Handheld methanol detector for beverage analysis: interlaboratory validation.

Methanol is a toxic alcohol contained in alcoholic beverages as a natural byproduct of fermentation or added intentionally to counterfeits to increase profit. To ensure consumer safety, many countries and the EU have established strict legislation limits for methanol content. Methanol concentration is mostly detected by laboratory instrumentation since mobile devices for routine on-site testing of beverages in distilleries, at border stations or even at home are not available. Here, we validated a handheld methanol detector for beverage analysis in an ISO 5725 interlaboratory trial: a total of 119 measurements were performed by 17 independent participants (distilleries, universities, authorities, and competence centers) from six countries on samples with relevant methanol concentrations (0.1, 1.5 vol%). The detector was based on a microporous separation filter and a nanostructured gas sensor allowing on-site measurement of methanol down to 0.01 vol% (in the liquid) within only 2 min by laymen. The detector showed excellent repeatability (<5.4%), reproducibility (<9.5%) and small bias (<0.012 vol%). Additional measurements on various methanol-spiked alcoholic beverages (whisky, rum, gin, vodka, tequila, port, sherry, liqueur) indicated that the detector is not interfered by environmental temperature and spirit composition, featuring excellent linearity (R2 > 0.99) down to methanol concentrations of 0.01 vol%. This device has been recently commercialized (Alivion Spark M-20) with comparable accuracy to the gold-standard gas chromatography and can be readily applied for final product inspection, intake control of raw materials or to identify toxic counterfeit products.

Lower and upper extremity contributions to propulsion and resistance during semi-tethered load-velocity profiling in front crawl swimming.

The study estimated lower and upper extremity contributions to whole-body front crawl swimming using semi-tethered load-velocity profiling. Nine female and 11 male (inter)national-level swimmers performed 20 m semi-tethered sprints, each with five progressive loads for lower (leg kicking), upper (arm stroke), and whole-body front crawl movements. The theoretical maximal speed (v0) and load (L0), and active drag (Da) were expressed as a percentage of the sum of both extremities for the movements of each extremity to calculate their contributions. The difference of whole-body values minus the sum of both extremities was used to estimate whole-body reserves. Lower (upper) body contributions were 43.8 ± 2.8% (56.2%) for v0, 37.3 ± 7.1% (62.7%) for L0, and 39.6 ± 5.6% (60.4%) for Da. Statistically significant whole-body reserves were found for v0 (-30.9 ± 3.9%, p < 0.001) and Da (-5.7 ± 11.7%, p = 0.04). V0 reserves correlated very highly with whole-body v0 in males (r = 0.71, p = 0.014) and moderately in females (r = 0.47, p = 0.21). The lower extremities contribute substantially to front crawl load-velocity profiles of highly trained swimmers. Higher sprint swimming speeds are associated with an efficient speed transfer from lower- and upper- to whole-body movement.

Development and Interplay of Metabolic and Mechanical Performance Determinants Over an Annual Training Period in Adolescent National-Level Squad Swimmers.

PURPOSE: The study examined the longitudinal interplay of anthropometric, metabolic, and neuromuscular development related to performance in adolescent national-level swimmers over 12 months. METHODS: Seven male and 12 female swimmers (14.8 [1.3] y, FINA [International Swimming Federation] points 716 [51]) were tested before (T0) and after the preparation period (T1), at the season's peak (T2), and before the next season (T3). Anthropometric (eg, fat percentage) and neuromuscular parameters (squat and bench-press load-velocity profile) were assessed on dry land. Metabolic (cost of swimming [C], maximal oxygen uptake [V˙O2peak], and peak blood lactate [bLapeak]) and performance (sprinting speed [vsprint] and lactate thresholds [LT1 and 2]) factors were determined using a 500-m submaximal, 200-m all-out, 20-second sprint, and incremental test (+0.03 m·s-1, 3 min), respectively, in front-crawl swimming. RESULTS: vsprint (+0.6%) and LT1 and 2 (+1.9-2.4%) increased trivially and slightly, respectively, from T0 to T2 following small to moderate strength increases (≥+10.2%) from T0 to T1 and V˙O2peak (+6.0%) from T1 to T2. Bench-press maximal strength and peak power correlated with vsprint from T0 to T2 (r ≥ .54, P < .05) and LT2 at T1 (r ≥ .47, P < .05). Changes in fat percentage and V˙O2peak (T2-T1 and T3-T2, r ≤ -.67, P < .01) and C and LT2 (T2-T0, r = -.52, P = .047) were also correlated. CONCLUSIONS: Increases in strength and V˙O2peak from preparation to the competition period resulted in improved sprint and endurance performance. Across the season, upper-body strength was associated with vsprint and LT2, although their changes were unrelated.

MetaProFi: an ultrafast chunked Bloom filter for storing and querying protein and nucleotide sequence data for accurate identification of functionally relevant genetic variants.

MOTIVATION: Bloom filters are a popular data structure that allows rapid searches in large sequence datasets. So far, all tools work with nucleotide sequences; however, protein sequences are conserved over longer evolutionary distances, and only mutations on the protein level may have any functional significance. RESULTS: We present MetaProFi, a Bloom filter-based tool that, for the first time, offers the functionality to build indexes of amino acid sequences and query them with both amino acid and nucleotide sequences, thus bringing sequence comparison to the biologically relevant protein level. MetaProFi implements additional efficient engineering solutions, such as a shared memory system, chunked data storage and efficient compression. In addition to its conceptual novelty, MetaProFi demonstrates state-of-the-art performance and excellent memory consumption-to-speed ratio when applied to various large datasets. AVAILABILITY AND IMPLEMENTATION: Source code in Python is available at https://github.com/kalininalab/metaprofi.

Modeling lactate threshold in young squad athletes: influence of sex, maximal oxygen uptake, and cost of running.

PURPOSE: This study aimed to investigate: 1. The influence of sex and age on the accuracy of the classical model of endurance performance, including maximal oxygen uptake ([Formula: see text]), its fraction (LT2%), and cost of running (CR), for calculating running speed at lactate threshold 2 (vLT2) in young athletes. 2. The impact of different CR determination methods on the accuracy of the model. 3. The contributions of [Formula: see text], LT2%, and CR to vLT2 in different sexes. METHODS: 45 male and 55 female young squad athletes from different sports (age: 15.4 ± 1.3 years; [Formula: see text]: 51.4 ± 6.8 [Formula: see text]) performed an incremental treadmill test to determine [Formula: see text], LT2%, CR, and vLT2. CR was assessed at a fixed running speed (2.8 [Formula: see text]), at lactate threshold 1 (LT1), and at 80% of [Formula: see text], respectively. RESULTS: Experimentally determined and modeled vLT2 were highly consistent independent of sex and age (ICC [Formula: see text] 0.959). The accuracy of vLT2 modeling was improved by reducing random variation using individualized CR at 80% [Formula: see text] (± 4%) compared to CR at LT1 (± 7%) and at a fixed speed (± 8%). 97% of the total variance of vLT2 was explained by [Formula: see text], LT2%, and CR. While [Formula: see text] and CR showed the highest unique (96.5% and 31.9% of total [Formula: see text], respectively) and common (- 31.6%) contributions to the regression model, LT2% made the smallest contribution (7.5%). CONCLUSION: Our findings indicate: 1. High accuracy of the classical model of endurance performance in calculating vLT2 in young athletes independent of age and sex. 2. The importance of work rate selection in determining CR to accurately predict vLT2. 3. The largest contribution of [Formula: see text] and CR to vLT2, the latter being more important in female athletes than in males, and the least contribution of LT2%.

Information Contained in EEG Allows Characterization of Cognitive Decline in Neurodegenerative Disorders.

Over the last few decades, electroencephalography (EEG) has evolved from being a method that purely relies on visual inspection into a quantitative method. Quantitative EEG, or QEEG, enables the assessment of neurological disorders based on spectral features, dynamic characterizations of EEG resting-state activity, brain connectivity analyzes or quantification of EEG signal complexity. The information contained in EEG is multidimensional: Electrodes, positioned at different scalp locations, provide a spatial dimension to the analysis of EEG while time provides a dynamic dimension: This multidimensional property of EEG makes its quantification a challenging task. In this narrative review we present quantitative models focused on different aspects of EEG: While microstate models focus more on the quantification of the dynamic aspects of EEG, spectral methods, connectivity analysis and entropy based models are more concerned with its spatial aspects. Nevertheless, these diverse approaches have provided neurophysiology based biomarkers, especially for monitoring and predicting the course of various neurodegenerative disorders. However, their translation into clinical practice crucially depends on the ability to automate the analysis of EEG in a user-friendly manner, without compromising on the validity of the provided results. Once this has been accomplished, EEG would provide an inexpensive and widely available method for monitoring disease progression, identifying patients at risk of neurodegeneration-especially before the onset of clinical symptoms, and predicting future cognition. For stratification of patients to clinical trials, EEG would allow shortening the trial duration and lowering the number of necessary participants by identifying patients at risk of fast cognitive decline.

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed.

This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.

d-StructMAn: Containerized structural annotation on the scale from genetic variants to whole proteomes.

BACKGROUND: Structural annotation of genetic variants in the context of intermolecular interactions and protein stability can shed light onto mechanisms of disease-related phenotypes. Three-dimensional structures of related proteins in complexes with other proteins, nucleic acids, or ligands enrich such functional interpretation, since intermolecular interactions are well conserved in evolution. RESULTS: We present d-StructMAn, a novel computational method that enables structural annotation of local genetic variants, such as single-nucleotide variants and in-frame indels, and implements it in a highly efficient and user-friendly tool provided as a Docker container. Using d-StructMAn, we annotated several very large sets of human genetic variants, including all variants from ClinVar and all amino acid positions in the human proteome. We were able to provide annotation for more than 46% of positions in the human proteome representing over 60% proteins. CONCLUSIONS: d-StructMAn is the first of its kind and a highly efficient tool for structural annotation of protein-coding genetic variation in the context of observed and potential intermolecular interactions. d-StructMAn is readily applicable to proteome-scale datasets and can be an instrumental building machine-learning tool for predicting genotype-to-phenotype relationships.

Comparison of different test protocols to determine maximal lactate steady state intensity in swimming.

OBJECTIVES: This study compared step test, lactate minimum (LM) test and reverse lactate threshold (RLT) test protocols with maximal lactate steady state (MLSS) in free-swimming. All test protocols used fixed duration increments and high work-rate resolution (≤ 0.03 m·s-1) to ensure high sensitivity. DESIGN: Validation study. METHODS: 23 swimmers or triathletes (12 male and 11 female) of different ages (19.0 ±â€¯5.9 yrs) and performance levels (400 m personal best 1.38 ±â€¯0.13 m·s-1, FINA points 490 ±â€¯118) completed an incremental step test (+0.03 m·s-1 every 3 min) to determine speed at 4 mmol·L-1 and at modified maximal distance method, a LM test, a RLT test and two to five 30 min tests (±0.015 m·s-1) to determine MLSS. Following a 200 m all-out and a 5 min rest, LM was determined during an incremental segment (+0.03 m·s-1 every 2 min) as the nadir of the speed-lactate curve. After a priming segment with four increments (+0.06 m·s-1), RLT was determined as the lactate apex during a reverse segment (-0.03 m·s-1) every 3 min. RESULTS: The mean differences (± limits of agreement) to speed at MLSS were +1.0 ±â€¯4.1% (speed at 4 mmol·L-1), +1.5 ±â€¯3.5% (modified maximum distance method), -0.2 ±â€¯4.7% (LM) and 2.0 ±â€¯3.1% (RLT). All threshold concepts showed good agreement with MLSS pace (intraclass correlation coefficient ≥ 0.886). CONCLUSIONS: Test protocols with a fixed step duration and fine increments allowed high accuracy in estimating MLSS pace. With similar criterion agreement to the LM and RLT tests, incremental step tests appear more practicable due to less prior knowledge required and derivation of individual training zones.

Speed Rope Skipping - Performance and Coordination in a Four-Limb Task.

This study investigated biomechanical characteristics of Speed Rope Skipping (RS) and estimated the contribution of the lower and upper limbs to overall performance. Lower (jumping), upper (turning), and whole-body (skipping) performance were examined in 23 rope skippers. All tests were recorded by 2 D video and nine skipping tests were performed in a 3 D motion capture system. Similar movement patterns were observed for the lower limbs in all participants, while handle trajectories differed in shape and symmetry according to performance. In general, turning unlike jumping performance was close to and significantly correlated with skipping performance. Therefore, it appears that lower extremity movement may be adapted to the limiting capacity of the upper extremity to maintain movement stability.

Learning Extremal Representations with Deep Archetypal Analysis.

Archetypes represent extreme manifestations of a population with respect to specific characteristic traits or features. In linear feature space, archetypes approximate the data convex hull allowing all data points to be expressed as convex mixtures of archetypes. As mixing of archetypes is performed directly on the input data, linear Archetypal Analysis requires additivity of the input, which is a strong assumption unlikely to hold e.g. in case of image data. To address this problem, we propose learning an appropriate latent feature space while simultaneously identifying suitable archetypes. We thus introduce a generative formulation of the linear archetype model, parameterized by neural networks. By introducing the distance-dependent archetype loss, the linear archetype model can be integrated into the latent space of a deep variational information bottleneck and an optimal representation, together with the archetypes, can be learned end-to-end. Moreover, the information bottleneck framework allows for a natural incorporation of arbitrarily complex side information during training. As a consequence, learned archetypes become easily interpretable as they derive their meaning directly from the included side information. Applicability of the proposed method is demonstrated by exploring archetypes of female facial expressions while using multi-rater based emotion scores of these expressions as side information. A second application illustrates the exploration of the chemical space of small organic molecules. By using different kinds of side information we demonstrate how identified archetypes, along with their interpretation, largely depend on the side information provided. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11263-020-01390-3.

Cooling During Endurance Cycling in the Heat: Blunted Core Temperature but Not Inflammatory Responses.

PURPOSE: This study assessed the effects of cooling during endurance cycling (percooling) on changes in core body temperature (Tcore), inflammatory, and metabolic responses. METHODS: A total of 12 male cyclists (peak oxygen uptake 60 [4] mL·kg-1·min-1) completed a 60-minute constant workload trial (55% of peak power output and ambient temperature 30.4°C [0.6°C]) in a randomized order both with (ICE) and without (CON) an ice vest. An ingestible capsule was used to measure Tcore. Blood samples were collected immediately before and after each trial to determine concentrations of blood lactate, serum cortisol, interleukin-6, and reactive oxygen and nitrogen species. RESULTS: Tcore increased statistically (P < .001) both in CON (7.0% [1.4%], effect size [ES] = 6.3) and ICE (5.1% [1.1%], ES = 5.7). The increase in CON was statistically larger compared with ICE (P = .006, ES = 1.4). Concentrations of blood lactate (CON: 163% [63%], ES = 1.3; ICE: 149% [91%], ES = 1.3), cortisol (CON: 138% [123%], ES = 1.7; ICE: 81% [102%], ES = 1.0), and interleukin-6 (CON: 661% [324%], ES = 2.1; ICE: 624% [368%], ES = 1.2) statistically increased in both conditions (P < .01) to a similar extent. In addition, reactive oxygen and nitrogen species statistically decreased in both conditions (CON: -19.2% [14.9%], P = .002, ES = 0.9; ICE: -15.1% [16.5%], P = .02, ES = 0.9). No correlations were found between the changes of Tcore and blood parameters across the conditions. CONCLUSIONS: Despite attenuated Tcore, similar inflammatory and metabolic responses were observed. Our findings suggest percooling to be a promising strategy to attenuate thermal strain without compromising physiological function.

Comparison of two different cooling systems in alleviating thermal and physiological strain during prolonged exercise in the heat.

This study compared the efficacy of an ice vest comprising of water (WATER) or a water-carbon (CARBON) emulsion on thermophysiological responses to strenuous exercise in the heat. Twelve male cyclists completed three 50-minute constant workload trials (55% of peak power output, ambient temperature 30.4 ± 0.6°C) with WATER, CARBON, and without ice vest (CONTROL), respectively. The increase in core body temperature (Tcore) was lower in WATER at 40 (-0.49 ± 0.34 °C) and 50 minutes (-0.48 ± 0.48 °C) and in CARBON at 30 (-0.41 ± 0.48 °C), 40 (-0.54 ± 0.51 °C), and 50 minutes (-0.67 ± 0.62 °C) as compared to CONTROL (p < 0.05, ES > 0.8). While heart rate and blood lactate kinetics did not differ between the conditions, statistical main effects in favour of both WATER and CARBON were found for thermal sensation (condition p < 0.001 and interaction p < 0.01) and rating of perceived exertion (condition p < 0.05). Per-cooling with CARBON and WATER similarly reduced Tcore but not physiological strain during prolonged exercise in the heat. Practitioner Summary: Exercise in the heat is characterised by increases in thermophysiological strain. Both per-cooling with a novel carbon-based and a conventional water-based ice vest were shown to reduce core temperature significantly. However, due to its lower mass, the carbon-based system may be recommended especially for weight-bearing sports.

Cognitive decline in Parkinson's disease is associated with reduced complexity of EEG at baseline.

Parkinson's disease is a neurodegenerative disorder requiring motor signs for diagnosis, but showing more widespread pathological alterations from its beginning. Compared to age-matched healthy individuals, patients with Parkinson's disease bear a 6-fold lifetime risk of dementia. For individualized counselling and treatment, prognostic biomarkers for assessing future cognitive deterioration in early stages of Parkinson's disease are needed. In a case-control study, 42 cognitively normal patients with Parkinson's disease were compared with 24 healthy control participants matched for age, sex and education. Tsallis entropy and band power of the δ, θ, α, ß and γ-band were evaluated in baseline EEG at eyes-open and eyes-closed condition. As the θ-band showed the most pronounced differences between Parkinson's disease and healthy control groups, further analysis focussed on this band. Tsallis entropy was then compared across groups with 16 psychological test scores at baseline and follow-ups at 6 months and 3 years. In group comparison, patients with Parkinson's disease showed lower Tsallis entropy than healthy control participants. Cognitive deterioration at 3 years was correlated with Tsallis entropy in the eyes-open condition (P < 0.00079), whereas correlation at 6 months was not yet significant. Tsallis entropy measured in the eyes-closed condition did not correlate with cognitive outcome. In conclusion, the lower the EEG entropy levels at baseline in the eyes-open condition, the higher the probability of cognitive decline over 3 years. This makes Tsallis entropy a candidate prognostic biomarker for dementia in Parkinson's disease. The ability of the cortex to execute complex functions underlies cognitive health, whereas cognitive decline might clinically appear when compensatory capacity is exhausted.

9-Methyl-ß-carboline inhibits monoamine oxidase activity and stimulates the expression of neurotrophic factors by astrocytes.

ß-Carbolines (BC) are pyridoindoles, which can be found in various exogenous and endogenous sources. Recent studies revealed neurostimulative, neuroprotective, neuroregenerative and anti-inflammatory effects of 9-methyl-BC (9-Me-BC). Additionally, 9-me-BC increased neurite outgrowth of dopaminergic neurons independent of dopamine uptake into these neurons. In this study, the role of astrocytes in neurostimulative, neuroregenerative and neuroprotective properties of 9-me-BC was further explored.9-Me-BC exerted anti-proliferative effects without toxic properties in dopaminergic midbrain and cortical astrocyte cultures. The organic cation transporter (OCT) but not the dopamine transporter seem to mediate at least part the effect of 9-me-BC on astrocytes. Remarkably, 9-me-BC stimulated the gene expression of several important neurotrophic factors for dopaminergic neurons like Artn, Bdnf, Egln1, Tgfb2 and Ncam1. These factors are well known to stimulate neurite outgrowth and to show neuroprotective and neuroregenerative properties to dopaminergic neurons against various toxins. Further, we show that effect of 9-me-BC is mediated through phosphatidylinositol 3-kinase (PI3K) pathway. Additionally, 9-me-BC showed inhibitory properties to monoamine oxidase (MAO) activity with an IC50 value of 1 µM for MAO-A and of 15.5 µM for MAO-B. The inhibition of MAO by 9-me-BC might contribute to the observed increased dopamine content and anti-apoptotic properties in cell culture after 9-me-BC treatment in recent studies. Thus, 9-me-BC have a plethora of beneficial effects on dopaminergic neurons warranting its exploration as a new multimodal anti-parkinsonian medication.

Palladium embedded in SnO2 enhances the sensitivity of flame-made chemoresistive gas sensors.

Palladium is used commonly to enhance the performance of chemoresistive metal-oxide gas sensors. Typically, this enhancement is attributed to the presence of Pd clusters on the surface of their metal-oxide support (i.e. SnO2). Possible Pd incorporation or embedding into the support rarely has been considered. Here, SnO2 particles (15 - 21 nm in diameter measured by N2 adsorption) with different Pd contents (0 - 3 mol%) were prepared by flame spray pyrolysis (FSP). Leaching these particles with HNO3 and characterization by inductively coupled plasma - optical emission spectrometry (ICP-OES) indicated that only 36 - 60% of Pd have been removed (e.g., from the SnO2 surface). The rest was embedded within the SnO2 particles. Annealing prior to leaching decreased by ~30% that Pd surface content. Most interestingly, such SnO2 particles (with only embedded Pd) show higher sensor response to acetone, ethanol and CO at 350 °C compared to SnO2 particles containing both surface and embedded Pd (i.e. before leaching). As a result, such sensors can detect acetone with high (> 25) signal-to-noise ratio at levels down to 5 ppb at 50% relative humidity. Graphical abstractFlame-made SnO2 nanoparticles with embedded and surface Pd (triangles) exhibit lower sensor response to acetone, ethanol and CO than SnO2 from which the surface Pd had been removed by leaching (circles).

How to Improve Change-of-Direction Speed in Junior Team Sport Athletes-Horizontal, Vertical, Maximal, or Explosive Strength Training?

Keller, S, Koob, A, Corak, D, von Schöning, V, and Born, DP. How to improve change-of-direction speed in junior team sport athletes-Horizontal, vertical, maximal, or explosive strength training? J Strength Cond Res 34(2): 473-482, 2020-The purpose of the study was to compare the effects of 4 different training methods on change-of-direction (COD) speed in junior team sport athletes. Specifically, we investigated whether horizontal load training incorporating lateral acceleration and deceleration would induce superior performance adaptations with respect to COD speed, compared with common vertically oriented maximal strength (squats and deadlifts), explosive strength (power clean and high pull), and vertical jumping exercises. Male U15 team sport athletes (n = 45) were assigned to 1 of 4 groups and performed 2 intervention training sessions per week for 4 weeks, in addition to their usual sport-specific training. Before and after the training period, COD speed, countermovement and drop jump heights, 1-legged lateral jump, and standing long jump performance were assessed. All 4 training groups improved COD speed (p ≤ 0.01, effect size [ES] ≥1.35). Countermovement and 1-legged lateral jump performance improved with the horizontal load (p < 0.01, ES = 0.81 and p < 0.01, ES = 1.36), maximal (p = 0.01, ES = 0.56 and p < 0.01, ES = 1.14), and explosive strength training (p < 0.01, ES = 0.95 and p < 0.01, ES = 1.60, respectively). The standing long jump improved with the maximal (p < 0.01, ES = 1.14) and explosive strength training (p < 0.01, ES = 0.60). In conclusion, all 4 training methods improved the COD speed in junior U15 team sport athletes. These findings emphasize the importance of well-developed lower-body strength and power, which contribute to fast COD speed. From a practical perspective, conditioning programs for junior athletes can incorporate horizontally and vertically oriented exercises with similar effectiveness on COD speed.

OpenMolcas: From Source Code to Insight.

In this Article we describe the OpenMolcas environment and invite the computational chemistry community to collaborate. The open-source project already includes a large number of new developments realized during the transition from the commercial MOLCAS product to the open-source platform. The paper initially describes the technical details of the new software development platform. This is followed by brief presentations of many new methods, implementations, and features of the OpenMolcas program suite. These developments include novel wave function methods such as stochastic complete active space self-consistent field, density matrix renormalization group (DMRG) methods, and hybrid multiconfigurational wave function and density functional theory models. Some of these implementations include an array of additional options and functionalities. The paper proceeds and describes developments related to explorations of potential energy surfaces. Here we present methods for the optimization of conical intersections, the simulation of adiabatic and nonadiabatic molecular dynamics, and interfaces to tools for semiclassical and quantum mechanical nuclear dynamics. Furthermore, the Article describes features unique to simulations of spectroscopic and magnetic phenomena such as the exact semiclassical description of the interaction between light and matter, various X-ray processes, magnetic circular dichroism, and properties. Finally, the paper describes a number of built-in and add-on features to support the OpenMolcas platform with postcalculation analysis and visualization, a multiscale simulation option using frozen-density embedding theory, and new electronic and muonic basis sets.

Structural and functional analysis of an l-serine O-phosphate decarboxylase involved in norcobamide biosynthesis.

Structural diversity of natural cobamides (Cbas, B12 vitamers) is limited to the nucleotide loop. The loop is connected to the cobalt-containing corrin ring via an (R)-1-aminopropan-2-ol O-2-phosphate (AP-P) linker moiety. AP-P is produced by the l-threonine O-3-phosphate (l-Thr-P) decarboxylase CobD. Here, the CobD homolog SMUL_1544 of the organohalide-respiring epsilonproteobacterium Sulfurospirillum multivorans was characterized as a decarboxylase that produces ethanolamine O-phosphate (EA-P) from l-serine O-phosphate (l-Ser-P). EA-P is assumed to serve as precursor of the linker moiety of norcobamides that function as cofactors in the respiratory reductive dehalogenase. SMUL_1544 (SmCobD) is a pyridoxal-5'-phosphate (PLP)-containing enzyme. The structural analysis of the SmCobD apoprotein combined with the characterization of truncated mutant proteins uncovered a role of the SmCobD N-terminus in efficient l-Ser-P conversion.