Improving the response to lenvatinib in partial responders using a Constrained-Disorder-Principle-based second-generation artificial intelligence-therapeutic regimen: a proof-of-concept open-labeled clinical trial.

Introduction: The main obstacle in treating cancer patients is drug resistance. Lenvatinib treatment poses challenges due to loss of response and the common dose-limiting adverse events (AEs). The Constrained-disorder-principle (CDP)-based second-generation artificial intelligence (AI) systems introduce variability into treatment regimens and offer a potential strategy for enhancing treatment efficacy. This proof-of-concept clinical trial aimed to assess the impact of a personalized algorithm-controlled therapeutic regimen on lenvatinib effectiveness and tolerability. Methods: A 14-week open-label, non-randomized trial was conducted with five cancer patients receiving lenvatinib-an AI-assisted application tailored to a personalized therapeutic regimen for each patient, which the treating physician approved. The study assessed changes in tumor response through FDG-PET-CT and tumor markers and quality of life via the EORTC QLQ-THY34 questionnaire, AEs, and laboratory evaluations. The app monitored treatment adherence. Results: At 14 weeks of follow-up, the disease control rate (including the following outcomes: complete response, partial response, stable disease) was 80%. The FDG-PET-CT scan-based RECIST v1.1 and PERCIST criteria showed partial response in 40% of patients and stable disease in an additional 40% of patients. One patient experienced a progressing disease. Of the participants with thyroid cancer, 75% showed a reduction in thyroglobulin levels, and 60% of all the participants showed a decrease in neutrophil-to-lymphocyte ratio during treatment. Improvement in the median social support score among patients utilizing the system supports an ancillary benefit of the intervention. No grade 4 AEs or functional deteriorations were recorded. Summary: The results of this proof-of-concept open-labeled clinical trial suggest that the CDP-based second-generation AI system-generated personalized therapeutic recommendations may improve the response to lenvatinib with manageable AEs. Prospective controlled studies are needed to determine the efficacy of this approach.

Oral Insulin Alleviates Liver Fibrosis and Reduces Liver Steatosis in Patients With Metabolic Dysfunction-associated Steatohepatitis and Type 2 Diabetes: Results of Phase II Randomized, Placebo-controlled Feasibility Clinical Trial.

Background and Aims: Metabolic dysfunction-associated steatohepatitis is an advanced form of nonalcoholic fatty liver disease and a leading cause of end-stage liver disease and transplantation. Insulin resistance and inflammation underlie the pathogenesis of the disease. Methods: This double-blind, randomized, placebo-controlled, multicenter feasibility clinical trial aimed to determine the safety of oral 8 mg insulin in patients with metabolic dysfunction-associated steatohepatitis and type 2 diabetes mellitus. Patients were treated twice daily for 12 weeks with an 8 mg insulin (n = 21) or placebo (n = 11) capsule. Safety was monitored throughout the study. MRI-proton density fat fraction assessed liver fat content, and Fibroscan® measured liver fibrosis and steatosis levels at screening and after 12 weeks of treatment. Results: No severe drug-related adverse events were reported during the study. After 12 weeks of treatment, mean percent reductions in whole-liver (-11.2% vs -6.5%, respectively) and liver segment 3 (-11.7% vs +0.1%, respectively) fat content was higher in the insulin than in the placebo arm. Patients receiving insulin showed a median -1.2 kPa and -21.0 dB/m reduction from baseline fibrosis and steatosis levels, respectively, while placebo-treated patients showed median increases of 0.3 kPa and 13.0 dB/m, respectively. At Week 12, oral insulin was associated with a mean of 0.27% reduction and placebo with a 0.23% increase from baseline hemoglobin A1c levels. Mean percent changes from baseline alanine aminotransferase, and aspartate aminotransferase levels were -10% and -0.8%, respectively, in the oral insulin and 3.0% and 13.4%, in the placebo arm. Conclusion: The results of this feasibility study support the safety and potential therapeutic effect of orally delivered insulin on liver fibrosis, fat accumulation, and inflammatory processes (NIH Clinical Trials No. NCT04618744).

Practicing Emergency Medicine in the Metaverse: A Novel Mixed Reality Casualty Care Training Platform.

BACKGROUND: Current casualty care training modalities present several challenges, including limited simulation facilities, instructor dependence, lack of standardization, documentation of trainees' performance and training personalization. The study presents the design, development and preliminary evaluation of a novel hybrid training platform to address these challenges. METHODS: A mixed reality platform was chosen and developed to address field operators' requirements. The platform is easy to operate and can be set up by laypeople within 20-min in multiple environments. Individual-level training documentation is generated autonomously following each session, evaluating 30 aspects of performance. From this, a unique aggregated dataset emerges as a substrate for executives' dashboards and intelligent planning of future sessions. RESULTS: An evaluation process took part using simulator-based training in different stages along the project using a questionnaire (Likert-scale based). Fifty military physicians took part in an identical head injury scenario requiring airway management by endotracheal intubation and were immediately surveyed. CONCLUSION: TrauMR is an agile hybrid training that harbors the potential to address many of the emerging challenges of training for prehospital care in combat and civilian environments.

A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial.

INTRODUCTION: Diuretics are a mainstay therapy for congestive heart failure (CHF); however, over one-third of patients develop diuretic resistance. Second-generation artificial intelligence (AI) systems introduce variability into treatment regimens to overcome the compensatory mechanisms underlying the loss of effectiveness of diuretics. This open-labeled, proof-of-concept clinical trial sought to investigate the ability to improve diuretic resistance by implementing algorithm-controlled therapeutic regimens. METHODS: Ten CHF patients with diuretic resistance were enrolled in an open-labeled trial where the Altus Care™ app managed diuretics' dosage and administration times. The app provides a personalized therapeutic regimen creating variability in dosages and administration times within pre-defined ranges. Response to therapy was measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ) score, 6-minute walk test (SMW), N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, and renal function. RESULTS: The second-generation, AI-based, personalized regimen alleviated diuretic resistance. All evaluable patients demonstrated clinical improvement within ten weeks of intervention. A dose reduction (based on a three-week average before and last three weeks of intervention) was achieved in 7/10 patients (70 %, p = 0.042). The KCCQ score improved in 9/10 (90 %, p = 0.002), the SMW improved in 9/9 (100 %, p = 0.006), NT-proBNP was decreased in 7/10 (70 %, p = 0.02), and serum creatinine was decreased in 6/10 (60 %, p = 0.05). The intervention was associated with reduced number of emergency room visits and the number of CHF-associated hospitalizations. SUMMARY: The results support that the randomization of diuretic regimens guided by a second-generation personalized AI algorithm improves the response to diuretic therapy. Prospective controlled studies are needed to confirm these findings.

Using chronobiology-based second-generation artificial intelligence digital system for overcoming antimicrobial drug resistance in chronic infections.

Antimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents. Numerous methods are used to overcome this problem with moderate success. Besides efforts of antimicrobial stewards, several artificial intelligence (AI)-based technologies are being explored for preventing resistance development. These first-generation systems mainly focus on improving patients' adherence. Chronobiology is inherent in all biological systems. Host response to infections and pathogens activity are assumed to be affected by the circadian clock. This paper describes the problem of antimicrobial resistance and reviews some of the current AI technologies. We present the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance. An algorithm-controlled regimen that improves the long-term effectiveness of antimicrobial agents is being developed based on the implementation of variability in dosing and drug administration times. The method provides a means for ensuring a sustainable response and improved outcomes. Ongoing clinical trials determine the effectiveness of this second-generation system in chronic infections. Data from these studies are expected to shed light on a new aspect of resistance mechanisms and suggest methods for overcoming them.IMPORTANCE SECTIONThe paper presents the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance.Key messagesAntimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents.We present the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance.

Massive Intestinal Bleeding in an Adult with IgA Vasculitis Treated with Intravenous Immunoglobulin.

We report the case of a 29-year-old adult presenting with severe IgA vasculitis, with cutaneous, urologic, and renal manifestations. The late appearance of severe gastrointestinal bleeding dominated the clinical picture, necessitating the administration of tens of units of packed cells and the augmentation of the immunosuppressive protocol. It was not until therapy with intravenous immunoglobulin (IVIG) was introduced that the massive bleeding was controlled. We herein discuss the patient's presentation, the gastrointestinal manifestations of IgA vasculitis, the recommended treatments, and the existent evidence about IVIG therapy.

Native aortic valve Staphylococcus warneri endocarditis after COVID-19 infection: a case report and a review of literature.

We report a case of Staphylococcus warneri native valve endocarditis in an immunocompetent healthy adult, without known risk factors for infective endocarditis, two months following COVID-19 infection, who recovered with conservative treatment. Additionally, we reviewed previous cases of native valve endocarditis caused by Staphylococcus warneri and summarized the main clinical implications.

A Subject-Tailored Variability-Based Platform for Overcoming the Plateau Effect in Sports Training: A Narrative Review.

The plateau effect in training is a significant obstacle for professional athletes and average subjects. It evolves from both the muscle-nerve-axis-associated performance and various cardiorespiratory parameters. Compensatory adaptation mechanisms contribute to a lack of continuous improvement with most exercise regimens. Attempts to overcome this plateau in exercise have been only partially successful, and it remains a significant unmet need in both healthy subjects and those suffering from chronic neuromuscular, cardiopulmonary, and metabolic diseases. Variability patterns characterize many biological processes, from cellular to organ levels. The present review discusses the significant obstacles in overcoming the plateau in training and establishes a platform to implement subject-tailored variability patterns to prevent and overcome this plateau in muscle and cardiorespiratory performance.

Cold Agglutinin-Mediated Autoimmune Hemolytic Anemia in Association with Antiphospholipid Syndrome.

Antiphospholipid syndrome and cold agglutinin-mediated autoimmune hemolytic anemia are 2 distinct immune-mediated hematologic disorders. While no clear association exists between these 2 entities, complement activation is known to occur in both of them. Herein, we report a unique case of cold agglutinin hemolytic anemia in a patient with a known primary antiphospholipid syndrome.

Compassionate use of convalescent plasma for treatment of moderate and severe pneumonia in COVID-19 patients and association with IgG antibody levels in donated plasma.

BACKGROUND: We assessed outcome of patients with moderate and severe COVID-19 following treatment with convalescent plasma (CP) and the association with IgG levels in transfused CP. METHODS: A prospective cohort study. Primary outcome was improvement at day 14 defined as alive, not on mechanical ventilation, and moderate, mild, or recovered from COVID-19. Antibody levels in CP units were unknown at the time of treatment. IgG against the spike protein S1 was subsequently measured by ELISA. Neutralizing antibodies titers were determined in a subset. Outcome was assessed in relation to the mean antibody level transfused to the patients (≤4.0 versus >4.0). FINDINGS: Of 49 patients, 11 (22.4%) had moderate, 38 (77.6%) had severe disease, 28 were ventilated. At day 14, 24 (49.0%) patients improved, 9 (18.4%) died, and 13 (26.5%) were ventilated. In 14/98 (14.3%) CP units IgG was < 1.1 (cutoff calibration) and in 60 (61.2%) ≤4.0. IgG level and neutralizing antibody titer were correlated (0.85 p < 0.001). In patients receiving ≤4.0 antibody levels, 11/30 improved (36.7%) versus 13/19 (68.4%) in patients receiving >4.0 odds ratio (OR) 0.267 [95% confidence interval (CI) 0.079-0.905], P = 0.030. In patients diagnosed >10 days prior to treatment, 4/14 (22.4%) improved in the ≤4.0 antibody group, versus 6/7 (85.7%) in the >4.0 antibody group, OR 0.048 (95% CI, 0.004-0.520), P = 0.007. No serious adverse events were reported. INTERPRETATION: Treatment with CP with higher levels of IgG against S1 may benefit patients with moderate and severe COVID-19. IgG against S1 level in CP predicts neutralization antibodies titers.

Clinical Course and Outcomes of Severe Covid-19: A National Scale Study.

Knowledge of the outcomes of critically ill patients is crucial for health and government officials who are planning how to address local outbreaks. The factors associated with outcomes of critically ill patients with coronavirus disease 2019 (Covid-19) who required treatment in an intensive care unit (ICU) are yet to be determined. METHODS: This was a retrospective registry-based case series of patients with laboratory-confirmed SARS-CoV-2 who were referred for ICU admission and treated in the ICUs of the 13 participating centers in Israel between 5 March and 27 April 2020. Demographic and clinical data including clinical management were collected and subjected to a multivariable analysis; primary outcome was mortality. RESULTS: This study included 156 patients (median age = 72 years (range = 22-97 years)); 69% (108 of 156) were male. Eighty-nine percent (139 of 156) of patients had at least one comorbidity. One hundred three patients (66%) required invasive mechanical ventilation. As of 8 May 2020, the median length of stay in the ICU was 10 days (range = 0-37 days). The overall mortality rate was 56%; a multivariable regression model revealed that increasing age (OR = 1.08 for each year of age, 95%CI = 1.03-1.13), the presence of sepsis (OR = 1.08 for each year of age, 95%CI = 1.03-1.13), and a shorter ICU stay(OR = 0.90 for each day, 95% CI = 0.84-0.96) were independent prognostic factors. CONCLUSIONS: In our case series, we found lower mortality rates than those in exhausted health systems. The results of our multivariable model suggest that further evaluation is needed of antiviral and antibacterial agents in the treatment of sepsis and secondary infection.

Targeting SARS-CoV-2 receptors as a means for reducing infectivity and improving antiviral and immune response: an algorithm-based method for overcoming resistance to antiviral agents.

The ongoing severe acute respiratory syndrome pandemic caused by the novel coronavirus 2 (SARS-CoV-2) is associated with high morbidity and mortality rates, and it has created a pressing global need for effective antiviral therapies against it. COVID-19 disease pathogenesis is characterized by an initial virus-mediated phase, followed by inappropriate hyperactivation of the immune system leading to organ damage. Targeting of the SARS-CoV-2 viral receptors is being explored as a therapeutic option for these patients. In this paper, we summarize several potential receptors associated with the infectivity of SARS-CoV-2 and discuss their association with the immune-mediated inflammatory response. The potential for the development of resistance towards antiviral drugs is also presented. An algorithm-based platform to improve the efficacy of and overcome resistance to viral receptor blockers through the introduction of personalized variability is described. This method is designed to ensure sustained antiviral effectiveness when using SARS-CoV-2 receptor blockers.

Increased serum C-reactive protein levels are associated with shorter survival and development of second cancers in chronic lymphocytic leukemia.

BACKGROUND: Chronic lymphocytic leukemia (CLL) is characterized by a heterogeneous clinical course, ranging from stable to more aggressive disease. Herein, we determined the prognostic significance of serum C-reactive protein (CRP) levels in patients with CLL Methods: A retrospective cohort study reviewing the records of 107 consecutive treatment naïve patients with CLL and a control group comprised of apparently healthy individuals attending for periodic health examinations. RESULTS: The median CRP level of patients with CLL was 0.19 mg/dL (0-2.9). In univariate analysis, high-CRP levels (≥0.4 mg/dL) were significantly associated with an increased risk of mortality (HR = 3.97, 95%CI 1.64-9.62, p = .002) and development of second solid cancers (HR = 4.54, 95%CI 1.57-13.11, p = .005), compared to low-CRP values (<0.4 mg/dL). In multivariate analysis, high-CRP retained statistical significance for all-cause mortality (HR = 2.81, 95%CI 1.04-7.57, p = .04) and the development of second solid malignancies (HR = 4.54, 95%CI 1.57-13.11, p = .005). Moreover, when compared to an apparently healthy population, CLL patients with high CRP levels had more than an eightfold risk of cancer. CONCLUSIONS: Elevated baseline CRP levels are associated with shorter survival and development of second cancers in patients with CLL. We suggest that increased CRP in patients with CLL may justify a more rigorous search for second cancers. KEY MESSAGES Elevated CRP levels are associated with a shorter overall survival in CLL. Elevated CRP levels are associated with an increased risk of second cancers in CLL. Increased CRP in patients with CLL may justify a more rigorous search for second cancers.