Field Of Clinical Medicine Research Articles

Human exposure pathways to poly- and perfluoroalkyl substances (PFAS) from indoor media: A systematic review protocol

BackgroundHuman exposure to per- and polyfluoroalkyl substances (PFAS) has been primarily attributed to contaminated food and drinking water. However, additional PFAS exposure pathways have been raised by a limited number of studies reporting correlations between commercial and industrial products and PFAS levels in human media and biomonitoring. Systematic review (SR) methodologies have been widely used to evaluate similar questions using an unbiased approach in the fields of clinical medicine, epidemiology, and toxicology, but the deployment in exposure science is ongoing. Here we present a systematic review protocol that adapts existing systematic review methodologies and study evaluation tools to exposure science studies in order to investigate evidence for important PFAS exposure pathways from indoor media including consumer products, household articles, cleaning products, personal care products, plus indoor air and dust. ObjectivesWe will systematically review exposure science studies that present both PFAS concentrations from indoor exposure media and PFAS concentrations in blood serum or plasma. Exposure estimates will be synthesized from the evidence to answer the question, “For the general population, what effect does exposure from PFAS chemicals via indoor media have on blood, serum or plasma concentrations of PFAS?” We adapt existing systematic review methodologies and study evaluation tools from the U.S. EPA’s Systematic Review Protocol for the PFBA, PFHxA, PFHxS, PFNA, and PFDA IRIS Assessments and the Navigation Guide for exposure science studies, as well as present innovative developments of exposure pathway-specific search strings for use in artificial intelligence screening software. Data SourcesWe will search electronic databases for potentially relevant literature, including Web of Science, PubMed, and ProQuest. Literature search results will be stored in EPA’s Health and Environmental Research Online (HERO) database. Study eligibility and criteriaIncluded studies will present exposure measures from indoor media including consumer products, household articles, cleaning products, personal care products, plus indoor air and dust, paired with PFAS concentrations in blood, serum or plasma from adults and/or children in the general population. We focus on a subset of PFAS chemicals including perfluorooctanoic acid (PFOA), perfluorooctanesulfonate (PFOS), perfluorobutanoic acid (PFBA), perfluorobutane sulfonate (PFBS), perfluorodecanoic acid (PFDA), perfluorohexanoic acid (PFHxA), perfluorohexanesulfonate (PFHxS), and perfluorononanoic acid (PFNA). Study appraisal and synthesis methodsStudies will be prefiltered at the title and abstract level using computationally intelligent search strings to expedite the screening process for reviewers. Two independent reviewers will screen the prefiltered studies against inclusion criteria at the title/abstract level and then full-text level, after which the reviewers will assess the studies’ risk of bias using an approach modified from established systematic review tools for exposure studies. Exposure estimates will be calculated to investigate the proportion of blood, serum or plasma) PFAS concentrations that can be explained by exposure to PFAS in indoor media.

Global research hot points on cardiovascular disease--bibliometric analysis based on the ESI hot papers

With the heavier burden of cardiovascular disease, an abundance of papers emerge every year in the research hotspots, which cover a wide range of types and content. In order to let readers interested in the cardiovascular field quickly understand the research hotspots and research frontier, it is necessary to sort out and summarize the research topic in time. According to the discipline classification, we screened papers in cardiovascular field from the Essential Science Indicators (ESI) hot papers published in 2019. Methods such as bibliometrics, statistical description, hierarchical induction, analysis and interpretation were used a step further to reveal the context and characteristics of research in the field of cardiovascular diseases, summarize the latest progress and development direction in this field, and provide information and hints for the expansion of future research directions. A total of 297 papers were finally included, which were mainly in the field of clinical medicine; The country with the most publications was the United States, while China ranked the fifth in terms of contribution; the research institution with the highest number of published papers was Harvard University; the New England Journal of Medicine (NEJM) has published the most papers, with contribution also from journals such as Circulation, Europe Heart Journal, JAMA, and Lancet. All the papers were categorized into disease burden, disease risk, drug treatment, device treatment and surgical treatment, clinical diagnosis, basic research and others, so as to review and summarize the research front in the field of cardiovascular diseases.

Intelligent analytical system as a tool to ensure the reproducibility of biomedical calculations

The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. At the conditions of pandemic, the success of health care system depends significantly on the regular implementation of effective research tools and population monitoring. The earlier the risks of disease can be identified, the more effective process of preventive measures or treatments can be. This publication is about the creation of a prototype for such a tool within the project «Development of methods, algorithms and intelligent analytical system for processing and analysis of heterogeneous clinical and biomedical data to improve the diagnosis of complex diseases» (M/99-2019, M/37-2020 with support of the Ministry of Education and Science of Ukraine), implementted by the V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, together with the United Institute of Informatics Problems, National Academy of Sciences of Belarus (F19UKRG-005 with support of the Belarussian Republican Foundation for Fundamental Research). The insurers, entering the market, can insure mostly low risks by facilitating more frequent changes of insurers by consumers (policyholders) and mixing the overall health insurance market. Socio-demographic variables can be risk adjusters. Since age and gender have a relatively small explanatory power, other socio-demographic variables were studied – marital status, retirement status, disability status, educational level, income level. Because insurers have an interest in beneficial diagnoses for their policyholders, they are also interested in the ability to interpret relevant information – upcoding: insurers can encourage their policyholders to consult with doctors more often to select as many diagnoses as possible. Many countries and health care systems use diagnostic information to determine the reimbursement to a service provider, revealing the necessary data. For processing and analysis of these data, software implementations of construction for classifiers, allocation of informative features, processing of heterogeneous medical and biological variables for carrying out scientific research in the field of clinical medicine are developed. The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. Particularly, attention is paid to containerization of biomedical applications (Docker, Singularity containerization technology), this permits to get reproducibility of the conditions in which the calculations took place (invariability of software including software and libraries), technologies of software pipelining of calculations, that allows to organize flow calculations, and technologies for parameterization of software environment, that allows to reproduce, if necessary, an identical computing environment. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. The experience of using the developed linear classifier, gained during its testing on artificial and real data, allows us to conclude about several advantages provided by the containerized form of the created application: it permits to provide access to real data located in cloud environment; it is possible to perform calculations to solve research problems on cloud resources both with the help of developed tools and with the help of cloud services; such a form of research organization makes numerical experiments reproducible, i.e. any other researcher can compare the results of their developments on specific data that have already been studied by others, in order to verify the conclusions and technical feasibility of new results; there exists a universal opportunity to use the developed tools on technical devices of various classes from a personal computer to powerful cluster.

ANTIBACTERIAL AND ANTI-FUNGAL EFFECT OF ANTISEPTIC PREPARATION “CIDIPOL”

The increase in resistance of pathogenic microflora to antibiotics over the world has become one of the challenges for biomedical science. Therefore, further development of antimicrobials and their use in various fields of medicine are extremely important. There are a wide range of antiseptic preparations in different fields of clinical medicine (octenisept, eludril, triclosan, myramistin, chlorhexidine, bigluconate-syn. hexinone, hibiscrab, hibitsan, eugel, fervex and others) in our country today. In 1985 the researchers of the Department of Skin and Sexually transmitted diseases, UMSA, created an antiseptic for treating venereal diseases. The name "Cidipol", proposed by the author, prof. V. G. Kravchenko, was approved by the Nomenclature Commission of the Pharmacological Committee, the Ministry of Public Health of the former USSR. The medicine as an invention was registered at the International Patent Centre (Geneva, Switzerland), and patents for the invention were obtained in Ukraine, the USA and the Russian Federation. In the United States, the drug has been reported as a preparation for individual prevention of sexually transmitted diseases and the treatment of urogenital trichomoniasis in women. Considering that antiseptics can produce an effect on the wide range of microbial flora, it is quite relevant to study the effect produced by Cidipol on certain types of bacteria and fungi. The purpose of the study was to investigate the fungicidal and bactericidal action of Cidipol on a number of gram-negative and gram-positive microorganisms. The study was carried out at the Department of Microbiology, Virology and Immunology, UMSA; we used museum strains of the following microorganisms: C.albicans ATCC10231, E.coli ATCC25922, S.aureus ATCC25923, E.faecalis ATCC29213, M.luteus ATCC4698, S.epudermidis ATCC14990. The antibacterial composition, prepared ex tempore according to the prescription "Cidipol", was used: 0.3% ciminal (p-nitro-alpha-chloride aldehyde), 5.0% dimexide, 94.7% polyethylene oxide. The investigated museum strains of C.albicans ATCC10231, S.aureus ATCC25923, E.coli ATCC25922, were found out to be sensitive to the effect of Cidipol; the fungicidal effect of the Cidipol composition exceeded its bactericidal effect in 4 times. The strains of E.faecalis, M.luteus, and S.epidermidis were the least sensitive. Conclusions. The results of the studies have demonstrated the presence of pronounced antimicrobial effect of Cidipol to museum microorganism strains with different levels of sensitivity.

The mechanisms of antibiotic resistance in major pathogens of purulent-inflammatory complications in cancer patients

The problem of microbial antibiotic resistance and investigation of its underlying mechanisms is of paramount importance for all fields of clinical medicine, including oncology. The aim of the study was to examine the mechanisms of antibiotic resistance for major pathogens causing purulent-inflammatory complications in cancer patients. Materials and methods. In 2012—2015 there was conducted a prospective examination of 184 cancer patients, including 67 patients at the Department of Surgery no. 1 and 117 patients at the Intensive Care Unit of the Krasnoyarsk Regional Clinical Oncology Center named after A.I. Kryzhanovsky. For this, we collected bronchoalveolar lavage fluid, wound discharge and investigated the material by using bacteriological method, as well as MALDI-TOF. Antibiotic sensitivity was studied as follows: disco-diffusion, double disc method, carbapenem inactivation method, staphylococcal sensitivity — by screening method, PCR, E-test method, and serial dilutions in Muller-Hinton broth. Genotyping and antibiotic resistance mechanisms study were performed by using PCR, M-PCR, and sequencing. The WHONET program (WHO) was used, with significance level set at p 0.05. Results. Microbiological examination of bronchoalveolar lavage fluid and wound discharge samples allowed to uncover prevalent associations of multi-resistant (MDR) and extremely resistant pathogens (XDR). The microflora of the lower respiratory tract and in the wound secretion in cancer patients were found to be dominated by non-fermenting Gram-negative bacteria reaching up to 44.5% and 48%, respectively; as well as order Enterobacteriales found in 24% and 34.9%, respectively; Gram-positive bacteria — 24% and 17.1%, respectively. Imipenem- and/or meropenem-resistant P. aeruginosa and A. baumannii, K. pneumoniae strains, were assessed for MBL production phenotypically, as well as the genes of the most common VIM, IMP types, whereas A. baumannii — for OXA-23, OXA-40, and OXA-58; and K. pneumoniae — for OXA-48. 20 strains and 16 strains of P. aeruginosa and A. baumannii, respectively, were studied by PCR. It was found that A. baumannii strains formed no MBL, but 56.3% of A. baumannii isolates (9 strains) produced OXA-23 and OXA-40 carbapenemases. Among P. aeruginosa strains there were three of them which possessed VIM (15.0%), whereas the remaining strains formed no MBL, but were resistant to carbapenems being associated with other resistance mechanisms, e.g. efflux, decreased permeability of cell wall etc. Among 6 isolates of K. pneumoniae, 1 strain produced OXA-48. In cancer patients, the percentage of methicillin-resistant strains among all members of the genus Staphylococcus was 48.9% (4 strains belonged to MRSA). PVL- MRSA strains belonged to the clones ST239/spa3(t037)/SCCmecIIIA/tst,sek,seq+ (75%) and ST8/ spa1(t008)/SCCmecIVc/sea+ (25%). MRSA ST239 showed multiple antibiotic resistance: to aminoglycosides (aacA-aphD, aadD genes were detected), linkcosamides/macrolides (the ermA gene was detected), fluoroquinolones (mutations in the GyrA gene — Ser84Leu; in GrlA- Ser80Phe), rifampicin (MIC more than 128 gg/ml; mutations in the rpoB gene are His481Asn, Ile527Met), sulfamethoxazole, tetracycline (tetM gene), and chloramphenicol (66.7% of isolates, the cat gene encoding chloramphenicol acetyl transferase was detected); but sensitive to vancomycin (MIC 1.0 gg/ ml), linezolid in 100% of cases. MRSA ST8 are resistant to aminoglycosides (aacA-aphD, aadD genes), lincosamides/macrolides (ermC gene), tetracyclines (tetK gene), chloramphenicol (cat gene); and 100% sensitive to fluoroquinolones, rifampicin (MIC 0.006 gg/ml), sulfamethaxazole, vancomycin (MIC 1.0 gg/ml), daptomycin (MIC 0.094 gg/ml), linezolid (MIC 0.75 gg/ml). Conclusion. Thus, it was found that members of the order Enterobacteriales, A. baumannii, P. aeruginosa and MRSA retain high resistance to a large number of antibacterial drugs of almost all classes. These data should be taken into account while choosing proper antibiotic therapy, as well as controlling spread of nosocomial infections caused by multiresistant microorganisms.

A novel end-to-end 1D-ResCNN model to remove artifact from EEG signals

Electroencephalography (EEG) signals are an important tool in the field of clinical medicine, brain research and the study of neurological diseases. EEG is very susceptible to a variety of physiological signals, which brings great difficulties to the research and analysis of EEG signals. Therefore, removing noise from EEG signals is a key prerequisite for analyzing EEG signals. In this paper, a one-dimensional residual Convolutional Neural Networks (1D-ResCNN) model for raw waveform-based EEG denoising is proposed to solve the above problem. An end-to-end (i.e. waveform in and waveform out) manner is used to map a noisy EEG signal to a clean EEG signal. In the training stage, an objective function is often adopted to optimize the model parameters and in the test stage, the trained 1D-ResCNN model is used as a filter to automatically remove noise from the contaminated EEG signal. The proposed model is evaluated on the EEG signal from the CHB-MIT Scalp EEG Database, and the added noise signals are obtained from the database. We compared the proposed model with the independent of the composite analysis (ICA), the fast independent composite analysis (FICA),Recursive least squares(RLS) filter,Wavelet Transform (WT) and Deep neural network(DNN) models. Experimental Results show that the proposed model can yield cleaner waveforms and achieve significant improvement in SNR and RMSE.Meanwhile, the proposed model can also preserve the nonlinear characteristics of EEG signals.

Statistical methods to assess the prognostic value of risk prediction rules in clinical research.

Prognosis aims at estimating the future course of a given disease in probabilistic terms. As in diagnosis, where clinicians are interested in knowing the accuracy of a new test to identify patients affected by a given disease, in prognosis they wish to accurately identify patients at risk of a future event conditional to one or more prognostic factors. Thus, accurate risk predictions play a primary role in all fields of clinical medicine and in geriatrics as well because they can help clinicians to tailor the intensity of a treatment and to schedule clinical surveillance according to the risk of the concerned patient. Statistical methods able to evaluate the prognostic accuracy of a risk score demand the assessment of discrimination (the Harrell's C-index), calibration (Hosmer-May test) and risk reclassification abilities (IDI, an index of risk reclassification) of the same risk prediction rule whereas, in spite of the popular belief that traditional statistical techniques providing relative measures of effect (such as the hazard ratio derived by Cox regression analysis or the odds ratio obtained by logistic regression analysis) could be per se enough to assess the prognostic value of a biomarker or of a risk score. In this paper we provide a brief theoretical background of each statistical test and a practical approach to the issue. For didactic purposes, in the paper we also provide a dataset (n = 40) to allow the reader to train in the application of the proposed statistical methods.

New Machine Learning Applications to Accelerate Personalized Medicine in Breast Cancer: Rise of the Support Vector Machines.

Artificial intelligence, machine learning, health care robots, and algorithms for clinical decision-making are currently being sought after in diverse fields of clinical medicine and bioengineering. The field of personalized medicine stands to benefit from new technologies so as to harness the omics big data, for example, to individualize and accelerate cancer diagnostics and therapeutics in particular. In this overarching context, breast cancer is one of the most common malignancies worldwide with multiple underlying molecular etiologies and each subtype displaying diverse clinical outcomes. Disease stratification for breast cancer is, therefore, vital to its effective and individualized clinical care. The support vector machine (SVM) is a rising machine learning approach that offers robust classification of high-dimensional big data into small numbers of data points (support vectors), achieving differentiation of subgroups in a short amount of time. Considering the rapid timelines required for both diagnosis and treatment of most aggressive cancers, this new machine learning technique has important clinical and public applications and implications for high-throughput data analysis and contextualization. This expert review describes and examines, first, the SVM models employed to forecast breast cancer subtypes using diverse systems science data, including transcriptomics, epigenetics, proteomics, and radiomics, as well as biological pathway, clinical, pathological, and biochemical data. Then, we compare the performance of the present SVM and other diagnostic and therapeutic prediction models across the data types. We conclude by emphasizing that data integration is a critical bottleneck in systems science, cancer research and development, and health care innovation and that SVM and machine learning approaches offer new solutions and ways forward in biomedical, bioengineering, and clinical applications.

Is Regional Anesthesia Safe Enough in Suspected or Confirmed COVID-19 Patients?

COVID-19 is a new entity in the field of clinical medicine. In near future, anesthesiologists around the globe increasingly will encounter patients who need surgery and at the same time are suspected or confirmed cases of COVID-19. Planning for a safe anesthesia technique is inevitable.

In Pursuit of Slowness

In Pursuit of Slowness

Status of clinical toxicology education and ethics in medical care of poisoned patients in the Islamic Republic of Iran and a comparison with other countries.

Clinical toxicology is not recognized as a clinical speciality in Iran. After the chemical war gas attack by the Iraqi army against the Iranian troops in the 1980s, health professionals and Iranian authorities noticed the importance of this field in clinical medicine. Collaboration between the clinical toxicologists and toxicologists of pharmacy schools resulted in the establishment of the Iranian Society of Toxicology and Poisonings in 1991 and the National Board of Toxicology in 1993. Clinical toxicology fellowship was also formed as a joint collaboration between the toxicology and internal medicine boards in 2010. Medical doctors who specialized in clinical medicine are eligible to take the entrance examination of the fellowship. In spite of the advancement of clinical toxicology and increased number of acute poisonings and drug abuse, undergraduate teaching in this field is still lacking and being taught as part of the forensic medicine curriculum since 1952. There is a lack of an efficient national poison information and control centre (s) in Iran, and no action plan and practical efforts have been done for poisoning prevention. Therefore, the number of drug abuse and acute poisonings has increased over the past four decades and induced cultural, social and health problems. According to Iranian legal medicine organization reports, poisoning is the second-most occurring cause of unnatural death. The suicidal attempt is the most common method of acute poisoning in adults. Suicidal attempt including self-poisoning is not accepted in the Islamic point of view, and thus self-poisoning is mostly neglected and may not be treated appropriately in time in some regions of Iran. Accidental poisoning in children is also common in Iran and estimated to be between 20000 and 25000 cases annually over the recent years. In addition, social, cultural and economic problems have induced more health problems such as drug abuse and addiction even in children. Adulterated opium to lead for economic gaining has produced thousands of cases of lead poisoning over the past few years in nearly all opium addicts, which is still a major health problem in Iran. Ban on alcoholic beverages leads some people to make their own home-made spirits, which is unfortunately contaminated with methanol. Thousands of cases of methanol poisoning and even some epidemics have occurred over the past four decades in some parts of the country. Lack of availability of essential antidotes such as succimer and fomepizole has been a major problem for the effective treatment of poisoned patients. Despite the well-known fact that cases of poisoning and drug overdose constitute a significant proportion of hospital admissions in some developing countries, clinical toxicology education and medical care of the poisoned patients are lacking. Therefore, policymakers and health authorities should realize the importance of toxicology in clinical medicine. The Iranian Ministry of Health, medical care and Medical Education should implement clinical toxicology courses for medical students; establish effective national poisons information and control centres and advance clinical toxicology services for appropriate management of poisoned patients to improve public health and the overall health policy goals.

Hybrid installations for multimodal PET/SPECT/CT visualization in Ukraine and quality control in nuclear medicine

P.L. Shupyk National University of Health of Ukraine, Kyiv, Ukraine SI "O.O. Shalimov National Institute of Surgery and Transplantology of the NAMS of Ukraine", Kiev, Ukraine The article considers the prospects of using hybrid imaging methods (PET/SPECT/CT) and quality control in nuclear medicine. The quality control system is a comprehensive measure that involves the creation and implementation of quality guidelines, quality control programs, instructions and protocols for checking control parameters. A quality control audit is a measure that allows you to verify the proper functioning of the department, identify and eliminate errors and improve the quality of patient care. All technical parameters of the devices should be checked according to standardized protocols to ensure reproduction and comparability of results. The availability of additional equipment for inspections of control parameters must be provided in advance, as well as a set of actions aimed at maintaining the quality of equipment and its timely update in order to meet modern requirements. Due to the integration of SPECT, PET and CT modules, the multimodal system is used for use in various fields of clinical medicine, in particular in oncology, cardiology, endocrinology and neurology. The comprehensive implementation of a quality management system for diagnostic tests, as an end result, allows to increase the effectiveness of these tests (not only in nuclear medicine) and to guarantee "trust" in these methods. Key words: hybrid imaging, nuclear medicine, positron emission tomography, single-photon emission computed tomography, quality control.

Encapsulation and release of drug nanoparticles in functional polymeric vesicles.

We investigated the co-assembly of amphiphilic diblock copolymers in solutions containing drugs and functional nanoparticles using the dissipative particle dynamics (DPD) method. By controlling the size and the concentration of the functional nanoparticles, the length of the hydrophobic blocks, and the interaction parameters between the hydrophobic block/solvent and the functional nanoparticles, we obtained the desired aggregates to load drugs. The aggregates loaded with drugs can be disk-like micelles, sphere-like micelles and vesicles with functional nanoparticles on the surface. When the solvent environment changes, the drugs loaded in the functional vesicles can release into the solvent. The release content is critically dependent on the repulsive interaction between the drugs and the solvent. The dynamic curve of drug release is obtained. The result is in agreement with the experiments about drug release. Our studies showed that we can precisely control the formation of functional vesicles to load and release drugs. Loading drugs in the process of self-assembly and controlling the release have broad potential in the field of clinical medicine and adding functional nanoparticles can be of great help in drug delivery and medical diagnosis.

Growth through adversity: The impact of COVID-19 pandemic on the american college of academic international medicine

The COVID-19 pandemic has been especially challenging to the academic international medical (AIM) community. The impact on the field of clinical medicine has been the most pronounced, particularly in the way that education is provided and academic medicine is pursued by clinicians. With the goal of providing top quality, highly relevant content for our membership, the American College of Academic International Medicine (ACAIM) teamed up with our sister organizations, the World Academic Congress of Emergency Medicine (WACEM), the Global Research on Acute conditions Team (GREAT, Rome, Italy and Basel, Switzerland), and EMA-INDIA (Indirapuram, India). The goal of this truly global coalition was to jointly host weekly web meetings that focus on topics relevant to participating stakeholder communities, with additional focus on the ongoing COVID-19 pandemic. Summary of these efforts and outcomes is provided in this article.The following core competencies are addressed in this article: Interpersonal and communication skills; Professionalism; Practice-based learning and improvement

3D Printed Multi-Functional Hydrogel Microneedles Based on High-Precision Digital Light Processing.

Traditional injection and extraction devices often appear painful and cumbersome for patients. In recent years, polymer microneedles (MNs) have become a novel tool in the field of clinical medicine and health. However, the cost of building MNs into any shapes still remains a challenge. In this paper, we proposed hydrogel microneedles fabricated by high-precision digital light processing (H-P DLP) 3D printing system. Benefits from the sharp protuberance and micro-porous of the hydrogel microneedle, the microneedle performed multifunctional tasks such as drug delivery and detection with minimally invasion. Critical parameters for the fabrication process were analyzed, and the mechanical properties of MNs were measured to find a balance between precision and stiffness. Results shows that the stiffness and precision were significantly influenced by exposure time of each layer, and optimized printing parameters provided a balance between precision and stiffness. Bio-compatible MNs based on our H-P DLP system was able to execute drug injection and drug detection in our experiments. This work provided a low-cost and fast method to build MNs with 3D building, qualified the mechanical performance, drug injection, drug detection ability of MNs, and may be helpful for the potential clinical application.

Mussel inspired bio-adhesive with multi-interactions for tissue repair

Bio-adhesives based on biopolymers have been widely researched for tissue repair. However, the adhesive properties are still insufficient to meet the practical applications. Introducing functional groups into the polymer chains that have multi-interactions among inter/intra-molecules and with substrates is an efficient way to increase cohesion force and further improve the adhesive properties. In this study, 3,4-dihydroxyphenyl propionic acid (DPA) and dopamine (DA) containing adhesion functional catechol groups were employed to modify chitosan (CS) and γ-polyglutamic acid (γPGA), respectively. The substituted degrees of the catechol groups were controlled by the catechol compositions. DPA modified chitosan/DA modified γPGA (CS-DPA/γPGA-DA) adhesives prepared by mixing CS-DPA and γPGA-DA. Effects of the substituted degrees and substrates on the adhesion strength were measured by tensile testing machine. The results showed good adhesion property of the CS-DPA/γPGA-DA adhesive on many surfaces of the substrates. Especially on the arthrodial cartilage, the adhesive strength reached around 150 kPa, much higher than commercially available tissue adhesives. The high adhesion property might be due to the adhesion interactions between the catechol groups and substrates and the high cohesion forces induced by the crosslinking interactions formation among the catechol groups and the electrostatic interactions between the CS and γPGA polymers. In vitro experiments demonstrated that the adhesive had good biocompatibility. These results suggested the catechol-based adhesive is a very suitable and promising biomaterial in the clinical medicine field.

Research progress in the application status and development trend of artificial intelligence in the diagnosis and treatment of spinal disease

The cross-fusion research of artificial intelligence technology and spinal surgery represented by machine learning and neural network model is a new research direction and hot issue in the field of artificial intelligence in recent years. The anatomy and disease symptoms of the spine are complex, and the diagnosis and treatment of spinal surgery require rich clinical experience. However, the distribution of medical resources in China is seriously uneven. How to improve the ability of primary medical services so that the most extensive patient groups can benefitis still an urgent problem to be solved. Artificial intelligence is a technical science that researches and develops theories, methods, technologies, and application systems for simulating, extending and expanding human intelligence. With the advent of the era of big data medical technology, artificial intelligence technology may solve this problem by transforming experts sinking into tech sinking . At present, technologies such as confrontation learning, weakly supervised learning, intensive learning and graph neural networks have become research hotspots in the field of artificial intelligence, and have also played an important role in many fields of clinical medicine. Based on the advantages of deep learning and neural network in disease learning, many spine surgeons combine it with the diagnosis and treatment of cervical spondylosis, low back pain, lumbar degenerative diseases, spinal deformity, spinal tumors, and other spine-related diseases. The rapid location and accurate diagnosis of the disease not only makes it an effective tool for the comprehensive diagnosis of spinal diseases but also provides the basis for the most reasonable treatment options for spinal diseases. In the domestic application of artificial intelligence in the diagnosis and treatment of spinal surgery, it can also solve the problems of difficult diagnosis and complicated treatment of spinal diseases faced by primary doctors, reduce the rate of misdiagnosis and missed diagnosis, and effectively reduce the economic and social burden of spinal diseases. This paper reviews the research progress of artificial intelligence represented by deep learning in the field of diagnosis and treatment of spinal surgery at home and abroad, and the advantages and application prospects of artificial intelligence in the diagnosis and treatment of spinal surgery.

Teaching a difficult topic using a problem-based concept resembling a computer game: development and evaluation of an e-learning application for medical molecular genetics

BackgroundGenetic testing rapidly penetrates into all medical specialties and medical students must acquire skills in this area. However, many of them consider it difficult. Furthermore, many find these topics less appealing and not connected to their future specialization in different fields of clinical medicine. Student-centred strategies such as problem-based learning, gamification and the use of real data can increase the appeal of a difficult topic such as genetic testing, a field at the crossroads of genetics, molecular biology and bioinformatics.MethodsWe designed an electronic teaching application which students registered in the undergraduate Medical Biology course can access online. A study was carried out to assess the influence of implementation of the new method. We performed pretest/posttest evaluation and analyzed the results using the sign test with median values. We also collected students’ personal comments.ResultsThe newly developed interactive application simulates the process of molecular genetic diagnostics of a hereditary disorder in a family. Thirteen tasks guide students through clinical and laboratory steps needed to reach the final diagnosis. Genetics and genomics are fields strongly dependent on electronic databases and computer-based data analysis tools. The tasks employ publicly available internet bioinformatic resources used routinely in medical genetics departments worldwide. Authenticity is assured by the use of modified and de-identified clinical and laboratory data from real families analyzed in our previous research projects. Each task contains links to databases and data processing tools needed to solve the task, and an answer box. If the entered answer is correct, the system allows the user to proceed to the next task. The solving of consecutive tasks arranged into a single narrative resembles a computer game, making the concept appealing. There was a statistically significant improvement of knowledge and skills after the practical class, and most comments on the application were positive. A demo version is available at https://medbio.lf2.cuni.cz/demo_m/. Full version is available on request from the authors.ConclusionsOur concept proved to be appealing to the students and effective in teaching medical molecular genetics. It can be modified for training in the use of electronic information resources in other medical specialties.

Current understanding of the effects of inspiratory resistance on the interactions between systemic blood pressure, cerebral perfusion, intracranial pressure, and cerebrospinal fluid dynamics.

Negative intrathoracic pressure (nITP) is generated by the respiratory muscles during inspiration to overcome inspiratory resistance, thus enabling lung ventilation. Recently developed noninvasive techniques have made it possible to assess the effects of nITP in real time in several physiological aspects such as systemic blood pressure (BP), intracranial pressure (ICP), and cerebral blood flow (CBF). It has been shown that nITP from 0 to -20 cmH2O elevates BP and diminishes ICP, which facilitates brain perfusion. The effects of nITP from -20 to -40 cmH2O on BP, ICP, and CBF remain largely unrecognized, yet even nITP at -40 cmH2O may facilitate CBF by diminishing ICP. Importantly, nITP from -20 to -40 cmH2O has been documented in adults in commonly encountered obstructive sleep apnea, which justifies research in this area. Recent revelations about interactions between ICP and BP have opened up new fields of research in physiological regulation and the pathophysiology of common diseases, such as hypertension, brain injury, and respiratory disorders. A better understanding of these interactions may translate directly into new therapies in various fields of clinical medicine.

Application of probe electrospray ionization-tandem mass spectrometry to ultra-rapid determination of glufosinate and glyphosate in human serum

Glufosinate and glyphosate, which are non-selective herbicides that include an amino acid moiety in their structures, are frequently used worldwide to control unwanted vegetation. Unfortunately, these readily available herbicides are also used by people to commit suicide, and thus represent important chemicals of interest in the fields of clinical medicine and forensics. Because of the high water solubility of these herbicides, most analytical methods for their detection require a derivatization step, which results in longer analysis times. Therefore, derivatization-based methods do not currently contribute to judgements on treatment decisions in emergency medicine. In this study, we addressed this limiting factor by developing an ultra-rapid and simple analytical technique using a combination of probe electrospray ionization (PESI) and tandem mass spectrometry (MS/MS), which gives quantitative results within 0.3 min. Herbicide standards were added to human serum that was then subjected to analysis (N = 5 per concentration). The analysis was repeated daily over eight consecutive days. The limit of detection (LOD) was 0.59 μg/mL for glufosinate and 0.20 μg/mL for glyphosate. The limit of quantitation (LOQ), i.e., the lowest point on the calibration curves, was 1.56 μg/mL for both the herbicides. The matrix effects were observed at three different concentrations (between 95.7%–104% for glufosinate, and between 90.7%–95.7% for glyphosate). When applied to samples taken from actual poisoning cases (six samples for each herbicide), the present method gave almost the same quantitative values as those obtained by conventional high-performance liquid chromatography with fluorescence detection. Thus, we believe that PESI-MS/MS could emerge as a rapid diagnosis method in the clinical emergency field.