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Los sistemas agroforestales son potenciales sumideros de dióxido de carbono, contribuyendo así a mitigar el calentamiento de la tierra por efecto de las emisiones de C02 . El propósito de la presente investigación, es cuantificar carbono orgánico almacenado en sistema de café. Esta investigación se desarrolló en la hacienda Santa Maura, Jinotega., altitud 1000–1250 msnm, temperatura promedio de 19 a 23º C, suelos del tipo molisol. Se identificaron tres tipologías de cafeto de estudio que se diferencian por su variedad, edad y densidad de establecimiento. Se realizó un muestreo sistemático, intensidad del 2 %. La unidad de muestreo fue una parcela circular de 250 m2, en cada parcela de muestreo se tomó un árbol de eje central, procediendo a inventariar e identificar las especies de árboles y cafeto. Se midieron la altura total, altura fuste limpio, diámetro a la altura del pecho del que muestrea, pesos húmedo y seco de los diferente componentes. En los depósitos aéreos de cafetos y especies de sombra, se estimó la biomasa y contenido de carbono. En la tipología dos se encontró el mayor promedio de C almacenado con 19.86 tonelada métricas de carbono por hectárea (tMC ha-1), seguido del tipo tres, con 11.12 tMC ha-1 y por último, el tipo uno con 5.5 tMC ha-1. La diferencia de contenido de C entre tipología, está directamente ligado a la densidad, especie de árbol de sombra, edad y manejo de la plantación. Palabras clave: Almacenamiento de carbono, servicio ambiental.

Large language models (LLMs)-based chatbots use natural language processing and are a type of generative artificial intelligence (AI) that are capable of comprehending user input and generating output in various formats. They offer potential benefits in medical education. This study explored the student's feedback on the utilization of LLMs in medical education. We conducted an in-depth interview with open-ended questions with Indian medical students via telephone conversation. The recording (average time 55.28±18.04 min) was transcribed and thematically analyzed to find major themes and sub-themes. We used QDA Miner Lite v.2.0.8 (Provalis Research: Montreal, Canada) for the thematic analysis of the text. A total of 25 students from eight Indian states studying from the first to final year of studies participated in this study. Three major themes were identified about usage scenario, augmented learning, and limitation of LLMs. Students use LLMs for clarifying complex topics, searching for customized answers, solving MCQs, making simplified notes, and streamlining assignments. While they appreciated the ease of access, ready reference for getting clarity on doubts, lucid explanation of questions, and time-saving aspects of LLMs, concerns were raised regarding erroneous results, limited usage due to reliability and privacy issues, and the overreliance on chatbots for educational needs. Hence, they emphasized the need for training for the integration of LLM in medical education. In conclusion, according to students' perception, LLMs have the potential to enhance medical education. However, addressing challenges and leveraging the strengths of LLMs are crucial for optimizing their integration into medical education.

Competency-based physiology and biochemistry education can benefit from the creative integration of imaginative narratives into traditional teaching methods. This paper proposes an innovative model using a pen and palm analogy to visualize enzyme function theories. The pen (substrate) must fit snugly into the palm (enzyme's active site) for catalysis to occur, akin to induced-fit theory. Pressing the pen's top button with the thumb represents the strain needed to convert substrate (pen with nib inside) into product (pen with nub out, ready to write). By leveraging everyday objects creatively, students can enhance their understanding and engagement with enzymatic reactions. NEW & NOTEWORTHY Understanding how enzymes work can be tricky, but a new teaching method using everyday objects like pens and palms helps make it easier. Two main theories explain this: the induced-fit model and the substrate-strain model. To visualize this, imagine a pen as the substrate and your palm as the enzyme. When you hold the pen with your fingers (induced-fit), it's like the enzyme changing shape to hold the substrate. Pressing the pen's button with your thumb (substrate-strain) is like the enzyme applying pressure to make the pen ready to write. This simple analogy helps students better understand these complex processes, making learning more engaging and accessible.

Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest.

Background Answer script presentation is an effective means of conveying knowledge and understanding. It reflects clarity of thought and organization, which can positively influence scoring. Additionally, well-structured answers reduce the chances of misinterpretation, ensuring that your knowledge is accurately assessed. Despite its importance, there is limited research focusing on the specific errors students make in presenting their answers. Hence, this study explored common errors in answer script presentation from the perspectives of both teachers and students. Methods A cross-sectional study was conducted involving 240 students and 50 teachers in July 2024 at Mata Gujri Memorial Medical College, Bihar, India. A questionnaire was developed by a three-member panel of experts in education and assessment to ensure it was comprehensive and relevant to the study's objectives. The questionnaire comprised 12 items rated on a 5-point Likert scale where a higher score indicates higher perceptions of the error. Data were collected from teachers and students using the pre-tested self-administered printed questionnaire. The scores among the different perceived errors were compared by ANOVA and the scores between teachers and students were compared by unpaired t-test. Results Students perceived that their highest error was inconsistent handwriting (2.72±1.4), followed by incomplete diagrams (2.52±1.2) and disorganization (2.47±1.17). The error perceived to be least important was incorrect numbering (1.53±0.97), F=12.49, p-value<0.0001. Teachers perceived the error in illegible handwriting (4.36±0.48), followed by lack of emphasis (4.16±0.62) and disorganization (3.94±0.91) as the errors most likely to contribute to poor performance. The error perceived to be least important was inconsistent handwriting (2.4±1.01), F=18.22, p-value<0.0001. When the data were compared between teachers and students, except for inconsistent handwriting, the perceived error score by teachers was higher than the students perceived. Conclusion There was a significant disparity between students' and teachers' perceptions of common presentation errors, with teachers consistently rating the severity of errors higher than students. Both groups identified inconsistent handwriting as a prominent error. This underscores the need for better alignment and communication between students and educators regarding the importance of specific aspects of written presentation in assessments., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Ethics Committee of Mata Gujri Memorial Medical College issued approval MGM/IEC/102/2024. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Deb Roy et al.)

Leptospirosis is a zoonosis with global public health impact, particularly in poor socio-economic settings in tropical regions. Transmitted through urine-contaminated water or soil from rodents, dogs, and livestock, leptospirosis causes over a million clinical cases annually. Risk factors include outdoor activities, livestock production, and substandard housing that foster high densities of animal reservoirs. This One Health study in southern Chile examined Leptospira serological evidence of exposure in people from urban slums, semi-rural settings, and farm settings, using the Extreme Gradient Boosting algorithm to identify key influencing factors. In urban slums, age, shrub terrain, distance to Leptospira -positive households, and neighborhood housing density were contributing factors. Human exposure in semi-rural communities was linked to environmental factors (trees, shrubs, and lower vegetation terrain) and animal variables ( Leptospira -positive dogs and rodents and proximity to Leptospira -positive households). On farms, dog counts, animal Leptospira prevalence, and proximity to Leptospira -contaminated water samples were significant drivers. The study underscores that disease dynamics vary across landscapes, with distinct drivers in each community setting. This case study demonstrates how the integration of machine learning with comprehensive cross-sectional epidemiological and geospatial data provides valuable insights into leptospirosis eco-epidemiology. These insights are crucial for informing targeted public health strategies and generating hypotheses for future research.

Objective The present study aimed to assess and compare the surgical outcomes of hemorrhoidectomies performed using two different techniques: conventional Milligan-Morgan and another popular vessel sealing approach of LigaSure hemorrhoidectomy. Methods This retrospective study was conducted at our tertiary care hospital and involved patients who underwent either of the surgical procedures from June 2016 to March 2022. The patient demographics and data on the duration of operation, hospital stay, and postoperative recovery were collected and evaluated. Results Of the 91 cases reviewed, a total of 44 patients underwent Milligan-Morgan open hemorrhoidectomy and 47 had LigaSure hemorrhoidectomy. The mean operative time was significantly shorter for LigaSure hemorrhoidectomy (33.84 ±9.18 vs. 23.15 ±3.36 minutes for Milligan-Morgan and LigaSure, respectively, p<0.0001). Additionally, in comparison to Milligan-Morgan open hemorrhoidectomy, the LigaSure hemorrhoidectomy group exhibited a significant reduction in hospital stay (2.20 ±0.79 vs. 1.47 ±0.50 days), lower pain score [6.55 ±1.19 vs. 5.30 ±1.10 on the visual analog scale (VAS) on day one and 2.25 ±1.26 vs. 1.47 ±0.78 VAS on day seven], and faster return to normal activities (18.18 ±4.30 vs. 14.85 ±3.15 days). Conclusions When pitted against the traditional Milligan-Morgan method, the LigaSure approach to performing a hemorrhoidectomy is superior, owing to the shorter duration of operation, shorter hospital stays, lesser pain, and earlier return to normal activities. In light of these findings, surgeons may consider choosing this procedure to improve surgical outcomes and efficiency., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Ethics Committee at Dayanand Medical College and Hospital (DMCH), Ludhiana issued approval IEC No: 2022-737. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Virk et al.)

Background Recently, elective posting has been introduced by the National Medical Commission (NMC) of India in the undergraduate competency-based medical education (CBME) curriculum. To successfully implement it in medical colleges, facilitators (medical teachers) need to commit extra time. Hence, this study aimed to evaluate the impact of online teaching-learning methods for implementing an elective module for undergraduate medical students at Burdwan Medical College and Hospital, West Bengal, India. Methods An online module for systematic review methods was developed using the Delphi method. This module was used to train 30 medical students divided into six groups. One resident and one faculty facilitated each group. After the elective program of 15 days, program feedback and evaluation using the Kirkpatrick model were obtained from the students. Results A total of 30 undergraduate medical students with a mean age of 22.7±0.95 years participated in the study. All of them successfully conducted a systematic review per group. The students' feedback was 86.33% positive, and the project evaluation showed an 84% positive opinion. The highest score was for understanding, facilitators' knowledge, and experience. The lowest score was for the immediate applicability of the knowledge. Conclusion An online systematic review training module can be used for elective teaching-learning for final-year medical students, particularly within limited time and resource constraints. Students appreciated the module's clear objectives, appropriate complexity, and facilitators' expertise, leading to improved communication, engagement, and critical-thinking skills. Despite some limitations, these findings suggest that online learning can complement traditional methods and address logistical challenges in medical education, warranting further research on its long-term impact and broader applicability., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Ethics Committee of Burdwan Medical College, Burdwan, West Bengal issued approval BMC/IEC/159. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Chaudhuri et al.)

Background  Artificial intelligence chatbots have demonstrated potential to enhance clinical decision-making and streamline health care workflows, potentially alleviating administrative burdens. However, the contribution of AI chatbots to radiologic decision-making for clinical scenarios remains insufficiently explored. This study evaluates the accuracy and reliability of four prominent Large Language Models (LLMs)-Microsoft Bing, Claude, ChatGPT 3.5, and Perplexity-in offering clinical decision support for initial imaging for suspected pulmonary embolism (PE). Methods  Open-ended (OE) and select-all-that-apply (SATA) questions were crafted, covering four variants of case scenarios of PE in-line with the American College of Radiology Appropriateness Criteria. These questions were presented to the LLMs by three radiologists from diverse geographical regions and setups. The responses were evaluated based on established scoring criteria, with a maximum achievable score of 2 points for OE responses and 1 point for each correct answer in SATA questions. To enable comparative analysis, scores were normalized (score divided by the maximum achievable score). Result  In OE questions, Perplexity achieved the highest accuracy (0.83), while Claude had the lowest (0.58), with Bing and ChatGPT each scoring 0.75. For SATA questions, Bing led with an accuracy of 0.96, Perplexity was the lowest at 0.56, and both Claude and ChatGPT scored 0.6. Overall, OE questions saw higher scores (0.73) compared to SATA (0.68). There is poor agreement among radiologists' scores for OE (Intraclass Correlation Coefficient [ICC] = -0.067, p  = 0.54), while there is strong agreement for SATA (ICC = 0.875, p  < 0.001). Conclusion  The study revealed variations in accuracy across LLMs for both OE and SATA questions. Perplexity showed superior performance in OE questions, while Bing excelled in SATA questions. OE queries yielded better overall results. The current inconsistencies in LLM accuracy highlight the importance of further refinement before these tools can be reliably integrated into clinical practice, with a need for additional LLM fine-tuning and judicious selection by radiologists to achieve consistent and reliable support for decision-making., Competing Interests: Conflict of Interest None declared., (Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

QT interval in an electrocardiogram (ECG) is interpreted after correction (QTc) by various formulas. This study aimed to compare the QTcs calculated by nine formulas. Sinus rhythm ECG reports of 1140 anonymous subjects showed uncorrected QT interval of 388.49 ± 42.74 ms. The QTc calculated by Bazett (443.96 ± 57.58 ms), Fridericia (424.37 ± 50.1 ms), Dmitrienko (433.59 ± 53.37 ms), Framingham (422.59 ± 45.55 ms), Schlamowitz (433.89 ± 48.05 ms), Hodges (421.6 ± 46.4 ms), Ashman (434.33 ± 54.05 ms), Rautaharju (427.75 ± 47.4 ms), and Sarma (429.22 ± 48.67 ms) showed a significant difference F (8, 10251) = 22.78 p < 0.0001. Hence, ECG should contain the formula for proper reporting and ease of interpretation by clinicians., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Cardiological Society of India. Published by Elsevier, a division of RELX India, Pvt. Ltd. All rights reserved.)

Background: Occupational and lifestyle factors, such as smoking and street vending, may pose risks to pulmonary health. Previous studies explored the effect of both smoking and exposure to street pollutants on health. However, a study comparing the pulmonary functions of street vendors (who do not smoke) and smokers has not been conducted before., Objective: The objective of this study was to compare the pulmonary function parameters among three groups consisting of smokers, street vendors and controls in order to discern potential differences in respiratory health between the three groups., Methods: This cross-sectional study was conducted in the Deoghar district of the Jharkhand state, in India, over a period of five months (between January 2023 and May 2023). A total of 90 male participants, including 30 smokers, 30 street vendors and 30 age-matched control research participants, underwent pulmonary function testing (forced spirometry) using standardized methods. The comparison among the three groups was conducted by one-way analysis of variance with the post-hoc test., Results: A total of 30 controls with a mean age of 33.77±6.01 years, street vendors with a mean age of 32.93±6.29 years and smokers with a mean age of 32.27±7.86 years participated in the present study. There was an average exposure to road pollutants for 13.47±9.48 years and smoking for 13.23±8.29 years (P=0.92). Lung function parameters, except for the forced expiratory volume in one second divided by the forced vital capacity (FEV1/FVC), were lower in street vendors and smokers than controls., Conclusion: Street vendors in Deoghar, Jharkhand, have lung function parameters comparable to smokers. Hence, although they are not smoking tobacco, their lung health is at risk. Hence, early interventions are required to protect them from pollutants.

Emotional intelligence (EI) has a positive correlation with the academic performance of medical students. However, why there is a positive correlation needs further exploration. We hypothesized that the capability of answering higher-order knowledge questions (HOQs) is higher in students with higher EI. Hence, we assessed the correlation between EI and the capability of medical students to answer HOQs in physiology. First-year undergraduate medical students ( n = 124) from an Indian medical college were recruited as a convenient sample. EI was assessed by the Schutte Self-Report Emotional Intelligence Test (SSEIT), a 33-item self-administered validated questionnaire. A specially designed objective examination with 15 lower-order and 15 higher-order multiple-choice questions was conducted. The correlation between the examination score and the EI score was tested by Pearson's correlation coefficient. Data from 92 students (33 females and 59 males) with a mean age of 20.14 ± 1.87 yr were analyzed. Overall, students got a percentage of 53.37 ± 14.07 in the examination, with 24.46 ± 9.1 in HOQs and 28.91 ± 6.58 in lower-order knowledge questions (LOQs). They had a mean score of 109.58 ± 46.2 in SSEIT. The correlation coefficient of SSEIT score with total marks was r = 0.29 ( P = 0.0037), with HOQs was r = 0.41 ( P < 0.0001), and with LOQs was r = 0.14 ( P = 0.19). Hence, there is a positive correlation between EI and the capability of medical students to answer HOQs in physiology. This study may be the foundation for further exploration of the capability of answering HOQs in other subjects. NEW & NOTEWORTHY This study assessed the correlation between emotional intelligence (EI) and the capability of medical students to answer higher-order knowledge questions (HOQs) in the specific context of physiology. The finding reveals one of the multifaceted dimensions of the relationship between EI and academic performance. This novel perspective opens the door to further investigations to explore the relationship in other subjects and other dimensions to understand why students with higher EI have higher academic performance.

Competing Interests: Conflict of Interest None declared.

Background The rapid advancements in natural language processing have brought about the widespread use of large language models (LLMs) across various medical domains. However, their effectiveness in specialized fields, such as naturopathy, remains relatively unexplored. Objective The study aimed to assess the capability of freely available LLM chatbots in providing naturopathy consultations for various types of diseases and disorders. Methods Five free LLMs (viz., Gemini, Copilot, ChatGPT, Claude, and Perplexity) were used to converse with 20 clinical cases (simulation of real-world scenarios). Each case had the case details and questions pertinent to naturopathy. The responses were presented to three naturopathy doctors with > 5 years of practice. The answers were rated by them on a five-point Likert-like scale for language fluency, coherence, accuracy, and relevancy. The average of these four attributes is termed perfection in his study. Results The overall score of the LLMs were Gemini 3.81±0.23, Copilot 4.34±0.28, ChatGPT 4.43±0.2, Claude 3.8±0.26, and Perplexity 3.91±0.28 (ANOVA F [3.034, 57.64] = 33.47, P <0.0001. Together, they showed overall ~80% perfection in consultation. The average measure intraclass correlation coefficient among the LLMs for the overall score was 0.463 (95% CI = -0.028 to 0.76), P = 0.03. Conclusion Although the LLM chatbots could help in providing naturopathy and yoga treatment consultation with approximately an overall fair level of perfection, their solution to the user varies across different chatbots and there was very low reliability among them., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Mondal et al.)

Competing Interests: There are no conflicts of interest.

The field of clinical research continues to advance, and for ethical conduct of research, researchers need to have a strong foundation in good clinical practice (GCP). GCP guidelines are internationally recognized standards that govern the conduct of clinical trials, ensuring the protection of human subjects and the generation of reliable data. However, novice researchers or postgraduate medical students who would delve into research activities may face difficulty getting avenues for GCP training. Hence, in this brief review article, we discuss the significance of GCP in the field of clinical research with a glimpse of its history, development, and key principles. We provide a list of online courses, benefits, and disadvantages of those courses, and a list of organizations that conduct GCP workshops or continued medical education programs in India., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Indian Dermatology Online Journal.)