Rational fusion design inspired by cell-penetrating peptide: SS31/S-14 G Humanin hybrid peptide with amplified multimodal efficacy and bio-permeability for the treatment of Alzheimer's disease.

Alzheimer's disease is a neurodegenerative disease induced by multiple interconnected mechanisms. Peptide drug candidates with multi-modal efficacy generated from fusion strategy are suitable for addressing multi-facet pathology. However, clinical translation of peptide drugs is greatly hampered by their low permeability into brain. Herein, a hybrid peptide HNSS is generated by merging two therapeutic peptides (SS31 and S-14 G Humanin (HNG)), using a different approach from the classical shuttle-therapeutic peptide conjugate design. HNSS demonstrated increased bio-permeability, with a 2-fold improvement in brain distribution over HNG, thanks to its structure mimicking the design of signal peptide-derived cell-penetrating peptides. HNSS efficiently alleviated mitochondrial dysfunction through the combined effects of mitochondrial targeting, ROS scavenging and p-STAT3 activation. Meanwhile, HNSS with increased Aß affinity greatly inhibited Aß oligomerization/fibrillation, and interrupted Aß interaction with neuron/microglia by reducing neuronal mitochondrial Aß deposition and promoting microglial phagocytosis of Aß. In 3× Tg-AD transgenic mice, HNSS treatment efficiently inhibited brain neuron loss and improved the cognitive performance. This work validates the rational fusion design-based strategy for bio-permeability improvement and efficacy amplification, providing a paradigm for developing therapeutic peptide candidates against neurodegenerative disease.

Predicting fracture risk for elderly osteoporosis patients by hybrid machine learning model.

Background and Objective: Osteoporotic fractures significantly impact individuals's quality of life and exert substantial pressure on the social pension system. This study aims to develop prediction models for osteoporotic fracture and uncover potential risk factors based on Electronic Health Records (EHR). Methods: Data of patients with osteoporosis were extracted from the EHR of Xinhua Hospital (July 2012-October 2017). Demographic and clinical features were used to develop prediction models based on 12 independent machine learning (ML) algorithms and 3 hybrid ML models. To facilitate a nuanced interpretation of the results, a comprehensive importance score was conceived, incorporating various perspectives to effectively discern and mine critical features from the data. Results: A total of 8530 patients with osteoporosis were included for analysis, of which 1090 cases (12.8%) were fracture patients. The hybrid model that synergistically combines the Support Vector Machine (SVM) and XGBoost algorithms demonstrated the best predictive performance in terms of accuracy and precision (above 90%) among all benchmark models. Blood Calcium, Alkaline phosphatase (ALP), C-reactive Protein (CRP), Apolipoprotein A/B ratio and High-density lipoprotein cholesterol (HDL-C) were statistically found to be associated with osteoporotic fracture. Conclusions: The hybrid machine learning model can be a reliable tool for predicting the risk of fracture in patients with osteoporosis. It is expected to assist clinicians in identifying high-risk fracture patients and implementing early interventions.

Precise Modulation of Pericyte Dysfunction by a Multifunctional Nanoprodrug to Ameliorate Alzheimer's Disease.

Pericyte dysfunction severely undermines cerebrovascular integrity and exacerbates neurodegeneration in Alzheimer's disease (AD). However, pericyte-targeted therapy is a yet-untapped frontier for AD. Inspired by the elevation of vascular cell adhesion molecule-1 (VCAM-1) and reactive oxygen species (ROS) levels in pericyte lesions, we fabricated a multifunctional nanoprodrug by conjugating the hybrid peptide VLC, a fusion of the VCAM-1 high-affinity peptide VHS and the neuroprotective apolipoprotein mimetic peptide COG1410, to curcumin (Cur) through phenylboronic ester bond (VLC@Cur-NPs) to alleviate complex pericyte-related pathological changes. Importantly, VLC@Cur-NPs effectively homed to pericyte lesions via VLC and released their contents upon ROS stimulation to maximize their regulatory effects. Consequently, VLC@Cur-NPs markedly increased pericyte regeneration to form a positive feedback loop and thus improved neurovascular function and ultimately alleviated memory defects in APP/PS1 transgenic mice. We present a promising therapeutic strategy for AD that can precisely modulate pericytes and has the potential to treat other cerebrovascular diseases.

Application and prospect of BSA method based on bibliometrics in crop breeding.

In order to understand the progress and frontier in the application of BSA(bulked segregant analysis) method in crop breeding and to reflect objectively the contribution of different countries, institutions and researchers in this field at home and abroad, this study analyzed 2111 items in the WOS (Web of Science) database from 2000 to 2023 and 446 items in the CNKI (China National through Knowledge Infrastructure) database from 2003 to 2023, regarding the researches of the application of BSA in crop breeding, basing on bibliometric analysis methods using CiteSpace software including keyword co-occurrence analysis, highlight word analysis, keyword clustering analysis, clustering timeline analysis and author co-citation. The results showed that there was an consistent increasing trend in the publication number of the application of BSA in crop breeding both in the domestic and foreign journals year by year. Ranking of the top countries according to the number of publications was China, the United States and India. The Huazhong Agricultural University displayed the highest number of publications in the CNKI database, while the Chinese Academy of Agricultural Sciences was found to have the highest number of publications in the WOS database. The published articles related to the application of BSA in crop breeding abroad mainly focused on the disciplines such as plant science, agronomy, horticulture and genetics, while those in China mainly concentrated on such disciplines as plant science, plant protection, horticulture and biology. The top three authors in terms of influence in the field of appling BSA in crop breeding were Michelmore RW, Kosambi DD and Li H, while Michelmore RW, Lander ES and Li H had closer cooperations with other authors. The top three crops relating to the studies of BSA were rice(Oryza sativa), soybean(Glycine max), corn(Zea mays L.) with the hot spot traits of disease resistance and plant height domestically. The top three crops involving the studies of BSA were rice, Arabidopsis thaliana and wheat(Triticum aestivum L.) with hot spot traits of disease resistance abroad. Up to now, BSA was mainly used to localize and functionally verify the candidate genes linking target traits and the mutated genes in crops in the domestical documents, while the foreign published studies based on BSA were mainly focused on the fine mapping and functional verification of target trait genes aiming at the revelation of genetic mechanisms in crops. Research frontier analysis indicated that rice, peanuts(Arachis hypogaea L.), upland cotton(Gossypium hirsutum L.) would be the main objects of studies concerning application of BSA in crop breeding with the hot topics of crop mutants and crop metabolites in the future.

Multidimensional autophagy nano-regulator boosts Alzheimer's disease treatment by improving both extra/intraneuronal homeostasis.

Intraneuronal dysproteostasis and extraneuronal microenvironmental abnormalities in Alzheimer's disease (AD) collectively culminate in neuronal deterioration. In the context of AD, autophagy dysfunction, a multi-link obstacle involving autophagy downregulation and lysosome defects in neurons/microglia is highly implicated in intra/extraneuronal pathological processes. Therefore, multidimensional autophagy regulation strategies co-manipulating "autophagy induction" and "lysosome degradation" in dual targets (neuron and microglia) are more reliable for AD treatment. Accordingly, we designed an RP-1 peptide-modified reactive oxygen species (ROS)-responsive micelles (RT-NM) loading rapamycin or gypenoside XVII. Guided by RP-1 peptide, the ligand of receptor for advanced glycation end products (RAGE), RT-NM efficiently targeted neurons and microglia in AD-affected region. This nano-combination therapy activated the whole autophagy-lysosome pathway by autophagy induction (rapamycin) and lysosome improvement (gypenoside XVII), thus enhancing autophagic degradation of neurotoxic aggregates and inflammasomes, and promoting Aß phagocytosis. Resultantly, it decreased aberrant protein burden, alleviated neuroinflammation, and eventually ameliorated memory defects in 3 × Tg-AD transgenic mice. Our research developed a multidimensional autophagy nano-regulator to boost the efficacy of autophagy-centered AD therapy.

Dual Enzyme Cascade-Activated Popcorn-Like Nanoparticles Efficiently Remodeled Stellate Cells to Alleviate Pancreatic Desmoplasia.

In pancreatic cancer, excessive desmoplastic stroma severely impedes drug access to tumor cells. By reverting activated pancreatic stellate cells (PSCs) to quiescence, all-trans retinoic acid (ATRA) can attenuate their stromal synthesis and remodel the tumor-promoting microenvironment. However, its modulatory effects have been greatly weakened due to its limited delivery to PSCs. Therefore, we constructed a tripeptide RFC-modified gelatin/oleic acid nanoparticle (RNP@ATRA), which delivered ATRA in an enzyme-triggered popcorn-like manner and effectively resolved the delivery challenges. Specifically, surface RFC was cleaved by aminopeptidase N (APN) on the tumor endothelium to liberate l-arginine, generating nitric oxide (NO) for tumor-specific vasodilation. Then, massive nanoparticles were pushed from the vessels into tumors, showing 5.1- and 4.0-fold higher intratumoral accumulation than free ATRA and APN-inert nanoparticles, respectively. Subsequently, in the interstitium, matrix metalloproteinase-2-induced gelatin degradation caused RNP@ATRA to rapidly release ATRA, promoting its interstitial penetration and PSC delivery. Thus, activated PSCs were efficiently reverted to quiescence, and stroma secretion and vascular compression were reduced, thereby enhancing intratumoral delivery of small-molecule or nanosized chemotherapeutics. Ultimately, RNP@ATRA combined with chemotherapeutics markedly suppressed tumor growth and metastasis without causing additional toxicities. Overall, this work provides a potential nanoplatform for the efficient delivery of PSC-modifying agents in pancreatic cancer and other stroma-rich tumors.

Enhancement of Microglia Functions by Developed Nano-Immuno-Synergist to Ameliorate Immunodeficiency for Malignant Glioma Treatment.

Resident microglia are key factors in mediating immunity against brain tumors, but the microglia in malignant glioma are functionally impaired. Little immunotherapy is explored to restore microglial function against glioma. Herein, oleanolic acid (OA) (microglia "restorer") and D PPA-1 peptide (immune checkpoint blockade) are integrated on a nano-immuno-synergist (D PAM@OA) to work coordinately. The self-assembled OA core is coated with macrophage membrane for efficient blood-brain barrier penetration and microglia targeting, on which D PPA-1 peptide is attached via acid-sensitive bonds for specific release in tumor microenvironment. With the enhanced accumulation of the dual drugs in their respective action sites, D PAM@OA effectively promotes the recruitment and activation of effector T cells by inhibiting aberrant activation of Signal transducer and activator of transcription (STAT-3) pathway in microglia, and assists activated effector T cells in killing tumor cells by blocking elevated immune checkpoint proteins in malignant glioma. Eventually, as adjuvant therapy, the rationally designed nano-immuno-synergist hinders malignant glioma progression and recurrence with or without temozolomide. The work demonstrates the feasibility of a nano-formulation for microglia-based immunotherapy, which may provide a new direction for the treatment of brain tumors.

Effects of N and P addition on nutrient and stoichiometry of rhizosphere and non-rhizosphere soils of alfalfa in alkaline soil.

Nitrogen (N) and phosphorus (P) are important nutrients for plant growth and development. Soil alkalization is one of the main obstacles limiting the sustainable development of agriculture. Northern Ningxia is located in the arid and semi-arid region, with serious soil alkalinization. Alfalfa has the advantages of strong saline-alkali tolerance, high yield, high quality, and wide adaptability. It is an important forage for the comprehensive improvement and rational utilization of saline-alkali land and has great significance for solving land resource shortages, improving the ecological environment, and ensuring food security. It is important to study soil organic carbon (SOC), total N (TN), total P (TP), and stoichiometry of the rhizosphere and non-rhizosphere of alfalfa in alkaline soils. Therefore, N and P were added to the alkaline alfalfa field in the Yinchuan Plain of Hetao Basin in our experiment. Six treatments were set up, i.e., N-free (WN), medium N (MN) for 90 kg/hm2, high N (HN) for 180 kg/hm2, P-free (WP), medium P (MP) for 135 kg/hm2, and high P (HP) for 270 kg/hm2. The results are as follows: The N addition promotes SOC and TN but inhibits TP, and P addition promotes SOC and TP but inhibits TN of three soil layers. The N addition decreases C/N but increases C/P and N/P, while the P addition increases C/N but decreases C/P and N/P of three soil layers. The SOC, TN, TP, C/N, C/P, and N/P under HN and HP treatment reach the significance level (P < 0.05). Appropriate additions of N and P can improve rhizosphere and non-rhizosphere nutrients and stoichiometric structure, facilitating absorption and utilization by alfalfa and improve the production potential of alfalfa in alkaline soil.

Widely Targeted HPLC-MS/MS Metabolomics Analysis Reveals Natural Metabolic Insights in Insects.

Insect metabolites play vital roles in regulating the physiology, behavior, and numerous adaptations of insects, which has contributed to them becoming the largest class of Animalia. However, systematic metabolomics within the insects is still unclear. The present study performed a widely targeted metabolomics analysis based on the HPLC-MS/MS technology to construct a novel integrated metabolic database presenting comprehensive multimetabolite profiles from nine insect species across three metamorphosis types. A total of 1442 metabolites were identified, including amino acids and their metabolites, organic acids and their derivatives, fatty acids (FAs), glycerophospholipids (GPs), nucleotides and their metabolites, and benzene and its substituted derivatives. Among them, 622 metabolites were used to generate a 0 and 1 matrix based on their presence or absence, and these metabolites were enriched in arachidonic acid metabolism, tyrosine metabolism, phenylalanine metabolism, and insect hormone biosynthesis pathways. Our study revealed that there is a high coincidence between the evolutionary relationships of the species and the hierarchical cluster based on the types of metabolites, while the quantities of the metabolites show a high diversity among species. The metabolome of the nine representative insects provides an important platform for implementing the analysis of insect systemic metabolites and biological events at the metabolic level.

Medium-chain triglyceride-stabilized docetaxel-loaded HSA nanoparticles effectively inhibited metastatic non-small cell lung cancer.

Metastatic non-small cell lung cancer (NSCLC) is refractory with a very poor prognosis. Docetaxel (DTX) injection (Taxotere®) has been approved for the treatment of locally advanced or metastatic NSCLC. However, its clinical application is restricted by severe adverse effects and non-selective tissue distribution. In this study, we successfully developed DTX-loaded human serum albumin (HSA) nanoparticles (DNPs) with modified Nab technology, by introducing medium-chain triglyceride (MCT) as a stabilizer. The optimized formulation had a particle size of approximately 130 nm and a favorable stabilization time of more than 24 h. DNPs dissociated in circulation in a concentration-dependent manner and slowly released DTX. Compared with DTX injection, DNPs were more effectively taken up by NSCLC cells, thus exerting stronger inhibitory effects on their proliferation, adhesion, migration, and invasion. In addition, DNPs showed prolonged blood retention and increased tumor accumulation relative to DTX injection. Ultimately, DNPs produced more potent inhibitory effects on primary or metastatic tumor foci than DTX injections but caused markedly lower organ toxicity and hematotoxicity. Overall, these results support that DNPs hold great potential for the treatment of metastatic NSCLC in clinical.

Effective Value Analysis of Fuzzy Similarity Relation in HQSS for Efficient Granulation.

Hierarchical quotient space structure (HQSS), as a typical description of granular computing (GrC), focuses on hierarchically granulating fuzzy data and mining hidden knowledge. The key step of constructing HQSS is to transform the fuzzy similarity relation into fuzzy equivalence relation. However, on one hand, the transformation process has high time complexity. On the other hand, it is difficult to mine knowledge directly from fuzzy similarity relation due to its information redundancy, i.e., sparsity of effective information. Therefore, this article mainly focuses on proposing an efficient granulation approach for constructing HQSS by quickly extracting the effective value of fuzzy similarity relation. First, the effective value and effective position of fuzzy similarity relation are defined according to whether they could be retained in fuzzy equivalence relation. Second, the number and composition of effective values are presented to confirm that which elements are effective values. Based on these above theories, redundant information and sparse effective information in fuzzy similarity relation could be completely distinguished. Next, both isomorphism and similarity between two fuzzy similarity relations are researched based on the effective value. The isomorphism between two fuzzy equivalence relations is discussed based on the effective value. Then, the algorithm with low time complexity for extracting effective values of fuzzy similarity relation is introduced. On the basis, the algorithm for constructing HQSS is presented to realize efficient granulation of fuzzy data. The proposed algorithms could accurately extract effective information from the fuzzy similarity relation and construct the same HQSS with the fuzzy equivalence relation while greatly reducing the time complexity. Finally, relevant experiments on 15 UCI datasets, 3 UKB datasets, and 5 image datasets are shown and analyzed to verify the effectiveness and efficiency of the proposed algorithm.

Brain-neuron targeted nanoparticles for peptide synergy therapy at dual-target of Alzheimer's disease.

Since the complex interactions of multiple mechanisms involved in Alzheimer's disease (AD) preclude the monotherapeutic approaches from clinical application, combination therapy has become an attractive strategy for AD treatment. However, to be emphasized, the realization of the edges of combination therapy greatly depends on the reasonable choice of targets and the rational design of combination scheme. Acknowledgedly, amyloid plaques and hyperphosphorylated tau (p-tau) are two main hallmarks in AD with close pathological correlations, implying the hopeful prospect of combined intervention in them for AD treatment. Herein, we developed the nano-combination system, neuron-targeting PEG-PLA nanoparticles (CT-NP) loading two peptide drugs H102, a ß-sheet breaker acting on Aß, and NAP, a microtubule stabilizer acting on p-tau. Compared with free peptide combination, nano-combination system partly aligned the in vivo behaviors of combined peptides and enhanced peptide accumulation in lesion neurons by the guidance of targeting peptide CGN and Tet1, facilitating the therapeutic performance of peptide combination. Further, to maximize the therapeutic potential of nano-combination system, the combination ratio and mode were screened by the quantitative evaluation with combination index and U test, respectively, in vitro and in vivo. The results showed that the separated-loading CT-NP at the combination molar ratio of 2:1 (H102:NAP), CT-NP/H102 + CT-NP/NAP(2:1), generated the strongest synergistic therapeutic effects on Aß, p-tau and their linkage, and effectually prevented neuroinflammation, reversed the neuronal damage and restored cognitive performance in 3 × Tg-AD transgenic mice. Our studies provide critical data on the effectiveness of nano-combination therapy simultaneously intervening in Aß and p-tau, confirming the promising application of nano-combination strategy in AD treatment.

Egfr signaling promotes juvenile hormone biosynthesis in the German cockroach.

BACKGROUND: In insects, an interplay between the activities of distinct hormones, such as juvenile hormone (JH) and 20-hydroxyecdysone (20E), regulates the progression through numerous life history hallmarks. As a crucial endocrine factor, JH is mainly synthesized in the corpora allata (CA) to regulate multiple physiological and developmental processes, including molting, metamorphosis, and reproduction. During the last century, significant progress has been achieved in elucidating the JH signal transduction pathway, while less progress has been made in dissecting the regulatory mechanism of JH biosynthesis. Previous work has shown that receptor tyrosine kinase (RTK) signaling regulates hormone biosynthesis in both insects and mammals. Here, we performed a systematic RNA interference (RNAi) screening to identify RTKs involved in regulating JH biosynthesis in the CA of adult Blattella germanica females. RESULTS: We found that the epidermal growth factor receptor (Egfr) is required for promoting JH biosynthesis in the CA of adult females. The Egf ligands Vein and Spitz activate Egfr, followed by Ras/Raf/ERK signaling, and finally activation of the downstream transcription factor Pointed (Pnt). Importantly, Pnt induces the transcriptional expression of two key enzyme-encoding genes in the JH biosynthesis pathway: juvenile hormone acid methyltransferase (JHAMT) and methyl farnesoate epoxidase (CYP15A1). Dual-luciferase reporter assay shows that Pnt is able to activate a promoter region of Jhamt. In addition, electrophoretic mobility shift assay confirms that Pnt directly binds to the - 941~ - 886 nt region of the Jhamt promoter. CONCLUSIONS: This study reveals the detailed molecular mechanism of Egfr signaling in promoting JH biosynthesis in the German cockroach, shedding light on the intricate regulation of JH biosynthesis during insect development.

Combination of Se-methylselenocysteine, D-α-tocopheryl succinate, ß-carotene, and L-lysine can prevent cancer metastases using as an adjuvant therapy.

OBJECTIVES: Primary tumor treatment through surgical resection and adjuvant therapy has been extensively studied, but there is a lack of effective strategies and drugs for the treatment of tumor metastases. Here, we describe a functional product based on a combination of compounds, which can be used as an adjuvant therapy and has well-known mechanisms for inhibiting cancer metastases, improving anti-cancer treatment, and enhancing immunity and antioxidant capacity. Our designed combination, named MVBL, consists of four inexpensive compounds: L-selenium-methylselenocysteine (MSC), D-|α|-tocopheryl succinic acid (VES), ß|-carotene (ß|-Ca), and L-lysine (Lys). METHODS: The effects of MVBL on cell viability, cell cycle, cell apoptosis, cell migration, cell invasion, reactive oxygen species (ROS), and paclitaxel (PTX)-combined treatment were studied in vitro. The inhibition of tumor metastasis, antioxidation, and immune enhancement capacity of MVBL were determined in vivo. RESULTS: MVBL exhibited higher toxicity to tumor cells than to normal cells. It did not significantly affect the cell cycle of cancer cells, but increased their apoptosis. Wound healing, adhesion, and transwell assays showed that MVBL significantly inhibited tumor cell migration, adhesion, and invasion. MVBL sensitized MDA-MB-231 breast cancer cells to PTX, indicating that it can be used as an adjuvant to enhance the therapeutic effect of chemotherapy drugs. In mice, experimental data showed that MVBL inhibited tumor metastasis, prolonged their survival time, and enhanced their antioxidant capacity and immune function. CONCLUSIONS: This study revealed the roles of MVBL in improving immunity and antioxidation, preventing tumor growth, and inhibiting metastasis in vitro and in vivo. MVBL may be used as an adjuvant drug in cancer therapy for improving the survival and quality of life of cancer patients.

Cholinergic Neuron Targeting Nanosystem Delivering Hybrid Peptide for Combinatorial Mitochondrial Therapy in Alzheimer's Disease.

Mitochondrial dysfunction in neurons has recently become a promising therapeutic target for Alzheimer's disease (AD). Regulation of dysfunctional mitochondria through multiple pathways rather than antioxidation monotherapy indicates synergistic therapeutic effects. Therefore, we developed a multifunctional hybrid peptide HNSS composed of antioxidant peptide SS31 and neuroprotective peptide S14G-Humanin. However, suitable peptide delivery systems with excellent loading capacity and effective at-site delivery are still absent. Herein, the nanoparticles made of citraconylation-modified poly(ethylene glycol)-poly(trimethylene carbonate) polymer (PEG-PTMC(Cit)) exhibited desirable loading of HNSS peptide through electrostatic interactions. Meanwhile, based on fibroblast growth factor receptor 1(FGFR1) overexpression in both the blood-brain barrier and cholinergic neuron, an FGFR1 ligand-FGL peptide was modified on the nanosystem (FGL-NP(Cit)/HNSS) to achieve 4.8-fold enhanced accumulation in brain with preferred distribution into cholinergic neurons in the diseased region. The acid-sensitive property of the nanosystem facilitated lysosomal escape and intracellular drug release by charge switching, resulting in HNSS enrichment in mitochondria through directing of the SS31 part. FGL-NP(Cit)/HNSS effectively rescued mitochondria dysfunction via the PGC-1α and STAT3 pathways, inhibited Aß deposition and tau hyperphosphorylation, and ameliorated memory defects and cholinergic neuronal damage in 3xTg-AD mice. The work provides a potential platform for targeted cationic peptide delivery, harboring utility for peptide therapy in other neurodegenerative diseases.

Signaling repurposable drug combinations against COVID-19 by developing the heterogeneous deep herb-graph method.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has spurred a boom in uncovering repurposable existing drugs. Drug repurposing is a strategy for identifying new uses for approved or investigational drugs that are outside the scope of the original medical indication. MOTIVATION: Current works of drug repurposing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are mostly limited to only focusing on chemical medicines, analysis of single drug targeting single SARS-CoV-2 protein, one-size-fits-all strategy using the same treatment (same drug) for different infected stages of SARS-CoV-2. To dilute these issues, we initially set the research focusing on herbal medicines. We then proposed a heterogeneous graph embedding method to signaled candidate repurposing herbs for each SARS-CoV-2 protein, and employed the variational graph convolutional network approach to recommend the precision herb combinations as the potential candidate treatments against the specific infected stage. METHOD: We initially employed the virtual screening method to construct the 'Herb-Compound' and 'Compound-Protein' docking graph based on 480 herbal medicines, 12,735 associated chemical compounds and 24 SARS-CoV-2 proteins. Sequentially, the 'Herb-Compound-Protein' heterogeneous network was constructed by means of the metapath-based embedding approach. We then proposed the heterogeneous-information-network-based graph embedding method to generate the candidate ranking lists of herbs that target structural, nonstructural and accessory SARS-CoV-2 proteins, individually. To obtain precision synthetic effective treatments forvarious COVID-19 infected stages, we employed the variational graph convolutional network method to generate candidate herb combinations as the recommended therapeutic therapies. RESULTS: There were 24 ranking lists, each containing top-10 herbs, targeting 24 SARS-CoV-2 proteins correspondingly, and 20 herb combinations were generated as the candidate-specific treatment to target the four infected stages. The code and supplementary materials are freely available at https://github.com/fanyang-AI/TCM-COVID19.

Precise gene delivery systems with detachable albumin shell remodeling dysfunctional microglia by TREM2 for treatment of Alzheimer's disease.

Intervention of the over-activated microglia-aggravated neuroinflammation represents a promising therapeutic strategy for Alzheimer's disease (AD). Upregulation of triggering receptor expressed on myeloid cells-2 (TREM2) attenuates the neuroinflammatory processes and normalizes the dysfunctional microglia. However, Trem2-gene therapy for AD by the effective non-invasive delivery systems is unexploited. Herein, we report the microglia-targeted gene delivery systems (PHSA@PF/pTREM2) composed of a core of fluorinated polyethylenimine condensing the TREM2-encoding plasmid (PF/pTREM2) and a shell of human serum albumin conjugated with both cis-aconitic anhydride and neural cell adhesion molecule-mimetic peptide P2 (PHSA). Thanks to the shedding effect of the albumin coated, PHSA@PF/pTREM2 exhibit prolonged blood circulation and low cytotoxicity. PHSA@PF/pTREM2 achieve brain accumulation as high as 2.17% injected dose per gram of brain and the microglial-targeting effect (targeting specificity of 41.9%) via the systemic administration. The nanocomplexes can be detached PHSA-shell in the acidic endo-lysosomes via the cleavage of cis-aconitic amide bond, resulting in PF/pTREM2 exposure for efficient endo-lysosomal escape and gene transfection. PHSA@PF/pTREM2 upregulate the TREM2 level and regulate microglial polarization toward M2-phenotype for remodeling the inflammatory microenvironment and enhanced Aß clearance, leading to an improvement of cognitive performance in APP/PS1 mice. This work provides a promising gene delivery platform to reverse dysfunctional microglia for AD therapy.

Modulating autophagic flux via ROS-responsive targeted micelles to restore neuronal proteostasis in Alzheimer's disease.

Compromised autophagy and defective lysosomal clearance significantly contribute to impaired neuronal proteostasis, which represents a hallmark of Alzheimer's disease (AD) and other age-related neurodegenerative disorders. Growing evidence has implicated that modulating autophagic flux, instead of inducing autophagosome formation alone, would be more reliable to rescue neuronal proteostasis. Concurrently, selectively enhancing drug concentrations in the leision areas, instead of the whole brain, will maximize therapeutic efficacy while reduing non-selective autophagy induction. Herein, we design a ROS-responsive targeted micelle system (TT-NM/Rapa) to enhance the delivery efficiency of rapamycin to neurons in AD lesions guided by the fusion peptide TPL, and facilitate its intracellular release via ROS-mediated disassembly of micelles, thereby maximizing autophagic flux modulating efficacy of rapamycin in neurons. Consequently, it promotes the efficient clearance of intracellular neurotoxic proteins, ß-amyloid and hyperphosphorylated tau proteins, and ameliorates memory defects and neuronal damage in 3 × Tg-AD transgenic mice. Our studies demonstrate a promising strategy to restore autophagic flux and improve neuronal proteostasis by rationally-engineered nano-systems for delaying the progression of AD.

Optimal Scale Combination Selection Integrating Three-Way Decision With Hasse Diagram.

Multi-scale decision system (MDS) is an effective tool to describe hierarchical data in machine learning. Optimal scale combination (OSC) selection and attribute reduction are two key issues related to knowledge discovery in MDSs. However, searching for all OSCs may result in a combinatorial explosion, and the existing approaches typically incur excessive time consumption. In this study, searching for all OSCs is considered as an optimization problem with the scale space as the search space. Accordingly, a sequential three-way decision model of the scale space is established to reduce the search space by integrating three-way decision with the Hasse diagram. First, a novel scale combination is proposed to perform scale selection and attribute reduction simultaneously, and then an extended stepwise optimal scale selection (ESOSS) method is introduced to quickly search for a single local OSC on a subset of the scale space. Second, based on the obtained local OSCs, a sequential three-way decision model of the scale space is established to divide the search space into three pair-wise disjoint regions, namely the positive, negative, and boundary regions. The boundary region is regarded as a new search space, and it can be proved that a local OSC on the boundary region is also a global OSC. Therefore, all OSCs of a given MDS can be obtained by searching for the local OSCs on the boundary regions in a step-by-step manner. Finally, according to the properties of the Hasse diagram, a formula for calculating the maximal elements of a given boundary region is provided to alleviate space complexity. Accordingly, an efficient OSC selection algorithm is proposed to improve the efficiency of searching for all OSCs by reducing the search space. The experimental results demonstrate that the proposed method can significantly reduce computational time.

Neuroprosthetic baroreflex controls haemodynamics after spinal cord injury.

Spinal cord injury (SCI) induces haemodynamic instability that threatens survival1-3, impairs neurological recovery4,5, increases the risk of cardiovascular disease6,7, and reduces quality of life8,9. Haemodynamic instability in this context is due to the interruption of supraspinal efferent commands to sympathetic circuits located in the spinal cord10, which prevents the natural baroreflex from controlling these circuits to adjust peripheral vascular resistance. Epidural electrical stimulation (EES) of the spinal cord has been shown to compensate for interrupted supraspinal commands to motor circuits below the injury11, and restored walking after paralysis12. Here, we leveraged these concepts to develop EES protocols that restored haemodynamic stability after SCI. We established a preclinical model that enabled us to dissect the topology and dynamics of the sympathetic circuits, and to understand how EES can engage these circuits. We incorporated these spatial and temporal features into stimulation protocols to conceive a clinical-grade biomimetic haemodynamic regulator that operates in a closed loop. This 'neuroprosthetic baroreflex' controlled haemodynamics for extended periods of time in rodents, non-human primates and humans, after both acute and chronic SCI. We will now conduct clinical trials to turn the neuroprosthetic baroreflex into a commonly available therapy for people with SCI.