IL-27-engineered CAR.19-NK-92 cells exhibit enhanced therapeutic efficacy.

Chimeric antigen receptor (CAR) engineering of natural killer (NK) cells has shown promising results in early-phase clinical studies. However, advancing CAR-NK cell therapeutic efficacy is imperative. In this study, we investigated the impact of a fourth-generation CD19-targeted CAR (CAR.19) coexpressing IL-27 on NK-92 cells. We observed a significant improvement in NK-92 cell proliferation and cytotoxicity activity against B-cell cancer cell lines, both in vitro and in a xenograft mouse B-cell lymphoma model. Our systematic transcriptome analysis of the activated NK-92 CAR variants further supports the potential of IL-27 in fourth-generation CARs to overcome limitations of NK cell-based targeted tumor therapies by providing essential growth and activation signals. Integrating IL-27 into CAR-NK cells emerges as a promising strategy to enhance their therapeutic potential and elicit robust responses against cancer cells. These findings contribute substantially to the mounting evidence supporting the potential of fourth-generation CAR engineering in advancing NK cell-based immunotherapies.

AI as a Medical Device Adverse Event Reporting in Regulatory Databases: Protocol for a Systematic Review.

BACKGROUND: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack of knowledge of how to report AEs, and a general culture of nonreporting. The introduction of artificial intelligence as a medical device (AIaMD) requires a robust safety monitoring environment that recognizes both generic risks of a medical device and some of the increasingly recognized risks of AIaMD (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems and explore potential mechanisms for how AEs could be detected, attributed, and reported with a view to improving the early detection of safety signals. OBJECTIVE: The systematic review outlined in this protocol aims to yield insights into the frequency and severity of AEs while characterizing the events using existing regulatory guidance. METHODS: Publicly accessible AE databases will be searched to identify AE reports for AIaMD. Scoping searches have identified 3 regulatory territories for which public access to AE reports is provided: the United States, the United Kingdom, and Australia. AEs will be included for analysis if an artificial intelligence (AI) medical device is involved. Software as a medical device without AI is not within the scope of this review. Data extraction will be conducted using a data extraction tool designed for this review and will be done independently by AUK and a second reviewer. Descriptive analysis will be conducted to identify the types of AEs being reported, and their frequency, for different types of AIaMD. AEs will be analyzed and characterized according to existing regulatory guidance. RESULTS: Scoping searches are being conducted with screening to begin in April 2024. Data extraction and synthesis will commence in May 2024, with planned completion by August 2024. The review will highlight the types of AEs being reported for different types of AI medical devices and where the gaps are. It is anticipated that there will be particularly low rates of reporting for indirect harms associated with AIaMD. CONCLUSIONS: To our knowledge, this will be the first systematic review of 3 different regulatory sources reporting AEs associated with AIaMD. The review will focus on real-world evidence, which brings certain limitations, compounded by the opacity of regulatory databases generally. The review will outline the characteristics and frequency of AEs reported for AIaMD and help regulators and policy makers to continue developing robust safety monitoring processes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48156.

Roxadustat versus placebo for patients with lower-risk myelodysplastic syndrome: MATTERHORN phase 3, double-blind, randomized controlled trial.

In patients with lower-risk myelodysplastic syndromes/neoplasms (MDS), response to first-line therapy is limited and transient. The MATTERHORN randomized, double-blind, phase 3 trial evaluated roxadustat versus placebo for patients with transfusion-dependent, lower-risk MDS. Eligible patients had very low-, low-, or intermediate-risk MDS with or without prior erythropoiesis-stimulating agent treatment, and a transfusion burden of 1-4 packed red blood cell (pRBC) units every 8 weeks (Q8W). Patients were randomized (3:2) to oral roxadustat (2.5 mg/kg) or placebo, both three times weekly, with best supportive care. Primary efficacy endpoint was transfusion independence (TI) for ≥56 days within 28 weeks (TI responders). MATTERHORN was terminated due to interim analysis outcomes not meeting statistical significance. In total, 272 patients were screened, and 140 patients were enrolled (82, roxadustat, and 58, placebo). At final analysis, 38/80 (47.5%) patients and 19/57 (33.3%) in the roxadustat and placebo arms, respectively, were TI responders (p = .217). A greater percentage of patients in the roxadustat arm with a transfusion burden of ≥2 pRBC units Q4W were TI responders (36.1%; 13/36) compared with the placebo arm (11.5%; 3/26; p-nominal = .047). The seven on-study deaths (4, roxadustat, and 3, placebo) were considered unrelated to treatment. Three roxadustat patients progressed to acute myeloid leukemia. Despite MATTERHORN not meeting its primary endpoint, a numerically higher TI rate was achieved with roxadustat treatment compared with placebo. Further analyses are needed to confirm the MDS patient subgroups deriving clinical benefit from this novel treatment.

Dopamine-mediated plasticity preserves excitatory connections to direct pathway striatal projection neurons and motor function in a mouse model of Parkinson's disease.

The cardinal symptoms of Parkinson's disease (PD) such as bradykinesia and akinesia are debilitating, and treatment options remain inadequate. The loss of nigrostriatal dopamine neurons in PD produces motor symptoms by shifting the balance of striatal output from the direct (go) to indirect (no-go) pathway in large part through changes in the excitatory connections and intrinsic excitabilities of the striatal projection neurons (SPNs). Here, we report using two different experimental models that a transient increase in striatal dopamine and enhanced D1 receptor activation, during 6-OHDA dopamine depletion, prevent the loss of mature spines and dendritic arbors on direct pathway projection neurons (dSPNs) and normal motor behavior for up to 5 months. The primary motor cortex and midline thalamic nuclei provide the major excitatory connections to SPNs. Using ChR2-assisted circuit mapping to measure inputs from motor cortex M1 to dorsolateral dSPNs, we observed a dramatic reduction in both experimental model mice and controls following dopamine depletion. Changes in the intrinsic excitabilities of SPNs were also similar to controls following dopamine depletion. Future work will examine thalamic connections to dSPNs. The findings reported here reveal previously unappreciated plasticity mechanisms within the basal ganglia that can be leveraged to treat the motor symptoms of PD.

Detecting Algorithmic Errors and Patient Harms for AI-Enabled Medical Devices in Randomized Controlled Trials: Protocol for a Systematic Review.

BACKGROUND: Artificial intelligence (AI) medical devices have the potential to transform existing clinical workflows and ultimately improve patient outcomes. AI medical devices have shown potential for a range of clinical tasks such as diagnostics, prognostics, and therapeutic decision-making such as drug dosing. There is, however, an urgent need to ensure that these technologies remain safe for all populations. Recent literature demonstrates the need for rigorous performance error analysis to identify issues such as algorithmic encoding of spurious correlations (eg, protected characteristics) or specific failure modes that may lead to patient harm. Guidelines for reporting on studies that evaluate AI medical devices require the mention of performance error analysis; however, there is still a lack of understanding around how performance errors should be analyzed in clinical studies, and what harms authors should aim to detect and report. OBJECTIVE: This systematic review will assess the frequency and severity of AI errors and adverse events (AEs) in randomized controlled trials (RCTs) investigating AI medical devices as interventions in clinical settings. The review will also explore how performance errors are analyzed including whether the analysis includes the investigation of subgroup-level outcomes. METHODS: This systematic review will identify and select RCTs assessing AI medical devices. Search strategies will be deployed in MEDLINE (Ovid), Embase (Ovid), Cochrane CENTRAL, and clinical trial registries to identify relevant papers. RCTs identified in bibliographic databases will be cross-referenced with clinical trial registries. The primary outcomes of interest are the frequency and severity of AI errors, patient harms, and reported AEs. Quality assessment of RCTs will be based on version 2 of the Cochrane risk-of-bias tool (RoB2). Data analysis will include a comparison of error rates and patient harms between study arms, and a meta-analysis of the rates of patient harm in control versus intervention arms will be conducted if appropriate. RESULTS: The project was registered on PROSPERO in February 2023. Preliminary searches have been completed and the search strategy has been designed in consultation with an information specialist and methodologist. Title and abstract screening started in September 2023. Full-text screening is ongoing and data collection and analysis began in April 2024. CONCLUSIONS: Evaluations of AI medical devices have shown promising results; however, reporting of studies has been variable. Detection, analysis, and reporting of performance errors and patient harms is vital to robustly assess the safety of AI medical devices in RCTs. Scoping searches have illustrated that the reporting of harms is variable, often with no mention of AEs. The findings of this systematic review will identify the frequency and severity of AI performance errors and patient harms and generate insights into how errors should be analyzed to account for both overall and subgroup performance. TRIAL REGISTRATION: PROSPERO CRD42023387747; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=387747. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/51614.

Frameworks for procurement, integration, monitoring, and evaluation of artificial intelligence tools in clinical settings: A systematic review.

Research on the applications of artificial intelligence (AI) tools in medicine has increased exponentially over the last few years but its implementation in clinical practice has not seen a commensurate increase with a lack of consensus on implementing and maintaining such tools. This systematic review aims to summarize frameworks focusing on procuring, implementing, monitoring, and evaluating AI tools in clinical practice. A comprehensive literature search, following PRSIMA guidelines was performed on MEDLINE, Wiley Cochrane, Scopus, and EBSCO databases, to identify and include articles recommending practices, frameworks or guidelines for AI procurement, integration, monitoring, and evaluation. From the included articles, data regarding study aim, use of a framework, rationale of the framework, details regarding AI implementation involving procurement, integration, monitoring, and evaluation were extracted. The extracted details were then mapped on to the Donabedian Plan, Do, Study, Act cycle domains. The search yielded 17,537 unique articles, out of which 47 were evaluated for inclusion based on their full texts and 25 articles were included in the review. Common themes extracted included transparency, feasibility of operation within existing workflows, integrating into existing workflows, validation of the tool using predefined performance indicators and improving the algorithm and/or adjusting the tool to improve performance. Among the four domains (Plan, Do, Study, Act) the most common domain was Plan (84%, n = 21), followed by Study (60%, n = 15), Do (52%, n = 13), & Act (24%, n = 6). Among 172 authors, only 1 (0.6%) was from a low-income country (LIC) and 2 (1.2%) were from lower-middle-income countries (LMICs). Healthcare professionals cite the implementation of AI tools within clinical settings as challenging owing to low levels of evidence focusing on integration in the Do and Act domains. The current healthcare AI landscape calls for increased data sharing and knowledge translation to facilitate common goals and reap maximum clinical benefit.

Coding with the machines: machine-assisted coding of rare event data.

While machine coding of data has dramatically advanced in recent years, the literature raises significant concerns about validation of LLM classification showing, for example, that reliability varies greatly by prompt and temperature tuning, across subject areas and tasks-especially in "zero-shot" applications. This paper contributes to the discussion of validation in several different ways. To test the relative performance of supervised and semi-supervised algorithms when coding political data, we compare three models' performances to each other over multiple iterations for each model and to trained expert coding of data. We also examine changes in performance resulting from prompt engineering and pre-processing of source data. To ameliorate concerns regarding LLM's pre-training on test data, we assess performance by updating an existing dataset beyond what is publicly available. Overall, we find that only GPT-4 approaches trained expert coders when coding contexts familiar to human coders and codes more consistently across contexts. We conclude by discussing some benefits and drawbacks of machine coding moving forward.

Symmetric dimethylarginine correlates with the urea, creatinine, potassium, and clinical scores in feline urethral obstructions.

BACKGROUND: A urethral obstruction (UO) is an emergency commonly observed in male cats, which can result in significant clinical and laboratory alterations, leading to complications and death. OBJECTIVES: This study aimed to correlate symmetric dimethylarginine (SDMA) with the urea, creatinine, potassium, and bicarbonate levels in cats with UO. In addition, the correlation between clinical score and time of obstruction was evaluated. METHODS: Thirty male cats were selected and allocated into a control group (CG, n = 13) and an obstruction group (OG, n = 17). The laboratory analyses were conducted before treatment (M0) and at different times after treatment (12 h [M12], 24 h [M24], and 48 h [M48]). Correlations were established between SDMA and creatinine, urea, bicarbonate, potassium, time of obstruction, and the clinical score. RESULTS: A strong correlation (r > 0.6) was observed between SDMA and creatinine, urea, and potassium in the OG. Furthermore, there was substantial agreement (kappa value) between SDMA and creatinine at M24. A higher clinical score was associated with a longer time of obstruction. In the OG, at M48, the SDMA and creatinine levels were 50% and 41.2% higher, respectively. CONCLUSIONS: A correlation was observed between SDMA and creatinine in obstructed cats, and significant agreement between these values was observed 24 h after the unblocking treatment. A correlation among SDMA, urea, and potassium was observed. Approximately 9% more cats continued to have elevated SDMA levels after 48 h of treatment compared to creatinine. This suggests a slightly lower sensitivity of the latter biomarker but does not exclude the possibility of congruent and normalized values after a longer evaluation period.

Acute post-orchiectomy pain does not reduce alpha rams' interest in feed resources.

Sheep pain is an animal welfare issue monitored based on behavioral responses, including appetite. Dominant (alpha) males have priority for accessing limited feed resources, however, the effects of pain on feed interest in members of a group with defined social hierarchy are unknown. Our objective was to investigate effects of acute post-orchiectomy pain on alpha rams' interest in accessing a limited feed resource. Eighteen rams were randomly housed in pens of 3 rams. After acclimation, the first 5-d (consecutive) battery of a behavior test was performed. In this test, 180 g of the regular diet concentrate was placed in a portable trough in the center of the pen; this feed was supplemental to the diet and represented a limited, albeit strongly preferable feed resource. Rams were filmed for 5 min after the feed introduction. Hierarchical levels (alpha, beta, and gamma) were defined based on the social hierarchical index according to higher initiator and lower receptor agonistic behaviors from the social network analyses. After 15 d, a second 5-d behavioral test battery was repeated. On the following day, alpha rams were castrated. Flunixin meglumine was given immediately before surgery and a final behavioral test was performed 8 h post-orchiectomy, concurrent with an expected peak in postoperative pain. For all recordings, the latency, frequency, and duration of time that each ram had its mouth inside the feed trough were recorded, and the Unesp-Botucatu sheep acute pain scale pain scale (USAPS) was applied. The social hierarchical index was highest in alpha rams, followed by beta and gamma. The pain scores were statistically equivalent across the 11 evaluation days for beta and gamma rams, whereas there was an increase in the final evaluation for alpha. There was no difference in latency, frequency, and duration between alpha, beta, and gamma rams across evaluations. We concluded that acute post-orchiectomy pain did not decrease alpha rams' interest in accessing limited feed. Routine feeding offers a valuable chance to detect pain-related behavior using the USAPS in rams. However, dominance may confound appetite-related behaviors in assessing acute pain, as alpha rams' interest in limited feed remained unaffected by the pain.

Evolution of the data and methods in real-world COVID-19 vaccine effectiveness studies on mortality: a scoping review protocol.

BACKGROUND: Early evidence on COVID-19 vaccine efficacy came from randomised trials. Many important questions subsequently about vaccine effectiveness (VE) have been addressed using real-world studies (RWS) and have informed most vaccination policies globally. As the questions about VE have evolved during the pandemic so have data, study design, and analytical choices. This scoping review aims to characterise this evolution and provide insights for future pandemic planning-specifically, what kinds of questions are asked at different stages of a pandemic, and what data infrastructure and methods are used? METHODS AND ANALYSIS: We will identify relevant studies in the Johns Hopkins Bloomberg School of Public Health VIEW-hub database, which curates both published and preprint VE RWS identified from PubMed, Embase, Scopus, Web of Science, the WHO COVID Database, MMWR, Eurosurveillance, medRxiv, bioRxiv, SSRN, Europe PMC, Research Square, Knowledge Hub, and Google. We will include RWS of COVID-19 VE that reported COVID-19-specific or all-cause mortality (coded as 'death' in the 'effectiveness studies' data set).Information on study characteristics; study context; data sources; design and analytic methods that address confounding will be extracted by single reviewer and checked for accuracy and discussed in a small group setting by methodological and analytic experts. A timeline mapping approach will be used to capture the evolution of this body of literature.By describing the evolution of RWS of VE through the COVID-19 pandemic, we will help identify options for VE studies and inform policy makers on the minimal data and analytic infrastructure needed to support rapid RWS of VE in future pandemics and of healthcare strategies more broadly. ETHICS AND DISSEMINATION: As data is in the public domain, ethical approval is not required. Findings of this study will be disseminated through peer-reviewed publications, conference presentations, and working-papers to policy makers. REGISTRATION: https://doi.org/10.17605/OSF.IO/ZHDKR.

AI as a Medical Device for Ophthalmic Imaging in Europe, Australia, and the United States: Protocol for a Systematic Scoping Review of Regulated Devices.

BACKGROUND: Artificial intelligence as a medical device (AIaMD) has the potential to transform many aspects of ophthalmic care, such as improving accuracy and speed of diagnosis, addressing capacity issues in high-volume areas such as screening, and detecting novel biomarkers of systemic disease in the eye (oculomics). In order to ensure that such tools are safe for the target population and achieve their intended purpose, it is important that these AIaMD have adequate clinical evaluation to support any regulatory decision. Currently, the evidential requirements for regulatory approval are less clear for AIaMD compared to more established interventions such as drugs or medical devices. There is therefore value in understanding the level of evidence that underpins AIaMD currently on the market, as a step toward identifying what the best practices might be in this area. In this systematic scoping review, we will focus on AIaMD that contributes to clinical decision-making (relating to screening, diagnosis, prognosis, and treatment) in the context of ophthalmic imaging. OBJECTIVE: This study aims to identify regulator-approved AIaMD for ophthalmic imaging in Europe, Australia, and the United States; report the characteristics of these devices and their regulatory approvals; and report the available evidence underpinning these AIaMD. METHODS: The Food and Drug Administration (United States), the Australian Register of Therapeutic Goods (Australia), the Medicines and Healthcare products Regulatory Agency (United Kingdom), and the European Database on Medical Devices (European Union) regulatory databases will be searched for ophthalmic imaging AIaMD through a snowballing approach. PubMed and clinical trial registries will be systematically searched, and manufacturers will be directly contacted for studies investigating the effectiveness of eligible AIaMD. Preliminary regulatory database searches, evidence searches, screening, data extraction, and methodological quality assessment will be undertaken by 2 independent review authors and arbitrated by a third at each stage of the process. RESULTS: Preliminary searches were conducted in February 2023. Data extraction, data synthesis, and assessment of methodological quality commenced in October 2023. The review is on track to be completed and submitted for peer review by April 2024. CONCLUSIONS: This systematic review will provide greater clarity on ophthalmic imaging AIaMD that have achieved regulatory approval as well as the evidence that underpins them. This should help adopters understand the range of tools available and whether they can be safely incorporated into their clinical workflow, and it should also support developers in navigating regulatory approval more efficiently. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52602.

Quality use of publicly subsidised tapentadol in Australia: a population-based analysis.

BACKGROUND: Sustained-release (SR) tapentadol was listed on Australia's Pharmaceutical Benefits Scheme (PBS) in 2014 for chronic severe pain requiring long-term opioid treatment. Dispensings have increased since listing despite declining trends in other PBS-listed opioids. Preferential prescribing of SR opioids may increase the risk of dependence and accidental overdose, particularly when used to treat acute pain. AIMS: To explore the quality use of publicly subsidised tapentadol in Australia. METHODS: We examined annual initiation rates and patterns of use of tapentadol (SR) in the dispensing records of a 10% random sample of PBS-eligible Australians (2014-2021). We used national tapentadol sales data to assess the proportion of sales attributable to the PBS. RESULTS: Tapentadol initiation increased from 2014, peaking at 7.5/1000 adult population in 2019 before declining to 5.3/1000 in 2021. We identified 63 766 new users between 2014 and 2020, of whom 92.8% discontinued in the first year following initiation, 58.0% had only a single dispensing and 34.3% had no other opioids dispensed in the 3 months before or after initiation. 27.8% of new users were dispensed tapentadol on the same day as potentially interacting medicines. There was a sustained drop in the proportion of sales attributable to the PBS from June 2020 onwards, from an average of 69.1%, to 63.9% of pack sales. CONCLUSIONS: Patterns of use suggest tapentadol (SR) is generally used for short duration. Although most tapentadol sold in Australia is subsidised, there is evidence of a shift towards private sales.

Development and validation of a novel stemness-related prognostic model for neuroblastoma using integrated machine learning and bioinformatics analyses.

Background: Neuroblastoma (NB) is a common solid tumor in children, with a dismal prognosis in high-risk cases. Despite advancements in NB treatment, the clinical need for precise prognostic models remains critical, particularly to address the heterogeneity of cancer stemness which plays a pivotal role in tumor aggressiveness and patient outcomes. By utilizing machine learning (ML) techniques, we aimed to explore the cancer stemness features in NB and identify stemness-related hub genes for future investigation and potential targeted therapy. Methods: The public dataset GSE49710 was employed as the training set for acquire gene expression data and NB sample information, including age, stage, and MYCN amplification status and survival. The messenger RNA (mRNA) expression-based stemness index (mRNAsi) was calculated and patients were grouped according to their mRNAsi value. Stemness-related hub genes were identified from the differentially expressed genes (DEGs) to construct a gene signature. This was followed by evaluating the relationship between cancer stemness and the NB immune microenvironment, and the development of a predictive nomogram. We assessed the prognostic outcomes including overall survival (OS) and event-free survival, employing machine learning methods to measure predictive accuracy through concordance indices and validation in an independent cohort E-MTAB-8248. Results: Based on mRNAsi, we categorized NB patients into two groups to explore the association between varying levels of stemness and their clinical outcomes. High mRNAsi was linked to the advanced International Neuroblastoma Staging System (INSS) stage, amplified MYCN, and elder age. High mRNAsi patients had a significantly poorer prognosis than low mRNAsi cases. According to the multivariate Cox analysis, the mRNAsi was an independent risk factor of prognosis in NB patients. After least absolute shrinkage and selection operator (LASSO) regression analysis, four key genes (ERCC6L, DUXAP10, NCAN, DIRAS3) most related to mRNAsi scores were discovered and a risk model was built. Our model demonstrated a significant prognostic capacity with hazard ratios (HR) ranging from 18.96 to 41.20, P values below 0.0001, and area under the receiver operating characteristic curve (AUC) values of 0.918 in the training set, suggesting high predictive accuracy which was further confirmed by external verification. Individuals with a low four-gene signature score had a favorable outcome and better immune responses. Finally, a nomogram for clinical practice was constructed by integrating the four-gene signature and INSS stage. Conclusions: Our findings confirm the influence of CSC features in NB prognosis. The newly developed NB stemness-related four-gene signature prognostic signature could facilitate the prognostic prediction, and the identified hub genes may serve as promising targets for individualized treatments.

Treatment Patterns of Bone-targeting Agents Among Solid Tumor Patients With Bone Metastases: An Analysis of Electronic Health Record Data in the United States From 2014 to 2018.

OBJECTIVES: This study evaluated real-world treatment patterns of approved bone-targeting agents (BTAs) with various mechanisms of action-pamidronate, zoledronic acid, and denosumab-for the prevention of skeletal-related events in patients with bone metastases (BM) from solid tumors. METHODS: Adult patients with BM secondary to solid tumors between January 1, 2014, and December 31, 2018, were identified from the Flatiron Health Oncology Services Comprehensive Electronic Records database and categorized by BTA use and therapy type. Time from diagnosis to initiation, persistence (mean time on treatment), and compliance (≥12 administrations/year) with BTA with up to 4 years of follow-up were examined. RESULTS: This study included 27,268 patients with BM (breast cancer, 32.7%; lung cancer, 16.5%; prostate cancer, 17.2%; and other solid tumors, 33.6%); of these, 41.4% initiated denosumab after BM diagnosis; 21.3%, zoledronic acid; 0.6%, pamidronate; and 36.7% had no treatment record. Mean (SD) time to initiation for denosumab or zoledronic acid was 68.6 (157.0) days (denosumab, 70.3 (160.4) days; zoledronic acid, 65.2 [150.2] days). Mean persistence and compliance (first year of treatment) were significantly higher for denosumab than for zoledronic acid (22.0 vs. 14.9 mo [ P <0.0001] and 42.3% vs. 34.8% [ P <0.0001], respectively). Treatment compliance was the highest in patients with breast cancer (denosumab, 48.2%; zoledronic acid, 39.1%). CONCLUSION: Real-world BTA treatment patterns in the United States suggest that over one-third of patients with BM secondary to solid tumors remain untreated and less than 50% of the patients received ≥12 administrations/year of BTA therapy.

Evaluating the use of clinical decision aids in an Australian emergency department: A cross-sectional survey.

OBJECTIVE: To identify healthcare professionals' knowledge, self-reported use, and documentation of clinical decision aids (CDAs) in a large ED in Australia, to identify behavioural determinants influencing the use of CDAs, and healthcare professionals preferences for integrating CDAs into the electronic medical record (EMR) system. METHODS: Healthcare professionals (doctors, nurses and physiotherapists) working in the ED at the Gold Coast Hospital, Queensland were invited to complete an online survey. Quantitative data were analysed using descriptive statistics, and where appropriate, mapped to the theoretical domains framework to identify potential barriers to the use of CDAs. Qualitative data were analysed using content analysis. RESULTS: Seventy-four healthcare professionals (34 medical officers, 31 nurses and nine physiotherapists) completed the survey. Healthcare professionals' knowledge and self-reported use of 21 validated CDAs was low but differed considerably across CDAs. Only 4 out of 21 CDAs were reported to be used 'sometimes' or 'always' by the majority of respondents (Ottawa Ankle Rule for ankle injury, Wells' criteria for pulmonary embolism, Wells' criteria for deep vein thrombosis and PERC rule for pulmonary embolism). Most respondents wanted to increase their use of valid and reliable CDAs and supported the integration of CDAs into the EMR to facilitate their use and support documentation. Potential barriers impacting the use of CDAs represented three theoretical domains of knowledge, social/professional role and identity, and social influences. CONCLUSIONS: CDAs are used variably by healthcare professionals and are inconsistently applied in the clinical encounter. Preferences of healthcare professionals need to be considered to allow the successful integration of CDAs into the EMR.

Assessment of the safety of nivolumab in people living with HIV with advanced cancer on antiretroviral therapy: the AIDS Malignancy Consortium 095 Study.

BACKGROUND: Although immunotherapy has emerged as a therapeutic strategy for many cancers, there are limited studies establishing the safety and efficacy in people living with HIV (PLWH) and cancer. METHODS: PLWH and solid tumors or Kaposi sarcoma (KS) receiving antiretroviral therapy and a suppressed HIV viral load received nivolumab at 3 mg/kg every 2 weeks, in two dose deescalation cohorts stratified by CD4 count (stratum 1: CD4 count > 200/µL and stratum 2: CD4 count 100-199/µL). An expansion cohort of 24 participants with a CD4 count > 200/µL was then enrolled. RESULTS: A total of 36 PLWH received nivolumab, including 15 with KS and 21 with a variety of other solid tumors. None of the first 12 participants had dose-limiting toxicity in both CD4 strata, and five patients (14%) overall had grade 3 or higher immune related adverse events. Objective partial response occurred in nine PLWH and cancer (25%), including in six of 15 with KS (40%; 95% CI, 16.3-64.7). The median duration of response was 9.0 months overall and 12.5 months in KS. Responses were observed regardless of PDL1 expression. There were no significant changes in CD4 count or HIV viral load. CONCLUSIONS: Nivolumab has a safety profile in PLWH similar to HIV-negative subjects with cancer, and also efficacy in KS. Plasma HIV remained suppressed and CD4 counts remained stable during treatment and antiretroviral therapy, indicating no adverse impact on immune function. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02408861.

Exact Solutions Modelling Nonlinear Atmospheric Gravity Waves.

Exact solutions to the governing equations for atmospheric motion are derived which model nonlinear gravity wave propagation superimposed on atmospheric currents. Solutions are explicitly prescribed in terms of a Lagrangian formulation, which enables a detailed exposition of intricate flow characteristics. It is shown that our solutions are well-suited to modelling two distinct forms of mountain waves, namely: trapped lee waves in the Equatorial f-plane, and vertically propagating mountain waves at general latitudes.

Use of Silica Nanoparticles for Drug Delivery in Cardiovascular Disease.

PURPOSE: Cardiovascular disease (CVD) is the leading cause of death worldwide. The current CVD therapeutic drugs require long-term treatment with high doses, which increases the risk of adverse effects while offering only marginal treatment efficacy. Silica nanoparticles (SNPs) have been proven to be an efficient drug delivery vehicle for numerous diseases, including CVD. This article reviews recent progress and advancement in targeted delivery for drugs and diagnostic and theranostic agents using silica nanoparticles to achieve therapeutic efficacy and improved detection of CVD in clinical and preclinical settings. METHODS: A search of PubMed, Scopus, and Google Scholar databases from 1990 to 2023 was conducted. Current clinical trials on silica nanoparticles were identified through ClinicalTrials.gov. Search terms include silica nanoparticles, cardiovascular diseases, drug delivery, and therapy. FINDINGS: Silica nanoparticles exhibit biocompatibility in biological systems, and their shape, size, surface area, and surface functionalization can be customized for the safe transport and protection of drugs in blood circulation. These properties also enable effective drug uptake in specific tissues and controlled drug release after systemic, localized, or oral delivery. A range of silica nanoparticles have been used as nanocarrier for drug delivery to treat conditions such as atherosclerosis, hypertension, ischemia, thrombosis, and myocardial infarction. IMPLICATIONS: The use of silica nanoparticles for drug delivery and their ongoing development has emerged as a promising strategy to improve the effectiveness of drugs, imaging agents, and theranostics with the potential to revolutionize the treatment of CVD.

Research Note: The effects of a Lactobacillus helveticus ATCC 15009-derived postbiotic mitigating Salmonella Gallinarum colonization in commercial layer chicks.

This study aimed to assess the effects of a Lactobacillus helveticus ATCC 15009-derived postbiotic in mitigating experimental Salmonella Gallinarum infection. For this purpose, a sample of Lactobacillus sp. was inoculated in 2 different media, each containing different postbiotics (sensitized and nonsensitized). Both inocula had their antagonistic effect over S. Gallinarum tested through the spot-on-the-lawn method. It revealed that the sensitized postbiotic had a higher action potential over Lactobacillus sp. than the nonsensitized one (P < 0.05). Then, 48 day of hatch chicks were divided into 4 groups: A = Lactobacillus sp. (109 CFU/mL) inoculum on the 18th day; B = Lactobacillus sp. (109 CFU/mL) inoculum on the 18th day and postbiotic inoculum on the 19th day; C = postbiotic inoculum on the 19th day; and D = sterile saline inoculum on 18th and 19th days. On the 21st day, all chicks were infected with S. Gallinarum (109 CFU/mL). On the 23rd day, the animals were euthanized by cervical dislocation, and the ceca and liver were aseptically removed. Bacterial count of S. Gallinarum with serial decimal dilution was performed with these organs. It revealed that the prophylactic treatment with the postbiotic that modulates the intestinal microbiota was as efficient as the probiotic administration in reducing S. Gallinarum in the cecum and liver of chicks (P < 0.05). These data point to a new range of alternatives for preventing S. Gallinarum, which might help the poultry industry produce safer food for human consumption.

Formulation of zinc foliar sprays for wheat grain biofortification: a review of current applications and future perspectives.

Agronomic biofortification of wheat grain with zinc can improve the condition of about one billion people suffering from zinc (Zn) deficiency. However, with the challenge of cultivating high-yielding wheat varieties in Zn-deficient soils and the global need to produce higher-quality food that nourishes the growing population, innovation in the strategies to deliver Zn directly to plants will come into play. Consequently, existing foliar formulations will need further refinement to maintain the high agronomic productivity required in competitive global grain markets while meeting the dietary Zn intake levels recommended for humans. A new generation of foliar fertilisers that increase the amount of Zn assimilated in wheat plants and the translocation efficiency of Zn from leaves to grains can be a promising solution. Research on the efficacy of adjuvants and emerging nano-transporters relative to conventional Zn forms applied as foliar fertilisers to wheat has expanded rapidly in recent years. This review scopes the range of evidence available in the literature regarding the biofortification of bread wheat (Triticum aestivum L.) resulting from foliar applications of conventional Zn forms, Zn nanoparticles and novel Zn-foliar formulations. We examine the foliar application strategies and the attained final concentration of grain Zn. We propose a conceptual model for the response of grain Zn biofortification of wheat to foliar Zn application rates. This review discusses some physiological aspects of transportation of foliarly applied Zn that need further investigation. Finally, we explore the prospects of engineering foliar nano-formulations that could effectively overcome the physicochemical barrier to delivering Zn to wheat grains.