Energy Absorption Characteristics of Composite Material with Fiber-Foam Metal Sandwich Structure Subjected to Gas Explosion.

Based on the previous research on the energy absorption of foam metal materials with different structures, a composite blast-resistant energy-absorbing material with a flexible core layer was designed. The material is composed of three different fiber materials (carbon fiber, aramid fiber, and glass fiber) as the core layer and foamed iron-nickel metal as the front and rear panels. The energy absorption characteristics were tested using a self-built gas explosion tube network experimental platform, and the energy absorption effects of different combinations of blast-resistant materials were analyzed. The purpose of this paper is to evaluate the performance of blast-resistant materials designed with flexible fiber core layers. The experimental results show that the composite structure blast-resistant material with a flexible core layer has higher energy absorption performance. The work performed in this paper shows that the use of flexible core layer materials has great research potential and engineering research value for improving energy absorption performance, reducing the mass of blast-resistant materials, and reducing production costs. It also provides thoughts for the research of biomimetic energy-absorbing materials.

Multi-modal molecular determinants of clinically relevant osteoporosis subtypes.

Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes. Accordingly, through DLSF, we identified two subtypes of the osteoporosis population in Chinese individuals with corresponding molecular phenotypes, i.e., clinical intervention relevant subtypes (CISs), in which bone mineral density benefits response to calcium supplements in 2-year follow-up samples. Many snpGenes associated with these molecular phenotypes reveal diverse candidate biological mechanisms underlying osteoporosis, with xQTL preferences of osteoporosis and its subtypes indicating an omnigenic effect on different biological domains. Finally, these two subtypes were found to have different relevance to prior fracture and different fracture risk according to 4-year follow-up data. Thus, in clinical application, M3S could help us further develop improved diagnostic and treatment strategies for osteoporosis and identify a new composite index for fracture prediction, which were remarkably validated in an independent cohort (166 participants).

Lifestyle factors and subacromial impingement syndrome of the shoulder: potential associations in finnish participants.

BACKGROUND: Emerging evidence has indicated the associations between subacromial impingement syndrome (SIS) of shoulder and lifestyle factors. However, whether unhealthy lifestyle factors causally increase SIS risk is not determined. This study aims to evaluate whether lifestyle factors are the risk factors of SIS. METHODS: A two-sample Mendelian randomization (MR) study was designed to evaluate the effect of 11 lifestyle factors on SIS risk. Causality was determined using the inverse-variance weighted method to calculate the odds ratio (OR) and establish a 95% confidence interval (CI). Weighted median method, MR-Egger method and MR-PRESSO method were conducted as sensitivity analysis. RESULTS: Four lifestyle factors were identified causally associated with an increased risk of SIS using the IVW method: insomnia (OR: 1.66 95% CI 1.38, 2.00; P = 8.86 × 10- 8), short sleep duration (OR: 1.53 95% CI 1.14, 2.05: P = 0.0043), mobile phone usage (OR: 4.65, 95% CI 1.59, 13.64; P = 0.0051), and heavy manual or physical work (OR: 4.24, 95% CI 2.17, 8.26; P = 2.20 × 10- 5). Another causal but weak association was found between smoking initiation on SIS (OR: 1.17, 95% CI 1.01, 1.35; P = 3.50 × 10- 2). Alcohol, coffee consumption, physical activity, sedentary behavior, sleep duration and computer usage were not found to be causally associated with an increased risk of SIS. Sensitivity analyses indicated that the MR estimates were robust and no heterogeneity and pleiotropy were identified in these MR analyses. CONCLUSION: Sleep habits and shoulder usage were identified as causal factors for SIS. This evidence supports the development of strategies aimed at improving sleep behaviors and optimizing shoulder usage patterns as effective measures to prevent SIS.

Predictive Analysis of Linoleic Acid in Red Meat Employing Advanced Ensemble Models of Bayesian and CNN-Bi-LSTM Decision Layer Fusion Based Hyperspectral Imaging.

Rapid non-destructive testing technologies are effectively used to analyze and evaluate the linoleic acid content while processing fresh meat products. In current study, hyperspectral imaging (HSI) technology was combined with deep learning optimization algorithm to model and analyze the linoleic acid content in 252 mixed red meat samples. A comparative study was conducted by experimenting mixed sample data preprocessing methods and feature wavelength extraction methods depending on the distribution of linoleic acid content. Initially, convolutional neural network Bi-directional long short-term memory (CNN-Bi-LSTM) model was constructed to reduce the loss of the fully connected layer extracted feature information and optimize the prediction effect. In addition, the prediction process of overfitting phenomenon in the CNN-Bi-LSTM model was also targeted. The Bayesian-CNN-Bi-LSTM (Bayes-CNN-Bi-LSTM) model was proposed to improve the linoleic acid prediction in red meat through iterative optimization of Gaussian process acceleration function. Results showed that best preprocessing effect was achieved by using the detrending algorithm, while 11 feature wavelengths extracted by variable combination population analysis (VCPA) method effectively contained characteristic group information of linoleic acid. The Bi-directional LSTM (Bi-LSTM) model combined with the feature extraction data set of VCPA method predicted 0.860 Rp2 value of linoleic acid content in red meat. The CNN-Bi-LSTM model achieved an Rp2 of 0.889, and the optimized Bayes-CNN-Bi-LSTM model was constructed to achieve the best prediction with an Rp2 of 0.909. This study provided a reference for the rapid synchronous detection of mixed sample indicators, and a theoretical basis for the development of hyperspectral on-line detection equipment.

Ailanthone synergizes with PARP1 inhibitor in tumour growth inhibition through crosstalk of DNA repair pathways in gastric cancer.

In our previous research, we proved that ailanthone (AIL) inhibits the growth of gastric cancer (GC) cells and causes apoptosis by inhibiting P23. However, we still find some GC organoids are insensitive to AIL. We have done some sequencing analysis and found that the insensitive strains are highly expressed in PARP1. In this study, we investigated whether AIL can enhance the anti-tumour effect of PARPi in GC. CCK8 and spheroid colony formation assay were used to measure anti-tumour effects. SynergyFinder software was used to calculate the synergy score of the drug combination and flow cytometry was used to detect apoptosis. Western blot, IHC, IF tests were used to measure protein expression. Finally, nude mouse xenograft models were used to verify the in vitro mechanisms. High expression of PARP1 was found to be the cause of drug insensitivity. When AIL is paired with a PARP1 inhibitor, olaparib (OLP), drug sensitivity improves. We discovered that this combination functions by blocking off HSP90-BRCA1 interaction and inhibiting the activity of PARP1, thus in turn inhibiting the homologous recombination deficiency and base excision repair pathway to finally achieve synthetic lethality through increased sensitivity. Moreover, P23 can regulate BRCA1 in GC in vitro. This study proves that the inhibitory effect of AIL on BRCA1 allowed even cancer cells with normal BRCA1 function to be sensitive to PARP inhibitors when it is simultaneously administered with OLP. The results greatly expanded the scope of the application of PARPi.

Dynamic changes in the water and volatile compounds of chicken breast during the frying process.

The influence of frying times (0, 2, 4, 6, 8, and 10 min) on the continuous changes in the water distribution and the concentrations of key volatile compounds in chicken breast during the frying process were studied. The fried chicken samples could be distinguished by PCA of E-nose and PLS-DA of GC-MS. A total of 40 volatile compounds were identified by GC-MS, and 28 compounds were verified to be the key compounds after further screening by OAVs. The T22 was increased first and then decreased, while the M22 and M23 in fried chicken were considerably decreased and increased with increasing frying time, respectively. The content of the water and the total peak area of LF-NMR in fried chicken samples during the frying process significantly decreased, and the water was transferred from high to low degrees of freedom. In addition, water content, T21, T22, M22 and L* value were positively correlated with most alcohols and aldehydes, and were negatively correlated with pyrazines, while a*, b*, M23 and all amino acids were positively correlated with pyrazines and were negatively correlated with most alcohols and aldehydes. The results may guide the production processes of fried chicken and help produce high-quality chicken products.

A new comprehensive quantitative index for the assessment of essential amino acid quality in beef using Vis-NIR hyperspectral imaging combined with LSTM.

The quality of beef is usually predicted by measuring a single index rather than a comprehensive index. To precisely determine the essential amino acid (EAA) contents in 360 beef samples, the feasibility of optimized spectral detection techniques based on the comprehensive EAA index (CEI) and comprehensive weight index (CWI) constructed by factor analysis was explored. Two-dimensional correlation spectroscopy (2D-COS) was used to analyse the mechanisms of spectral peak shifts in complex disturbance systems with CEI and CWI contents, and 15 sensitive feature variables were extracted to establish a quantitative analysis model of a long short-term memory network (LSTM). The results indicated that 2D-COS had good predictive performance in both CEI-LSTM (R2P of 0.9095 and RPD of 2.76) and CWI-LSTM (R2P of 0.8449 and RPD of 2.45), which reduced data information by 88%. This indicates that utilizing 2D-COS can eliminate collinearity and redundant information among variables while achieving data dimensionality reduction and simplification of calibration models. Furthermore, a spatial distribution map of the comprehensive EAA content was generated by combining the optimal prediction model. This study demonstrated that the comprehensive index method furnishes a new approach to rapidly evaluate EAA content.

Genetically Proxied Sarcopenia-Related Muscle Traits and Depression: Evidence from the FinnGen Cohort.

BACKGROUND: Sarcopenia and depression are common and often coexist in the elderly. This study aims to determine the impact of sarcopenia-related muscle traits on depression. METHODS: A two-sample Mendelian randomization (MR) study was performed on the summary-level data from the FinnGen cohort to estimate the causal association of appendicular lean mass (ALM), walking pace, or low hand grip strength with depression. Additionally, multivariable MR (MVMR) was performed to assess the dependence of each muscle trait in the causality and adjust the effect of body mass index (BMI). Supplementary backward MR analyses were performed to estimate the effect of depression on sarcopenia-related muscle traits. RESULTS: Univariable MR analyses demonstrated that there were causal associations of ALM (odds ratio [OR]: 0.94; 95% confidence interval [CI]: 0.88-0.99), walking pace (OR: 0.53; 95% CI: 0.32-0.88), and low hand grip strength (OR: 1.20; 95% CI: 1.05-1.38) with depression. MVMR analyses showed that ALM was the only trait that had a significant causal relationship with depression (OR: 0.91; 95% CI: 0.85-0.98) after accounting for the other two muscle traits. Moreover, the independent association of ALM with depression remained (OR: 0.92; 95% CI: 0.85-0.99) after being adjusted by BMI. The backward MR analyses showed no causal associations of depression with any sarcopenia-related muscle traits. CONCLUSION: Low muscle mass independently increases the risk of depression. This study determined the muscle-related risk factors of depression, which may help establish the causality between sarcopenia and depression and provide evidence-based recommendations for improving mental health in the elderly.

Distributed genotyping and clustering of Neisseria strains reveal continual emergence of epidemic meningococcus over a century.

Core genome multilocus sequence typing (cgMLST) is commonly used to classify bacterial strains into different types, for taxonomical and epidemiological applications. However, cgMLST schemes require central databases for the nomenclature of new alleles and sequence types, which must be synchronized worldwide and involve increasingly intensive calculation and storage demands. Here, we describe a distributed cgMLST (dcgMLST) scheme that does not require a central database of allelic sequences and apply it to study evolutionary patterns of epidemic and endemic strains of the genus Neisseria. We classify 69,994 worldwide Neisseria strains into multi-level clusters that assign species, lineages, and local disease outbreaks. We divide Neisseria meningitidis into 168 endemic lineages and three epidemic lineages responsible for at least 9 epidemics in the past century. According to our analyses, the epidemic and endemic lineages experienced very different population dynamics in the past 100 years. Epidemic lineages repetitively emerged from endemic lineages, disseminated worldwide, and apparently disappeared rapidly afterward. We propose a stepwise model for the evolutionary trajectory of epidemic lineages in Neisseria, and expect that the development of similar dcgMLST schemes will facilitate epidemiological studies of other bacterial pathogens.

Injectable photocrosslinking spherical hydrogel-encapsulated targeting peptide-modified engineered exosomes for osteoarthritis therapy.

Osteoarthritis (OA) is a common degenerative joint disease urgently needing effective treatments. Bone marrow mesenchymal stromal cell-derived exosomes (Exo) are considered good drug carriers whereas they have limitations such as fast clearance and low retention. This study aimed to overcome the limitations of Exo in drug delivery using multiple strategies. Novel photocrosslinking spherical gelatin methacryloyl hydrogel (GelMA)-encapsulated cartilage affinity WYRGRL (W) peptide-modified engineered Exo were developed for OA treatment and the performance of the engineered Exo (W-Exo@GelMA) loaded with a small inhibitor LRRK2-IN-1 (W-Exo-L@GelMA) was investigated in vitro and in vivo. The W-Exo-L@GelMA showed an effective targeting effect on chondrocytes and a pronounced action on suppressing catabolism and promoting anabolism in vitro. Moreover, W-Exo-L@GelMA remarkably inhibited OA-related inflammation and immune gene expression, rescuing the IL-1ß-induced transcriptomic responses. With enhanced retention in the joint, W-Exo-L@GelMA demonstrated superior anti-OA activity and cartilage repair ability in the OA murine model. The therapeutic effect was validated in the cultured human OA cartilage. In conclusion, photocrosslinking spherical hydrogel-encapsulated targeting peptide-modified engineered Exo exhibit notable potential in OA therapy. Engineering Exo by a series of strategies enhanced the targeting ability and retention and cartilage-targeting and Exo-mediated drug delivery may offer a novel strategy for OA treatment.Clinical trial registration: Not applciable.

The impact of acupuncture combined with acupoint catgut embedding on simple obesity: A systematic review and meta-analysis.

BACKGROUND: Obesity is a widespread chronic metabolic disease that significantly impairs quality of life. Studies have demonstrated the efficacy of both acupuncture and acupoint catgut embedding (ACE) in the management of obesity. However, the superiority of acupuncture combined with ACE over acupuncture alone remains a subject of controversy. This study aims to elucidate this controversy and provide robust clinical evidence. METHODS: A comprehensive search of relevant literature from the initiation to July 2022 was carried out in 8 databases (PubMed, EMBASE, Cochrane database, Web of Science, CBM Database, CNKI, Wan-fang Database, and VIP Database). We included randomized controlled trials (RCTs) that investigated the treatment of simple obesity using acupuncture paired with ACE, with acupuncture alone as the control group. The pooled outcomes included body mass index (BMI), body weight (BW), %BF, waist circumference (WC), hip circumferences (HC), waist-to-hip ratio (WHR), therapeutic effective rate (TER), and adverse events. Two independent reviewers performed screening (using EndNote X9) and quality assessment (using the Cochrane Risk of Bias tool) for the included studies. with the software RevMan 5.3 was used to perform pooling of effect sizes. The certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). RESULTS: A total of 20 trials involving 15 datasets (1616 participants) were included. The findings demonstrated significant improvements in outcome measures when acupuncture was combined with ACE, compared with acupuncture alone (BMI: MD = -1.49 kg/m2, 95% confidence interval [CI] = -1.93 to -1.04, P < .01; BW: MD = -2.38, 95% CI = -3.86 to -0.89, P < .01; %BF: MD = -2.19, 95% CI = -3.23 to -1.15, P < .01; WC: MD = -2.01, 95% CI = -3.66 to -0.35, P < .05; HC: MD = -0.83, 95% CI = -1.64 to -0.02, P < .05; WHR: MD = -0.02, 95% CI = -0.03 to -0.01, P < .01; TER: OR = 2.68, 95% CI = 1.93-3.74, P < .01). Adverse effects were reported in 4 studies. CONCLUSION SUBSECTIONS: The results of this meta-analysis indicate that acupuncture combined with ACE is superior to acupuncture alone in the treatment of obesity, which is supported by the subgroup analysis. The assessment of efficacy may have been influenced by variations in study quality, potentially amplifying the observed effects. RCTs with larger sample sizes and improved methodological quality are needed to enhance the validity of the findings.

PZR promotes tumorigenicity of lung cancer cells by regulating cell migration and invasion via modulating oxidative stress and cell adhesion.

PZR is a transmembrane glycoprotein encoded by the MPZL1 gene. It serves as a specific binding protein and substrate of tyrosine phosphatase SHP-2 whose mutations cause developmental diseases and cancers. Bioinformatic analyses of cancer gene databases revealed that PZR is overexpressed in lung cancer and correlated with unfavorable prognosis. To investigate the role of PZR in lung cancer, we employed the CRISPR technique to knockout its expression and recombinant lentiviruses to overexpress it in lung adenocarcinoma SPC-A1 cells. While knockout of PZR reduced colony formation, migration, and invasion, overexpression of PZR had the opposite effects. Furthermore, when implanted in immunodeficient mice, PZR-knockout SPC-A1 cells showed suppressed tumor-forming ability. Finally, the underlying molecular mechanism for these functions of PZR is its positive role in activating tyrosine kinases FAK and c-Src and in maintaining the intracellular level of reactive oxygen species (ROS). In conclusion, our data indicated that PZR plays an important role in lung cancer development, and it may serve as a therapeutic target for anti-cancer development and as a biomarker for cancer prognosis.

Combination of hyperspectral imaging and entropy weight method for the comprehensive assessment of antioxidant enzyme activity in Tan mutton.

The antioxidant enzymes play the crucial role in inhibiting mutton spoilage. In this study, visible near-infrared (Vis-NIR) hyperspectral imaging (HSI) combined with entropy weight method (EWM) was developed for the first time to evaluate the antioxidant properties of Tan mutton. The comprehensive index of antioxidant enzymes (AECI) consisting of peroxidase (49.34%), catalase (37.97%) and superoxidase (12.69%) was constructed by the EWM. Partial least squares regression, least squares support vector machine and artificial neural networks (ANN) were developed based on characteristic wavelengths extracted by successful projections algorithm, uninformative variable selection, iteratively retains informative variables (IRIV), regression coefficient and competitive adaptive reweighted sampling (CARS). The textural features (TF) were extracted by the gray level co-occurrence matrix and fused with the spectral data to establish models. Visualization of the changes in antioxidant enzyme activity was constructed from the optimal model. In addition, two-dimensional correlation spectra (2D-COS) with AECI as a perturbation variable was used to identify spectral features, revealing chemical bond changes order under the characteristic peaks at 612-799-473-708-559 nm. The results showed that the IRIV-CARS-TF-ANN model performed the best, with prediction set coefficient of determination (RP2) of 0.8813, which improved 2.12%, 1.11% and 2.77% over the RP2 of full band, IRIV and IRIV-CARS, respectively. It was suggested that fusion data of HSI may effectively predict the activity of antioxidant enzymes in Tan mutton.

A new sensor for the rapid electrochemical detection of ractopamine in meats with high sensitivity.

In this research, g-C3N4/Cu@CoO/NC, which contained graphitic phase carbon nitride (g-C3N4) with a binary nanostructure and Cu@CoO/NC with a bimetallic MOF precursor, was constructed by a low-temperature pyrolysis process. The g-C3N4/Cu@CoO/NC was characterised by several techniques, including X-ray diffraction, scanning electron microscope, transmission electron microscope and X-ray photoelectron spectroscopy. Further, it was used to prepare an electrochemical sensor for the detection of ractopamine (RAC) in meat samples. The sensor showed excellent electrochemical oxidation characteristics for RAC detection, with a wide linear range (0.005 µmol/L to 32.73 µmol/L) and low detection limit (1.53 nmol/L). Meanwhile, the reproducibility, stability and interference of the g-C3N4/Cu@CoO/NC/GCE sensor were found to be excellent. Besides, the g-C3N4/Cu@CoO/NC/GCE sensor was well-used for the detection of RAC in pork, pig liver and lamb samples with recovery rates ranging from 96.5 % to 102.2 %.

Effect of constraint-induced movement therapy on lower extremity motor dysfunction in post-stroke patients: A systematic review and meta-analysis.

Objective: Constraint-induced movement therapy (CIMT) is a common treatment for upper extremity motor dysfunction after a stroke. However, whether it can effectively improve lower extremity motor function in stroke patients remains controversial. This systematic review comprehensively studies the current evidence and evaluates the effectiveness of CIMT in the treatment of post-stroke lower extremity motor dysfunction. Methods: We comprehensively searched randomized controlled trials related to this study in eight electronic databases (PubMed, Embase, The Cochrane Library, Web of Science, CBM, CNKI, WAN FANG, and VIP). We evaluated CIMT effectiveness against post-stroke lower extremity motor dysfunction based on the mean difference and corresponding 95% confidence interval (95% CI). We assessed methodological quality based on the Cochrane Bias Risk Assessment Tool. After extracting the general information, mean, and standard deviation of the included studies, we conducted a meta-analysis using RevMan 5.3 and Stata 16.0. The primary indicator was the Fugl-Meyer Assessment scale on lower limbs (FMA-L). The secondary indicators were the Berg balance scale (BBS), 10-meter walk test (10MWT), gait speed (GS), 6-min walk test (6MWT), functional ambulation category scale (FAC), timed up and go test (TUGT), Brunnstrom stage of lower limb function, weight-bearing, modified Barthel index (MBI), functional independence measure (FIM), stroke-specific quality of life questionnaire (SSQOL), World Health Organization quality of life assessment (WHOQOL), and National Institute of Health stroke scale (NIHSS). Results: We initially identified 343 relevant studies. Among them, 34 (totaling 2,008 patients) met the inclusion criteria. We found that patients treated with CIMT had significantly better primary indicator (FMA-L) scores than those not treated with CIMT. The mean differences were 3.46 (95% CI 2.74-4.17, P < 0.01, I2 = 40%) between CIMT-treated and conventional physiotherapy-treated patients, 3.83 (95% CI 2.89-4.77, P < 0.01, I2 = 54%) between patients treated with CIMT plus conventional physiotherapy and patients treated only with conventional physiotherapy, and 3.50 (95% CI 1.08-5.92, P < 0.01) between patients treated with CIMT plus western medicine therapy and those treated only with western medicine therapy. The secondary indicators followed the same trend. The subgroup analysis showed that lower extremity CIMT with device seemed to yield a higher mean difference in FMA-L scores than lower extremity CIMT without device (4.52, 95% CI = 3.65-5.38, P < 0.01 and 3.37, 95% CI = 2.95-3.79, P < 0.01, respectively). Conclusion: CIMT effectively improves lower extremity motor dysfunction in post-stroke patients; however, the eligible studies were highly heterogeneous.Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=277466.

A Combination of Near-Infrared Hyperspectral Imaging with Two-Dimensional Correlation Analysis for Monitoring the Content of Alanine in Beef.

Alanine (Ala), as the most important free amino acid, plays a significant role in food taste characteristics and human health regulation. The feasibility of using near-infrared hyperspectral imaging (NIR-HSI) combined with two-dimensional correlation spectroscopy (2D-COS) analysis to predict beef Ala content quickly and nondestructively is first proposed in this study. With Ala content as the external disturbance condition, the sequence of chemical bond changes caused by synchronous and asynchronous correlation spectrum changes in 2D-COS was analyzed, and local sensitive variables closely related to Ala content were obtained. On this basis, the simplified linear, nonlinear, and artificial neural network models developed by the weighted coefficient based on the feature wavelength extraction method were compared. The results show that with the change in Ala content in beef, the double-frequency absorption of the C-H bond of CH2 in the chemical bond sequence occurred prior to the third vibration of the C=O bond and the first stretching of O-H in COOH. Furthermore, the wavelength within the 1136-1478 nm spectrum range was obtained as the local study area of Ala content. The linear partial least squares regression (PLSR) model based on effective wavelengths was selected by competitive adaptive reweighted sampling (CARS) from 2D-COS analysis, and provided excellent results (R2C of 0.8141, R2P of 0.8458, and RPDp of 2.54). Finally, the visual distribution of Ala content in beef was produced by the optimal simplified combination model. The results show that 2D-COS combined with NIR-HSI could be used as an effective method to monitor Ala content in beef.

Unbiased comparison and modularization identify time-related transcriptomic reprogramming in exercised rat cartilage: Integrated data mining and experimental validation.

Exercise is indispensable for maintaining cartilage integrity in healthy joints and remains a recommendation for knee osteoarthritis. Although the effects of exercise on cartilage have been implied, the detailed mechanisms, such as the effect of exercise time which is important for exercise prescription, remain elusive. In this study, bioinformatic analyses, including unbiased comparisons and modularization, were performed on the transcriptomic data of rat cartilage to identify the time-related genes and signaling pathways. We found that exercise had a notable effect on cartilage transcriptome. Exercise prominently suppressed the genes related to cell division, hypertrophy, catabolism, inflammation, and immune response. The downregulated genes were more prominent and stable over time than the upregulated genes. Although exercise time did not prominently contribute to the effects of exercise, it was a factor related to a batch of cellular functions and signaling pathways, such as extracellular matrix (ECM) homeostasis and cellular response to growth factors and stress. Two clusters of genes, including early and late response genes, were identified according to the expression pattern over time. ECM organization, BMP signaling, and PI3K-Akt signaling were early responsive in the exercise duration. Moreover, time-related signaling pathways, such as inositol phosphate metabolism, nicotinate/nicotinamide metabolism, cell cycle, and Fc epsilon RI signaling pathway, were identified by unbiased mapping and polarization of the highly time-correlated genes. Immunohistochemistry staining showed that Egfr was a late response gene that increased on day 15 of exercise. This study elucidated time-related transcriptomic reprogramming induced by exercise in cartilage, advancing the understanding of cartilage homeostasis.

Computer-Aided Drug Design Boosts RAS Inhibitor Discovery.

The Rat Sarcoma (RAS) family (NRAS, HRAS, and KRAS) is endowed with GTPase activity to regulate various signaling pathways in ubiquitous animal cells. As proto-oncogenes, RAS mutations can maintain activation, leading to the growth and proliferation of abnormal cells and the development of a variety of human cancers. For the fight against tumors, the discovery of RAS-targeted drugs is of high significance. On the one hand, the structural properties of the RAS protein make it difficult to find inhibitors specifically targeted to it. On the other hand, targeting other molecules in the RAS signaling pathway often leads to severe tissue toxicities due to the lack of disease specificity. However, computer-aided drug design (CADD) can help solve the above problems. As an interdisciplinary approach that combines computational biology with medicinal chemistry, CADD has brought a variety of advances and numerous benefits to drug design, such as the rapid identification of new targets and discovery of new drugs. Based on an overview of RAS features and the history of inhibitor discovery, this review provides insight into the application of mainstream CADD methods to RAS drug design.

Smoking, alcohol and coffee consumption and risk of low back pain: a Mendelian randomization study.

PURPOSE: Low back pain (LBP) is a common health problem in the global population. This study aims to assess whether smoking initiation, alcohol consumption, and coffee consumption are causally with an increased risk of LBP. METHODS: A two-sample Mendelian Randomization (MR) study was designed, based on summary-level data from the largest published genome-wide association studies. Single nucleotide polymorphisms with genome-wide significance level (P < 5.0 × 10-8) were selected as instrumental variables for each exposure. Standard inverse-variance weighted (IVW) method was used as the primary statistical method. The weighted median, MR-Egger regression, and MR-PRESSO methods, which relax some IV assumptions, were used for sensitivity analysis. RESULTS: Genetically predicted smoking initiation was causally associated with higher odds of LBP. The pooled OR of LBP using IVW method was 1.36 (95%CI 1.22 1.52; P = 6.0 × 10-8) for one SD increase in the prevalence of smoking initiation, which was supported by the weighted median method (OR: 1.41, 95%CI 1.22, 1.64; P = 5.7 × 10-6). Sensitivity analysis confirmed the robustness of pooled OR of LBP. There was no evidence to suggest a causal effect of alcohol and coffee consumption on LBP. The pooled ORs of LBP were 1.36 (95%CI 0.94, 1.97; P = 0.10) for alcohol consumption and 1.00 (95%CI 0.99, 1.00; P = 0.17) for coffee consumption, respectively. CONCLUSION: Smoking is casually associated with an increased risk of LBP. Smoking control should be recommended in LBP patients to avoid worsening the disease. The safety of LBP with moderate alcohol and coffee consumption merits more study.