DL-3-n-butylphthalide (NBP) alleviates poststroke cognitive impairment (PSCI) by suppressing neuroinflammation and oxidative stress

Currently, the recovery of cognitive function has become an essential part of stroke rehabilitation. DL-3-n-butylphthalide (NBP) is a neuroprotective reagent and has been used in stroke treatment. Clinical studies have confirmed that NBP can achieve better cognitive outcomes in ischemic stroke patients than in healthy controls. In this study, we aimed to investigate the influences of NBP on cognitive function in an ischemic reperfusion (I/R) rat model. Our results showed that NBP profoundly decreased neurological scores, reduced cerebral infarct areas and enhanced cerebral blood flow (CBF). NBP potently alleviated poststroke cognitive impairment (PSCI) including depression-like behavior and learning, memory and social cognition impairments, in I/R rats. NBP distinctly suppressed the activation of microglia and astrocytes and improved neuron viability in the ischemic brain. NBP inhibited the expression of inflammatory cytokines, including interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α), by targeting the nuclear factor kappa B/inducible nitric oxide synthase (NF-κB/iNOS) pathway and decreased cerebral oxidative stress factors, including reactive oxygen species (ROS) and malondialdehyde (MDA), by targeting the kelch like ECH associated protein 1/nuclear factor-erythroid 2 p45-related factor 2 (Keap1/Nrf2) pathway in the ischemic brain. The current study revealed that NBP treatment improved neurological function and ameliorated cognitive impairment in I/R rats, possibly by synergistically suppressing inflammation and oxidative stress.

Pharmacokinetics effects of chuanxiong rhizoma on warfarin in pseudo germ-free rats

Aim: In China, warfarin is usually prescribed with Chuanxiong Rhizoma for treating thromboembolism diseases. However, the reason for their combination is still being determined. The present study explored the pharmacokinetics interactions of warfarin, Chuanxiong Rhizoma, and gut microbiota in the rat model of middle cerebral artery occlusion (MCAO). Methods: A total of 48 rats were randomly divided into six groups: MCAO rats orally administered warfarin (W group), pseudo germ-free MCAO rats orally administered warfarin (W-f group), MCAO rats co-administered Chuanxiong Rhizoma and warfarin (C + W group), pseudo germ-free MCAO rats co-administered Chuanxiong Rhizoma and warfarin (C + W-f group), MCAO rats co-administered warfarin and senkyunolide I (S + W group); pseudo germ-free MCAO rats co-administered warfarin and senkyunolide I (S + W-f group). After treatment, all animals' blood and stool samples were collected at different time points. The stool samples were used for 16S rRNA sequencing analysis. Ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) method was established to quantify warfarin, internal standards, and the main bioactive components of Chuanxiong in blood samples. The main pharmacokinetics parameters of warfarin were calculated by DAS 2.1.1 software. Results: The relative abundance of Allobaculum and Dubosiella in the pseudo germ-free groups (W-f, C + W-f, S + W-f) was lower than that in the other three groups (W, C + W, S + W). The relative abundance of Lactobacillus in the W-f group was higher than that of the W group, while the relative abundance of Akkermansia decreased. The relative abundance of Ruminococcaceae_UCG-014 and Ruminococcaceae_NK4A214_group in the S + W-f group was lower than in the S + W group. Compared to the W group, the AUC_0-t and C_max of warfarin in the W-f group increased significantly to 51.26% and 34.58%, respectively. The AUC_0-t and C_max in the C + W group promoted 71.20% and 65.75% more than the W group. Compared to the W group, the AUC_0-t and C_max increased to 64.98% and 64.39% in the S + W group. Conclusion: Chuanxiong Rhizoma and senkyunolide I (the most abundant metabolites of Chuanxiong Rhizoma aqueous extract) might affect the pharmacokinetics features of warfarin in MCAO rats through, at least partly, gut microbiota.

MNNMDA: Predicting human microbe-disease association via a method to minimize matrix nuclear norm

Identifying the potential associations between microbes and diseases is the first step for revealing the pathological mechanisms of microbe-associated diseases. However, traditional culture-based microbial experiments are expensive and time-consuming. Thus, it is critical to prioritize disease-associated microbes by computational methods for further experimental validation. In this study, we proposed a novel method called MNNMDA, to predict microbe-disease associations (MDAs) by applying a Matrix Nuclear Norm method into known microbe and disease data. Specifically, we first calculated Gaussian interaction profile kernel similarity and functional similarity for diseases and microbes. Then we constructed a heterogeneous information network by combining the integrated disease similarity network, the integrated microbe similarity network and the known microbe-disease bipartite network. Finally, we formulated the microbe-disease association prediction problem as a low-rank matrix completion problem, which was solved by minimizing the nuclear norm of a matrix with a few regularization terms. We tested the performances of MNNMDA in three datasets including HMDAD, Disbiome, and Combined Data with small, medium and large sizes respectively. We also compared MNNMDA with 5 state-of-the-art methods including KATZHMDA, LRLSHMDA, NTSHMDA, GATMDA, and KGNMDA, respectively. MNNMDA achieved area under the ROC curves (AUROC) of 0.9536 and 0.9364 respectively on HDMAD and Disbiome, better than the AUCs of compared methods under the 5-fold cross-validation for all microbe-disease associations. It also obtained a relatively good performance with AUROC 0.8858 in the combined data. In addition, MNNMDA was also better than other methods in area under precision and recall curve (AUPR) under the 5-fold cross-validation for all associations, and in both AUROC and AUPR under the 5-fold cross-validation for diseases and the 5-fold cross-validation for microbes. Finally, the case studies on colon cancer and inflammatory bowel disease (IBD) also validated the effectiveness of MNNMDA. In conclusion, MNNMDA is an effective method in predicting microbe-disease associations.

Availability

The codes and data for this paper are freely available at Github https://github.com/Haiyan-Liu666/MNNMDA.

[Value of clear cell likelihood score in differentiation between renal oncocytoma and clear cell renal cell carcinoma]

Objective: To evaluate the value of clear cell likelihood score (ccLS) in identifying renal oncocytoma (RO) and clear cell renal cell carcinoma (ccRCC). Methods: Retrospective data of pathologically confirmed 43 RO patients [24 men and 19 women, aged 22-77 (54±14) years] between February 2008 and September 2021 and 43 ccRCC patients [30 men and 13 women, aged 29-78 (56±12) years] between May and July 2021 were consecutively included in the department of radiology, Chinese PLA General Hospital. Two radiologists used ccLS to assess each case independently, and disagreements were resolved by consensus. The ability of ccLS to identify RO and ccRCC was examined by the receiver operating characteristic (ROC) curve which identified the best optimal diagnostic cut-off values, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. Results: The mean tumor diameter was 3.8 cm in RO patients and 3.7 cm in ccRCC patients. Central scar and segmental enhancement inversion (SEI) were more frequently observed in the RO group compared to the ccRCC group [53.5% (23∶43) versus 11.6% (5∶43) and 41.9% (18∶43) versus 7.0% (3∶43), respectively], with statistical differences (P<0.001). The ccLS scores in the RO group ranged from 1 to 4, while 79.0% of the cases were 3. The ccLS scores in the ccRCC group ranged from 2 to 5, while 72% of the cases were 4. The scores of the two groups were statistically different (P<0.001). The ccLS showed the best performance when the threshold was 4 according to the ROC curve. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of ccLS for distinguishing RO from ccRCC were 83.7%, 90.7%, 87.2%, 90.0%, and 84.8%, respectively, and the area under the ROC curve value was 0.879. Conclusion: The ccLS has credible sensitivity and specificity in differentiating renal oncocytoma from clear cell carcinoma, which may be helpful for the preoperative diagnosis.

Drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization

Coronavirus disease 2019 (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently spreading rapidly around the world. Since SARS-CoV-2 seriously threatens human life and health as well as the development of the world economy, it is very urgent to identify effective drugs against this virus. However, traditional methods to develop new drugs are costly and time-consuming, which makes drug repositioning a promising exploration direction for this purpose. In this study, we collected known antiviral drugs to form five virus-drug association datasets, and then explored drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization (VDA-GKSBMF). By the 5-fold cross-validation, we found that VDA-GKSBMF has an area under curve (AUC) value of 0.8851, 0.8594, 0.8807, 0.8824, and 0.8804, respectively, on the five datasets, which are higher than those of other state-of-art algorithms in four datasets. Based on known virus-drug association data, we used VDA-GKSBMF to prioritize the top-k candidate antiviral drugs that are most likely to be effective against SARS-CoV-2. We confirmed that the top-10 drugs can be molecularly docked with virus spikes protein/human ACE2 by AutoDock on five datasets. Among them, four antiviral drugs ribavirin, remdesivir, oseltamivir, and zidovudine have been under clinical trials or supported in recent literatures. The results suggest that VDA-GKSBMF is an effective algorithm for identifying potential antiviral drugs against SARS-CoV-2.

DGHNE: network enhancement-based method in identifying disease-causing genes through a heterogeneous biomedical network

The identification of disease-causing genes is critical for mechanistic understanding of disease etiology and clinical manipulation in disease prevention and treatment. Yet the existing approaches in tackling this question are inadequate in accuracy and efficiency, demanding computational methods with higher identification power. Here, we proposed a new method called DGHNE to identify disease-causing genes through a heterogeneous biomedical network empowered by network enhancement. First, a disease-disease association network was constructed by the cosine similarity scores between phenotype annotation vectors of diseases, and a new heterogeneous biomedical network was constructed by using disease-gene associations to connect the disease-disease network and gene-gene network. Then, the heterogeneous biomedical network was further enhanced by using network embedding based on the Gaussian random projection. Finally, network propagation was used to identify candidate genes in the enhanced network. We applied DGHNE together with five other methods into the most updated disease-gene association database termed DisGeNet. Compared with all other methods, DGHNE displayed the highest area under the receiver operating characteristic curve and the precision-recall curve, as well as the highest precision and recall, in both the global 5-fold cross-validation and predicting new disease-gene associations. We further performed DGHNE in identifying the candidate causal genes of Parkinson's disease and diabetes mellitus, and the genes connecting hyperglycemia and diabetes mellitus. In all cases, the predicted causing genes were enriched in disease-associated gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, and the gene-disease associations were highly evidenced by independent experimental studies.

Effects of Artemisia argyi Powder on Egg Quality, Antioxidant Capacity, and Intestinal Development of Roman Laying Hens

This study was conducted to evaluate the effect of dietary supplementation with Artemisia argyi (A. argyi) on egg quality, serum biochemical, antioxidant capacity, and intestinal development in Roman laying hens. A total of 432 (34-week-old) Roman hens were randomly divided into control group and three experimental groups. The control group was fed a basal diet, and the experimental group was fed a basal diet with 1%, 2%, and 3% A. argyi powder, respectively. The results showed that dietary supplementation of 2% A. argyi to the diet increased egg weight and egg white weight, and the daturic acid (C17:0), stearic acid (C18:0), eicosadienoic acid (C20:2), docosahexaenoic acid (C22:6n-3), α-linolenic acid (C18:3n-3), linoleic acid (C18:2n-6c), and polyunsaturated fatty acid (PUFA) in egg yolk. Meanwhile, the addition of 1∼3% A. argyi decreased serum urea. Moreover, dietary supplementation of 1% A. argyi promoted the antioxidative capacity of the hens by increasing hepatic T-SOD and CAT activities, as well as GSH-Px content. However, the addition of 3% A. argyi to the diet significantly increased the content of malondialdehyde in serum and liver and destroyed the intestinal morphology by increasing duodenal crypt depth. In conclusion, the addition level of A. argyi promoting egg quality and antioxidant capacity was at 2% and 1%, respectively.

Auricular acupressure for treating early stage of knee osteoarthritis: a randomized, sham-controlled prospective study

OBJECTIVE

We examined whether auricular acupressure (AA) at four specifically preselected AA points can alleviate knee pain and decrease non-steroidal anti-inflammatory drugs (NSAIDs) consumption and its adverse effects for osteoarthritis patients.

METHODS

Sixty-two patients (more than 40 years) with knee osteoarthritis of Kellgren-Lawrence grades of I or II upon radiographic classification were enrolled in this randomized, sham-controlled prospective study, and divided into two groups (AA group and control group). The AA group received true AA by embedding vaccaria seeds at four specific AA points (knee joint, shenmen, subcortex and sympathesis) ipsilateral to the knee osteoarthritis site, while the control group received four nonacupuncture points on the auricular helix. Visual analog scale (VAS), the Western Ontario and McMaster Universities Arthritis Index (WOMAC) score, the number of patients who needed celecoxib pills and adverse effects were recorded.

RESULTS

VAS and WOMAC scores in the AA group were significantly lower than that in the control group (P < 0.05) at Days 3 and 7 postsugery. The VAS and WOMAC score were significantly decreased after the treatment in the AA group compared with that before the treatment (P < 0.05). The use of celebrex is significantly lower in the AA group than in the control group (P < 0.05), no major side effects were observed during the auricular acupressure treatment.

CONCLUSION

Auricular acupressure plays a role in analgesic effect and can effectively decrease NSAIDs requirements without causing adverse events for the treatment of human knee osteoarthritis.

Evaluating the performance of dropout imputation and clustering methods for single-cell RNA sequencing data

Recent advances in single-cell RNA sequencing (scRNA-seq) provide exciting opportunities for transcriptome analysis at single-cell resolution. Clustering individual cells is a key step to reveal cell subtypes and infer cell lineage in scRNA-seq analysis. Although many dedicated algorithms have been proposed, clustering quality remains a computational challenge for scRNA-seq data, which is exacerbated by inflated zero counts due to various technical noise. To address this challenge, we assess the combinations of nine popular dropout imputation methods and eight clustering methods on a collection of 10 well-annotated scRNA-seq datasets with different sample sizes. Our results show that (i) imputation algorithms do typically improve the performance of clustering methods, and the quality of data visualization using t-Distributed Stochastic Neighbor Embedding; and (ii) the performance of a particular combination of imputation and clustering methods varies with dataset size. For example, the combination of single-cell analysis via expression recovery and Sparse Subspace Clustering (SSC) methods usually works well on smaller datasets, while the combination of adaptively-thresholded low-rank approximation and single-cell interpretation via multikernel learning (SIMLR) usually achieves the best performance on larger datasets.

Short period-administration of myo-inositol and metformin on hormonal and glycolipid profiles in patients with polycystic ovary syndrome: a systematic review and updated meta-analysis of randomized controlled trials

OBJECTIVE

This meta-analysis aims to perform an updated meta-analysis to evaluate myo-inositol (myo-ins) and the classical insulin sensitizer metformin in terms of efficacy and safety for treating women with polycystic ovary syndrome (PCOS).

MATERIALS AND METHODS

A comprehensive literature search was performed using PubMed, Web of Science, EMBASE, Cochrane Library, PhRMA Clinical Study Results, Wan Fang, and CNKI databases; the database was searched from inception to June 2021. The random effects model was chosen to synthesize the effect sizes of individual trails. The registration number is CRD42021239786.

RESULTS

Nine randomized controlled trials (RCTs) and 612 patients were included in the analysis. Compared with metformin, myo-ins might be more effective in lowering triglycerides (TG) levels (SMD -0.49, 95% CI -0.74 to -0.24, p=0.0001, I2 = 0%) and avoiding side effects (RR=0.14, 95% CI 0.08-0.24, p<0.00001, I2 = 2%), while no significant differences were observed in other relevant indexes, such as total testosterone (TT) and sex-hormone binding globulin (SHBG).

CONCLUSIONS

Compared with metformin, the suitable supplemental dosage of myo-ins may be helpful in lowering levels of TG and avoiding adverse events (AEs).

Robust but weak winter atmospheric circulation response to future Arctic sea ice loss

The possibility that Arctic sea ice loss weakens mid-latitude westerlies, promoting more severe cold winters, has sparked more than a decade of scientific debate, with apparent support from observations but inconclusive modelling evidence. Here we show that sixteen models contributing to the Polar Amplification Model Intercomparison Project simulate a weakening of mid-latitude westerlies in response to projected Arctic sea ice loss. We develop an emergent constraint based on eddy feedback, which is 1.2 to 3 times too weak in the models, suggesting that the real-world weakening lies towards the higher end of the model simulations. Still, the modelled response to Arctic sea ice loss is weak: the North Atlantic Oscillation response is similar in magnitude and offsets the projected response to increased greenhouse gases, but would only account for around 10% of variations in individual years. We further find that relationships between Arctic sea ice and atmospheric circulation have weakened recently in observations and are no longer inconsistent with those in models.

Migration inhibition and selective cytotoxicity of cobalt hydroxide nanosheets on different cancer cell lines

5 nm-thick cobalt hydroxide nanosheets exhibited concentration-dependent selective antitumor activity and cell migration inhibition against a variety of cancer cells.

Morphological classification and clinical significance of medial malleolus based on computed tomography three-dimensional reconstruction

BACKGROUND

Internal malleolus fractures and postoperative functional limitations are serious complications of deltoid ligament repair, reconstruction, while studies on conducting beak. Anatomical structure classification of medial malleolus at home and abroad is reported rarely. Hence, this morphological study is mainly designed to investigate the anatomical morphological classification and clinical significance of medial malleolus based on computed tomography (CT) three-dimensional reconstruction.

MATERIALS AND METHODS

From October 2018 to January 2021, 373 patients who underwent CT examination of malleolus medialis joint in the Jiang'an Hospital of Traditional Chinese Medicine were observed. The medial malleolus was observed and classified; then, geometric parameters were measured according to different medial malleolus types.

RESULTS

According to the results of 373 cases, medial malleolus can be divided into four types: omega type (66%), radical sign type (16%), inverted triangle type (14%), and wave type (4%).

CONCLUSIONS

There are four main shapes: omega, inverted triangle, radical sign, and wave in the medial malleolus of all normal ankles. The measurement of medial malleolus parameters according to medial malleolus in different shapes was of importance to guide smooth operation of medial malleolus fixation and deltoid ligament reconstruction and epidemiological.

Evaluating Cancer-Related Biomarkers Based on Pathological Images: A Systematic Review

Many diseases are accompanied by changes in certain biochemical indicators called biomarkers in cells or tissues. A variety of biomarkers, including proteins, nucleic acids, antibodies, and peptides, have been identified. Tumor biomarkers have been widely used in cancer risk assessment, early screening, diagnosis, prognosis, treatment, and progression monitoring. For example, the number of circulating tumor cell (CTC) is a prognostic indicator of breast cancer overall survival, and tumor mutation burden (TMB) can be used to predict the efficacy of immune checkpoint inhibitors. Currently, clinical methods such as polymerase chain reaction (PCR) and next generation sequencing (NGS) are mainly adopted to evaluate these biomarkers, which are time-consuming and expansive. Pathological image analysis is an essential tool in medical research, disease diagnosis and treatment, functioning by extracting important physiological and pathological information or knowledge from medical images. Recently, deep learning-based analysis on pathological images and morphology to predict tumor biomarkers has attracted great attention from both medical image and machine learning communities, as this combination not only reduces the burden on pathologists but also saves high costs and time. Therefore, it is necessary to summarize the current process of processing pathological images and key steps and methods used in each process, including: (1) pre-processing of pathological images, (2) image segmentation, (3) feature extraction, and (4) feature model construction. This will help people choose better and more appropriate medical image processing methods when predicting tumor biomarkers.

Evaluation of the MGISEQ-2000 Sequencing Platform for Illumina Target Capture Sequencing Libraries

Illumina is the leading sequencing platform in the next-generation sequencing (NGS) market globally. In recent years, MGI Tech has presented a series of new sequencers, including DNBSEQ-T7, MGISEQ-2000 and MGISEQ-200. As a complex application of NGS, cancer-detecting panels pose increasing demands for the high accuracy and sensitivity of sequencing and data analysis. In this study, we used the same capture DNA libraries constructed based on the Illumina protocol to evaluate the performance of the Illumina Nextseq500 and MGISEQ-2000 sequencing platforms. We found that the two platforms had high consistency in the results of hotspot mutation analysis; more importantly, we found that there was a significant loss of fragments in the 101-133 bp size range on the MGISEQ-2000 sequencing platform for Illumina libraries, but not for the capture DNA libraries prepared based on the MGISEQ protocol. This phenomenon may indicate fragment selection or low fragment ligation efficiency during the DNA circularization step, which is a unique step of the MGISEQ-2000 sequence platform. In conclusion, these different sequencing libraries and corresponding sequencing platforms are compatible with each other, but protocol and platform selection need to be carefully evaluated in combination with research purpose.

Zoledronic acid and fracture risk: a meta-analysis of 12 randomized controlled trials

OBJECTIVE

Zoledronic acid is widely used in patients with osteoporosis, and this meta-analysis aims to explore the influence of zoledronic acid on fracture risk and mortality in patients with osteoporosis or osteopenia.

MATERIALS AND METHODS

We searched PubMed, Google Scholar, and Cochrane Library for randomized clinical trials comparing zoledronic acid with control intervention (i.e., placebo or nothing) for osteoporosis or osteopenia. The fracture and mortality were estimated using the random-effect model.

RESULTS

12 randomized trials were included in this meta-analysis. Compared to control intervention, zoledronic acid was associated with significantly reduced incidence of fracture at the follow-up of 12 months, 24 months, 36 months and 72 months. In addition, zoledronic acid could remarkably reduce mortality at 12 months and 24 months than control intervention but revealed no influence on mortality at 36 months or 72 months. In terms of adverse events, zoledronic acid might result in the increase in serious atrial fibrillation and death from stroke than control intervention.

CONCLUSIONS

Zoledronic acid is beneficial to reduce the incidence of fracture, while its benefits to reduce the mortality are only observed at the follow-up time of 24 months.

Preparation and preliminary quality evaluation of aspirin/L-glutamate compound pellets

L-glutamate is an important component of protein. It can prevent gastrointestinal damage caused by NSAIDs. We constructed two-phase enteric-coated granules of aspirin and L-glutamate compound by extrusion spheronization method and fluidized bed coating. The subliminal effective dose of L-glutamate is 100 mg/kg tested by model of gastric ulcer of rats induced by aspirin and drug administration. HPLC-UV and UV-Vis methods were adopted to determine content and cumulative release of aspirin and L-glutamate as quality analysis method indexes. The prescription and process optimization were carried out with yield, sphericity and dissolution. The two-phase compound granules have good sphericity of 0.93 ± 0.05 (aspirin pellets) and 0.94 ± 0.02 (L-glutamate pellets), content of salicylic acid (0.24 ± 0.03)%, dissolution of aspirin (2.36 ± 0.11)%. Quality evaluation and preliminary stability meet the commercial requirements. The stored environment of compound preparation should be sealed in a cool and dark place.

[Imaging phenotypes of chronic obstructive pulmonary disease based on biphasic quantitative CT features]

Quantitative analysis was performed on the biphasic CT of 40 patients [43-80 (66.1±9.0) years old, including 37 males] with stable chronic obstructive pulmonary disease (COPD) to measure the percentage of emphysema (Emph%); the percentage of small airway disease (SAD%) and the square root of the wall area of hypothetical airway with internal perimeter of 10 mm (Pi10). Based on the cluster analysis of Emph%, SAD% and Pi10, the patients were divided into five imaging phenotypes including no obvious imaging abnormality type (n=11), small airway disease-dominant type (n=9), bronchial wall thickening-dominant type (n=8), emphysema-dominant type (n=6) and mixed type (n=6). Patients with the same Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade had similar degree of airflow limitation, but the lesion components were not identical. Being different from the traditional imaging classification, even in the cases of mild emphysema, they can be further divided into small airway disease-dominant type and bronchial wall thickening-dominant type according to the difference of airway disease.

A Review of Current In Silico Methods for Repositioning Drugs and Chemical Compounds

Drug repositioning is a new way of applying the existing therapeutics to new disease indications. Due to the exorbitant cost and high failure rate in developing new drugs, the continued use of existing drugs for treatment, especially anti-tumor drugs, has become a widespread practice. With the assistance of high-throughput sequencing techniques, many efficient methods have been proposed and applied in drug repositioning and individualized tumor treatment. Current computational methods for repositioning drugs and chemical compounds can be divided into four categories: (i) feature-based methods, (ii) matrix decomposition-based methods, (iii) network-based methods, and (iv) reverse transcriptome-based methods. In this article, we comprehensively review the widely used methods in the above four categories. Finally, we summarize the advantages and disadvantages of these methods and indicate future directions for more sensitive computational drug repositioning methods and individualized tumor treatment, which are critical for further experimental validation.

Potential and applications of capillary electrophoresis for analyzing traditional Chinese medicine: a critical review

Capillary electrophoresis (CE) presents a promising possibility for analyzing traditional Chinese medicine (TCM) due to its low reagent consumption, high analysis speed, and enhanced efficiency. Herein we review the employment of CE for analyzing the effective components in TCM and identifying TCM via a fingerprint. Furthermore, we discuss the application of state-of-the-art capillary electrophoresis modes for screening enzyme inhibitors and investigating the interactions between TCM and plasma proteins. The review concludes with recommendations for future studies and improvements in this field of research. The general development trend identified in this review indicates that the application of CE has significantly improved TCM assay performance.

Successful removal of a trapped epidural catheter facilitated by using a nickel/titanium alloy (nitinol) suture as a guidewire

Epidural catheters are often used in the provision of surgical anaesthesia and analgesia. These catheters need to be removed after a certain period, but difficulties may be encountered during this process. We present a case of difficult epidural catheter removal in an elderly woman who had undergone surgery for reduction and internal fixation of a comminuted intertrochanteric fracture at the left femur under combined spinal epidural anaesthesia. Anaesthesia was satisfactory during the operation; however, initial attempts to remove the catheter at the end of the procedure was met with significant resistance. Normal saline (5 ml) was injected through the catheter without difficulty, suggesting that the catheter was likely trapped and compressed but not obstructed. A nickel/titanium memory alloy suture was used as a guidewire to remove the catheter without damaging it. This case was analysed subsequently, and the management of future problematic removals is discussed herein. This article aims to raise awareness of, and to explore techniques for managing difficult epidural catheter removal.

The phytotoxin COR induces transcriptional reprogramming of photosynthetic, hormonal and defence networks in tomato

Coronatine (COR) is a non-host specific phytotoxin secreted by Pseudomonas syringae pv. tomato that can induce leaf chlorosis and increase the virulence of pathogens during plant-pathogen interactions. Studies have shown that COR can regulate multiple physiological processes in plants, but its involvement in bacterial pathogenesis and plant growth regulation is not well understood. In this study, transcriptome sequencing was carried out on 4-week-old tomato leaves that were either mock-treated or treated with COR. Transcriptome sequencing led to the identification of 6144 differentially expressed genes (DEGs), of which 4361 genes were downregulated and 1783 genes were upregulated upon COR treatment. To obtain functional information on the DEGs, we annotated these genes using GO and KEGG databases. Functional classification analysis showed that the DEGs were primarily involved in photosynthesis, chlorophyll and carotenoid biosynthesis, jasmonic acid (JA) synthesis and phenylpropane metabolism. A total of 23 genes related to chlorophyll biosynthesis had significant changes, of which 22 genes were downregulated and one gene was upregulated, indicating that chlorophyll biosynthesis was inhibited upon COR treatment. A total of 17 photosystem I related genes and 22 photosystem II related genes involving 20 protein subunits were also downregulated. In the JA synthesis pathway, 25 genes were up regulated, and six genes were downregulated in COR treated samples. COR was also involved in the regulation of multiple secondary metabolites. The identified DEGs will help us better understand the virulence effects and physiological functions of COR and provide a theoretical basis for breeding resistance into economically important crops.