Construction of a nomogram for preoperative prediction of the risk of lymph node metastasis in early gastric cancer

BackgroundThe status of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) is particularly important for the formulation of clinical treatment. The purpose of this study was to construct a nomogram to predict the risk of LNM in EGC before operation.MethodsUnivariate analysis and logistic regression analysis were used to determine the independent risk factors for LNM. The independent risk factors were included in the nomogram, and the prediction accuracy, discriminant ability and clinical practicability of the nomogram were evaluated by the receiver operating characteristic curve (ROC), calibration curve and clinical decision curve (DCA), and 100 times ten-fold cross-validation was used for internal validation.Results33 (11.3%) cases of AGC were pathologically confirmed as LNM. In multivariate analysis, T stage, presence of enlarged lymph nodes on CT examination, carbohydrate antigen 199 (CA199), undifferentiated histological type and systemic inflammatory response index (SIRI) were risk factors for LNM. The area under the ROC curve of the nomogram was 0.86, the average area under the ROC curve of the 100-fold ten-fold cross-validation was 0.85, and the P value of the Hosmer-Lemeshow test was 0.60. In addition, the clinical decision curve, net reclassification index (NRI) and Integrated Discriminant Improvement Index (IDI) showed that the nomogram had good clinical utility.ConclusionsWe found that SIRI is a novel biomarker for preoperative prediction of LNM in EGC, and constructed a nomogram for preoperative prediction of the risk of LNM in EGC, which is helpful for the formulation of the clinical treatment strategies

Nitric oxide-induced lipophagic defects contribute to testosterone deficiency in rats with spinal cord injury

IntroductionMales with acute spinal cord injury (SCI) frequently exhibit testosterone deficiency and reproductive dysfunction. While such incidence rates are high in chronic patients, the underlying mechanisms remain elusive.Methods and resultsHerein, we generated a rat SCI model, which recapitulated complications in human males, including low testosterone levels and spermatogenic disorders. Proteomics analyses showed that the differentially expressed proteins were mostly enriched in lipid metabolism and steroid metabolism and biosynthesis. In SCI rats, we observed that testicular nitric oxide (NO) levels were elevated and lipid droplet-autophagosome co-localization in testicular interstitial cells was decreased. We hypothesized that NO impaired lipophagy in Leydig cells (LCs) to disrupt testosterone biosynthesis and spermatogenesis. As postulated, exogenous NO donor (S-nitroso-N-acetylpenicillamine (SNAP)) treatment markedly raised NO levels and disturbed lipophagy via the AMPK/mTOR/ULK1 pathway, and ultimately impaired testosterone production in mouse LCs. However, such alterations were not fully observed when cells were treated with an endogenous NO donor (L-arginine), suggesting that mouse LCs were devoid of an endogenous NO-production system. Alternatively, activated (M1) macrophages were predominant NO sources, as inducible NO synthase inhibition attenuated lipophagic defects and testosterone insufficiency in LCs in a macrophage-LC co-culture system. In scavenging NO (2-4-carboxyphenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (CPTIO)) we effectively restored lipophagy and testosterone levels both in vitro and in vivo, and importantly, spermatogenesis in vivo. Autophagy activation by LYN-1604 also promoted lipid degradation and testosterone synthesis.DiscussionIn summary, we showed that NO-disrupted-lipophagy caused testosterone deficiency following SCI, and NO clearance or autophagy activation could be effective in preventing reproductive dysfunction in males with SCI

3D quantification for aggregate morphology using surface discretization based on solid modeling

Sphericity, form dimensions, and angularity are important morphological properties of aggregates that significantly affect the microstructure of grain-based materials and their macromechanical performance. The objective of this paper was to quantify aggregate morphology, including sphericity index (SI), dimension index (DI), and angularity index (AI) based on three-dimensional (3D) solid modeling. The methodology consisted of three main steps, as follows: (1) the 3D solid model of each aggregate was developed from X-ray computed tomography (CT) imaging; (2) the model surface was discretized into triangle facets, and the vertexes of facets were used to accurately retrieve the minimum bounding sphere (MBS) and the minimum bounding box (MBB) of the aggregate model for SI and DI calculation, respectively; and (3) consequently, the facets were well clustered to represent aggregate angles for their magnitude measurements, which were used to quantify the AI. The 3D SI, DI, and AI of 11 grains were measured virtually with the proposed approach, which indicates the benefits of the 3D method in the accurate quantification of aggregate sphericity, form dimensions, and angularity

Prediction of Surface Roughness of 304 Stainless Steel and Multi-Objective Optimization of Cutting Parameters Based on GA-GBRT

Establishing and controlling the prediction model of a machined surface quality is known as the basis for sustainable manufacturing. An ensemble learning algorithm—the gradient boosting regression tree—is incorporated into the surface roughness modeling. In order to address the problem of a high time cost and tendency to fall into a local optimum solution when the grid search and conjugate gradient method is adopted to obtain the super-parameters of the ensemble learning algorithm, a genetic algorithm is employed to search for the optimal super-parameters in the training process, and a genetic-gradient boosting regression tree (GA-GBRT) algorithm is developed. A fitting goodness of fit is taken as the fitness function value of the genetic algorithm and combined with k-fold cross-validation, as such, the initial model parameters of the gradient boosting regression tree are optimized. Compared to the optimized artificial neural network (ANN) and support vector regression (SVR) and combined with the cutting experiment of 304 stainless steel with a micro-groove tool, a genetic algorithm multi-objective optimization model with the highest cutting efficiency and a supreme surface quality was constructed by applying the GA-GBRT model. The response relationship reveals the non-linear interaction that occurs between the cutting parameters and the surface roughness of 304 stainless steel that is machined by the micro-groove tool. As indicated by the results obtained from the multi-objective optimization, the cutting efficiency can be enhanced by increasing the cutting speed and depth within a small range of surface quality variations. The GA-GBRT model is validated to be reliable in making a prediction of the surface roughness and optimizing the cutting parameters with turning and milling data

eDNA Biomonitoring of Macroinvertebrate Communities for the Bioassessment of a River’s Ecological Status

Environmental DNA (eDNA) becomes a promising technology for macroinvertebrate monitoring worldwide. In recent decades, with increasing humanization processes, such as water pollution and habitat fragmentation, the richness and abundance of macroinvertebrates show a dramatic decline, which is particularly evident in tropical or subtropical rivers. The high-throughput and rapid monitoring of species’ survival and the ecological status of their habitats are relevant to river management. Here, we used the eDNA technology to detect macroinvertebrates in the Dongjiang River—a typical subtropical river in Southern China, to assess the ecological status, based on eDNA datasets. Our data showed a total of 640 OTUs detected by eDNA technology, belonging to three phyla, five classes, 13 orders, 33 families and 71 genera of macroinvertebrates, and these taxa had a 36.6% coverage rate with historical data at the genus level. The traditional water quality index (WQI) showed that the upstream of Dongjiang River were mainly levels I~II, the middle stream were levels II~III, and the downstream were levels IV~V. The eDNA-based biotic indices showed almost the same findings, that is, the overall ecological status of Dongjiang River was: upstream > middle reaches > downstream. Overall, this study provides important datasets and technical support for eDNA technology in macroinvertebrate monitoring and ecosystem management in the subtropical rivers

Tribological Performance of Micro-Groove Tools of Improving Tool Wear Resistance in Turning AISI 304 Process

AISI 304 has good physical and chemical properties and thus is widely used. However, due to the low thermal diffusivity, the cutting temperature of AISI 304 is high accelerating the wear of the tool. Therefore, tool wear is a major problem in machining hard cutting materials. In this study, we developed a new type of micro-groove tool whose rake surface was distributed with micro-groove by powder metallurgy based on the finite element temperature field morphology. We compared the wear of the proposed micro-groove tool with an untreated one by using a scanning electron microscope (SEM) and an X-ray energy spectrum. The abrasive, adhesive, and oxidation wear of the rake and the flank face of the micro-groove tool were lower than that of the untreated one. Due to the micro-groove on the rake face of the tool, the contact length between the tool and chip was reduced, leaving more extension space. Furthermore, chip extrusion deformation was avoided, and the energy caused by chip deformation was reduced. After 70 min of cutting, the counterpart reached the specified wear amount while the main cutting force, the feed resistance, and the cutting depth resistance of the proposed micro-groove tool were reduced by 16.1%, 33.9%, and 40.1%, respectively. With regard to steady state, the cutting temperature was reduced by 17.2% and the wear width of the flank face was reduced by 36.7%

Complete mitochondrial genome and phylogenetic position of Pangasius sanitwongsei (Siluriformes: Pangasiidae)

In this study, the complete mitochondrial genome of Pangasius sanitwongsei was firstly reported and analyzed. It had a double-stand DNA molecule with 16536 bp in length, consisting of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and one control region. The structural organization and gene order was similar to other bony fishes. The complete mitochondrial genome of P. sanitwongsei provided in this work would be helpful for further research on phylogenetics and conservation genetics of the Siluriformes and other orders

A 3-D net based on weak metallophilic (Cu⋯Cu) interactions

A novel 3-D binary copper(I) polymer [Cu(IN)]n (1, IN = isonicotinate) has been solvothermally synthesized. 1-D [Cu(IN)] chains of 1 are interconnected by weak metallophilic (Cu⋯Cu) interactions to form a 3-D net. The theoretical band structure and photocatalytic and fluorescence properties have also been studied