Biological treatment for bullous pemphigoid

BackgroundBullous pemphigoid (BP) is the most common autoimmune subepidermal bullous disease. Topical or systemic corticosteroids are often used as the first-line treatment. However, long-term corticosteroid use may lead to significant side effects. Therefore, various adjuvant immunosuppressant therapies are used as steroid-sparing agents, with accumulating reports of biological treatments for severely recalcitrant BP.ObjectiveTo describe the clinical and immunological features of a series of patients with recalcitrant BP treated with immunobiological therapies. To assess the efficacy and safety of their therapies.MethodsPatients receiving biological treatment for BP from two centers were assessed. Here, we described the clinical, immunopathological, and immunofluorescence findings of adult patients with BP and analyzed the clinical response and adverse events associated with various biological therapies.ResultsWe identified nine eligible patients treated with rituximab (seven), omalizumab (three), or dupilumab (one). The mean age at diagnosis was 60.4 years, the average BP duration before biologic initiation was 1.9 years, and the average previous treatment failure was 2.11 therapies. The mean follow-up period from the first biological treatment to the last visit was 29.3 months. Satisfactory response, defined as clinical improvement, was achieved in 78% (7) of the patients, and total BP clearance was achieved in 55% (5) of the patients at the last follow-up visit. Additional rituximab courses improved the disease outcomes. No adverse events were reported.ConclusionsEfficient and safe novel therapies can be considered in recalcitrant steroid-dependent BP non-responsive to conventional immunosuppressant therapies

Spontaneous Neck Hematoma in a Patient with Fibromuscular Dysplasia: A Case Report and a Review of the Literature

Background. Fibromuscular dysplasia (FMD) is a vascular disease that may present as aneurysms in the cervical arteries. Spontaneous neck hematoma is a rare life threatening medical condition. This is the first report of neck hematoma in a patient with FMD. Methods and Results. We present a case of a 69-year-old woman, with diagnosed cervical FMD and a 3-day history of sore throat and neck pain, who presented with enlarging neck hematoma. No active bleeding was noticed on CT angiography, airway was not compromised, and patient was managed conservatively. Next day, invasive angiography was performed, and no bleeding vessel was demonstrated. Patient has improved and was discharged after 5 days of hospitalization. We have discussed the different etiology of this condition, focusing on systemic vascular diseases. Conclusion. Complaint of neck pain in a patient with a FMD should raise suspicion for possible neck hematoma. Conversely, spontaneous neck hematoma without clear etiology should raise suspicion for a systemic vascular disease

The Glycemic Response to Infant Formulas: A Randomized Clinical Trial

Background: Commercial infant formulas attempt to imitate human milk’s unique composition. However, lactose-free and milk protein-free formulas are often chosen due to medical reasons or personal preferences. The aim of this study was to determine the glycemic and insulinemic indices of a variety of infant formulas. Methods: We conducted a three-arm, randomized, double-blind, crossover study. Participants were 25–40-year-old healthy adults. Three commercial infant formulas (cow’s milk protein-based [“standard”], soy protein-based, and lactose-free) were randomly given to each participant. Glycemic and insulinemic responses were determined and compared between the three formulas. Results: Twenty subjects were enrolled (11 females/9 males, mean age 32.8 ± 2.9 years). No significant difference was found in the glycemic index between the three formulas (21.5, 29.1, and 21.5 for the standard, soy protein-based, and lactose-free formulas, respectively, p = 0.21). However, maximal glucose levels were significantly higher for the soy protein-based formula compared to both the standard and lactose-free formulas (111.5 compared to 101.8 and 105.8 mg/dL, respectively, p = 0.001). Conclusion: Cow’s milk protein-based, soy protein-based, and lactose-free formulas have a similar glycemic index. However, soy protein-based formula produced a significantly higher increase in postprandial glucose levels. The implication and biological significance of these results have yet to be determined

sj-docx-1-wso-10.1177_17474930231217670 – Supplemental material for Lung cancer is associated with acute ongoing cerebral ischemia: A population-based study

Supplemental material, sj-docx-1-wso-10.1177_17474930231217670 for Lung cancer is associated with acute ongoing cerebral ischemia: A population-based study by Jonathan Naftali, Rani Barnea, Ruth Eliahou, Keshet Pardo, Assaf Tolkovsky, Meital Adi, Vadim Hasminski, Walid Saliba, Sivan Bloch, Guy Raphaeli, Avi Leader and Eitan Auriel in International Journal of Stroke</p

Validation of a Novel Assay to Distinguish Bacterial and Viral Infections

Reliably distinguishing bacterial from viral infections is often challenging, leading to antibiotic misuse. A novel assay that integrates measurements of blood-borne host-proteins (tumor necrosis factor-related apoptosis-inducing ligand, interferon γ-induced protein-10, and C-reactive protein [CRP]) was developed to assist in differentiation between bacterial and viral disease

Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis

ObjectiveGestational diabetes mellitus (GDM) is a condition in which women without diabetes are diagnosed with glucose intolerance during pregnancy, typically in the second or third trimester. Early diagnosis, along with a better understanding of its pathophysiology during the first trimester of pregnancy, may be effective in reducing incidence and associated short-term and long-term morbidities. DesignWe comprehensively profiled the gut microbiome, metabolome, inflammatory cytokines, nutrition and clinical records of 394 women during the first trimester of pregnancy, before GDM diagnosis. We then built a model that can predict GDM onset weeks before it is typically diagnosed. Further, we demonstrated the role of the microbiome in disease using faecal microbiota transplant (FMT) of first trimester samples from pregnant women across three unique cohorts. ResultsWe found elevated levels of proinflammatory cytokines in women who later developed GDM, decreased faecal short-chain fatty acids and altered microbiome. We next confirmed that differences in GDM-associated microbial composition during the first trimester drove inflammation and insulin resistance more than 10 weeks prior to GDM diagnosis using FMT experiments. Following these observations, we used a machine learning approach to predict GDM based on first trimester clinical, microbial and inflammatory markers with high accuracy. ConclusionGDM onset can be identified in the first trimester of pregnancy, earlier than currently accepted. Furthermore, the gut microbiome appears to play a role in inflammation-induced GDM pathogenesis, with interleukin-6 as a potential contributor to pathogenesis. Potential GDM markers, including microbiota, can serve as targets for early diagnostics and therapeutic intervention leading to prevention.Peer reviewe

The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections

Background The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. Results Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). Conclusions We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections