The drug loading capacity prediction and cytotoxicity analysis of metal-organic frameworks using stacking algorithms of machine learning.

Metal-organic frameworks (MOFs) have shown excellent performance in the field of drug delivery. Despite the synthesis of a vast array of MOFs exceeding 100,000 varieties, certain formulations have exhibited suboptimal performance characteristics. Therefore, there is a pressing need to enhance their efficacy by identifying MOFs with superior drug loading capacities and minimal cytotoxicity, which can be achieved through machine learning (ML). In this study, a stacking regression model was developed to predict drug loading capacity and cytotoxicity of MOFs using datasets compiled from various literature sources. The model exhibited exceptional predictive capabilities, achieving R2 values of 0.907 for drug loading capacity and 0.856 for cytotoxicity. Furthermore, various model interpretation methods including partial dependence plots, individual conditional expectation, Shapley additive explanation, decision tree, random forest, CatBoost Regressor, and light gradient-boosting machine were employed for feature importance analysis. The results revealed that specific metal atoms such as Zn, Cr, Fe, Zr, and Cu significantly influenced the drug loading capacity and cytotoxicity of MOFs. Through model validation encompassing experimental validation and computational verification, the reliability of the model was thoroughly established. In general, it is a good practice to use ML methods for predicting drug loading capacity and cytotoxicity analysis of MOFs, guiding the development of future property prediction methods for MOFs.

Targeting epigenetic and post-translational modifications regulating pyroptosis for the treatment of inflammatory diseases.

Inflammatory diseases, including infectious diseases, diabetes-related diseases, arthritis-related diseases, neurological diseases, digestive diseases, and tumor, continue to threaten human health and impose a significant financial burden despite advancements in clinical treatment. Pyroptosis, a pro-inflammatory programmed cell death pathway, plays an important role in the regulation of inflammation. Moderate pyroptosis contributes to the activation of native immunity, whereas excessive pyroptosis is associated with the occurrence and progression of inflammation. Pyroptosis is complicated and tightly controlled by various factors. Accumulating evidence has confirmed that epigenetic modifications and post-translational modifications (PTMs) play vital roles in the regulation of pyroptosis. Epigenetic modifications, which include DNA methylation and histone modifications (such as methylation and acetylation), and post-translational modifications (such as ubiquitination, phosphorylation, and acetylation) precisely manipulate gene expression and protein functions at the transcriptional and post-translational levels, respectively. In this review, we summarize the major pathways of pyroptosis and focus on the regulatory roles and mechanisms of epigenetic and post-translational modifications of pyroptotic components. We also illustrate these within pyroptosis-associated inflammatory diseases. In addition, we discuss the effects of novel therapeutic strategies targeting epigenetic and post-translational modifications on pyroptosis, and provide prospective insight into the regulation of pyroptosis for the treatment of inflammatory diseases.

Gene replacement therapy in Bietti crystalline corneoretinal dystrophy: an open-label, single-arm, exploratory trial.

Bietti crystalline corneoretinal dystrophy is an inherited retinal disease caused by mutations in CYP4V2, which results in blindness in the working-age population, and there is currently no available treatment. Here, we report the results of the first-in-human clinical trial (NCT04722107) of gene therapy for Bietti crystalline corneoretinal dystrophy, including 12 participants who were followed up for 180-365 days. This open-label, single-arm exploratory trial aimed to assess the safety and efficacy of a recombinant adeno-associated-virus-serotype-2/8 vector encoding the human CYP4V2 protein (rAAV2/8-hCYP4V2). Participants received a single unilateral subretinal injection of 7.5 × 1010 vector genomes of rAAV2/8-hCYP4V2. Overall, 73 treatment-emergent adverse events were reported, with the majority (98.6%) being of mild or moderate intensity and considered to be procedure- or corticosteroid-related; no treatment-related serious adverse events or local/systemic immune toxicities were observed. Compared with that measured at baseline, 77.8% of the treated eyes showed improvement in best-corrected visual acuity (BCVA) on day 180, with a mean ± standard deviation increase of 9.0 ± 10.8 letters in the 9 eyes analyzed (p = 0.021). By day 365, 80% of the treated eyes showed an increase in BCVA, with a mean increase of 11.0 ± 10.6 letters in the 5 eyes assessed (p = 0.125). Importantly, the patients' improvement observed using multifocal electroretinogram, microperimetry, and Visual Function Questionnaire-25 further supported the beneficial effects of the treatment. We conclude that the favorable safety profile and visual improvements identified in this trial encourage the continued development of rAAV2/8-hCYP4V2 (named ZVS101e).

Inhibition of METTL3 in macrophages provides protection against intestinal inflammation.

Inflammatory bowel disease (IBD) is prevalent, and no satisfactory therapeutic options are available because the mechanisms underlying its development are poorly understood. In this study, we discovered that increased expression of methyltransferase-like 3 (METTL3) in macrophages was correlated with the development of colitis and that depletion of METTL3 in macrophages protected mice against dextran sodium sulfate (DSS)-induced colitis. Mechanistic characterization indicated that METTL3 depletion increased the YTHDF3-mediated expression of phosphoglycolate phosphatase (PGP), which resulted in glucose metabolism reprogramming and the suppression of CD4+ T helper 1 (Th1) cell differentiation. Further analysis revealed that glucose metabolism contributed to the ability of METTL3 depletion to ameliorate colitis symptoms. In addition, we developed two potent small molecule METTL3 inhibitors, namely, F039-0002 and 7460-0250, that strongly ameliorated DSS-induced colitis. Overall, our study suggests that METTL3 plays crucial roles in the progression of colitis and highlights the potential of targeting METTL3 to attenuate intestinal inflammation for the treatment of colitis.

Machine learning methods predict recurrence of pN3b gastric cancer after radical resection.

Background: The incidence of stage pN3b gastric cancer (GC) is low, and the clinical prognosis is poor, with a high rate of postoperative recurrence. Machine learning (ML) methods can predict the recurrence of GC after surgery. However, the prognostic significance for pN3b remains unclear. Therefore, we aimed to predict the recurrence of pN3b through ML models. Methods: This retrospective study included 336 patients with pN3b GC who underwent radical surgery. A 3-fold cross-validation was used to partition the participants into training and test cohorts. Linear combinations of new variable features were constructed using principal component analysis (PCA). Various ML algorithms, including random forest, support vector machine (SVM), logistic regression, multilayer perceptron (MLP), extreme gradient boosting (XGBoost), and Gaussian naive Bayes (GNB), were utilized to establish a recurrence prediction model. Model performance was evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Python was used for the analysis of ML algorithms. Results: Nine principal components with a cumulative variance interpretation rate of 90.71% were identified. The output results of the test set showed that random forests had the highest AUC (0.927) for predicting overall recurrence with an accuracy rate of 80.5%. Random forests had the highest AUC (0.940) for predicting regional recurrence with an accuracy of 89.7%. For predicting distant recurrence, random forests had the highest AUC (0.896) with an accuracy of 84.3%. For peritoneal recurrence, random forests had the highest AUC (0.923) with an accuracy of 83.3%. Conclusions: ML can personalize the prediction of postoperative recurrence in patients with GC with stage pN3b.

The Effect of Respiratory Muscle Training on Swallowing Function in Patients With Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: The improvement of swallowing function after stroke is a significant challenge faced by patients and health care professionals. However, the current evidence synthesis of the effects of respiratory muscle training (RMT) on swallowing function is limited. OBJECTIVE: To assess the effectiveness of RMT on swallowing recovery in patients undergoing stroke. METHODS: The CKNI, WanFang Data, PubMed, CINAHL, Web of Science, Embase, MEDLINE, and Cochrane Library databases were searched for studies evaluating RMT interventions' effect on swallowing outcomes. Risks of bias were evaluated using the approach recommended by the Cochrane Collaboration tool and a summary of findings table was generated using the GRADE approach. Outcomes were synthesized using a random-effects meta-analysis model. RESULTS: RMT interventions reduced the risk of aspiration (SMD = 1.19; 95% CI, 0.53-1.84), the recovery process of water swallowing function (RR = 1.22; 95% CI, 1.05-1.42), and the activity of the swallowing muscles (SMD = 2.91; 95% CI, 2.22-3.61). However, there was no significant effect of RMT on the functional level of oral intake (SMD = 0.70; 95% CI, -0.03 to 1.42). CONCLUSIONS: RMT can be regarded as an innovative, auxiliary means in the near future to better manage and improve swallowing function, given its improving effect on work outcomes in this review.

Self-Reporting Microsensors Inspired by Noctiluca Scintillans for Small-Defect Positioning and Electrical-Stress Visualization in Polymers.

Small defects induce concentrated electrical stress in dielectric polymers, leading to premature failure of materials. Existing sensing methods fail to effectively visualize these defects owing to the invisible-energy state of the electric field. Thus, it is necessary to establish a nondestructive method for the real-time detection of small defects in dielectric polymers. In this study, a self-reporting microsensor (SRM) inspired by Noctiluca scintillans is designed to endow materials with the ability of self-detection for defects and electrical stress. The SRM leverages the energy of a nearby electric field to emit measurable fluorescence, enabling defect localization and diagnosis as well as electrical-stress visualization. A controllable dielectric microsphere is constructed to achieve an adjustable electroluminescence threshold for the SRM, thereby increasing its detection accuracy while decreasing the electroluminescence threshold. The potential degradation in the polymer performance owing to SRM implantation is addressed by assembling long molecular chains on the SRM surface to spontaneously generate an interpenetrating network. Results of finite element analyses and experiments demonstrate that the SRM can effectively realize nondestructive visualization and positioning of small defects and concentrated electrical stress in polymers, positioning it as a promising sensing method for monitoring the electric field and charge distribution in materials.

Label-free Raman imaging for screening of anti-inflammatory function food.

Natural bioactive compounds and plant constituents are considered to have a positive anti-inflammatory effect. This study aimed to establish a screening technique for anti-inflammatory function in foods based on label-free Raman imaging. A visible anti-inflammatory analysis method based on coherent anti-Stokes Raman scattering (CARS) was established with an LPS-induced RAW264.7 cell model. Dynamic changes in proteins and lipids were determined at laser pump light wavelengths of 2956 cm-1 and 2856 cm-1, respectively. The method was applied to a plant-based formula (JC) with anti-inflammatory activity. Q-TOF-MS and HPLC analyses revealed the main active constituents of JC as quercetin, kaempferol, l-glutamine, and sodium copper chlorophyllin. In in vitro and in vivo verification experiments, JC showed significant anti-inflammatory activity by regulating the TLR4/NF-κB pathway. In conclusion, this study successfully established a label-free and visible method for screening anti-inflammatory constituents in plant-based food products, which will facilitate the evaluation of functional foods.

Revealing new insights: Two-center evidence of microplastics in human vitreous humor and their implications for ocular health.

Microplastics (MPs), an emerging environmental contaminant, have raised growing health apprehension due to their detection in various human biospecimens. Despite extensive research into their prevalence in the environment and the human body, the ramifications of their existence within the enclosed confines of the human eye remain largely unexplored. Herein, we assembled a cohort of 49 patients with four ocular diseases (macular hole, macular epiretinal membrane, retinopathy and rhegmatogenous retinal detachment) from two medical centers. After processing the samples with an optimized method, we utilized Laser Direct Infrared (LD-IR) spectroscopy and Pyrolysis Gas Chromatography/Mass Spectrometry (Py-GC/MS) to analyze 49 vitreous samples, evaluating the characteristics of MPs within the internal environment of the human eye. Our results showed that LD-IR scanned a total of 8543 particles in the composite sample from 49 individual vitreous humor samples, identifying 1745 as plastic particles, predominantly below 50 µm. Concurrently, Py-GC/MS analysis of the 49 individual samples corroborated these findings, with nylon 66 exhibiting the highest content, followed by polyvinyl chloride, and detection of polystyrene. Notably, correlations were observed between MP levels and key ocular health parameters, particularly intraocular pressure and the presence of aqueous humor opacities. Intriguingly, individuals afflicted with retinopathy demonstrated heightened ocular health risks associated with MPs. In summary, this research provides significant insights into infiltration of MP pollutants within the human eye, shedding light on their potential implications for ocular health and advocating for further exploration of this emerging health risk.

Identification and Verification of Novel Biomarkers Involving Rheumatoid Arthritis with Multimachine Learning Algorithms: An In Silicon and In Vivo Study.

Background: Rheumatoid arthritis (RA) remains one of the most prevalent chronic joint diseases. However, due to the heterogeneity among RA patients, there are still no robust diagnostic and therapeutic biomarkers for the diagnosis and treatment of RA. Methods: We retrieved RA-related and pan-cancer information datasets from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. Six gene expression profiles and corresponding clinical information of GSE12021, GSE29746, GSE55235, GSE55457, GSE77298, and GSE89408 were adopted to perform differential expression gene analysis, enrichment, and immune component difference analyses of RA. Four machine learning algorithms, including LASSO, RF, XGBoost, and SVM, were used to identify RA-related biomarkers. Unsupervised cluster analysis was also used to decipher the heterogeneity of RA. A four-signature-based nomogram was constructed and verified to specifically diagnose RA and osteoarthritis (OA) from normal tissues. Consequently, RA-HFLS cell was utilized to investigate the biological role of CRTAM in RA. In addition, comparisons of diagnostic efficacy and biological roles among CRTAM and other classic biomarkers of RA were also performed. Results: Immune and stromal components were highly enriched in RA. Chemokine- and Th cell-related signatures were significantly activated in RA tissues. Four promising and novel biomarkers, including CRTAM, PTTG1IP, ITGB2, and MMP13, were identified and verified, which could be treated as novel treatment and diagnostic targets for RA. Nomograms based on the four signatures might aid in distinguishing and diagnosing RA, which reached a satisfactory performance in both training (AUC = 0.894) and testing (AUC = 0.843) cohorts. Two distinct subtypes of RA patients were identified, which further verified that these four signatures might be involved in the immune infiltration process. Furthermore, knockdown of CRTAM could significantly suppress the proliferation and invasion ability of RA cell line and thus could be treated as a novel therapeutic target. CRTAM owned a great diagnostic performance for RA than previous biomarkers including MMP3, S100A8, S100A9, IL6, COMP, LAG3, and ENTPD1. Mechanically, CRTAM could also be involved in the progression through immune dysfunction, fatty acid metabolism, and genomic instability across several cancer subtypes. Conclusion: CRTAM, PTTG1IP, ITGB2, and MMP13 were highly expressed in RA tissues and might function as pivotal diagnostic and treatment targets by deteriorating the immune dysfunction state. In addition, CRTAM might fuel cancer progression through immune signals, especially among RA patients.

Quantitative analysis of the quality constituents of Lonicera japonica Thunberg based on Raman spectroscopy.

Quantitative analysis of the quality constituents of Lonicera japonica (Jinyinhua [JYH]) using a feasible method provides important information on its evaluation and applications. Limitations of sample pretreatment, experimental site, and analysis time should be considered when identifying new methods. In response to these considerations, Raman spectroscopy combined with deep learning was used to establish a quantitative analysis model to determine the quality of JYH. Chlorogenic acid and total flavonoids were identified as analysis targets via network pharmacology. High performance liquid chromatograph and ultraviolet spectroscopy were used to construct standard curves for quantitative analysis. Raman spectra of JYH extracts (1200) were collected. Subsequently, models were built using partial least squares regression, Support Vector Machine, Back Propagation Neural Network, and One-dimensional Convolutional Neural Network (1D-CNN). Among these, the 1D-CNN model showed superior prediction capability and had higher accuracy (R2 = 0.971), and lower root mean square error, indicating its suitability for rapid quantitative analysis.

Extraction and characterization of nanocellulose from cattail leaves: Morphological, microstructural and thermal properties.

Hydrogen peroxide combined with acid treatment demonstrates its respective characteristics for the separation of lignocellulosic biomass. Herein, holocellulose was extracted from Cattail leaves (CL) by a two-step treatment with alkali and hydrogen peroxide-acetic acid (HPAA). Then carboxylated nanocellulose was hydrolyzed with a mixed organic/inorganic acid. The chemical composition of the holocellulose and the physicochemical properties of the separated carboxylated nanocellulose were comparable. Carboxyl groups were introduced on the nanocellulose as a result of the esterification process with citric acid (CA), which endows the nanocellulose with high thermal stability (315-318 °C) and good light transmission (>80 %). Furthermore, morphological analyses revealed that nanocellulose had a spider-web-like structure with diameter between 5 and 20 nm.

Isoliquiritin Ameliorates Ulcerative Colitis in Rats through Caspase 3/HMGB1/TLR4 Dependent Signaling Pathway.

BACKGROUND: Isoliquiritin belongs to flavanol glycosides and has a strong antiinflammatory activity. This study sought to investigate the anti-inflammatory effect of isoliquiritin and its underlying mechanism. METHODS: The inflammatory (trinitro-benzene-sulfonic acid-TNBS-induced ulcerative colitis (UC)) model was established to ascertain the effect of isoliquiritin on the caspase-3/HMGB1/TLR4 pathway in rats. We also explored its protective effect on intestinal inflammation and its underlying mechanism using the LPS-induced inflammation model of Caco-2 cells. Besides, Deseq2 was used to analyze UCassociated protein levels. RESULTS: Isoliquiritin treatment significantly attenuated shortened colon length (induced by TNBS), disease activity index (DAI) score, and body weight loss in rats. A decrease in the levels of inflammatory mediators (IL-1ß, I IL-4, L-6, IL-10, PGE2, and TNF-α), coupled with malondialdehyde (MDA) and superoxide dismutase (SOD), was observed in colon tissue and serum of rats after they have received isoliquiritin. Results of techniques (like western blotting, real-time PCR, immunohistochemistry, and immunofluorescence-IF) demonstrated the potential of isoliquiritin to decrease expressions of key genes in the TLR4 downstream pathways, viz., MyD88, IRAK1, TRAF6, NF-κB, p38, and JNK at mRNA and protein levels as well as inhibit HMGB1 expression, which is the upstream ligand of TLR4. Bioinformational analysis showed enteritis to be associated with a high expression of HMGB1, TLR4, and caspase-3. CONCLUSION: Isoliquiritin could reduce intestinal inflammation and mucosal damage of TNBS-induced colitis in rats with a certain anti-UC effect. Meanwhile, isoliquiritin treatment also inhibited the expression of HMGB1, TLR4, and MyD88 in LPS-induced Caco-2 cells. These results indicated that isoliquiritin could ameliorate UC through the caspase-3/HMGB1/TLR4-dependent signaling pathway.

Comparative transcriptome analysis reveals the molecular mechanism of sterility induced by irradiation of Plutella xylostella (Linnaeus).

Plutella xylostella (Linnaeus) is an important pest of cruciferous plants, which is harmful all over the world, causing serious economic losses, and its drug resistance is increasing rapidly. The sterile insect technique (SIT) is a green control method and does not cause resistance. In this study, transcriptomics and bioinformatics were used to explore the effects of irradiation on the reproductive function of Plutella xylostella, and the response mechanism of sterility under irradiation was initially revealed. We identified 3342 (1682 up-regulated, 1660 down-regulated), 1963 (1042 up-regulated, 921 down-regulated) and 1531 (721 up-regulated, 810 down-regulated) differentially expressed genes (DEGs) in the 200 Gy vs CK (Control Check), 400 Gy vs CK and 400 Gy vs 200 Gy groups, respectively. GO and KEGG analyses were performed for DEGs in each group. The results showed that 200 Gy activated the downstream phosphorylation pathway and inhibited the cytochrome p450 immune response mechanism. 400 Gy promoted protein decomposition and absorption pathways, autophagy pathways, etc. Down-regulated genes were concentrated in the transformation process of energy metabolizing substances such as ATP, phosphorylation signaling pathway, and insulin, while up-regulated genes were concentrated in biological regulation and metabolic processes. Eight genes in the phosphorylation pathway were selected for qRT-PCR verification, and the results showed that the phosphorylation of different dose groups was regulated in different ways. 400 Gy used positive feedback regulation, while the phosphorylation of F1 used negative feedback regulation.

Integration of transcriptomic, proteomic, and metabolomic data to identify lncRNA rPvt1 associations in lipopolysaccharide-treated H9C2 cardiomyocytes.

Background: Recent evidence has shown that the long non-coding RNA (lncRNA) rPvt1 is elevated in septic myocardial tissues and that its knockdown attenuates sepsis-induced myocardial injury. However, the mechanism underlying the role of rPvt1 in septic myocardial dysfunction has not been elucidated. Methods: In this study, we performed transcriptomic, proteomic, and metabolomic assays and conducted an integrated multi-omics analysis to explore the association between rPvt1 and lipopolysaccharide (Lipopolysaccharide)-induced H9C2 cardiomyocyte injury. LncRNA rPvt1 silencing was achieved using a lentiviral transduction system. Results: Compared to those with the negative control, rPvt1 knockdown led to large changes in the transcriptome, proteome, and metabolome. Specifically, 2,385 differentially expressed genes (DEGs), 272 differentially abundant proteins and 75 differentially expressed metabolites (DEMs) were identified through each omics analysis, respectively. Gene Ontology functional annotation, Kyoto Encyclopedia of Genes and Genomes, Nr, eukaryotic orthologous groups, and Clusters of Orthologous Groups of Proteins pathway analyses were performed on these differentially expressed/abundant factors. The results suggested that mitochondrial energy metabolism might be closely related to the mechanism through which Pvt1 functions. Conclusion: These genes, proteins, metabolites, and their related dysregulated pathways could thus be promising targets for studies investigating the rPvt1-regluatory mechanisms involved in septic myocardial dysfunction, which is important for formulating novel strategies for the prevention, diagnosis and treatment of septic myocardial injury.

On-surface synthesis of Au-C4 and Au-O4 alternately arranged organometallic coordination networks via selective aromatic C-H bond activation.

Selective activation of the C-H bond of aromatic hydrocarbons is significant in synthetic chemistry. However, achieving oriented C-H activation remains challenging due to the poor selectivity of aromatic C-H bonds. Herein, we successfully constructed alternately arranged Au-C4 and Au-O4 organometallic coordination networks through selective aromatic C-H bond activation on Au(111) substrate. The stepwise reaction process of the 5, 12-dibromopyrene 3,4,9, 10-tetracarboxylic dianhydride precursor is monitored by high-resolution scanning tunneling microscopy. Our results show that the gold atoms in C-Au-C organometallic chains play a crucial role in promoting the selective ortho C-H bonds activation and forming Au-C4 coordination structure, which is further demonstrated by a comparative experiment of PTCDA precursor on Au(111). Furthermore, our experiment of 2Br-PTCDA precursor on Cu(111) substrate confirms that copper atoms in C-Cu-C organometallic chains can also assist the formation of Cu-C4 coordination structure. Our results reveal the vital effect of organometallic coordination on selective C-H bond activation of reactants, which holds promising implications for controllable on-surface synthesis.

Exosome-derived circ_0001785 delays atherogenesis through the ceRNA network mechanism of miR-513a-5p/TGFBR3.

PURPOSE: Endothelial cell dysfunction is a major cause of early atherosclerosis. Although the role of extracellular vesicles in stabilizing atherosclerotic plaques is well established, the effect of circulating exosomes on plaque formation is still unknown. Here, we explored the effect of exosomes on atherosclerosis based on the function that exosomes can act on intercellular communication. PATIENTS AND METHODS: We extracted serum exosomes from the blood of CHD patients (CHD-Exo) and healthy individuals (Con-Exo). The obtained exosomes were co-cultured with human umbilical vein endothelial cells (HUVECs) in vitro. In addition, we determined that circ_0001785 functions as a competing endogenous RNA (ceRNAs) in coronary artery disease by dual luciferase reporter gene analysis. The protective effect of circ_0001785 against endothelial cell injury was also verified using over-expression lentiviral transfection functional assays. In vivo experiments, we injected over-expressed circ_0001785 lentivirus into the tail vein of mice to observe its therapeutic effect on a mouse model of atherosclerosis. RESULTS: The vitro co-cultured results showed that the amount of plasma-derived exosomes have an increase in patients with coronary artery disease, and the inflammation and apoptosis of endothelial cells were exacerbated. Over-expression of circ_0001785 reduced endothelial cell injury through the ceRNA network pathway of miR-513a-5p/TGFBR3. Quantitative reverse transcription-polymerase chain reaction identified that the expressed amount of circ_0001785 was reduced in the circulating peripheral blood of CHD patients and increased within human and mouse atherosclerotic plaque tissue. The results of in vivo experiments showed that circ_0001785 reduced aortic endothelial cell injury and the formation of intraplaque neo-vascularization, and enhanced left ventricular diastolic function, thereby delaying the development of atherosclerosis in mice. CONCLUSION: Our results demonstrated a new biomarker, exosome-derived circ_0001785, for atherogenesis, which can reduce endothelial cell injury and thus delay atherogenesis through the miR-513a-5p/TGFBR3 ceRNA network mechanism, providing an exosome-based intervention strategy for atherosclerosis.

DVT: a high-throughput analysis pipeline for locomotion and social behavior in adult Drosophila melanogaster.

BACKGROUND: Drosophila melanogaster is excellent animal model for understanding the molecular basis of human neurological and motor disorders. The experimental conditions and chamber design varied between studies. Moreover, most previously established paradigms focus on fly trace detection algorithm development. A comprehensive understanding on how fly behaves in the chamber is still lacking. RESULTS: In this report, we established 74 unique behavior metrics quantifying spatiotemporal characteristics of adult fly locomotion and social behaviors, of which 49 were newly proposed. By the aiding of the developed analysis pipeline, Drosophila video tracking (DVT), we identified siginificantly different patterns of fly behavior confronted with different chamber height, fly density, illumination and experimental time. Meanwhile, three fly strains which are widely used as control lines, Canton-S(CS), w1118 and Oregon-R (OR), were found to exhibit distinct motion explosiveness and exercise endurance. CONCLUSIONS: We believe the proposed behavior metrics set and pipeline should help identify subtle spatial and temporal differences of drosophila behavior confronted with different environmental factors or gene variants.

Muti-objective optimization on energy consumption, CO2 emission and production cost for iron and steel industry.

Due to high material density, high energy consumption density and CO2 emission density, it is not only difficult but significant to clarify the relationship between energy consumption, the CO2 emission and the production cost in different conditions. However, the previous researches rarely refer how to balance the energy consumption, the CO2 emission and the production cost after the fluctuation of material, energy and carbon price as well as what will happen to them if production structure changes. Therefore, based on the conservation law of mass and energy, to study iron and steel manufacturing process (ISMP), this paper, taking carbon price into consideration, establishes a muti-optimization model of energy consumption, CO2 emission and cost. After optimization with different objectives, the production cost per tonne of crude steel is reduced by 192.03 CNY (7.71%), the CO2 emission per tonne of crude steel is reduced by 224.22 kg (13.37%), and the energy consumption per tonne of steel is reduced by 51.20 kgce (9.10%). Moreover, based on the optimization results under different objectives, it is ironmaking process (coal ratio and ore ratio) and steelmaking process (amount of scrap steel) that has more impact on three above as well as ore blending and coal blending have a great influence on production cost but little effect on energy consumption and CO2 emission.

Cytoskeletal activation of NHE1 regulates cell volume and DNA methylation.

The regulation of mammalian cell volume is crucial for maintaining key cellular processes. Cells can rapidly respond to osmotic and hydrostatic pressure imbalances during environmental challenges, generating fluxes of water and ions that alter volume within minutes. While the role of ion pump and leak in cell volume regulation has been well-established, the role of the actomyosin cytoskeleton and its substantial interplay with ion transporters are still unclear. In this work, we discover a system of cell volume regulation controlled by cytoskeletal activation of ion transporters. Under hypotonic shock, NIH-3T3 and MCF-10A display a 20% secondary volume increase (SVI) following the initial regulatory volume decrease. We show that SVI is initiated by Ca 2+ influx through stretch activated channel Piezo1 and subsequent actomyosin remodeling. Rather than contracting cells, actomyosin triggers cell swelling by activating Na + -H + exchanger 1 (NHE1) through their co-binding partner ezrin. Cytoskeletal activation of NHE1 can be similarly triggered by mechanical stretch and attenuated by soft substrates. This mechanism is absent in certain cancer cell lines such as HT1080 and MDA-MB-231, where volume regulation is dominated by intrinsic response of ion transporters. Moreover, cytoskeletal activation of NHE1 during SVI induces nuclear deformation, leading to DNA demethylation and a significant, immediate transcriptomic response in 3T3 cells, a phenomenon that is absent in HT1080 cells. Overall, our findings reveal the central role of Ca 2+ and actomyosin-mediated mechanosensation in the regulation of ion transport, cell volume, DNA methylation, and transcriptomics.