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Abstract Inflammatory bowel disease (IBD) has a close association with transketolase (TKT) that links glycolysis and the pentose phosphate pathway (PPP). However, how TKT functions in the intestinal epithelium remains to be elucidated. To address this question, we specifically delete TKT in intestinal epithelial cells (IECs). IEC TKT-deficient mice are growth retarded and suffer from spontaneous colitis. TKT ablation brings about striking alterations of the intestine, including extensive mucosal erosion, aberrant tight junctions, impaired barrier function, and increased inflammatory cell infiltration. Mechanistically, TKT deficiency significantly accumulates PPP metabolites and decreases glycolytic metabolites, thereby reducing ATP production, which results in excessive apoptosis and defective intestinal barrier. Therefore, our data demonstrate that TKT serves as an essential guardian of intestinal integrity and barrier function as well as a potential therapeutic target for intestinal disorders.

Objective The objective of this study was to determine net energy (NE) of expeller-press (EP-RSM) and solvent-extracted rapeseed meal (SE-RSM) and to establish equations for predicting the NE in rapeseed meal (RSM) fed to growing pigs. Methods Thirty-six barrows (initial body weight [BW], 41.1±2.2 kg) were allotted into 6 diets comprising a corn-soybean meal basal diet and 5 diets containing 19.50% RSM added at the expense of corn and soybean meal. The experiment had 6 periods and 6 replicate pigs per diet. During each period, the pigs were individually housed in metabolism crates for 16 days which included 7 days for adaption to diets. On day 8, pigs were transferred to respiration chambers and fed their respective diet at 2,000 kJ metabolizable energy (ME)/kg BW0.6/d. Feces and urine were collected, and daily heat production was measured from day 9 to 13. On days 14 and 15, the pigs were fed at 890 kJ ME/kg BW0.6/d and fasted on day 16 for evaluation of fasting heat production (FHP). Results The FHP of pigs averaged 790 kJ/kg BW0.6/d and was not affected by the diet composition. The NE values were 10.80 and 8.45 MJ/kg DM for EP-RSM and SE-RSM, respectively. The NE value was positively correlated with gross energy (GE), digestible energy (DE), ME, and ether extract (EE). The best fit equation for NE of RSM was NE (MJ/kg DM) = 1.14×DE (MJ/kg DM)+0.46×crude protein (% of DM)–25.24 (n = 8, R2 = 0.96, p

Objective Feed energy required for pigs is first prioritized to meet maintenance costs. Additional energy intake in excess of the energy requirement for maintenance is retained as protein and fat in the body, leading to weight gain. The objective of this study was to estimate the metabolizable energy requirements for maintenance (MEm) by regressing body weight (BW) gain against metabolizable energy intake (MEI) in growing pigs. Methods Thirty-six growing pigs (26.3±1.7 kg) were allotted to 1 of 6 treatments with 6 replicates per treatment in a randomized complete block design. Treatments were 6 feeding levels which were calculated as 50%, 60%, 70%, 80%, 90%, or 100% of the estimated ad libitum MEI (2,400 kJ/kg BW0.60 d). All pigs were individually housed in metabolism crates for 30 d and weighed every 5 d. Moreover, each pig from each treatment was placed in the open-circuit respiration chambers to measure heat production (HP) and energy retained as protein (REp) and fat (REf) every 5 d. Serum biochemical parameters of pigs were analyzed at the end of the experiment. Results The average daily gain (ADG) and HP as well as the REp and REf linearly increased with increasing feed intake (p

This study was conducted to determine the effect of different growing stages on digestible energy (DE) and metabolizable energy (ME) in soybean meal (SBM), cottonseed meal (CSM), rapeseed meal (RSM), corn gluten meal (CGM), and corn distillers dried grains with solubles (DDGS) fed to crossbred barrows. Thirty-six growing barrows (GS 1: 29.1 ± 2.85 kg BW), 36 growing barrows (GS 2: 59.2 ± 4.91 kg BW), and 36 finishing barrows (GS 2: 105.4 ± 6.91 kg BW) were allotted to 6 diets in a completely randomized design with 6 replicated pigs per diet per growth stage or BW. Faecal and urine samples were collected for 5 days after a 12-day adaption period. The results showed that the concentration of DE in corn for pigs at GS 3 was greater (P

The pentose phosphate pathway (PPP) branches from glucose 6-phosphate (G6P), produces NADPH and ribose 5-phosphate (R5P), and shunts carbons back to the glycolytic or gluconeogenic pathway. The PPP has been demonstrated to be a major regulator for cellular reduction-oxidation (redox) homeostasis and biosynthesis. Enzymes in the PPP are reported to play important roles in many human diseases. In this review, we will discuss the role of the PPP in type 2 diabetes and cancer.

Objective The objective of this experiment was to determine the net energy (NE) content of full-fat rice bran (FFRB), corn germ meal (CGM), corn gluten feed (CGF), solvent-extracted peanut meal (PNM), and dehulled sunflower meal (SFM) fed to growing pigs using indirect calorimetry or published prediction equations. Methods Twelve growing barrows with an average initial body weight (BW) of 32.4±3.3 kg were allotted to a replicated 3×6 Youden square design with 3 successive periods and 6 diets. During each period, pigs were individually housed in metabolism crates for 16 d, which included 7 days for adaptation. On d 8, the pigs were transferred to the respiration chambers and fed one of the 6 diets at 2.0 MJ metabolizable energy (ME)/kg BW0.6/d. Total feces and urine were collected and daily heat production was measured from d 9 to d 13. On d 14 and d15, pigs were fed at their maintenance energy requirement level. On the last day pigs were fasted and fasting heat production was measured. Results The NE of FFRB, CGM, CGF, PNM, and SFM measured by indirect calorimetry method was 12.33, 8.75, 7.51, 10.79, and 6.49 MJ/kg dry matter (DM), respectively. The NE/ME ratios ranged from 67.2% (SFM) to 78.5% (CGF). The NE values for the 5 ingredients calculated according to the prediction equations were 12.22, 8.55, 6.79, 10.51, and 6.17 MJ/kg DM, respectively. Conclusion The NE values were the highest for FFRB and PNM and the lowest in the corn co-products and SFM. The average NE of the 5 ingredients measured by indirect calorimetry method in the current study was greater than values predicted from NE prediction equations (0.32 MJ/kg DM).

Abstract In the past two decades, a considerable amount of research has focused on the determination of the digestible (DE) and metabolizable energy (ME) contents of feed ingredients fed to swine. Compared with the DE and ME systems, the net energy (NE) system is assumed to be the most accurate estimate of the energy actually available to the animal. However, published data pertaining to the measured NE content of ingredients fed to growing pigs are limited. Therefore, the Feed Data Group at the Ministry of Agricultural Feed Industry Centre (MAFIC) located at China Agricultural University has evaluated the NE content of many ingredients using indirect calorimetry. The present review summarizes the NE research works conducted at MAFIC and compares these results with those from other research groups on methodological aspect. These research projects mainly focus on estimating the energy requirements for maintenance and its impact on the determination, prediction, and validation of the NE content of several ingredients fed to swine. The estimation of maintenance energy is affected by methodology, growth stage, and previous feeding level. The fasting heat production method and the curvilinear regression method were used in MAFIC to estimate the NE requirement for maintenance. The NE contents of different feedstuffs were determined using indirect calorimetry through standard experimental procedure in MAFIC. Previously generated NE equations can also be used to predict NE in situations where calorimeters are not available. Although popular, the caloric efficiency is not a generally accepted method to validate the energy content of individual feedstuffs. In the future, more accurate and dynamic NE prediction equations aiming at specific ingredients should be established, and more practical validation approaches need to be developed.

Objective The objective of this experiment was to determine apparent ileal digestibility (AID) and standardized ileal digestibility (SID) of crude protein (CP) and amino acid (AA) in 15 sources of soybean meal (SBM) produced from soybeans from different countries and subsequently to establish equations for predicting the AID and SID in SBM based on their chemical composition. Methods Eighteen barrows (57.9±6.1 kg) fitted with a simple T-cannula were allotted into three 6×6 Latin square designs. Each period comprised a 6-d adaption period followed by a 2-d collection of ileal digesta. The 15 test diets included SBM as a sole source of AA in the diet. Another nitrogen-free diet was used to measure basal endogenous losses of CP and AA. Chromic oxide (0.3%) was used as an inert marker in each diet. Results The AID of lysine in SBM from China and USA tended to be greater than in SBM from Brazil (p

Abstract Background Two experiments were conducted to estimate the net energy (NE) of corn, soybean meal, expeller-pressed rapeseed meal (EP-RSM) and solvent-extracted rapeseed meal (SE-RSM) using indirect calorimetry and to validate the NE of these four ingredients using pig growth performance. Methods In Exp.1, 24 barrows (initial BW = 36.4 ± 1.6 kg) were allotted to 1 of 4 diets which included a corn basal diet, a corn-soybean meal basal diet and two rapeseed meal diets containing 20% EP-RSM (9.5% ether extract) or SE-RSM (1.1% ether extract) substituted for corn and soybean meal. The design allowed the calculation of NE values of corn, soybean meal and rapeseed meals according to the difference method. In Exp.2, 175 growing pigs (initial BW = 36.0 ± 5.2 kg) were fed 1 of 5 diets for 28 d, with five pigs per pen and seven replications (pens) per treatment in order to validate the measured energy values. Diets were a corn-soybean meal diet and four diets including 10% or 20% EP-RSM and 10% or 20% SE-RSM. Results The NE of corn, soybean meal, EP-RSM and SE-RSM were 12.46, 11.34, 11.71 and 8.83 MJ/kg DM, respectively. The NE to ME ratio of corn (78%) was similar to tabular values, however, the NE to ME ratios of soybean meal (70%) and rapeseed meal (76%) were greater than tabular values. The greater NE value in EP-RSM than in SE-RSM is consistent with its higher EE content. Increasing EP-RSM or SE-RSM did not affect the growth performance of pigs and the caloric efficiency of NE was comparable for all diets. Conclusions The NE of EP-RSM was similar to soybean meal, and both were greater than SE-RSM. The DE, ME and NE values measured in Exp.1 are confirmed by results of Exp. 2 with comparable caloric efficiencies of DE, ME or NE for all diets.

Abstract Background and Objectives Anastomotic leakage is a serious complication following surgery for cancer of the rectum. It is not clear whether reinforcing sutures could prevent anastomotic leakage. Therefore, this study aims at evaluating the efficacy of reinforcing sutures on anastomotic leakage. Methods We searched PubMed, Embase, and the Cochrane Library databases from inception to January 31, 2023. We included studies comparing anastomosis with reinforcing sutures to anastomosis without reinforcing sutures after low anterior resection. Risk of bias was assessed by the Cochrane tool for RCTs and the Risk of Bias in Non‐Randomized Studies (ROBINS)‐I tool for observational studies. The overall quality of evidence for primary outcome was assessed using Grading of Recommendations Assessment, Development, and Evaluations methodology. Results Two RCTs (345 patients) and four observational studies (783 patients) were included. Anastomotic leakage occurred in 4.4% (24 of 548) of patients with reinforcing sutures and 11.9% (69 of 580) of patients without reinforcing sutures. Meta‐analysis showed a lower incidence of anastomotic leakage (RR, 0.41; 95% CI 0.25 to 0.66, low certainty) in patients with reinforcing sutures. Operative time (WMD, −3.66; 95% CI −18.58 to 11.25) and reoperation for anastomotic leakage (RR, 0.69; 95% CI 0.23 to 2.08) were similar between patients with reinforcing sutures and those without reinforcing sutures. Conclusions While observational data suggest that, there is a clear benefit in terms of reducing the risk of anastomotic leakage with the use of reinforcing sutures, RCT data are less clear. Further large, prospective studies are warranted to determine whether a true clinically important benefit exists with this technique.

Abstract The construction of a household integrated energy system will reduce greenhouse gas emissions and promote sustainable development. Firstly, a household energy system is proposed, which consists of a photovoltaic, wind turbine, electrolysis cell, hydrogen storage tank, and hydrogen‐fired gas turbine. The proposed system is modelled as a bi‐objective optimization problem in which the minimum daily system economic cost, and the minimum loss of energy supply probability. Secondly, a novel multi‐objective egret swarm optimization algorithm with strong search capability and fast convergence is proposed. Thirdly, a household load corresponding to a typical day in spring is chosen as the study case. The optimization results show that the daily system economic cost with the optimal number of devices is 97.48 RMB, and the loss of energy supply probability is 8.33% at the lowest. Finally, to validate the efficiency of the proposed method, the proposed method is compared with NSGA‐II (a widely used multi‐objective evolutionary algorithm). The comparison indicates that the proposed method has a better diversity due to the random searchability. As a consequence, the proposed method can be used in the optimization capacity design of the integrated energy system.

As the grid coverage rises, foreign objects invade more and more frequently, causing grid failures to rise every year. To address this issue, this paper proposes a deep learning-based transmission line unmanned inspection of foreign objects recognition algorithm. The algorithm is based on YOLOv7 (You Only Look Once) algorithm, combining with hyperparameter optimization based on genetic algorithm (GA) and space-to-depth (SPD) convolution to complete the foreign object recognition of transmission line Unmanned Aerial Vehicle (UAV) images. The proposed method can promptly determine and locate these targets’ presence in aerial images. Finally, this paper compares the improved YOLOv7 algorithm with other YOLO series algorithms (Faster-rcnn, Centernet, and other target detection models). The comparison results show that the method has the highest Mean Average Precision (mAP) of 92.2% and the Frames Per Second (FPS) of 19 is second only to Centernet. Compared with the unimproved YOLOv7, the average accuracy in the recognition of tower cranes has increased by 11.9%, which is the most obvious improvement in accuracy compared with other detection targets. Meanwhile, the hyperparameter optimization based on genetic algorithm speeds up the convergence of the model.

Abstract Background Gastric cancer (GC) ranks second in mortality among all malignant diseases worldwide. However, the cause and molecular mechanism underlying gastric cancer are not clear. Here, we used integrated bioinformatics to identify possible key genes and reveal the pathogenesis and prognosis of gastric cancer. Methods The gene expression profiles of GSE118916, GSE79973, and GSE29272 were available from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between GC and normal gastric tissues were screened by R software and Venn diagram software. GO and KEGG pathway enrichment of DEGs was performed using the DAVID database. A protein-protein interaction (PPI) network was established by STRING and visualized using Cytoscape software. Then the influence of hub genes on expression and survival was assessed using TCGA database. Results A total of 83 DEGs were found in the three datasets, including 41 up-regulated genes and 42 down-regulated genes. These DEGs were mainly enriched in extracellular matrix organization and cell adhesion. The enriched pathways obtained in the KEGG pathway analysis were extracellular matrix (ECM)-receptor interaction and focal adhesion. A PPI network of DEGs was analyzed using the Molecular Complex Detection (MCODE) app of Cytoscape. Four genes were considered hub genes, including COL5A1, FBN1, SPARC, and LUM. Among them, LUM was found to have a significantly worse prognosis based on TCGA database. Conclusions We screened DEGs associated with GC by integrated bioinformatics analysis and found one potential biomarker that may be involved in the progress of GC. This hub gene may serve as a guide for further molecular biological experiments.

Three-dimensional (3D) bioprinting is a promising and rapidly evolving technology in the field of additive manufacturing. It enables the fabrication of living cellular constructs with complex architectures that are suitable for various biomedical applications, such as tissue engineering, disease modeling, drug screening, and precision regenerative medicine. The ultimate goal of bioprinting is to produce stable, anatomically-shaped, human-scale functional organs or tissue substitutes that can be implanted. Although various bioprinting techniques have emerged to develop customized tissue-engineering substitutes over the past decade, several challenges remain in fabricating volumetric tissue constructs with complex shapes and sizes and translating the printed products into clinical practice. Thus, it is crucial to develop a successful strategy for translating research outputs into clinical practice to address the current organ and tissue crises and improve patients’ quality of life. This review article discusses the challenges of the existing bioprinting processes in preparing clinically relevant tissue substitutes. It further reviews various strategies and technical feasibility to overcome the challenges that limit the fabrication of volumetric biological constructs and their translational implications. Additionally, the article highlights exciting technological advances in the 3D bioprinting of anatomically shaped tissue substitutes and suggests future research and development directions. This review aims to provide readers with insight into the state-of-the-art 3D bioprinting techniques as powerful tools in engineering functional tissues and organs.

ABSTRACT: In this paper, the models describing the charge transfer between two sand particles due to collisions are reviewed. By comparing the experimental results and the calculated results by the models carried on an individual particle due to a single collision, it indicates the Mosaic model is more reasonable to describe the collision charging mechanism. The Mosaic model cannot only describe the dependence of the collision charges on the relative collision speed and the particle size, but also reveal the relationship between the collision charges with the environmental temperature, the relative humidity and the material parameters, e.g., the absorption energy. Based on the Mosaic model, the model to describe the charges transfer due to multiple collisions is also developed, which can be used to calculate the charges carried by sand particles due to multiple collisions in the wind blown sand flux.

Spring operation mechanism is widely used in high voltage circuit breakers, and its reliability is related to the ability of the circuit breaker breaking fault current. During the life cycle of spring operating mechanism, stress relaxation, metal fatigue, and any other mechanical defects are easily occurring. And the mechanical performance of the circuit breaker will be influenced by the above defects. Therefore, identifying and predicting the mechanical conditions of the spring operation mechanism can improve the reliability of the circuit breaker. In the present paper, the 252 kV circuit breakers are used as test objects. Firstly, the spring stress relaxation test, the life-cycle test, and the failure simulated test of 252 kV circuit breakers are carried out. Secondly, a multi-body dynamics simulation model of the experimental prototype is established. Thirdly, support vector machine, random forest, and deep neural network are used in the condition identification of the circuit breaker to compare their performances. Then, the prediction model of spring in stress relaxation test is built, however, the model is not suitable for the life-cycle test of repeat close-open operation. Finally, the remaining useful life prediction model is proposed by using Wiener Process.

Objective To develop and externally validate a prognostic nomogram to predict overall survival (OS) in patients with resectable colon cancer. Methods Data for 50,996 patients diagnosed with non-metastatic colon cancer were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were assigned randomly to the training set (n = 34,168) or validation set (n = 16,828). Independent prognostic factors were identified by multivariate Cox proportional hazards regression analysis and used to construct the nomogram. Harrell’s C-index and calibration plots were calculated using the SEER validation set. Additional external validation was performed using a Chinese dataset (n = 342). Results Harrell’s C-index of the nomogram for OS in the SEER validation set was 0.71, which was superior to that using the 7th edition of the American Joint Committee on Cancer TNM staging (0.59). Calibration plots showed consistency between actual observations and predicted 1-, 3-, and 5-year survival. Harrell’s C-index (0.72) and calibration plot showed excellent predictive accuracy in the external validation set. Conclusions We developed a nomogram to predict OS after curative resection for colon cancer. Validation using the SEER and external datasets revealed good discrimination and calibration. This nomogram may help predict individual survival in patients with colon cancer.