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Quantification of gastroesophageal regurgitation in brachycephalic dogs
Get PDFBackground
Gastroesophageal reflux and regurgitation occurs in brachycephalic dogs, but objective assessment is lacking.
Objectives
Quantify reflux in brachycephalic dogs using an esophageal pH probe and determine the association with scored clinical observations.
Animals
Fifty-one brachycephalic dogs.
Methods
Case review study. Signs of respiratory and gastrointestinal disease severity were graded based on owner assessment. An esophageal pH probe with 2 pH sensors was placed for 18-24 hours in brachycephalic dogs that presented for upper airway assessment. Proximal and distal reflux were indicated by detection of fluid with a pH ≤4. The median reflux per hour, percentage time pH ≤4, number of refluxes ≥5 minutes and longest reflux event for distal and proximal sensors were recorded. Association of preoperative respiratory and gastrointestinal grade, laryngeal collapse grade, and previous airway surgery with the distal percentage time pH ≤4 was examined using 1-way ANOVA.
Results
A total of 43 of 51 dogs (84%; 95% confidence interval 72-92) displayed abnormal reflux with a median (range) distal percentage time pH ≤4 of 6.4 (2.5-36.1). There was no significant association between the distal percentage time pH ≤4 and respiratory grade, gastrointestinal grade, laryngeal collapse grade, or previous upper airway surgery.
Conclusions and Clinical Importance
The occurrence of reflux is not associated with owner-assessed preoperative respiratory and gastrointestinal grade, laryngeal collapse grade, and previous airway surgery. Esophageal pH measurement provides an objective assessment tool before and after surgery
Oncologist counseling practice and COVID‐19 vaccination outcomes for patients with history of PEG‐asparaginase hypersensitivity
No full textVaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an effective strategy to prevent serious coronavirus disease 2019 (COVID-19) and is important for oncology patients. mRNA-based COVID-19 vaccines are contraindicated in those with a history of severe or immediate allergy to any vaccine component, including polyethylene glycol (PEG)2000. Patients with acute lymphoblastic leukemia/lymphoma receive asparaginase conjugated to PEG5000 (PEG-ASNase) and those with PEG-ASNase-associated hypersensitivity may be unnecessarily excluded from receiving mRNA COVID-19 vaccines. We, therefore, surveyed oncologists on COVID-19 vaccine counseling practice and vaccination outcomes in COVID-19 vaccination-eligible patients and show safe receipt of mRNA vaccines despite PEG-ASNase hypersensitivit
Is there a role for small molecule metabolite biomarkers in the development of a diagnostic test for endometriosis?
No full textEndometriosis is a disease defined by the presence of benign lesions of endometrial-like glands and stroma outside the endometrial cavity. Affecting an estimated 11.4% of Australian women, symptoms include chronic pelvic pain, dysmenorrhea and infertility. The current gold standard of diagnosis requires an expensive and invasive laparoscopic surgery, resulting in delayed time to treatment. The identification of a non-invasive endometriosis biomarker – a measurable factor correlating with disease presence or activity – has therefore become a priority in endometriosis research, although no biomarker has yet been validated. As small molecule metabolites and lipids have emerged as a potential focus, this review with systematic approach, aims to summarize studies examining metabolomic biomarkers of endometriosis in order to guide future research. EMBASE, PubMed and Web of Science were searched using keywords: lipidomics OR metabolomics OR metabolome AND diagnostic tests OR biomarkers AND endometriosis, and only studies written in English from August 2000 to August 2020 were included. Twenty-nine studies met inclusion and exclusion criteria and were included. These studies identified potential biomarkers in serum, ectopic tissue, eutopic endometrium, peritoneal fluid, follicular fluid, urine, cervical swabs and endometrial fluid. Glycerophospholipids were identified as potential biomarkers in all specimens, except urine and cervical swab specimens. However, no individual molecule or metabolite combination has reached clinical diagnostic utility. Further research using large study populations with robust patient phenotype and specimen characterisation is required if we are to make progress in identifying and validating a non-invasive diagnostic test for endometriosis
A framework-based wind forecasting to assess wind potential with improved grey wolf optimization and support vector regression
Get PDFWind energy is one of the most promising alternates of fossil fuels because of its abundant availability, low cost, and pollution-free attributes. Wind potential estimation, wind forecasting, and effective wind-energy management are the critical factors in planning and managing wind farms connected to wind-pooling substations. Hence, this study proposes a hybrid framework-based approach for wind-resource estimation and forecasting, namely IGWO-SVR (improved grey wolf optimization method (IGWO)-support vector regression (SVR)) for a real-time power pooling substation. The wind resource assessment and behavioral wind analysis has been carried out with the proposed IGWO-SVR optimization method for hourly, daily, monthly, and annual cases using 40 years of ERA (European Center for Medium-Range Weather Forecast reanalysis) data along with the impact of the El Niño effect. First, wind reassessment is carried out considering the impact of El Niño, wind speed, power, pressure, and temperature of the selected site Radhapuram substation in Tamilnadu, India and reported extensively. In addition, statistical analysis and wind distribution fitting are performed to demonstrate the seasonal effect. Then the proposed model is adopted for wind speed forecasting based on the dataset. From the results, the proposed model offered the best assessment report and predicted the wind behavior with greater accuracy using evaluation metrics, namely root mean square error (RMSE), mean absolute error (MAE), and mean squared error (MSE). For short-term wind speed, power, and El Niño forecasting, IGWO-SVR optimization effectively outperforms other existing models. This method can be adapted effectively in any potential locations for wind resource assessment and forecasting needs for better renewable energy management by power utilities
Investigating the implications of CFTR exon skipping using a Cftr exon 9 deleted mouse model
Get PDFIntroduction: Severity and disease progression in people with Cystic Fibrosis (CF) is typically dependent on their genotype. One potential therapeutic strategy for people with specific mutations is exon skipping with antisense oligonucleotides (AO). CFTR exon 9 is an in-frame exon and hence the exclusion of this exon would excise only 31 amino acids but not alter the reading frame of the remaining mRNA. Splice mutations 1209 + 1 G > C and 1209 + 2 T > G were documented to cause CFTR exon 9 skipping and these variants were reported to manifest as a milder CF disease, therefore exon 9 skipping could be beneficial for people with class I mutations that affect exon 9 such as p.Trp401X. While the impact of exon 9 skipping on gene expression and cellular pathways can be studied in cells in vitro, trace amount of full-length normal or mutated material could confound the evaluation. To overcome this limitation, the impact of CFTR exon 9 skipping on disease phenotype and severity is more effectively evaluated in a small animal model. It was hypothesised that antisense oligonucleotide-mediated skipping this particular exon could result in a “mild mouse CF phenotype”.
Methods: Cftr exon 9 deleted mice were generated using homologous recombination. Survival of homozygous (CftrΔ9/Δ9) and heterozygous (CftrΔ9/+) mice was compared to that of other CF mouse models, and lung and intestinal organ histology examined for any pathologies. Primary airway epithelial cells (pAECs) were harvested from CftrΔ9/Δ9 mice and cultured at the Air Liquid Interface for CFTR functional assessment using Ussing Chamber analysis.
Results: A CftrΔ9/Δ9 mouse model presented with intestinal obstructions, and at time of weaning (21 days). CftrΔ9/Δ9 mice had a survival rate of 83% that dropped to 38% by day 50. Histological sections of the small intestine from CftrΔ9/Δ9 mice showed more goblet cells and mucus accumulation than samples from the CftrΔ9/+ littermates. Airway epithelial cell cultures established from CftrΔ9/Δ9 mice were not responsive to forskolin stimulation.
Summary: The effect of Cftr exon 9 deletion on Cftr function was assessed and it was determined that the encoded Cftr isoform did not result in a milder “mouse CF disease phenotype,” suggesting that Cftr exon 9 is not dispensable, although further investigation in human CF pAECs would be required to confirm this observation
Service system well-being: Scale development and validation
No full textPurpose
Recent marketing research provides conceptual models to investigate the well-being of collectives, but service system well-being (SSW) remains untested empirically. This research conceptualises and develops a measure for SSW at the micro, meso and macro levels.
Design/methodology/approach
Using a series of studies, a multidimensional SSW scale is developed and validated to ensure its generalisability. After the development of preliminary items, Study 1 (N = 435 of service employees) was used to purify items using factor analyses. Study 2 (N = 592 of service employees) used structural equation modelling (SEM) with AMOS and SmartPLS to test the scale's dimensionality, reliability and validity.
Findings
The results confirm the validity and reliability of the nine dimensions of SSW. The measure was validated as a third-order micro-, meso- and macro-level construct. The dimensions of existential and transformative well-being contribute to micro-level well-being. The dimensions of social, community and collaborative well-being contribute to meso-level well-being. Government, leadership, strategic and resource well-being drive macro-level well-being. In addition, a nomological network was specified to assess the impact of SSW on service actor life satisfaction and customer orientation.
Research limitations/implications
The study contributes to services literature by theorising SSW as a hierarchical structure and empirically validating the dimensions and micro-meso-macro levels that contribute to SSW.
Practical implications
The SSW scale is a useful diagnostic tool for assessing levels of well-being across different systems and providing insights that can help develop interventions to improve the well-being of collectives.
Originality/value
The research is the first study to theorise the micro, meso and macro levels of service system well-being and operationally validate the SSW construct
Enhancement of PHA Production by a Mixed Microbial Culture Using VFA Obtained from the Fermentation of Wastewater from Yeast Industry
Get PDFWastewater from the yeast production industry (WWY) is potentially harmful to surface water due to its high nitrogen and organic matter content; it can be used to produce compounds of higher commercial value, such as polyhydroxyalkanoates (PHA). PHA are polyester-type biopolymers synthesized by bacteria as energy reservoirs that can potentially substitute petrochemical-derived plastics. In this exploratory work, effluent from WWY was used to produce PHA, using a three-step setup of mixed microbial cultures involving one anaerobic and two aerobic reactors. First, volatile fatty acids (VFA; 2.5 g/L) were produced on an anaerobic batch reactor (reactor A) fed with WWY, using a heat pretreated sludge inoculum to eliminate methanogenic activity. Concurrently, PHA-producing bacteria were enriched using synthetic VFA in a sequencing batch reactor (SBR, reactor C) operated for 78 days. Finally, a polyhydroxybutyrate (PHB)-producing reactor (reactor B) was assembled using the inoculum enriched with PHA-producing bacteria and the raw and distilled effluent from the anaerobic reactor as a substrate. A maximum accumulation of 17% of PHB based on cell dry weight was achieved with a yield of 1.2 g PHB/L when feeding with the distilled effluent. Roche 454 16S rRNA gene amplicon pyrosequencing of the PHA-producing reactor showed that the microbial community was dominated by the PHA-producing bacterial species Paracoccus alcalophilus (32%) and Azoarcus sp. (44%). Our results show promising PHB accumulation rates that outperform previously reported results obtained with real substrates and mixed cultures, demonstrating a sustainable approach for the production of PHA less prone to contamination than a pure culture
Weed recognition using deep learning techniques on class-imbalanced imagery
Get PDFContext: Most weed species can adversely impact agricultural productivity by competing for nutrients required by high-value crops. Manual weeding is not practical for large cropping areas. Many studies have been undertaken to develop automatic weed management systems for agricultural crops. In this process, one of the major tasks is to recognise the weeds from images. However, weed recognition is a challenging task. It is because weed and crop plants can be similar in colour, texture and shape which can be exacerbated further by the imaging conditions, geographic or weather conditions when the images are recorded. Advanced machine learning techniques can be used to recognise weeds from imagery.
Aims: In this paper, we have investigated five state-of-the-art deep neural networks, namely VGG16, ResNet-50, Inception-V3, Inception-ResNet-v2 and MobileNetV2, and evaluated their performance for weed recognition.
Methods: We have used several experimental settings and multiple dataset combinations. In particular, we constructed a large weed-crop dataset by combining several smaller datasets, mitigating class imbalance by data augmentation, and using this dataset in benchmarking the deep neural networks. We investigated the use of transfer learning techniques by preserving the pre-trained weights for extracting the features and fine-tuning them using the images of crop and weed datasets.
Key results: We found that VGG16 performed better than others on small-scale datasets, while ResNet-50 performed better than other deep networks on the large combined dataset.
Conclusions: This research shows that data augmentation and fine tuning techniques improve the performance of deep learning models for classifying crop and weed images.
Implications: This research evaluates the performance of several deep learning models and offers directions for using the most appropriate models as well as highlights the need for a large scale benchmark weed dataset
Disseminated T-cell lymphoma with non-epitheliotropic cutaneous involvement in a cat with erythematous patches and regenerative anemia
No full textA 14-y-old, castrated male, diabetic, domestic longhaired cat was presented for investigation of anemia. General examination revealed widespread cutaneous erythematous macules and patches. Hematology and bone marrow aspiration revealed severe regenerative anemia and marked erythroid hyperplasia, respectively. Low numbers of intermediate-to-large, atypical lymphocytes were observed in the blood smear and bone marrow aspirates. Various imaging modalities demonstrated a diffuse pulmonary bronchial pattern, multifocal mural thickening of the urinary bladder, splenomegaly, and mild tri-cavitary effusion. Skin biopsies and cytologic examination of the pleural effusion demonstrated round-cell neoplasia consistent with lymphoma. Autopsy confirmed disseminated T-cell lymphoma, mostly affecting the urinary bladder, stomach, lymph nodes, and interscapular subcutis and muscles. Angiocentrism and nerve infiltration were present. The cutaneous erythematous patches, characterized by perivascular neoplastic lymphocytic infiltrates and angiodestruction, were a manifestation of the disseminated lymphoma in this cat, similar to the lesions reported in humans affected by angioimmunoblastic T-cell lymphoma
Genome-wide association mapping of seed oligosaccharides in chickpea
Get PDFChickpea (Cicer arietinum L.) is one of the major pulse crops, rich in protein, and widely consumed all over the world. Most legumes, including chickpeas, possess noticeable amounts of raffinose family oligosaccharides (RFOs) in their seeds. RFOs are seed oligosaccharides abundant in nature, which are non-digestible by humans and animals and cause flatulence and severe abdominal discomforts. So, this study aims to identify genetic factors associated with seed oligosaccharides in chickpea using the mini-core panel. We have quantified the RFOs (raffinose and stachyose), ciceritol, and sucrose contents in chickpea using high-performance liquid chromatography. A wide range of variations for the seed oligosaccharides was observed between the accessions: 0.16 to 15.13 mg g-1 raffinose, 2.77 to 59.43 mg g-1 stachyose, 4.36 to 90.65 mg g-1 ciceritol, and 3.57 to 54.12 mg g-1 for sucrose. Kabuli types showed desirable sugar profiles with high sucrose, whereas desi types had high concentrations RFOs. In total, 48 single nucleotide polymorphisms (SNPs) were identified for all the targeted sugar types, and nine genes (Ca_06204, Ca_04353, and Ca_20828: Phosphatidylinositol N-acetylglucosaminyltransferase; Ca_17399 and Ca_22050: Remorin proteins; Ca_11152: Protein-serine/threonine phosphatase; Ca_10185, Ca_14209, and Ca_27229: UDP-glucose dehydrogenase) were identified as potential candidate genes for sugar metabolism and transport in chickpea. The accessions with low RFOs and high sucrose contents may be utilized in breeding specialty chickpeas. The identified candidate genes could be exploited in marker-assisted breeding, genomic selection, and genetic engineering to improve the sugar profiles in legumes and other crop species