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Background: The impact of acute unilateral injury on spontaneous electrical activity in both vagus nerves at the heart level is poorly understood. We investigated the immediate neuroelectrical response after right or left cardiac vagal nerve transection (VNTx) by recording spiking activity of each heart vagus nerve (VN)., Methods: Fourteen male Göttingen minipigs underwent sternotomy. Multi-electrode cuffs were implanted below the cut level to record vagal electroneurographic signals during electrocardiographic and hemodynamic monitoring, before and immediately after cardiac VNTx (left: L-cut, n = 6; right: R-cut, n = 8)., Results: Left cardiac VNTx significantly reduced multi-unit electrical activity (MUA) firing rate in the vagal stump (-30.7% vs pre-cut) and intact right VN (-21.8% vs pre-cut) at the heart level, without affecting heart rate, heart rate variability, or hemodynamics. In contrast, right cardiac VNTx did not acutely alter MUA in either VN but slightly increased (p < 0.022) the root mean square of successive RR interval differences (rMSSD), an index of parasympathetic outflow, without affecting hemodynamics., Conclusions: Our study reveals an early left-lateralized pattern in vagal spiking activity following unilateral cardiac vagotomy. These findings enhance understanding of the neuroelectrical response to vagal injury and provide insights into preserving vagal outflow after unilateral cardiac vagotomy. Importantly, monitoring spiking activity of the cardiac right VN may predict onset of left vagal pathway injury, which is detrimental to cardiac patients and can occur as a complication of catheter ablation for atrial fibrillation., (Copyright © 2023. Published by Elsevier B.V.)

Objectives: Falls are associated with several negative outcomes. Early identification of those who are at risk of falling is of importance in geriatrics, and comprehensive geriatric assessment (CGA) seems to be promising in this regard. Therefore, the present study investigated whether the multidimensional prognostic index (MPI), based on a standard CGA, is associated with falls in the Osteoarthritis Initiative (OAI)., Design: Longitudinal, 8 years of follow-up., Setting and Participants: Community-dwelling older people (≥65 years of age) with knee osteoarthritis or at high risk for this condition., Methods: A standardized CGA including information on functional, nutritional, mood, comorbidities, medications, quality of life, and cohabitation status was used to calculate a modified version of the MPI, categorized as MPI-1 (low), MPI-2 (moderate), and MPI-3 (high risk). Falls were self-reported and recurrent fallers were defined as ≥2 in the previous year. Logistic regression was carried out and results are reported as odds ratio (ORs) with their 95% confidence intervals (CIs)., Results: The final sample consisted of 885 older adults (mean age 71.3 years, female = 54.6%). Recurrent fallers showed a significant higher MPI than their counterparts (0.46 ± 0.17 vs 0.38 ± 0.16; P < .001). Compared with those in MPI-1 category, participants in MPI-2 (OR 2.13; 95% CI 1.53‒2.94; P < .001) and in MPI-3 (OR 5.98; 95% CI 3.29-10.86; P < .001) reported a significant higher risk of recurrent falls over the 8-years of follow-up. Similar results were evident when using an increase in 0.1 points in the MPI or risk of falls after 1 year., Conclusions and Implications: Higher MPI values at baseline were associated with an increased risk of recurrent falls, suggesting the importance of CGA in predicting falls in older people., (Copyright © 2019 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.)

Despite research progresses, the chance to accurately predict the risk for diabetic nephropathy (DN) is still poor. So far, the first evidence of DN is micro-albuminuria, which is detected only 10-20 years after the onset of diabetes. Our goal is to develop new predictive tools of nephropathy starting from urine, which can be easily obtained using noninvasive procedures and it is directly related to kidney. Since it is reasonable to suppose that, in predisposed patients, the mechanisms leading to nephropathy start acting since the diabetes onset, urine from children with recent diagnosis of type 1 diabetes was subjected to proteomic analysis in comparison to age-matched controls. Targeted confirmation was performed on children with a longer history of diabetes using Western Blotting and applying a urinary lipidomic approach. To definitively understand whether the observed alterations could be related to diabetic nephropathy, urine from diabetic adults with or without albuminuria was also examined. For the first time, lipid metabolisms of prostaglandin and ceramide, which are significantly and specifically modified in association with DN, are shown to be already altered in children with a recent diabetes diagnosis. Future studies on larger cohorts are needed to improve the validity and generalizability of these findings. Data are available via ProteomeXchange with identifier PXD011183 Submission details: Project Name: Urinary proteomics by 2DE and LC-MS/MS. Project accession: PXD011183 Project DOI: https://doi.org/10.6019/PXD011183 SIGNIFICANCE: Nephropathy is a very common diabetic complication. Once established, its progression can only be slowed down but full control or remission is achieved in very few cases, thus posing a large burden on worldwide health. The first evidence of diabetic nephropathy (DN) is micro-albuminuria, but only 30% of patients with micro-albuminuria progress to proteinuria, while in some patients it spontaneously reverts to normo-albuminuria. Thus, there is clear need for biomarkers that can accurately predict the risk to develop DN. Herein, by applying proteomic and lipidomic approaches on urine samples, we show that alteration of prostaglandin and ceramide metabolisms specifically occurs in association with DN. Interestingly, we demonstrate that the modification of these metabolic pathways is an early event in diabetic patients, suggesting the identified changed proteins as possible predictive biomarkers of diabetes-induced renal function decline., (Copyright © 2018 Elsevier B.V. All rights reserved.)