Chiari malformation type I: a case-control association study of 58 developmental genes

Chiari malformation type I (CMI) is a disorder characterized by hindbrain overcrowding into an underdeveloped posterior cranial fossa (PCF), often causing progressive neurological symptoms. The etiology of CMI remains unclear and is most likely multifactorial. A putative genetic contribution to CMI is suggested by familial aggregation and twin studies. Experimental models and human morphometric studies have suggested an underlying paraxial mesoderm insufficiency. We performed a case-control association study of 303 tag single nucleotide polymorphisms (SNP) across 58 candidate genes involved in early paraxial mesoderm development in a sample of 415 CMI patients and 524 sex-matched controls. A subgroup of patients diagnosed with classical, small-PCF CMI by means of MRI-based PCF morphometry (n = 186), underwent additional analysis. The genes selected are involved in signalling gradients occurring during segmental patterning of the occipital somites (FGF8, Wnt, and retinoic acid pathways and from bone morphogenetic proteins or BMP, Notch, Cdx and Hox pathways) or in placental angiogenesis, sclerotome development or CMI-associated syndromes. Single-marker analysis identified nominal associations with 18 SNPs in 14 genes (CDX1, FLT1, RARG, NKD2, MSGN1, RBPJ1, FGFR1, RDH10, NOG, RARA, LFNG, KDR, ALDH1A2, BMPR1A) considering the whole CMI sample. None of these overcame corrections for multiple comparisons, in contrast with four SNPs in CDX1, FLT1 and ALDH1A2 in the classical CMI group. Multiple marker analysis identified a risk haplotype for classical CMI in ALDH1A2 and CDX1. Furthermore, we analyzed the possible contributions of the most significantly associated SNPs to different PCF morphometric traits. These findings suggest that common variants in genes involved in somitogenesis and fetal vascular development may confer susceptibility to CMI

Press reslease from the Premier and Tourism Minister, Mr Dunstan: New amenity block for Moonta Bay Caravan Park

Getting rid of the tubes: An assessment of the retention of functionalized multi-walled carbon nanotubes (MWNTs) in the organs of mice was carried out using single photon emission computed tomography and quantitative scintigraphy (see scheme). Increasing the degree of functionalization on MWNTs enhanced renal clearance, while lower functionalization promoted reticuloendethelial system accumulation

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods. MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions. ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models' prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR. ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods.MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions.ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models’ prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR.ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

Adaptación del puesto de trabajo y competitividad: Realidad u Utopía

La adaptación de los puestos de trabajo siempre ha sido un objeto de estudio para las empresas, ya sea porque asumen esta competencia mediante un servicio propio de prevención/ mancomunado o bien porque la externalicen mediante un servicio de prevención ajeno. Es por ello que el presente documento parte de dos objetivos, por un lado, estudiar si la adaptación de los puestos de trabajo es una realidad efectiva y, por otro lado, si ésta se realiza de manera óptima. Para concretar, se ha tomado como referencia una empresa multinacional con sede en Madrid cuya actividad se centra en el sector de la limpieza, jardinería, mantenimiento técnico, servicios auxiliares y de restauración, la cual anónimamente ha cedido tanto datos cuantitativos como cualitativos a nivel catalán. El análisis se centra, en primer lugar, en mostrar datos cuantitativos de esta empresa para mostrar si la adaptación de puestos es una realidad efectiva y, en segundo lugar, estudiar seis casos una vez estos han sido clasificados por el sistema de la Vigilancia de la Salud como aptos/as con limitaciones para ver si la adaptación que se lleva a cabo es efectiva y óptima

Adaptación del puesto de trabajo y competitividad: Realidad u Utopía

La adaptación de los puestos de trabajo siempre ha sido un objeto de estudio para las empresas, ya sea porque asumen esta competencia mediante un servicio propio de prevención/ mancomunado o bien porque la externalicen mediante un servicio de prevención ajeno. Es por ello que el presente documento parte de dos objetivos, por un lado, estudiar si la adaptación de los puestos de trabajo es una realidad efectiva y, por otro lado, si ésta se realiza de manera óptima. Para concretar, se ha tomado como referencia una empresa multinacional con sede en Madrid cuya actividad se centra en el sector de la limpieza, jardinería, mantenimiento técnico, servicios auxiliares y de restauración, la cual anónimamente ha cedido tanto datos cuantitativos como cualitativos a nivel catalán. El análisis se centra, en primer lugar, en mostrar datos cuantitativos de esta empresa para mostrar si la adaptación de puestos es una realidad efectiva y, en segundo lugar, estudiar seis casos una vez estos han sido clasificados por el sistema de la Vigilancia de la Salud como aptos/as con limitaciones para ver si la adaptación que se lleva a cabo es efectiva y óptima

First record of Peckia (Sarcodexia) lambens (Wiedemann, 1830) (Diptera: Sarcophagidae) parasitizing Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae) in Brazil

ABSTRACT: Collections of larvae of Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae) carried out in the field in three localities in the city of Campo Grande, Mato Grosso do Sul, Brazil, from October 2012 to March 2014, recorded the presence of three species of Diptera parasitizing Spodoptera frugiperda: two species of Tachinidae, Achytas incertus (Macquart, 1851) and Winthemia trinitatis Thompson, 1963, and one species of Sarcophagidae, Peckia (Sarcodexia) lambens (Wiedemann, 1830). The latter is identified for the first time parasitizing S. frugiperda in Brazil

Forward Modeling of a Pseudostreamer

International audienceIn this paper, we present an analysis of a pseudostreamer embedding a filament cavity, observed on 2015 April 18 on the solar southwest limb. We use the flux-rope insertion method to construct nonlinear force-free field (NLFFF) models constrained by observed Solar Dynamics Observatory (SDO)/AIA coronal structures and the SDO/Helioseismic Magnetic Imager photospheric magnetogram. The resulting magnetic field models are forward-modeled to produce synthetic data directly comparable to Mauna Loa Solar Observatory/Coronal Multichannel Polarimeter (CoMP) observations of the intensity and linear polarization of the Fe XIII 1074.7 nm infrared coronal emission line using FORWARD. In addition, we determine the location of quasi-separatrix layers in the magnetic models, producing a Q-map from which the signatures of magnetic null points and separatrices can be identified. An apparent magnetic null observed in linear polarization by CoMP is reproduced by the model and appears in the region of the 2D-projected magnetic null in the Q-map. Further, we find that the height of the CoMP null is better reproduced by our NLFFF model than by the synthetic data we produce with potential-field source-surface models, implying the presence of a flux rope in the northern lobe of the pseudostreamer

Chiari Malformation Type I : a Case-Control Association Study of 58 Developmental Genes

Chiari malformation type I (CMI) is a disorder characterized by hindbrain overcrowding into an underdeveloped posterior cranial fossa (PCF), often causing progressive neurological symptoms. The etiology of CMI remains unclear and is most likely multifactorial. A putative genetic contribution to CMI is suggested by familial aggregation and twin studies. Experimental models and human morphometric studies have suggested an underlying paraxial mesoderm insufficiency. We performed a case-control association study of 303 tag single nucleotide polymorphisms (SNP) across 58 candidate genes involved in early paraxial mesoderm development in a sample of 415 CMI patients and 524 sex-matched controls. A subgroup of patients diagnosed with classical, small-PCF CMI by means of MRI-based PCF morphometry (n = 186), underwent additional analysis. The genes selected are involved in signalling gradients occurring during segmental patterning of the occipital somites (FGF8, Wnt, and retinoic acid pathways and from bone morphogenetic proteins or BMP, Notch, Cdx and Hox pathways) or in placental angiogenesis, sclerotome development or CMI-associated syndromes. Single-marker analysis identified nominal associations with 18 SNPs in 14 genes (CDX1, FLT1, RARG, NKD2, MSGN1, RBPJ1, FGFR1, RDH10, NOG, RARA, LFNG, KDR, ALDH1A2, BMPR1A) considering the whole CMI sample. None of these overcame corrections for multiple comparisons, in contrast with four SNPs in CDX1, FLT1 and ALDH1A2 in the classical CMI group. Multiple marker analysis identified a risk haplotype for classical CMI in ALDH1A2 and CDX1. Furthermore, we analyzed the possible contributions of the most significantly associated SNPs to different PCF morphometric traits. These findings suggest that common variants in genes involved in somitogenesis and fetal vascular development may confer susceptibility to CMI

Synthesis and characterization of a carbon nanotube-dendron series for efficient siRNA delivery

International audienceA new series of dendron-functionalized multiwalled carbon nanotube (MWNT) derivatives, characterized by the presence of numerous positively charged tetraalkyl ammonium salts at the periphery of the dendron, has been synthesized. The positive charges on the MWNT surface, coupled with the unique ability of carbon nanotubes (CNTs) to penetrate cell membranes, make the new derivatives potentially ideal vectors for siRNA delivery. Using a fluorescently labeled, noncoding siRNA sequence, we demonstrate that cytoplasmic delivery of the nucleic acid is remarkably increased throughout the different dendron generations. The work reported here highlights the fact that dendron-functionalized CNTs can be rationally designed as efficient carriers of siRNA that can eventually lead to gene silencing