Vibrationally-resolved RIXS reveals OH-group formation in oxygen redox active Li-ion battery cathodes.

Vibrationally-resolved resonant inelastic X-ray scattering (VR-RIXS) at the O K-edge is emerging as a powerful tool for identifying embedded molecules in lithium-ion battery cathodes. Here, we investigate two known oxygen redox-active cathode materials: the commercial LixNi0.90Co0.05Al0.05O2 (NCA) used in electric vehicles and the high-capacity cathode material Li1.2Ni0.13Co0.13Mn0.54O2 (LRNMC) for next-generation Li-ion batteries. We report the detection of a novel vibrational RIXS signature for Li-ion battery cathodes appearing in the O K pre-peak above 533 eV that we attribute to OH-groups. We discuss likely locations and pathways for OH-group formation and accumulation throughout the active cathode material. Initial-cycle behaviour for LRNMC shows that OH-signal strength correlates with the cathodes state of charge, though reversibility is incomplete. The OH-group RIXS signal strength in long-term cycled NCA is retained. Thus, VR-RIXS offers a path for gaining new insights to oxygen reactions in battery materials.

Inferring compound heterozygosity from large-scale exome sequencing data.

Recessive diseases arise when both copies of a gene are impacted by a damaging genetic variant. When a patient carries two potentially causal variants in a gene, accurate diagnosis requires determining that these variants occur on different copies of the chromosome (that is, are in trans) rather than on the same copy (that is, in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. Here we developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in the Genome Aggregation Database (v2, n = 125,748 exomes). Our approach estimates phase with 96% accuracy, both in trio data and in patients with Mendelian conditions and presumed causal compound heterozygous variants. We provide a public resource of phasing estimates for coding variants and counts per gene of rare variants in trans that can aid interpretation of rare co-occurring variants in the context of recessive disease.

A genomic mutational constraint map using variation in 76,156 human genomes.

The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders1-4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)-the largest public open-access human genome allele frequency reference dataset-and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.

A preliminary quantification of the clinical gesture during vacuum assisted delivery on a training dummy.

BACKGROUND: The vacuum assisted delivery represents, in France, the most used operative vaginal delivery technique. The purpose was to provide a preliminar quantification of the operator's hand kinematics while performing a vacuum assisted delivery. METHODS: A group of 21 participants composed of 12 trainees and 9 obstetricians were recorded performing a vacuum assisted delivery on a training dummy, the matching fetal presentation was a left occiput anterior position. FINDINGS: The mean movement was composed of a first phase corresponding to a descendant pull, followed by an ascendant finish of the gesture. No significative difference were found between the trainees and the obstetricians' mean gesture. INTERPRETATION: This is the first quantification of the clinical gesture associated with the vacuum assisted delivery.

Characterization of the skin-to-bone mechanical interaction on porcine scalp: A combined experimental and computational approach.

Fasciae are soft tissues permitting a large but finite sliding between organs, but also between skin and its underlying elements. The contribution of fasciae has been seldomly reported in the literature, and is usually neglected or overly simplified within simulations. In the present contribution, we propose to use peeling tests in order to quantify the skin-to-bone interaction associated with a simple computational approach based on a geometrical modeling of the skin-to-bone interface. To this aim, a new experimental set up combined with a computational model to characterize the skin-to-bone interaction were proposed. The current work is devoted to the porcine scalp complex since it constitutes a common mechanical surrogate for the human scalp complex. The ad hoc computational approach and peeling set up were firstly evaluated on a validation material, before being used to characterize the skin-to-bone interaction within 6 porcine specimens harvested from the scalp. Our experimental setup allowed to measure the peeling response of porcine scalp, showing a three-regimes response including a plateau force. The computational approach satisfyingly reproduced the peeling response based uniquely on experimental-based parameters and on a discrete modeling of skin-to-bone interface. The presented methodology is a first attempt to propose a computationally efficient geometrically based model able to take into account the skin-to-bone interaction up to failure and corroborated by experimental data, and may be largely extended to the modeling of soft interactions between biological human tissues in the future.

Inferring compound heterozygosity from large-scale exome sequencing data.

Recessive diseases arise when both the maternal and the paternal copies of a gene are impacted by a damaging genetic variant in the affected individual. When a patient carries two different potentially causal variants in a gene for a given disorder, accurate diagnosis requires determining that these two variants occur on different copies of the chromosome (i.e., are in trans) rather than on the same copy (i.e. in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. We developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in exome sequencing data from the Genome Aggregation Database (gnomAD v2, n=125,748). When applied to trio data where phase can be determined by transmission, our approach estimates phase with 95.7% accuracy and remains accurate even for very rare variants (allele frequency < 1×10-4). We also correctly phase 95.9% of variant pairs in a set of 293 patients with Mendelian conditions carrying presumed causal compound heterozygous variants. We provide a public resource of phasing estimates from gnomAD, including phasing estimates for coding variants across the genome and counts per gene of rare variants in trans, that can aid interpretation of rare co-occurring variants in the context of recessive disease.

Hepaticojejunostomy for bile duct injury: state of the art.

BACKGROUND: Hepaticojejunostomy (HJ) is the gold standard procedure for the reconstruction of the bile duct in many benign and malignant situations. One of the major situation is the bile duct injury (BDI) after cholecystectomy, either for early or late repair. This procedure presents some specificities associated to a debated management of BDI. PURPOSE: This article provides a state-of-the-art of the hepaticojejunostomy procedure focusing on bile duct injury including its indications and outcomes CONCLUSION: Performed at the right moment and respecting the technical rules, HJ provides a restoration of the biliary patency in the long term of 80 to 90%. It is the main surgical technique to repair BDI. Complications and failure of this procedure can be difficult to manage. That is why the primary repair requires an appropriate multidisciplinary approach associated with an expert high quality surgical technique.

An alternative generic groundwater-to-indoor air attenuation factor for application in commercial, industrial, and other nonresidential settings.

The default groundwater-to-indoor air attenuation factor (AF) of 10-3 (0.001) to assess the vapor intrusion (VI) pathway and generate VI screening levels for groundwater was developed by the United States Environmental Protection Agency (EPA) based on chlorinated volatile organic compound (VOC) indoor air and groundwater data collected in residential buildings and compiled in EPA's 2012 VI database. In their VI guidance published in 2015, EPA recognized that this default AF may be overly conservative for nonresidential buildings. In 2015, the Department of Defense (DoD) began developing a first-of-its-kind VI database to assess AFs at commercial and industrial buildings at DoD installations and support the development of alternative generic AF values. This database was expanded in 2019 to include 76 buildings at 22 DoD installations across the United States and is comparable in size to the EPA VI database. The DoD database includes chlorinated VOC data from groundwater and indoor air samples collected from multiple sampling zones within these buildings. Empirical groundwater-to-indoor air AFs were calculated using similar screening methods employed by EPA, including a source strength screen, to filter out potential background source contributions unrelated to VI. Analysis of indoor air-groundwater data pairs found that there is more attenuation occurring from groundwater to indoor air in DoD commercial and industrial buildings relative to residential buildings and that the DoD buildings' AFs are one to four orders of magnitude lower than EPA's residential-based default of 10-3. The results support the use of a generic groundwater AF of 10-4 (0.0001) to support VI assessment and develop groundwater screening levels specific to large commercial and industrial buildings as an alternative to the residential default AF.Implications: The use of groundwater-to-indoor air attenuation factors (AFs) is a key component of vapor intrusion (VI) pathway assessments and VI screening-level development for groundwater. Currently, the United States Environmental Protection Agency (EPA) and many state regulatory agencies use a default groundwater AF of 10-3 (0.001) based on chlorinated volatile organic compound (VOC) data collected in residential buildings. VI assessment data collected at Department of Defense (DoD) installations indicate that there is significantly more groundwater-to-indoor air attenuation occurring at DoD commercial and industrial buildings. For that reason, the default AF of 10-3 results in groundwater screening levels that are overestimating VI-related risks in these types of building. The DoD data support the use of a generic groundwater AF of 10-4 (0.0001) for conducting VI assessment and developing groundwater screening levels at large commercial and industrial buildings.

A flexible design framework to design graded porous bone scaffolds with adjustable anisotropic properties.

Since the success of bone regenerative medicine depends on scaffold morphological and mechanical properties, numerous scaffolds designs have been proposed in the last decade, including graded structures that are suited to enhance tissue ingrowth. Most of these structures are based either on foams with a random pore definition, or on the periodic repetition of a unit cell (UC). These approaches are limited by the range of target porosities and obtained effective mechanical properties, and do not permit to easily generate a pore size gradient from the core to the periphery of the scaffold. In opposition, the objective of the present contribution is to propose a flexible design framework to generate various three-dimensional (3D) scaffolds structures including cylindrical graded scaffolds from the definition of a UC by making use of a non-periodic mapping. Conformal mappings are firstly used to generate graded circular cross-sections, while 3D structures are then obtained by stacking the cross-sections with or without a twist between different scaffold layers. The effective mechanical properties of different scaffold configurations are presented and compared using an energy-based efficient numerical method, pointing out the versatility of the design procedure to separately govern longitudinal and transverse anisotropic scaffold properties. Among these configurations, a helical structure exhibiting couplings between transverse and longitudinal properties is proposed and permits to extend the adaptability of the proposed framework. In order to investigate the capacity of common additive manufacturing techniques to fabricate the proposed structures, a subset of these configurations is elaborated using a standard SLA setup, and subjected to experimental mechanical testing. Despite observed geometric differences between the initial design and the actual obtained structures, the effective properties are satisfyingly predicted by the proposed computational method. Promising perspectives are offered concerning the design of self-fitting scaffolds with on-demand properties depending on the clinical application.

Impacts of production conditions on goat milk vitamin, carotenoid contents and colour indices.

The content, composition and variation of vitamin compounds in goat milk have been little studied. An experimental design was based on 28 commercial farms, selected considering the main feeding system (based on main forage and especially pasture access), goat breed (Alpine vs Saanen) and reproductive management (seasonal reproduction), in the main French goat milk production area. Each farm received two visits (spring and autumn) that included a survey on milk production conditions and bulk milk sampling. Milk vitamins (A, E, B2, B6, B9, B12) and carotenoid concentrations plus colour indices were evaluated. A stepwise approach determined the variables of milk production conditions that significantly altered milk indicators. The main forage in the diet was the major factor altering goat milk vitamin and carotenoid concentrations and colour indices. Bulk milk from goats eating fresh grass as forage was richer in α-tocopherol (+64%), pyridoxal (+35%) and total vitamin B6 (+31%), and b* index (characterising milk yellowness in the CIELAB colour space) was also higher (+12%) than in milk from goats eating conserved forages. In milk from goats eating fresh grass, concentrations of pyridoxamine, lutein and total carotenoids were higher than in milk of goats fed corn silage (+24, +118 and +101%, respectively), and retinol and α-tocopherol concentrations were higher than in milk of goats fed partially dehydrated grass (+45 and +55%). Vitamin B2 concentration was higher in milk of goats eating fresh grass than in milk of goats fed hay or corn silage as forage (+10%). However, bulk milk when goats had access to fresh grass was significantly poorer in vitamin B12 than when fed corn silage (-46%) and in γ-tocopherol (-31%) than when fed conserved forage. Alpine goats produced milk with higher vitamin B2 and folate concentrations than Saanen goats (+18 and +14%, respectively). Additionally, the milk colour index that discriminates milks based on their yellow pigment contents was 7% higher in milk from Alpine than Saanen herds, but milk from Saanen goats was richer in lutein (+46%). Goat milks were richer in vitamins B2 and B12 and folates, but poorer in vitamin B6 in autumn than in spring (+12, +133, +15 and -13%, respectively). This work highlights that goat milk vitamin and carotenoid concentrations and colour indices vary mainly according to the main forage of the diet and secondly according to the breed and season.

Regression trees to identify combinations of farming practices that achieve the best overall intrinsic quality of milk.

Many studies over the last 30 years have shown the effects of farming practices on milk compounds. Combinations of practices may have antagonistic or synergistic effects on milk compounds, but these combination effects remain underinvestigated. Research needs to focus on overall intrinsic milk quality (including sensory, technological, health, and nutritional dimensions) and identify the combinations that can optimize it. The aim of this study was to identify which combinations of farming practices achieved the best scores for sensory, technological, health, and nutritional dimensions and for overall intrinsic milk quality. Ninety-nine private farms were visited once each to sample their bulk tank milk and survey their farming practices. The surveyed practices concerned herd characteristics, feeding management, housing conditions, and milking and milk storage conditions on the day of test. Analyses of bulk tank milk were designed to evaluate the overall intrinsic quality of the milk for 2 target products: raw milk cheese and semi-skimmed UHT milk. Regression trees were then used to identify the combinations of farming practices that achieved the best scores on each dimension and on overall intrinsic quality of the milk. Breed and diet (type of forage) were the most influential factors for sensory and health dimensions and for technological and nutritional dimension scores, respectively, in the cheese assessment. Overall cheese quality was highly positively correlated with these 4 dimension scores. Therefore, breed and diet emerged as the most influential practices in the regression tree for overall cheese quality. However, the combinations of practices that resulted in the best quality scores differed according to dimension studied and product targeted. This suggests that advice on farming practices to improve intrinsic milk quality needs to be adapted according to the end-purpose of the collected milk. This innovative approach combining on-farm data and regression trees provides farm managers with a valuable and practical tool to prioritize practices in terms of their role in shaping milk quality, and to identify the combinations of practices that promote good milk quality and practice thresholds or modalities needed to achieve it.

Analysis of suction-based gripping strategies in wildlife towards future evolutions of the obstetrical suction cup.

The design of obstetrical suction cups used for vacuum assisted delivery has not substantially evolved through history despite of its inherent limitations. The associated challenges concern both the decrease of risk of soft tissue damage and failure of instrumental delivery due to detachment of the cup. The present study firstly details some of the suction-based strategies that have been developed in wildlife in order to create and maintain an adhesive contact with potentially rough and uneven substratum in dry or wet environments. Such strategies have permitted the emergence of bioinspired suction-based devices in the fields of robotics or biomedical patches that are briefly reviewed. The objective is then to extend the observations of such suction-based strategies toward the development of innovative medical suction cups. We firstly conclude that the overall design, shape and materials of the suction cups could be largely improved. We also highlight that the addition of a patterned surface combined with a viscous fluid at the interface between the suction cup and scalp could significantly limit the detachment rate and the differential pressure required to exert a traction force. In the future, the development of a computational model including a detailed description of scalp properties should allow to experiment various designs of bioinspired suction cups.

Polygenic Health Index, General Health, and Pleiotropy: Sibling Analysis and Disease Risk Reduction.

We construct a polygenic health index as a weighted sum of polygenic risk scores for 20 major disease conditions, including, e.g., coronary artery disease, type 1 and 2 diabetes, schizophrenia, etc. Individual weights are determined by population-level estimates of impact on life expectancy. We validate this index in odds ratios and selection experiments using unrelated individuals and siblings (pairs and trios) from the UK Biobank. Individuals with higher index scores have decreased disease risk across almost all 20 diseases (no significant risk increases), and longer calculated life expectancy. When estimated Disability Adjusted Life Years (DALYs) are used as the performance metric, the gain from selection among ten individuals (highest index score vs average) is found to be roughly 4 DALYs. We find no statistical evidence for antagonistic trade-offs in risk reduction across these diseases. Correlations between genetic disease risks are found to be mostly positive and generally mild. These results have important implications for public health and also for fundamental issues such as pleiotropy and genetic architecture of human disease conditions.

Prediction of Cognitive Decline for Enrichment of Alzheimer's Disease Clinical Trials.

BACKGROUND: A key issue to Alzheimer's disease clinical trial failures is poor participant selection. Participants have heterogeneous cognitive trajectories and many do not decline during trials, which reduces a study's power to detect treatment effects. Trials need enrichment strategies to enroll individuals who are more likely to decline. OBJECTIVES: To develop machine learning models to predict cognitive trajectories in participants with early Alzheimer's disease and presymptomatic individuals over 24 and 48 months respectively. DESIGN: Prognostic machine learning models were trained from a combination of demographics, cognitive tests, APOE genotype, and brain imaging data. SETTING: Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), National Alzheimer's Coordinating Center (NACC), Open Access Series of Imaging Studies (OASIS-3), PharmaCog, and a Phase 3 clinical trial in early Alzheimer's disease were used for this study. PARTICIPANTS: A total of 2098 participants who had demographics, cognitive tests, APOE genotype, and brain imaging data, as well as follow-up visits for 24-48 months were included. MEASUREMENTS: Baseline magnetic resonance imaging, cognitive tests, demographics, and APOE genotype were used to separate decliners, defined as individuals whose CDR-Sum of Boxes scores increased during a predefined time window, from stable individuals. A prognostic model to predict decline at 24 months in early Alzheimer's disease was trained on 1151 individuals who had baseline diagnoses of mild cognitive impairment and Alzheimer's dementia from ADNI and NACC. This model was validated on 115 individuals from a placebo arm of a Phase 3 clinical trial and 76 individuals from the PharmaCog dataset. A second prognostic model to predict decline at 48 months in presymptomatic populations was trained on 628 individuals from ADNI and NACC who were cognitively unimpaired at baseline. This model was validated on 128 individuals from OASIS-3. RESULTS: The models achieved up to 79% area under the curve (cross-validated and out-of-sample). Power analyses showed that using prognostic models to recruit enriched cohorts of predicted decliners can reduce clinical trial sample sizes by as much as 51% while maintaining the same detection power. CONCLUSIONS: Prognostic tools for predicting cognitive decline and enriching clinical trials with participants at the highest risk of decline can improve trial quality, derisk endpoint failures, and accelerate therapeutic development in Alzheimer's disease.

The Validity of Perceived Recovery Status as a Marker of Daily Recovery Following a High-Volume Back-Squat Protocol.

Although a variety of tools to monitor recovery have been developed, many are impractical for daily use due to cost, time, and challenges with interpretation. The Perceived Recovery Status (PRS) scale was recently developed as an expeditious, noninvasive tool to assess recovery status. While PRS has been strongly associated with repeated sprinting performance, a paucity of research exists relating PRS and performance recovery following resistance exercise. PURPOSE: The purpose of this study was to evaluate the sensitivity of PRS as a subjective marker of recovery up to 72 hours after a high-volume back-squat protocol. METHODS: Eleven resistance-trained men reported to the laboratory on 5 separate occasions (1 familiarization session and 4 testing sessions). The first testing session was considered the baseline session and consisted of a nonfatiguing performance assessment (ie, countermovement jumps and back squats) and a fatiguing back-squat protocol of 8 sets of 10 at 70% 1-repetition maximum separated by 2 minutes of recovery. Participants returned 24, 48, and 72 hours following baseline to provide a PRS rating and complete the performance assessment. RESULTS: Repeated-measures correlations revealed strong associations between PRS countermovement jump (r = .84) and mean bar velocity (r = .80) (both P < .001). CONCLUSIONS: The current findings suggest that PRS can be used as a method to effectively assess daily recovery following a fatiguing bout of resistance exercise. Practitioners are cautioned that the relationship between PRS and performance recovery is individualized, and equivalent PRS scores between individuals are not indicative of similar recovery.

Optical phased array neural probes for beam-steering in brain tissue.

Implantable silicon neural probes with integrated nanophotonic waveguides can deliver patterned dynamic illumination into brain tissue at depth. Here, we introduce neural probes with integrated optical phased arrays and demonstrate optical beam steering in vitro. Beam formation in brain tissue is simulated and characterized. The probes are used for optogenetic stimulation and calcium imaging.