Hasil untuk "Medicine"

Benjamin Levy, L. Paulozzi, K. Mack et al.

Kunle, Oluyemisi Folashade, Egharevba et al.

S. Pan, Shufeng Zhou, Si-Hua Gao et al.

With tens of thousands of plant species on earth, we are endowed with an enormous wealth of medicinal remedies from Mother Nature. Natural products and their derivatives represent more than 50% of all the drugs in modern therapeutics. Because of the low success rate and huge capital investment need, the research and development of conventional drugs are very costly and difficult. Over the past few decades, researchers have focused on drug discovery from herbal medicines or botanical sources, an important group of complementary and alternative medicine (CAM) therapy. With a long history of herbal usage for the clinical management of a variety of diseases in indigenous cultures, the success rate of developing a new drug from herbal medicinal preparations should, in theory, be higher than that from chemical synthesis. While the endeavor for drug discovery from herbal medicines is “experience driven,” the search for a therapeutically useful synthetic drug, like “looking for a needle in a haystack,” is a daunting task. In this paper, we first illustrated various approaches of drug discovery from herbal medicines. Typical examples of successful drug discovery from botanical sources were given. In addition, problems in drug discovery from herbal medicines were described and possible solutions were proposed. The prospect of drug discovery from herbal medicines in the postgenomic era was made with the provision of future directions in this area of drug development.

R. Nussbaum, Christopher E. Ellis

Laura E. Bothwell, J. Greene, S. Podolsky et al.

Yuan Wu, Zongxian Yang, Jiayu Qian et al.

Large vision-language models (VLMs) often benefit from chain-of-thought (CoT) prompting in general domains, yet its efficacy in medical vision-language tasks remains underexplored. We report a counter-intuitive trend: on medical visual question answering, CoT frequently underperforms direct answering (DirA) across general-purpose and medical-specific models. We attribute this to a \emph{medical perception bottleneck}: subtle, domain-specific cues can weaken visual grounding, and CoT may compound early perceptual uncertainty rather than correct it. To probe this hypothesis, we introduce two training-free, inference-time grounding interventions: (i) \emph{perception anchoring} via region-of-interest cues and (ii) \emph{description grounding} via high-quality textual guidance. Across multiple benchmarks and model families, these interventions improve accuracy, mitigate CoT degradation, and in several settings reverse the CoT--DirA inversion. Our findings suggest that reliable clinical VLMs require robust visual grounding and cross-modal alignment, beyond extending text-driven reasoning chains. Code is available \href{https://github.com/TianYin123/Better_Eyes_Better_Thoughts}{here}.

André de Gouvêa, Hitoshi Murayama, Mark Palmer et al.

In this document we update the status of U.S. community inputs for the European Strategy for Particle Physics Update (ESPPU) since April 1, 2025, and offer responses to the revised questions. Major new inputs include a long-term strategy report from the National Academies of Sciences, Engineering, and Medicine and the formal formation of a U.S. Muon Collider Collaboration.

GUI Yuxin, HAN Yefen, ZHAO Jianing et al.

ObjectiveTo construct a quality evaluation index system for traditional Chinese medicine nursing of sequelae of pelvic inflammatory disease(SPID)(kidney deficiency and blood stasis syndrome).MethodsBased on the three-dimensional quality structure model of "structure-process-outcome",a quality evaluation index system for traditional Chinese medicine nursing of SPID(kidney deficiency and blood stasis syndrome) was constructed through literature review,semi⁃structured interviews,and the Delphi expert consultation method.The weight of each indicator was determined by the analytic hierarchy process.ResultsThe effective response rates for the two rounds of expert consultations were both 100.00%.The expert opinion proposal rates were 60.0% and 26.7%,respectively.The expert authority coefficients were 0.877 and 0.910,respectively.The Kendall's harmony coefficients were 0.241 and 0.370,respectively(both <italic>P</italic>&lt;0.01).The final constructed index system included 3 first-level indicators,14 second-level indicators,and 60 third⁃level indicators.ConclusionsThe quality evaluation index system for traditional Chinese medicine nursing of SPID(kidney deficiency and blood stasis syndrome) constructed in this study is scientific,reliable,systematic,and comprehensive.It could provide a reference for the evaluation and continuous improvement of the quality of traditional Chinese medicine nursing.

Zhixuan Wang

Epilepsy is a prevalent neurological disease with millions of patients worldwide. Many patients have turned to alternative medicine due to the limited efficacy and side effects of conventional antiepileptic drugs. In this study, we developed a computational approach to optimize herbal epilepsy treatment through AI-driven analysis of global natural products and statistically validated randomized controlled trials (RCTs). Our intelligent prescription system combines machine learning (ML) algorithms for herb-efficacy characterization, Bayesian optimization for personalized dosing, and meta-analysis of RCTs for evidence-based recommendations. The system analyzed 1,872 natural compounds from traditional Chinese medicine (TCM), Ayurveda, and ethnopharmacological databases, integrating their bioactive properties with clinical outcomes from 48 RCTs covering 48 epilepsy conditions (n=5,216). Using LASSO regression and SHAP value analysis, we identified 17 high-efficacy herbs (e.g., Gastrodia elata [using é for accented characters], Withania somnifera), showing significant seizure reduction (p$<$0.01, Cohen's d=0.89) with statistical significance confirmed by multiple testing (p$<$0.001). A randomized double-blind validation trial (n=120) demonstrated 28.5\% greater seizure frequency reduction with AI-optimized herbal prescriptions compared to conventional protocols (95\% CI: 18.7-37.3\%, p=0.003).

Nakhul Kalaivanan, Senthil Arumugam Muthukumaraswamy, Girish Balasubramanian

This research presents a multi-robot system for inpatient care, designed using swarm intelligence principles and incorporating wearable health sensors, RF-based communication, and AI-driven decision support. Within a simulated hospital environment, the system adopts a leader-follower swarm configuration to perform patient monitoring, medicine delivery, and emergency assistance. Due to ethical constraints, live patient trials were not conducted; instead, validation was carried out through controlled self-testing with wearable sensors. The Leader Robot acquires key physiological parameters, including temperature, SpO2, heart rate, and fall detection, and coordinates other robots when required. The Assistant Robot patrols corridors for medicine delivery, while a robotic arm provides direct drug administration. The swarm-inspired leader-follower strategy enhanced communication reliability and ensured continuous monitoring, including automated email alerts to healthcare staff. The system hardware was implemented using Arduino, Raspberry Pi, NRF24L01 RF modules, and a HuskyLens AI camera. Experimental evaluation showed an overall sensor accuracy above 94%, a 92% task-level success rate, and a 96% communication reliability rate, demonstrating system robustness. Furthermore, the AI-enabled decision support was able to provide early warnings of abnormal health conditions, highlighting the potential of the system as a cost-effective solution for hospital automation and patient safety.

Jérôme Houdu, Maxime Barron, Thierry Civit et al.

ABSTRACT After surgery involving cranial nerves and more generally the central nervous system, nonbacterial meningitis should raise suspicion of herpes simplex virus type 1 reactivation. No time should be wasted in diagnosis and treatment; therefore, a polymerase chain reaction testing on cerebrospinal fluid should be systematic in this situation, without neglecting to consider other differential diagnoses.

Lili Tian, Lili Tian, Jian Sun et al.

IntroductionMethicillin-resistant Staphylococcus aureus (MRSA) is a major clinical challenge due to its virulence and multidrug resistance. Antivirulence strategies targeting key pathogenic mechanisms without affecting bacterial viability provide a promising alternative to conventional antibiotics.MethodsThe inhibitory effect of isoliquiritigenin (ISL) on S. aureus sortase A (SrtA) was assessed using a fluorescence resonance energy transfer assay. Fluorescence quenching and molecular docking analyses were performed to elucidate the binding interaction between ISL and SrtA. Adhesion and biofilm formation were evaluated on fibrinogen- and fibronectin-coated surfaces, and bacterial growth was monitored to confirm non-bactericidal activity. The therapeutic efficacy of ISL was further examined in a murine pneumonia model through bacterial load quantification, histopathological analysis, and survival evaluation.ResultsISL inhibited SrtA activity in a dose-dependent manner (IC50 = 13.34 µg/mL), disrupted adhesion and biofilm formation without affecting bacterial growth, and bound reversibly to key catalytic residues of SrtA. In vivo, ISL treatment significantly reduced pulmonary bacterial burden, alleviated tissue damage, and improved survival in infected mice.DiscussionISL effectively attenuates MRSA pathogenicity by targeting SrtA-mediated virulence rather than bacterial viability. These results highlight ISL as a promising antivirulence agent and a potential adjuvant for combating antibiotic-resistant S. aureus infections.

Sharon Paoli Bias Ramos, Gabriel Rodrigues Martins de Freitas, Silvana Teresa Lacerda Jales

Objetivo: analisar o perfil pós-consumo dos medicamentos descartados pela comunidade universitária no coletor disponibilizado no Centro de Ciências da Saúde da Universidade Federal da Paraíba. Métodos: O projeto de extensão Descarta CIM instalou um coletor no Centro de Informações sobre Medicamentos - CIM do Departamento de Ciências Farmacêuticas e promoveu campanhas educativas em outros centros de ensino do Campus I. A partir disso, foi feita a pesagem e catalogação dos medicamentos descartados durante um período de 6 meses, seguida de análise detalhada do tipo de medicamento, categoria regulatória, classificação ATC (Anatomical Therapeutic Chemical), forma farmacêutica, tipo de embalagem e prazo de validade. Resultados: Os dados encontrados indicam que os medicamentos genéricos representam 42,5% do volume descartado, seguidos por medicamentos de referência (35,7%) e similares (21,7%). A análise da classificação ATC revela uma prevalência de medicamentos relacionados ao sistema digestivo e metabolismo, seguidos por sistema cardiovascular, sistema nervoso e músculo-esquelético. Observa-se uma alta porcentagem de medicamentos fora do prazo de validade (72,8%), levantando questões sobre a prática de automedicação e a necessidade de conscientização sobre o uso racional de medicamentos. Conclusão: O estudo demonstra algumas limitações, sobretudo quando não se pode determinar com exatidão se todos os medicamentos descartados foram efetivamente utilizados pela comunidade universitária. Contudo, a análise demonstrou que a promoção de campanhas educativas e a presença de coletores incentivam o descarte adequado de medicamentos e estimulam uma mudança de comportamento e a prática de ações de proteção ambiental.  

Alexandre D´Agostini Zottis, Júlia Luiz Agostinho, Eduardo Ricardo Santana et al.

Resumo: Introdução/Justificativa: O câncer engloba mais de 100 tipos de doenças malignas caracterizadas pelo crescimento descontrolado de células, que podem invadir tecidos adjacentes ou se espalhar para outras partes do corpo. Há décadas, as nanopartículas magnéticas (NPMs) de óxido de ferro vêm sendo estudadas por apresentarem grande potencial para aplicações biomédicas, especialmente na oncologia, no uso de agentes de contraste para imagem por ressonância magnética no realçamento de contraste negativo nos tecidos com a presença de tumores e não tumorais, em magneto hipertermia para destruição seletiva de células cancerosas e atuando no transporte vetorizado de fármacos quimioterápicos. Independente de suas aplicações biomédicas, para evitar a aglomeração das NPMs em células, tecidos e órgãos, que pode levar a embolismos, é essencial recobri-las com materiais biocompatíveis e não citotóxicos. Poliésteres derivados de lactonas e macrolactonas, como o copoliéster poli(globalide-co-ε-caprolactona) (PGlCL), têm sido explorados devido à sua biocompatibilidade, hidrofilicidade e biodegradabilidade. Objetivos: Este trabalho teve como objetivo a modificação e a funcionalização do copoliéster PGICL com cisteína, a fim de atingir três objetivos associados a funcionalização das NPMs, que garantirão sua aplicação em nanomedicina, tais como: a) melhorar sua hidrofilicidade (diminuindo sua cristalinidade) para que seja carreado com mais facilidade no meio intracelular; b) permitir que grupos amina e tiol sejam pontos de ancoragem para constituírem partes de ligantes com receptores de superfície celular, tais como o ácido fólico (AF) que só são expressos em células tumorais e c) possibilitar a ligação desses grupos químicos em sistemas de ''drug-delivery'' com o análogo do AF, o quimioterápico metotrexato (MTX) para o tratamento de câncer de mama. Neste estudo, o PGlCL foi modificado com cisteína (PGlCL-Cys) e utilizado para recobrir NPMs de óxido de ferro (Fe3O4 - magnetita), visando futuramente em um segundo passo, a funcionalização com AF e MTX em aplicações como vetorização ativas em sistemas como “drug-delivery” e a posteriori, em ensaios in vitro de radiosensibilização em células de câncer de mama. Materiais e Métodos: Soluções de Fe³⁺ e Fe²⁺ em HCl. Sob refluxo, adicionaram-se H₂O aquecida, NH₄OH (30mL, pH10, 90°C), PGICL em etanol. Agitou-se 45min, purificou-se com imã, lavou-se e armazenou as NPMs. Resultados: A caracterização físico-química das NPMs recobertas com PGlCL-Cys foi realizada por espectroscopia no infravermelho, confirmando a presença de bandas características da cisteína (ligações C-S-C em 715,21 cm⁻¹ e C-N em 1573,1 cm⁻¹) e do recobrimento das NPMs (bandas de deformação angular da ligação Fe- O em 635,63 cm⁻¹ e ∼590 cm⁻¹, correspondentes aos sítios octaédricos e tetraédricos da magnetita, respectivamente). A Microscopia Eletrônica de Transmissão (MET) revelou que as NPMs de Fe3O4@PGlCL-Cys possuem um diâmetro médio de 11,44 nm e exibem comportamento superparamagnético. Conclusão: Conclui-se que o método de coprecipitação e a síntese do copoliéster modificado com cisteína (PGlCL-Cys) foi eficaz, produzindo NPMs estáveis e monodispersas de modo que serão realizados futuramente outras caracterizações físico-químcias para avançar os estudos em ensaios biológicos in vitro para citotoxicidade e biocompatibilidade a fim de serem aplicadas no diagnóstico e tratamento de câncer de mama.

Marzena Zielińska, Alicja Bartkowska-Śniatkowska, Magdalena Mierzewska-Schmidt et al.

The anaesthesia of a young child under 3 years of age is a challenge for every anaesthetist. The peculiarities of this group of patients, particularly neonates and infants, resulting primarily from differences in both physiology, anatomy and the immaturity of individual organs which translate into different pharmacokinetics and pharmacodynamics of the drugs used in anaesthesiology, underlie the significantly more frequently recorded critical events during anaesthesia compared with the adult patient population. Concerned about the safety of children undergoing anaesthesia and aiming to ensure the highest possible quality and uniform standard of anaesthetic services, the Expert Panel of the Section of Paediatric Anaesthesiology and Intensive Care has prepared a Section position paper on anaesthesia in children under 3 years of age.

Zhongqiu Guo, Yanrong Chen, Ronghuo Liu et al.

ABSTRACT Insulinomas are the primary etiology of endogenous hyperinsulinemic hypoglycemia, which often manifest with Whipple’s triad and neuroglycopenic symptoms. Given the diverse clinical manifestation and subtle onset of insulinomas generally in a small size, detecting a minority of these generally small tumors can be challenging. We reported a case of a 44‐year‐old female patient with recurrent hypoglycemia accompanied by hyperinsulinemia, and the conventional imaging revealed no abnormality. With the aid of endoscopic ultrasound‐guided fine‐needle aspiration biopsy (EUS‐FNAB), the insulinoma was precisely diagnosed and localized, and successfully excised via operation. The patient’s hyperinsulinemia and hypoglycemic episodes were relieved significantly after surgery. The application of EUS‐FNAB notably enhances the diagnostic accuracy for occult insulinomas, thereby informing appropriate surgical management. Herein, we advocate for invasive EUS examination in patients exhibiting strong clinical and laboratory indicators of insulinoma, even when conventional imaging results are negative.

Soroosh Tayebi Arasteh, Tomas Arias-Vergara, Paula Andrea Perez-Toro et al.

Integration of speech into healthcare has intensified privacy concerns due to its potential as a non-invasive biomarker containing individual biometric information. In response, speaker anonymization aims to conceal personally identifiable information while retaining crucial linguistic content. However, the application of anonymization techniques to pathological speech, a critical area where privacy is especially vital, has not been extensively examined. This study investigates anonymization's impact on pathological speech across over 2,700 speakers from multiple German institutions, focusing on privacy, pathological utility, and demographic fairness. We explore both deep-learning-based and signal processing-based anonymization methods. We document substantial privacy improvements across disorders-evidenced by equal error rate increases up to 1933%, with minimal overall impact on utility. Specific disorders such as Dysarthria, Dysphonia, and Cleft Lip and Palate experience minimal utility changes, while Dysglossia shows slight improvements. Our findings underscore that the impact of anonymization varies substantially across different disorders. This necessitates disorder-specific anonymization strategies to optimally balance privacy with diagnostic utility. Additionally, our fairness analysis reveals consistent anonymization effects across most of the demographics. This study demonstrates the effectiveness of anonymization in pathological speech for enhancing privacy, while also highlighting the importance of customized and disorder-specific approaches to account for inversion attacks.

Antonio Moreno-Sandoval, Leonardo Campillos-Llanos, Ana García-Serrano

This work describes the language resources and models developed for automatic simplification of Spanish texts in three domains: Finance, Medicine and History studies. We created several corpora in each domain, annotation and simplification guidelines, a lexicon of technical and simplified medical terms, datasets used in shared tasks for the financial domain, and two simplification tools. The methodology, resources and companion publications are shared publicly on the web-site: https://clara-nlp.uned.es/.

Jayanth Mohan, Arrun Sivasubramanian, V Sowmya et al.

Skin diseases affect over a third of the global population, yet their impact is often underestimated. Automating skin disease classification to assist doctors with their prognosis might be difficult. Nevertheless, due to efficient feature extraction pipelines, deep learning techniques have shown much promise for various tasks, including dermatological disease identification. This study uses a skin disease dataset with 31 classes and compares it with all versions of Vision Transformers, Swin Transformers and DivoV2. The analysis is also extended to compare with benchmark convolution-based architecture presented in the literature. Transfer learning with ImageNet1k weights on the skin disease dataset contributes to a high test accuracy of 96.48\% and an F1-Score of 0.9727 using DinoV2, which is almost a 10\% improvement over this data's current benchmark results. The performance of DinoV2 was also compared for the HAM10000 and Dermnet datasets to test the model's robustness, and the trained model overcomes the benchmark results by a slight margin in test accuracy and in F1-Score on the 23 and 7 class datasets. The results are substantiated using explainable AI frameworks like GradCAM and SHAP, which provide precise image locations to map the disease, assisting dermatologists in early detection, prompt prognosis, and treatment.

Peter E. Shamamian, Jr, BS, Daniel Y. Kwon, BS, Esther Kim, BS et al.