A cross-sectional study to assess medication safety,knowledge,attitude,and practices regarding nutrition and medication among pregnant women

Objective:To assess pregnant women's knowledge,attitude,and practice regarding nutrition and medication usage,analyse the prescribing pattern,and categorize them based on the Food and Drug Administration(FDA)guidelines.Methods:A cross-sectional study was conducted with 264 pregnant women in the obstetrics and gynaecology department of a tertiary care hospital from October 2022 to August 2023.A knowledge,attitude,and practice(KAP)questionnaire was prepared in English language by the researchers and validated by an expert panel consisting of 12 members.The validated questionnaire was then translated into regional languages,Kannada and Malayalam.The reliability of the questionnaire was assessed with test-retest method with a representative sample population of 30 subjects(10 subjects for each language).The subjects'knowledge,attitude,and practice were evaluated using the validated KAP questionnaire.The safety of the medication was assessed using the FDA drug safety classification for pregnancy.Results:The mean scores for nutritional and medication usage knowledge,attitude,and practice were 4.14±1.15,4.50±1.09,and 3.00±1.47,respectively.Among 30 prescribed medications,3 belong to category A(no risk in human studies),8 belong to category B(no risk in animal studies),18 belong to category C(risk cannot be ruled out)and 1 drug is not classified.A significant association was observed between medication knowledge and practice(r=0.159,P=0.010).Conclusions:Most of the study population knows the need to maintain good dietary and medication practices during pregnancy.Counselling pregnant women regarding diet and medication usage is crucial in maternal care.

Medical management of urolithiasis: Great efforts and limited progress

Objective:To provide a comprehensive review on the existing literature on medical management of urolithiasis.Methods:A thorough literature review was performed using Medline,PubMed/PMC,Embase,and the Cochrane Database of Systematic Reviews up to December 2022 to identify publications on the medical management of urolithiasis.Studies that assessed dietary and pharmacologic management of urolithiasis were reviewed;studies on medical expulsive therapy were not included in this review.Results:Medical management of urolithiasis ranges from the prophylactic management of kidney stone disease to dissolution therapies.While most treatment concepts have been long established,large randomized controlled trials are scarce.Dietary modification and increased fluid intake remain cornerstones in the conservative management of urolithiasis.A major limitation for medical management of urolithiasis is poor patient compliance.Conclusion:Medical management of urolithiasis is more important in patients with recurrent urolithiasis and patients with metabolic abnormalities putting them at higher risk of developing stones.Although medical management can be effective in limiting stone recurrence,medical interventions often fail due to poor compliance.

Mindfulness training in medical education as a means to improve resilience,empathy,and mental health in the medical profession

The high rates of depression,burnout,and increased risk of suicide among medical students,residents,and physicians in comparison with other careers signal a mental health crisis within our profession.We contend that this crisis coupled with the inadequate acquisition of interpersonal skills during medical education results from the interaction between a challenging environment and the mental capital of individuals.Additionally,we posit that mindfulness-based practices are instrumental for the development of major components of mental capital,such as resilience,flexibility of mind,and learning skills,while also serving as a pathway to enhance empathy,compassion,self-awareness,conflict resolution,and relational abilities.Importantly,the evidence base supporting the effectiveness of mindfulness-based interventions has been increasing over the years,and a growing number of medical schools have already integrated mindfulness into their curricula.While we acknowledge that mindfulness is not a panacea for all educational and mental health problems in this field,we argue that there is currently an unprecedented opportunity to gather momentum,spread and study mindfulness-based programs in medical schools around the world as a way to address some longstanding shortcomings of the medical profession and the health and educational systems upon which it is rooted.

Importance-aware 3D volume visualization for medical content-based image retrieval-a preliminary study

Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.

Special Issue: The Global Cross-cultural Integration of TCM in the Mainstream Healthcare, Medical Education and the Practice of Medicine

Ioannis Solos Ph.D.,M.D.(China),L.Ac.currently serves as President and CEO at the Saint George Clinic and Research Institute,Scottsdale,AZ.,and Associate Editor for Chinese Medicine and Culture.Professor Solos has earned his Master of Medicine in Traditional Diagnosis at the Beijing University of Chinese Medicine,and his Medical Ph.D.in Chinese and Western Integrative Medicine at the Jinan University in Guangzhou.He practices and teaches integrative clinical medicine,Jing Fang(经方TCM formulas),martial lineage acupuncture,and his personalized style of“tendon and fascia reconditioning manipulations for bone and joint disease”.

Designing a medical ethics curriculum in ophthalmology

Ethical principles form a bedrock to medical practice in any specialty,guiding physicians to appropriate attitudes and behaviors.A formal ethics curriculum can be difficult to generate de novo in an ophthalmology training program.A number of barriers exist in most ophthalmology departments:trainees may think ethics is of secondary importance compared to core basic and clinical science topics;most ophthalmology faculty have no formal degree in medical ethics;there is limited didactic time with competing academic,clinical,and surgical priorities;work-hours regulations may limit the time available to deliver“para-professional”lectures;and there is a belief that the medical ethics lectures during medical school is a sufficient amount of coursework to last through a physician’s career with no need for continuing professional development.The four pillars of medical ethics are beneficence,non-maleficence,autonomy,and justice.In addition,morals,ethics,and professionalism are important aspects of sound medical practice.A curriculum specific to medical ethics in ophthalmology can be developed in any of our sub-specialties and include lectures,curated readings,case rounds,and clinic wrap-up sessions.Ethical considerations are part of everyday clinical practice,and a structured ethics curriculum can be incorporated into ophthalmology training programs.The concept of backward design can be used to structure the curriculum,starting with the expected outcome,then designing authentic assessments,and finally putting together a learning plan that has students actively involved in ethical discussions.This paper will provide a guide to developing an ethics curriculum for an ophthalmology training program utilizing the concept of backwards design and guide the reader through the process of developing expected learning outcomes,authentic assessments,and a unified learning plan.

Knowledge towards Physical Medicine and Rehabilitation among Training Doctors and Medical Students at the Mohammed VI University Hospital of Marrakech

The aim of our study is to evaluate the knowledge regarding physical medicine and rehabilitation among physicians in training and medical students at the Mohammed VI University Hospital in Marrakech, to approach the knowledge, attitudes, and practices of doctors regarding physical medicine and rehabilitation and evaluate the knowledge in theoretical training related to PRM among the students. We conducted a monocentric cross-sectional analytical study, using a web-based anonymous survey, carried out among 558 undergraduate student and training doctors, randomly selected in the form of a survey on the knowledge towards Physical Medicine and rehabilitation. We received 558 survey duly completed by students of the Faculty of Medicine and Pharmacy of Marrakech (62.4%) and training doctors (37.6%). The mean age of the participants was 24.53 ± 3.9 years, with extremes ranging from 17 to 39 years. 52.7% of the participants were from the former educational reform, The predominance of participation was remarkable among pediatricians 23%, The population who knew PRM was the majority (79.3%), 40.7% of the participants were unaware of the availability of a PRM department at Mohamed VI University Hospital, 0.5% of all training doctors and medical students questioned strongly agreed with the sufficiency of their training in disability management were belonging to the new reform, 84.1% of participants had never attended or referred a patient to the PRM department. 23.2% of training doctors affirmed the referral of patients to PRM for further management. Despite the essential role of PRM in the management of diseases, it remains little known by training doctors and medical students. This lack of knowledge of PRM reflects the lack of the undergraduate and postgraduate of the medical education in the field of rehabilitation.

Exploration of Curriculum Ideology and Politics Integrating Medical Humanities Cultivation Model to Enhance Medical Core Values

Purpose:To explore the application effect of the cultivation mode of Curriculum Ideology and Political Integration of Medical Humanities to enhance the core values of medicine in the clinical internship stage of medical students.Methods:Students in the clinical internship stage of the First Affiliated Hospital of Baotou Medical College were selected,and a total of 156 students in one random class in each grade were taken as the observation group and received the integration cultivation mode;148 students were taken as the control group and employed the traditional mode.The teaching effect of interns in the two groups was analyzed.Results:The teaching performance of students in both groups after clinical internship teaching was improved compared with that before admission;the teaching performance,teaching effect,teaching evaluation,and teaching satisfaction of the observation group were higher than that of the control group.Conclusion:The integration of the medical humanities training model with curriculum ideology and politics in the clinical internship of medical students is conducive to the improvement of teaching performance,teaching evaluation,teaching satisfaction of teachers and students,and the development and improvement of core values of medical students,which is of good value for teaching application.

The Practice and Exploration of Applying EBM to Bilingual Teaching of Medical Genetics at OSBCM

In the process of teaching medical genetics of undergraduate clinical medicine, the practice and exploration of applying EBM to the bilingual teaching of OSBCM medical genetics are carried out. Using CBL and PBL as the carrier can make up for the shortcomings of a single teaching mode, synthesize the advantages of multiple teaching modes. It starts from integrating the basic theoretical knowledge of medicine and clinical practice knowledge, improving students’ bilingual level of medical genetics, cultivating students’ literature retrieval ability, and promoting early clinical, multi-clinical and repeated clinical consciousness for medical students. Therefore, it is more conducive to cultivate students’ ability to learn independently, accurately analyze and solve problems, improve medical students’ clinical thinking ability and scientific research awareness, improve medical students’ ability of international communication, and lay a solid foundation for improving medical students’ future post competence, innovative spirit and lifelong learning ability.

Study on the Changes of Medical Income Structure in Governmentrun Hospitals of Traditional Chinese Medicine from 2012 to 2021

Objective To study the changing characteristics and trend of medical income structure in the government-run hospitals of traditional Chinese medicine(TCM),evaluate the effects of relevant reform measures,and to put forward corresponding suggestions for further optimizing their income structure.Methods The data related to the average medical income of government-run hospitals of TCM from 2012 to 2021 were sorted out.Then,descriptive analysis method was used to analyze the changes of related indicators.Besides,structural change method was applied to investigate the changes of outpatient income and inpatient income.Results and Conclusion From 2012 to 2021,the growth of medical income in government-run hospitals of TCM tended to be stable,and the proportion of medical service income increased from 22.62%(2012)to 29.38%(2021),but the average annual growth rate was only 0.68%.The main items that caused the change of outpatient income structure were medicine revenue,laboratory tests,diagnosis and treatment,and the cumulative contribution rate was 89.15%.The main items that caused the change of inpatient income structure were medicine revenue,sanitary materials,and auxiliary examinations income,with a cumulative contribution rate of 80.04%.However,the contribution rate of registration,diagnosis,treatment,surgery and nursing income reflecting the value of medical personnel’s technical labor was relatively small.The medical income structure of government-run hospitals of TCM underwent great changes and gradually became reasonable,but the medical service income increased slowly,and not all indicators achieved the expectations.To promote the sustainable development of public hospitals of TCM and enable them to provide high-quality and efficient TCM medical and health services,it is necessary to further improve the relevant policy mechanism.

Pushing the frontiers of military medical excellence:updates,progress and future needs

Since its establishment in 2014,Military Medical Research has come a long way in becoming a premier journal for scientific articles from various different specialties,with a special emphasis on topics with military relevance.The field of military medicine may be obscure,and may not be readily encountered by the typical clinician on a day-today basis.This journal aims not only to pursue excellence in military research,but also to keep current with the latest advancements on general medical topics from each and every specialty.This editorial serves to recap and synthesize the existing progress,updates and future needs of military medical excellence,discussing foremostly the unique traits of literature published in this journal,and subsequently presenting the discourse regarding wartime and peacetime medicine,the role of the military in a public health emergency,as well as wound healing and organ regeneration.Special attention has been devoted to military topics to shed light on the effects of Chemical,Biological,Radiological and Explosive warfare,environmental medicine and military psychiatry,topics which rarely have a chance to be discussed elsewhere.The interconnectedness between military combat and soldier physical and mental well-being is intricate,and has been distorted by pandemics such as coronavirus disease 2019(COVID-19).This journal has come a long way since its first article was published,steadily contributing to the existing knowledge pool on general medical topics with a military slant.Only with continuous research and sharing,can we build upon the work of the scientific community,with hopes for the betterment of patient care.

Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

This article proposes a novel fractional heterogeneous neural network by coupling a Rulkov neuron with a Hopfield neural network(FRHNN),utilizing memristors for emulating neural synapses.The study firstly demonstrates the coexistence of multiple firing patterns through phase diagrams,Lyapunov exponents(LEs),and bifurcation diagrams.Secondly,the parameter related firing behaviors are described through two-parameter bifurcation diagrams.Subsequently,local attraction basins reveal multi-stability phenomena related to initial values.Moreover,the proposed model is implemented on a microcomputer-based ARM platform,and the experimental results correspond to the numerical simulations.Finally,the article explores the application of digital watermarking for medical images,illustrating its features of excellent imperceptibility,extensive key space,and robustness against attacks including noise and cropping.

Informing policy makers in developing countries:Practices and limitations of geriatric home medication review in Malaysia-A qualitative inquiry

Objective:To explore existing practices and challenges in the delivery of geriatric home medication review(HMR).The study was part of a larger study aimed to offer solution to expand the range of geriatric HMR.Methods:This study employed qualitative exploratory design through semi-structured individual in-depth interviews with the public pharmacists involved in the delivery of geriatric HMR at public hospitals.The purpose of the interviews was to explore challenges faced by them in the delivery of geriatric HMR.Results:Based on the emerging themes from the qualitative data,the study reveals that geriatric HMR in Malaysia is integrated as part of multidisciplinary home care visits,encompassing a diverse patient population with various healthcare needs.However,it faces challenges such as the lack of outcome monitoring,formal training,and workforce constraints.Despite these hurdles,there is a pressing need for the expansion of this service to better serve the community,and collaboration with community pharmacists holds potential to broaden its scope.Ultimately,the findings suggest that pharmacist-led HMR is both warranted and feasible within the Malaysian healthcare context.In order to optimize medicine-use among older people living in the community,approaches for expanding geriatric HMR services in Malaysia must be developed.Conclusions:This study holds profound implications as it attempts to illuminate policy makers in developing countries,enabling them to formulate effective HMR plans.By considering the challenges highlighted within this research,policy makers can design a comprehensive HMR service that caters adeptly to the healthcare needs of the mass population.

Advancements in medical treatment for pancreatic neuroendocrine tumors:A beacon of hope

This editorial highlights the remarkable advancements in medical treatment strategies for pancreatic neuroendocrine tumors(pan-NETs),emphasizing tailored approaches for specific subtypes.Cytoreductive surgery and somatostatin analogs(SSAs)play pivotal roles in managing tumors,while palliative options such as molecular targeted therapy,peptide receptor radionuclide therapy,and chemotherapy are reserved for SSA-refractory patients.Gastrinomas,insul-inomas,glucagonomas,carcinoid tumors and VIPomas necessitate distinct thera-peutic strategies.Understanding the genetic basis of pan-NETs and exploring immunotherapies could lead to promising avenues for future research.This review underscores the evolving landscape of pan-NET treatment,offering renewed hope and improved outcomes for patients facing this complex disease.

Attitude and willingness on gamete donation among medical students:An experience from a state university in Sri Lanka

Objective:To assess the attitude and willingness of medical students of the Faculty of Medicine,University of Jaffna,regarding gamete donation.Methods:An institutional-based descriptive cross-sectional study was conducted at the Faculty of Medicine,University of Jaffna,from September 2022 to May 2023 among undergraduate medical students who gave their voluntary participation.A self-administered questionnaire was used as a study instrument to collect data regarding their attitude and willingness toward gamete donation.Results:A total of 345 participants were recruited and their sociodemographic data revealed that 56.8%of the participants were female,62.3%aged between 26 and 30 years,and 92.2%were unmarried.Many of them received information regarding gamete donations during their clinical appointments.Over half(67.8%)of them showed a negative attitude towards gamete donation.Regarding willingness,only 39.7%of participants had a positive approach for being a gamete donor;among them,84.7%preferred anonymous donations.Religion and ethnicity had a significant influence on their attitudes and willingness.In addition,male was also found to be more willing to donate gametes.Conclusions:Most medical students have negative views about gamete donation.Imparting awareness and knowledge of assisted reproductive technology and gamete donation within medical students'sociocultural and ethical backgrounds might facilitate a change in attitude towards gamete donation amongst future medical practitioners.

DCFNet:An Effective Dual-Branch Cross-Attention Fusion Network for Medical Image Segmentation

Automatic segmentation of medical images provides a reliable scientific basis for disease diagnosis and analysis.Notably,most existing methods that combine the strengths of convolutional neural networks(CNNs)and Transformers have made significant progress.However,there are some limitations in the current integration of CNN and Transformer technology in two key aspects.Firstly,most methods either overlook or fail to fully incorporate the complementary nature between local and global features.Secondly,the significance of integrating the multiscale encoder features from the dual-branch network to enhance the decoding features is often disregarded in methods that combine CNN and Transformer.To address this issue,we present a groundbreaking dual-branch cross-attention fusion network(DCFNet),which efficiently combines the power of Swin Transformer and CNN to generate complementary global and local features.We then designed the Feature Cross-Fusion(FCF)module to efficiently fuse local and global features.In the FCF,the utilization of the Channel-wise Cross-fusion Transformer(CCT)serves the purpose of aggregatingmulti-scale features,and the Feature FusionModule(FFM)is employed to effectively aggregate dual-branch prominent feature regions from the spatial perspective.Furthermore,within the decoding phase of the dual-branch network,our proposed Channel Attention Block(CAB)aims to emphasize the significance of the channel features between the up-sampled features and the features generated by the FCFmodule to enhance the details of the decoding.Experimental results demonstrate that DCFNet exhibits enhanced accuracy in segmentation performance.Compared to other state-of-the-art(SOTA)methods,our segmentation framework exhibits a superior level of competitiveness.DCFNet’s accurate segmentation of medical images can greatly assist medical professionals in making crucial diagnoses of lesion areas in advance.

Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

A review of medical ocular image segmentation

Deep learning has been extensively applied to medical image segmentation,resulting in significant advancements in the field of deep neural networks for medical image segmentation since the notable success of U Net in 2015.However,the application of deep learning models to ocular medical image segmentation poses unique challenges,especially compared to other body parts,due to the complexity,small size,and blurriness of such images,coupled with the scarcity of data.This article aims to provide a comprehensive review of medical image segmentation from two perspectives:the development of deep network structures and the application of segmentation in ocular imaging.Initially,the article introduces an overview of medical imaging,data processing,and performance evaluation metrics.Subsequently,it analyzes recent developments in U-Net-based network structures.Finally,for the segmentation of ocular medical images,the application of deep learning is reviewed and categorized by the type of ocular tissue.

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.