The effect of metabolic factors on the association between hyperuricemia and chronic kidney disease: a retrospective cohort mediation analysis.

BACKGROUND: Hyperuricemia, hyperglycemia, hypertension, hyperlipidemia, and hyperhomocysteinemia are all established risk factors for chronic kidney disease (CKD), and their interplay could exacerbate CKD progression. This study aims to evaluate the potential mediation effects of hyperglycemia, hypertension, hyperlipidemia, and hyperhomocysteinemia on the association between hyperuricemia (HUA) and chronic kidney disease (CKD). METHODS: We collected electronic medical record data from 2055 participants who underwent physical examinations at the Affiliated Hospital of Qingdao University. The data were utilized to investigate the mediating effect of various factors including systolic blood pressure (SBP), diastolic blood pressure (DBP), homocysteine (HCY), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), blood glucose (Glu), and hemoglobin A1c (HbA1c) on the relationship between HUA and CKD. RESULTS: Upon adjusting for confounding variables, mediation analysis indicated that only HCY acted as a mediator in the HUA-CKD relationship (p value < 0.05), exhibiting a statistically significant mediation effect of 7.04%. However, after adjustment for multiple testing, none of these variables were statistically significant. CONCLUSIONS: Considering the observed associations between hyperuricemia, hyperglycemia, hypertension, hyperlipidemia, and CKD, none of the factors of interest remained statistically significant after adjusting for multiple testing as potential mediators of hyperuricemia on CKD.

Renoprotective Effect of Isoorientin in Diabetic Nephropathy via Activating Autophagy and Inhibiting the PI3K-AKT-TSC2-mTOR Pathway.

Diabetic nephropathy (DN) is one of the most serious complications of diabetes and the most common cause of death. The autophagy of podocytes plays an important role in the pathogenesis of DN. Here, through screening the constituent compounds of practical and useful Chinese herbal formulas, we identified that isoorientin (ISO) strongly promoted the autophagy of podocytes and could effectively protect podocytes from high glucose (HG)-induced injury. ISO significantly improved autophagic clearance of damaged mitochondria under HG conditions. Through a proteomics-based approach, we identified that ISO could reverse the excessive phosphorylation of TSC2 S939 under HG conditions and stimulate autophagy through inhibition of the PI3K-AKT-TSC2-mTOR pathway. Furthermore, ISO was predicted to bind to the SH2 domain of PI3Kp85[Formula: see text], which is crucial for the recruitment and activation of PI3K. The protective effect of ISO and its effects on autophagy and particularly on mitophagy were further proved using a DN mice model. To summarize, our study identified the protective effects of ISO against DN and demonstrated that ISO was a strong activator of autophagy, which could provide a basis for drug development.

Relationship between the deep features of the full-scan pathological map of mucinous gastric carcinoma and related genes based on deep learning.

Background: Long-term differential expression of disease-associated genes is a crucial driver of pathological changes in mucinous gastric carcinoma. Therefore, there should be a correlation between depth features extracted from pathology-based full-scan images using deep learning and disease-associated gene expression. This study tried to provides preliminary evidence that long-term differentially expressed (disease-associated) genes lead to subtle changes in disease pathology by exploring their correlation, and offer a new ideas for precise analysis of pathomics and combined analysis of pathomics and genomics. Methods: Full pathological scans, gene sequencing data, and clinical data of patients with mucinous gastric carcinoma were downloaded from TCGA data. The VGG-16 network architecture was used to construct a binary classification model to explore the potential of VGG-16 applications and extract the deep features of the pathology-based full-scan map. Differential gene expression analysis was performed and a protein-protein interaction network was constructed to screen disease-related core genes. Differential, Lasso regression, and extensive correlation analyses were used to screen for valuable deep features. Finally, a correlation analysis was used to determine whether there was a correlation between valuable deep features and disease-related core genes. Result: The accuracy of the binary classification model was 0.775 ± 0.129. A total of 24 disease-related core genes were screened, including ASPM, AURKA, AURKB, BUB1, BUB1B, CCNA2, CCNB1, CCNB2, CDCA8, CDK1, CENPF, DLGAP5, KIF11, KIF20A, KIF2C, KIF4A, MELK, PBK, RRM2, TOP2A, TPX2, TTK, UBE2C, and ZWINT. In addition, differential, Lasso regression, and extensive correlation analyses were used to screen eight valuable deep features, including features 51, 106, 109, 118, 257, 282, 326, and 487. Finally, the results of the correlation analysis suggested that valuable deep features were either positively or negatively correlated with core gene expression. Conclusion: The preliminary results of this study support our hypotheses. Deep learning may be an important bridge for the joint analysis of pathomics and genomics and provides preliminary evidence for long-term abnormal expression of genes leading to subtle changes in pathology.

Establishment and validation of a clinical model for predicting diabetic ketosis in patients with type 2 diabetes mellitus.

Background: Diabetic ketosis (DK) is one of the leading causes of hospitalization among patients with diabetes. Failure to recognize DK symptoms may lead to complications, such as diabetic ketoacidosis, severe neurological morbidity, and death. Purpose: This study aimed to develop and validate a model to predict DK in patients with type 2 diabetes mellitus (T2DM) based on both clinical and biochemical characteristics. Methods: A cross-sectional study was conducted by evaluating the records of 3,126 patients with T2DM, with or without DK, at The Affiliated Hospital of Qingdao University from January 2015 to May 2022. The patients were divided randomly into the model development (70%) or validation (30%) cohorts. A risk prediction model was constructed using a stepwise logistic regression analysis to assess the risk of DK in the model development cohort. This model was then validated using a second cohort of patients. Results: The stepwise logistic regression analysis showed that the independent risk factors for DK in patients with T2DM were the 2-h postprandial C-peptide (2hCP) level, age, free fatty acids (FFA), and HbA1c. Based on these factors, we constructed a risk prediction model. The final risk prediction model was L= (0.472a - 0.202b - 0.078c + 0.005d - 4.299), where a = HbA1c level, b = 2hCP, c = age, and d = FFA. The area under the curve (AUC) was 0.917 (95% confidence interval [CI], 0.899-0.934; p<0.001). The discriminatory ability of the model was equivalent in the validation cohort (AUC, 0.922; 95% CI, 0.898-0.946; p<0.001). Conclusion: This study identified independent risk factors for DK in patients with T2DM and constructed a prediction model based on these factors. The present findings provide an easy-to-use, easily interpretable, and accessible clinical tool for predicting DK in patients with T2DM.

Prediction and verification of the effect of psoriasis on coronary heart disease based on artificial neural network.

Background and objectives: Psoriasis is an independent risk factor for coronary heart disease. It is important for predicting the complications of coronary heart disease in patients with psoriasis. Methods: In this study, related cases were collected from the case system of Qingdao University, and commonly used laboratory indicators were extracted. Artificial neural network (ANN) and logistics regression analysis were used to learn to distinguish psoriasis patients, coronary heart disease patients, and psoriasis patients with coronary heart disease. We identified independent risk factors for coronary heart disease in psoriasis patients that exacerbate coronary heart disease symptoms in patients with psoriasis. Findings: Analysis shows that the accuracy of the ANN model was higher than 79%. It was determined that age, chlorinated, phosphorus, magnesium, low-density lipoprotein, triglycerides, high density lipoprotein and total cholesterol are independent risk factors for coronary heart disease in patients with psoriasis. Similarly, gender, age, chlorinated, magnesium, triglycerides, and high density lipoprotein are risk factors that exacerbate coronary heart disease symptoms in patients with psoriasis. Interpretation: The presented approach is a valuable tool for identifying psoriasis patients, coronary heart disease patients, and psoriasis patients with coronary heart disease. It can also serve as a support tool clinicians in the diagnostic process, by providing an outstanding support in the diagnostics prevention of coronary heart disease in psoriasis.

Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images.

Introduction: The purpose of this study is to use deep learning and machine learning to learn and classify patients with cutaneous melanoma with different prognoses and to explore the application value of deep learning in the prognosis of cutaneous melanoma patients. Methods: In deep learning, VGG-19 is selected as the network architecture and learning model for learning and classification. In machine learning, deep features are extracted through the VGG-19 network architecture, and the support vector machine (SVM) model is selected for learning and classification. Compare and explore the application value of deep learning and machine learning in predicting the prognosis of patients with cutaneous melanoma. Result: According to receiver operating characteristic (ROC) curves and area under the curve (AUC), the average accuracy of deep learning is higher than that of machine learning, and even the lowest accuracy is better than that of machine learning. Conclusion: As the number of learning increases, the accuracy of machine learning and deep learning will increase, but in the same number of cutaneous melanoma patient pathology maps, the accuracy of deep learning will be higher. This study provides new ideas and theories for computational pathology in predicting the prognosis of patients with cutaneous melanoma.

The role of mitochondrial fission factor in podocyte injury in diabetic nephropathy.

Diabetic nephropathy (DN) is one of the most important complications of diabetes mellitus (DM) and has become the second cause of end-stage renal disease (ESRD). This study intends to investigate the molecular mechanism of increased mitochondrial fission in podocytes under the effect of high glucose (HG), and to preliminarily study the role of mitochondrial fission factor (MFF)-mediated mitochondrial fission in podocyte injury of DN. In vitro studies, we found that HG induced increased mitochondrial fission and podocyte damage. At the same time MFF mRNA and protein levels was increased, suggesting that MFF was transcriptional upregulated under HG conditions. Consistent with this, in vivo studies found that mitochondrial fission was also significantly increased in podocytes of diabetic nephropathy mice, and MFF expression was up-regulated. Therefore, our study proves that mitochondrial fission increases in podocytes under DM both in vitro and in vivo, and the up-regulation of MFF expression may be one of the reasons for the increase of mitochondrial fission. After inhibiting the expression of MFF, the survival rate of podocytes was significantly decreased under HG conditions, suggesting that MFF may play a protective role in podocyte injury in DN.

Impaired glucose tolerance is associated with enhanced postprandial pancreatic polypeptide secretion.

BACKGROUND: The purpose of this study is to compare serum pancreatic polypeptide (PP), insulin, C-peptide, and glucagon in different glucose tolerance stages; analyze the influencing factors of PP secretion; and further explore the role of PP in the pathogenesis of diabetes mellitus. METHODS: Data were collected from 100 subjects from hospital. According to the results of oral glucose tolerance test (OGTT), the subjects were divided into a normal glucose tolerance (NGT) group, an impaired glucose regulation (IGR) group, and a newly diagnosed type 2 diabetes mellitus (T2DM) group. PP and the related parameters were measured, and the area under the curve (AUC) 120 min after OGTT was calculated. AUCpp (AUC of PP) was used as the dependent variable and the potentially influencing factors were used as the independent variable for multiple linear regression analysis. RESULTS: Postprandial 60 min PP in the IGR group was higher than those in the NGT group (2973.80 [±547.49] pg·h/mL vs 2663.55 [±594.89] pg·h/mL, p < 0.05). AUCpp was significantly higher in the IGR group (428.76 pg·h/mL, 95% confidence interval [CI] [41.06 -816.46], p = 0.031) and newly diagnosed T2DM group (404.35 pg·h/mL, 95% CI [5.37-803.33], p = 0.047) than in the NGT group. AUCpp was negatively correlated with body mass index (BMI) (r = -0.235, p = 0.038) and positively correlated with postprandial 60 min blood glucose (r = 0.370, p = 0.001) and AUCbg (AUC of blood glucose) (r = 0.323, p = 0.007). Multiple linear regression analysis indicated that there was a linear correlation between BMI, AUCbg , and AUCpp (p = 0.004, p = 0.001), and the regression equation was calculated as: AUCpp  = 6592.272 + 86.275 × AUCbg -95.291 × BMI (R2  = 12.7%, p < 0.05). CONCLUSIONS: Compared with NGT subjects, IGR and T2DM patients have an enhanced postprandial PP secretion. In T2DMs, the secretion of PP is mainly affected by BMI and blood glucose.

The draft genome of the Asian corn borer yields insights into ecological adaptation of a devastating maize pest.

The Asian corn borer (ACB) is the most devastating pest on maize in the western Pacific region of Asia. Despite broad interests in insecticide resistance, seasonal adaptation, and larval color mimicry regarding the ACB system, lacking of reference genomic information and a powerful gene editing approach have hindered the in-depth studies of these aspects. Here we present a 455.7 Mb draft genome of ACB with 98.4% completeness. Comparative genomics analysis showed an evident expansion in gene families of gustatory receptors (105), which is related to polyphagous characteristics. Based on the comparative transcriptome analysis of resistant and susceptible ACB against Bt Cry1Ab toxin, we identified 26 genes related to Cry1Ab resistance. Additionally, transcriptomics of insects exposed to conditions of low temperature and diapause (LT) vs. room temperature and diapause (RT) provided insights into the genetic mechanisms of cold adaptation. We also successfully developed an efficient CRISPR/Cas9-based genome editing system and applied it to explore the role of color pattern genes in the ecological adaptation of ACB. Taken together, our study provides a fully annotated high-quality reference genome and efficient gene editing system to realize the potential of ACB as a study system to address important biological questions such as insecticide resistance, seasonal adaptation, and coloration. These valuable genomic resources will also benefit the development of novel strategies for maize pest management.

Habenula lesions improve glucose metabolism in rats with type 2 diabetes by increasing insulin sensitivity and inhibiting gluconeogenesis.

INTRODUCTION: The habenular nucleus (Hb), a famous relay station in the midbrain, is vital for controlling many physiological functions of vertebrates. The role of Hb in the pathogenesis of depression has been thoroughly studied, but whether it functions in the pathogenesis of diabetes remains unknown. In this study, we found that Hb lesions could improve glucose metabolism in type 2 diabetes mellitus (T2DM) by inhibiting the peripheral sympathetic nervous system and hepatic glucose production. RESEARCH DESIGN AND METHODS: T2DM rats were induced by a high-carbohydrate and fat diet combined with streptozotocin. Electrical lesion method was applied to suppress the function of Hb. Serum and tissue samples of rats in the control group, T2DM group, sham group, and Hb lesion group were detected by ELISA, western blotting, and biochemical methods. RESULTS: Compared with the sham group, the expression levels of AMPK phosphorylation and insulin receptor (IR) were significantly increased, whereas glucose-6-phosphatase and phosphoenolpyruvate carboxylated kinase were reduced in the liver of the Hb lesion group. In the glucose tolerance test and pyruvate tolerance test, the lesion group showed stronger glucose tolerance and lower hepatic gluconeogenesis than the sham. These results suggest that Hb lesions not only effectively increase insulin sensitivity and improve insulin resistance but also inhibit gluconeogenesis in T2DM rats. Moreover, Hb lesions increase the expression of brain-derived neurotrophic factor, tropomyosin receptor kinase B, glucocorticoid receptor, and IR in the hippocampus. In this study, we also found that Hb lesions increase the content of acetylcholine in the adrenal glands and reduce the content of epinephrine in both the adrenal glands and the liver, which may be the main reason for the Hb lesions to regulate glucose metabolism in the liver. CONCLUSION: Hb is an important neuroanatomical target for the regulation of glucose metabolism in the central nervous system of diabetic rats.

Comparative sialotranscriptome analysis of the rare Chinese cicada Subpsaltria yangi, with identification of candidate genes related to host-plant adaptation.

Little is known about the mechanisms underlying the relationship between changes in salivary proteins and the adaptation of insects to different host-plants. To address this knowledge gap, the transcriptional profiles of salivary glands were compared among three populations of the rare cicada Subpsaltria yangi, in which two populations specialize on Zizyphus jujuba var. spinosa, but the population occurring in the Helan (HL) Mountains is locally specialized on the endemic plant Ephedra lepidosperma. The comparisons indicate that genes related to digestion and detoxification are differentially regulated in populations feeding on different plants, possibly reflecting adaptative changes in salivary proteins of S. yangi in response to different host chemistries. In detail, 38 differentially expressed genes and 21 up-regulated genes related to digestion and detoxification were identified respectively in two pairwise comparisons among the populations using different hosts, with some genes exclusively expressed in the HL population. Our results are consistent with the hypothesis that the host plant shift in the HL population was facilitated by differential regulation of genes related to digestion and detoxification. This study provides new information for elucidating the molecular mechanisms underlying the relationship between changed salivary proteins and the adaptability of plant-feeding insects to novel host plants.

Degradation of nitrobenzene by synchronistic oxidation and reduction in an internal circulation microelectrolysis reactor.

The degradation of nitrobenzene by synchronistic oxidation and reduction was investigated using an internal circulation microelectrolysis (ICE) reactor with an active volume of 0.018 m3. Compared with a conventional fixed bed reactor with and without aeration, the ICE reactor exhibited a markedly higher nitrobenzene degradation efficiency. The effects of various operational parameters such as reaction time, aeration rate, initial nitrobenzene concentration, initial pH, and a volume ratio of iron and carbon (Fe/C) were also investigated. The optimal operating conditions (reaction time = 60 min, aeration rate = 5 × 10-4 m3/s, initial concentration of nitrobenzene = 300 mg/L, pH = 3.0, Fe/C = 1:1) gave removal efficiencies of nitrobenzene and chemical oxygen demand of 98.2% and 58%, respectively. The biodegradability index of the treated nitrobenzene solution was 0.45, which is 22 times that of the original solution. The reaction intermediates were identified through high-performance liquid chromatography, ultraviolet-visible spectroscopy, Fourier transform infrared spectroscopy, gas chromatography-mass spectrometry, and ion chromatography. The primary intermediates were determined to be aniline, phenol, and carboxylic acids, indicating that nitrobenzene was synchronously oxidized and reduced in the ICE reactor. Based on the identified intermediates, a possible pathway for nitrobenzene degradation in the ICE reactor is proposed.

Identification of candidate olfactory genes in cicada Subpsaltria yangi by antennal transcriptome analysis.

Olfaction in antennae is essential for regulating insect behaviors such as host preference and oviposition site selection. To better understand the olfactory mechanisms in the cicada Subpsaltria yangi that has a very narrow host range far fewer than diets of most other cicadas, an antennal transcriptome was constructed in this study. We identified 10 unigenes encoding putative odorant-binding proteins (OBPs), 10 chemosensory proteins (CSPs), 8 sensory neuron membrane proteins (SNMPs), 7 gustatory receptors (GRs), 29 odorant receptors (ORs) and 13 ionotropic receptors (IRs). We found that the OBPs were separated into two groups, Classic OBPs and Plus-C OBPs, according to their motifs. Based on sequence alignment and phylogenetic analysis, we found five Orcos in OR family. However, no pheromone receptor was identified, which may be related to that cicadas are sound-producing insects and acoustic signals other than pheromones play most important role in sexual communication. We used qRT-PCR to examine the expression profile of ten OBPs genes in various organs, and found that they were mainly expressed in olfactory organs such as antennae and mouthparts. Our results make it possible for future research of the olfactory system of S. yangi at the molecular level, and provide important bases for elucidation of the molecular mechanisms and evolution of chemosensation in sap-sucking insects.

[Clinical observation of superior gluteal nerve entrapment syndrome treated with needle-in-row combined with herb-partition moxibustion].

OBJECTIVE: To compare the effects of need-in-row combined with herb-partition moxibustion,need-in-row and conventional acupuncture for superior gluteal nerve entrapment syndrome. METHODS: Totally 105 patients were randomly assigned into a combination group,a need-in-row group and an acupuncture group,35 cases in each one. In the combination group and needle-in-row group,needle-in-row therapy was used at the pain tendon region of the pathological waist-hip part,and TDP was combined. Also,herb-partition moxibustion was applied at the same part after needle-in-row in the combined group. In the acupuncture group,conventional acupuncture was implemented at Weizhong(BL 40),Yanglingquan(GB 34),Zhibian(BL 54),Huantiao(GB 30),Sanyinjiao(SP 6) and Jiaji of L1-L5(EX-B 2),and TDP was applied. All the treatment was given once a day for four weeks. The changes of pain scores were compared after treatment. RESULTS: The pain scores decreased obviously after treatment in all the groups(all P<0.05). The scores of the combination group and the needle-in-row group declined more apparently than that of the acupuncture group(both P<0.05). The score of the combination group reduced more obviously than that of the needle-in-low group(P<0.05). The markedly effective rates of the combination group and the needle-in-row group were 88.6%(31/35) and 68.6%(24/35),which were higher than 40.0%(14/35) of the acupuncture group(both P<0.05),and the markedly effective rate of the combination group was better than that of the needle-in-row group(P<0.05). CONCLUSIONS: Need-in-row combined with herb-partition moxibustion show definite effect for superior gluteal nerve entrapment syndrome,and it is better than those of simple needle-in-row therapy and conventional acupuncture.