Predicting lncRNA-protein interactions through deep learning framework employing multiple features and random forest algorithm.

RNA-protein interaction (RPI) is crucial to the life processes of diverse organisms. Various researchers have identified RPI through long-term and high-cost biological experiments. Although numerous machine learning and deep learning-based methods for predicting RPI currently exist, their robustness and generalizability have significant room for improvement. This study proposes LPI-MFF, an RPI prediction model based on multi-source information fusion, to address these issues. The LPI-MFF employed protein-protein interactions features, sequence features, secondary structure features, and physical and chemical properties as the information sources with the corresponding coding scheme, followed by the random forest algorithm for feature screening. Finally, all information was combined and a classification method based on convolutional neural networks is used. The experimental results of fivefold cross-validation demonstrated that the accuracy of LPI-MFF on RPI1807 and NPInter was 97.60% and 97.67%, respectively. In addition, the accuracy rate on the independent test set RPI1168 was 84.9%, and the accuracy rate on the Mus musculus dataset was 90.91%. Accordingly, LPI-MFF demonstrated greater robustness and generalization than other prevalent RPI prediction methods.

eccDB: a comprehensive repository for eccDNA-mediated chromatin contacts in multi-species.

SUMMARY: We developed the eccDB database to integrate available resources for extrachromosomal circular DNA (eccDNA) data. eccDB is a comprehensive repository for storing, browsing, searching, and analyzing eccDNAs from multispecies. The database provides regulatory and epigenetic information on eccDNAs, with a focus on analyzing intrachromosomal and interchromosomal interactions to predict their transcriptional regulatory functions. Moreover, eccDB identifies eccDNAs from unknown DNA sequences and analyzes the functional and evolutionary relationships of eccDNAs among different species. Overall, eccDB offers web-based analytical tools and a comprehensive resource for biologists and clinicians to decipher the molecular regulatory mechanisms of eccDNAs. AVAILABILITY AND IMPLEMENTATION: eccDB is freely available at http://www.xiejjlab.bio/eccDB.

Clinical data mining: challenges, opportunities, and recommendations for translational applications.

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

Effects of apparent temperature on daily outpatient and inpatient visits for cause-specific respiratory diseases in Ganzhou, China: a time series study.

BACKGROUND: Non-optimum temperatures are associated with increased risk of respiratory diseases, but the effects of apparent temperature (AT) on respiratory diseases remain to be investigated. METHODS: Using daily data from 2016 to 2020 in Ganzhou, a large city in southern China, we analyzed the impact of AT on outpatient and inpatient visits for respiratory diseases. We considered total respiratory diseases and five subtypes (influenza and pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma and chronic obstructive pulmonary disease [COPD]). Our analysis employed a distributed lag nonlinear model (DLNM) combined with a generalized additive model (GAM). RESULTS: We recorded 94,952 outpatients and 72,410 inpatients for respiratory diseases. We found AT significantly non-linearly associated with daily outpatient and inpatient visits for total respiratory diseases, influenza and pneumonia, and URTI, primarily during comfortable AT levels, while it was exclusively related with daily inpatient visits for LRTI and COPD. Moderate heat (32.1 °C, the 75.0th centile) was observed with a significant effect on both daily outpatient and inpatient visits for total respiratory diseases at a relative risk of 1.561 (1.161, 2.098) and 1.276 (1.027, 1.585), respectively (both P < 0.05), while the results of inpatients became insignificant with the adjustment for CO and O3. The attributable fractions in outpatients and inpatients were as follows: total respiratory diseases (24.43% and 18.69%), influenza and pneumonia (31.54% and 17.33%), URTI (23.03% and 32.91%), LRTI (37.49% and 30.00%), asthma (9.83% and 3.39%), and COPD (30.67% and 10.65%). Stratified analyses showed that children ≤5 years old were more susceptible to moderate heat than older participants. CONCLUSIONS: In conclusion, our results indicated moderate heat increase the risk of daily outpatient and inpatient visits for respiratory diseases, especially among children under the age of 5.

[Randomized,double-blind,parallel controlled,multicenter clinical trial of effectiveness and safety of Shexiang Zhuifeng Zhitong Ointment in alleviating pain in knee osteoarthritis(syndrome of cold-dampness obstruction)].

The Shexiang Zhuifeng Zhitong Ointment with the effects of dispelling wind, removing dampness, dissipating cold, and relieving pain is used for treating arthralgia, muscular pain, and sprain pain caused by cold-dampness obstruction. To evaluate the efficacy and safety of Shexiang Zhuifeng Zhitong Ointment in relieving the pain due to knee osteoarthritis(syndrome of cold-dampness obstruction), a randomized, double-blind, parallel controlled, multicenter clinical trial was conducted. The stratified randomization method was used to randomize the 240 subjects into a treatment group and a control group in a ratio of 1∶1. In each group, 60 patients received external application for 12 h and the other 60 patients received external application for 6 h. The treatment group received external application of Shexiang Zhuifeng Zhitong Ointment, while the control group received external application of Shexiang Zhuifeng Ointment. The treatment lasted for 21 days in both groups. Follow-up was conducted on days 7, 14, and 21 of treatment. The results based on the full analysis set were as follows.(1)In visual analog scale(VAS) score, the mean difference in the VAS score between baseline and 12 h post-treatment was 3.02 in the treatment group and 2.31 in the control group, with a significant difference(P<0.05). The mean difference in the VAS score between baseline and 6 h post-treatment was 3.19 in the treatment group and 2.48 in the control group, with a significant difference(P<0.05).(2)Response rate in terms of VAS score, after treatment for 12 h, the response rate was 93.22% in the treatment group and 73.33% in the control group, with a significant difference(P<0.05). After treatment for 6 h, theresponse rate in the treatment group was 88.33%, which was higher than that(63.33%) in the control group(P<0.05).The results showed that Shexiang Zhuifeng Zhitong Ointment applied for 12 and 6 h effectively relieved the knee joint pain of patients with knee osteoarthritis due to cold-dampness obstruction, as demonstrated by the reduced VAS score, Western Ontario and McMaster Universities Arthritis Index(WOMAC), stiffness, and joint function score. Moreover, Shexiang Zhuifeng Zhitong Ointment outperformed the positive control Shexiang Zhuifeng Ointment in terms of reducing the VAS score, demonstrating a definitetherapeutic effect on the pain due to knee osteoarthritis(syndrome of cold-dampness obstruction).In addition, Shexiang Zhuifeng Zhitong Ointment did not cause other adverse reactions except for mild allergic reactions, which were common in the external application of traditional Chinese medicine plasters on the skin, inseveral patients.Neither other adverse reactions nor abnormalities of liver and kidney functions and electrocardiogram were observed. This ointment had high safety and could be popularized in clinical application.

Construct of qualitative diagnostic biomarkers specific for glioma by pairing serum microRNAs.

BACKGROUND: Serum microRNAs (miRNAs) are promising non-invasive biomarkers for diagnosing glioma. However, most reported predictive models are constructed without a large enough sample size, and quantitative expression levels of their constituent serum miRNAs are susceptible to batch effects, decreasing their clinical applicability. METHODS: We propose a general method for detecting qualitative serum predictive biomarkers using a large cohort of miRNA-profiled serum samples (n = 15,460) based on the within-sample relative expression orderings of miRNAs. RESULTS: Two panels of miRNA pairs (miRPairs) were developed. The first was composed of five serum miRPairs (5-miRPairs), reaching 100% diagnostic accuracy in three validation sets for distinguishing glioma and non-cancer controls (n = 436: glioma = 236, non-cancers = 200). An additional validation set without glioma samples (non-cancers = 2611) showed a predictive accuracy of 95.9%. The second panel included 32 serum miRPairs (32-miRPairs), reaching 100% diagnostic performance in training set on specifically discriminating glioma from other cancer types (sensitivity = 100%, specificity = 100%, accuracy = 100%), which was reproducible in five validation datasets (n = 3387: glioma = 236, non-glioma cancers = 3151, sensitivity> 97.9%, specificity> 99.5%, accuracy> 95.7%). In other brain diseases, the 5-miRPairs classified all non-neoplastic samples as non-cancer, including stroke (n = 165), Alzheimer's disease (n = 973), and healthy samples (n = 1820), and all neoplastic samples as cancer, including meningioma (n = 16), and primary central nervous system lymphoma samples (n = 39). The 32-miRPairs predicted 82.2 and 92.3% of the two kinds of neoplastic samples as positive, respectively. Based on the Human miRNA tissue atlas database, the glioma-specific 32-miRPairs were significantly enriched in the spinal cord (p = 0.013) and brain (p = 0.015). CONCLUSIONS: The identified 5-miRPairs and 32-miRPairs provide potential population screening and cancer-specific biomarkers for glioma clinical practice.

Chaetonigrisins A-L, a group of 3-Indole-1,2-Propanediol derived alkaloids from Chaetomium nigricolor YT-2.

Thirteen new alkaloids (1-13) as well as ten known compounds were isolated from the solid-state fermented rice medium of the fungus Chaetomium nigricolor YT-2. Their structures were elucidated on the basis of spectroscopic data, quantum calculations, and single crystal X-ray crystallographic analysis. Chaetonigrisin A (1) represents an unprecedented carbon skeleton featuring a polycyclic 1H-pyrano[3,2:3,4-]​furo[2,​3-​b]​indole. Chaetonigrisin B (2) displays a unique carbon skeleton with a 1,3­dioxolane bridged-ring. Chaetonigrisin C (3) is a spirocyclic indole alkaloid. Chaetonigrisins D-H (4-8) are a group of asymmetric dimers, formed with two 3-indol-3yl-1,2-propanediol (4-6) or with a 3-indol-3yl-1,2-propanediol and a 3-indol-2yl-1,2-propanediol (7-8) by a pyran ring. Chaetonigrisins I-L (9-12) each contains a 3-indol-3yl-1,2-propanediol or 3-indol-2yl-1,2-propanediol substructure. Chaetonigrisin M (13) is a new quinoline alkaloid. The neuroprotective activity assay showed that at the concentration of 40 µM, compounds (4-7, 11, and 12) improved the cell viability of PC12 cells were 49.26 %, 74.69 %, 74.76 %, 86.63 %, 66.89 %, and 69.92 %, respectively induced by 6-OHDA, compound 7 showed significant neuroprotective activity via upregulation of SOD1 mRNA and Bcl-2 mRNA.

Molecular and Morphological Identification of Monilia yunnanensis Causing Brown Rot on Chinese Quince and Peach in Yunnan, China.

More than 30% of fruits of Chinese Quince (Chaenomeles speciosa) and peach (Prunus persica) showed circular, water-soaked and brown spots in July 2022 in Kunming, Yunnan, China. The center of these spots was covered by a large number of earthy brown and oblate sporogeneous mycelium containing conidiophore and conidia, which were one-celled, limoniform, hyaline (13.73 to 22.77 x 8.17 to 12.84 µm, n=50). By September 2022, almost 100% of fruits showed symptoms. Later, most of them fell or a few stiff, black and mummified fruits were left on the trees. Fungal isolates were isolated by single-spore technique on Potato Dextrose agar (PDA) from the diseased fruits, and incubated at room temperature (20-28 °C) in darkness for 14 days. The colony was gray, smooth at margins, 7.6-8.0 cm in diameter. To fullfill Koch's postulates, mycelial plugs of one representative isolate YHD611 from Chinese Quince and another YHD610 from peach were used to inoculate three wounded and three non-wounded surface-disinfected fruits of both hosts at room temperature (19-27 °C), respectively. Three wounded and three non-wounded fruits inoculated with sterile PDA plugs served as the control. The wounded peaches appeared water-soaked and had brown lesions after three days of inoculation, then completely decayed after nine days, while non-wounded fruits showed symptoms after five days. The wounded fruits of Chinese Quince developed similar symptoms after eight days of inoculation, and completely decayed after 13 days, while non-wounded fruits showed obvious symptoms after 15 days. In a subsequent study, isolate YHD611 was inoculated to peach while isolate YHD610 was inoculated to Chinese Quince to understand host specificity of the isolates. The results showed that when peaches were infected with YHD611, symptoms were observed on wounded fruits after three days while on non-wounded fruits after five days. When Chinese Quince was infected with YHD610, symptoms were observed on wounded fruits after 14 days while on non-wounded fruits after 21 days. Fungal isolates from symptomatic fruits were identical to the original isolates. There were no symptoms on the control fruits of both hosts. Molecular identification was confirmed based on the sequences of internal transcribed spacer (ITS, primers ITS1 and ITS4) and ß-tubulin (TUB2, primers Bt2a and Bt2b) genes (Niu et al. 2016). BLASTn analysis of the ITS (OQ15519and OQ155196) and TUB2 (OQ185202 and OQ185201) of YHD611 and YHD610 revealed a 100% sequence identity, respectively, to Monilia yunnanensis AH7-2 (KT735924.1 for ITS, KT736008.1 for TUB2). In the phylogenetic analyses based on ITS and TUB2 sequence data, the isolates YHD611 and YHD610 belonged to the M. yunnanensis clade. Based on morphological and molecular identification, both isolates were identified as M. yunnanensis, which was reported as the pathogen causing brown rot of plum, peach, apple and pear in Yunnan, China (Hu et al. 2011; Yin et al. 2015). To our knowledge, this is the first report of M. yunnanensis causing brown rot on the fruits of Chinese Quince in Yunnan, China. This study also reports that M. yunnanensis from Chinese Quince can infect peach, and the pathogen from peach can infect Chinese Quince. These findings suggest that M. yunnanensis can transfer from one host to another and causing serious economic losses in multiple fruit crops in Yunnan, China. References: Hu, M. J., et al. 2011. PLoS One. 6:e24990. Niu, C. W., et al. 2016. Mycosystema, 35(10):1. Yin, L. F., et al. 2015. Plant Dis. 99:1775.

Researching pointing error effect on laser linewidth tolerance in space coherent optical communication systems.

In order to evaluate the pointing error effect on laser linewidth tolerance in a space coherent optical communication system, we derive a closed-form bit error rate (BER) model for binary phase-shift-keying (BPSK) modulation and heterodyne detection, under atmospheric turbulence, pointing error and laser phase noise. Based on the BER model, the linewidth tolerance is given, and numerical simulation is conducted. We find that laser linewidth tolerance decreases greatly with the increase of pointing error. Considering that pointing error consists of jitter and boresight, the effect of jitter and boresight are discussed separately and jointly in detail. Our results show that laser linewidth tolerance is more sensitive to the jitter variation than the boresight variation. In addition, with the increasing of the pointing error, the linewidth tolerance decreases faster under the large pointing error as compared to the case under the small pointing error. This paper is a good reference for designing space coherent optical communication systems.

A 1D Mixed-Valence Cuprofullerene Pyrazolate Polymer as a Semiconductor Material.

Polymeric {Cu6[(µ3-η2:η2:η2)2-C60](FPz)6Cl·3C6H5Cl}∞ [FPz = 4-(trifluoromethyl)pyrazolate], synthesized solvothermally with chlorobenzene as the solvent, is a doubly-connecting trans bis-adduct hexanuclear cuprofullerene that has copper in mixed valence. The compound is an example of a metallofullerene having semiconductivity character.

Association between gait features assessed by artificial intelligent system and cognitive function decline in patients with silent cerebrovascular disease: study protocol of a multicenter prospective cohort study (ACCURATE-2).

BACKGROUND: Gait disturbances may appear prior to cognitive dysfunction in the early stage of silent cerebrovascular disease (SCD). Subtle changes in gait characteristics may provide an early warning of later cognitive decline. Our team has proposed a vision-based artificial intelligent gait analyzer for the rapid detection of spatiotemporal parameters and walking pattern based on videos of the Timed Up and Go (TUG) test. The primary objective of this study is to investigate the relationship between gait features assessed by our artificial intelligent gait analyzer and cognitive function changes in patients with SCD. METHODS: This will be a multicenter prospective cohort study involving a total of 14 hospitals from Shanghai and Guizhou. One thousand and six hundred patients with SCD aged 60-85 years will be consecutively recruited. Eligible patients will undergo the intelligent gait assessment and neuropsychological evaluation at baseline and at 1-year follow-up. The intelligent gait analyzer will divide participant into normal gait group and abnormal gait group according to their walking performance in the TUG videos at baseline. All participants will be naturally observed during 1-year follow-up period. Primary outcome are the changes in Mini-Mental State Examination (MMSE) score. Secondary outcomes include the changes in intelligent gait spatiotemporal parameters (step length, gait speed, step frequency, step width, standing up time, and turning back time), the changes in scores on other neuropsychological tests (Montreal Cognitive Assessment, the Stroop Color Word Test, and Digit Span Test), falls events, and cerebrovascular events. We hypothesize that both groups will show a decline in MMSE score, but the decrease of MMSE score in the abnormal gait group will be more significant. CONCLUSION: This study will be the first to explore the relationship between gait features assessed by an artificial intelligent gait analyzer and cognitive decline in patients with SCD. It will demonstrate whether subtle gait abnormalities detected by the artificial intelligent gait analyzer can act as a cognitive-related marker for patients with SCD. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov ( NCT04456348 ; 2 July 2020).

A rank-based algorithm of differential expression analysis for small cell line data with statistical control.

To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data.

Silencing BLNK protects against interleukin-1ß-induced chondrocyte injury through the NF-κB signaling pathway.

BACKGROUND: Osteoarthritis (OA) is the most common joint disease in the elderly and is characterized by the progressive degeneration of articular cartilage. It is necessary to study the molecular pathology of OA. This study aimed to explore the role and mechanism of BLNK in regulating interleukin-1ß (IL-1ß)-induced chondrocyte injury and OA progression. METHODS: GSE1919 (5 normal samples and 5 OA samples) was downloaded from the Gene Expression Omnibus (GEO) database. The limma package in R software was used to identify differentially expressed genes (DEGs) between control and OA-affected cartilage. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the differentially expressed genes were also performed. Apoptosis was assessed by flow cytometry. An OA rat model was established, and the relative expression of BLNK was assessed by real time quantitative PCR (qRT-PCR) and immunohistochemical staining. The expression of collagen II, MMP9, p65 and p-p65 was measured by Western blot analysis. Moreover, inflammatory factors (TNF-α and IL-18) were assessed by ELISA. The NF-κB inhibitor JSH-23 was used to assess the impact of BLNK on the NF-κB signaling pathway. RESULTS: In total, 1318 DEGs were identified between normal and OA-affected cartilage according to the criteria (P-value <0.05 and |logFC > 1|). These DEGs were mainly enriched in the NF-κB pathway. BLNK was highly expressed in OA cartilage tissue and injured chondrocytes. Silencing BLNK significantly downregulated the IL-1ß-induced apoptosis of chondrocytes. Silencing BLNK partially increased collagen II expression and downregulated MMP13 expression. Moreover, silencing BLNK partially decreased TNF-α and IL-18 expression. BLNK silencing inhibited the activation of NF-κB in OA. Silencing BLNK delayed OA progression through the NF-κB signaling pathway. CONCLUSION: Silencing BLNK delayed OA progression and IL-1ß-induced chondrocyte injury by regulating the NF-κB pathway.

Tripartite Motif-Containing 44 is Involved in the Tumorigenesis of Laryngeal Squamous Cell Carcinoma, and its Expression is Downregulated by Nuciferine.

Tripartite motif-containing 44 (TRIM44) was reported to be involved in the tumorigenesis of several tumors, but its function in laryngeal squamous cell carcinoma has not been investigated yet. In the present study, we aimed to elucidate the function of TRIM44 in laryngeal squamous cell carcinoma, and identify the compounds which could inhibit TRIM44 expression. Our results showed that TRIM44 was upregulated in tumor tissues and cell lines of laryngeal squamous cell carcinoma. Knockdown of TRIM44 significantly inhibited cell growth of laryngeal squamous cell carcinoma by suppressing TLR4, phosphorylated AKT and phosphorylated NF-κB p65 expression in vitro. Moreover, TRIM44 knockdown inhibited tumor growth in nude mice, which further suggested that TRIM44 exerted oncogenic activity in laryngeal squamous cell carcinoma. Interestingly, it was found that nuciferine significantly inhibited the mRNA levels of TRIM44 after screening a small natural compound library. Our further studies showed nuciferine markedly downregulated the protein levels of TRIM44 and its substrate TLR4 in a concentration-dependent manner in laryngeal squamous cell carcinoma cells. Moreover, the activation of downstream kinases of TLR4 such as AKT signaling pathway was also inhibited by nuciferine. Additionally, nuciferine markedly inhibited cell survival of laryngeal squamous cell carcinoma in a concentration-dependent manner. In contrast, TRIM44 overexpression significantly reduced the cytotoxicity of nuciferine in laryngeal squamous cell carcinoma cells. In conclusion, this study indicated that inhibiting TRIM44 would be a useful strategy for the treatment of laryngeal squamous cell carcinoma, and nuciferine could be a potential chemical applicated in the therapy of laryngeal squamous cell carcinoma.

Design, synthesis, herbicidal activity and CoMFA of aryl-formyl piperidinone HPPD inhibitors.

Isoxazole, nicotinic acid and benzoic acid are important components in many natural products and useful synthons to build macrostructures having valuable biological activities. In continuation of our effort to discover 4-hydroxyphenylpyruvate dioxygenase (HPPD, EC 1.13.11.27) inhibitors and search for active fragments from natural products, a series of substituted aryl-formyl piperidinone derivatives with natural product fragments was rationally designed, synthesized and tested for their herbicidal activity. Compound I-9 was considered the most effective candidate with an IC50 value of 0.260 µM. The molecular docking results showed that the triketone group of compound I-9 forms a bidentate complex with a metal ion, and the benzene ring interacted with Phe424 and Phe381 via π-π stacking, which was similar to the mechanisms of mesotrione. The present work indicates that compound I-9 may serve as a potential lead compound for further development of green HPPD inhibitors.

[Mechanism of Huangqi Guizhi Wuwu Decoction in treatment of rheumatoid arthritis based on UPLC-LTQ-Orbitrap-MS, network pharmacology, and cell experiment].

In this study, ultra-high performance liquid chromatography-linear ion trap/electrostatic field orbit trap combined-type mass spectrometry(UPLC-LTQ-Orbitrap-MS) was used to analyze the main active components of Huangqi Guizhi Wuwu Decoction(HQGZ). A total of 50 active components were identified from HQGZ and 108 potential targets of the components related to the treatment of rheumatoid arthritis were retrieved based on network pharmacology, including 87 key targets, followed by Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment of the targets. The result indicated that HQGZ may exert therapeutic effects mainly through the sphingolipid signaling pathway, tumor necrosis factor(TNF) signaling pathway, as well as the positive regulation of ribonucleic acid(RNA) polymerase Ⅱ promoter transcription, inflammatory response and other biological processes. At the same time, cell experiment was performed to verify the key proteins in the TNF signaling pathway. The results demonstrated that HQGZ significantly reduced the expression of caspase-3(CASP3), TNF, relaxed(RELA) protein, and IkappaB kinase beta(IKBKB) in fibroblast-like synoviocytes induced by TNF-α. The results of UPLC-LTQ-Orbitrap-MS, network pharmacology and cell experiment showed that the active components in HQGZ may inhibit inflammatory response and regulate immune function and cell apoptosis by modulating key proteins in TNF signaling pathway to treat rheumatoid arthritis.

Individualized analysis of differentially expressed miRNAs with application to the identification of miRNAs deregulated commonly in lung cancer tissues.

Identifying differentially expressed microRNAs (DE miRNAs) between cancer samples and normal controls is a common way to investigate carcinogenesis mechanisms. However, for a DE miRNA detected at the population-level, we do not know whether it is DE in a particular cancer sample. Here, based on the finding that the within-sample relative expression orderings of miRNA pairs are highly stable in a particular type of normal tissues but widely disrupted in the corresponding cancer tissues, we proposed a method, called RankMiRNA, to identify DE miRNAs in each cancer tissue compared with its own normal state. Evaluated with pair-matched miRNA expression profiles of cancer tissues and adjacent normal tissues for lung and liver cancers, RankMiRNA exhibited excellent performance. Finally, we exemplified an application of the individual-level differential expression analysis by finding miRNAs DE in at least 90% lung cancer tissues, defined as common DE miRNAs of lung cancer. After identifying DE miRNAs for each of 991 lung cancer samples from The Cancer Genome Atlas with RankMiRNA, we found that hsa-mir-210 was upregulated, while hsa-mir-490 and hsa-mir-486 were downregulated in > 90% of the 991 lung cancer samples. These common DE miRNAs were validated in independent pair-matched samples of cancer tissues and adjacent normal tissues measured with different platforms. In conclusion, RankMiRNA provides us a novel tool to find common and subtype-specific miRNAs for a type of cancer, allowing us to study cancer mechanisms in a novel way.

Effect of external mismatch and internal mismatch caused by pointing error on performances of space chaos laser communication system.

In order to evaluate the effect of pointing error on space chaos laser communication system, we conduct bit error rate (BER) analysis with external mismatch and internal mismatch caused by pointing error. Based on BER formulae, numerical simulations are conducted to investigate the effect of external and internal mismatches on performance of the system under different boresight and jitter. Our results indicate that jitter will affect BER more than boresight and internal mismatch will affect the performance of system more than external mismatch. These results are significant for optimizing space chaos laser communication system design.

Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit.

The current study suggests that the identification of predictive signatures of fluorouracil (5-FU) response for stage II and III colorectal cancer (CRC) could be confounded by chemotherapy-irrelevant low relapse risk. Using the samples of patients with stage II and III CRC who were treated with curative surgery only, we identified a signature with which to predict chemotherapy-irrelevant relapse risk for patients after curative surgery. By applying this signature to the samples of patients with stage II and III CRC who were treated with 5-FU-based adjuvant chemotherapy (ACT) after surgery, we predicted the relapse risk if treated with surgery only. From high-risk samples, we further identified another signature with which to predict therapeutic benefit from 5-FU-based ACT. On the basis of the relative expression orderings of gene pairs, a postsurgery relapse risk signature that consisted of 44 gene pairs was developed and verified in 3 independent data sets. A 5-FU therapeutic benefit signature that consisted of 4 gene pairs was then developed to predict the response of 5-FU-based ACT for those patients with high relapse risk after curative surgery. The signature was verified in 4 independent datasets. For patients with stage II and III CRC, the coupled signatures can first identify patients with high relapse risk after curative surgery, then predict therapeutic benefit from 5-FU-based ACT.-Song, K., Guo, Y., Wang, X., Cai, H., Zheng, W., Li, N., Song, X., Ao, L., Guo, Z., Zhao, W. Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit.

Assessment of Acute Pulmonary Embolism by Computer-Aided Technique: A Reliability Study.

BACKGROUND Acute pulmonary embolism is one of the most common cardiovascular diseases. Computer-aided technique is widely used in chest imaging, especially for assessing pulmonary embolism. The reliability and quantitative analyses of computer-aided technique are necessary. This study aimed to evaluate the reliability of geometry-based computer-aided detection and quantification for emboli morphology and severity of acute pulmonary embolism. MATERIAL AND METHODS Thirty patients suspected of acute pulmonary embolism were analyzed by both manual and computer-aided interpretation of vascular obstruction index and computer-aided measurements of emboli quantitative parameters. The reliability of Qanadli and Mastora scores was analyzed using computer-aided and manual interpretation. RESULTS The time costs of manual and computer-aided interpretation were statistically different (374.90±150.16 versus 121.07±51.76, P<0.001). The difference between the computer-aided and manual interpretation of Qanadli score was 1.83±2.19, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (intraclass correlation coefficient, ICC=0.998). The difference between the computer-aided and manual interpretation of Mastora score was 1.46±1.62, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (ICC=0.997). The emboli quantitative parameters were moderately correlated with the Qanadli and Mastora scores (all P<0.001). CONCLUSIONS Computer-aided technique could reduce the time costs, improve the and reliability of vascular obstruction index and provided additional quantitative parameters for disease assessment.