Search Results (9)

Objective: We evaluate the performance and relevance of MRI to detect csPC in men with normal PSA. Methods: Out of our database of patients referred for prostate MRI, we selected men with PSA < 4 ng/mL for whom histopathology or at least 2 years of clinical follow-up data were available as standard of reference. Subgroup analyses were performed for the patients with PSA < 3 ng/mL, <2 ng/mL, and 2–3.9 ng/mL. The reasons for prostate MRI referral despite their normal PSA level were retrieved by exploring the patients’ files. The prostate MRIs were reported according to the Prostate Imaging and Reporting Data System (PI-RADS), and the overall assessment score was registered. For evaluation of the performance, PI-RADS ≥ 3 was set as a threshold for a positive exam. The patients without PC or only International Society of Urological Pathology (ISUP) grade group 1 PC (Gleason 3+3) were considered as one category having no csPC. The performance of prostate MRI was separately evaluated for detection of ISUP ≥ 2 and for ISUP ≥ 3 csPC. Results: A total of 148 men were included, with PSA ranging from 0.42 to 3.99 ng/mL (median 2.95, IQR 1.68–3.50) and age ranging from 36 to 84 years (median 58, IQR 52–66). A total of 74 men (50.0%) had a PSA level < 3 ng/mL, 42 (28.4%) had a PSA level < 2 ng/mL, and 106 (71.6%) had a PSA level of 2–3.9 ng/mL. They were referred for prostate MRI for a wide variety, and usually a combination of, reasons, such as younger age (<60 years in 55.4%, N = 82; <50 years in 17.6%, N = 26), abnormal digital rectal examination in 31.8% of cases (N = 47), suspicious PSA dynamics in 29.7% (N = 44), positive familial history in 27.0% (N = 40), clinical signs of prostatitis in 18.2% (N = 27), suspicious findings on Transrectal Ultrasound (TRUS) in 16.9% (N = 25), hematospermia in 7.4% (N = 11), hematuria in 4.1% (N = 6), incidental hot spot in the prostate on Fluoro-Deoxy-Glucose (FDG) Positron Emission Tomography (PET)–Computed Tomography (CT) in 4.1% (N = 6), lymphadenopathies on CT in 2.7% (N = 4), or severe patient anxiety in 3.4% (N = 5). Overall, ISUP ≥ 2 PC was present in 18.9% (N = 28) of cases, and MRI detected this with a sensitivity of 92.9%, a specificity of 66.7%, and a positive predictive value of 39.4%. ISUP ≥ 3 PC was present in 9.5% (N = 14) of cases, and prostate MRI detected this with a sensitivity of 100%, a specificity of 61.2%, and a positive predictive value of 21.2%. In patients with PSA < 2 ng/mL (N = 42), no csPC was found, but MRI generated false positives in 33.3%. Conclusions: Performing prostate MRI in men with normal PSA (<4 ng/mL) seems useful if there are other reasons that increase the clinical suspicion of csPC. In about one-fifth of these patients, csPC is present and MRI has high sensitivity for its detection. Prostate MRI has, however, low positive predictive value in this patient group, and clinicians should be aware of the risk of false-positive MRI. Below a PSA level of 2 ng/mL, no csPC was found and prostate MRI generated only false positives, suggesting limited value in this subgroup. Full article

(1) Each year, thousands of students leave their pets behind to attend university, often causing separation anxiety and losing a vital stress-coping resource. While many universities offer animal visitation programs (AVPs), their effectiveness in supporting student wellbeing during this transition remains unclear. This randomized controlled trial evaluated psychological mood risk and resilience in a randomly selected sample of first-year university students (n = 145) separated from their childhood pets. (2) Participants were randomly assigned to receive access to a seven-session, biweekly 2 h drop-in program (n = 77) featuring unstructured interactions with therapy dogs or a waitlist control group (n = 68). Assessments of wellbeing were conducted at the start, middle, and end of the semester including depression, anxiety, worry, stress, cognitive reappraisal, expressive suppression, and self-compassion. (3) Regression analyses showed that access to the semester-long drop-in program significantly flattened trajectories of depression (B = −3.05, p = 0.01, d = 0.514), worry (B = −3.92, p = 0.04, d = 0.416), and stress (B = −1.94, p = 0.05, d = 0.386) compared to the control group. Students in experimental conditions also showed improvements in self-compassion (B = 4.03, p < 0.001, d = 0.605). (4) These findings suggest regular access to unstructured drop-in programs featuring therapy dogs may provide valuable psychological support for students adjusting to university life. Full article

Neuroimaging holds an essential position in global healthcare, as brain-related disorders are a substantial and growing burden. Non-degenerative disorders such as stress, depression and anxiety share common function related traits of diffuse and fluctuating changes, such as change in brain-based functions of mood, behavior and cognitive abilities, where underlying physiological mechanism remain unresolved. In this study we developed a novel application for studying intra-subject task-activated brain function by the quantitative physiological measurement of the change in glucose metabolism in a single scan setup. Data were acquired on a PET/MR-scanner. We implemented a functional [¹⁸F]-FDG PET-scan with double boli-tracer administration and finger-tapping activation, as proof-of-concept, in five healthy participants. The [¹⁸F]-FDG data were analyzed using a two-tissue compartment double boli kinetic model with an image-derived input function. For stand-alone visual reference, blood oxygenation level dependent (BOLD) functional MRI (fMRI) was acquired in the same session and analyzed separately. We were able to measure the cerebral glucose metabolic rate during baseline as well as activation. Results showed increased glucose metabolic rate during activation by 36.3–87.9% mean 62.0%, locally in the peak seed region of M1 in the brain, on an intra-subject level, as well as very good spatial accuracy on group level, and localization compared to the BOLD fMRI result at subject and group level. Our novel method successfully determined the relative increase in the cerebral metabolic rate of glucose on a voxel level with good visual association to fMRI at the subject-level, holding promise for future individual clinical application. This approach will be easily adapted in future clinical perspectives and pharmacological interventions studies. Full article

In this new era, it is no longer impossible to create a smart home environment around the household. Moreover, users are not limited to humans but also include pets such as dogs. Dogs need long-term close companionship with their owners; however, owners may occasionally need to be away from home for extended periods of time and can only monitor their dogs’ behaviors through home security cameras. Some dogs are sensitive and may develop separation anxiety, which can lead to disruptive behavior. Therefore, a novel smart home solution with an affective recommendation module is proposed by developing: (1) an application to predict the behavior of dogs and, (2) a communication platform using smartphones to connect with dog friends from different households. To predict the dogs’ behaviors, the dog emotion recognition and dog barking recognition methods are performed. The ResNet model and the sequential model are implemented to recognize dog emotions and dog barks. The weighted average is proposed to combine the prediction value of dog emotion and dog bark to improve the prediction output. Subsequently, the prediction output is forwarded to a recommendation module to respond to the dogs’ conditions. On the other hand, the Real-Time Messaging Protocol (RTMP) server is implemented as a platform to contact a dog’s friends on a list to interact with each other. Various tests were carried out and the proposed weighted average led to an improvement in the prediction accuracy. Additionally, the proposed communication platform using basic smartphones has successfully established the connection between dog friends. Full article

Anthropomorphic practices are increasing worldwide. Anthropomorphism is defined as the tendency to attribute human forms, behaviors, and emotions to non-human animals or objects. Anthropomorphism is particularly relevant for companion animals. Some anthropomorphic practices can be beneficial to them, whilst others can be very detrimental. Some anthropomorphic behaviors compromise the welfare and physiology of animals by interfering with thermoregulation, while others can produce dehydration due to the loss of body water, a condition that brings undesirable consequences such as high compensatory blood pressure and heat shock, even death, depending on the intensity and frequency of an animal’s exposure to these stressors. Malnutrition is a factor observed due to consumption of junk food or an imbalance in caloric proportions. This can cause obesity in pets that may have repercussions on their locomotor apparatus. Intense human–animal interaction can also lead to the establishment of attachment that impacts the mental state and behavior of animals, making them prone to develop aggression, fear, or anxiety separation syndrome. Another aspect is applying cosmetics to pets, though scientific studies have not yet determined whether cosmetic products such as coat dyes, nail polish, and lotions are beneficial or harmful for the animals, or to what extent. The cohabitation of animals in people’s homes can also constitute a public health risk due to infectious and zoonotic diseases. In this context, this paper aims to analyze the adverse effects of anthropomorphism on the welfare of companion animals from several angles—physiological, sanitary, and behavioral—based on a discussion of current scientific findings. Full article

The influence of the COVID-19 pandemic on human-pet interactions within New Zealand, particularly during lockdown, was investigated via two national surveys. In Survey 1, pet owners (n = 686) responded during the final week of the five-week Alert Level 4 lockdown (highest level of restrictions—April 2020), and survey 2 involved 498 respondents during July 2020 whilst at Alert Level 1 (lowest level of restrictions). During the lockdown, 54.7% of owners felt that their pets’ wellbeing was better than usual, while only 7.4% felt that it was worse. Most respondents (84.0%) could list at least one benefit of lockdown for their pets, and they noted pets were engaged with more play (61.7%) and exercise (49.7%) than pre-lockdown. Many respondents (40.3%) expressed that they were concerned about their pet’s wellbeing after lockdown, with pets missing company/attention and separation anxiety being major themes. In Survey 2, 27.9% of respondents reported that they continued to engage in increased rates of play with their pets after lockdown, however, the higher levels of pet exercise were not maintained. Just over one-third (35.9%) of owners took steps to prepare their pets to transition out of lockdown. The results indicate that pets may have enjoyed improved welfare during lockdown due to the possibility of increased human-pet interaction. The steps taken by owners to prepare animals for a return to normal life may enhance pet wellbeing long-term if maintained. Full article

Early life stress (ELS) is strongly associated with psychiatric disorders such as anxiety, depression, and schizophrenia in adulthood. To date, biological, behavioral, and structural aspects of ELS have been studied extensively, but their functional effects remain unclear. Here, we examined NeuroPET studies of dopaminergic, glutamatergic, and serotonergic systems in ELS animal models. Maternal separation and restraint stress were used to generate single or complex developmental trauma. Body weights of animals exposed to single trauma were similar to those of control animals; however, animals exposed to complex trauma exhibited loss of body weight when compared to controls. In behavioral tests, the complex developmental trauma group exhibited a decrease in time spent in the open arm of the elevated plus-maze and an increase in immobility time in the forced swim test when compared to control animals. In NeuroPET studies, the complex trauma group displayed a reduction in brain uptake values when compared to single trauma and control groups. Of neurotransmitter systems analyzed, the rate of decrease in brain uptake was the highest in the serotonergic group. Collectively, our results indicate that developmental trauma events induce behavioral deficits, including anxiety- and depressive-like phenotypes and dysfunction in neurotransmitter systems. Full article

Although fish and other aquatic species are popular privately-kept pets, little is known about the effects of watching live fish on the perceptions of arousal and the link between those perceptions and physiological measures of arousal. In two separate experiments, participants were asked to watch identically-equipped fish tanks for five minutes in each of three conditions: (1) Live fish, (2) plants and water, and (3) empty tank. Linear mixed models used across both experiments revealed similar results: Greater perceptions of relaxation and mood, and less anxiety during or after viewing the live fish condition, compared with the other conditions. Heart rate and heart rate variability responded to the arousal associated with a math task, but did not differ consistently across viewing conditions. These results suggest that the link between perceptions of arousal, and the physiological measures associated with arousal, may not be strong or immediate, or that heart rate and heart rate variability may not be appropriate measures for the test population. Implications of these results for the biophilia hypothesis and the biopsychosocial model are discussed. Full article

The use of IoT (Internet of Things) technology for the management of pet dogs left alone at home is increasing. This includes tasks such as automatic feeding, operation of play equipment, and location detection. Classification of the vocalizations of pet dogs using information from a sound sensor is an important method to analyze the behavior or emotions of dogs that are left alone. These sounds should be acquired by attaching the IoT sound sensor to the dog, and then classifying the sound events (e.g., barking, growling, howling, and whining). However, sound sensors tend to transmit large amounts of data and consume considerable amounts of power, which presents issues in the case of resource-constrained IoT sensor devices. In this paper, we propose a way to classify pet dog sound events and improve resource efficiency without significant degradation of accuracy. To achieve this, we only acquire the intensity data of sounds by using a relatively resource-efficient noise sensor. This presents issues as well, since it is difficult to achieve sufficient classification accuracy using only intensity data due to the loss of information from the sound events. To address this problem and avoid significant degradation of classification accuracy, we apply long short-term memory-fully convolutional network (LSTM-FCN), which is a deep learning method, to analyze time-series data, and exploit bicubic interpolation. Based on experimental results, the proposed method based on noise sensors (i.e., Shapelet and LSTM-FCN for time-series) was found to improve energy efficiency by 10 times without significant degradation of accuracy compared to typical methods based on sound sensors (i.e., mel-frequency cepstrum coefficient (MFCC), spectrogram, and mel-spectrum for feature extraction, and support vector machine (SVM) and k-nearest neighbor (K-NN) for classification). Full article