Modified zero-valent iron nanoparticles enhanced remediation of PCBs-contaminated soil.

The high toxicity and persistence of polychlorinated biphenyls (PCBs) in the environment require effective remediation of PCBs-contaminated soil. This study used polylactic acid (PLA) and polyethylene glycol 4000 (PEG-4000) to modify zero-valent iron nanoparticles (nZVI) and conducted characterization analysis. It was found that when the addition amount of PLA was 2 %, the dispersion of modified nZVI was better. The initial pH and water to soil ratio were subjected to single factor experiments and fitted using RSM response surface methodology. The optimal reaction conditions were obtained as follows: the addition amount was 84 g·kg-1, the initial pH was 5.41, and the optimal removal rate was 74 % when the ratio of water to soil was 1.8:1. PLA and PEG-4000 were biodegradable substances that played crucial roles in enhancing the effectiveness of nZVI for PCBs-contaminated soil. By encapsulating nZVI with PLA, we significantly reduced its oxidation when exposed to air. Additionally, the inclusion of PEG-4000 helped prevent the particles from clumping together. The synergistic effect of them increased the effective reaction of nZVI and PCBs and ultimately leading to more efficient remediation. This study offered a new pathway for the efficient green remediation of PCBs-contaminated soil.

A Dataset on Population Activity Patterns in Typical Regions of North China.

This data article describes the "Typical Regional Activity Patterns" (TRAP) dataset, which is based on the Tackling Key Problems in Air Pollution Control Program. In order to explore the interaction between air pollution and physical activity, we collected activity patterns of 9,221 residents with different occupations and lifestyles for three consecutive days in typical regions (Jinan and Baoding) where air pollutant concentrations were higher than those in neighboring areas. The TRAP dataset consists of two aspects of information: demographic indicators (personal information, occupation, personal habits, and living situation) and physical activity pattern data (activity location and intensity); additionally, the exposure measures of physical activity patterns are included, which data users can match to various endpoints for their specific purpose. This dataset provides evidence for exploring the attributes of activity patterns of residents in northern China and for interdisciplinary researchers to develop strategies and measures for health education and health promotion.

A Dynamics-Learning Multirate Estimation Approach for the Feeding Condition Perception of Complex Industry Processes.

In this study, we propose a dynamics-learning multirate estimation approach to perceive the quality-related indices (QRIs) of the feeding solution of a unit process. A quality-related index for estimation is an intermediate technical indicator between a unit process and a proceeding unit process; hence, the estimation problem is formulated as a two-stage estimation problem utilizing the production data of both unit processes. Dynamics-learning bidirectional long short-term memory (BiLSTM) with different inputs for the forward and backward layers is proposed to manage the input data from the different unit processes. In the dynamics-learning BiLSTM, a cycle control gate is added in the memory cell to learn the dynamics of the QRIs, thereby enabling a high-rate estimation under multirate conditions. A Bayesian estimation model is then combined with the dynamics-learning BiLSTM model to manage the process delay. Ablation and comparative experiments are conducted to evaluate the feasibility and effectiveness of the proposed estimation approach. The experimental results illustrate the performance and high-rate estimation ability of the proposed approach.

Microscale Corrosion Inhibition Behavior of Four Corrosion Inhibitors (BTA, MBI, MBT, and MBO) on Archeological Silver Artifacts Based on Scanning Electrochemical Cell Microscopy.

The problem of corrosion-induced discoloration and embrittlement in silverware is a significant concern for the long-term preservation of excavated archeological silver artifacts, even after thermal restoration. The key to addressing this issue lies in the meticulous selection and evaluation of corrosion inhibitors that possess targeted corrosion inhibition capabilities. This study focuses on the evaluation of corrosion inhibitors for archeological silver artifacts using scanning electrochemical cell microscopy (SECCM) and X-ray photoelectron spectroscopy (XPS). The researchers aimed to compare the inhibition effects of four corrosion inhibitors [1,2,3-benzotriazole (BTA), 2-mercaptobenzimidazole (MBI), 2-mercaptobenzothiazole (MBT), and 2-mercaptobenzoxazole (MBO)] on a simulated Ag-Cu alloy sample and understand their mechanisms. The results showed that MBT exhibited better corrosion inhibition for microstructural regions with higher silver content due to its ability to form stable chelation structures with Ag(I). MBO exhibited better corrosion inhibition for microstructural regions with higher copper content due to its strong affinity with Cu(I). The targeted corrosion inhibition ability for the ß-phase was ranked as MBO > BTA ≈ MBI > MBT, while for the α-phase the ranking was MBT > MBO > MBI > BTA. The study demonstrated the feasibility and capabilities of SECCM in the targeted screening of corrosion inhibitors for different compositions and microstructural regions in archeological metal artifacts. This study highlights the potential of SECCM in corrosion inhibitor research for archeological metal artifacts and wider applications in metal material corrosion protection.

Analysis of the complete plastomes of Albizia kalkora (Roxb.) Prain 1897 (Fabaceae).

Albizia kalkora (Roxb.) Prain 1897, belonging to the family Fabaceae, is not only a landscape tree but also a medicinal plant. At present, few plastomes have been reported from Albizia, which delays the in-depth phylogenomic studies and the development of high-resolution discriminating markers for this genus. Herein, we sequenced the first plastome of A. kalkora by NGS technology. The genome is a circular structure (176,158 bp), containing a large single-copy (LSC) region (91,521 bp), a small copy (SSC) region (5237 bp), and two inverted repeat (IR) regions (39,700 bp each). It has 35.45% GC content and encodes 109 unique genes, which are 76 protein-coding, 4 rRNA, and 29 tRNA genes. The genetic distance analysis of the intergenic spacer regions for A. kalkora, A. odoratissima and A. bracteate shows four intergenic regions with very high K2p values, namely, ccsA-ndhD (15.04), matK-rps16 (10.77), rps11-rpl36 (17.63) and rps3-rps19 (20.08), which can discriminate the three Albizia species. In addition, we identified ten pairs of regions that could be utilized to design primers to discriminate the three Albizia species. The phylogenetic analysis showed Albizia was closely related to Samanea. The results in this study will provide valuable information to elucidate the classification, identification and evolutionary history of Albizia.

Efficient removal of Hg0 from cement kiln flue gas using CexFeyOz composite catalyst.

In this study, a kind of CexFeyOz composite with oxygen vacancy structure and strong oxygen storage capacity was prepared by coprecipitation method. Under the condition of no HCl of flue gas, the Hg0 in the flue gas of cement kiln was efficiently and economically removed by using 6-8% oxygen. The results showed that the optimum preparation conditions of the catalyst were Ce-Fe molar ratio of 1-11 and calcination temperature of 550 °C. In addition, the reaction temperature, space velocity, the concentration of O2, SO2, and NO had significant effects on the removal efficiency of Hg0 at different rates. More precisely, at the reaction temperature of 350 °C, low airspeed, high concentration of O2, and low concentration of SO2 and NO, the efficiency reached the highest value. According to XPS results, the elemental valence of the CexFeyOz composite changed after the reaction. The redox pairs of Ce3+-Ce4+ and Fe3+-Fe2+ had the ability to transfer electrons, which enabled more oxygen adsorbed on the catalyst surface to be converted into O2-, leading to the improvement of the oxidation efficiency of Hg0.

Reconstructing the earliest known composite-tiled roofs from the Chinese Loess Plateau.

The origins of composite tiles, one of the oldest forms of roofing, are still unclear. This study is based on a set of over 5000 clay tile fragments excavated from a single context in the Qiaocun site on the Chinese Loess Plateau, dated to ~ 2400-2200 BCE (Early Longshan Period). By combining morphological measurement statistics, 3D modeling, computer-based simulations, and reference to historical and archaeological records, we reconstruct the earliest known composite-tile roofing techniques and demonstrate that tile production was under a low-level standardization, with manual control forming a key agent during the roofing process. The quantitative study of the composite roof tiles from Qiaocun was then placed in its archaeological context and compared with other sites on the Loess Plateau. It was found that tile-roofed buildings were, by necessity, community projects. Such structures served as nodes in larger social communication networks; additionally, their appearance was linked to intensified social complexity in public affairs during the Longshan Period. The invention of clay tiles was associated with the inception of thick rammed-earth walls which had sufficient strength to serve as load-bearing structures for heavy tiled roofs. The roof tiles excavated from Qiaocun site indicate that the Loess Plateau was a key center for the origin and spread of composite tiles and related roofing and construction methods, suggesting a Longshan-Western Zhou tradition of roofing techniques in East Asia.

Immunogenicity of a spike protein subunit-based COVID-19 vaccine with broad protection against various SARS-CoV-2 variants in animal studies.

SARS-CoV-2 pandemic has profound impacts on human life and global economy since the outbreak in 2019. With the new variants continue to emerge with greater immune escaping capability, the protectivity of the available vaccines is compromised. Therefore, development a vaccine that is capable of inducing immunity against variants including omicron strains is in urgent need. In this study, we developed a protein-based vaccine BCVax that is consisted of antigen delta strain spike protein and QS21-based adjuvant AB801 in nanoparticle immune stimulation complex format (AB801-ISCOM). Results from animal studies showed that high level of anti-S protein IgG was induced after two doses of BCVax and the IgG was capable of neutralizing multiple variants of pseudovirus including omicron BA.1 or BA.2 strains. In addition, strong Th1 response was stimulated after BCVax immunization. Furthermore, BCvax with AB801-ISCOM as the adjuvant showed significant stronger immunity compared with the vaccine using aluminum hydroxide plus CpG 1018 as the adjuvant. BCVax was also evaluated as a booster after two prior vaccinations, the IgG titers and pseudovirus neutralization activities against BA.2 or BA.4/BA.5 were further enhanced suggesting BCVax is a promising candidate as booster. Taken together, the pre-clinical data warrant BCVax for further development in clinic.

Impacts of Statin Therapy Strategies on Incidence of Ischemic Cerebrovascular Events in Patients With Aneurysmal Subarachnoid Hemorrhage: A Systematic Review and Bayesian Network Meta-Analysis.

BACKGROUND: The exacerbation of neurological outcomes often occurs in aneurysmal subarachnoid hemorrhage (aSAH). Statins have been commonly used for aSAH; however, there is lack of evidence of the pharmacological efficacy of different dosages and types of statins. OBJECTIVE: To apply the Bayesian network meta-analysis to analyze the optimal dosage and type of statins for the amelioration of ischemic cerebrovascular events (ICEs) in patients with aSAH. METHODS: We developed the Bayesian network meta-analysis and systemic review to analyze the effects of statins on functional prognosis and the impacts of optimal dosage and type of statins on ICEs in patients with aSAH. The outcome variables of the analysis were the incidence of ICEs and functional prognosis. RESULTS: A total of 2569 patients with aSAH across 14 studies were included. Analysis of 6 randomized controlled trials showed that statin use significantly improved functional prognosis in patients with aSAH (risk ratio [RR], 0.73; 95% CI, 0.55-0.97). Statins significantly reduced the incidence of ICEs (RR, 0.78; 95% CI, 0.67-0.90). Pravastatin (40 mg/d) decreased the incidence ICEs compared with placebo (RR, 0.14; 95% CI, 0.03-0.65) and was ranked the most effective, presenting with a significantly lower rate of the incidence ICEs than the worst-ranked simvastatin (40 mg/d) (RR, 0.13; 95% CI, 0.02-0.79). CONCLUSION: Statins could significantly diminish the incidence of ICEs and enhance functional prognosis in patients with aSAH. Various types and dosages of statins show distinct efficacies.

CPGView: A package for visualizing detailed chloroplast genome structures.

Chloroplast genomes have been widely used in studying plant phylogeny and evolution. Several chloroplast genome visualization tools have been developed to display the distribution of genes on the genome. However, these tools do not draw features, such as exons, introns, repetitive elements, and variable sites, disallowing in-depth examination of the genome structures. Here, we developed and validated a software package called Chloroplast Genome Viewers (CPGView). CPGView can draw three maps showing (i) the distributions of genes, variable sites, and repetitive sequences, including microsatellites, tandem and dispersed repeats; (ii) the structure of the cis-splicing genes after adjusting the exon-intron boundary positions using a coordinate scaling algorithm, and (iii) the structure of the trans-splicing gene rps12. To test the accuracy of CPGView, we sequenced, assembled, and annotated 31 chloroplast genomes from 31 genera of 22 families. CPGView drew maps correctly for all the 31 chloroplast genomes. Lastly, we used CPGView to examine 5998 publicly released chloroplast genomes from 2513 genera of 553 families. CPGView succeeded in plotting maps for 5882 but failed to plot maps for 116 chloroplast genomes. Further examination showed that the annotations of these 116 genomes had various errors needing manual correction. The test on newly generated data and publicly available data demonstrated the ability of CPGView to identify errors in the annotations of chloroplast genomes. CPGView will become a widely used tool to study the detailed structure of chloroplast genomes. The web version of CPGView can be accessed from http://www.1kmpg.cn/cpgview.

Adsorption of Pb (II) and Cu (II) by magnetic beads loaded with xanthan gum.

Green and environmentally friendly and efficient separation adsorbents have attracted much attention in the treatment of heavy metal ions wastewater. In this study, xanthan gum (XG) was supported by fly ash magnetic beads (FAMB) to prepare adsorbent XG@FAMB. The effects of XG@FAMB dosage, pH value of the solution, adsorption time, and initial Pb (II) and Cu (II) concentration on its adsorption performance for Pb (II) and Cu (II) were investigated. The results show that under the conditions of pH 6, dosage of XG@FAMB 4.0 g/L, adsorption time 120 min, and initial concentration 60 mg/L, the maximum adsorption capacity of XG@FAMB for Pb (II) and Cu (II) was 14.93 mg/g and 14.88 mg/g, respectively. The adsorption process of Pb (II) and Cu (II) by XG@FAMB could be better described by the quasi-second-order kinetic model and Langmuir isothermal adsorption model, that is, the adsorption process is monolayer adsorption controlled by chemical action. The adsorption mechanism is that Pb (II) and Cu (II) coordinate with oxygen-containing functional groups hydroxyl and carboxyl on XG@FAMB surface, accompanied by electrostatic adsorption. XG@FAMB has the advantages of environmental protection of XG and easy solid-liquid separation of FAMB, and has a good removal effect on Pb (II) and Cu (II).

Characteristics of Artificial Intelligence Clinical Trials in the Field of Healthcare: A Cross-Sectional Study on ClinicalTrials.gov.

Artificial intelligence (AI) has driven innovative transformation in healthcare service patterns, despite a lack of understanding of its performance in clinical practice. We conducted a cross-sectional analysis of AI-related trials in healthcare based on ClinicalTrials.gov, intending to investigate the trial characteristics and AI's development status. Additionally, the Neo4j graph database and visualization technology were employed to construct an AI technology application graph, achieving a visual representation and analysis of research hotspots in healthcare AI. A total of 1725 eligible trials that were registered in ClinicalTrials.gov up to 31 March 2022 were included in this study. The number of trial registrations has dramatically grown each year since 2016. However, the AI-related trials had some design drawbacks and problems with poor-quality result reporting. The proportion of trials with prospective and randomized designs was insufficient, and most studies did not report results upon completion. Currently, most healthcare AI application studies are based on data-driven learning algorithms, covering various disease areas and healthcare scenarios. As few studies have publicly reported results on ClinicalTrials.gov, there is not enough evidence to support an assessment of AI's actual performance. The widespread implementation of AI technology in healthcare still faces many challenges and requires more high-quality prospective clinical validation.

Biosynthesis, distribution, nutritional and organoleptic properties of bitter compounds in fruit and vegetables.

Compounds that confer a bitter taste on fruits and vegetables (FAVs) play crucial roles in both plant defense and health promotion. This review details the current knowledge of the distribution, properties (toxicity, pharmacological effects and receptors) and environmental plant responses relating to the biosynthesis, catabolism and transcriptional regulation of 53 bitter plant metabolites in diverse species of FAVs. Some bitter compounds, such as flavonoids, are common in all plant species and make a minor contribution to bitter flavor, but many are synthesized only in specific taxa. They make major contributions to the bitter taste of the corresponding species and some also have significant pharmacological effects. Levels of bitter metabolites are genetically determined, but various environmental cues can affect their final concentration during preharvest development and postharvest storage processes. Molecular approaches are helping to unravel the mechanisms of biosynthesis and regulation of bitter compounds in diverse crop species. This review not only discusses the theoretical basis for utilizing breeding programs and other agricultural technologies to produce FAVs with improved safety, favorable taste and healthier profiles, but also suggests new directions for the utilization of bitter compounds in FAVs for the development of natural pesticides and health-promoting medicines.

Modulation of Tumor Immune Microenvironment and Prognostic Value of Ferroptosis-Related Genes, and Candidate Target Drugs in Glioblastoma Multiforme.

Glioblastoma multiforme (GBM) is the most common type of malignant brain tumor, among which IDH1-wild type GBM has a poor prognosis. Recent studies have shown that ferroptosis-related genes (FRGs) are correlated with the development and progression of cancer. In GBM, the role of FRGs associated with IDH1 status as biological indicators and therapeutic targets remains to be clarified. Ten of FRGs (STEAP3, HSPB1, MAP1LC3A, SOCS1, LOX, CAPG, CP, GDF15, CDKN1A, and CD44) associated with IDH1 status in GBM were identified as key genes through screening by survival analysis and Random Forest using The Cancer Genome Atlas (TCGA) datasets, and the protein expressions of key genes were verified. Transwell and qPCR results showed that ferroptosis promoted the migration of glioblastoma cells and affected the expression of key genes. Our study established the ferroptosis-related prognostic model for GBM patients based on ten key genes by a different modeling method from previous study, the GSVA algorithm. Further, we took the methods of functional enrichment analysis, clinical characteristics, immune cell infiltration, immunomodulator, ESTIMATE and single nucleotide variant (SNV) analysis to study the molecular mechanisms of prognostic model and key genes. The results showed that ten key genes were strongly associated with immune-related factors and were significantly involved in the p53 signaling pathway, senescence and autophagy in cancer, and in the negative regulation of protein kinase activity. Moreover, potential therapeutic drugs were identified by Virtual Screening and Molecular Docking. Our study indicated that the novel ferrotosis-related prognostic model for GBM patients and key genes possessed the prognostic and therapeutic values.

Immunotherapeutic Value of MAP1LC3C and Its Candidate FDA-Approved Drugs Identified by Pan-Cancer Analysis, Virtual Screening and Sensitivity Analysis.

Background: The autophagy pathway within the tumour microenvironment can be regulated to inhibit or promote tumour development. In the fight against tumour growth, immunotherapy induces an anti-tumour immune response, whereas autophagy modulates this immune response. A key protein in the autophagy pathway, microtubule-associated protein 1 light chain 3 (MAP1LC3), has recently become a hotspot for tumour research. As a relatively novel member, the function of MAP1LC3C in tumours still need to be investigated. Therefore, the goal of this study was to look into the possible link between MAP1LC3C and immunotherapy for 33 kinds of human malignancies by using pan-cancer analysis. Methods: High-throughput sequencing data from The Cancer Genome Atlas, Genotype-Tissue Expression Project and Cancer Cell Line Encyclopedia databases, combined with clinical data, were used to analyze the expression of MAP1LC3C in 33 types of cancer, as well as patient prognosis and neoplasm staging. Activity scores were calculated using ssGSEA to assess the MAP1LC3C activity in pan-cancer. Associations between MAP1LC3C and the tumour microenvironment, including immune cell infiltration and immunomodulators, were analyzed. Moreover, tumour tissue ImmuneScores and StromalScores were analyzed using the ESTIMATE algorithm. Additionally, associations between MAP1LC3C and tumour mutational burden/microsatellite instability, were investigated. Finally, based on the expression and structure of MAP1LC3C, the United States Food and Drug Administration (FDA)-approved drugs, were screened by virtual screening, molecular docking and NCI-60 drug sensitivity analysis. Results: Our study found that MAP1LC3C was differentially expressed in tumour and normal tissues in 23 of 33 human cancer types, among which MAP1LC3C had prognostic effects in 12 cancer types, and MAP1LC3C expression was significantly correlated with tumour stage in four cancer types. In addition, MAP1LC3C activity in 14 cancer types was consistent with changes in transcription levels. Moreover, MAP1LC3C strongly correlated with immune infiltration, immune modulators and immune markers. Finally, a number of FDA-approved drugs were identified via virtual screening and drug sensitivity analysis. Conclusion: Our study investigated the prognostic and immunotherapeutic value of MAP1LC3C in 33 types of cancer, and several FDA-approved drugs were identified to be highly related to MAP1LC3C and can be potential cancer therapeutic candidates.

Preparation of graphene-based catalysts and combined DBD reactor for VOC degradation.

The objective of this study was to compare the transformation of by-products between single dielectric barrier discharge (SDBD) and double dielectric barrier discharge (DDBD), to optimize the preparation of graphene-based catalysts and apply them in combination with DBD for volatile organic compound degradation. We compared the degradation performance of SDBD and DDBD, prepared, and characterized graphene-based catalysts. SEM, BET, XRD, and FTIR analyses showed that the morphologies and internal structures of the three catalysts were the best when 0.25 mL of [BMIM]PF6 was added. When MnOx/rGO, FeOx/rGO, and TiOx/rGO were used in combination with DDBD, the degradation rates of benzene were found to be 83.5%, 77.2%, and 63.8%, respectively, whereas the O3 transformation rates were 60%, 79%, and 40%, respectively. Moreover, the NO2 transformation rates were 70%, 55%, and 42.5%, respectively, whereas the NO transformation rates were 69%, 39%, and 33.5%, respectively. The CO2 selectivity was 62%, 51%, and 49%, respectively. MnOx/rGO exhibited superior performance in the degradation of benzene series, NO transformation, NO2 transformation, CO2 selectivity, and energy efficiency. On the other hand, FeOx/rGO exhibited superior performance for O3 transformation. Based upon the XPS analysis, it was found that Mn3O4 and Fe3O4 played a leading role in promoting the degradation of benzene series and the transformation of by-products.

The complete chloroplast genome sequence of Clerodendranthus spicatus, a medicinal plant for preventing and treating kidney diseases from Lamiaceae family.

BACKGROUND: Clerodendranthus spicatus (Thunb.) C. Y. Wu ex H. W. Li is one of the most important medicines for the treatment of nephrology in the southeast regions of China. To understand the taxonomic classification of Clerodendranthus species and identify species discrimination markers, we sequenced and characterized its chloroplast genome in the current study. METHODS AND RESULTS: Total genomic DNA were isolated from dried leaves of C. spicatus and sequenced using an Illumina sequencing platform. The data were assembled and annotated by the NOVOPlasty software and CpGAVAS2 web service. The complete chloroplast genome of C. spicatus was 152,155 bp, including a large single-copy region of 83,098 bp, a small single-copy region of 17,665 bp, and a pair of inverted repeat regions of 25,696 bp. The Isoleucine codons are the most abundant, accounting for 4.17% of all codons. The codons of AUG, UUA, and AGA demonstrated a high degree of usage bias. Twenty-eight simple sequence repeats, thirty-six tandem repeats, and forty interspersed repeats were identified. The distribution of the specific rps19, ycf1, rpl2, trnH, psbA genes were analyzed. Analysis of the genetic distance of the intergenic spacer regions shows that ndhG-ndhI, accD-psaI, rps15-ycf1, rpl20-clpP, ccsA-ndhD regions have high K2p values. Phylogenetic analysis showed that C. spicatu is closely related to two Lamiaceae species, Tectona grandis, and Glechoma longituba. CONCLUSIONS: In this study, we sequenced and characterized the chloroplast genome of C. spicatus. Phylogenomic analysis has identified species closely related to C. spicatus, which represent potential candidates for the development of drugs improving renal functions.

Optimal Course of Statins for Patients With Aneurysmal Subarachnoid Hemorrhage: Is Longer Treatment Better? A Meta-Analysis of Randomized Controlled Trials.

Statins are used in clinical practice to prevent from complications such as cerebral vasospasm (CVS) after aneurysmal subarachnoid hemorrhage (aSAH). However, the efficacy and safety of statins are still controversial due to insufficient evidence from randomized controlled trials and inconsistent results of the existing studies. This meta-analysis aimed to systematically review the latest evidence on the time window and complications of statins in aSAH. The randomized controlled trials in the databases of The Cochrane Library, PubMed, Web of Science, Embase, CNKI, and Wanfang from January 2005 to April 2021 were searched and analyzed systematically. Data analysis was performed using Stata version 16.0. The fixed-effects model (M-H method) with effect size risk ratio (RR) was used for subgroups with homogeneity, and the random-effects model (D-L method) with effect size odds ratio (OR) was used for subgroups with heterogeneity. The primary outcomes were poor neurological prognosis and all-cause mortality, and the secondary outcomes were cerebral vasospasm (CVS) and statin-related complications. This study was registered with PROSPERO (International Prospective Register of Systematic Reviews; CRD42021247376). Nine studies comprising 1,464 patients were included. The Jadad score of the patients was 5-7. Meta-analysis showed that poor neurological prognosis was reduced in patients who took oral statins for 14 days (RR, 0.73 [0.55-0.97]; I 2 = 0%). Surprisingly, the continuous use of statins for 21 days had no significant effect on neurological prognosis (RR, 1.04 [0.89-1.23]; I 2 = 17%). Statins reduced CVS (OR, 0.51 [0.36-0.71]; I 2 = 0%) but increased bacteremia (OR, 1.38 [1.01-1.89]; I 2 = 0%). In conclusion, a short treatment course of statins over 2 weeks may improve neurological prognosis. Statins were associated with reduced CVS. Based on the pathophysiological characteristics of CVS and the evaluation of prognosis, 2 weeks could be the optimal time window for statin treatment in aSAH, although bacteremia may increase.

Detection of Dental Apical Lesions Using CNNs on Periapical Radiograph.

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion.

Characterization and comparative analysis of the plastome sequence from Justicia ventricosa (Lamiales: Acanthaceae).

Justicia ventricosa is a characteristic ethnic herb commonly used to treat Orthopedic pains. Here, to confirm its phylogenetic position and to develop molecular markers that can distinguish different Justicia species, we obtained and analyzed the plastome of Justicia ventricosa. The plastome was sequenced using the Illumina HiSeq sequencing platform, assembled with NOVOPlasty, and annotated with CPGAVAS2. The genome has a circular structure of 149,700 bp, containing a large single-copy region of 82,324 bp, a small single-copy region of 17,260 bp, and two reverse repeat regions of 25,058 bp each. It encodes 112 unique genes, including 76 protein-coding genes, eight ribosomal RNA genes, and 28 transfer RNA genes. Twenty cis-splicing genes were found. In total, we predicted 19 microsatellite repeats and 13 tandem repeat sequences. For distributed repeats, four were palindrome repeats and five were direct repeats. To find the highly variable intergenic spacer (IGS) regions, we calculated the K2P distances for IGS regions from four Justicia species. The K2P values ranged from 6.11 to 57.82. The largest K2P distances were found for ccsA-ndhD, petB-petD, psbK-psbI, and ycf4-cemA. Phylogenetic analysis results showed that J. ventricosa was most closely related to J. leptostachya. To determine how Justicia species adapt to the environment, we performed selection pressure analysis. Nine genes were found to have undergone positive selection. Lastly, we performed a genome-wise DNA barcode prediction, seven pairs of primers were found. The results provide valuable information that can be used for molecular marker development and bioprospecting in Justicia species.