Evaluation of a combination of alfaxalone and methadone, with or without midazolam, for premedication in healthy dogs

Introduction: The study objective was to evaluate sedative and physiologic effects of midazolam associated with a combination of methadone and alfaxalone for IM premedication in dogs. Methods: Sixteen healthy dogs of various breeds, weighing 5–12 kg, classified ASA status I-II, randomly received a combination of 0.5 mg kg−1 of methadone and 1 mg kg−1 of alfaxalone with (MMA) or without (MA) 0.5 mg kg−1 of midazolam by IM injection. Quality of sedation was assessed at 10, 15, 20 and 25 minutes post-injection, by an observer blinded to treatment. Cardiovascular, respiratory variables and additional intravenous alfaxalone required for endotracheal intubation were recorded. Data were analyzed with mixed-effect linear model on rank or Mann-Whitney rank-sum test (p≤0.05). Results: There was no significant difference over time in heart rate, respiratory rate, systolic blood pressure, SpO2 and temperature between MA and MMA premedication. Sedation increased over time (p < 0.01), however dogs premedicated with MMA appeared significantly less sedated than dogs premedicated with MA at 15 (p=0.02), 20 (p=0.02) and 25 minutes (p=0.01) post-injection. This was substantiated by the fact that dogs premedicated with MMA were almost four times more likely to show delirium than those premedicated with MA (OR 3.95, CI 0.69-7.21, p=0.02). The amount of alfaxalone needed for intubation did not differ between treatments (p=0.92). Conclusion: Results suggest that adding midazolam to an IM combination of methadone and alfaxalone does not improve sedation scores or amount of agent needed for intubation in healthy dogs

Outcome after Modified Maquet Procedure in dogs with unilateral cranial cruciate ligament rupture: Evaluation of recovery limb function by use of force plate gait analysis

Introduction Cranial cruciate ligament failure is one of the principal causes of canine lameness. Several surgical procedures were proposed to achieve joint stabilisation; among these, the Modified Maquet Procedure involves using a titanium foam wedge to achieve and maintain the tibial tuberosity advancement. The force-plate analysis provides to objectively assess normal and abnormal gait and the outcome of different surgical techniques. The study evaluates the outcome of limbs that underwent Modified Maquet Procedure using land-force plate analysis comparing the operated limb with its healthy contralateral one as a control. Materials and methods Thirty-five dogs with unilateral cranial cruciate ligament rupture were evaluated. Outcome after surgery was assessed by orthopaedic and radiographic evaluations and force plate gait analysis performed before surgery, at 15, 30 and 90 days after surgery. For objective comparison of ground reaction forces, data of operated limb were compared to contralateral limb on each time control and Symmetry Index at 90 days was determined. Healing radiographic signs, minor and major complication were reported. Results A significant improvement in ground reaction forces was reached in all the treated limbs between set time intervals. The median percentage increase in ground reaction forces was constant from 15 to 90 days, with a Symmetry Index >9 in 54.2% of patients suggesting a normal gait symmetry. A complete bone healing was noticed at 90 days follow-up radiographic assessment. We experienced three major (8.5%) and one minor (2.8%) complications. Conclusions To the Authors' knowledge, this is the first study in the veterinary literature that assessed outcomes of dogs undergoing Modified Maquet Procedure for the treatment of cranial cruciate ligament rupture using force plate gait analysis and healthy contralateral limb as a control group. Our results confirm that Modified Maquet Procedure is an effective method to stabilise the stifle joint

Normal ultrasonographic features of loggerhead (Caretta caretta) eyes

The Loggerhead sea turtle (Caretta caretta) is widely distributed in the Mediterranean Sea but, like other sea turtles, it is considered a threatened species. Improving anatomical knowledge on normal aspects of the species is important for correct diagnosis and proper therapy and, therefore, for improving the chances of a complete recovery and a fast reintroduction into the wild for a greater number of sea turtle bycatch and other mishaps. For this reason, 15 Loggerhead turtles, with clinically healthy eyes, were submitted to ocular ultrasonographic (US) examinations. The US exam was quick, non-invasive, and simple to perform and permitted researchers to assess all the ocular features. © 2020, Croatian Natural History Museum. All rights reserved

Activity of N-Acetylcysteine Alone and in Combination with Colistin against Pseudomonas aeruginosa Biofilms and Transcriptomic Response to N-Acetylcysteine Exposure

Chronic colonization by Pseudomonas aeruginosa is critical in cystic fibrosis (CF) and other chronic lung diseases, contributing to disease progression. Biofilm growth and a propensity to evolve multidrug resistance phenotypes drastically limit the available therapeutic options. In this perspective, there has been growing interest in evaluating combination therapies, especially for drugs that can be administered by nebulization, which allows high drug concentrations to be reached at the site of infections while limiting systemic toxicity. Here, we investigated the potential antibiofilm activity of N-acetylcysteine (NAC) alone and in combination with colistin against a panel of P. aeruginosa strains (most of which are from CF patients) and the transcriptomic response of a P. aeruginosa CF strain to NAC exposure. NAC alone (8,000 mg/L) showed a limited and strain-dependent antibiofilm activity. Nonetheless, a relevant antibiofilm synergism of NAC-colistin combinations (NAC at 8,000 mg/L plus colistin at 2 to 32 mg/L) was observed with all strains. Synergism was also confirmed with the artificial sputum medium model. RNA sequencing of NAC-exposed planktonic cultures revealed that NAC (8,000 mg/L) mainly induced (i) a Zn21 starvation response (known to induce attenuation of P. aeruginosa virulence), (ii) downregulation of genes of the denitrification apparatus, and (iii) downregulation of flagellar biosynthesis pathway. NAC-mediated inhibition of P. aeruginosa denitrification pathway and flagellum-mediated motility were confirmed experimentally. These findings suggested that NAC-colistin combinations might contribute to the management of biofilm-associated P. aeruginosa lung infections. NAC might also have a role in reducing P. aeruginosa virulence, which could be relevant in the very early stages of lung colonization. © 2022 Valzano et al

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

OBJECTIVE: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer’s disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. METHODS: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients’ classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. RESULTS: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. DISCUSSION: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer’s disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients’ classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD

A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations

Frontal and Cerebellar Atrophy Supports FTSD-ALS Clinical Continuum

Background: Frontotemporal Spectrum Disorder (FTSD) and Amyotrophic Lateral Sclerosis (ALS) are neurodegenerative diseases often considered as a continuum from clinical, epidemiologic, and genetic perspectives. We used localized brain volume alterations to evaluate common and specific features of FTSD, FTSD-ALS, and ALS patients to further understand this clinical continuum. Methods: We used voxel-based morphometry on structural magnetic resonance images to localize volume alterations in group comparisons: patients (20 FTSD, seven FTSD-ALS, and 18 ALS) versus healthy controls (39 CTR), and patient groups between themselves. We used mean whole-brain cortical thickness (CT¯¯¯¯¯) to assess whether its correlations with local brain volume could propose mechanistic explanations of the heterogeneous clinical presentations. We also assessed whether volume reduction can explain cognitive impairment, measured with frontal assessment battery, verbal fluency, and semantic fluency. Results: Common (mainly frontal) and specific areas with reduced volume were detected between FTSD, FTSD-ALS, and ALS patients, confirming suggestions of a clinical continuum, while at the same time defining morphological specificities for each clinical group (e.g., a difference of cerebral and cerebellar involvement between FTSD and ALS). CT¯¯¯¯¯ values suggested extensive network disruption in the pathological process, with indications of a correlation between cerebral and cerebellar volumes and CT¯¯¯¯¯ in ALS. The analysis of the neuropsychological scores indeed pointed toward an important role for the cerebellum, along with fronto-temporal areas, in explaining impairment of executive, and linguistic functions. Conclusion: We identified common elements that explain the FTSD-ALS clinical continuum, while also identifying specificities of each group, partially explained by different cerebral and cerebellar involvement