribution for the fusion problem using neural networks. Since all parameters in this posterior distribution are explicitly modeled, the degradation parameters of the multispectral image and the panchromatic image are easily estimated. Furthermore, we designed VPBN composed of degradation estimation and image fusion subnetworks, which can optimize the fusion results guided by the variational inference according to the testing data. As a result, the blind pansharpening performance can be improved. In general, VPBN has good interpretability and generalization ability by combining the advantages of model-based and deep-learning-based approaches. Experiments on simulated and real datasets prove that VPBN can achieve state-of-the-art fusion results.

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INTRODUCTION: Asciminib is primarily utilized for treating Philadelphia chromosome-positive chronic myeloid leukemia in its chronic phase among patients harboring the T315I mutation or those who have been previously treated with at least two tyrosine kinase inhibitors. The safety profile of asciminib across a broad patient population over an extended timeframe remains unverified. This study uses a real-world pharmacovigilance database to evaluate the adverse events (AEs) linked with asciminib, providing valuable insights for clinical drug safety. METHODS: Data from the FDA Adverse Event Reporting System (FAERS) database, spanning from October 2021 to December 2023, served as the basis for this analysis. The extent of disproportional events was assessed using sophisticated metrics such as the reporting odds ratio, proportional reporting ratio, information component, and empirical Bayesian geometric mean. RESULTS: Within the specified period, the FAERS database documented 3,913,574 AE reports, with asciminib being associated with 966 incidents. Reactions to asciminib spanned 27 system organ categories. Utilizing four distinct analytical algorithms, 663 significant preferred terms exhibiting disproportional frequencies were identified. Notably, this investigation uncovered 26 significant AEs linked to off-label asciminib use, encompassing conditions such as gynecomastia, nephrotic syndrome, orchitis, pyelonephritis, hepatotoxicity, and pancreatitis. The median onset time for asciminib-related AEs was 52.5 days, ranging from 17 to 122.75 days. CONCLUSION: The study sheds light on additional potential AEs associated with asciminib use, warranting further research to confirm these findings.

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BACKGROUND: Tamoxifen (TAM) is recommended as the first-line strategy for men with estrogen receptor (ER)-positive early breast cancer who are candidates for adjuvant endocrine therapy in ASCO guideline. Our study aims to analyze the cost-effectiveness of receiving adjuvant endocrine therapy with TAM compared to no TAM, and to assess the cost-effectiveness of using TAM with high adherence over low adherence for ER-positive early male breast cancer in the USA. METHODS: Two Markov models comprising three mutually exclusive health states were constructed: (1) the first Markov model compared the cost-effectiveness of adding TAM with not using TAM (TAM versus Not-TAM); (2) the second model compared the cost-effectiveness of receiving TAM with high adherence and low adherence (High-adherence-TAM versus Low-adherence-TAM). The simulation time horizon for both models was the lifetime of patients. The efficacy and safety data of two models were elicited from the real-world studies. Model inputs were derived from the US website and published literature. The main outcomes of two models both included the total cost, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). RESULTS: In the first model, TAM yielded an ICER of $5707.29 per QALY compared to Not-TAM, which was substantially below the WTP threshold of $50,000.00 per QALY in the USA. Probabilistic sensitivity analysis results demonstrated a 100.00% probability of cost-effectiveness for this strategy. In the second model, High-adherence-TAM was dominated absolutely compared to Low-adherence-TAM. The High-adherence-TAM was cost-effective with a 99.70% probability over Low-adherence-TAM when WTP was set as $50,000.00/QALY. All of these parameters within their plausible ranges did not reversely change the results of our models. CONCLUSIONS: Our study will offer valuable guidance for physicians or patients when making treatment decisions and provide an effective reference for decision-making to consider the appropriate allocation of funds to this special group.

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BACKGROUND: Sepsis is a life-threatening disease accompanied by disorders of the coagulation and immune systems. P2Y12 inhibitors, widely used for arterial thrombosis prevention and treatment, possess recently discovered anti-inflammatory properties, raising potential for improved sepsis prognosis. METHOD: We conducted a retrospective analysis using the data from Medical Information Mart for Intensive Care-IV database. Patients were divided into an aspirin-alone group versus a combination group based on the use of a P2Y12 inhibitor or not. Differences in 30-day mortality, length of stay (LOS) in intensive care unit (ICU), LOS in hospital, bleeding events and thrombotic events were compared between the two groups. RESULT: A total of 1701 pairs of matched patients were obtained by propensity score matching. We found that no statistically significant difference in 30-day mortality in aspirin-alone group and combination group (15.3% vs. 13.7%, log-rank p = 0.154). In addition, patients received P2Y12 inhibitors had a higher incidence of gastrointestinal bleeding (0.5% vs. 1.6%, p = 0.004) and ischemic stroke (1.7% vs. 2.9%, p = 0.023), despite having a shorter LOS in hospital (11.1 vs. 10.3, days, p = 0.043). Cox regression showed that P2Y12 inhibitor was not associated with 30-day mortality (HR = 1.14, 95% CI 0.95-1.36, p = 0.154). CONCLUSION: P2Y12 inhibitors did not provide a survival benefit for patients with sepsis 3 and even led to additional adverse clinical outcomes.

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Brentuximab vedotin (BV) has obtained approval for the therapeutic management of classical Hodgkin lymphoma as well as systemic anaplastic large cell lymphoma. Given the inherent constraints of conventional clinical trials, the correlation between BV and cardiac adverse events (AEs) remains enigmatic. The objective of this investigation is to comprehensively assess cardiac AEs attributed to BV by employing advanced data mining techniques, utilizing the FDA Adverse Event Reporting System (FAERS). The indices for the assessment of disproportionality encompass the reporting odds ratio (ROR), the proportional reporting ratio, the information component, and the empirical Bayesian geometric mean. Employing these sophisticated metrics, we gauged the extent of disproportionate occurrences. The dataset was sourced from the FAERS from the first quarter of 2012 to first quarter of 2023, facilitating a comprehensive analysis of the potential correlation between BV and cardiac AEs. This scrutiny encompassed a comparative analysis of both cardiac and non-cardiac AEs. A total of 495 cases of BV's cardiac AEs were discerned, with the identification of 31 preferred terms (PTs). Among these, 8 PTs emerged as conspicuous signals of cardiac AEs, notably encompassing ventricular hypokinesia (ROR 7.59), tachyarrhythmia (ROR 7.06), sinus tachycardia (ROR 6.18), cardiopulmonary failure (ROR 4.44), pericardial effusion (ROR 4.32), acute coronary syndrome (ROR 4.02), cardiomyopathy (ROR 3.30), and tachycardia (ROR 2.76). The manifestation of severe outcomes demonstrates a discernible correlation with the cardiac AEs (P < 0.001). Our investigation furnishes invaluable insights for healthcare practitioners to proactively mitigate the incidence of BV-associated cardiac AEs.

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Anti-tumor necrosis factor (anti-TNF) agents are widely applied for patients with inflammatory bowel disease (IBD); however, the timing of the last dosing for IBD pregnancy and time to elimination in anti-TNF agent-exposed infants is controversial. This study aimed to determine the optimal timing for the last dosing of anti-TNF agents (infliximab, adalimumab, and golimumab) in pregnant women with IBD, as well as to investigate the recommended vaccine schedules for infants exposed to these drugs. A physiologically-based pharmacokinetic (PBPK) model of anti-TNF agents was built for adults and extrapolated to pregnant patients, fetuses, and infants. The PBPK models successfully predicted and verified the pharmacokinetics (PKs) of infliximab, adalimumab, and golimumab in pregnancy, fetuses, and infants. The predicted PK data were within two-fold of the observed data. The simulated results were used as timing advice. According to the dose of administration, the suggested timing of the last dosing for infliximab, adalimumab, and golimumab is successfully provided based on PBPK predictions. PBPK models indicated that, for infants, the advocated timing of vaccination is 12, 8, and 5 months after birth for infliximab, adalimumab, and golimumab, respectively. Our study illustrated that PBPK models can provide a valuable tool to predict the PKs of large macromolecules in pregnant women, fetuses, and infants, ultimately informing drug-treatment decisions for pregnancy and vaccination regimens for infants.

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Pregabalin (PGB) is widely used clinically; however, its pharmacokinetics (PK) has not been studied in pediatric patients with renal impairment (RI). To design optimized PGB regimens for pediatric patients with varying degrees of RI and predict exposure to PGB, physiologically based pharmacokinetic (PBPK) models of PGB were developed and verified, and its disposition was simulated in the healthy population and adults with RI. The simulated results from the PBPK models after single-dose and multi-dose administrations of PGB were consistent with the corresponding observed data based on the fold error values of less than 2. The area under curve ratios were 1.23 ± 0.06, 2.02 ± 0.10, 3.86 ± 0.21, and 9.92 ± 0.79 in pediatric patients with mild, moderate, severe, and end-stage RI, respectively. Based on the predictions for pediatric patients with moderate, severe, and end-stage RI, the maximum dose should not exceed 7, 3.5, and 1.4 mg/kg/day, respectively, among those weighing < 30 kg, and it should not exceed 5, 2.5, and 1 mg/kg/day, respectively, among those weighing > 30 kg. In conclusion, the developed PBPK model is a valuable tool for predicting PGB dosage for pediatric patients with RI.

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