A rare case of monozygotic triplets with Duchenne muscular dystrophy

Twins with Duchenne muscular dystrophy (DMD) have been widely studied. We report the first rare case of monozygotic triplets with DMD who shared consistent phenotypes, including delayed motor and language milestones, muscle wasting and weakness, joint contracture, and lumbar lordosis. Muscle magnetic resonance imaging and biopsy revealed the similar muscle injury characteristics and dystrophin absence. Short tandem repeat analysis confirmed monozygosity. A de novo mutation (exon 49–52 deletion) was found in the triplets but not in their mother. Treatment included prednisone, idebenone, and rehabilitation management. At the 2-year follow-up, motor function had deteriorated, and muscle fatty infiltration was more extensive and severe. Our case offers a unique opportunity for genetic and therapeutic research. Furthermore, it highlights the critical role of genetic factors in DMD phenotypes and provides a potential choice for treatment observations.     

Circulating CCL20: A potential biomarker for active vitiligo together with the number of Th1/17 cells

Background

Vitiligo is an autoimmune disease with varying pathological features. Activation of the CCL20-CCR6 axis plays an important role in chronic inflammatory diseases. However, whether CCL20-CCR6 and Th1/17 cells are indicative of active vitiligo is unclear.

Protective mechanism of Wnt4 gene on Parkinson’s disease (PD) transgenic Drosophila

Objective: The main pathological change of Parkinson’s disease (PD) is progressive degeneration and necrosis of dopaminergic neurons in the midbrain, forming a Lewy body in many of the remaining neurons. Studies have found that in transgenic Drosophila, mutations in the PTEN-inducible kinase 1 (PINK1) gene may cause indirect flight muscle defects in Drosophila, and mitochondrial structural dysfunction as well.

Methods: In this study, Wnt4 gene overexpression and knockdown were performed in PINK1 mutant PD transgenic Drosophila, and the protective effect of Wnt4 gene on PD transgenic Drosophila and its possible mechanism were explored. The Wnt4 gene was screened in the previous experiment; And by using the PD transgenic Drosophila model of the MHC-Gal4/UAS system, the PINK1 gene could be specifically activated in the Drosophila muscle tissue.

Results: In PINK1 mutation transgenic fruit flies, the Wnt4 gene to study its implication on PD transgenic fruit flies’ wing normality and flight ability. We found that overexpression of Wnt4 gene significantly reduced abnormality rate of PD transgenic Drosophila and improved its flight ability, and then, increased ATP concentration, enhanced mitochondrial membrane potential and normalized mitochondrial morphology were found. All of these findings suggested Wnt4 gene may have a protective effect on PD transgenic fruit flies. Furthermore, in Wnt4 gene overexpression PD transgenic Drosophila, down-regulation autophagy and apoptosis-related proteins Ref(2)P, Pro-Caspase3, and up-regulation of Beclin1, Atg8a, Bcl2 protein were confirmed by Western Blotting.

Conclusion: The results imply that the restoring of mitochondrial function though Wnt4 gene overexpression in the PINK1 mutant transgenic Drosophila may be related to autophagy and/or apoptosis.     

Impact of Multifocality and Multilocation of Positive Surgical Margin After Radical Prostatectomy on Predicting Oncological Outcome

Objective

To assess the impact of focality and location of positive surgical margins (PSM) on long-term outcomes after radical prostatectomy (RP) for prostate cancer (PCa), including biochemical recurrence (BCR), metastasis and overall mortality.

Analysis of Stroke Detection during the COVID-19 Pandemic Using Natural Language Processing of Radiology Reports

BACKGROUND AND PURPOSE:The coronavirus disease 2019 (COVID-19) pandemic has led to decreases in neuroimaging volume. Our aim was to quantify the change in acute or subacute ischemic strokes detected on CT or MR imaging during the pandemic using natural language processing of radiology reports.MATERIALS AND METHODS:We retrospectively analyzed 32,555 radiology reports from brain CTs and MRIs from a comprehensive stroke center, performed from March 1 to April 30 each year from 2017 to 2020, involving 20,414 unique patients. To detect acute or subacute ischemic stroke in free-text reports, we trained a random forest natural language processing classifier using 1987 randomly sampled radiology reports with manual annotation. Natural language processing classifier generalizability was evaluated using 1974 imaging reports from an external dataset.RESULTS:The natural language processing classifier achieved a 5-fold cross-validation classification accuracy of 0.97 and an F1 score of 0.74, with a slight underestimation (−5%) of actual numbers of acute or subacute ischemic strokes in cross-validation. Importantly, cross-validation performance stratified by year was similar. Applying the classifier to the complete study cohort, we found an estimated 24% decrease in patients with acute or subacute ischemic strokes reported on CT or MR imaging from March to April 2020 compared with the average from those months in 2017–2019. Among patients with stroke-related order indications, the estimated proportion who underwent neuroimaging with acute or subacute ischemic stroke detection significantly increased from 16% during 2017–2019 to 21% in 2020 (P = .01). The natural language processing classifier performed worse on external data.CONCLUSIONS:Acute or subacute ischemic stroke cases detected by neuroimaging decreased during the COVID-19 pandemic, though a higher proportion of studies ordered for stroke were positive for acute or subacute ischemic strokes. Natural language processing approaches can help automatically track acute or subacute ischemic stroke numbers for epidemiologic studies, though local classifier training is important due to radiologist reporting style differences.

There is much concern regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on the quality of stroke care, including issues with hospital capacity, clinical resource re-allocation, and the safety of patients and clinicians.^1,2 Previous reports have shown that there have been substantial decreases in stroke neuroimaging volume during the pandemic.^3,4 In addition, acute ischemic infarcts have been found on neuroimaging studies in many hospitalized patients with COVID-19, though the causal relationship is unclear.^5,6 Studies like these and other epidemiologic analyses usually rely on the creation of manually curated databases, in which identification of cases can be time-consuming and difficult to update in real-time. One way to facilitate such research is to use natural language processing (NLP), which has shown utility for automated analysis of radiology report data.⁷ NLP algorithms have been developed previously for the classification of neuroradiology reports for the presence of ischemic stroke findings and acute ischemic stroke subtypes.^8,9 Thus, NLP has the potential to facilitate COVID-19 research.In this study, we developed an NLP machine learning model that classifies radiology reports for the presence or absence of acute or subacute ischemic stroke (ASIS), as opposed to chronic stroke. We used this model to quantify the change in ASIS detected on all CT or MR imaging studies performed at a large comprehensive stroke center during the COVID-19 pandemic in the United States. We also evaluated NLP model generalizability and different training strategies using a sample of radiology reports from a second stroke center.     

A small molecule LS-1-2F promotes the endocytosis of macromolecules into tumor cells

In the previous research, we found that anticancer agent LS-1-2F could cause the vacuolation of tumor cells. Herein we investigated the effect of compound LS-1-2F on the endocytosis of macromolecules, including fluorescence quantum dots, human serum albumin, single-stranded RNA, and monoclonal antibody, into tumor cells. We found that LS-1-2F could accelerate the endocytosis of these large molecules by laser confocal microscope and flow cytometry. The effect of LS-1-2F on the improvement of the internalization efficiency of Herceptin biosimilar was particularly significant. Promoting endocytosis will help increase the efficiency of liquid-phase drug uptake in drug-resistant cancer cells and could potentially facilitate the use of drugs in nanoparticle delivery vehicles.     

Genome-Wide Meta-Analysis Identifies Three Novel Susceptibility Loci and Reveals Ethnic Heterogeneity of Genetic Susceptibility for IgA Nephropathy

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