Factors associated with intrinsic capacity impairment in hospitalized older adults: a latent class analysis.

BACKGROUND: Intrinsic capacity (IC) is proposed by the World Health Organization (WHO) to promote healthy aging. Although some studies have examined the factors influencing IC, few studies have comprehensively confirmed lifestyle factors on IC, especially IC impairment patterns. The present study aimed to identify the patterns of IC impairment and explore the lifestyle and other factors associated with different patterns of IC impairment. METHODS: This cross-sectional study was conducted in a Chinese geriatric hospital. IC was evaluated in five domains according to the recommendations of WHO: cognition, locomotion, vitality, sensory and psychological domains. The sociodemographic and health-related characteristics of participants were assessed.The health promoting lifestyle was evaluated using the Health-Promoting Lifestyle Profile-II scale, including nutrition, health responsibility, interpersonal relationships, physical activity, spiritual growth and stress management. We applied latent class analysis to identify IC impairment patterns and compared basic activities of daily living, instrumental activities of daily living, frailty, quality of life and falls among different IC impairment patterns. Multinomial logistic regression analysis was conducted to identify factors influencing the IC impairment patterns. RESULTS: Among 237 participants included, the latent class analysis identified three patterns of IC impairment: 44.7% high IC (Class 1), 31.2% intermediate IC mainly locomotor impairment (Class 2) and 24.1% low IC mainly cognitive impairment (Class 3). Older adults in class 1 had the best function ability and quality of life, while class 3 had the highest levels of disability and frailty, the poorest quality of life and a higher prevalence of falls. Compared with class 1, older adults with advanced age (OR = 22.046, 95%CI:1.735-280.149), osteoporosis (OR = 3.377, 95%CI:1.161-9.825), and lower scores in physical activity (OR = 0.842, 95%CI:0.749-0.945), stress management (OR = 0.762, 95%CI:0.585-0.993) and social support (OR = 0.897, 95%CI:0.833-0.965) were more likely to belong to the class 2. Simultaneously, compared with class 1, older adults with advanced age (OR = 104.435, 95%CI:6.038-1806.410), stroke (OR = 3.877, 95%CI:1.172-12.823) and lower scores in physical activity (OR = 0.784, 95%CI:0.667-0.922) and social support (OR = 0.909, 95%CI:0.828-0.998) were more likely to be class 3. In addition, compared with class 2, older adults with a lower score in nutrition (OR = 0.764, 95%CI:0.615-0.950) were more likely to belong to the class 3. CONCLUSIONS: This study provides evidence that there are heterogeneous IC impairment patterns in older adults and identifies various associated factors in each pattern, including age, stroke, osteoporosis, social support and lifestyle behaviors such as nutrition, physical activity and stress management. It informs stakeholders on which modifiable factors should be targeted through public health policy or early intervention to promote IC and healthy aging in older adults.

Functional Characterization of PmDXR, a Critical Rate-Limiting Enzyme, for Turpentine Biosynthesis in Masson Pine (Pinus massoniana Lamb.).

As one of the largest and most diverse classes of specialized metabolites in plants, terpenoids (oprenoid compounds, a type of bio-based material) are widely used in the fields of medicine and light chemical products. They are the most important secondary metabolites in coniferous species and play an important role in the defense system of conifers. Terpene synthesis can be promoted by regulating the expressions of terpene synthase genes, and the terpene biosynthesis pathway has basically been clarified in Pinus massoniana, in which there are multiple rate-limiting enzymes and the rate-limiting steps are difficult to determine, so the terpene synthase gene regulation mechanism has become a hot spot in research. Herein, we amplified a PmDXR gene (GenBank accession no. MK969119.1) of the MEP pathway (methyl-erythritol 4-phosphate) from Pinus massoniana. The DXR enzyme activity and chlorophyll a, chlorophyll b and carotenoid contents of overexpressed Arabidopsis showed positive regulation. The PmDXR gene promoter was a tissue-specific promoter and can respond to ABA, MeJA and GA stresses to drive the expression of the GUS reporter gene in N. benthamiana. The DXR enzyme was identified as a key rate-limiting enzyme in the MEP pathway and an effective target for terpene synthesis regulation in coniferous species, which can further lay the theoretical foundation for the molecularly assisted selection of high-yielding lipid germplasm of P. massoniana, as well as provide help in the pathogenesis of pine wood nematode disease.

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery.

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG.

Inhibition of hyphal formation together with biochar addition promotes erythritol production by Yarrowia lipolytica.

This study aimed to investigate the effect of hyphal formation in Yarrowia lipolytica and biochar addition on erythritol production by submerged fermentation. Hyphal formation significantly inhibited erythritol production by Y. lipolytica. Transcriptome analysis suggested that the impaired erythritol synthesis of hyphal cells was associated with the differential expression of genes involved in amino acid metabolism, lipid metabolism, and cell wall stability. Deletion of RAS2 responsible for yeast-to-hypha transition and EYD1 included in erythritol degradation blocked hyphal formation and improved erythritol production. Biochar prepared from corncob, sugarcane bagasse (SB), corn straw, peanut shell, coconut shell, and walnut shell (WS) had a positive effect on erythritol production, of which WS pyrolyzed at 500°C (WSc) performed the best in flask fermentation. In a 3.7 L bioreactor, 220.20 ± 10 g/L erythritol with a productivity of 2.30 ± 0.10 g/L/h was obtained in the presence of 1.4% (w/v) WSc and 0.7% SBc (SB pyrolyzed at 500°C) within 96 h. These results suggest that inhibition of hyphal formation together with biochar addition is an efficient way to promote erythritol production.

Blocking methionine catabolism induces senescence and confers vulnerability to GSK3 inhibition in liver cancer.

Availability of the essential amino acid methionine affects cellular metabolism and growth, and dietary methionine restriction has been implicated as a cancer therapeutic strategy. Nevertheless, how liver cancer cells respond to methionine deprivation and underlying mechanisms remain unclear. Here we find that human liver cancer cells undergo irreversible cell cycle arrest upon methionine deprivation in vitro. Blocking methionine adenosyl transferase 2A (MAT2A)-dependent methionine catabolism induces cell cycle arrest and DNA damage in liver cancer cells, resulting in cellular senescence. A pharmacological screen further identified GSK3 inhibitors as senolytics that selectively kill MAT2A-inhibited senescent liver cancer cells. Importantly, combined treatment with MAT2A and GSK3 inhibitors therapeutically blunts liver tumor growth in vitro and in vivo across multiple models. Together, methionine catabolism is essential for liver tumor growth, and its inhibition can be exploited as an improved pro-senescence strategy for combination with senolytic agents to treat liver cancer.

(±)-Heterocageflavone, anti-inflammatory isoprenylated flavonoids with a tricyclo[5.3.1.03,8]undecane moiety from Artocarpus heterophyllus.

(±)-Heterocageflavone (1), a pair of enantiomeric isoprenylated flavonoids, were isolated from Artocarpus heterophyllus. Compound 1 incorporates an unusual tricyclo[5.3.1.03,8]undecane moiety, forming a unique caged polycyclic system. The structures of the pair were determined by spectroscopic analysis, ECD calculations, and single-crystal X-ray diffraction. Compound 1 showed significant inhibitory activity against LPS-induced NO production in RAW264.7 cells with an IC50 value of 49.2 µM.

Characterization and Interaction Analysis of the Secondary Cell Wall Synthesis-Related Transcription Factor PmMYB7 in Pinus massoniana Lamb.

In vascular plants, the importance of R2R3-myeloblastosis (R2R3-MYB) transcription factors (TFs) in the formation of secondary cell walls (SCWs) has long been a controversial topic due to the lack of empirical evidence of an association between TFs and downstream target genes. Here, we found that the transcription factor PmMYB7, which belongs to the R2R3-MYB subfamily, is involved in lignin biosynthesis in Pinus massoniana. PmMYB7 was highly expressed in lignified tissues and upon abiotic stress. As a bait carrier, the PmMYB7 protein had no toxicity or autoactivation in the nucleus. Forty-seven proteins were screened from the P. massoniana yeast library. These proteins were predicted to be mainly involved in resistance, abiotic stress, cell wall biosynthesis, and cell development. We found that the PmMYB7 protein interacted with caffeoyl CoA 3-O-methyltransferase-2 (PmCCoAOMT2)-which is involved in lignin biosynthesis-but not with beta-1, 2-xylosyltransferase (PmXYXT1) yeast two-hybrid (Y2H) studies. Our in vivo coimmunoprecipitation (Co-IP) assay further showed that the PmMYB7 and PmCCoAOMT2 proteins could interact. Therefore, we concluded that PmMYB7 is an upstream TF that can interact with PmCCoAOMT2 in plant cells. These findings lay a foundation for further research on the function of PmMYB7, lignin biosynthesis and molecular breeding in P. massoniana.

Prediction of Virus-Receptor Interactions Based on Improving Similarities.

Viral infectious diseases have been seriously threatening human health. The receptor binding is the first step of viral infection. Predicting virus-receptor interactions will be helpful for the interaction mechanism of viruses and receptors, and further find some effective ways of preventing and treating viral infectious diseases so as to reduce the morbidity and mortality caused by viruses. Some computation algorithms have been proposed for identifying potential virus-receptor interactions. However, a common problem in those methods is the presence of noise in the similarity network. A new computational model (Network Enhancement and the Regularized Least Squares [NERLS]) is proposed to predict virus-receptor interactions based on improving similarities by Network Enhancement (NE). NERLS integrates the virus sequence similarity, the receptor sequence similarity and known virus-receptor interactions. We compute the virus sequence similarity and known virus-receptor interactions to construct the virus similarity network. The receptor similarity network is constructed by the Gaussian interaction profile kernel similarity and the receptor sequence similarity. To obtain the final virus similarity network and the final receptor similarity network, NE is, respectively, applied for reducing the noise of the virus similarity network and the receptor similarity network. Finally, NERLS employs the regularized least squares to predict interactions of viruses and receptors. The experiment results show that NERLS achieves the area under curve value of 0.893 and 0.921 in 10-fold cross-validation and leave-one-out cross-validation, respectively, which is consistently superior to four related methods [which include Initial interaction scores method via the neighbors and the Laplacian regularized Least Square (IILLS), Bi-random walk on a heterogeneous network (BRWH), Laplacian regularized least squares classifier (LapRLS), and Collaborative matrix factorization (CMF)]. Furthermore, a case study also demonstrates that NERLS effectively predicts potential virus-receptor interactions.

Modulation Recognition of Radar Signals Based on Adaptive Singular Value Reconstruction and Deep Residual Learning.

Automatically recognizing the modulation of radar signals is a necessary survival technique in electronic intelligence systems. In order to avoid the complex process of the feature extracting and realize the intelligent modulation recognition of various radar signals under low signal-to-noise ratios (SNRs), this paper proposes a method based on intrapulse signatures of radar signals using adaptive singular value reconstruction (ASVR) and deep residual learning. Firstly, the time-frequency spectrums of radar signals under low SNRs are improved after ASVR denoising processing. Secondly, a series of image processing techniques, including binarizing and morphologic filtering, are applied to suppress the background noise in the time-frequency distribution images (TFDIs). Thirdly, the training process of the residual network is achieved using TFDIs, and classification under various conditions is realized using the new-trained network. Simulation results show that, for eight kinds of modulation signals, the proposed approach still achieves an overall probability of successful recognition of 94.1% when the SNR is only -8 dB. Outstanding performance proves the superiority and robustness of the proposed method.

Characterization and Function of the 1-Deoxy-D-xylose-5-Phosphate Synthase (DXS) Gene Related to Terpenoid Synthesis in Pinus massoniana.

In the methyl-D-erythritol-4-phosphate (MEP) pathway, 1-deoxy-D-xylose-5-phosphate synthase (DXS) is considered the key enzyme for the biosynthesis of terpenoids. In this study, PmDXS (MK970590) was isolated from Pinus massoniana. Bioinformatics analysis revealed homology of MK970590 with DXS proteins from other species. Relative expression analysis suggested that PmDXS expression was higher in roots than in other plant parts, and the treatment of P. massoniana seedlings with mechanical injury via 15% polyethylene glycol 6000, 10 mM H2O2, 50 µM ethephon (ETH), 10 mM methyl jasmonate (MeJA), and 1 mM salicylic acid (SA) resulted in an increased expression of PmDXS. pET28a-PmDXS was expressed in Escherichia coli TransB (DE3) cells, and stress analysis showed that the recombinant protein was involved in resistance to NaCl and drought stresses. The subcellular localization of PmDXS was in the chloroplast. We also cloned a full-length 1024 bp PmDXS promoter. GUS expression was observed in Nicotiana benthamiana roots, stems, and leaves. PmDXS overexpression significantly increased carotenoid, chlorophyll a, and chlorophyll b contents and DXS enzyme activity, suggesting that DXS is important in isoprenoid biosynthesis. This study provides a theoretical basis for molecular breeding for terpene synthesis regulation and resistance.

Design, synthesis, and biological activity of novel 1,2,4-oxadiazole derivatives.

BACKGROUND: Plant diseases seriously threaten food security, it is urgent to discover efficient and low-risk chemical pesticides. 1,2,4-Oxadiazole derivatives exhibit broad spectrum of agricultural biological activities. For discovering novel molecules with excellent agricultural activities, novel 1,2,4-oxadiazole derivatives were synthesized and evaluated for their agricultural activities. RESULT: Bioassays results showed that the title compounds exhibited moderate nematocidal activity against Meloidogyne incognita and anti-fungal activity to Rhizoctonia solani. It's worth noting that compounds 5m, 5r, 5u, 5v, 5x and 5y showed strong antibacterial effects on Xanthomonas oryzae pv. oryzae (Xoo), with EC50 values of 36.25, 24.14, 28.82, 19.44, 25.37 and 28.52 µg/mL, respectively, superior to bismerthiazol (BMT, EC50 = 77.46 µg/mL) and thiodiazole copper (TDC, EC50 = 99.31 µg/mL). Compounds 5p, 5u and 5v exhibited excellent antibacterial ability against Xanthomonas oryzae pv. oryzicola (Xoc), with EC50 values of 31.40, 19.04 and 21.78 µg/mL, respectively, better than that of BMT (EC50 = 68.50 µg/mL) and TDC (EC50 = 91.05 µg/mL). In addition, compound 5v exerted moderate antibacterial effects on rice bacterial leaf blight. CONCLUSIONS: Twenty-six novel 1,2,4-oxadiazole derivatives were obtained and their biological activities were evaluated. Compound 5u and 5v exhibited excellent antibacterial activity Xoo and Xoc. These results indicated that 1,2,4-oxadiazole derivatives containing a trifluoromethyl pyridine moiety could be as potential alternative templates for discovering novel antibacterial agents.

Inferring microRNA-Environmental Factor Interactions Based on Multiple Biological Information Fusion.

Accumulated studies have shown that environmental factors (EFs) can regulate the expression of microRNA (miRNA) which is closely associated with several diseases. Therefore, identifying miRNA-EF associations can facilitate the study of diseases. Recently, several computational methods have been proposed to explore miRNA-EF interactions. In this paper, a novel computational method, MEI-BRWMLL, is proposed to uncover the relationship between miRNA and EF. The similarities of miRNA-miRNA are calculated by using miRNA sequence, miRNA-EF interaction, and the similarities of EF-EF are calculated based on the anatomical therapeutic chemical information, chemical structure and miRNA-EF interaction. The similarity network fusion is used to fuse the similarity between miRNA and the similarity between EF, respectively. Further, the multiple-label learning and bi-random walk are employed to identify the association between miRNA and EF. The experimental results show that our method outperforms the state-of-the-art algorithms.

Activation of NALP1 inflammasomes in rats with adjuvant arthritis; a novel therapeutic target of carboxyamidotriazole in a model of rheumatoid arthritis.

BACKGROUND AND PURPOSE: Pro-inflammatory cytokines are important in rheumatoid arthritis (RA) and their production is mainly regulated by NF-κB and inflammasomes. Carboxyamidotriazole (CAI) exhibits potent anti-inflammatory activities by decreasing cytokines. Here, we have investigated NACHT, LRR and PYD domains-containing protein (NALP) inflammasomes in a rat model of RA and explored the therapeutic effects of CAI in this model and the involvement of NF-κB and inflammasomes in the actions of CAI. EXPERIMENTAL APPROACH: The anti-arthritic effects of CAI were assessed in the adjuvant arthritis (AA) model in rats, using radiological and histological techniques. NALP1 and NALP3 inflammasomes, NF-κB pathway and pro-inflammatory cytokines levels were measured with Western blots, immunohistochemistry and ELISA. KEY RESULTS: CAI decreased the arthritis index, improved radiological and histological changes, and reduced synovial IL-1ß, IL-6, IL-18 and TNF-α levels in rats with AA. Compared with normal rats, the 70 kDa NALP1 isoform was up-regulated, NALP3 was down-regulated, and levels of the 165 kDa NALP1 isoform and the adaptor protein ASC were unchanged in synovial tissue from AA rats. CAI reduced the 70 kDa NALP1 isoform and restored NALP3 levels in AA rats; CAI inhibited caspase-1 activation in AA synovial tissue, but not its enzymic activity in vitro. In addition, CAI reduced expression of p65 NF-κB subunit and IκBα phosphorylation and degradation in AA rats. CONCLUSION AND IMPLICATIONS: NALP1 inflammasomes were activated in synovial tissues from AA rats and appeared to be a novel therapeutic target for RA. CAI could have therapeutic value in RA by inhibiting activation of NF-κB and NALP1 inflammasomes and by decreasing pro-inflammatory cytokines.

N-[(E)-4-Bromo-benzyl-idene]-2,3-di-methyl-aniline.

The title compound, C15H14BrN, has an E conformation about the C=N bond and the dihedral angle between the benzene rings is 50.7 (2)°. In the crystal, mol-ecules are linked via C-H⋯π inter-actions, forming columns propagating along [010].

N-[(E)-4-Bromo-benzyl-idene]-3,4-di-methyl-aniline.

In the title compound, C15H14BrN, the dihedral angle between the benzene rings is 6.4 (2)° and the mol-ecule has an E conformation about the C=N bond. In the crystal, mol-ecules are linked by C-H⋯π inter-actions, forming two-dimensional networks lying parallel to (001).