Search

Background: Near-infrared spectroscopy (NIRS) enables a non-invasive measurement of tissue oxygen saturation (StO2) in regions illuminated by near-infrared lights. Vascular occlusion test (VOT) serves as a model to artificially induce forearm ischemia-reperfusion. The combination of StO2 monitoring and VOT allows for dynamic evaluation of the balance between oxygen delivery and consumption in tissue, as well as the functional reserve of microcirculation. However, the implications of these measurements for patient outcomes remain inadequately understood. This study aimed to investigate the association between StO2-VOT measurements and the occurrence of postoperative acute kidney injury (AKI), in patients undergoing cardiac surgery with cardiopulmonary bypass (CPB). Methods: Between March 2020 and March 2021, 100 adult patients who scheduled to undergo cardiac surgery with mild hypothermic CPB were enrolled to this prospective observational study. StO2 was continuously monitored at the right forearm and ipsilateral VOT procedure was performed before initiation of CPB, at the time before weaning from CPB, and at the end of surgery. Preoperative and intraoperative factors, along with StO2-VOT parameters, were evaluated for their independent association with the occurrence of AKI following cardiac surgery. StO2-VOT parameters were also compared between patients with hyperlactatemia (peak blood lactate ≥ 4 mmol/L) and those without hyperlactatemia. Results: In our patient population (n = 87), 13.79% (12/87) patients developed AKI after surgery. Multivariable analysis revealed that CPB time and post-CPB desaturation speed (D-speed) were independently associated with AKI. Post-CPB D-speed had an area under receiver operating characteristic (ROC) curve of 0.79 (95% CI, 0.66–0.93) with a cutoff value of 0.08%·min− 1 in predicting AKI. Patients with hyperlactatemia had longer pre-CPB T1 and higher D-speed during CPB. However, ROC analysis indicated that T1 and D-speed exhibited limited predictive capacity for hyperlactatemia. Patients with AKI exhibited an increased risk of prolonged ICU stays, postoperative stroke, reoperation, and in-hospital mortality. Conclusions: NIRS monitoring combined with VOT shows promise in predicting postoperative AKI in patients undergoing cardiac surgery with mild hypothermic CPB. Trial registration: ChiCTR1900021436 with registered date 21/02/2019. [ABSTRACT FROM AUTHOR]

SIRT6, a member of the sirtuin protein family, is recognized as a tumor suppressor. This study investigates the evolutionary history of the SIRT gene family and examines the selective pressures shaping their functional divergence. Insights into the evolution of these genes may enhance our understanding of their roles in disease pathology. Seventy-three amino acid sequences and full-length mRNA sequences from 22 vertebrate species and one invertebrate were retrieved from public databases. Phylogenetic relationships among the seven SIRT gene family members were reconstructed using Bayesian inference. Codon-based models were applied to detect site-specific positive selection, and likelihood ratio tests (LRTs) were used to compare model fits. Positively selected sites were identified using Bayesian empirical Bayes (BEB) methods. Phylogenetic analysis revealed that the seven SIRT gene family members in vertebrates originated from gene duplication events. Asymmetric evolutionary rates and natural selection were identified as the primary drivers of SIRT gene divergence. Eleven positively selected sites (23I, 310 S, 311I, 313 A, 316 K, 320 C, 321 A, 322Q, 323 H, 327E, 328P) were identified with high confidence (posterior probability ≥ 99%), suggesting critical roles in functional divergence. The evolution of the SIRT gene family is characterized by gene duplication and natural selection. The reconstructed phylogenetic tree elucidates the relationships among the seven members, with SIRT6 emerging as a key evolutionary node. Positively selected sites identified in this study may represent mutation hotspots, providing potential targets for future cancer therapy research. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Methods Results Conclusions Repetitive negative thinking (RNT) as a cognitive process in multiple mental disorders is a key risk factor for mental disorders. It is associated with the development and maintenance of the illness. The perseverative thinking questionnaire (PTQ) is an instrument to evaluate RNT with excellent reliability and validity. Nevertheless, a Chinese version of the perseverative thinking questionnaire (C‐PTQ) is lack of validation in Chinese college students. The study aimed to establish a C‐PTQ, explore its psychometric properties in college students.After translating PTQ into Chinese, we investigated 696 college students. We conducted exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to examine the psychometric properties and factor structures of the C‐PTQ. Content validity was assessed using the content validity index and internal consistency was assessed using the Cronbach's α and McDonald's Omega ω. Multi‐variable linear regressions explored the relationships between variables. We used receiver operating characteristic (ROC) curves to determine the ability of C‐PTQ in identifying depression and anxiety.The EFA showed a one‐factor structure, which explained 52.227% of the total variance. The CFA showed that both one‐factor structure in this research and three‐factor structure of original demonstrated eligible model fits. The content validity index of 0.93. Results demonstrated good internal consistency (Cronbach's α = 0.934, McDonald's Omega ω = 0.934) and convergent validity. The PTQ is a useful tool in identifying depression (sensitivity = 85.5%, specificity = 64.6%) and anxiety (sensitivity = 84.6%, specificity = 68.5%).The C‐PTQ has good psychometric properties, which is valid and reliable for assessing RNT in Chinese college students. [ABSTRACT FROM AUTHOR]

The rapid digitalization of organizations has positioned the digital transformation of Human Resources (HR) as a critical trend for the future. In particular, exponential organizations—characterized by their ability to leverage digital technology to achieve disproportionately large impacts relative to their size—require a fundamental shift in the role and competencies of HR professionals. This study focuses on the competencies required of Human Resource Directors (HRDs) within these highly adaptive and scalable organizations, using Shandong Province as a case sample. Grounded in the Resource-Based View (RBV), which emphasizes that a firm's internal resources are essential for sustaining competitive advantage, we argue that HRDs competencies are critical resources for organizations undergoing digital transformation. Through the application of methods such as questionnaire surveys, structural equation modeling, and t-tests, we identified and validated 11 key competency indicators for HRDs in the context of digital transformation. These indicators are grouped into four dimensions based on Dave Ulrich's framework: Strategic Partner, Change Agent, Administrative Expert, and Employee Champion. Our research organizes these 11 competencies within the four dimensions, providing a structured framework for evaluating the evolving role of HRDs in the digital era. These 11 competencies offer organizations valuable insights, particularly in organizational development, talent acquisition and deployment, employee training and upskilling, and performance evaluation, contributing to a more comprehensive understanding of the competencies needed for HR leadership in the digital age. [ABSTRACT FROM AUTHOR]

Objectives: To search for pathogenic gene of a family with non‐syndromic tooth agenesis, and explore the possible pathogenesis. Materials and Methods: A Chinese family with non‐syndromic tooth agenesis was recruited and screened for the pathogenic variants by whole exome sequencing technology and co‐segregation analysis. The subcellular localization of wild‐type and mutant protein was detected by immunofluorescence assay. Cycloheximide chase assay was performed to examine the difference in degradation rate between mutant protein and wild‐type one. Dual‐luciferase reporter assays were conducted to explore the alterations of mutant protein in the regulation of downstream target genes. Results: A novel missense variant of PAX9 (c.296C>A:p.A99D) was found in this family. Bioinformatics software showed β‐return and the random coil were shortened in the p.A99D. The variant did not affect the subcellular localization of PAX9, but the degradation rate of p.A99D was accelerated (p < 0.05). p.A99D inhibited the activation of downstream target gene BMP4 (p < 0.05). Conclusions: This novel variant expands the pathogenic gene spectrum. The variant impaired the protein structure, accelerated the degradation of protein, and inhibited the activation of the downstream target gene BMP4, an upstream molecule in the TGF‐β/BMP pathway, which may contribute to tooth agenesis in this family. [ABSTRACT FROM AUTHOR]

To date, SARS‐CoV‐2 has caused millions of deaths, but the choice of treatment is limited. We previously established a platform for identifying Food and Drug Administration (FDA)‐approved repurposed drugs for avian influenza A virus infections that could be used for coronavirus disease 2019 (COVID‐19) treatment. In this study, we analyzed blood samples from two cohorts of 63 COVID‐19 patients, including 19 patients with severe disease. Among the 39 FDA‐approved drugs we identified for COVID‐19 therapy in both cohorts, 23 drugs were confirmed by literature mining data, including 14 drugs already under COVID‐19 clinical trials and 9 drugs reported for COVID‐19 treatments, suggesting the remaining 16 FDA‐approved drugs may be candidates for COVID‐19 therapy. Additionally, we previously reported that herbal small RNAs (sRNAs) could be effective components in traditional Chinese medicine (TCM) for treating COVID‐19. Based on the abundance of sRNAs, we screened the 245 TCMs in the Bencao (herbal) sRNA Atlas that we had previously established, and we found that the top 12 TCMs for COVID‐19 treatment was consistent across both cohorts. We validated the efficiency of the top 30 sRNAs from each of the top 3 TCMs for COVID‐19 treatment in poly(I:C)‐stimulated human non‐small cell lung cancer cells (A549 cells). In conclusion, our study recommends potential COVID‐19 remedies using FDA‐approved repurposed drugs and herbal sRNAs from TCMs. [ABSTRACT FROM AUTHOR]

To explore effective measures to control the flavor of spicy salted duck irradiated by 60Co-γ ray and electron beam, the effects of antioxidants and irradiation temperature on the flavor and electron beam were studied using electronic nose and electronic tongue detection techniques. Radar analysis, principal component analysis (PCA), and linear discriminant analysis (LDA) were performed on the E-tongue and E-nose experimental data. The results indicated that there were significant differences in the flavor of spicy salted duck samples with different treatments (p

Aiming at the difficulty of detecting the surface defects of complex texture tiles, a salient target detection method based on the human visual attention mechanism is proposed and used for the detection of tile surface defects. Firstly, the image of ceramic tile surface is pretreated using the single-scale SSR light correction method and bilateral filtering method; Secondly, according to the principle of contrast and high-frequency suppression in the visual attention mechanism, aiming at the "imaging" and "aggregation" characteristics of complex background textures, a detection model based on the visual attention mechanism is established to determine and mark defects.According to the contrast principle and high-frequency suppression principle in visual attention mechanism, feature extraction of ceramic tile surface is carried out. Then, the image color patch weight salient map and image feature fused salient map are obtained, and the two maps are fused according to the image saliency criteria.Finally, the marked ceramic tile defects are determined and marked.Finally the marked ceramic tile defects are obtained. This defect detection algorithm and the other two algorithms are applied to three kinds of randomly selected complex texture ceramic tiles. The experimental results show that compared with other algorithms, our algorithm can achieve a comprehensive detection rate of more than 96% for complex texture ceramic tiles, and can obtain a good effect of ceramic tile defect detection as well.

Abstract Calamansi or Philippine lime (Citrofortunella macrocarpa) is an important crop for local economic in Hainan Island. There is no study about Calamansi germplasm evaluation and cultivar development. In this study, Calamansi data were collected from 151 of Calamansi seedling trees, and 37 phenotypic traits were analyzed to investigate their genetic diversities. The cluster analysis and principal component analysis were conducted aiming to provide a theoretical basis for the Calamansi genetic improvement. The results of the diversity analysis revealed: (1) the diversity indexes for qualitative traits were ranged from 0.46–1.39, and the traits with the highest genetic diversity level were fruit shaped and pulp colored (H′ > 1.20); and the diversity indexes for quantitative traits ranged from 0.67–2.10, with the exception of a lower in fruit juice rate (1.08) and lower in number of petals (0.67). (2) The clustering analysis of phenotypic traits have arranged the samples into 4 categories: the first group characterized by fewer flesh Segment number per fruit (SNF) and more Oil cell number (OCN); the second group had 7 samples, all characterized with larger Crown breadth (CB), higher Yield per tree (YPT), the lager leaf, the higher Ascorbic acid (AA), and less Seed number per fruit (SNPF); the third group had 25 samples characterized by smaller Tree foot diameter (TFD),smaller Fruit shape index (FSI) and higher Total soluble solids (TSS) contain; the fourth group had 87 samples, they were characterized by shorter Petiole length (PEL), larger fruit, higher Juice ratio (JR), multiple Stamen number (SN) and longer Pistil length (PIL). (3) The principal component analysis showed the values of the first 9 major components characteristic vectors were all greater than 3, the cumulative contribution rate reach 72.20%, including the traits of single fruit weight, fruit diameter, tree height, tree canopy width etc. Finally, based on the comprehensive main component value of all samples, the Calamansi individuals with higher testing scores were selected for further observation. This study concludes that Calamansi seedling populations in the Hainan Island holds great genetic diversity in varies traits, and can be useful for the Calamansi variety improvements.

The weight-loading swimming assay, liver glycogen and serum urea nitrogen tests in mice were used to evaluate the alleviating physical fatigue effects of Lijiang and Peru Maca. The mouse mating assay, sperm quantity, survival rate and gonadal organ index tests were used to observe the improving sexual function between them. The acute toxicity test was used to evaluate the safety of two samples. The result showed that compared with the blank control group, Lijiang and Peru Maca can significantly increase the swimming time and the level of liver glycogen, as well as reduce the level of urea nitrogen in mice. Compared with the blank control group, Lijiang and Peru Maca can obviously improve the mating ability, sperm quantity and testis index in mice, but it has no obvious effect on sperm viability, seminal vesicles and Foreskin gland index. Compared with the Peru Maca group, there was no significant difference in the activity of anti-fatigue and improving sexual function. The acute toxicity test showed that the maximum dose of Lijiang and Peru Maca was 17.48g/kg. There was no toxicity or death after administration.

The ultimate bearing capacity of K-type tube-gusset plate joints was experimentally investigated in the engineering context of ultrahigh voltage (UHV) steel tube transmission towers. Three K-joint specimens were fabricated: ZK30, ZK50 and PK30, where the eccentricity e of the ZK and PK specimens was 0 and D/4, respectively. The branch and main load ratios λ are 29.41% and 50% for ZK30 and ZK50, respectively, and 29.41% for PK30. The experimental results show that increasing λ has a negative effect on the bearing capacity of the main tube. Compared with ZK30, ZK50 has 17% lower main tube axial force and 33% higher branch tube axial force when the specimen was failed. In contrast, the negative eccentricity is beneficial to the bearing capacity of the main tube. Compared with ZK30, PK30 has the same main tube axial force and 6.7% higher branch tube axial force when the specimen was failed. Local buckling occurs in both ZK30 and ZK50, while overall failure occurs in the PK specimen. The finite element model (FEM) in the ABAQUS platform with initial geometric defects was verified by the experimental results. The stress distribution, failure mode and ultimate bearing capacity of the FEM show agreement with the experimental results. The simplified FEM was employed to analyze the bending capacity of K-joints with different diameters of the main tube, different thicknesses of the main tube and different lengths of the gusset plate. The results show that for the K-joints analyzed in this paper, the bending bearing capacity only decreased by 16.41% as the diameter of the main pipe increased by 50.25%, increased by 48.99% as the length of the node plate increased by 37.50%, and increased by 145.33% as the wall of the main pipe increased by 71.43%. The formula for calculating the bending capacity of the K-type tube-gusset plate joint was fitted. Compared with the existing specifications, calculation results with the fitting formula are more similar to those of the FEM.

The characteristics of acoustic emission signals generated in the process of rock deformation and fission contain rich information on internal rock damage. The use of acoustic emissions monitoring technology can analyze and identify the precursor information of rock failure. At present, in the field of acoustic emissions monitoring and the early warning of rock fracture disasters, there is no real-time identification method for a disaster precursor characteristic signal. It is easy to lose information by analyzing the characteristic parameters of traditional acoustic emissions to find signals that serve as precursors to disasters, and analysis has mostly been based on post-analysis, which leads to poor real-time recognition of disaster precursor characteristics and low application levels in the engineering field. Based on this, this paper regards the acoustic emissions signal of rock fracture as a kind of speech signal generated by rock fracture uses this idea of speech recognition for reference alongside spectral analysis (STFT) and Mel frequency analysis to realize the feature extraction of acoustic emissions from rock fracture. In deep learning, based on the VGG16 convolutional neural network and AlexNet convolutional neural network, six intelligent real-time recognition models of rock fracture and key acoustic emission signals were constructed, and the network structure and loss function of traditional VGG16 were optimized. The experimental results show that these six deep-learning models can achieve the real-time intelligent recognition of key signals, and Mel, combined with the improved VGG16, achieved the best performance with 87.68% accuracy and 81.05% recall. Then, by comparing multiple groups of signal recognition models, Mel+VGG-FL proposed in this paper was verified as having a high recognition accuracy and certain recognition efficiency, performing the intelligent real-time recognition of key acoustic emission signals in the process of rock fracture more accurately, which can provide new ideas and methods for related research and the real-time intelligent recognition of rock fracture precursor characteristics.