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Maternal-to-Infant Transfer of Medications for Type 2 Diabetes Mellitus Via Breastmilk: A Systematic Review of Available Evidence and Clinical Guidelines.
No full textThis review evaluates the available pharmacokinetic data on the plasma-to-breastmilk transfer of first- and second-line T2DM drugs against available clinical guideline recommendations. A list of drug therapies for treating T2DM was generated from national and international clinical guidelines. A systematic search of research articles reporting human plasma and breastmilk drug concentrations was conducted in Scopus, PubMed, Google Scholar, and LactMed® in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies evaluating breastmilk drug transfer in T2DM, with fully accessible abstract and main text reported in English, were included. Study quality was evaluated using the ClinPK checklist. Authors evaluated clinical guideline recommendations on the use of T2DM drugs in lactation and the basis upon which such recommendations were made. Only 5 out of 20 drugs (metformin, glyburide, glipizide, tolbutamide, and semaglutide) have clinical data on plasma-to-breastmilk transfer. Metformin and tolbutamide were detectable in maternal plasma and breastmilk. Half (51.7%) of guideline recommendations provide explicit guidance. Only 4.4% of recommendations were based on clinical evidence. Over half (57.8%) of recommendations were accessible online, and most guideline recommendations (78%) were against the use of antiglycemic agents while breastfeeding. The scarce clinical evidence to guide T2DM drug therapy during breastfeeding available has several design and methodological limitations. Published recommendations remain largely inconsistent, thus perpetuating uncertainty in the use of T2DM drug therapies in lactation. Addressing knowledge gaps is critical in developing clinical consensus to optimize T2DM drug therapy among breastfeeding mothers
An Efficient and Automated Smart Healthcare System Using Genetic Algorithm and Two-Level Filtering Scheme
No full textThis paper proposes an efficient and automated smart healthcare communication framework that integrates a two-level filtering scheme with a multi-objective Genetic Algorithm (GA) to enhance the reliability, timeliness, and energy efficiency of Internet of Medical Things (IoMT) systems. In the first stage, physiological signals collected from heterogeneous sensors (e.g., blood pressure, glucose level, ECG, patient movement, and ambient temperature) were pre-processed using an adaptive least-mean-square (LMS) filter to suppress noise and motion artifacts, thereby improving signal quality prior to analysis. In the second stage, a GA-based optimization engine selects optimal routing paths and transmission parameters by jointly considering end-to-end delay, Signal-to-Noise Ratio (SNR), energy consumption, and packet loss ratio (PLR). The two-level filtering strategy, i.e., LMS, ensures that only denoised and high-priority records are forwarded for more processing, enabling timely delivery for supporting the downstream clinical network by optimizing the communication. The proposed mechanism is evaluated via extensive simulations involving 30–100 devices and multiple generations and is benchmarked against two existing smart healthcare schemes. The results demonstrate that the integrated GA and filtering approach significantly reduces end-to-end delay by 10%, as well as communication latency and energy consumption, while improving the packet delivery ratio by approximately 15%, as well as throughput, SNR, and overall Quality of Service (QoS) by up to 98%. These findings indicate that the proposed framework provides a scalable and intelligent communication backbone for early disease detection, continuous monitoring, and timely intervention in smart healthcare environments.</jats:p
Novel biosensor documents toxin-producing taxa ( <i>Gambierdiscus</i> and <i>Ostreopsis)</i> along the Iberian coastline
No full textIncreases in Harmful Algal Blooms (HABs) of toxic microalgae represent a growing concern worldwide. Poleward spread of HAB distribution is linked to climate change. Molecular tools permit more rapid and accurate responses, which complement traditional tools, for HAB species identification. Our electrochemical detection method, with a single unlabelled capture probe, represents a vast improvement over earlier methods using a sandwich hybridization method with two probes in that it is 10 times more sensitive. We analysed samples taken twice weekly in July 2022, from two locations in the northwestern Iberian Peninsula within the INTECMAR monitoring system in Galicia (Spain), and single samples from IPMA monitoring points in Porto and Aveiro (Portugal). Gambierdiscus spp. earlier reported offshore, were documented molecularly in coastal waters for the first time. Ostreopsis spp. earlier detected with microscopical and molecular methods, was also documented molecularly. This genus displayed an apparent range expansion in the southwestern Portuguese coasts, and along the northern (Bay of Biscay) and Mediterranean coasts of Spain. To increase species detection levels, 10 L samples were filtered, which is likely the reason why we found molecular signals where none of these cells were detected in the 50 mL settled volumes taken by the monitoring agencies and IEO. Improved calibration curves may revise lower inferred cell numbers because signals were normalized against a no DNA control, which was often high. The present study provides new information on emergent toxin-producing taxa of interest for regional monitoring programmes and their potential expansion in the area
Avelumab in combination with axitinib for advanced renal cell carcinoma [ID1547]: A Single Technology Appraisal
Get PDFIn situ ATR-SEIRAS investigations on the effects of Li+ and dissolved O2 on electrochemical interfacial reorganisation in an ionic liquid
Get PDFInterfacial reorganisation at a gold electrode within an ionic liquid (1-methyl-1-propylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide, ([Pyrr13][TFSI])) electrolyte was investigated via in situ electrochemical attenuated total reflection surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS). The in...</jats:p
Ribosome heterogeneity and specialization in musculoskeletal physiology and pathology
Get PDFMusculoskeletal (MSK) tissues are highly dynamic systems that rely on tightly regulated protein synthesis to maintain homeostasis and structural integrity, adapt to physiological stimuli, and respond to injury. The deregulation of protein synthesis is implicated in a wide range of MSK pathologies. At the core of protein synthesis are ribosomes, complex molecular nanomachines that translate mRNAs and generate proteins. Once considered uniform entities passively exerting their function, ribosomes are now recognized to be heterogeneous in their composition and capable of specialized functions. These emerging concepts of ribosome heterogeneity and specialization are increasingly recognized as key regulators of physiological and pathological cellular processes across fields. Although the MSK field has yet to fully embrace and integrate ribosome-centered research, accumulating evidence suggests that ribosome heterogeneity and specialization might have profound implications for MSK (patho)biology. In this review, we summarize the emerging data across MSK tissues (bone, skeletal muscle, articular cartilage, tendons, and ligaments), highlighting the roles of ribosomes in supporting development, maintaining homeostasis, and facilitating cellular and tissue functions and adaptations, but also driving pathological changes and disease progression. Furthermore, we also outline recent key technological and methodological advances that are critical for uncovering the full scope, significance, and dynamic regulation of ribosome heterogeneity and specialization in MSK (patho)biology. As the field moves forward, ribosome-centered research holds great promise in revealing new mechanisms underlying MSK biology and identifying novel therapeutic targets
Leptotrombidium imphalum Chiggers as Vector for Scrub Typhus in Human Settlements, India, 2022–2023
Get PDFScrub typhus is a common bacterial infection in many parts of Asia. The causative agent, Orientia tsutsugamushi, is transmitted by trombiculid mite (chigger) larvae that require small mammals as maintaining hosts. We studied the prevalence of O. tsutsugamushi infection in mites and small mammals in villages and land surrounding them in South India to determine high-risk settings. We identified 12,431 mite larvae on 883 small mammals, 32% of which were bandicoot rats, 31% black rats, and 31% Asian house shrews. Leptotrombidium imphalum was the most common mite species and the only species associated with O. tsutsugamushi infection (prevalence 3.6%). Orien tia infection increased with mite population size on a host. Host numbers, the L. imphalum index, and the prevalence of Orientia infection in chiggers were considerably higher within human settlements than in surrounding fields, suggesting that most human scrub typhus infection occurs inside villages rather than during agricultural work
Concepts of Suffering at the End of Life Amongst Emergency, Palliative Care and Geriatric Medicine Physicians in Malaysia
No full textBackground: Palliative Care, Geriatrics and Emergency physicians are exposed to death, terminally ill patients and distress of patients and their families. As physicians bear witness to patients’ suffering, they are vulnerable to the costs of caring—the emotional distress associated with providing compassionate and empathetic care to patients. If left unattended, this may culminate in burnout and compromise professional identity. This study aims to provide a better understanding of suffering across various practice settings and specialties to guide the design of support frameworks for physicians and their patients. Methods: From August 2023 to September 2024, semi-structured interviews were conducted with sixteen Palliative Care, 12 Geriatrics and 13 Emergency physicians from various hospitals in Malaysia. Interview transcripts were analyzed using both inductive and deductive qualitative analyses. Results: Data analysis revealed three key domains: (1) living and dying well, (2) definition of suffering, and (3) impact of patient suffering on physicians. Conclusion: Physicians’ concepts of a good life and death frame their notions of suffering beyond the antithesis of a good life. Suffering is found to be distress at a loss of control, independence and dignity, alongside the presence of physical, emotional and existential distress. Witnessing patient suffering predisposes to physician suffering as they question their goals and roles in patient care. Our findings underscore the need for host organizations, hospitals and clinical departments to invest more in the care of their physicians. We believe these findings ought to be applicable to many resource-limited nations and other health care professionals beyond Malaysian shores
OveRcoming Adverse ChiLdhood Experiences (ORACLE): A Mixed Methods Intervention Co-design Study to Improve Outcomes for Children and Young People Experiencing or at Risk of Adversity
No full textChildhood exposures to adversity are common and increase risk for negative health and social outcomes throughout the life course. There is limited evidence regarding interventions to prevent or reduce the impact of adverse childhood experiences (ACEs), particularly for families with multiple adversities. Here we present the findings of mixed methods research to co-design a complex intervention to prevent adverse childhood experiences, and their impacts. Using established research methods, and the framework of the Medical Research Council (MRC) complex interventions development guidance, the work was conducted in four stages, shaped by stakeholder engagement and input at every stage. The first stage, Discover, was exploratory and employed evidence synthesis and quantitative (n = 11,564) and qualitative (n = 31) research methods to understand needs, experiences, and evidence gaps. The Define stage developed three intervention principles and identified intervention options, through a series of six co-design workshops with 41 participants and an academic research team workshop. The Develop and Deliver stages were undertaken through a Policy Lab (22 participants), and developed options for intervention design, before converging on a defined intervention that could be delivered and tested. Through this process, we developed a ‘village-style’ intervention, which functions at three levels: individual service users, operational, and system/strategy. Central to this are link or community health workers who would build relationships with family members, and act as a single point of contact. They should develop an understanding of family needs and the interaction of multiple complex adversities, and advocate for families, facilitating access to services. Crucially, they should use this understanding to work at and feed into operational and strategic levels to reshape services and enhance access for all families at risk of or experiencing adversity. Entry into the intervention through assessments at existing universal touch points, for example at routine perinatal or newborn appointments, should provide a prevention focus and follow the principles of proportionate universalism. Sensitive enquiry regarding financial stress may be a component of the assessment, in response to the findings of this work regarding the contexts created through the interaction of poverty and other adversities. The proposed intervention is designed to improve individual and family outcomes, and generate positive system-level changes. A feasibility study and evaluation will be required in future work, to assess the effects, costs and benefits. The processes and frameworks we developed and used may provide an adaptable template for future intervention co-design work
Optimizing delivery systems within the e-retail context: a weighted self-organizing map for delivery region partitioning
Get PDFToday, e-tailing operations are well-established. However, managing dispersed same-day, next-day, or immediate deliveries remains a significant challenge. This necessitates refined vehicle routing and scheduling, which depends on efficient partitioning of the delivery regions. To tackle this, this paper develops a novel Weighted Self-Organizing Map Delivery Region Partitioning (WSOM-DRP) model that jointly generates delivery clusters and suggests optimal collection points for e-orders within each cluster. Using real data from a third-party logistics provider, our model is evaluated against alternative clustering methods (k-means, Ward hierarchical clustering, fuzzy c-means) using common clustering performance measures, travel distance and computation time. A comprehensive sensitivity analysis across varying cluster numbers confirms the model's robustness, showing travel distance reduction of up to 36 % compared to the second-best method, particularly in high-density and high-traffic scenarios. Additionally, it yields significant improvements in clustering quality (e.g., a minimum of 15 % improvement in the silhouette index across scenarios) and an 18 % reduction in computation time compared to the next fastest benchmark. These findings highlight the practical value and adaptability of WSOM-DRP for optimizing delivery operations under diverse operational conditions and across different cluster granularities. The model also offers guidance on how to balance efficiency gains with operational complexity when selecting the number of clusters. By generating efficient delivery partitions and recommending optimal e-order collection locations during online checkout, our proposed WSOM-DRP model offers an e-commerce solution which is delivery efficient and cost-effective
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