The paradigm of tax-reward and tax-punishment strategies in the advancement of public resource management dynamics.

In contemporary society, the effective utilization of public resources remains a subject of significant concern. A common issue arises from defectors seeking to obtain an excessive share of these resources for personal gain, potentially leading to resource depletion. To mitigate this tragedy and ensure sustainable development of resources, implementing mechanisms to either reward those who adhere to distribution rules or penalize those who do not, appears advantageous. We introduce two models: a tax-reward model and a tax-punishment model, to address this issue. Our analysis reveals that in the tax-reward model, the evolutionary trajectory of the system is influenced not only by the tax revenue collected but also by the natural growth rate of the resources. Conversely, the tax-punishment model exhibits distinct characteristics when compared with the tax-reward model, notably the potential for bistability. In such scenarios, the selection of initial conditions is critical, as it can determine the system's path. Furthermore, our study identifies instances where the system lacks stable points, exemplified by a limit cycle phenomenon, underscoring the complexity and dynamism inherent in managing public resources using these models.

Evolution of trust in N-player trust games with loss assessment.

Trust plays a crucial role in social and economic interactions, serving as the foundation for social stability and human cooperation. Previous studies have explored the evolution of trust between investors and trustees by constructing trust game models, incorporating factors such as network structure, reputation, and incentives. However, these studies often assume that investors consistently maintain their investment behavior, neglecting the potential influence of the investment environment on investment behavior. To address this gap, we introduce a loss assessment mechanism and construct a trust game model. Specifically, investors first allocate their investment amount to an assessment agency, which divides the amount into two parts according to a certain allocation ratio. One part is used for investment assessment, and the results are fed back to the investors. If the payoff from this portion exceeds the investors' expected value, the remaining amount is invested; otherwise, it is returned to the investors. The results indicate that investors with moderate expectations are more likely to form alliances with trustworthy trustees, thereby effectively promoting the evolution of trust. Conversely, lower or higher expectations yield opposite results. Additionally, we find that as investors' expected values increase, the corresponding allocation ratio should also increase to achieve higher payoffs.

Threshold incentive mechanisms for the sustainable management of public resources.

Maintaining global ecological balance is inextricably linked to the effective governance of public resources. Previous studies have proposed the introduction of incentive mechanisms to mitigate the defection behavior within the scope of public resource management to facilitate sustainable utilization. However, these incentive strategies often present a considerable financial burden. Here, we first propose a two-threshold incentive scheme based on group state objectives, where the reward mechanism is triggered when the number of cooperators is below the threshold M, and the punishment mechanism is triggered when the number of cooperators is above the threshold Q. We further introduce an incentive mechanism by considering both resource and group thresholds, where incentives are implemented separately when the number of cooperators and the current quantity of resources meet thresholds. Our theoretical results reveal that introducing these two new mechanisms can effectively maintain cooperative behavior and sustainable resources while reducing management costs. However, if the initial resource level is low, the tragedy of the commons will still occur. It is recommended that the number of developers be reduced, the allocation be lowered, or the development simply suspended and the natural regeneration of resources be waited for.

Complementary use of visual and olfactory cues to assess capture of Bactrocera dorsalis (Hendel): Implementation and field verification via an IoT-based automatic monitoring system.

This study examined the effect of combining visual and olfactory cues to attract oriental fruit flies (OFFs). Six different colored light-emitting diodes (LEDs) served as a visual attractant and methyl eugenol served as olfactory bait to lure male flies. An internet of things (IoT)-based pest monitoring system, consisting of sensor nodes, a gateway, and automatic counting traps, was deployed in the field to automatically collect environmental data and pest counts. The results of the calibrated experiments indicated that green, yellow, or red LEDs exhibited better performance in attracting flies than white, purple, or blue LEDs or no LEDs. With an accurate combination of visual and olfactory cues, the proposed IoT-based pest monitoring system may be an effective tool in agricultural pest management, given its advantages for efficiently capturing OFFs in a labor and time saving manner, providing accurate information regarding increases in pest populations, and enabling long-term, real-time data collection.

Network pharmacology and molecular docking of endogenous active metabolites in diabetic kidney disease.

OBJECTIVES: Network pharmacology and molecular docking were used to predict endogenous active metabolites with protective effects in diabetic kidney disease (DKD). METHODS: We utilized metabolomics to screen differentially expressed metabolites in kidney tissues of mice with type 2 DKD and predicted potential targets using relevant databases. The interaction network between endogenous active metabolites and target proteins was established by integrating differentially expressed metabolites and proteins associated with DKD identified through proteomics. Gene ontology (GO) and signaling pathway enrichment analysis were performed. The biological functions of the active candidate metabolites and their effects on downstream pathways were also verified. RESULTS: Metabolomics revealed 130 differentially expressed metabolites. Through co-expression network analysis coupled with the investigation of differentially expressed proteins in proteomics, 2-hydroxyphenylpropionylglycine (2-HPG) emerged as a key regulator of DKD. 2-HPG was found to modulate the progression of DKD by regulating the conformation and activity of synaptophysin 1 (SYNJ1), with a correlation coefficient of 0.974. In vivo experiments revealed that SYNJ1 expression was significantly downregulated in the Macroalbuminuria Group compared to the Control Group and negatively correlated with proteinuria (r = -0.7137), indicating its important role in DKD progression. Immunofluorescence demonstrated that treatment with 2-HPG restores the expression of the foot process marker protein Wilms tumor-1 (WT-1) in podocytes injured by high glucose levels. Western blot and polymerase chain reaction support the involvement of SYNJ1 in this process. CONCLUSIONS: This study demonstrated the significance of the 2-HPG/SYNJ1 signaling axis in safeguarding the foot process of podocytes in DKD.

miR-30b-5p modulate renal epithelial-mesenchymal transition in diabetic nephropathy by directly targeting SNAI1.

OBJECT: Renal tubulointerstitial fibrosis plays a significant role in the development of diabetic nephropathy (DN). SNAI1 is a main activator of epithelial-to-mesenchymal transition (EMT) in the process of fibrosis. This study aimed to investigate the effect of miR-30b-5p targeting SNAI1 on the EMT in DN. METHODS: Bioinformatics and miRNAs microarray analyses were used to predict the candidate miRNA targeting SNAI1, that is miR-30b-5p. The db/db mice was as DN animal model and renal tissues of mice were stained with PAS. The miR-30b-5p expression in mouse and human renal tissue were examined by quantitative RT-PCR (qRT-PCR) and fluorescence in situ hybridization (FISH), while SNAI1 expression was determined by qRT-PCR and immunohistochemistry. Luciferase reporter gene assay was used to confirm miR-30b-5p directly target 3'-UTR of the SNAI1 mRNA. In vitro, HK-2 cells were treated with high glucose to establish hyperglycemia cell model and transfected with miR-30b-5p mimics to overexpress miR-30b-5p. Expression of miR-30b-5p, SNAI1 and EMT related indicators (E-cadherin, a-SMA and Vimentin) in HK-2 cells under different treatments were determined by qRT-PCR and/or western-blot. In addition, immunofluorescence was performed to evaluate a-SMA expression in HK-2 cells under different treatments. RESULTS: Bioinformatics analyses revealed miR-30b-5p had complementary sequences with SNAI1 mRNA and the seed region of miR-30b-5p was conserved in human and a variety of animals, including mice. Microarray analysis showed miR-30b expression decreased in DN mice, which was further verified in db/db mice by qRT-PCR and in human DN by FISH. Contrary to miR-30b-5p, SNAI1 expression level was upregulated in db/db mice. Correlation analysis suggested SNAI1 mRNA level was negatively with miR-30b-5p level in renal tissue of db/db mice. Luciferase reporter gene assay confirmed miR-30b-5p directly targeted SNAI1 mRNA. In high glucose induced HK-2 cells, expression levels of miR-30b-5p and E-cadherin were decreased, while SNAI1, a-SMA and Vimentin were increased. Overexpression miR-30b-5p in high glucose induced HK-2 cells could reverse that phenomenon to some extent. CONCLUSION: These findings suggest that miR-30b-5p play a protective role by targeting SNAI1 in renal EMT in DN.

Clinical and pathological analysis of IgA nephropathy with chronic renal failure.

OBJECTIVE: To investigative clinical and pathological characteristics of IgA nephropathy with chronic renal failure. METHOD: Clinical and pathological findings from 65 cases of IgA nephropathy with chronic renal failure were reviewed. Pathological characteristics of all the cases were analyzed according to WHO definition and Oxford Classification. Evaluating the severity of pathological lesions by the Katafuchi R semiquantitative scoring system, and analyzing their relationship with clinical indexes of renal function. RESULTS: Of all 65 cases the male and female ratio was 1.4, and the mean age was 37 ± 13 years old. Levels of systolic pressure, mean arterial pressure (MAP), blood urea nitrogen (BUN), serum creatinine (Scr), uric acid (UA), album (Alb), serum IgG and 24 h urinary protein were related with eGRF level (p < 0.05, respectively). The most common pathological type was proliferative sclerosis glomerulonephritis (PSGN) and M1S1E0T0 according to WHO definition and Oxford Classification, respectively, and most of the 65 cases had glomerulosclerosis. Simple IgA deposition was the most common immunopathologic type. Of all the cases, 44.6% accompanied with C3 while 4.6% with C1q. Further analysis revealed there were no relationships between severity of pathological lesion and levels of clinical indexes (Scr and eGRF) (p > 0.05). CONCLUSION: IgA nephropathy with chronic renal failure usually occurred in young adults, and it had severe clinical condition and pathological changes, while there was no significant relationship between them.

New insights into the pathogenesis of IgA nephropathy: do toll like receptor 9-B cell activation factor-IgA class switching recombination signaling axis induce IgA hyper-production?

IgA nephropathy (IgAN) has become the most common form of primary glomerular disease worldwide. So far, it is still not very clear about the exact pathogenesis of IgAN, thus has no specific therapy. Generally mesangial deposition of IgA, especially polymeric IgA1 (pIgA1), suggests to be the initiating event in the pathogenesis of IgAN. In addition to decreased IgA clearance, IgA over production may also participate in the pathogenesis of IgAN. IgA class switching recombination (CSR) played key role during the process of IgA production. Stimulated with hemolytic streptococcus, tonsillar mononuclear cells (TMCs) of patients with IgAN presented with increased levels of Ia-Ca and activation-induced cytidine deaminase (AID), which are significant for IgA CSR. Human B cells and plasmacytoid dendritic cells express Toll-like receptor (TLR)-9, whose natural ligands are unmethylated cytosine-guanine dinucleotide (CpG) motifs characteristic of bacterial DNA (CpG-DNA). Unmethylated deoxycytidylic-deoxyguanosine oligodeoxynucleotide (CpG-ODN) is able to mimic the immunostimulatory activity of microbial DNA. Study found a significant increase in B cell activation factor (BAFF) production when tonsillar mononuclear cells stimulated with CpG-ODN in patients with IgAN. BAFF can induce germline Cα gene expression, AID expression, and IgA class switching in a CD40-independent manner. Therefore, it could be hypothesized that in IgAN there may exist TLR9-BAFF-IgA CSR axis, which induces excessive IgA production. If the hypothesis is correct, it could be of great significance for pathogenesis of IgAN elucidate and IgAN treatment.

Inhibition effect of small interfering RNA of connective tissue growth factor on the expression of extracellular matrix molecules in cultured human renal proximal tubular cells.

OBJECTIVE: In this study, we investigated the effect of small interfering RNA (siRNA) of connective tissue growth factor (CTGF) by pRetro-Super (PRS) retrovirus vector on the expression of CTGF and related extracellular matrix molecules in human renal proximal tubular cells (HKCs) induced by high glucose, to provide help for renal tubulointerstitial fibrosis therapy. METHODS: HKCs were exposed to d-glucose to observe their dose and time effect, while the mannitol as osmotic control. Retrovirus producing CTGF siRNA were constructed from the inverted oligonucleotides and transferred into packaging cell line PT67 with lipofectamine, and the virus supernatant was used to infect HKC. The expression of CTGF, fibronectin (FN) and collagen-type I (col1) were measured by semi-quantitative RT-PCR and Western blot. RESULTS: In response to high glucose, CTGF expression in HKCs was increased in a dose- and time-dependent manner, whereas the increase did not occur in the osmotic control. Introduction of PRS-CTGF-siRNA resulted in the significant reduction of CTGF, FN, col1 mRNA (p < 0.01, respectively) and CTGF, col1 protein (p < 0.05, respectively) expression, while PRS void vector group did not have these effects (p > 0.05). CONCLUSIONS: CTGF siRNA therapy can effectively reduce the levels of CTGF, FN and col1 induced by high glucose in cultured HKCs, which suggested that it may be a potential therapeutic strategy to prevent the renal interstitial fibrosis in the future.

[Research progress on the dynamic role and intervention value of autophagy in neonatal hypoxic-ischemic brain damage].

The repair of the nervous system after hypoxic-ischemic brain damage (HIBD) in neonates lacks specific therapeutic approaches, posing a challenge and hot topic in the medical field. Autophagy, as a cellular self-repair mechanism, plays a role through different signaling pathways at different stages, yet its specific roles and mechanisms in different stages of HIBD remain unclear. This article reviews the recent research advancements on autophagy in different neonatal HIBD stages: heightened autophagic activity manifests during the acute hypoxic-ischemic phase, with its neuroprotective or deleterious impact subject to ongoing debate; during the subacute and chronic phases, autophagy exert dual effects on neuronal death and repair; in sequelae period, autophagy-related studies are still insufficient, but the expression levels of autophagy-related genes (ATG) in children with cerebral palsy suggest both positive and negative aspects of autophagy post-HIBD. Collectively, optimal autophagic flux facilitates the elimination of detrimental substrates and toxic proteins, thereby engendering neuroprotection. Further studies on the roles and mechanisms of autophagy in HIBD therapy holds promise for devising efficacious preventative and therapeutic strategies rooted in autophagy, and to improve the survival rate and quality of life of the children.

Translation Consistent Semi-supervised Segmentation for 3D Medical Images.

3D medical image segmentation methods have been successful, but their dependence on large amounts of voxel-level annotated data is a disadvantage that needs to be addressed given the high cost to obtain such annotation. Semi-supervised learning (SSL) solves this issue by training models with a large unlabelled and a small labelled dataset. The most successful SSL approaches are based on consistency learning that minimises the distance between model responses obtained from perturbed views of the unlabelled data. These perturbations usually keep the spatial input context between views fairly consistent, which may cause the model to learn segmentation patterns from the spatial input contexts instead of the foreground objects. In this paper, we introduce the Translation Consistent Co-training (TraCoCo) which is a consistency learning SSL method that perturbs the input data views by varying their spatial input context, allowing the model to learn segmentation patterns from foreground objects. Furthermore, we propose a new Confident Regional Cross entropy (CRC) loss, which improves training convergence and keeps the robustness to co-training pseudo-labelling mistakes. Our method yields state-of-the-art (SOTA) results for several 3D data benchmarks, such as the Left Atrium (LA), Pancreas-CT (Pancreas), and Brain Tumor Segmentation (BraTS19). Our method also attains best results on a 2D-slice benchmark, namely the Automated Cardiac Diagnosis Challenge (ACDC), further demonstrating its effectiveness. Our code, training logs and checkpoints are available at https://github.com/yyliu01/ TraCoCo.

Brain imaging derived phenotypes: a biomarker for the onset of inflammatory bowel disease and a potential mediator of mental complications.

Background and aims: Inflammatory bowel disease (IBD), mainly categorized into Crohn's disease (CD) and ulcerative colitis (UC), is a chronic relapsing gastrointestinal disorder that significantly impairs patients' quality of life. IBD patients often experience comorbidities such as anxiety and depression, and the underlying mechanisms and treatment strategies remain areas of investigation. Methods: We conducted a Mendelian randomization(MR) analysis utilizing brain image derived phenotypes (IDP) from the UK Biobank database to investigate the causal relationships between IBD and alterations in brain structural morphology and connectivity of neural tracts. This study aimed to identify biological evidence linking IBD to psychiatric disorders such as anxiety and depression. Results: Specifically, the volume of grey matter in the Left Frontal Orbital Cortex exhibited a negative association with the onset of Crohn's disease (odds ratio (OR) [95% confidence interval (CI)]: 0.315[0.180~0.551], adjusted P=0.001), while the volume of the superior frontal cortex in the right hemisphere showed a positive correlation with the development of Ulcerative colitis (OR [95% CI]: 2.285[1.793~2.911], adjusted P<0.001), and the volume of lateral occipital cortex in the left hemisphere demonstrated a positive relationship with Crohn's disease onset (OR [95% CI]: 1.709[1.671~1.747], adjusted P<0.001). In the context of reverse causality, the onset of UC or CD has led to alterations in imaging derived phenotypes associated with five disorders (anxiety, depression, schizophrenia, bipolar disorder, pain) and three functions (memory, emotion, language). Conclusion: Our study has demonstrated a causal relationship between IBD and IDPs. IDPs may serve as potential biomarkers for the progression of IBD and as predictive intermediaries for the development of neurological diseases in IBD patients.

BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations.

Methods to detect malignant lesions from screening mammograms are usually trained with fully annotated datasets, where images are labelled with the localisation and classification of cancerous lesions. However, real-world screening mammogram datasets commonly have a subset that is fully annotated and another subset that is weakly annotated with just the global classification (i.e., without lesion localisation). Given the large size of such datasets, researchers usually face a dilemma with the weakly annotated subset: to not use it or to fully annotate it. The first option will reduce detection accuracy because it does not use the whole dataset, and the second option is too expensive given that the annotation needs to be done by expert radiologists. In this paper, we propose a middle-ground solution for the dilemma, which is to formulate the training as a weakly- and semi-supervised learning problem that we refer to as malignant breast lesion detection with incomplete annotations. To address this problem, our new method comprises two stages, namely: (1) pre-training a multi-view mammogram classifier with weak supervision from the whole dataset, and (2) extending the trained classifier to become a multi-view detector that is trained with semi-supervised student-teacher learning, where the training set contains fully and weakly-annotated mammograms. We provide extensive detection results on two real-world screening mammogram datasets containing incomplete annotations and show that our proposed approach achieves state-of-the-art results in the detection of malignant breast lesions with incomplete annotations.

Glutamate ionotropic receptor NMDA type subunit 1: A novel potential protein target of dapagliflozin against renal interstitial fibrosis.

Renal interstitial fibrosis (RIF) is the final pathway for chronic kidney diseases (CKD) to end-stage renal disease, with no ideal therapy at present. Previous studies indicated that sodium glucose co-transporter-2 inhibitor (SGLT2i) dapagliflozin had the effect of anti-RIF, but the mechanism remains elusive and the renal protective effect could not be fully explained by singly targeting SGLT2. In this study, we aimed to explore the mechanism of dapagliflozin against RIF and identify novel potential targets. Firstly, dapagliflozin treatment improved pro-fibrotic indicators in unilateral ureteral obstruction mice and transforming growth factor beta 1 induced human proximal tubular epithelial cells. Then, transcriptomics and bioinformatics analysis were performed, and results revealed that dapagliflozin against RIF by regulating inflammation and oxidative stress related signals. Subsequently, targets prediction and analysis demonstrated that glutamate ionotropic receptor NMDA type subunit 1 (GRIN1) was a novel potential target of dapagliflozin, which was related to inflammation and oxidative stress related signals. Moreover, molecular dynamics simulation revealed that dapagliflozin could stably bind to GRIN1 protein and change its spatial conformation. Furthermore, human renal samples and Nephroseq data were used for GRIN1 expression evaluation, and the results showed that GRIN1 expression were increased in renal tissues of CKD and RIF patients than controls. Additionally, further studies demonstrated that dapagliflozin could reduce intracellular calcium influx in renal tubular cells, which depended on regulating GRIN1 protein but not gene. In conclusion, GRIN1 is probably a novel target of dapagliflozin against RIF.

The protective mechanism of Dehydromiltirone in diabetic kidney disease is revealed through network pharmacology and experimental validation.

Background: Salvia miltiorrhiza (SM) is an effective traditional Chinese medicine for treating DKD, but the exact mechanism is elusive. In this study, we aimed to investigate and confirm the method underlying the action of the active components of SM in the treatment of DKD. Methods: Renal tissue transcriptomics and network pharmacology of DKD patients was performed to identify the active components of SM and the disease targets of DKD. Next, the point of convergence among these three groups was studied. Potential candidate genes were identified and analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The component-target networks were modelled and visualized with Cytoscape. In addition, docking studies were performed to validate our potential target predictions. Lastly, in vitro and in vivo experiments were performed to understand the role of Dehydromiltirone (DHT), the active component of SM, in the phenotypic switching of mesangial cells. Results: Transcriptomics of DKD patients' renal tissues screened 4,864 differentially expressed genes. Eighty-nine active components of SM and 161 common targets were found. Functional enrichment analysis indicated that 161 genes were enriched in apoptosis, the PI3K-AKT signaling pathway, and the AGE-RAGE signaling pathway in diabetes complications. Molecular docking and molecular dynamic simulations show that DHT can bind to functional PIK3CA pockets, thereby becoming a possible inhibitor of PIK3CA. In vitro study demonstrated that DHT reduced the expression of phenotypic switching markers α-SMA, Col-I, and FN in HMCs by downregulating the over-activation of the PI3K-AKT signaling pathway through the inhibition of PIK3CA. Furthermore, the DKD mouse model confirmed that DHT could reduce proteinuria and improve glomerular hypertrophy in vivo. Conclusion: DHT was identified as the key active component of SM, and its therapeutic effect on DKD was achieved by inhibiting the phenotypic switching of mesangial cells via the PIK3CA signaling pathway.

Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images.

Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images. UAD is an important medical image analysis (MIA) method to be applied in disease screening problems because the training sets available for those problems usually contain only normal images. However, the exclusive reliance on normal images may result in the learning of ineffective low-dimensional image representations that are not sensitive enough to detect and segment unseen abnormal lesions of varying size, appearance, and shape. Pre-training UAD methods with self-supervised learning, based on computer vision techniques, can mitigate this challenge, but they are sub-optimal because they do not explore domain knowledge for designing the pretext tasks, and their contrastive learning losses do not try to cluster the normal training images, which may result in a sparse distribution of normal images that is ineffective for anomaly detection. In this paper, we propose a new self-supervised pre-training method for MIA UAD applications, named Pseudo Multi-class Strong Augmentation via Contrastive Learning (PMSACL). PMSACL consists of a novel optimisation method that contrasts a normal image class from multiple pseudo classes of synthesised abnormal images, with each class enforced to form a dense cluster in the feature space. In the experiments, we show that our PMSACL pre-training improves the accuracy of SOTA UAD methods on many MIA benchmarks using colonoscopy, fundus screening and Covid-19 Chest X-ray datasets.

Investigating the effect of dehydromiltirone on septic AKI using a network pharmacology method, molecular docking, and experimental validation.

Acute kidney injury (AKI) is a severe and frequent complication of sepsis that occurs in intensive care units with inflammation and rapid decline in renal function as the main pathological features. Systemic inflammation, microvascular dysfunction, and tubule injury are the main causes of sepsis-induced AKI (SI-AKI). The high prevalence and death rate from SI-AKI is a great challenge for clinical treatment worldwide. However, in addition to hemodialysis, there is no effective drug to improve renal tissue damage and alleviate the decline in kidney function. We conducted a network pharmacological analysis of Salvia miltiorrhiza (SM), a traditional Chinese medicine, which is widely used for the treatment of kidney disease. Then, we combined molecular docking and a dynamics simulation to screen for the active monomer dehydromiltirone (DHT) that has therapeutic effects on SI-AKI and investigated its potential mechanism of action through experimental validation. The components and targets of SM were obtained by searching the database, and 32 overlapping genes were screened by intersection analysis with AKI targets. GO and KEGG data showed that the functions of a common gene were closely related to oxidative stress, mitochondrial function, and apoptosis. The molecular docking results combined with molecular dynamics simulations provide evidence for a binding model between DHT and cyclooxygenase-2 (COX2), both of which are mainly driven by van der Waals interactions and a hydrophobic effect. In vivo, we found that mice pretreated with an intraperitoneal injection of DHT (20 mg/kg/d) for 3 days ameliorated CLP surgery-induced renal function loss and renal tissue damage and inhibited inflammatory mediators IL-6, IL-1ß, TNF-α, and MCP-1 production. In vitro, the DHT pretreatment decreased LPS-induced expression of COX2, inhibited cell death and oxidative stress, alleviated mitochondrial dysfunction, and restrained apoptosis in HK-2 cells. Our research indicates that the renal preventive effect of DHT is related to maintaining mitochondrial dynamic balance, restoring mitochondrial oxidative phosphorylation, and inhibiting cell apoptosis. The findings in this study provide a theoretical basis and a novel method for the clinical therapy of SI-AKI.

A mendelian randomization study with populations of European ancestry rules out a causal relationship between inflammatory bowel disease and colorectal cancer.

Background: Ulcerative colitis (UC), a subtype of inflammatory bowel disease (IBD), has been found to be associated with colorectal cancer (CRC) in observational studies, but there is no evidence to support a causal relationship or reverse causality between the two diseases. Methods: We employed two-sample bidirectional Mendelian randomization to estimate an unconfounded bidirectional causal relationship between IBD (including UC and Crohn's disease (CD)) and colorectal cancer. After searching IEU GWAS database and filtering SNPs, we applied a variety of MR methods including IVW method using qualified instrumental variables, and conducted sensitivity analysis to detect the heterogeneity and pleiotropy of instrumental variables. Results: After using three groups of SNPs (CD: 106, UC: 113, IBD: 70), the IVW method MR analysis showed that the results were not significant (result for UC: odds ratio (OR) [95% Confidence Interval (CI)]: 0.9998 [0.9991-1.0005], p value: 0.58; result for CD: OR [95%CI]: 0.99962 [0.99912-1.00012], p value: 0.14; results for IBD: OR [95%CI]: 0.99959 [0.99869-1.00048], p value: 0.36). MR-Egger regression, WM method and MR-RAPS method reached the same conclusion. Sensitivity analysis did not reveal heterogeneity and pleiotropy. Bidirectional MR analysis was performed using the same procedure, and the results of IVW MR analysis were also not significant (result for CD: OR [95%CI]: 1.07985 [0.00049-2372.38304], p value 0.98; result for UC: OR [95%CI]: 0.27117 [0.00014-528.3707], p value: 0.74; result for IBD: OR [95%CI]: 0.47101 [0.0001-2242.94159], p value: 0.86). MR-Egger regression, WM method and MR-RAPS method also reached the same conclusion. Sensitivity analysis did not find any evidence of heterogeneity and pleiotropy. Conclusion: Contrary to the conclusions of previous observational studies, a two-sample MR analysis did not find a causal relationship or reverse causal relationship between IBD and CRC. Sporadic CRC (sCRC) may differ in pathogenesis from IBD-related CRC.

Investigation into the effect and mechanism of dapagliflozin against renal interstitial fibrosis based on transcriptome and network pharmacology.

BACKGROUND: Renal interstitial fibrosis (RIF) is the final pathway for chronic kidney diseases (CKD) to end-stage renal disease (ESRD). Dapagliflozin, a selective inhibitor of the sodium glucose co-transporter 2, reduced the risk of renal events in non-diabetic CKD patients in the DAPA-CKD trial. However, the effect and mechanism of dapagliflozin on RIF are not very clear. Currently, we evaluate the effects of dapagliflozin on RIF and systematically explore its mechanism. METHODS AND RESULTS: Firstly, unilateral ureteral obstruction (UUO) mouse model was established to evaluate effects of dapagliflozin on RIF, and results demonstrated dapagliflozin improved renal function and RIF of UUO mice independent of blood glucose control. Subsequently, transcriptome analysis was performed to explore the potential mechanism of dapagliflozin against RIF, which exhibited the therapeutic effect of dapagliflozin on RIF may be achieved through multiple pathways regulation. Then we verified the potential mechanisms with molecular biology methods, and found that dapagliflozin treatment significantly alleviated inflammation, apoptosis, oxidative stress and mitochondrial injury in kidneys of UUO mice. Furthermore, network pharmacology analysis was used to investigate the potential targets of dapagliflozin against RIF. Moreover, we also applied molecular docking and molecular dynamics simulation to predict the specific binding sites and binding capacity of dapagliflozin and hub target. CONCLUSIONS: Dapagliflozin had therapeutic effect on RIF independent of blood glucose control, and the protective effects probably mediated by multiple pathways and targets regulation.

Exploring the Role of CircRNA in Diabetic Kidney Disease from a Novel Perspective: Focusing on Both Glomeruli and Tubuli.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease, but the molecular mechanisms of disease remain not very clear and there is no curative therapeutic strategy so far. This study was carried out to identify the expression profile of circular RNA (circRNA) in human DKD and explore circRNA regulatory function in glomeruli and tubuli simultaneously. As a result, a total of 40 upregulated and 23 downregulated differentially expressed circRNAs (DEcircRNAs) were detected. Six candidate DEcircRNAs were verified by quantitative real-time polymerase chain reaction in high glucose-treated human mesangial cells and human proximal renal tubular epithelial cells, respectively. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that both in glomeruli and in tubuli the DEcircRNAs-targeted genes participated in many pathophysiological processes of DKD. Correlation analysis with renal function showed that expression level of DEcircRNA-targeted hub gene was related to renal function. In conclusion, this is the first study to report expression profiles of circRNAs in kidney of DKD patients, and further analysis demonstrated that circRNA probably played a significant regulatory role, providing help for understanding the pathogenesis of DKD and investigating novel diagnostic and therapeutic strategy.