T-cell prolymphocytic leukaemia: spontaneous immunophenotypical switch from CD4 to CD8 expression

published_or_final_versionSpringer Open Choice, 21 Feb 201

Epigenetic Inactivation of the miR-124-1 in Haematological Malignancies

miR-124-1 is a tumour suppressor microRNA (miR). Epigenetic deregulation of miRs is implicated in carcinogenesis. Promoter DNA methylation and histone modification of miR-124-1 was studied in 5 normal marrow controls, 4 lymphoma, 8 multiple myeloma (MM) cell lines, 230 diagnostic primary samples of acute myeloid leukaemia (AML), acute lymphoblastic leukaemia (ALL), chronic myeloid leukaemia (CML), chronic lymphocytic leukaemia (CLL), MM, and non-Hodgkin's lymphoma (NHL), and 53 MM samples at stable disease or relapse. Promoter of miR-124-1 was unmethylated in normal controls but homozygously methylated in 4 of 4 lymphoma and 4 of 8 myeloma cell lines. Treatment of 5-Aza-2′-deoxycytidine led to miR-124-1 demethylation and re-expression of mature miR-124, which also associated with emergence of euchromatic trimethyl H3K4 and consequent downregulation of CDK6 in myeloma cells harboring homozygous miR-124-1 methylation. In primary samples at diagnosis, miR-124-1 methylation was absent in CML but detected in 2% each of MM at diagnosis and relapse/progression, 5% ALL, 15% AML, 14% CLL and 58.1% of NHL (p<0.001). Amongst lymphoid malignancies, miR-124-1 was preferentially methylated in NHL than MM, CLL or ALL. In primary lymphoma samples, miR-124-1 was preferentially hypermethylated in B- or NK/T-cell lymphomas and associated with reduced miR-124 expression. In conclusion, miR-124-1 was hypermethylated in a tumour-specific manner, with a heterochromatic histone configuration. Hypomethylation led to partial restoration of euchromatic histone code and miR re-expression. Infrequent miR-124-1 methylation detected in diagnostic and relapse MM samples showed an unimportant role in MM pathogenesis, despite frequent methylation found in cell lines. Amongst haematological cancers, miR-124-1 was more frequently hypermethylated in NHL, and hence warrants further study

Modulation of microglia by Wolfberry on the survival of retinal ganglion cells in a rat ocular hypertension model

The active component of Wolfberry (Lycium barbarum), lycium barbarum polysaccharides (LBP), has been shown to be neuroprotective to retinal ganglion cells (RGCs) against ocular hypertension (OH). Aiming to study whether this neuroprotection is mediated via modulating immune cells in the retina, we used multiphoton confocal microscopy to investigate morphological changes of microglia in whole-mounted retinas. Retinas under OH displayed slightly activated microglia. One to 100 mg/kg LBP exerted the best neuroprotection and elicited moderately activated microglia in the inner retina with ramified appearance but thicker and focally enlarged processes. Intravitreous injection of lipopolysaccharide decreased the survival of RGCs at 4 weeks, and the activated microglia exhibited amoeboid appearance as fully activated phenotype. When activation of microglia was attenuated by intravitreous injection of macrophage/microglia inhibitory factor, protective effect of 10 mg/kg LBP was attenuated. The results implicated that neuroprotective effects of LBP were partly due to modulating the activation of microglia

Lupus nephritis in Chinese children--a territory-wide cohort study in Hong Kong

We report a multicenter study of Chinese children in Hong Kong with systemic lupus erythematosus (SLE) nephritis. Children were included if: they fulfilled the ACR criteria, had significant proteinuria or casturia, were Chinese and younger than 19 years and had been diagnosed with SLE between January 1990 and December 2003. Investigators in each center retrieved data on clinical features, biopsy reports, treatment and outcome of these patients. There were 128 patients (eight boys, 120 girls; mean age: 11.9+/-2.8 years). About 50% presented with multisystem illness and 40% with nephritic/nephrotic symptoms. Negative anti-dsDNA antibodies were found in 6% of the patients. Renal biopsy revealed WHO Class II, III, IV and V nephritis in 13 (10%), 22 (17%), 69 (54%) and 13 (10%) patients, respectively. The clinical severity of the nephritis did not accurately predict renal biopsy findings. The follow-up period ranged from 1 to 16.5 years (mean+/-SD: 5.76+/-3.61 years). During the study five patients died (two from lupus flare, one from cardiomyopathy, two from infections). Four patients had endstage renal failure (ESRF) (one died during a lupus flare). All deaths and end-stage renal failure occurred in the Class IV nephritis group. Chronic organ damage was infrequent in the survivors. The actuarial patient survival rates at 5, 10 and 15 years of age were 95.3, 91.8, and 91.8%, respectively. For Class IV nephritis patients, the survival rates without ESRF at 5, 10, and 15 years were 91.5, 82.3 and 76%, respectively. The survival and chronic morbidity rates of the Chinese SLE children in the present study are comparable to those of other published studies.postprin

Differential Spectral Normalization (DSN) for PDE Discovery

Partial differential equations (PDEs) play a prominent role in many disciplines for describing the governing systems of interest. Traditionally, PDEs are derived based on first principles. In the era of big data, the needs of uncovering PDEs from massive data-set are emerging and become essential. One of the latest advance in PDE discovery models is PDE-Net, which has shown promising predictive power with its moment-constrained convolutional filters, but may suffer from noisy data and numerical instability intrinsic in numerical differentiation. We propose a novel and robust regularization method tailored for moment-constrained convolutional filters, namely, Differential Spectral Normalization (DSN), to allow accurate estimation of coefficient functions and stable prediction of dynamics in a long time horizon. We investigated the effectiveness of DSN against batch normalization, dropout, spectral normalization, weight decay, weight normalization, jacobian regularization and orthonormal regularization and supported with empirical evidence that DSN owns the highest effectiveness by learning the convolutional filters in a robust manner. Numerical experiments further reveal that with DSN there is a substantial potential to uncover the hidden PDEs in a scarce data setting and predict the dynamical behavior for a long time horizon, even in a noisy environment where all data samples are contaminated with noise