Protective effects of Lactococcus lactis subsp. lactis HFY14 supplementation on the brain, intestines, and motor function of antibiotic-treated mice.

Introduction: This study aimed to explore the anti-oxidative and anti-inflammatory properties of Lactococcus lactis subsp. lactis HFY14 (LLSLHFY14) and investigate its effects on the intestinal barrier, cranial nerve, and motor function in mice treated with antibiotics. Methods: Mice were administered an antibiotic mixture (neomycin 5 mg/mL, vancomycin 25 mg/mL, amphotericin B 0.1 mg/mL, ampicillin 10 mg/mL, metronidazole file 5 mg/mL, and lipopolysaccharide 1.5 µg/mL) intraperitoneally, and oxidative stress and inflammatory markers in the serum and brain tissues, and liver index were measured. H&E staining was performed to detect pathological alterations in brain tissues. The expression of intestinal-barrier-related genes and that of genes involved in inflammatory pathways in the brain were detected using polymerase chain reaction (PCR). Results: LLSLHFY14 administration extended the weight-loaded swimming and running times of mice and decreased the liver index. Moreover, the levels of malondialdehyde (MDA), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α) in the serum and brain tissue were reduced, whereas those of superoxide dismutase (SOD), glutathione (GSH), and interleukin-10 (IL-10) were elevated. Elevated brain expression of the protein kinase B (AKT)/cAMP-response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF)/extracellular signal-regulated kinase 1 (ERK1) pathway, decreased brain expression of the IL-6 gene, and elevated cecum expression of zonula occludens-1 (ZO-1), occludin-1, and claudin-1 genes were noted. LLSLHFY14 supplementation significantly increased Bacteroidetes expression but decreased Firmicutes expression, thus increasing the Bacteroidetes/Firmicutes ratio. Discussion: Overall, LLSLHFY14 supplementation ameliorated antibiotic-induced oxidative stress and inflammation in the mouse central nervous system, intestinal barrier dysfunction, and increased motor function, thus confirming its potential application as probiotics.

Chitosan and hyaluronic acid based injectable dual network hydrogels - Mediating antimicrobial and inflammatory modulation to promote healing of infected bone defects.

In bone defects, infections lead to excessive inflammation, increased bacterial, and bone lysis, resulting in irregular wounds that hinder new bone regeneration. Injectable bioactive materials with adequate antimicrobial activity and strong osteogenic potential are urgently required to remedy irregular defects, eradicate bacteria, and facilitate the generation of new bone tissue. In this research, injectable dual-network composite hydrogels consisting of sulfated chitosan, oxidized hyaluronic acid, ß-sodium glycerophosphate, and CuSr doped mesoporous bioactive glass loaded with bone morphogenetic protein (CuSrMBGBMP-2) were utilized for the first time to treat infectious bone defects. Initially, the hydrogel was injected into the wound at 37 °C with minimal invasion to establish a stable state and prevent hydrogel loss. Subsequently, sulfated chitosan eliminated bacteria at the wound site and facilitated cell proliferation with oxidized hyaluronic acid. Additionally, CuSrMBGBMP-2 strengthened antibacterial properties, regulated inflammatory reactions, promoted angiogenesis and osteogenic differentiation, addressing the deficiency in late-stage osteogenesis. Specifically, the injectable dual-network hydrogel based on chitosan and hyaluronic acid is minimally invasive, offering antibacterial, anti-inflammatory, pro-angiogenic, and bone regeneration properties. Therefore, this hydrogel with injectable dual network properties holds great promise for the treatment of bone infections in the future.

Expression of Multicopy Tandem Recombinant Ginseng Hexapeptide in Bacillus subtilis and the Evaluation of Antiaging Activity.

Ginseng oligopeptides are naturally occurring small-molecule peptides extracted from ginseng that exhibit positive effects on health and longevity. However, the current industrial production of ginseng oligopeptides primarily relies on plant extraction and chemical synthesis. In this study, we proposed a novel genetic engineering approach to produce active ginseng peptides through multicopy tandem insertion (5 and 15 times). The recombinant ginseng peptides were successfully produced from engineered Bacillus subtilis with an increasing yield from 356.55 to 2900 mg/L as the repeats multiple. Additionally, an oxidative stress-induced aging model caused by H2O2 was established to evaluate whether the recombinant ginseng peptides, without enzymatic hydrolysis into individual peptides, also have positive effects on antiaging. The results demonstrated that all two kinds of recombinant ginseng peptides could also delay cellular aging through various mechanisms, such as inhibiting cell cycle arrest, suppressing the expression of pro-inflammatory factors, and enhancing cellular antioxidant capacity.

Dysregulated inter-mitochondrial crosstalk in glioblastoma cells revealed by in situ cryo-electron tomography.

Glioblastomas (GBMs) are the most lethal primary brain tumors with limited survival, even under aggressive treatments. The current therapeutics for GBMs are flawed due to the failure to accurately discriminate between normal proliferating cells and distinctive tumor cells. Mitochondria are essential to GBMs and serve as potential therapeutical targets. Here, we utilize cryo-electron tomography to quantitatively investigate nanoscale details of randomly sampled mitochondria in their native cellular context of GBM cells. Our results show that compared with cancer-free brain cells, GBM cells own more inter-mitochondrial junctions of several types for communications. Furthermore, our tomograms unveil microtubule-dependent mitochondrial nanotunnel-like bridges in the GBM cells as another inter-mitochondrial structure. These quantified inter-mitochondrial features, together with other mitochondria-organelle and intra-mitochondrial ones, are sufficient to distinguish GBM cells from cancer-free brain cells under scrutiny with predictive modeling. Our findings decipher high-resolution inter-mitochondrial structural signatures and provide clues for diagnosis and therapeutic interventions for GBM and other mitochondria-related diseases.

Integrating network pharmacology and experimental models to identify notoginsenoside R1 ameliorates atherosclerosis by inhibiting macrophage NLRP3 inflammasome activation.

Atherosclerosis is a cardiovascular disease, accounting for the most common mortality cause worldwide. Notoginsenoside R1 (NGR1) is a characteristic saponin of Radix notoginseng that exhibits anti-inflammatory and antioxidant effects while modulating lipid metabolism. Evidence suggests that NGR1 exerts cardioprotective, neuroprotective, and anti-atherosclerosis effects. However, underlying NGR1 mechanisms alleviating atherosclerosis (AS) have not been examined. This study used a network pharmacology approach to construct the drug-target-disease correlation and protein-protein interaction (PPI) network of NGR1 and AS. Moreover, functional annotation and pathway enrichment analyses deciphered the critical biological processes and signaling pathways potentially regulated by NGR1. The protective effect of NGR1 against AS and the underlying mechanism(s) was assessed in an atherogenic apolipoprotein E-deficient (ApoE-/-) mice in vivo and an oxidized low-density lipoprotein (ox-LDL)-induced macrophage model in vitro. The network pharmacology and molecular docking analyses revealed that NGR1 protects against AS by targeting the NLRP3/caspase-1/IL-1ß pathway. NGR1 reduced foam cell formation in ox-LDL-induced macrophages and decreased atherosclerotic lesion formation, serum lipid metabolism, and inflammatory cytokines in AS mice in vivo. Therefore, NGR1 downregulates the NLRP3 inflammasome complex gene expression of NLRP3, caspase-1, ASC, IL-1ß, and IL-18, in vivo and in vitro.

Lifting the veils on transmembrane proteins: Potential anticancer targets.

Cancer, as a prevalent cause of mortality, poses a substantial global health burden and hinders efforts to enhance life expectancy. Nevertheless, the prognosis of patients with malignant tumors remains discouraging, owing to the lack of specific diagnostic and therapeutic targets. Therefore, the development of early diagnostic indicators and novel therapeutic drugs for the prevention and treatment of cancer is essential. Transmembrane proteins (TMEMs) are a class of proteins that can span the phospholipid bilayer and are stably anchored. They are associated with fibrotic diseases, neurodegenerative diseases, autoimmune diseases, developmental disorders, and cancer. It has been found that the expression levels of TMEMs were elevated or reduced in cancer cells, exerting pro/anticancer effects. These aberrant expression levels have also been linked to the prognostic and clinicopathological features of diverse tumors. In this review, the structures, functions, and roles of TMEMs in cancer were discussed, and the scientific perspectives were described. This review also explored the potential of TMEMs as tumor drug candidates from the perspective of targeted therapies, and the challenges that need to be overcome in a wide range of preclinical and clinical anticancer research were summarized.

Construction of Coarse-Grained Molecular Dynamics with Many-Body Non-Markovian Memory.

We introduce a machine-learning-based coarse-grained molecular dynamics model that faithfully retains the many-body nature of the intermolecular dissipative interactions. Unlike the common empirical coarse-grained models, the present model is constructed based on the Mori-Zwanzig formalism and naturally inherits the heterogeneous state-dependent memory term rather than matching the mean-field metrics such as the velocity autocorrelation function. Numerical results show that preserving the many-body nature of the memory term is crucial for predicting the collective transport and diffusion processes, where empirical forms generally show limitations.

Clear Cell Renal Cell Carcinoma with Hemangioblastoma-Like Features: A Case Report.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) constitutes the most frequently encountered sporadic class of kidney cancer in adults. Recently, a rare form of clear cell kidney cancer known as ccRCC with hemangioblastoma-like features was proposed, with unique immunological characteristics and a good prognosis. The tumor expressed alpha-inhibin and carbonic anhydrase Ⅸ (CA9) as examined by immunohistochemistry. METHODS: Herein, we report a clinical instance of ccRCC with hemangioblastoma-like features. A 49-year-old woman presenting with a chief complaint of hematuria underwent a comprehensive and meticulous assessment. Imaging findings indicated the presence of a mass in the right kidney. Subsequently, she underwent a partial nephrectomy. RESULTS: Histopathological analysis of the resected specimen confirmed the presence of ccRCC with hemangioblastoma-like features. The patient was discharged from the hospital six days post-surgery and could resume her daily activities. During a one-year follow-up after surgery, no signs of recurrence were detected. CONCLUSIONS: This case demonstrates the importance of including ccRCC with hemangioblastoma-like features in the differential diagnosis of renal masses in patients with hematuria, and suggests partial nephrectomy as an effective treatment modality for this rare subtype of renal cell carcinoma. However, because of the small number of reported cases and insufficient follow-up time, further investigation is necessary to determine the optimal therapeutic approach and to identify the molecular and genetic characteristics of this tumor.

ATP2C2 as a novel immune-related marker that defines the tumor microenvironment in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is an aggressive cancer that affects about 13/100,000 women yearly. Patients with TNBC are often resistant to endocrine and molecular targeted therapy, making clinical treatment challenging. Researches indicate that tumor microenvironment (TME) is related to prognosis in many cancers. Therefore, we aim to identify TME immune-related biomarkers to enhance the prognosis and immunotherapy efficacy in patients with TNBC. Methods: The bulk mRNA transcriptome data and clinical information of the (GSE58812) and (GSE25055) datasets were downloaded from the Gene Expression Omnibus (GEO) database, and the ESTIMATE algorithm was used to calculate the ImmuneScore, StromalScore, and ESTIMATEScore. Patients were divided into low and high groups according to the quartiles of ImmuneScore, StromalScore, and the median of ESTIMATEScore to filter differential expression genes (DEGs), respectively. The DEGs were then evaluated using univariate and multivariate Cox regression to identify TME-related genes and its association with survival rate for the construction of a TMErisk model with three biomarkers. Then Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) data were used to compare the gene expression in cancer and normal tissues. xCell analysis calculated the proportion of tumor-infiltrating immune cells in low and high expression of ATPase Secretory Pathway Ca2+ Transporting 2 (ATP2C2). In addition, samples from 20 TNBC patients admitted to our institution were used for immunohistochemical (IHC) examination. Results: Three immune-related DEGs were identified, including prolyl 3-hydroxylase 2 (P3H2), sodium voltage-gated channel beta subunit 3 (SCN3B), and ATP2C2 and a TMErisk model was constructed and validated. However, only ATP2C2 was selected for further analysis. ATP2C2 mRNA level of TNBC patients was higher than that of normal breast tissue. Survival analysis showed that patients with high expression of ATP2C2 had a bad prognosis. xCell analysis demonstrated that the expression of ATP2C2 was associated with 16 kinds of tumor-infiltrating immune cells. Protein expression of ATP2C2 in TNBC tissues was higher compared to paired normal tissues in IHC. Conclusions: This study constructed and validated a TMErisk model that can effectively predict 3- and 5-year survival rate for TNBC patients. TNBC patients with lower expression of ATP2C2 had a good prognosis.

Clear Cell Renal Cell Carcinoma with Hemangioblastoma-Like Features: A Case Report

Abstract Background: Clear cell renal cell carcinoma (ccRCC) constitutes the most frequently encountered sporadic class of kidney cancer in adults. Recently, a rare form of clear cell kidney cancer known as ccRCC with hemangioblastoma-like features was proposed, with unique immunological characteristics and a good prognosis. The tumor expressed alpha-inhibin and carbonic anhydrase Ⅸ (CA9) as examined by immunohistochemistry. Methods: Herein, we report a clinical instance of ccRCC with hemangioblastoma-like features. A 49-year-old woman presenting with a chief complaint of hematuria underwent a comprehensive and meticulous assessment. Imaging findings indicated the presence of a mass in the right kidney. Subsequently, she underwent a partial nephrectomy. Results: Histopathological analysis of the resected specimen confirmed the presence of ccRCC with hemangioblastoma-like features. The patient was discharged from the hospital six days post-surgery and could resume her daily activities. During a one-year follow-up after surgery, no signs of recurrence were detected. Conclusions: This case demonstrates the importance of including ccRCC with hemangioblastoma-like features in the differential diagnosis of renal masses in patients with hematuria, and suggests partial nephrectomy as an effective treatment modality for this rare subtype of renal cell carcinoma. However, because of the small number of reported cases and insufficient follow-up time, further investigation is necessary to determine the optimal therapeutic approach and to identify the molecular and genetic characteristics of this tumor (AU)

Low level of ARID1A contributes to adaptive immune resistance and sensitizes triple-negative breast cancer to immune checkpoint inhibitors.

BACKGROUND: Immune checkpoint inhibitors (ICIs) shed new light on triple-negative breast cancer (TNBC), but only a minority of patients demonstrate response. Therefore, adaptive immune resistance (AIR) needs to be further defined to guide the development of ICI regimens. METHODS: Databases, including The Cancer Genome Atlas, Gene Ontology Resource, University of California Santa Cruz Genome Browser, and Pubmed, were used to screen epigenetic modulators, regulators for CD8+ T cells, and transcriptional regulators of programmed cell death-ligand 1 (PD-L1). Human peripheral blood mononuclear cell (Hu-PBMC) reconstruction mice were adopted for xenograft transplantation. Tumor specimens from a TNBC cohort and the clinical trial CTR20191353 were retrospectively analyzed. RNA-sequencing, Western blotting, qPCR and immunohistochemistry were used to assess gene expression. Coculture assays were performed to evaluate the regulation of TNBC cells on T cells. Chromatin immunoprecipitation and transposase-accessible chromatin sequencing were used to determine chromatin-binding and accessibility. RESULTS: The epigenetic modulator AT-rich interaction domain 1A (ARID1A) gene demonstrated the highest expression association with AIR relative to other epigenetic modulators in TNBC patients. Low ARID1A expression in TNBC, causing an immunosuppressive microenvironment, promoted AIR and inhibited CD8+ T cell infiltration and activity through upregulating PD-L1. However, ARID1A did not directly regulate PD-L1 expression. We found that ARID1A directly bound the promoter of nucleophosmin 1 (NPM1) and that low ARID1A expression increased NPM1 chromatin accessibility as well as gene expression, further activating PD-L1 transcription. In Hu-PBMC mice, atezolizumab demonstrated the potential to reverse ARID1A deficiency-induced AIR in TNBC by reducing tumor malignancy and activating anti-tumor immunity. In CTR20191353, ARID1A-low patients derived more benefit from pucotenlimab compared to ARID1A-high patients. CONCLUSIONS: In AIR epigenetics, low ARID1A expression in TNBC contributed to AIR via the ARID1A/NPM1/PD-L1 axis, leading to poor outcome but sensitivity to ICI treatment.

TMEM200A is a potential prognostic biomarker and correlated with immune infiltrates in gastric cancer.

Background: Gastric cancer (GC) is one of the most common malignant tumors in the digestive system. Several transmembrane (TMEM) proteins are defined as tumor suppressors or oncogenes. However, the role and underlying mechanism of TMEM200A in GC remain unclear. Methods: We analyzed the expression of TMEM200A in GC. Furthermore, the influence of TMEM200A on survival of GC patients was evaluated. The correlations between the clinical information and TMEM200A expression were analyzed using chi-square test and logistic regression. Relevant prognostic factors were identified performing univariate and multivariate analysis. Gene set enrichment analysis (GSEA) was performed based on the TCGA dataset. Finally, we explore the relationship between TMEM200A expression and cancer immune infiltrates using CIBERSORT. Results: TMEM200A was up-regulated in GC tissues than that in adjacent non-tumor tissues based on TCGA database. Meta-analysis and RT-qPCR validated the difference in TMEM200A expression. Kaplan-Meier curves suggested the increased TMEM200A had a poor prognosis in GC patients. The chi-square test and logistic regression analyses showed that the TMEM200A expression correlates significantly with T stage. Multivariate analysis showed that TMEM200A expression might be an important independent predictor of poor overall survival in GC patients. GSEA identified five immune-related signaling pathways and five tumor-related signaling pathways significantly enriched in the high TMEM200A expression phenotype pathway. Finally, we found CD8+ T cells is apparently decreased in high TMEM200A expression group. Conversely, eosinophils is increased in high expression group compared with low expression group. Conclusion: TMEM200A is a potential prognostic biomarker and correlated with immune infiltrates in GC.

Mesh Convolution With Continuous Filters for 3-D Surface Parsing.

Geometric feature learning for 3-D surfaces is critical for many applications in computer graphics and 3-D vision. However, deep learning currently lags in hierarchical modeling of 3-D surfaces due to the lack of required operations and/or their efficient implementations. In this article, we propose a series of modular operations for effective geometric feature learning from 3-D triangle meshes. These operations include novel mesh convolutions, efficient mesh decimation, and associated mesh (un)poolings. Our mesh convolutions exploit spherical harmonics as orthonormal bases to create continuous convolutional filters. The mesh decimation module is graphics processing unit (GPU)-accelerated and able to process batched meshes on-the-fly, while the (un)pooling operations compute features for upsampled/downsampled meshes. We provide an open-source implementation of these operations, collectively termed Picasso. Picasso supports heterogeneous mesh batching and processing. Leveraging its modular operations, we further contribute a novel hierarchical neural network for perceptual parsing of 3-D surfaces, named PicassoNet ++ . It achieves highly competitive performance for shape analysis and scene segmentation on prominent 3-D benchmarks. The code, data, and trained models are available at https://github.com/EnyaHermite/Picasso.

COVID-19 contact tracking based on person reidentification and geospatial data.

Efficient contact tracing is a crucial step in preventing the spread of COVID-19. However, the current methods rely heavily on manual investigation and truthful reporting by high-risk individuals. Mobile applications and Bluetooth-based contact tracing methods have also been adopted, but privacy concerns and reliance on personal data have limited their effectiveness. To address these challenges, in this paper, a geospatial big data method that combines person reidentification and geospatial information for contact tracing is proposed. The proposed real-time person reidentification model can identify individuals across multiple surveillance cameras, and the surveillance data is fused with geographic information and mapped onto a 3D geospatial model to track movement trajectories. After real-world verification, the proposed method achieves a first accuracy rate of 91.56%, a first-five accuracy rate of 97.70%, and a mean average precision of 78.03% with an inference speed of 13 ms per image. Importantly, the proposed method does not rely on personal information, mobile phones, or wearable devices, avoiding the limitations of existing contact tracing schemes and providing significant implications for public health in the post-COVID-19 era.

Identification of key pathways, genes and immune cell infiltration in hypoxia of high-altitude acclimatization via meta-analysis and integrated bioinformatics analysis.

Background: For individuals acutely exposed to high-altitude regions, environmental hypobaric hypoxia induces several physiological or pathological responses, especially immune dysfunction. Therefore, hypoxia is a potentially life-threatening factor, which has closely related to high-altitude acclimatization. However, its specific molecular mechanism is still unclear. Methods: The four expression profiles about hypoxia and high altitude were downloaded from the Gene Expression Omnibus database in this study. Meta-analysis of GEO datasets was performed by NetworkAnalyst online tool. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO) enrichment analysis, and visualization were performed using R (version 4.1.3) software, respectively. The CIBERSORT analysis was conducted on GSE46480 to examine immune cell infiltration. In addition, we experimentally verified the bioinformatics analysis with qRT-PCR. Results: The meta-analysis identified 358 differentially expressed genes (DEGs), with 209 upregulated and 149 downregulated. DEGs were mostly enriched in biological processes and pathways associated with hypoxia acclimatization at high altitudes, according to both GO and KEGG enrichment analyses. ERH, VBP1, BINP3L, TOMM5, PSMA4, and POLR2K were identified by taking intersections of the DEGs between meta-analysis and GSE46480 and verified by qRT-PCR experiments, which were inextricably linked to hypoxia. Immune infiltration analysis showed significant differences in immune cells between samples at sea level and high altitudes. Conclusion: Identifying the DEGs and pathways will improve our understanding of immune function during high-altitude hypoxia at a molecular level. Targeting hypoxia-sensitive pathways in immune cells is interesting in treating high-altitude sickness. This study provides support for further research on high-altitude acclimatization.

Exploring the Mechanism of Buyang Huanwu Decoction Alleviating Restenosis by Regulating VSMC Phenotype Switching and Proliferation by Network Pharmacology and Molecular Docking.

BACKGROUND: Buyang Huanwu Decoction (BHD) is used to regulate blood circulation and clear collaterals and is widely used in coronary heart disease. However, the active compounds and the mechanism of BHD used to treat restenosis are less understood. OBJECTIVE: The study aimed to explore the potential mechanism of Buyang Huanwu decoction BHD for the treatment of restenosis using network pharmacology and molecular docking experiments. METHODS: The bioactive components of BHD and their corresponding targets were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Encyclopaedia of Traditional Chinese Medicine (ETCM) databases as well as literature. Restenosisassociated therapeutic genes were identified from the OMIM, Drugbank, GEO, and Dis- GeNET databases. Genes related to the vascular smooth muscle cell (VSMC) phenotype were obtained from the gene ontology (GO) database and literature. The core target genes for the drug-disease-VSMC phenotype were identified using the Venn tool and Cytoscape software. Moreover, the "drug-component-target-pathway" network was constructed and analyzed, and pathway enrichment analysis was performed. The connection between the main active components and core targets was analyzed using the AutoDock tool, and PyMOL was used to visualize the results. RESULTS: The "compound-target-disease" network included 80 active ingredients and 599 overlapping targets. Among the bioactive components, quercetin, ligustrazine, ligustilide, hydroxysafflor yellow A, and dihydrocapsaicin had high degree values, and the core targets included TP53, MYC, APP, UBC, JUN, EP300, TGFB1, UBB, SP1, MAPK1, SMAD2, CTNNB1, FOXO3, PIN1, EGR1, TCF4, FOS, SMAD3, and CREBBP. A total of 365 items were obtained from the GO functional enrichment analysis (p < 0.05), whereas the enrichment analysis of the KEGG pathway identified 30 signaling pathways (p < 0.05), which involved the TGF-ß signaling pathway, Wnt signaling pathway, TRAF6-mediated induction of NF-κB and MAPK pathway, TLR7/8 cascade, and others. The molecular docking results revealed quercetin, luteolin, and ligustilide to have good affinity with the core targets MYC and TP53. CONCLUSION: The active ingredients in BHD might act on TP53, MYC, APP, UBC, JUN, and other targets through its active components (such as quercetin, ligustrazine, ligustilide, hydroxysafflor yellow A, and dihydrocapsaicin). This action of BHD may be transmitted via the involvement of multiple signaling pathways, including the TGF-ß signaling pathway, Wnt signaling pathway, TRAF6-mediated induction of NF-κB and MAPK pathway, and TLR7/8 cascade, to treat restenosis by inhibiting the phenotype switching and proliferation of VSMC.

Machine learning assisted coarse-grained molecular dynamics modeling of meso-scale interfacial fluids.

A hallmark of meso-scale interfacial fluids is the multi-faceted, scale-dependent interfacial energy, which often manifests different characteristics across the molecular and continuum scale. The multi-scale nature imposes a challenge to construct reliable coarse-grained (CG) models, where the CG potential function needs to faithfully encode the many-body interactions arising from the unresolved atomistic interactions and account for the heterogeneous density distributions across the interface. We construct the CG models of both single- and two-component polymeric fluid systems based on the recently developed deep coarse-grained potential [Zhang et al., J. Chem. Phys. 149, 034101 (2018)] scheme, where each polymer molecule is modeled as a CG particle. By only using the training samples of the instantaneous force under the thermal equilibrium state, the constructed CG models can accurately reproduce both the probability density function of the void formation in bulk and the spectrum of the capillary wave across the fluid interface. More importantly, the CG models accurately predict the volume-to-area scaling transition for the apolar solvation energy, illustrating the effectiveness to probe the meso-scale collective behaviors encoded with molecular-level fidelity.

Numerical hemolysis performance evaluation of a rotary blood pump under different speed modulation profiles.

Introduction: Speed modulation methods have been studied and even used clinically to create extra pulsation in the blood circulatory system with the assistance of a continuous flow rotary blood pump. However, fast speed variations may also increase the hemolysis potential inside the pump. Methods: This study investigates the hemolysis performance of a ventricular assist rotary blood pump under sinusoidal, square, and triangular wave speed modulation profiles using the computational fluid dynamics (CFD) method. The CFD boundary pressure conditions of the blood pump were obtained by combining simulations with the pump's mathematical model and a complete cardiovascular lumped parameter model. The hemolysis performance of the blood pump was quantified by the hemolysis index (HI) calculated from a Eulerian scalar transport equation. Results: The HI results were obtained and compared with a constant speed condition when the blood pump was run under three speed profiles. The speed modulations were revealed to slightly affect the pump hemolysis, and the hemolysis differences between the different speed modulation profiles were insignificant. Discussion: This study suggests that speed modulations could be a feasible way to improve the flow pulsatility of rotary blood pumps while not increasing the hemolysis performance.

Data-driven construction of stochastic reduced dynamics encoded with non-Markovian features.

One important problem in constructing the reduced dynamics of molecular systems is the accurate modeling of the non-Markovian behavior arising from the dynamics of unresolved variables. The main complication emerges from the lack of scale separations, where the reduced dynamics generally exhibits pronounced memory and non-white noise terms. We propose a data-driven approach to learn the reduced model of multi-dimensional resolved variables that faithfully retains the non-Markovian dynamics. Different from the common approaches based on the direct construction of the memory function, the present approach seeks a set of non-Markovian features that encode the history of the resolved variables and establishes a joint learning of the extended Markovian dynamics in terms of both the resolved variables and these features. The training is based on matching the evolution of the correlation functions of the extended variables that can be directly obtained from the ones of the resolved variables. The constructed model essentially approximates the multi-dimensional generalized Langevin equation and ensures numerical stability without empirical treatment. We demonstrate the effectiveness of the method by constructing the reduced models of molecular systems in terms of both one-dimensional and four-dimensional resolved variables.

The antihyperglycemic effect of pulsed electric field-extracted polysaccharide of Kaempferia elegans officinale on streptozotocin induced diabetic mice.

Kaempferia elegans polysaccharide (KEP) was extracted using a high-voltage pulsed electric field-assisted hot water method. Its physicochemical properties, in vitro activity and hypoglycemic effect was investigated. Experiments were undertaken with diabetic mice models and the potential mechanism of KEP to improve blood glucose levels was unveiled through measurements of relevant indicators in the serum and liver of the mice. Results showed that KEP is mainly composed of glucose, rhamnose, arabinose, and galactose. It has certain DPPH and ABTS free radical scavenging ability and good α-glucosidase inhibitory ability, indicating that KEP has the potential to improve blood glucose levels in diabetes patients. The experimental results of KEP treatment on mice showed that KEP could control the continuous increase of fasting blood glucose levels. The potential mechanisms behind this blood glucose level control composes of (1) increasing the glucokinase and C peptide levels and decreasing Glucose-6-phosphatase content for improving key enzyme activity in the glucose metabolism pathway. This promotes the consumption of blood glucose during glycolysis, thereby inhibiting the production of endogenous glucose in gluconeogenesis pathway; (2) reducing triglyceride, total cholesterol, low density lipoprotein cholesterol, and increasing high density lipoprotein cholesterol content, for regulating blood lipid indicators to normal levels; and (3) by improving the activities of catalase, glutathione peroxidase, and antioxidant enzymes superoxide dismutase for further improving the antioxidant defense system in the body to reduce blood glucose.