Growth of mesenchymal stem cells at the surface of silicone, mineral and plant-based oils.

Bioemulsions are attractive platforms for the expansion of adherent cells in bioreactors. Their design relies on the self-assembly of protein nanosheets at liquid-liquid interfaces, displaying strong interfacial mechanical properties and promoting integrin-mediated cell adhesion. However, most systems developed to date have focused on fluorinated oils, which are unlikely to be accepted for direct implantation of resulting cell products for regenerative medicine, and protein nanosheets self-assembly at other interfaces has not been investigated. In this report, the composition of aliphatic pro-surfactants palmitoyl chloride and sebacoyl chloride, on the assembly kinetics of poly(L-lysine) at silicone oil interfaces and characterisation of ultimate interfacial shear mechanics and viscoelasticity is presented. The impact of the resulting nanosheets on the adhesion of mesenchymal stem cells (MSCs) is investigated via immunostaining and fluorescence microscopy, demonstrating the engagement of the classic focal adhesion-actin cytoskeleton machinery. The ability of MSCs to proliferate at the corresponding interfaces is quantified. In addition, expansion of MSCs at other non-fluorinated oil interfaces, based on mineral and plant-based oils is investigated. Finally, the proof-of-concept of such non-fluorinated oil systems for the formulation of bioemulsions supporting stem cell adhesion and expansion is demonstrated.

Mesenchymal Stem Cells Sense the Toughness of Nanomaterials and Interfaces.

Stem cells are known to sense and respond to the mechanical properties of biomaterials. In turn, cells exert forces on their environment that can lead to striking changes in shape, size and contraction of associated tissues, and may result in mechanical disruption and functional failure. However, no study has so far correlated stem cell phenotype and biomaterials toughness. Indeed, disentangling toughness-mediated cell response from other mechanosensing processes has remained elusive as it is particularly challenging to uncouple Youngs' or shear moduli from toughness, within a range relevant to cell-generated forces. In this report, it is shown how the design of the macromolecular architecture of polymer nanosheets regulates interfacial toughness, independently of interfacial shear storage modulus, and how this controls the expansion of mesenchymal stem cells at liquid interfaces. The viscoelasticity and toughness of poly(l-lysine) nanosheets assembled at liquid-liquid interfaces is characterised via interfacial shear rheology. The local (microscale) mechanics of nanosheets are characterised via magnetic tweezer-assisted interfacial microrheology and the thickness of these assemblies is determined from in situ ellipsometry. Finally, the response of mesenchymal stem cells to adhesion and culture at corresponding interfaces is investigated via immunostaining and confocal microscopy.

Impact of the multiscale viscoelasticity of quasi-2D self-assembled protein networks on stem cell expansion at liquid interfaces.

Although not typically thought to sustain cell adhesion and expansion, liquid substrates have recently been shown to support such phenotypes, providing protein nanosheets could be assembled at corresponding liquid-liquid interfaces. However, the precise mechanical properties required from such quasi-2D nanoassemblies and how these correlate with molecular structure and nanoscale architecture has remained unclear. In this report, we screen a broad range of surfactants, proteins, oils and cell types and correlate interfacial mechanical properties with stem cell expansion. Correlations suggest an impact of interfacial viscoelasticity on the regulation of such behaviour. We combine interfacial rheology and magnetic tweezer-based interfacial microrheology to characterise the viscoelastic profile of protein nanosheets assembled at liquid-liquid interfaces. Based on neutron reflectometry and transmission electron microscopy data, we propose that the amorphous nanoarchitecture of quasi-2D protein nanosheets controls their multi-scale viscoelasticity which, in turn, correlates with cell expansion. This understanding paves the way for the rational design of protein nanosheets for microdroplet and bioemulsion-based stem cell manufacturing and screening platforms.

Bibliometric analysis of the global literature productivity of adult-onset Still's disease (2011-2020).

Adult-onset Still's disease is a nonfamilial, or sporadic, systemic autoinflammatory disorder accompanied by peak fever ≥ 39 °C, arthralgia or arthritis, skin rashes, leukocytosis (≥ 10,000 cells/mm3) with neutrophils ≥ 80%, and other clinical symptoms. This study aimed to analyze the quantity and quality of publications, and to exhibit the current global status and trend of adult-onset Still's disease research. Searched with the search term 'Adult onset Still disease' on the Web of Science for time limited to 2011-2020. Original articles and reviews were selected. A total of 537 articles were retrieved from 44 countries, of which 13 met the criteria of major active countries. High-income countries contributed 378 articles (70.39%). The number of articles annually increased significantly in the 10-year period (P < 0.001). China (n = 90, 16.76%), Japan (n = 79, 14.71%), Italy (n = 59, 10.99%), the United States (n = 52, 9.68%) and South Korea (n = 45, 8.38%) are the five most productive countries. Adjusted by population, Italy led the top list, followed by South Korea and Israel. According to gross domestic product analysis, Italy ranked first, followed by Portugal and Turkey. A significant correlation was detected between average citations and AAS (P = 0.002), MRC (P < 0.001). From 2011 to 2020, the number of global articles was increasing rapidly. Most papers came from high-income countries. The relationship between the bibliometric and altmetric analyses are basically consistent, therefore the two can prove/complement each other.

Long term expansion profile of mesenchymal stromal cells at protein nanosheet-stabilised bioemulsions for next generation cell culture microcarriers.

Tremendous progress in the identification, isolation and expansion of stem cells has allowed their application in regenerative medicine and tissue engineering, and their use as advanced in vitro models. As a result, stem cell manufacturing increasingly requires scale up, parallelisation and automation. However, solid substrates currently used for the culture of adherent cells are poorly adapted for such applications, owing to their difficult processing from cell products, relatively high costs and their typical reliance on difficult to recycle plastics and microplastics. In this work, we show that bioemulsions formed of microdroplets stabilised by protein nanosheets displaying strong interfacial mechanics are well-suited for the scale up of adherent stem cells such as mesenchymal stromal cells (MSCs). We demonstrate that, over multiple passages (up to passage 10), MSCs retain comparable phenotypes when cultured on such bioemulsions, solid microcarriers (Synthemax II) and classic 2D tissue culture polystyrene. Phenotyping (cell proliferation, morphometry, flow cytometry and differentiation assays) of MSCs cultured for multiple passages on these systems indicate that, although stemness is lost at late passages when cultured on these different substrates, stem cell phenotypes remained comparable between different culture conditions, at any given passage. Hence our study validates the use of bioemulsions for the long term expansion of adherent stem cells and paves the way to the design of novel 3D bioreactors based on microdroplet microcarriers.

Carotid intima-media thickness in patients with hyperuricemia: a systematic review and meta-analysis.

OBJECTIVE: Despite the high incidence and mortality of cardiovascular events in hyperuricemia patients, the role of serum uric acid in cardiovascular diseases is still controversial. The aim of this meta-analysis was to explore the difference of carotid intima-media thickness in hyperuricemia and control groups. METHODS: We performed this meta-analysis by searching the PubMed, Cochrane Library, Embase and Web of Science databases up to July 2020. The 95% confidence intervals and standard mean differences were calculated to analyze the differences in carotid intima-media thickness in hyperuricemia groups and control groups. Sensitivity analysis, subgroup analysis and meta-regression were used to explore the sources of heterogeneity. Publication bias was evaluated by funnel plot and Begg's regression test. We used Stata 14.0 software to complete our analyses. RESULTS: A total of 8 articles were included. The results showed that there was a significant increase in carotid intima-media thickness in the hyperuricemia groups compared with the control groups [SMD = 0.264, 95% CI (0.161-0.366), P < 0.001]. Subgroup analyses showed that age, sample size, blood pressure and body mass index were not the source of heterogeneity. Meta-regression enrolled the method of CIMT measurement, location, age, smoking and diabetes mellitus as categorical variables, but none of these factors was found to be significant in the model. The Begg's test value (P = 0.174) was greater than 0.05, indicating there was no publication bias. CONCLUSION: The results showed that carotid intima-media thickness was increased in hyperuricemia patients compared with controls, which indicated that hyperuricemia patients may have a higher risk of cardiovascular diseases.

Extreme reversal in mechanical anisotropy in liquid-liquid interfaces reinforced with self-assembled protein nanosheets.

The structuring of liquid-liquid and liquid-air interfaces may play an important role in novel microfabrication platforms and biotechnologies, from the spontaneous formation of microfilaments from liquid droplets and the 3D printing of liquids, to the culture of stem cells on emulsions. Understanding the mechanical anisotropy of associated liquid interfaces is essential for the development of such systems. Models of AFM indentation at liquid interfaces, based on the Young-Laplace model, currently do not allow the quantification of interfacial mechanical properties of associated molecular films. This report presents such a model and compares its predictions to interfacial mechanical properties characterised via interfacial shear rheology. An extreme reversal of mechanical anisotropy of liquid-liquid interfaces is observed, upon self-assembly of protein nanosheets, by 5 orders of magnitude. Results indicate that, although interfacial rheology is more sensitive than AFM indentation to the mechanics of molecular films in the low range of interfacial mechanics, AFM indentation allows the quantification of mechanical properties of stiffer molecular films, and remains better adapted to the characterisation of small samples and enables the characterisation of local heterogeneity.

Does vitamin D improve symptomatic and structural outcomes in knee osteoarthritis? A systematic review and meta-analysis.

OBJECTIVE: To provide evidence on the effects of vitamin D supplementation on knee osteoarthritis (KOA) and new targets for clinical prevention and treatment of KOA. METHOD: The PubMed, Embase, Web of science, Wanfang, CNKI and SinoMed databases were retrieved to investigate the effects of vitamin D supplementation on patients with KOA. The search time was from databases establishment to 15 November 2020. RevMan5.3 software was used for meta-analysis. The results were expressed as standardized mean difference (SMD) with 95% confidence interval (CI) or weighted mean difference (WMD) with 95% confidence interval (CI). RESULTS: A total of 1599 patients with osteoarthritis of the knee were included in the study, which involved six articles. The results of the meta-analysis showed that vitamin D supplementation is statistically significant for WOMAC score (SMD = - 0.67, 95% CI - 1.23 to - 0.12) in patients with KOA, including WOMAC pain score (SMD = - 0.32, 95% CI - 0.63 to - 0.02), function score (SMD = - 0.34, 95% CI - 0.60 to - 0.08) and stiffness score (SMD = - 0.13, 95% CI - 0.26 to - 0.01). In subgroup analysis, vitamin D supplementation less than 2000 IU was statistically significant for the reduction of stiffness score (SMD = - 0.22, 95% CI - 0.40 to - 0.04). Vitamin D supplements can reduce synovial fluid volume progression in patients with KOA (SMD = - 0.20, 95% CI - 0.39 to - 0.02). There was no statistical significance in improving tibia cartilage volume (SMD = 0.12, 95% CI - 0.05 to 0.29), joint space width (SMD = - 0.10, 95% CI - 0.26 to 0.05) and bone marrow lesions (SMD = 0.03, 95% CI - 0.26 to 0.31). CONCLUSION: Vitamin D supplements can improve WOMAC pain and function in patients with KOA. But there is a lack of strong evidence that vitamin D supplementation can prevent structural progression in patients with KOA.

CNN-Based Volume Flow Rate Prediction of Oil-Gas-Water Three-Phase Intermittent Flow from Multiple Sensors.

In this paper, we propose a deep-learning-based method using a convolutional neural network (CNN) to predict the volume flow rates of individual phases in the oil-gas-water three-phase intermittent flow simultaneously by analyzing the measurement data from multiple sensors, including a temperature sensor, a pressure sensor, a Venturi tube and a microwave sensor. To build datasets, a series of experiments for the oil-gas-water three-phase intermittent flow in a horizontal pipe, in which gas volume fraction and water-in-liquid ratio ranges are 23.77-94.45% and 14.95-86.97%, respectively, and gas flow superficial velocity and liquid flow superficial velocity ranges are 0.66-5.23 and 0.27-2.14 m/s, respectively, have been carried out on a test loop pipeline. The preliminary results indicate that the model can provide relative prediction errors on the testing-1 dataset for the volume flow rates of oil-phase, gas-phase and water-phase within ±10% with 94.49%, 92.56% and 95.71% confidence levels, respectively. Additionally, the prediction results on the testing-2 dataset also demonstrate the generalization ability of the model. The consuming time of a prediction with one sample is 0.43 s on an Intel Xeon CPU E5-2678 v3, and 0.01 s on an NVIDIA GeForce GTX 1080 Ti GPU. Hence, the proposed CNN-based prediction model, which can fulfill the real-time application requirements in the petroleum industry, reveals the potential of using deep learning to obtain accurate results in the multiphase flow measurement field.

HDAC1 potentiates CD4 + T cell activation by inhibiting miR-124 and promoting IRF1 in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease leading to considerable morbidity worldwide, which can be developed from a breakdown in immunological tolerance, resulting in T cell hyperactivation. T cell hyperactivation has been implicated in the tissue damage associated with many diseases. Although many researchers have identified the involvement of T-cell receptor-associated signaling molecules in T-cell activation, the mechanisms underlying this process are yet to be elaborated. In the current study, we set out to reveal a novel transcriptional mechanism required for CD4 + T cell immunoactivity involved in SLE. First of all, miR-124 was experimentally determined to be under-expressed in peripheral blood samples of SLE patients relative to healthy individuals. We further isolated CD4 + T cells from the peripheral blood samples of SLE patients and healthy individuals, and found that miR-124 was poorly expressed in peripheral blood-derived CD4 + T cells of SLE patients. Subsequent experiments demonstrated that re-expression of miR-124 inhibited the immunoactivity of CD4 + T cells from SLE patients, which was achieved through the down-regulation of IRF1 since dual-luciferase reporter gene assay findings indicated that miR-124 could target IRF1. In addition, HDAC1 was found to be enriched at the miR-124 promoter resulting in inhibition of miR-124 expression, thereby promoting the immunoactivity of CD4 + T cells. In conclusion, we identify that as a stimulator of CD4 + T cell immunoactivity, HDAC1 may be implicated in the immunopathology of SLE. The study will open up new avenues to explore future immunotherapy strategies for SLE.

Top 100 Cited Articles on Osteoarthritis from 1990 to 2020.

Objectives: The purpose of this study was to identify and analyze the 100 top-cited articles in the field of osteoarthritis (OA) from 1990 to 2020. Methods: We used the Web of Science to retrieve the articles related to OA. Then we selected 100 target articles and manually collected their general information, including article title, author, year of publication, journal, type of article, and the number of citations. Results: The 100 top-cited articles were published in the period from 1990 to 2015. These articles have been cited 66,494 times in total, with the highest being 2382 times, the lowest being 433 times, the median number being 613, and a mean of 664.94 times. The 100 top-cited articles appeared in a total of 35 influential journals. The greatest number of articles in the top of 100 was published in Arthritis and Rheumatism. The authors of these articles came from 18 countries, led by the United States (n = 48), followed by the United Kingdom (n = 15). Among all the institutions, Boston University led the list with 10 articles. The most prevalent type of the study was review (n = 38) and clinical study (n = 38), followed by guideline (n = 12), basic science (n = 10) and other types. Conclusions: This study provided some insights on the literature development and citation of OA in the recent 30 years. Articles published in high-impact journals are more likely to be cited in the field of OA. As recent studies did not have enough time to accumulate the number of citations, the latest articles may not be included in the top 100 cited articles.

The risk of leukemia in patients with rheumatoid arthritis: a systematic review and meta-analysis.

OBJECTIVES: The relationship between rheumatoid arthritis (RA) and the risk of leukemia was still controversial. This study aimed to assess the risk of leukemia in patients with rheumatoid arthritis by systematic review and meta-analysis. METHODS: Relevant studies were identified by searching PubMed, Embase, Cochrane Library, and SinoMed up to December 2019. Random effects model analysis was used to pool standardized incidence ratios (SIRs) and 95% confidence interval. RESULTS: A total of 15 relevant studies that met the criteria were included. Compared with the general population, patients with RA showed an increased risk of leukemia (SIR = 1.51, 95% CI: 1.34-1.70). The statistical heterogeneity was moderate with an I2 of 55.5%. In subgroup analysis, the source of heterogeneity may be due to differences in sample size. Publication bias was not found in the Begg funnel plot and the Egger test. CONCLUSION: Our findings suggested that the risk of leukemia in RA was increased compared with the general population. Key points • This is the first systematic review and meta-analysis to assess the risk of leukemia in RA. • Our study suggested that the risk of leukemia in RA was increased compared with the general population. • This study indicated that the risk of leukemia in RA was higher in non-Asian populations.

Silencing long non-coding RNA NEAT1 attenuates rheumatoid arthritis via the MAPK/ERK signalling pathway by downregulating microRNA-129 and microRNA-204.

The participation of long noncoding RNAs (lncRNAs) and microRNAs (miRs) in the progression of rheumatoid arthritis (RA) is a key area of investigation. The current study aimed to investigate the action of lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) in fibroblast-like synoviocyte (FLS) proliferation and synovitis in RA. A rat model of RA was established. LncRNA NEAT1 expression in the synovial tissues of patients with RA and FLSs from the RA rat model was determined using RT-qPCR. Next, dual luciferase reporter gene assay was applied to investigate the relationship between miR-129/204 and mitogen-activated protein kinase (MAPK)/extracellular regulated protein kinase (ERK). A putative binding relationship between miR-204 and lncRNA NEAT1 was evaluated by RIP assay, and miR-129 promoter methylation was determined using MSP. After the expression of lncRNA NEAT1, miR-129 or miR-204 was altered in FLSs, the extent of ERK1/2 phosphorylation was assessed. In addition, FLS synovitis and proliferation were determined by ELISA and EdU assay, respectively. In RA rats, lncRNA NEAT1 was silenced and miR-129/miR-204 was overexpressed to explore their roles in vivo. LncRNA NEAT1 was upregulated, while miR-129 and miR-204 were downregulated in RA synovial tissues and FLSs. MAPK1 was target gene of both miR-129 and miR-204. LncRNA NEAT1 bound to miR-204 and promoted miR-129 promoter methylation. Silencing lncRNA NEAT1 or overexpressing miR-129/miR-204 enhanced miR-129/miR-204 expression, but reduced the extent of ERK1/2 phosphorylation, proliferation of FLSs, and synovitis in RA. Collectively, silencing lncRNA NEAT1 promoted miR-129 and miR-204 to inhibit the MAPK/ERK signalling pathway, reducing FLS synovitis in RA.Abbreviations: ACR: American College of Rheumatology; ELISA: Enzyme-linked immunosorbent assay; ERK: extracellular signal-regulated kinase; FLS: fibroblast-like synoviocyte; GADPH: glyceraldehyde-3-phosphate dehydrogenase; HRP: horseradish peroxidase; IFA: Incomplete Freund's Adjuvant; lncRNAs: long noncoding RNAs; MSP: Methylation-specific PCR; NC: negative control; NEAT1: nuclear paraspeckle assembly transcript 1; OD: optical density; RA: rheumatoid arthritis; RIPA: Radio Immunoprecipitation Assay; RLU: relative light units; RT-qPCR: reverse transcription quantitative polymerase chain reaction; UTR: untranslated region.

Exosomal miRNA-486-5p derived from rheumatoid arthritis fibroblast-like synoviocytes induces osteoblast differentiation through the Tob1/BMP/Smad pathway.

The pathogenesis of rheumatoid arthritis (RA) is related to the inhibition of osteoblast differentiation. Exosomes secreted from RA fibroblast-like synoviocytes (RA-FLSs-exos) are associated with the pathogenesis of RA and microRNAs (miRNAs) being crucial for RA progression. Accordingly, the aim of the present study is to elucidate the effect of RA-FLS-derived exosomes on osteoblast differentiation and further identify exosomal cargos responsible for this effect. RA-FLSs were isolated from a RA patient and osteoblasts from the donor bone. Isolated RA-FLSs-exos were co-cultured with osteoblasts. Osteoblast differentiation was evaluated by ALP quantification assays, Alizarin Red S staining, and determining markers of osteoblast activity (Osx, OC, Col1a1 and Dlx2). Collagen induced arthritis (CIA)-induced mouse models were established. RA-FLSs-exo could be phagocytosed by osteoblasts. Elevating the expression of miR-486-5p in RA-FLSs-exo promoted osteoblast differentiation. miR-486-5p targeted Tob1 and activated the BMP/Smad signaling pathway in osteoblasts. In addition, RA-FLSs-exo containing miR-486-5p facilitated osteoblast differentiation by activating the BMP/Smad signaling pathway and repressing Tob1. Moreover, RA-FLSs-exo containing miR-486-5p alleviated the disease severity of RA by decreasing Tob1 expression in CIA-induced mice. To sum up, RA-FLSs-exo carrying miR-486-5p serve as a promoter for osteoblast differentiation in RA, ultimately highlighting a promising competitive new target for RA treatment.

An Electrical Capacitance Array for Imaging of Water Leakage inside Insulating Slabs with Porous Cells.

The paper proposes a capacitance-sensor-array-based imaging system to detect water leakage inside insulating slabs with porous cells, such as anechoic acoustic rubber tiles. The modeling is conducted by using the finite element method to obtain the electrical potential distribution and sensitivity map with the proposed capacitance sensor array. An experimental test setup, which is composed of an eight-electrode capacitance sensor array and a commercialized capacitance bridge instrument for measurement, is developed. Experiments regarding different leakage scenarios are carried out by using the test setup. Preliminary results standing for different water leakage cases, which are based on the experimental data obtained from the test setup, are presented and depicted as images reconstructed by using different algorithms including the linear back projection (LBP), the projected Landweber iteration, and the total variation regularization. These results demonstrate that the proposed capacitance sensor array is feasible and has a great potential for imaging of water leakage inside insulating slabs with porous cells. A cost-effective capacitance measurement circuit for practical applications is also proposed and simulated.

A Benchmark Dataset and Deep Learning-Based Image Reconstruction for Electrical Capacitance Tomography.

Electrical Capacitance Tomography (ECT) image reconstruction has developed for decades and made great achievements, but there is still a need to find a new theoretical framework to make it better and faster. In recent years, machine learning theory has been introduced in the ECT area to solve the image reconstruction problem. However, there is still no public benchmark dataset in the ECT field for the training and testing of machine learning-based image reconstruction algorithms. On the other hand, a public benchmark dataset can provide a standard framework to evaluate and compare the results of different image reconstruction methods. In this paper, a benchmark dataset for ECT image reconstruction is presented. Like the great contribution of ImageNet that transformed machine learning research, this benchmark dataset is hoped to be helpful for society to investigate new image reconstruction algorithms since the relationship between permittivity distribution and capacitance can be better mapped. In addition, different machine learning-based image reconstruction algorithms can be trained and tested by the unified dataset, and the results can be evaluated and compared under the same standard, thus, making the ECT image reconstruction study more open and causing a breakthrough.

Stem Cell Expansion and Fate Decision on Liquid Substrates Are Regulated by Self-Assembled Nanosheets.

The culture of adherent cells is overwhelmingly relying on the use of solid substrates to support cell adhesion. Indeed, it is typically thought that relatively strong bulk mechanical properties (bulk moduli in the range of kPa to GPa) are essential to promote cell adhesion and, in turn, regulate cell expansion and fate decision. In this report, we show that adherent stem cells such as mesenchymal stem cells and primary keratinocytes can be cultured at the surface of liquid substrates and that this phenomenon is mediated by the assembly of polymer nanosheets at the liquid-liquid interface. We use interfacial rheology to quantify this assembly and demonstrate the strong mechanical properties of such nanosheets. Importantly, we show that cell adhesion to such quasi-2D materials is mediated by the classical integrin/acto-myosin machinery, despite the absence of bulk mechanical properties of the underlying liquid substrate. Finally, we show that stem cell proliferation and fate decision are also regulated by the mechanical properties of these self-assembled protein nanosheets. Liquid substrates offer attractive features for the culture of adherent cells and stem cells, and the development of novel stem cell technologies, such as liquid-liquid systems, are particularly well-adapted to automated parallel processing and scale up.

Optimal donor for severe aplastic anemia patient requiring allogeneic hematopoietic stem cell transplantation: A large-sample study from China.

HLA-haploidentical hematopoietic stem cell transplantation (HSCT) may be an option for severe aplastic anemia (SAA) patients. However, to date, no large-sample studies have been performed to determine which types of SAA patients are suitable for HLA-haploidentical HSCT. We retrospectively studied 189 consecutive patients with SAA who underwent HLA-identical or HLA-haploidentical HSCT at seven transplant centers in China. Propensity score matching (PSM) was applied in this study to reduce the influence of potential confounders. The 5-year overall survival (OS) rate was 72.0% in the HLA-haploidentical group and 76.5% in the HLA-identical group. The median time to achieve engraftment and the incidence of acute GVHD/chronic GVHD were not significantly different between the two groups. In the subgroup analysis, the outcome of patients older than 40 years in the HLA-haploidentical group was significantly poorer than that of patients younger than 40 years in the same group and that of patients older than 40 years in the HLA-identical group. Based on the above results, we suggest that HLA-haploidentical relative HSCT should be considered as a valid alternative option for patients younger than 40 years with SAA for whom no matched sibling donor is available.

Exploiting ensemble learning for automatic cataract detection and grading.

Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs. To date, studies reported in the literature utilize a single learning model for retinal image classification in grading cataract severity. We present an ensemble learning based approach as a means to improving diagnostic accuracy. Three independent feature sets, i.e., wavelet-, sketch-, and texture-based features, are extracted from each fundus image. For each feature set, two base learning models, i.e., Support Vector Machine and Back Propagation Neural Network, are built. Then, the ensemble methods, majority voting and stacking, are investigated to combine the multiple base learning models for final fundus image classification. Empirical experiments are conducted for cataract detection (two-class task, i.e., cataract or non-cataractous) and cataract grading (four-class task, i.e., non-cataractous, mild, moderate or severe) tasks. The best performance of the ensemble classifier is 93.2% and 84.5% in terms of the correct classification rates for cataract detection and grading tasks, respectively. The results demonstrate that the ensemble classifier outperforms the single learning model significantly, which also illustrates the effectiveness of the proposed approach.

Bortezomib-thalidomide-based regimens improved clinical outcomes without increasing toxicity as induction treatment for untreated multiple myeloma: a meta-analysis of phase III randomized controlled trials.

Novel agents thalidomide and bortezomib have significantly improved myeloma treatment. However, it remains unclear whether patients will benefit more from the combination therapy of these two agents. Our meta-analysis aims to compare the efficiency, and more importantly, the safety of bortezomib-thalidomide-based (VT-based) versus bortezomib-based or thalidomide-based (V-based/T-based) regimens as induction therapy in patients with previously untreated myeloma. Overall, five phase III RCTs including 1765 patients were identified. Compared with V-based or T-based regimens, VT-based regimens significantly improved CR (OR=2.22, 95% CI [1.44, 3.43]), ORR (OR=2.19, 95% CI [1.51, 3.19]) as well as PFS (HR=0.69, 95% CI [0.54, 0.88]), but not OS (HR=1.04, 95% CI [0.91, 1.19]). Notably, most expected side effects of bortezomib or thalidomide were comparable in both groups, including hematologic (anemia, neutropenia, thrombocytopenia), nonhematologic (peripheral neuropathy, deep venous thrombosis, infections, gastrointestinal events) side effects and discontinuation during or after induction therapy. These results suggest that combination of thalidomide and bortezomib might be a better first-line choice for patients with untreated myeloma.