Title: U.S. Nursing Homes Reducing Use of Antipsychotic Drugs
Category: Health News
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Title: FDA Approves 1st Topical Gel to Ease Redness of Rosacea
Category: Health News
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Title: Health Tip: Keep Battery-Powered Devices Away From Kids
Category: Health News
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Last Editorial Review: 8/29/2013 12:00:00 AM

Title: Humans Hardwired to Feel Others' Pain, Study Finds
Category: Health News
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Title: Your Gut Bacteria May Predict Your Obesity Risk
Category: Health News
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Category: Health News
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Category: Health News
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Category: Health News
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Category: Health News
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Title: Here Are the Top 15 Anti-Inflammatory Foods for Your Diet To Reduce Inflammation
Category: Health and Living
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Category: Health and Living
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Category: Diseases and Conditions
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Background

Immature lung development and respiratory morbidity place preterm-born children at high risk of long-term pulmonary sequelae. This systematic review and meta-analysis aims to quantify lung function in preterm-born children and identify risk factors for a compromised lung function.

Pulmonary hypertension (PH) is highly prevalent in patients with interstitial lung disease (ILD) and is associated with increased morbidity and mortality. Widely available noninvasive screening tools are warranted to identify patients at risk for PH, especially severe PH, that could be managed at expert centres. This review summarises current evidence on noninvasive diagnostic modalities and prediction models for the timely detection of PH in patients with ILD. It critically evaluates these approaches and discusses future perspectives in the field. A comprehensive literature search was carried out in PubMed and Scopus, identifying 39 articles that fulfilled inclusion criteria. There is currently no single noninvasive test capable of accurately detecting and diagnosing PH in ILD patients. Estimated right ventricular pressure (RVSP) on Doppler echocardiography remains the single most predictive factor of PH, with other indirect echocardiographic markers increasing its diagnostic accuracy. However, RVSP can be difficult to estimate in patients due to suboptimal views from extensive lung disease. The majority of existing composite scores, including variables obtained from chest computed tomography, pulmonary function tests and cardiopulmonary exercise tests, were derived from retrospective studies, whilst lacking validation in external cohorts. Only two available scores, one based on a stepwise echocardiographic approach and the other on functional parameters, predicted the presence of PH with sufficient accuracy and used a validation cohort. Although several methodological limitations prohibit their generalisability, their use may help physicians to detect PH earlier. Further research on the potential of artificial intelligence may guide a more tailored approach, for timely PH diagnosis.

Background

In adults with serious respiratory illness, breathlessness is prevalent and associated with reduced health-related quality of life. The aim of this review was to assess the impact of breathing techniques on breathlessness in adults with serious respiratory illness.

Mapping transcriptomic variations using either short- or long-read RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, whereas short reads still provide improved coverage and error rates. Yet, open questions remain, such as how to quantitatively compare the technologies, can we combine them, and what is the benefit of such a combined view? We tackle these questions by first creating a pipeline to assess matched long- and short-read data using a variety of transcriptome statistics. We find that across data sets, algorithms, and technologies, matched short-read data detects ~30% more splice junctions, such that ~10%–30% of the splice junctions included at ≥20% by short reads are missed by long reads. In contrast, long reads detect many more intron-retention events and can detect full isoforms, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software, to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long-read technology or algorithm and can be combined with short-read data for improved transcriptome analysis.

Introduction:

High-quality primary care can reduce avoidable emergency department visits and emergency hospitalizations. The availability of electronic medical record (EMR) data and capacities for data storage and processing have created opportunities for predictive analytics. This systematic review examines studies which predict emergency department visits, hospitalizations, and mortality using EMR data from primary care.

BACKGROUND:This study sought to estimate the overall cumulative incidence and odds of Hospital-acquired venous thromboembolism (VTE) among critically ill children with and without exposure to invasive ventilation. In doing so, we also aimed to describe the temporal relationship between invasive ventilation and hospital-acquired VTE development.METHODS:We performed a retrospective cohort study using Virtual Pediatric Systems (VPS) data from 142 North American pediatric ICUs among children < 18 y of age from January 1, 2016–December 31, 2022. After exclusion criteria were applied, cohorts were identified by presence of invasive ventilation exposure. The primary outcome was cumulative incidence of hospital-acquired VTE, defined as limb/neck deep venous thrombosis or pulmonary embolism. Multivariate logistic regression was used to determine whether invasive ventilation was an independent risk factor for hospital-acquired VTE development.RESULTS:Of 691,118 children studied, 86,922 (12.4%) underwent invasive ventilation. The cumulative incidence of hospital-acquired VTE for those who received invasive ventilation was 1.9% and 0.12% for those who did not (P < .001). The median time to hospital-acquired VTE after endotracheal intubation was 6 (interquartile range 3–14) d. In multivariate models, invasive ventilation exposure and duration were each independently associated with development of hospital-acquired VTE (adjusted odds ratio 1.64 [95% CI 1.42–1.86], P < .001; and adjusted odds ratio 1.03 [95% CI 1.02–1.03], P < .001, respectively).CONCLUSIONS:In this multi-center retrospective review from the VPS registry, invasive ventilation exposure and duration were independent risk factors for hospital-acquired VTE among critically ill children. Children undergoing invasive ventilation represent an important target population for risk-stratified thromboprophylaxis trials.

Visible particle is an important issue in the biopharmaceutical industry, and it may occur across all the stages in the life cycle of biologics. Upon the occurrence of visible particles, it is often necessary to conduct chemical identification and root cause analysis to safeguard the safety and efficacy of the biotherapeutic products. In this article, we present a number of typical particles and relevant root cause analysis in the categories of extrinsic, intrinsic, and inherent particles that are commonly encountered in the biopharma industry. In particular, the optical images of particles obtained both in situ and after isolation are provided, along with spectral and elemental information. The particle identification was carried out with multiple microscopic and microspectroscopic techniques, including stereo optical microscopy, Fourier-transform infrared microscopy, confocal Raman microscopy, scanning electron microscopy, and energy dispersive X-ray spectroscopy. Both commercial and in-house spectral databases were used for comparison and identification. In addition to particle identification, we placed significant efforts on the root cause analysis of the addressed particles with the intention to provide a relatively whole picture of the particle-related issues and practical references to particle mitigation for our peers in the biopharmaceutical industry.

For clean-room technologies such as isolators and restricted access barrier systems (RABS), decontamination using hydrogen peroxide (H₂O₂) is increasingly attractive to fulfill regulatory requirements. Several approaches are currently used, ranging from manual wipe disinfection to vapor phase hydrogen peroxide (VPHP) or automated nebulization sanitization. Although the residual airborne H₂O₂ concentration can be easily monitored, detection of trace H₂O₂ residues in filled products is rather challenging. To simulate the filling process in a specific clean room, technical runs with water for injection (WfI) are popular. Thus, the ability to detect traces of H₂O₂ in water is an important prerequisite to ensure a safe and reliable use of H₂O₂ for isolator or clean room decontamination. The objective of this study was to provide a validated quantitative, fluorometric Amplex UltraRed assay, which satisfies the analytical target profile of quantifying H₂O₂ in WfI at low nanomolar to low micromolar concentrations (ppb range) with high accuracy and high precision. The Amplex UltraRed technology provides a solid basis for this purpose; however, no commercial assay kit that fulfills these requirements is available. Therefore, a customized Amplex UltraRed assay was developed, optimized, and validated. This approach resulted in an assay that is capable of quantifying H₂O₂ in WfI selectively, sensitively, accurately, precisely, and robustly. This assay is used in process development and qualification approaches using WfI in H₂O₂-decontaminated clean rooms and isolators.

The brain's capacity to predict and anticipate changes in internal and external environments is fundamental to initiating efficient adaptive responses, behaviors, and reflexes that minimize disruptions to physiology. In the context of feeding control, the brain predicts and anticipates responses to the consumption of dietary substances, thus driving adaptive behaviors in the form of food choices, physiological preparation for meals, and engagement of defensive mechanisms. Here, we provide an integrative perspective on the multisensory computation between exteroceptive and interoceptive cues that guides feeding strategy and may result in food-related disorders.

The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases, including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.

Background

Halm's clinical stability criteria have long guided antibiotic treatment and hospital discharge decisions for patients hospitalised with community-acquired pneumonia (CAP). Originally introduced in 1998, these criteria were established based on a relatively small and select patient population. Consequently, our study aims to reassess their applicability in the management of CAP in a contemporary real-world setting.

Organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 are important hepatic transporters. We previously identified OATP1B3 being critically implicated in the disposition of abiraterone. We aimed to further investigate the effects of abiraterone on the activities of OATP1B1 and OATP1B3 utilizing a validated endogenous biomarker coproporphyrin I (CP-I). We used OATP1B-transfected cells to characterize the inhibitory potential of abiraterone against OATP1B-mediated uptake of CP-I. Inhibition constant (K_i) was incorporated into our physiologically based pharmacokinetic (PBPK) modeling to simulate the systemic exposures of CP-I among cancer populations receiving either our model-informed 500 mg or clinically approved 1000 mg abiraterone acetate (AA) dosage. Simulated data were compared with clinical CP-I concentrations determined among our nine metastatic prostate cancer patients receiving 500 mg AA treatment. Abiraterone inhibited OATP1B3-mediated, but not OATP1B1-mediated, uptake of CP-I in vitro, with an estimated K_i of 3.93 μM. Baseline CP-I concentrations were simulated to be 0.81 ± 0.26 ng/ml and determined to be 0.72 ± 0.16 ng/ml among metastatic prostate cancer patients, both of which were higher than those observed for healthy subjects. PBPK simulations revealed an absence of OATP1B3-mediated interaction between abiraterone and CP-I. Our clinical observations confirmed that CP-I concentrations remained comparable to baseline levels up to 12 weeks post 500 mg AA treatment. Using CP-I as an endogenous biomarker, we identified the inhibition of abiraterone on OATP1B3 but not OATP1B1 in vitro, which was predicted and observed to be clinically insignificant. We concluded that the interaction risk between AA and substrates of OATP1Bs is low.

Antifolates are important for chemotherapy in non–small cell lung cancer (NSCLC). They mainly rely on reduced folate carrier (RFC) and proton-coupled folate transporter (PCFT) to enter cells. PCFT is supposed to be the dominant transporter of the two in tumors, as it operates optimally at acidic pH and has limited transport activity at physiological pH, whereas RFC operates optimally at neutral pH. In this study, we found RFC showed a slightly pH-dependent uptake of antifolates, with similar affinity values at pH 7.4 and 6.5. PCFT showed a highly pH-dependent uptake of antifolates, with an optimum pH of 6.0 for pemetrexed and 5.5 for methotrexate. The Michaelis-Menten constant (K_m) value of PCFT for pemetrexed at pH 7.4 was more than 10 times higher than that at pH 6.5. Interestingly, we found that antifolate accumulations mediated by PCFT at acidic pH were significantly affected by the efflux transporter, breast cancer resistance protein (BCRP). The highest pemetrexed concentration was observed at pH 7.0–7.4 after a 60-minute accumulation in PCFT-expressing cells, which was further evidenced by the cytotoxicity of pemetrexed, with the IC₅₀ value of pemetrexed at pH 7.4 being one-third of that at pH 6.5. In addition, the in vivo study indicated that increasing PCFT and RFC expression significantly enhanced the antitumor efficacy of pemetrexed despite the high expression of BCRP. These results suggest that both RFC and PCFT are important for antifolates accumulation in NSCLC, although there is an acidic microenvironment and high BCRP expression in tumors.

Exercise significantly alters human physiological functions, such as increasing cardiac output and muscle blood flow and decreasing glomerular filtration rate (GFR) and liver blood flow, thereby altering the absorption, distribution, metabolism, and excretion of drugs. In this study, we aimed to establish a database of human physiological parameters during exercise and to construct equations for the relationship between changes in each physiological parameter and exercise intensity, including cardiac output, organ blood flow (e.g., muscle blood flow and kidney blood flow), oxygen uptake, plasma pH and GFR, etc. The polynomial equation P = a_iHRⁱ was used for illustrating the relationship between the physiological parameters (P) and heart rate (HR), which served as an index of exercise intensity. The pharmacokinetics of midazolam, quinidine, digoxin, and lidocaine during exercise were predicted by a whole-body physiologically based pharmacokinetic (WB-PBPK) model and the developed database of physiological parameters following administration to 100 virtual subjects. The WB-PBPK model simulation results showed that most of the observed plasma drug concentrations fell within the 5^th–95^th percentiles of the simulations, and the estimated peak concentrations (C_max) and area under the curve (AUC) of drugs were also within 0.5–2.0 folds of observations. Sensitivity analysis showed that exercise intensity, exercise duration, medication time, and alterations in physiological parameters significantly affected drug pharmacokinetics and the net effect depending on drug characteristics and exercise conditions. In conclusion, the pharmacokinetics of drugs during exercise could be quantitatively predicted using the developed WB-PBPK model and database of physiological parameters.

Early detection of drug-drug interactions (DDIs) can facilitate timely drug development decisions, prevent unnecessary restrictions on patient enrollment, resulting in clinical study populations that are not representative of the indicated study population, and allow for appropriate dose adjustments to ensure safety in clinical trials. All of these factors contribute to a streamlined drug approval process and enhanced patient safety. Here we describe a new approach for early prediction of the magnitude of change in exposure for cytochrome P450 (P450) CYP3A4-related DDIs of small-molecule anticancer drugs based on the model-based extrapolation of human-CYP3A4-transgenic mice pharmacokinetics to humans. Victim drugs brigatinib and lorlatinib were evaluated with the new approach in combination with the perpetrator drugs itraconazole and rifampicin. Predictions of the magnitude of change in exposure deviated at most 0.99- to 1.31-fold from clinical trial results for inhibition with itraconazole, whereas exposure predictions for the induction with rifampicin were less accurate, with deviations of 0.22- to 0.48-fold. Results for the early prediction of DDIs and their clinical impact appear promising for CYP3A4 inhibition, but validation with more victim and perpetrator drugs is essential to evaluate the performance of the new method.

ABSTRACTIntroduction: Nigeria has the highest number of children who have not received any vaccines in Africa. The training-of-trainers (TOT) model used to train program managers (PMs) and health care workers (HCWs) is ineffective for adult learning and limits immunization programs’ success. We incorporated adult learning principles (ALPs) in designing and delivering TOT for immunization PMs and HCWs to use data to engage communities for tailored immunization strategies.Methods: Our study was implemented in 3 local government areas (LGAs) of the Federal Capital Territory, Nigeria. A training curriculum was developed, integrating ALPs and technical and operational content based on best practices in delivering immunization training and the training needs assessment findings. State PMs (n=10), LGA PMs (n=30), and HCWs (n=42) were trained on the human-centered design for tailoring immunization programs (HCD-TIP) approaches using ALPs. We used interviews and surveys with purposively and conveniently sampled PMs and HCWs, respectively, and observations to assess participants’ satisfaction, knowledge and competence, behavior changes, and results. The interviews were analyzed thematically, and surveys were statistically.Results: There was a high level of satisfaction with the training among LGA PMs (100%), state PMs (91%), and HCWs (85%), with significant knowledge and competence improvements post-training (P<.001). The trained participants conducted 2 HCD sessions with 24 undervaccinated communities and co-designed 24 prototype solutions for testing. Results showed increased coverage of the pentavalent vaccine first dose (54%) and third dose (188%) across 12 participating communities. Improved community colaboration, communication skills, and data-driven approaches were the most cited behavior changes in practice.Conclusion: The application of ALPs in training, use of HCD-TIP approaches and tools, and supportive supervision enhanced PMs’ and HCWs’ capacity for tailored interventions. Countries should consider adopting a holistic approach that focuses on using these approaches in immunization programs to strengthen the health system for equitable vaccine coverage.

The aim of this study was to validate a previously developed deep learning model in 5 independent clinical trials. The predictive performance of this model was compared with the international prognostic index (IPI) and 2 models incorporating radiomic PET/CT features (clinical PET and PET models). Methods: In total, 1,132 diffuse large B-cell lymphoma patients were included: 296 for training and 836 for external validation. The primary outcome was 2-y time to progression. The deep learning model was trained on maximum-intensity projections from PET/CT scans. The clinical PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, SUV_peak, age, and performance status. The PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, and SUV_peak. Model performance was assessed using the area under the curve (AUC) and Kaplan–Meier curves. Results: The IPI yielded an AUC of 0.60 on all external data. The deep learning model yielded a significantly higher AUC of 0.66 (P < 0.01). For each individual clinical trial, the model was consistently better than IPI. Radiomic model AUCs remained higher for all clinical trials. The deep learning and clinical PET models showed equivalent performance (AUC, 0.69; P > 0.05). The PET model yielded the highest AUC of all models (AUC, 0.71; P < 0.05). Conclusion: The deep learning model predicted outcome in all trials with a higher performance than IPI and better survival curve separation. This model can predict treatment outcome in diffuse large B-cell lymphoma without tumor delineation but at the cost of a lower prognostic performance than with radiomics.

[¹⁷⁷Lu]Lu-PSMA-617 was approved by the U.S. Food and Drug Administration for patients with prostate-specific membrane antigen (PSMA)–positive metastatic castration-resistant prostate cancer (mCRPC). Since the time of regulatory approval, however, real-world data have been lacking. This study investigated the efficacy, safety, and outcome predictors of [¹⁷⁷Lu]Lu-PSMA-617 at a major U.S. academic center. Methods: Patients with mCRPC who received [¹⁷⁷Lu]Lu-PSMA-617 at the Johns Hopkins Hospital outside clinical trials were screened for inclusion. Patients who underwent [¹⁷⁷Lu]Lu-PSMA-617 and had available outcome data were included in this study. Outcome data included prostate-specific antigen (PSA) response (≥50% decline), PSA progression-free survival (PFS), and overall survival (OS). Toxicity data were evaluated according to the Common Terminology Criteria for Adverse Events version 5.03. The study tested the association of baseline circulating tumor DNA mutational status in homologous recombination repair, PI3K alteration pathway, and aggressive-variant prostate cancer–associated genes with treatment outcome. Baseline PSMA PET/CT images were analyzed using SelectPSMA, an artificial intelligence algorithm, to predict treatment outcome. Associations with the observed treatment outcome were evaluated. Results: All 76 patients with PSMA-positive mCRPC who received [¹⁷⁷Lu]Lu-PSMA-617 met the inclusion criteria. A PSA response was achieved in 30 of 74 (41%) patients. The median PSA PFS was 4.1 mo (95% CI, 2.0–6.2 mo), and the median OS was 13.7 mo (95% CI, 11.3–16.1 mo). Anemia of grade 3 or greater, thrombocytopenia, and neutropenia were observed in 9 (12%), 3 (4%), and 1 (1%), respectively, of 76 patients. Transient xerostomia was observed in 23 (28%) patients. The presence of aggressive-variant prostate cancer–associated genes was associated with a shorter PSA PFS (median, 1.3 vs. 6.3 mo; P = 0.040). No other associations were observed between circulating tumor DNA mutational status and treatment outcomes. Eighteen of 71 (25%) patients classified by SelectPSMA as nonresponders had significantly lower rates of PSA response than patients classified as likely responders (6% vs. 51%; P < 0.001), a shorter PSA PFS (median, 1.3 vs. 6.3 mo; P < 0.001), and a shorter OS (median, 6.3 vs. 14.5 mo; P = 0.046). Conclusion: [¹⁷⁷Lu]Lu-PSMA-617 offered in a real-world setting after regulatory approval in the United States demonstrated antitumor activity and a favorable toxicity profile. Artificial-intelligence–based analysis of baseline PSMA PET/CT images may improve patient selection. Validation of these findings on larger cohorts is warranted.

This single-center, single-arm, phase II trial (ChiCTR2100050057) investigated the ability of ¹⁸F-labeled fibroblast activation protein inhibitor ([¹⁸F]AlF-NOTA-FAPI-04, denoted as ¹⁸F-FAPI) PET/CT to predict the response to neoadjuvant camrelizumab plus chemotherapy (nCC) in locally advanced esophageal squamous cell carcinoma (LA-ESCC). Methods: This study included 32 newly diagnosed LA-ESCC participants who underwent ¹⁸F-FAPI PET/CT at baseline, of whom 23 also underwent scanning after 2 cycles of nCC. The participants underwent surgery after 2 cycles of nCC. Recorded PET parameters included maximum, peak, and mean SUVs and tumor-to-background ratios (TBRs), metabolic tumor volume, and total lesion FAP expression. PET parameters were compared between patient groups with good and poor pathologic responses, and the predictive performance for treatment response was analyzed. Results: The good and poor response groups each included 16 participants (16/32, 50.0%). On ¹⁸F-FAPI PET/CT, the posttreatment SUVs were significantly lower in good responders than in poor responders, whereas the changes in SUVs with treatment were significantly higher (all P < 0.05). SUV_max (area under the curve [AUC], 0.87; P = 0.0026), SUV_peak (AUC, 0.89; P = 0.0017), SUV_mean (AUC, 0.88; P = 0.0021), TBR_max (AUC, 0.86; P = 0.0031), and TBR_mean (AUC, 0.88; P = 0.0021) after nCC were significant predictors of pathologic response to nCC, with sensitivities of 63.64%–81.82% and specificities of 83.33%–100%. Changes in SUV_max (AUC, 0.81; P = 0.0116), SUV_peak (AUC, 0.82; P = 0.0097), SUV_mean (AUC, 0.81; P = 0.0116), and TBR_mean (AUC, 0.74; P = 0.0489) also were significant predictors of the pathologic response to nCC, with sensitivities and specificities in similar ranges. Conclusion: ¹⁸F-FAPI PET/CT parameters after treatment and their changes from baseline can predict the pathologic response to nCC in LA-ESCC participants.

Understanding the differences between prognostic and predictive indices is imperative for medical research advances. We have developed a new prognostic measure that will identify the strengths, limitations, and potential applications in clinical practice.

BACKGROUND AND PURPOSE:

Neuronal ceroid lipofuscinoses are a group of neurodegenerative disorders. Recently, enzyme replacement therapy (ERT) was approved for neuronal ceroid lipofuscinosis type 2 (CLN2), a subtype of neuronal ceroid lipofuscinoses. The aim of this study was to quantify brain volume loss in CLN2 disease in patients on ERT in comparison with a natural history cohort using MRI.

BACKGROUND AND PURPOSE:

Overuse of CT-based cerebrovascular imaging in the emergency department and inpatient settings, notably CTA of the head and neck for minor and nonfocal neurologic presentations, stresses imaging services and exposes patients to radiation and contrast. Furthermore, such CT-based imaging is often insufficient for definitive diagnosis, necessitating additional MR imaging. Recent advances in fast MRI may allow timely assessment and a reduced need for head and neck CTA in select populations.