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An editorial is presented on Catheter ablation vs. thoracoscopic surgical ablation in long-standing persistent atrial fibrillation. Topics include patients with symptomatic paroxysmal atrial fibrillation (AF) despite antiarrhythmic drug (AAD) treatment responding very well to pulmonary vein isolation (PVI) by catheter ablation; and embracing a simplified minimally invasive surgical ablation (SA) by video-assisted thoracoscopic high-energy radiofrequency (RF) ablation.

Introductions: Psychosis is a condition of severe mental disorder characterised by the presence of disability in assessing reality. Schizophrenia is the most common psychotic disorder. It is also associated with long-term disability. ACT is one of the newest psychological interventions for psychotic patients. This paper aims to describe ACT as the newest psychotherapy intervention and its advantages for psychotic patients. Review: The management of psychosis is a combination of the use of antipsychotics, psychotherapy, and psychosocial therapy. ACT is one of the newest psychological interventions for psychotic patients that aims to increase the patient’s psychological flexibility through six core processes of therapy: acceptance, cognitive defusion, being present, self as context, value, and committed action. ACT does not target symptom reduction. Therapists help patients recognise and reduce unnecessary struggles with psychological content so that patients can develop an accepting attitude and be able to move towards the values they hold. Conclusions: The use of third-wave behavioural therapy based on mindfulness and acceptance showed good results in patients with psychotic disorders. ACT aims to help individuals accept things that are beyond their control and commit to actions that can improve their lives. Research on the clinical adaptation of ACT for psychosis has shown good initial results in reducing distress due to psychotic symptoms, better regulation of emotions, and reducing relapsing rates. [ABSTRACT FROM AUTHOR]

The article addresses the problem of the presence of selected pharmaceuticals in waters by determining the state of scientific knowledge. The sources of drug residues in the aquatic environment were characterized and the most important information was collected on the toxicity measures of the most commonly used drugs, including NLPZ: (1) non-steroidal analgesics and antipyretics (diclofenac, ibuprofen, phenazone, acetaminophen, propyphenazone, indomethacin, ketoprofen, pentoxifylline, and phenacetin), (2) pharmaceuticals used to reduce blood lipid levels (bezafibrate, fenofibrate, gemfibrozil), (3) drugs used in cardiac conditions, in particular those used to lower blood pressure and treat arrhythmia (atenolol, sotalol, metoprolol), (4) antibiotics (trimethoprim, clarithromycin, amoxicillin, sulfamethoxazole, piperacillin, erythromycin, sulfadimidine, dehydrate-erythromycin, 4N-Acetylsulfamethoxazol), (5)drugs used to treat rheumatoid arthritis (naproxen, fenoprofen), and (6) anticonvulsants, drugs used in neuropathic disorders and tranquilisers (carbamazepine, diazepam, primidone, oxazepam, temazepam). The authors reviewed research papers dealing with the indicated issue, taking into account: (1) research on the presence of pharmaceuticals in water, (2) studies on the health and environmental risk of drinking water for the presence of drug residues and their mixtures, (3) research on the effectiveness of water treatment in terms of pharmaceuticals. Gaps in scientific knowledge have been demonstrated, which are a hint for the directions of future research work. [ABSTRACT FROM AUTHOR]

Recently, titanate nanotubes (TNTs) have been receiving more attention and becoming an attractive candidate for use in several disciplines. With their promising results and outstanding performance, they bring added value to any field using them, such as green chemistry, engineering, and medicine. Their good biocompatibility, high resistance, and special physicochemical properties also provide a wide spectrum of advantages that could be of crucial importance for investment in different platforms, especially medical and pharmaceutical ones. Hydrothermal treatment is one of the most popular methods for TNT preparation because it is a simple, cost-effective, and environmentally friendly water-based procedure. It is also considered as a strong candidate for large-scale production intended for biomedical application because of its high yield and the special properties of the resulting nanotubes, especially their small diameters, which are more appropriate for drug delivery and long circulation. TNTs' properties highly differ according to the preparation conditions, which would later affect their subsequent application field. The aim of this review is to discuss the factors that could possibly affect their synthesis and determine the transformations that could happen according to the variation of factors. To fulfil this aim, relevant scientific databases (Web of Science, Scopus, PubMed, etc.) were searched using the keywords titanate nanotubes, hydrothermal treatment, synthesis, temperature, time, alkaline medium, post treatment, acid washing, calcination, pharmaceutical applications, drug delivery, etc. The articles discussing TNTs preparation by hydrothermal synthesis were selected, and papers discussing other preparation methods were excluded; then, the results were evaluated based on a careful reading of the selected articles. This investigation and comprehensive review of different parameters could be the answer to several problems concerning establishing a producible method of TNTs production, and it might also help to optimize their characteristics and then extend their application limits to further domains that are not yet totally revealed, especially the pharmaceutical industry and drug delivery. [ABSTRACT FROM AUTHOR]

Background: There is limited research on the experiences of access to medicines for non-communicable diseases (NCDs) in health facilities among older persons in Uganda. This paper explores the perspectives of older persons and healthcare providers concerning older persons' access to essential medicines in Uganda. Methods: It is based on qualitative data from three districts of Hoima, Kiboga, and Busia in Uganda. Data collection methods included seven (07) focus group discussions (FGDs) and eighteen (18) in-depth interviews with older persons. Nine (9) key informant interviews with healthcare providers were conducted. Deductive and inductive thematic analysis (using Health Access Livelihood Framework) was used to analyze the barriers and facilitators of access to healthcare using QSR International NVivo software. Results: The key facilitators and barriers to access to healthcare included both health system and individual-level factors. The facilitators of access to essential medicines included family or social support, earning some income or Social Assistance Grants for Empowerment (SAGE) money, and knowing a healthcare provider at a health facility. The health system barriers included the unavailability of specialized personnel, equipment, and essential medicines for non-communicable diseases, frequent stock-outs, financial challenges, long waiting times, high costs for medicines for NCDs, and long distances to health facilities. Conclusion: Access to essential medicines for NCDs is a critical challenge for older persons in Uganda. The Ministry of Health should make essential drugs for NCDS to be readily available and train geriatricians to provide specialized healthcare for older persons to reduce health inequities in old age. Social support systems need to be strengthened to enable older persons to access healthcare. [ABSTRACT FROM AUTHOR]

Canada has one of the most complex and rigorous drug approval and public reimbursement processes and is, unfortunately, one of the countries with the longest delays in drug access. To assess the overall impact of systemic delays in access to cancer therapy, a targeted literature review (TLR) was performed to identify studies associated with the clinical, economic, and quality of life impacts of delayed access to oncology drugs. Using MEDLINE/PubMed databases and snowballing, four unique records met the eligibility criteria. Results revealed that clinical outcomes were the most impacted by systemic delays in access to oncology drugs (e.g., life years lost, overall survival, and progression-free survival). The four articles retrieved by the TLR specifically illustrated that a substantial number of life years could potentially be saved by increasing systemic efficiency regarding the development, approval, and reimbursement processes of new drugs for advanced malignancies. It is imperative that initiatives are put in place to improve the performance and speed of Canadian drug regulatory and health technology assessment (HTA) processes, especially for new cancer therapeutics. The proposed solutions in this paper include better coordination between HTA and Canadian payers to harmonize coverage decisions, international collaborations, information sharing, and national standards for timeliness in oncology drug access. [ABSTRACT FROM AUTHOR]

The journal Medicines has updated its scope to align more closely with the papers it publishes. The journal aims to provide more space for publications in the fields of therapeutic agents and advanced drug studies, while excluding topics such as diet and nutrition, biological and stem-cell therapy, radiation and other nonsurgical therapeutic strategies, palliative care and physical therapy, and multimodal therapy. The journal welcomes manuscripts covering various aspects of drug discovery and clinical application, including target molecules, specificity, side effects, resistance, combinational treatment, and factors that modify pharmacological actions. The goal is to encourage scientists to publish detailed experimental and theoretical results. [Extracted from the article]

In this paper, we study an automatic hypothesis generation (HG) problem, which refers to the discovery of meaningful implicit connections between scientific terms, including but not limited to diseases, chemicals, drugs, and genes extracted from databases of biomedical publications. Most prior studies of this problem focused on the use of static information of terms and largely ignored the temporal dynamics of scientific term relations. Even when the dynamics were considered in a few recent studies, they learned the representations for the scientific terms, rather than focusing on the term-pair relations. Since the HG problem is to predict term-pair connections, it is not enough to know with whom the terms are connected, it is more important to know how the connections have been formed (in a dynamic process). We formulate this HG problem as a future connectivity prediction in a dynamic attributed graph. The key is to capture the temporal evolution of node-pair (term-pair) relations. We propose an inductive edge (node-pair) embedding method named T-PAIR, utilizing both the graphical structure and node attribute to encode the temporal node-pair relationship. We demonstrate the efficiency of the proposed model on three real-world datasets, which are three graphs constructed from Pubmed papers published until 2019 in Neurology, Immunotherapy, and Virology, respectively. Evaluations were conducted on predicting future term-pair relations between millions of seen terms (in the transductive setting), as well as on the relations involving unseen terms (in the inductive setting). Experiment results and case study analyses show the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The negative consequences of Substandard and falsified (SF) medicines are widely documented nowadays and there is still an urgent need to find them in more efficient ways. Several screening tools have been developed for this purpose recently. In this study, three screening tools were used on 292 samples of ciprofloxacin and metronidazole collected in Cameroon. Each sample was then analyzed by HPLC and disintegration tests. Seven additional samples from the nitro-imidazole (secnidazole, ornidazole, tinidazole) and the fluoroquinolone (levofloxacin, ofloxacin, norfloxacin, moxifloxacin) families were analyzed to mimic falsified medicines. Placebo samples that contained only inert excipients were also tested to mimic falsified samples without active pharmaceutical ingredient (API). The three screening tools implemented were: a simplified visual inspection checklist, a low-cost handheld near infrared (NIR) spectrophotometer and paper analytical devices (PADs). Overall, 61.1% of the samples that failed disintegration and assay tests also failed the visual inspection checklist test. For the handheld NIR, one-class classifier models were built to detect the presence of ciprofloxacin and metronidazole, respectively. The APIs were correctly identified in all the samples with sensitivities and specificities of 100%. However, the importance of a representative and up-to-date spectral database was underlined by comparing models built with different calibration set spanning different variability spaces. The PADs were used only on ciprofloxacin samples and detected the API in all samples in which the presence of ciprofloxacin was confirmed by HPLC. However, these PADs were not specific to ciprofloxacin since they reacted like ciprofloxacin to other fluoroquinolone compounds. The advantages and drawbacks of each screening tool were highlighted. They are promising means in the frame of early detection of SF medicines and they can increase the speed of decision about SF medicines in the context of pharmaceutical post-marketing surveillance. [ABSTRACT FROM AUTHOR]

This paper proposes a leader–follower-based model of mobile molecular communication networks for target detection applications. The proposed model divides the application functionalities of molecular communication networks into two types of mobile bio-nanomachine: leader and follower bio-nanomachines. Leader bio-nanomachines distribute in the environment to detect a target and create an attractant gradient around the target. Follower bio-nanomachines move according to the attractant gradient established by leader bio-nanomachines; they approach the target and perform necessary functionalities, such as releasing drug molecules. This paper develops mathematical expressions for the proposed model, describes wet laboratory experiments designed to estimate model parameters, and performs biologically realistic computer simulation experiments to evaluate the performance of the proposed model. The main contributions of this paper are to demonstrate the functional division of molecular communication networks, which will facilitate the design and development of molecular communication networks. Furthermore, insight into the application-level performance of molecular communication networks will be provided based on the proposed model. [ABSTRACT FROM PUBLISHER]

The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference. However, in conjunction with a lack of a representative KG construction taxonomy, several existing approaches in this designated domain are inadequate and inferior. This paper is the first to provide a comprehensive taxonomy and a bird's eye view of healthcare KG construction. Additionally, a thorough examination of the current state-of-the-art techniques drawn from academic works relevant to various healthcare contexts is carried out. These techniques are critically evaluated in terms of methods used for knowledge extraction, types of the knowledge base and sources, and the incorporated evaluation protocols. Finally, several research findings and existing issues in the literature are reported and discussed, opening horizons for future research in this vibrant area. [ABSTRACT FROM AUTHOR]

This paper validates two approximate dynamic programming approaches on a maritime interdiction problem involving the allocation of multiple heterogeneous assets over a large area of responsibility to interdict multiple drug smugglers using heterogeneous types of transportation on the sea with varying contraband weights. The asset allocation is based on a probability of activity surface, which represents spatio-temporal target activity obtained by integrating intelligence data on drug smuggler whereabouts/waypoints for contraband transportation, behavior models, and meteorological and oceanographic information. We validate the proposed architectural and algorithmic concepts via several realistic mission scenarios. We conduct sensitivity analyses to quantify the robustness and proactivity of our approach, as well as to measure the value of information used in the allocation process. The contributions of this paper have been transitioned to and are currently being tested by Joint Interagency Task Force—South, an organization tasked with providing the initial line of defense against drug trafficking in the East Pacific and Caribbean Oceans. [ABSTRACT FROM AUTHOR]

In high-throughput drug screening applications, as manual drug sample delivery is time-consuming and error-prone, there is an urgent need for accurate and efficient drug sample delivery biochip for large-scale microwell arrays. This paper proposes a new microfluidic biochip architecture, where drugs are automatically prepared with different concentration values, and then delivered into multiple microwells. For large-scale drug sample delivery biochips, the routing of drug sample delivery channels is a very challenging task without effective routing solutions. This paper proposes an ultrafast rule-based escape routing method, called URBER, to address the large-scale routing of drug sample delivery channels, which scales well in both runtime and memory even for a very large problem size. URBER runs very fast because it routes channels based on a set of predefined rules, which avoids runtime consumed in solution space exploration. All benchmarks for 30 ${\le }~{N}$ , ${M} {\le }~100$ have been tested, where ${N}$ and ${M}$ are the number of columns and rows of the terminal array. Among these benchmarks, about ~91.9% are routed with optimal solutions, and the runtime is order of magnitudes faster than optimal min-cost flow-based methods (speedup is from ~600 to ~340 k). Specifically, for all benchmarks with (${M}/{N}$) ${\in }$ ((3/4), (4/3)), optimal routing solutions are always obtained. URBER also shows promise of routing large-scale designs with up to 500 k terminals efficiently. [ABSTRACT FROM AUTHOR]

Background: The goal of the public procurement of pharmaceuticals is to purchase sufficient quantities of high-quality pharmaceuticals at cost-effective prices for a given population. This goal can be undercut if corruption infiltrates the procurement process. Good procurement practices can help mitigate the risks of corruption and support equitable access to affordable and high-quality medicines. Objectives: This paper aims to 1) examine manifestations of corruption in the pharmaceutical procurement process and key factors behind them, and 2) identify how to design and implement effective anti-corruption, transparency and accountability mechanisms within this process. Methods: This paper was informed by a narrative literature review from 1996 to the present. The search focused on publications that addressed the issue of pharmaceutical procurement and governance and corruption issues. Our search included peer-reviewed literature, books, grey literature such as working papers, reports published by international organizations and donor agencies, and some media articles. Some documents used in this paper were already known to the authors. Results: Procurement is highly vulnerable to corruption particularly in the health sector. What is more, corruption in the procurement process does not appear to be limited to any one level of government or type of health system. The better integration of accountability, transparency and anti-corruption mechanisms in the procurement process is needed to reduce the risk of corruption. Conclusions: Lessons learned suggest that anti-corruption, transparency and accountability mechanisms in the pharmaceutical procurement process, such as open contracting and integrity pacts are helpful towards reducing the risk of corruption. [ABSTRACT FROM AUTHOR]

BACKGROUND: A greater understanding of Over the Counter (OTC) and Prescription Only Medication (POM) misuse amongst adults accessing substance misuse services (SMS) during COVID-19 is required to identify how SMS can better meet the needs of the people who require treatment. AIM: To use a questionnaire to explore OTC/POM misuse during COVID-19 in adults accessing community SMS in England. METHODS: In 2020 to 2021 anonymous self-administered online/paper questionnaires which collated quantitative and qualitative data were completed. They were piloted for suitability and ethical approval was obtained. Thematic analysis was conducted for qualitative data and chi-square tests used to assess the relationship between quantitative variables. RESULTS: Participants were Caucasian (94.6% British), majority male (58.9%), aged 18 to 61 years. Most were prescribed medication for problematic substance use, with a 92.5% self-reported adherence rate. The misuse of benzodiazepines (22.2%) codeine products (30.8%) and pregabalin (14.5%) predominated and 37.5% misused 2 or more medicines. Administration was usually oral and concomitant use of other substances was common: alcohol 44.6% (52% daily), tobacco/vaping 73.2% and illicit substances 58.9%. There were statistically significant associations identified, including between changes during COVID-19 to OTC/POM misuse and illicit use. Only 56 questionnaires were included in the analysis: we believe this low number was because of infection control measures, limited footfall in services, pressures on staff limiting their capacity to distribute the paper questionnaires and reliance upon telephone consultations limiting online distribution. Increasing OTC/POM misuse and obtaining illicit supplies were reported when access to usual supplies were restricted; however, changes to doses/dispensing arrangement liberalisation in response to COVID-19 were positively viewed. CONCLUSION: OTC/POM misuse, including polypharmacy and concomitant use of other substances occurred during COVID-19: SMS need to be vigilant for these issues and mitigate the associated risks for example with harm reduction interventions. Further qualitative research is required to explore the issues identified. [ABSTRACT FROM AUTHOR]

This article deals with chromatographic identification of organic compounds. Chromatography, particularly paper and gas chromatography, have rapidly come into general use in criminalistics and toxicological laboratories, hence, a discussion of its application for identification of organic chemical compounds, particularly narcotics, poisons and drugs is timely. By chromatography, unless a specified method is designated, all types of chromatography paper, gas, column, and electrophoresis are included. This discussion will be limited to an analysis of the information which can be derived from the position parameters measured in the process for the purpose of identification, and nothing will be said about the conditions of chromatography or the advantages of chromatographic separation and purification. A given chromatographic identification process, when established with a limited number of reference compounds, may appear to be quite specific; this is particularly true when reference compounds include only closely related simple compounds of one homologous chemical series. However, as an increasing number of reference compounds are included in the analytical system, and as the sensitivity of detection increases, or the detection method is made less specific, more and more apparent identities appear.

Introduction: Depression is the leading cause of disability worldwide and has become a health issue of global concern. Based on the "System of Health Accounts 2011" (SHA 2011) for patients with depression, this paper studies the changes in the current curative expenditure (CCE) of outpatient depression in Liaoning Province, China, and provides policy recommendations. Method: A stratified multistage random sample of 56,994 patients with depression included from 1,227 healthcare facilities in Liaoning Province were included. The significance of differences in variables within groups was analyzed by univariate analysis (including descriptive statistics analysis, Mann-Whitney U test and Kruskal-WallisH test), and factors influencing depression outpatient CCE were analyzed by multiple linear regression analysis and constructing structural equation models (SEM). Results: The CCE of outpatient depression was ranging from CNY 75.57 million to CNY 100.53 million in 2015-2020, with the highest of CNY 100.53 million in 2018, CNY 103.28 million in 2019. Medical expenditures are mainly concentrated in general hospitals and provincial healthcare institutions, accounting for about 90% of all provincial scope expenditures. The multiple regression results show that provincial healthcare institutions, purchase of drug, select medical treatment for depression, general hospitals and urban employees' health insurance are the main influencing factors for depression outpatient CCE. The results of SEM show that insurance status negative impact outpatient expenditure. Conclusion: Health insurance is an important factor in equitable access to healthcare resources for patients, and medication expenditure is the influential factor affecting the high expenditure of outpatient clinics. It is of great importance to reduce the medical burden of patients by increasing the coverage of medical insurance, increasing the proportion of bills that are eligible for reimbursement, and improving the system by guaranteeing the supply of psychotropic medication. [ABSTRACT FROM AUTHOR]

Navigating the healthcare conundrum in the Blue Zone of Loma Linda, California, requires understanding the unique factors that make this region stand out in terms of health and longevity. But more important is understanding the healthcare system sustaining the Blue Zone in Loma Linda, California. In an era marked by soaring healthcare costs and diminishing reimbursement rates, hospitals and physicians face an unprecedented challenge: providing excellent patient care while maintaining financial sustainability. This leadership perspective publication paper delves into the multifaceted struggles encountered by healthcare and hospital leaders, exploring the root causes, implications, and potential solutions for this complex issue. As we examine the evolving healthcare landscape, we aim to shed light on the critical need for innovative approaches to sustain the future of healthcare excellence in one of the five original Blue Zones. [ABSTRACT FROM AUTHOR]

The unique expression patterns of circRNAs linked to the advancement and prognosis of cancer underscore their considerable potential as valuable biomarkers. Repurposing existing drugs for new indications can significantly reduce the cost of cancer treatment. Computational prediction of circRNA-cancer and drug-cancer relationships is crucial for precise cancer therapy. However, prior computational methods fail to analyze the interaction between circRNAs, drugs, and cancer at the systematic level. It is essential to propose a method that uncover more valuable information for achieving cancer-centered multi-association prediction. In this paper, we present a novel computational method, AutoEdge-CCP, to unveil cancer-associated circRNAs and drugs. We abstract the complex relationships between circRNAs, drugs, and cancer into a multi-source heterogeneous network. In this network, each molecule is represented by two types information, one is the intrinsic attribute information of molecular features, and the other is the link information explicitly modeled by autoGNN, which searches information from both intra-layer and inter-layer of message passing neural network. The significant performance on multi-scenario applications and case studies establishes AutoEdge-CCP as a potent and promising association prediction tool. Author summary: CircRNAs serve as crucial biomarkers and drug targets in cancer therapy. Predicting cancer-associated circRNAs and drugs contributes to uncover intricate molecular mechanisms driving tumorigenesis, thus offering novel insights into cancer diagnosis, treatment, and research. However, prevailing predictive methods often neglect the comprehensive interactions within circRNAs, drugs, and cancer, leading to an incomplete understanding of their complex interplay. In response, we introduce AutoEdge-CCP, a framework that models circRNA-cancer-drug interactions within a multi-source heterogeneous network. Each molecule combines intrinsic attribute information describing molecular features with interaction information derived through autoGNN, revealing pivotal circRNAs and drugs associated with cancer. Experimental results across multi-scenario attest to AutoEdge-CCP's superior performance compared to competing methods, particularly in predicting novel circRNAs and drugs associated with cancer. Additionally, visualization of edge embeddings and case studies provide interpretable insights into the prediction outcomes. [ABSTRACT FROM AUTHOR]

Background: Decisions on the frequency of physician encounters for patients with type 2 diabetes mellitus (T2DM) have significant impacts on both patients' health outcomes and burden on health systems, whereas definitive intervals for physician encounters are still lacking in most clinical guidelines. This study systematically reviewed the existing evidence evaluating different frequencies of physician encounters among T2DM patients. Methods: Systematic search of studies evaluating different visit frequencies for follow - up care in T2DM patients was performed in MEDLINE Ovid, Embase Ovid, and Cochrane library from database inception to 25 March 2022. Studies on the follow - up encounters driven by non - physicians and those on the episodic visits in the acute care settings were excluded in the screening. Citation searching was conducted via Google Scholar on the identified papers after screening. The risk of bias was assessed using Cochrane RoB2 tool for randomized controlled trials and Newcastle - Ottawa Scale for cohort studies. Findings were summarized narratively. Results: Among 6363 records from the database search and 231 references from the citation search, 12 articles were eligible for in - depth review. The results showed that for patients who had not achieved cardiometabolic control, intensifying encounter frequency could enhance medication adherence, shorten the time to achieve the treatment target, and improve the patients' quality of life. However, for the patients who had already achieved the treatment targets, less frequent encounters were equivalent to intensive encounters in maintaining their cardiometabolic control, and could save considerable healthcare costs without substantially lowering the quality of care and patients' satisfaction. Conclusion: Existing evidence suggested that the optimal frequency of physician encounters for patients with T2DM should be individualized, which can be stratified by patients' risk levels based on the cardiometabolic control to guide the differential scheduling of physician encounters in the follow - up. More research is needed to determine how to optimize the frequency of physician encounters for this large and heterogeneous population. [ABSTRACT FROM AUTHOR]

Background: Temporomandibular disorders (TMD) are manifested by soreness in the jaw joint area and jaw muscles, clicks or creaks when opening or closing the mouth. All these symptoms can be disabling and occur during chewing and when the patient yawns or speaks. Several classes of drugs are used to treat symptoms. This review aims to assess which drug suits the different signs. Methods: Pubmed, Web of Science and Lilacs were systematically searched until 01/02/2023. Clinical trials were selected that dealt with drugs used in temporomandibular dysfunction Results: Out of 830 papers, eight studies were included. The Meta-Analysis with Continuous Outcomes with Pre-Calculated Effect Sizes resulted in the rejection that there is intergroup variability (p.0.74). Conclusions: Treatment of orofacial pain is still a significant challenge for dentistry. We can conclude that there is no drug of first choice in the treatment of temporomandibular pain. However, the clinician must distinguish the type of pain and the aetioloic cause of the pain so that the patient can be treated and managed pharmacologically. [ABSTRACT FROM AUTHOR]

The objectives of this study were to explore the prescription and medication rules of famous and old Chinese medicine practitioners in the treatment of hyperuricemia (HUA) and the targets and pathways of high-frequency medication in combination with network pharmacology, so as to provide ideas for clinical justification and prescription. We searched CNKI, Wanfang, VIP, and CBM for literatures related to famous and old Chinese medicine practitioners and "hyperuricemia" and performed association rule analysis and cluster analysis with the help of SPSS Modeler18 and SPSS Statistics21. TCMSP was used to screen the active ingredients of HF medicines, GeneCards and OMIM databases were used to collect disease targets, and STRING and DAVID websites were used to analyze protein interactions (PPI) and GO and KEGG enrichment pathways. A total of 25 papers were included in the study including 58 prescriptions and involving 170 flavors of traditional Chinese medicine. The highfrequency drugs included Coix seed, Rhizona atractylodes macrocephala, Indian bread, Poria cocos, and Rhizoma dioscoreae tokoro. The core constituents were quercetin, naringenin, loksinoside, stigmasterol, and steroidal alcohol. The core targets were TNF, IL6, TP53, and IL-1. The efficacy of the drug is to diuretic and seepage of dampness, while the medicinal properties are cold and bitter, and most medicines are attributed to the liver meridian. The combination of drug pairs was the strongest with the association of Rhizoma atractylodis macrocephalae-Poria cocos, Radix clematidis-Rhizoma dioscoreae tokoro, Indian Bread-Rhizoma dioscoreae tokoro, Indian bread-Coix seed, and Rhizoma atractylodis macrocephalae-Astragalus. The results showed that treatment of HUA by famous Chinese medicine practitioners was based on diuresis and seepage of dampness, clearing heat, and removing toxins. Coix seed, Atractylodes macrocephala, and Poria cocos were the most commonly used in the treatment process. The core components were quercetin, naringenin, and luo xinwuoside, which agonized the lipid and atherosclerotic pathways, TNF signaling, and other pathways, and worked together to treat HUA. [ABSTRACT FROM AUTHOR]

Background: Drug delivery systems (DDSs) encompass a wide range of methods, including oral, injectable, and topical routes of administration, all tailored to meet specific patient needs. Micro and nanorobots, equipped with pioneering propulsion mechanisms that convert external energy sources into precise movements, have revolutionized drug delivery. This cutting-edge technology ensures highly efficient drug delivery, particularly when targeting specific targets within intricate physiological environments. In contrast to traditional drug delivery approaches that rely on bloodstream circulation, engineered micro/nanorobots have autonomous mobility, enabling drug delivery to previously unreachable areas. Integrating micro/nanorobots into drug delivery raises vital safety and biocompatibility issues. These encompass material selection, degradation in-vivo, overcoming biological barriers, controlled movement, external interference, immune response, chemical reactions, systemic effects, long-term impact, and real-time monitoring. While micro/nanorobots hold immense transformative potential, they confront significant hurdles in their journey toward practical applications. Chief among these challenges are concerns regarding biocompatibility, ensuring that these tiny devices do not trigger adverse reactions. Long-term safety remains a critical issue, as understanding the effects of prolonged exposure and potential accumulations within the body and navigating complex biological environments with precision is another obstacle. Short conclusion: The paper summarizes how to explore the various ways in which micro/nanorobots can be employed to enhance drug delivery, including their precision, targeting capabilities, and adaptability to different physiological conditions. Additionally, the review seeks to highlight the transformative potential of these technologies and their impact on the pharmaceutical industry. [ABSTRACT FROM AUTHOR]

Among women of reproductive age, PCOS (polycystic ovarian syndrome) is one of the most prevalent endocrine illnesses. In addition to decreasing female fertility, this condition raises the risk of cardiovascular disease, diabetes, dyslipidemia, obesity, psychiatric disorders and other illnesses. In this paper, we constructed a fractional order model for polycystic ovarian syndrome by using a novel approach with the memory effect of a fractional operator. The study population was divided into four groups for this reason: Women who are at risk for infertility, PCOS sufferers, infertile women receiving therapy (gonadotropin and clomiphene citrate), and improved infertile women. We derived the basic reproductive number, and by utilizing the Jacobian matrix and the Routh-Hurwitz stability criterion, it can be shown that the free and endemic equilibrium points are both locally stable. Using a two-step Lagrange polynomial, solutions were generated in the generalized form of the power law kernel in order to explore the influence of the fractional operator with numerical simulations, which shows the impact of the sickness on women due to the effect of different parameters involved. [ABSTRACT FROM AUTHOR]

Aristolochic acids (AAs) are a toxic substance present in certain natural plants. Direct human exposure to these plants containing AAs leads to a severe and irreversible condition known as aristolochic acid nephropathy (AAN). Additionally, AAs accumulation in the food chain through environmental mediators can trigger Balkan endemic nephropathy (BEN), an environmental variant of AAN. This paper presents a concise overview of the oncogenic pathways associated with AAs and explores the various routes of environmental exposure to AAs. The detection and removal of AAs in natural plants, drugs, and environmental and biological samples were classified and summarized, and the advantages and disadvantages of the various methods were analyzed. It is hoped that this review can provide effective insights into the detection and removal of AAs in the future. [ABSTRACT FROM AUTHOR]

Heterocyclic compounds have been the subject of extensive research due to their diverse pharmacological effects. Among these molecules are quinazolinone analogs, which have demonstrated a range of pharmacological potentials. In search of novel therapeutic pharmaceutical molecules, medicinal chemistry researchers are drawn to the quinazolinone nucleus. This article aims to provide an overview of the many pharmacological activities of the quinazolinone moiety. Based on the quinazolinone moiety, more modern molecules have been developed and synthesized. These compounds show negligible toxicity and outstanding anti-disease capabilities. This paper reviews several different quinazolinone analogs and makes recommendations for future research paths in the quest to create effective quinazolinone drugs for a range of biological objectives. [ABSTRACT FROM AUTHOR]

The complexity of the movements of the bones of the knee joint requires an anatomical study to construct a knee prosthesis. The reasons for knee replacement are related to wear of the articular cartilage, which leads to pain, deformation, and limitation of movements. The consequences of the surgical intervention allow functional restoration of the knee joint and the supporting function of the lower limb. Kinesitherapy begins the day after surgery and aims to reduce pain, restore mobility of the knee joint, actively lock the knee during extension, increase and maintain muscle strength, and ensure the functional independence of patients. To a large extent, the volume of movement is restored, and the pain symptoms are reduced. Patients have the comfort of everyday movements and the possibility of participating in certain sports activities-swimming, cycling, and golf. The paper deals with pharmacological prophylaxis, the kinesitherapeutic program, and total knee arthroprosthesis. [ABSTRACT FROM AUTHOR]

This paper focuses on addressing the complex healthcare needs of patients struggling with discordant chronic comorbidities (DCCs). Managing these patients within the current healthcare system often proves to be a challenging process, characterized by evolving treatment needs necessitating multiple medical appointments and coordination among different clinical specialists. This makes it difficult for both patients and healthcare providers to set and prioritize medications and understand potential drug interactions. The primary motivation of this research is the need to reduce medication conflict and optimize medication regimens for individuals with DCCs. To achieve this, we allowed patients to specify their health conditions and primary and major treatment concerns, for example, costs of medication, interactions with current drugs, and weight gain. Utilizing data gathered from MTurk and Qualtrics, we gained insights into healthcare providers' strategies for making/customizing medication regimens. We constructed a dataset and subsequently deployed machine learning algorithms to predict optimal medication regimens for DCC patients with specific treatment concerns. Following the benchmarking different models, Random forest emerged as the top performer, achieving an accuracy of 0.93. This research contributes significantly to the enhancement of decision-making processes, empowers patients to take a more active role in their healthcare, and promotes more informed and productive discussions between patients and their care teams. [ABSTRACT FROM AUTHOR]

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Copyright of Kemija u Industriji is the property of Croatian Society of Chemical Engineers 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.)

Background: The restrictions introduced to stop the spread of the COVID-19 virus have also had a direct impact on people with chronic diseases and especially on diseases to which lifestyles are relevant in their control and management, such as diabetes, hypertension, chronic obstructive pulmonary disease (COPD), etc. The purpose of this paper is to conduct a longitudinal analysis of new comorbidities, mortality, medication use, and the use of health resources in patients with chronic diseases who did not contract COVID-19, comparing the six months before the strict lockdown to the 12 months following the end of the strict lockdown. Method: An observational real world data pre-post study of 668,974 people was undertaken. The patients studied were over 16 years of age, had been receiving care from the Aragon Health Service (Northeastern Spain), were diagnosed with one or more chronic diseases, and had not contracted COVID-19. Sociodemographic, comorbidity, pharmacological and health resource use variables were collected during the six months before the onset of the lockdown and during the six and 12 months following the end of the lockdown. The comparisons by sex were carried out using a Student T-test or chi-squared test to analyse differences. Results: Dyslipidaemia (42.1%) followed by hypertension (35.1%) and anxiety and depression (34.6%) were the most prevalent chronic diseases among the study population. 78.% of patients had between one and four chronic illnesses. There was a decrease in new diagnoses of other chronic comorbidities in this population and a decrease in medications prescribed and the use of health services. Although women received more diagnoses of chronic diseases, the number of medications dispensed was lower, but the use of health services was higher. These figures were maintained throughout the pandemic. Conclusion: Our results suggest an underdiagnosis of new chronic comorbidities and a decrease in mortality rates from causes unrelated to COVID-19 due to the closure of health centres in Aragón (Spain) during the lockdown. This trend was exacerbated in women. The underdiagnosis of new chronic comorbidities during confinement can cause the disease to worsen, with the consequent increase in symptoms and the worsening of chronic pathologies in patients with a severe evolution. [ABSTRACT FROM AUTHOR]

The prevalence of diabetes and its associated complications continues to rise globally, creating a pressing need for effective and safe therapeutic approaches. Herbal remedies have gained significant attention as potential adjuncts or alternatives to conventional diabetes management. Syzygium cumini (Linn), commonly known as Jamun or Indian blackberry, possesses established antidiabetic and antioxidant properties. This research paper aims to optimize herbal drug formulations using Syzygium cumini extracts to enhance their antidiabetic and antioxidant effects. The study will involve extraction optimization, formulation development, and evaluation of the final products for potential therapeutic application. [ABSTRACT FROM AUTHOR]

Certain poisons and drugs can influence the growth and developmental patterns of necrophagous species, possibly affecting the accuracy of the postmortem interval (PMI) estimation. Since an accurate PMI estimate may prove an alibi (a critical aspect in criminal investigations), failure to consider factors that may affect the growth of necrophagous insects can subsequently result in the miscarriage of justice. In addition, the use of entomological specimens for diagnosing causes and circumstances surrounding death has been suggested for highly decomposed bodies, whereby conventional toxicological specimens are unavailable and/or unsuitable for analysis. In these two aspects, having the ability to determine poisons and drugs in entomological specimens appears imperative. Hence, this paper reviews pertinent articles on the analysis of poisons and drugs in entomological specimens published between 1977 and 2022, emphasizing on advantages/disadvantages of the reported instrumental analytical methods and their applications. It is organized according to the different classes of poisons and drugs, their extraction and analytical methods, as well as the results reported. Where available, information on the validation parameters of the published methods is duly discussed. This review aims to provide suitable references and guidance for future investigators wanting to carry out experiments concerning entomotoxicology for forensic applications. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has impacted access to and use of maternal, newborn, and child health services. Due to lockdowns and travel restrictions implemented during the first wave of the pandemic, the provision of essential maternal health services such as family planning was critically affected. Unlike most healthcare, contraception-related services are impractical for virtual care provision as women need to attend the clinic in person. Therefore, most women across the world might have been left with an unmet need for contraception during the lockdown period. Interruptions in contraception services have led to an increased number of unintended pregnancies. With the emergence of several pocket studies, it is essential to pool the available evidence reporting the effects of COVID-19 on contraception to inform maternal health policy and practice. Objective: The aims of this review are (1) to determine the effects of the COVID-19 pandemic on access to contraceptives among sexually active women and (2) to identify the magnitude of unintended pregnancy linked to interruptions of contraceptives due to the COVID-19 pandemic. Methods: The protocol for this systematic review was registered in PROSPERO (CRD42021267077). Electronic databases such as MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Scopus, Web of Science, and Google Scholar will be searched for articles using appropriate key terms. The identified articles will be assessed against the eligibility criteria. Two reviewers (A.B. and T.B.) will independently screen titles and abstracts of all retrieved articles followed by a full-text review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. The quality of the papers will be assessed by using the Risk of Bias Assessment tool for Non-Randomized Studies. Quantitative findings will be pooled using a random-effects model meta-analysis, while qualitative findings will be presented using a narrative synthesis. Ethics and dissemination: Ethical approval is not required. The findings will be disseminated through conference presentations and peer-reviewed publications. Discussion: This systematic review will present current data needed to design evidence-based programmes for improving access to contraception and preventing unintended pregnancy during the COVID-19 pandemic and future emergencies. Systematic review registration: PROSPERO CRD42021267077. [ABSTRACT FROM AUTHOR]

Even though named entity recognition (NER) has seen tremendous development in recent years, some domain-specific use-cases still require tagging of unique entities, which is not well handled by pre-trained models. Solutions based on enhancing pre-trained models or creating new ones are efficient, but creating reliable labeled training for them to learn on is still challenging. In this paper, we introduce PharmKE, a text analysis platform tailored to the pharmaceutical industry that uses deep learning at several stages to perform an in-depth semantic analysis of relevant publications. The proposed methodology is used to produce reliably labeled datasets leveraging cutting-edge transfer learning, which are later used to train models for specific entity labeling tasks. By building models for the well-known text-processing libraries spaCy and AllenNLP, this technique is used to find Pharmaceutical Organizations and Drugs in texts from the pharmaceutical domain. The PharmKE platform also incorporates the NER findings to resolve co-references of entities and examine the semantic linkages in each phrase, creating a foundation for further text analysis tasks, such as fact extraction and question answering. Additionally, the knowledge graph created by DBpedia Spotlight for a specific pharmaceutical text is expanded using the identified entities. The obtained results with the proposed methodology result in about a 96% F1-score on the NER tasks, which is up to 2% better than those of the fine-tuned BERT and BioBERT models developed using the same dataset. The ultimate benefits of the platform are that pharmaceutical domain specialists may more easily identify the knowledge extracted from the input texts thanks to the platform's visualization of the model findings. Likewise, the proposed techniques can be integrated into mobile and pervasive systems to give patients more relevant and comprehensive information from scanned medication guides. Similarly, it can provide preliminary insights to patients and even medical personnel on whether a drug from a different vendor is compatible with the patient's prescription medication. [ABSTRACT FROM AUTHOR]