Coupling machine learning and theoretical models to compare key properties of biochar in adsorption kinetics rate and maximum adsorption capacity for emerging contaminants.

Insights into key properties of biochar with a fast adsorption rate and high adsorption capacity are urgent to design biochar as an adsorbent in pollution emergency treatment. Machine learning (ML) incorporating classical theoretical adsorption models was applied to build prediction models for adsorption kinetics rate (i.e., K) and maximum adsorption capacity (i.e., Qm) of emerging contaminants (ECs) on biochar. Results demonstrated that the prediction performance of adaptive boosting algorithm significantly improved after data preprocessing (i.e., log-transformation) in the small unbalanced datasets with R2 of 0.865 and 0.874 for K and Qm, respectively. The surface chemistry, primarily led by ash content of biochar significantly influenced the K, while surface porous structure of biochar showed a dominant role in predicting Qm. An interactive platform was deployed for relevant scientists to predict K and Qm of new biochar for ECs. The research provided practical references for future engineered biochar design for ECs removal.

Elucidation of the evolutionary history of Stipa in China using comparative transcriptomic analysis.

Phylogenetic analysis provides crucial insights into the evolutionary relationships and diversification patterns within specific taxonomic groups. In this study, we aimed to identify the phylogenetic relationships and explore the evolutionary history of Stipa using transcriptomic data. Samples of 12 Stipa species were collected from the Qinghai-Tibet Plateau and Mongolian Plateau, where they are widely distributed, and transcriptome sequencing was performed using their fresh spikelet tissues. Using bidirectional best BLAST analysis, we identified two sets of one-to-one orthologous genes shared between Brachypodium distachyon and the 12 Stipa species (9397 and 2300 sequences, respectively), as well as 62 single-copy orthologous genes. Concatenation methods were used to construct a robust phylogenetic tree for Stipa, and molecular dating was used to estimate divergence times. Our results indicated that Stipa originated during the Pliocene. In approximately 0.8 million years, it diverged into two major clades each consisting of native species from the Mongolian Plateau and the Qinghai-Tibet Plateau, respectively. The evolution of Stipa was closely associated with the development of northern grassland landscapes. Important external factors such as global cooling during the Pleistocene, changes in monsoonal circulation, and tectonic movements contributed to the diversification of Stipa. This study provided a highly supported phylogenetic framework for understanding the evolution of the Stipa genus in China and insights into its diversification patterns.

Middle Meningeal Artery Embolization Combined With Endoscopic Treatment for Chronic Subdural Hematoma.

OBJECTIVE: To explore the clinical feasibility of middle meningeal artery (MMA) embolization combined with endoscopic treatment for new or recurrent chronic subdural hematoma (CSDH). METHODS: Twenty patients with CSDH treated in the Binzhou Medical University Hospital from June 2020 to October 2022 were analyzed retrospectively. The clinical information, prognosis, imaging results, and surgical results of the patients were collected and analyzed. The authors first performed MMA embolization, and then endoscopic treatment of CSDH was performed after successful embolization of MMA. Results: All 20 patients with CSDH were successfully treated with MMA embolization combined with endoscope-assisted evacuation. The symptoms of all patients were relieved, no surgical complications occurred, and no rebleeding and recurrence were found in follow-up computed tomography. CONCLUSION: Middle meningeal artery embolization combined with endoscopic treatment of CSDH has a good clinical effect, and it may prevent postoperative recurrence.

Vitamin E Exerts Neuroprotective Effects in Pentylenetetrazole Kindling Epilepsy via Suppression of Ferroptosis.

Epilepsy is one of the most common chronic neurological diseases. There is increasing evidence for ferroptosis playing an important role in the occurrence and development of epilepsy. Vitamin E is a common fat-soluble antioxidant that can regulate ferroptosis. The aim of this study was to investigate the effects of vitamin E on ferroptosis of hippocampal neurons in epileptic rats. Sixty-four male Sprague-Dawley (SD) rats were randomly divided into control, pentylenetetrazol (PTZ; 35 mg/kg), vitamin E (200 mg/kg) + PTZ, and Ferrostatin-1 (Fer-1; 2.5 µmol/kg) + PTZ groups, with drugs administered intraperitoneally 15 times every other day for 29 days. The behavioral manifestations (epileptic score, latency, and number of seizures in 30 min) and EEG changes were observed and recorded. Nissl staining and electrophysiological recording were used to assess neuronal damage and excitability in the hippocampal CA1 region, respectively. The levels of iron, glutathione (GSH), and malondialdehyde (MDA) in the hippocampus were assessed by spectrophotometry. Immunofluorescence staining was used to detect lipoxygenase 15 (15-LOX) expression. Western blot was used to determine glutathione peroxidase 4 (GPX4) and 15-LOX protein levels. Vitamin E treatment was associated with decreased epileptic grade, seizure latency, and number of seizures in the PTZ-kindled epileptic model. Vitamin E treatment also decreased 15-LOX expression, inhibited MDA and iron accumulation, and increased GPX4 and GSH expression. In conclusion, vitamin E can reduce neuronal ferroptosis and seizures by inhibiting 15-LOX expression.

Highly Stable and Recyclable Sequestration of CO2 Using Supported Melamine on Layered-Chain Clay Mineral.

A type of highly stable and recyclable clay-based composite was developed for sequestration of CO2, which was synthesized by loading melamine (MEL) onto attapulgite (ATT) via a wet impregnation method. The synthesized materials were characterized by N2 adsorption-desorption, Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG), and transmission electron microscopy (TEM). By means of thermal and acidic treatments more active sites of ATT were exposed, and large surface areas were obtained. The MEL molecules were well combined with those exposed sites, which enhanced stability and cyclability for CO2 sequestration. On the basis of CO2 adsorption-desorption measurements, the composite of ATT-MEL was found to have a higher CO2 adsorption capacity (4.91 cm3/g) which was much higher than that of CO2 absorption on bare MEL (1.30 cm3/g) at 30 °C. After ten cycles of reusing, the composite exhibited even higher capacity for CO2 adsorption by an increased percentage of 5.91% (30 °C) and 5.77% (70 °C) compared to the capacity in the first cycle. The reason lies in the strong interaction between melamine and attapulgite matrix which was further confirmed by DFT calculations. The MEL was validated to have advantages over aliphatic amines (TEPA) in modifying ATT to get high stability of CO2-adsorbents.

First Report of Fusarium fujikuroi Causing Leaf spot of Dalbergia odorifera T.Chen in China.

Dalbergia odorifera T. Chen is a national second-grade protected and one of the four famous trees in China, with high medicinal and economic value. Leaf spot disease in this plant can cause the leaves to dry up, perforate or even fall off, which affects the growth and development, and also has a great influence on its products. In May 2019, the leaf spot of Dalbergia odorifera T. Chen was found and observed in Chengmai County (N19°40', E110°0'), Hainan Province, China, and the symptomatic leaves were brought back to the laboratory for research; According to our survey at that time, the incidence of the disease was between 10% and 15%. A sterile stainless-steel scalpel was used to cut the tissues at the junction of the leaf lesions and placed on a clean bench, soaked in alcohol (75 %) for 30 s, and rinsed thrice with sterile water. Then it was inserted obliquely onto lactic acid-containing potato dextrose agar (PDA) and incubated at 28 °C for 5 days. The growing prominent colonies were singled out and re-inoculated on PDA and SNA plates. Preliminary identification was based on morphological characteristics, followed by molecular identification of strains by evaluating genes for translation elongation factor-1α(TEF-1α), beta-tubulin, mitochondrial small subunit (mtSSU)( Duan et al. 2019; Cao et al.2019; Stenglein et al.2010), and histone H3 (Jacobs, et al. 2010) . Through morphological observation, the isolate was identified as Fusarium fujikuroi. At the initial stage of growth on PDA, the strain produced a large number of white hyphae, followed by pink and purple-brown hyphae in the center of the colony which spread to the surrounding area. The microspores were abundant, colorless, elliptic or clavate, without septum or at 1-2 septate, and the size was about 3.3 to 13.5 × 1.2 to 3.2 µm. After nine days of culturing on SNA medium, few, large conidia were observed, typically sickle-like, with 3-4 septa with a size of about 20 to 40.2 × 2.3 to 4.4 µm. The identity of the strains was determined by comparing the gene sequences of TEF-1α, mtSSU, beta-tubulin and histone H3 by NCBI BLAST. The results showed that TEF-1 α (MN958396), mtSSU (MN958394), ß - tubulin (MN958395), and histone H3 (MN958397) from the target strain (jxht0302) had 100% sequence homology with F. fujikuroi (GenBank, accession numbers KF604040.1, MF984420.1, XM023575231.1, and MF356523.1 respectively). Next, the infection of D. odorifera T. Chen seedlings with and without injury was studied using a fungus block, with PDA as a control. Two days after inoculation with injury, obvious lesions were observed on the leaves, which appeared at least 5 days post- inoculation without injury, with no lesions in the control group. F. fujikuroi could be re-isolated from the leaves with lesions, but not from the control group. F. fujikuroi causes Black Rot of Macleaya cordata and maize ear rot (Yull et al.2019; Duan et al. 2019). As far as we know, this is the first report of F. fujikuroi causing leaf spot disease of D. odorifera T. Chen. Given the importance of D. odorifera T. Chen products, this disease needs more attention to tackle it.

Ibuprofen Exerts Antiepileptic and Neuroprotective Effects in the Rat Model of Pentylenetetrazol-Induced Epilepsy via the COX-2/NLRP3/IL-18 Pathway.

Epilepsy is one of the most common diseases of the central nervous system. Recent studies have shown that a variety of inflammatory mediators play a key role in the pathogenesis of the disease. Ibuprofen (IBP) is a well-known anti-inflammatory agent that reduces the neuroinflammatory response and neuronal damage. In this study, we examined the effect of IBP in a rat model of pentylenetetrazol (PTZ)-induced chronic epilepsy. PTZ injection was given a total of 15 times on alternate days (over a period of 29 days) to induce epilepsy. The effects of IBP were evaluated by behavioral observation, EEG recording, Nissl staining, immunohistochemistry, Western blot analysis, and electrophysiological recording. The results showed that IBP alone affected the expression of cyclooxygenase-2 (COX-2) and neuronal excitability but did not cause epilepsy. IBP reduced seizure scores in the PTZ-treated rats, and it minimized the loss of hippocampal neurons. In addition, IBP decreased the secretion of COX-2, inhibited the activation of the NOD-like receptor 3 inflammasome, and reduced the secretion of the inflammatory cytokine interleukin-18. Furthermore, the results of whole-cell patch-clamp revealed that IBP affected action potential properties, including frequency, latency and duration in epileptic rats, suggesting that it may impact neuronal excitability. These effects of IBP may underlie its antiepileptic and neuroprotective actions.

The transcriptional reprograming and functional identification of WRKY family members in pepper's response to Phytophthora capsici infection.

BACKGROUND: Plant transcription factors (TFs) are key transcriptional regulators to manipulate the regulatory network of host immunity. However, the globally transcriptional reprogramming of plant TF families in response to pathogens, especially between the resistant and susceptible host plants, remains largely unknown. RESULTS: Here, we performed time-series RNA-seq from a resistant pepper line CM334 and a susceptible pepper line EC01 upon challenged with Phytophthora capsici, and enrichment analysis indicated that WRKY family most significantly enriched in both CM334 and EC01. Interestingly, we found that nearly half of the WRKY family members were significantly up-regulated, whereas none of them were down-regulated in the two lines. These induced WRKY genes were greatly overlapped between CM334 and EC01. More strikingly, most of these induced WRKY genes were expressed in time-order patterns, and could be mainly divided into three subgroups: early response (3 h-up), mid response (24 h-up) and mid-late response (ML-up) genes. Moreover, it was found that the responses of these ML-up genes were several hours delayed in EC01. Furthermore, a total of 19 induced WRKY genes were selected for functional identification by virus-induced gene silencing. The result revealed that silencing of CaWRKY03-6, CaWRKY03-7, CaWRKY06-5 or CaWRKY10-4 significantly increase the susceptibility to P. capsici both in CM334 and EC01, indicating that they might contribute to pepper's basal defense against P. capsici; while silencing of CaWRKY08-4 and CaWRKY01-10 significantly impaired the disease resistance in CM334 but not in EC01, suggesting that these two WRKY genes are prominent modulators specifically in the resistant pepper plants. CONCLUSIONS: These results considerably extend our understanding of WRKY gene family in pepper's resistance against P. capsici and provide potential applications for genetic improvement against phytophthora blight.

Genome and Transcriptome Analyses Provide Insight Into the Omega-3 Long-Chain Polyunsaturated Fatty Acids Biosynthesis of Schizochytrium limacinum SR21.

Schizochytrium sp. is the best natural resource for omega-3 long-chain polyunsaturated fatty acids. We report a high-quality genome sequence of Schizochytrium limacinum SR21, which has a 63 Mb genome size, with a contig N50 of 2.67 Mb and 6,838 protein-coding genes. Phylogenomic and comparative genomic analyses revealed that DHA-producing Schizochytrium and Aurantiochytrium strains were highly similar and possessed similar genes. Analysis of the fatty acid synthase (FAS) for LC-PUFAs production results in the annotation of all genes in map00062 and map01212. A gene cluster and 10 ORFs related to PKS pathway were found in the genome. 1,402 differentially expressed genes (DEGs) of the treated groups (0.5 g/L yeast extract) were identified by comparing with the control groups (1.0 g/L yeast extract) at 36 h. A weighted gene coexpression network analysis revealed that 2 of 7 modules correlated highly with the fatty acid and DHA contents. The DEGs and transcription factors were significantly correlated with fatty acid biosynthesis, including MYB, Zinc Finger and ACOX. The results showed that these hub genes are regulated by genes involved in fatty acid biosynthesis pathways. The results providing an important reference for further research on promoting fatty acid and DHA accumulation in S. limacinum SR21.

Effect of Ibuprofen on Autophagy of Astrocytes During Pentylenetetrazol-Induced Epilepsy and its Significance: An Experimental Study.

Epilepsy is a chronic neurological disease. Astrogliosis is an important pathological change in epileptic lesions. Studies have reported that ibuprofen can affect autophagy and/or inhibit cell proliferation in many diseases. This study investigated the effect and significance of ibuprofen on autophagy of astrocytes during pentylenetetrazol (PTZ) induced epilepsy. 60 male Sprague-Dawley (SD) rats were randomly divided into five groups: control group (received normal saline), PTZ group, 3-methyladenine (3-MA) + PTZ group, ibuprofen + PTZ group and 3-MA + ibuprofen + PTZ group. Dose of each agent was 35 mg/kg (PTZ), 10 mg/kg (3-MA) and 30 mg/kg (ibuprofen) and all drugs were administered intraperitoneally 15 times on alternate days (29 days). Human astrocytes were cultured in vitro. Behavioral performance (i.e., latency, grade and duration of seizures) and EEG of rats were observed and recorded. Proliferation of astrocytes was detected by CCK-8 method. Immunofluorescence and Western blot test were used to detect the expression of LC3 and GFAP. Mean number, grade and duration of seizures were markedly reduced in ibuprofen + PTZ group and 3-MA + ibuprofen + PTZ group (P < 0.05). Similarly, peak of EEG waves were markedly reduced in ibuprofen + PTZ group and 3-MA + ibuprofen + PTZ group (P < 0.05). Compared to the control group, the level of LC3 in ibuprofen group was significantly increased in vitro (P < 0.05). While, levels of LC3 were significantly higher and that of GFAP were significantly lower in ibuprofen + PTZ group (P < 0.05) compared to PTZ group in vivo. Ibuprofen reduces the proliferation of astrocytes by increasing autophagy, thus affecting the development of epilepsy. Therefore, ibuprofen may be used as an adjuvant to improve efficacy of treatment in epilepsy.

Maximum Likelihood Estimation-Based Joint Sparse Representation for the Classification of Hyperspectral Remote Sensing Images.

A joint sparse representation (JSR) method has shown superior performance for the classification of hyperspectral images (HSIs). However, it is prone to be affected by outliers in the HSI spatial neighborhood. In order to improve the robustness of JSR, we propose a maximum likelihood estimation (MLE)-based JSR (MLEJSR) model, which replaces the traditional quadratic loss function with an MLE-like estimator for measuring the joint approximation error. The MLE-like estimator is actually a function of coding residuals. Given some priors on the coding residuals, the MLEJSR model can be easily converted to an iteratively reweighted JSR problem. Choosing a reasonable weight function, the effect of inhomogeneous neighboring pixels or outliers can be dramatically reduced. We provide a theoretical analysis of MLEJSR from the viewpoint of recovery error and evaluate its empirical performance on three public hyperspectral data sets. Both the theoretical and experimental results demonstrate the effectiveness of our proposed MLEJSR method, especially in the case of large noise.

Correlation and clinical significance of LC3, CD68+ microglia, CD4+ T lymphocytes, and CD8+ T lymphocytes in gliomas.

OBJECTIVE: To investigate the relationship between the expression of microtubule-associated protein LC3 and the numbers of CD68 + microglia, CD4 + T lymphocytes and CD8 + T lymphocytes, as well as the clinical significance of those factors in gliomas. PATIENTS AND METHODS: The study group consisted of 127 patients with gliomas who were operated to our hospital, we examined the expression of LC3 by Immunohistochemistry and Western blot, and we assessed the numbers of CD68 + microglia, CD4 + T lymphocytes and CD8 + T lymphocytes by Immunohistochemistry, we analyze the relationship between all the factors and explore the significance. RESULTS: Immunohistochemistry and Western blotting showed that the expression of LC3 in normal brain tissue, low-grade gliomas, and high-grade gliomas are elevated to varying degrees (P < 0.01); Immunohistochemical detection showed that the numbers of CD68 + microglia, CD4 + T lymphocytes and CD8 + T lymphocytes in gliomas was higher than that in normal brain tissues (P < 0.01), and the high-grade gliomas were higher than those in low-grade gliomas (P < 0.01); The results of Spearman correlation showed that the expression of LC3 was positively correlated with the numbers of CD68 + microglia, CD4 + T lymphocytes, and CD8 + T lymphocytes (P < 0.05); Furthermore, survival analysis showed that LC3, CD68 + microglia, CD8 + T lymphocytes and tumor grade were independent prognostic factors of glioma. CONCLUSIONS: LC3 may be one of the factors that affect the tumor cellular immunity response in gliomas. The simultaneous detection of LC3, CD68 + microglia and CD8 + T lymphocytes can be used to assess the prognosis of glioma.

Maximum likelihood estimation based regression for multivariate calibration.

In this paper, we propose a maximum likelihood estimation based regression (MLER) model for multivariate calibration. The proposed MLER method seeks for the maximum likelihood estimation (MLE) solution of the least-squares problem, and it is much more robust to noise or outliers and accurate than the traditional least-squares method. An efficient iteratively reweighted least squares technique is proposed to solve the MLER model. As a result, our model can obtain accurate spectra-concentrate relations. Experimental results on three real near-infrared (NIR) spectra data sets demonstrate that the proposed MLER model is much more efficacious and effective than state-of-the-art partial least squares (PLS) methods.

Near and Mid-Infrared Emission Characteristics of Er³âº/Tm³âº/Ho³âº-Doped LiYF4 Single Crystals Excited by Laser Diode.

Yttrium lithium fluoride (LiYF4) single crystals triply doped with Er³âº/Tm³âº/Ho³âº are synthesized by a vertical Bridgman method. Absorption spectra, emission spectra, and decay curves are measured to investigate the luminescent properties of the crystals. Compared with Er³âº singly doped and Er³âº/Tm³âº and Er³âº/Ho³âº doubly doped LiYF4 crystals, an intense emission around 2.7 µm can be obtained in the triply doped LiYF4 crystal under excitation of 980 nm laser diode. Meanwhile, the near infrared emission at 1.5 µm from Er³âº in the triply doped crystal is effectively reduced. The possible energy transfer processes and the luminescent mechanisms for enhancing emission at 2.7 µm and quenching emission at 1.5 µm in the Er³âº/Ho³âº/Tm³âº triply doped crystals are proposed. The large energy transfer efficiency of 82.0% and excellent optical transmission indicate that this Er³âº/Tm³âº/Ho³âº triply doped crystal can be considered as a promising material for a mid- infrared laser at 2.7 µm.

Extreme learning machine for ranking: generalization analysis and applications.

The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods.

[FTIR spectral fitting algorithm based on continuous wavelet transform].

An FTIR spectrum fitting algorithm based on continuous wavelet transform is proposed. In calculating the factor of difference spectrum, the algorithm takes into account both the original spectrum and its continuous wavelet transformed spectra, which effectively overcomes the problem of reference peak selection and manual factor selection in most commercial software. The detailed discussions on wavelet scale, order and basis are included. The spectral fitting is performed on six wavelet basis functions and the obtained scale factor is used to quantify the content of liquor, and the corresponding mean absolute error ranges from 0.047 to 0.072, and the standard deviation ranges from 0.056 to 0.091. Experimental results show that the CWT combined with least squares fitting provides an accurate and reliable new method for FTIR spectral subtraction.

An improved ensemble partial least squares for analysis of near-infrared spectra.

Traditional ensemble regression algorithms such as BAgging Partial Least Squares (BAPLS) and BOosting Partial Least Squares (BOPLS) do not perform very well in the data set that is relatively small or contaminated by random noise. To make the method robust and improve its prediction ability, inspired from bias-variance-covariance decomposition, we propose an improved ensemble partial least squares method based on the diversity. The new method is applied to quantitative analysis of Near InfraRed (NIR) data sets. A comparative study between the proposed method and other previous methods including BAPLS and BOPLS on two NIR data sets is provided. Experimental results show that the proposed method can achieve better performance than other methods.

Partial least squares and random sample consensus in outlier detection.

A novel outlier detection method in partial least squares based on random sample consensus is proposed. The proposed algorithm repeatedly generates partial least squares solutions estimated from random samples and then tests each solution for the support from the complete dataset for consistency. A comparative study of the proposed method and leave-one-out cross validation in outlier detection on simulated data and near-infrared data of pharmaceutical tablets is presented. In addition, a comparison between the proposed method and PLS, RSIMPLS, PRM is provided. The obtained results demonstrate that the proposed method is highly efficient.

Baseline correction combined partial least squares algorithm and its application in on-line Fourier transform infrared quantitative analysis.

In order to eliminate the lower order polynomial interferences, a new quantitative calibration algorithm "Baseline Correction Combined Partial Least Squares (BCC-PLS)", which combines baseline correction and conventional PLS, is proposed. By embedding baseline correction constraints into PLS weights selection, the proposed calibration algorithm overcomes the uncertainty in baseline correction and can meet the requirement of on-line attenuated total reflectance Fourier transform infrared (ATR-FTIR) quantitative analysis. The effectiveness of the algorithm is evaluated by the analysis of glucose and marzipan ATR-FTIR spectra. BCC-PLS algorithm shows improved prediction performance over PLS. The root mean square error of cross-validation (RMSECV) on marzipan spectra for the prediction of the moisture is found to be 0.53%, w/w (range 7-19%). The sugar content is predicted with a RMSECV of 2.04%, w/w (range 33-68%).

Near-infrared calibration transfer based on spectral regression.

A calibration transfer method for near-infrared (NIR) spectra based on spectral regression is proposed. Spectral regression method can reveal low dimensional manifold structure in high dimensional spectroscopic data and is suitable to transfer the NIR spectra of different instruments. A comparative study of the proposed method and piecewise direct standardization (PDS) for standardization on two benchmark NIR data sets is presented. Experimental results show that spectral regression method outperforms PDS and is quite competitive with PDS with background correction. When the standardization subset has sufficient samples, spectral regression method exhibits excellent performance.