Predicting herb-disease associations using network-based measures in human protein interactome.

BACKGROUND: Natural herbs are frequently used to treat diseases or to relieve symptoms in many countries. Moreover, as their safety has been proven for a long time, they are considered as main sources of new drug development. However, in many cases, the herbs are still prescribed relying on ancient records and/or traditional practices without scientific evidences. More importantly, the medicinal efficacy of the herbs has to be evaluated in the perspective of MCMT (multi-compound multi-target) effects, but most efforts focus on identifying and analyzing a single compound experimentally. To overcome these hurdles, computational approaches which are based on the scientific evidences and are able to handle the MCMT effects are needed to predict the herb-disease associations. RESULTS: In this study, we proposed a network-based in silico method to predict the herb-disease associations. To this end, we devised a new network-based measure, WACP (weighted average closest path length), which not only quantifies proximity between herb-related genes and disease-related genes but also considers compound compositions of each herb. As a result, we confirmed that our method successfully predicts the herb-disease associations in the human protein interactome (AUROC = 0.777). In addition, we observed that our method is superior than the other simple network-based proximity measures (e.g. average shortest and closest path length). Additionally, we analyzed the associations between Brassica oleracea var. italica and its known associated diseases more specifically as case studies. Finally, based on the prediction results of the WACP, we suggested novel herb-disease pairs which are expected to have potential relations and their literature evidences. CONCLUSIONS: This method could be a promising solution to modernize the use of the natural herbs by providing the scientific evidences about the molecular associations between the herb-related genes targeted by multiple compounds and the disease-related genes in the human protein interactome.

Normalization of RNA-Seq data using adaptive trimmed mean with multi-reference.

The normalization of RNA sequencing data is a primary step for downstream analysis. The most popular method used for the normalization is the trimmed mean of M values (TMM) and DESeq. The TMM tries to trim away extreme log fold changes of the data to normalize the raw read counts based on the remaining non-deferentially expressed genes. However, the major problem with the TMM is that the values of trimming factor M are heuristic. This paper tries to estimate the adaptive value of M in TMM based on Jaeckel's Estimator, and each sample acts as a reference to find the scale factor of each sample. The presented approach is validated on SEQC, MAQC2, MAQC3, PICKRELL and two simulated datasets with two-group and three-group conditions by varying the percentage of differential expression and the number of replicates. The performance of the present approach is compared with various state-of-the-art methods, and it is better in terms of area under the receiver operating characteristic curve and differential expression.

The dysadherin/FAK axis promotes individual cell migration in colon cancer.

Dysregulation of cancer cell motility is a key driver of invasion and metastasis. High dysadherin expression in cancer cells is correlated with invasion and metastasis. Here, we found the molecular mechanism by which dysadherin regulates the migration and invasion of colon cancer (CC). Comprehensive analysis using single-cell RNA sequencing data from CC patients revealed that high dysadherin expression in cells is linked to cell migration-related gene signatures. We confirmed that the deletion of dysadherin in tumor cells hindered local invasion and distant migration using in vivo tumor models. In this context, by performing cell morphological analysis, we found that aberrant cell migration resulted from impaired actin dynamics, focal adhesion turnover and protrusive structure formation upon dysadherin expression. Mechanistically, the activation of focal adhesion kinase (FAK) was observed in dysadherin-enriched cells. The dysadherin/FAK axis enhanced cell migration and invasion by activating the FAK downstream cascade, which includes the Rho family of small GTPases. Overall, this study illuminates the role of dysadherin in modulating cancer cell migration by forcing actin dynamics and protrusive structure formation via FAK signaling, indicating that targeting dysadherin may be a potential therapeutic strategy for CC patients.

STAT3 Decoy Oligodeoxynucleotides Suppress Liver Inflammation and Fibrosis in Liver Cancer Cells and a DDC-Induced Liver Injury Mouse Model.

Liver damage caused by various factors results in fibrosis and inflammation, leading to cirrhosis and cancer. Fibrosis results in the accumulation of extracellular matrix components. The role of STAT proteins in mediating liver inflammation and fibrosis has been well documented; however, approved therapies targeting STAT3 inhibition against liver disease are lacking. This study investigated the anti-fibrotic and anti-inflammatory effects of STAT3 decoy oligodeoxynucleotides (ODN) in hepatocytes and liver fibrosis mouse models. STAT3 decoy ODN were delivered into cells using liposomes and hydrodynamic tail vein injection into 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC)-fed mice in which liver injury was induced. STAT3 target gene expression changes were verified using qPCR and Western blotting. Liver tissue fibrosis and bile duct proliferation were assessed in animal experiments using staining techniques, and macrophage and inflammatory cytokine distribution was verified using immunohistochemistry. STAT3 decoy ODN reduced fibrosis and inflammatory factors in liver cancer cell lines and DDC-induced liver injury mouse model. These results suggest that STAT3 decoy ODN may effectively treat liver fibrosis and must be clinically investigated.

Slow gut transit increases the risk of Alzheimer's disease: An integrated study of the bi-national cohort in South Korea and Japan and Alzheimer's disease model mice.

INTRODUCTION: Although the association between Alzheimer's disease (AD) and constipation is controversial, its causality and underlying mechanisms remain unknown. OBJECTIVES: To investigate the potential association between slow gut transit and AD using epidemiological data and a murine model. METHODS: We conducted a bi-national cohort study in South Korea (discovery cohort, N=3,130,193) and Japan (validation cohort, N=4,379,285) during the pre-observation period to determine the previous diagnostic history (2009-2010) and the follow-up period (2011-2021). To evaluate the causality, we induced slow gut transit using loperamide in 5xFAD transgenic mice. Changes in amyloid-beta (Aß) and other markers were examined using ELISA, qRT-PCR, RNA-seq, and behavioral tests. RESULTS: Constipation was associated with an increased risk of AD in the discovery cohort (hazard ratio, 2.04; 95% confidence interval [CI], 2.01-2.07) and the validation cohort (hazard ratio; 2.82; 95% CI, 2.61-3.05). We found that loperamide induced slower gut transit in 5xFAD mice, increased Aß and microglia levels in the brain, increased transcription of genes related to norepinephrine secretion and immune responses, and decreased the transcription of defense against bacteria in the colonic tissue. CONCLUSION: Impaired gut transit may contribute to AD pathogenesis via the gut-brain axis, thus suggesting a cyclical relationship between intestinal barrier disruption and Aß accumulation in the brain. We propose that gut transit or motility may be a modifiable lifestyle factor in the prevention of AD, and further clinical investigations are warranted.

Assessment of effectiveness in stabilization/solidification of arsenic-contaminated soil: long-term leaching test and geophysical measurement.

This study focused on evaluating the effectiveness of stabilizer/binding agents in immobilizing arsenic (As) in contaminated soil using both geochemical and geophysical monitoring methods. The effluent from the stabilizer/binding agent's application and control columns was analyzed, and the status of the columns was monitored using electrical resistivity (ER) and induced polarization (IP) methods. As stabilizers/binder, acid mine drainage sludge (AMDS) and steel slag (SS) were used, which delayed As and Ca leaching time and significantly reduced As leaching amount. Determination coefficients for As and Fe leaching exhibited elevated values (control column, R2 = 0.955; AMDS column, R2 = 0.908; and SS column, R2 = 0.833). A discernible decline in the concentration of leached Fe was accompanied by a corresponding reduction in IP. The determination coefficients correlating IP and Fe leaching remained substantial (control column, R2 = 0.768; AMDS column, R2 = 0.807; and SS column, R2 = 0.818). Such IP measurements manifest as instrumental tools in monitoring and assessing the retention capacity of applied stabilizer/binding agents in As-affected soils, thereby furnishing crucial data for the enduring surveillance of stabilization/solidification locales. This research posits a swift and continuous monitoring method for solidification/stabilization locales in situ.

Current therapeutic targets and multifaceted physiological impacts of caffeine.

Caffeine, which shares consubstantial structural similarity with purine adenosine, has been demonstrated as a nonselective adenosine receptor antagonist for eliciting most of the biological functions at physiologically relevant dosages. Accumulating evidence supports caffeine's beneficial effects against different disorders, such as total cardiovascular diseases and type 2 diabetes. Conversely, paradoxical effects are also linked to caffeine ingestion in humans including hypertension-hypotension and tachycardia-bradycardia. These observations suggest the association of caffeine action with its ingested concentration and/or concurrent interaction with preferential molecular targets to direct explicit events in the human body. Thus, a coherent analysis of the functional targets of caffeine, relevant to normal physiology, and disease pathophysiology, is required to understand the pharmacology of caffeine. This review provides a broad overview of the experimentally validated targets of caffeine, particularly those of therapeutic interest, and the impacts of caffeine on organ-specific physiology and pathophysiology. Overall, the available empirical and epidemiological evidence supports the dose-dependent functional activities of caffeine and advocates for further studies to get insights into the caffeine-induced changes under specific conditions, such as asthma, DNA repair, and cancer, in view of its therapeutic applications.

Integrative analysis of mitochondrial metabolic reprogramming in early-stage colon and liver cancer.

Gastrointestinal malignancies, including colon adenocarcinoma (COAD) and liver hepatocellular carcinoma (LIHC), remain leading causes of cancer-related deaths worldwide. To better understand the underlying mechanisms of these cancers and identify potential therapeutic targets, we analyzed publicly accessible Cancer Genome Atlas datasets of COAD and LIHC. Our analysis revealed that differentially expressed genes (DEGs) during early tumorigenesis were associated with cell cycle regulation. Additionally, genes related to lipid metabolism were significantly enriched in both COAD and LIHC, suggesting a crucial role for dysregulated lipid metabolism in their development and progression. We also identified a subset of DEGs associated with mitochondrial function and structure, including upregulated genes involved in mitochondrial protein import and respiratory complex assembly. Further, we identified mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase (HMGCS2) as a crucial regulator of cancer cell metabolism. Using a genome-scale metabolic model, we demonstrated that HMGCS2 suppression increased glycolysis, lipid biosynthesis, and elongation while decreasing fatty acid oxidation in colon cancer cells. Our study highlights the potential contribution of dysregulated lipid metabolism, including ketogenesis, to COAD and LIHC development and progression and identifies potential therapeutic targets for these malignancies.

Trogocytic molting of T cell microvilli upregulates T cell receptor surface expression and promotes clonal expansion.

Although T cell activation is known to involve the internalization of the T cell antigen receptor (TCR), much less is known regarding the release of TCRs following T cell interaction with cognate antigen-presenting cells. In this study, we examine the physiological mechanisms underlying TCR release following T cell activation. We show that T cell activation results in the shedding of TCRs in T cell microvilli, which involves a combined process of trogocytosis and enzymatic vesiculation, leading to the loss of membrane TCRs and microvilli-associated proteins and lipids. Surprisingly, unlike TCR internalization, this event results in the rapid upregulation of surface TCR expression and metabolic reprogramming of cholesterol and fatty acid synthesis to support cell division and survival. These results demonstrate that TCRs are lost through trogocytic 'molting' following T cell activation and highlight this mechanism as an important regulator of clonal expansion.

Magnetic delivery and ultrasound-responsive release of chelating microcapsules for selective removal of urolithiasis.

A novel urolithiasis treatment in which a chelating solution encapsulated in poly(lactic-co-glycolic acid); PLGA-based microcapsules was delivered magnetically to specific urolithiasis sites and then subjected to ultrasound (US) to release the chelating solution and dissolve the stones. Using a double-droplet microfluidics method, a hexametaphosphate (HMP) chelating solution was encapsulated in an Fe3O4 nanoparticle (Fe3O4 NP)-loaded PLGA polymer shell with a thickness of <15 µm, forming homogenous microcapsules of 319 ± 14 µm in size. The obtained microcapsules (HMP/Fe3O4@PLGA) exhibited efficient magnetic mobility and US-responsive solution release. Moreover, in a Ψ-shaped flow chip, selective delivery of HMP from the microcapsules was achieved with high magnetic delivery efficiency (>90%), and an effective removal efficacy (>95%, 7 repeat cycles) of artificial calcium oxalate (5 mm in size) via a chelating effect. Eventually, the potential removal of urolithiasis in the body was verified using a PDMS-based kidney urinary flow-imitating chip with a human kidney stone (CaOx 100%, 5-7 mm in size) located in the minor calyx under an artificial urine counter flow (0.5 mL min-1). In the end, more than 50% of the stone, even in surgically tricky regions, was removed by 10 repeated treatments. Therefore, the selective approach of stone-dissolution capsules will help to develop alternative urolithiasis treatments to conventional surgical and systemic dissolution approaches.

Association between Preoperative 18-FDG PET-CT SUVmax and Next-Generation Sequencing Results in Postoperative Ovarian Malignant Tissue in Patients with Advanced Ovarian Cancer.

This study investigated the association between maximum standardized uptake values (SUVmax) on preoperative 18-FDG PET-CT and next-generation sequencing (NGS) results in post-surgical ovarian malignant tissue in patients with advanced ovarian cancer. Twenty-five patients with stage IIIC or IV ovarian cancer who underwent both preoperative 18-FDG PET-CT and postoperative NGS for ovarian malignancies were retrospectively enrolled. Two patients had no detected variants, 21 of the 23 patients with any somatic variant had at least one single nucleotide variant (SNV) or insertion/deletion (indel), 10 patients showed copy number variation (CNV), and two patients had a fusion variant. SUVmax differed according to the presence of SNVs/indels, with an SUVmax of 13.06 for patients with ≥ 1 SNV/indel and 6.28 for patients without (p = 0.003). Seventeen of 20 patients with Tier 2 variants had TP53 variants, and there was a statistically significant association between SUVmax and the presence of TP53 variants (13.21 vs. 9.35, p = 0.041). Analysis of the correlation between the sum of the Tier 1 and Tier 2 numbers and SUVmax showed a statistically significant correlation (p = 0.002; Pearson's r = 0.588). In conclusion, patients with advanced ovarian cancer with SNVs/indels on NGS, especially those with TP53 Tier 2 variants, showed a proportional association with tumor SUVmax on preoperative PET-CT.

Integrated analysis of the microbiota-gut-brain axis in response to sleep deprivation and diet-induced obesity.

Introduction: Sleep deprivation (SD) and obesity are common in modern societies. SD and obesity frequently coexist, but research on the combined consequences of SD and obesity has been limited. In this study, we investigated the gut microbiota and host responses to SD and high-fat diet (HFD)-induced obesity. In addition, we attempted to identify key mediators of the microbiota-gut-brain axis. Methods: C57BL/6J mice were divided into four groups based on whether they were sleep deprived and whether they were fed a standard chow diet (SCD) or HFD. We then performed fecal microbiome shotgun sequencing, gut transcriptome analysis using RNA sequencing, and brain mRNA expression analysis using the nanoString nCounter Mouse Neuroinflammation Panel. Results: The gut microbiota was significantly altered by the HFD, whereas the gut transcriptome was primarily influenced by SD. Sleep and diet are both important in the inflammatory system of the brain. When SD and the HFD were combined, the inflammatory system of the brain was severely disrupted. In addition, inosine-5' phosphate may be the gut microbial metabolite that mediates microbiota-gut-brain interactions. To identify the major drivers of this interaction, we analyzed the multi-omics data. Integrative analysis revealed two driver factors that were mostly composed of the gut microbiota. We discovered that the gut microbiota may be the primary driver of microbiota-gut-brain interactions. Discussion: These findings imply that healing gut dysbiosis may be a viable therapeutic target for enhancing sleep quality and curing obesity-related dysfunction.

Metabolic modelling of the human gut microbiome in type 2 diabetes patients in response to metformin treatment.

The human gut microbiome has been associated with several metabolic disorders including type 2 diabetes mellitus. Understanding metabolic changes in the gut microbiome is important to elucidate the role of gut bacteria in regulating host metabolism. Here, we used available metagenomics data from a metformin study, together with genome-scale metabolic modelling of the key bacteria in individual and community-level to investigate the mechanistic role of the gut microbiome in response to metformin. Individual modelling predicted that species that are increased after metformin treatment have higher growth rates in comparison to species that are decreased after metformin treatment. Gut microbial enrichment analysis showed prior to metformin treatment pathways related to the hypoglycemic effect were enriched. Our observations highlight how the key bacterial species after metformin treatment have commensal and competing behavior, and how their cellular metabolism changes due to different nutritional environment. Integrating different diets showed there were specific microbial alterations between different diets. These results show the importance of the nutritional environment and how dietary guidelines may improve drug efficiency through the gut microbiota.

Machine learning with in silico analysis markedly improves survival prediction modeling in colon cancer patients.

BACKGROUND: Predicting the survival of cancer patients provides prognostic information and therapeutic guidance. However, improved prediction models are needed for use in diagnosis and treatment. OBJECTIVE: This study aimed to identify genomic prognostic biomarkers related to colon cancer (CC) based on computational data and to develop survival prediction models. METHODS: We performed machine-learning (ML) analysis to screen pathogenic survival-related driver genes related to patient prognosis by integrating copy number variation and gene expression data. Moreover, in silico system analysis was performed to clinically assess data from ML analysis, and we identified RABGAP1L, MYH9, and DRD4 as candidate genes. These three genes and tumor stages were used to generate survival prediction models. Moreover, the genes were validated by experimental and clinical analyses, and the theranostic application of the survival prediction models was assessed. RESULTS: RABGAP1L, MYH9, and DRD4 were identified as survival-related candidate genes by ML and in silico system analysis. The survival prediction model using the expression of the three genes showed higher predictive performance when applied to predict the prognosis of CC patients. A series of functional analyses revealed that each knockdown of three genes reduced the protumor activity of CC cells. In particular, validation with an independent cohort of CC patients confirmed that the coexpression of MYH9 and DRD4 gene expression reflected poorer clinical outcomes in terms of overall survival and disease-free survival. CONCLUSIONS: Our survival prediction approach will contribute to providing information on patients and developing a therapeutic strategy for CC patients.

Protective Effects of Carnosol on Renal Interstitial Fibrosis in a Murine Model of Unilateral Ureteral Obstruction.

Renal fibrosis is a common feature of chronic kidney disease and is a promising therapeutic target. However, there is still limited treatment for renal fibrosis, so the development of new anti-fibrotic agents is urgently needed. Accumulating evidence suggest that oxidative stress and endoplasmic reticulum (ER) stress play a critical role in renal fibrosis. Carnosol (CS) is a bioactive diterpene compound present in rosemary plants and has potent antioxidant and anti-inflammatory properties. In this study, we investigated the potential effects of CS on renal injury and fibrosis in a murine model of unilateral ureteral obstruction (UUO). Male C57BL/6J mice underwent sham or UUO surgery and received intraperitoneal injections of CS (50 mg/kg) daily for 8 consecutive days. CS improved renal function and ameliorated renal tubular injury and interstitial fibrosis in UUO mice. It suppressed oxidative injury by inhibiting pro-oxidant enzymes and activating antioxidant enzymes. Activation of ER stress was also attenuated by CS. In addition, CS inhibited apoptotic and necroptotic cell death in kidneys of UUO mice. Furthermore, cytokine production and immune cell infiltration were alleviated by CS. Taken together, these findings indicate that CS can attenuate renal injury and fibrosis in the UUO model.

Efficient Anti-Tumor Immunotherapy Using Tumor Epitope-Coated Biodegradable Nanoparticles Combined With Polyinosinic-Polycytidylic Acid and an Anti-PD1 Monoclonal Antibody.

Vaccination with tumor peptide epitopes associated with MHC class I molecules is an attractive approach directed at inducing tumor-specific CTLs. However, challenges remain in improving the therapeutic efficacy of peptide epitope vaccines, including the low immunogenicity of peptide epitopes and insufficient stimulation of innate immune components in vivo. To overcome this, we aimed to develop and test an innovative strategy that elicits potent CTL responses against tumor epitopes. The essential feature of this strategy is vaccination using tumor epitope-loaded nanoparticles (NPs) in combination with polyinosinic-polycytidylic acid (poly-IC) and anti-PD1 mAb. Carboxylated NPs were prepared using poly(lactic-co-glycolic acid) and poly(ethylene/maleic anhydride), covalently conjugated with anti-H-2Kb mAbs, and then attached to H-2Kb molecules isolated from the tumor mass (H-2b). Native peptides associated with the H-2Kb molecules of H-2Kb-attached NPs were exchanged with tumor peptide epitopes. Tumor peptide epitope-loaded NPs efficiently induced tumor-specific CTLs when used to immunize tumor-bearing mice as well as normal mice. This activity of the NPs significantly was increased when co-administered with poly-IC. Accordingly, the NPs exerted significant anti-tumor effects in mice implanted with EG7-OVA thymoma or B16-F10 melanoma, and the anti-tumor activity of the NPs was significantly increased when applied in combination with poly-IC. The most potent anti-tumor activity was observed when the NPs were co-administered with both poly-IC and anti-PD1 mAb. Immunization with tumor epitope-loaded NPs in combination with poly-IC and anti-PD1 mAb in tumor-bearing mice can be a powerful means to induce tumor-specific CTLs with therapeutic anti-tumor activity.

Synthetic Non-Coding RNA for Suppressing mTOR Translation to Prevent Renal Fibrosis Related to Autophagy in UUO Mouse Model.

The global burden of chronic kidney disease is increasing, and the majority of these diseases are progressive. Special site-targeted drugs are emerging as alternatives to traditional drugs. Oligonucleotides (ODNs) have been proposed as effective therapeutic tools in specific molecular target therapies for several diseases. We designed ring-type non-coding RNAs (ncRNAs), also called mTOR ODNs to suppress mammalian target rapamycin (mTOR) translation. mTOR signaling is associated with excessive cell proliferation and fibrogenesis. In this study, we examined the effects of mTOR suppression on chronic renal injury. To explore the regulation of fibrosis and inflammation in unilateral ureteral obstruction (UUO)-induced injury, we injected synthesized ODNs via the tail vein of mice. The expression of inflammatory-related markers (interleukin-1ß, tumor necrosis factor-α), and that of fibrosis (α-smooth muscle actin, fibronectin), was decreased by synthetic ODNs. Additionally, ODN administration inhibited the expression of autophagy-related markers, microtubule-associated protein light chain 3, Beclin1, and autophagy-related gene 5-12. We confirmed that ring-type ODNs inhibited fibrosis, inflammation, and autophagy in a UUO mouse model. These results suggest that mTOR may be involved in the regulation of autophagy and fibrosis and that regulating mTOR signaling may be a therapeutic strategy against chronic renal injury.

Therapeutic Effect of Bee Venom and Melittin on Skin Infection Caused by Streptococcus pyogenes.

Streptococcus pyogenes (S. pyogenes) bacteria cause almost all primary skin infections in humans. Bee venom (BV) and melittin (Mel) have multiple effects, including antibacterial and anti-inflammatory activities. This study aims to demonstrate their effects on bacterial mouse skin infection using S. pyogenes. The dorsal skin was tape-stripped, then S. pyogenes was topically applied. BV or Mel were topically applied to the lesion. The tissues were stained with hematoxylin and eosin, while immunohistochemical staining was performed with anti-neutrophil. S. pyogenes-infected skin revealed increased epidermal and dermal layers, but it was reduced in the BV and Mel groups. Finding increased neutrophils in the mice infected with S. pyogenes, but the BV and Mel mice showed decreased expression. These results suggest that BV and Mel treatments could reduce the inflammatory reactions and help improve lesions induced by S. pyogenes skin infection. This study provides additional assessment of the potential therapeutic effects of BV and Mel in managing skin infection caused by S. pyogenes, further suggesting that it could be a candidate for developing novel treatment alternative for streptococcal skin infections.

Host-mycobiome metabolic interactions in health and disease.

Fungal communities (mycobiome) have an important role in sustaining the resilience of complex microbial communities and maintenance of homeostasis. The mycobiome remains relatively unexplored compared to the bacteriome despite increasing evidence highlighting their contribution to host-microbiome interactions in health and disease. Despite being a small proportion of the total species, fungi constitute a large proportion of the biomass within the human microbiome and thus serve as a potential target for metabolic reprogramming in pathogenesis and disease mechanism. Metabolites produced by fungi shape host niches, induce immune tolerance and changes in their levels prelude changes associated with metabolic diseases and cancer. Given the complexity of microbial interactions, studying the metabolic interplay of the mycobiome with both host and microbiome is a demanding but crucial task. However, genome-scale modelling and synthetic biology can provide an integrative platform that allows elucidation of the multifaceted interactions between mycobiome, microbiome and host. The inferences gained from understanding mycobiome interplay with other organisms can delineate the key role of the mycobiome in pathophysiology and reveal its role in human disease.