IGFBP2 induces podocyte apoptosis promoted by mitochondrial damage via integrin α5/FAK in diabetic kidney disease.

Podocyte apoptosis or loss is the pivotal pathological characteristic of diabetic kidney disease (DKD). Insulin-like growth factor-binding protein 2 (IGFBP2) have a proinflammatory and proapoptotic effect on diseases. Previous studies have shown that serum IGFBP2 level significantly increased in DKD patients, but the precise mechanisms remain unclear. Here, we found that IGFBP2 levels obviously increased under a diabetic state and high glucose stimuli. Deficiency of IGFBP2 attenuated the urine protein, renal pathological injury and glomeruli hypertrophy of DKD mice induced by STZ, and knockdown or deletion of IGFBP2 alleviated podocytes apoptosis induced by high concentration of glucose or in DKD mouse. Furthermore, IGFBP2 facilitated apoptosis, which was characterized by increase in inflammation and oxidative stress, by binding with integrin α5 (ITGA5) of podocytes, and then activating the phosphorylation of focal adhesion kinase (FAK)-mediated mitochondrial injury, including membrane potential decreasing, ROS production increasing. Moreover, ITGA5 knockdown or FAK inhibition attenuated the podocyte apoptosis caused by high glucose or IGFBP2 overexpression. Taken together, these findings unveiled the insight mechanism that IGFBP2 increased podocyte apoptosis by mitochondrial injury via ITGA5/FAK phosphorylation pathway in DKD progression, and provided the potential therapeutic strategies for diabetic kidney disease.

All-trans retinoic acid pretreatment of mesenchymal stem cells enhances the therapeutic effect on acute kidney injury.

A promising new therapy option for acute kidney injury (AKI) is mesenchymal stem cells (MSCs). However, there are several limitations to the use of MSCs, such as low rates of survival, limited homing capacity, and unclear differentiation. In search of better therapeutic strategies, we explored all-trans retinoic acid (ATRA) pretreatment of MSCs to observe whether it could improve the therapeutic efficacy of AKI. We established a renal ischemia/reperfusion injury model and treated mice with ATRA-pretreated MSCs via tail vein injection. We found that AKI mice treated with ATRA-MSCs significantly improved renal function compared with DMSO-MSCs treatment. RNA sequencing screened that hyaluronic acid (HA) production from MSCs promoted by ATRA. Further validation by chromatin immunoprecipitation experiments verified that retinoic acid receptor RARα/RXRγ was a potential transcription factor for hyaluronic acid synthase 2. Additionally, an in vitro hypoxia/reoxygenation model was established using human proximal tubular epithelial cells (HK-2). After co-culturing HK-2 cells with ATRA-pretreated MSCs, we observed that HA binds to cluster determinant 44 (CD44) and activates the PI3K/AKT pathway, which enhances the anti-inflammatory, anti-apoptotic, and proliferative repair effects of MSCs in AKI. Inhibition of the HA/CD44 axis effectively reverses the renal repair effect of ATRA-pretreated MSCs. Taken together, our study suggests that ATRA pretreatment promotes HA production by MSCs and activates the PI3K/AKT pathway in renal tubular epithelial cells, thereby enhancing the efficacy of MSCs against AKI.

Bibliometric and visual analysis of machine learning-based research in acute kidney injury worldwide.

Background: Acute kidney injury (AKI) is a serious clinical complication associated with adverse short-term and long-term outcomes. In recent years, with the rapid popularization of electronic health records and artificial intelligence machine learning technology, the detection rate and treatment of AKI have been greatly improved. At present, there are many studies in this field, and a large number of articles have been published, but we do not know much about the quality of research production in this field, as well as the focus and trend of current research. Methods: Based on the Web of Science Core Collection, studies reporting machine learning-based AKI research that were published from 2013 to 2022 were retrieved and collected after manual review. VOSviewer and other software were used for bibliometric visualization analysis, including publication trends, geographical distribution characteristics, journal distribution characteristics, author contributions, citations, funding source characteristics, and keyword clustering. Results: A total of 336 documents were analyzed. Since 2018, publications and citations have increased dramatically, with the United States (143) and China (101) as the main contributors. Regarding authors, Bihorac, A and Ozrazgat-Baslanti, T from the Kansas City Medical Center have published 10 articles. Regarding institutions, the University of California (18) had the most publications. Approximately 1/3 of the publications were published in Q1 and Q2 journals, of which Scientific Reports (19) was the most prolific journal. Tomasev et al.'s study that was published in 2019 has been widely cited by researchers. The results of cluster analysis of co-occurrence keywords suggest that the construction of AKI prediction model related to critical patients and sepsis patients is the research frontier, and XGBoost algorithm is also popular. Conclusion: This study first provides an updated perspective on machine learning-based AKI research, which may be beneficial for subsequent researchers to choose suitable journals and collaborators and may provide a more convenient and in-depth understanding of the research basis, hotspots and frontiers.

Targeted VEGFA therapy in regulating early acute kidney injury and late fibrosis.

Damage to peritubular capillaries is a key process that contributes to acute kidney injury (AKI) progression. Vascular endothelial growth factor A (VEGFA) plays a critical role in maintaining the renal microvasculature. However, the physiological role of VEGFA in various AKI durations remains unclear. A severe unilateral ischemia‒reperfusion injury model was established to provide an overview of VEGFA expression and the peritubular microvascular density from acute to chronic injury in mouse kidneys. Therapeutic strategies involving early VEGFA supplementation protecting against acute injury and late anti-VEGFA treatment for fibrosis alleviation were analyzed. A proteomic analysis was conducted to determine the potential mechanism of renal fibrosis alleviation by anti-VEGFA. The results showed that two peaks of extraglomerular VEGFA expression were observed during AKI progression: one occurred at the early phase of AKI, and the other occurred during the transition to chronic kidney disease (CKD). Capillary rarefaction progressed despite the high expression of VEGFA at the CKD stage, and VEGFA was associated with interstitial fibrosis. Early VEGFA supplementation protected against renal injury by preserving microvessel structures and counteracting secondary tubular hypoxic insults, whereas late anti-VEGFA treatment attenuated renal fibrosis progression. The proteomic analysis highlighted an array of biological processes related to fibrosis alleviation by anti-VEGFA, which included regulation of supramolecular fiber organization, cell-matrix adhesion, fibroblast migration, and vasculogenesis. These findings establish the landscape of VEGFA expression and its dual roles during AKI progression, which provides the possibility for the orderly regulation of VEGFA to alleviate early acute injury and late fibrosis.

Sevoflurane induces neurotoxic effects on developing neurons through the WNK1/NKCC1/Ca2+ /Drp-1 signalling pathway.

Children repeatedly exposed to anaesthesia have a high risk of cognitive impairment, but the mechanism of its regulation in this context is unknown. The objective of this study was to investigate the possible toxic mechanism of sevoflurane through the WNK1/NKCC1/Ca2+ /Drp-1 signalling pathway. The hippocampal neuronal HT22 cell line was used in this study. The intervention group was treated with the WNK1 inhibitor WNK-463, CaN inhibitor FK506 and Drp-1 inhibitor Mdivi-1 respectively in the medium for 30 min before sevoflurane anaesthesia. The sevofluane group and all intervention group treated with 4.1% sevoflurane for 6 h. Compared with the control group, sevoflurane treatment decreased cell viability and increased cellular apoptosis. Our study found that WNK-463, FK506 and Mdivi-1 can all alleviate the sevoflurane-induced reduction in cell viability, decrease the cell apoptosis. In addition, WNK-463 pretreatment could inhibit the increase of WNK1 kinase and NKCC1 protein concentration caused by sevoflurane. Further, sevoflurane anaesthesia causes intracellular calcium overload, increases the expression of CaN and induces the dephosphorylation of Drp-1 protein at ser637, while CaN inhibitor FK506 pretreatment could reduce the dephosphorylation of Drp-1. Therefore, the WNK1/NKCC1/Ca2+ /Drp-1 signalling pathway plays an important role in sevoflurane-related neurotoxicity. Reducing intracellular calcium influx may be one of the important mechanism to ameliorate sevoflurane toxicity.

Machine learning for acute kidney injury: Changing the traditional disease prediction mode.

Acute kidney injury (AKI) is a serious clinical comorbidity with clear short-term and long-term prognostic implications for inpatients. The diversity of risk factors for AKI has been recognized in previous studies, and a series of predictive models have been developed using traditional statistical methods in conjunction with its preventability, but they have failed to meet the expectations in limited clinical applications, the rapid spread of electronic health records and artificial intelligence machine learning technology has brought new hope for the construction of AKI prediction models. In this article, we systematically review the definition and classification of machine learning methods, modeling ideas and evaluation methods, and the characteristics and current status of modeling studies. According to the modeling objectives, we subdivided them into critical care medical setting models, all medical environment models, special surgery models, special disease models, and special nephrotoxin exposure models. As the first review article to comprehensively summarize and analyze machine learning prediction models for AKI, we aim to objectively describe the advantages and disadvantages of machine learning approaches to modeling, and help other researchers more quickly and intuitively understand the current status of modeling research, inspire ideas and learn from experience, so as to guide and stimulate more research and more in-depth exploration in the future, which will ultimately provide greater help to improve the overall status of AKI diagnosis and treatment.

Identifying Patients at Risk of Acute Kidney Injury among Patients Receiving Immune Checkpoint Inhibitors: A Machine Learning Approach.

Background: The benefits of immune checkpoint inhibitors (ICPis) in the treatment of patients with malignancies emerged recently, but immune-related adverse events (IRAEs), including acute kidney injury (AKI), cannot be ignored. The present study established and validated an ICPi-AKI prediction model based on machine learning algorithms to achieve early prediction of AKI events and timely intervention adjustment. Methods: We performed a retrospective study based on data from the First Medical Center of the PLA General Hospital. Patients with malignancy who received at least one dose of ICPi between January 2014 and December 2019 were included in the study. The characteristics of available variables were included after case review, and the baseline characteristics and clinical data of ICPi AKI and non-AKI patients were compared. After variable preprocessing, eight machine learning algorithms were used to construct a full variable availability model. Variable simplification models were constructed after screening important variables using the random forest recursive feature elimination method, and the performance of different machine learning methods and two types of modeling strategies were evaluated using multiple indicators. Results: Among the 1616 patients receiving checkpoint inhibitors, the overall incidence of AKI was 6.9% during the total follow-up time. Sixty-eight patients were associated with ICPi treatment after chart review, primarily in AKI stage 1 (70.5%), with a median time from first ICPi administration to AKI of 12.7 (IQR 2 to 56) weeks. The demographic characteristics, comorbidities, and proportions of malignancy types were similar between the ICPi-AKI and non-AKI groups, but there were significant differences in multiple characteristics, such as concomitant medications and laboratory test indicators. For model performance evaluation and comparison, the AUC values of all 38 variable availability models ranged from 0.7204−0.8241, and the AUC values of the simplicity model constructed using 16 significant variables ranged from 0.7528−0.8315. The neural networks model (NNs) and support vector machine (SVM) model had the best performance in the two types of modeling strategies, respectively; however, there was no significant difference in model performance comparison (p > 0.05). In addition, compared with the full variable availability model, the performance of the variable simplicity model was slightly improved. We also found that concomitant medications contributed more to the model prediction performance by screening the optimal feature combination. Conclusion: We successfully developed a machine learning-based ICPi-AKI prediction model and validated the best prediction performance of each machine model. It is reasonable to believe that clinical decision models driven by artificial intelligence can improve AKI prediction in patients with malignancies treated with ICPi. These models can be used to assist clinicians in the early identification of patients at high risk of AKI, support effective prevention and intervention, and ultimately improve the overall benefit of antitumor therapy in the target population.

Clinicopathological features and short outcomes of oliguric acute tubular injury.

PURPOSE: To explore the clinicopathological features and analyze the relevant risk factors and short-term renal outcomes of acute tubular injury (ATI) patients. MATERIALS AND METHODS: A total of 83 patients with biopsy-proven ATI were included in this retrospective cohort study. Clinical characteristic and histological feature data were collected, and renal recovery at 1 month postbiopsy was recorded. RESULTS: The severity of renal dysfunction, percentage of acute tubular lesions, interstitial inflammation and fibrosis of oliguric ATI patients were all significantly higher than those of nonoliguric patients. In the subgroup analysis of the oliguric patients, the serum creatinine and urinary microalbumin levels, severity of epithelial cell degeneration and cast formation of patients in the polyuric phase at biopsy were significantly lower than those of patients in the oliguric phase. A total of 59 patients had 1-month follow-up records, and complete renal recovery was observed in 42 patients. In the multivariate analysis, the total acute tubular injury area at biopsy was the most important independent risk factor for poor renal outcomes. CONCLUSIONS: Oliguric ATI patients had severe clinicopathological conditions. The severity of tubular lesions seriously influenced renal function recovery, demonstrating the importance of renal biopsy in assessing the prognosis of patients with kidney disease.

Comparison of the treatment efficacy of umbilical mesenchymal stem cell transplantation via renal subcapsular and parenchymal routes in AKI-CKD mice.

BACKGROUND: Mesenchymal stem cells (MSCs) have emerged as a promising cell-based therapy for acute kidney injury (AKI). However, the optimal route of MSC transplantation remains controversial, and there have been no comparisons of the therapeutic benefits of MSC administration through different delivery routes. METHODS: In this study, we encapsulated MSCs into a collagen matrix to help achieve local MSC retention in the kidney and assessed the survival of MSCs in vitro and in vivo. After transplanting collagen matrix-encapsulated-MSCs (Col-MSCs) under the renal capsule or into the parenchyma using the same cell dose and suspension volume in an ischemia/reperfusion injury model, we evaluated the treatment efficacy of two local transplantation routes at different stages of AKI. RESULTS: We found that Col-MSCs could be retained in the kidney for at least 14 days. Both local MSC therapies could reduce tubular injury, promote the proliferation of renal tubular epithelial cells on Day 3 and alleviate renal fibrosis on Day 14 and 28. MSC transplantation via the subcapsular route exerts better therapeutic effects for renal functional and structural recovery after AKI than MSC administration via the parenchymal route. CONCLUSIONS: Subcapsular MSC transplantation may be an ideal route of MSC delivery for AKI treatment, and collagen I can provide a superior microenvironment for cell-cell and cell-matrix interactions to stabilize the retention rate of MSCs in the kidney.

Effects of individualized PEEP obtained by two different titration methods on postoperative atelectasis in obese patients: study protocol for a randomized controlled trial.

BACKGROUND: The incidence of postoperative pulmonary complications (PPCs) is higher in obese patients undergoing general anesthesia and mechanical ventilation due to the reduction of oxygen reserve, functional residual capacity, and lung compliance. Individualized positive end-expiratory pressure (iPEEP) along with other lung-protective strategies is effective in alleviating postoperative atelectasis. Here, we compared the best static lung compliance (Cstat) titration of iPEEP with electrical impedance tomography (EIT) titration to observe their effects on postoperative atelectasis in obese patients undergoing laparoscopic surgery. METHODS: A total number of 140 obese patients with BMI ≥ 32.5kg/m2 undergoing elective laparoscopic gastric volume reduction and at moderate to high risk of developing PPCs will be enrolled and randomized into the optimal static lung compliance-directed iPEEP group and EIT titration iPEEP group. The primary endpoint will be pulmonary atelectasis measured and calculated by EIT immediately after extubation and 2 h after surgery. Secondary endpoints will be intraoperative oxygenation index, organ dysfunction, incidence of PPCs, hospital expenses, and length of hospital stay. DISCUSSION: Many iPEEP titration methods effective for normal weight patients may not be appropriate for obese patients. Although EIT-guided iPEEP titration is effective in obese patients, its high price and complexity limit its application in many clinical facilities. This trial will test the efficacy of iPEEP via the optimal static lung compliance-guided titration procedure by comparing it with EIT-guided PEEP titration. The results of this trial will provide a feasible and convenient method for anesthesiologists to set individualized PEEP for obese patients during laparoscopic surgery. TRIAL REGISTRATION: ClinicalTrials.gov ChiCTR2000039144 . Registered on October 19, 2020.

Perioperative transcutaneous electrical acupoint stimulation for improving postoperative gastrointestinal function: A randomized controlled trial.

BACKGROUND: Postoperative gastrointestinal dysfunction (PGD) is one of the most common complications in patients undergoing major abdominal surgery. Acupuncture has been used widely in gastrointestinal diseases due to its effectiveness and minimally invasive nature. OBJECTIVE: This study evaluated the efficacy of using transcutaneous electrical acupoint stimulation (TEAS) during the surgery and postoperative recovery in patients with gastric and colorectal surgery for improving postoperative gastrointestinal function. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS: A total of 280 patients undergoing abdominal surgery were stratified by type of surgery (i.e., gastric or colorectal surgery) and randomly allocated into the TEAS group (group T) or the sham group (group S). Patients in group T received TEAS at LI4, PC6, ST36 and ST37. Patients in group S received pseudo-TEAS at sham acupoints. The stimulation was given from 30 min before anesthesia until the end of surgery. The same treatment was performed at 9 am on the 1st, 2nd and 3rd days after surgery, until the recovery of flatus in patients. MAIN OUTCOME MEASURES: The primary outcome was the time to the first bowel motion, as detected by auscultation. The secondary outcomes included the first flatus and ambulation time, changes of perioperative substance P (SP), incidence of PGD, postoperative pain, postoperative nausea and vomiting (PONV) and some economic indicators. RESULTS: The time to first bowel motion, first flatus and first ambulation in group T was much shorter than that in group S (P < 0.01). In patients undergoing colorectal surgery, the concentration of SP was lower in group T than in group S on the third day after the operation (P < 0.05). The average incidence of PGD in all patients was 25%, and the frequency of PGD was significantly lower in group T than in group S (18.6% vs. 31.4%, respectively; P < 0.05). TEAS treatment (odds ratio = 0.498; 95% confidence interval: 0.232-0.786) and type of surgery were relevant factors for the development of PGD. Postoperative pain score and PONV occurrence were significantly lower in group T (P < 0.01). Postoperative hospitalization days and the resulting cost to patients were greatly reduced in the TEAS group (P < 0.01). CONCLUSION: Perioperative TEAS was able to promote the recovery of postoperative gastrointestinal function, reduce the incidence of PGD and PONV. The concentration of SP was decreased by TEAS treatment, which indicates that the brain-gut axis may play a role in how TEAS regulates gastrointestinal function. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1900023263.

Validity and Usability of a Smartphone Image-Based Dietary Assessment App Compared to 3-Day Food Diaries in Assessing Dietary Intake Among Canadian Adults: Randomized Controlled Trial.

BACKGROUND: Accurate dietary assessment is needed in studies that include analysis of nutritional intake. Image-based dietary assessment apps have gained in popularity for assessing diet, which may ease researcher and participant burden compared to traditional pen-to-paper methods. However, few studies report the validity of these apps for use in research. Keenoa is a smartphone image-based dietary assessment app that recognizes and identifies food items using artificial intelligence and permits real-time editing of food journals. OBJECTIVE: This study aimed to assess the relative validity of an image-based dietary assessment app - Keenoa - against a 3-day food diary (3DFD) and to test its usability in a sample of healthy Canadian adults. METHODS: We recruited 102 participants to complete two 3-day food records. For 2 weeks, on 2 non-consecutive days and 1 weekend day, in random order, participants completed a traditional pen-to-paper 3DFD and the Keenoa app. At the end of the study, participants completed the System Usability Scale. The nutrient analyses of the 3DFD and Keenoa data before (Keenoa-participant) and after they were reviewed by dietitians (Keenoa-dietitian) were analyzed using analysis of variance. Multiple tests, including the Pearson coefficient, cross-classification, kappa score, % difference, paired t test, and Bland-Altman test, were performed to analyze the validity of Keenoa (Keenoa-dietitian). RESULTS: The study was completed by 72 subjects. Most variables were significantly different between Keenoa-participant and Keenoa-dietitian (P<.05) except for energy, protein, carbohydrates, fiber, vitamin B1, vitamin B12, vitamin C, vitamin D, and potassium. Significant differences in total energy, protein, carbohydrates, % fat, saturated fatty acids, iron, and potassium were found between the 3DFD and Keenoa-dietitian data (P<.05). The Pearson correlation coefficients between the Keenoa-dietitian and 3DFD ranged from .04 to .51. Differences between the mean intakes assessed by the 3DFD and Keenoa-dietitian were within 10% except for vitamin D (misclassification rate=33.8%). The majority of nutrients were within an acceptable range of agreement in the Bland-Altman analysis; no agreements were seen for total energy, protein, carbohydrates, fat (%), saturated fatty acids, iron, potassium, and sodium (P<.05). According to the System Usability Scale, 34.2% of the participants preferred using Keenoa, while 9.6% preferred the 3DFD. CONCLUSIONS: The Keenoa app provides acceptable relative validity for some nutrients compared to the 3DFD. However, the average intake of some nutrients, including energy, protein, carbohydrates, % fat, saturated fatty acids, and iron, differed from the average obtained using the 3DFD. These findings highlight the importance of verifying data entries of participants before proceeding with nutrient analysis. Overall, Keenoa showed better validity at the group level than the individual level, suggesting it can be used when focusing on the dietary intake of the general population. Further research is recommended with larger sample sizes and objective dietary assessment approaches.

The polydopamine-enhanced superadhesion and fracture strength of honeycomb polyurethane porous membranes.

The superhydrophobic properties of biological surfaces in nature have attracted extensive attention in scientific and industrial circles. Relative to the rolling superhydrophobic state of lotus leaves, the adhesive superhydrophobic state of geckos and Parthenocissus tricuspidata is also significant in many fields. In this work, polydopamine (PDA) with its excellent biological compatibility and strong adhesion was selected as a substance to simulate the secretion of the suckers of P. tricuspidata and it was precipitated at the surface of honeycomb polyurethane porous membranes (PUPM). The results demonstrated that the honeycomb PUPM, as prepared, displayed special super-adhesion properties similar to those of geckos and P. tricuspidata. PDA formed via self-polymerization in aqueous solution was equivalent to a double-sided adhesive, acquiring a micro-nano structure of PDA and PUPM and displaying increased surface hydrophobicity and improved adhesion properties. Even when the surface precipitation of PDA and modification with n-dodecyl mercaptan made the contact angle increase to more than 160°, the surface adhesion to water was rather strong and remained stable. The addition of the PDA adhesive can effectively change the microporous structure of PUPM, enhancing the viscosity, and facilitating an enhancement in the fracture strength.