Notes

First usefulness regarding teprotumumab for the treatment of dysthyroid optic neuropathy: A multicenter study.
We explored minimal residual disease (MRD) in relapsed/refractory multiple myeloma (RRMM) and transplant-ineligible newly diagnosed multiple myeloma (TIE NDMM) using data from four phase 3 studies (POLLUX, CASTOR, ALCYONE, and MAIA). Each study previously demonstrated that daratumumab-based therapies improved MRD-negativity rates and reduced the risk of disease progression or death by approximately half versus standards of care. We conducted a large-scale pooled analysis for associations between patients achieving complete response (CR) or better with MRD-negative status, and progression-free survival (PFS). MRD was assessed via next-generation sequencing (10‒5 threshold). Patient-level data were pooled from all four studies, and for patients with TIE NDMM plus patients with RRMM who received ≤2 prior lines of therapy (≤2PL). CX-5461 PFS was evaluated by response and MRD status. Median follow-up (months) was POLLUX, 54.8; CASTOR, 50.2; ALCYONE, 40.1; and MAIA, 36.4. Patients who achieved ≥CR and MRD negativity had improved PFS versus those who failed to reach CR or were MRD positive (TIE NDMM and RRMM hazard ratio [HR] 0.20, P less then .0001; TIE NDMM and RRMM ≤2PL HR 0.20, P less then .0001). This benefit occurred irrespective of therapy or disease setting. A time-varying Cox proportional hazard model confirmed that ≥CR with MRD negativity was associated with improved PFS. Daratumumab-based treatment was associated with more patients reaching ≥CR and MRD negativity. These findings represent the first large-scale analysis with robust methodology to support ≥CR with MRD negativity as a prognostic factor for PFS in RRMM and TIE NDMM. These trials were registered at www.ClinicalTrials.gov NCT02076009/NCT02136134/NCT02195479/NCT02252172.The prevailing coronavirus disease (COVID-19) caused by a novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has presented some neurological manifestations including hyposmia, hypogeusia, headache, stroke, encephalitis, Guillain‒Barre syndrome, and some neuropsychiatric disorders. Although several cell types in the brain express angiotensin converting enzyme-2 (ACE2), the main SARS-CoV-2 receptor, and other related proteins, it remains unclear whether the observed neurological manifestations are attributed to virus invasion into the brain or just comorbidities caused by dysregulation of systemic factors. Here, we briefly review the neurological manifestations of SARS-CoV-2, summarize recent evidence for the potential neurotropism of SARS-CoV-2, and discuss the potential mechanisms of COVID-19-associated neurological diseases.Tests based on the dN/dS statistic are used to identify positive selection of nonsynonymous polymorphisms. Using these tests on alignments of all orthologs from related species can provide insights into which gene categories have been most frequently positively selected. However, longer alignments have more power to detect positive selection, creating a detection bias that could create misleading results from functional enrichment tests. Most studies of positive selection in plant pathogens focus on genes with specific virulence functions, with little emphasis on broader molecular processes. Furthermore, no studies in plant pathogens have accounted for detection bias due to alignment length when performing functional enrichment tests. To address these research gaps, we analyze 12 genomes of the phytopathogenic fungal genus Botrytis, including two sequenced in this study. To establish a temporal context, we estimated fossil-calibrated divergence times for the genus. We find that Botrytis likely originated 16-18 Ma in the Miocene and underwent continuous radiation ending in the Pliocene. An untargeted scan of Botrytis single-copy orthologs for positive selection with three different statistical tests uncovered evidence for positive selection among proteases, signaling proteins, CAZymes, and secreted proteins. There was also a strong overrepresentation of transcription factors among positively selected genes. This overrepresentation was still apparent after two complementary controls for detection bias due to sequence length. Positively selected sites were depleted within DNA-binding domains, suggesting changes in transcriptional responses to internal and external cues or protein-protein interactions have undergone positive selection more frequently than changes in promoter fidelity.Progranulin (PGRN) is a multifunctional growth factor expressed in central nervous system. Although PGRN expression is regulated by various stressors, its precise role(s) and regulatory mechanism(s) remain elusive. In this study, we used HT22 cells to investigate the physiological implications of oxidative stress-induced PGRN expression and the regulation of PGRN expression by oxidative stress. We observed that p38 MAP kinase was activated upon the addition of H2O2, and a selective p38 MAP kinase inhibitor, attenuated PGRN induction by H2O2. To explore the physiological role(s) of the PGRN induction, we first confirmed H2O2-dependent responses of HT22 cells and found that the length and number of neurites were increased by H2O2. Pgrn knockdown experiments suggested these changes were mediated by H2O2-induced PGRN expression, at least in part. Overall, the results suggested that an increase in oxidative stress in HT22 cells induced PGRN expression via p38 MAP kinase pathway, thereby controlling neurite outgrowth.
Cancer subtype identification aims to divide cancer patients into subgroups with distinct clinical phenotypes and facilitate the development for subgroup specific therapies. The massive amount of multi-omics datasets accumulated in the public databases have provided unprecedented opportunities to fulfill this task. As a result, great computational efforts have been made to accurately identify cancer subtypes via integrative analysis of these multi-omics datasets.

In this paper, we propose a Consensus Guided Graph Autoencoder (CGGA) to effectively identify cancer subtypes. First, we learn for each omic a new feature matrix by using graph autoencoders, where both structure information and node features can be effectively incorporated during the learning process. Second, we learn a set of omic-specific similarity matrices together with a consensus matrix based on the features obtained in the first step. The learned omic-specific similarity matrices are then fed back to the graph autoencoders to guide the feature learning. By iterating the two steps above, our method obtains a final consensus similarity matrix for cancer subtyping. To comprehensively evaluate the prediction performance of our method, we compare CGGA with several approaches ranging from general-purpose multi-view clustering algorithms to multi-omics-specific integrative methods. The experimental results on both generic datasets and cancer datasets confirm the superiority of our method. Moreover, we validate the effectiveness of our method in leveraging multi-omics datasets to identify cancer subtypes. In addition, we investigate the clinical implications of the obtained clusters for glioblastoma and provide new insights into the treatment for patients with different subtypes.

The source code of our method is freely available at https//github.com/alcs417/CGGA.

Supplementary data are available at Bioinformatics online.
Supplementary data are available at Bioinformatics online.Like the sword of Damocles, the threat of a post-antibiotic era is hanging over humanity's head. The scientific and medical community is thus reconsidering bacteriophage therapy (BT) as a partial but realistic solution for treatment of difficult to eradicate bacterial infections. Here, we summarize the latest developments in clinical BT applications, with a focus on developments in the following areas i) pharmacology of bacteriophages of major clinical importance and their synergy with antibiotics; ii) production of therapeutic phages; and iii) clinical trials, case studies, and case reports in the field. We address regulatory concerns, which are of paramount importance insofar as they dictate the conduct of clinical trials, which are needed for broader BT application. The increasing amount of new available data confirm the particularities of BT as being innovative and highly personalized. The current circumstances suggest that the immediate future of BT may be advanced within the framework of national BT centers in collaboration with competent authorities, which are urged to adopt incisive initiatives originally launched by some national regulatory authorities.
Sjögren's Syndrome (SS) with childhood onset is a rare autoimmune disease characterised by heterogeneous presentation. The lack of validated classification criteria makes it challenging to diagnose. Evidence-based guidelines for treatment of juvenile SS are not available due to the rarity of disease and the paucity of research in this patient population. This systematic review aims to summarise and appraise the current literature focused on pharmacological strategies for management of SS with childhood onset.

PubMed and MEDLINE/Scopus databases up to December 2020 have been screened for suitable reports highlighting pharmacological treatment of SS with childhood onset using the PRISMA 2009 reporting checklist. Animal studies have been excluded.

43 studies (34 case reports, 8 mini case series and one pilot study) were eligible for analysis. The studies retrieved included girls in 88% (120/137) of cases and had very low confidence level.Hydroxychloroquine (HCQ) was prescribed for parotid swelling, as well as in association with methotrexate (MTX) and non-steroidal anti-inflammatory drugs (NSAIDS) in patients with arthritis and arthralgia. Corticosteroids such as long courses of oral prednisone and IV methylprednisolone were commonly prescribed for children with severe disease presentations. Rituximab was mainly indicated for MALT lymphoma, and renal and nervous system complications. Other conventional DMARDs were prescribed in selected cases with extra-glandular manifestations.

Various therapies are used for the management of juvenile SS and are prescribed based on expert clinician's opinion. There are currently no good quality studies that allow clinical recommendations for treatment in SS with childhood onset.
Various therapies are used for the management of juvenile SS and are prescribed based on expert clinician's opinion. There are currently no good quality studies that allow clinical recommendations for treatment in SS with childhood onset.
Systemic sclerosis (SSc) is a rheumatic autoimmune disease affecting roughly 20 000 people worldwide and characterized by excessive collagen accumulation in the skin and internal organs. Despite the high morbidity and mortality associated with SSc, there are no approved disease-modifying agents. Our objective in this study was to explore transcriptomic and model-based drug discovery approaches for systemic sclerosis.

In this study, we explored the molecular basis for SSc pathogenesis in a well-studied mouse model of scleroderma. We profiled the skin and lung transcriptomes of mice at multiple timepoints, analyzing the differential gene expression that underscores the development and resolution of bleomycin-induced fibrosis.

We observed shared expression signatures of upregulation and downregulation in fibrotic skin and lung tissue, and observed significant upregulation of key pro-fibrotic genes including GDF15, Saa3, Cxcl10, Spp1, and Timp1. To identify changes in gene expression in responses to anti-fibrotic therapy, we assessed the effect of TGF-β pathway inhibition via oral ALK5 (TGF-β receptor I) inhibitor SB525334 and observed a time-lagged response in the lung relative to skin.
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