We investigated the coupling between glycolytic and mitochondrial membrane potential oscillations in Saccharomyces cerevisiae under semianaerobic conditions. Glycolysis was measured as NADH autofluorescence, and mitochondrial membrane potential was measured using the fluorescent dye 3,3'-diethyloxacarbocyanine iodide. The responses of glycolytic and membrane potential oscillations to a number of inhibitors of glycolysis, mitochondrial electron flow, and mitochondrial and plasma membrane H(+)-ATPase were investigated. Furthermore, the glycolytic flux was determined as the rate of production of ethanol in a number of different situations (changing pH or the presence and absence of inhibitors). Finally, the intracellular pH was determined and shown to oscillate. The results support earlier work suggesting that the coupling between glycolysis and mitochondrial membrane potential is mediated by the ADP/ATP antiporter and the mitochondrial F(0)F(1)-ATPase. The results further suggest that ATP hydrolysis, through the action of the mitochondrial F(0)F(1)-ATPase and plasma membrane H(+)-ATPase, are important in regulating these oscillations. We conclude that it is glycolysis that drives the oscillations in mitochondrial membrane potential.

Connexins in renal arterioles affect autoregulation of arteriolar tonus and renal blood flow and are believed to be involved in the transmission of the tubuloglomerular feedback (TGF) response across the cells of the juxtaglomerular apparatus. Connexin40 (Cx40) also plays a significant role in the regulation of renin secretion. We investigated the effect of deleting the Cx40 gene on autoregulation of afferent arteriolar diameter in response to acute changes in renal perfusion pressure. The experiments were performed using the isolated blood perfused juxtamedullary nephron preparation in kidneys obtained from wild-type or Cx40 knockout mice. Renal perfusion pressure was increased in steps from 75 to 155 mmHg, and the response in afferent arteriolar diameter was measured. Hereafter, a papillectomy was performed to inhibit TGF, and the pressure steps were repeated. Conduction of intercellular Ca2+changes in response to local electrical stimulation was examined in isolated interlobular arteries and afferent arterioles from wild-type or Cx40 knockout mice. Cx40 knockout mice had an impaired autoregulatory response to acute changes in renal perfusion pressure compared with wild-type mice. Inhibition of TGF by papillectomy significantly reduced autoregulation of afferent arteriolar diameter in wild-type mice. In Cx40 knockout mice, papillectomy did not affect the autoregulatory response, indicating that these mice have no functional TGF. Also, Cx40 knockout mice showed no conduction of intercellular Ca2+changes in response to local electrical stimulation of interlobular arteries, whereas the Ca2+response to norepinephrine was unaffected. These results suggest that Cx40 plays a significant role in the renal autoregulatory response of preglomerular resistance vessels.

Background Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. Methods Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse – Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. Results Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. Conclusions RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

Background Many individuals who will experience a first episode of psychosis (FEP) are not detected before occurrence, limiting the effect of preventive interventions. The combination of machine-learning methods and electronic health records (EHRs) could help address this gap.Methods This case-control development and validation study is based on EHR data from IBM Explorys. The IBM Explorys Platform holds standardised, longitudinal, de-identified, patient-level EHR data pooled from different health-care systems with distinct EHRs. The present EHR-based studies were retrospective, matched (1:1), casecontrol studies compliant with RECORD, STROBE, and TRIPOD statements. The study included individuals in the IBM Explorys database who at some point between 1990 and 2018 had a diagnosis of FEP followed by schizophrenia, and psychosis-free matched control individuals from a random subsample of the full cohort. For every individual in the FEP cohort, the individual in the control cohort was matched to have a similar date for inclusion in the database and a similar total observation time. Individuals in the FEP cohort had their index date defined as the first diagnosis of psychosis or the first prescription of antipsychotic medication. Individuals in the control cohort had their index date defined to occur the same number of days after inclusion in the database as their matching FEP individual. The FEP and control cohorts were both randomly split into development and validation datasets in a ratio of 7:3. The subset of individuals in the validation dataset who had all their health-care encounters at providers that were not seen in the development dataset made up the external validation subset. A novel recurrent neural network model was developed to predict the risk of FEP 1 year before the index date by employing demographics and medical events (in the categories diagnoses, prescriptions, procedures, encounters and admissions, observations, and laboratory test results) dynamically collected in the EHR as part of clinical routine. We named the recurrent neural network Dynamic ElecTronic hEalth reCord deTection (DETECT). The main outcomes were accuracy and area under receiver operating characteristic curve (AUROC). Decision-curve analyses and dynamic patient journey plots were used to evaluate clinical usefulness. FindingsThe FEP and control cohorts each comprised 72 860 individuals. 102 030 individuals (51 015 matching pairs) were randomly allocated to the development dataset and the remaining 43 690 to the validation dataset. In the validation dataset, 4770 individuals had all their encounters outside of the 118 790 health-care providers that were encountered in the development dataset. The data from these individuals made up the external validation subset. The median follow-up (observation time before index date) was 6•0 years (IQR 3•0-10•4). In the development dataset, DETECT's prognostic accuracy was 0•787 and AUROC was 0•868. In the validation dataset, DETECT's prognostic accuracy was 0•774 and AUROC was 0•856. In the ...

, located in the apical dense microvilli (brush border), plays a major role in the reabsorption of NaCl and water in the renal proximal tubule. In response to a rise in blood pressure NHE3 redistributes in the plane of the plasma membrane to the base of the brush border, where NHE3 activity is reduced. This NHE3 redistribution is assumed to provoke pressure natriuresis; however, it is unclear how NHE3 redistribution per se reduces NHE3 activity. To investigate if the distribution of NHE3 in the brush border can change the reabsorption rate, we constructed a spatiotemporal mathematical model of NHE3-mediated Na ϩ reabsorption across a proximal tubule cell and compared the model results with in vivo experiments in rats. The model predicts that when NHE3 is localized exclusively at the base of the brush border, it creates local pH microdomains that reduce NHE3 activity by Ͼ30%. We tested the model's prediction experimentally: the rat kidney cortex was loaded with the pH-sensitive fluorescent dye BCECF, and cells of the proximal tubule were imaged in vivo using confocal fluorescence microscopy before and after an increase of blood pressure by ϳ50 mmHg. The experimental results supported the model by demonstrating that a rise of blood pressure induces the development of pH microdomains near the bottom of the brush border. These local changes in pH reduce NHE3 activity, which may explain the pressure natriuresis response to NHE3 redistribution.