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Abstract Background This paper aimed to describe the diagnostic service trajectory of families of children with autism or intellectual disability in the province of Québec and identify predictors of parents’ perceptions of its quality. Methods The Evaluation of the services Trajectory in Autism by Parents instrument was completed by 259 parents at an assessment clinic. Children’s clinical records were also examined. Results On average 26 months elapsed between their first concerns and their child’s diagnosis, a period during which few (25%) received support. Parents’ evaluations were generally positive but were lower for the accessibility of the pre-assessment phase and the flexibility of the assessment process. Longer delays and a greater number of professionals consulted were associated with lower quality ratings. Some language-, immigration status-, and income-related differences in families’ appraisals were noted. Conclusion The diagnostic trajectory for neurodevelopmental disorders within public services in Québec presents some efficiency and accessibility challenges. Possible improvements are proposed to facilitate screening and to support families throughout this phase of their trajectory.

There is a need to develop interventions to slow or reverse the degeneration of dopamine neurons in Parkinson’s disease after diagnosis. Given that preclinical and clinical studies suggest benefits of dietary n-3 polyunsaturated fatty acids, such as docosahexaenoic acid, and exercise in Parkinson’s disease, we investigated whether both could synergistically interact to induce recovery of the dopaminergic pathway. First, mice received a unilateral stereotactic injection of 6-hydroxydopamine into the striatum to establish an animal model of nigrostriatal denervation. Four weeks after lesion, animals were fed a docosahexaenoic acid-enriched or a control diet for the next 8 weeks. During this period, the animals had access to a running wheel, which they could use or not. Docosahexaenoic acid treatment, voluntary exercise, or the combination of both had no effect on (i) distance traveled in the open field test, (ii) the percentage of contraversive rotations in the apomorphine-induction test or (iii) the number of tyrosine-hydroxylase-positive cells in the substantia nigra pars compacta. However, the docosahexaenoic acid diet increased the number of tyrosine-hydroxylase-positive terminals and induced a rise in dopamine concentrations in the lesioned striatum. Compared to docosahexaenoic acid treatment or exercise alone, the combination of docosahexaenoic acid and exercise (i) improved forelimb balance in the stepping test, (ii) decreased the striatal DOPAC/dopamine ratio and (iii) led to increased dopamine transporter levels in the lesioned striatum. The present results suggest that the combination of exercise and docosahexaenoic acid may act synergistically in the striatum of mice with a unilateral lesion of the dopaminergic system and provide support for clinical trials combining nutrition and physical exercise in the treatment of Parkinson’s disease.

Background: Individuals with affective-prosodic deficits have difficulty understanding or expressing emotions and attitudes through prosody. Affective prosody disorders can occur in multiple neurological conditions, but the limited knowledge about the clinical groups prone to deficits complicates their identification in clinical settings. Additionally, the nature of the disturbance underlying affective prosody disorder observed in different neurological conditions remains poorly understood. Aims: To bridge these knowledge gaps and provide relevant information to speech-language pathologists for the management of affective prosody disorders, this study provides an overview of research findings on affective-prosodic deficits in adults with neurological conditions by answering two questions: (1) Which clinical groups present with acquired affective prosodic impairments following brain damage? (2) Which aspects of affective prosody comprehension and production are negatively affected in these neurological conditions? Methods & Procedures: We conducted a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. A literature search was undertaken in five electronic databases (MEDLINE, PsycINFO, EMBASE, CINAHL and Linguistics, and Language Behavior Abstracts) to identify primary studies reporting affective prosody disorders in adults with neurological impairments. We extracted data on clinical groups and characterised their deficits based on the assessment task used. Outcomes & Results: The review of 98 studies identified affective-prosodic deficits in 17 neurological conditions. The task paradigms typically used in affective prosody research (discrimination, recognition, cross-modal integration, production on request, imitation and spontaneous production) do not target the processes underlying affective prosody comprehension and production. Therefore, based on the current state of knowledge, it is not possible to establish the level of processing at which impairment occurs in clinical groups. Nevertheless, deficits in the comprehension of affective prosody are observed in 14 clinical groups (mainly recognition deficits) and deficits in the production of affective prosody (either on request or spontaneously) in 10 clinical groups. Neurological conditions and types of deficits that have not been investigated in many studies are highlighted. Conclusions & Implications: The aim of this scoping review was to provide an overview on acquired affective prosody disorders and to identify gaps in knowledge that warrant further investigation. Deficits in the comprehension or production of affective prosody are common to numerous clinical groups with various neurological conditions. However, the underlying cause of affective prosody disorders across them is still unknown. Future studies should implement standardised assessment methods with specific tasks based on a cognitive model to identify the underlying deficits of affective prosody disorders.

During the diagnostic evaluation period for autism or intellectual disability (ID), families of young children are at risk for poor adjustment. The present study aimed to document family quality of life (FQOL), along with associated risk and protective factors, during this critical step of families' services trajectory. FQOL was measured in a large sample of families of children recently diagnosed with a neurodevelopmental disorder and examined in relation to the type of services received, children's clinical profile, and family variables. FQOL was related to types of services, children's challenging behavior, parenting stress, and several aspects of family composition and status. These findings highlight a need for mental health support for parents, coaching interventions for challenging behaviors, and family-centered supports.

Abstract One of the main burdens in the treatment of diseases is imputable to the delay between the appearance of molecular dysfunctions in the first affected disease cells and their presence in sufficient number for detection in specific tissues or organs. This delay obviously plays in favor of disease progression to an extent that makes efficient treatments difficult, as they arrive too late. The development of a novel medical strategy, termed cell-based interception and precision medicine, seeks to identify dysfunctional cells early, when tissue damages are not apparent and symptoms not yet present, and develop therapies to treat diseases early. Central to this strategy is the use of single-cell technologies that allow detection of molecular changes in cells at the time of phenotypical bifurcation from health to disease. In this article we describe a general procedure to support such an approach applied to neurodegenerative disorders. This procedure combines four components directed towards highly complementary objectives: 1) a high-performance single-cell proteomics (SCP) method (Detect), 2) the development of disease experimental cell models and predictive computational models of cell trajectories (Understand), 3) the discovery of specific targets and personalized therapies (Cure), and 4) the creation of a community of collaborating laboratories to accelerate the development of this novel medical paradigm (Collaborate). A global initiative named 37TrillionCells (37TC) was launched to advance the development of cell-based interception and precision medicine.

Neutrophils are the first immune cells to reach inflamed sites and contribute to the pathogenesis of chronic inflammatory skin diseases. Yet, little is known about the pattern of neutrophil infiltration in inflamed skin in vivo and the mechanisms mediating their recruitment. Here, we provide insight into the dynamics of neutrophil infiltration in skin in response to acute or repeated inflammatory stress, highlighting a novel keratinocyte- and keratin 17 (K17)-dependent mechanism that regulates neutrophil recruitment to inflamed skin. We used the phorbol ester TPA and UVB, alone or in combination, to induce sterile inflammation in mouse skin. A single TPA treatment results in a neutrophil influx in the dermis that peaks at 12 h and resolves within 24 h. A subsequent TPA treatment or a UVB challenge, when applied 24 h but not 48 h later, accelerates, amplifies, and prolongs neutrophil infiltration. This transient amplification response (TAR) is mediated by local signals in inflamed skin, can be recapitulated in ex vivo culture, and involves the K17-dependent sustainment of protein kinase Cα (PKCα) activity and release of chemoattractants by stressed keratinocytes. K17 binds RACK1, a scaffold protein essential for PKCα activity. The N-terminal head domain of K17 is crucial for its association with RACK1 and regulation of PKCα activity. Analysis of RNAseq data reveals a signature consistent with TAR and PKCα activation in inflammatory skin diseases. These findings uncover a novel, keratin-dependent mechanism that amplifies neutrophil recruitment in skin under stress, with direct implications for inflammatory skin disorders.

Syphilis is known as the great masquarader. We describe a case of a young patient with an atypical chancre.

Abstract. Introduction:. Isolating the effect of an intervention from the natural course and fluctuations of a condition is a challenge in any clinical trial, particularly in the field of pain. Regression to the mean (RTM) may explain some of these observed fluctuations. Objectives:. In this paper, we describe and quantify the natural trajectory of questionnaire scores over time, based on initial scores. Methods:. Twenty-seven untreated chronic low back pain patients and 25 healthy controls took part in this observational study, wherein they were asked to complete an array of questionnaires commonly used in pain studies during each of 3 visits (V1, V2, V3) at the 2-month interval. Scores at V1 were classified into 3 subgroups (extremely high, normal, and extremely low), based on z-scores. The average delta (∆ = V2 − V1) was calculated for each subgroup, for each questionnaire, to describe the evolution of scores over time based on initial scores. This analysis was repeated with the data for V2 and V3. Results:. Our results show that high initial scores were widely followed by more average scores, while low initial scores tended to be followed by similar (low) scores. Conclusion:. These trajectories cannot be attributable to RTM alone because of their asymmetry, nor to the placebo effect as they occurred in the absence of any intervention. However, they could be the result of an Effect of Care, wherein participants had meaningful improvements simply from taking part in a study. The improvement observed in patients with high initial scores should be carefully taken into account when interpreting results from clinical trials.

Abstract Adolescent idiopathic scoliosis is a complex three-dimensional deformity of the spine, the moderate forms of which require treatment with an orthopedic brace. Existing brace design approaches rely mainly on empirical manual processes, vary considerably depending on the training and expertise of the orthotist, and do not always guarantee biomechanical effectiveness. To address these issues, we propose a new automated design method for creating bespoke nighttime braces requiring virtually no user input in the process. From standard biplanar radiographs and a surface topography torso scan, a personalized finite element model of the patient is created to simulate bracing and the resulting spine growth over the treatment period. Then, the topography of an automatically generated brace is modified and simulated over hundreds of iterations by a clinically driven optimization algorithm aiming to improve brace immediate and long-term effectiveness while respecting safety thresholds. This method was clinically tested on 17 patients prospectively recruited. The optimized braces showed a highly effective immediate correction of the thoracic and lumbar curves (70% and 90% respectively), with no modifications needed to fit the braces onto the patients. In addition, the simulated lumbar lordosis and thoracic apical rotation were improved by 5° ± 3° and 2° ± 3° respectively. Our approach distinguishes from traditional brace design as it relies solely on biomechanically validated models of the patient’s digital twin and a design strategy that is entirely abstracted from empirical knowledge. It provides clinicians with an efficient way to create effective braces without relying on lengthy manual processes and variable orthotist expertise to ensure a proper correction of scoliosis.

This paper introduces a novel deep-learning assisted video list decoding method for error-prone video transmission systems. Unlike traditional list decoding techniques, our proposed system uses a Transformer-based no-reference image quality assessment method to select the highest-scoring reconstructed video candidate after reception. Three new components are defined and used in the Transformer-assisted image quality evaluation metric: neighborhood-based patch fidelity aggregation, discriminant color texture transformation and ranking-constrained penalty loss function. We have also created our own database of non-uniformly distorted images, similar to those that might result from transmission errors, in a High Efficiency Video Coding (HEVC) context. In our specific testing context, our improved Transformer-assisted method has a decision accuracy of 100% for intra-coded image, while, for errors occurring in an inter image, it is 96%. Notably, in the few cases where a wrong choice is made, the selected candidate’s quality remains similar to the intact frame. Code: https://github.com/Yujing0926/Robust-Video-List-Decoding-Using-a-Deep-Learning-Approach.

In recent years, numerous studies have investigated the development of methods for video quality assessment (VQA). These studies have predominantly focused on specific types of video degradation tailored to the application of interest. However, natural videos or recent videos generated by users (UGC) present complex distortions that are not easy to model. Consequently, most current VQA approaches struggle to achieve high performance when applied to these videos. In this paper, we propose a novel Transformer-based architecture that extracts spatial distortion features and spatio-temporal features from videos in two specialized branches. The spatial distortion branch leverages a transfer learning strategy where a standard ViT is pre-trained using a masked autoencoder (MAE) self-supervised learning task, and then fine-tuned to predict the distortion type of corrupted images from the CSIQ database. The features from this branch capture degradation at the level of individual frames. On the other hand, the second branch employs a 3D Shifted Windows Transformer (Swin-T) to extract spatio-temporal features across multiple frames. Once again, we use transfer learning to extract rich features by pre-training this 3D Swin-T model on a video dataset for human action recognition. Finally, a temporal memory block hinged on an attention recurrent neural networks is proposed to predict the final video quality score from the spatio-temporal sequence of features. We evaluate the performance of our method on two popular UGC databases, namely KoNViD-1k and LIVE-VQC. Results show it outperforms state-of-the-art models on the KoNViD-1k database, achieving a SROCC performance of 0.927 and a PLCC of 0.925, while also delivering highly competitive results on the LIVE-VQC database.

Abstract Background Neural tube defects (NTDs) are caused by genetic and environmental factors. ARMC5 is part of a novel ubiquitin ligase specific for POLR2A, the largest subunit of RNA polymerase II (Pol II). Results We find that ARMC5 knockout mice have increased incidence of NTDs, such as spina bifida and exencephaly. Surprisingly, the absence of ARMC5 causes the accumulation of not only POLR2A but also most of the other 11 Pol II subunits, indicating that the degradation of the whole Pol II complex is compromised. The enlarged Pol II pool does not lead to generalized Pol II stalling or a generalized decrease in mRNA transcription. In neural progenitor cells, ARMC5 knockout only dysregulates 106 genes, some of which are known to be involved in neural tube development. FOLH1, critical in folate uptake and hence neural tube development, is downregulated in the knockout intestine. We also identify nine deleterious mutations in the ARMC5 gene in 511 patients with myelomeningocele, a severe form of spina bifida. These mutations impair the interaction between ARMC5 and Pol II and reduce Pol II ubiquitination. Conclusions Mutations in ARMC5 increase the risk of NTDs in mice and humans. ARMC5 is part of an E3 controlling the degradation of all 12 subunits of Pol II under physiological conditions. The Pol II pool size might have effects on NTD pathogenesis, and some of the effects might be via the downregulation of FOLH1. Additional mechanistic work is needed to establish the causal effect of the findings on NTD pathogenesis.

Abstract Background Immune checkpoint inhibitors (ICIs) have emerged as one of the most promising first-line therapeutics in the management of non-small cell lung cancer (NSCLC). However, only a subset of these patients responds to ICIs, highlighting the clinical need to develop better predictive and prognostic biomarkers. This study will leverage pre-treatment imaging profiles to develop survival risk models for NSCLC patients treated with first-line immunotherapy. Methods Advanced NSCLC patients (n = 149) were retrospectively identified from two institutions who were treated with first-line ICIs. Radiomics features extracted from pretreatment imaging scans were used to build the predictive models for progression-free survival (PFS) and overall survival (OS). A compendium of five feature selection methods and seven machine learning approaches were utilized to build the survival risk models. The concordance index (C-index) was used to evaluate model performance. Results From our results, we found several combinations of machine learning algorithms and feature selection methods to achieve similar performance. K-nearest neighbourhood (KNN) with ReliefF (RL) feature selection was the best-performing model to predict PFS (C-index = 0.61 and 0.604 in discovery and validation cohorts), while XGBoost with Mutual Information (MI) feature selection was the best-performing model for OS (C-index = 0.7 and 0.655 in discovery and validation cohorts). Conclusion The results of this study highlight the importance of implementing an appropriate feature selection method coupled with a machine learning strategy to develop robust survival models. With further validation of these models on external cohorts when available, this can have the potential to improve clinical decisions by systematically analyzing routine medical images.

Social work curricula increasingly prepare prospective social workers for practice with lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority (LGBTQ+) communities. Yet much of this pedagogy continues to neglect specific attention to the issues of transgender (trans) people specifically. In this article, we draw on critical ecosystemic and intersectional traditions of scholarship to develop a framework for centering trans experiences in social work curricula broadly addressing LGBTQ+ issues. After reviewing relevant literature, we conceptualize approaches to foregrounding trans issues in education intended to prepare social work students for generalist, direct, and indirect practice with LGBTQ+ populations. We conclude the article with a critical discussion on our analysis while providing suggested innovations in trans social work curricula.

Abstract A substantial fraction of nitrogen (N) fertilizer applied in agricultural systems is not incorporated into crops and moves below the rooting zone as nitrate (NO3−). Understanding mechanisms for soil N retention below the rooting zone and leaching to groundwater is essential for our ability to track the fate of added N. We used dual stable isotopes of nitrate (δ15N–NO3− and δ18O–NO3−) and water (δ18O–H2O and δ2H–H2O) to understand the mechanisms driving nitrate leaching at three depths (0.8, 1.5, and 3.0 m) of an irrigated corn field sampled every 2 weeks from 2016 to 2020 in the southern Willamette Valley, Oregon, USA. Distinct periods of high nitrate concentrations with lower δ15N–NO3− values indicated that a portion of that nitrate was from recent fertilizer applications. We used a mixing model to quantify nitrate fluxes associated with recently added fertilizer N versus older, legacy soil N during these “fertilizer signal periods.” Nitrate leached below 3.0 m in these periods made up a larger proportion of the total N leached at that depth (∼52%) versus the two shallower depths (∼13%–16%), indicating preferential movement of recently applied fertilizer N through the deep soil into groundwater. Further, N associated with recent fertilizer additions leached more easily when compared to remobilized legacy N. A high volume of fall and winter precipitation may push residual fertilizer N to depth, potentially posing a larger threat to groundwater than legacy N. Optimizing fertilizer N additions could minimize fertilizer losses and reduce nitrate leaching to groundwater.

The prevailing model behind synapse development and specificity is that a multitude of adhesion molecules engage in transsynaptic interactions to induce pre- and postsynaptic assembly. How these extracellular interactions translate into intracellular signal transduction for synaptic assembly remains unclear. Here, we focus on a synapse organizing complex formed by immunoglobulin superfamily member 21 (IgSF21) and neurexin2α (Nrxn2α) that regulates GABAergic synapse development in the mouse brain. We reveal that the interaction between presynaptic Nrxn2α and postsynaptic IgSF21 is a high-affinity receptor-ligand interaction and identify a binding interface in the IgSF21-Nrxn2α complex. Despite being expressed in both dendritic and somatic regions, IgSF21 preferentially regulates dendritic GABAergic presynaptic differentiation whereas another canonical Nrxn ligand, neuroligin2 (Nlgn2), primarily regulates perisomatic presynaptic differentiation. To explore mechanisms that could underlie this compartment specificity, we targeted multiple signaling pathways pharmacologically while monitoring the synaptogenic activity of IgSF21 and Nlgn2. Interestingly, both IgSF21 and Nlgn2 require c-jun N-terminal kinase (JNK)-mediated signaling, whereas Nlgn2, but not IgSF21, additionally requires CaMKII and Src kinase activity. JNK inhibition diminished de novo presynaptic differentiation without affecting the maintenance of formed synapses. We further found that Nrxn2α knockout brains exhibit altered synaptic JNK activity in a sex-specific fashion, suggesting functional linkage between Nrxns and JNK. Thus, our study elucidates the structural and functional relationship of IgSF21 with Nrxn2α and distinct signaling pathways for IgSF21-Nrxn2α and Nlgn2-Nrxn synaptic organizing complexes in vitro. We therefore propose a revised hypothesis that Nrxns act as molecular hubs to specify synaptic properties not only through their multiple extracellular ligands but also through distinct intracellular signaling pathways of these ligands.

Background: A large body of evidence suggest that parents of young children with autism spectrum disorder or intellectual disability experience low levels of satisfaction with the diagnostic evaluation process. This study sought to document parents' satisfaction with the services of a pilot clinic implemented in Québec, Canada. Method: Two-hundred fifty-nine (259) parents were recruited following their child's diagnosis. A mixed methods approach was used to investigate parents' satisfaction globally and with specific aspects of the assessment process. Results: Parents expressed overall high satisfaction with the assessment process. Parental satisfaction with specific aspects of the assessment process was negatively related to paternal stress, fathers' unemployment and household income and positively related to maternal stress. Conclusions: This pilot clinic could meet parents' needs at this crucial moment in their care and services trajectory. The factors associated with satisfaction in the present study may inform future improvements to its services.

The present article outlines the internationalization strategy of the Center for International Studies and Cooperation (CECI) developed within the context of Canadian policy and international normative frameworks that call for the strengthening and empowerment of ecosystems. The results of this collaborative research, conducted using a mixed-methods methodology, reveal the organizational drivers and barriers within CECI’s transformation strategy. Our analysis, rooted in the work of critical humanitarian action authors within NGOs, enriches Permultter’s model by highlighting key transition moments during the implementation of CECI’s organizational strategy to decolonize its network.

Cell-based interception and precision medicine is a novel approach aimed at improving healthcare through the early detection and treatment of diseased cells. Here, we describe our recent progress towards developing cell-based interception and precision medicine to detect, understand, and advance the development of novel therapeutic approaches through a single-cell omics and drug screening platform, as part of a multi-laboratory collaborative effort, for a group of neurodegenerative disorders named leukodystrophies. Our strategy aims at the identification of diseased cells as early as possible to intercept progression of the disease prior to severe clinical impairment and irreversible tissue damage.

Abstract Background Heterogeneous nuclear ribonucleoprotein K (HNRNPK) regulates pre-mRNA processing and long non-coding RNA localization in the nucleus. It was previously shown that shuttling of HNRNPK to the cytoplasm promotes cell proliferation and cancer metastasis. However, the mechanism of HNRNPK cytoplasmic localization, its cytoplasmic RNA ligands, and impact on post-transcriptional gene regulation remain uncharacterized. Results Here we show that the intermediate filament protein Keratin 19 (K19) directly interacts with HNRNPK and sequesters it in the cytoplasm. Correspondingly, in K19 knockout breast cancer cells, HNRNPK does not localize in the cytoplasm, resulting in reduced cell proliferation. We comprehensively mapped HNRNPK binding sites on mRNAs and showed that, in the cytoplasm, K19-mediated HNRNPK-retention increases the abundance of target mRNAs bound to the 3’ untranslated region (3’UTR) at the expected cytidine-rich (C-rich) sequence elements. Furthermore, these mRNAs protected by HNRNPK in the cytoplasm are typically involved in cancer progression and include the p53 signaling pathway that is dysregulated upon HNRNPK knockdown (HNRNPK KD) or K19 knockout (KRT19 KO). Conclusions This study identifies how a cytoskeletal protein can directly regulate gene expression by controlling the subcellular localization of RNA-binding proteins to support pathways involved in cancer progression.

Abstract Hematopoietic stem and progenitor cells (HSPCs) originate from an endothelial-to-hematopoietic transition (EHT) during embryogenesis. Characterization of early hemogenic endothelial (HE) cells is required to understand what drives hemogenic specification and to accurately define cells capable of undergoing EHT. Using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), we define the early subpopulation of pre-HE cells based on both surface markers and transcriptomes. We identify the transcription factor Meis1 as an essential regulator of hemogenic cell specification in the embryo prior to Runx1 expression. Meis1 is expressed at the earliest stages of EHT and distinguishes pre-HE cells primed towards the hemogenic trajectory from the arterial endothelial cells that continue towards a vascular fate. Endothelial-specific deletion of Meis1 impairs the formation of functional Runx1-expressing HE which significantly impedes the emergence of pre-HSPC via EHT. Our findings implicate Meis1 in a critical fate-determining step for establishing EHT potential in endothelial cells.

Mechatronics and Robotics (MaR) have recently gained importance in product development and manufacturing settings and applications. Therefore, the Center for Space Emerging Technologies (C-SET) has managed an international multi-disciplinary study to present, historically, the first Latin American general review of industrial, collaborative, and mobile robotics, with the support of North American and European researchers and institutions. The methodology is developed by considering literature extracted from Scopus, Web of Science, and Aerospace Research Central and adding reports written by companies and government organizations. This describes the state-of-the-art of MaR until the year 2023 in the 3 Sub-Regions: North America, Central America, and South America, having achieved important results related to the academy, industry, government, and entrepreneurship; thus, the statistics shown in this manuscript are unique. Also, this article explores the potential for further work and advantages described by robotic companies such as ABB, KUKA, and Mecademic and the use of the Robot Operating System (ROS) in order to promote research, development, and innovation. In addition, the integration with industry 4.0 and digital manufacturing, architecture and construction, aerospace, smart agriculture, artificial intelligence, and computational social science (human-robot interaction) is analyzed to show the promising features of these growing tech areas, considering the improvements to increase production, manufacturing, and education in the Region. Finally, regarding the information presented, Latin America is considered an important location for investments to increase production and product development, taking into account the further proposal for the creation of the LATAM Consortium for Advanced Robotics and Mechatronics, which could support and work on roboethics and education/R+D+I law and regulations in the Region. Doi: 10.28991/ESJ-2023-07-04-025 Full Text: PDF

Abstract With the increasing use of immune checkpoint inhibitors (ICIs), there is an urgent need to identify biomarkers to stratify responders and non-responders using programmed death-ligand (PD-L1) expression, and to predict patient-specific outcomes such as progression free survival (PFS). The current study is aimed to determine the feasibility of building imaging-based predictive biomarkers for PD-L1 and PFS through systematically evaluating a combination of several machine learning algorithms with different feature selection methods. A retrospective, multicenter study of 385 advanced NSCLC patients amenable to ICIs was undertaken in two academic centers. Radiomic features extracted from pretreatment CT scans were used to build predictive models for PD-L1 and PFS (short-term vs. long-term survivors). We first employed the LASSO methodology followed by five feature selection methods and seven machine learning approaches to build the predictors. From our analyses, we found several combinations of feature selection methods and machine learning algorithms to achieve a similar performance. Logistic regression with ReliefF feature selection (AUC = 0.64, 0.59 in discovery and validation cohorts) and SVM with Anova F-test feature selection (AUC = 0.64, 0.63 in discovery and validation datasets) were the best-performing models to predict PD-L1 and PFS. This study elucidates the application of suitable feature selection approaches and machine learning algorithms to predict clinical endpoints using radiomics features. Through this study, we identified a subset of algorithms that should be considered in future investigations for building robust and clinically relevant predictive models.

Lentiviral vectors (LVs) are important for cell therapy because of their capacity to stably modify the genome after integration. This study describes a novel and relatively simple approach to generate packaging cells and producer clones for self-inactivating (SIN) LVs pseudotyped with the vesicular stomatitis virus glycoprotein (VSV-G). A novel gene regulation system, based on the combination of the cumate and coumermycin induction systems, was developed to ensure tight control for the expression of cytotoxic packaging elements. To accelerate clone isolation and ensure monoclonality, the packaging genes were transfected simultaneously into human embryonic kidney cells (293SF-3F6) previously engineered with the induction system, and clones were isolated after limiting dilution into nanowell arrays using a robotic cell picking instrument with scanning capability. The method’s effectiveness to isolate colonies derived from single cells was demonstrated using mixed populations of cells labeled with two different fluorescent markers. Because the recipient cell line grew in suspension culture, and all the procedures were performed without serum, the resulting clones were readily adaptable to serum-free suspension culture. The best producer clone produced LVs expressing GFP at a titer of 2.3 × 108 transduction units (TU)/mL in the culture medium under batch mode without concentration.

Summary: A group of keratin intermediate filament genes, the type II KRT6A-C and type I KRT16 and KRT17, are deemed stress responsive as they are induced in keratinocytes of surface epithelia in response to environmental stressors, in skin disorders (e.g., psoriasis) and in carcinomas. Monitoring stress keratins is widely used to identify keratinocytes in an activated state. Here, we analyze single-cell transcriptomic data from healthy and diseased human skin to explore the properties of stress keratins. Relative to keratins occurring in healthy skin, stress-induced keratins are expressed at lower levels and show lesser type I-type II pairwise regulation. Stress keratins do not “replace” the keratins expressed during normal differentiation nor reflect cellular proliferation. Instead, stress keratins are consistently co-regulated with genes with roles in differentiation, inflammation, and/or activation of innate immunity at the single-cell level. These findings provide a roadmap toward explaining the broad diversity and contextual regulation of keratins.

With sizable volatile envelopes but smaller radii than the solar system ice giants, sub-Neptunes have been revealed as one of the most common types of planet in the galaxy. While the spectroscopic characterization of larger sub-Neptunes (2.5–4 R _⊕ ) has revealed hydrogen-dominated atmospheres, smaller sub-Neptunes (1.6–2.5 R _⊕ ) could either host thin, rapidly evaporating, hydrogen-rich atmospheres or be stable, metal-rich “water worlds” with high mean molecular weight atmospheres and a fundamentally different formation and evolutionary history. Here, we present the 0.6–2.8 μ m JWST/NIRISS/SOSS transmission spectrum of GJ 9827 d, the smallest (1.98 R _⊕ ) warm ( T _eq,A=0.3 ∼ 620 K) sub-Neptune where atmospheric absorbers have been detected to date. Our two transit observations with NIRISS/SOSS, combined with the existing HST/WFC3 spectrum, enable us to break the clouds–metallicity degeneracy. We detect water in a highly metal-enriched “steam world” atmosphere (O/H of ∼4 by mass and H _2 O found to be the background gas with a volume mixing ratio of >31%). We further show that these results are robust to stellar contamination through the transit light source effect. We do not detect escaping metastable He, which, combined with previous nondetections of escaping He and H, supports the steam atmosphere scenario. In water-rich atmospheres, hydrogen loss driven by water photolysis happens predominantly in the ionized form, which eludes observational constraints. We also detect several flares in the NIRISS/SOSS light curves with far-UV energies of the order of 10 ^30 erg, highlighting the active nature of the star. Further atmospheric characterization of GJ 9827 d probing carbon or sulfur species could reveal the origin of its high metal enrichment.

LHS 1140 b is the second-closest temperate transiting planet to Earth with an equilibrium temperature low enough to support surface liquid water. At 1.730 ± 0.025 R _⊕ , LHS 1140 b falls within the radius valley separating H _2 -rich mini-Neptunes from rocky super-Earths. Recent mass and radius revisions indicate a bulk density significantly lower than expected for an Earth-like rocky interior, suggesting that LHS 1140 b could be either a mini-Neptune with a small envelope of hydrogen (∼0.1% by mass) or a water world (9%–19% water by mass). Atmospheric characterization through transmission spectroscopy can readily discern between these two scenarios. Here we present two JWST/NIRISS transit observations of LHS 1140 b, one of which captures a serendipitous transit of LHS 1140 c. The combined transmission spectrum of LHS 1140 b shows a telltale spectral signature of unocculted faculae (5.8 σ ), covering ∼20% of the visible stellar surface. Besides faculae, our spectral retrieval analysis reveals tentative evidence of residual spectral features, best fit by Rayleigh scattering from a N _2 -dominated atmosphere (2.3 σ ), irrespective of the consideration of atmospheric hazes. We also show through Global Climate Models (GCMs) that H _2 -rich atmospheres of various compositions (100×, 300×, 1000× solar metallicity) are ruled out to >10 σ . The GCM calculations predict that water clouds form below the transit photosphere, limiting their impact on transmission data. Our observations suggest that LHS 1140 b is either airless or, more likely, surrounded by an atmosphere with a high mean molecular weight. Our tentative evidence of a N _2 -rich atmosphere provides strong motivation for future transmission spectroscopy observations of LHS 1140 b.

The hot Neptune desert is one of the most sparsely populated regions of the exoplanet parameter space, and atmosphere observations of its few residents can provide insights into how such planets have managed to survive in such an inhospitable environment. Here, we present transmission observations of LTT 9779 b, the only known hot Neptune to have retained a significant H/He-dominated atmosphere, taken with JWST NIRISS/SOSS. The 0.6–2.85 μ m transmission spectrum shows evidence for muted spectral features, rejecting a perfectly flat line at >5 σ . We explore water- and methane-dominated atmosphere scenarios for LTT 9779 b’s terminator, and retrieval analyses reveal a continuum of potential combinations of metallicity and cloudiness. Through comparisons to previous population synthesis works and our own interior structure modeling, we are able to constrain LTT 9779 b’s atmosphere metallicity to 20–850× solar. Within this range of metallicity, our retrieval analyses prefer solutions with clouds at millibar pressures, regardless of whether the atmosphere is water or methane dominated—though cloud-free atmospheres with metallicities >500× solar cannot be entirely ruled out. By comparing self-consistent atmosphere temperature profiles with cloud condensation curves, we find that silicate clouds can readily condense in the terminator region of LTT 9779 b. Advection of these clouds onto the dayside could explain the high dayside albedo previously inferred for this planet and be part of a feedback loop aiding the survival of LTT 9779 b’s atmosphere in the hot Neptune desert.

IntroductionAdolescent Idiopathic Scoliosis (AIS) is a 3D deformity of the spine that affects 3% of the adolescent population. Conservative treatments like bracing aim to halt the progression of the curve to the surgical threshold. Computer-aided design and manufacturing (CAD/CAM) methods for brace design and manufacturing are becoming increasingly used. Linked to CAD/CAM and 3D radiographic reconstruction techniques, we developed a finite element model (FEM) enabling to simulate the brace effectiveness before its fabrication, as well as a semi-automatic design processes. The objective of this randomized controlled trial is to compare and validate such FEM semi-automatic algorithm used to design nighttime Providence-type braces.Methods and analysisFifty-eight patients with AIS aged between 10 to 16-years and skeletally immature will be recruited. At the delivery stage, all patients will receive both a Providence-type brace optimized by the semi-automatic algorithm leveraging a patient-specific FEM (Test) and a conventional Providence-type brace (Control), both designed using CAD/CAM methods. Biplanar radiographs will be taken for each patient with both braces in a randomized crossover approach to evaluate immediate correction. Patients will then be randomized to keep either the Test or Control brace as prescribed with a renewal if necessary, and will be followed over two years. The primary outcome will be the change in Cobb angle of the main curve after two years. Secondary outcomes will be brace failure rate, quality of life (QoL) and immediate in-brace correction. This is a single-centre study, double-blinded (participant and outcome assessor) randomized controlled trial (RCT).Trial registration numberClinicalTrials.gov: NCT05001568.