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Glycolysis which converts each molecule of glucose to two of pyruvate is the most important source of energy in erythrocytes and in some types of skeletal muscle fibres, therefore inherited diseases of glycolysis are mainly characterized by haemolytic anaemia and/or metabolic myopathy. Ten inborn errors of the glycolytic pathway are known. The pentose phosphate pathway consists of two distinct parts: the first part, an oxidative, non-reversible pathway, produces NADPH, and the second part, a non-oxidative, reversible pathway, produces ribose for nucleotide and nucleic acid synthesis and connects intermediates to glycolysis. Four inborn errors in the pentose phosphate pathway (PPP) are known.

The role of clouds for radiative transfer, precipitation formation, and their interaction with atmospheric dynamics depends strongly on cloud microphysics. The parameterization of cloud microphysical processes in weather and climate models is a well‐known source of uncertainties. Hence, robust quantification of this uncertainty is mandatory. Sensitivity analysis to date has typically investigated only a few model parameters. We propose algorithmic differentiation (AD) as a tool to detect the magnitude and timing at which a model state variable is sensitive to any of the hundreds of uncertain model parameters in the cloud microphysics parameterization. AD increases the computational cost by roughly a third in our simulations. We explore this methodology as the example of warm conveyor belt trajectories, that is, air parcels rising rapidly from the planetary boundary layer to the upper troposphere in the vicinity of an extratropical cyclone. Based on the information of derivatives with respect to the uncertain parameters, the ten parameters contributing most to uncertainty are selected. These uncertain parameters are mostly related to the representation of hydrometeor diameter and fall velocity, the activation of cloud condensation nuclei, and heterogeneous freezing. We demonstrate the meaningfulness of the AD‐estimated sensitivities by comparing the AD results with ensemble simulations spawned at different points along the trajectories, where different parameter settings are used in the various ensemble members. The ranking of the most important parameters from these ensemble simulations is consistent with the results from AD. Thus, AD is a helpful tool for selecting parameters contributing most to cloud microphysics uncertainty., Plain Language Summary: The formation of clouds is determined by processes that act on smaller scales than weather prediction models can resolve. Consequently, a parameterization with typically hundreds of parameters is constructed to determine the effects of these processes on the resolved larger scales. These parameters are a well‐known source of uncertainty in weather and climate models. Classical attempts to quantify this uncertainty are typically limited to a few parameters. We propose algorithmic differentiation (AD) as a tool to detect parameters with the largest impact for any of the hundreds of parameters on multiple model state variables at every time step in our simulation. This increases the computational cost by roughly a third. The relevance of the AD‐estimated impact is demonstrated by comparing the AD results with ensemble simulations, where different parameter settings are used in the various ensemble members. The ranking of the most important parameters from these ensemble simulations is consistent with the results from AD. Thus, AD is a helpful tool to identify parameters objectively that contribute most to uncertainty in cloud parameterizations., Key Points: Quantification of multi‐parameter uncertainty of cloud microphysical evolution of WCB trajectories using algorithmic differentiation. Uncertainty at every time step derived with algorithmic differentiation representative for key uncertainty over at least 30 min intervals. Parameterization of CCN activation, diameter size, and fall velocity of hydrometeors have the largest mean impact on water vapor contents., Deutsch Forschungsgemeinschaft DFG

The goals of this study were to investigate hair cortisol concentration (HCC) in seven different breeds of cows, to establish reference intervals for HCC in Brown Swiss cows and to compare cortisol concentrations of hair collected from four different areas of the body. Three groups of cows were used. Group 1 comprised 70 healthy cows representing four dairy breeds (Brown Swiss, Swiss Fleckvieh, Holstein Friesian, Water Buffalo) and three beef breeds (Raetian Grey, Limousin, Highland). Group 2 consisted of 60 healthy Brown Swiss cows in which two different hair samples were collected from the thoracic region to establish reference intervals; A samples consisted of hair that had grown for one month in a pre-clipped area, and B samples consisted of hair from a previously unshorn area. Group 3 comprised 21 healthy Brown Swiss cows, in which HCCs were measured in A and B samples from four different body regions (neck, shoulder, thorax, rump). Liquid chromatography tandem mass-spectrometry was used for cortisol measurement. In group 1, the highest HCCs were measured in Holstein Friesian cows at 1,75 pg/mg, which was significantly higher than those of the Brown Swiss, the Swiss Fleckvieh and the Water Buffalo cows. Hair cortisol concentration and daily milk yield of the 40 dairy cows were highly correlated (r = 0,57, P0,01). In group 2, the HCCs of 77 % of the A samples and 85 % of the B samp-les were below the laboratory's limit of quantification (LOQ) of 0,50 pg/mg and the results were expressed semiquantitatively as.Das Ziel war es, die Haarcortisolkonzentrationen (HCC) bei 7 Rinderrassen zu untersuchen, Referenzwerte für Braunviehkühe zu bestimmen und 4 Entnahmestellen in Bezug auf die HCC zu vergleichen. Die Untersuchungen wurden an 3 Gruppen von Kühen durchgeführt. In der Gruppe 1 wurden die HCC bei 70 Kühen von 4 Milchvieh- (Brown Swiss, Swiss Fleckvieh, Holstein Friesian, Wasserbüffel) und 3 Mutterkuhrassen (Rätisches Grauvieh, Limousin, Schottisches Hochland­rind) untersucht. In der Gruppe 2 wurden bei 60 gesunden Brown-Swiss-Kühen A- und B-Proben zur Ermittlung von Referenzwerten am Thorax entnommen. Die A-Proben bestanden aus nachgewachsenen Haaren aus einer vor einem Monat geschorenen Fläche und die B-Proben aus nicht vorgeschorenem Haar. Die Gruppe 3 bestand aus 21 gesunden Brown-Swiss-Kühen, bei denen die HCC in A- und B-Proben von 4 verschiedenen Körperstellen (Hals, Schulter, Thorax, Kruppe) untersucht und miteinander verglichen wurden. Die HCC-Bestimmung erfolgte mittels LC-MS/MS (Flüssigkeitschromatographie, gekoppelt mit Massenspektrometrie). In der Gruppe 1 waren die HCC der Holstein-Friesian-Kühe mit 1,75 pg/mg signifikant höher als diejenigen der Brown Swiss-, Swiss Fleckvieh- und Wasserbüffelkühe. Zwischen den HCC und der Tagesmilchleistung der 40 Milchkühe bestand eine signifikante Korrelation (r = 0,57, P0,01). Bei der Gruppe 2 waren die HCC in 77 % der A- und 85 % der B-Proben unterhalb der Bestimmungsgrenze (limit of quantification, LOQ) von 0,50 pg/mg und wurden semiquantitativ alsLOQ angegeben. In den restlichen Proben lagen die HCC zwischen 0,50 und 1,20 pg/mg. Die Werte der A- und B-Proben unterschieden sich nicht signifikant. Bei der Gruppe 3 lagen die HCC-Medianwerte der messbaren Proben für die 4 Lokalisationen zwischen 0,50 und 1,00 pg/mg Haar. Die HCC unterschieden sich weder zwischen den verschiedenen Körperstellen noch zwischen den A- und Proben signifikant. Die Untersuchungen lassen die Vermutung zu, dass Holstein-Friesian-Kühe signifikant höhere HCC als Brown Swiss-, Swiss Fleckvieh- und Wasserbüffelkühe aufweisen und dass dies mindestens teilweise durch die hohe Milchleistung bedingt ist.Les objectifs de cette étude étaient d’étudier la concentration de cortisol dans les poils (hair cortisol concentration (HCC)) chez sept races de vaches différentes, d’établir des intervalles de référence pour le HCC chez les vaches de race Suisse Brune et de comparer les concentrations de cortisol dans les poils prélevés sur quatre zones différentes du corps. Trois groupes de vaches ont été utilisés. Le groupe 1 comprenait 70 vaches saines représentant quatre races laitières (Brown Swiss, Swiss Fleckvieh, Holstein Friesian, Buffle d’eau) et trois races à viande (Grise rhétique, Limousin, Highland). Le groupe 2 était composé de 60 vaches Brown Swiss en bonne santé, pour lesquelles deux échantillons de poils différents ont été prélevés dans la région thoracique afin d’établir des intervalles de référence ; les échantillons A étaient constitués de poils ayant poussé pendant un mois sur une zone précédemment tondue et les échantillons B étaient constitués de poils provenant d’une zone non tondue auparavant. Le groupe 3 comprenait 21 vaches suisses brunes en bonne santé, chez lesquelles les HCC ont été mesurés dans des échantillons A et B provenant de quatre régions corporelles différentes (cou, épaule, thorax, croupe). La chromatographie liquide en tandem avec spectrométrie de masse a été utilisée pour la mesure du cortisol. Dans le groupe 1, les HCC les plus élevés ont été mesurés chez les vaches Holstein Friesian à 1,75 pg/mg, ce qui était significativement plus élevé que ceux des vaches Brown Swiss, Swiss Fleckvieh et Buffle d’eau. La concentration de cortisol dans les poils et le rendement laitier quotidien des 40 vaches laitières étaient fortement corrélés (r = 0,57, P0,01). Dans le groupe 2, les HCC étaient inférieures à la limite de quantification (LOQ) de 0,50 pg/mg dans 77 % des échantillons A et 85 % des échantillons B et ils ont été indiquées de manière semi-quantitative commeLOQ. Dans les échantillons restants, les HCC se situaient entre 0,50 et 1,20 pg/mg. Les valeurs des échantillons A et B n’étaient pas significativement différentes. Dans le groupe 3, les valeurs médianes des HCC des échantillons mesurables pour les 4 localisations se situaient entre 0,50 et 1,00 pg/mg de poils. Les HCC ne différaient pas significativement entre les différentes localisations corporelles ni entre les échantillons A et B. Les analyses permettent de supposer que les vaches Holstein-Friesian présentent des HCC significativement plus élevées que les vaches Brown Swiss, Swiss Fleckvieh et les bufflonnes d’eau et que cela est dû au moins en partie à leur production laitière élevée.L’obiettivo di questo studio è stato quello di analizzare la concentrazione di cortisolo (HCC) nel pelo in sette diverse razze bovine, di stabilire gli intervalli di riferimento per l’HCC nelle vacche di razza Bruna e di confrontare le concentrazioni di cortisolo nei peli raccolti da quattro diverse aree del corpo. Sono stati utilizzati tre gruppi di vacche. Il gruppo 1 comprendeva 70 vacche sane che rappresentavano quattro razze da latte (Bruna svizzera, Swiss Fleckvieh, Frisona, Bufalo d’acqua) e tre razze da carne (Grigia alpina, Limousine, Highlander). Il gruppo 2 era composto da 60 vacche Bruna svizzera sane in cui sono stati raccolti due diversi campioni di pelo dalla regione toracica per stabilire gli intervalli di riferimento. I campioni A erano costituiti da peli cresciuti per un mese in un’area tosata, mentre i campioni B erano costituiti da peli provenienti da un’area precedentemente non tosata. Il gruppo 3 comprendeva 21 vacche Bruna svizzera sane, in cui le HCC sono stati misurate in campioni A e B provenienti da quattro diverse regioni del corpo (collo, spalla, torace, groppa). Per la misurazione del cortisolo è stata utilizzata la cromatografia liquida accoppiata con spettrometria di massa (LC-MS/MS). Nel gruppo 1, le HCC più elevate sono state misurate nelle vacche di razza Frisona con 1,75 pg/mg, significativamente più alte di quelle delle vacche di razza Bruna svizzera, Swiss Fleckvieh e Bufalo d’acqua. La concentrazione di cortisolo nel pelo e la produzione giornaliera di latte delle 40 vacche da latte erano altamente correlate (r = 0,57, P0,01). Nel gruppo 2, le HCC del 77 % dei campioni A e dell’85 % dei campioni B erano inferiori al limite di quantificazione (LOQ) del laboratorio di 0,50 pg/mg e i risultati sono stati espressi semi-quantitativamente come.

Deregulation of mitochondrial network in terminally differentiated cells contributes to a broad spectrum of disorders. Methylmalonic acidemia (MMA) is one of the most common inherited metabolic disorders, due to deficiency of the mitochondrial methylmalonyl-coenzyme A mutase (MMUT). How MMUT deficiency triggers cell damage remains unknown, preventing the development of disease–modifying therapies. Here we combine genetic and pharmacological approaches to demonstrate that MMUT deficiency induces metabolic and mitochondrial alterations that are exacerbated by anomalies in PINK1/Parkin–mediated mitophagy, causing the accumulation of dysfunctional mitochondria that trigger epithelial stress and ultimately cell damage. Using drug–disease network perturbation modelling, we predict targetable pathways, whose modulation repairs mitochondrial dysfunctions in patient–derived cells and alleviate phenotype changes in mmut–deficient zebrafish. These results suggest a link between primary MMUT deficiency, diseased mitochondria, mitophagy dysfunction and epithelial stress, and provide potential therapeutic perspectives for MMA.