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Evidence regarding screen use and outdoor activity during very early childhood (i. e., from aged 1 to 3 years) and their potential combined links to the later preschool myopia is limited. This information is needed to release effective public health messages and propose intervention strategies against preschool myopia. We collected information regarding very early childhood screen use, outdoor activity and the kindergartens vision screenings of 26,611 preschoolers from Longhua Child Cohort Study by questionnaires. Logistic regression models were used to examine the associations between reported outdoor activity, screen use from 1 to 3 years of age, and preschool myopia. Throughout very early childhood, from 1 to 3 years, the proportion of children exposed to screens increased (from 35.8 to 68.4%, p < 0.001), whereas the proportion of children who went outdoors ≥7 times/week (67.4–62.1%, p < 0.001) and who went outdoors for ≥60 min/time (53.3–38.0%, p < 0.001) declined. Exposure to fixed screen devices [adjusted odds ratio (AOR) = 2.66, 95% confidence interval (CI) = 2.09–3.44], mobile screen devices (AOR = 2.76, 95% CI = 2.15–3.58), and limited outdoor activity (AOR = 1.87, 95% CI = 1.42–2.51) during early childhood were associated with preschool myopia. Among children whose parents were myopic, the interactions between outdoor activity and fixed or mobile screen use on later preschool myopia were significant; the ORs and 95% CI were 3.34 (1.19–9.98) and 3.04 (1.06–9.21), respectively. Our findings suggest the possibility that the impact of screen exposure during early childhood on preschool myopia could be diminished by outdoor activity for children whose parents have myopia.

With the wide application of neodymium oxide nanoparticles (NPs-Nd2O3) in various fields, their health hazards have aroused public concern in recent years. However, data regarding the cytotoxicity of NPs-Nd2O3 is limited. In this study, we investigated the function and mechanism of long-chain non-coding RNAs (lncRNAs) in NPs-Nd2O3-induced airway inflammation. Treatment with NPs-Nd2O3 induced an inflammatory response in human bronchial epithelial cells (16HBE) by upregulating the expression of interleukin-6 (IL-6) and interleukin-8 (IL-8). The levels of LDH and intracellular ROS in the cells treated by various doses of NPs-Nd2O3 also increased significantly. After treatment with 10 μg/ml NPs-Nd2O3, RNA microarray and real-time quantitative polymerase chain reaction (qRT-PCR) showed a significant upregulation of lncRNA loc105377478. Functional experiments suggested lncRNA loc105377478 enhanced the expression of IL-6, IL-8 and ROS in NPs-Nd2O3-treated 16HBE cells, and it was further demonstrated that lncRNA loc105377478 promoted the activation of NF-κB by negatively regulating ADIPOR1 expression. Moreover, the expression of IL-6 and IL-8 in NPs-Nd2O3-treated 16HBE cells was regulated by lncRNA loc105377478, which was mediated by the NF-κB signaling pathway. In conclusion, lncRNA loc105377478 promotes NF-κB activation by negatively regulating ADIPOR1 expression, thereby upregulating the expression of IL-6 and IL-8 in 16HBE cells treated with NPs-Nd2O3.

Traditional Chinese medicines (TCMs) are medicines that are widely used in oriental countries under the guidance of ancient Chinese medicinal philosophies. With thousands of years of experiences in fighting against diseases, TCMs are gaining increasing importance in the world. Although the efficacy of TCMs is well recognized in clinic, the toxicity of TCMs has become a serious issue around the world in recent years. In general, the toxicity of TCMs is caused by the toxic medicinal compounds and contaminants in TCMs such as pesticides, herbicides, and heavy metals. Recent studies have demonstrated that gut microbiota can interact with TCMs and thus influence the toxicity of TCMs. However, there is no focused review on gut microbiota and the toxicity of TCMs. Here, we summarized the influences of the gut microbiota on the toxicity of medicinal compounds in TCMs and the corresponding mechanisms were offered. Then, we discussed the relationships between gut microbiota and the TCM contaminants. In addition, we discussed the methods of manipulating gut microbiota to reduce the toxicity of TCMs. At the end of this review, the perspectives on gut microbiota and the toxicity of TCMs were also discussed.

Transcription factors (TFs) are key proteins that modulate gene transcription and thereby lead to changes in the gene expression profile and the subsequent alteration of cellular functions. In the silk gland (SG) of silkworm Bombyx mori, an important silk-producing insect, TFs are of vital importance in the regulation of silk protein synthesis in this organ. However, which TFs exist and express in the SG remains largely unknown. Here, we report the large-scale identification of TFs in the SG based on available full-length transcript sequences and the most recent version of silkworm genome data. In total, 348 candidate TFs were identified by strict filtration and were classified into 56 TF families. Chromosomal distribution, motif composition, and phylogenetic relationship analyses revealed the typical characteristics of these TFs. In addition, the expression patterns of 348 TFs in various tissues of B. mori, especially the SG of fourth-molt (4LM) and day-3 and day-4 fifth-instar (5L3D and 5L4D) larvae, were investigated based on public RNA-seq data and gene microarray data, followed by spatiotemporal verification of TF expression levels by quantitative real-time PCR (qRT-PCR). This report describes the first comprehensive analysis of TFs in the B. mori SG. The results can serve as a baseline for further studies of the roles of TFs in the B. mori SG.

Aiming at the problems of low accuracy, low efficiency, and many parameters required in the current calculation of rock slope stability, a prediction model of rock slope stability is proposed, which combines principal component analysis (PCA) and relevance vector machine (RVM). In this model, PCA is used to reduce the dimension of several influencing factors, and four independent principal component variables are selected. With the help of RVM mapping the nonlinear relationship between the safety factor of slope stability and the principal component variables, the prediction model of rock slope stability based on PCA-RVM is established. The results show that under the same sample, the maximum relative error of the PCA-RVM model is only 1.26%, the average relative error is 0.95%, and the mean square error is 0.011, which is far lower than that of the RVM model and the GEP model. By comparing the results of traditional calculation method and PCA-RVM model, it can be concluded that the PCA-RVM model has the characteristics of high prediction accuracy, small discreteness, and high reliability, which provides reference value for accurately predicting the stability of rock slope.

N6-methyladenosine (m6A) is a post-transcriptional RNA modification and one of the most abundant types of RNA chemical modifications. m6A functions as a molecular switch and is involved in a range of biomedical aspects, including cardiovascular diseases, the central nervous system, and cancers. Conceptually, m6A methylation can be dynamically and reversibly modulated by RNA methylation regulatory proteins, resulting in diverse fates of mRNAs. This review focuses on m6A demethylases fat-mass- and obesity-associated protein (FTO) and alkB homolog 5 (ALKBH5), which especially erase m6A modification from target mRNAs. Recent advances have highlighted that FTO and ALKBH5 play an oncogenic role in various cancers, such as acute myeloid leukemias (AML), glioblastoma, and breast cancer. Moreover, studies in vitro and in mouse models confirmed that FTO-specific inhibitors exhibited anti-tumor effects in several cancers. Accumulating evidence has suggested the possibility of FTO and ALKBH5 as therapeutic targets for specific diseases. In this review, we aim to illustrate the structural properties of these two m6A demethylases and the development of their specific inhibitors. Additionally, this review will summarize the biological functions of these two m6A demethylases in various types of cancers and other human diseases.

Adverse drug reactions (ADRs) are a huge public health issue. Identifying text that mentions ADRs from a large volume of social media data is important. However, we need to address two challenges for high-performing ADR-related text detection: the data imbalance problem and the requirement of simultaneously using data-driven information and handcrafted information. Therefore, we propose an approach named multi-view active learning using domain-specific and data-driven document representations (MVAL4D), endeavoring to enhance the predictive capability and alleviate the requirement of labeled data. Specifically, a new view-generation mechanism is proposed to generate multiple views by simultaneously exploiting various document representations obtained using handcrafted feature engineering and by performing deep learning methods. Moreover, different from previous active learning studies in which all instances are chosen using the same selection criterion, MVAL4D adopts different criteria (i.e., confidence and informativeness) to select potentially positive instances and potentially negative instances for manual annotation. The experimental results verify the effectiveness of MVAL4D. The proposed approach can be generalized to many other text classification tasks. Moreover, it can offer a solid foundation for the ADR mention extraction task, and improve the feasibility of monitoring drug safety using social media data.

There exist various text-classification tasks using user-generated contents (UGC) on social media in the big data era. In view of advantages and disadvantages of feature-engineering-based machine-learning models and deep-learning models, we argue that fusing handcrafted-text representation via feature engineering and data-driven deep-text representations extracted by performing deep-learning methods is conducive to enhancing text-classification capability. Given the characteristics of different deep neural networks, their complementary effect needs to be investigated. Moreover, contributions of these representations need to be adaptively learned when it comes to addressing different tasks or predicting different samples. Therefore, in this paper, we propose a novel fused deep-neural-network architecture with a hierarchical attention mechanism for text classification with social media data. Specifically, in the context that handcraft features are available, we employ the attention mechanism to adaptively fuse totally data-driven-text representation and handcrafted representation. For the generation of the data-driven-text representation, we propose a data-driven encoder that fuses text representations derived from three deep-learning methods with the attention mechanism, to adaptively select discriminative representation and explore their complementary effect. To verify the effectiveness of our approach, we performed two text-classification tasks, i.e., identifying adverse drug reaction (ADR)-relevant tweets from social media and identifying comparative-relevant reviews from an E-commerce platform. Experimental results demonstrate that our approach outperforms other baselines.

ObjectivePrevious studies made controversial claims about the alleged effects of Kinesio taping (KT) on pain relief. To date, the mechanism by which KT relieves pain remains unclear. Moreover, pain evaluation lacks objective and quantitative parameters. This study compared the acute effects of different KT interventions on the local thresholds of pressure pain and current perception in healthy adults to determine the potential mechanisms by which KT relieves pain.MethodsThirty healthy female subjects randomly received four KT interventions, namely, no taping (NT), placebo taping (PT), Y strips of KT (KY), and fan strips of KT (KF), on the waist. Current perception threshold (CPT), pressure pain threshold (PPT), soft tissue hardness, and the visual analog scale (VAS) scores of the subjects’ perceived pain were immediately measured after taping. Repeated-measures ANOVA was performed to determine significant differences in these parameters among the four interventions.ResultsSignificant differences in CPT values among the interventions were observed at the frequency of 5 Hz (F = 3.499, p = 0.019, ηp2 = 0.111). Post hoc analysis revealed that CPT was significantly higher for KF than for NT (p = 0.008, 95% CI = 1.390–11.990). Significant differences in PPT values (F = 4.352, p = 0.012, ηp2 = 0.130) and soft tissue hardness (F = 2.957, p = 0.049, ηp2 = 0.093) were observed among the different taping conditions. Post hoc analysis revealed that PPT was significantly higher for KF than for PT (p = 0.011, 95% CI = 0.071–0.749), and soft tissue hardness was significantly higher for KF than for NT (p = 0.010, 95% CI = 0.461–4.586) and KY (p = 0.040, 95% CI = 0.059–3.800). No significant differences in self-perceived pain among the interventions were observed.ConclusionThe healthy adult females had higher PPT values, lower soft tissue hardness, and higher CPT values at 5 Hz under KF intervention applied on the waist than those under the other taping interventions. Moreover, the different taping conditions had no significant differences in terms of VAS of perceived pain. These results provide guidance for the application of KT on pain management.

Ischemia-reperfusion (I/R) induced acute kidney injury (AKI) is a significant health problem with high morbidity and mortality, yet prophylaxis strategies and effective drugs are limited. Sanqi oral solution (SQ) is a formulated medicine widely used in clinical settings to treat various renal diseases via enriching qi and activating blood circulation while its role on I/R-AKI remains unclear. Herein, by establishing rat I/R-AKI models, we intended to investigate the effect of SQ on the prevention of I/R-AKI and explore its underlying mechanisms. We demonstrated that SQ treatment significantly attenuated renal dysfunction of I/R-AKI, alleviated histological damages, inhibited renal apoptosis, and enhanced autophagy. Further investigation proved that SQ could significantly inhibit the activation of ERK and mTOR signaling pathways. Moreover, its renoprotective effect can be abolished by autophagy inhibitor 3-methyladenine (3-MA). Collectively, our results suggest that SQ exerts renoprotective effects on renal I/R injury via reducing apoptosis and enhancing autophagy, which are associated with regulating ERK/mTOR pathways.

Background: Cases of excessive neutrophil counts in the blood in severe coronavirus disease (COVID-19) patients have drawn significant attention. Neutrophil infiltration was also noted on the pathological findings from autopsies. It is urgent to clarify the pathogenesis of neutrophils leading to severe pneumonia in COVID-19.Methods: A retrospective analysis was performed on 55 COVID-19 patients classified as mild (n = 22), moderate (n = 25), and severe (n = 8) according to the Guidelines released by the National Health Commission of China. Trends relating leukocyte counts and lungs examined by chest CT scan were quantified by Bayesian inference. Transcriptional signatures of host immune cells of four COVID19 patients were analyzed by RNA sequencing of lung specimens and BALF.Results: Neutrophilia occurred in 6 of 8 severe patients at 7–19 days after symptom onset, coinciding with lesion progression. Increasing neutrophil counts paralleled lesion CT values (slope: 0.8 and 0.3–1.2), reflecting neutrophilia-induced lung injury in severe patients. Transcriptome analysis revealed that neutrophil activation was correlated with 17 neutrophil extracellular trap (NET)-associated genes in COVID-19 patients, which was related to innate immunity and interacted with T/NK/B cells, as supported by a protein–protein interaction network analysis.Conclusion: Excessive neutrophils and associated NETs could explain the pathogenesis of lung injury in COVID-19 pneumonia.

Background Retinal arteriolar narrowing and venular widening has been widely suggested to be associated with subclinical changes in cardiac structure. The novel retinal vascular geometric indices might reflect more comprehensive information on microvasculature other than vascular caliber alone. However, the association between suboptimal retinal vascular geometry and cardiac structural alteration has not been studied. Methods and Results We recruited 50 participants without cardiovascular disease from the Cardiac Aging Study conducted between 2014 and 2016. We performed transthoracic echocardiography imaging to measure cardiac structure indices such as left ventricular internal diameter end diastole index, left ventricular internal diameter end systole index, left ventricular mass index, and left atrial volume index, and retinal imaging to measure retinal vascular geometric indices including branching angle, curvature tortuosity, and fractal dimension. We applied multiple linear regressions to examine associations between indices of cardiac structure and retinal vascular geometry, adjusting for age, sex, body mass index, mean blood pressure, and comorbidity. The average age of all participants was 62.54 years old and slightly more than half were male (27; 54%). Each unit increase in a set of cardiac structure indices was associated with larger retinal arteriolar branching angle (β and 95% CI: for left ventricular internal diameter end systole index, 26.93°; 6.00–47.86; for left ventricular internal diameter end diastole index, 17.86°; 1.61–34.11; for left ventricular mass index, 0.39°; 0.10–0.67; for left atrial volume index, 0.91°; 0.24–1.58). Conclusions Adverse retinal arteriolar geometric morphology mirrored suboptimal cardiac structural alteration.

Objective. To investigate the association of the serum adiponectin level with the intima media thickness of the dorsalis pedis artery (D-IMT) and macroangiopathy in type 2 diabetes (T2DM). Methods. We recruited 173 patients with T2DM, of whom 83 had macroangiopathy (MA group) and 90 did not have macroangiopathy (NM group), and 40 normal control subjects (NC group). We measured D-IMT using color B-mode Doppler ultrasonography. Serum adiponectin, blood glucose, lipids, and other clinical characteristics were analyzed. Participants were divided into three subgroups according to serum adiponectin level (high, moderate, and low). Results. Compared with the NM and NC groups, serum adiponectin levels were significantly decreased in the MA group after adjusting for sex and body mass index. Compared with the NM and NC groups, D-IMT was significantly increased in the MA group. Compared with the moderate- and high-adiponectin subgroups, D-IMT was significantly increased in the low-adiponectin subgroup. The prevalence of diabetic macroangiopathy increased gradually with decreasing adiponectin levels. After controlling for age, sex, smoking, and alcohol drinking, partial correlation analysis showed that adiponectin was negatively correlated with D-IMT. Elevated serum adiponectin was independently associated with a decreased risk for diabetic macroangiopathy by logistic regression analysis. Multiple linear regression analysis revealed that adiponectin was an independent factor of D-IMT. In receiver operating characteristic analyses, the area under the curve for traditional risk factors plus adiponectin for prediction of macroangiopathy was 0.984, while that of traditional risk factors alone was 0.972. Conclusions. Adiponectin is lower in patients with T2DM with macroangiopathy. We suggest that D-IMT could represent a noninvasive indicator of diabetic macroangiopathy. Decrease of adiponectin as an independent risk factor for both macroangiopathy and D-IMT among Chinese patients with T2DM suggests that adiponectin might have clinical utility in the prediction of diabetic macroangiopathy. This clinical trial is registered in the “Chinese Clinical Trial Registry.” The registration number is ChiCTR-ROC-17011731.

Recently, support vector machines, a supervised learning algorithm, have been widely used in the scope of credit risk management. However, noise may increase the complexity of the algorithm building and destroy the performance of classifier. In our work, we propose an ensemble support vector machine model to solve the risk assessment of supply chain finance, combined with reducing noises method. The main characteristics of this approach include that (1) a novel noise filtering scheme that avoids the noisy examples based on fuzzy clustering and principal component analysis algorithm is proposed to remove both attribute noise and class noise to achieve an optimal clean set, and (2) support vector machine classifiers, based on the improved particle swarm optimization algorithm, are seen as component classifiers. Then, we obtained the final classification results by combining finally individual prediction through AdaBoosting algorithm on the new sample set. Some experiments are applied on supply chain financial analysis of China’s listed companies. Results indicate that the credit assessment accuracy can be increased by applying this approach.

Abstract Background Astragalus membranaceus, a traditional Chinese medicine (TCM), has been widely used in the treatment of chronic kidney disease (CKD) in China. Astragaloside IV is one of the major compounds of Astragalus membranaceus. Recent research has shown that astragaloside IV demonstrates pharmacological effects, such as anti-inflammatory, anti-fibrotic and anti-oxidative stress activities. Our aim was to investigate the effects of astragaloside IV on indoxyl sulfate (IS)-induced kidney injury in vivo, and to study the underlying mechanism. Methods Forty C57BL/6 mice with ½ nephrectomy were divided into four groups: control group (n = 10), IS group (n = 10), IS plus 10 mg/kg of astragaloside IV group (n = 10) and IS plus 20 mg/kg of astragaloside IV group (n = 10). IS intraperitoneal injection and astragaloside IV treatment were administered continuously for 1 month. Next, the blood urea nitrogen (BUN) level, serum IS level, tubulointerstitial injury, renal oxidative stress and inflammatory injury were assessed. Results The IS intraperitoneal injection mouse group showed increasing levels of serum IS, BUN, tubulointerstitial injury, renal oxidative stress and inflammatory injury. Astragaloside IV treatment couldn’t reduce the serum IS level or renal nuclear factor-κB and interleukin-1β levels. However, 20 mg/kg astragaloside IV treatment reduced the BUN level and significantly attenuated IS-induced tubulointerstitial injury. Renal oxidative stress was decreased by the administration of astragaloside IV. Conclusions These results suggest that astragaloside IV prevents IS-induced tubulointerstitial injury by ameliorating oxidative stress and may be a promising agent for the treatment of uremia toxin-induced injury.

Summary: Charcot-Marie-Tooth disease type 1A (CMT1A), one of the most frequent inherited peripheral neuropathies, is associated with PMP22 gene duplication. Previous studies of CMT1A mainly relied on rodent models, and it is not yet clear how PMP22 overexpression leads to the phenotype in patients. Here, we generated the human induced pluripotent stem cell (hiPSC) lines from two CMT1A patients as an in vitro cell model. We found that, unlike the normal control cells, CMT1A hiPSCs rarely generated Schwann cells through neural crest stem cells (NCSCs). Instead, CMT1A NCSCs produced numerous endoneurial fibroblast-like cells in the Schwann cell differentiation system, and similar results were obtained in a PMP22-overexpressing iPSC model. Therefore, despite the demyelination-remyelination and/or dysmyelination theory for CMT1A pathogenesis, developmental disabilities of Schwann cells may be considered as an underlying cause of CMT1A. Our results may have important implications for the uncovering of the underlying mechanism and the development of a promising therapeutic strategy for CMT1A neuropathy.

An HBsAg-HBIG therapeutic vaccine (Yeast-derived Immune Complexes, YIC) for chronic hepatitis B (CHB) patients has undergone a series of clinical trials. The HBeAg sero-conversion rate of YIC varied from 21.9% to 14% depending on the immunization protocols from 6 to 12 injections. To analyze the immunological mechanisms exerted by 6 injections of YIC, 44 CHB patients were separately immunized with YIC, alum as adjuvant control or normal saline as blank control, with add on of antiviral drug Adefovir in all groups. Kinetic increase in Th1 and Th2 cells CD4+ T cell sub-populations with association in decrease in Treg cells and increase of Tc1 and Tc17 cells in CD8+ T cells were observed in YIC immunized group. No such changes were found in the other groups. By multifunctional analysis of cytokine profiles, significant increase of IL-2 levels was observed, both in CD4+ and CD8+ T cells in the YIC immunized group, accompanied by increase in IFN-gamma and decrease of inhibitory factors (IL-10, TGF-β and Foxp3) in CD4+ T cells. In the alum immunized group, slight increase of IL-10, TGF-β and Foxp3 in CD4+ T cells was found after the second injection, but decreased after more injections, suggesting that alum induced early inflammatory responses to a certain extent. Similar patterns of responses of IL-17A and TNF-α in CD8+T cells were shown between YIC and the saline group. Results indicate that add on of Adefovir, did not affect host specific immune responses.

Primary biliary cholangitis is an autoimmune liver disease. Here, the authors show that variants in interleukin genes which potentially deregulate their expression are associated with this condition, and suggest that the IL21 signalling pathway may have a role in disease aetiology.

Abstract Somatic cells can be successfully reprogrammed into pluripotent stem cells by the ectopic expression of defined transcriptional factors. However, improved efficiency and better understanding the molecular mechanism underlying reprogramming are still required. In the present study, a scrape loading/dye transfer assay showed that human induced pluripotent stem cells (hiPSCs) contained functional gap junctions partially contributed by Connexin 45 (CX45). We then found CX45 was expressed in human embryonic stem cells (hESCs) and human dermal fibroblasts (hDFs) derived hiPSCs. Then we showed that CX45 was dramatically upregulated during the reprogramming process. Most importantly, the ectopic expression of CX45 significantly enhanced the reprogramming efficiency together with the Yamanaka factors (OCT4, SOX2, KLF4, cMYC - OSKM), whereas knockdown of endogenous CX45 expression significantly blocked cellular reprogramming and reduced the efficiency. Our further study demonstrated that CX45 overexpression or knockdown modulated the cell proliferation rate which was associated with the reprogramming efficiency. In conclusion, our data highlighted the critical role of CX45 in reprogramming and may increase the cell division rate and result in an accelerated kinetics of iPSCs production.

Chemokine (C–C motif) ligand 19 (CCL19) is a critical regulator of the induction of T cell activation, immune tolerance, and inflammatory responses during continuous immune surveillance, homeostasis, and development. Migration of CC-chemokine receptor 7 (CCR7)-expressing cells to secondary lymphoid organs is a crucial step in the onset of adaptive immunity, which is initiated by a complex interaction between CCR7 and its cognate ligands. Recent advances in knowledge regarding the response of the CCL19-CCR7 axis to viral infections have elucidated the complex network of interplay among the invading virus, target cells and host immune responses. Viruses use various strategies to evade or delay the cytokine response, gaining additional time to replicate in the host. In this review, we summarize the impacts of CCL19 and CCR7 expression on the regulation of viral pathogenesis with an emphasis on the corresponding signaling pathways and adjuvant mechanisms. We present and discuss the expression, signaling adaptor proteins and effects of CCL19 and CCR7 as these molecules differentially impact different viral infections and viral life cycles in host homeostatic strategies. The underlying mechanisms discussed in this review may assist in the design of novel agents to modulate chemokine activity for viral prevention.

Pemetrexed, one of the most commonly used drugs in advanced non–small cell lung cancer (NSCLC) therapies, often leads to various therapeutic responses in patients. These therapeutic responses to pemetrexed, including adverse drug reactions (ADRs) and its intended therapeutic effects, have been demonstrated to be highly individual-specific. Such difference in therapeutic responses across individuals may be caused by the unique genetic variations in each patient. However, only a few pemetrexed-based studies have been performed using Han Chinese patients. In this study, we aimed to identify genetic signatures of therapeutic responses of pemetrexed-based treatment using 203 Han Chinese patients with advanced NSCLC. All the participants received two different types of therapies: 1) treatment with only pemetrexed and 2) treatment with both pemetrexed and platinum (mainly cisplatin and carboplatin). We then performed a genetic association analysis on 16 selected single-nucleotide polymorphisms (SNPs) in 7 genes using these 2 groups. The analysis of patients receiving only pemetrexed suggests that the SNP rs1051298 on the SLC19A1 gene (c.*746C > T) increased the risk of all ADRs (collected all types of ADRs) in different cycles of pemetrexed therapy [1-2 cycles: P = 0.0059, odds ratio (OR) = 3.143; 1-4 cycles: P = 0.0072, OR = 2.340; 1-6 cycles: P = 0.0071, OR = 2.243]. This influence of rs1051298 is particularly significant in terms of liver injury (1-4 cycles: P = 0.0056, OR = 3.863; 1-6 cycles: P = 0.0071, OR = 3.466). In all the patients, including patients who received both pemetrexed and platinum, SNP rs1801133 on the MTHFR gene (665C > T) was found to be significantly associated with hematological ADRs in 1 to 2 cycles (P = 0.0079, OR = 3.566). Additionally, we discovered that SNP rs12995526 (c.815-102T > C) in the ATIC gene and SNP rs11545077 (c.91G > T) in the GGH gene were associated with both ADRs and therapeutic effects. In summary, our study identified several potential biomarkers that were significantly associated with ADRs and therapeutic effects of pemetrexed-related treatments using Han Chinese patients. Our discoveries will provide important clues for personalized pemetrexed-based treatment design for Han Chinese NSCLC patients in the future.

Membranous nephropathy (MN) is one of the leading causes of nephrotic syndrome in adults. However, the current treatment of MN has been a matter of fierce debate for decades, and the needs for more advanced pharmaceuticals are critical for improving the treatment strategies. Sanqi oral solution (SQ), mainly consisting of Radix Astragali and Radix Notoginseng, is a formulated product to treat chronic kidney disease for over 20 years with good efficiency in clinic, while the role of SQ on MN remains unclear. In this study, by establishing an experimental rat model of membranous nephropathy induced by cationic Bovine Serum Albumin (C-BSA), we tried to investigate the effects of SQ. We found that administration of SQ ameliorated MN by reducing proteinuria, elevating serum albumin, and ameliorating pathological renal damages. SQ also significantly reduced the C3 and IgG depositions, and restored podocin and synaptopodin expressions. Furthermore, SQ inhibited the activation of nuclear factor-kappa B (NF-κB) signaling pathway. Our results provide evidence that SQ exerts a novel therapeutic effect on MN via reducing proteinuria, ameliorating renal damage and restoring podocyte injuries, which are associated with the suppression of NFκB.

YTH N6-methyladenosine (m6A) RNA binding protein 1 (YTHDF1) is a core factor in RNA methylation modification. Recent studies have shown that m6A is closely related to multiple tumors, thus YTHDF1 may also play a role in tumorigenesis. This study, aimed to explore the role of YTHDF1 in the colorectal cancer (CRC). In this study, we identified YTHDF1 as being highly expressed at the mRNA and protein levels in TCGA, GEO CRC and primary CRC. Furthermore, the YTHDF1 gene copy number was positively correlated with YTHDF1 mRNA expression in CRC. Knocking down the expression of YTHDF1 significantly inhibited the CRC cell's tumorigenicity in vitro and murine xenograft tumor growth in vivo. Furthermore, silencing of YTHDF1 inhibited the colonosphere formation ability in vitro. Mechanistically, we found that silencing YTHDF1 significantly inhibited Wnt/β-catenin pathway activity in CRC cells. Together, YTHDF1 is overexpressed in CRC and plays a vital oncogenic role in CRC, and this novel finding may provide a potential therapeutic target for CRC.

Nowadays, support vector machines are widely applied to land cover classification although this method is sensitive to parameter selection and noise samples. AdaBoost is an effective approach to find a highly accurate classifier by combining many weak and accurate classifiers. In this article, a novel ensemble support vector machine model that uses AdaBoost approach is proposed to mitigate the influence of noises and error parameters with focus on application on land cover classification. The key characteristics of this approach are that (1) a novel noise filtering scheme that avoids the noisy examples based on fuzzy clustering and principal component analysis algorithm is proposed to remove both attribute noises and class noises to achieve an optimal clean set and (2) support vector machine classifiers, based on the particle swarm optimization algorithm, are seen to component classifiers. We then combined finally individual prediction through AdaBoost algorithm to induce the final classification results on this new training set. A set of experiments is conducted on land cover classification for testing the performance of the proposed algorithm. Experimental results show that the classification accuracy can be increased using our proposed learning model, which results in the smallest generalization error compared with the other learning methods.

Underwater images are important carriers and forms of underwater information, playing a vital role in exploring and utilizing marine resources. However, underwater images have characteristics of low contrast and blurred details because of the absorption and scattering of light. In recent years, deep learning has been widely used in underwater image enhancement and restoration because of its powerful feature learning capabilities, but there are still shortcomings in detailed enhancement. To address the problem, this paper proposes a deep supervised residual dense network (DS_RD_Net), which is used to better learn the mapping relationship between clear in-air images and synthetic underwater degraded images. DS_RD_Net first uses residual dense blocks to extract features to enhance feature utilization; then, it adds residual path blocks between the encoder and decoder to reduce the semantic differences between the low-level features and high-level features; finally, it employs a deep supervision mechanism to guide network training to improve gradient propagation. Experiments results (PSNR was 36.2, SSIM was 96.5%, and UCIQE was 0.53) demonstrated that the proposed method can fully retain the local details of the image while performing color restoration and defogging compared with other image enhancement methods, achieving good qualitative and quantitative effects.