Effect of acupuncture in the acute phase of intracerebral hemorrhage on the prognosis and serum BDNF: a randomized controlled trial

BackgroundIntracerebral hemorrhage (ICH) is a common cerebrovascular disease, with a high rate of disability. In the literature on Chinese traditional medicine, there is increasing evidence that acupuncture can help hematoma absorption and improve neurological deficits after cerebral hemorrhage. Brain-derived neurotrophic factor (BDNF), one of the most studied neurotrophic factors, is involved in a variety of neurological functions and plays an important role in brain injury recovery. We investigated the effect of acupuncture intervention in the acute phase of ICH on the prognosis and serum BDNF levels of several patient groups.ObjectiveTo investigate the influence of acupuncture on the prognosis and brain-derived neurotrophic factor (BDNF) levels in patients in the acute phase of ICH.MethodsFrom November 2021 to May 2022, 109 subjects were consecutively enrolled, including patients with ICH, who were randomized into the acupuncture group (AG) and sham acupuncture group (SAG), and a control group (CG). The CG received the same acupuncture intervention as the AG, and the SAG received sham acupuncture, with 14 interventions in each group. The level of consciousness of patients with ICH was assessed and serum BDNF levels were measured in all three groups before the intervention and at 3 weeks after onset, and the level of consciousness and outcomes were assessed at 12 weeks after onset.ResultsAfter the intervention, the level of consciousness of the AG improved significantly (P < 0.05); the BDNF level of only the AG increased significantly (P < 0.05); the changes in Glasgow Coma Scale (GCS) score and BDNF level were significantly greater in the AG than in the SAG (P < 0.05), especially for locomotion (P < 0.05). At 12 weeks post-onset, the AG showed better outcomes and recovery of consciousness than the SAG (P < 0.05)

Molecular phylogenetic characterization and analysis of the WRKY transcription factor family responsive to Rhizoctonia solani in maize

In this study we have identified, based on the maize genome, 85 WRKY genes that were phylogenetically clustered into three families formed by 8 distinct subfamilies. The exon/intron structures and motif compositions of these WRKY genes were highly conserved in each subfamily suggesting their functional conservation. Moreover, based on qTelller analyses, the majority of these WRKY genes showed a specific temporal and spatial expression pattern. These WRKY genes, within the same group, manifested a distinct expression, indicating a similar function in their expression during the evolutionary process; this is reflected by their sub-functionalizations in their expression pattern concerning leaf developmental gradient, while mature bundle sheath, and mesophyll cells had a similar cellular localization and modality of expression. This study has also provided evidence of the presence of a subset of WRKY genes exhibiting a putative functional role in leaf sheath when infected with Rhizoctonia solani. This finding appears helpful for future functional investigations to unravel the roles of WRKY genes in plant pathogen resistance. Interestingly, in this study we have identified three WRKY genes that are predicted to be potential targets of miR160 and miR171b families. Therefore, this finding appears relevant in elucidating the biological functions of these transcription factors to clarify the molecular mechanisms affecting leaf sheath growth and development during fungal infection and plant resistance

Identification of miRNAs and their target genes in developing maize ears by combined small RNA and degradome sequencing

Background In plants, microRNAs (miRNAs) are endogenous ~22 nt RNAs that play important regulatory roles in many aspects of plant biology, including metabolism, hormone response, epigenetic control of transposable elements, and stress response. Extensive studies of miRNAs have been performed in model plants such as rice and Arabidopsis thaliana. In maize, most miRNAs and their target genes were analyzed and identified by clearly different treatments, such as response to low nitrate, salt and drought stress. However, little is known about miRNAs involved in maize ear development. The objective of this study is to identify conserved and novel miRNAs and their target genes by combined small RNA and degradome sequencing at four inflorescence developmental stages. Results We used deep-sequencing, miRNA microarray assays and computational methods to identify, profile, and describe conserved and non-conserved miRNAs at four ear developmental stages, which resulted in identification of 22 conserved and 21-maize-specific miRNA families together with their corresponding miRNA*. Comparison of miRNA expression in these developmental stages revealed 18 differentially expressed miRNA families. Finally, a total of 141 genes (251 transcripts) targeted by 102 small RNAs including 98 miRNAs and 4 ta-siRNAs were identified by genomic-scale high-throughput sequencing of miRNA cleaved mRNAs. Moreover, the differentially expressed miRNAs-mediated pathways that regulate the development of ears were discussed. Conclusions This study confirmed 22 conserved miRNA families and discovered 26 novel miRNAs in maize. Moreover, we identified 141 target genes of known and new miRNAs and ta-siRNAs. Of these, 72 genes (117 transcripts) targeted by 62 differentially expressed miRNAs may attribute to the development of maize ears. Identification and characterization of these important classes of regulatory genes in maize may improve our understanding of molecular mechanisms controlling ear development

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Obtaining Human Experience for Intelligent Dredger Control: A Reinforcement Learning Approach

This work presents a reinforcement learning approach for intelligent decision-making of a Cutter Suction Dredger (CSD), which is a special type of vessel for deepening harbors, constructing ports or navigational channels, and reclaiming landfills. Currently, CSDs are usually controlled by human operators, and the production rate is mainly determined by the so-called cutting process (i.e., cutting the underwater soil into fragments). Long-term manual operation is likely to cause driving fatigue, resulting in operational accidents and inefficiencies. To reduce the labor intensity of the operator, we seek an intelligent controller the can manipulate the cutting process to replace human operators. To this end, our proposed reinforcement learning approach consists of two parts. In the first part, we employ a neural network model to construct a virtual environment based on the historical dredging data. In the second part, we develop a reinforcement learning model that can lean the optimal control policy by interacting with the virtual environment to obtain human experience. The results show that the proposed learning approach can successfully imitate the dredging behavior of an experienced human operator. Moreover, the learning approach can outperform the operator in a way that can make quick responses to the change in uncertain environments

Research on the influence of uneven solar radiation distribution on the radiant floor heating system in railway stations on Tibetan Plateau

In cold regions, radiant floor heating systems are commonly used in public buildings due to better thermal comfort and lower energy consumption. However, in transportation buildings with many transparent envelopes such as railway stations on Tibetan Plateau, the strong solar radiation entering into the station may cause local overheating, which has a great effect on the radiant floor heating system. In this paper, a railway station on Tibetan Plateau is simulated to investigate the influence of uneven solar radiation distribution on the radiant floor heating system. Results show that due to the strong solar radiation, the floor surface temperature and indoor operative temperature in some parts of the waiting hall can reach up to 30 °C and 26 °C, respectively. The temperature difference of the floor surface can even exceed 5 °C occasionally during the heating period. According to the results, it can be found that the method of reducing the heating in the area with strong solar radiation and making full use of solar radiation for heating is an effective way to improve the indoor thermal comfort and reduce the heating energy consumption of heating system

Research on surface defect detection model of steel strip based on MFFA‐YOLOv5

Abstract The surface quality of steel strip is a critical indicator of the quality of hot‐rolled strip, so accurate inspection of its surface is essential. However, the complex texture of steel strip surface defects makes the detection challenging. Here, a multi‐scale feature fusion and attention based YOLOv5 (MFFA‐YOLOv5) model is proposed. Specifically, the bottom layer features are up‐sampled and fused not only with the middle layer features, but also with the top layer features, so that the model better captures the surface texture information of the steel strip. Secondly, an improved attention mechanism module is introduced to deal with the global and local information of the steel strip surface by introducing down‐sampling and up‐sampling paths based on Convolutional Block Attention Module (CBAM). Meanwhile, a self‐attention mechanism path is added to improve the capability of feature representation. Experimental results on the NEU‐DET dataset show that the MFFA‐YOLOv5 model significantly outperforms other state‐of‐the‐art methods

Proteome identification of binding-partners interacting with cell polarity protein Par3 in Jurkat cells

The evolutionarily conserved cell polarity protein Par3, a scaffold-like PDZ-containing protein, plays a critical role in the establishment and maintenance of epithelial cell polarity. Although the role of Par3 in establishing cell polarity in epithelial cells has been intensively explored, the function of Par3 in hematopoietic cells remains elusive. To address this issue, we generated GST-fusion proteins of Par3 PDZ domains. By combining the GST-pull-down approach with liq-uid chromatography-tandem mass spectrometry, we identi-fied 10 potential novel binding proteins of PDZ domains of Par3 in Jurkat cells (a T-cell line). The interaction of Par3 with three proteins––nuclear transport protein importin-α4 and proteasome activators PA28β and PA28γ––was con-firmed using in vitro binding assay, co-immunoprecipitation assay and immunofluorescence microscopy. Our results hav

Methanation of Carbon Dioxide over Ni–Ce–Zr Oxides Prepared by One-Pot Hydrolysis of Metal Nitrates with Ammonium Carbonate

Ni–Ce–Zr mixed oxides were prepared through one-pot hydrolysis of mixed metal nitrates with ammonium carbonate for CO2 methanation. The effects of Ce/Zr molar ratio and Ni content on catalysts’ physical and chemical properties, reduction degree of Ni2+, and catalytic properties were systematically investigated. The results showed that Zr could lower metallic Ni particle sizes and alter interaction between Ni and supports, resulting in enhancements in the catalytic activity for CO2 methanation. The Ni–Ce–Zr catalyst containing 40 wt % Ni and Ce/Zr molar ratio of 9:1 exhibited the optimal catalytic properties, with 96.2% CO2 conversion and almost 100% CH4 selectivity at a low temperature of 275 °C. During the tested period of 500 h, CO2 conversion and CH4 selectivity over Ni–Ce–Zr catalyst kept constant under 300 °C

Relationship among post-traumatic growth, spiritual well-being, and perceived social support in Chinese women with gynecological cancer

Abstract This study aimed to examine the correlation between post-traumatic growth (PTG), spiritual well-being (SWB), perceived social support (PSS), and demographic and clinical factors in Chinese gynecological cancer patients. Through convenience sampling, we conducted a cross-sectional study of 771 adult patients with gynecological cancer. The European Organization for Research and Treatment for Cancer Quality of Life Questionnaire-Spiritual Well-being 32 (EORTC QLQ-SWB32), Post-traumatic Growth Inventory (PTGI), and Multidimensional Scale of Perceived Social Support (MSPSS) were used to measure SWB, PTG, and PSS. A Multiple Linear Regression Model was used to determine the possible factors contributing to PTG. The subscale with the highest centesimal score in the PTGI was the Appreciation of Life Scale, and the lowest was New Possibility. Gynecologic cancer patients with younger ages (B =  − 0.313, P = 0.002), perceived more family support (B = 1.289, P < 0.001), had more existential (B = 0.865, P = 0.010), and had religious belief (B = 5.760, P = 0.034) may have more PTG. Spiritual well-being, perceived social support, younger age, and religious beliefs are associated with post-traumatic growth in gynecological cancer patients. Healthcare staff could provide more professional support to younger patients with religious beliefs. Promoting social support and spiritual well-being could potentially serve as effective interventions for boosting PTG among gynecological cancer