Underlying mechanisms of phosphodiesterase 10A and glutamate-ammonia ligase genes that regulate inosine monophosphate deposition and thereby affect muscle tenderness in Jingyuan chickens

Wang, Weizhen,Zhang, Juan,Hu, Honghong,Yu, Baojun,He, Jintong,Yao, Tingting,Gu, Yaling,Cai, Zhengyun,Xin, Guosheng Asian Australasian Association of Animal Productio 2022 Animal Bioscience Vol.35 No.11

Objective: Inosine monophosphate (IMP) is a key factor that imparts of meat flavor. Differences in the IMP content in the muscles were evaluated to improve chicken meat quality. Methods: For this study, the IMP content was detected by high performance liquid chromatography. The gene expression profiles of Jingyuan chickens with different feeding patterns and different sexes were analyzed by RNA-sequencing (RNA-seq). Results: Breast muscle IMP content in free-range chickens was extremely significantly higher than that of caged chickens (p<0.01). Breast muscle IMP content in hens was also higher than that of cocks, but the difference was not significant. Correlation analysis showed that the breast muscle IMP content in caged hens and cocks was negatively correlated with the shear force, and the breast muscle IMP content in free-range hens was significantly negatively correlated with the shear force (p<0.05). The two key genes associated with IMP synthesis in chickens with different feeding patterns were glutamate-ammonia ligase (GLUL) and phosphodiesterase 10A (PDE10A). Bioinformatics analysis revealed that the GLUL and PDE10A genes are involved in glutamine biosynthesis and purine salvage pathways respectively. In addition, GLUL expression was positively correlated with the IMP content in caged and free-range chickens, and PDE10A expression was significantly positively correlated with the IMP content in caged and free-range chickens (p<0.05). Conclusion: These findings will facilitate the comprehension of the deposition of IMP in the muscles and thereby aid the process of selection and breeding of good quality local chickens.

Dehydrogenation versus hydrogenolysis in the reaction of light alkanes over Ni-based catalysts

Guowei Wang,Shan Zhang,Xiaolin Zhu,Chunyi Li,Honghong Shan 한국공업화학회 2020 Journal of Industrial and Engineering Chemistry Vol.86 No.-

Given the high cost of Pt-based catalysts and the environmental issue of CrOx-based catalysts indehydrogenation processes, Ni-based catalysts have been extensively explored as alternatives. In order totake the advantage of the high activation ability of Ni towards alkanes, herein, the reaction behaviors oflight alkanes, primarily dehydrogenation versus hydrogenolysis, over Ni-based catalysts have beenreviewed and probed. Ni-based catalysts exhibit an extremely high hydrogenolysis activity for lightalkanes. Different from the single hydrogenolysis reaction on the surface of Pt, multiple hydrogenolysis ofalkane molecules occurs over Ni sites. The successive α-scission of C C bond over Ni sites results in thegeneration of abundant methane and coke. To selectively activate C H bond of alkanes and prohibit C Cbond rupture, one feasible approach is to introduce effective barriers to destroy the aggregated Niensembles active for hydrogenolysis. The promoting mechanism of different barriers (S, P, Cu, Sn, etc.) hasbeen summarized and analyzed. The geometric effect of introduced barriers facilitates the dispersion ofNi particles, and electronic effect reduces the desorption energy of olefins and avoids undesiredsecondary reactions. Among all these catalysts, NiS and NiSn-based catalysts demonstrate the mostoutstanding dehydrogenation performance and show great potential for industrial applications.

The Association Between Fasting C-peptide and Gastrointestinal Symptoms of Gastroparesis in Type 2 Diabetic Patients

( Yun Huang ),( Honghong Zhang ),( Minxia Zhang ),( Wenya Li ),( Jinhua Wang ),( Ji Hu ) 대한소화기기능성질환·운동학회 2017 Journal of Neurogastroenterology and Motility (JNM Vol.23 No.2

Background/Aims The relationship between C-peptide levels and gastrointestinal (GI) symptoms in type 2 diabetic patients is not clear. The purpose of this study is to examine the association between fasting C-peptide and GI symptoms of gastroparesis in type 2 diabetic patients. Methods We recruited 333 type 2 diabetic patients into the present study. All patients filled out questionnaires of gastroparesis cardinal symptom index (GCSI) to evaluate GI symptoms. Hospital anxiety and depression scale were adopted to define anxiety and depression. Patients with GCSI scores ≥ 1.9 were regarded as having symptoms of gastroparesis. Results In our study, 71 (21.3%) type 2 diabetic patients had GCSI scores ≥ 1.9. In comparison to patients with scores < 1.9, those with scores ≥ 1.9 had significantly lower fasting c-peptide levels (1.49 ng/mL vs 1.94 ng/mL, P < 0.001), higher prevalence of depression (40.9% vs 18.3%, P < 0.001) and anxiety (28.2% vs 13.0%, P = 0.002). Multivariate logistic regression revealed that fasting C-peptide was still significantly associated with symptoms of gastroparesis (odds ratio, 0.67; 95% confidence intervals, 0.48-0.94; P = 0.021), even after adjustments for age, sex, body mass index, HbA1c, current smoking and drinking status, anxiety, and depression. Furthermore, linear regressions showed that fasting C-peptide was independently and negatively related to GCSI scores (standardized regression coefficient, -0.29; P < 0.001) in patients with at least one GI symptom. Conclusion GI symptoms of diabetic gastroparesis affect approximately 20% of type 2 diabetes patients and are associated with lower fasting C-peptide levels independent of depression and anxiety status. (J Neurogastroenterol Motil 2017;23:254-261)

Prevalence and risk factors of low back and pelvic pain in women with rectus abdominis diastasis: a multicenter retrospective cohort study

Sue Yuan,Honghong Wang,Jie Zhou 대한통증학회 2022 The Korean Journal of Pain Vol.35 No.1

Background: To explore the association between low back pain (LBP) and pelvic pain (PP) and rectus abdominis diastasis (RAD) in postpartum women and identify the characteristics and risk factors. Methods: Women diagnosed with RAD and a history of labor and delivery, between 2009 and 2018, were identified from six hospitals within the Partners Healthcare System. Univariate and multivariable binary logistic regression analyses were used to identify the risk factors associated with pain. Results: Age at onset of RAD in the non-cesarean delivery group was earlier than those in cesarean delivery (CD) group (P = 0.017). Women who underwent CD demonstrated 4.5 times greater risk of RAD than those who had no CD exposure. The cumulative composition ratio of LBP at every age stage of the period from 8 years pre-first delivery to 8 years post-first delivery was significantly higher than the other five conditions (RAD, umbilical hernia, PP, depressive disorder [DD], and strain of muscle, fascia, and tendon [SMFT]) (P for trend < 0.001). Women with DD, SMFT, and PP were more likely to have LBP (odds ratio [OR] = 1.91, 95% confidence interval [CI] 1.06 to 3.47, P = 0.032; OR = 4.50, 95% CI 1.64 to 12.36, P = 0.003; OR = 2.14, 95% CI 1.17 to 3.89, P = 0.013; respectively). Conclusions: In postpartum women with RAD, DD, SMFT, and PP were found to be risk factors contributing to the development of LBP. Race and LBP also played roles in the development of PP.

Design of Four-Axis Winding Machine for Tapered Composite Pole Using Heated-Mandrel Curing

Jiazhong Xu,Rongguo Wang,Tao Sun,Qingmin Huang,Honghong Yang 보안공학연구지원센터(IJUNESST) 2014 International Journal of u- and e- Service, Scienc Vol.7 No.1

Real-time online optimal control of current-fed dual active bridges based on machine learning

Han, Ming,Liu, Xiaosheng,Pu, Honghong,Zhao, Liang,Wang, Kaixuan,Xu, Dianguo The Korean Institute of Power Electronics 2020 JOURNAL OF POWER ELECTRONICS Vol.20 No.1

This paper proposes a real-time online optimal (RT-OPT) control method based on machine learning for a current-fed dual active bridge (CF-DAB). The basis of this control strategy is the linear quadratic optimal control, which designs the sliding surface and realizes power control based on sliding mode control (SMC). For the parameters of Q and R in the objective function of the linear quadratic regulator (LQR), a genetic algorithm is used to find the optimal value, and the optimal value is taken as the sample data. Through machine learning offline training, a neural network is obtained and run online to realize real-time online optimal control. The control method was verified by simulations in MATLAB/Simulink. The RT-OPT method achieves the expected functionality, and has better dynamic and steady-state performance than the PI controller.