Field Of Medicine Research Articles

Cutting Through Stereotypes: A Scoping Review of Preclinical Medical Student Perceptions of Surgery.

Medical students enter clerkships with preconceived notions of the culture, attitudes, and behavior of surgeons and the field of surgery. These preconceived notions may contribute to student anxiety regarding surgery clerkship and ultimately influence career exploration. With the pervasive changes in the surgical workplace over the past 2 decades, we seek to understand the current state of the literature regarding medical students' perceptions of the surgical clerkship, surgeons, and the field of surgery. A comprehensive literature review was performed using the electronic databases Medline, Scopus, and Web of Science. We included studies involving US allopathic preclinical medical student perceptions of surgical education, surgery as a field of medicine, and surgeons as physicians. Following the PRISMA guidelines for scoping reviews, 2316 abstracts were identified, and 25 studies were included. We included 25 studies and collected 3 broad student perspectives: student perceptions of surgeons, the surgical clerkship, and surgery as a career. The review identified relevant themes within each perspective. Themes included work life balance, student mistreatment, student education, racial and sexual minority acceptance, competitiveness, and anxiety regarding the surgery clerkship. The results of this review suggest that preclinical medical students have overall negative perceptions of surgery, surgeons, and the surgical clerkship, but the origins of these perceptions remain unclear. Understanding the preconceived notions of preclinical students may lead to earlier interventions that could prevent negative stereotypes directed toward surgeons and surgery as a field.

Cell therapy: A beacon of hope in the battle against pulmonary fibrosis.

Pulmonary fibrosis (PF) is a chronic and progressive interstitial lung disease characterized by abnormal activation of myofibroblasts and pathological remodeling of the extracellular matrix, with a poor prognosis and limited treatment options. Lung transplantation is currently the only approach that can extend the life expectancy of patients; however, its applicability is severely restricted due to donor shortages and patient-specific limitations. Therefore, the search for novel therapeutic strategies is imperative. In recent years, stem cells have shown great promise in the field of regenerative medicine due to their self-renewal capacity and multidirectional differentiation potential, and a growing body of literature supports the efficacy of stem cell therapy in PF treatment. This paper systematically summarizes the research progress of various stem cell types in the treatment of PF. Furthermore, it discusses the primary methods and clinical outcomes of stem cell therapy in PF, based on both preclinical and clinical data. Finally, the current challenges and key factors to consider in stem cell therapy for PF are objectively analyzed, and future directions for improving this therapy are proposed, providing new insights and references for the clinical treatment of PF patients.

Advances in Scaffolds and Additives for Infection Control in Autologous Chondrocyte Transplantation.

Cartilage tissue engineering (CTE) has revolutionized the field of regenerative medicine, offering significant advancements in surgeries such as autologous chondrocyte transplantation. However, despite these advancements, infections associated with cartilage implants remain a persistent challenge, compromising the success of surgeries and patient recovery. To address these challenges, this review provides a comprehensive foundation for researchers interested in addressing infections in CTE. It begins by briefly outlining the major scaffolds currently used in CTE and distinguishing those with antimicrobial properties. Among the antimicrobial scaffolds identified, chitosan and chondroitin sulfate stand out for their promising compatibility and antibacterial properties. The review then explores additives that meet three essential criteria: compatibility with chondrocytes, suitability for use in CTE scaffolds, and antibacterial efficacy. Chitosan, zinc oxide, silver, and copper emerge as leading candidates due to their compatibility with chondrocytes and proven antibacterial capabilities. Importantly, the criteria used in this review were chosen to provide researchers with a practical and reliable starting point for immediate application. However, it is acknowledged that other promising antibacterial modifications such as fabrication processes and additives such as bioactive glass and graphene oxide, which may not fit these criteria, also hold potential for future research and innovation. This review underscores the need for further research and development to enhance infection control measures and improve patient outcomes.

US Medical Schools' 2024 Commencements and Antisemitism: Addressing Unprofessional Behavior.

Antisemitism and antisemitic incidents have been increasing in United States medical institutions since the Hamas attack of October 7, 2023. Such incidents include anecdotal reports of antisemitic displays at medical school commencements. This study examined unprofessional behavior observed at the commencement ceremonies of the 25 US medical schools top-ranked for research excellence. This issue is significant since these graduates are expected to become future leaders in the field of medicine. Based on publicly available videotaped commencements, we assessed the number of students in the graduating classes wearing non-school-provided regalia, carrying signs, wearing protest buttons, or engaging in verbal protests related to the Israel-terror groups conflict that were either openly antisemitic or potentially offensive or insensitive. Symbols representing antisemitic themes (keffiyehs and three-part graduation stoles conveying antisemitic messages) were worn by students at just over half (13) of the medical schools. The mean number of students in each school wearing keffiyehs or non-official school stoles was 4.0 (95% confidence interval [CI] 2.2-5.8), ranging from 0%-13% of the classes, or 2.5% of the overall graduating cohort. The wearing of buttons, carrying of banners or signs, verbal protests interrupting the ceremony, or students deviating from script ranged from 0% to 22.5% of graduating students, with a mean of 2.7 per school (95% CI -0.8-6.2), or 1.7% of the medical schools graduating cohort. We identified unprofessional behavior at commencements of top-ranked medical schools consisting of antisemitism and displaying offensive and insensitive symbols and messaging. There is an urgent need for medical schools in the US to educate medical trainees about the dangers of antisemitism and all forms of hate and insensitivity.

Bibliometric analysis methods for the medical literature

A bibliometric analysis of medical literature provides valuable insights into the structure, trends, and impact of research in the medical field. It can be a critical tool for advancing knowledge, improving healthcare outcomes, and supporting strategic decisions in the medical and scientific communities. In this article, the authors describe a step-by-step approach on how to perform a bibliometric analysis of the medical literature, based on review of many different styles of bibliometric analyses in various fields of medicine and surgery.

Rapid and Sensitive Detection of Mutations in SARS-CoV-2 by Surface-Enhanced Raman Spectroscopy.

Since the outbreak of the novel coronavirus (SARS-CoV-2), the world has suffered significant losses. At present, the pneumonia disease caused by SARS-CoV-2 virus has not been eliminated, and SARS-CoV-2 has a high mutation rate, and its variant strains also have a high prevalence rate, which has always threatened the health of all mankind. This study aims to develop a rapid and sensitive method to complement existing SARS-CoV-2 diagnostic tools by utilizing surface-enhanced Raman spectroscopy (SERS) for the direct detection of the intrinsic SERS signal from the S proteins of SARS-CoV-2 and its variants (Omicron and Delta) within 5 min using a portable Raman spectrometer. The linear range of S protein detection of Wild-type, Omicron and Delta variants ranged from 1.0 × 10-7 to 1.0 × 10-3 g·mL-1, the limits of detection (LOD) were down to ∼10-8 g·mL-1 level. Our proposed method uses portable Raman spectrometer for direct detection, which is characterized by its simplicity, rapidity, portability, and wide applicability. It enables simultaneous detection of diverse mutated targets, thereby playing a pivotal role in the early diagnosis of viral diseases. Moreover, it holds promising prospects in the fields of chemistry, biology, and medicine.

Analysis of the Quality of Patient Treatment Data in MIMIC-IV Using Alpha, Heuristic, and Inductive Miner

MIMIC-IV (Medical Information Mart for Intensive Care IV), is a medical dataset used for research in the fields of medicine and health computer science. This dataset contains health information collected from intensive care units (ICUs) at the Beth Israel Deaconess Medical Center in Boston, MA. This research uses process mining to analyze data quality of patient treatment in the MIMIC-IV dataset using the Alpha Miner, Heuristic Miner, and Inductive Miner algorithms. It begins with planning and justification, followed by database reconstruction, data quality assessment, and data extraction, leading to the development of a control flow model. Subsequently, conformance checking is performed, and the study concludes with an evaluation of the results. It is expected that the results of this study will provide a better understanding of the quality of patient care process data in the MIMIC-IV dataset and a positive contribution to developing more effective health services.

EEG-derived brainwave patterns for depression diagnosis via hybrid machine learning and deep learning frameworks

In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040. For early diagnosis, a patient-friendly, cost-effective approach based on readily observable and objective indicators is essential. The objective of this research is to develop machine learning and deep learning techniques that utilize electroencephalogram (EEG) signals to diagnose depression. Different statistical features were extracted from the EEG signals and fed into the models. Three classifiers were constructed: 1D Convolutional Neural Network (1DCNN), Support Vector Machine (SVM), and Logistic Regression (LR). The methods were tested on a dataset comprising EEG signals from 34 patients with Major Depressive Disorder (MDD) and 30 healthy subjects. The signals were collected under three distinct conditions: TASK, when the subject was performing a task; Eye Close (EC), when the subject’s eyes were closed; and Eye Open (EO), when the subject’s eyes were open. All three classifiers were applied to each of the three types of signals, resulting in nine (3 × 3) experiments. The results showed that TASK signals yielded the highest accuracies of 88.4%, 89.3%, and 90.21% for LR, SVM, and 1DCNN, respectively, compared to EC and EO signals. Additionally, the proposed methods outperformed some state-of-the-art approaches. These findings highlight the potential of EEG-based approaches for the clinical diagnosis of depression and provide promising avenues for further research. Additionally, the proposed methodology demonstrated statistically significant improvements in classification accuracy, with p-values < 0.05, ensuring robustness and reliability.

Reimagining Physician Assistant Education: Championing Cognitive Diversity to Promote Inclusivity, Neurodiversity Awareness, and a Sense of Belonging.

Neurodiversity, encompassing conditions such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and dyslexia, represents a significant and often under-recognized segment of the population, including within science, technology, engineering, mathematics, and medicine fields like medicine. Neurodiverse individuals possess unique skills, including enhanced creativity, analytical thinking, and meticulous attention to detail, which are valuable in health care professions. However, failure to recognize and support these individuals can result in missed opportunities, social isolation, and mental health challenges. Despite a growing emphasis on diversity, equity, inclusion, and belonging in higher education, neurodiversity is frequently overlooked, particularly in physician assistant (PA) education. This article examines the unique challenges faced by neurodiverse PA student learners and the existing literature gap regarding neurodiversity in PA education. It underscores the need for greater awareness, reduced stigma, and improved support systems. Recommendations include integrating neurodiversity into the PA curriculum, providing faculty training on inclusive teaching practices, and establishing tailored accommodations to foster a sense of belonging. PA programs can foster a more equitable health care system by creating inclusive learning environments that acknowledge and cater to the unique needs of neurodiverse student learners, thereby enhancing student-faculty interactions and promoting academic success. The aim of this article was to facilitate the reimagining of PA education to champion cognitive diversity. By promoting a more inclusive learning environment, PA programs can cultivate future clinicians who are better equipped to serve diverse patient populations.

Umbilical Cord-derived Mesenchymal Stem Cells (CLV-100) Infusion in Healthy Subjects: a 5-Year Follow-up Study on Safety and Immunomodulatory Effect

Abstract Purpose Umbilical cord-derived mesenchymal stem cells (UCMSCs) have garnered significant attention in the field of regenerative medicine, specifically in inflammation-related diseases. Our team has previously demonstrated that a single infusion of allogeneic UCMSCs by Cytopeutics® (CLV-100), at both low dose (65 million cells) and high dose (130 million cells), in 11 healthy volunteers was safe up to 6 months with a dose-dependent immunomodulatory effect. In this present follow-up study, we investigated the medium-term safety and efficacy of intravenous administration of CLV-100 in the same healthy subjects. Methods All 11 subjects were enrolled in this 5-year follow-up, and none dropped out (NMRR-13–1152-17400, 28/09/2016). Clinicians conducted consultations to assess overall health indicators. Blood samples and serum were collected for laboratory testing and biomarker analysis, respectively. Results Five years after the CLV-100 infusion, all subjects remained healthy, with no reported side effects or major health conditions. Levels of cancer markers also remained within normal ranges. The anti-inflammatory effect of CLV-100 remained statistically significant in the high-dose group. Notably, major organ health parameters, including those subjects aged over 60 years, remained stable even after 5 years. Conclusion The findings demonstrated the medium-term safety of a single CLV-100 infusion and persistent dose-dependent immunomodulatory effects. CLV-100 may also confer protection against age- and inflammation-related frailty. Lay Summary The current follow-up study provides insight into the safety and immunomodulatory effects of a single infusion of allogeneic umbilical cord-derived mesenchymal stem cells (CLV-100) for up to 5 years in healthy subjects. The effects on the inflammatory cytokines CLV-100 were more pronounced in the high-dose group. In addition, other biomarker levels were comparable between the older and younger age groups. CLV-100 is therefore safe over the medium-term with sustained anti-inflammatory effect in a dose-dependent manner.

Gene mining, recombinant expression and enzymatic characterization of N-acetylglucosamine deacetylase

Abstract Objectives Glucosamine (GlcN) is an important bioactive substance that is widely used in medicine, dietary supplements, cosmetics, and other fields. The traditional method of producing GlcN is mainly through chitosan hydrolysis catalyzed by strong acid, but this process is usually accompanied by environmental pollution and high energy consumption. Therefore, the development of green and efficient production methods of glucosamine has become the focus of current research. Methods In this study, N-acetylglucosamine (GlcNAc) was used as the substrate to facilitate the enzymatic synthesis of GlcN by deacetylase. Four deacetylases (TkDAc, PkDAc, PpDAc and AbDAc) were selected from marine thermophilic microorganisms, and Escherichia coli (E. coli) was used as the host for recombinant expression. Results The soluble expression of PpDAc was poor, so several groups of solubilizing labels were tried, and the results showed that the soluble expression of recombinant plasmid ArsC-PpDAc carrying pro-solubilization labels was greatly improved. Conclusions The effects of temperature and pH on enzyme activity were investigated by single factor analysis. Kinetic parameters further revealed that ArsC-PpDAc exhibited the highest catalytic activity, with a Kcat/Km value of 7.29, and achieved a conversion rate of over 95 %. The condition of ArsC-PpDAc was optimized, and the results showed that ArsC-PpDAc showed good tolerance to organic solvents, and its catalytic activity was not significantly affected.

Bayesian method for comparing F1 scores in the absence of a gold standard

ABSTRACT In the field of medicine, evaluating the diagnostic performance of new diagnostic methods can be challenging, especially in the absence of a gold standard. This study proposes a methodology for assessing the performance of diagnostic tests by estimating the posterior distribution of the F 1 score using latent class analysis, without relying on a gold standard. The proposed method utilizes Markov Chain Monte Carlo sampling to estimate the posterior distribution of the F 1 score, enabling a comprehensive evaluation of diagnostic test methods. By applying this method to internet addiction, we demonstrate how latent class analysis can be effectively used to assess diagnostic performance, offering a practical solution for situations where no gold standard is available. The effectiveness of the proposed approach was evaluated through simulation studies by examining the coverage probability of the 95% highest density interval of the estimated posterior distributions.

Clinical characteristics and cause analysis of false-positive results in treponemal testing among patients

Background Currently, there is a dearth of systematic research data on the phenomenon of false-positive reactions in treponemal tests. The aim of this study is to analyze the clinical characteristics and influencing factors associated with false-positive treponemal tests in patients, so as to enhance the diagnostic accuracy of syphilis and mitigate misdiagnosis-induced incorrect treatment. Methods From January 2017 to December 2023, a total of 759 cases with false-positive results for treponema were screened for blood transfusion, surgery, or other medical interventions at Jinling hospital. The demographic, clinical, and laboratory characteristics of patients were retrospectively analyzed to identify the risk factors associated with false-positive reactions in treponemal antibody screening. Results The results indicated that individuals under 18 years old, over 45 years old and males exhibited a higher false-positive rate for treponemal tests (p < 0.001). The false-positive rates of treponema were found to be higher in the fields of pediatrics, nephrology, and internal medicine (p < 0.05). There was no difference observed in ABO blood group distribution (p > 0.05). .Furthermore, the levels of treponema antibody and coagulation function were found to be associated with the occurrence of false-positive syphilis test results. Multivariate logistic regression analysis indicated that ≤18 years, ≥45 years, male were independent risk factors (p < 0.01). Conclusion This study demonstrates that the false-positive rate of treponemal tests can be increased by factors such as age, gender, immune diseases, and coagulation disorders. The treponemal antibodies titer level is a valuable reference for assessing false-positive results. To enhance the accuracy of syphilis diagnosis, multiple risk factors should be considered when interpreting results from treponemal tests.

Attitudes toward artificial intelligence and robots in healthcare in the general population: a qualitative study

BackgroundThe growth of the use of artificial intelligence (AI) and robotic solutions in healthcare is accompanied by high expectations for improved efficiency and quality of services. However, the use of such technologies can be a source of anxiety for patients whose expectations and experiences with such technology differ from medical staff's. This study assessed attitudes toward AI and robots in delivering health services and performing various tasks in medicine and related fields in Polish society.Methods50 semistructured in-depth interviews were conducted with participants of diversified socio-demographic profiles. The interviewees were initially recruited for the interviews in a convenience sample; then, the process was continued using the snowballing technique. The interviews were transcribed and analyzed using the MAXQDA Analytics Pro 2022 program (release 22.7.0). An interpretative approach to qualitative content analysis was applied to the responses to the research questions.ResultsThe analysis of interviews yielded three main themes: positive and negative perceptions of the use of AI and robots in healthcare and ontological concerns about AI, which went beyond objections about the usefulness of the technology. Positive attitudes toward AI and robots were associated with overall higher trust in technology, the need to adequately respond to demographic challenges, and the conviction that AI and robots can lower the workload of medical personnel. Negative attitudes originated from convictions regarding unreliability and the lack of proper technological and political control over AI; an equally important topic was the inability of artificial entities to feel and express emotions. The third theme was that the potential interaction with machines equipped with human-like traits was a source of insecurity.ConclusionsThe study showed that patients' attitudes toward AI and robots in healthcare vary according to their trust in technology, their recognition of urgent problems in healthcare (staff workload, time of diagnosis), and their beliefs regarding the reliability and functioning of new technologies. Emotional concerns about contact with artificial entities looking or performing like humans are also important to respondents' attitudes.

Abstract A006: Using ChatGPT to solve clinical radiobiology problems

Abstract ChatGPT is a powerful large language model and has been applied to many fields in medicine. Radiobiology is the key in the determining of radiation dose in radiation oncology. We would like to test the efficacy of using ChatGPT in clinical radiobiology. A set of 30 clinical radiobiology questions were used in this study. OpenAI API was used to query GPT-4O and generate corresponding answers (Access Date: 2024/6/26). Five different prompts (involving role-playing, role-playing with in-context learning, chain of thought, chain of thought with in-context training, and in-context training) and no prompt were used to test the ability of the model. Questions were further divided into two subgroups, 15 questions without alpha-beta ratio and 15 questions with alpha-beta ratio(s). Answers were graded using the below grading system: Grade 1: totally incorrect; Grade 2: partially correct (either answer or calculation process is correct); Grade 3: totally correct (both answer and calculation process are correct). The chi-square test was used to compare results between different situations. R studio and R language were used in the statistical analysis; p &amp;lt;0.05 is set as statistically significant. The detailed results for each prompt are shown below: No prompt(grade 1: 9, grade 2: 3, grade 3: 18), role-playing (grade 1: 7, grade 2: 6, grade 3: 17), role-playing with in-context learning(grade 1: 10, grade 2: 7, grade 3: 13), chain of thought(grade 1: 10, grade 2: 5, grade 3: 15), chain of thought with in-context learning(grade 1: 11, grade 2: 2, grade 3: 17), and in-context learning(grade 1: 10, grade 2: 4, grade 3: 16). For grade 1 versus grade 2-3, Chi-square test showed p-value = 0.6708, and for grade 1-2 versus grade 3, chi-square test showed p-value = 0.829. That meant that the performances were similar regardless of the prompt. The detailed results for two question types are shown below: questions without alpha-beta ratio (grade 1: 53, grade 2: 10, grade 3: 27), questions with alpha-beta ratio(s) (grade 1: 4, grade 2: 17, grade 3: 69). For grade 1 versus grade 2-3, Chi-square test showed p-value &amp;lt;0.01, and for grade 1-2 versus grade 3, chi-square test showed p-value &amp;lt;0.01. That meant that the performances were different between question with and without alpha-beta ratio(s). In conclusion, without prompting, ChatGPT can correct about 60% of questions. Using different prompts cannot enhance performance. ChatGPT can perform well in questions with alpha-beta ratio(s). Citation Format: Yung-Shuo Kao, Che-Wei Su, Kun-Yao Dai. Using ChatGPT to solve clinical radiobiology problems. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr A006.

Technical considerations and review of urinary microRNAs as biomarkers for chronic kidney disease in dogs and cats.

MicroRNAs (miRNAs or miRs) are small, non-coding RNAs that play a crucial role in gene regulation, making them potential biomarkers for various diseases. In the field of veterinary medicine, there is a growing interest in exploring the diagnostic and therapeutic potential of miRNAs in kidney diseases affecting dogs and cats. This review focuses on the use of urinary miRNAs as biomarkers for chronic kidney disease (CKD) in these companion animals. We introduce miRNAs, their biogenesis, and their presence in biofluids, particularly within exosomes, and discuss studies investigating miRNAs in kidney tissue and urine. We acknowledge the challenges associated with miRNA studies, including preanalytical factors such as biological variation, sample collection/processing, storage conditions, and experimental design. We highlight the importance of technical considerations, such as sample pooling, sequencing depth, multiplexing, and the various steps of the miRNA experimental workflow. Furthermore, we discuss RNA isolation methods, small RNA sequencing data analysis, and the use of quantitative reverse transcription PCR (qRT-PCR) and droplet digital PCR for verification. We emphasize the importance of internal controls, spike-ins, and normalization methods to minimize technical variation and ensure reliable results in qRT-PCR analysis. This review concludes that while urinary miRNAs hold promise as non-invasive biomarkers for CKD in dogs and cats, addressing the challenges and standardization of protocols is vital for the successful translation of this research into clinical practice.

Laboratory animals anesthesia recommendations for biomedical research purposes

Anesthesia is widely used in experimental biomedical research to anesthetize and immobilize laboratory animals during surgical interventions and experimental procedures. In contrast to clinical and veterinary anesthesiology, an important aspect of anesthesia in laboratory animals is to minimize the effect of anesthetics on the results of the study. On November 19, 2022, the IV Scientific and Practical Conference “Experimental Surgery, Anesthesiology and Reanimatology of Laboratory Animals” was held in Moscow, where the community of specialists in the field of laboratory animal science, experimental surgery, pathophysiology, veterinary medicine, clinical and veterinary anesthesiology discussed various aspects of anesthesia in laboratory animals. This review is based on the conference proceedings and is devoted to general issues of animal anesthesia, its technological aspects (methods, equipment and consumables), consideration of advantages and disadvantages of the most commonly used inhalation and injection anesthetics.The advantages and schemes of modern combined anesthesia are substantiated, in particular, the need for adequate intraoperative analgesia and the possibility of regional anesthesia. The use of obsolete and non-recommended drugs is also discussed. The review and recommendations have a practical orientation and are intended for biomedical researchers who use laboratory animals in basic, translational and regulated preclinical studies.

Bibliometric analysis of literature on natural medicines against chronic kidney disease from 2001 to 2024.

Chronic kidney disease (CKD) is a globally common and progressive disease. There has been few bibliometric study to analyze the status, hot spots, and trends in the field of natural medicines (NMs) against CKD. To comprehensively understand the status, hot spots, and trends in the field of NMs against CKD. The documents concerning NMs against CKD are extracted from the Web of Science Core Collection database (WOSCC). The literature analysis was conducted using VOSviewer 1.6.20 and CiteSpace 6.3.R1 software. In total, 641 publications were encompassed, which were produced by 3 548 authors and 823 organizations, 241 journals, and 56 countries/regions. The most productive author, institution, country, and journal were Li, Ping, Nanjing University of Chinese Medicine, China, and Journal of Ethnopharmacology, respectively. The first high-cited article was published in Medicinal Research Reviews with 457 citations authored by Huang and colleagues in 2007. Oxidative stress, anti-inflammatory, renal fibrosis, and gut microbiota were the emerging keywords. Rhubarb, Astragalus, Angelica, and Cordyceps, which contain anthraquinones, cordycepin, adenosine, or various polysaccharides, are promising NMs to prevent or treat CKD. Currently, the main hot spot is the elucidation of cellular and molecular mechanisms using novel technologies such as network pharmacology, molecular docking, and experimental validation. Future studies are needed to focus on the inherent molecular mechanisms and clinical applications. In addition, potential side effects of the bioactive compounds cannot be ignored.

Comparison of brain activity metrics in Chinese and Russian students while perceiving information referencing self or others

Neurocomputing technology is a field of interdisciplinary research and development widely applied in modern digital medicine. One of the problems of neuroimaging technology is the creation of methods for studying human brain activity in socially oriented conditions by using modern information approaches. The aim of this study is to develop a methodology for collecting and processing psychophysiological data, which makes it possible to estimate the functional states of the human brain associated with the attribution of external information to oneself or other people. Self-reference is a person’s subjective assessment of information coming from the external environment as related to himself/herself. Assigning information to other people or inanimate objects is evaluating information as a message about someone else or about things. In modern neurophysiology, two approaches to the study of self-referential processing have been developed: (1) recording brain activity at rest, then questioning the participant for self-reported thoughts; (2) recording brain activity induced by self-assigned stimuli. In the presented paper, a technology was tested that combines registration and analysis of EEG with viewing facial video recordings. The novelty of our approach is the use of video recordings obtained in the first stage of the survey to induce resting states associated with recognition of information about different subjects in later stages of the survey. We have developed a software and hardware module, i. e. a set of related programs and procedures for their application consisting of blocks that allow for a full cycle of registration and processing of psychological and neurophysiological data. Using this module, brain electrical activity (EEG) indicators reflecting individual characteristics of recognition of information related to oneself and other people were compared between groups of 30 Chinese (14 men and 16 women, average age 23.2 ± 0.4 years) and 32 Russian (15 men, 17 women, average age 22.1 ± 0.4 years) participants. We tested the hypothesis that differences in brain activity in functional rest intervals between Chinese and Russian participants depend on their psychological differences in collectivism scores. It was revealed that brain functional activity depends on the subject relevance of the facial video that the participants viewed between resting-state intervals. Interethnic differences were observed in the activity of the anterior and parietal hubs of the default-mode network and depended on the subject attribution of information. In Chinese, but not Russian, participants significant positive correlations were revealed between the level of collectivism and spectral density in the anterior hub of the default-mode network in all experimental conditions for a wide range of frequencies. The developed software and hardware module is included in an integrated digital platform for conducting research in the field of systems biology and digital medicine.

Real world efficacy of omalizumab in reducing surgical intervention for nasal polyps in Samter’s triad

The advancements in the field of medicine, particularly in the field of drug application, has told us that Omalizumab has a significant impact on the management of nasal polyps, especially in the context of Samter’s triad. Our letter highlights the role of omalizumab in reducing the surgical interventions for nasal polyps which has been a longstanding challenge in the population in the past.