Hasil untuk "Other systems of medicine"

Mayuranath SureshKumar, Hanumanthrao Kannan

Classic problem-space theory models problem solving as a navigation through a structured space of states, operators, goals, and constraints. Systems Engineering (SE) employs analogous constructs (functional analysis, operational analysis, scenarios, trade studies), yet still lacks a rigorous systems-theoretic representation of the problem space itself. In current practice, reasoning often proceeds directly from stakeholder goals to prescriptive artifacts. This makes foundational assumptions about the operational environment, admissible interactions, and contextual conditions implicit or prematurely embedded in architectures or requirements. This paper addresses that gap by formalizing the problem space as an explicit semantic world model containing theoretical constructs that are defined prior to requirements and solution commitments. These constructs along with the developed axioms, theorems and corollary establish a rigorous criterion for unambiguous boundary semantics, context-dependent interaction traceability to successful stakeholder goal satisfaction, and sufficiency of problem-space specification over which disciplined reasoning can occur independent of solution design. It offers a clear distinction between what is true of the problem domain and what is chosen as a solution. The paper concludes by discussing the significance of the theory on practitioners and provides a dialogue-based hypothetical case study between a stakeholder and an engineer, demonstrating how the theory guides problem framing before designing any prescriptive artifacts.

Marios Impraimakis, Andrew W. Smyth

The input-parameter-state estimation capabilities of a novel unscented Kalman filter is examined herein on both linear and nonlinear systems. The unknown input is estimated in two stages within each time step. Firstly, the predicted dynamic states and the system parameters provide an estimation of the input. Secondly, the corrected with measurements states and parameters provide a final estimation. Importantly, it is demonstrated using the perturbation analysis that, a system with at least a zero or a non-zero known input can potentially be uniquely identified. This output-only methodology allows for a better understanding of the system compared to classical output-only parameter identification strategies, given that all the dynamic states, the parameters, and the input are estimated jointly and in real-time.

Thomas I. Strasser, Filip Pröstl Andrén

A driving force for the realization of a sustainable energy supply is the integration of renewable energy resources. Due to their stochastic generation behaviour, energy utilities are confronted with a more complex operation of the underlying power grids. Additionally, due to technology developments, controllable loads, integration with other energy sources, changing regulatory rules, and the market liberalization, the systems operation needs adaptation. Proper operational concepts and intelligent automation provide the basis to turn the existing power system into an intelligent entity, a cyber-physical energy system. The electric energy system is therefore moving from a single system to a system of systems. While reaping the benefits with new intelligent behaviors, it is expected that system-level developments, architectural concepts, advanced automation and control as well as the validation and testing will play a significantly larger role in realizing future solutions and technologies. The implementation and deployment of these complex systems of systems are associated with increasing engineering complexity resulting also in increased engineering costs. Proper engineering and validation approaches, concepts, and tools are partly missing until now. Therefore, this paper discusses and summarizes the main needs and requirements as well as the status quo in research and development related to the engineering and validation of cyber-physical energy systems. Also research trends and necessary future activities are outlined.

Pedram Fard, Alaleh Azhir, Neguine Rezaii et al.

Artificial intelligence in medicine is built to serve the average patient. By minimizing error across large datasets, most systems deliver strong aggregate accuracy yet falter at the margins: patients with rare variants, multimorbidity, or underrepresented demographics. This average patient fallacy erodes both equity and trust. We propose a different design: a multi-agent ecosystem for N-of-1 decision support. In this environment, agents clustered by organ systems, patient populations, and analytic modalities draw on a shared library of models and evidence synthesis tools. Their results converge in a coordination layer that weighs reliability, uncertainty, and data density before presenting the clinician with a decision-support packet: risk estimates bounded by confidence ranges, outlier flags, and linked evidence. Validation shifts from population averages to individual reliability, measured by error in low-density regions, calibration in the small, and risk--coverage trade-offs. Anticipated challenges include computational demands, automation bias, and regulatory fit, addressed through caching strategies, consensus checks, and adaptive trial frameworks. By moving from monolithic models to orchestrated intelligence, this approach seeks to align medical AI with the first principle of medicine: care that is transparent, equitable, and centered on the individual.

Vundrala Sumedha Reddy, S. Shiva, Srinidhi Manikantan et al.

Caffeine is the world's most popular stimulant and psychoactive substance. Given the ubiquitous use of caffeine, it is crucial for us to comprehend how our body interacts with caffeine. The pharmacokinetics of caffeine and its action mechanisms have been reviewed in this paper. The safety and recommended dosage of caffeine in healthy adults and vulnerable populations like children and pregnant women are also discussed in this paper. While caffeine consumption is generally safe, this review paper also examines the potential effects that caffeine could have on human health and development. Studies indicated that caffeine exhibits neuroprotective properties, potentially serving as a preventive measure against the onset of neurodegenerative conditions such as Alzheimer's and Parkinson's disease. The article also explores various physiological effects of caffeine on the body, in addition to investigating novel drug delivery techniques, particularly nano-delivery systems designed to efficiently administer caffeine.

MHD Anas Alsakkal, Jayawan Wijekoon

This paper presents a novel FPGA-based neuromorphic cochlea, leveraging the general-purpose spike-coding algorithm, Spiketrum. The focus of this study is on the development and characterization of this cochlea model, which excels in transforming audio vibrations into biologically realistic auditory spike trains. These spike trains are designed to withstand neural fluctuations and spike losses while accurately encapsulating the spatial and precise temporal characteristics of audio, along with the intensity of incoming vibrations. Noteworthy features include the ability to generate real-time spike trains with minimal information loss and the capacity to reconstruct original signals. This fine-tuning capability allows users to optimize spike rates, achieving an optimal balance between output quality and power consumption. Furthermore, the integration of a feedback system into Spiketrum enables selective amplification of specific features while attenuating others, facilitating adaptive power consumption based on application requirements. The hardware implementation supports both spike-based and non-spike-based processors, making it versatile for various computing systems. The cochlea's ability to encode diverse sensory information, extending beyond sound waveforms, positions it as a promising sensory input for current and future spike-based intelligent computing systems, offering compact and real-time spike train generation.

Verônica Ebrahim Queiroga, Isli Maria Oliveira Martins, Ailma de Souza Barbosa et al.

Este estudo teve o objetivo de avaliar o efeito de uma intervenção educativa no conhecimento de enfermeiros sobre saúde sexual e reprodutiva, com enfoque no Dispositivo Intrauterino (DIU). Utilizou o delineamento de estudo quase experimental, do tipo grupo único, antes e depois, desenvolvido em um município da região Nordeste do Brasil. A intervenção educativa foi um curso de capacitação, teórico-prático, na modalidade remota, com carga horária de 30 horas, para enfermeiros em consulta ginecológica com enfoque no DIU. Utilizou-se um instrumento, avaliado por especialistas na área da saúde da mulher. Os dados foram coletados entre outubro de 2021 e janeiro de 2022. Foram seguidas as recomendações éticas para pesquisas com seres humanos. Participaram do estudo 31 enfermeiros da Atenção Primária à Saúde. O nível de conhecimento dos enfermeiros no pré-teste foi classificado como “satisfatório” (n=21; 67,7%) e no pós-teste como “muito satisfatório” (n=16; 51,6%). Houve diferença estatística significativa entre o número de acertos no pré e pós testes dos participantes, com aumento de acertos no pós-teste. A intervenção educativa mostrou-se efetiva para promover mudanças no conhecimento de enfermeiros sobre saúde sexual e reprodutiva com enfoque no DIU.

Camille C. Cioffi, Patrick F. Hibbard, Angela Hagaman et al.

Background The field of implementation science acknowledges the importance of diversity within research teams including members from diverse disciplines and with lived expertise in practical implementation (e.g., administrators, front-line workers, patients/clients). Gaps remain in the successful implementation of proven substance use treatment interventions. Methods This paper will outline the rationale for the purposeful inclusion of researchers with lived experience (RLE) related to substance use disorder (SUD) within implementation science research studies focused on improving SUD services. Results We posit that researchers with such experience can help address research-to-practice gaps by (1) building strong community partnerships, (2) engaging in conversations around effective interventions through knowledge translation, (3) providing community-congruent approaches to evaluation, and (4) aiding in dissemination and sustainability efforts. Conclusions We end by offering recommendations for researchers without lived experience as they intentionally collaborate with RLE.

Jaykrishan Prasad, Anureet K. Shah, Naranjan S. Dhalla

Protein kinases, a family of enzymes responsible for regulating various cellular processes, have been implicated in the development and progression of various heart diseases, making them attractive therapeutic targets. This review focuses on the role of protein kinases induced phosphorylation and protein phosphatase-induced dephosphorylation in cardiovascular disorders, including heart failure, ischemic heart disease, arrhythmias, hypertension, and diabetic cardiomyopathy. This paper explores the potential of novel kinase-targeted therapies and emerging technologies for the prevention and treatment of these conditions. It also discusses the involvement of protein kinase A (PKA), protein kinase C (PKC), phosphoinositide 3-kinases (PI3Ks), mitogen-activated protein kinases (MAPKs), and Ca2+/calmodulin-dependent protein kinase II (CaMKII) in heart dysfunction and alterations in their function that contribute to their respective cardiac disorders. Furthermore, this article presents a comprehensive overview of protein kinases in cardiac disorders and the potential of innovative kinase-targeted therapies, advanced technologies, and multidisciplinary approaches for the effective prevention and treatment of cardiovascular diseases, ultimately aiming to improve patient outcomes and quality of life.

Yoon-Jae Won, Sun-Woo Kang, Myeong-Yeol Yang et al.

The discoid meniscus is an innate modified form of the meniscus, characterized by middle hypertrophy and a larger than the regular diameter, leading to an absence of the characteristic “C” arrangement. Previously, no study has reported the traditional Korean medicine treatment of knee pain mainly due to discoid meniscus. Here, we report two cases of a discoid meniscus of the knee as the cause of knee pain. Patients were diagnosed with magnetic resonance imaging for discoid meniscus and received traditional Korean medicine treatments, including pharmacopuncture, acupuncture, herbal medicine, and chuna. The pain was alleviated when assessed by patient-reported pain scale scores, and the general knee condition was improved. Thus, traditional Korean medicine treatments could be effective for patients who had discoid meniscus of the knee joint in this case report.

Shan-bo Ma, Lun Liu, Xiang Li et al.

Abstract Background The dried bark of Ailanthus altissima (Mill.) Swingle is widely used in traditional Chinese medicine for the treatment of ulcerative colitis. The objective of this study was to explore the therapeutic basis of the dried bark of Ailanthus altissima (Mill.) Swingle for the treatment of ulcerative colitis based on Virtual Screening–Molecular Docking–Activity Evaluation technology. Methods By searching the Traditional Chinese Medicine Systems Pharmacology TCMSP Database and Analysis Platform, 89 compounds were obtained from the chemical components of the dried bark of Ailanthus altissima (Mill.) Swingle. Then, after preliminarily screening the compounds based on Lipinski’s rule of five and other relevant conditions, the AutoDock Vina molecular docking software was used to evaluate the affinity of the compounds to ulcerative colitis-related target proteins and their binding modes through use of the scoring function to identify the best candidate compounds. Further verification of the compound’s properties was achieved through in vitro experiments. Results Twenty-two compounds obtained from the secondary screening were molecularly docked with ulcerative colitis-related target proteins (IL-1R, TLR, EGFR, TGFR, and Wnt) using AutoDock Vina. The free energies of the highest scoring compounds binding to the active cavity of human IL-1R, TLR, EGFR, TGFR, and Wnt proteins were − 8.7, − 8.0, − 9.2, − 7.7, and − 8.5 kcal/mol, respectively. The potential compounds, dehydrocrebanine, ailanthone, and kaempferol, were obtained through scoring function and docking mode analysis. Furthermore, the potential compound ailanthone (1, 3, and 10 µM) was found to have no significant effect on cell proliferation, though at 10 µM it reduced the level of pro-inflammatory factors caused by lipopolysaccharide. Conclusion Among the active components of the dried bark of Ailanthus altissima (Mill.) Swingle, ailanthone plays a major role in its anti-inflammatory properties. The present study shows that ailanthone has advantages in cell proliferation and in inhibiting of inflammation, but further animal research is needed to confirm its pharmaceutical potential.

Bingfeng Luo, Walid Theib Mohammad, Abduladheem Turki Jalil et al.

Background and aims: Several randomized controlled trials (RCTs) have shown that almonds can improve oxidative stress indices, but the results are controversial. Therefore, the goal of this research was to carry out a systematic review and meta-analysis of all RCTs that evaluated the effect of almonds on selected oxidative stress indices. Methods: A systematic search was conducted up to April 2022 on PubMed, Scopus, Web of Science, and Google Scholar. We have selected the studies that investigated the effects of almonds on malondialdehyde (MDA), and oxidized low-density lipoprotein (Ox-LDL) levels in adults. Data were pooled by using the random-effects model. The risk of bias in individual studies was assessed using the Cochrane Collaboration risk of bias tool. Results: Seven RCTs involving 424 participants were analyzed. The results indicated that almond intake led to a significant decrease in MDA levels (WMD: − 6.63 nmol/ml; 95 % CI: − 8.72 to − 4.54; P < 0.001). However, no significant effect was observed on Ox-LDL (Hedges’ g: − 0.12; 95 % CI: − 0.34 to 0.10; P = 0.28). Sensitivity analysis showed that overall estimates were not affected by the elimination of any study. We did not observe any evidence regarding publication bias. Conclusion: The present meta-analysis suggests that almond intake can improve MDA levels and might play a beneficial role in the reinforcement of the antioxidant defense system and amelioration of oxidative stress in adults. There is a need for more studies with larger groups to better estimate this effect.

Yujie Wang, Xiangru Xu

This paper presents a novel approach for the safe control design of systems with parametric uncertainties in both drift terms and control-input matrices. The method combines control barrier functions and adaptive laws to generate a safe controller through a nonlinear program with an explicitly given closed-form solution. The proposed approach verifies the non-emptiness of the admissible control set independently of online parameter estimations, which can ensure the safe controller is singularity-free. A data-driven algorithm is also developed to improve the performance of the proposed controller by tightening the bounds of the unknown parameters. The effectiveness of the control scheme is demonstrated through numerical simulations.

Mercedes Castejón-Castejón, M.A. Murcia-González, J. Todri et al.

Ying-Yong Zhao

Chronic kidney disease (CKD) is a worldwide public health issue and has ultimately progressed to an end-stage renal disease that requires life-long dialysis or renal transplantation. However, the underlying molecular mechanism of these pathological development and progression remains to be fully understood. The human gut microbiota is made up of approximately 100 trillion microbial cells including anaerobic and aerobic species. In recent years, more and more evidence has indicated a clear association between dysbiosis of gut microbiota and CKD including immunoglobulin A (IgA) nephropathy, diabetic kidney disease, membranous nephropathy, chronic renal failure and end-stage renal disease. The current review describes gut microbial dysbiosis and metabolites in patients with CKD thus helping to understand human disease. Treatment with prebiotics, probiotics and natural products can attenuate CKD through improving dysbiosis of gut microbiota, indicating a novel intervention strategy in patients with CKD. This review also discusses therapeutic options, such as prebiotics, probiotics and natural products, for targeting dysbiosis of gut microbiota in patients to provide more specific concept-driven therapy strategy for CKD treatment.

Kashif Haider, Mohd Shafeeque, Shaikh Yahya et al.

Cancer is one of the leading causes of death globally, around 10 million deaths are reported every year due to cancer. Some clinically approved anticancer drugs play a riveting role in its treatment. Still, due to the severe emergence of drug resistance, side effects, and multidrug-resistant cancers due to mutations, it creates a significant demand for novel, potent, and safe candidates as an anticancer agent with diverse mechanisms of action. In medicinal chemistry, several heterocyclic derivatives and hybrids are studied and reported as potent anticancer agents; Pyrazoline is one of the versatile and ubiquitous scaffolds for developing novel anticancer agents. Many pyrazoline scaffolds bearing drugs are used clinically for the treatment of cancer. Few are in the late phase of the clinical trial for treating various cancers, for example, Indibulin, a novel microtubule inhibitor and AT9283. The hybridization strategy of a pyrazoline scaffold with various heterocyclic rings is very promising to minimize the side effects and drug resistance. In light of this pyrazoline containing hybrids monopolize an important place in developing potent, safe and novel anticancer agents. The presented review outlined recent advances studied and reported towards developing pyrazoline-containing hybrids as potent anticancer agents. The review covers synthetic strategy, structure-activity relationship and anticancer activities of pyrazoline hybrid derivatives. The sole purpose is to shed light on the design and development of pyrazoline hybrids compounds with high efficacy and reduced toxicity.

Lianghao Xia, Chao Huang, Yong Xu et al.

As the deep learning techniques have expanded to real-world recommendation tasks, many deep neural network based Collaborative Filtering (CF) models have been developed to project user-item interactions into latent feature space, based on various neural architectures, such as multi-layer perceptron, auto-encoder and graph neural networks. However, the majority of existing collaborative filtering systems are not well designed to handle missing data. Particularly, in order to inject the negative signals in the training phase, these solutions largely rely on negative sampling from unobserved user-item interactions and simply treating them as negative instances, which brings the recommendation performance degradation. To address the issues, we develop a Collaborative Reflection-Augmented Autoencoder Network (CRANet), that is capable of exploring transferable knowledge from observed and unobserved user-item interactions. The network architecture of CRANet is formed of an integrative structure with a reflective receptor network and an information fusion autoencoder module, which endows our recommendation framework with the ability of encoding implicit user's pairwise preference on both interacted and non-interacted items. Additionally, a parametric regularization-based tied-weight scheme is designed to perform robust joint training of the two-stage CRANet model. We finally experimentally validate CRANet on four diverse benchmark datasets corresponding to two recommendation tasks, to show that debiasing the negative signals of user-item interactions improves the performance as compared to various state-of-the-art recommendation techniques. Our source code is available at https://github.com/akaxlh/CRANet.

Maryam Sajde, Hamed Malek, Mehran Mohsenzadeh

Background and Objective High medicine diversity has always been a significant challenge for prescription, causing confusion or doubt in physicians' decision-making process. This paper aims to develop a medicine recommender system called RecoMed to aid the physician in the prescription process of hypertension by providing information about what medications have been prescribed by other doctors and figuring out what other medicines can be recommended in addition to the one in question. Methods There are two steps to the developed method: First, association rule mining algorithms are employed to find medicine association rules. The second step entails graph mining and clustering to present an enriched recommendation via ATC code, which itself comprises several steps. First, the initial graph is constructed from historical prescription data. Then, data pruning is performed in the second step, after which the medicines with a high repetition rate are removed at the discretion of a general medical practitioner. Next, the medicines are matched to a well-known medicine classification system called the ATC code to provide an enriched recommendation. And finally, the DBSCAN and Louvain algorithms cluster medicines in the final step. Results A list of recommended medicines is provided as the system's output, and physicians can choose one or more of the medicines based on the patient's clinical symptoms. Only the medicines of class 2, related to high blood pressure medications, are used to assess the system's performance. The results obtained from this system have been reviewed and confirmed by an expert in this field.

Ahmed Mahrous Elsayed, Elham Elsayed Salem, Sahar Mohamed Nour Eldin et al.

Abstract Background Adaptive seating is commonly used as an intervention method to enhance postural control. The aim of this study is to investigate the effect of using therapy ball as a seat alternative to using typical chair on grasping and visual motor integration in the children with hemiparetic cerebral palsy. For this aim, thirty children with hemiparetic cerebral palsy from both sexes were included in this study. The children ages ranged from 3 to 6 years old. The degree of spasticity was 1 to 1+ according to modified Ashworth scale. The children were able to sit independently and follow instructions. Children were randomly assigned into two groups (experimental group and control group). Each child was evaluated before and after 3 successive months of selected occupational therapy exercises program. All the children of both groups received the same selected occupational therapy exercises program, but the children in the experimental group performed the exercises while sitting on therapy ball, and the children in the control group performed the exercises while sitting on typical chair. Results There was a significant improvement in the measured variables for both groups after treatment. The post-treatment results of the two groups of grasping and visual motor integration for age equivalent scores revealed significant difference (p=0.008 and p=0.011 respectively) in favor of the experimental group. Conclusions Therapy ball could be used as a seat alternative to using typical chair to facilitate visual motor integration and grasping in the children with hemiparetic cerebral palsy.