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Purposes A fixed severe valgus knee is a surgical challenge. A safe post-operative Hip-Knee-Ankle angle (HKA) range of 180° ± 4 was recommended, but recent studies mentioned equal results from outliers of this range. Nevertheless, no distinction was made between varus and valgus knees, as well as over-corrected or under-corrected knees. Did post-operative nonaligned total knee replacements (TKR) from fixed severe valgus knees behave differently from the properly aligned population? Did over-corrected knees behave differently from under-corrected knees? Methods Through a multi-center retrospective cohort study, we provided 557 knees of at least 10° of minimal pre-operative valgus; in this population 75 presented a post-operative Hip-Knee-Ankle angle (HKA) outside of the 180° ± 4 range; 23 of them had at least 5° of varus; 52 of them had at least 5° of valgus. Median pre-operative HKA of the entire cohort was 194° (range 190–198). Median follow-up was 8 years (range 5–11); Knee Society Score (KSS) results, HKA, Femoral and Tibial Mechanical Angles (FMA, TMA) and complication rates were obtained. The outlier group (HKA ≤ 175 or ≥ 185) was compared to the control group (HKA 180 ± 4); over-corrected (HKA ≤ 175) and under-corrected (HKA ≥ 185) sub-groups were individually tested against the control group. Results The outlier group had a lower Final Knee Score than the aligned group ( p  = 0.023). In the over-corrected sub-group, median post-operative FMA was 88° (SD 4°) and median TMA was 87° (SD 4°). The complication rate was higher ( p  = 0.019). Knee ( p  = 0.018), Function ( p  = 0.034) and Final Knee Scores ( p  = 0.03) were statistically lower than in the control group. In the under-corrected sub-group, mean post-operative FMA was 93° (SD 2°) and mean TMA was 91° (SD 2°). The complication rate was lower ( p  = 0.019) and there was no difference with the control group concerning KSS. Conclusions In case of pre-operative fixed severe valgus knee, one should avoid over-correcting HKA angle and especially the TMA. Over-correction of a severe preoperative valgus in a post-operative varus was prejudicial for TKA survival. Keeping a severe valgus knee in low valgus to avoid using a more constrained implant and/or ligament releases will not decrease the 5–10 year implant survival and functional scores. Level of evidence Level IV—Case series.

The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity. We then construct the multimodal AI-severity score that includes 5 clinical and biological variables (age, sex, oxygenation, urea, platelet) in addition to the deep learning model. We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity (oxygenation, LDH, and CRP) explaining the measurable but limited 0.03 increase of AUC obtained when adding CT-scan information to clinical variables. Here, we show that when comparing AI-severity with 11 existing severity scores, we find significantly improved prognosis performance; AI-severity can therefore rapidly become a reference scoring approach. The SARS-COV-2 pandemic has put pressure on intensive care units, so that predicting severe deterioration early is a priority. Here, the authors develop a multimodal severity score including clinical and imaging features that has significantly improved prognostic performance in two validation datasets compared to previous scores.

We aimed to study whether social patterns of exposure to SARS-CoV-2 infection changed in France throughout the year 2020, in light to the easing of social contact restrictions. A population-based cohort of individuals aged 15 years or over was randomly selected from the national tax register to collect socio-economic data, migration history, and living conditions in May and November 2020. Home self-sampling on dried blood was proposed to a 10% random subsample in May and to all in November. A positive anti-SARS-CoV-2 ELISA IgG result against the virus spike protein (ELISA-S) was the primary outcome. The design, including sampling and post-stratification weights, was taken into account in univariate and multivariate analyses. Of the 134,391 participants in May, 107,759 completed the second questionnaire in November, and respectively 12,114 and 63,524 were tested. The national ELISA-S seroprevalence was 4.5% [95%CI: 4.0%-5.1%] in May and 6.2% [5.9%-6.6%] in November. It increased markedly in 18-24-year-old population from 4.8% to 10.0%, and among second-generation immigrants from outside Europe from 5.9% to 14.4%. This group remained strongly associated with seropositivity in November, after controlling for any contextual or individual variables, with an adjusted OR of 2.1 [1.7-2.7], compared to the majority population. In both periods, seroprevalence remained higher in healthcare professions than in other occupations. The risk of Covid-19 infection increased among young people and second-generation migrants between the first and second epidemic waves, in a context of less strict social restrictions, which seems to have reinforced territorialized socialization among peers.

Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening condition, and its diagnosis may be challenging. In particular, some cases show close similarities to sepsis (fever, organ failure, and high ferritin), but their treatment, while urgent, differ: prompt broad-spectrum antibiotherapy for sepsis and immunosuppressive treatment for HLH. We questioned whether monocyte human leucocyte antigen (mHLA)-DR could be a diagnostic marker for secondary HLH (sHLH). We retrospectively reviewed data from patients with a sHLH diagnosis and mHLA-DR quantification. mHLA-DR data from healthy children and children with septic shock, whose HLA-DR expression is reduced, from a previously published study were also included for comparison. Six patients with sHLH had mHLA-DR quantification. The median level of monocyte mHLA-DR expression in patients with sHLH [79,409 antibodies bound per cell (AB/C), interquartile range (IQR) (75,734-86,453)] was significantly higher than that in healthy children and those with septic shock (29,668 AB/C, IQR (24,335-39,199), and 7,493 AB/C, IQR (3,758-14,659), respectively). Each patient with sHLH had a mHLA-DR higher than our laboratory normal values. Four patients had a second mHLA-DR sampling 2 to 4 days after the initial analysis and treatment initiation with high-dose corticosteroids; for all patients, mHLA-DR decreased to within or close to the normal range. One patient with systemic juvenile idiopathic arthritis had repeated mHLA-DR measurements over a 200-day period during which she underwent four HLH episodes. mHLA-DR increased during relapses and normalized after treatment incrementation. In this small series, mHLA-DR was systematically elevated in patients with sHLH. Elevated mHLA-DR could contribute to sHLH diagnosis and help earlier distinction with septic shock.

This perspective paper considers thrombolysis in the context of ischemic strokes, intending to build eventually a numerical model capable of simulating the thrombolytic treatment and predicting patient outcomes. Numerical modeling is a scientific methodology based on an abstraction of a system but requires understanding their spatio-temporal interactions. However, although important, the current knowledge on thrombolysis is fragmented in contributions from which it is difficult to obtain a complete picture of the process, especially in a clinically relevant setup. This paper discusses, from a general point of view, how to develop a numerical model to describe the evolution of a patient clot under the action of a thrombolytic drug. We will present critical, yet fundamental, open questions that have emerged during this elaboration and discuss original experimental observations that challenge some of our current knowledge of thrombolysis.

At a crime scene, investigators are faced with a multitude of traces. Among them, biological traces are of primary interest for the rapid genetic-based identification of individuals. “Touch DNA” consists of invisible biological traces left by the simple contact of a person’s skin with objects. To date, these traces remain undetectable with the current methods available in the field. This study proposes a proof-of-concept for the original detection of touch DNA by targeting cell-derived fragments in addition to DNA. More specifically, adhesive-structure proteins (laminin, keratin) as well as carbohydrate patterns (mannose, galactose) have been detected with keratinocyte cells derived from a skin and fingermark touch-DNA model over two months in outdoor conditions. Better still, this combinatory detection strategy is compatible with DNA profiling. This proof-of-concept work paves the way for the optimization of tools that can detect touch DNA, which remains a real challenge in helping investigators and the delivery of justice.

The interferometric control of dissipation in a two-port system is a fruitful concept enabling the enhancement or cancellation of the input amplitudes as a function of their relative phases. Here, beyond the canonical configuration of Coherent Perfect Absorption (CPA), we apply this concept to two simultaneously excited strongly-coupled nanoscale electromechanical resonators submitted to independently controlled phase-shifted excitations. Both subsystems are read simultaneously by optical means allowing us to completely reconstruct the signature of coherent annihilation or amplification on both quadrature. We evidence that the mechanical modes amplitude can be enhanced or inhibited with respect to the case of single port excitation while phase experiences strong variations with the excitation imbalance and phase difference. Meanwhile, phase singularities with opposite topological charges are observed for mechanical normal modes. Close to the phase singularity, we demonstrate that the input of a weak phase modulation induces a large, pure phase modulation of the normal mode. These experimental demonstrations are fully modelled via the mechanical dynamical equations of our system. The interferometric control may open avenues for low-power amplitude controlled phase modulation schemes and vice-versa for potential switches and logical gates. Coherent perfect absorption allows to entirely dissipate the energy impinging on both single and multimode systems, but it typically does not allow for a control of the phase quadratures. Here, the authors implement coherent interferometric control of the phase quadratures in two strongly-coupled electromechanical nanoresonators.

Touch DNA, which can be found at crime scenes, consists of invisible biological traces deposited through a person’s skin’s contact with an object or another person. Many factors influence touch DNA transfer, including the “destination” substrate’s surface. The latter’s physicochemical characteristics (wettability, roughness, surface energy, etc.) will impact touch DNA deposition and persistence on a substrate. We selected a representative panel of substrates from objects found at crime scenes (glass, polystyrene, tiles, raw wood, etc.) to investigate the impact of these characteristics on touch DNA deposition and detection. These were shown to impact cell deposition, morphology, retention, and subsequent touch DNA genetic analysis. Interestingly, cell-derived fragments found within keratinocyte cells and fingermarks using in vitro touch DNA models could be successfully detected whichever the substrates’ physicochemistry by targeting cellular proteins and carbohydrates for two months, indoors and outdoors. However, swabbing and genetic analyses of such mock traces from different substrates produced informative profiles mainly for substrates with the highest surface free energy and therefore the most hydrophilic. The substrates’ intrinsic characteristics need to be considered to better understand both the transfer and persistence of biological traces, as well as their detection and collection, which require an appropriate methodology and sampling device to get informative genetic profiles.

One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient’s bloodstream, which breaks down the thrombi’s fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable. The causes of this variability remain unclear, and it is likely that some fundamental aspects still require thorough investigations. For that reason, we conducted in vitro flow-driven fibrinolysis experiments to study pure fibrin thrombi breakdown in controlled conditions and observed that the lysis front evolved non-linearly in time. To understand these results, we developed an analytical 1D lysis model in which the thrombus is considered a porous medium. The lytic cascade is reduced to a second-order reaction involving fibrin and a surrogate pro-fibrinolytic agent. The model was able to reproduce the observed lysis evolution under the assumptions of constant fluid velocity and lysis occurring only at the front. For adding complexity, such as clot heterogeneity or complex flow conditions, we propose a 3-dimensional mesoscopic numerical model of blood flow and fibrinolysis, which validates the analytical model’s results. Such a numerical model could help us better understand the spatial evolution of the thrombi breakdown, extract the most relevant physiological parameters to lysis efficiency, and possibly explain the failure of the clinical treatment. These findings suggest that even though real-world fibrinolysis is a complex biological process, a simplified model can recover the main features of lysis evolution.

This paper presents a navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a line finding algorithm and a control algorithm. The paper proposes several line finding algorithms (based on PEARL/Ruby approach) that extract lines from a LiDAR data set. Once the lines have been processed from the data set, a control algorithm filters these lines and, using a fuzzy controller, generates the wheel speed commands to move the robot among the crop rows. This navigation approach was tested using a simulator built on ROS middle-ware and Gazebo (the source codes of the simulation are available on GitHub). The results of the simulated experiments show that the proposed approach performs well for a large range of crop configurations (with or without considering weeds, with or without holes in the crop rows…).