Sushree Nibedita Panda, Manish Barik, P. Ratna
et al.
Shaped by its colonial origins, tropical medicine sustains inequitable power dynamics in global health, sidelining low-middle-income countries (LMICs) in critical decision-making processes over research agendas and priorities. Editorial boards of tropical medicine journals, dominated by scholars from high-income countries (HICs), risk reinforcing power imbalances and excluding context-driven expertise from endemic regions. This study examines the diversity of editorial boards across gender, geographic, socioeconomic, and geopolitical dimensions to assess systemic inequities. A systematic search of the National Library of Medicine (NLM) catalog was conducted via a targeted strategy between October and December 2024. After screening 153 journals for title relevance and applying exclusion criteria based on publication status, availability of editorial information, and global scope, 24 journals were selected. Data on 2,226 editorial board members were extracted from journal and institutional websites. Data on gender, country of affiliation (classified by World Bank income/regions), and geopolitical groups (G7, G20, BRICS) were extracted from public sources. Gender determination used a sequential approach (journal descriptions, Genderize.io, and consensus). Descriptive statistics were used to perform the analysis. The editorial board comprised 2,226 members, 66% male, 31.2% female, and 2.8% undetermined, from 120 nations. The regional contributions included Europe and Central Asia (21.9%), North America (20.9%), East Asia and the Pacific (16.6%), and Latin America and the Caribbean (16.2%), whereas Sub-Saharan Africa (11.2%), South Asia (9.7%), and the Middle East and North Africa (3.4%) were underrepresented. Over half (52.8%) were affiliated with high-income countries. Geopolitically, 40.3% were from the G7, 67.1% were from the G20, and 24.2% were from the BRICS. Some journals showed skewing, with 85.2% North American representation and 90.3% East Asia–Pacific dominance. Tropical medicine editorial boards are steeped in systemic inequities that echo colonial legacies, with the overrepresentation of HICs and men limiting LMIC perspectives and local expertise. This imbalance undermines research relevance and ethical integrity by prioritizing Global North agendas over the needs of populations most affected by tropical diseases. To address these disparities, substantial reforms are essential. Strategies such as instituting DEI (Diversity, Equity and Inclusion), creating targeted mentorship programs for LMIC researchers, and enforcing transparent, bias-resistant recruitment practices are important. Such measures will create a more inclusive editorial landscape that aligns research priorities with global health needs, promoting equitable and contextually relevant solutions.
Artificial intelligence (AI) has become increasingly central to precision medicine by enabling the integration and interpretation of multimodal data, yet implementation in clinical settings remains limited. This paper provides a scoping review of literature from 2019-2024 on the implementation of AI in precision medicine, identifying key barriers and enablers across data quality, clinical reliability, workflow integration, and governance. Through an ecosystem-based framework, we highlight the interdependent relationships shaping real-world translation and propose future directions to support trustworthy and sustainable implementation.
Richard Massey, Jacob A. Kegerreis, Juan Paolo Lorenzo Gerardo Barrios
et al.
From 2002 to 2025, the Hubble Space Telescope's Advanced Camera for Surveys has suffered in the harsh radiation environment above the protection of the Earth's atmosphere. We track the degradation of its image quality, as Solar protons and galactic cosmic rays have damaged its photosensitive charge-coupled device (CCD) imaging sensors. The rate of damage in low Earth orbit is modulated by $18.5^{+4.5}_{-0.5}$ per cent during an 11 year Solar cycle, peaking $430^{+11}_{-5}$ days after Solar minimum as recorded in the number of sunspots. The type of damage is consistent with defects in the silicon lattice that have all stabilised into one of three configurations. We also present the open-source Algorithm for Charge Transfer Inefficiency correction (ArCTIc) v7. This models the (instantaneous or gradual) capture of photoelectrons into lattice defects, and their release after (a discrete set or continuum of) characteristic time delays, which creates spurious trailing in an image. Calibrated using the trailing of hot pixels, and applied during post-processing of astronomical images, ArCTIc can correct 99.5% of Charge Transfer Inefficiency trailing averaged over the camera's lifetime, and 99.9% of trailing in the worst-affected recent data.
F. Salvador, Cristina Bocanegra, B. Treviño
et al.
BACKGROUND Acute schistosomiasis occurs most often in travelers to endemic regions. The aim of the study is to describe the epidemiological, clinical and parasitological characteristics of patients with schistosomiasis acquired during an international travel. METHODS Observational retrospective study including all travel-related schistosomiasis cases seen at the International Health Unit Vall d'Hebron-Drassanes (Barcelona, Spain) from 2009 to 2022. Diagnosis of schistosomiasis was defined by the presence of Schistosoma eggs in stools or urine or the positivity of a serological test. We collected demographic, epidemiological, clinical, parasitological, and therapeutic information. RESULTS 917 cases of schistosomiasis were diagnosed, from whom 96 (10.5%) were travel-related. Mean age of the patients was 34.9 years, and 53.1% were women. Median duration of the travel was 72 days, and geographical areas where travelers had contact with fresh water were Africa (82.3%), Asia (12.5%), and South America (5.2%). Twenty (20.8%) patients reported having had some clinical symptom, being gastrointestinal symptoms the most frequent. Two patients developed the classical Katayama syndrome. In eleven (11.5%) cases eggs were observed in urine or feces samples, and 85 (88.5%) cases were diagnosed by a positive serology. Ninety-one (94.8%) patients received treatment with praziquantel with different therapeutic schemes. The two patients with Katayama syndrome received concomitant treatment with corticosteroids. CONCLUSIONS Schistosomiasis in travelers represented 10% of the overall schistosomiasis cases in our center. Increasing the awareness in the pre-travel advice and implementing specific screening in those travelers at risk (long travelers, contact with fresh water) could reduce the incidence and associated morbidity in this group.
Abstract Background Delusional infestation (DI) is a well-recognized delusional disorder presenting as the persisting belief of being infested. Combined clinics have been run by dermatology and psychiatry in a small number of centres. In this article we focus on our Liverpool University Hospitals NHS Foundation Trust clinic hosted at the Liverpool School of Tropical Medicine, UK, where we run a specialist clinic for DI. Methods We describe the specific set-up and approach of our clinic as a guide for clinicians working in specialties likely to see patients with DI (including tropical medicine, infectious diseases and dermatology) who may either want to set up similar clinics or be better equipped to manage DI patients promptly within existing practice. Results We describe the details of the clinic's approach. Between 2018 and 2023, the service saw 208 patients, of which 82.7% could be assessed and 55.7% had DI. The female:male ratio was 2:1. Conclusion Interdisciplinary combined clinics with medical and psychiatry consultants working together offer an approach to managing this rare, challenging and high-consequence condition.
The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.
This report presents a small language model (SLM) for Japanese clinical and medicine, named NCVC-slm-1. This 1B parameters model was trained using Japanese text classified to be of high-quality. Moreover, NCVC-slm-1 was augmented with respect to clinical and medicine content that includes the variety of diseases, drugs, and examinations. Using a carefully designed pre-processing, a specialized morphological analyzer and tokenizer, this small and light-weight model performed not only to generate text but also indicated the feasibility of understanding clinical and medicine text. In comparison to other large language models, a fine-tuning NCVC-slm-1 demonstrated the highest scores on 6 tasks of total 8 on JMED-LLM. According to this result, SLM indicated the feasibility of performing several downstream tasks in the field of clinical and medicine. Hopefully, NCVC-slm-1 will be contributed to develop and accelerate the field of clinical and medicine for a bright future.
ABSTRACT Background: To analyze the temporal evolution of research on Neglected Tropical Diseases (NTDs) published by the Journal of the Brazilian Society of Tropical Medicine (JBSTM). Methods: We performed an analysis of the scientific production in JBSTM on NTDs using an advanced search, which included authors’ descriptors, title, and abstract, and by combining specific terms for each NTDs from 1991 to 2021. Data related to authors, countries of origin, institutions, and descriptors, were evaluated and analyzed over time. Bibliographic networks were constructed using VOSviewer 1.6.16. Results: The JBSTM published 4,268 scientific papers during this period. Of these 1,849 (43.3%) were related to NTDs. The number of publications on NTDs increased by approximately 2.4-fold, from 352 (total 724) during 1991-2000 to 841 (total 2,128) during 2011-2021, despite the proportional reduction (48.6% versus 39.5%). The most common singular NTDs subject of publications included Chagas disease (31.4%; 581/1,849), leishmaniasis (25.5%, 411/1,849), dengue (9.4%, 174/1,849), schistosomiasis (9.0%; 166/1,849), and leprosy (6.5%, 120/1,849), with authorship mostly from Brazil’s South and Southeast regions. Conclusions: Despite the proportional reduction in publications, JBSTM remains an important vehicle for disseminating research on NTDs during this period. There is a need to strengthen the research and subsequent publications on specific NTDs. Institutions working and publishing on NTDs in the country were concentrated in the South and Southeast regions, requiring additional investments in institutions in other regions of the country.
Augmented reality becomes popular in education gradually, which provides a contextual and adaptive learning experience. Here, we develop a Chinese herb medicine AR platform based the 3dsMax and the Unity that allows users to visualize and interact with the herb model and learn the related information. The users use their mobile camera to scan the 2D herb picture to trigger the presentation of 3D AR model and corresponding text information on the screen in real-time. The system shows good performance and has high accuracy for the identification of herbal medicine after interference test and occlusion test. Users can interact with the herb AR model by rotating, scaling, and viewing transformation, which effectively enhances learners' interest in Chinese herb medicine.
Abstract Background The COVID-19 pandemic has impacted medical professionals’ job satisfaction and was a call to adopt telemedicine. Finding out how far medical professionals are satisfied and ready to use telemedicine would be important to improve medical practice. Methods Data was collected from 959 medical professionals from both the governmental and private health sectors in Egypt in 2021 using a specifically designed online questionnaire, to evaluate job satisfaction, perception of telemedicine, and propose solutions to improve medical practice. Results The study revealed low to moderate job satisfaction at governmental (27.2%) and private (58.7%) sectors. Underpayment was the most reported challenge at both sectors (37.8% and 28.3%, respectively). Dissatisfaction with government salary was independently predicted by working at the Ministry of Health and Population (OR = 5.54, 95%CI = 2.39,12.8; p < 0.001). Wage increase (46.10%), medical training of professionals (18.1%), and management of non-human resources (14.4%) were the most proposed solutions to improve medical practice in Egypt. During the COVID-19 pandemic, 90.7% of medical professionals had practiced telemedicine with moderate level of perception of its benefits (56%). Conclusions During the COVID-19 pandemic, medical professionals reported low to moderate job satisfaction and a moderate level of perception of telemedicine. It is recommended to analyze the healthcare financing system and provide continuous training of medical professionals to improve medical practice in Egypt.
Arctic medicine. Tropical medicine, Public aspects of medicine
Sabrina Maniscalco, Elsi-Mari Borrelli, Daniel Cavalcanti
et al.
Scientific and technological advances in medicine and systems biology have unequivocally shown that health and disease must be viewed in the context of the interplay among multiple molecular and environmental factors. Understanding the effects of cellular interconnection on disease progression may lead to the identification of novel disease genes and pathways, and hence influence precision diagnostics and therapeutics. To accomplish this goal, the emerging field of network medicine applies network science approaches to investigate disease pathogenesis, integrating information from relevant Omics databases, including protein-protein interaction, correlation-based, gene regulatory, and Bayesian networks. However, this requires analysing and computing large amounts of data. Moreover, if we are to efficiently search for new drugs and new drug combinations, there is a pressing need for computational methods that could allow us to access the immense chemical compound space until now largely unexplored. Finally, at the microscopic level, drug-target chemistry simulation is ultimately a quantum problem, and hence it requires a quantum solution. As we will discuss, quantum computing may be a key ingredient in enabling the full potential of network medicine. We propose to combine network medicine and quantum algorithms in a novel research field, quantum network medicine, to lay the foundations of a new era of disease prevention and drug design.
In practically every industry today, artificial intelligence is one of the most effective ways for machines to assist humans. Since its inception, a large number of researchers throughout the globe have been pioneering the application of artificial intelligence in medicine. Although artificial intelligence may seem to be a 21st-century concept, Alan Turing pioneered the first foundation concept in the 1940s. Artificial intelligence in medicine has a huge variety of applications that researchers are continually exploring. The tremendous increase in computer and human resources has hastened progress in the 21st century, and it will continue to do so for many years to come. This review of the literature will highlight the emerging field of artificial intelligence in medicine and its current level of development.
Peter N-Jonaam Mahama, Amos Tiereyangn Kabo-Bah, Justine I. Blanford
et al.
The current epidemiological transition makes us wonder how the parallel of infectious diseases (IDs) might be at the end of each passing year. Yet, the surveillance of these IDs continues to focus on high-profile diseases of public health importance without keeping track of the broad spectrum of the IDs we face. Here, we presented the prevalence of the broad spectrum of IDs in Ghana. Data from the annual reports on Gold Coast now Ghana, Global Infectious Diseases and Epidemiology Network (GIDEON), and the District Health Information Management System II (DHIMS2) databases were examined for records of ID prevalence in Ghana. Using the IDs from these databases, the paper assessed the epidemiological transition, pathogen-host interactions, spatiotemporal distribution, transmission routes, and their potential areas of impact in Ghana. The topmost ID recorded in health facilities in Ghana transitioned from yaws in the 1890s to malaria in the 1950s through 2020. We then presented the hosts of a pathogen and the pathogens of a host, the administrative districts where a pathogen was found, and the pathogens found in each district of Ghana. The highest modes of transmission routes were through direct contact for bacteria and airborne or droplet-borne for viral pathogens. From GIDEON, 226 IDs were identified as endemic or potentially endemic in Ghana, with 42% cited in peer-reviewed articles from 2000 to 2020. From the extent of risk of endemic or potentially endemic IDs, Ghana faces a high risk of ID burden that we should be mindful of their changing patterns and should keep track of the state of each of them.
This mini review is to introduce the readers of Plasma to the field of plasma medicine. This is a multidisciplinary field of research at the intersection of physics, engineering, biology and medicine. Plasma medicine is only about two decades old, but the research community active in this emerging field has grown tremendously in the last few years. Today, research is being conducted on a number of applications including wound healing and cancer treatment. Although a lot of knowledge has been created and our understanding of the fundamental mechanisms that play important roles in the interaction between low temperature plasma and biological cells and tissues has greatly expanded, much remains to be done to get a thorough and detailed picture of all the physical and biochemical processes that enter into play.
The practice of bloodletting gradually fell into disfavor as a growing body of scientific evidence showed its ineffectiveness and demonstrated the effectiveness of various pharmaceuticals for the prevention and treatment of certain diseases. At the same time, the patent medicine industry promoted ineffective remedies at medicine shows featuring entertainment, testimonials, and pseudo-scientific claims with all the trappings--but none of the methodology--of science. Today, many producing parties and eDiscovery vendors similarly promote obsolete technology as well as unvetted tools labeled "artificial intelligence" or "technology-assisted review," along with unsound validation protocols. This situation will end only when eDiscovery technologies and tools are subject to testing using the methods of information retrieval.
Gene mutation prediction in hepatocellular carcinoma (HCC) is of great diagnostic and prognostic value for personalized treatments and precision medicine. In this paper, we tackle this problem with multi-instance multi-label learning to address the difficulties on label correlations, label representations, etc. Furthermore, an effective oversampling strategy is applied for data imbalance. Experimental results have shown the superiority of the proposed approach.
1000 words comment on a paper published in the European Journal of Internal Medicine by a panel of experts. My point is authors address the magnitude of the change (one hour) but fail to consider in any way its seasonal features. DST is not a random change of an hour but an specific change on specific dates and in a specific direction ---spring forward, fall back---. DST is the way many contemporary societies handles the seasonality. The way many contemporary societies turn a nonseasonal clock (the mechanical clock) into a seasonal clock.
Abhijeet R. Sonawane, Scott T. Weiss, Kimberly Glass
et al.
Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale biomedical data generation offers a unique opportunity to assess the effect and impact of cellular heterogeneity and environmental perturbations on the observed phenotype. Marrying the two, network medicine with biomedical data provides a framework to build meaningful models and extract impactful results at a network level. In this review, we survey existing network types and biomedical data sources. More importantly, we delve into ways in which the network medicine approach, aided by phenotype-specific biomedical data, can be gainfully applied. We provide three paradigms, mainly dealing with three major biological network archetypes: protein-protein interaction, expression-based, and gene regulatory networks. For each of these paradigms, we discuss a broad overview of philosophies under which various network methods work. We also provide a few examples in each paradigm as a test case of its successful application. Finally, we delineate several opportunities and challenges in the field of network medicine. Taken together, the understanding gained from combining biomedical data with networks can be useful for characterizing disease etiologies and identifying therapeutic targets, which, in turn, will lead to better preventive medicine with translational impacts on personalized healthcare.
The Han Nguyen, Thi Huyen Nguyen, Van Minh Nguyen
et al.
Objective: To investigate antidiabetic and antioxidant activities of the extract and fractions from Vietnamese red seaweed Laurencia dendroidea.
Methods: The seaweed Laurencia dendroidea was extracted by using microwave-assisted extraction method in 80% methanol. The seaweed extract was then fractionated using different solvents (n-hexane, chloroform, ethyl acetate, butanol and water). These obtained fractions were evaluated for α -glucosidase inhibitory and antioxidant activities. Antioxidant activities were tested using DPPH, nitric oxide radical scavenging and metal chelating assays. The enzyme inhibition mode was determined using Lineweaver-Burk plot. For acidic and thermal stabilities, the ethyl acetate fraction was treated at pH 2.0 and 100 °C, respectively. The residual inhibitory activity of the fraction was calculated based on the initial inhibitory activity. For in vivo antidiabetic activity, mice were divided into four groups, including normal control, diabetic control, diabetic mice treated with ethyl acetate fraction and diabetic mice treated with gliclazide. Blood glucose level of treated mice during acute and prolonged treatments was measured. To evaluate the toxicity of the ethyl acetate fraction, the body weight changes and activities of liver function enzymes (aspartate transaminase, alanine transaminase and gamma-glutamyl transferase) were carried out.
Results: The extract of Laurencia dendroidea showed strong α-glucosidase inhibitory and DPPH radical scavenging activities. Methanolic concentrations affected both α-glucosidase inhibitory and antioxidant activities. A 80% aqueous methanol was the suitable solvent for extraction of enzyme inhibitors and antioxidants. Among solvent fractions, ethyl acetate fraction had the highest inhibitory activities against α -glucosidase with a mixed type of inhibition and the strongest antioxidant activities, and was stable under acidic and thermal conditions. The ethyl acetate fraction treated diabetic mice significantly reduced blood glucose level compared with the diabetic control group (13.16 mmol/L vs. 22.75 mmol/L after 3 hours of treatment). Oral administration of ethyl acetate fraction did not exhibit toxicity at a dose of 100 mg/kg body weight as determined by body weight changes and liver biochemical parameters.
Conclusions: Laurencia dendroidea could be a potential source for production of antidiabetic and antioxidative agents.