Octreotide ameliorates hepatic ischemia-reperfusion injury through SNHG12/TAF15-mediated Sirt1 stabilization and YAP1 transcription.

BACKGROUND: Hepatic ischemia-reperfusion (HIR) injury is a pathological condition initiated by interrupted hepatic blood supply and exaggerated after reperfusion, which is one of the most lethal risks in liver transplantation and other liver surgeries. We aimed to investigate the protective mechanism of octreotide (Oct) against HIR injury. METHODS: The function of Oct was evaluated in the in vivo mouse model of HIR injury. Histological examinations were performed to assess the pathological changes. Serum parameters including ALT and AST were measured to evaluate the liver damage. qRT-PCR and western blot analysis were employed to determine the levels of long non-coding RNA SNHG12 (SNHG12) and autophagy or apoptosis-related proteins. RNA pull-down and RIP assays were used to verify the interaction between SNHG12 and TAF15. The transcriptional regulation of TAF15 in YAP1 was validated by ChIP and luciferase reporter assays. RESULTS: In the in vivo HIR injury model, Oct efficiently alleviated HIR-caused hepatic damage by suppressing apoptosis and activating autophagy. However, silencing of SNHG12 abrogated the protective effects of Oct via inactivating autophagy. Further mechanism investigation revealed that SNHG12 promoted the stabilization of Sirt1 and increased YAP1 transcriptional activity via interacting with TAF15. Up-regulation of Sirt1 and YAP1 was essential for maintaining the protective effect of Oct against HIR injury through increasing autophagic flux and suppressing apoptosis. CONCLUSIONS: Oct-induced up-regulation of SNHG12 attenuated HIR injury via promoting Sirt1 stabilization and YAP1 transcription to activate autophagy and repress apoptosis.

Screening high-risk population of persistent postpartum hypertension in women with preeclampsia using latent class cluster analysis.

BACKGROUND: A significant proportion of women with preeclampsia (PE) exhibit persistent postpartum hypertension (PHTN) at 3 months postpartum associated with cardiovascular morbidity. This study aimed to screen patients with PE to identify the high-risk population with persistent PHTN. METHODS: This retrospective cohort study enrolled 1,000 PE patients with complete parturient and postpartum blood pressure (BP) profiles at 3 months postpartum. The enrolled patients exhibited new-onset hypertension after 20 weeks of pregnancy, while those with PE superimposed upon chronic hypertension were excluded. Latent class cluster analysis (LCCA), a method of unsupervised learning in machine learning, was performed to ascertain maternal exposure clusters from eight variables and 35 subordinate risk factors. Logistic regression was applied to calculate odds ratios (OR) indicating the association between clusters and PHTN. RESULTS: The 1,000 participants were classified into three exposure clusters (subpopulations with similar characteristics) according to persistent PHTN development: high-risk cluster (31.2%), medium-risk cluster (36.8%), and low-risk cluster (32.0%). Among the 1,000 PE patients, a total of 134 (13.4%) were diagnosed with persistent PHTN, while the percentages of persistent PHTN were24.68%, 10.05%, and 6.25% in the high-, medium-, and low-risk clusters, respectively. Persistent PHTN in the high-risk cluster was nearly five times higher (OR, 4.915; 95% confidence interval (CI), 2.92-8.27) and three times (OR, 2.931; 95% CI, 1.91-4.49) than in the low- and medium-risk clusters, respectively. Persistent PHTN did not differ between the medium- and low-risk clusters. Subjects in the high-risk cluster were older and showed higher BP, poorer prenatal organ function, more adverse pregnancy events, and greater medication requirement than the other two groups. CONCLUSION: Patients with PE can be classified into high-, medium-, and low-risk clusters according to persistent PHTN severity; each cluster has cognizable clinical features. This study's findings stress the importance of controlling persistent PHTN to prevent future cardiovascular disease.

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model.

BACKGROUND: Chronic heart failure (CHF) comorbid with atrial fibrillation (AF) is a serious threat to human health and has become a major clinical burden. This prospective cohort study was performed to design a risk stratification system based on the light gradient boosting machine (LightGBM) model to accurately predict the 1- to 3-year all-cause mortality of patients with CHF comorbid with AF. METHODS: Electronic medical records of hospitalized patients with CHF comorbid with AF from January 2014 to April 2019 were collected. The data set was randomly divided into a training set and test set at a 3:1 ratio. In the training set, the synthetic minority over-sampling technique (SMOTE) algorithm and fivefold cross validation were used for LightGBM model training, and the model performance was performed on the test set and compared using the logistic regression method. The survival rate was presented on a Kaplan-Meier curve and compared by a log-rank test, and the hazard ratio was calculated by a Cox proportional hazard model. RESULTS: Of the included 1796 patients, the 1-, 2-, and 3-year cumulative mortality rates were 7.74%, 10.63%, and 12.43%, respectively. Compared with the logistic regression model, the LightGBM model showed better predictive performance, the area under the receiver operating characteristic curve for 1-, 2-, and 3-year all-cause mortality was 0.718 (95%CI, 0.710-0.727), 0.744(95%CI, 0.737-0.751), and 0.757 (95%CI, 0.751-0.763), respectively. The net reclassification index was 0.062 (95%CI, 0.044-0.079), 0.154 (95%CI, 0.138-0.172), and 0.148 (95%CI, 0.133-0.164), respectively. The differences between the two models were statistically significant (P < 0.05). Patients in the high-risk group had a significantly higher hazard of death than those in the low-risk group (hazard ratios: 12.68, 13.13, 14.82, P < 0.05). CONCLUSION: Risk stratification based on the LightGBM model showed better discriminative ability than traditional model in predicting 1- to 3-year all-cause mortality of patients with CHF comorbid with AF. Individual patients' prognosis could also be obtained, and the subgroup of patients with a higher risk of mortality could be identified. It can help clinicians identify and manage high- and low-risk patients and carry out more targeted intervention measures to realize precision medicine and the optimal allocation of health care resources.

Roles of diencephalon/mesencephalon homeobox 1 in the development and prognosis of hepatocellular carcinoma.

INTRODUCTION AND OBJECTIVES: The oncogene diencephalon/mesencephalon homeobox 1 (DMBX1) is widely overexpressed in a variety of human cancers. The present study aimed to analyze the expression and clinical importance of DMBX1 in nonneoplastic tissues and tumor tissues from patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS: DMBX1 expression in HCC and adjacent nontumor tissues was analyzed using immunohistochemical staining. Chi-square tests were applied to compare DMBX1 expression between the tumors and the adjacent normal tissues. We explored the correlation of DMBX1 expression with clinicopathological factors and its effect on the prognosis of HCC. Finally, we investigated the role of DMBX1 in HCC via knockdown experiments, which analyzed changes in cell invasion, cell proliferation and epithelial-mesenchymal transition (EMT) biomarkers (E-cadherin, N-cadherin, vimentin). The mRNAs that were coexpressed with DMBX1 in HCC, based on the TCGA cohort (n = 366), were obtained from the cBioPortal database. RESULTS: The average score for DMBX1 expression was significantly different (P < 0.001) between HCC and paired adjacent nontumor tissues, and DMBX1 expression correlated with hepatitis B virus (HBV) infection, tumor size, metastasis, and tumor node metastasis (TNM) stage (P < 0.05). A multivariate Cox regression analysis identified significant correlations of DMBX1 expression with tumor metastasis, TNM stage, and tumor capsule. Moreover, Kaplan-Meier survival analysis revealed an association between DMBX1 overexpression and shorter overall survival of patients with HCC (P < 0.05). In HCC cell lines, silencing DMBX1 markedly inhibited migration, proliferation and EMT markers. The mRNAs that were negatively (R ≤ -0.25, n = 1094) or positively (R ≥ 0.25, n = 2906) coexpressed with DMBX1 mRNA were selected for further Gene Ontology enrichment analysis, and the results revealed that the predicted functions of DMBX1 in HCC support the in vitro experimental results. CONCLUSIONS: Our data provide evidence that DMBX1 overexpression is associated with HCC metastasis and poor prognosis, suggesting that DMBX1 represents a therapeutic target in HCC.

A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure.

BACKGROUND: Health-related quality of life, as evaluated by a patient-reported outcomes measure (PROM), is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure. METHODS: Using a PROM as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising of 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. A Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results. RESULTS: The median follow-up period in the study was 372 days. After a final COX regression analysis, the gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with a concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability. CONCLUSIONS: This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

Assessment of the synergic effect of immunomodulation on nerve repair using multiparametric magnetic resonance imaging.

INTRODUCTION: The immune system plays a pivotal role in nerve injury. The aim of this study was to determine the role of multiparametric magnetic resonance imaging (MRI) in evaluation of the synergic effect of immunomodulation on nerve regeneration in neurotmesis. METHODS: Rats with sciatic nerve neurotmesis and surgical repair underwent serial multiparametric MR examinations over an 8-week period after subepineurial microinjection of lipopolysaccharide (LPS) and subsequent subcutaneous injection of FK506 or subepineurial microinjection of LPS or phosphate-buffered saline (PBS) alone. RESULTS: Nerves treated with immunomodulation showed more prominent regeneration than those treated with LPS or PBS alone and more rapid restoration toward normal T2, fractional anisotropy (FA), and radial diffusivity (RD) values than nerves injected with LPS or PBS. DISCUSSION: Nerves treated with immunomodulation exert synergic beneficial effects on nerve regeneration that can be predicted by T2 measurements and FA and RD values. Muscle Nerve 57: E38-E45, 2018.

Monitoring of macrophage recruitment enhanced by Toll-like receptor 4 activation with MR imaging in nerve injury.

INTRODUCTION: Macrophage recruitment is critical for nerve regeneration after an injury. The aim of this study was to investigate whether ultrasmall superparamagnetic iron oxide (USPIO) nanoparticle-based MRI could be used to monitor the enhanced macrophage recruitment by Toll-like receptor 4 (TLR4) activation in nerve injury. METHODS: Rats received intraperitoneal injections of either lipopolysaccharide (LPS) or phosphate buffered saline (PBS) or no injection (controls) after a sciatic nerve crush injury. After intravenous injection of the USPIOs (LPS and PBS groups) or PBS (control group), MRI was performed and correlated with histological findings. RESULTS: LPS group showed more remarkable hypointense signals on T2*-weighted imaging and lower T2 values in the crushed nerves than PBS group. The hypointense signal areas were associated with an enhanced recruitment of iron-loaded macrophages to the injured nerves. DISCUSSION: USPIO-enhanced MRI can be used to monitor the enhanced macrophage recruitment by means of TLR4 signal pathway activation in nerve injury. Muscle Nerve, 2018.

DTI metrics can be used as biomarkers to determine the therapeutic effect of stem cells in acute peripheral nerve injury.

PURPOSE: To determine the role of diffusion tensor imaging (DTI) metrics as biomarkers for the therapeutic effects of mesenchymal stem cells (MSCs) in acute peripheral nerve injury. MATERIALS AND METHODS: Forty-four adult rats received subepineurial microinjection of MSCs (n = 22) or phosphate buffered saline (PBS, n = 22) 1 week after the sciatic nerve trunk crush injury. Sequential fat-suppressed T2-weighted imaging, T2 measurement, DTI and sciatic nerve functional assessment were performed at a 3.0 Tesla MR unit over an 8-week follow-up, with histological assessments performed at regular intervals. The sciatic nerve function index, T2 value, and DTI metrics, including fractional anisotropy (FA), axial diffusivity, radial diffusivity (RD), and mean diffusivity values of the distal stumps of crushed nerves were measured and compared between the two groups. RESULTS: Nerves treated with MSCs showed better functional recovery and exhibited more pronounced nerve regeneration compared with nerves treated with PBS. T2 values in nerves treated with MSCs or PBS showed a similar change pattern (P = 0.174), while FA and RD values in nerves treated with MSCs showed more rapid return (one week earlier) to baseline level than nerves treated with PBS (P = 0.045; 0.035). Nerves treated with MSCs had higher FA and lower RD values than nerves treated with PBS during the period from 2 to 3 weeks after surgery (P ≤ 0.0001, 0.004; P = 0.004, 0.006). CONCLUSION: FA and RD values derived from DTI might be used as sensitive biomarkers for detecting the therapeutic effect of stem cells in acute peripheral nerve crush injuries. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:855-862.

Guaranteed classification via regularized similarity learning.

Learning an appropriate (dis)similarity function from the available data is a central problem in machine learning, since the success of many machine learning algorithms critically depends on the choice of a similarity function to compare examples. Despite many approaches to similarity metric learning that have been proposed, there has been little theoretical study on the links between similarity metric learning and the classification performance of the resulting classifier. In this letter, we propose a regularized similarity learning formulation associated with general matrix norms and establish their generalization bounds. We show that the generalization error of the resulting linear classifier can be bounded by the derived generalization bound of similarity learning. This shows that a good generalization of the learned similarity function guarantees a good classification of the resulting linear classifier. Our results extend and improve those obtained by Bellet, Habrard, and Sebban (2012). Due to the techniques dependent on the notion of uniform stability (Bousquet & Elisseeff, 2002), the bound obtained there holds true only for the Frobenius matrix-norm regularization. Our techniques using the Rademacher complexity (Bartlett & Mendelson, 2002) and its related Khinchin-type inequality enable us to establish bounds for regularized similarity learning formulations associated with general matrix norms, including sparse L1-norm and mixed (2,1)-norm.

Assessing the stress-relief impact of an art-based intervention inspired by the broaden-and-build theory in college students.

Background and objectives: This study's primary objective is to investigate the impact of art-making on the mental well-being of college students, who often experience heightened stress during their initial university years. Methods: Employing a comprehensive methodology, combining interviews and the Perceived Stress Scale (PSS), the research aimed to assess whether a four-week art-making intervention can effectively alleviate stress levels among college students. In the experimental group, participants engaged in a variety of art-making activities, including freehand drawing, clay modeling, and crafting. Results: The results revealed that, in the pre-test, there were no significant differences between the experimental and control groups for each assessed indicator. However, in the post-test, significant differences emerged across all indicators. Further analysis demonstrated a significant reduction in stress perception among the experimental group participants between the pre-test and post-test phases. Conclusion: In conclusion, this study provides compelling evidence that art-making has the potential to foster positive personal development and significantly reduce stress levels among college students.

Joint Exposure to Multiple Air Pollutants, Genetic Susceptibility, and Incident Dementia: A Prospective Analysis in the UK Biobank Cohort.

Objectives: This study aimed to evaluate the joint effects of multiple air pollutants including PM2.5, PM10, NO2, and NOx with dementia and examined the modifying effects of genetic susceptibility. Methods: This study included 220,963 UK Biobank participants without dementia at baseline. Weighted air pollution score reflecting the joint exposure to multiple air pollutants were constructed by cross-validation analyses, and inverse-variance weighted meta-analyses were performed to create a pooled effect. The modifying effect of genetic susceptibility on air pollution score was assessed by genetic risk score and APOE ε4 genotype. Results: The HR (95% CI) of dementia for per interquartile range increase of air pollution score was 1.13 (1.07∼1.18). Compared with the lowest quartile (Q1) of air pollution score, the HR (95% CI) of Q4 was 1.26 (1.13∼1.40) (P trend = 2.17 × 10-5). Participants with high air pollution score and high genetic susceptibility had higher risk of dementia compared to those with low air pollution score and low genetic susceptibility. Conclusion: Our study provides evidence that joint exposure to multiple air pollutants substantially increases the risk of dementia, especially among individuals with high genetic susceptibility.

Alleviation of Salt Stress and Changes in Glycyrrhizic Acid Accumulation by Dark Septate Endophytes in Glycyrrhiza glabra Grown under Salt Stress.

This study aimed to investigate the mechanisms by which dark septate endophytes (DSE) regulate salt tolerance and the accumulation of bioactive constituents in licorice. First, the salt stress tolerance and resynthesis with the plant effect of isolated DSE from wild licorice were tested. Second, the performance of licorice inoculated with DSE, which had the best salt-tolerant and growth-promoting effects, was examined under salt stress. All isolated DSE showed salt tolerance and promoted plant growth, withCurvularia lunata D43 being the most effective. Under salt stress, C. lunata D43 could promote growth, increase antioxidant enzyme activities, enhance glycyrrhizic acid accumulation, improve key enzyme activities in the glycyrrhizic acid synthesis pathway, and induce the expression of the key enzyme gene and salt tolerance gene of licorice. The structural equation model demonstrated that DSE alleviate the negative effects of salt stress through direct and indirect pathways. Variations in key enzyme activities, gene expression, and bioactive constituent concentration can be attributed to the effects of DSE. These results contribute to revealing the value of DSE for cultivating medicinal plants in saline soils.

Enhanced active-site electric field accelerates enzyme catalysis.

The design and improvement of enzymes based on physical principles remain challenging. Here we demonstrate that the principle of electrostatic catalysis can be leveraged to substantially improve a natural enzyme's activity. We enhanced the active-site electric field in horse liver alcohol dehydrogenase by replacing the serine hydrogen-bond donor with threonine and replacing the catalytic Zn2+ with Co2+. Based on the electric field enhancement, we make a quantitative prediction of rate acceleration-50-fold faster than the wild-type enzyme-which was in close agreement with experimental measurements. The effects of the hydrogen bonding and metal coordination, two distinct chemical forces, are described by a unified physical quantity-electric field, which is quantitative, and shown here to be additive and predictive. These results suggest a new design paradigm for both biological and non-biological catalysts.

Long-term adverse influence of smoking during pregnancy on height and body size of offspring at ten years old in the UK Biobank cohort.

Background: To explore the long-term relationship between maternal smoking during pregnancy and early childhood growth in the UK Biobank cohort. Methods: To estimate the effect of maternal smoking during pregnancy on offspring height and body size at ten years old, we performed binary logistic analyses and reported odds ratios (OR) as well as 95% confidence intervals (95%CIs). We also implemented the cross-contextual comparison study to examine whether such influence could be repeatedly observed among three different ethnicities in the UK Biobank cohort (n = 22,140 for White, n = 7094 for South Asian, and n = 5000 for Black). In particular, we conducted the sibling cohort study in White sibling cohort (n = 9953 for height and n = 7239 for body size) to control for unmeasured familial confounders. Results: We discovered that children whose mothers smoked during pregnancy had greater risk of being shorter or plumper at age ten in the full UK Biobank White cohort, with 15.3% (95% CIs: 13.0%∼17.7%) higher risk for height and 32.4% (95%CIs: 29.5%∼35.4%) larger risk for body size. Similar associations were identified in the South Asian and Black ethnicities. These associations were robust and remained significant in the White sibling cohort (12.6% [95%CIs: 5.0%∼20.3%] for height and 36.1% [95%CIs: 26.3%∼45.9%] for body size) after controlling for family factors. Conclusion: This study robustly confirms that maternal smoking during pregnancy can promote height deficit and obesity for offspring at ten years old. Our findings strongly encourage mothers to quit smoking during pregnancy for improving growth and development of offspring.

Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006-2022 UK Biobank data.

Objectives: Adverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs. Methods: Seven categories of ACE and four classifications of psychiatric disorders were defined in a sample of 126,064 participants identified by the UK Biobank from 2006-2022, and correlations were investigated using logistic regression models. Then, to explore nonlinear relationships, restricted spline models were developed to examine differences in sex and age across cohorts (n = 126,064 for the full cohort and n = 121,934 for the European cohort). Finally, the impact of the category of ACEs on psychiatric disorders was examined. Results: After controlling for confounders, ACEs scores showed dose-dependent relationships with depression, anxiety, anxiety-depression co-morbidity, and at least one (any of the first three outcomes) in all models. ACEs with different scores were significantly positively correlated with the four psychiatric disorders classifications, with the highest odds of anxiety-depression co-morbidity (odds ratio [OR] = 4.87, 95% confidence intervals [CI]: 4.37 ~ 5.43), p = 6.08 × 10-178. In the restricted cubic spline models, the risk was relatively flat for females at ACEs = 0-1 and males at ACEs = 0-2/3 (except in males, where ACEs were associated with a lower risk of anxiety, all other psychiatric disorders had an increased risk of morbidity after risk smoothing). In addition, the risk of having anxiety, depression, anxiety-depression co-morbidity, and at least one of these disorders varies with each category of ACEs. Conclusion: The prevalence of anxiety-depression comorbidity was highest across ACE scores after controlling for confounding factors and had a significant effect on each category of ACEs.

Ecological shifts of salivary microbiota associated with metabolic-associated fatty liver disease.

Introduction: Metabolic-associated fatty liver disease (MAFLD) is the most common chronic liver disease related to metabolic syndrome. However, ecological shifts in the saliva microbiome in patients with MAFLD remain unknown. This study aimed to investigate the changes to the salivary microbial community in patients with MAFLD and explore the potential function of microbiota. Methods: Salivary microbiomes from ten MAFLD patients and ten healthy participants were analyzed by 16S rRNA amplicon sequencing and bioinformatics analysis. Body composition, plasma enzymes, hormones, and blood lipid profiles were assessed with physical examinations and laboratory tests. Results: The salivary microbiome of MAFLD patients was characterized by increased α-diversity and distinct ß-diversity clustering compared with control subjects. Linear discriminant analysis effect size analysis showed a total of 44 taxa significantly differed between the two groups. Genera Neisseria, Filifactor, and Capnocytophaga were identified as differentially enriched genera for comparison of the two groups. Co-occurrence networks suggested that the salivary microbiota from MAFLD patients exhibited more intricate and robust interrelationships. The diagnostic model based on the salivary microbiome achieved a good diagnostic power with an area under the curve of 0.82(95% CI: 0.61-1). Redundancy analysis and spearman correlation analysis revealed that clinical variables related to insulin resistance and obesity were strongly associated with the microbial community. Metagenomic predictions based on Phylogenetic Investigation of Communities by Reconstruction of Unobserved States revealed that pathways related to metabolism were more prevalent in the two groups. Conclusions: Patients with MAFLD manifested ecological shifts in the salivary microbiome, and the saliva microbiome-based diagnostic model provides a promising approach for auxiliary MAFLD diagnosis.

Typical Zollinger-Ellison syndrome-atypical location of gastrinoma and absence of hypergastrinemia: A case report and review of literature.

BACKGROUND: Zollinger-Ellison syndrome (ZES) results from hypersecretion of gastrin from pancreatic or duodenal neuroendocrine tumors, commonly referred to as gastrinomas. The high levels of gastrin lead to a typical presentation involving watery diarrhea and multiple ulcers in the duodenum. Here, we have presented the rare case of a patient with ZES and absence of hypergastrinemia as well as an atypical location of gastrinoma. CASE SUMMARY: A 72-year-old woman presented with the typical clinical manifestations of ZES, including upper abdominal pain, significant watery diarrhea, and acidic liquid vomitus. Surprisingly, however, she did not have an increased level of serum gastrin. In addition, there was no evidence of gastrinoma or any other ulcerogenic tumor. Esophagogastroduodenoscopy was conducted to examine the upper digestive tract. Revised diagnoses were considered, and an individualized treatment plan was developed. The patient responded to antacid medication while experiencing intermittent, recurring bouts of ZES. 18F-AlF-NOTA-octreotide positron emission tomography (18F-OC PET)/computed tomography (CT) helped locate the tumor. Postoperative pathology and immunohistochemistry results suggested that the tumor was a gastrinoma located at an unconventional site. CONCLUSION: This present case study demonstrates the possibility of ZES-like manifestation in patients with absence of hypergastrinemia. 18F-OC PET/CT is a relatively new imaging technique that can be applied for diagnosing even tiny gastrinomas that are atypical in terms of location.

An immunomodulatory polypeptide hydrogel for osteochondral defect repair.

Osteochondral injury is a common and frequent orthopedic disease that can lead to more serious degenerative joint disease. Tissue engineering is a promising modality for osteochondral repair, but the implanted scaffolds are often immunogenic and can induce unwanted foreign body reaction (FBR). Here, we prepare a polypept(o)ide-based PAA-RGD hydrogel using a novel thiol/thioester dual-functionalized hyperbranched polypeptide P(EG3Glu-co-Cys) and maleimide-functionalized polysarcosine under biologically benign conditions. The PAA-RGD hydrogel shows suitable biodegradability, excellent biocompatibility, and low immunogenicity, which together lead to optimal performance for osteochondral repair in New Zealand white rabbits even at the early stage of implantation. Further in vitro and in vivo mechanistic studies corroborate the immunomodulatory role of the PAA-RGD hydrogel, which induces minimum FBR responses and a high level of polarization of macrophages into the immunosuppressive M2 subtypes. These findings demonstrate the promising potential of the PAA-RGD hydrogel for osteochondral regeneration and highlight the importance of immunomodulation. The results may inspire the development of PAA-based materials for not only osteochondral defect repair but also various other tissue engineering and bio-implantation applications.

Joint elasticity produces energy efficiency in underwater locomotion: Verification with deep reinforcement learning.

Underwater snake robots have received attention because of their unique mechanics and locomotion patterns. Given their highly redundant degrees of freedom, designing an energy-efficient gait has been a main challenge for the long-term autonomy of underwater snake robots. We propose a gait design method for an underwater snake robot based on deep reinforcement learning and curriculum learning. For comparison, we consider the gait generated by a conventional parametric gait equation controller as the baseline. Furthermore, inspired by the joints of living organisms, we consider elasticity (stiffness) in the joints of the snake robot to verify whether it contributes to the generation of energy efficiency in the underwater gait. We first demonstrate that the deep reinforcement learning controller can produce a more energy-efficient gait than the gait equation controller in underwater locomotion, by finding the control patterns which maximize the effect of energy efficiency through the exploitation of joint elasticity. In addition, appropriate joint elasticity can increase the maximum velocity achievable by a snake robot. Finally, simulation results in different liquid environments confirm that the deep reinforcement learning controller is superior to the gait equation controller, and it can find adaptive energy-efficient motion even when the liquid environment is changed. The video can be viewed at https://youtu.be/wpwQihhntEY.

NCP-BiRW: A Hybrid Approach for Predicting Long Noncoding RNA-Disease Associations by Network Consistency Projection and Bi-Random Walk.

Long non-coding RNAs (lncRNAs) play significant roles in the disease process. Understanding the pathological mechanisms of lncRNAs during the course of various diseases will help clinicians prevent and treat diseases. With the emergence of high-throughput techniques, many biological experiments have been developed to study lncRNA-disease associations. Because experimental methods are costly, slow, and laborious, a growing number of computational models have emerged. Here, we present a new approach using network consistency projection and bi-random walk (NCP-BiRW) to infer hidden lncRNA-disease associations. First, integrated similarity networks for lncRNAs and diseases were constructed by merging similarity information. Subsequently, network consistency projection was applied to calculate space projection scores for lncRNAs and diseases, which were then introduced into a bi-random walk method for association prediction. To test model performance, we employed 5- and 10-fold cross-validation, with the area under the receiver operating characteristic curve as the evaluation indicator. The computational results showed that our method outperformed the other five advanced algorithms. In addition, the novel method was applied to another dataset in the Mammalian ncRNA-Disease Repository (MNDR) database and showed excellent performance. Finally, case studies were carried out on atherosclerosis and leukemia to confirm the effectiveness of our method in practice. In conclusion, we could infer lncRNA-disease associations using the NCP-BiRW model, which may benefit biomedical studies in the future.