Impaired sense of smell in a Drosophila Parkinson's model.

Parkinson’s disease (PD) is one of the most common neurodegenerative disease characterized by the clinical triad: tremor, akinesia and rigidity. Several studies have suggested that PD patients show disturbances in olfaction at the earliest onset of the disease. The fruit fly Drosophila melanogaster 32 is becoming a powerful model organism to study neurodegenerative diseases. We sought to use this system to explore olfactory dysfunction, if any, in PINK1 mutants, which is a model for PD. PINK1 mutants display many important diagnostic symptoms of the disease such as akinetic motor behavior. In the present study, we describe for the first time, to the best of our knowledge, neurophysiological and neuroanatomical results concerning the olfactory function in PINK1 mutant flies. Electroantennograms were recorded in response to synthetic and natural volatiles (essential oils) from groups of PINK1 mutant adults at three different time points in their life cycle: one from 3-5 day-old flies, from 15-20 and from 27-30 days. The results obtained were compared with the same age-groups of wild type flies. We found that mutant adults showed a decrease in the olfactory response to 1-hexanol, α-pinene and essential oil volatiles. This olfactory response in mutant adults decreased even more as the flies aged. Immunohistological analysis of the antennal lobes in these mutants revealed structural abnormalities, especially in the expression of Bruchpilot protein, a marker for synaptic active zones. The combination of electrophysiological and morphological results suggests that the altered synaptic organization may be due to a neurodegenerative process. Our results indicate that this model can be used as a tool for understanding PD pathogensis and pathophysiology. These results help to explore the potential of using olfaction as a means of monitoring PD progression and developing new treatments

Multidisciplinary study of biological parameters and fatigue evolution in quay crane operators

In intermodal terminals the handling of containers and the number of accidents still depends on a wide range of human errors due to fatigue despite the automation level reached nowadays. For this reason it is very important to increase knowledge about the factors affecting the propensity of operators to make errors, increasing the chance of accidents happening. The aim of this work is to propose a novel approach to assess fatigue and performance lev els in quay crane operators as a function of physiological parameters and of the many varying boundary conditions encountered in daily work. During their work, quay crane operators have to deal with variable environmental conditions, such as task type, wind speed and direction, lighting conditions that redu ce visibility that can require an exacting level of attention. In the trial eight operators have been examined in a session lastin g four hours. All actual conditions are reproduced through a fully imme rsive quay crane simulator. The operator completes the assigned task (the same for each one) and can see through four wide monito rs a high quality virtual reality view of the simulation. Most biological parameters are acquired using different devices including a Holter ECG monitor, electromyographic monitoring the four trunk muscles most involved in the test, eye tracker and seat - body pressure interface for both seat pan and backrest. Changes in physiological parameters have been monitored during the trial and interesting correlations with performance levels and boundary conditions ha ve been f ound for each operator, in accord ance with their age and skills. The present study can form the basis for further investigations aimed at developing a cost effective, reliable and robust system for monitoring increasing fat igue and for predicting the critical conditions that may result in an acciden

Mucuna pruriens (Velvet bean) Rescues Motor, Olfactory, Mitochondrial and Synaptic Impairment in PINK1(B9) Drosophila melanogaster Genetic Model of Parkinson's Disease

The fruit fly Drosophila melanogaster (Dm) mutant for PTEN-induced putative kinase 1 (PINK1B9) gene is a powerful tool to investigate physiopathology of Parkinson's disease (PD). Using PINK1B9 mutant Dm we sought to explore the effects of Mucuna pruriens methanolic extract (Mpe), a L-Dopa-containing herbal remedy of PD. The effects of Mpe on PINK1B9 mutants, supplied with standard diet to larvae and adults, were assayed on 3–6 (I), 10–15 (II) and 20–25 (III) days old flies. Mpe 0.1% significantly extended lifespan of PINK1B9 and fully rescued olfactory response to 1-hexanol and improved climbing behavior of PINK1B9 of all ages; in contrast, L-Dopa (0.01%, percentage at which it is present in Mpe 0.1%) ameliorated climbing of only PINK1B9 flies of age step II. Transmission electron microscopy analysis of antennal lobes and thoracic ganglia of PINK1B9 revealed that Mpe restored to wild type (WT) levels both T-bars and damaged mitochondria. Western blot analysis of whole brain showed that Mpe, but not L-Dopa on its own, restored bruchpilot (BRP) and tyrosine hydroxylase (TH) expression to age-matched WT control levels. These results highlight multiple sites of action of Mpe, suggesting that its effects cannot only depend upon its L-Dopa content and support the clinical observation of Mpe as an effective medication with intrinsic ability of delaying the onset of chronic L-Dopa-induced long-term motor complications. Overall, this study strengthens the relevance of using PINK1B9 Dm as a translational model to study the properties of Mucuna pruriens for PD treatment

A Measurement of the Branching Ratio of KL→e+e−γγK_L \to e^+e^-\gamma\gamma

We report on a study of the decay $K_L \to e^+e^-\gamma\gamma$ carried out as a part of the KTeV/E799 experiment at Fermilab. The 1997 data yielded a sample of 1543 events, including an expected background of $56 \pm 8$ events. An effective form factor was determined from the observed distribution of the $e^+e^-$ invariant mass. Using this form factor in the calculation of the detector acceptance, the branching ratio was measured to be ${\mathcal B}(K_L \to e^+ e^- \gamma \gamma, E^*_\gamma > 5 {MeV}) = (5.84 \pm 0.15 {\rm ~(stat)} \pm 0.32 {\rm ~(sys)})\times 10^{-7}$.Comment: 5 pages, 4 figure

GLocalX - From Local to Global Explanations of Black Box AI Models

Artificial Intelligence (AI) has come to prominence as one of the major components of our society, with applications in most aspects of our lives. In this field, complex and highly nonlinear machine learning models such as ensemble models, deep neural networks, and Support Vector Machines have consistently shown remarkable accuracy in solving complex tasks. Although accurate, AI models often are “black boxes” which we are not able to understand. Relying on these models has a multifaceted impact and raises significant concerns about their transparency. Applications in sensitive and critical domains are a strong motivational factor in trying to understand the behavior of black boxes. We propose to address this issue by providing an interpretable layer on top of black box models by aggregating “local” explanations. We present GLOCALX, a “local-first” model agnostic explanation method. Starting from local explanations expressed in form of local decision rules, GLOCALX iteratively generalizes them into global explanations by hierarchically aggregating them. Our goal is to learn accurate yet simple interpretable models to emulate the given black box, and, if possible, replace it entirely. We validate GLOCALX in a set of experiments in standard and constrained settings with limited or no access to either data or local explanations. Experiments show that GLOCALX is able to accurately emulate several models with simple and small models, reaching state-of-the-art performance against natively global solutions. Our findings show how it is often possible to achieve a high level of both accuracy and comprehensibility of classification models, even in complex domains with high-dimensional data, without necessarily trading one property for the other. This is a key requirement for a trustworthy AI, necessary for adoption in high-stakes decision making applications.Artificial Intelligence (AI) has come to prominence as one of the major components of our society, with applications in most aspects of our lives. In this field, complex and highly nonlinear machine learning models such as ensemble models, deep neural networks, and Support Vector Machines have consistently shown remarkable accuracy in solving complex tasks. Although accurate, AI models often are “black boxes” which we are not able to understand. Relying on these models has a multifaceted impact and raises significant concerns about their transparency. Applications in sensitive and critical domains are a strong motivational factor in trying to understand the behavior of black boxes. We propose to address this issue by providing an interpretable layer on top of black box models by aggregating “local” explanations. We present GLOCALX, a “local-first” model agnostic explanation method. Starting from local explanations expressed in form of local decision rules, GLOCALX iteratively generalizes them into global explanations by hierarchically aggregating them. Our goal is to learn accurate yet simple interpretable models to emulate the given black box, and, if possible, replace it entirely. We validate GLOCALX in a set of experiments in standard and constrained settings with limited or no access to either data or local explanations. Experiments show that GLOCALX is able to accurately emulate several models with simple and small models, reaching state-of-the-art performance against natively global solutions. Our findings show how it is often possible to achieve a high level of both accuracy and comprehensibility of classification models, even in complex domains with high-dimensional data, without necessarily trading one property for the other. This is a key requirement for a trustworthy AI, necessary for adoption in high-stakes decision making applications

Cardiac rehabilitation after transcatheter versus surgical prosthetic valve implantation for aortic stenosis in the elderly

Background: Transcatheter aortic valve implantation plays a leading role in the management of aortic stenosis in patients with comorbidities but no data are available about cardiac rehabilitation in these subjects. This study aimed to compare safety and efficacy of an early, exercise-based, cardiac rehabilitation programme in octogenarians after a traditional surgical aortic valve replacement versus transcatheter aortic valve implantation.Methods: Seventy-eight consecutive transcatheter aortic valve implantation patients were studied in order to evaluate the effect of an exercise-based cardiac rehabilitation programme in comparison to 80 of a similar age having surgical aortic valve replacement. Functional capacity was assessed by a 6 min walking test on admission and at the end of the programme. When possible, a cardiopulmonary exercise test was also performed before discharge.Results: The two groups were similar in terms of gender and length of stay in cardiac rehabilitation; as expected, the transcatheter aortic valve implantation group had more comorbidities but no major complications occurred in either group during rehabilitation. All patients enhanced autonomy and mobility and were able to walk at least with the assistance of a stick. In those patients who were able to perform the 6 min walking test, the distance walked at discharge did not significantly differ between the groups (272.7.108 vs. 294.2. 101 m, p=0.42), neither did the exercise capacity assessed by cardiopulmonary exercise test (peak-VO2 12.5.3.6 vs. 13.9.2.7 ml/kg/min, p=0.16).Conclusions: Cardiac rehabilitation is feasible, safe and effective in octogenarian patients after transcatheter aortic valve implantation as well as after traditional surgery. An early cardiac rehabilitation programme enhances independence, mobility and functional capacity and should be highly encouraged

Intermuscular technique for implantation of the subcutaneous implantable defibrillator: a propensity-matched case-control study

Aims A previous randomized study demonstrated that the subcutaneous implantable cardioverter defibrillator (S-ICD) was noninferior to transvenous ICD with respect to device-related complications and inappropriate shocks. However, that was performed prior to the widespread adoption of pulse generator implantation in the intermuscular (IM) space instead of the traditional subcutaneous (SC) pocket. The aim of this analysis was to compare survival from device-related complications and inappropriate shocks between patients who underwent S-ICD implantation with the generator positioned in an IM position in comparison with an SC pocket. Methods and results We analysed 1577 consecutive patients who had undergone S-ICD implantation from 2013 to 2021 and were followed up until December 2021. Subcutaneous patients (n = 290) were propensity matched with patients of the IM group (n = 290), and their outcomes were compared. : During a median follow-up of 28 months, device-related complications were reported in 28 (4.8%) patients and inappropriate shocks were reported in 37 (6.4%) patients. The risk of complication was lower in the matched IM group than in the SC group [hazard ratio 0.41, 95% confidence interval (CI) 0.17-0.99, P = 0.041], as well as the composite of complications and inappropriate shocks (hazard ratio 0.50, 95% CI 0.30-0.86, P = 0.013). The risk of appropriate shocks was similar between groups (hazard ratio 0.90, 95% CI 0.50-1.61, P = 0.721). There was no significant interaction between generator positioning and variables such as gender, age, body mass index, and ejection fraction. Conclusion Our data showed the superiority of the IM S-ICD generator positioning in reducing device-related complications and inappropriate shocks