Antibiotics, improper food, and stress have created a dysbiotic state in the gut and almost 81% of the world\'s population has been affected due to the pandemic of COVID-19 and the prevalence of dengue virus in the past few years. The main intent of this study is to synthesize nanosynbiotics as nu traceuticals by combining probiotics, and prebiotics with nanoformulation. The effectiveness of the nanosynbiotics was evaluated using a variety of Nutra-pharmacogenetic assays leading to an AI-integrated formulation profiling was assessed by using machine learning methods. Consequently, Acetobacter oryzoeni as a probiotic and inulin as a prebiotic has been chosen and iron-mediated nanoformulation of symbiotic is achieved. Nanosynbiotics possessed 89.4, 96.7, 93.57, 83.53, 88.53% potential powers of Nutra-pharmacogenetic assays. Artificial intelligent solid dispersion formulation of nanosynbiotics has high dissolution, absorption, distribution, and synergism, in addition, they are non-tox, non-allergen and have a docking score of - 10.83 kcal/mol, implying the best interaction with Pregnane X receptor involved in dysbiosis. The potential of nanosynbiotics to revolutionize treatment strategies through precise targeting and modulation of the gut microbiome for improved health outcomes and disease management is promising. Their transformational influence is projected to be powered by integration with modern technology and customized formulas. Further in-vivo studies are required for the validation of nanosynbiotics as nutraceuticals.

Central nervous system (CNS) disorders have a complicated pathogenesis, and to date, no single mechanism can fully explain them. Most drugs used for CNS disorders primarily aim to manage symptoms and delay disease progression, and none have demonstrated any pathological reversal. Fucoidan is a safe, sulfated polysaccharide from seaweed that exhibits multiple pharmacological effects, and it is anticipated to be a novel treatment for CNS disorders. To assess the possible clinical uses of fucoidan, this review aims to provide an overview of its neuroprotective mechanism in both in vivo and in vitro CNS disease models, as well as its pharmacokinetics and safety. We included 39 articles on the pharmacology of fucoidan in CNS disorders. In vitro and in vivo experiments demonstrate that fucoidan has important roles in regulating lipid metabolism, enhancing the cholinergic system, maintaining the functional integrity of the blood-brain barrier and mitochondria, inhibiting inflammation, and attenuating oxidative stress and apoptosis, highlighting its potential for CNS disease treatment. Fucoidan has a protective effect against CNS disorders. With ongoing research on fucoidan, it is expected that a natural, highly effective, less toxic, and highly potent fucoidan-based drug or nutritional supplement targeting CNS diseases will be developed.

UNASSIGNED: Acute kidney injury (AKI) is a marker of clinical deterioration and renal toxicity. While there are many studies offering prediction models for the early detection of AKI, those predicting AKI occurrence using distributed research network (DRN)-based time series data are rare.
UNASSIGNED: In this study, we aimed to detect the early occurrence of AKI by applying an interpretable long short-term memory (LSTM)-based model to hospital electronic health record (EHR)-based time series data in patients who took nephrotoxic drugs using a DRN.
UNASSIGNED: We conducted a multi-institutional retrospective cohort study of data from 6 hospitals using a DRN. For each institution, a patient-based data set was constructed using 5 drugs for AKI, and an interpretable multivariable LSTM (IMV-LSTM) model was used for training. This study used propensity score matching to mitigate differences in demographics and clinical characteristics. Additionally, the temporal attention values of the AKI prediction model\'s contribution variables were demonstrated for each institution and drug, with differences in highly important feature distributions between the case and control data confirmed using 1-way ANOVA.
UNASSIGNED: This study analyzed 8643 and 31,012 patients with and without AKI, respectively, across 6 hospitals. When analyzing the distribution of AKI onset, vancomycin showed an earlier onset (median 12, IQR 5-25 days), and acyclovir was the slowest compared to the other drugs (median 23, IQR 10-41 days). Our temporal deep learning model for AKI prediction performed well for most drugs. Acyclovir had the highest average area under the receiver operating characteristic curve score per drug (0.94), followed by acetaminophen (0.93), vancomycin (0.92), naproxen (0.90), and celecoxib (0.89). Based on the temporal attention values of the variables in the AKI prediction model, verified lymphocytes and calcvancomycin ium had the highest attention, whereas lymphocytes, albumin, and hemoglobin tended to decrease over time, and urine pH and prothrombin time tended to increase.
UNASSIGNED: Early surveillance of AKI outbreaks can be achieved by applying an IMV-LSTM based on time series data through an EHR-based DRN. This approach can help identify risk factors and enable early detection of adverse drug reactions when prescribing drugs that cause renal toxicity before AKI occurs.

The characteristics of subvisible particles (SbVPs) are critical quality attributes of injectable and ophthalmic solutions in pharmaceutical manufacturing. However, current compendial SbVP testing methods, namely the light obstruction method and the microscopic particle count method, are destructive and wasteful of target samples. In this study, we present the development of a non-destructive SbVP analyzer aiming to analyze SbVPs directly in drug product (DP) containers while keeping the samples intact. Custom sample housings are developed and incorporated into the analyzer to reduce optical aberrations introduced by the curvature of typical pharmaceutical DP sample containers. The analyzer integrates a light-sheet microscope structure and models the side scattering event from a particle with Mie scattering theory with refractive indices as prior information. Equivalent spherical particle size under assigned refractive index values is estimated, and the particle concentration is determined based on the number of scattering events and the volume sampled by the light sheet. The resulting analyzer\'s capability and performance to non-destructively analyze SbVPs in DP containers were evaluated using a series of polystyrene bead suspensions in ISO 2R and 6R vials. Our results and analysis show the particle analyzer is capable of directly detecting SbVPs from intact DP containers, sorting SbVPs into commonly used size bins (e.g. ≥ 2 µm, ≥ 5 µm, ≥ 10 µm, and ≥ 25 µm), and reliably quantifying SbVPs in the concentration range of 4.6e2 to 5.0e5 particle/mL with a margin of ± 15 % error based on a 90 % confidence interval.

The prevalence of metabolic dysfunction associated-steatotic liver disease (MASLD) (formerly known as nonalcoholic fatty liver disease; NAFLD) is estimated at around 32% of the world\'s population, resulting in a major healthcare concern in recent times. Current pharmaceutical methods lack efficacy for the treatment of the disease because of suboptimal pharmacokinetic parameters including poor bioavailability, short half-life, and premature clearance. Designing an efficient drug delivery system that provides a protective environment is critical for addressing these challenges. Such a system should aim to enhance the cellular uptake of drugs, improve their bioavailability, and reduce the chances of rapid clearance. Here, we developed nanoengineered natural cell membrane-derived nanoparticles (CMNs) incorporated with a model drug, rosuvastatin, in the bilayer assembly of CMNs to reduce the accumulation of lipids in hepatocytes, a hallmark of MASLD. We used a cell extrusion technique to develop self-assembled CMNs with precise size control compared to the cell shearing method. Interestingly, the prepared CMNs were found to be nonphagocytic, representing around 1.13% of phosphatidylserine receptors on healthy cells, which allows the possibility of their use as stealth nanoparticles for drug delivery. Furthermore, CMNs exhibit higher drug-loading efficiency, excellent cytocompatibility, and enhanced cellular internalization capabilities. Moreover, we show that the delivery of rosuvastatin-loaded CMNs in the in vitro MASLD model efficiently reduced hepatocyte lipid accumulation, including total cholesterol (26.8 ± 3.1%) and triglycerides (11.8 ± 0.8%), compared to the negative control. Taken together, the nanoengineered biomimetic CMNs enhance the drug\'s bioactivity in hepatic cells, establishing a foundation for further investigation of this drug delivery system in treating MASLD.

BACKGROUND: Nonadherence to medication among patients with cardiovascular diseases undermines the desired therapeutic outcomes. eHealth interventions emerge as promising strategies to effectively tackle this issue.
OBJECTIVE: The aim of this study was to conduct a network meta-analysis (NMA) to compare and rank the efficacy of various eHealth interventions in improving medication adherence among patients with cardiovascular diseases (CVDs).
METHODS: A systematic search strategy was conducted in PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure Library (CNKI), China Science and Technology Journal Database (Weipu), and WanFang databases to search for randomized controlled trials (RCTs) published from their inception on January 15, 2024. We carried out a frequentist NMA to compare the efficacy of various eHealth interventions. The quality of the literature was assessed using the risk of bias tool from the Cochrane Handbook (version 2.0), and extracted data were analyzed using Stata16.0 (StataCorp LLC) and RevMan5.4 software (Cochrane Collaboration). The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach.
RESULTS: A total of 21 RCTs involving 3904 patients were enrolled. The NMA revealed that combined interventions (standardized mean difference [SMD] 0.89, 95% CI 0.22-1.57), telephone support (SMD 0.68, 95% CI 0.02-1.33), telemonitoring interventions (SMD 0.70, 95% CI 0.02-1.39), and mobile phone app interventions (SMD 0.65, 95% CI 0.01-1.30) were statistically superior to usual care. However, SMS compared to usual care showed no statistical difference. Notably, the combined intervention, with a surface under the cumulative ranking curve of 79.3%, appeared to be the most effective option for patients with CVDs. Regarding systolic blood pressure and diastolic blood pressure outcomes, the combined intervention also had the highest probability of being the best intervention.
CONCLUSIONS: The research indicates that the combined intervention (SMS text messaging and telephone support) has the greatest likelihood of being the most effective eHealth intervention to improve medication adherence in patients with CVDs, followed by telemonitoring, telephone support, and app interventions. The results of these network meta-analyses can provide crucial evidence-based support for health care providers to enhance patients\' medication adherence. Given the differences in the design and implementation of eHealth interventions, further large-scale, well-designed multicenter trials are needed.
BACKGROUND: INPLASY 2023120063; https://inplasy.com/inplasy-2023-12-0063/.

Diffuse midline glioma (DMG), including tumors diagnosed in the brainstem (diffuse intrinsic pontine glioma - DIPG), is the primary cause of brain tumor-related death in pediatric patients. DIPG is characterized by a median survival of <12 months from diagnosis, harboring the worst 5-year survival rate of any cancer. Corticosteroids and radiation are the mainstay of therapy; however, they only provide transient relief from the devastating neurological symptoms. Numerous therapies have been investigated for DIPG, but the majority have been unsuccessful in demonstrating a survival benefit beyond radiation alone. Although many barriers hinder brain drug delivery in DIPG, one of the most significant challenges is the blood-brain barrier (BBB). Therapeutic compounds must possess specific properties to enable efficient passage across the BBB. In brain cancer, the BBB is referred to as the blood-brain tumor barrier (BBTB), where tumors disrupt the structure and function of the BBB, which may provide opportunities for drug delivery. However, the biological characteristics of the brainstem\'s BBB/BBTB, both under normal physiological conditions and in response to DIPG, are poorly understood, which further complicates treatment. Better characterization of the changes that occur in the BBB/BBTB of DIPG patients is essential, as this informs future treatment strategies. Many novel drug delivery technologies have been investigated to bypass or disrupt the BBB/BBTB, including convection enhanced delivery, focused ultrasound, nanoparticle-mediated delivery, and intranasal delivery, all of which are yet to be clinically established for the treatment of DIPG. Herein, we review what is known about the BBB/BBTB and discuss the current status, limitations, and advances of conventional and novel treatments to improving brain drug delivery in DIPG.

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UNASSIGNED: Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are one of the most commonly used drugs for type 2 diabetes mellitus. Clinical guidelines recommend GLP-1 RAs as an adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, and obesity. The weight loss observed in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment.
UNASSIGNED: Although the adverse event profile is relatively safe, most GLP-1 RAs come with a labeled boxed warning for the risk of thyroid cancers, based on animal models and some postmarketing case reports in humans. Considering the increasing popularity of this drug class and its expansion into a new popular indication, a further review of the most recent postmarketing safety data was warranted to quantify thyroid hyperplasia and neoplasm instances.
UNASSIGNED: GLP-1 RA patient reports from the US Food and Drug Administration (FDA) Adverse Event Reporting System database were analyzed using reporting odds ratios and 95% CIs.
UNASSIGNED: In this study, we analyzed over 18 million reports from the US FDA Adverse Event Reporting System and provided evidence of significantly increased propensity for thyroid hyperplasias and neoplasms in patients taking GLP-1 RA monotherapy when compared to patients taking sodium-glucose cotransporter-2 (SGLT-2) inhibitor monotherapy.
UNASSIGNED: GLP-1 RAs, regardless of indication, are associated with an over 10-fold increase in thyroid neoplasm and hyperplasia adverse event reporting when compared to SGLT-2 inhibitors.