World Of Health Care Research Articles

Artificial intelligence in the healthcare sector

A subfield of artificial intelligence called "machine learning" enables computers to learn from data without explicit human programming. In a broad sense, artificial intelligence (AI) refers to any computer or system behavior that resembles human behavior. One of the most significant contemporary trends in global healthcare is the use of artificial intelligence (AI) technologies in medicine. Technologies based on artificial intelligence are profoundly transforming the world's healthcare system, enabling a dramatic reconstruction of the medical diagnostics system while simultaneously lowering healthcare expenditures. Identifying the class of diseases to which a disease belongs is crucial before treating it. It is feasible to categorize the type of disease based on the feature space of the condition. Algorithms for machine learning can address this issue.

890 ARTIFICIAL INTELLIGENCE EMPOWERS REMOTE MONITORING OF IMPLANTABLE LOOP RECORDERS

Abstract Background The implantable loop recorder (ILR) is a subcutaneous device used to diagnose heart rhythm disorders, allowing the detection of any arrhythmic episodes which are related to the onset of patient-reported symptoms. Although the importance of implantable cardiac monitors has been widely recognized, it is also true that due to their subcutaneous nature, they are inclined to detect false-positive episodes which generate several warnings requiring additional checks from the health care personnel. For this reason implanted cardiac devices monitoring has been recently implemented by the use of artificial intelligence (AI), which applies deep learning algorithms for speeding up the telemetry follow-up checks without affecting the accuracy. Considering the increased need of remote monitoring during pandemics, such achievement should reduce the overwork superimposed on healthcare providers, but to date it is not known to what extent this technology confers a quantitative gain. Our main purpose is to demonstrate how AI can enhance remote monitoring of patients with implantable cardiac monitors, reducing false positives and improving the accuracy of information received by cardiologist. Methods we included twenty-six patients who undergoing ILR implantation between May 2019 and April 2022. Mean age was 58 ± 28 years and there was a higher prevalence of male subjects (n = 20; 76,9%). Fifteen patients received ILR implemented by the use of AI, eleven patients received ILR with standard remote monitoring system. We did follow up from April 2022 to September 2022 with dedicated remote monitoring platforms. The main events detected by ILR were atrial fibrillation (AF), pauses > 3 sec, supraventricular and ventricular arrhythmias, patient's symptom. Results among AI-ILR a total of 25 events were recorded and 92% (n= 23) of these were correctly identified, meanwhile 4% (n= 1) event was considered as false positive. AI implementation showed a sensitivity of 93% (95% CI 0,7018 to 0,9966) and specificity of 90% (95% CI 0,5958 to 0,9949) Among the ILR not supported by AI a total of 26 events were registered, in 76,9% (n=20) of these there was a true correspondence between the event reported and the real event, while in 19,1% (n=5) there wasn't correspondence with a sensitivity of 91% (95% CI 0,6461 to 0,9957) and specificity of 64% (95% CI 0,3876 to 0,8366). Based on these data, AI improves the accuracy of diagnosis, reducing the incidence of false positives with an important saving time for health care providers. Conclusions with our analysis we support the hypothesis that AI algorithms can augment diagnostic capabilities and provides an important contribute to clinical decision-making. The implementation of ILR monitoring with AI is still at the beginning, but continuously further investigations will determine the real added value of these algorithm. The wider adoption of AI technology in cardiovascular medicine seems eventually inevitable in the digital world of 21st century healthcare.

Isolation and characterization of Klebsiella pneumoniae bacteriophages encoding polysaccharide depolymerases with rare capsule specificity

Bacterial infections caused by antibiotic resistant strains of Klebsiella pneumoniae are among the most dangerous threats for the world's public healthcare. Treatment with bacteriophages and/or their derivatives could become one of the alternative methods for therapy of infections caused by K. pneumoniae. The study was aimed to isolate from the environment and characterize the capsule-specific K. pneumoniae bacteriophages that are useful for therapy and possess the polysaccharide depolymerase genes. Bacteriophages were isolated from the river water samples by enrichment method. The host range of bacteriophages were assessed using the collection of 180 K. pneumoniae clinical strains. Bacteriophage whole genome sequencing was performed on the MiSeq platform (Illumina). Four new bacteriophages from different taxonomic groups were isolated and characterized during the study: vB_KpnM_NDO71 (Vequintavirinae family), vB_KpnS_MAG26fr (Casjensviridae family), vB_KpnS_MDA2066 (Ackermannviridae family), and vB_KpnS_PMM-G3 (Drexlerviridae family). Bacteriophages vB_KpnM_NDO71, vB_KpnS_MAG26fr, and vB_KpnS_PMM-G3 had a narrow lytic spectrum and lysed all strains with the capsular type of the host: KL45, KL19 or KL28, respectively. Bacteriophage vB_KpnS_MDA2066 showed lytic activity against strains with two different capsular types: KL19 and KL107. Bacteriophages were strictly virulent and contained no integrase genes, potentially dangerous toxin genes or antibiotic resistance determinants. This allows them to be used in therapeutic practice. Receptor-binding proteins represented by polysaccharide depolymerases were predicted for each bacteriophage.

Robotics for Health

Robots are transforming the world of healthcare in everything from patient care right up to lifesaving surgery.

Fluoroquinolone antibiotics: Occurrence, mode of action, resistance, environmental detection, and remediation – A comprehensive review

Antibiotics play an essential role in the medical healthcare world, but their widespread usage and high prevalence have posed negative environmental consequences. During the past few decades, various antibiotic drugs have been detected in aquatic and terrestrial ecosystems. Among them, the Fluoroquinolones (FQ) group is ubiquitous in the environment and has emerged as a major environmental pollutant. FQs are very significant, broad-spectrum antibiotics used in treating various pathogenic diseases of humans and animals. The most known and used FQs are ciprofloxacin, norfloxacin, ofloxacin, levofloxacin, enrofloxacin, danofloxacin, and moxifloxacin. After human and animal administration, about 70% of these drugs are excreted out in unaltered form into the environment. Besides, wastewater discharge from pharmaceutical industries, hospitals, and agriculture runoff is the major contributor to the accumulation of FQs into the ecosystem. Their long-term presence in the environment creates selection pressure on microorganisms and contributes to the emergence of multi-drug-resistant bacteria. In addition to the resistance, these antibiotics also impose ecotoxicological effects on various animals and plant species. The presence of the fluorine atom in Fluoroquinolones makes them highly electronegative, strong, recalcitrant, and less compatible with microbial degradation. Many biological and chemical processes have been invented and successfully implemented during the past few decades for the elimination of these pollutants from the environment. This review provides a detailed overview of the classification, occurrence, distribution, and ecotoxicological effects of Fluoroquinolones. Their modes of action, resistance mechanism, detection and analysis methods, and remediation strategies have also been discussed in detail.

Non-Specialized Nurses Roles in Diabetes Inpatient Care in Cyprus: An Interpretive Phenomenological Analysis

Aim: The aim of the study was to understand how non-specialized nurses and people with diabetes understand nurses’ roles in diabetes inpatient care. Background: Diabetes mellitus is a major public health issue that places a significant burden on patients and healthcare systems and world leaders have targeted it for priority action. Design: An interpretative phenomenology approach (IPA). Methods: A total of 24 non-specialized nurses working in medical, surgical and nephrology wards and 24 people with type 1 diabetes who use the services of the state hospitals in Cyprus. The data were collected in two phases: firstly, focus groups with nurses (n = 1) and people with diabetes (n = 2) were conducted and analysed and then individual semi-structured interviews with nurses (n = 18) and with people with diabetes (n = 12) were conducted. Findings: It is evident from the study findings that nurses experience several roles in diabetes inpatient care. Most of these roles have been identified by people with diabetes as well. These roles are summarized as follows: medication administration, patient education, screening of complications, diet and psychological support. However, most of the participants raised concerns about nurses’ ability to conduct such roles. Conclusion: Participants suggest that nurses experience several roles in caring for diabetes inpatients and this view was also shared by people with diabetes. However, it was obvious that these roles differ between specialities. The findings showed that even though participants recognized a number of roles in diabetes inpatient care, their description of how they perform these roles was vague, and they raised concerns about their readiness to take on some of these roles.

Plasma Cytokines Level and Spinal Cord MRI Predict Clinical Outcome in a Rat Glial Scar Cryoinjury Model.

Traumatic injury of the spinal cord is still one of the most challenging problems in the neurosurgical practice. Despite a long history of implementation of translational medicine in the field of spinal cord injury (SCI), it remains one of the most frequent causes of human disability and a critical situation for world healthcare systems. Here, we used our rat model of the of unilateral controlled SCI induced by a cryoinjury, which consistently reproduces glial scarring and posttraumatic cyst formation, and specifically evaluated histological, bioimaging and cytokine data. We propose a 10-grade scoring scale, which can objectively estimate the extent of damage of the experimental SCI according to the magnetic resonance imaging (MRI) results. It provides a homogeneous and reliable visual control of the dynamics of the posttraumatic processes, which makes it possible to clearly distinguish the extent of early damage, the formation of glial scars and the development of posttraumatic syringomyelic cysts. The concentration of cytokines and chemokines in the plasma following the experimental SCI increased up to two orders of magnitude in comparison with intact animals, suggesting that a traumatic injury of the spinal cord was accompanied by a remarkable cytokine storm. Our data suggested that the levels of IL-1α, IL-1β, TNFα, GRO/KC, G-CSF, IFNγ and IL-13 may be considered as a reliable prognostic index for SCI. Finally, we demonstrated that MRI together with plasma cytokines level directly correlated and reliably predicted the clinical outcome following SCI. The present study brings novel noninvasive and intravital methods for the evaluation of the therapeutic efficacy of SCI treatment protocols, which may be easily translated into the clinical practice.

How the COVID-19 pandemic has affected the colorectal cancer screening in Italy: A minireview.

The coronavirus disease 2019 (COVID-19) pandemic has caused detrimental effects on many aspects of healthcare practice. Screening programs for the commonest malignancies, namely colorectal cancer (CRC), breast cancer and cervical cancer have been discontinued or interrupted since the beginning of restriction measures aimed to limit transmission of the new coronavirus infection. Robust evidence exists in favour of the role of screening campaigns in reducing mortality from CRC. In fact, the majority of pre-malignant lesions of the colon and rectum can be diagnosed with colonoscopy and treated by endoscopic or surgical resection. Besides, colonoscopy screening allows the diagnosis of CRCs in their pre-clinical stage. Italy was one of the first European countries where a high level of COVID-19 infections and deaths was observed, and one of the first where lockdowns and strict measures were adopted to reduce the risk of COVID-19 diffusion among the population. A systematic review of the literature was performed, including the PubMed, Scopus, Web of Sciences, and Reference Citation Analysis databases, with the aim of critically evaluating the impact of the COVID-19 pandemic on CRC screening in Italy. We found that reduction of CRC screening activity surpassed 50% in most endoscopic units, with almost 600000 fewer CRC screening exams conducted in the first 5 mo of 2020 vs the same period of 2019. While the consequences of the discontinuation of endoscopy screening for the prognosis and mortality of CRC will be evident in the next few years, recent data confirm that CRC is currently treated at a more advanced stage than in the pre-COVID-19 era. Since delays in CRC prevention and early diagnosis may translate to increased CRC-specific mortality, world healthcare systems should adopt strategies to maintain the regularity of CRC screening during subsequent peaks of the COVID-19 pandemic, or future events that might hamper screening programs.

PIKfyve-specific inhibitors restrict replication of multiple coronaviruses in vitro but not in a murine model of COVID-19

The ongoing COVID-19 pandemic has claimed more than 6 million lives and continues to test the world economy and healthcare systems. To combat this pandemic, the biological research community has shifted efforts to the development of medical countermeasures, including vaccines and therapeutics. However, to date, the only small molecules approved for the treatment of COVID-19 in the United States are the nucleoside analogue Remdesivir and the protease inhibitor Paxlovid, though multiple compounds have received Emergency Use Authorization and many more are currently being tested in human efficacy trials. One such compound, Apilimod, is being considered as a COVID-19 therapeutic in a Phase II efficacy trial. However, at the time of writing, there are no published efficacy data in human trials or animal COVID-19 models. Here we show that, while Apilimod and other PIKfyve inhibitors have potent antiviral activity in various cell lines against multiple human coronaviruses, these compounds worsen disease in a COVID-19 murine model when given prophylactically or therapeutically.

A critical review of bioactive glasses and glass–ceramics in cancer therapy

AbstractThere is an ongoing profound shift in using glass as a primarily passive material to one that instills active properties. We believe and demonstrate that bioactive glasses (BGs) and glass–ceramics (BGCs) as functional biomaterials for cancer therapy can transform the world of healthcare in the 21st century. Melt/gel‐derived BGs and BGCs can carry many exotic elements, including less common rare‐earth, and trigger highly efficient anticancer properties via the combination of radiotherapy, photothermal therapy, magnetic hyperthermia, along with drug or therapeutic ions delivery. The addition of these dopants modifies the bioactivity, imparts novel functionalities, and induces specific biological effects that are not achievable using other classes of biomaterials. In this paper, we have briefly reviewed and discussed the current knowledge on promising compositions, processing parameters, and applications of BGs and BGCs in treating cancer. We also envisage the need for further research on this particular, unique class of BGs and BGCs.

Authentication in the Internet of Medical Things: Taxonomy, Review, and Open Issues

The Internet of Medical Things (IoMT) has revolutionized the world of healthcare by remotely connecting patients to healthcare providers through medical devices connected over the Internet. IoMT devices collect patients’ medical data and share them with healthcare providers, who analyze it for early control of diseases. The security of patients’ data is of prime importance in IoMT. Authentication of users and devices is the first layer of security in IoMT. However, because of diverse and resource-constrained devices, authentication in IoMT is a challenging task. Several authentication schemes for IoMT have been proposed in the literature. However, each of them has its own pros and cons. To identify, evaluate and summarize the current literature on authentication in IoMT, we conducted a systematic review of 118 articles published between 2016 and 2021. We also established a taxonomy of authentication schemes in IoMT from seven different perspectives. We observed that most of the authentication schemes use a distributed architecture and public key infrastructure. It was also observed that hybrid cryptography approaches have become popular to overcome the shortcomings of single cryptographic approaches. Authentication schemes in IoMT need to support end-to-end, cross-layer, and cross-domain authentication. Finally, we discuss some open issues and future directions.

Welcome Note

“Good information is the best medicine.” – Dr. Michael E. DeBakey With this quote in mind from a giant leader in medicine, I welcome all the readers to the inaugural edition of International JRMC. In today’s world of healthcare where there is an overload of information some good, some poor, and some false it is very encouraging that RMU has taken the bold step of launching JRMC International. This is unique in nature for Pakistan as it is primarily focused on bridging the divide between good scientific research being done in Pakistan and that from outside of Pakistan. With contributions from local, national, and international researchers, doctors, and scientists, whether local projects or international this journal hopes to elevate the scholarly activity of learners in Pakistan. Globalization of the world has brought new opportunities and new challenges. On the one hand, access to information and the opportunities to publish and collaborate have expanded. Still, on the other hand, clinicians have been forced to stay abreast with up-to-date information in their respective fields. Fast-changing paradigms of each sub-specialty of Medicine, the ever-increasing role of Artificial-Intelligence (AI), the importance of data mining, and complex misinformation (infodemic) call for a further refined approach to curriculum. Scholarly journals anchored and supported by esteemed and prestigious institutions like RMU play a vital role in this regard. Pakistan is lucky to have a glorious reputation for its medical colleges and physicians, many of whom are now at leading positions at international institutions. Bringing global experience to embed it in unique epidemiologic data and research outcomes of a country like Pakistan will go a long way in nurturing future scientists. In this issue, you will hear about a variety of topics and varied authors from different parts of the world. I encourage you to submit your original research so that this journal becomes a reference for a bigger audience.

EE437 Healthcare Resource Utilization and Costs in Patients with Multiple Myeloma Who Received 1 to 3 Prior Lines of Therapy, Including a Proteasome Inhibitor, an Immunomodulatory Drug, and Exposed to (AND DISCONTINUED) Lenalidomide in the United States

Proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs) have significantly improved survival in Multiple Myeloma (MM) patients, but patients continue to progress or become refractory to these treatments, requiring the use of additional lines of therapy (LOTs). This retrospective study assessed real world healthcare resource utilization (HCRU) and subsequent costs in MM patients in the United States, after receiving 1-3 LOTs, exposed to a PI and an IMiD, and exposed to (and discontinued) lenalidomide.

Prognostic Value of Transaminases and Bilirubin Levels at Admission to Hospital on Disease Progression and Mortality in Patients with COVID-19-An Observational Retrospective Study.

Introduction: Given the impact of COVID-19 on the world healthcare system, and the efforts of the healthcare community to find prognostic factors for hospitalization, disease progression, and mortality, the aim of the present study was to investigate the prognostic impact of transaminases and bilirubin levels at admission to hospital on disease progression and mortality in COVID-19 patients. Methods: Using the CoviCamp database, we performed a multicenter, observational, retrospective study involving 17 COVID-19 Units in southern Italy. We included all adult patients hospitalized for SARS-CoV-2 infection with at least one determination at hospital admission of aminotransaminases and/or total bilirubin. Results: Of the 2054 patients included in the CoviCamp database, 1641 were included in our study; 789 patients (48%) were considered to have mild COVID-19, 347 (21%) moderate COVID-19, 354 (22%) severe COVID-19, and 151 patients (9%) died during hospitalization. Older age (odds ratio (OR): 1.02; 95% confidence interval (CI) 1.01–1.03), higher Charlson comorbidity index (CCI) (OR 1.088; 95%CI 1.005–1.18), presence of dementia (OR: 2.20; 95% CI: 1.30–3.73), higher serum AST (OR: 1.002; 95% CI: 1.0001–1.004), and total bilirubin (OR: 1.09; 95% CI: 1.002–1.19) values were associated with a more severe clinical outcome. Instead, the 151 patients who died during hospitalization showed a higher serum bilirubin value at admission (OR 1.1165; 95% CI: 1.017–1.335); the same did not apply for AST. Discussion: Patients with COVID-19 with higher levels of AST and bilirubin had an increased risk of disease progression.

Covid Fungal Detection Using Deep Learning

Abstract: COVID-19, also known as 2019-nCoV, is no longer a pandemic, but a pandemic that has killed more than 651,247 people worldwide. COVID-19 currently has no specific treatment or cure, so living with this condition and its symptoms is unavoidable. This fact has made it increasingly difficult for the world's health care system, especially in developing lands. Despite the fact that there is no effective or proven clinical trial of an antibacterial agent, Although there is no mandatory goal of ending the COVID19 epidemic, there are options that can help reduce the burden. Data development is not only limited health care programs but also economics. Famous learning, data mining, in-depth learning, and other practical strategies are examples. Other alternatives such as the 2019-nCoV epidemiological diagnosis and prognosis will be simplified. shrink, decision tree, vector support machine, Naive Bayes, and neutral network. Prior to the creation of the models, an analysis of the coefficient of correlation between different dependent and independent variables was performed to determine the interaction potential between each dependent element and independent data. Training data collection was used to train models 80 percent of the time, and the remaining 20% was used to test models.

Optimised release of tetracycline hydrochloride from core-sheath fibres produced by pressurised gyration

In recent years, there has been a surge of interest in the design, processing, and use of core-sheath fibres, especially in the production of wound healing bandages and drug delivery. In this research, a novel core-sheath pressurised gyration technique was utilised to create antibacterial fibre patches (tetracycline hydrochloride, TEHCL) using polyvinyl pyrrolidone (PVP) and polycaprolactone (PCL). Antibiotic patches showed uniform fibres with a porous surface giving rise to a biphasic delivery system, which provided an initial burst of 30–48% drug release in the first 24 h followed by a constant rate of release throughout the course of 168 h, suitable for wound-dressings application. The effect of operating parameters on fibre morphology, the influence of the core-sheath structure and drug loading as well as a mathematical modelling was investigated and analysed. Fourier-transform infrared spectroscopy, and differential scanning calorimetry results demonstrated successful TEHCL encapsulation as well as the presence of both polymers in the core-sheath fibres. The surface morphology of the fibres was studied using scanning electron microscopy and the core-sheath structure was verified using confocal scanning microscopy. Therefore, the core-sheath pressurised gyration method offers an exciting chance to customise fibre patches in a hybrid polymeric system. These advancements are crucial in the world of healthcare to meet demands where antibacterial dressings cannot be produced rapidly or when a personalised approach is necessary.

Augmented reality application for localization and classification of glioma in human brain using color-coding

Biomedical imaging involves the complex chain of acquiring, processing, and visualizing structural or functional images of living objects or systems, including extraction and processing of image-related information. Medical imaging is truly a vital element of the healthcare world–an essential tool for physicians to assist with diagnostics, treatment, and prevention. Imaging can provide uniquely valuable information about tissue composition, morphology and function, as well as quantitative descriptions of many fundamental biological processes. The main benefit of medical image processing is that it allows for in-depth, but non-invasive exploration of internal anatomy. Brain tumors are the most common and aggressive disease, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of patients. Artificial intelligence (AI) developments have created opportunities for human life in a wide range of industries, business, education, and healthcare [1,2].The main aim of the project is to provide an environment where doctors can view and interact with patient specific anatomical form.

Image-based decision making for reliable and proper diagnosing in NIFTI format using watermarking

Nowadays, advancement in Magnetic Resonance Imaging (MRI) and Computed Tomography Scan (CT-Scan) technologies have defined modern neuroimaging and drastically change the diagnosing of disease in the world healthcare system. These imaging technologies generate NIFTI (Neuroimaging Informatics Technology Initiative) images. Due to COVID-19 last several months CT-Scan has been performed on millions of the CORONA patients, so billions of the NIFTI images have been produced and communicate over the internet for the diagnosing purpose to detect the coronavirus. The communication of these medical images over the internet yielding the major problem of integrity, copyright protection, and other ethical issues for the world health care system. Another critical problem is that; is doctor diagnose the impeccable medical image of the patient because a large amount of COVID-19 patient’s data exists. For proper diagnosing it is also necessary to identify impeccable medical image. Therefore, to address these problems a secure and robust watermarking scheme is needed for these images. Various watermarking schemes have been developed for bmp, .jpg, .png, DICOM, and other image formats but the noticeable contribution is not reported for the NIFTI images. In this paper a robust and hybrid watermarking scheme for NIFTI images based on Lifting Wavelet Transform (LWT), MSVD (Multiresolution Singular Value Decomposition) and QR factorization. The combination of LWT, QR, and MSVD helps in retaining the sensitivity of the NIFTI image and improve the robustness of the watermarking scheme. In this scheme, multiple watermarks are inserted across the first slice of the NIFTI image. The proposed watermarking scheme is sustained against various noise attacks and performance is measured in terms of PSNR, SNR, SSIM, Quality of image, and Normalized correlation. Quality of the image is much significant that lie between .99994 to .99998 and SSIM reported from .94 to .99. Whereas the PSNR of the proposed scheme lies between 56.76 to 57.28 db and NC values lie between .9993 to .9998. which shows that the results are better than the existing schemes where PSNR is lies between 32.66 to 52.02 db. Watermarking, NIFTI, MSVD, LWT, QR and Image.

The Effectiveness of the Anteroom (Vestibule) Area on Hospital Infection Control and Health Staff Safety: A Systematic Review.

The emergence of SARS-CoV2 in 2019 showed again that the world's healthcare system is not fully equipped and well-designed for preventing the transmission of nosocomial respiratory infections. One of the great tools for preventing the spread of infectious organisms in hospitals is the anteroom. Several articles have investigated the role of the anteroom in disease control but the lack of a comprehensive study in this field prompted us to provide more in-depth information to fill this gap. Also, this study aimed to assess the necessity to construct an anteroom area for hospital staff members at the entrance of each ward of the hospital, and specify the equipment and facilities which make the anteroom more efficient. Articles were identified through searches of Scopus, Web of Sciences, PubMed, and Embase for studies published in English until May 2020 reporting data on the effect of the anteroom (vestibule) area in controlling hospital infections. Data from eligible articles were extracted and presented according to PRISMA's evidence-based data evaluation search strategy. Also, details around the review aims and methods were registered with the PROSPERO. From the database, 209 articles were identified, of which 25 studies met the study criteria. Most studies demonstrated that an anteroom significantly enhances practical system efficiency. The results showed that the equipment such as ventilation system, high-efficiency particulate absorption filter, hand dispensers, alcohol-based disinfection, sink, mirror, transparent panel, UVC disinfection, and zone for PPE change, and parameters like temperature, door type, pressure, and size of the anteroom are factors that are effective on the safety of the hospital environment. Studies demonstrated that providing an anteroom for changing clothing and storing equipment may be useful in reducing the transmission of airborne infections in hospitals. Since the transmission route of SARS-CoV2 is common with other respiratory infectious agents, it can be concluded that a well-designed anteroom could potentially decrease the risk of SARS-CoV2 transmission during hospitalization as well.

Chronic Experimental Model of TNBS-Induced Colitis to Study Inflammatory Bowel Disease.

Background: Inflammatory bowel disease (IBD) is a world healthcare problem. In order to evaluate the effect of new pharmacological approaches for IBD, we aim to develop and validate chronic trinitrobenzene sulfonic acid (TNBS)-induced colitis in mice. Methods: Experimental colitis was induced by the rectal administration of multiple doses of TNBS in female CD-1 mice. The protocol was performed with six experimental groups, depending on the TNBS administration frequency, and two control groups (sham and ethanol groups). Results: The survival rate was 73.3% in the first three weeks and, from week 4 until the end of the experimental protocol, the mice’s survival remained unaltered at 70.9%. Fecal hemoglobin presented a progressive increase until week 4 (5.8 ± 0.3 µmol Hg/g feces, p < 0.0001) compared with the ethanol group, with no statistical differences to week 6. The highest level of tumor necrosis factor-α was observed on week 3; however, after week 4, a slight decrease in tumor necrosis factor-α concentration was verified, and the level was maintained until week 6 (71.3 ± 3.3 pg/mL and 72.7 ± 3.6 pg/mL, respectively). Conclusions: These findings allowed the verification of a stable pattern of clinical and inflammation signs after week 4, suggesting that the chronic model of TNBS-induced colitis develops in 4 weeks.