What Is the Metabolic Amplification of Insulin Secretion and Is It (Still) Relevant?

The pancreatic beta-cell transduces the availability of nutrients into the secretion of insulin. While this process is extensively modified by hormones and neurotransmitters, it is the availability of nutrients, above all glucose, which sets the process of insulin synthesis and secretion in motion. The central role of the mitochondria in this process was identified decades ago, but how changes in mitochondrial activity are coupled to the exocytosis of insulin granules is still incompletely understood. The identification of ATP-sensitive K+-channels provided the link between the level of adenine nucleotides and the electrical activity of the beta cell, but the depolarization-induced Ca2+-influx into the beta cells, although necessary for stimulated secretion, is not sufficient to generate the secretion pattern as produced by glucose and other nutrient secretagogues. The metabolic amplification of insulin secretion is thus the sequence of events that enables the secretory response to a nutrient secretagogue to exceed the secretory response to a purely depolarizing stimulus and is thus of prime importance. Since the cataplerotic export of mitochondrial metabolites is involved in this signaling, an orienting overview on the topic of nutrient secretagogues beyond glucose is included. Their judicious use may help to define better the nature of the signals and their mechanism of action

Athletes with high knee abduction moments show increased vertical center of mass excursions and knee valgus angles across sport-specific fake-and-cut tasks of different complexities

Young female handball players represent a high-risk population for anterior cruciate ligament (ACL) injuries. While the external knee abduction moment (KAM) is known to be a risk factor, it is unclear how cutting technique affects KAMs in sport-specific cutting maneuvers. Further, the effect of added game specificity (e.g., catching a ball or faking defenders) on KAMs and cutting technique remains unknown. Therefore, this study aimed: (i) to test if athletes grouped into different clusters of peak KAMs produced during three sport-specific fake-and-cut tasks of different complexities differ in cutting technique, and (ii) to test whether technique variables change with task complexity. Fifty-one female handball players (67.0 ± 7.7 kg, 1.70 ± 0.06 m, 19.2 ± 3.4 years) were recruited. Athletes performed at least five successful handball-specific sidestep cuts of three different complexities ranging from simple pre-planned fake-and-cut maneuvers to catching a ball and performing an unanticipated fake-and-cut maneuver with dynamic defenders. A k-means cluster algorithm with squared Euclidean distance metric was applied to the KAMs of all three tasks. The optimal cluster number of koptimal = 2 was calculated using the average silhouette width. Statistical differences in technique variables between the two clusters and the tasks were analyzed using repeated-measures ANOVAs (task complexity) with nested groupings (clusters). KAMs differed by 64.5%, on average, between clusters. When pooling all tasks, athletes with high KAMs showed 3.4° more knee valgus, 16.9% higher downward and 8.4% higher resultant velocity at initial ground contact, and 20.5% higher vertical ground reaction forces at peak KAM. Unlike most other variables, knee valgus angle was not affected by task complexity, likely due to it being part of inherent movement strategies and partly determined by anatomy. Since the high KAM cluster showed higher vertical center of mass excursions and knee valgus angles in all tasks, it is likely that this is part of an automated motor program developed over the players' careers. Based on these results, reducing knee valgus and downward velocity bears the potential to mitigate knee joint loading and therefore ACL injury risk

Application of artificial intelligence in Geodesy – A review of theoretical foundations and practical examples

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Artificial Intelligence (AI) is one of the key technologies in many of today's novel applications. It is used to add knowledge and reasoning to systems. This paper illustrates a review of AI methods including examples of their practical application in Geodesy like data analysis, deformation analysis, navigation, network adjustment, and optimization of complex measurement procedures. We focus on three examples, namely, a geo-risk assessment system supported by a knowledge-base, an intelligent dead reckoning personal navigator, and evolutionary strategies for the determination of Earth gravity field parameters. Some of the authors are members of IAG Sub-Commission 4.2 – Working Group 4.2.3, which has the main goal to study and report on the application of AI in Engineering Geodesy

EFFECT OF DOWNHILL RUNNING ON BIOMECHANICAL RISK FACTORS ASSOCIATED WITH ILIOTIBIAL BAND SYNDROME

The purpose of this study was to identify the influence of downhill running on biomechanical risk factors for iliotibial band syndrome. We conducted a 3D motion analysis of 22 females and males running on an instrumented treadmill at four different inclinations (0%, -5%, -10%, -15%) at a speed of 3.5 m/s. We found significant differences for biomechanical risk factors associated with iliotibial band syndrome. Peak knee flexion angle at initial ground contact (p \u3c .001), peak knee adduction angle (p = .005), and iliotibial band strain (p \u3c .001) systematically increased with increasing slope. Downhill running increases biomechanical risk factors for iliotibial band syndrome. Our results highlight the need to consider the individual running environment in assessing overuse injury risk in runners

KNEE KINEMATICS AND KINETICS OF SPORT-SPECIFIC FAKE-AND-CUT MANEUVERS OF VARYING COMPLEXITY IN FEMALE HANDBALL PLAYERS

The purpose of this study was to 1) compare knee joint kinematics and kinetics of fake-and-cut tasks of varying complexity in 51 female handball players and 2) present a case study of one athlete who ruptured her ACL three weeks post data collection. External knee joint moments and knee joint angles in all planes at the instance of the peak external knee abduction moment (KAM) as well as moment and angle time curves were analyzed. Peak KAMs and knee internal rotation moments were substantially higher than published values obtained during simple change-of-direction tasks and, along with flexion angles, differed significantly between the tasks. Introducing a ball reception and a static defender increased joint loads while they partially decreased again when anticipation was lacking. Our results suggest to use game-specific assessments of injury risk while complexity levels do not directly increase knee loading. Extreme values of several risk factors for a post-test injured athlete highlight the need and usefulness of appropriate screenings

CAN A SIMPLIFIED KNEE ABDUCTION MOMENT ESTIMATION BE USED FOR ATHLETE SCREENING? IMPLICATIONS FOR ACL INJURY PREVENTION

This study aimed to compare a simplified calculation of the knee abduction moment with the traditional inverse dynamics calculation when athletes perform fake-cut maneuvers with different complexities. In the simplified calculation, we multiply the force vector with its lever arm to the knee, projected onto the local coordinate system of the proximal thigh, hence neglecting the inertial contributions from distal segments. We found very strong ranking consistency using Spearman’s rank correlation coefficient when using the simplified method compared to the traditional calculation. Independent of the tasks, the simplified method resulted in higher moments than the inverse dynamics. This was caused by ignoring the moment caused by segment linear acceleration generating a counteracting moment by about 7%. An alternative to the complex calculations of inverse dynamics can be used to investigate the contributions of the GRF magnitude and its lever arm to the knee

Gastrointestinal failure in intensive care: a retrospective clinical study in three different intensive care units in Germany and Estonia

BACKGROUND: While gastrointestinal problems are common in ICU patients with multiple organ failure, gastrointestinal failure has not been given the consideration other organ systems receive. The aim of this study was to evaluate the incidence of gastrointestinal failure (GIF), to identify its risk factors, and to determine its association with ICU mortality. METHODS: A retrospective analysis of adult patients (n = 2588) admitted to three different ICUs (two ICUs at the university hospital Charité-Universitätsmedizin Berlin, Germany and one at Tartu University Clinics, Estonia) during the year 2002 was performed. Data recorded in a computerized database were used in Berlin. In Tartu, the data documented in the patients' charts was retrospectively transferred into a similar database. GIF was defined as documented gastrointestinal problems (food intolerance, gastrointestinal haemorrhage, and/or ileus) in the patient data at any period of their ICU stay. ICU mortality, length of stay, and duration of mechanical ventilation were assessed as outcome parameters. RESULTS: GIF was identified in 252 patients (9.7% of all patients). Only 20% of GIF patients were identifiable at admission. GIF was related to significantly higher mortality (43.7% vs. 5.3% in patients without GIF), as well as prolonged length of ICU stay (10 vs. 2 days) and mechanical ventilation (8 vs. 1 day), p < 0.001, respectively. Patients' profile (emergency surgical or medical), APACHE II and SOFA scores and the use of catecholamines at admission were identified as independent risk factors for the development of GIF. Development of GIF during ICU stay was an independent predictor for death. CONCLUSION: Gastrointestinal failure represents a relevant clinical problem accompanied by an increased mortality, longer ICU stay and mechanical ventilation

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Abstract: Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria