Gene prediction of the relationship between iron deficiency anemia and immune cells.

Background: Observational studies have shown a potential link between immune factors and the risk of iron deficiency anemia (IDA), yet the causal relationship between immune cells and IDA remains enigmatic. Herein, we used Mendelian randomization (MR) to assess whether this association is causal.

Methods: We selected IDA genetic variants, including 8376 samples and 9810691 single nucleotide polymorphisms, and immune cells from a large open genome-wide association study (GWAS) for a bidirectional MR study.

[Expression and Clinical Significance of MMSA-8 and MMSA-1 in Bone Marrow of Patients with M2 Acute Myeloid Leukemia].

Objective: To detect the expression of multiple myeloma-associated antigen (MMSA)-8 and MMSA-1 in bone marrow mononuclear cells of patients with acute myeloid leukemia, and explore their roles in acute myeloid leukemia.

Methods: A total of 83 patients with M2 acute myeloid leukemia in our hospital from January 2019 to January 2020 were selected as research group, during the same period, 15 patients diagnosed iron deficiency anemia were selected as control group. Real-time fluorescence quantitative PCR was used to detect the levels of MMSA-8 and MMSA-1 in bone marrow mononuclear cells.

Efficacy and safety of chimeric antigen receptor (CAR)-T cell therapy in the treatment of relapsed and refractory multiple myeloma: a systematic-review and meta-analysis of clinical trials.

Background: Multiple myeloma (MM) is a malignant tumor originating from plasma cells in the bone marrow. The existing treatment methods can prolong the survival time of patients, but they still face the problems of myeloma relapse and refractory disease. Chimeric antigen receptor (CAR)-T cell therapy is a new cellular immunotherapy that can target and recognize antigens and kill tumor cells but the efficacy and safety data varied in different studies.

[Effect of Carvacrol on the Biological Behavior of Leukemia Cells and Its Mechanism].

Objective: To explore the effect of carvacrol on the biological behavior of leukemia cells and its regulation to circ-0008717/miR-217 molecular axis.

Methods: Human acute lymphoblastic leukemia cells Molt-4 were cultured in vitro, and different concentrations of carvacrol were added to the cells. si-NC and si-circ-0008717 were transfected into Molt-4 cells (si-NC group, si-circ-0008717 group).

Deep residual contextual and subpixel convolution network for automated neuronal structure segmentation in micro-connectomics.

Background And Objective: The goal of micro-connectomics research is to reconstruct the connectome and elucidate the mechanisms and functions of the nervous system via electron microscopy (EM). Due to the enormous variety of neuronal structures, neuron segmentation is among most difficult tasks in connectome reconstruction, and neuroanatomists desperately need a reliable neuronal structure segmentation method to reduce the burden of manual labeling and validation.

Methods: In this article, we proposed an effective deep learning method based on a deep residual contextual and subpixel convolution network to obtain the neuronal structure segmentation in anisotropic EM image stacks.

Tensorial Multiview Representation for Saliency Detection via Nonconvex Approach.

In the study of salient object detection, multiview features play an important role in identifying various underlying salient objects. As to current common patch-based methods, all different features are handled directly by stacking them into a high-dimensional vector to represent related image patches. These approaches ignore the correlations inhering in the original spatial structure, which may lead to the loss of certain underlying characterization such as view interaction.

High efficacy and safety of CD38 and BCMA bispecific CAR-T in relapsed or refractory multiple myeloma.

Background: B-cell maturation antigen (BCMA) chimeric antigen receptor T (CAR-T) cell therapy has obtained promising results in relapsed or refractory multiple myeloma (R/R MM), while some patients do not response, or relapse in short term after treatment. Combining with anti-CD38 might solve the problem of targeting BCMA alone. We aimed to assess the efficacy and safety of BCMA and CD38 (BCMA-CD38) bispecific CAR-T cells in R/R MM patients.

hsa‑miR‑429 targets CBX8 to promote cell apoptosis in diffuse large B‑cell lymphoma.

Diffuse large B‑cell lymphoma (DLBCL) is the most common type of non‑Hodgkin lymphoma worldwide. Several studies have indicated that (hsa)‑microRNA (miR)‑429 exerts a tumor‑suppressive effect on a variety of malignant tumors. To the best of our knowledge, the molecular function and mechanism of action of hsa‑miR‑429 in DLBCL have not been evaluated to date.

A Contour Co-Tracking Method for Image Pairs.

We proposed a contour co-tracking method for co-segmentation of image pairs based on active contour model. Our method comprehensively re-models objects and backgrounds signified by level set functions, and leverages Hellinger distance to measure the similarity between image regions encoded by probability distributions. The main contribution are as follows.

Efficient Unsupervised Dimension Reduction for Streaming Multiview Data.

Multiview learning has received substantial attention over the past decade due to its powerful capacity in integrating various types of information. Conventional unsupervised multiview dimension reduction (UMDR) methods are usually conducted in an offline manner and may fail in many real-world applications, where data arrive sequentially and the data distribution changes periodically. Moreover, satisfying the requirements of high memory consumption and expensive retraining of the time cost in large-scale scenarios are difficult.

Clinical characteristics of patients with 2019 coronavirus disease in a non-Wuhan area of Hubei Province, China: a retrospective study.

Background: Since December 2019, the 2019 coronavirus disease (COVID-19) has expanded to cause a worldwide outbreak that more than 600,000 people infected and tens of thousands died. To date, the clinical characteristics of COVID-19 patients in the non-Wuhan areas of Hubei Province in China have not been described.

Methods: We retrospectively analyzed the clinical characteristics and treatment progress of 91 patients diagnosed with COVID-19 in Jingzhou Central Hospital.

Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information.

The dorsal hand vein images captured by cross-device may have great differences in brightness, displacement, rotation angle and size. These deviations must influence greatly the results of dorsal hand vein recognition. To solve these problems, the method of dorsal hand vein recognition was put forward based on bit plane and block mutual information in this paper.

Fusing multi-scale information in convolution network for MR image super-resolution reconstruction.

Background: Magnetic resonance (MR) images are usually limited by low spatial resolution, which leads to errors in post-processing procedures. Recently, learning-based super-resolution methods, such as sparse coding and super-resolution convolution neural network, have achieved promising reconstruction results in scene images. However, these methods remain insufficient for recovering detailed information from low-resolution MR images due to the limited size of training dataset.

[Application of Real-time Quantitative PCR in Detecting Atypical BCR/ABL mRNA Transcripts in Chronic Myelocytic Leukemia].

Objective: To detect atypical BCR/ABL mRNA transcript by real-time quantitative PCR in CML patients without e13a2/e14a2,e19a2 or e1a2 transcripts, and investigate its value of clinical application.

Methods: Twelve cases of CML with positive for t(9;22) translocation, but negative for common major and minor breakpoint cluster regions comfirmed by chromosome karyotyping or FISH analysis, were collected from July 2012 to December 2015. These 12 cases were then detected for b2a3(e13a3), b3a3(e14a3), e6a2, e8a2 and e1a3 fusion variants by real-time quantitative PCR.

A Regularization Approach for Instance-Based Superset Label Learning.

Different from the traditional supervised learning in which each training example has only one explicit label, superset label learning (SLL) refers to the problem that a training example can be associated with a set of candidate labels, and only one of them is correct. Existing SLL methods are either regularization-based or instance-based, and the latter of which has achieved state-of-the-art performance. This is because the latest instance-based methods contain an explicit disambiguation operation that accurately picks up the groundtruth label of each training example from its ambiguous candidate labels.

Non-fragile sampled-data robust synchronization of uncertain delayed chaotic Lurie systems with randomly occurring controller gain fluctuation.

This paper proposes a new non-fragile stochastic control method to investigate the robust sampled-data synchronization problem for uncertain chaotic Lurie systems (CLSs) with time-varying delays. The controller gain fluctuation and time-varying uncertain parameters are supposed to be random and satisfy certain Bernoulli distributed white noise sequences. Moreover, by choosing an appropriate Lyapunov-Krasovskii functional (LKF), which takes full advantage of the available information about the actual sampling pattern and the nonlinear condition, a novel synchronization criterion is developed for analyzing the corresponding synchronization error system.

Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time.

Robust Nonnegative Patch Alignment for Dimensionality Reduction.

Dimensionality reduction is an important method to analyze high-dimensional data and has many applications in pattern recognition and computer vision. In this paper, we propose a robust nonnegative patch alignment for dimensionality reduction, which includes a reconstruction error term and a whole alignment term. We use correntropy-induced metric to measure the reconstruction error, in which the weight is learned adaptively for each entry.

Error analysis of stochastic gradient descent ranking.

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc.

Error analysis of coefficient-based regularized algorithm for density-level detection.

In this letter, we consider a density-level detection (DLD) problem by a coefficient-based classification framework with [Formula: see text]-regularizer and data-dependent hypothesis spaces. Although the data-dependent characteristic of the algorithm provides flexibility and adaptivity for DLD, it leads to difficulty in generalization error analysis. To overcome this difficulty, an error decomposition is introduced from an established classification framework.

[Regulatory effect of curcumin on p300 and HDAC1 in B-NHL cells].

The purpose of this study was to investigate the effect of curcumin on proliferation of B-NHL Raji cell line and explore the relationship between this effect and regulatory expression of p300 and HDAC1 transcription. The in vitro cultured Raji cells were treated with curcumin at various concentrations (6.25-50 micromol/L) and at different time points (0, 6, 12, 24 and 48 hours), the inhibitory ratio of cell growth was measured by MTT assay, the cell apoptosis rate was detected by flow cytometry with Annexin V-FITC/PI double staining, the changes of p300 and HDAC1 mRNA expression and protein level in Raji cells were determined by RT-PCR and Western blot.

An improved LDA approach.

Linear discrimination analysis (LDA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Despite these efforts, there persist in LDA at least three areas of weakness. The first weakness is that not all the discrimination vectors that are obtained are useful in pattern classification.