Notes

Determining related features for selecting landrace accessions of Phaseolus lunatus D. pertaining to pest opposition.
Presence of esophageal perforation preoperatively, undergoing a thoracotomy, and whether a gastrostomy tube was placed were significantly associated with not surviving to discharge. Follow-up information was available for 38 of 47 dogs (80.9%; mean follow-up time, 46.5 months). Infrequent vomiting or regurgitation was reported by 5 of 20 (25%) owners, with 1 dog receiving medication.

Results suggested that surgical management of EFBs can be associated with a high success rate. Surgery should be considered when an EFB cannot be removed safely with minimally invasive methods or esophageal perforation is present.
Results suggested that surgical management of EFBs can be associated with a high success rate. Surgery should be considered when an EFB cannot be removed safely with minimally invasive methods or esophageal perforation is present.
To replicate a previously defined behavioral procedure to acclimate adult cats to temporary restriction in indirect calorimetry chambers and measure energy expenditure and respiratory quotient changes during acclimation.

8 healthy adult cats (4 spayed females, and 4 neutered males; mean ± SEM age, 2.5 ± 1.5 years; mean body weight, 4.8 ± 1.8 kg).

Cats underwent a 13-week incremental acclimation procedure whereby cats were acclimated to the chambers in their home environment (weeks 1 to 3), to the study room (weeks 4 to 6), and to increasing lengths of restriction within their home environment (weeks 7 to 8) and the chambers (weeks 9 to 13). Cat stress score, respiratory rate, fearfulness (assessed with a novel object test), energy expenditure, and respiratory quotient were measured. Data were analyzed by use of a repeated-measures mixed model.

Stress, based on cat stress scores, fearfulness, and respiration, peaked at weeks 4, 9, and 10 but returned to baseline levels by week 11. Energy expenditure anessary for indirect calorimetry studies.
To evaluate the effect of a constant rate infusion of ketamine on cardiac index (CI) in sheep, as estimated using noninvasive cardiac output (NICO) monitoring by partial carbon dioxide rebreathing, when anesthetized with sevoflurane at the previously determined minimum alveolar concentration that blunts adrenergic responses (MACBAR).

12 healthy Dorset-crossbred adult sheep.

Sheep were anesthetized 2 times in a balanced placebo-controlled crossover design. Anesthesia was induced with sevoflurane delivered via a tight-fitting face mask and maintained at MACBAR. Following induction, sheep received either ketamine (1.5 mg/kg IV, followed by a constant rate infusion of 1.5 mg/kg/h) or an equivalent volume of saline (0.9% NaCl) solution (placebo). After an 8-day washout period, each sheep received the alternate treatment. NICO measurements were performed in triplicate 20 minutes after treatment administration and were converted to CI. Blood samples were collected prior to the start of NICO measurements for analysis of ketamine plasma concentrations. The paired t test was used to compare CI values between groups and the ketamine plasma concentrations with those achieved during the previous study.

Mean ± SD CI of the ketamine and placebo treatments were 2.69 ± 0.65 and 2.57 ± 0.53 L/min/m2, respectively. No significant difference was found between the 2 treatments. Mean ketamine plasma concentration achieved prior to the NICO measurement was 1.37 ± 0.58 µg/mL, with no significant difference observed between the current and prior study.

Ketamine, at the dose administered, did not significantly increase the CI in sheep when determined by partial carbon dioxide rebreathing.
Ketamine, at the dose administered, did not significantly increase the CI in sheep when determined by partial carbon dioxide rebreathing.
To determine the prevalence of pectoral girdle fractures in wild passerines found dead following presumed window collision and evaluate the diagnostic accuracy of various radiographic views for diagnosis of pectoral girdle fractures.

Cadavers of 103 wild passerines that presumptively died as a result of window collisions.

Seven radiographic projections (ventrodorsal, dorsoventral, lateral, and 4 oblique views) were obtained for each cadaver. A necropsy was then performed, and each bone of the pectoral girdle (coracoid, clavicle, and scapula) was evaluated for fractures. Radiographs were evaluated in a randomized order by a blinded observer, and results were compared with results of necropsy.

Fifty-six of the 103 (54%) cadavers had ≥ 1 pectoral girdle fracture. Overall accuracy of using individual radiographic projections to diagnose pectoral girdle fractures ranged from 63.1% to 72.8%, sensitivity ranged from 21.3% to 51.1%, and specificity ranged from 85.7% to 100.0%. The sensitivity of using various combinations of radiographic projections to diagnose pectoral girdle fractures ranged from 51.1% to 66.0%; specificity ranged from 76.8% to 96.4%.

Radiography alone appeared to have limited accuracy for diagnosing fractures of the bones of the pectoral girdle in wild passerines after collision with a window. Both individual radiographic projections and combinations of projections resulted in numerous false negative but few false positive results.
Radiography alone appeared to have limited accuracy for diagnosing fractures of the bones of the pectoral girdle in wild passerines after collision with a window. Both individual radiographic projections and combinations of projections resulted in numerous false negative but few false positive results.
To evaluate the radiographic outcome of root canal treatment (RCT) in dogs and compare outcomes with those reported for a previous study performed at the same institution in 2002.

204 dogs representing 281 teeth that underwent RCT.

The medical record database of a veterinary teaching hospital was searched to identify dogs that underwent RCT between 2001 and 2018. Only dogs that had undergone at least 1 radiographic recheck appointment a minimum of 50 days after RCT were included in the study. Dental radiographs were reviewed. Treatment was considered successful if the periapical periodontal ligament space was within reference limits and preexisting external inflammatory root resorption (EIRR), if present, had stabilized. find more Treatment was considered to show no evidence of failure (NEF) if preoperative EIRR had stabilized and any preoperative periapical lucency (PAL) remained the same or had decreased in size but had not completely resolved. Treatment was considered to have failed if EIRR or a PAL developed after RCT, if a preoperative PAL increased in size, or if preexisting EIRR progressed.

Follow-up time ranged from 52 to 3,245 days (mean, 437 days). RCT was classified as successful for 199 (71%) teeth, NEF for 71 (25%) teeth, and failed for 11 (4%) teeth.

Results showed that almost 2 decades after RCT outcome in dogs was first evaluated, during which time numerous advances in dental materials and techniques had been made, the success rate of RCT was virtually unchanged.
Results showed that almost 2 decades after RCT outcome in dogs was first evaluated, during which time numerous advances in dental materials and techniques had been made, the success rate of RCT was virtually unchanged.Leveraging consumer technology such as smartwatches to objectively and remotely assess people with voiding dysfunction could capture unique features for prompt diagnosis of a disease. This paper presents the UroSound, the first platform that performs non-intrusive sound-based uroflowmetry with a smartwatch. We study the feasibility of using a smartwatch to assess how well the urinary tract functions by processing the sound generated when the urine stream hits the water level in the toilet bowl, which can be modelled through the sound envelope. Signal-based features related to the sound envelope were extracted from a smartwatch's built-in microphone. The constructed model achieves a good correlation between acoustic and standard uroflowmetry in terms of the voiding shape and it can extract relevant voiding parameters. This indicates that accurate and remote measurement of the ambulatory characteristics of voiding dysfunction can be achieved with smartwatch-based uroflowmetry. UroSound also facilitates the collection of a voiding diary by measuring multiple uroflows during daytime and nighttime. Finally, the performance of 6 commercial smartwatches was analysed while recording a voiding event. The results demonstrate that the presence of an automatic gain control in the smartwatch microphone has a negative impact on the signal envelope, and should be avoided. Overall, this work demonstrates the potential for the use of smartwatches in the assessment of voiding dysfunction, to deliver more personalized and effective health care at home with less waste of time and resources, in particular in rural or less developed areas where access to a urology specialist is more difficult.Functional near-infrared spectroscopy (fNIRS) is a promising neuroimaging technology. The fNIRS classification problem has always been the focus of the brain-computer interface (BCI). Inspired by the success of Transformer based on self-attention mechanism in the fields of natural language processing and computer vision, we propose an fNIRS classification network based on Transformer, named fNIRS-T. We explore the spatial-level and channel-level representation of fNIRS signals to improve data utilization and network representation capacity. Besides, a preprocessing module, which consists of one-dimensional average pooling and layer normalization, is designed to replace filtering and baseline correction of data preprocessing. It makes fNIRS-T an end-to-end network, called fNIRS-PreT. Compared with traditional machine learning classifiers, convolutional neural network (CNN), and long short-term memory (LSTM), the proposed models obtain the best accuracy on three open-access datasets. Specifically, in the most extensive ternary classification task (30 subjects) that includes three types of overt movements, fNIRS-T, CNN, and LSTM obtain 75.49%, 72.89%, and 61.94% on test sets, respectively. Compared to traditional classifiers, fNIRS-T is at least 27.41% higher than statistical features and 6.79% higher than well-designed features. In the individual subject experiment of the ternary classification task, fNIRS-T achieves an average subject accuracy of 78.22% and surpasses CNN and LSTM by a large margin of +4.75% and +11.33%. fNIRS-PreT using raw data also achieves competitive performance to fNIRS-T. Therefore, the proposed models improve the performance of fNIRS-based BCI significantly.Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learning models has been highly effective in many aspects of e-health analytics. Nevertheless, in the classic cloud-based/centralized e-health paradigms, all the data will be centrally stored on the server to facilitate model training, which inevitably incurs privacy concerns and high time delay. Distributed solutions like Decentralized Stochastic Gradient Descent (D-SGD) are proposed to provide safe and timely diagnostic results based on personal devices. However, methods like D-SGD are subject to the gradient vanishing issue and usually proceed slowly at the early training stage, thereby impeding the effectiveness and efficiency of training. In addition, existing methods are prone to learning models that are biased towards users with dense data, compromising the fairness when providing E-health analytics for minority groups. In this paper, we propose a Decentralized Block Coordinate Descent (D-BCD) learning framework that can better optimize deep neural network-based models distributed on decentralized devices for E-health analytics.
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