A new classification for surgical NEC during exploratory laparotomy: introduction and reproducibility assessment.

PURPOSE: Variability in necrosis patterns and operative techniques in surgical necrotizing enterocolitis (NEC) necessitates a standardized classification system for consistent assessment and comparison. This study introduces a novel intraoperative reporting system for surgical NEC, focusing on reliability and reproducibility. METHODS: Analyzing surgical NEC cases from January 2018 to June 2023 at two tertiary neonatal and pediatric surgery units, a new classification system incorporating anatomical details and intestinal involvement extent was developed. Its reproducibility was quantified using kappa coefficients (κ) for interobserver and intraobserver reliability, assessed by four specialists. Furthermore, following surgery, the occurrence of mortality and enteric autonomy were evaluated on the basis of surgical decision-making of the novel intraoperative classification system for surgical NEC. RESULTS: In total, 95 patients with surgical NEC were included in this analysis. The mean κ value of the intra-observer reliability was 0.889 (range, 0.790-0.941) for the new classification, indicating excellent agreement and the inter-observer reliability was 0.806 (range, 0.718-0.883), indicating substantial agreement. CONCLUSION: The introduced classification system for surgical NEC shows high reliability, deepening the understanding of NEC's intraoperative exploration aspects. It promises to indicate operative strategies, enhance prognosis prediction, and substantially facilitate scholarly communication in pediatric surgery. Importantly, it explores the potential for a standardized report and may represent a step forward in classifying surgical NEC, if pediatric surgeons are open to change.

Vascular Aging: Assessment and Intervention.

Vascular aging represents a collection of structural and functional changes in a blood vessel with advancing age, including increased stiffness, vascular wall remodeling, loss of angiogenic ability, and endothelium-dependent vasodilation dysfunction. These age-related alterations may occur earlier in those who are at risk for or have cardiovascular diseases, therefore, are defined as early or premature vascular aging. Vascular aging contributes independently to cardio-cerebral vascular diseases (CCVDs). Thus, early diagnosis and interventions targeting vascular aging are of paramount importance in the delay or prevention of CCVDs. Here, we review the direct assessment of vascular aging by examining parameters that reflect changes in structure, function, or their compliance with age including arterial wall thickness and lumen diameter, endothelium-dependent vasodilation, arterial stiffness as well as indirect assessment through pathological studies of biomarkers including endothelial progenitor cell, lymphocytic telomeres, advanced glycation end-products, and C-reactive protein. Further, we evaluate how different types of interventions including lifestyle mediation, such as caloric restriction and salt intake, and treatments for hypertension, diabetes, and hyperlipidemia affect age-related vascular changes. As a single parameter or intervention targets only a certain vascular physiological change, it is recommended to use multiple parameters to evaluate and design intervention approaches accordingly to prevent systemic vascular aging in clinical practices or population-based studies.

Mechanistic insight into the degradation of 1H-benzotriazole and 4-methyl-1H-benzotriazole by •OH-based advanced oxidation process and toxicity assessment.

Benzotriazoles (BTs) are highly produced chemicals that are commonly used in the manufacture of aircraft de-icing/antifreeze fluids (ADAFs), coolants, etc. BTs have been detected in a variety of water environments, causing health hazards to aquatic species and humans. In this study, 1H-benzotriazole (BTri) and 4-methyl-1H-benzotriazole (4-TTri) were selected to investigate their degradation mechanisms in the aqueous phase initiated by ·OH using a theoretical calculation method. Addition reactions are the main type of reactions of ·OH with BTri and 4-TTri. The total rate constants for the reactions of BTri and 4-TTri with ·OH at 298 K are 8.26 × 109 M-1 s-1 and 1.81 × 1010 M-1 s-1, respectively. The reaction rate constants increase as the temperature rises, indicating that rising temperatures promote the degradation of BTri and 4-TTri. 7-hydroxy-1H-benzotriazole (1-P1) and 4-hydroxy-benzotriazoles (1-P2) produced via multiple reaction pathways are important transformation products of BTri. After successive reactions with ·OH, 1-P1 and 1-P2 can be successively converted to 4,7-dihydroxy-1H-benzotriazole (1-P7), 4,7-dione-1H-benzotriazole (1-P8), and 1,2,3-triazole-4,5-dicarboxylic acid (1-P9), which is consistent with the product compositions detected in the experiments. The toxicity assessment indicated that the acute toxicity and chronic toxicity of the resulting transformation products are significantly reduced compared to BTri as the degradation process progressed, and ultimately showed no harm to all three aquatic organisms (fish, daphnia, and green algae). Hence, advanced oxidation processes (AOPs) can not only effectively remove BTs from water, but also reduce their toxic effects on aquatic organisms.

Digital-Twin-Assisted Edge-Computing Resource Allocation Based on the Whale Optimization Algorithm.

With the rapid increase of smart Internet of Things (IoT) devices, edge networks generate a large number of computing tasks, which require edge-computing resource devices to complete the calculations. However, unreasonable edge-computing resource allocation suffers from high-power consumption and resource waste. Therefore, when user tasks are offloaded to the edge-computing system, reasonable resource allocation is an important issue. Thus, this paper proposes a digital-twin-(DT)-assisted edge-computing resource-allocation model and establishes a joint-optimization function of power consumption, delay, and unbalanced resource-allocation rate. Then, we develop a solution based on the improved whale optimization scheme. Specifically, we propose an improved whale optimization algorithm and design a greedy initialization strategy to improve the convergence speed for the DT-assisted edge-computing resource-allocation problem. Additionally, we redesign the whale search strategy to improve the allocation results. Several simulation experiments demonstrate that the improved whale optimization algorithm reduces the resource allocation and allocation objective function value, the power consumption, and the average resource allocation imbalance rate by 12.6%, 15.2%, and 15.6%, respectively. Overall, the power consumption with the assistance of the DT is reduced to 89.6% of the power required without DT assistance, thus, improving the efficiency of the edge-computing resource allocation.

Effects of phloridzin on blood glucose and key enzyme G-6-Pase of gluconeogenesis in mice.

The effects of phloridzin (PHL), main component of Malus hupehensis (MH) tea leaves, on blood glucose (BG) and glucose-6-phosphatase (G-6-Pase) were investigated to provide a basis for finding a scheme of stabilizing BG. Glucose uptake of insulin resistant HepG2 cells was measured by glucose oxidase method. Glucose tolerance, fasting BG (FBG) and postprandial BG (PBG) were determined by BG test strips. The expression of G-6-Pase was detected by Western blot. The results showed that glucose uptake was enhanced and the expression of G-6-Pase was inhibited by PHL in insulin resistant HepG2 cells. Glucose tolerance was enhanced, FBG level was increased and PBG level was decreased by PHL in mice. The expression of G-6-Pase in the liver was enhanced under fasting state, and was inhibited by the low and medium dose under postprandial state. It indicated that PHL has a positive effect on stabilizing BG in mice, which is related to bidirectional regulation of G-6-Pase activity. PRACTICAL APPLICATIONS: Malus hupehensis, edible and medicinal plant, which has been proved by long-term application and experiments that it has a good effect on stabilizing blood glucose, preventing diabetes and adjuvant treatment. Its effect is closely related to its main component PHL. Thus, MH can be used as a dietary regulating drink for daily life to maintain blood glucose. Its main ingredient is PHL, which can be developed as a candidate drug for diabetes treatment.

Differences in oxidative susceptibilities between glycerophosphocholine and glycerophosphoethanolamine in dried scallop (Argopecten irradians) adductor muscle during storage: an oxidation kinetic assessment.

BACKGROUND: Phospholipids, the main lipid component in marine shellfish, mainly comprise glycerophosphocholine (GPC) and glycerophosphoethanolamine (GPE). GPC and GPE in marine shellfish, especially scallop, carry n-3 long-chain polyunsaturated fatty acids, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), although different types of glycerophospholipids (GP) have different health benefits on human health. Moreover, different GP subclasses such as GPC and GPE have different oxidative susceptibilities in complex food systems. The present study compared the oxidative susceptibilities of GPC and GPE in dried scallop during storage by high-performance liquid chromatography-tandem mass spectrometry and kinetic models, and also investigated the effects of natural phenolic antioxidant on their susceptibilities. RESULTS: The results showed that GPC and GPE molecular species (carrying EPA or DHA) contents in samples continuously reduced during storage at two different temperatures. The first-order kinetic model better reflected the changes of GPC and GPE molecular species (carrying EPA or DHA) in samples than the zero-order kinetic model during storage. According to the oxidation rate (k) obtained from first-order kinetic models, GPE possessed a greater oxidation rate than GPC during storage. Moreover, the results showed that antioxidants of bamboo leaves (AOB, polar polyphenolic antioxidants) significantly decreased the oxidation rates of GPC and GPE molecular species (carrying EPA or DHA) in samples during storage, and GPC could be more effectively protected by AOB compared to GPE. CONCLUSION: The present study provides a practical method for accurately evaluating the oxidative susceptibility of different phospholipid classes in complex food systems. © 2020 Society of Chemical Industry.

Three-Column Classification for Acetabular Fractures: Introduction and Reproducibility Assessment.

BACKGROUND: The Judet-Letournel classification has been widely used to diagnose acetabular fractures since it was proposed. However, there has been growing evidence of incompleteness and comprehension difficulty in this classification, which may adversely affect its clinical use. The purposes of this study were to introduce a novel 3-column classification system for acetabular fractures and to evaluate its reliability and reproducibility. METHODS: A total of 1,028 patients with acetabular fractures, who had undergone surgical treatment from June 2011 to January 2017 in 7 level-I trauma centers, were recruited into this study. Preoperative radiographs and computed tomographic (CT) scans were conducted for each patient. To evaluate the reproducibility of the 3-column classification system for acetabular fractures, the interobserver and intraobserver reliability (kappa coefficient, κ) of this classification system compared with those of the Judet-Letournel classification system was investigated by 4 observers. RESULTS: A total of 209 patients (20.33%) could not be classified by the Judet-Letournel classification, and 3 cases (0.29%) could not be classified by the novel 3-column classification. The mean κ value of the interobserver reliability for the Judet-Letournel classification was 0.591 (range, 0.508 to 0.681), indicating moderate agreement, whereas the mean κ value was 0.735 (range, 0.594 to 0.930), indicating substantial agreement, when using the 3-column classification. The mean κ value for the intraobserver reliability was 0.751 (range, 0.708 to 0.793) for the Judet-Letournel classification and 0.909 (range, 0.792 to 0.957) for the 3-column classification. CONCLUSIONS: The 3-column classification, based on the anatomic character of the acetabulum, showed higher interobserver and intraobserver reliability than the Judet-Letournel classification. Additionally, certain fracture patterns in the 3-column classification scheme generally correlated with surgical approaches. This novel classification system may be used as a supplement to the traditional Judet-Letournel classification system. CLINICAL RELEVANCE: The 3-column concept of the acetabulum proposed in this study is helpful to master acetabular fractures for less experienced surgeons. The novel classification system could assist with acetabular fracture diagnosis and the choice of surgical approaches.

Toxicity assessment of artificially added zinc, selenium, and strontium in water.

The present research was to study the toxicology of artificially added Zn, Se and Sr in water. Specifically, we investigated the mortality and liver toxicity in zebrafish (Danio rerio), caused by different water concentrations of zinc sulfate (ZnSO4), sodium selenite (Na2SeO3), and strontium chloride hexahydrate (6H2O·SrCl2). Adult and embryo-larval zebrafish were used in the experiment. Analysis was performed of mortality, liver area and impermeability, delayed absorption area of the yolk sac, and liver tissue structure. The concentration change of sodium selenite exerted the most significant effect on the mortality of adult zebrafish, followed by that of strontium chloride hexahydrate, and zinc sulfate. Elevated strontium chloride hexahydrate concentration was associated with liver toxicity in zebrafish in the preliminary experiment. However, embryo-larval zebrafish were observed to die when the concentration of Zn2+ or Se4+ increased to a certain extent, without obvious liver toxicity. Our results indicated strontium chloride hexahydrate was hepatotoxic to embryo-larval zebrafish, which was manifested mainly as hepatomegaly and delayed absorption of the yolk sac. In addition, the artificially added strontium chloride hexahydrate destroyed liver tissue structure, resulting in hepatocyte enlargement, cell nucleus enlargement, blurred cytoplasmic boundaries, and formation of a vacuolar liver. These findings suggest the amount of strontium chloride hexahydrate added in soft drinks should be limited to certain levels.

[Distribution and Removal of Antibiotic Resistance Genes in Two Sequential Wastewater Treatment Plants].

Wastewater treatment plants (WWTPs) have been regarded as important point-sources of antibiotic resistance genes (ARGs) in aquatic environments. To investigate the distribution and removal of ARGs in WWTPs, a pharmaceutical wastewater treatment plant (PWWTP) and an integrated wastewater treatment plant (IWWTP) in a fine-chemical industrial park were chosen, and polymerase chain reaction (PCR) and real-time PCR techniques were used to determine the occurrence and abundances of ARGs along the treatment processes. Ten and fifteen ARGs were detected initially in the influents of PWWTP and IWWTP respectively, in which tetracycline and sulfonamide resistance genes were frequently reported, while dfrA13 was first reported in WWTPs. The most abundant ARGs in the influents were sul Ⅰ and sul Ⅱ, followed by dfrA13, tetQ, floR, tetO, and tetW. The total ARGs increased by 0.21 log after the treatment by PWWTP, whose effluent contributed 0.87% to the inflow yet 5.05% to the total ARGs of IWWTP. Finally the total ARGs removed by IWWTP was 1.03 log, with the remaining ARGs then transported within the final effluent to the nearby coastal area. The authors concluded that the environmental and other impacts from the spread of ARGs on the microbial communities of the coastal environment needed further study.

Heavy metal pollution of oil-based drill cuttings at a shale gas drilling field in Chongqing, China: A human health risk assessment for the workers.

With the flourish of shale gas industry in China, the characteristic hazardous waste, oil-based drill cuttings (OBDC), was also produced in large quantities. Unlike traditional petroleum industry, shale gas exploitation covers a wider area and there are more well sites, the adverse effects of OBDC piled up around well sites are even greater. This study investigated the pollution status and leaching toxicity of eight heavy metals (Cd, Cr, Cu, Hg, Mn, Ni, Pb and Zn) in OBDC of shale gas exploitation, and evaluated the health risks of the drilling workers. The results showed that heavy metal pollution in OBDC was moderate, and the leaching toxicity was far below the standard value. Non-carcinogenic and carcinogenic risks of drilling workers were within an acceptable range. Meanwhile, in order to reduce the health risks of drilling workers, some suggestions are proposed to reduce the exposure risks of workers and the content of heavy metals in OBDC.

CLImAT-HET: detecting subclonal copy number alterations and loss of heterozygosity in heterogeneous tumor samples from whole-genome sequencing data.

BACKGROUND: Copy number alterations (CNA) and loss of heterozygosity (LOH) represent a large proportion of genetic structural variations of cancer genomes. These aberrations are continuously accumulated during the procedure of clonal evolution and patterned by phylogenetic branching. This invariably results in the emergence of multiple cell populations with distinct complement of mutational landscapes in tumor sample. With the advent of next-generation sequencing technology, inference of subclonal populations has become one of the focused interests in cancer-associated studies, and is usually based on the assessment of combinations of somatic single-nucleotide variations (SNV), CNA and LOH. However, cancer samples often have several inherent issues, such as contamination of normal stroma, tumor aneuploidy and intra-tumor heterogeneity. Addressing these critical issues is imperative for accurate profiling of clonal architecture. METHODS: We present CLImAT-HET, a computational method designed for capturing clonal diversity in the CNA/LOH dimensions by taking into account the intra-tumor heterogeneity issue, in the case where a reference or matched normal sample is absent. The algorithm quantitatively represents the clonal identification problem using a factorial hidden Markov model, and takes an integrated analysis of read counts and allele frequency data. It is able to infer subclonal CNA and LOH events as well as the fraction of cells harboring each event. RESULTS: The results on simulated datasets indicate that CLImAT-HET has high power to identify CNA/LOH segments, it achieves an average accuracy of 0.87. It can also accurately infer proportion of each clonal population with an overall Pearson correlation coefficient of 0.99 and a mean absolute error of 0.02. CLImAT-HET shows significant advantages when compared with other existing methods. Application of CLImAT-HET to 5 primary triple negative breast cancer samples demonstrates its ability to capture clonal diversity in the CAN/LOH dimensions. It detects two clonal populations in one sample, and three clonal populations in one other sample. CONCLUSIONS: CLImAT-HET, a novel algorithm is introduced to infer CNA/LOH segments from heterogeneous tumor samples. We demonstrate CLImAT-HET's ability to accurately recover clonal compositions using tumor WGS data without a match normal sample.

Identification of Genomic Aberrations in Cancer Subclones from Heterogeneous Tumor Samples.

Tumor samples are usually heterogeneous, containing admixture of more than one kind of tumor subclones. Studies of genomic aberrations from heterogeneous tumor data are hindered by the mixed signal of tumor subclone cells. Most of the existing algorithms cannot distinguish contributions of different subclones from the measured single nucleotide polymorphism (SNP) array signals, which may cause erroneous estimation of genomic aberrations. Here, we have introduced a computational method, Cancer Heterogeneity Analysis from SNP-array Experiments (CHASE), to automatically detect subclone proportions and genomic aberrations from heterogeneous tumor samples. Our method is based on HMM, and incorporates EM algorithm to build a statistical model for modeling mixed signal of multiple tumor subclones. We tested the proposed approach on simulated datasets and two real datasets, and the results show that the proposed method can efficiently estimate tumor subclone proportions and recovery the genomic aberrations.

Comprehensive study of tumour single nucleotide polymorphism array data reveals significant driver aberrations and disrupted signalling pathways in human hepatocellular cancer.

The authors describe an integrated method for analysing cancer driver aberrations and disrupted pathways by using tumour single nucleotide polymorphism (SNP) arrays. The authors new method adopts a novel statistical model to explicitly quantify the SNP signals, and therefore infers the genomic aberrations, including copy number alteration and loss of heterozygosity. Examination on the dilution series dataset shows that this method can correctly identify the genomic aberrations even with the existence of severe normal cell contamination in tumour sample. Furthermore, with the results of the aberration identification obtained from multiple tumour samples, a permutation-based approach is proposed for identifying the statistically significant driver aberrations, which are further incorporated with the known signalling pathways for pathway enrichment analysis. By applying the approach to 286 hepatocellular tumour samples, they successfully uncover numerous driver aberration regions across the cancer genome, for example, chromosomes 4p and 5q, which harbour many known hepatocellular cancer related genes such as alpha-fetoprotein (AFP) and ectodermal-neural cortex (ENC1). In addition, they identify nine disrupted pathways that are highly enriched by the driver aberrations, including the systemic lupus erythematosus pathway, the vascular endothelial growth factor (VEGF) signalling pathway and so on. These results support the feasibility and the utility of the proposed method on the characterisation of the cancer genome and the downstream analysis of the driver aberrations and the disrupted signalling pathways.

GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays.

There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies.

MixHMM: inferring copy number variation and allelic imbalance using SNP arrays and tumor samples mixed with stromal cells.

BACKGROUND: Genotyping platforms such as single nucleotide polymorphism (SNP) arrays are powerful tools to study genomic aberrations in cancer samples. Allele specific information from SNP arrays provides valuable information for interpreting copy number variation (CNV) and allelic imbalance including loss-of-heterozygosity (LOH) beyond that obtained from the total DNA signal available from array comparative genomic hybridization (aCGH) platforms. Several algorithms based on hidden Markov models (HMMs) have been designed to detect copy number changes and copy-neutral LOH making use of the allele information on SNP arrays. However heterogeneity in clinical samples, due to stromal contamination and somatic alterations, complicates analysis and interpretation of these data. METHODS: We have developed MixHMM, a novel hidden Markov model using hidden states based on chromosomal structural aberrations. MixHMM allows CNV detection for copy numbers up to 7 and allows more complete and accurate description of other forms of allelic imbalance, such as increased copy number LOH or imbalanced amplifications. MixHMM also incorporates a novel sample mixing model that allows detection of tumor CNV events in heterogeneous tumor samples, where cancer cells are mixed with a proportion of stromal cells. CONCLUSIONS: We validate MixHMM and demonstrate its advantages with simulated samples, clinical tumor samples and a dilution series of mixed samples. We have shown that the CNVs of cancer cells in a tumor sample contaminated with up to 80% of stromal cells can be detected accurately using Illumina BeadChip and MixHMM. AVAILABILITY: The MixHMM is available as a Python package provided with some other useful tools at http://genecube.med.yale.edu:8080/MixHMM.

[Prediction of protein solvent accessibility with Markov chain model].

Residues in protein sequences can be classified into two (exposed / buried) or three (exposed/intermediate/buried) states according to their relative solvent accessibility. Markov chain model (MCM) had been adopted for statistical modeling and prediction. Different orders of MCM and classification thresholds were explored to find the best parameters. Prediction results for two different data sets and different cut-off thresholds were evaluated and compared with some existing methods, such as neural network, information theory and support vector machine. The best prediction accuracies achieved by the MCM method were 78.9% for the two-state prediction problem and 67.7% for the three-state prediction problem, respectively. A comprehensive comparison for all these results shows that the prediction accuracy and the correlative coefficient of the MCM method are better than or comparable to those obtained by the other prediction methods. At the same time, the advantage of this method is the lower computation complexity and better time-consuming performance.

PPSP: prediction of PK-specific phosphorylation site with Bayesian decision theory.

BACKGROUND: As a reversible and dynamic post-translational modification (PTM) of proteins, phosphorylation plays essential regulatory roles in a broad spectrum of the biological processes. Although many studies have been contributed on the molecular mechanism of phosphorylation dynamics, the intrinsic feature of substrates specificity is still elusive and remains to be delineated. RESULTS: In this work, we present a novel, versatile and comprehensive program, PPSP (Prediction of PK-specific Phosphorylation site), deployed with approach of Bayesian decision theory (BDT). PPSP could predict the potential phosphorylation sites accurately for approximately 70 PK (Protein Kinase) groups. Compared with four existing tools Scansite, NetPhosK, KinasePhos and GPS, PPSP is more accurate and powerful than these tools. Moreover, PPSP also provides the prediction for many novel PKs, say, TRK, mTOR, SyK and MET/RON, etc. The accuracy of these novel PKs are also satisfying. CONCLUSION: Taken together, we propose that PPSP could be a potentially powerful tool for the experimentalists who are focusing on phosphorylation substrates with their PK-specific sites identification. Moreover, the BDT strategy could also be a ubiquitous approach for PTMs, such as sumoylation and ubiquitination, etc.