Analysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learning

Standing and lying are the fundamental behaviours of quadrupedal animals, and the ratio of their durations is a significant indicator of calf health. In this study, we proposed a computer vision method for non-invasively monitoring of calves' behaviours. Cameras were deployed at four viewpoints to monitor six calves on six consecutive days. YOLOv8n was trained to detect standing and lying calves. Daily behavioural budget was then summarised and analysed based on automatic inference on untrained data. The results show a mean average precision of 0.995 and an average inference speed of 333 frames per second. The maximum error in the estimated daily standing and lying time for a total of 8 calf-days is less than 14 min. Calves with diarrhoea had about 2 h more daily lying time (p < 0.002), 2.65 more daily lying bouts (p < 0.049), and 4.3 min less daily lying bout duration (p = 0.5) compared to healthy calves. The proposed method can help in understanding calves' health status based on automatically measured standing and lying time, thereby improving their welfare and management on the farm.

Improving the health status of Afghan mothers living in the Islamic Republic of Iran

Background

The healthcare system of the Islamic Republic of Iran provides special maternal health care services for mothers, regardless of their nationality.

Aim

This study, supported by the United Nations Population Fund, was conducted to review available data associated with health indicators of Afghan mothers living in Islamic Republic of Iran.

Methods

This descriptive study used data from the electronic registration system of the Maternal Health Office of the Ministry of Health and Medical Education on characteristics, morbidity and mortality among Afghan mothers in the Islamic Republic of Iran from 2017 to 2019. The data were analysed using SPSS version 23.0. Based on the results, we propose interventions to improve health services for vulnerable Afghan mothers.

Results

There were 168 488 deliveries over the 3 years of the study (2017-2019). Deliveries by Afghan women increased from 3.4% in 2017 to 5.2% in 2019, and more than 70% of these Afghan women were vulnerable. Ten percent of deliveries among Afghan mothers were performed by traditional birth attendants. The rate of caesarean section among Afghan mothers was 30%. Maternal mortality ratio among the Afghan mothers was 43 per 100 000 for the 3 years.

Conclusion

Afghan mothers in the Islamic Republic of Iran use primary health care services provided for mothers in the country. However, healthcare delivery to these mothers is inadequate, although considered better than the care provided to Afghan mothers living in Afghanistan. We recommend targeted interventions to improve the health status of Afghan women living in the Islamic Republic of Iran.

A GIS-based approach to identifying communities underserved by primary health care services-An Afghanistan case study

Afghanistan has been in an active state of conflict and war for twenty continuous years. Social services like health and education have been badly affected, facing issues such as service disruption, brain drain, and generalized instability. Health indices that provide proxy indicators for general population wellness, such as maternal health, child mortality, and immunization coverage, show that the health services available to the Afghan population are sub-optimal. Investment in social service and interventions has increased. The World Bank and the United Nations through its agencies (The World Health Organization (WHO) and United Nations' Children's Fund (UNICEF) are providing social support through targeted and strategic programs. However, the topographic and environmental realities of Afghanistan, with its broad mountain coverage, propensity toward natural disasters, and latent conflict, has made data and information gathering arduous. Since data is essential for measurement and management, the WHO Health Emergencies (WHE) information management unit at WHO Afghanistan has delivered an innovative form of data analysis, specialized and targeted at providing improved information on communities that are not adequately covered by health services. Deploying a geographical information system (GIS) approach, the WHE team has collated primary and secondary data from a combination of datasets to produce a far-reaching piece of analysis. The analysis of underserved communities in hard to reach, remote locations, provides a live, evidence-based information product. This provides a working tool that is essential to primary health programming and intervention in Afghanistan. The estimates show that approximately 9.5 million individuals in 22,181 villages across 34 provinces are underserved by primary health services. This paper is presented to explain the underpinning methodology.

Degradation-Sensitive Health Indicator Construction for Precise Insulation Degradation Monitoring of Electromagnetic Coils

Electromagnetic coils are indispensable components for energy conversion and transformation in various systems across industries. However, electromagnetic coil insulation failure occurs frequently, which can lead to serious consequences. To facilitate predictive maintenance for industrial systems, it is essential to monitor insulation degradation prior to the formation of turn-to-turn shorts. This paper experimentally investigates coil insulation degradation from both macro and micro perspectives. At the macro level, an evaluation index based on a weighted linear combination of trend, monotonicity and robustness is proposed to construct a degradation-sensitive health indicator (DSHI) based on high-frequency electrical response parameters for precise insulation degradation monitoring. While at the micro level, a coil finite element analysis and twisted pair accelerated degradation test are conducted to obtain the actual turn-to-turn insulation status. The correlation analysis between macroscopic and microscopic effects of insulation degradation is used to verify the proposed DSHI-based method. Further, it helps to determine the threshold of DSHI. This breakthrough opens new possibilities for predictive maintenance for industrial equipment that incorporates coils.

An Unsupervised Machine Learning Approach for Monitoring Data Fusion and Health Indicator Construction

The prediction of system degradation is very important as it serves as an important basis for the formulation of condition-based maintenance strategies. An effective health indicator (HI) plays a key role in the prediction of system degradation as it enables vital information for critical tasks ranging from fault diagnosis to remaining useful life prediction. To address this issue, a method for monitoring data fusion and health indicator construction based on an autoencoder (AE) and a long short-term memory (LSTM) network is proposed in this study to improve the predictability and effectiveness of health indicators. Firstly, an unsupervised method and overall framework for HI construction is built based on a deep autoencoder and an LSTM neural network. The neural network is trained fully based on the normal operating monitoring data and then the construction error of the AE model is adopted as the health indicator of the system. Secondly, we propose related machine learning techniques for monitoring data processing to overcome the issue of data fusion, such as mutual information for sensor selection and t-distributed stochastic neighbor embedding (T-SNE) for operating condition identification. Thirdly, in order to verify the performance of the proposed method, experiments are conducted based on the CMAPSS dataset and results are compared with algorithms of principal component analysis (PCA) and a vanilla autoencoder model. Result shows that the LSTM-AE model outperforms the PCA and Vanilla-AE model in the metrics of monotonicity, trendability, prognosability, and fitness. Fourthly, in order to analyze the impact of the time step of the LSMT-AE model on HI construction, we construct and analyze the system HI curve under different time steps of 5, 10, 15, 20, and 25 cycles. Finally, the results demonstrate that the proposed method for HI construction can effectively characterize the health state of a system, which is helpful for the development of further failure prognostics and converting the scheduled maintenance into condition-based maintenance.

Core health indicators in countries with high proportion of expatriates: Case study of Qatar

Background

Population size and structure have a huge impact on health indicators. In countries with a high proportion of expatriates, there are some limitations in estimating, aggregating and reporting of the health indicators, and corrections may be required in the established estimation methodologies. We review the case of Qatar to see how its specific population characteristics affect its health indicators.

Methods

We used routinely collected data and reviewed and calculated a selected list of health indicators for Qatari and non-Qatari populations residing in Qatar. Mortality and cancer incidence rates, stratified by nationality, were used for this purpose. Also, a direct method was used to estimate completeness of the death registry, compared to the mortuary data.

Results

Age and sex distribution of Qatari and non-Qatari populations are completely different. Compared to the mortuary data, completeness of death registration for the total population was estimated at 98.9 and 94.3%, with and without considering overseas deaths, respectively. Both estimates were considerably higher than estimates from the indirect methods. Mortality patterns were different even after standardization of age and stratification of sex groups; male age-standardized mortality rates were 502.7 and 242.3 per 100,000 individuals, respectively for Qataris and non-Qataris. The rates were closer in female populations (315.6 and 291.5, respectively). The leading types of cancer incidents were different in Qataris and non-Qataris.

Conclusions

Expatriates are a dynamic population with high-turnover, different from Qatari population in their age-sex structure and health status. They are more likely to be young or middle-aged and are less affected by age related diseases and cancers. Also, they might be at higher risks for specific diseases or injuries. Aggregating indicators of Qatari and non-Qatari populations might be mis-leading for policy making purposes, and common estimation correction approaches cannot alleviate the limitations. High-proportion of expatriate population also imposes significant errors to some of the key demographic estimates (such as completeness of death registry). We recommend a standardized approach to consider nationality in addition to age and sex distributions for analysis of health data in countries with a high proportion of expatriates.

Predicting Smoking Prevalence in Japan Using Search Volumes in an Internet Search Engine: Infodemiology Study

BACKGROUND

Tobacco smoking is an important public health issue and a core indicator of public health policy worldwide. However, global pandemics and natural disasters have prevented surveys from being conducted.

OBJECTIVE

The purpose of this study was to predict smoking prevalence by prefecture and sex in Japan using Internet search trends.

METHODS

This study used the infodemiology approach. The outcome variable was smoking prevalence by prefecture, obtained from national surveys. The predictor variables were the search volumes on Yahoo! Japan Search. We collected the search volumes for queries related to terms from the thesaurus of the Japanese medical article database Ichu-shi. Predictor variables were converted to per capita values and standardized as z scores. For smoking prevalence, the values for 2016 and 2019 were used, and for search volume, the values for the April 1 to March 31 fiscal year (FY) 1 year prior to the survey (ie, FY 2015 and FY 2018) were used. Partial correlation coefficients, adjusted for data year, were calculated between smoking prevalence and search volume, and a regression analysis using a generalized linear mixed model with random effects was conducted for each prefecture. Several models were tested, including a model that included all search queries, a variable reduction method, and one that excluded cigarette product names. The best model was selected with the Akaike information criterion corrected (AICC) for small sample size and the Bayesian information criterion (BIC). We compared the predicted and actual smoking prevalence in 2016 and 2019 based on the best model and predicted the smoking prevalence in 2022.

RESULTS

The partial correlation coefficients for men showed that 9 search queries had significant correlations with smoking prevalence, including cigarette (r=-0.417, P<.001), cigar in kanji (r=-0.412, P<.001), and cigar in katakana (r=-0.399, P<.001). For women, five search queries had significant correlations, including vape (r=0.335, P=.001), quitting smoking (r=0.288, P=.005), and cigar (r=0.286, P=.006). The models with all search queries were the best models for both AICC and BIC scores. Scatter plots of actual and estimated smoking prevalence in 2016 and 2019 confirmed a relatively high degree of agreement. The average estimated smoking prevalence in 2022 in the 47 prefectures for the total sample was 23.492% (95% CI 21.617%-25.367%), showing an increasing trend, with an average of 29.024% (95% CI 27.218%-30.830%) for men and 8.793% (95% CI 7.531%-10.054%) for women.

CONCLUSIONS

This study suggests that the search volume of tobacco-related queries in internet search engines can predict smoking prevalence by prefecture and sex in Japan. These findings will enable the development of low-cost, timely, and crisis-resistant health indicators that will enable the evaluation of health measures and contribute to improved public health.

Long Short-Term Memory Neural Network with Transfer Learning and Ensemble Learning for Remaining Useful Life Prediction

Prediction of remaining useful life (RUL) is greatly significant for improving the safety and reliability of manufacturing equipment. However, in real industry, it is difficult for RUL prediction models trained on a small sample of faults to obtain satisfactory accuracy. To overcome this drawback, this paper presents a long short-term memory (LSTM) neural network with transfer learning and ensemble learning and combines it with an unsupervised health indicator (HI) construction method for remaining-useful-life prediction. This study consists of the following parts: (1) utilizing the characteristics of deep belief networks and self-organizing map networks to translate raw sensor data to a synthetic HI that can effectively reflect system health; and (2) introducing transfer learning and ensemble learning to provide the required degradation mechanism for the RUL prediction model based on LSTM to improve the performance of the model. The performance of the proposed method is verified by two bearing datasets collected from experimental data, and the results show that the proposed method obtains better performance than comparable methods.

A Deep-Learning-Based Health Indicator Constructor Using Kullback-Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures

This paper proposes a new technique for the construction of a concrete-beam health indicator based on the Kullback-Leibler divergence (KLD) and deep learning. Health indicator (HI) construction is a vital part of remaining useful lifetime (RUL) approaches for monitoring the health of concrete structures. Through the construction of a HI, the deterioration process can be processed and portrayed so that it can be forwarded to a prediction module for RUL prognosis. The degradation progression and failure can be identified by predicting the RUL based on the situation of the current specimen; as a result, maintenance can be planned to reduce safety risks, reduce financial costs, and prolong the specimen's useful lifetime. The portrayal of deterioration through HI construction from raw acoustic emission (AE) data is performed using a deep neural network (DNN), whose parameters are obtained by pretraining and fine tuning using a stack autoencoder (SAE). Kullback-Leibler divergence, which is calculated between a reference normal-conditioned signal and a current unknown signal, was used to represent the deterioration process of concrete structures, which has not been investigated for the concrete beams so far. The DNN-based constructor then learns to generate HI from raw data with KLD values as the training label. The HI construction result was evaluated with run-to-fail test data of concrete specimens with two measurements: fitness analysis of the construction result and RUL prognosis. The results confirm the reliability of KLD in portraying the deterioration process, showing a large improvement in comparison to other methods. In addition, this method requires no adept knowledge of the nature of the AE or the system fault, which is more favorable than model-based approaches where this level of expertise is compulsory. Furthermore, AE offers in-service monitoring, allowing the RUL prognosis task to be performed without disrupting the specimen's work.

IR-Based Novel Device for Real-Time Online Acquisition of Fish Heart ECG Signals

We developed an infrared (IR)-based real-time online monitoring device (US Patent No: US 10,571,448 B2) to quantify heart electrocardiogram (ECG) signals to assess the water quality based on physiological changes in fish. The device is compact, allowing us to monitor cardiac function for an extended period (from 7 to 30 days depending on the rechargeable battery capacity) without function injury and disturbance of swimming activity. The electrode samples and the biopotential amplifier and microcontroller process the cardiac-electrical signals. An infrared transceiver transmits denoised electrocardiac signals to complete the signal transmission. The infrared receiver array and biomedical acquisition signal processing system send signals to the computer. The software in the computer processes the data in real time. We quantified ECG indexes (P-wave, Q-wave, R-wave, S-wave, T-wave, PR-interval, QRS-complex, and QT-interval) of carp precisely and incessantly under the different experimental setup (CuSO₄ and deltamethrin). The ECG cue responses were chemical-specific based on CuSO₄ and deltamethrin exposures. This study provides an additional technology for noninvasive water quality surveillance.

Assessment of the Methodology That Is Used to Determine the Nutritional Sustainability of the Mediterranean Diet-A Scoping Review

Mediterranean diet (MedDiet) is often used as an example of a sustainable diet that promotes a sustainable food system. MedDiet presents low environmental impacts, is characterized by high sociocultural food values, allows for positive local economic returns, and presents major health and nutrition benefits. Previous studies have not systematically examined the methodological assessment of MedDiet nutritional sustainability. In our study, we review the methodological assessment of nutritional sustainability, filling a crucial gap in the literature that can inform the state of the art regarding the cross-disciplinary assessment of MedDiet nutritional sustainability. Through a systematic search on PubMed and Scopus, we identified 28 studies, published between 2013 and 2021, that dealt with the MedDiet nutritional sustainability. Studies that assessed the sustainability of MedDiet based on dietary consumption data, studies that explored the MedDiet sustainability resorting to dietary scenarios, and studies with a mixed approach (dietary consumption and dietary scenarios) and proposals of methodological approaches to assess the MedDiet nutritional sustainability were summarized. We identified 24 studies exploring the dimensions of nutritional sustainability of the MedDiet, and 4 proposing the methodological approaches to assess the MedDiet nutritional sustainability or the sustainability of MedDiet typical agro-foods. From the 24 studies exploring the sustainability of MedDiet, none fully addressed the complexity of the four dimensions of nutritional sustainability (environmental, economic, socio-cultural, and health-nutrition). One of the methodological proposals to assess the MedDiet nutritional sustainability contemplated on the four dimensions of nutritional sustainability, as well as one of the methodological proposals to assess the sustainability of typical agro-foods of MedDiet. Environmental sustainability was the most well-studied dimension, while no study focuses on the socio-cultural dimension of sustainability. Our study reviewed for the first time the assessment of nutritional sustainability of MedDiet. To the best of our knowledge, no research has been made assessing MedDiet in all the dimensions of the complex concept, that is nutritional sustainability. Integrating health and nutrition, environmental, economic, and socio-cultural considerations across scales and contexts can offer a more complete understanding of the opportunities and barriers to achieving nutritional sustainability not only in MedDiet but also in other dietary patterns and food products.

[The characteristics of medical demographic indices in the Jewish autonomous oblast]

The research in the field of regional trends and risk factors related to population morbidity is considered as background of management decision-making in health care. The article presents the results of analysis of medical demographic indices and population health status in the Jewish Autonomous Oblast in 2000-2019. It is established that in in the Jewish Autonomous Oblast population size reduced by 35 100 people to 2019. The negative migration dispositions facilitate losses of population size from 0.5% to 1.23% annually. The gradual increase of number of the elderly brought to ratio working/non-working people 100 to 128. The infant mortality rate decreased from 20.2 in 2000 to 9.2 per 1000 newborns in 2019 and continues to decrease. The total morbidity increase (diagnosed for the first time) of cardiovascular diseases and neoplasms is probably related to preventive measures efficiency. In the structure of malignant neoplasms leading positions are taken by tumors of bronchopulmonary system, skin affections and breast cancer. In the Jewish Autonomous Oblast, mortality of cardiovascular diseases comprised 807.32±22.87 per 100 000 of population. In the last decade, this most important indicator decreased up to 2.12%. The mortality of malignant neoplasms made up to 217.31±15.25 per 100 000 of population. The mortality due to consolidated causes "Traumas, poisonings and some other consequences of external causes exposure" made up to 16.19±3.28 per 100 000 of population. In 2019, the average life interval made up to 68.8 years, having increased by 6.2 years since 2000. The evaluation of medical demographic indices and population health status demonstrate necessity of adjusting medical organizational measures targeting to improve medical care of population considering regional characteristics.

The Validation of a Non-Invasive Skin Sampling Device for Detecting Cetacean Poxvirus

Simple Summary

The current growing social awareness of animal welfare has led to the development of welfare indicators, which are effective tools for assessing each of the integrated aspects of this multidisciplinary issue. Hence, skin diseases have been suggested as potential general health indicators for use in cetaceans. Particularly cetacean poxvirus causes distinguishable hyperpigmented “ring” or “tattoo” lesions that affect cetaceans both in the wild and in managed facilities. However, most studies have analyzed these characteristic lesions through visual appraisal, while only a few have implemented diagnostic methods to corroborate the presence of the virus. To this end, skin biopsies are usually the sampling method selected, although they are considered to be an intrusive procedure. In this study, we analyzed sloughed skin sampled with cytology cell samplers (CCSs) in 12 tattoo-like lesions from two free-ranging cetaceans stranded in the Canary Islands. We employed two different DNA extraction methods and compared the effectiveness of the device with that of biopsies. All the lesions resulted positive for cetacean poxvirus, obtaining reliable data from the use of this device. Thus, CCS is considered to be a promising non-invasive tool for further assessing skin diseases in cetaceans, particularly those under human care, without affecting their welfare.

Abstract

Poxvirus-like lesions are widely used as a potential health indicator in cetaceans, although for this application, corroboration of Poxvirus skin disease is imperative. Aiming to address skin biopsies intrusiveness, a preliminary investigation of a non-invasive skin sampling procedure to molecularly detect CePV-1 in 12 tattoo-like-lesions from two free-ranging stranded cetaceans in the Canary Islands was performed. Skin lesions were brushed with cytology cell samplers (CCSs) and placed into 1.5 mL microcentrifuge tubes with 1 mL of RNAlater^TM Stabilization Solution. For factual comparisons, DNA extractions from sloughed skin obtained with CCS and biopsies from the same lesions were accomplished with DNA Tissue Kit S^TM (QuickGene, Kurabo, Japan). Moreover, a second DNA extraction from sloughed skin with DNeasy^TM Blood and Tissue Kit (Qiagen, Inc., Valencia, CA, USA) was performed to ascertain kit suitability for CCS. Molecular detection of CePV-1 was performed through a real-time PCR. As a result, a 91.7% and 83.3% rates of positivity were obtained with biopsies and CCS through Quickgene, respectively, compared to the rate of 100% using CCS with Qiagen. Accordingly, CCS is a reliable non-invasive sampling device to obtain sufficient genetic material to be analyzed for CePV-1 in tattoo-skin-lesions as well as for other purposes in cetaceans under human care.

Intelligent Online Monitoring of Rolling Bearing: Diagnosis and Prognosis

This paper suggests a new method to predict the Remaining Useful Life (RUL) of rolling bearings based on Long Short Term Memory (LSTM), in order to obtain the degradation condition of the rolling bearings and realize the predictive maintenance. The approach is divided into three parts: the first part is the clustering to detect the damage state by the density-based spatial clustering of applications with noise. The second one is the health indicator construction which could give a better reflection of the bearing degradation tendency and is selected as the input for the prediction model. In the third part of the RUL prediction, the LSTM approach is employed to improve the accuracy of the prediction. The rationale of this work is to combine the two methods-the density-based spatial clustering of applications with noise and LSTM-to identify the abnormal state in rolling bearings, then estimate the RUL. The suggested method is confirmed by experimental data of bearing life cycle, and the RUL prediction results of the model LSTM are compared with the nonlinear au-regressive model with exogenous input model. In addition, the constructed health indicator is compared with the spectral kurtosis feature. The results demonstrated that the suggested method is more appropriate than the nonlinear au-regressive model with exogenous input model for the prediction of bearing RUL.

Effects of the 2018 heat wave on health in the elderly: implications for adaptation strategies to climate change

There has been growing concern over the effects of heat waves on health. However, the effects of heat waves on the health of individuals in vulnerable groups have rarely been examined. We aimed to investigate the acute health effects of heat waves in elderly individuals living in rural areas and to survey their adaptation capacity. Repeated measurements of body temperature (BT), blood pressure, sleep disturbance, and indoor temperature were conducted up to six times for each of 104 elderly individuals living in rural areas of South Korea during the 2018 heat wave. Changes in BT, systolic blood pressure (SBP), and diastolic blood pressure (DBP) according to variations in indoor and outdoor temperature were analyzed using linear mixed effect models controlling for age, sex, smoking, and drug use. We also surveyed heat wave adaptation capacity, heat wave shelters, and self-reported health problems. The average indoor temperature measured during the study period was 30.5°C (range: 22.9-38.3°C) and that of ambient temperature was 30.6°C (range: 24.6-36.3°C). BT significantly increased with indoor and outdoor temperatures. The effect on BT was greater in elderly women and the elderly with hypertension. DBP generally decreased with increasing indoor temperature, though the correlation was only statistically significant among the elderly with hypertension. Only 22 (21.2%) individuals used air conditioners during the heat wave. Most did not use an air conditioner mainly to avoid high electricity costs. Of the participants, 58.7% reported experiencing sleep disturbance, which was the most frequent self-reported health problem. Elderly individuals living in rural areas are directly exposed to high temperatures during heat waves, and their vital signs are sensitive to increases in indoor temperature due to poor adaptation capacity. Well-designed strategies for alleviating health-related stress during heat waves are necessary.

Lifestyle Acquired Immunity, Decentralized Intelligent Infrastructures, and Revised Healthcare Expenditures May Limit Pandemic Catastrophe: A Lesson From COVID-19

Throughout history, the human race has often faced pandemics with substantial numbers of fatalities. As the COVID-19 pandemic has now affected the whole planet, even countries with moderate to strong healthcare support and expenditure have struggled to contain disease transmission and casualties. Countries affected by COVID-19 have different demographics, socioeconomic, and lifestyle health indicators. In this context, it is important to find out to what extent these parametric variations are modulating disease outcomes. To answer this, this study selected demographic, socioeconomic, and health indicators e.g., population density, percentage of the urban population, median age, health expenditure per capita, obesity, diabetes prevalence, alcohol intake, tobacco use, case fatality of non-communicable diseases (NCDs) as independent variables. Countries were grouped according to these variables and influence on dependent variables e.g., COVID-19 positive tests, case fatality, and case recovery rates were statistically analyzed. The results suggested that countries with variable median age had a significantly different outcome on positive test rate (P < 0.01). Both the median age (P = 0.0397) and health expenditure per capita (P = 0.0041) showed a positive relation with case recovery. An increasing number of tests per 100 K of the population showed a positive and negative relationship with the number of positives per 100 K population (P = 0.0001) and the percentage of positive tests (P < 0.0001), respectively. Alcohol intake per capita in liter (P = 0.0046), diabetes prevalence (P = 0.0389), and NCDs mortalities (P = 0.0477) also showed a statistical relation to the case fatality rate. Further analysis revealed that countries with high healthcare expenditure along with high median age and increased urban population showed more case fatality but also had a better recovery rate. Investment in the health sector alone is insufficient in controlling the severity of the pandemic. Intelligent and sustainable healthcare both in urban and rural settings and healthy lifestyle acquired immunity may reduce disease transmission and comorbidity induced fatalities, respectively.

Effects of dietary incorporation of linseed oil with soybean isoflavone on fatty acid profiles and lipid metabolism-related gene expression in breast muscle of chickens

The meat quality of chicken is an important factor affecting the consumer's health. It was hypothesized that n-3 polyunsaturated fatty acid (n-3 PUFA) could be effectively deposited in chicken, by incorporating antioxidation of soybean isoflavone (SI), which led to improved quality of chicken meat for good health of human beings. Effects of partial or complete dietary substitution of lard (LA) with linseed oil (LO), with or without SI on growth performance, biochemical indicators, meat quality, fatty acid profiles, lipid-related health indicators and gene expression of breast muscle were examined in chickens. A total of 900 males were fed a corn-soybean meal diet supplemented with 4% LA, 2% LA + 2% LO and 4% LO and the latter two including 30 mg SI/kg (2% LA + 2% LO + SI and 4% LO + SI) from 29 to 66 days of age; each of the five dietary treatments included six replicates of 30 birds. Compared with the 4% LA diet, dietary 4% LO significantly increased the feed efficiency and had no negative effect on objective indices related to meat quality; LO significantly decreased plasma triglycerides and total cholesterol (TCH); abdominal fat percentage was significantly decreased in birds fed the 4% LO and 4% LO + SI diets. Chickens with LO diets resulted in higher contents of α-linolenic acid (C18:3n-3), EPA (C20:5n-3) and total n-3 PUFA, together with a lower content of palmitic acid (C16:0), lignoceric acid (C24:0), saturated fatty acids and n-6:n-3 ratio in breast muscle compared to 4% LA diet (P < 0.05); they also significantly decreased atherogenic index, thrombogenic index and increased the hypocholesterolemic to hypercholesterolemic ratio. Adding SI to the LO diets enhanced the contents of EPA and DHA (C22:6n-3), plasma total superoxide dismutase, reduced glutathione (GSH)/oxidized glutathione and muscle GSH content, while decreased plasma total triglyceride and TCH and malondialdehyde content in plasma and breast muscle compared to its absence (P < 0.05). Expression in breast muscle of fatty acid desaturase 1 (FADS1), FADS2, elongase 2 (ELOVL2) and ELOVL5 genes were significantly higher with the LO diets including SI than with the 4% LA diet. Significant interactions existed between LO level and inclusion of SI on EPA and TCH contents. These findings indicate that diet supplemented with LO combined with SI is an effective alternative when optimizing the nutritional value of chicken meat for human consumers.

Assessing the utility of leukocyte differential cell counts for predicting morbidity, mortality, and growth in a grain-fed veal facility: A prospective single cohort study

Selective antimicrobial treatment strategies present a means to reduce antimicrobial use at the time of arrival at a veal or dairy beef operation. On-farm machine leukocyte differential cell counts (DCC) that can be acquired quickly may be useful to augment calf risk identification protocols. The objective of this study was to assess the utility of DCC taken at the time of arrival at a grain-fed veal facility and 72 h postarrival for determining morbidity risk, mortality risk, and growth during the production cycle. Data were collected between June and October 2018 from 240 calves upon arrival and from a subset of 160 calves 72 h postarrival at a commercial grain-fed veal facility in Ontario, Canada. Blood samples were evaluated using the QScout BLD test for leukocyte DCC (Advanced Animal Diagnostic, Morrisville, NC). All calves were screened using a standardized health examination, and a blood sample was collected to evaluate serum total protein and DCC. Cox proportional hazards models were constructed for both morbidity and mortality outcomes. Mixed linear regression models were constructed to evaluate average daily gain. Results from data collected at the time of arrival suggest that total protein values ≥5.2 g/dL reduced the hazard of mortality and that a rectal temperature >39.6°C was associated with an increased hazard of morbidity. Calves that were dehydrated gained less, whereas calves with an increased lymphocyte count had a higher rate of growth. Results from DCC collected 72 h postarrival suggest that lymphocyte counts between 4.8 and 5.8 × 10⁹ cells/L decreased the hazard of mortality and counts >7.0 × 10⁹ cells/L decreased the hazard of morbidity, whereas neutrophil counts >6.0 × 10⁹ cells/L increased the hazard of mortality. This study demonstrates that machine DCC at the time of arrival and 72 h after arrival has potential for use in identifying high-risk calves that might require treatment, as part of selective antimicrobial therapy protocols, with the purpose of reducing antimicrobial use without sacrificing animal health in veal facilities.

Validation of an automated cell counter to determine leukocyte differential counts in neonatal Holstein calves

Recent advances in the understanding of risk factors and biomarkers in calves entering rearing facilities show promise for identifying high-risk calves on arrival at veal and dairy beef operations. Rapid automated leukocyte differential cell counts may be a good addition for augmenting or refining calf risk identification on-farm. The objective of this study was to validate an automated leukocyte cell counter, the QScout BLD test (Advanced Animal Diagnostics, Morrisville, NC), for its ability to determine leukocyte differential cell counts in neonatal Holstein calves. From June to July 2018, blood samples collected in EDTA anticoagulant from 235 calves upon arrival at an independent veal research facility in Ontario, Canada, were evaluated using the QScout BLD test and manually by microscopy. We compared these leukocyte differential counts using Lin's concordance correlation coefficient (ρ) and found very good agreement between tests for neutrophil counts (ρ = 0.83); fair agreement for lymphocyte counts (ρ = 0.32); fair agreement for the ratio of neutrophils to lymphocytes (ρ = 0.36); slight agreement for monocyte counts (ρ = 0.14); and slight agreement for eosinophil counts (ρ = 0.20). We further examined test results to determine if they differed in their classification of samples as being above, within, or below reported 95% reference intervals for neonatal Holstein calves. Classification between tests resulted in very good agreement for neutrophils and lymphocytes, with only 4.2% and 5.8% disagreement in classification, respectively. We observed moderate agreement for monocytes, with 23.3% classified differently, and poor agreement for eosinophils, with 70.3% classified differently. Further study is required to determine the role of leukocyte profiling in the risk assessment of calves arriving at calf-rearing facilities.

Enhancing Sustainability in Healthcare Delivery-A Challenge to the New Malaysia

There have been substantial improvements in the health indicators since Malaysia achieved independence. These were accomplished through strong primary healthcare services addressing maternal and paediatric health, as well as the successful control of communicable diseases. The rate of decline in the mortality statistics has been at a virtual standstill, or at best, almost plateaued since 2000. However, with the plethora of national health issues at both the policy and delivery levels, we cannot continue on with ‘business as usual’. Therefore, we must strategise effective and practical approaches to a renewed and revamped national healthcare services for a modern ‘New Malaysia’ that are compatible with our quest toward the status of a ‘truly developed’ nation.

A Reliable Health Indicator for Fault Prognosis of Bearings

Estimation of the remaining useful life (RUL) of bearings is important to avoid abrupt shutdowns in rotary machines. An important task in RUL estimation is the construction of a suitable health indicator (HI) to infer the bearing condition. Conventional health indicators rely on features of the vibration acceleration signal and are predominantly calculated without considering its non-stationary nature. This often results in an HI with a trend that is difficult to model, as well as random fluctuations and poor correlation with bearing degradation. Therefore, this paper presents a method for constructing a bearing’s HI by considering the non-stationarity of the vibration acceleration signals. The proposed method employs the discrete wavelet packet transform (DWPT) to decompose the raw signal into different sub-bands. The HI is extracted from each sub-band signal, smoothened using locally weighted regression, and evaluated using a gradient-based method. The HIs showing the best trends among all the sub-bands are iteratively accumulated to construct an HI with the best trend over the entire life of the bearing. The proposed method is tested on two benchmark bearing datasets. The results show that the proposed method yields an HI that correlates well with bearing degradation and is relatively easy to model.

Doing it hard in the bush: Aligning what gets measured with what matters

What gets measured gets managed. Funding of health services is substantially determined by operational activity and specific outcome indicators. In day-to-day clinical decision-making, surrogate markers, such as glycosylated haemoglobin and blood pressure, are commonly used to modify risks of 'hard' outcomes that include kidney failure, ischaemic cardiac events, stroke and all-cause mortality. In many settings, surrogates are all we have to go on. As a consequence, current health funding models heavily rely on surrogate-based key performance indicators [KPIs]. While surrogates are convenient and provide immediate information, there is an obligation to ensure that they are appropriate, reliable and validated in context. In contrast, hard outcomes, the real consequences of illness, are usually realised over an extended timeframe. Additionally, and for a host of reasons, hard endpoints have the greatest social, emotional and economic impact for people at the far end of the health system; those in rural and remote settings - 'in the bush' - especially Indigenous Australians. We propose a health service assessment approach that aligns short-term decision-making with patient-centred and longer term hard outcomes, one that takes into account community, cultural and environmental factors, especially remoteness. Communities should have a major say in determining what health indicators are measured and managed.

Proximate causes of the red face of the bald uakari monkey (Cacajao calvus)

In social species, such as primates, facial appearances transmit a variety of social signals. Although it is suggested that the intense red colour of the face of the bald uakari monkey might be an indicator of health, this hypothesis still has not been verified. This study describes the histological structure of the skin of the face in the bald uakari, compared with other non-red neotropical primates, to better understand the maintenance of its colour. The facial skin of the bald uakari monkey is characterized by a thinner epidermis, absence of melanin pigments and a high density of vascular capillaries that spread below the epidermis. These vascular capillaries are larger and more tortuous than in other neotropical primates. The skin of the face of the bald uakari monkey allows a direct external assessment of haematological status, suggesting that the colour of the face would be an honest indicator of health, but could also signal sexual or behavioural states.

Health inequalities associated with neighbourhood deprivation in the Quebec population with hypertension in primary prevention of cardiovascular disease

INTRODUCTION

Although a number of studies look at prevalence, incidence, treatment, mortality and morbidity in relation to hypertension, few have taken into account the effect of residential neighbourhood on these health indicators in the population diagnosed with hypertension.

OBJECTIVES

The objective of this study was to measure and compare prevalence, mortality, morbidity, use of medical resources and treatments in relation to the level of material and social deprivation of the area of residence, in a population with a diagnosis of hypertension in primary prevention for cardiovascular disease (CVD) in Quebec in 2006-2007.

METHODS

This study is based on a secondary analysis of the medical administrative data of the Quebec health insurance board, the Régie de l'assurance maladie du Québec, for a cohort of 276 793 patients aged 30 years or older who had been diagnosed with hypertension in 2006 or 2007, but who did not have a known diagnosis of CVD. The health indicators adjusted for age and sex are prevalence, death, a cardiovascular event, physician visits, emergency department visits and use of antihypertensives. Twenty-five types of areas of residence were obtained by crossing the material and social deprivation quintiles.

RESULTS

Compared with patients living in materially and socially advantaged areas, those living in deprived areas were at 46% higher risk of a cardiovascular event, 47% higher risk of being frequent emergency department visitors and 31% higher risk of being frequent users of a general practitioner's services, but 25% lower risk of being frequent users of medical specialists' services. Little or no variation was observed in the use of antihypertensives.

CONCLUSION

This study reveals the existence, in a CVD primary prevention context, of large variations in a number of health indicators among hypertensive patients owing to the material and social deprivation of residential neighbourhood. It is therefore important to take the socioeconomic context into account when planning interventions to prevent CVDs and their consequences.

Self-rated health mediates the association between functional status and health-related quality of life in Parkinson's disease

AIMS AND OBJECTIVES

To explore whether self-rated health acts as a potential mediator in the association between functional status and health-related quality of life in Parkinson's disease.

BACKGROUND

Older persons (as most patients with Parkinson's disease are) who reported poor self-rated health compared with those with excellent self-rated health were two-and-a-half times more likely to have experienced a decline in functional ability.

DESIGN

Cross-sectional.

METHODS

Socio-demographic and clinical data of the patients (n = 176) were obtained during a structured interview and from medical records. Functional status was measured with the Unified Parkinson's Disease Rating Scale (total score), self-rated health with the first item of the Short-Form 36-item Health Survey Questionnaire and health-related quality of life with the disease-specific questionnaire called the Parkinson's Disease Quality of Life Questionnaire-39. Multiple linear regression analyses and the Sobel test were employed to assess mediation.

RESULTS

Self-rated health seems to have a mediating effect on the association between functional status and health-related quality of life. The Sobel test confirmed an indirect effect of functional status via self-rated health on health-related quality of life and showed a statistically significant indirect effect of functional status on health-related quality of life via self-rated health against the direct route without the mediator.

CONCLUSIONS

Self-rated health partially mediates the deteriorating effect of functional status on health-related quality of life.

RELEVANCE TO CLINICAL PRACTICE

Supportive and adaptation psychosocial intervention programmes leading to restored self-rated health may enhance the quality of life regardless of disability in Parkinson's disease.