Distinct gut microbiomes in Thai patients with colorectal polyps.

BACKGROUND: Colorectal polyps that develop via the conventional adenoma-carcinoma sequence [e.g., tubular adenoma (TA)] often progress to malignancy and are closely associated with changes in the composition of the gut microbiome. There is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway, such as hyperplastic polyps (HP). Exploration of microbiome alterations associated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal carcinogenesis. AIM: To investigate gut microbiome signatures, microbial associations, and microbial functions in HP and TA patients. METHODS: Full-length 16S rRNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps [control group (CT), n = 40], patients with HP (n = 52), and patients with TA (n = 60). Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or TA. Analytical techniques in this study included differential abundance analysis, co-occurrence network analysis, and differential pathway analysis. RESULTS: Colorectal cancer (CRC)-associated bacteria, including Streptococcus gallolyticus (S. gallolyticus), Bacteroides fragilis, and Clostridium symbiosum, were identified as characteristic microbial species in TA patients. Mediterraneibacter gnavus, associated with dysbiosis and gastrointestinal diseases, was significantly differentially abundant in the HP and TA groups. Functional pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively, whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis (e.g., mevalonate); S. gallolyticus was a major contributor. Co-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients, whereas TA patients exhibited co-occurrence of CRC-associated bacteria. Furthermore, the co-occurrence of SCFA-producing bacteria was lower in TA patients than HP patients. CONCLUSION: This study revealed distinct gut microbiome signatures associated with pathways of colorectal polyp development, providing insights concerning the roles of microbial species, functional pathways, and microbial interactions in colorectal carcinogenesis.

Shared genetic correlations between kidney diseases and sepsis.

Background: Clinical studies have indicated a comorbidity between sepsis and kidney diseases. Individuals with specific mutations that predispose them to kidney conditions are also at an elevated risk for developing sepsis, and vice versa. This suggests a potential shared genetic etiology that has not been fully elucidated. Methods: Summary statistics data on exposure and outcomes were obtained from genome-wide association meta-analysis studies. We utilized these data to assess genetic correlations, employing a pleiotropy analysis method under the composite null hypothesis to identify pleiotropic loci. After mapping the loci to their corresponding genes, we conducted pathway analysis using Generalized Gene-Set Analysis of GWAS Data (MAGMA). Additionally, we utilized MAGMA gene-test and eQTL information (whole blood tissue) for further determination of gene involvement. Further investigation involved stratified LD score regression, using diverse immune cell data, to study the enrichment of SNP heritability in kidney-related diseases and sepsis. Furthermore, we employed Mendelian Randomization (MR) analysis to investigate the causality between kidney diseases and sepsis. Results: In our genetic correlation analysis, we identified significant correlations among BUN, creatinine, UACR, serum urate, kidney stones, and sepsis. The PLACO analysis method identified 24 pleiotropic loci, pinpointing a total of 28 nearby genes. MAGMA gene-set enrichment analysis revealed a total of 50 pathways, and tissue-specific analysis indicated significant enrichment of five pairs of pleiotropic results in kidney tissue. MAGMA gene test and eQTL information (whole blood tissue) identified 33 and 76 pleiotropic genes, respectively. Notably, genes PPP2R3A for BUN, VAMP8 for UACR, DOCK7 for creatinine, and HIBADH for kidney stones were identified as shared risk genes by all three methods. In a series of immune cell-type-specific enrichment analyses of pleiotropy, we identified a total of 37 immune cells. However, MR analysis did not reveal any causal relationships among them. Conclusions: This study lays the groundwork for shared etiological factors between kidney and sepsis. The confirmed pleiotropic loci, shared pathogenic genes, and enriched pathways and immune cells have enhanced our understanding of the multifaceted relationships among these diseases. This provides insights for early disease intervention and effective treatment, paving the way for further research in this field.

Testing the Significance of Ranked Gene Sets in Genome-wide Transcriptome Profiling Data Using Weighted Rank Correlation Statistics.

Background: Popular gene set enrichment analysis approaches assumed that genes in the gene set contributed to the statistics equally. However, the genes in the transcription factors (TFs) derived gene sets, or gene sets constructed by TF targets identified by the ChIP-Seq experiment, have a rank attribute, as each of these genes have been assigned with a p-value which indicates the true or false possibilities of the ownerships of the genes belong to the gene sets. Objectives: Ignoring the rank information during the enrichment analysis will lead to improper statistical inference. We address this issue by developing of new method to test the significance of ranked gene sets in genome-wide transcriptome profiling data. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called "Flaver" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.

Research progress on the correlation between intestinal flora and colorectal cancer.

Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies in the world. With the rapid pace of life and changes in diet structure, the incidence and mortality of CRC increase year by year posing a serious threat to human health. As the most complex and largest microecosystem in the human body, intestinal microecology is closely related to CRC. It is an important factor that affects and participates in the occurrence and development of CRC. Advances in next-generation sequencing technology and metagenomics have provided new insights into the ecology of gut microbes. It also helps to link intestinal flora with CRC, and the relationship between intestinal flora and CRC can be continuously understood from different levels. This paper summarizes the relationship between intestinal flora and CRC and its potential role in the diagnosis of CRC providing evidence for early screening and treatment of CRC.

Correlation between abdominal computed tomography signs and postoperative prognosis for patients with colorectal cancer.

BACKGROUND: Patients with different stages of colorectal cancer (CRC) exhibit different abdominal computed tomography (CT) signs. Therefore, the influence of CT signs on CRC prognosis must be determined. AIM: To observe abdominal CT signs in patients with CRC and analyze the correlation between the CT signs and postoperative prognosis. METHODS: The clinical history and CT imaging results of 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University were retrospectively analyzed. Univariate and multivariate Cox regression analyses were used to explore the independent risk factors for postoperative death in patients with CRC. The three-year survival rate was analyzed using the Kaplan-Meier curve, and the correlation between postoperative survival time and abdominal CT signs in patients with CRC was analyzed using Spearman correlation analysis. RESULTS: For patients with CRC, the three-year survival rate was 73.86%. The death group exhibited more severe characteristics than the survival group. A multivariate Cox regression model analysis showed that body mass index (BMI), degree of periintestinal infiltration, tumor size, and lymph node CT value were independent factors influencing postoperative death (P < 0.05 for all). Patients with characteristics typical to the death group had a low three-year survival rate (log-rank χ 2 = 66.487, 11.346, 12.500, and 27.672, respectively, P < 0.05 for all). The survival time of CRC patients was negatively correlated with BMI, degree of periintestinal infiltration, tumor size, lymph node CT value, mean tumor long-axis diameter, and mean tumor short-axis diameter (r = -0.559, 0.679, -0.430, -0.585, -0.425, and -0.385, respectively, P < 0.05 for all). BMI was positively correlated with the degree of periintestinal invasion, lymph node CT value, and mean tumor short-axis diameter (r = 0.303, 0.431, and 0.437, respectively, P < 0.05 for all). CONCLUSION: The degree of periintestinal infiltration, tumor size, and lymph node CT value are crucial for evaluating the prognosis of patients with CRC.

Exploring the Relationship Between Instagram Use and Self-Criticism, Self-Compassion, and Body Dissatisfaction in the Spanish Population: Observational Study.

BACKGROUND: The widespread use of online social networks, particularly among the younger demographic, has catalyzed a growing interest in exploring their influence on users' psychological well-being. Instagram (Meta), a visually oriented platform, has garnered significant attention. Prior research has consistently indicated that Instagram usage correlates with heightened levels of perfectionism, body dissatisfaction, and diminished self-esteem. Perfectionism is closely linked to self-criticism, which entails an intense self-scrutiny and is often associated with various psychopathologies. Conversely, self-compassion has been linked to reduced levels of perfectionism and stress, while fostering greater positive affect and overall life satisfaction. OBJECTIVE: This study investigates the relationship between Instagram usage (time of use and content exposure) and users' levels of self-compassion, self-criticism, and body dissatisfaction. METHODS: This study comprised 1051 adult participants aged between 18 and 50 years, either native to Spain or residing in the country for at least a decade. Each participant completed a tailored questionnaire on Instagram usage, along with abbreviated versions of the Self-Compassion Scale, the Body Shape Questionnaire, and the Depressive Experiences Questionnaire, spanning from January 23 to February 25, 2022. RESULTS: A positive correlation was observed between daily Instagram usage and self-criticism scores. Participants of all age groups who spent over 3 hours per day on Instagram exhibited higher self-criticism scores than users who spent less than 1 hour or between 1 and 3 hours per day. Contrary to previous findings, no significant relationship was detected between Instagram usage time and levels of self-compassion or body dissatisfaction. Furthermore, content centered around physical appearance exhibited a positive correlation with self-criticism and body dissatisfaction scores. Among younger participants (aged 18-35 years), those who primarily viewed beauty or fashion content reported higher self-criticism scores than those consuming science-related content. However, this association was not significant for participants aged 35-50 years. Conversely, individuals who predominantly engaged with sports or fitness or family or friends content exhibited higher levels of body dissatisfaction than those focusing on science-related content. No significant associations were observed between self-compassion scores and daily Instagram usage or most-viewed content categories. CONCLUSIONS: The findings of this study underscore the considerable impact of Instagram usage on self-criticism and body dissatisfaction-2 variables known to influence users' psychological well-being and be associated with various symptoms and psychological disorders.

Characteristics and partitions of traditional and emerging organophosphate esters in soil and groundwater based on machine learning.

Organophosphate esters (OPEs) pose hazards to both humans and the environment. This study applied target screening to analyze the concentrations and detection frequencies of OPEs in the soil and groundwater of representative contaminated sites in the Pearl River Delta. The clusters and correlation characteristics of OPEs in soil and groundwater were calculated by self-organizing map (SOM). The risk assessment and partitions of OPEs in industrial park soil and groundwater were conducted. The results revealed that 14 out of 23 types of OPEs were detected. The total concentrations (Σ23OPEs) ranged from 1.931 to 743.571 ng/L in the groundwater, and 0.218 to 79.578 ng/g in the soil, the former showed highly soluble OPEs with high detection frequencies and concentrations, whereas the latter exhibited the opposite trend. SOM analysis revealed that the distribution of OPEs in the soil differed significantly from that in the groundwater. In the industrial park, OPEs posed acceptable risks in both the soil and groundwater. The soil could be categorized into Zone I and II, and the groundwater into Zone I, II, and III, with corresponding management recommendations. Applying SOM to analyze the characteristics and partitions of OPEs may provide references for other new pollutants and contaminated sites.

Modeling spatial correlation between earthquake insured losses in New Zealand: A mixed-effects analysis.

Earthquake insurance is a critical risk management strategy that contributes to improving recovery and thus greater resilience of individuals. Insurance companies construct premiums without taking into account spatial correlations between insured assets. This leads to potentially underestimating the risk, and therefore the exceedance probability curve. We here propose a mixed-effects model to estimate losses per ward that is able to account for heteroskedasticity and spatial correlation between insured losses. Given the significant impact of earthquakes in New Zealand due to its particular geographical and demographic characteristics, the government has established a public insurance company that collects information about the insured buildings and any claims lodged. We thus develop a two-level variance component model that is based on earthquake losses observed in New Zealand between 2000 and 2021. The proposed model aims at capturing the variability at both the ward and territorial authority levels and includes independent variables, such as seismic hazard indicators, the number of usual residents, and the average dwelling value in the ward. Our model is able to detect spatial correlation in the losses at the ward level thus increasing its predictive power and making it possible to assess the effect of spatially correlated claims that may be considerable on the tail of loss distribution.

Comparative morphology of the cruciate ligaments: A radiological study.

Background: The anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) are important structures to maintain knee stability. The present study aimed to further enrich understandings of the morphology of the cruciate ligaments and explore the relationship between the diameter of ACL and PCL. Method: This study collected valid MRI samples of 50 male and 50 female normal right knee joints and measured the diameter of each point of the ACL and PCL through the 3D Slicer. Results: The diameter of the ACL in the sagittal MRI of the normal right knee joint was significantly different from the diameter of each point of the PCL. The average diameter of each point of the ACL was larger than the diameter of the corresponding point of the PCL. Males and females had statistical differences in their PCL origin point, PCL midpoint, ACL origin point, ACL midpoint, and ACL insertion point diameters under sagittal MRI examination. The average diameter of males was greater than the average diameter of females at the above corresponding sites. In sagittal MRI scans of the normal right knee joint, we observed that only the origin point of the PCL exhibited a moderate correlation with the midpoint and insertion point of the ACL in terms of their respective diameters. Conclusion: The correlation between diameters of normal ACL and PCL in knee joint MRI was moderate and may help clinicians determine appropriate graft for cruciate ligament reconstruction surgery quickly for severe cruciate ligament injuries.

EXPRESS: Simultaneous Measurement of Two-Trace Two-Dimensional (2T2D) Near-Infrared (NIR) Asynchronous Correlation Spectra and Small Angle X-ray Scattering (SAXS) to Characterize Thermally Aged Polypropylene (PP).

In this study, a new system was developed to carry out simultaneous near-infrared (NIR) and small-angle X-ray scattering (SAXS) measurements. Aged PP was examined with the NIR-SAXS system to demonstrate how it can be utilized to derive pertinent information about polymer structure. Pairs of SAXS profiles and NIR spectra of PP in its initial state and after aging were measured to derive an in-depth understanding of the aging phenomenon. The SAXS profiles of the PP samples showed a clear shift of the SAXS peak to the lower q direction induced by the thermal aging, indicating an increase in the length of the long-period structure. Two-trace two-dimensional (2T2D) asynchronous correlation spectra derived from NIR spectra clearly revealed that the aging treatment leads to the substantial increase in the spectral intensity of the regularity bands representing the longer helix present in a folded lamellar structure. In other words, it suggest that the long helix structure is more abundantly present than the short helix structure in the aged PP than in the initial PP. By combining the information derived from the SAXS profiles and NIR spectra, the details of the aging-induced variation were clearly determined. Namely, aging causes additional crystallization of the PP by developing more helix structures, which involves an increase in lamellar thickness as well as a decrease in the amorphous region. The growth of the rigid crystalline phase restricts the elastic deformation in the amorphous structure, which eventually induces the deterioration of PP by making the polymer hard but brittle. Such observation, in turn, implies that the retarding or accelerating the crystallized structure of PP substantially works to control the progress of the aging.

EXPRESS: Can Two-Dimensional Correlation Spectroscopy (2D-COS) Indicate Biocompatible Material?

Carbon nanofibers are a new type of carbon materials. One of the methods of obtaining them is the carbonization of a polymer precursor. They are attractive in many areas, including medicine, due to the possibility of modifying their properties in a wide range. For example, the conditions of the carbonization process result in the creation of materials with designed structures and surface parameters. In the current work, the nanoprecursor was polyacrylonitrile (PAN) fibers. Two types of carbon fibers obtained by carbonization of the PAN precursor at 1000 °C were tested. The first electrospun carbon nanofibers (ESCNFs) were cytotoxic, while the second ESCNF-f were biocompatible after functionalization. The parameters obtained from Raman tests did not clearly discriminate between the tested materials. Multiwavelength Raman studies, analyzed using the two-dimensional correlation spectroscopy (2D-COS), treating the laser energy as an external disturbance, showed a difference between both fibrous structures. 2D-COS indicates that structures resembling graphite systems, devoid of disordered carbon forms, are nontoxic.

Identification of key physicochemical properties and volatile flavor compounds for the sensory formation of roasted tilapia.

Tilapia is suitable for industrial roasting production because of its good flavor and processing adaptability. In this study, the key physicochemical properties and volatile compounds for sensory formation of roasted tilapia were identified after roasting condition optimization. The highest sensory score was obtained at 215 °C, 45 min, and 4% oil. During roasting, the a*, b*, hardness, chewiness, and oxidation of proteins and lipids significantly increased, the moisture content decreased, and the myofibrillar protein aggregation was observed by scanning electron microscope. After identification and quantification by headspace-gas chromatography-ion mobility spectrometry, 10 compounds with odor active value ≥1 were selected as characteristic flavor compounds. The correlation network indicated that the sensory formation mainly resulted from Maillard reaction, myofibrillar protein aggregation, and improvement of pleasant volatile flavor compounds induced by oxidation of proteins and lipids and water loss. This study provides an important theoretical basis and technical support for roasted tilapia production.

Beyond Pearson's Correlation: Modern Nonparametric Independence Tests for Psychological Research.

When examining whether two continuous variables are associated, tests based on Pearson's, Kendall's, and Spearman's correlation coefficients are typically used. This paper explores modern nonparametric independence tests as an alternative, which, unlike traditional tests, have the ability to potentially detect any type of relationship. In addition to existing modern nonparametric independence tests, we developed and considered two novel variants of existing tests, most notably the Heller-Heller-Gorfine-Pearson (HHG-Pearson) test. We conducted a simulation study to compare traditional independence tests, such as Pearson's correlation, and the modern nonparametric independence tests in situations commonly encountered in psychological research. As expected, no test had the highest power across all relationships. However, the distance correlation and the HHG-Pearson tests were found to have substantially greater power than all traditional tests for many relationships and only slightly less power in the worst case. A similar pattern was found in favor of the HHG-Pearson test compared to the distance correlation test. However, given that distance correlation performed better for linear relationships and is more widely accepted, we suggest considering its use in place or additional to traditional methods when there is no prior knowledge of the relationship type, as is often the case in psychological research.

Quantification of natural uranium and its risk evaluation in groundwater of Chikkaballapur district in Karnataka, India.

The present study focused on the distribution of uranium in groundwater samples collected from various sources in the Chikkaballapur district and its associated risk in humans. Seventy-five groundwater samples were collected during pre-monsoon and post-monsoon seasons and were analysed for uranium concentration along with different water quality parameters. The uranium concentration ranged from 0.23 to 285.23 µg/L in the pre-monsoon season and from 0.02 to 107.87 µg/L in the post-monsoon season. More than 90% of samples, except a few, were under the safe limits of 60 µg/L as directed by the Department of Atomic Energy (DAE) of India's Atomic Energy Regulatory Board (AERB). The study analysed physicochemical parameters like pH, total dissolved solids (TDS), nitrate, total hardness, phosphate, sulphate and fluoride in collected water samples. Out of all samples, few samples noted higher values of TDS, nitrate and fluoride. Their correlation along with uranium is detailed in the study. Owing to its slightly elevated content, an evaluation of the radiological and chemical hazards associated with uranium consumption was analysed. When the risk resulting from chemical toxicity was evaluated, relatively few samples had a hazard quotient (HQ) score higher than 1, which suggested that the people were vulnerable to chemical danger. This study also evaluates the dangers of elevated uranium levels in groundwater samples to the general public's health. It also acknowledges the importance of routinely evaluating and treating the drinking water sources in the region.

Analysis of the Adsorption Behavior of Phenanthrene on Microplastics Based on Two-Dimensional Correlation Spectroscopy.

Microplastics (MPs), an emerging pollutant, widely co-occur with polycyclic aromatic hydrocarbons (PAHs) in the environment. Therefore, the interaction between MPs and PAHs has been the focus of much attention in recent years. In this study, three types of MPs, i.e., polypropylene, polystyrene, and poly(vinyl chloride), with the same main chain were selected as the adsorbents, with phenanthrene (PHE) as the representative PAHs. The adsorption mechanisms were explored from the perspective of the molecular spectral level using a combination of Fourier transform infrared spectroscopy (FT-IR) with a two-dimensional correlation technique. The adsorption kinetics results showed that the adsorption of PHE on the three MPs was dominated by chemisorption. However, the FT-IR analysis results indicated that no new covalent bond was created during the adsorption process. Based on the above research, a generalized two-dimensional (2D) correlation spectral technique was employed to investigate the sequence of functional group changes during the adsorption process for different MPs. Furthermore, the hybrid 2D correlation spectral technique explored the effect of side groups attached to the main chain molecules of MPs on adsorption. The results showed that for all three MPs, the functional groups in the side chain have a higher affinity for PHE, which is due to their higher hydrophobicity. This study provides a feasible way to analyze the adsorption of pollutants on MPs, and the results are important for understanding the adsorption interaction between PAHs and MPs in the aquatic environment.

The evaluation value of atherogenic index of plasma and high-sensitivity C-reactive protein for the degree of coronary artery lesion in premature coronary artery disease.

BACKGROUND: Premature coronary artery disease (PCAD) is prevailing. We aimed to investigate the evaluation value of atherogenic index of plasma (AIP) and high-sensitivity C-reactive protein (hs-CRP) for the occurrence and severity of coronary artery lesion in PCAD patients. METHODS: PCAD (PACD group)/non-PCAD (control group) patients were enrolled. The coronary artery lesion degree was evaluated using Gensini score (GS). PCAD patients were allocated into the low/medium/high GS groups, with general clinical baseline data analyzed. Plasma hs-CRP/AIP levels were compared in PCAD patients with different disease degree. Correlations between plasma hs-CRP/AIP with Gensini score, independent risk factors affecting the occurrence of PCAD, and the predictive value of hs-CRP/AIP/their combination for the occurrence and degree of PCAD were evaluated by Spearman correlation analysis/Logistic multivariate regression/receiver operating characteristic (ROC) curve. The differences in the area under the curve (AUC) were compared using MedCalc-Comparison of ROC curves. RESULTS: Plasma hs-CRP/AIP levels in the PCAD group were increased. Plasma hs-CRP/AIP levels varied significantly among PCAD patients with different disease degree. Plasma hs-CRP/AIP levels were markedly positively correlated with the Gensini score. Smoking history/homocysteine/fasting blood-glucose/hs-CRP/AIP were all independent risk factors affecting PCAD occurrence. The AUC of hs-CRP and AIP combination predicting the occurrence of PCAD was 0.950 (90.80% sensitivity/93.33% specificity). hs-CRP/AIP combination assisted in predicting the disease degree in PCAD patients. CONCLUSIONS: AIP and hs-CRP are independent risk factors for the occurrence of PCAD, and their combination has high predictive value for PCAD occurrence and disease degree, which are both positively correlated with coronary artery lesion degree.

Influence of prosthetic index structures and implant materials on stress distribution in implant restorations: a three-dimensional finite element analysis.

BACKGROUND: Mechanical complications affect the stability of implant restorations and are a key concern for clinicians, especially with the frequent introduction of new implant designs featuring various structures and materials. This study evaluated the effect of different prosthetic index structure types and implant materials on the stress distribution of implant restorations using both in silico and in vitro methods. METHODS: Four finite element analysis (FEA) models of implant restorations were created, incorporating two prosthetic index structures (cross-fit (CF) and torc-fit (TF)) and two implant materials (titanium and titanium-zirconium). A static load was applied to each group. An in vitro study using digital image correlation (DIC) with a research scenario identical to that of the FEA was conducted for validation. The primary strain, sensitivity index, and equivalent von Mises stress were used to evaluate the outcomes. RESULTS: Changing the implant material from titanium to titanium-zirconium did not significantly affect the stress distribution or maximum stress value of other components, except for the implant itself. In the CF group, implants with a lower elastic modulus increased the stress on the screw. The TF group showed better stress distribution on the abutment and a lower stress value on the screw. The TF group demonstrated similar sensitivity for all components. DIC analysis revealed significant differences between TF-TiZr and CF-Ti in terms of the maximum (P < 0.001) and minimum principal strains (P < 0.05) on the implants and the minimum principal strains on the investment materials in both groups (P < 0.001). CONCLUSIONS: Changes in the implant material significantly affected the maximum stress of the implant. The TF group exhibited better structural integrity and reliability.

A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data.

BACKGROUND: Social network analysis of animal societies allows scientists to test hypotheses about social evolution, behaviour, and dynamic processes. However, the accuracy of estimated metrics depends on data characteristics like sample proportion, sample size, and frequency. A protocol is needed to assess for bias and robustness of social network metrics estimated for the animal populations especially when a limited number of individuals are monitored. METHODS: We used GPS telemetry datasets of five ungulate species to combine known social network approaches with novel ones into a comprehensive five-step protocol. To quantify the bias and uncertainty in the network metrics obtained from a partial population, we presented novel statistical methods which are particularly suited for autocorrelated data, such as telemetry relocations. The protocol was validated using a sixth species, the fallow deer, with a known population size where ∼ 85 % of the individuals have been directly monitored. RESULTS: Through the protocol, we demonstrated how pre-network data permutations allow researchers to assess non-random aspects of interactions within a population. The protocol assesses bias in global network metrics, obtains confidence intervals, and quantifies uncertainty of global and node-level network metrics based on the number of nodes in the network. We found that global network metrics like density remained robust even with a lowered sample size, while local network metrics like eigenvector centrality were unreliable for four of the species. The fallow deer network showed low uncertainty and bias even at lower sampling proportions, indicating the importance of a thoroughly sampled population while demonstrating the accuracy of our evaluation methods for smaller samples. CONCLUSIONS: The protocol allows researchers to analyse GPS-based radio-telemetry or other data to determine the reliability of social network metrics. The estimates enable the statistical comparison of networks under different conditions, such as analysing daily and seasonal changes in the density of a network. The methods can also guide methodological decisions in animal social network research, such as sampling design and allow more accurate ecological inferences from the available data. The R package aniSNA enables researchers to implement this workflow on their dataset, generating reliable inferences and guiding methodological decisions.

A Concept of Local Coordination Number for the Characterization of Solute Clusters within Atom Probe Tomography Data.

Identifying clusters of solute atoms in a matrix of solvent atoms helps to understand precipitation phenomena in alloys, for example, during the age hardening of certain aluminum alloys. Atom probe tomography datasets can deliver such information, provided that appropriate cluster identification routines are available. We investigate algorithms based on the local composition of the neighborhood of solute atoms and compare them with traditional approaches based on the local solute number density, such as the maximum separation distance method. For an ideal solid solution, the pair correlation functions of the kth nearest solute atom in the coordination number representation are derived, and the percolation threshold and the size distribution of clusters are studied. A criterion for selecting optimal control parameters based on maximizing the phase separation by the degree of clustering is proposed for a two-phase system. A map of phase compositions accessible for cluster analysis is constructed. The coordination number approach reduces the influence of density variations commonly observed in atom probe tomography data. Finally, a practical cluster analysis technique applied to the early stages of aluminum alloy aging is described.

Effects of industrial-scale pickling processes on the dynamic changes in the physicochemical indicators and microbial diversities of Yacai.

The effects of dry-salted and salt-fermented processing on the physicochemical characteristics and microbial communities of Yacai were systematically investigated. The results showed that the contents of total acid, amino acid nitrogen (AAN) and nitrite in the final products of dry-salted Yacai were greater than those in salt-fermented Yacai. Lactic acid was the dominant organic acid in the two types of Yacai. Dry-salted processing is more conducive to forming a high-quality reddish-brown color. During whole pickling process, the microbial diversity of dry-salted Yacai was higher than that of salt-fermented Yacai, particularly in the early and middle stages of fermentation. For dry-salted Yacai, 8 bacteria (Natribacillus, Chromohalobacter, Marinococcus, Lentibacillus, Nesterenkonia, Gracilibacillus, Oceanobacillus and Tetragenococcus) and 1 fungus (Zygosaccharomyces) showed a significant positive correlation with AAN. For salt-fermented Yacai, 8 bacteria (Gracilibacillus, Alkalibacillus, Oceanobacillus, Virgibacillus, Lentibacillus, Salibacterium, Chromohalobacter and Tetragenococcus) and 3 fungi (Zygosaccharomyces, Millerozyma, and Wickerhamomyces) exhibited significant positive correlations with AAN.