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Sunitinib malate (SM) is a chemical compound belonging to the class of kinase inhibitors and is mainly used in cancer treatment. However, despite its effectiveness, SM can cause multiple side effects, including fatigue, nausea, vomiting, and diarrhea, which can affect the patient's quality of life. Therefore, rapid and accurate diagnosis of SM is very important in many fields, especially for human health. Surface-enhanced Raman spectroscopy (SERS), an improved method for identifying biological and chemical substances with very low concentrations, is fast, reliable, and accurate. In order to identify the SM drug, filter paper substrates covered with silver nanoparticles (AgNPs) were used as SERS biosensors. First, AgNPs were prepared using a chemical reduction method. Then, the characteristics of the produced AgNPs were examined using FE-SEM, TEM, XRD, AFM, and UV–Vis analyses. The AgNPs were then coated on the substrates to create plasmonic active sites for identifying molecular vibrations of the SM drug. By coating the SM drug onto these substrates, the AgNPs reacted with the SM drug, successfully identifying trace amounts of the drug. The detection limit of the SERS plasmonic substrates for identifying the SM drug was 10−10 M. The average RSD for six repeated measurements was calculated at 5.39%. The enhancement factor for identifying molecular vibrations of the SM drug was experimentally calculated at 2.741 × 105 and numerically as 2.504 × 105. Therefore, the results indicate that these substrates are suitable for identifying low concentrations of this drug and can be used for drug monitoring purposes. [ABSTRACT FROM AUTHOR]

Background: In the U.S. there are significant racial and gender disparities in the uptake of pre-exposure prophylaxis (PrEP). Black Americans represented 14% of PrEP users in 2022, but accounted for 42% of new HIV diagnoses in 2021 and in the South, Black people represented 48% of new HIV diagnoses in 2021 but only 21% of PrEP users in 2022. Women who use drugs may be even less likely than women who do not use drugs have initiated PrEP. Moreover, women involved in community supervision programs (CSP) are less likely to initiate or use PrEP, More PrEP interventions that focus on Black women with recent history of drug use in CSPs are needed to reduce inequities in PrEP uptake. Methods: We conducted a secondary analysis from a randomized clinical trial with a sub-sample (n = 336) of the total (N = 352) participants from the parent study (E-WORTH), who tested HIV negative at baseline were considered PrEP-eligible. Black women were recruited from CSPs in New York City (NYC), with recent substance use. Participants were randomized to either E-WORTH (n = 172) an HIV testing plus, receive a 5-session, culturally-tailored, group-based HIV prevention intervention, versus an HIV testing control group (n = 180). The 5 sessions included an introduction to PrEP and access. This paper reports outcomes on improved awareness of PrEP, willingness to use PrEP, and PrEP uptake over the 12-month follow-up period. HIV outcomes are reported in a previous paper. Results: Compared to control participants, participants in this study assigned to E-WORTH had significantly greater odds of being aware of PrEP as a biomedical HIV prevention strategy (OR = 3.25, 95% CI = 1.64–6.46, p = 0.001), and indicated a greater willingness to use PrEP as an HIV prevention method (b = 0.19, 95% CI = 0.06–0.32, p = 0.004) over the entire 12-month follow-up period. Conclusions: These findings underscore the effectiveness of a culturally-tailored intervention for Black women in CSP settings in increasing awareness, and intention to initiate PrEP. Low uptake of PrEP in both arms highlight the need for providing more robust PrEP-on-demand strategies that are integrated into other services such as substance abuse treatment. Trial Registration: ClinicalTrials.gov Identifier: NCT02391233. [ABSTRACT FROM AUTHOR]

Background: Drug checking services (DCS) provide harm reduction support and advice to individuals based on chemical analysis of submitted substances of concern. Whilst there are currently no DCS in Scotland, community-based services are being planned in three cities. Methods: In this paper, we report qualitative findings based on interviews with 43 participants, focused on perceptions of DCS and their implementation. Participants were relevant professionals, those with experience of drug use, and family members of those with experience of drug use. The Consolidated Framework for Implementation Research (CFIR) was used to inform data collection and analysis. We report findings under nine constructs/themes across the five CFIR domains. Results: Participants noted the importance of DCS being implemented in low-threshold, trusted services with a harm reduction ethos, and outlined a range of further service design considerations such as speed of testing, and information provided through the analysis process. In relation to the 'inner setting', a key finding related to the potential value of leveraging existing resources in order to expand both reach and effectiveness of drug trend communication. The approach of local and national police to DCS, and the attitudes of the public and local community, were described as important external factors which could influence the success (or otherwise) of implementation. Bringing together a range of stakeholders in dialogue and developing tailored communication strategies were seen as ways to build support for DCS. Overall, we found high levels of support and perceived need for DCS amongst all stakeholder groups. Conclusions: Our findings present initial implementation considerations for Scotland which could be further explored as DCS are operationalised. Further, our focus on implementation contexts is relevant to research on DCS more generally, given the minimal consideration of such issues in the literature. [ABSTRACT FROM AUTHOR]

Dimethyl 2-[2-(1-phenyl-4,5-dihydro-1H-imidazol-2-yl)hydrazinylidene]butanedioate (DIHB) and 8-(3-chlorophenyl)-2,6,7,8-tetrahydroimidazo[2,1-c][1,2,4]triazine-3,4-dione (HDIT) are promising candidates for anticancer agents, the first analytical procedures of which are presented in this paper. The commercially available unmodified glassy carbon electrode (GCE) was used as a sensor for the individual and simultaneous differential pulse voltammetric (DPV) determination of these possible anticancer drugs. The findings concerning the electrochemical behaviour indicated that DIHB and HDIT display at GCE, as a sensor, the oxidation peaks at 1.18 and 0.98 V, respectively (vs. Ag/AgCl, 3.0 mol L−1 KCl) in the 0.125 mol L−1 acetate buffer of pH = 4.5, which were employed for their quantification. Various experimental parameters were carefully investigated, to achieve high sensitivity in voltammetric measurements. Finally, under the optimised conditions (t of 60 s, ΔEA of 75 mV, ν of 225 mV s−1, and tm of 2 ms), the proposed DPV procedure with the GCE demonstrated broad linear sensing ranges (1–200 nmol L−1—DIHB and 5–200 nmol L−1—HDIT), boasting the detection limits of 0.18 nmol L−1 for DIHB and 1.1 nmol L−1 for HDIT. Moreover, the developed procedure was distinguished by good selectivity, repeatability of DIHB and HDIT signals and sensor reproducibility. The practical application of this method was demonstrated by analysing the urine reference material without any prior treatment. The results showed that this environmentally friendly approach, with a modification-free sensor, is suitable for the sensitive, selective and rapid quantification of DIHB and HDIT. [ABSTRACT FROM AUTHOR]

Background: Harm reduction is a crucial approach in addressing the multifaceted challenges of injectable drug use. This paper presents an analysis and mapping of the existing literature on harm reduction research in the context of injectable drug use. By reviewing a comprehensive set of scholarly articles, this study identifies research hotspots, knowledge gaps, and future directions in the field. The findings provide valuable insights for researchers, policymakers, and practitioners to guide future research efforts and inform evidence-based harm reduction interventions. Methods: Data for the study was obtained from the Scopus database, using keywords and phrases related to harm reduction and injectable drug use. Validation methods were employed to verify the accuracy and comprehensiveness of the search strategy. Data analysis involved identifying growth patterns, key contributors, mapping frequent terms, identifying research hotspots, and identifying emerging research directions. Results: A total of 971 articles were found, with a notable increase from 2015 to 2022. The International Journal of Drug Policy (n = 172, 17.7%) and the Harm Reduction Journal (n = 104, 10.7%) were the most prolific journals, and the United States (n = 558, 57.5%) had the highest number of publications. The Johns Hopkins University (n = 80, 8.5%) was the most prolific institution. Mapping of frequent author keywords revealed the main keywords, including harm reduction, HIV, hepatitis C, and opioid overdose. The highly cited articles cover a broad time span and focus on topics like naloxone distribution, HIV and hepatitis C transmission, while recent articles concentrate on emerging issues such as the impact of the COVID-19 pandemic, fentanyl-related concerns, stigma reduction, and needle and syringe programs. Both sets of articles share a common focus on harm reduction strategies, but recent publications highlight current challenges and developments in the field. Conclusions: This study provides insights into research landscape on harm reduction in injectable drug use. Research is concentrated in high-income countries, emphasizing the need for more research in low- and middle-income countries. Recent publications focus on emerging challenges like COVID-19 and fentanyl. Research gaps highlight the need for studies in diverse populations, social determinants, program evaluation, and implementation strategies to enhance harm reduction interventions. [ABSTRACT FROM AUTHOR]

This paper explores the intersections between two phenomena that have shaped eastern Kachin State in Myanmar's northern borderlands with China since the late 1980s: the transformation of once-remote spaces into resource frontiers shaped by overlapping and cumulative forms of export-oriented resource extraction, and the upsurge of opium cultivation and drug use. Through the analytic of extractivism, we examine how the modalities surrounding logging and plantations in the Myanmar-China borderlands offer critical insights into how drugs have become entrenched in the region's political economy and the everyday lives of people 'living with' the destruction, violence and insecurity wrought by extractive development. [ABSTRACT FROM AUTHOR]

The battle against viral drug resistance highlights the need for innovative approaches to replace time-consuming and costly traditional methods. Deep generative models offer automation potential, especially in the fight against Human immunodeficiency virus (HIV), as they can synthesize diverse molecules effectively. In this paper, an application of an LSTM-based deep generative model named "LSTM-ProGen" is proposed to be tailored explicitly for the de novo design of drug candidate molecules that interact with a specific target protein (HIV-1 protease). LSTM-ProGen distinguishes itself by employing a long-short-term memory (LSTM) architecture, to generate novel molecules target specificity against the HIV-1 protease. Following a thorough training process involves fine-tuning LSTM-ProGen on a diverse range of compounds sourced from the ChEMBL database. The model was optimized to meet specific requirements, with multiple iterations to enhance its predictive capabilities and ensure it generates molecules that exhibit favorable target interactions. The training process encompasses an array of performance evaluation metrics, such as drug-likeness properties. Our evaluation includes extensive silico analysis using molecular docking and PCA-based visualization to explore the chemical space that the new molecules cover compared to those in the training set. These evaluations reveal that a subset of 12 de novo molecules generated by LSTM-ProGen exhibit a striking ability to interact with the target protein, rivaling or even surpassing the efficacy of native ligands. Extended versions with further refinement of LSTM-ProGen hold promise as versatile tools for designing efficacious and customized drug candidates tailored to specific targets, thus accelerating drug development and facilitating the discovery of new therapies for various diseases. [ABSTRACT FROM AUTHOR]

N‐Heterocyclic compounds have been appealing pharmacophores in their use as drug production substrates. In this review paper, the cyclization of N‐heterocycles, using iron as a catalyst, and their mechanistic pathways have been highlighted and presented comprehensively. This paper will provide researchers with in‐depth knowledge of their approach to synthesis by employing a greener way rather than a conventional one. The present review firmly establishes that iron catalysts by their innate ability and inherent potential to acquire the four oxidation states coupled with their easy accessibility, inexpensive, and environment‐friendly nature have remained the mainstay in chemistry as the evergreen catalyst in the domain of organic synthesis. This review paper extensively explores iron‐catalyzed cyclization of N‐heterocycles, elucidating mechanistic pathways and emphasizing greener synthesis methods. Iron's versatility, accessibility, and eco‐friendliness solidify its position as a cornerstone in organic synthesis. [ABSTRACT FROM AUTHOR]

Background: When addressing antisocial behaviour among adolescents, programs based on the paradigm of positive psychology through enhancing self-efficacy have demonstrated their effectiveness in furthering the positive development of young people with a history of antisocial behaviour. Nevertheless, there has been little research into the effectiveness of these type of programs in mitigating substance abuse among juvenile offenders. The aim of this paper is to analyse the effectiveness of a contingency management program in reducing the prevalence of relapses into drug consumption among adolescents who have committed serious crimes. Methods: The study consisted of a sample of 91 male adolescents, between 15 and 19 years, in juvenile detention, who were divided into two treatment groups. For both groups, biological testing was used to detect drug consumption upon their re-turn from leave permits from the Centre. Results: The quasi-experimental group had significantly lower rates of relapse than the quasi-control group. Furthermore, being part of the quasi-experimental group was a significant predictor of reduced rates of relapses. Conclusion: The results suggest that the incorporation of treatment strategies which reinforce feelings of self-efficacy and adequate orientation towards the future, as a complement to disciplinary sanctions, are effective in reducing relapses in drug use among adolescent offenders. [ABSTRACT FROM AUTHOR]

In recent years, the frequency of strokes has been on the rise year by year and has become the second leading cause of death around the world, which is characterized by a high mortality rate, high recurrence rate, and high disability rate. Ischemic strokes account for a large percentage of strokes. A reperfusion injury in ischemic strokes is a complex cascade of oxidative stress, neuroinflammation, immune infiltration, and mitochondrial damage. Conventional treatments are ineffective, and the presence of the blood–brain barrier (BBB) leads to inefficient drug delivery utilization, so researchers are turning their attention to nano-drug delivery systems. Functionalized nano-drug delivery systems have been widely studied and applied to the study of cerebral ischemic diseases due to their favorable biocompatibility, high efficiency, strong specificity, and specific targeting ability. In this paper, we briefly describe the pathological process of reperfusion injuries in strokes and focus on the therapeutic research progress of nano-drug delivery systems in ischemic strokes, aiming to provide certain references to understand the progress of research on nano-drug delivery systems (NDDSs). [ABSTRACT FROM AUTHOR]

Alcohol or drug impairment is a major risk factor for road traffic crashes, and studies on this issue are essential to provide evidence-based data for policymakers. In low- and middle-income countries (LMICs), such studies are often conducted in partnership with one or more organizations in high-income countries (HICs). The aim of this article is to provide recommendations for improving project planning and decision-making processes in epidemiological studies on alcohol, drug and traffic safety in LMICs involving HICs. We searched Pubmed, Google Scholar, and Google Search for articles and reports in English about lessons learned when conducting collaborative research in LMIC as well as papers presenting recommendations for effective research collaboration with partners in LMICs. Based on the search results, we selected 200 papers for full text examination. Few were related to studies on the effect of alcohol or drug use on road traffic safety. However, several conclusions and recommendations from other studies were found to be relevant. We combined the findings with our own experience in a narrative review. We also present a checklist for risk and quality assessment. Many papers presented similar recommendations, which included the importance of addressing local needs, ensuring adequate resources, local project ownership and leadership, establishing strong partnerships among all involved stakeholders, promoting shared decision-making and planning, and implementing strategies to translate research findings into policy, practice, and publications. It is also important to avoid HIC bias, which prioritizes the interests or perspectives of HICs over those of LMICs. [ABSTRACT FROM AUTHOR]

Monitoring blood pressure, a parameter closely related to cardiovascular activity, can help predict imminent cardiovascular events. In this paper, a novel method is proposed to customize an existing mechanistic model of the cardiovascular system through feature extraction from cardiopulmonary acoustic signals to estimate blood pressure using artificial intelligence. As various factors, such as drug consumption, can alter the biomechanical properties of the cardiovascular system, the proposed method seeks to personalize the mechanistic model using information extracted from vibroacoustic sensors. Simulation results for the proposed approach are evaluated by calculating the error in blood pressure estimates compared to ground truth arterial line measurements, with the results showing promise for this method. [ABSTRACT FROM AUTHOR]

Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens; one way to alleviate this burden and better inform future trials is to build reliable models for drug administration. This paper presents a mixed-integer program for combination chemotherapy (utilization of multiple drugs) optimization that incorporates various important operational constraints and, besides dose and concentration limits, controls treatment toxicity based on its effect on the count of white blood cells. To address the uncertainty of tumor heterogeneity, we also propose chance constraints that guarantee reaching an operable tumor size with a high probability in a neoadjuvant setting. We present analytical results pertinent to the accuracy of the model in representing biological processes of chemotherapy and establish its potential for clinical applications through a numerical study of breast cancer. History: Accepted by Paul Brooks, Area Editor for Applications in Biology, Medicine, & Healthcare. Funding: This work was supported by the National Science Foundation [Grants CMMI-1933369 and CMMI-1933373]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0207) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0207). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]

This paper explored the novel use of an educational tool to assess its influence on County Lines victimisation. Participants (n = 122) were randomly assigned to receive either County Lines education or no County Lines education and then, rate their likelihood to engage in five hypothetical scenarios typical of County Lines victimisation verses a text scam. County Lines education did not significantly reduce participant willingness to engage in the scenarios, whilst most participants were not susceptible to a text scam. Demographic data, drug use, social isolation, poor mental health, and financial instability were weak predictors of engagement. Findings suggest that the public may be vulnerable to victimisation and that future research should continue to explore the role that education can have in reducing the likelihood of engaging in County Lines activity. [ABSTRACT FROM AUTHOR]

For over a decade, jihadi terrorism in Europe, and the recruitment of Europeans to fight for ISIS in Syria, have increasingly involved marginalized youths from a social context of street culture, illegal drug use and crime. Existing theoretical models of the crime-terrorism nexus and radicalization arguably do not sufficiently explain the fluid and dynamic ways by which the street cultural come to be politico-religiously violent. This paper provides a novel retheorization, the street-jihadi spectrum, which is better placed to explain a wide range of behaviours, from the merely stylistic to the spectacularly violent. On the street culture end it includes subcultural play with provocative jihadi symbols and on the jihadi end the terrorism of 'gangster-jihadists'. We emphasize that the spectrum, consisting of a multitude of confluences of street and jihadi cultures, also includes resistance to jihadism. [ABSTRACT FROM AUTHOR]

Calcium carbonate (CaCO3), a natural common inorganic material with good biocompatibility, low toxicity, pH sensitivity, and low cost, has a widespread use in the pharmaceutical and chemical industries. In recent years, an increasing number of CaCO3-based nano-drug delivery systems have been developed. CaCO3 as a drug carrier and the utilization of CaCO3 as an efficient Ca2+ and CO2 donor have played a critical role in tumor diagnosis and treatment and have been explored in increasing depth and breadth. Starting from the CaCO3-based nano-drug delivery system, this paper systematically reviews the preparation of CaCO3 nanoparticles and the mechanisms of CaCO3-based therapeutic effects in the internal and external tumor environments and summarizes the latest advances in the application of CaCO3-based nano-drug delivery systems in tumor therapy. In view of the good biocompatibility and in vivo therapeutic mechanisms, they are expected to become an advancing biomedicine in the field of tumor diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H2S) is a toxic, essential gas used in various biological and physical processes and has been the subject of many targeted studies on its role as a new gas transmitter. These studies have mainly focused on the production and pharmacological side effects caused by H2S. Therefore, effective strategies to remove H2S has become a key research topic. Furthermore, the development of novel nanoplatforms has provided new tools for the targeted removal of H2S. This paper was performed to review the association between H2S and disease, related H2S inhibitory drugs, as well as H2S responsive nanoplatforms (HRNs). This review first analyzed the role of H2S in multiple tissues and conditions. Second, common drugs used to eliminate H2S, as well as their potential for combination with anticancer agents, were summarized. Not only the existing studies on HRNs, but also the inhibition H2S combined with different therapeutic methods were both sorted out in this review. Furthermore, this review provided in-depth analysis of the potential of HRNs about treatment or detection in detail. Finally, potential challenges of HRNs were proposed. This study demonstrates the excellent potential of HRNs for biomedical applications. [ABSTRACT FROM AUTHOR]

Blackwater fever (BWF) is a severe syndrome occurring in patients with malaria upon antimalarial treatment, characterized by massive intravascular haemolysis and haemoglobinuria. BWF is a neglected condition and management recommendations are unavailable. We performed a scoping review to appraise available data on clinical picture, treatment and physiopathology of BWF, which could guide rationally its clinical management. MEDLINE, EMBASE, LILACS, Web of Science, and Scopus databases, and the reference list of relevant publications, were searched. Papers reporting original data on BWF cases or investigating the physiopathology of BWF were eligible. Data regarding case characteristics, trigger event, clinical management and outcome were extracted. For papers investigating the physiopathology of BWF, study design and principal findings were extracted. No quality assessment was performed. Data are presented as numbers and percentages, and summary of findings, grouped by paper focus (clinical description or physiopathology). 101 papers were included. The majority of BWF cases were observed in autochthonous children (75.7%) and adults (15.3%), in contrast with historical perception that BWF patients were typically expatriates. Clinical management was described for 794 cases; corticosteroids were used in 23. Outcome was reported for 535 patients, with 18.1% mortality. The trigger was reported for 552 (47.5%) cases; in 70.4% identified as quinine. However, two RCT comparing artesunate and quinine for falciparum malaria treatment did not find significant difference in BWF occurrence after their administration. Two case-control studies did not find significant difference in G6PDH deficiency between malaria patients with and without BWF. The physiopathology and optimal treatment of BWF remain similarly unknown as they were over a century ago. Empirical supporting treatment approach seems reasonable, while change of antimalarial drug and use of corticosteroids remain object of debate. [ABSTRACT FROM AUTHOR]

This article builds on fieldwork conducted during lockdown in Denmark among users of services at the intersection of homelessness and drug use. The paper bridges two distinct approaches to understanding the relation between marginalization and crisis, with one focused on the impact of "big events" on marginalized populations, and another on everyday strategies employed to survive situations of homelessness and drug use. The paper shows how past experiences of hardship became relevant for coping with pandemic crisis. It further exploreshow, through critical engagement with dominant accounts of vulnerability, research participants carved out a space for negotiating their marginality in the Danish welfare state. [ABSTRACT FROM AUTHOR]

Copyright of Acta Facultatis Medicae Naissensis is the property of Nis University, Faculty of Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

OBJECTIVE: Drug utilization studies (DUS) provide a framework for drug utilization at the national or targeted population level and important information on unmet medical needs, particularly in assessing the rationality of drug use. We aimed to systematically review DUS conducted in Turkiye. METHODS: We examined 162 DUS with an accessible full-text, published as "research articles" and conducted in Turkiye between 2000 and 2021 using medical records and prescription data. We included English or Turkish papers with English abstracts. We examined the scientific characteristics of the publications, source of the data, place/time of collection, research designs, and studied drug groups. RESULTS: We found that 79.6% of articles were in English, 45.1% were listed in SCI/SCIE, and 63.0% were on the WOS platform with 3.5 (interquartile range: 1-15) citations. The mean study period and publication time were 2.9±3.1 and 2.9±2.1 years, respectively. The highest number of studies (17.9%) were published in 2021 and (26.5%) were conducted nationwide. We identified that 93.8% of the studies had retrospective design, 67.8% were conducted in secondary/tertiary health-care institutions, and 54.9% used direct hospital data. We detected that 68.5% of the studies were conducted on the general population, 19.1% on adults, 12.4% on children, and 44.4% were antibiotic oriented. CONCLUSION: Our study showed that a significant portion of the DUS, the trend of which has gained momentum in recent years, was antibiotic focused and conducted with a retrospective design from hospital-based data collected on the general patient population. This situation points to the necessity of expanding the existing DUS range by effectively using the new advantages provided by medical record databases and conducting more DUS that can provide critical clues for specific patients and drug groups. [ABSTRACT FROM AUTHOR]

Copyright of Revista Chilena de Derecho Privado is the property of Fundacion Fernando Fueyo Laneri and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Gastrointestinal cancers are characterized by a frequent incidence, a high number of associated deaths, and a tremendous burden on the medical system and patients worldwide. As conventional chemotherapeutic drugs face numerous limitations, researchers started to investigate better alternatives for extending drug efficacy and limiting adverse effects. A remarkably increasing interest has been addressed to chitosan and cyclodextrins, two highly versatile natural carbohydrate materials endowed with unique physicochemical properties. In this respect, numerous studies reported on fabricating various chitosan and cyclodextrin-based formulations that enabled prolonged circulation times, improved cellular internalization of carried drugs, preferential uptake by the targeted cells, reduced side effects, enhanced apoptosis rates, and increased tumor suppression rates. Therefore, this paper aims to briefly present the advantageous properties of these oligo- and polysaccharides for designing drug delivery systems, further focusing the discussion on nanocarrier systems based on chitosan/cyclodextrins for treating different gastrointestinal cancers. Specifically, there are reviewed studies describing promising solutions for colorectal, liver, gastric, pancreatic, and other types of cancers of the digestive system towards creating an updated framework of what concerns anticancer chitosan/cyclodextrin-based drug delivery systems. [ABSTRACT FROM AUTHOR]

Hydrotropic solubilization is a technique that can be used to improve the solubility of drugs that are poorly soluble. This technique involves adding a large amount of a second solute, known as a hydrotrope, which increases the aqueous solubility of the poorly soluble drug. Hydrotropes such as sodium citrate, sodium benzoate, and urea have been shown to be effective in enhancing the solubility of poorly soluble drugs. This technique has several advantages over other solubility enhancement techniques, including its cost-effectiveness, eco-friendliness, and the fact that it does not require chemical modification of hydrophobic drugs or the use of organic solvents. Hydrotropic agents are now being used to develop various dosage forms, including solid dispersions, mouth-dissolving tablets, and injections, to improve poorly water-soluble drugs' therapeutic effectiveness and bioavailability. This review paper will provide an overview of hydrotropic solubilization techniques. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions Previous systematic reviews suggest that deprescribing may improve survival, particularly in frail older people. Evidence is rapidly accumulating, suggesting a need for an updated review of the literature.We updated a 2016 systematic review and meta‐analysis to include studies published from inception to 26 April 2024 from specified databases. Studies in which older people had at least one medication deprescribed were included and grouped by study designs and targeted medications. The risk of bias was assessed using the Cochrane tool and the Newcastle‐Ottawa tool. Odds ratios (OR) or mean differences were calculated as the effect measures using either the Mantel–Haenszel or generic inverse‐variance method with fixed‐ or random‐effects meta‐analyses. The primary outcome was mortality. Secondary outcomes were adverse drug withdrawal events, physical health, cognitive function, quality of life and effect on medication regimen. Subgroup analyses were performed based on age and intervention types.A total of 259 studies (reported in 286 papers) were included in this updated review. Deprescribing polypharmacy did not result in a significant reduction in mortality in both randomized (OR 0.96, 95% confidence interval [CI] 0.84–1.09) and non‐randomized studies (OR 0.70, 95% CI 0.36–1.38). Further subgroup analyses of randomized studies on deprescribing polypharmacy demonstrated a significant reduction in mortality in the young old (aged 65–79) (OR 0.71, 95% CI 0.51–0.99) and when patient‐specific interventions were applied (OR 0.79, 95% CI 0.63–0.99).Deprescribing can be achieved with potentially important benefits in terms of improved survival, particularly when patient‐specific interventions are applied and initiated early in the young old. [ABSTRACT FROM AUTHOR]

Cytochrome P450 3A4 (CYP3A4) is a crucial enzyme in the metabolism of xenobiotics, particularly in drug metabolism interactions (DDIs), making it a significant factor in clinical drug use. However, current assay techniques are both laborious and costly, making it difficult to construct a high-throughput monitoring method that can be used in conjunction with the clinic. This poses certain safety hazards for drug combination. Therefore, it is crucial to develop a synchronized monitoring method for the inhibition and induction of CYP3A4. In this study, we utilized 3D culture technology to develop a HepaRG cells spheroid model. The CYP450 and transporter expression, the albumin secretion, and urea synthesis capacity characteristics were analyzed. The NEN probe was utilized as a tracer molecule for CYP3A4. The fluorescence intensity of metabolites was characterized by laser confocal technique to determine the inhibition and expression of CYP3A4 in the HepaRG cell spheroid model by the antibiotics for sepsis. The results indicate that the HepaRG sphere model successfully possessed the physiological phenotype of the liver, which could be used for drug interaction monitoring. Through positive drug testing, NEN probe was able to achieve bidirectional characterization of CYP3A4 induction and inhibition. The monitoring method described in this paper was successfully applied to drug interaction monitoring of commonly used antibiotics in sepsis patients, which is a convenient and rapid monitoring method. The proposed method offers a new strategy for monitoring CYP3A4-mediated drug-drug interactions with a high-throughput assay, which will help to improve the safety of clinical drug combination. [ABSTRACT FROM AUTHOR]

Immunosuppressive drugs are the mainstay of treatment for many feline and canine autoimmune skin diseases, either as monotherapy or in combination with other drugs. Treatment with these drugs is often lifelong and may have long‐term consequences on the affected animal's overall quality‐of‐life. Clinicians need to understand the pharmacology of immunosuppressants in planning and executing the treatment regimen for the best possible clinical outcome, as well as reducing the risk of adverse effects. This review paper will focus on the mechanism of action, pharmacokinetics and pharmacodynamics, clinical uses and adverse effects of immunosuppressive drugs used to treat autoimmune dermatoses in cats and dogs. These include glucocorticoids, ciclosporin A, azathioprine, chlorambucil, mycophenolate mofetil, oclacitinib and Bruton's tyrosine kinase inhibitors. [ABSTRACT FROM AUTHOR]

This paper analyses the relationship between drug-related detentions for possession or petty dealing and drug-related violence. Two theoretical mechanisms are explored: (i) when a dealer is detained, the market is disrupted, and competition increases; (ii) when a consumer is detained, other consumers are deterred and seek new dealers, generating competition among groups and, consequently, increasing violence. These hypotheses are quantitatively evaluated using geocoded data from local San Luis Potosí, Mexico markets. Results suggest a relationship between drug-related violence and detentions occurring in a nearby location. These results emphasize the inefficacy of drug law enforcement strategies for reducing violence related to illegal drug markets in local settings and open the discussion for exploring different policies to reduce violence related to organized crime and the harms associated with illegal drug consumption. [ABSTRACT FROM AUTHOR]

Sexualized drug use (SDU) describes drug-facilitated sexual enhancement, and chemsex is an SDU subculture involving the use of specific drugs by men who have sex with men (MSM). This study aimed to identify research trends, foci, and themes within the SDU and chemsex-specific literature. The Web of Science Core Collection was searched with a list of SDU synonyms. All SDU-related articles were analyzed using the R package, bibliometrix. Full text review identified chemsex-specific records, and text was extracted verbatim for content analysis in Leximancer. The search returned 1,866 unique records. A total of 521 addressed SDU, and 301 papers specifically addressed chemsex. The small but growing SDU literature primarily addressed consensual encounters between MSM, and drug-facilitated assault experienced by women, in Western settings. Little attention was given to transgender communities or consensual SDU in cisgender heterosexual individuals. The literature primarily viewed SDU through a public health lens, specifically focusing on the risk conferred to sexual health.The SDU and chemsex-specific literature are potentially limited in scope and may inadequately capture the geographical, demographic, and cultural diversity of these phenomena. Future research should address the myriad social and health implications of SDU and chemsex participation across all relevant communities and settings. [ABSTRACT FROM AUTHOR]

Introduction: People who inject drugs experience stigma across multiple settings, including when accessing health‐care services, however, comparatively little is known about experiences of stigma towards other groups of people who use illegal drugs. This paper examines experience of, and factors associated with, stigma among two samples of people who use illegal drugs when visiting both specialist alcohol and other drug (AOD) and general health‐care services. Methods: Australians who regularly (i.e., ≥monthly) inject drugs (n = 879; illicit drug reporting system [IDRS]) or use ecstasy and/or other illegal stimulants (n = 700; ecstasy and related drugs reporting system [EDRS]) were surveyed between April and July 2022 about past 6‐month experience of stigma in the above services. Multi‐variable regression analyses were performed to determine the socio‐demographic, drug use and health factors associated with stigma. Results: Experiences of stigma in general health‐care services were more common among IDRS (40%) than EDRS (24%; p < 0.001) participants, however, experiences were comparable in specialist AOD health‐care settings (22% and 20%, respectively; p = 0.687). Gender identity and experiencing high psychological distress were associated with experiencing stigma across both samples. Past‐year overdose was associated with experiencing stigma among the IDRS sample, while unstable housing and incomplete high school education were associated with experiencing stigma in the EDRS sample. Discussion and Conclusions: Experiences of stigma when accessing health‐care services are relatively common across different populations of people who use illegal drugs. Our findings highlight the multiple and intersecting dimensions of stigma and provide further support for recent calls for a universal precautions approach to stigma in health care. [ABSTRACT FROM AUTHOR]

Oklahoma's medical cannabis is some of the least restrictive in the US. Previous research suggests that American Indian/Alaska Native (AIAN) have higher rates of cannabis use than other racial or ethnic groups. The goals of this paper are, first, to look at cannabis use among high school students living on the Cherokee Nation Reservation before (2017) and after (2019) medical cannabis because legal in Oklahoma (2018) utilizing the Cherokee Nation Youth Risk Behavior Survey (CNYRBS). Second, to describe the socio-demographic characteristics of youth using cannabis in the Cherokee Nation Reservation. Data were retrieved from the 2017 and 2019 CNYRBS. The data for this study included 1,216 high school students who completed the 2017 and 1,476 who completed the 2019 CNYRBS. After removal of incomplete records, there were 2,602 students whose data was analyzed in this study. Data were weighted to be representative of public-school students attending grades 9–12 within Cherokee Nation Reservation. Despite the legalization of medical cannabis in Oklahoma in 2018, there was no change in cannabis use among youth between 2017 and 2019. There were variations in cannabis use based on demographic factors and other substance uses. AIAN individuals had higher odds of current cannabis use compared to non-Hispanic White students, but there were no differences based on ethnicity. Additionally, the use of cigarettes, e-cigarettes, alcohol, and illegal drugs were associated with increased odds of cannabis use among both current and former users compared to those who had never used it. There was no spike in use among youth at least immediately after the legalization of cannabis in the Cherokee Nation Reservation. There were socio-demographic as well as substance use disparities in the use of cannabis. [ABSTRACT FROM AUTHOR]

Anti-counterfeiting strategies primarily target the supply-side. The majority of studies on demand side strategies focused on developed-country consumers. This paper aims to examine ways to reduce counterfeit drug consumption by analyzing emerging markets from the consumers' demand side. In addition, this research is one of the first to provide empirical support for the notion that in persuasion, the product's domain matters, when it comes to regulatory fit. Consumers frame product domains in terms of approach or avoidance. If the framing of the message fits the product domain, it becomes more effective, more persuasive and even reduces purchase intentions regardless of individual's motivational regulatory state. We show that the most effective combination for advertisers and marketers, in emerging markets context, to reduce demand for counterfeit drugs, is to apply a fear/avoidance ad coupled with a prevention goal, regardless of individuals' motivational regulatory state. [ABSTRACT FROM AUTHOR]

Since 2002, seven iterations of the Drug Use Monitoring in Australia (DUMA) programme survey have asked arrested offenders about their stealing behaviours, including questions relating to stolen goods target selection and disposal. Throughout this same time period, stealing and domestic burglary rates in Australia have steadily declined. This paper examines the DUMA data with these high-level acquisitive crime trends in mind. Survey findings point to offenders having shifted away from stealing increasingly devalued electronic consumer goods for resale purposes, and toward stealing increasingly expensive food and clothing for personal consumption. This is consistent with what would be expected according to Consumer Price Index data, the opportunity-based CRAVED framework, and offender domain expertise. Applied and theoretical implications are discussed. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most leading deadly diseases in the world whose ranks first among all oncological diseases in women and it is the second spearheading reason of cancer deadness after lung cancer in the United States. Researchers from all over the world are working for finding better ways for preventing, identifying, and treating breast cancer. Topological indices are the functions generating a numerical value from the molecular graph of compounds and they are also a useful tool to estimate the pyhsicochemical and biological properties of molecules in the quantitative structure-property (activity) relationship (QSPR/QSAR) studies. In this paper, some drugs are studied which are used for the treatment of breast cancer. CoM-polynomials based on degree are occurred for chemical graphs of these drugs and the values of some variable topological coindices are calculated via these polynomials. The results obtained by regression analysis show that the correlations of the chosen coindices with the physicochemical properties of the determined drugs are good even strong for some of them. The QSPR models are constructed using the curvilinear regression method with topological coindices. [ABSTRACT FROM AUTHOR]

Background: Spontaneous reporting of adverse drug reactions (ADRs) is essential for the post-marketing safety evaluation of drugs. Therefore, good monitoring of ADRs is vital for strengthening drug supervision, management, and guiding rational drug use. Chinese medical institutions are the primary source of ADR case reports, but the proportion of the reports in grade IIIA hospitals is still low due to serious under-reporting. The 3rd Affiliated Hospital of Chengdu Medical College, Chengdu Pidu District People's Hospital, also has such a problem. Objective: To improve the quantity and quality of ADR reports and enhance the level of pharmacovigilance in hospitals, the Third Affiliated Hospital of Chengdu Medical College, People's Hospital of Chengdu Pidu District experienced 10 years to gradually establish a management model to improve the medical staff's reporting rate of spontaneous reporting of ADRs. The management model is led by clinical pharmacists and combines the PDCA with Teach-back methods. The purpose of this paper is to introduce the management model and discuss its advantages and shortcomings of this model. Methods: This study was conducted at the Third Affiliated Hospital of Chengdu Medical College—Chengdu Pidu District People's Hospital. From 2016, the daily management of reporting, auditing, and data improvement of adverse drug reactions in the hospital was carried out by clinical pharmacists, who used the PDCA method combined with the Teach-back method to continuously improve the reporting program of ADRs in the hospital during 2016–2021. Then, the proportion of spontaneous reports of total, new, and serious ADRs was compared before and after the intervention. Also, we performed a time series analysis using an autoregressive moving average model to assess changes in the total number of spontaneous ADR reports before the intervention (2013–2015), the first intervention (2016–2018), and the second intervention (2019–2021). Results: After the combined PDCA and Teach-back method intervention, the median number of reported ADRs per year increased from 50 (range 37–55) in the pre-intervention period to 88 (range 83–162) in the first intervention period and to 374 in the second (range 312–566). Breakpoint regression analysis of the spontaneous reporting rate of ADRs showed that the instantaneous increase after the first intervention was not statistically significant (P = 0.526). However, the reporting rate of ADRs increased at a month-by-month growth rate during the second intervention compared to the first intervention. Its spontaneous reporting rate improved 1.034 times (P = 0.002). After the second intervention, the spontaneous reporting rate of ADRs transiently increased 6.111-fold (P < 0.001), and the month-to-month growth rate increased 1.024-fold (P < 0.001) again. Conclusion: The management model that combines the PDCA and the Teach-back method significantly improves the reporting rate of adverse drug reactions. [ABSTRACT FROM AUTHOR]

Product consumption is an important yet understudied aspect of marketing. Over-the-counter medicines present a unique consumption context because consumers are expected to follow product label instructions. For acetaminophen, a widely consumed over-the-counter drug, the authors study which consumers tend to deviate from the label instructions, why they do so, and the interventions that are most promising to mitigate such deviations. They develop a dynamic structural model of consumption that enables them to investigate the probability of different types of label deviations (e.g., >4 g per day) and drivers of such behaviors. Label deviations are infrequent "tail area" behaviors, and the model uncovers them well. The analysis is based on a unique online consumption diary in which consumers select from two classes of acetaminophen products (single ingredient or a combination of ingredients) to treat their pain or non-pain-related symptoms. Consumers have a higher probability of taking >4 g of acetaminophen when they have multiple symptoms, and a variety of observable factors explain the individual propensity to deviate from the label. The authors propose two interventions—a new label instruction and consumer education—to mitigate the observed label deviations and assess the expected impact of each. [ABSTRACT FROM AUTHOR]

Introduction: The accurate identification and timely updating of adverse reactions in drug labeling are crucial for patient safety and effective drug use. Postmarketing surveillance plays a pivotal role in identifying previously undetected adverse events (AEs) that emerge when a drug is used in broader and more diverse patient populations. However, traditional methods of updating drug labeling with new AE information have been manual, time consuming, and error prone. This paper introduces the LabelComp tool, an innovative artificial intelligence (AI) tool designed to enhance the efficiency and accuracy of postmarketing drug safety surveillance. Utilizing a combination of text analytics and a trained Bidirectional Encoder Representations from Transformers (BERT) model, the LabelComp tool automatically identifies changes in AE terms from updated drug labeling documents.Our objective was to create and validate an AI tool with high accuracy that could enable researchers and FDA reviewers to efficiently identify safety-related drug labeling changes.Our validation study of 87 drug labeling PDF pairs demonstrates the tool's high accuracy, with F1 scores of overall performance ranging from 0.795 to 0.936 across different evaluation tiers and a recall of at least 0.997 with only one missed AE out of 483 total AEs detected, indicating the tool's efficacy in identifying new AEs.The LabelComp tool can support drug safety surveillance and inform regulatory decision-making. The publication of this tool also aims to encourage further community-driven enhancements, aligning with broader interests in applying AI to advance regulatory science and public health.Objective: The accurate identification and timely updating of adverse reactions in drug labeling are crucial for patient safety and effective drug use. Postmarketing surveillance plays a pivotal role in identifying previously undetected adverse events (AEs) that emerge when a drug is used in broader and more diverse patient populations. However, traditional methods of updating drug labeling with new AE information have been manual, time consuming, and error prone. This paper introduces the LabelComp tool, an innovative artificial intelligence (AI) tool designed to enhance the efficiency and accuracy of postmarketing drug safety surveillance. Utilizing a combination of text analytics and a trained Bidirectional Encoder Representations from Transformers (BERT) model, the LabelComp tool automatically identifies changes in AE terms from updated drug labeling documents.Our objective was to create and validate an AI tool with high accuracy that could enable researchers and FDA reviewers to efficiently identify safety-related drug labeling changes.Our validation study of 87 drug labeling PDF pairs demonstrates the tool's high accuracy, with F1 scores of overall performance ranging from 0.795 to 0.936 across different evaluation tiers and a recall of at least 0.997 with only one missed AE out of 483 total AEs detected, indicating the tool's efficacy in identifying new AEs.The LabelComp tool can support drug safety surveillance and inform regulatory decision-making. The publication of this tool also aims to encourage further community-driven enhancements, aligning with broader interests in applying AI to advance regulatory science and public health.Results: The accurate identification and timely updating of adverse reactions in drug labeling are crucial for patient safety and effective drug use. Postmarketing surveillance plays a pivotal role in identifying previously undetected adverse events (AEs) that emerge when a drug is used in broader and more diverse patient populations. However, traditional methods of updating drug labeling with new AE information have been manual, time consuming, and error prone. This paper introduces the LabelComp tool, an innovative artificial intelligence (AI) tool designed to enhance the efficiency and accuracy of postmarketing drug safety surveillance. Utilizing a combination of text analytics and a trained Bidirectional Encoder Representations from Transformers (BERT) model, the LabelComp tool automatically identifies changes in AE terms from updated drug labeling documents.Our objective was to create and validate an AI tool with high accuracy that could enable researchers and FDA reviewers to efficiently identify safety-related drug labeling changes.Our validation study of 87 drug labeling PDF pairs demonstrates the tool's high accuracy, with F1 scores of overall performance ranging from 0.795 to 0.936 across different evaluation tiers and a recall of at least 0.997 with only one missed AE out of 483 total AEs detected, indicating the tool's efficacy in identifying new AEs.The LabelComp tool can support drug safety surveillance and inform regulatory decision-making. The publication of this tool also aims to encourage further community-driven enhancements, aligning with broader interests in applying AI to advance regulatory science and public health.Conclusion: The accurate identification and timely updating of adverse reactions in drug labeling are crucial for patient safety and effective drug use. Postmarketing surveillance plays a pivotal role in identifying previously undetected adverse events (AEs) that emerge when a drug is used in broader and more diverse patient populations. However, traditional methods of updating drug labeling with new AE information have been manual, time consuming, and error prone. This paper introduces the LabelComp tool, an innovative artificial intelligence (AI) tool designed to enhance the efficiency and accuracy of postmarketing drug safety surveillance. Utilizing a combination of text analytics and a trained Bidirectional Encoder Representations from Transformers (BERT) model, the LabelComp tool automatically identifies changes in AE terms from updated drug labeling documents.Our objective was to create and validate an AI tool with high accuracy that could enable researchers and FDA reviewers to efficiently identify safety-related drug labeling changes.Our validation study of 87 drug labeling PDF pairs demonstrates the tool's high accuracy, with F1 scores of overall performance ranging from 0.795 to 0.936 across different evaluation tiers and a recall of at least 0.997 with only one missed AE out of 483 total AEs detected, indicating the tool's efficacy in identifying new AEs.The LabelComp tool can support drug safety surveillance and inform regulatory decision-making. The publication of this tool also aims to encourage further community-driven enhancements, aligning with broader interests in applying AI to advance regulatory science and public health. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to estimate behavioural curves from Near-Infra-Red (NIR) iris images for classifying Fitness for Duty using a biometric capture device. Fitness for Duty (FFD) techniques detect whether a subject is Fit to safely perform a given task, which means no reduced alertness condition and security, or the subject is unfit, that could impact a reduced alertness condition by sleepiness or consumption of alcohol and drugs. The analysis showed essential differences in pupil and iris behaviour to classify the workers in "Fit" or "Unfit" conditions. The best results can distinguish subjects robustly under alcohol, drug consumption, and sleep conditions. The Multi-Layer-Perceptron and Gradient Boosted Machine reached the best results in all groups with an overall accuracy for Fit and Unfit classes of 74.0% and 75.5%, respectively. These results open a new application for iris capture devices. • This work is a step forward in Iris biometric applications. • This research proposes a new database and method to detect Fitness for Duty. • This paper proposes a new method to estimate behavioural curves from iris images • Fitness for Duty allows us to detect Fit/Unfit subjects and save lives • This method classifies alcohol, drug, and sleepiness using an iris image. [ABSTRACT FROM AUTHOR]

Patents prevent generic drug entry. Brand firms file new "method of use" patents for old drugs to prevent generic entry. Congress addressed this issue by creating the "skinny label" pathway, which allows generic firms to use the drug label to indicate that the old drug can only be used for non‐patented uses. This pathway is now in jeopardy due to a recent court case. This paper outlines the issues and suggests possible legislative solutions. [ABSTRACT FROM AUTHOR]

[Display omitted] • The paper presents a method of Ti6Al4V modification using ciprofloxacin. • The influence of a cations on the effectiveness of drug sorption was determined. • The most effective cation was zinc and the least effective was calcium. • The antibiotic was evenly distributed on alloys modified with titanates. • The biocompatibility of the obtained materials is indicated. The paper presents a new method of titanium alloy (Ti6Al4V) modification using bioactive titanate layers containing various divalent ions (Ca2+, Mg2+, Sr2+, Zn2+) and surface-coordinated ciprofloxacin. Due to the coordination of ciprofloxacin (antibiotic) on the surface of the alloy, it has great application potential. In the paper, the influence of a given cation on the effectiveness of drug sorption was determined. The most effective cation was zinc and the least effective was calcium. The distribution of the antibiotic on the alloy surface was determined using FT-IR imaging. The antibiotic was evenly distributed on alloys modified with magnesium, strontium and zinc titanates. In the case of calcium titanate, the analysis could not be performed because the amount of the drug was too small. The release profiles of ciprofloxacin indicate that it can be released for as long as 3 h for strontium and zinc titanates. The biocompatibility of the obtained materials is indicated by the results of the BSA adsorption, and HA growth test. The obtained results confirm that the proposed modification can be used in the modification of titanium implants. The big advantage of this layer is that ciprofloxacin is coordinated on the surface of the material and thus will not be removed during the surgical procedure. The creation of this type of layer may in the future allow for fewer perioperative infections, and thus fewer complications. [ABSTRACT FROM AUTHOR]

The combined use of multiple medications is common in treatment, which may lead to severe drug–drug interactions (DDIs). Deep learning methods have been widely used to predict DDIs in recent years. However, current models need help to fully understand the characteristics of drugs and the relationships between these characteristics, resulting in inaccurate and inefficient feature representations. Beyond that, existing studies predominantly focus on analyzing a single DDIs, failing to explore multiple similar DDIs simultaneously, thus limiting the discovery of common mechanisms underlying DDIs. To address these limitations, this research proposes a method based on M-Transformer and knowledge graph for predicting DDIs, comprising a dual-pathway approach and neural network. In the first pathway, we leverage the interpretability of the transformer to capture the intricate relationships between drug features using the multi-head attention mechanism, identifying and discarding redundant information to obtain a more refined and information-dense drug representation. However, due to the potential difficulty for a single transformer model to understand features from multiple semantic spaces, we adopted M-Transformer to understand the structural and pharmacological information of the drug as well as the connections between them. In the second pathway, we constructed a drug–drug interaction knowledge graph (DDIKG) using drug representation vectors obtained from M-Transformer as nodes and DDI types as edges. Subsequently, drug edges with similar interactions were aggregated using a graph neural network (GNN). This facilitates the exploration and extraction of shared mechanisms underlying drug–drug interactions. Extensive experiments demonstrate that our MTrans model accurately predicts DDIs and outperforms state-of-the-art models. [ABSTRACT FROM AUTHOR]

Cancer treatment has become one of the biggest challenges in the world today. Different treatments are used against cancer; drug-based treatments have shown better results. On the other hand, designing new drugs for cancer is costly and time-consuming. Some computational methods, such as machine learning and deep learning, have been suggested to solve these challenges using drug repurposing. Despite the promise of classical machine-learning methods in repurposing cancer drugs and predicting responses, deep-learning methods performed better. This study aims to develop a deep-learning model that predicts cancer drug response based on multi-omics data, drug descriptors, and drug fingerprints and facilitates the repurposing of drugs based on those responses. To reduce multi-omics data's dimensionality, we use autoencoders. As a multi-task learning model, autoencoders are connected to MLPs. We extensively tested our model using three primary datasets: GDSC, CTRP, and CCLE to determine its efficacy. In multiple experiments, our model consistently outperforms existing state-of-the-art methods. Compared to state-of-the-art models, our model achieves an impressive AUPRC of 0.99. Furthermore, in a cross-dataset evaluation, where the model is trained on GDSC and tested on CCLE, it surpasses the performance of three previous works, achieving an AUPRC of 0.72. In conclusion, we presented a deep learning model that outperforms the current state-of-the-art regarding generalization. Using this model, we could assess drug responses and explore drug repurposing, leading to the discovery of novel cancer drugs. Our study highlights the potential for advanced deep learning to advance cancer therapeutic precision. [ABSTRACT FROM AUTHOR]

Drug substances and excipients must be stored in recommended storage conditions and should comply with their specifications during the retest period for their use in the manufacture of drug products. The ICH (International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use) and WHO (World Health Organization) regulatory guidelines mandate that after the retest period, the drug substances must be retested for compliance with the specification and then used immediately in the manufacture of the finished product. Although these substances can be retested multiple times, an emphasis is placed on immediate use following a retest and compliance with standards. The phrase "used immediately" is ambiguous and is left for interpretation. In this article, we will look at the various processes that must be completed to determine the retest date. In addition, we present a risk-based method for establishing retest dates and the time during which material can be used. [ABSTRACT FROM AUTHOR]

Drug testing is a common practice for community supervision in the U.S., despite limited research on its effectiveness at deterring future drug use. The present study explores the purpose of drug testing by examining the relationship between drug test frequency and positive test results. The impact of the type of drug tested (any vs. serious) and the risk and need level of the individuals tested are also examined. Results indicate that after controlling for risk and substance abuse need, more frequent testing schedules are associated with an increased rate of positive drug tests, suggesting more frequent testing detects rather than deters drug use. Policy implications for community corrections' purpose and use of drug testing are discussed. [ABSTRACT FROM AUTHOR]

To date, the definition that the off-label usage of drugs refers to the unapproved use of approved drugs, which covers unapproved indications, patient populations, doses, and/or routes of administration, has been in existence for many years. Currently, there is a limited frequency and prevalence of research on the off-label use of antineoplastic drugs, mainly due to incomplete definition and classification issues. It is time to embrace new categories for the off-label usage of anticancer drugs. This review provided an insight into an updated overview of the concept and categories of the off-label use of anticancer drugs, along with illustrating specific examples to establish the next studies about the extent of the off-label usage of anticancer drugs in the oncology setting. The scope of the offlabel use of current anticancer drugs beyond the previous definitions not only includes off-label uses in terms of indications, patient populations, doses, and/or routes of administration but also off-label use in terms of medication course, combination, sequence of medication, clinical purpose, contraindications scenarios, etc. In addition, the definition of the off-label usage of anticancer drugs should be added to the condition at a given time, and it varies from approval authorities. We presented a new and relatively comprehensive classification, providing extensive analysis and illustrative examples of the off-label usage of antineoplastic drugs for the first time. Such a classification has the potential to promote practical adoption and enhance management strategies for the offlabel use of antitumor drugs. [ABSTRACT FROM AUTHOR]

Featured Application: Featured Application: Bioequivalence studies of highly variable drugs require the utilization of large numbers of volunteers. The EMA and FDA propose the utilization of scaled limits. In this study, we introduce the use of artificial neural networks, along with the typical 80–125% limits, as a tool for virtually increasing sample size and thus reducing the actual human exposure. The bioequivalence (BE) of highly variable drugs is a complex issue in the pharmaceutical industry. The impact of this variability can significantly affect the required sample size and statistical power. In order to address this issue, the EMA and FDA propose the utilization of scaled limits. This study suggests the use of generative artificial intelligence (AI) algorithms, particularly variational autoencoders (VAEs), to virtually increase sample size and therefore reduce the need for actual human subjects in the BE studies of highly variable drugs. The primary aim of this study was to show the capability of using VAEs with constant acceptance limits (80–125%) and small sample sizes to achieve high statistical power. Monte Carlo simulations, incorporating two levels of stochasticity (between-subject and within-subject), were used to synthesize the virtual population. Various scenarios focusing on high variabilities were simulated. The performance of the VAE-generated datasets was compared to the official approaches imposed by the FDA and EMA, using either the constant 80–125% limits or scaled BE limits. To demonstrate the ability of AI generative algorithms to create virtual populations, no scaling was applied to the VAE-generated datasets, only to the actual data of the comparators. Across all scenarios, the VAE-generated datasets demonstrated superior performance compared to scaled or unscaled BE approaches, even with less than half of the typically required sample size. Overall, this study proposes the use of VAEs as a method to reduce the necessity of recruiting large numbers of subjects in BE studies. [ABSTRACT FROM AUTHOR]

Background: Policies to address substance use differ greatly between settings, where goals may range from zero-tolerance to harm reduction. Different approaches impact formats of care, policing, and even interpersonal interactions, and may play a role in the labelling and stigmatization of people who use drugs (PWUD). Where Sweden has a more restrictive policy, aiming to have a society free from drugs, Denmark has embraced harm reduction principles. The aim of this study was to explore PWUDs' experiences of interpersonal interactions, policing, and service formats in the two countries. Methods: The data consists of 17 qualitative semi-structured interviews with Swedish PWUD who have been in both Sweden and Denmark. Recruitment took place at harm reduction sites in both countries, and through snowball sampling. Results: Participants reflected on how they were perceived by those in public spaces, and received by care systems and personnel. In public settings in Sweden, participants felt they were ignored, rendered invisible, and lost their humanity. In Denmark, they were perceived and acknowledged, valued as people. This was simultaneously linked to being embodied by the availability of differing service offerings and policing practices, which solidified their "right to be out" in public. Reflecting on their reception in the treatment system, strict formatting in Sweden caused participants to feel that an identity was projected upon them, limiting their opportunities or growth of new facets of identity. Care relations in Denmark fostered more opportunity for autonomy and trust. Conclusion: A zero-tolerance policy and associated public discourses could solidify and universalize stigmatizing categorizations as a central feature of PWUD identity and reception from those around them, exacerbating social exclusion. Conversely, harm reduction-centered policies fostered positive interactions between individuals with care providers, public, and police, which may promote inclusion, empowerment, and wellbeing. [ABSTRACT FROM AUTHOR]

Background: Causal mediation analysis plays a crucial role in examining causal effects and causal mechanisms. Yet, limited work has taken into consideration the use of sampling weights in causal mediation analysis. In this study, we compared different strategies of incorporating sampling weights into causal mediation analysis. Methods: We conducted a simulation study to assess 4 different sampling weighting strategies-1) not using sampling weights, 2) incorporating sampling weights into mediation "cross-world" weights, 3) using sampling weights when estimating the outcome model, and 4) using sampling weights in both stages. We generated 8 simulated population scenarios comprising an exposure (A), an outcome (Y), a mediator (M), and six covariates (C), all of which were binary. The data were generated so that the true model of A given C and the true model of A given M and C were both logit models. We crossed these 8 population scenarios with 4 different sampling methods to obtain 32 total simulation conditions. For each simulation condition, we assessed the performance of 4 sampling weighting strategies when calculating sample-based estimates of the total, direct, and indirect effects. We also applied the four sampling weighting strategies to a case study using data from the National Survey on Drug Use and Health (NSDUH). Results: Using sampling weights in both stages (mediation weight estimation and outcome models) had the lowest bias under most simulation conditions examined. Using sampling weights in only one stage led to greater bias for multiple simulation conditions. Discussion: Using sampling weights in both stages is an effective approach to reduce bias in causal mediation analyses under a variety of conditions regarding the structure of the population data and sampling methods. [ABSTRACT FROM AUTHOR]

Introduction: A growing body of literature is investigating the difficulties that some individuals encounter after psychedelic experiences. Existing research has explored the nature and predictors of these difficulties; however, a research gap exists in understanding how individuals endeavour to cope with such difficulties. Methods: The current study collected data from an international cohort of 608 participants who reported experiencing difficulties that persisted for at least one day after a psychedelic experience. They provided written data on how they used coping strategies to alleviate these difficulties. The qualitative analysis of the written data on coping was conducted using Structured Tabular Thematic Analysis. Results: A wide range of individual and social coping strategies were employed that were found helpful. The most common individual strategies were meditation and prayer, followed by self-educational activities such as reading and journaling. The most prevalent forms of social coping involved seeking support from friends or family members, followed by obtaining assistance from a therapist or coach. Features of social coping that were reported to be helpful included feeling heard/accepted, a non-judgemental attitude and sharing similar experiences. Discussion: Our findings hold potential for informing the design of therapeutic interventions and educational resources aimed at enhancing positive outcomes for those experiencing extended difficulties after psychedelic use. [ABSTRACT FROM AUTHOR]