Search

Passive acoustic monitoring (PAM) is commonly used to obtain year‐round continuous data on marine soundscapes harboring valuable information on species distributions or ecosystem dynamics. This continuously increasing amount of data requires highly efficient automated analysis techniques in order to exploit the full potential of the available data. Here, we propose a benchmark, which consists of a public dataset, a well‐defined task and evaluation procedure to develop and test automated analysis techniques. This benchmark focuses on the special case of detecting animal vocalizations in a real‐world dataset from the marine realm. We believe that such a benchmark is necessary to monitor the progress in the development of new detection algorithms in the field of marine bioacoustics. We ultimately use the proposed benchmark to test three detection approaches, namely ANIMAL‐SPOT, Koogu and a simple custom sequential convolutional neural network (CNN), and report performances. We report the performance of the three detection approaches in a blocked cross‐validation fashion with 11 site‐year blocks for a multi‐species detection scenario in a large marine passive acoustic dataset. Performance was measured with three simple metrics (i.e., true classification rate, noise misclassification rate and call misclassification rate) and one combined fitness metric, which allocates more weight to the minimization of false positives created by noise. Overall, ANIMAL‐SPOT performed the best with an average F metric of 0.83, followed by the custom CNN with an average fitness metric of 0.79 and finally Koogu with an average fitness metric of 0.59. The presented benchmark is an important step to advance in the automatic processing of the continuously growing amount of PAM data that are collected throughout the world's oceans. To ultimately achieve usability of developed algorithms, the focus of future work should be laid on the reduction of the false positives created by noise. [ABSTRACT FROM AUTHOR]

Background and Objectives: Sound is an important environmental factor that influences the expression of behavioral and psychological symptoms of dementia. Recent research on the effect of soundscape has shown promising results in improving environmental impact on people with dementia. However, no controlled studies have aimed to quantify the effects of soundscape intervention on resident outcomes. The aim of this study was to assess the feasibility and impact of a soundscape intervention on people with dementia and behavioral symptoms. Research Design and Methods: Pilot single-blind repeated-measures randomized controlled trial of an augmented soundscape intervention. Participants were people with dementia in a hospital-based specialized dementia unit. Participants were randomized to an augmented soundscape intervention delivered in their room in the morning and evening or treatment as usual, with 2 baseline weeks and 4 weekly post-randomization assessments of the primary and secondary behavioral outcomes. Results: The soundscape intervention was feasible in terms of recruitment, retention, and delivery of the intervention. There were improvements in the neuropsychiatric inventory total scores over time in both groups (−5.89, 95%CI −8.45 to −3.28, p < .001), but no differences between groups. There were no significant group, time, or group × time differences for the Pittsburgh Agitation Scale (PAS) total score. For the PAS-resisting care subscale, there was a significant group × time difference, with a greater reduction in the soundscape group over the study period (−0.81, 95% CI −1.59 to −0.03, p = .042). Discussion and Implications: In this pilot study, soundscape augmentation was a feasible and effective nonpharmacological approach to reducing resistance to care in people with dementia, although it did not improve neuropsychiatric symptoms more globally. Further studies with larger samples and of longer duration are needed to investigate the long-term effects of augmented sonic environments on people with dementia. Clinical Trials Registration Number: NCT04809545 [ABSTRACT FROM AUTHOR]

We navigate through the environment using our sensory stimuli. Sound is significant in guiding us through space and making us aware of time. Soundscape is an acoustic environment as perceived and experienced by a person. While an unfamiliar and chaotic soundscape can increase anxiety and stress, a well-designed soundscape can make the experience pleasant and improve moods. People with dementia suffer from a neurodegenerative disorder, leading to a progressive decline in cognitive health. Behavioural and psychological symptoms of dementia (BPSD) refer to a group of noncognitive behaviours that affect the prediction and control of dementia. Reducing the occurrence of BPSD is one of the main goals of dementia care. People with severe dementia usually live in nursing homes, long-term care facilities or memory care units where sensory perception is unfamiliar. The strange sensory stimuli add to the anxiety and distress of residents as care facilities are often not customized based on individual needs. Research shows that incorporating pleasant sounds into the environment, known as an 'augmented soundscape,' positively impacts behaviour and reduces BPSD. Most design tools and guidelines include eliminating unwanted noise. To date, there are no guidelines for sound augmentation in dementia care design. The previous study of sound selection showed promising results in sound augmentation and identifying sounds that a person with dementia may prefer during a specific time of the day. The sharpness and high-pitch sounds, such as animal localization, had positive results. Cricket sounds showed positive feedback during nighttime and evening; either its tranquillity made it favourable, or the continuous sound masked other noises during the night (like white noise). These results can be used to introduce sound augmentation guidelines. The goal is to introduce sound as a positive design implementation to enhance mood, reduce apathy and depression, lower anxiety and stress, and promote health. [ABSTRACT FROM AUTHOR]

Settlement is a critical period in the life cycle of marine invertebrates with a planktonic larval stage. For reef-building invertebrates such as oysters and corals, settlement rates are predictive for long-term reef survival. Increasing evidence suggests that marine invertebrates use information from ocean soundscapes to inform settlement decisions. Sessile marine invertebrates with a planktonic stage are particularly reliant on environmental cues to direct them to ideal habitats. As gregarious settlers, oysters prefer to settle amongst members of the same species. It has been hypothesized that oyster larvae from species Crassostrea virginica and Ostrea angasi use distinct conspecific oyster reef sounds to navigate to ideal habitats. In controlled laboratory experiments we exposed Pacific Oyster Magallana gigas larvae to anthropogenic sounds from conspecific oyster reefs, vessels, combined reef-vessel sounds as well as off-reef and no speaker controls. Our findings show that sounds recorded at conspecific reefs induced higher percentages of settlement by about 1.44 and 1.64 times compared to off-reef and no speaker controls, respectively. In contrast, the settlement increase compared to the no speaker control was non-significant for vessel sounds (1.21 fold), combined reef-vessel sounds (1.30 fold), and off-reef sounds (1.18 fold). This study serves as a foundational stepping stone for exploring larval sound feature preferences within this species. [ABSTRACT FROM AUTHOR]

Studying marine soundscapes by detecting known sound events and quantifying their spatio-temporal patterns can provide ecologically relevant information. However, the exploration of underwater sound data to find and identify possible sound events of interest can be highly time-intensive for human analysts. To speed up this process, we propose a novel methodology that first detects all the potentially relevant acoustic events and then clusters them in an unsupervised way prior to manual revision. We demonstrate its applicability on a short deployment. To detect acoustic events, a deep learning object detection algorithm from computer vision (YOLOv8) is re-trained to detect any (short) acoustic event. This is done by converting the audio to spectrograms using sliding windows longer than the expected sound events of interest. The model detects any event present on that window and provides their time and frequency limits. With this approach, multiple events happening simultaneously can be detected. To further explore the possibilities to limit the human input needed to create the annotations to train the model, we propose an active learning approach to select the most informative audio files in an iterative manner for subsequent manual annotation. The obtained detection models are trained and tested on a dataset from the Belgian Part of the North Sea, and then further evaluated for robustness on a freshwater dataset from major European rivers. The proposed active learning approach outperforms the random selection of files, both in the marine and the freshwater datasets. Once the events are detected, they are converted to an embedded feature space using the BioLingual model, which is trained to classify different (biological) sounds. The obtained representations are then clustered in an unsupervised way, obtaining different sound classes. These classes are then manually revised. This method can be applied to unseen data as a tool to help bioacousticians identify recurrent sounds and save time when studying their spatio-temporal patterns. This reduces the time researchers need to go through long acoustic recordings and allows to conduct a more targeted analysis. It also provides a framework to monitor soundscapes regardless of whether the sound sources are known or not. [ABSTRACT FROM AUTHOR]

Within the broader context of improving interactions between artificial intelligence and humans, the question has arisen regarding whether auditory and rhythmic support could increase attention for visual stimuli that do not stand out clearly from an information stream. To this end, we designed an experiment inspired by pip-and-pop but more appropriate for eliciting attention and P3a-event-related potentials (ERPs). In this study, the aim was to distinguish between targets and distractors based on the subject's electroencephalography (EEG) data. We achieved this objective by employing different machine learning (ML) methods for both individual-subject (IS) and cross-subject (CS) models. Finally, we investigated which EEG channels and time points were used by the model to make its predictions using saliency maps. We were able to successfully perform the aforementioned classification task for both the IS and CS scenarios, reaching classification accuracies up to 76%. In accordance with the literature, the model primarily used the parietal–occipital electrodes between 200 ms and 300 ms after the stimulus to make its prediction. The findings from this research contribute to the development of more effective P300-based brain–computer interfaces. Furthermore, they validate the EEG data collected in our experiment. [ABSTRACT FROM AUTHOR]

Spiking neural networks (SNNs), which are composed of biologically plausible spiking neurons, and combined with bio-physically realistic auditory periphery models, offer a means to explore and understand human auditory processing-especially in tasks where precise timing is essential. However, because of the inherent temporal complexity in spike sequences, the performance of SNNs has remained less competitive compared to artificial neural networks (ANNs). To tackle this challenge, a fundamental research topic is the configuration of spike-timing and the exploration of more intricate architectures. In this work, we demonstrate a learnable axonal delay combined with local skip-connections yields state-of-the-art performance on challenging benchmarks for spoken word recognition. Additionally, we introduce an auxiliary loss term to further enhance accuracy and stability. Experiments on the neuromorphic speech benchmark datasets, NTIDIDIGITS and SHD, show improvements in performance when incorporating our delay module in comparison to vanilla feed forward SNNs. Specifically, with the integration of our delay module, the performance on NTIDIDIGITS and SHD improves by 14% and 18%, respectively. When paired with local skip-connections and the auxiliary loss, our approach surpasses both recurrent and convolutional neural networks, yet uses 10x fewer parameters for NTIDIDIGITS and 7x fewer for SHD. [ABSTRACT FROM AUTHOR]

Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of ∼1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets. [ABSTRACT FROM AUTHOR]

Green areas in urban environments, such as urban parks and urban gardens, are known to provide benefits called "ecosystem services" to the urban community. Green recreational spaces offer opportunities for physical activity, leading to improved physical and mental health of residents. For this reason, the presence and the quality of such areas has to be considered and promoted in sustainable urban planning, especially in the context of contributing to the achievement sustainable cities. As the biodiversity of an area is an indication of its quality, soundecological indicators have been used to assess the biodiversity in natural areas. Due to the presence of anthropogenic sounds in urban areas, the use of these indicators to determine the quality of urban areas can be questioned. However, the vocal activity of collectively singing birds during the dawn chorus contributes to the urban soundscape, and results in a prominent biophonic component of this soundscape, as can be clearly seen in its yearly pattern. The use of soundecological indicators through the estimation of the Bird Dawn Chorus Strength has the potential to provide a means of assessing the quality of urban green spaces. To demonstrate this potential, a pilot study is presented here on the annual temporal scale of the soundscape of a typical urban green space. [ABSTRACT FROM AUTHOR]

The world population is aging and more and more people suffer from dementia, which makes remembering and orientation in time and space difficult. Moreover dementia has a strong negative effect on the quality of living of the people suffering from it, but also of their relatives. In this paper, we investigate if and how the playback of carefully chosen and recognizable sounds, such as music, a clock tower, or nature sounds, can help these people and have a positive effect on the behavioral and psychological symptoms of dementia (BPSD). The selection and playback of these sounds, augmenting the existing soundscape, is performed in a personalized manner, since sounds can elicit a different response in different people. Caregivers can provide feedback on the soundscape based on the resident's behavior and response to hearing the sounds. This allows a continuous adaptation of the soundscape. The soundscape system was tested with 19 people suffering from dementia and resident of 6 different nursing homes. Comparison of the nursing home environment before and after installation of the soundscape system showed that most residents (13/19) experienced this as an improvement of the sound environment. [ABSTRACT FROM AUTHOR]

Natural marine soundscapes are being threatened by increasing anthropic noise, particularly in shallow coastal waters. To preserve and monitor these soundscapes, understanding them is essential. Here, we propose a new method for semi-supervised categorization of shallow marine soundscapes, with further interpretation of these categories according to concurrent environmental conditions. The proposed methodology uses a nonlinear mapping of short-term spectrograms to a two-dimensional space, followed by a density-based clustering algorithm to identify similar sound environments. A random forest classifier, based on additional environmental data, is used to predict their occurrence. Finally, explainable machine learning tools provide insight into the ecological explanation of the clusters. This methodology was tested in the Belgian part of the North Sea, and resulted in clearly identifiable categories of soundscapes that could be explained by spatial and temporal environmental parameters, such as distance to the shore, bathymetry, tide or season. Classifying soundscapes facilitates their identification, which can be useful for policy making or conservation programs. Soundscape categorization, as proposed in this work, could be used to monitor acoustic trends and patterns in space and time that might provide useful indicators of biodiversity and ecosystem functionality change. [ABSTRACT FROM AUTHOR]

In a century where humans and machines—powered by artificial intelligence or not—increasingly work together, it is of interest to understand human processing of multi-sensory stimuli in relation to attention and working memory. This paper explores whether and when supporting visual information with rhythmic auditory stimuli can optimize multi-sensory information processing. In turn, this can make the interaction between humans or between machines and humans more engaging, rewarding and activating. For this purpose a novel working memory paradigm was developed where participants are presented with a series of five target digits randomly interchanged with five distractor digits. Their goal is to remember the target digits and recall them orally. Depending on the condition support is provided by audio and/or rhythm. It is expected that the sound will lead to a better performance. It is also expected that this effect of sound is different in case of rhythmic and non-rhythmic sound. Last but not least, some variability is expected across participants. To make correct conclusions, the data of the experiment was statistically analyzed in a classic way, but also predictive models were developed in order to predict outcomes based on a range of input variables related to the experiment and the participant. The effect of auditory support could be confirmed, but no difference was observed between rhythmic and non-rhythmic sounds. Overall performance was indeed affected by individual differences, such as visual dominance or perceived task difficulty. Surprisingly a music education did not significantly affect the performance and even tended toward a negative effect. To better understand the underlying processes of attention, also brain activation data, e.g., by means of electroencephalography (EEG), should be recorded. This approach can be subject to a future work. [ABSTRACT FROM AUTHOR]

BACKGROUND: Traditional healthcare is centred around providing in-hospital services using hospital owned medical instruments. The COVID-19 pandemic has shown that this approach lacks flexibility to insure follow-up and treatment of common medical problems. In an alternative setting adapted to this problem, participatory healthcare can be considered centred around data provided by patients owning and operating medical data collection equipment in their homes. OBJECTIVE: In order to trigger such a shift reliable and price attractive devices need to become available. Snoring, as a human sound production during sleep, can reflect sleeping behaviour and indicate sleep problems as an element of the overall health condition of a person. METHODS: The use of off-the-shelf hardware from Internet of Things platforms and standard audio components allows the development of such devices. A prototype of a snoring sound detector with this purpose is developed. RESULTS: The device, controlled by the patient and with specific snoring recording and analysing functions is demonstrated as a model for future participatory healthcare. CONCLUSIONS: Design of monitoring devices following this model could allow market introduction of new equipment for participatory healthcare, bringing a care complementary to traditional healthcare to the reach of patients, and could result in benefits from enhanced patient participation. [ABSTRACT FROM AUTHOR]

Acoustic comfort is becoming an increasingly important dimension for practitioners in the context of design of care facilities for older adults, namely nursing homes. Defining the quality of these spaces based on room acoustics criteria alone might be challenging if aspects related to their functioning (e.g., speech-based activities) are not taken into account. The acoustical capacity concept has been previously proposed for eating establishments as a way to provide a quality assessment based on both physical characteristics of the space and the perceived quality of verbal communication. In this study, a revised version of a prediction model for ambient noise levels based on occupancy and an estimation of acoustical capacity are proposed for nursing homes hosting people with dementia, and the corresponding parameters of slope, group size and absorption per person are optimized for the specific application, using a Nursing Home in Flanders (Belgium) participating to the AcustiCare project as case study. Results show that, compared to normal eating establishments, lower absorption per person values and higher group size values should be used in nursing homes to reduce errors in ambient noise levels prediction. Furthermore, using a retrofit intervention carried out in the living room of the Nursing Home, the enhanced acoustical capacity of the space was analysed. Results, in this case, show that, prior to the retrofit intervention, the acoustical capacity was already exceeded with average occupancy (i.e., saturated in normal functioning conditions), while the reduction in reverberation time achieved with the retrofit increased considerably the acoustical capacity of the space, shifting the quality of verbal communication in the living room from insufficient to satisfactory. [ABSTRACT FROM AUTHOR]

The design of urban public spaces is typically performed by architects and urban planners, which often only focus on the visual aesthetics of the urban space. Yet, a visually pleasing public open space designed for relaxing will be underused if it sounds unpleasant. Ideally, sonic design should be integrated with visual design, a need the soundscape approach answers. The current trend of co-creating the urban space together with all stakeholders, including local residents, opens up new opportunities to account for all senses in the urban design process. Unfortunately, architects and urban planners struggle to incorporate the soundscape approach in the urban design process and to use it in the context of co-creation. In this work, a hackathon is proposed to generate creative concepts, methods and tools to co-create the urban public space. A soundscape hackathon was organized in the spring of 2019. Participants were challenged to apply their own immersive approaches or virtual and/or augmented reality solutions on selected urban soundscapes. They presented their results to colleagues in the field and to a professional jury. This paper describes the process and results of the event and shows that a hackathon is a viable approach to accelerate the co-creation of the urban public space. [ABSTRACT FROM AUTHOR]

There are relatively few studies on the acoustic environment of care facilities. However, sound is an important component of the users’ experience and quality of life in these spaces, and particularly in nursing homes, where both staff and residents have medium- to long-term perspectives, contrarily to hospital settings. This study included an online large-scale survey for nursing homes in Flanders and it targeted the group of professionals. It aimed at providing an overview about noise sensitivity and sound perception of the staff members in their work environment, as well as investigating the potential effects on sound perception of staff role and context. Results showed that limited differences emerged for staff roles, while more differences were found when exploring the context factor. Overall, the results of this study claim for further attention on the management and design of the sound environment in these facilities. [ABSTRACT FROM AUTHOR]

Recently there has been an increasing interest in the acoustic environment and its perceptual counterpart (i.e., the soundscape) of care facilities and their potential to affect the experience of residents with dementia. There is evidence that too loud sounds or poor soundscape quality more generally can affect negatively the quality of life of people with dementia and increase agitation. The AcustiCare project aims to use the soundscape approach to enhance the Quality of Life (QoL) of residents and to reduce Behavioral and Psychological Symptoms of Dementia (BPSD), as well as improving the everyday experience of nursing homes for both residents and staff members. In order to gain further insights into the sound environments of such facilities, sound level monitoring and soundscape data collection campaigns were conducted in the living rooms of five nursing homes in Flanders. Results showed that sound levels (dB) and loudness levels (sone) did not vary significantly between days of the week, but they did so between moments of the day and between living rooms. From the perceptual point of view, several soundscape attributes and the perceived prominence of different sound source types varied significantly between the living rooms investigated, and a positive correlation was found between sound levels and the number of persons present in the living rooms. These findings claim for further attention on the potential role of the sound domain in nursing homes, which should promote (and not only permit) better living and working conditions for residents and staff members of nursing homes. [ABSTRACT FROM AUTHOR]

Over the past 5 years, we have encountered 6 cases of diffuse pulmonary uptake of -Tc bone-scanning agents (incidence, 0.04%). To assess the significance of this phenomenon, we reviewed all of the cases reported since 1974 (Including our series, a total of 32 cases). Three groups can be discerned, the first consisting of 24 patients without radiological calcifications in the lungs and with hypercalcemia of different origins (mostly hyperparathyroidism). Of the eight autopsies performed in this group, seven revealed extensive calcifications in alveolar walls and lung vessels; the other autopsy showed no calcification at all and only bronchopneumonic lesions. The second group consists of 6 patients in chronic dialysis. The last group consists of 2 patients having diffuse pulmonary alveolar microlithiasis with extensive radiologic calcifications. The mechanism of lung uptake of -Tc bone-imaging agents is probably the same as that of bone uptake (chemisorption on hydroxyapatite crystals), although other uptake mechanisms have also been discussed. Bone scintigraphy can be useful in the detection of early pulmonary calcifications, which have been associated with impaired pulmonary function and, due to their size, are generally not detected by X-ray. [ABSTRACT FROM AUTHOR]

Bedside myocardial scintigraphy was performed on 149 patients admitted to the Coronary Care Unit (CCU), after IV injection of 74 MBq Tl, using a mobile gamma camera (Dynamo). The study was displayed on Polaroïd pictures, without any image treatment, and read by two independent readers. Clinical history, findings, and final diagnosis were assessed by an independent clinician. The following conclusions were reached: [ABSTRACT FROM AUTHOR]

The relation between bone mineralization and osteocalcin content was investigated in iliac crest cortical bone obtained at necropsy in young females and in two groups of elderly women with and without osteoarthritis of the hands evaluated by X-ray. Using density fractionation technique, the bone was separated into fractions of increasing density from 1.72 to 2.30 g/ml. The mineralization profile revealed a significant shift to higher densities in the osteoarthritis cases compared with young adults (P less than 0.005) and age-sex-matched controls (P less than 0.001). The ash, calcium, and phosphorus content of the bone increased with increasing density of the fractions whereas collagen content, measured as hydroxyproline, decreased. The osteocalcin concentration of each fraction was determined in the supernatants obtained after EDTA-extraction in the presence of protease inhibitors. In the young control and osteoarthritis group, the osteocalcin content in the lowest density fractions was higher compared with the older non-osteoarthritic group. Osteocalcin content of the high density fractions, representing highly mineralized osteons, was the same in the three groups studied. These findings support the hypothesis that quality differences in bone may explain the inverse relationship between osteoarthritis and osteoporosis. [ABSTRACT FROM AUTHOR]

We investigated the effect of short-term, 1,25-dihydroxyvitamin D3 therapy (4 micrograms/day for 4 days) on calcium metabolism in 27 postmenopausal women (11 cases with osteoporosis and 16 cases with osteoarthritis). Bone mass at the axial and appendicular skeleton was higher in osteoarthritis than in osteoporosis. Initial values of calcium metabolism were similar. Osteoporotic and osteoarthritic patients responded with a similar significant increase in serum osteocalcin (+61% and +54%, respectively), fasting urinary calcium excretion (+178% and +124%, respectively) and 24 hour calcium excretion (+148% and +142%, respectively). Parathyroid hormone (PTH) levels decreased significantly in both groups (-30% and -18%, respectively). Osteoclastic bone resorption, evaluated by urinary hydroxyproline excretion, was not stimulated in either group. We conclude that in osteoporosis and also in osteoarthritis (1) 1,25-dihydroxy-vitamin D3 (1,25(OH)2D3) stimulation of osteoblast function is similar in production of osteocalcin; (2) the vitamin D target tissues react adequately to 1,25(OH)2D3 stimulation; (3) short-term high dose of 1,25(OH)2D3 does not stimulate bone resorption; and (4) the differences in bone mass between osteoarthritis and osteoporosis are not related to an alteration of the responsiveness to stimulation by 1,25 (OH)2D3. [ABSTRACT FROM AUTHOR]

Serum vitamin D metabolites and urinary calcium excretion; parameters of bone formation (serum alkaline phosphatase, serum osteocalcin); parameters of bone resorption (24 hour hydroxyprolinuria, 2 hour fasting urinary hydroxyproline/creatinine ratio); and parameters of cortical and trabecular bone density, parathyroid hormone (iPTH, COOH terminal assay), and serum minerals (calcium, phosphorus) were followed serially in 55 young adults (21 women and 34 men) from December 1985 until January 1987 at four different times during the year. The effect of a low-dose cyclooxygenase inhibitor (piroxicam 5 mg daily) on the same parameters of bone density and bone turnover when given from December until May, was also evaluated in this study. At the end of the treatment period parameters of bone turnover and bone density were comparable between placebo and piroxicam-treated groups. Therefore, the results of all subjects were pooled in order to investigate seasonal variation. In both sexes, seasonal variation was found not only for 250HD3 but also for 1,25(OH)2D3, serum calcium and phosphorus, urinary calcium excretion, and for bone density at the lumbar spine. Parameters of bone formation (serum osteocalcin and alkaline phosphatase), bone resorption (24 hour urinary hydroxyprolinuria and fasting urinary hydroxyproline/creatinine ratio) and PTH were influenced by this seasonal variation. We conclude that in young adults, a significant seasonal variation occurs, with low winter and high summer values, for serum 25 and 1,25(OH)2D3 for urinary calcium apparently without important influence on parameters of bone turnover or parathyroid activity and for lumbar spine density. Treatment with a low-dose cyclooxygenase inhibitor was without influence on the observed changes. [ABSTRACT FROM AUTHOR]

We measured bone osteocalcin concentrations in EDTA extracts from iliac crest cortical bone specimens obtained postmortem from 63 men and 71 women (age range 19-90 years), and serum osteocalcin levels in healthy blood donors, 49 men and 49 women (age range 21-65 years). Bone and serum osteocalcin concentrations were higher in men than in women, and an age-related decline was observed in both sexes. In women, however, a temporary increase in serum (P less than 0.05) osteocalcin was seen in the sixth decade. This study shows sex- and age-related changes in bone osteocalcin consistent with changes in serum osteocalcin, confirming that serum measurement of osteocalcin reflects bone levels. As osteocalcin reflects osteoblastic activity and thus bone formation, the overall decline in bone and serum osteocalcin in men and women, and the increase in serum osteocalcin in the sixth decade in women, indicate that aging is associated with a decrease in bone formation and turnover and that osteoblastic activity and bone turnover are stimulated at the menopause. [ABSTRACT FROM AUTHOR]