Effects of different cold chain logistics modes on the quality and bacterial community succession of fresh pork.

The connection and temperature control of cold chain links are key to ensuring meat quality. Considering the practical production of cold chain logistics in China, this study investigated the impact of various cold chain logistics modes (including warehousing, transportation, and sales conditions) at different temperature settings (7 °C, 4 °C, and - 1 °C), modeled in the laboratory, on the quality and bacterial community succession of pork. The pork quality was evaluated by pH, water holding capacity, total volatile basic nitrogen (TVB-N), total viable count (TVC) and myowater status. Among the different cold chain logistics modes, the LL1 (samples being warehoused and transported at 4 °C for 96 h and sold at -1 °C) and the SL1 (samples being warehoused and transported at 4 °C for 30 h and sold at -1 °C) modes were suitable for inter-provincial and intra-provincial transportation due to their long shelf life (> 14 days), respectively. The bacterial community succession of pork in different cold chain logistics modes was accessed by high-throughput sequencing. The results indicated that the cold chain logistics modes had affected the bacterial community, with Latilactobacillus being the dominant bacteria in the LL1 mode and SL1 mode during spoilage. The study revealed that the entire or partial process supercooling treatment (-1 °C) during the cold chain logistics process could effectively preserve the meat quality, supporting the high-quality development of the fresh meat cold chain logistics.

Effects of phosphoglycerate kinase 1 and pyruvate kinase M2 on metabolism and physiochemical changes in postmortem muscle.

The objective of this work was to investigate the influence of phosphoglycerate kinase-1 (PGK1) and pyruvate kinase-M2 (PKM2) activity on glycolysis, myofibrillar proteins, calpain system, and apoptosis pathways of postmortem muscle. The activity of PGK1 and PKM2 was regulated by their inhibitors and activators to construct the postmortem glycolysis vitro model and then incubated at 4 °C for 24 h. The results showed that compared to PGK1 and PKM2 inhibitors groups, the addition of PGK1 and PKM2 activators could accelerate glycogen consumption, ATP and lactate production, while declining pH value. Moreover, the addition of PGK1 and PKM2 activators could increase desmin degradation, µ-calpain activity, and caspase-3 abundance. Interestingly, troponin-T degradation was significantly increased both in PKM2 inhibitor and activator groups. It was suggested that PGK1 and PKM2 might be used as robust indicators to regulate meat quality by affecting the glycolysis, myofibrillar proteins, µ-calpain and apoptosis pathways in postmortem muscle.

Validation of protein biological markers of lamb meat quality characteristics based on the different muscle types.

This work investigated the ability of 8 potential biomarkers (phosphoglycerate kinase-1 (PGK1), pyruvate kinase-M2 (PKM2), phosphoglucomutase-1 (PGM1), ß-enolase (ENO3, myosin-binding protein-C (MYBPC1), myosin regulatory light chain-2 (MYLPF), troponin C-1 (TNNC1) and troponin I-1 (TNNI1)) to characterize meat quality by analyzing their relative abundance and enzymatic activity. Two different meat quality groups (Quadriceps femoris (QF) and Longissimus thoracis (LT) muscles) were selected at 24 h postmortem from 100 lamb carcasses. The relative abundance of PKM2, PGK1, PGM1, ENO3, MYBPC1, MYLPF, and TNNI1 was significantly different between LT and QF muscle groups (P < 0.01). Moreover, PKM, PGK, PGM, and ENO activity in LT muscle group was significantly lower than that in QF muscle (P < 0.05). Suggesting that PKM2, PGK1, PGM1, ENO3, MYBPC1, MYLPF, and TNNI1 can be used as robust biomarkers of lamb meat quality, providing the reference for understanding the molecular mechanism of postmortem meat quality formation in future.

Phosphorylation of Calpastatin Negatively Regulates the Activity of Calpain.

Tenderness is an important characteristic of meat quality. Calpastatin and calpain play important roles in meat tenderization. However, it is not clear how phosphorylation affects the regulation of calpastatin on µ-calpain and, consequently, meat tenderness. Calpastatin with high and low phosphorylation levels were obtained in vitro corresponding to the treatments by protein kinase A (PKA) and alkaline phosphatase. Then, calpain was incubated with calpastatin with different phosphorylation levels, and the effect of calpastatin on calpain activity under different phosphorylation levels was analyzed. The results showed that PKA promoted the phosphorylation of calpastatin, and a high phosphorylation level was maintained during incubation. The degradation rate of µ-calpain in AP group was higher than that in the other groups, meaning there was lower inhibition of calpastatin on calpain activity. The degradation of calpastatin was lower and its structure was more stable after phosphorylation. One more serine 133 site of calpastatin was identified in PKA group compared with the other groups. Phosphorylation at serine 133 of calpastatin enhanced its inhibition on calpain activity by maintaining its structural stability, thus inhibiting the tenderization of meat.

Integrating identification and targeted proteomics to discover the potential indicators of postmortem lamb meat quality.

The aim of this study was to identify the potential indicators of lamb meat quality by TMT and PRM-based proteomics combined with bioinformatic analysis. Lamb muscles were divided into three different meat quality groups (high, middle and low) according to tenderness (shear force, MFI value), colour (a* value, R630/580), and water-holding capacity (cooking loss, drip loss) at 24 h postmortem. The results showed that the abundance of phosphoglycerate kinase 1 (PGK1), ß-enolase (ENO3), myosin-binding protein C (MYBPC1) and myosin regulatory light chain 2 (MYLPF) was significantly different in the three groups and could be used as potential indicators to characterize meat quality. Moreover, the postmortem processes of glycolysis, oxidative phosphorylation, and muscle contraction remarkably changed in different groups, and were the key biological pathways influencing meat quality. Overall, this study depicted the proteomic landscape of meat that furthers our understanding of the molecular mechanism of meat quality and provides a reference for developing non-destructive detection technology for meat quality.

A nonlinear associations of metabolic score for insulin resistance index with incident diabetes: A retrospective Chinese cohort study.

Background: The Metabolic score of insulin resistance (METS-IR) has recently been accepted as a reliable alternative to insulin resistance (IR), which was demonstrated to be consistent with the hyperinsulinemic-euglycemic clamp. Few pieces of research have focused on the relationship between METS-IR and diabetes in Chinese. The purpose of this research was to explore the effect of METS-IR on new-onset diabetes in a large multicenter Chinese study. Methods: At the baseline of this retrospective longitudinal research, 116855 participators were included in the Chinese cohort study administered from 2010 to 2016. The subjects were stratified by quartiles of METS-IR. To assess the effect of METS-IR on incident diabetes, the Cox regression model was constructed in this study. Stratification analysis and interaction tests were applied to detect the potential effect of METS-IR and incident diabetes among multiple subgroups. To verify whether there was a dose-response relationship between METS-IR and diabetes, a smooth curve fitting was performed. In addition, to further determine the performance of METS -IR in predicting incident diabetes, the receiver operating characteristic curve (ROC) was conducted. Results: The average age of the research participators was 44.08 ± 12.93 years, and 62868 (53.8%) were men. METS-IR were significant relationship with new-onset diabetes after adjusting for possible variables (Hazard ratio [HR]: 1.077; 95% confidence interval [CI]: 1.073-1.082, P < 0.0001), the onset risk for diabetes in Quartile 4 group was 6.261-fold higher than those in Quartile 1 group. Moreover, stratified analyses and interaction tests showed that interaction was detected in the subgroup of age, body mass index, systolic blood pressure, diastolic blood pressure, and fasting plasma glucose, there was no significant interaction between males and females. Furthermore, a dose-response correlation was detected between METS-IR and incident diabetes, the nonlinear relationship was revealed and the inflection point of METS-IR was calculated to be 44.43. When METS-IR≥44.43, compared with METS-IR < 44.43, the trend was gradually saturated, with log-likelihood ratio test P < 0.001. Additionally, the area under receiver operating characteristic of the METS-IR in predicting incident diabetes was 0.729, 0.718, and 0.720 at 3, 4, and 5 years, respectively. Conclusions: METS-IR was correlated with incident diabetes significantly, and showed a nonlinear relationship. This study also found that METS-IR had good discrimination of diabetes.

Sarcoplasmic and myofibrillar phosphoproteins profile of beef M. longissimus thoracis with different pHu at different days postmortem.

BACKGROUND: The abnormal ultimate pH (pHu ) in postmortem muscles affect the meat quality and results in substantial economic losses. Dark, firm, and dry (DFD) meat linked with the higher postmortem pHu values and exhibited many quality issues such as dark color, tough texture and shorter shelf life. This research aimed to investigate the effect of protein phosphorylation on variations in beef pHu in order to explore the possible mechanisms underlying DFD meat formation. RESULTS: Glycogen and lactate contents were higher, while L* and a* were lower in high pHu beef. Shear force was higher in intermediate pHu group. Global phosphorylation of sarcoplasmic proteins was higher in low pHu samples on day 1 and of myofibrillar proteins was higher in intermediate pHu meat on days 1 and 2 postmortem. Sarcoplasmic protein bands with different phosphorylation levels were identified as containing some glycometabolism and stress response proteins and phosphorylated myofibrillar protein bands were identified sarcomeric and metabolic proteins. CONCLUSIONS: Phosphorylation of multiple proteins of glycolytic pathway and contractile machinery may play critical roles in development of DFD beef. © 2021 Society of Chemical Industry.

Ambient carbon monoxide and increased risk of daily hospital outpatient visits for respiratory diseases in Dongguan, China.

BACKGROUND: The toxicity of high-concentration carbon monoxide (CO) on human health has previously been documented. However, the epidemiological evidence on the association between acute exposure to ambient CO and respiratory diseases is relatively lacking and controversial. OBJECTIVES: To examine the short-term association between ambient CO and hospital outpatient visits for respiratory diseases in Dongguan, China. METHODS: The number of daily hospital outpatient visits for respiratory diseases, and air pollution and meteorological data were collected from January 2013 to August 2017. A generalized additive model with a quasi-Poisson link was used to estimate the association between ambient CO concentration and the total number of hospital outpatient visits for all respiratory diseases and those for asthma, bronchiectasis, chronic obstructive pulmonary disease (COPD) and pneumonia. We further analyzed the effect of ambient CO by gender and age. RESULTS: Over the study period, a 24-h mean concentration of ambient CO of 0.88 mg/m3 (below the limit for CO in China) and a total of 89,484 hospital outpatient visits for respiratory diseases were recorded. Ambient CO was found to increase the risk for asthma, bronchiectasis, pneumonia and the total number of respiratory diseases. The per interquartile range (IQR) increase in ambient CO at lag03 day corresponded to a 5.62% (95% confidence interval (CI): 3.24%, 8.05%), 8.86% (95% CI: 4.89%, 12.98%), 6.67% (95% CI: 0.87%, 12.81%) and 7.20% (95% CI: 2.35%, 12.29%) increased risk in outpatient visits for all respiratory diseases, asthma, bronchiectasis and pneumonia, respectively. Each association was partially weakened after adjusting for co-pollutants. The effect of ambient CO on respiratory diseases appeared to be greater for females and the elderly. CONCLUSIONS: Short-term exposure to ambient CO was associated with increased risk of outpatient visits for respiratory diseases. Our analysis may help to understand the health effects of low-levels of CO and provide evidence for the creation of air quality standards.

Ambient fine and coarse particulate matter pollution and respiratory morbidity in Dongguan, China.

We estimated the short-term effects of particulate matter (PM) pollution with aerodynamic diameters ≤2.5 µm (PM2.5) and between 2.5 and 10 µm (PMc) on hospital outpatient visits due to overall and specific respiratory diseases, as well as the associated morbidity burden in Dongguan, a subtropical city in South China. A time-series model with quasi-Poisson link was used to examine the association between PM pollution and morbidities from respiratory diseases, COPD, asthma and pneumonia in Dongguan during 2013-2015. We further estimated the morbidity burden (population attributable fraction and attributable morbidity) due to ambient PM pollution. A total of 44,801 hospital outpatient visits for respiratory diseases were recorded during the study period. Both PM2.5 and PMc were found to be significantly associated with morbidity of overall respiratory diseases, COPD, and asthma. An IQR (interquartile range) increase in PM2.5 at lag03 day was associated with 15.41% (95% CI: 10.99%, 20.01%) increase in respiratory morbidity, and each IQR increase in PMc at lag03 corresponded to 7.24% (95% CI: 4.25%, 10.32%) increase in respiratory morbidity. We did not find significant effects of PM2.5 and PMc on pneumonia. Using WHO's guideline (25 µg/m3) as reference concentration, about 8.32% (95% CI: 5.90%, 10.86%) of respiratory morbidity (3727, 95% CI: 2642, 4867, in morbidity number) were estimated to be attributed to PM2.5, and 0.86% (95% CI: 0.50%, 1.23%) of respiratory morbidity, representing 385 (95% CI: 225, 551) hospital outpatient visits, could be attributed to coarse particulate pollutant. Our study suggests that both fine and coarse particulate pollutants are an important trigger of hospital outpatient visits for respiratory diseases, and account for substantial respiratory morbidity in Dongguan, China.

Predicting siRNA potency with random forests and support vector machines.

BACKGROUND: Short interfering RNAs (siRNAs) can be used to knockdown gene expression in functional genomics. For a target gene of interest, many siRNA molecules may be designed, whereas their efficiency of expression inhibition often varies. RESULTS: To facilitate gene functional studies, we have developed a new machine learning method to predict siRNA potency based on random forests and support vector machines. Since there were many potential sequence features, random forests were used to select the most relevant features affecting gene expression inhibition. Support vector machine classifiers were then constructed using the selected sequence features for predicting siRNA potency. Interestingly, gene expression inhibition is significantly affected by nucleotide dimer and trimer compositions of siRNA sequence. CONCLUSIONS: The findings in this study should help design potent siRNAs for functional genomics, and might also provide further insights into the molecular mechanism of RNA interference.

BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features.

BACKGROUND: Understanding how biomolecules interact is a major task of systems biology. To model protein-nucleic acid interactions, it is important to identify the DNA or RNA-binding residues in proteins. Protein sequence features, including the biochemical property of amino acids and evolutionary information in terms of position-specific scoring matrix (PSSM), have been used for DNA or RNA-binding site prediction. However, PSSM is rather designed for PSI-BLAST searches, and it may not contain all the evolutionary information for modelling DNA or RNA-binding sites in protein sequences. RESULTS: In the present study, several new descriptors of evolutionary information have been developed and evaluated for sequence-based prediction of DNA and RNA-binding residues using support vector machines (SVMs). The new descriptors were shown to improve classifier performance. Interestingly, the best classifiers were obtained by combining the new descriptors and PSSM, suggesting that they captured different aspects of evolutionary information for DNA and RNA-binding site prediction. The SVM classifiers achieved 77.3% sensitivity and 79.3% specificity for prediction of DNA-binding residues, and 71.6% sensitivity and 78.7% specificity for RNA-binding site prediction. CONCLUSIONS: Predictions at this level of accuracy may provide useful information for modelling protein-nucleic acid interactions in systems biology studies. We have thus developed a web-based tool called BindN+ (http://bioinfo.ggc.org/bindn+/) to make the SVM classifiers accessible to the research community.