Common pitfalls in statistical analysis: The use of correlation techniques

Correlation between the structures of natural polysaccharides and their properties in regulating gut microbiota: Current understanding and beyond

Natural polysaccharides have complex structural properties and a wide range of health-promoting effects. Accumulating evidence suggests that the effects are significantly mediated through fermentation by gut microbiota. In recent years, the relationship between the structures of natural polysaccharides and their properties in regulating gut microbiota has garnered significant research attention as researchers attempt to precisely understand the role of gut microbiota in the bioactivities of natural polysaccharides. Progress in this niche, however, remains limited. In this review, we first provide an overview of current research investigating this structure-property relationship. We then present a detailed correlation analysis between the structural characteristics of 159 purified natural polysaccharides and their effects on gut microbiota reported over the past two decades. The analysis revealed that diverse gut bacteria show specific correlations with the molecular weight, glycosidic linkages, and monosaccharide composition of natural polysaccharides. Multifaceted molecular mechanisms, including carbohydrate binding, enzymatic degradation, and cross-feeding, were proposed to be collectively involved in these correlations. Finally, we offer our perspective on future studies to further improve our understanding of the relationship between polysaccharide structure and gut microbiota regulation.

Correlation and causation for cardiothoracic surgeons: part 4-distinguishing relationships in data

Correlation indicates a relationship between variables without causation, while causation implies one variable directly influences the other in clinical research. Through various statistical approaches, including Pearson and Spearman correlation coefficients, we can explore the strength of linear and non-linear relationships. Phi coefficient and the point-biserial correlation are other alternative techniques. Scatter plots are used to illustrate correlations in real-world data, guiding surgeons in understanding how variables like experience impact complication rates. Emphasis is placed on recognizing confounding variables, applying appropriate statistical methods, and interpreting results accurately to inform clinical decisions. This paper highlights the importance of evidence-based, data-driven practices in enhancing surgical outcomes.

The hypotension prediction index versus mean arterial pressure in predicting intraoperative hypotension: A clinical perspective

BACKGROUND

The hypotension prediction index (HPI) predicts hypotension, with randomised trials showing a significant reduction in hypotension-related metrics. However, the reliability of previous validation studies is debated, and it's unclear if mean arterial pressure (MAP) can be used interchangeably with HPI.

OBJECTIVES

This study compared the effectiveness of HPI versus MAP thresholds in predicting intraoperative hypotension, focusing on three clinically relevant metrics: time from alert to event, positive predictive value (PPV), and proportion of missed hypotensive events.

DESIGN

Prospective observational study conducted between 2018 and 2020.

SETTING

Single-centre, academic hospital in the Netherlands.

PARTICIPANTS

Adults scheduled for elective non-cardiac surgery lasting over two hours. Of the 105 eligible patients, 91 had sufficient data for analysis.

MAIN OUTCOME MEASURES

The primary outcome was the time-to-hypotensive event intervals predicted by HPI popup alerts (≥85 for ≥40 s) and MAP-alerts (70-75 mmHg). Secondary analyses examined differences between these predictors regarding the PPV and missed event rates, as well as the difference in these metrics between instant HPI-85 alerts and the six MAP-alerts.

RESULTS

The largest time-to-event difference was seen between HPI-85 popup and MAP-70 alerts, with a gain of 0.58 (95% confidence interval (CI), 0.57 to 0.58) min, favouring HPI. Higher MAP thresholds reduced this time difference, but worsened PPV values, with 20.5 (95% CI, 20.3 to 20.6)% at MAP-75 compared to 55.6 (95% CI, 55.4 to 55.8)% for HPI-85 popups. Missed event proportions were similar: between one to three percent. Instant HPI-85 and MAP-72 alerts showed comparable performance, but both had suboptimal PPV values around 30%. However, adding a 40-s time-dependence to MAP's alert definition levelled the differences across the three evaluated metrics, aligning more closely with HPI-85 popup alerts.

CONCLUSIONS

Using HPI-85 popup alerts does not provide additional prediction time over MAP-alerts in the 70 to 75 mmHg range, but they may be preferred due to higher PPV values. Instant HPI-85 and MAP-alerts perform similarly, with MAP-72 being closest, though these alerts more frequently occur regardless of subsequent hypotension with the potential to introduce unnecessary treatment. Adding a 40-s time-dependence to MAP-alerts to match the HPI popup characteristic eliminates distinctions between prediction time and missed events, while maintaining the higher PPV. However, whether 40sec-MAP-alerts are clinically equivalent remains to be determined in prospective clinical trials.

TRIAL REGISTRATION

Clinicaltrials.gov (NCT03795831) on 10 January 2019. https://clinicaltrials.gov/study/NCT03795831.

Association between hedonic hunger and food addiction: A systematic review and meta-analysis

AIMS

In recent years, food addiction has gained significant interest from the scientific community. Hedonic hunger has been identified as a crucial risk factor contributing to food addiction. Therefore, this systematic review and meta-analysis aim to consolidate the current evidence regarding the relationship between hedonic hunger and food addiction among healthy individuals.

DATA SYNTHESIS

A comprehensive search was conducted across three databases - PubMed, Web of Science, and Scopus - up to October 2024. The review included all original observational studies published in English that utilized the Power of Food Scale (PFS) to measure hedonic hunger and the Yale Food Addiction Scale (YFAS) along with its derivatives to evaluate food addiction in healthy participants. The quality of the studies was assessed using the Joanna Briggs Institute checklist. The meta-analysis was performed using StataMP-17 software. Following the screening process, seven cross-sectional studies comprising a total of 2518 participants were included. The findings from the meta-analysis revealed a positive and statistically significant correlation between the score of PFS and the score of YFAS (r = 0.53, 95 % CI: 0.35, 0.71). Furthermore, the meta-regression analysis indicated that the percentage of female participants and sample size did not significantly affect the relationship between hedonic hunger and food addiction.

CONCLUSIONS

Given the established positive association, it may be advantageous to consider the impact of hedonic hunger in strategies aimed at managing food addiction.

Auto QSAR-based active learning docking for hit identification of potential inhibitors of Plasmodium falciparum Hsp90 as antimalarial agents

Malaria which is mainly caused by Plasmodium falciparum parasite remains a devastating public health concern, necessitating the need to develop new antimalarial agents. P. falciparum heat shock protein 90 (Hsp90), is indispensable for parasite survival and a promising drug target. Inhibitors targeting the ATP-binding pocket of the N-terminal domain have anti-Plasmodium effects. We proposed a de novo active learning (AL) driven method in tandem with docking to predict inhibitors with unique scaffolds and preferential selectivity towards PfHsp90. Reference compounds, predicted to bind PfHsp90 at the ATP-binding pocket and possessing anti-Plasmodium activities, were used to generate 10,000 unique derivatives and to build the Auto-quantitative structures activity relationships (QSAR) models. Glide docking was performed to predict the docking scores of the derivatives and > 15,000 compounds obtained from the ChEMBL database. Re-iterative training and testing of the models was performed until the optimum Kennel-based Partial Least Square (KPLS) regression model with a regression coefficient R2 = 0.75 for the training set and squared correlation prediction Q2 = 0.62 for the test set reached convergence. Rescoring using induced fit docking and molecular dynamics simulations enabled us to prioritize 15 ATP/ADP-like design ideas for purchase. The compounds exerted moderate activity towards P. falciparum NF54 strain with IC50 values of ≤ 6μM and displayed moderate to weak affinity towards PfHsp90 (KD range: 13.5-19.9μM) comparable to the reported affinity of ADP. The most potent compound was FTN-T5 (PfN54 IC50:1.44μM; HepG2/CHO cells SI≥ 29) which bound to PfHsp90 with moderate affinity (KD:7.7μM), providing a starting point for optimization efforts. Our work demonstrates the great utility of AL for the rapid identification of novel molecules for drug discovery (i.e., hit identification). The potency of FTN-T5 will be critical for designing species-selective inhibitors towards developing more efficient agents against malaria.

Hand fatigability, self-reported fatigue, and functionality in individuals with multiple sclerosis: A cross-sectional study

BACKGROUND

The individual experience of fatigue and fatigability in individuals with Multiple Sclerosis (MS) can vary greatly, beyond the high prevalence of fatigue in MS. Although fatigue is known as a common symptom that affects and potentially limits individuals with MS, it has recently been determined that fatigability also causes consequences that limit individuals' daily lives. The purpose of this study was to compare the associations between self-reported levels of fatigue, measured fatigability, and estimates of functional capacity in people with MS and sex- and age-matched healthy individuals.

METHODS

Twenty-three individuals with Relapsing-Remitting MS (RRMS) diagnosis and 23 age- and sex-matched healthy individuals were included in the study. To examine the fatigability level Dynamic and Static Fatigue Index were used for gross and pinch-grip, and manual dexterity and functionality levels the Scale for the Assessment and Rating of Ataxia (SARA), Nine Hole Peg Test (NHPT), and Dexterity Questionnaire-24 (DextQ-24) were used. While the Fatigue Severity Scale (FSS) and Fatigue Impact Scale (FIS) were used to examine self-reported fatigue, the Beck Depression Inventory (BDI) was used to assess emotional status.

RESULTS

There was no difference between RRMS and healthy individuals in terms of fatigability levels (p > 0.05). While the relationship between Static and Dynamic Fatigue Index gross grip fatigability and FSS and FIS was not found to be statistically significant, the relationship between non-dominant side pinch grip Static Fatigue Index and FSS and FIS was significant. In addition, the relationship between the non-dominant side gross grip Static Fatigue Index and the DextQ-24 dressing and daily activities subsections, and the dominant side pinch grip Dynamic Fatigue Index and the television/compact disk/digital video disk subsection of DextQ-24 was significant (p < 0.05).

CONCLUSION

Fatigability was related to daily life upper limb use for gross grip and self-reported fatigue for pinch grip in individuals with RRMS. It was concluded that future studies focusing on hand fatigability could also consider manual dexterity and self-reported fatigue in individuals with MS from the early-stage. Clarifying the relationship of between fatigability and self-reported fatigue to functioning will allow clinicians to plan more appropriate and directed treatment approaches for individuals with RRMS.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05880745.

Temporal analysis of water chemistry and smallmouth bass (Micropterus dolomieu) health at two sites with divergent land use in the Susquehanna River watershed, Pennsylvania, USA

Monitoring wild fish health and exposure effects in impacted rivers and streams with differing land use has become a valuable research tool. Smallmouth bass (Micropterus dolomieu) are a sensitive, indicator species that exhibit signs of immunosuppression and endocrine disruption in response to water quality changes and contaminant exposure. To determine the impact of agriculture and development on smallmouth bass health, two sites (a developed/agriculture site and a forested site) in the Susquehanna River watershed, Pennsylvania were selected where bass and water chemistry were sampled from 2015 to 2019. Smallmouth bass were sampled for histopathology to assess parasite and macrophage aggregate density in the liver and spleen, condition factor (Ktl), hepatic gene transcript abundance, hepatosomatic index (HSI), and a health assessment index (HAI). Land use at the developed/agriculture site included greater pesticide application rates and phytoestrogen crop cover and more detections and higher concentrations of pesticides, wastewater-associated contaminants, hormones, phytoestrogens, and mycotoxins than at the forested site. Additionally, at the developed/agriculture site, indicators of molecular changes, including oxidative stress, immune/inflammation, and lipid metabolism-related hepatic gene transcripts, were associated with more contaminants and land use variables. At both sites, there were multiple associations of contaminants with liver and/or spleen macrophage aggregate density, indicating that changes at the molecular level seemed to be a better indicator of exposures unique to each site. The findings illustrate the importance of timing for land management practices, the complex mixtures aquatic animals are exposed to, and the temporal changes in contaminant concentration. Agricultural practices that affect hepatic gene transcripts associated with immune function and disease resistance were demonstrated which could negatively affect smallmouth bass populations.

Acute Eye-Tracking Changes Correlated With Vestibular Symptom Provocation Following Mild Traumatic Brain Injury

OBJECTIVES

To quantify norms and changes in eye-tracking proficiency, and determine vestibular symptom correlations in varsity college athletes following acute mild traumatic brain injury (mTBI). We hypothesized that mTBI impacts central coordination between the vestibular and oculomotor systems with resultant changes in eye-tracking proficiency that are correlated with vestibular symptom provocation.

DESIGN

Retrospective cohort study.

SETTING

Sports medicine care at a single institution.

PATIENTS

One hundred and nineteen college athletes diagnosed with mTBI by a physician between 2013 and 2019.

INTERVENTIONS

N/A.

MAIN OUTCOME MEASURES

Standard deviation of tangential error, standard deviation of radian error, mean phase error, and horizontal gain from virtual reality-based, circular eye-tracking goggles used at baseline and within 72 hours post-mTBI. Headache, dizziness, nausea, and fogginess provocation after the Vestibular Ocular Motor Screening (VOMS) smooth pursuits subtest compared with pretest baseline, assessed within 72 hours post-mTBI.

RESULTS

One hundred and nineteen college athletes (N = 56 women and 63 men) aged 18 to 24 years sustained a total of 177 mTBI. Forty-four percent of athletes displayed abnormal eye-tracking on at least 1 eye-tracking measure following acute mTBI compared with their baseline. From the VOMS, horizontal gain showed medium-sized to large-sized positive correlations with headache ( r = 0.34) and dizziness ( r = 0.54), respectively. Mean phase error showed a medium-sized negative correlation with nausea ( r = -0.32) on the VOMS.

CONCLUSIONS

Eye-tracking proficiency was impaired and correlated with vestibular symptom provocation following acute mTBI in college athletes. Future research should examine eye-tracking proficiency testing in other acute care settings to support mTBI diagnosis.

Factor structure and psychometric properties of the Birth Satisfaction Scale-Revised in Portuguese postpartum women

OBJECTIVE

This study aims to develop a Portuguese-language version of the Birth Satisfaction Scale-Revised (BSS-R) for clinical and research use in Portugal (PT-BSS-R). The factor structure, its invariance across depression levels, and the internal consistency of the PT-BSS-R were analysed.

METHOD

A sample of 1373 Portuguese-speaking postpartum women completed a sociodemographic and clinical form, the PT-BSS-R, and the Edinburgh Postnatal Depression Scale through an online survey tool. Four competing models were tested through confirmatory factor analyses and bifactor model-based psychometric indices were calculated. The internal consistency and the divergent/convergent validity are analysed.

RESULTS

The psychometric properties of PT-BSS-R were found to be generally excellent. Both the original correlated three-factor model and the bifactor model exhibited a good fit to the data. Results from the bifactor model support the use of both the BSS-R total score and the subscale scores. Exemplary invariance findings were observed between groups stratified on the basis of depression screening. PT-BSS-R has demonstrated both divergent and convergent validity as well as internal consistency.

CONCLUSION

PT-BSS-R is a psychometrically robust measure of birth satisfaction appropriate for clinical and research use in Portugal.

Normative values of skeletal muscle mass, strength and performance in the Indian population

BACKGROUND AND OBJECTIVES

Skeletal muscle is characterized by its mass, strength and performance. These normative values are pivotal in defining sarcopenia. Sarcopenia is associated with poor outcome of numerous medical and surgical conditions. This study aimed to establish normative benchmarks for skeletal muscle mass, strength and performance within the context of the Asian (Indian) population.

METHODS

Our investigation utilized the computed tomography (CT) skeletal muscle index (SMI), handgrip strength (HGS), gait velocity and chair-stand test to construct reference values for muscle characteristics in the Indian population.

RESULTS

The SMI analysis incorporated 1485 cases of acute abdomen (54.7%) males). The calculated SMI (kg/m2) was 38.50 (35.05-42.30) in males and 36.30 (32.20-41.20) in females (p = 0.510). The study also involved 3083 healthy individuals (67.6% males) evaluated for muscle strength and performance between August 2017 and August 2018. Notably, HGS (kg force) was recorded at 34.95 (26.50-43.30) in males and 25.50 (18.60-31.20) in females (p < 0.001). Gait velocity (metres/second) exhibited values of 1.25 (1.04-1.56) in males and 1.24 (1.03-1.56) in females (p = 0.851). Additionally, chair-stand test (seconds) results were 10.00 (9.00-13.00) in males and 12.00 (10.00-14.00) in females (p < 0.001).

CONCLUSIONS

The investigation determined that males had greater muscle strength and performance than females. But gender wise, there was no significant difference in muscle mass. Interestingly, our population's muscle parameters were consistently lower compared to western literature benchmarks. These normative values will help to define sarcopenia parameters in our population, which have prognostic value in multiple ailments.

Prediction of potentially toxic elements in water resources using MLP-NN, RBF-NN, and ANFIS: a comprehensive review

Water resources are constantly threatened by pollution of potentially toxic elements (PTEs). In efforts to monitor and mitigate PTEs pollution in water resources, machine learning (ML) algorithms have been utilized to predict them. However, review studies have not paid attention to the suitability of input variables utilized for PTE prediction. Therefore, the present review analyzed studies that employed three ML algorithms: MLP-NN (multilayer perceptron neural network), RBF-NN (radial basis function neural network), and ANFIS (adaptive neuro-fuzzy inference system) to predict PTEs in water. A total of 139 models were analyzed to ascertain the input variables utilized, the suitability of the input variables, the trends of the ML model applications, and the comparison of their performances. The present study identified seven groups of input variables commonly used to predict PTEs in water. Group 1 comprised of physical parameters (P), chemical parameters (C), and metals (M). Group 2 contains only P and C; Group 3 contains only P and M; Group 4 contains only C and M; Group 5 contains only P; Group 6 contains only C; and Group 7 contains only M. Studies that employed the three algorithms proved that Groups 1, 2, 3, 5, and 7 parameters are suitable input variables for forecasting PTEs in water. The parameters of Groups 4 and 6 also proved to be suitable for the MLP-NN algorithm. However, their suitability with respect to the RBF-NN and ANFIS algorithms could not be ascertained. The most commonly predicted PTEs using the MLP-NN algorithm were Fe, Zn, and As. For the RBF-NN algorithm, they were NO3, Zn, and Pb, and for the ANFIS, they were NO3, Fe, and Mn. Based on correlation and determination coefficients (R, R2), the overall order of performance of the three ML algorithms was ANFIS > RBF-NN > MLP-NN, even though MLP-NN was the most commonly used algorithm.

The value of MRI-based radiomics for evaluating early parotid gland injury in primary Sjögren's syndrome

OBJECTIVE

This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren's syndrome (pSS).

METHODS

A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images. A total of 1548 texture features of the parotid glands were extracted using radiomics software. A radiomics score (Radscore) was constructed and calculated. A t-test was used to compare the Radscore between the two groups. Finally, five machine learning models were trained and tested to identify early pSS parotid injury, and the performance of the machine learning models was evaluated by calculating the acceptance operating curve (ROC) and other parameters.

RESULTS

The Radscores between the pSS and HC groups showed significant statistical differences (p<0.001). Among the five machine learning models, the Extra Trees Classifier (ETC) model performed high predictive efficacy in identifying early pSS parotid injury, with an AUC of 0.87 in the testing set.

CONCLUSION

MRI radiomics-based machine learning models can effectively diagnose early parotid gland injury in primary Sjögren's syndrome.

Low Dietary Betaine Intake Is Associated with Increased Blood Cholesterol in Mexican Subjects

BACKGROUND

Betaine, an osmolyte derivative of the metabolite choline and the amino acid glycine, acts as a methyl donor in the conversion of homocysteine to methionine and is involved in the maintenance of adequate lipid metabolism. There is growing evidence for the role of betaine in the development of various lipid-related diseases, including dyslipidemia and cardiovascular risk. This study aimed to analyze associations between betaine intake and blood lipid profiles in Mexican subjects.

METHODS

A total of 212 adults were randomly recruited in the city of Tijuana, Baja California, Mexico. Betaine intake was estimated using Nutritionist Pro software. Body composition and metabolic measurements were obtained by conventional methods. In the total sample, the average intake of betaine was 14.32 mg/d. Individuals were categorized into three groups according to tertiles of betaine consumption: tertile/group 1 (<4.16 mg/d), tertile/group 2 (4.16-12.02 mg/d), and tertile/group 3 (>12.02 mg/d).

RESULTS

Compared to group 3, subjects within group 1 had higher serum levels of total cholesterol (p = 0.001), LDL-c (p = 0.026), and non-HDL-c (p = 0.021). In addition, significant negative Pearson correlations were found between betaine intake and the serum levels of total cholesterol (r = -0.432, 95% CI, -0.684, -0.185, p = 0.001), LDL-c (r = -0.370, 95% CI, -0.606, -0.134, p = 0.002), and non-HDL-c (r = -0.351, 95%CI, -0.604, -0.098, p = 0.007).

CONCLUSIONS

Our results show that a low intake of betaine is associated with elevated blood cholesterol levels in Mexican subjects. On this basis, betaine consumption could be used as an additional dietary measure for cardiovascular care. However, additional studies are required to confirm our results in other Mexican regions as well as in other populations worldwide.

Myths and methodologies: Assessment of dynamic cerebral autoregulation by the mean flow index

The mean flow index-usually referred to as Mx-has been used for assessing dynamic cerebral autoregulation (dCA) for almost 30 years. However, concerns have arisen regarding methodological consistency, construct and criterion validity, and test-retest reliability. Methodological nuances, such as choice of input (cerebral perfusion pressure, invasive or non-invasive arterial pressure), pre-processing approach and artefact handling, significantly influence mean flow index values, and previous studies correlating mean flow index with other established dCA metrics are confounded by inherent methodological flaws like heteroscedasticity, while the mean flow index also fails to discriminate individuals with presumed intact versus impaired dCA (discriminatory validity), and its prognostic performance (predictive validity) across various conditions remains inconsistent. The test-retest reliability, both within and between days, is generally poor. At present, no single approach for data collection or pre-processing has proven superior for obtaining the mean flow index, and caution is advised in the further use of mean flow index-based measures for assessing dCA, as current evidence does not support their clinical application.

Deep squat test - Functional movement Screen: Convergent validity and ability to discriminate subjects with different levels of joint mobility

BACKGROUND

Functional Movement Screen (FMS) is an important tool in the assessment of exercise practice. Assuming FMS lacks precise validity for assessing postural deficits, further research is needed to assess whether it is a sufficiently precise tool for analysing joint mobility. Research aims were to evaluate: convergent validity of Deep Squat (DS) - one of FMS tests - regarding joint mobility, using data from a three-dimensional motion analysis as a comparable method; DS's ability to discriminate between subjects with different joint mobility levels.

METHODS

Sixty subjects were selected (23.6 ± 3.8 years). DS was performed according to FMS guidelines. Subjects' performance in frontal and sagittal planes was recorded by two video cameras and subsequently scored by two FMS-certified evaluators. Three-dimensional motion analyses of DS were acquired by a Vicon Motion Capture System (200 Hz). Ten trials were acquired for each subject. Ankle, knee, hip, and shoulder angular positions in sagittal plane were determined from the FullBody PlugInGait model. Spearman's coefficient examined the correlation between angular positions and DS score. Kruskal-Wallis test was used to assess the DS ability to discriminate between subjects with different joint mobility levels by comparing different scores.

RESULTS

Negligible to moderate correlations were found between DS score and angular positions (-0.5 < r < 0.5). Only shoulder angular positions showed differences between score "1" and "2" (p < 0.05). Shoulder and hip angular positions showed no differences between score "2" and "3" (p < 0.05).

CONCLUSIONS

DS yielded low convergent validity regarding joint mobility and did not show the ability to discriminate between subjects with different joint mobility levels.

Characterization of phenotypic traits associated with anthracnose resistance in selected common bean (Phaseolus vulgaris L.) breeding material

Anthracnose caused by Colletotrichum lindemuthianum is the major common bean disease worldwide causing complete yield loss under favourable disease conditions. This study aimed to determine phenotypic traits associated with anthracnose resistance for future use in breeding programmes. Twenty-two common bean varieties (CBVs) were selected basing on susceptibility to anthracnose, advanced breeding lines, improved variety resembling advanced breeding lines and the farmer variety widely grown in Tanzania. Selected varieties were planted in anthracnose hotspot fields and the same CBVs were planted in a screen house to validate resistance to anthracnose. Anthracnose infection score, leaf length, leaf width, length of fifth internode, length of petiole, plant vigour, canopy height and canopy width were recorded. Data on number of plants emerging; days to flowering; days to maturity; plant stands at harvest; and grain yield were also collected and analysed using R software. Phenotypic traits evaluated differed significantly among genotypes, environment and genotype by environment interaction. Seventy-five percent of phenotypic traits evaluated were positively correlated to anthracnose resistance. Highly-strong correlations to anthracnose were observed on number of days to maturity, plant stands at harvest, plant vigour and grain yield. Leaf length, leaf width, length of fifth internode, length of petiole and number of stands emerging were strongly correlated to anthracnose resistance. Additive main effects and multiplicative interaction analysis (AMMI) revealed highest contribution of environment on anthracnose infection-58.9% and grain yield -84.9% compared to genotype effects on anthracnose infection -32.7% and grain yield-15.7%. Based on these results, four traits - plant vigour, number of days to maturity, number of plant stands at harvest and grain yield - are recommended for selecting anthracnose-resistant varieties. NUA 48, NUA 64 and RWR 2154 were superior varieties, resistant to anthracnose and high yielding, while Sweet Violet and VTT 923-23-10 were most stable varieties across environments. Further on-farm research is suggested to assess their performance and identify traits preferred by farmers.

Choosing a nursing specialty: connection to nursing students' personality traits, clinical self-efficacy, adoption of technology changes, and specialty prestige; a cross-sectional study

BACKGROUND

Choosing a field of specialization within the nursing profession is affected by nurses' personality traits, self-confidence in performing clinical skills, and the field's prestige. A successful choice of area of expertise may improve nurses' job satisfaction and reduce job mobility. This study aims to examine the relationship between personality traits, clinical self-efficacy, perceived prestige, adoption of technological changes, and choice of specialty field among nursing students.

METHODS

A cross-sectional study was conducted. One-hundred-twenty-seven undergraduate nursing students in their fourth year of studies at a large university in Israel participated in the study. The questionnaire administered was comprised of six parts: demographic data, personality traits, adoption of technological changes, clinical self-efficacy, perceived prestige, and intention to select a field of specialization.

RESULTS

Acute disciplines were rated more prestigious than chronic disciplines, with intensive care and emergency medicine considered the most prestigious, while mental health and geriatrics were the least prestigious. Students' mean perceived confidence in performing nursing clinical skills was high and more than half considered themselves open to technology changes. Positive correlations were found between prestige and intention to choose a field of expertise (r = 0.41, p < 0.001) and the personality trait of openness and the intention to choose an acute care area (r = 0.26, p < 0.01).

CONCLUSIONS

Despite the gradual aging of the population and the increase in chronic morbidity, which demand a greater nursing focus on older adults, and notwithstanding the mental health reforms, nursing students perceive geriatrics and mental health as less prestigious fields. A career development path can be applied by developing a tool for occupational guidance designed to rank students' suitability for specialty fields and thus help them choose the area that best suits them.

Comparison of surveillance systems for monitoring COVID-19 in England: a retrospective observational study

BACKGROUND

During the COVID-19 pandemic, cases were tracked using multiple surveillance systems. Some systems were completely novel, and others incorporated multiple data streams to estimate case incidence and prevalence. How well these different surveillance systems worked as epidemic indicators is unclear, which has implications for future disease surveillance and outbreak management. The aim of this study was to compare case counts, prevalence and incidence, timeliness, and comprehensiveness of different COVID-19 surveillance systems in England.

METHODS

For this retrospective observational study of COVID-19 surveillance systems in England, data from 12 surveillance systems were extracted from publicly available sources (Jan 1, 2020-Nov 30, 2021). The main outcomes were correlations between different indicators of COVID-19 incidence or prevalence. These data were integrated as daily time-series and comparisons undertaken using Spearman correlation between candidate alternatives and the most timely (updated daily, clinical case register) and the least biased (from comprehensive household sampling) COVID-19 epidemic indicators, with comparisons focused on the period of Sept 1, 2020-Nov 30, 2021.

FINDINGS

Spearman statistic correlations during the full focus period between the least biased indicator (from household surveys) and other epidemic indicator time-series were 0·94 (95% CI 0·92 to 0·95; clinical cases, the most timely indicator), 0·92 (0·90 to 0·94; estimates of incidence generated after incorporating information about self-reported case status on the ZoeApp, which is a digital app), 0·67 (95% CI 0·60 to 0·73, emergency department attendances), 0·64 (95% CI 0·60 to 0·68, NHS 111 website visits), 0·63 (95% CI 0·56 to 0·69, wastewater viral genome concentrations), 0·60 (95% CI 0·52 to 0·66, admissions to hospital with positive COVID-19 status), 0·45 (95% CI 0·36 to 0·52, NHS 111 calls), 0·08 (95% CI -0·03 to 0·18, Google search rank for "covid"), -0·04 (95% CI -0·12 to 0·05, in-hours consultations with general practitioners), and -0·37 (95% CI -0·46 to -0·28, Google search rank for "coronavirus"). Time lags (-14 to +14 days) did not markedly improve these rho statistics. Clinical cases (the most timely indicator) captured a more consistent proportion of cases than the self-report digital app did.

INTERPRETATION

A suite of monitoring systems is useful. The household survey system was the most comprehensive and least biased epidemic monitor, but not very timely. Data from laboratory testing, the self-reporting digital app, and attendances to emergency departments were comparatively useful, fairly accurate, and timely epidemic trackers.

FUNDING

National Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, a partnership between the UK Health Security Agency, King's College London, and the University of East Anglia.

Within-individual leaf trait variation increases with phenotypic integration in a subtropical tree diversity experiment

Covariation of plant functional traits, that is, phenotypic integration, might constrain their variability. This was observed for inter- and intraspecific variation, but there is no evidence of a relationship between phenotypic integration and the functional variation within single plants (within-individual trait variation; WTV), which could be key to understand the extent of WTV in contexts like plant-plant interactions. We studied the relationship between WTV and phenotypic integration in c. 500 trees of 21 species in planted forest patches varying in species richness in subtropical China. Using visible and near-infrared spectroscopy (Vis-NIRS), we measured nine leaf morphological and chemical traits. For each tree, we assessed metrics of single and multitrait variation to assess WTV, and we used plant trait network properties based on trait correlations to quantify phenotypic integration. Against expectations, strong phenotypic integration within a tree led to greater variation across leaves. Not only this was true for single traits, but also the dispersion in a tree's multitrait hypervolume was positively associated with tree's phenotypic integration. Surprisingly, we only detected weak influence of the surrounding tree-species diversity on these relationships. Our study suggests that integrated phenotypes allow the variability of leaf phenotypes within the organism and supports that phenotypic integration prevents maladaptive variation.

Surface guidance compared with ultrasound-based monitoring and diaphragm position in cone-beam computed tomography during abdominal stereotactic radiotherapy in breath-hold

Background and purpose

Spirometry induced deep-inspiration-breath-hold (DIBH) reduces intrafractional motion during upper abdominal stereotactic body radiotherapy (SBRT). The aim of this prospective study was to evaluate whether surface scanning (SGRT) is an adequate surrogate for monitoring residual internal motion during DIBH. Residual motion detected by SGRT was compared with experimental 4D-ultrasound (US) and an internal motion detection benchmark (diaphragm-dome-position in kV cone-beam computed tomography (CBCT) projections).

Materials and methods

Intrafractional monitoring was performed with SGRT and US in 460 DIBHs of 12 patients. Residual motion detected by all modalities (SGRT (anterior-posterior (AP)), US (AP, craniocaudal (CC)) and CBCT (CC)) was analyzed. Agreement analysis included Wilcoxon signed rank test, Maloney and Rastogi's test, Pearson's correlation coefficient (PCC) and interclass correlation coefficient (ICC).

Results

Interquartile range was 0.7 mm (US(AP)), 0.8 mm (US(CC)), 0.9 mm (SGRT) and 0.8 mm (CBCT). SGRT(AP) vs. CBCT(CC) and US(CC) vs. CBCT(CC) showed comparable agreement (PCCs 0.53 and 0.52, ICCs 0.51 and 0.49) with slightly higher precision of CBCT(CC). Most agreement was observed for SGRT(AP) vs. US(AP) with largest PCC (0.61) and ICC (0.60), least agreement for SGRT(AP) vs. US(CC) with smallest PCC (0.44) and ICC (0.42).

Conclusions

Residual motion detected during spirometry induced DIBH is small. SGRT alone is no sufficient surrogate for residual internal motion in all patients as some high velocity motion could not be detected. Observed patient-specific residual errors may require individualized PTV-margins.

Development and Relative Validation of a Food Frequency Questionnaire to Assess Non-Nutritive Sweeteners Intake among Pregnant Women in Santiago, Chile: A Pilot Study

Studies on the effects of non-nutritive sweeteners (NNSs) among pregnant women are scarce and have produced mixed results. One of the major challenges is to accurately assess NNS intake, especially in countries that have implemented policies to prevent obesity and where many foods and beverages have been progressively reformulated to partially or totally replace sugar with NNSs. This study aimed to develop and assess the relative validity of a food frequency questionnaire (FFQ) for use in pregnant women. We developed an FFQ to examine the intake of seven NNSs (acesulfame-k, aspartame, cyclamate, saccharin, sucralose, steviol glycosides, and D-tagatose). This questionnaire was piloted in 29 pregnant women (median age = 31.2 y; 25th-75th percentile: 26.9-34.7) to assess NNS intake over the previous month, compared to 3-day dietary records (3-DR). The validity of this dietary method was assessed using Spearman's correlation coefficient, Lin´s concordance correlation coefficient (CCC), and Bland-Altman plots. Spearman's correlations between the FFQ on NNSs and 3-DR ranged from 0.50 for acesulfame K to 0.83 for saccharin. CCC ranged between 0.22 and 0.66. The Bland-Altman plots showed an overestimation of saccharin, sucralose, and steviol glycosides intake by the FFQ on NNSs compared with 3-DR, and an underestimation of acesulfame K and aspartame. Overall, the NNSs most frequently consumed were sucralose, and none of the participants exceeded the acceptable daily intake for any of the NNSs evaluated. The FFQ on NNSs seems to be reasonably valid in the assessment of NNSs among pregnant women.

Analyzing international airtime top-up transfers for migration and mobility

International airtime top-up transfers enable prepaid mobile phone users to send top-ups and data bundles to users in other countries, as well as make payments, in real time. These are heavily used by migrants to financially assist their families in their home countries and consequently could be a valuable source of information for migration and mobility analysis. However, top-up transfers are understudied as a form of money remittance in migration. In this paper, we explore the determinants and the potential of top-up transactions to complement remittance and migration statistics. Our results show that such data can provide insights into migrant groups, particularly for irregular migration and for estimating the real-time distribution of migrant groups for a given country.

Predicting feed efficiency traits in growing lambs from their ruminal microbiota

Selecting feed-efficient sheep could improve the sustainability of this livestock production. However, most sheep breeding companies cannot afford to record feed intake to select feed-efficient animals. Past studies underlined the potential of omics data, including microbiota metabarcoding data, as proxies for feed efficiency. The study involved 277 Romane lambs from two lines divergently selected for residual feed intake (RFI). There were two objectives: check the consequences of selecting for feed efficiency over the rumen microbiota, and assess the predictive ability of the rumen microbiota for host traits. The study assessed two contrasting diets (concentrate diet and mixed diet) and two microbial groups (prokaryotes and eukaryotes). Discriminant analyses did not highlight any significant effect of sheep selection for residual feed intake on the rumen microbiota composition. Indeed, prokaryotic and eukaryotic microbiota compositions poorly discriminated the RFI lines, with averaged balanced error rates ranging from 45% to 55%. Correlations between host traits (feed efficiency and production traits) and their predictions from microbiota data varied between -0.07 and 0.56, depending on the trait, diet and sequencing. Feed intake was the most accurately predicted trait. However, predictions from fixed effects and BW were more accurate than or as accurate as predictions from the microbiota. Environmental effects can greatly affect the variability of microbiota compositions. Considering batch and environmental effects should be paramount when the predictive ability of the microbiota is assessed. This study argues why metabarcoding the rumen microbiota is not the best way to predict meat sheep production traits: fixed effects and BW were more cost-effective proxies and they led to similar or better predictive accuracies than microbiota metabarcoding (16S and 18S sequencing).

Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts

Machine learning (ML) is becoming an integral aspect of several domains in medicine. Yet, most pathologists and laboratory professionals remain unfamiliar with such tools and are unprepared for their inevitable integration. To bridge this knowledge gap, we present an overview of key elements within this emerging data science discipline. First, we will cover general, well-established concepts within ML, such as data type concepts, data preprocessing methods, and ML study design. We will describe common supervised and unsupervised learning algorithms and their associated common machine learning terms (provided within a comprehensive glossary of terms that are discussed within this review). Overall, this review will offer a broad overview of the key concepts and algorithms in machine learning, with a focus on pathology and laboratory medicine. The objective is to provide an updated useful reference for those new to this field or those who require a refresher.

Mechanical Dyssynchrony of Isolated Left and Right Ventricular Human Myocardium in End-Stage Heart Failure

BACKGROUND

The left and right ventricles of the human heart differ in embryology, shape, thickness, and function. Ventricular dyssynchrony often occurs in cases of heart failure. Our objectives were to assess whether differences in contractile properties exist between the left and right ventricles and to evaluate signs of left/right ventricular mechanical synchrony in isolated healthy and diseased human myocardium.

METHODS

Myocardial left and right ventricular trabeculae were dissected from nonfailing and end-stage failing human hearts. Baseline contractile force and contraction/relaxation kinetics of the left ventricle were compared to those of the right ventricle in the nonfailing group (n=41) and in the failing group (n=29). Correlation analysis was performed to assess the mechanical synchrony between left and right ventricular myocardium isolated from the same heart, in nonfailing (n=41) and failing hearts (n=29).

RESULTS

The failing right ventricular myocardium showed significantly higher developed force (Fdev; P=0.001; d=0.98), prolonged time to peak (P<0.001; d=1.14), and higher rate of force development (P=0.002; d=0.89) and force decline (P=0.003; d=0.82) compared to corresponding left ventricular myocardium. In healthy myocardium, a strong positive relationship was present between the left and right ventricles in time to peak (r=0.58, P<0.001) and maximal kinetic rate of contraction (r=0.63, P<0.001). These coefficients were much weaker, often nearly absent, in failing myocardium.

CONCLUSIONS

At the level of isolated cardiac trabeculae, contractile performance, specifically of contractile kinetics, is correlated in the nonfailing myocardium between the left and right ventricles' but this correlation is significantly weaker, or even absent, in end-stage heart failure, suggesting an interventricular mechanical dyssynchrony.

Involvement and possible role of transglutaminases 1 and 2 in mediating fibrotic signalling, collagen cross-linking and cell proliferation in neonatal rat ventricular fibroblasts

Transglutaminase (TG) isoforms control diverse normal and pathophysiologic processes through their capacity to cross-link extracellular matrix (ECM) proteins. Their functional and signalling roles in cardiac fibrosis remain poorly understood, despite some evidence of TG2 involvement in abnormal ECM remodelling in heart diseases. In this study, we investigated the role of TG1 and TG2 in mediating fibrotic signalling, collagen cross-linking, and cell proliferation in healthy fibroblasts by siRNA-mediated knockdown. siRNA for TG1, TG2 or negative control was transfected into cultured neonatal rat ventricular fibroblasts and cardiomyocytes. mRNA expression of TGs and profibrotic, proliferation and apoptotic markers was assessed by qPCR. Cell proliferation and soluble and insoluble collagen were determined by ELISA and LC-MS/MS, respectively. TG1 and TG2 were both expressed in neonatal rat cardiomyocytes and fibroblasts before transfection. Other TGs were not detected before and after transfection. TG2 was predominantly expressed and more effectively silenced than TG1. Knocking down TG1 or TG2 significantly modified profibrotic markers mRNA expression in fibroblasts, decreasing connective tissue growth factor (CTGF) and increasing transforming growth factor-β1 compared to the negative siRNA control. Reduced expression of collagen 3A1 was found upon TG1 knockdown, while TG2 knockdown raised α-smooth muscle actin expression. TG2 knockdown further increased fibroblast proliferation and the expression of proliferation marker cyclin D1. Lower insoluble collagen content and collagen cross-linking were evidenced upon silencing TG1 or TG2. Transcript levels of collagen 1A1, fibronectin 1, matrix metalloproteinase-2, cyclin E2, and BCL-2-associated X protein/B-cell lymphoma 2 ratio were strongly correlated with TG1 mRNA expression, whereas TG2 expression correlated strongly with CTGF mRNA abundance. These findings support a functional and signalling role for TG1 and TG2 from fibroblasts in regulating key processes underlying myocardial ECM homeostasis and dysregulation, suggesting that these isoforms could be potential and promising targets for the development of cardiac fibrosis therapies.

Parents' Experiences of Communication in Neonatal Care (PEC): a neonatal survey refined for real-time parent feedback

OBJECTIVE

Assessing parent experiences of neonatal services can help improve quality of care; however, there is no formally evaluated UK instrument available to assess this prospectively. Our objective was to refine an existing retrospective survey for 'real-time' feedback.

METHODS

Co-led by a parent representative, we recruited a convenience sample of parents of infants in a London tertiary neonatal unit. Our steering group selected questions from the existing retrospective 61-question Picker survey (2014), added and revised questions assessing communication and parent involvement. We established face validity, ensuring questions adequately captured the topic, conducted parent cognitive interviews to evaluate parental understanding of questions,and adapted the survey in three revision cycles. We evaluated survey performance.

RESULTS

The revised Parents' Experiences of Communication in Neonatal Care (PEC) survey contains 28 questions (10 new) focusing on communication and parent involvement. We cognitively interviewed six parents, and 67 parents completed 197 PEC surveys in the survey performance evaluation. Missing entries exceeded 5% for nine questions; we removed one and format-adjusted the rest as they had performed well during cognitive testing. There was strong inter-item correlation between two question pairs; however, all were retained as they individually assessed important concepts.

CONCLUSION

Revised from the original 61-question Picker survey, the 28-question PEC survey is the first UK instrument formally evaluated to assess parent experience while infants are still receiving neonatal care. Developed with parents, it focuses on communication and parent involvement, enabling continuous assessment and iterative improvement of family-centred interventions in neonatal care.

Skin temperature normalizes faster than pressure pain thresholds, pain intensity, and pain distribution during recovery from eccentric exercise

INTRODUCTION

Acute musculoskeletal injuries have diverse symptomatology and a multidimensional recovery process, including changes in swelling, redness, hyperalgesia, and expanded pain distribution. In a small proportion of cases, the tissue heals, although these symptoms persist, reflecting altered peripheral and central pain mechanisms. However, the otherwise healthy multidimensional recovery process following damage and pain is less than clear. The objective was to assess mechanical muscle hyperalgesia, skin temperature, and pain intensity and distribution during the recovery process in response to eccentric exercise in the hamstring muscles.

METHODS

Twenty-four healthy males participated in four sessions (Day-0, Day-2, Day-4, and Day-7). Exercise-induced muscle soreness was induced on Day-0 by five sets of 20 repetitions of an eccentric exercise involving the hamstrings on the dominant leg. Each session included assessments of thermography, pressure pain thresholds (PPTs), pain intensity, and area of exercise-induced pain.

RESULTS

Decreased PPTs (P < 0.005), higher pain intensity (P < 0.001), and a larger area of pain (P < 0.001) were displayed on Day-2 and Day-4 than Day-0. Skin temperature decreased on Day-2 than Day-0 (P < 0.01) and returned to baseline assessments by Day-4, despite lower temperature than the contralateral tight (P < 0.01). Further, there was a positive correlation between pain intensity and area on Day-2 and Day-4 (P < 0.005), but no for changes in skin temperature.

CONCLUSION

Thermographic changes and pain-related variables altered following eccentric exercise demonstrate different recovery times. These results provide insights into potential mechanisms and measures that can be used to assess recovery from exercise-induced damage.

Health At Every Size intervention® under real-world conditions: the rights and wrongs of program implementation

Implementation integrity is known to be critical to the success of interventions. The Health At Every Size® (HAES®) approach is deemed to be a sustainable intervention on weight-related issues. However, no study in the field has yet investigated the effects of implementation on outcomes in a real-world setting.

Temperate Lianas Have More Acquisitive Strategies than Host Trees in Leaf and Stem Traits, but Not Root Traits

Increasingly, tropical studies based on aboveground traits have suggested that lianas have a more acquisitive strategy than trees, thereby possibly explaining the increase in lianas relative to trees in many tropical forests under global change. However, few studies have tested whether this pattern can be extended to root traits and temperate forests. In this study, we sampled 61 temperate liana-host tree pairs and quantified 11 commonly studied functional traits representative of plant economics in roots, stems, and leaves; we aimed to determine whether root, stem and leaf traits are coordinated across lifeforms, and whether temperate lianas are also characterized by more fast and acquisitive traits than trees. Our results showed that leaf and stem traits were coordinated across lifeforms but not with root traits, suggesting that aboveground plant economics is not always correlated with belowground economics, and leaf and stem economic spectra cannot be expanded to the root directly. Compared with host trees, lianas had more acquisitive leaf and stem traits, such as higher specific leaf area and lower leaf dry matter content, leaf carbon content, leaf mass per area, and wood density, suggesting that lianas have a more acquisitive strategy than host trees in the temperate forest. The differences between lianas and trees in plant strategy may drive their contrasting responses to the changing temperate forest environment under global change.

Transferring network analysis to the study of potential biogeochemical interactions of phosphorus-relevant elements in floodplain subsoils - A new use case for the Soilscape Network Approach (SNAp)

Subsurface phosphorus (P) loss from deep P stocks in floodplain subsoils can contribute to eutrophication of freshwaters. To date, knowledge on the complex biogeochemical interactions of P in floodplain subsoils is too scarce to enable targeted P management to mitigate subsurface P loss from deep P stocks. We propose using graph theory and the Soilscape Network Approach (SNAp) based on correlations between P-relevant elements to study these complex biogeochemical interactions in the soilscape. Complex interactions of several elements in soils are difficult to investigate from a holistic perspective with conventional data analysis. We translated soil element data from topsoils and subsoils of terrestrial sites, proximal and distal floodplain sites into relational data and analyzed network structure, centrality, and modularity. The results indicate that a higher frequency of groundwater level fluctuations in distal subsoils and proximal topsoils could result in 24-44 % less biogeochemical interaction compared to sites with stable conditions. Impeded microbial processes on the frequently disturbed sites may explain this finding. Our analyses suggest biogeochemical differences between floodplain topsoils and subsoils expressed in 24 % lower and 75 % higher network connectivity in distal and proximal subsoils (respectively). We also found 22 % lower network connectivity in distal than proximal floodplain subsoils, suggesting biogeochemical differences between both soil sections. These findings imply that floodplain P management should not take a whole-floodplain approach but a 3D-approach, which differentiates laterally between floodplain zones and vertically between soil sections. In addition, SNAp indicated that Fe(II) oxides are important in P biogeochemistry of floodplain subsoils but are not the key element. Instead, labile P forms are suggested to have different major associations in distal (Al_ox, Fe_ox) versus proximal deep P stocks (Al_ox, Mn, Ca). Our study provides new insights into the biogeochemistry of deep P stocks in floodplain subsoils which require targeted validation by other methods.

Characterization of dorsal recumbency syndrome associated with woody breast in broiler flocks from Ontario, Canada

A dorsal recumbency syndrome (DRS) has been recently described in market-age broiler chickens. Affected broilers fall onto their backs, and are unable to right themselves, and eventually die of cardiopulmonary insufficiency. These broilers are referred to as turtle chickens. A previous report and anecdotal evidence suggest that breast myopathies, such as woody breast (WB), may be associated with DRS due to impaired contractility of the pectoral muscles. In this study, we aimed to provide additional evidence to document DRS in broilers, and its possible association with breast myopathies. A total of 64 broilers (Ross 708), 33 DRS-affected and 31 controls, were culled between 42 and 48 d of age from 3 different commercial farms over 4 visits. All broilers underwent postmortem analysis; breast muscles were scored grossly and/or histologically to determine the presence and severity of myopathies, and sera were used to determine the level of aspartate aminotransferase (AST) and creatine kinase (CK). A gross diagnosis of WB was moderately associated with DRS broilers, and DRS broilers displayed a greater microscopic severity of lesions (P < 0.001) in the Pectoralis major, as typically observed with WB. Levels of AST and CK were greater (P < 0.001) in the sera of DRS-affected compared to control broilers, consistent with muscular damage. The frequency of cardiac changes, such as mild hydropericardium and right ventricular dilation, or severity of microscopic pulmonary lesions, such as edema, were not significantly different between the 2 groups. The odds of DRS increased with the histology score of the P. major (OR = 1.37, 95% CI 1.02-1.85). The data presented in this study support an association between DRS and muscular damage of the P. major, suggesting that WB may predispose broilers to DRS. DRS might be a cause of broiler death, and this syndrome could be responsible for significant financial loss to the farmers and to the whole poultry industry.

Lower activity linkage between caregivers and persons with neurodegenerative diseases is associated with greater caregiver anxiety

Physiological linkage refers to the degree to which two individuals' central/peripheral physiological activities change in coordinated ways. Previous research has focused primarily on linkage in the autonomic nervous system in laboratory settings, particularly examining how linkage is associated with social behavior and relationship quality. In this study, we examined how linkage in couples' daily somatic activity (e.g., synchronized movement measured from wrist sensors)-another important aspect of peripheral physiology-was associated with relationship quality and mental health. We focused on persons with neurodegenerative diseases (PWNDs) and their spousal caregivers, whose linkage might have direct implications for the PWND-caregiver relationship and caregiver's health. Twenty-two PWNDs and their caregivers wore wristwatch actigraphy devices that provided continuous measurement of activity over 7 days at home. PWND-caregiver activity linkage was quantified by the degree to which activity was "in-phase" or "anti-phase" linked (i.e., coordinated changes in the same or opposite direction) during waking hours, computed by correlating minute-by-minute activity levels averaged using a 10-min rolling window. Caregivers completed well-validated surveys that assessed their mental health (including anxiety and depression) and relationship quality with the PWND. We found that lower in-phase activity linkage, but not anti-phase linkage, was associated with higher caregiver anxiety. These dyad-level effects were robust, remaining significant after adjusting for somatic activity at the individual level. No effects were found for caregiver depression or relationship quality. These findings suggest activity linkage and wearables may be useful for day-by-day monitoring of vulnerable populations such as family caregivers. We offered several possible explanations for our findings.

Lateralization of early orthographic processing during natural reading is impaired in developmental dyslexia

Skilled reading requires specialized visual cortical processing of orthographic information and its impairment has been proposed as a potential correlate of compromised reading in dyslexia. However, which stage of orthographic information processing during natural reading is disturbed in dyslexics remains unexplored. Here we addressed this question by simultaneously measuring the eye movements and EEG of dyslexic and control young adults during natural reading. Isolated meaningful sentences were presented at five inter-letter spacing levels spanning the range from minimal to extra-large spacing, and participants were instructed to read the text silently at their own pace. Control participants read faster, performed larger saccades and shorter fixations compared to dyslexics. While reading speed peaked around the default letter spacing, saccade amplitude increased and fixation duration decreased with the increase of letter spacing in both groups. Lateralization of occipito-temporal fixation-related EEG activity (FREA) was found in three consecutive time intervals corresponding to early orthographic processing in control readers. Importantly, the lateralization in the time range of the first negative left occipito-temporal FREA peak was specific for first fixations and exhibited an interaction effect between reading ability and letter spacing. The interaction originated in the significant decrease of FREA lateralization at extra-large compared to default letter spacing in control readers and the lack of lateralization in both letter spacing conditions in the case of dyslexics. These findings suggest that expertise-driven hemispheric functional specialization for early orthographic processing thought to be responsible for letter identity extraction during natural reading is compromised in dyslexia.

Reliability of non-invasive arterial blood pressure measurement in patients with aneurysmal subarachnoid haemorrhage

Objective Invasively measured arterial blood pressure (ABP) is associated with complications, while non-invasively measured ABP is generally considered risk-free. This study aimed to investigate the reliability of non-invasive ABP measured using finger-cuff volume-clamp device compared to invasive ABP measured by an arterial catheter in patients with aneurysmal subarachnoid haemorrhage (SAH). Approach In 30 patients admitted for neurointensive care with SAH, invasive and non-invasive ABP were recorded simultaneously. Reliability was assessed for mean, diastolic and systolic ABP separately using intraclass correlation coefficient (ICC) agreement for each full period and each 3-second average. Main results A median of 3 (IQR: 2-3) periods were included for each participant. The full periods (n = 81) showed an ICC of 0.34 (95% CI: 0.14-0.52), 0.31 (95% CI: 0.10 to 0.49), and 0.20 (95% CI: 0.00 to 0.39) for mean, diastolic, and systolic ABP, respectively. Three-second averages (n = 33,786) for mean (ICC: 0.35; 95% CI: 0.33 to 0.36), diastolic (ICC: 0.25; 95% CI: 0.25 to 0.28), and systolic ABP (ICC: 0.26; 95% CI: 0.18 to 0.33) yielded similar findings. Pearson's correlation coefficient showed an R2 of 0.15 (p < 0.001), 0.15 (p < 0.001), 0.06 (p = 0.027) for mean, diastolic and systolic ABP, respectively. Significance In patients with SAH, non-invasive measurement of ABP using the widely used Nano system from Finapres Medical Systems - a finger-cuff volume-clamp device (Finapres, Chennai, India) showed poor reliability and therefore cannot be used interchangeably with invasively measured ABP.

Mortality Analysis of Patients with COVID-19 in Mexico Based on Risk Factors Applying Machine Learning Techniques

The new pandemic caused by the COVID-19 virus has generated an overload in the quality of medical care in clinical centers around the world. Causes that originate this fact include lack of medical personnel, infrastructure, medicines, among others. The rapid and exponential increase in the number of patients infected by COVID-19 has required an efficient and speedy prediction of possible infections and their consequences with the purpose of reducing the health care quality overload. Therefore, intelligent models are developed and employed to support medical personnel, allowing them to give a more effective diagnosis about the health status of patients infected by COVID-19. This paper aims to propose an alternative algorithmic analysis for predicting the health status of patients infected with COVID-19 in Mexico. Different prediction models such as KNN, logistic regression, random forests, ANN and majority vote were evaluated and compared. The models use risk factors as variables to predict the mortality of patients from COVID-19. The most successful scheme is the proposed ANN-based model, which obtained an accuracy of 90% and an F1 score of 89.64%. Data analysis reveals that pneumonia, advanced age and intubation requirement are the risk factors with the greatest influence on death caused by virus in Mexico.

Application of a Deep Learning Network for Joint Prediction of Associated Fluid Production in Unconventional Hydrocarbon Development

Machine learning (ML) approaches have risen in popularity for use in many oil and gas (O&G) applications. Time series-based predictive forecasting of hydrocarbon production using deep learning ML strategies that can generalize temporal or sequence-based information within data is fast gaining traction. The recent emphasis on hydrocarbon production provides opportunities to explore the use of deep learning ML to other facets of O&G development where dynamic, temporal dependencies exist and that also hold implications to production forecasting. This study proposes a combination of supervised and unsupervised ML approaches as part of a framework for the joint prediction of produced water and natural gas volumes associated with oil production from unconventional reservoirs in a time series fashion. The study focuses on the pay zones within the Spraberry and Wolfcamp Formations of the Midland Basin in the U.S. The joint prediction model is based on a deep neural network architecture leveraging long short-term memory (LSTM) layers. Our model has the capability to both reproduce and forecast produced water and natural gas volumes for wells at monthly resolution and has demonstrated 91 percent joint prediction accuracy to held out testing data with little disparity noted in prediction performance between the training and test datasets. Additionally, model predictions replicate water and gas production profiles to wells in the test dataset, even for circumstances that include irregularities in production trends. We apply the model in tandem with an Arps decline model to generate cumulative first and five-year estimates for oil, gas, and water production outlooks at the well and basin-levels. Production outlook totals are influenced by well completion, decline curve, and spatial and reservoir attributes. These types of model-derived outlooks can aid operators in formulating management or remedial solutions for the volumes of fluids expected from unconventional O&G development.

Disparities in depression among Chinese older adults with neurodegenerative diseases

OBJECTIVES

Neurodegenerative diseases (NDs), such as Parkinson's disease and Alzheimer's disease and related dementias, are a leading cause of death and disability in China. Although studies have demonstrated that depression is associated with NDs, little is known about the factors impacting this relationship. This study aimed to explore and identify the risk and protective factors of depression among Chinese older adults with NDs.

METHODS

Data selection was based on the behavioral model of late-life depression. Data from the latest wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS, 1998-2014) in 2014 were analyzed. Among the sample, 334 older adults aged 65 and older with NDs were included in the analysis. A logistic regression analysis was conducted by SPSS 24.0.

RESULTS

Participants who lived in urban areas (O.R.= 2.494, p< .05) or needed more support for Activity of Daily Living (O.R.= 1.136, p< .05) were more likely to have depression. Participants who lived with household members (O.R.= .380, p< .05), self-reported their health status as fair (O.R.= .250, p< .01), or believed their health status remained the same (O.R.= .331, p< .01) were less likely to have depression.

CONCLUSION

Our findings suggest that policymakers and healthcare professionals should pay specific attention to the regional disparities of healthcare services and the cultural background to understand the relationship between NDs and depression and improve the well-being of ND patients.

Reliability of cerebral autoregulation using different measures of perfusion pressure in patients with subarachnoid hemorrhage

Dynamic cerebral autoregulation to spontaneous fluctuations in cerebral perfusion pressure (CPP) is often assessed by transcranial Doppler (TCD) in the time domain, yielding primarily the mean flow index (Mx), or in the frequency domain using transfer function analysis (TFA), yielding gain and phase. For both domains, the measurement of blood pressure is critical. This study assessed the inter-method reliability of dynamic cerebral autoregulation using three different methods of pressure measurement. In 39 patients with aneurysmal subarachnoid hemorrhage, non-invasive arterial blood pressure (ABP), invasive ABP (measured in the radial artery) and CPP were recorded simultaneously with TCD. Intraclass correlation coefficient (ICC) was used to quantify reliability. Mx was higher when calculated using invasive ABP (0.39; 95% confidence interval [95% CI]: 0.33; 0.44) compared to non-invasive ABP, and CPP. The overall ICC showed poor to good reliability (0.65; 95% CI: 0.11; 0.84; n = 69). In the low frequency domain, the comparison between invasively measured ABP and CPP showed good to excellent (normalized gain, ICC: 0.87, 95CI: 0.81; 0.91; n = 96; non-normalized gain: 0.89, 95% CI: 0.84; 0.92; n = 96) and moderate to good reliability (phase, ICC: 0.69, 95% CI: 0.55; 0.79; n = 96), respectively. Different methods for pressure measurement in the assessment of dynamic cerebral autoregulation yield different results and cannot be used interchangeably.

Reliability and validity of the mean flow index (Mx) for assessing cerebral autoregulation in humans: A systematic review of the methodology

Cerebral autoregulation is a complex mechanism that serves to keep cerebral blood flow relatively constant within a wide range of cerebral perfusion pressures. The mean flow index (Mx) is one of several methods to assess dynamic cerebral autoregulation, but its reliability and validity have never been assessed systematically. The purpose of the present systematic review was to evaluate the methodology, reliability and validity of Mx.Based on 128 studies, we found inconsistency in the pre-processing of the recordings and the methods for calculation of Mx. The reliability in terms of repeatability and reproducibility ranged from poor to excellent, with optimal repeatability when comparing overlapping recordings. The discriminatory ability varied depending on the patient populations; in general, those with acute brain injury exhibited a higher Mx than healthy volunteers. The prognostic ability in terms of functional outcome and mortality ranged from chance result to moderate accuracy.Since the methodology was inconsistent between studies, resulting in varying reliability and validity estimates, the results were difficult to compare. The optimal method for deriving Mx is currently unknown.

Teamwork and Adherence to Guideline on Newborn Resuscitation-Video Review of Neonatal Interdisciplinary Teams

BACKGROUND

Little is known about the importance of non-technical skills for the adherence to guidelines, when teams of midwives, obstetricians, anesthesiologists, and pediatricians resuscitate and support the transition of newborns. Non-technical skills are competences underpinning successful teamwork in healthcare. These are usually referred to as leadership, situational awareness, communication, teamwork, decision making, and coping with stress and fatigue.

OBJECTIVE

By review of videos of teams managing newborns with difficult transition, we aimed to investigate whether the level of the teams' non-technical skills was associated with the degree of adherence to guidelines for newborn resuscitation and transitional support at birth.

METHODS

Four expert raters independently assessed 43 real-life videos of teams managing newborns with transitional difficulties, two assessed the non-technical score and two assessed the clinical performance. Exposure was the non-technical score, obtained by the Global Assessment Of Team Performance checklist (GAOTP). GAOTP was rated on a Likert Scale 1-5 (1 = poor, 3 = average and 5 = excellent). The outcome was the clinical performance score of the team assessed according to adherence of the European Resuscitation Counsel (ERC) guideline for neonatal resuscitation and transitional support. The ERC guideline was adapted into the checklist TeamOBS-Newborn to facilitate a structured and simple performance assessment (low score 0-60, average 60-84, high 85-100). Interrater agreement was analyzed by intraclass correlation (ICC), Bland-Altman analysis, and Cohen's kappa weighted. The risk of high and low clinical performance was analyzed on the logit scale to meet the assumptions of normality and constant standard deviation.

RESULTS

Teams with an excellent non-technical score had a relative risk 5.5 [95% confidence interval (CI) 2.4-22.5] of high clinical performance score compared to teams with average non-technical score. In addition, we found a dose response like association. The specific non-technical skills associated with the highest degree of adherence to guidelines were leadership and teamwork, coping with stress and fatigue, and communication with parents. Inter-rater agreement was high; raters assessing non-technical skills had an interclass coefficient (ICC) 0.88 (95% CI 0.79-0.94); the neonatologists assessing clinical performance had an ICC of 0.81 (95% CI 0.66-0.89).

CONCLUSION

Teams with an excellent non-technical score had five times the chance of high clinical performance compared to teams with average non-technical skills. High performance teams were characterized by good leadership and teamwork, coping with stress, and fatigue and communication with parents.

Narrative Analysis in Adolescents With Fragile X Syndrome

This study analyzed narratives of male and female adolescents with fragile X syndrome (FXS). The impact of structural language, cognition and autism symptomatology on narrative skills and the association between narratives and literacy were examined. Narratives from 32 adolescents with FXS (24 males, 8 females) were analyzed for macrostructure. Relationships between narrative macrostructure, language scores, cognitive scores, Childhood Autism Rating Scale-Second Edition scores and literacy skills were examined. Males produced more simplistic narratives, whereas the females' narratives were more complex. Language scores predicted narrative scores above and beyond nonverbal cognitive skills and autism symptomatology. Narrative scores correlated with literacy scores. Narrative skills in FXS are predicted by language skills and are correlated with literacy skills. Investigation into narrative interventions in FXS is needed.

A multi-herd study shows that saliva is more than a reflection of serum biomarkers in pigs

This study evaluates if biomarkers of porcine health status in saliva samples is a mere reflection of serum to detect disease in pigs under field conditions. Four farms from the same commercial company were included to obtain samples from animals with different pathological conditions. A total of 10 healthy animals and 10-15 animals from each farm with clinical symptoms of the disease were sampled for paired saliva and blood during a veterinary clinical visit. The biomarker panel included acute-phase proteins (APPs), C-reactive protein (CRP), haptoglobin (Hp), an inflammatory marker, adenosine deaminase (ADA), the total antioxidant capacity (TAC), the levels of essential trace elements, copper (Cu) and zinc (Zn), and the measurement of the total protein content (TP). After detailed statistical analysis, the results showed that saliva could replace serum for APP measurements since a good agreement has been observed between the concentrations of APPs in both body fluids. For any other biomarker, no agreement between the concentrations quantified in serum and saliva samples was observed visually. However, salivary ADA and TP concentrations were statistically significantly higher in the diseased, whereas the statistical tests with serum concentrations were inconclusive. Furthermore, greater differentiation between healthy and diseased animals could be observed when the distribution of biomarkers was analysed in saliva than in other serum samples. The diagnostic power to discriminate between healthy and diseased pigs is similar in saliva and in serum samples. Preliminary regression models may offer an optimal combination of biomarkers for disease detection in saliva (Hp, CRP, and TAC) and serum (Hp, CRP, and Cu), which demands less labour, sample, and financial cost for saliva determinations. The contradictory results observed for TAC, Cu, and Zn levels between body fluids indicate a need for further studies. To sum up, saliva-based biomarkers instead of serum-based biomarkers could contribute to more efficient detection of diseased animals.

Connectivity Analysis for Multivariate Time Series: Correlation vs. Causality

The study of the interdependence relationships of the variables of an examined system is of great importance and remains a challenging task. There are two distinct cases of interdependence. In the first case, the variables evolve in synchrony, connections are undirected and the connectivity is examined based on symmetric measures, such as correlation. In the second case, a variable drives another one and they are connected with a causal relationship. Therefore, directed connections entail the determination of the interrelationships based on causality measures. The main open question that arises is the following: can symmetric correlation measures or directional causality measures be applied to infer the connectivity network of an examined system? Using simulations, we demonstrate the performance of different connectivity measures in case of contemporaneous or/and temporal dependencies. Results suggest the sensitivity of correlation measures when temporal dependencies exist in the data. On the other hand, causality measures do not spuriously indicate causal effects when data present only contemporaneous dependencies. Finally, the necessity of introducing effective instantaneous causality measures is highlighted since they are able to handle both contemporaneous and causal effects at the same time. Results based on instantaneous causality measures are promising; however, further investigation is required in order to achieve an overall satisfactory performance.

Optimization of Flow-Cytometry Based Assay for Measuring Neutralizing Antibody Responses against Each of the Four Dengue Virus Serotypes

Dengue is an important public health problem worldwide, with India contributing nearly a third of global dengue disease burden. The measurement of neutralizing antibody responses is critical for understanding dengue pathophysiology, vaccine development and evaluation. Historically, dengue virus neutralization titers were measured using plaque reduction neutralization tests (PRNTs), which were later adapted to focus reduction neutralization tests (FRNTs). Given the slow and laborious nature of both these assays, there has been interest in adapting a high-throughput flow cytometry based neutralization assay. However, flow cytometry based assays typically underestimate neutralization titers, and in situations where the titers are low they can even fail to detect neutralization activity. In this study, by evaluating graded numbers of input Vero cell numbers and viral inoculum, we optimized the flow cytometry based neutralization assay in such a way that it is sensitive and scores titers that are in concordance with focus reduction neutralization tests for each of the four dengue virus serotypes (p < 0.0001). Given that dengue is a global public health concern, and several research groups are making efforts to understand its pathophysiology and accelerate vaccine development and evaluation both in India and worldwide, our findings have timely significance for facilitating these efforts.

The network interplay of interferon and Toll-like receptor signaling pathways in the anti-Candida immune response

Fungal infections represent a major global health problem affecting over a billion people that kills more than 1.5 million annually. In this study, we employed an integrative approach to reveal the landscape of the human immune responses to Candida spp. through meta-analysis of microarray, bulk, and single-cell RNA sequencing (scRNA-seq) data for the blood transcriptome. We identified across these different studies a consistent interconnected network interplay of signaling molecules involved in both Toll-like receptor (TLR) and interferon (IFN) signaling cascades that is activated in response to different Candida species (C. albicans, C. auris, C. glabrata, C. parapsilosis, and C. tropicalis). Among these molecules are several types I IFN, indicating an overlap with antiviral immune responses. scRNA-seq data confirmed that genes commonly identified by the three transcriptomic methods show cell type-specific expression patterns in various innate and adaptive immune cells. These findings shed new light on the anti-Candida immune response, providing putative molecular pathways for therapeutic intervention.

Analyzing Particularities of Sensor Datasets for Supporting Data Understanding and Preparation

Data scientists spend much time with data cleaning tasks, and this is especially important when dealing with data gathered from sensors, as finding failures is not unusual (there is an abundance of research on anomaly detection in sensor data). This work analyzes several aspects of the data generated by different sensor types to understand particularities in the data, linking them with existing data mining methodologies. Using data from different sources, this work analyzes how the type of sensor used and its measurement units have an important impact in basic statistics such as variance and mean, because of the statistical distributions of the datasets. The work also analyzes the behavior of outliers, how to detect them, and how they affect the equivalence of sensors, as equivalence is used in many solutions for identifying anomalies. Based on the previous results, the article presents guidance on how to deal with data coming from sensors, in order to understand the characteristics of sensor datasets, and proposes a parallelized implementation. Finally, the article shows that the proposed decision-making processes work well with a new type of sensor and that parallelizing with several cores enables calculations to be executed up to four times faster.