Necrotising myositis – learnings for a plastic surgeon

BackgroundNecrotising myositis (NM) is a life-threatening emergency. Prompt treatment is associated with more favourable outcomes, but early diagnosis is challenging. The initial absence of cutaneous signs and symptoms coupled with delayed recognition commonly result in higher rates of morbidity and mortality.ObjectivesAnalyse data regarding demographics, epidemiology, aetiology, clinical manifestations, diagnosis and treatment of previously reported cases. This publication is intended for plastic surgeons in training to help them look out for this disease.Search methods/criteriaPublications reporting necrotising myositis between 1974 to January 2020 were identified from Embase, Medline All, Web of Science Core Collection, Google Scholar and Cochrane Central Register of Controlled Trial.Data collection and analysis: Identified studies were exported to an end note library. In animal studies, studies relating to statin-induced myotoxicity and auto-immune myositis were excluded. The quality of included case reports was assessed using JBI Critical Appraisal Checklist for Case Reports.Main resultsThe most common initial presentation was a few days of antecedent prodromal flu-like symptoms associated with muscle pain. The mean age was 43.3 years and 82% had no significant medical history. The most frequent misdiagnoses were muscle strain (11%), deep vein thrombosis (10%) and viral illness (9%). Seventy-four per cent of presentations were due to Group A Streptococcus infections and only 3.5% of cases were polymicrobial. The most common clinical course following the initial presentation was rapid deterioration into profound sepsis and progression into multi-organ failure. The overall mortality rate was 36.5%.ConclusionsNM is a life-threatening muscle infection. It is a diagnostic conundrum as initial presentation is often only myalgia without features of preceding trauma. We propose that a high index of suspicion and increased awareness will reduce morbidity.OtherPROSPERO (registration number CRD42018087060). Nil funding/conflict of interest.     

An Artificial Gut/Absorption Simulator: Simultaneous Evaluation of Desupersaturation and Absorption from Ketoconazole Supersaturated Solutions

For supersaturating formulations of BCS-II compounds, which by definition have high intestinal permeability, a closed USP apparatus does not provide the necessary absorptive conditions during dissolution. To address this, an artificial gut simulator (AGS) has been constructed consisting of a 2.5 mL donor compartment in which a hollow fiber-based absorption module is suspended. Drug from donor diffuses across the hollow fiber membrane to be absorbed by the continuously flowing intraluminal receiver fluid. The membrane surface area and intraluminal fluid flow rate are tuned to obtain the physiologically observed absorption rate constant for a weakly basic, poorly water-soluble model compound, ketoconazole (KTZ). Supersaturated solutions of KTZ were generated in the donor in pH 6.5 phosphate buffer by the pH-shift method in the absence (closed system, control) and presence (open system, biorelevant) of an optimally or suboptimally tuned absorption module. Drug concentrations in the donor and intraluminal fluids were determined by in-line UV spectroscopy. The presence of an absorptive sink reduced the supersaturated solution's crystallization propensity, more so in the case of the optimally tuned AGS. This study demonstrates the significance of simulating absorption of drug at a physiological rate during dissolution studies, especially to predict the performance of formulations of BCS-II drugs.     

Fungal mycobiome drives IL-33 secretion and type 2 immunity in pancreatic cancer

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Computer-aided diagnosis tool for cervical cancer screening with weakly supervised localization and detection of abnormalities using adaptable and explainable classifier

While pap test is the most common diagnosis methods for cervical cancer, their results are highly dependent on the ability of the cytotechnicians to detect abnormal cells on the smears using brightfield microscopy. In this paper, we propose an explainable region classifier in whole slide images that could be used by cyto-pathologists to handle efficiently these big images (100,000x100,000 pixels). We create a dataset that simulates pap smears regions and uses a loss, we call classification under regression constraint, to train an efficient region classifier (about 66.8% accuracy on severity classification, 95.2% accuracy on normal/abnormal classification and 0.870 KAPPA score). We explain how we benefit from this loss to obtain a model focused on sensitivity and, then, we show that it can be used to perform weakly supervised localization (accuracy of 80.4%) of the cell that is mostly responsible for the malignancy of regions of whole slide images. We extend our method to perform a more general detection of abnormal cells (66.1% accuracy) and ensure that at least one abnormal cell will be detected if malignancy is present. Finally, we experiment our solution on a small real clinical slide dataset, highlighting the relevance of our proposed solution, adapting it to be as easily integrated in a pathology laboratory workflow as possible, and extending it to make a slide-level prediction.     

Prognostic validity of the American joint committee on cancer eighth edition staging system for well-differentiated pancreatic neuroendocrine tumors

BackgroundThe American Joint Committee on Cancer (AJCC) made improvements for staging pancreatic neuroendocrine tumors (pNETs) in its 8th Edition; however, multicenter studies were not included.MethodsWe collected multicenter datasets (n = 1,086, between 2004 and 2018) to validate the value of AJCC 8 and other coexisting staging systems through univariate and multivariate analysis for well-differentiated (G1/G2) pNETs.ResultsCompared to other coexisting staging systems, AJCC 7 only included 12 (1.1%) patients with stage III tumors. Patients with European Neuroendocrine Tumor Society (ENETS) stage IIB disease had a higher risk of death than patients with stage IIIA (hazard ratio [HR]: 4.376 vs. 4.322). For the modified ENETS staging system, patients with stage IIB disease had a higher risk of death than patients with stage III (HR: 6.078 vs. 5.341). According to AJCC 8, the proportions of patients with stage I, II, III, and IV were 25.7%, 40.3%, 23.6%, and 10.4%, respectively. As the stage advanced, the median survival time decreased (NA, 144.7, 100.8, 72.0 months, respectively), and the risk of death increased (HR: II = 3.145, III = 5.925, and IV = 8.762).ConclusionThese findings suggest that AJCC 8 had a more reasonable proportional distribution and the risk of death was better correlated with disease stage.