Therapeutic potential of mesenchymal stem cells for refractory inflammatory and immune skin diseases

Inflammatory and immunological skin diseases such as psoriasis, systemic sclerosis, dermatomyositis and atopic dermatitis, whose abnormal skin manifestations not only affected life quality but also caused social discrimination, have been wildly concerned. Complex variables such as hereditary predisposition, racial differences, age and gender can influence the prevalence and therapeutic options. The population of patients with unsatisfactory curative effects under current therapies is growing, it’s advisable to seek novel and advanced therapies that are less likely to cause systemic damage. Mesenchymal stem cells (MSCs) have been proven with therapeutic benefits in tissue regeneration, self-renewal and differentiation abilities when treating refractory skin disorders in preclinical and clinical studies. Here we highlighted the immune modulation and inflammation suppression of MSCs in skin diseases, summarized current studies, research progress and related clinical trials, hoping to strengthen the confidence of promising MSCs therapy in future clinical application

Magnetic Luffa-Leaf-Derived Hierarchical Porous Biochar for Efficient Removal of Rhodamine B and Tetracycline Hydrochloride

Luffa leaf (LL) is an agricultural waste produced by loofah. In this work, LL was used as biomass carbon source for biochars for the first time. After carbonization, activation, and chemical co-precipitation treatments, a magnetic lignocellulose-derived hierarchical porous biochar was obtained. The specific surface area and total pore volume were 2565.4 m2/g and 1.4643 cm3/g, and the surface was rich in carbon and oxygen functional groups. The synthetic dye rhodamine B (RhB) and the antibiotic tetracycline hydrochloride (TH) were selected as organic pollutant models to explore the ability to remove organic pollutants, and the results showed good adsorption performances. The maximum adsorption capacities were 1701.7 mg/g for RhB and 1755.9 mg/g for TH, which were higher than most carbon-based adsorbents. After 10 cycles of use, the removal efficiencies were still maintained at more than 70%, showing good stability. This work not only verified the feasibility of lignocellulose LL as a carbon source to prepare biochar but also prepared a magnetic hierarchical porous adsorbent with good performances that can better treat RhB and TH, which provided a new idea and direction for the efficient removal of organic pollutants in water

One-Step Synthesis of Nitrogen-Doped Porous Biochar Based on N-Doping Co-Activation Method and Its Application in Water Pollutants Control

In this work, birch bark (BB) was used for the first time to prepare porous biochars via different one-step methods including direct activation (BBB) and N-doping co-activation (N-BBB). The specific surface area and total pore volume of BBB and N-BBB were 2502.3 and 2292.7 m2/g, and 1.1389 and 1.0356 cm3/g, respectively. When removing synthetic methyl orange (MO) dye and heavy metal Cr6+, both BBB and N-BBB showed excellent treatment ability. The maximum adsorption capacities of BBB and N-BBB were 836.9 and 858.3 mg/g for MO, and 141.1 and 169.1 mg/g for Cr6+, respectively, which were higher than most previously reported biochar adsorbents. The probable adsorption mechanisms, including pore filling, π–π interaction, H-bond interaction, and electrostatic attraction, supported the biochars’ demonstrated high performance. In addition, after five recycles, the removal rates remained above 80%, which showed the high stability of the biochars. This work verified the feasibility of the one-step N-doping co-activation method to prepare high-performance biochars, and two kinds of biochars with excellent performance (BBB and N-BBB) were prepared. More importantly, this method provides new directions and ideas for the development and utilization of other biomasses

A Strong Machine Learning Classifier and Decision Stumps Based Hybrid AdaBoost Classification Algorithm for Cognitive Radios

Machine learning (ML) based classification methods have been viewed as one kind of alternative solution for cooperative spectrum sensing (CSS) in recent years. In this paper, ML techniques based CSS algorithms are investigated for cognitive radio networks (CRN). Specifically, a strong machine learning classifier (MLC) and decision stumps (DS) based adaptive boosting (AdaBoost) classification mechanism is proposed for pattern classification of the primary user’s behavior in the network. The conventional AdaBoost algorithm only combines multiple sub-classifiers and produces a strong weight based on their weights in classification. Taking into account the fact that the strong MLC and the weak DS serve as different sub-classifiers in classification, we propose employing a strong MLC as the first-stage classifier and DS as the second-stage classifiers, to eventually determine the class that the spectrum energy vector belongs to. We verify in simulations that the proposed hybrid AdaBoost algorithms are capable of achieving a higher detection probability than the conventional ML based spectrum sensing algorithms and the conventional hard fusion based CSS schemes

Influence of Microbial Treatment on the Preparation of Porous Biochar with Stepped-Up Performance and Its Application in Organic Pollutants Control

In this study, Irisensata Thunb grass (ITG) was used as a biomass carbon resource to prepare biochars for the first time. After microbial treatment, the obtained microbial-treated ITG (MITG) was activated by using a mixed base as an activator for preparation of biochar (MITGB). The specific surface area and total pore volume of MITGB were 3036.4 m2/g and 1.5252 cm3/g, which were higher than those of biochar prepared without microbial treatment (ITGB, 2930.0 m2/g and 1.5062 cm3/g). Besides, the physicochemical properties of MITGB and ITGB were also quite different including micro morphology, surface chemistry, functional groups, etc. In the experiment of removing organic pollutants with synthetic dye RhB and antibiotic TH as the models, MITGB showed excellent treatment ability. The maximum adsorption capacities of MITGB for RhB and TH were 1354.2 and 1462.6 mg/g, which were higher than most of the biochars. In addition, after five cycles of recycling, the adsorption capacities of the organic pollutant models can still be maintained at more than 80%, which showed high stability. This work verified the feasibility of microbial treatment to further improve the performance of biochar and provided a new idea and direction for exploring other biochars

The complicated use of dupilumab in the treatment of atypical generalized pemphigus erythematosus: A report of two cases

Pemphigus is a rare autoimmune disease and has the potential to be fatal without treatment. Pemphigus erythematosus (PE) is a benign type of pemphigus foliaceus. Glucocorticoids and immunosuppressive agents are primary therapeutic modalities in pemphigus erythematosus, which may lead to considerable side effects. There is a growing need for new pemphigus therapies with fewer adverse effects. Dupilumab is a humanized monoclonal IgG4 antibody that inhibits the signaling of interleukin-4 (IL-4) and interleukin-13 (IL-13) and has been applied for atopic dermatitis and asthma. Recently, dupilumab was thought to be beneficial in aggressive refractory pemphigus vulgaris. We report two cases: a 39-year-old male and a 59-year-old woman diagnosed with PE with atypical clinical features. With dupilumab, patients’ skin lesions significantly improved, and suitable maintenance glucocorticosteroid doses were reached. In conclusion, we reported the short-term effectiveness and safety of dupilumab in two cases of atypical generalized PE. As an adjunct, such a biologic agent is expected to be efficacious in pemphigus erythematosus

Preparation of a Highly Porous Carbon Material Based on Quinoa Husk and Its Application for Removal of Dyes by Adsorption

A porous carbon material was prepared from quinoa husk (QH) by carbonization and chemical activation with KOH. A series of experiments, including SEM (Scanning electron microscopy), FT-IR (Fourier transform infrared), XRD (X-ray diffraction), Raman, X-ray photoelectron spectroscopy (XPS), and N2 adsorption/desorption, were carried out on the porous carbon produced from quinoa husk (PC–QH). The results showed that PC–QH was mainly composed of activated carbon and graphite. Moreover, PC–QH exhibited a high level of porosity with a BET (the Brunauer–Emmett–Teller theory) surface area of 1713 m2 g−1. As a representative dye, malachite green (MG) was selected to evaluate the performance of PC–QH to absorb the contaminants in dyeing wastewater. In batch adsorption experiments, PC–QH exhibited a high adsorption rate toward malachite green (MG). An uptake capacity of 599.90 mg g−1 was achieved in the initial 5 min, and the MG adsorption capacity of PC–QH reached 1365.10 mg g−1, which was higher than many other adsorbents. The adsorption data were well fitted with the Freundlich isotherm model and the pseudo-second-order kinetic model. PC–QH also displayed a high absorption rate to rhodamine B (RhB), methyl violet (MV), methylene blue (MB), and methyl orange (MO). The results in this study suggest that PC–QH can be a promising adsorbent for quick treatment of dyeing wastewater

Time interval between breast cancer diagnosis and surgery is associated with disease outcome

Abstract Time interval between breast cancer (BC) diagnosis and surgery is of concern to patients and clinicians, but its impact on survival remains unclear. We identified 5130 BC patients receiving surgery between 2009 and 2017 from the Shanghai Jiaotong University Breast Cancer Database (SJTU-BCDB), and divided as Ruijin cohort and SJTU cohort. All participants were divided into three groups according to the interval between diagnosis and surgery: ≤ 1 week, 1–2 weeks, and > 2 weeks. Among 3144 patients of Ruijin cohort, the estimated 5-year breast cancer-free interval (BCFI) rates for the ≤ 1 week, 1–2 weeks and > 2 weeks groups were 91.8%, 87.5%, and 84.0% (P = 0.088), and the estimated 5-year overall survival (OS) rates were 95.6%, 89.6%, and 91.5% (P = 0.002). Multivariate analysis showed that patients with a TTS > 2 weeks had significantly lower BCFI (HR = 1.80, 95%CI 1.05–3.11, P = 0.034) and OS (HR = 2.07, 95% CI 1.04–4.13, P = 0.038) rates than patients with a TTS ≤ 1 week. Among 5130 patients when combining Ruijin cohort with SJTU cohort, the estimated 5-year BCFI rates for the ≤ 1 week, 1–2 weeks, and > 2 weeks groups were 91.0%, 87.9%, and 78.9%, and the estimated 5-year OS rates for the ≤ 1 week, 1–2 weeks, and > 2 weeks groups were 95.8%, 90.6%, and 91.5%, both with a significantly p value < 0.001. Our findings demonstrated the prolonged time to surgery (more than 2 weeks) after BC diagnosis was associated with poor disease outcomes, suggesting that efforts to early initiate treatment after diagnosis need to be pursued where possible to improve survival

Integrating Aerial LiDAR and Very-High-Resolution Images for Urban Functional Zone Mapping

This study presents a new approach for Urban Functional Zone (UFZ) mapping by integrating two-dimensional (2D) Urban Structure Parameters (USPs), three-dimensional (3D) USPs, and the spatial patterns of land covers, which can be divided into two steps. Firstly, we extracted various features, i.e., spectral, textural, geometrical features, and 3D USPs from very-high-resolution (VHR) images and light detection and ranging (LiDAR) point clouds. In addition, the multi-classifiers (MLCs), i.e., Random Forest, K-Nearest Neighbor, and Linear Discriminant Analysis classifiers were used to perform the land cover mapping by using the optimized features. Secondly, based on the land cover classification results, we extracted 2D and 3D USPs for different land covers and used MLCs to classify UFZs. Results for the northern part of Brooklyn, New York, USA, show that the approach yielded an excellent accuracy of UFZ mapping with an overall accuracy of 91.9%. Moreover, we have demonstrated that 3D USPs could considerably improve the classification accuracies of UFZs and land covers by 6.4% and 3.0%, respectively