The knee connectome: A novel tool for studying spatiotemporal change in cartilage thickness

Cartilage thickness change is a well-documented biomarker of osteoarthritis pathogenesis. However, there is still much to learn about the spatial and temporal patterns of cartilage thickness change in health and disease. In this study, we develop a novel analysis method for elucidating such patterns using a functional connectivity approach. Descriptive statistics are reported for 1186 knees that did not develop osteoarthritis during the 8 years of observation, which we present as a model of cartilage thickness change related to healthy aging. Within the control population, patterns vary greatly between male and female subjects, while body mass index (BMI) has a more moderate impact. Finally, several differences are shown between knees that did and did not develop osteoarthritis. Some but not all significance appears to be accounted for by differences in sex, BMI, and knee alignment. With this work, we present the connectome as a novel tool for studying spatiotemporal dynamics of tissue change.

Recent advances in taste transduction mechanism, analysis methods and strategies employed to improve the taste of taste peptides

Taste peptides are oligopeptides that enhance both aroma and taste of food, and they are classified into five categories based on their taste characteristics: salty, sour, umami, sweet, bitter, and kokumi peptide. Recently, taste peptides have attracted the attention of several fields of research in food science and commercial applications. However, research on taste receptors of taste peptides and their taste transduction mechanisms are not clearly understood and we present a comprehensive review about these topics here. This review covers the aspects of taste peptides perceived by their receptors in taste cells, the proposed transduction pathway, as well as structural features of taste peptides. Apart from traditional methods, molecular docking, peptidomic analysis, cell and animal models and taste bud biosensors can be used to explore the taste mechanism of taste peptides. Furthermore, synergistic effect, Maillard reaction, structural modifications and changing external environment are employed to improve the taste of taste peptides. Consequently, we discussed the current challenges and future trends in taste peptide research. Based on the summarized developments, taste peptides derived from food proteins potentially appear to be important taste substances. Their applications meet the principles of "safe, nutritious and sustainable" in food development.

[Current approaches for sampling to study the traces of gunshot residue]

An overview of researches, mainly by foreign specialists, on current available approaches for sampling to study the traces of gunshot residue (GSR) is presented. The comparative characteristics of traditional methods of samples (use of cotton and gauze tampons, blotting paper, textile fabrics, adhesive tapes, adhesives and vacuum samplers), as well as advanced technologies, including special devices and sorbents, are given. The characteristics of samplings from hands, scalp, nostrils, clothes of examined persons as well as procedures, that allow to increase the duration of GSR detection, are described in details. The importance of GSR sustainability over time is noted. On average, the most likely detection periods of particles are less than 1 hour for samples, collected from hands, more than 1 hour for samples from clothes and 2-3 hours for face. It is possible to detect the GSR particles in hair up to 24 h., and in nasal mucus after 6 h. of shot. The methods of identification and determination for analytes of inorganic and organic nature are discussed. The most common methods for determining heavy metal particles are atomic spectrometry, namely atomic absorption with electrothermal atomization and atomic emission. The combination of scanning laser ablation and mass-spectrometry with inductively coupled plasma makes it possible to detect more than 15 analytes in a single sample. Scanning electron microscopy with X-ray detectors is effective for the examination of powder particles. The described methods of sampling complement each other increasing the possibility of evidence base for court proceedings.

Current development and future challenges in microplastic detection techniques: A bibliometrics-based analysis and review

Microplastics have been considered a new type of pollutant in the marine environment and have attracted widespread attention worldwide in recent years. Plastic particles with particle size less than 5 mm are usually defined as microplastics. Because of their similar size to plankton, marine organisms easily ingest microplastics and can threaten higher organisms and even human health through the food chain. Most of the current studies have focused on the investigation of the abundance of microplastics in the environment. However, due to the limitations of analytical methods and instruments, the number of microplastics in the environment can easily lead to overestimation or underestimation. Microplastics in each environment have different detection techniques. To investigate the current status, hot spots, and research trends of microplastics detection techniques, this review analyzed the papers related to microplastics detection using bibliometric software CiteSpace and COOC. A total of 696 articles were analyzed, spanning 2012 to 2021. The contributions and cooperation of different countries and institutions in this field have been analyzed in detail. This topic has formed two main important networks of cooperation. International cooperation has been a common pattern in this topic. The various analytical methods of this topic were discussed through keyword and clustering analysis. Among them, fluorescent, FTIR and micro-Raman spectroscopy are commonly used optical techniques for the detection of microplastics. The identification of microplastics can also be achieved by the combination of other techniques such as mass spectrometry/thermal cracking gas chromatography. However, these techniques still have limitations and cannot be applied to all environmental samples. We provide a detailed analysis of the detection of microplastics in different environmental samples and list the challenges that need to be addressed in the future.

Managing the Training Process in Elite Sports: From Descriptive to Prescriptive Data Analytics

Elite sport practitioners increasingly use data to support training process decisions related to athletes' health and performance. A careful application of data analytics is essential to gain valuable insights and recommendations that can guide decision making. In business organizations, data analytics are developed based on conceptual data analytics frameworks. The translation of such a framework to elite sport may benefit the use of data to support training process decisions. Purpose: The authors aim to present and discuss a conceptual data analytics framework, based on a taxonomy used in business analytics literature to help develop data analytics within elite sport organizations. Conclusions: The presented framework consists of 4 analytical steps structured by value and difficulty/complexity. While descriptive (step 1) and diagnostic analytics (step 2) focus on understanding the past training process, predictive (step 3) and prescriptive analytics (step 4) provide more guidance in planning the future. Although descriptive, diagnostic, and predictive analytics generate insights to inform decisions, prescriptive analytics can be used to drive decisions. However, the application of this type of advanced analytics is still challenging in elite sport. Thus, the current use of data in elite sport is more focused on informing decisions rather than driving them. The presented conceptual framework may help practitioners develop their analytical reasoning by providing new insights and guidance and may stimulate future collaborations between practitioners, researchers, and analytics experts.

Current Diagnostic Methods for Assessing Transfer of Passive Immunity in Calves and Possible Improvements: A Literature Review

Simple Summary

The transfer of passive immunity (TPI) from cows to calves needs to be routinely assessed on farms and in field research. The gold standard method for assessing TPI is radial immunodiffusion (RID) because it directly assesses the immunoglobulin G (IgG) concentration in calf serum samples. In addition to RID, there are several other methods available for the assessment of TPI which determine the concentration of IgG or other serum components. It is known that several components present in the colostrum are absorbed by the calves and aid passive immunity. We conducted a literature review of the methods scientifically reported by experts in the field.

Abstract

Several direct or indirect methods can be used to assess immunoglobulin G (IgG) concentrations in calves, which evaluates the transfer of passive immunity (TPI). Radial immunodiffusion (RID) is the gold standard method to measure serum IgG in bovines. Previous studies have shown that colostrum provides several molecules in addition to immunoglobulins, which play an important role in the passive immunity of the calf. However, no studies have yet determined the level of interference of these components in the immunity, health and survival of calves. In this sense, the objective of this study is to review the methods of evaluation available for the laboratory and field diagnosis of TPI in calves and discuss the main aspects of each technique. Several methods available for TPI evaluation in calves may provide insights into the various components of colostrum involved in passive immunity.

Microplastics and Nanoplastics: Emerging Contaminants in Food

As current concerns about food safety issues around the world are still relatively serious, more and more food safety issues have become the focus of people's attention. What's more serious is that environmental pollution and changes in human lifestyles have also led to the emergence of contaminants in food, microplastics (MPs) and nanoplastics (NPs) being typical representatives. MPs and NPs (M/NPs) in food are gradually becoming recognized by regulatory authorities and the public. Most published reviews on M/NPs have been focused on the environmental ecosystems. In those papers, it is only sporadically mentioned that M/NPs can also appear in food. As far as we know, there has not been a systematic review of the pollution and existing status of M/NPs in food. This Review focuses on the harmfulness of M/NPs, the ways in which M/NPs contaminate food, the residual amount of M/NPs in food, and the current analysis and detection methods for M/NPs in food. Current analysis and detection methods have problems such as being time-consuming, involving cumbersome operation, and giving poor accuracy. In the future, it will be necessary to increase the research on methods for efficient and sensitive separation and detection of M/NPs in food. Finally, it is hoped that this Review will arouse more people's awareness of and attention to the seriousness of M/NPs in food.

Airway-On-A-Chip: Designs and Applications for Lung Repair and Disease

The lungs are affected by illnesses including asthma, chronic obstructive pulmonary disease, and infections such as influenza and SARS-CoV-2. Physiologically relevant models for respiratory conditions will be essential for new drug development. The composition and structure of the lung extracellular matrix (ECM) plays a major role in the function of the lung tissue and cells. Lung-on-chip models have been developed to address some of the limitations of current two-dimensional in vitro models. In this review, we describe various ECM substitutes utilized for modeling the respiratory system. We explore the application of lung-on-chip models to the study of cigarette smoke and electronic cigarette vapor. We discuss the challenges and opportunities related to model characterization with an emphasis on in situ characterization methods, both established and emerging. We discuss how further advancements in the field, through the incorporation of interstitial cells and ECM, have the potential to provide an effective tool for interrogating lung biology and disease, especially the mechanisms that involve the interstitial elements.

Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm

Significance: Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies may complicate the interpretation of data. Aim: We aim to assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, we determine whether averaging or generalized linear model (GLM)-based analysis generates different experimental conclusions when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach: 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design, comprising sounds of 5 s duration and 10 to 20 s silent intervals, was employed. Results: Both analysis procedures generated similar response morphologies and amplitude estimates, and both indicated that responses to speech were significantly greater than to noise or silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions: Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.

Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

Functional assessment of glaucoma: Uncovering progression

Clinicians who manage glaucoma patients carefully monitor the visual field to determine if treatments are effective or interventions are needed. Visual field tests may reflect disease progression or variability among examinations. We describe the approaches and perimetric tests used to evaluate glaucomatous visual field progression and factors that are important for identifying progression. These include stimulus size, which area of the visual field to assess (central versus peripheral), and the testing frequency, evaluating which is important to detect change early while minimizing patient testing burden. We also review the different statistical methods developed to identify change. These include trend- and event-based analyses, parametric and nonparametric tests, population-based versus individualized approaches, as well as pointwise and global analyses. We hope this information will prove useful and important to enhance the management of glaucoma patients. Overall, analysis procedures based on series of at least 5 to 6 examinations that require confirmation and persistence of changes, that are guided by the pattern and shape of the glaucomatous visual field deficits, and that are consistent with structural defects provide the best clinical performance.

Antibiotics Associated Disorders and Post-biotics Induced Rescue in Gut Health

The gut microbiota plays significant roles in the human body during all spheres' of life and influences innate immunity, promotes granulocyte signaling and provides resistance during pathogenic colonization of the gut; crucial for a healthy life. Antibiotics directly affect the gut microbiota that consequently alters the basic biological processes and imposes severe consequences in population falling under different age groups. In this article, we assessed the differences in microbial colonization and immune function of the intestinal tract in infants, adults, and the aged people and also examined the recent reports describing the impacts of antibiotics on infant microbiome assembly and functioning. The age old techniques have been compared to modern ones in relation to the functioning of the gut microbiome to draw inferences on significant impacts of various microbiota on human life starting from the womb, through infancy, adulthood and old age. It was observed that data is limited to different classes or origin of populace depicting variations in food habits and/or suffering from heavy metal associated diseases after continuous exposure to heavy metals/ metalloids/ biocides. Such extreme environmental factors significantly modulate the microbiota and assist in creating a 'co-resistant' gene pool that influences gut health. In the light of this finding, it is important to analyze the 'co-resistant' gene pool existing in gut-microbiome which supports to recoup and establish a healthy life. The hypothesis of 'postbiotics' is under process and their associations with antibiotic turn to be new-insight in antibiotic therapy. On one hand, postbiotics provide a great opportunity to understand the mechanism of action against pathobionts; on the other; they lead to postulation of newer pharmabiotic products and pharmacological strategies for better gut health.

Public Health Risks Associated with Tetrodotoxin and Its Analogues in European Waters: Recent Advances after The EFSA Scientific Opinion

Tetrodotoxin (TTX) and its analogues are naturally occurring toxins responsible worldwide for human intoxication cases and fatalities, mainly associated with pufferfish consumption. In the last decade, TTXs were detected in marine bivalves and gastropods from European waters. As TTXs are not regulated or monitored at EU level, their unexpected occurrence in shellfish raised concerns as a food safety hazard and revealed the necessity of a thorough assessment on the public health risks associated with their presence. For this reason, the European Food Safety Authority (EFSA) was requested by the European Commission to provide a scientific opinion, finally adopted in March 2017, according to which a provisional concentration below 44 μg TTX equivalents/kg shellfish meat, based on a large portion size of 400 g, was considered not to result in adverse effects in humans. The EFSA expert panel, however, recognized a number of shortcomings and uncertainties related to the unavailability of sufficient scientific data and provided relevant recommendations for future research to overcome these data gaps identified in order to further refine the risk assessment on TTXs. The present review aims to summarize the knowledge obtained towards addressing these recommendations in the two years following publication of the EFSA opinion, at the same time highlighting the points requiring further investigation.

Measuring Mental Workload With Low-Cost and Wearable Sensors: Insights Into the Accuracy, Obtrusiveness, and Research Usability of Three Instruments

The affordability of wearable psychophysiological sensors has led to opportunities to measure the mental workload of operators in complex sociotechnical systems in ways that are more objective and less obtrusive. This study primarily focuses on the sensors themselves by investigating low-cost and wearable sensors in terms of their accuracy, obtrusiveness, and usability for research purposes. Two sensors were assessed on their accuracy as tools to measure mental workload through heart rate variability (HRV): the E3 from Empatica and the emWave Pro from HeartMath. The BioPatch from Zephyr Technology, which is an U.S. Food and Drug Administration-approved device, was used as a gold standard to compare the data obtained from the other 2 devices regarding their accuracy on HRV. Linear dependencies for 6 of 10 HRV parameters were found between the emWave and BioPatch data and for 1 of 10 for the E3 sensor. In terms of research usability, both the E3 and the BioPatch had difficulty acquiring either sufficiently high data recording confidence values or normal distributions. However, the BioPatch output files do not require postprocessing, which reduces costs and effort in the analysis stage. None of the sensors was perceived as obtrusive by the participants.

Approaches to Analysis in Model-based Cognitive Neuroscience

Our understanding of cognition has been advanced by two traditionally nonoverlapping and non-interacting groups. Mathematical psychologists rely on behavioral data to evaluate formal models of cognition, whereas cognitive neuroscientists rely on statistical models to understand patterns of neural activity, often without any attempt to make a connection to the mechanism supporting the computation. Both approaches suffer from critical limitations as a direct result of their focus on data at one level of analysis (cf. Marr, 1982), and these limitations have inspired researchers to attempt to combine both neural and behavioral measures in a cross-level integrative fashion. The importance of solving this problem has spawned several entirely new theoretical and statistical frameworks developed by both mathematical psychologists and cognitive neuroscientists. However, with each new approach comes a particular set of limitations and benefits. In this article, we survey and characterize several approaches for linking brain and behavioral data. We organize these approaches on the basis of particular cognitive modeling goals: (1) using the neural data to constrain a behavioral model, (2) using the behavioral model to predict neural data, and (3) fitting both neural and behavioral data simultaneously. Within each goal, we highlight a few particularly successful approaches for accomplishing that goal, and discuss some applications. Finally, we provide a conceptual guide to choosing among various analytic approaches in performing model-based cognitive neuroscience.

Mechanisms controlling human head stabilization during random rotational perturbations in the horizontal plane revisited

This study repeats the experimental protocol for investigation of head stabilization in healthy humans, described by Keshner and Peterson (1995) but with a modification of the analysis. Head movements were considered with respect to the room instead of relative to the trunk. The aim was to investigate the approximate contribution of reflex and voluntary control across perturbing frequencies and conditions with modulation of visual information and mental attention and discuss the resulting outcome while comparing methods. Seventeen healthy individuals were asked to keep the head steady in space while subjected to pseudorandom rotational perturbations in the horizontal plane, firmly seated on an actuated chair. Both methods confirmed the results for gain in previous studies showing fair ability to keep the head steady in space below 1 Hz with vision. Compensation deteriorated when vision was removed and worsened further with addition of a mental task. Between 1 and 2 Hz, unity gain occurred between head and trunk movements, whereas above 2 Hz the head moved more than the trunk. For phase angles, the original method demonstrated a phase split occurring from ~1 Hz, a purely mathematical artifact that caused subjects with virtually identical movements to appear as significantly different. This artifact was eliminated by analyzing the head‐room relative to trunk‐room rather than head–trunk relative to trunk‐room angles, thus preventing potentially erroneous interpretations of the results.

Non-word repetition in 2-year-olds: Replication of an adapted paradigm and a useful methodological extension

Accurate non-word repetition (NWR) has been largely attributed to phonological memory, although the task involves other processes including speech production, which may confound results in toddlers with developing speech production abilities. This study is based on Hoff, Core and Bridges' adapted NWR task, which includes a real-word repetition (RWR) condition. We tested 86 typically developing 2-year-olds and found relationships between NWR and both receptive and expressive vocabulary using a novel measure that controls for speech production by comparing contextually matched targets in RWR. Post hoc analyses demonstrated the influence of lexical and sublexical factors in repetition tasks. Overall, results illustrate the importance of controlling for speech production differences in young children and support a useful methodological approach for testing NWR.

A methodological framework for the analysis of highly intensive, multimodal and heterogeneous data in the context of health-enabling technologies and ambient-assisted living

BACKGROUND

When applying health-enabling technologies (HET), researchers are faced with analyzing highly intensive, multimodal and heterogeneous data sets. Experience has shown that there is a lack of understanding concerning the relationship of analysis methods suitable for such data sets and their appropriate application.

OBJECTIVES

The objective of this paper is to describe the present situation when analyzing data of HET and the main problems in this context, to present a nomenclature suitable for analysis methods in the context of HET, to present an example dealing with geriatric diseases that highlights the problems and the urgent need for results and to explain some steps for future work.

METHODS

Nomenclatures as standard tools in information processing are applied.

RESULTS

We present an open three-axial mono-hierarchical nomenclature called SNOCAP-HET. Moreover, we explain other ideas to overcome the lack of systematization within the set of analysis methods suitable for HET.

CONCLUSIONS

Our approach allows for an extension of SNOCAP-HET and will allow for the development and evaluation of different measures for the appropriateness of analysis methods given a certain highly intensive, multimodal and heterogeneous data set in the context of HET. Our final future aim is to obtain better results when analyzing medical data.

Classic "broken cell" techniques and newer live cell methods for cell cycle assessment

Many common, important diseases are either caused or exacerbated by hyperactivation (e.g., cancer) or inactivation (e.g., heart failure) of the cell division cycle. A better understanding of the cell cycle is critical for interpreting numerous types of physiological changes in cells. Moreover, new insights into how to control it will facilitate new therapeutics for a variety of diseases and new avenues in regenerative medicine. The progression of cells through the four main phases of their division cycle [G(0)/G(1), S (DNA synthesis), G(2), and M (mitosis)] is a highly conserved process orchestrated by several pathways (e.g., transcription, phosphorylation, nuclear import/export, and protein ubiquitination) that coordinate a core cell cycle pathway. This core pathway can also receive inputs that are cell type and cell niche dependent. "Broken cell" methods (e.g., use of labeled nucleotide analogs) to assess for cell cycle activity have revealed important insights regarding the cell cycle but lack the ability to assess living cells in real time (longitudinal studies) and with single-cell resolution. Moreover, such methods often require cell synchronization, which can perturb the pathway under study. Live cell cycle sensors can be used at single-cell resolution in living cells, intact tissue, and whole animals. Use of these more recently available sensors has the potential to reveal physiologically relevant insights regarding the normal and perturbed cell division cycle.