Functional impairment of chronic migraine with medication overuse: Secondary analysis from the Medication Overuse Treatment Strategy (MOTS) trial.

BACKGROUND: Chronic migraine exerts substantial negative impacts on daily functioning. Efforts to manage impaired functioning may result in medication overuse, which contributes to the worsening profile and chronification of migraine. The Migraine Functional Impact Questionnaire (MFIQ) is a recently developed measure assessing the impact of migraine on physical, social, and emotional function. OBJECTIVE: The objective of this analysis was to assess changes in MFIQ scores following initiation or modification of migraine preventive medication and determine if changes in function are associated with changes in other aspects of migraine burden, such as headache frequency, headache intensity, and symptoms of anxiety and depression. METHODS: This is a secondary analysis of data from the Medication Overuse Treatment Strategy (MOTS) trial, a prospective pragmatic clinical trial that investigated two treatment strategies for those with chronic migraine and medication overuse. Data from both treatment arms were pooled and analyzed using a pre-post design. Prior to and 12 weeks following initiation or modification of migraine preventive medication, participants completed a series of questionnaires that captured migraine characteristics, medication use, migraine-related physical impairment (MFIQ), anxiety (Generalized Anxiety Disorder-7), and depression (Patient Health Questionnaire 9 [PHQ-9]) symptoms. Changes from baseline in all measures were assessed using the paired t-test. Relationships between changes in MFIQ scores and other measures were assessed using linear regression. Multivariable modeling was performed to determine which additional variables contributed to the change in MFIQ beyond that already explained by an individual variable. Model terms were selected by using elastic net regularization. Only those participants who completed the baseline and 12-week MFIQ were included in this analysis. RESULTS: Of the 537 patients, 88.2% were female, and the average age was 45 years (standard deviation 13). The mean frequency of days with moderate-to-severe headache improved 39.2% from 13.5 per 30 days at baseline to 8.1 per 30 days at week 12. The mean MFIQ Usual Activities Global score improved by 15.0 points (on a 100-point scale). All five domains (Usual Activities Global, Usual Activities, Social Function, Emotional Function, Physical Function) of the MFIQ improved by a mean of at least 13.0 points. Changes in PHQ-9 score, followed by changes in headache frequency, had the strongest associations with change in all domains of the MFIQ. CONCLUSIONS: The negative impact of chronic migraine with medication overuse on physical, social, and emotional functioning substantially lessened following initiation or modification of migraine preventive medication. Improved functioning, as measured by the MFIQ, was most strongly associated with reductions in depression scores and headache frequency, highlighting the importance of recognizing and monitoring changes in depressive symptoms, in addition to headache frequency and functional impairment, when evaluating response to preventive medications.

DVA: predicting the functional impact of single nucleotide missense variants.

BACKGROUND: In the past decade, single nucleotide variants (SNVs) have been identified as having a significant relationship with the development and treatment of diseases. Among them, prioritizing missense variants for further functional impact investigation is an essential challenge in the study of common disease and cancer. Although several computational methods have been developed to predict the functional impacts of variants, the predictive ability of these methods is still insufficient in the Mendelian and cancer missense variants. RESULTS: We present a novel prediction method called the disease-related variant annotation (DVA) method that predicts the effect of missense variants based on a comprehensive feature set of variants, notably, the allele frequency and protein-protein interaction network feature based on graph embedding. Benchmarked against datasets of single nucleotide missense variants, the DVA method outperforms the state-of-the-art methods by up to 0.473 in the area under receiver operating characteristic curve. The results demonstrate that the proposed method can accurately predict the functional impact of single nucleotide missense variants and substantially outperforms existing methods. CONCLUSIONS: DVA is an effective framework for identifying the functional impact of disease missense variants based on a comprehensive feature set. Based on different datasets, DVA shows its generalization ability and robustness, and it also provides innovative ideas for the study of the functional mechanism and impact of SNVs.

Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact.

BACKGROUND: Cancer, a disease with high morbidity and mortality rates, poses a significant threat to human health. Driver genes, which harbor mutations accountable for the initiation and progression of tumors, play a crucial role in cancer development. Identifying driver genes stands as a paramount objective in cancer research and precision medicine. RESULTS: In the present work, we propose a method for identifying driver genes using a Generalized Linear Regression Model (GLM) with Shrinkage and double-Weighted strategies based on Functional Impact, which is named GSW-FI. Firstly, an estimating model is proposed for assessing the background functional impacts of genes based on GLM, utilizing gene features as predictors. Secondly, the shrinkage and double-weighted strategies as two revising approaches are integrated to ensure the rationality of the identified driver genes. Lastly, a statistical method of hypothesis testing is designed to identify driver genes by leveraging the estimated background function impacts. Experimental results conducted on 31 The Cancer Genome Altas datasets demonstrate that GSW-FI outperforms ten other prediction methods in terms of the overlap fraction with well-known databases and consensus predictions among different methods. CONCLUSIONS: GSW-FI presents a novel approach that efficiently identifies driver genes with functional impact mutations using computational methods, thereby advancing the development of precision medicine for cancer.

Visual-functional impact of people affected by severe ocular trauma during social protests in Chile in 2019.

PURPOSE: To determine the impact on the functionality associated with visual loss (VFIP) in people with severe ocular trauma (SOT) caused by kinetic impact projectiles used in police crowd control through a prioritization tool in people admitted to a rehabilitation program in Santiago de Chile from December 02, 2019, to November 13, 2020. METHODS: A cross-sectional descriptive study of SOT victims (N = 85), average age 31.4 ± 11.9. The data were recorded through a new 9-item screening instrument for assessment and prioritization of rehabilitation created for this emergency scenario. RESULTS: The impact of the use of kinetic weapons resulted in monocular blindness in the majority of those affected (n = 68; 80.0%). The highest VFIP observed was among young men from lower social strata. There were extreme difficulties in the performance of productive tasks (occupational and/or educational) (n = 42; 49.4%) and the pursuit of hobbies and pastimes (n = 23; 27.1%), as well as a high difficulty in adapting to changes in brightness (n = 29; 34.1%) and handling objects accurately (n = 22; 25.9%). CONCLUSION: The use of kinetic weapons for crowd control resulted in high and extreme VFIP and, in most cases, monocular blindness, causing major difficulties in work, study, and development of hobbies and pastimes in the affected population, highlighting the urgent need for effective rehabilitative care, which requires special attention in order to generate an adequate rehabilitation program. The use of kinetic weapons for crowd control contravenes international goals, policies, and plans set by the WHO and the International Agency for the Prevention of Blindness on strategies to prevent avoidable blindness worldwide until 2020. It is essential to ban the use of these weapons in Chile and worldwide, as well as to revise police protocols for crowd control.

Predicting the DNA binding specificity of mutated transcription factors using family-level biophysically interpretable machine learning.

Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput in vitro binding assays coupled with computational analysis have made it possible to accurately define such sequence recognition in a biophysically interpretable yet mechanism-agonistic way for individual TFs. The fact that such sequence-to-affinity models are now available for hundreds of TFs provides new avenues for predicting how the DNA binding specificity of a TF changes when its protein sequence is mutated. To this end, we developed an analytical framework based on a tetrahedron embedding that can be applied at the level of a given structural TF family. Using bHLH as a test case, we demonstrate that we can systematically map dependencies between the protein sequence of a TF and base preference within the DNA binding site. We also develop a regression approach to predict the quantitative energetic impact of mutations in the DNA binding domain of a TF on its DNA binding specificity, and perform SELEX-seq assays on mutated TFs to experimentally validate our results. Our results point to the feasibility of predicting the functional impact of disease mutations and allelic variation in the cell-wide TF repertoire by leveraging high-quality functional information across sets of homologous wild-type proteins.

Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of a diverse feature set.

Gain-of-function (GOF) variants give rise to increased/novel protein functions whereas loss-of-function (LOF) variants lead to diminished protein function. Experimental approaches for identifying GOF and LOF are generally slow and costly, whilst available computational methods have not been optimized to discriminate between GOF and LOF variants. We have developed LoGoFunc, a machine learning method for predicting pathogenic GOF, pathogenic LOF, and neutral genetic variants, trained on a broad range of gene-, protein-, and variant-level features describing diverse biological characteristics. LoGoFunc outperforms other tools trained solely to predict pathogenicity for identifying pathogenic GOF and LOF variants and is available at https://itanlab.shinyapps.io/goflof/ .

Prevalencia y características clínicas del dolor en pacientes con enfermedad crónica avanzada / Prevalence and clinical characteristics of pain in patients with advanced chronic disease

Objetivos: Determinar la prevalencia y las características clínicas del dolor en pacientes con enfermedad crónica avanzada, e identificar la frecuencia del dolor irruptivo. Diseño: Estudio observacional, descriptivo y transversal. Emplazamiento: Tres equipos de atención primaria y un hospital de cuidados intermedios. Participantes: Se seleccionaron todos los pacientes con enfermedad crónica avanzada. Mediciones principales: Se realizó una entrevista semiestructurada para recoger variables demográficas, clínicas y específicas de dolor mediante escalas validadas. Se registraron la ubicación (domicilio, residencia u hospital) y la trayectoria de cronicidad avanzada (insuficiencia de órgano, enfermedad oncológica, demencia o multimorbilidad). Se valoró la presencia de dolor según la Brief Pain Inventory (BPI) y, en los casos de demencia invalidante, según la Pain Assessment in Advanced Dementia (PAINAD). Análisis estadístico descriptivo y comparativo entre variables utilizando el programa R. Resultados: Se incluyeron 223 pacientes (60,4% de los seleccionados). Prevalencia del dolor: 83,9% (n=187), sin diferencias según la ubicación ni según la trayectoria. Diferencias significativas en la intensidad del dolor según la ubicación (p=0,0046) (moderado-severo en domicilio, moderado en hospital y leve en residencia) y según la trayectoria (p<0,0001) (dolor moderado-severo en insuficiencia de órgano y multimorbilidad, moderado en cáncer y leve en demencia). Se observó impacto funcional por dolor leve-moderado, impacto emocional severo en el 41,5% de los pacientes (n=51) y dolor irruptivo en el 8,6% (n=13). Conclusiones: El dolor debe ser siempre explorado y evaluado en pacientes con cronicidad avanzada, ya que fue muy prevalente en todas las ubicaciones y trayectorias, especialmente intenso en la insuficiencia de órgano y en la multimorbilidad a domicilio. Apareció dolor irruptivo en trayectorias no oncológicas.(AU)

Objectives: Determine pain prevalence and clinical characteristics in patients with advanced chronic disease and identify breakthrough pain frequency. Design: Observational, descriptive, cross-sectional study. Location: Three primary care teams and one intermediate care hospital. Participants: All patients with advanced chronic disease. Main measurements: A semi-structured interview was performed to collect demographic, clinical, and specific variables of pain using validated scales. Patient location (home, nursing home or hospital) and advanced chronicity trajectory (organ failure, oncological disease, dementia, or multimorbidity) were recorded. Pain was assessed based on the Brief Pain Inventory (BPI) and, in cases of disabling dementia, using the Pain Assessment in Advanced Dementia (PAINAD). A statistical descriptive, comparative analysis between variables was performed using the R software. Results: Of all patients selected, 223 (60.4%) were included. Prevalence of pain: 83.9% (n=187), with no differences based on location or trajectory. Significant differences in pain intensity based on location (P=.0046) (moderate-severe in patients at home, moderate in hospital patients, and mild in nursing home patients) and on trajectory (P<.0001) (moderate-severe in patients with organ failure and multimorbidity, moderate in patients with cancer, and mild in patients with dementia). Global functional impact of pain was mild-moderate, emotional impact was severe in 41.5% of patients (n=51), and breakthrough pain was observed in 8.6% (n=13). Conclusions: Pain must always be explored and assessed in patients with advanced chronicity, since it was highly prevalent in all locations and trajectories, being particularly intense in patients at home with organ failure and multimorbidity. Breakthrough pain was found in non-oncological trajectories.(AU)

[Prevalence and clinical characteristics of pain in patients with advanced chronic disease]. / Prevalencia y características clínicas del dolor en pacientes con enfermedad crónica avanzada.

OBJECTIVES: Determine pain prevalence and clinical characteristics in patients with advanced chronic disease and identify breakthrough pain frequency. DESIGN: Observational, descriptive, cross-sectional study. LOCATION: Three primary care teams and one intermediate care hospital. PARTICIPANTS: All patients with advanced chronic disease. MAIN MEASUREMENTS: A semi-structured interview was performed to collect demographic, clinical, and specific variables of pain using validated scales. Patient location (home, nursing home or hospital) and advanced chronicity trajectory (organ failure, oncological disease, dementia, or multimorbidity) were recorded. Pain was assessed based on the Brief Pain Inventory (BPI) and, in cases of disabling dementia, using the Pain Assessment in Advanced Dementia (PAINAD). A statistical descriptive, comparative analysis between variables was performed using the R software. RESULTS: Of all patients selected, 223 (60.4%) were included. Prevalence of pain: 83.9% (n=187), with no differences based on location or trajectory. Significant differences in pain intensity based on location (P=.0046) (moderate-severe in patients at home, moderate in hospital patients, and mild in nursing home patients) and on trajectory (P<.0001) (moderate-severe in patients with organ failure and multimorbidity, moderate in patients with cancer, and mild in patients with dementia). Global functional impact of pain was mild-moderate, emotional impact was severe in 41.5% of patients (n=51), and breakthrough pain was observed in 8.6% (n=13). CONCLUSIONS: Pain must always be explored and assessed in patients with advanced chronicity, since it was highly prevalent in all locations and trajectories, being particularly intense in patients at home with organ failure and multimorbidity. Breakthrough pain was found in non-oncological trajectories.

Peripheral neuropathy in Parkinson's disease: prevalence and functional impact on gait and balance.

Peripheral neuropathy is a common problem in patients with Parkinson's disease. Peripheral neuropathy's prevalence in Parkinson's disease varies between 4.8-55%, compared with 9% in the general population. It remains unclear whether peripheral neuropathy leads to decreased motor performance in Parkinson's disease, resulting in impaired mobility and increased balance deficits. We aimed to determine the prevalence and type of peripheral neuropathy in Parkinson's disease patients and evaluate its functional impact on gait and balance. A cohort of consecutive Parkinson's disease patients assessed by movement disorders specialists based on the UK Brain Bank criteria underwent clinical, neurophysiological (nerve conduction studies and quantitative sensory testing) and neuropathological (intraepidermal nerve fibre density in skin biopsy punches) evaluation to characterize the peripheral neuropathy type and aetiology using a cross-sectional design. Gait and balance were characterized using wearable health-technology in OFF and ON medication states, and the main parameters were extracted using validated algorithms. A total of 99 Parkinson's disease participants with a mean age of 67.2 (±10) years and mean disease duration of 6.5 (±5) years were assessed. Based on a comprehensive clinical, neurophysiological and neuropathological evaluation, we found that 40.4% of Parkinson's disease patients presented peripheral neuropathy, with a predominance of small fibre neuropathy (70% of the group). In the OFF state, the presence of peripheral neuropathy was significantly associated with shorter stride length (P = 0.029), slower gait speed (P = 0.005) and smaller toe-off angles (P = 0.002) during straight walking; significantly slower speed (P = 0.019) and smaller toe-off angles (P = 0.007) were also observed during circular walking. In the ON state, the above effects remained, albeit moderately reduced. With regard to balance, significant differences between Parkinson's disease patients with and without peripheral neuropathy were observed in the OFF medication state during stance with closed eyes on a foam surface. In the ON states, these differences were no longer observable. We showed that peripheral neuropathy is common in Parkinson's disease and influences gait and balance parameters, as measured with mobile health-technology. Our study supports that peripheral neuropathy recognition and directed treatment should be pursued in order to improve gait in Parkinson's disease patients and minimize balance-related disability, targeting individualized medical care.

Associations between executive functioning, challenging behavior, and quality of life in children and adolescents with and without neurodevelopmental conditions.

The present study sought to clarify the impact of executive and social functioning on challenging behavior and the downstream influence of challenging behavior on quality of life and functioning in a large transdiagnostic sample. Understanding these relationships is crucial for developing and designing tailored intervention strategies. In a cross-sectional study, parent informants of 2,004 children completed measures of executive and social functioning, challenging behavior, child and family quality of life, and reported on functional impacts of challenging behavior. Using structural (path) modeling, analyses evaluated the associations between executive and social functioning, including emotion regulation and risk avoidance, with overall and specific types of challenging behavior. Structural models also examined the influence of challenging behavior on child and family quality of life, including measures of the immediate and extended environment, and functional impacts on the parent/child as well as interactions with the medical/legal systems. Finally, mediational models explored the direct and indirect effects of executive and social functioning on quality of life and impact measures via challenging behavior. Results indicated that executive functioning accounts for substantial variance (R 2 = 0.47) in challenging behavior. In turn, challenging behavior accounts for substantial variance in child and family quality of life (R 2 = 0.36) and parent/child impacts (R 2 = 0.31). Exploratory mediational models identified direct effects from executive and social functioning measures on quality of life and functional impacts and indirect effects for executive functioning via challenging behavior. These findings support the development of new intervention strategies and suggest the need to measure executive functioning when assessing and tailoring the treatment of challenging behavior in clinical practice.

Inferring Potential Cancer Driving Synonymous Variants.

Synonymous single nucleotide variants (sSNVs) are often considered functionally silent, but a few cases of cancer-causing sSNVs have been reported. From available databases, we collected four categories of sSNVs: germline, somatic in normal tissues, somatic in cancerous tissues, and putative cancer drivers. We found that screening sSNVs for recurrence among patients, conservation of the affected genomic position, and synVep prediction (synVep is a machine learning-based sSNV effect predictor) recovers cancer driver variants (termed proposed drivers) and previously unknown putative cancer genes. Of the 2.9 million somatic sSNVs found in the COSMIC database, we identified 2111 proposed cancer driver sSNVs. Of these, 326 sSNVs could be further tagged for possible RNA splicing effects, RNA structural changes, and affected RBP motifs. This list of proposed cancer driver sSNVs provides computational guidance in prioritizing the experimental evaluation of synonymous mutations found in cancers. Furthermore, our list of novel potential cancer genes, galvanized by synonymous mutations, may highlight yet unexplored cancer mechanisms.

Development of a Clinically Relevant Index for Tooth Wear Treatment Needs.

BACKGROUND: This study aimed to develop a tooth wear classification system that combined the extent, severity, and aesthetic impact of tooth wear and correlated them with the most appropriate clinical management strategy. METHODS: Three hundred photographs were used to develop a classification tool that contained four levels of severity and aesthetic impact (0, 1, 2, and 3) in three age groups of patients. Ten examiners assessed and classified the cases using validated forms. Additionally, they selected the recommended treatment modality for each level. The analysis was conducted using a coefficient correlation test. RESULTS: The coefficient correlation for the severity was 0.81, 0.82 in the upper anterior and posterior segments, and 0.85 and 0.77 for the lower anterior and posterior segments, respectively. The aesthetic impact correlation coefficient was 0.84. Examiners had agreed that minor cases required monitoring or simple restorative interventions. The moderate-level cases had variety in the recommended management options depending on the aim of treatment. The severe level cases often required rehabilitation at an increased occlusal vertical dimension. CONCLUSION: Within the limitations of this preliminary study, a good agreement between the examiners was found using the provided tools. More strict criteria in the classification part of the tool can further improve the examiners' agreement.

AmazonForest: In Silico Metaprediction of Pathogenic Variants.

ClinVar is a web platform that stores ∼789,000 genetic associations with complex diseases. A partial set of these cataloged genetic associations has challenged clinicians and geneticists, often leading to conflicting interpretations or uncertain clinical impact significance. In this study, we addressed the (re)classification of genetic variants by AmazonForest, which is a random-forest-based pathogenicity metaprediction model that works by combining functional impact data from eight prediction tools. We evaluated the performance of representation learning algorithms such as autoencoders to propose a better strategy. All metaprediction models were trained with ClinVar data, and genetic variants were annotated with eight functional impact predictors cataloged with SnpEff/SnpSift. AmazonForest implements the best random forest model with a one hot data-encoding strategy, which shows an Area Under ROC Curve of ≥0.93. AmazonForest was employed for pathogenicity prediction of a set of ∼101,000 genetic variants of uncertain significance or conflict of interpretation. Our findings revealed ∼24,000 variants with high pathogenic probability (RFprob≥0.9). In addition, we show results for Alzheimer's Disease as a demonstration of its application in clinical interpretation of genetic variants in complex diseases. Lastly, AmazonForest is available as a web tool and R object that can be loaded to perform pathogenicity predictions.

Unveiling the influence of factor VIII physicochemical properties on hemophilia A phenotype through an in silico methodology.

BACKGROUND AND OBJECTIVES: Hemophilia A (HA) is an X-linked blood disorder. It is caused by pathogenic F8 gene variants, among which missense mutations are the most prevalent. The resulting amino acid substitutions may have different impacts on physicochemical properties and, consequently, on protein functionality. Regular prediction tools do not include structural elements and their physiological significance, which hampers our ability to functionally link variants to disease phenotype, opening an ample field for investigation. The present study aims to elucidate how physicochemical changes generated by substitutions in different protein domains relate to HA, and which of these features are more consequential to protein function and its impact on HA phenotype. METHODS: An in silico evaluation of 71 F8 variants found in patients with different HA phenotypes (mild, moderate, severe) was performed to understand protein modifications and functional impact. Homology modeling was used for the structural analysis of physicochemical changes including electrostatic potential, hydrophobicity, solvent-accessible/excluded surface areas, disulfide disruptions, and substitutions indexes. These variants and properties were analyzed by hierarchical clustering analysis (HCA) and principal component analysis (PCA), independently and in combination, to investigate their relative contribution. RESULTS: About 69% of variants show electrostatic changes, and almost all show hydrophobicity and surface area modifications. HCA combining all physicochemical properties analyzed was better in reflecting the impact of different variants in disease severity, more so than the single feature analysis. On the other hand, PCA led to the identification of prominent properties involved in the clustering results for variants of different domains. CONCLUSIONS: The methodology developed here enables the assessment of structural features not available in other prediction tools (e.g., surface distribution of electrostatic potential), evaluating what kind of physicochemical changes are involved in FVIII functional disruption. HCA results allow distinguishing substitutions according to their properties, and yielded clusters which were more homogeneous in phenotype. All evaluated properties are involved in determining disease severity. The nature, as well as the position of the variants in the protein, were shown to be relevant for physicochemical changes, demonstrating that all these aspects must be collectively considered to fine-tune an approach to predict HA severity.

Aligning formal and functional assessments of Visuospatial Neglect: A mixed-methods study.

ABSTRACTThe occurrence of visuospatial neglect acts as a key predictor of recovery outcome following stroke. However, the specific behavioural profiles associated with various neglect subtypes are not well understood. This study aims to identify real-world functional impairments associated with neglect, to determine whether functional impairment profiles differ across patients with egocentric and allocentric neglect, and to investigate how neglect severity predicts functional impairments.Notes from 290 stroke patients' occupational therapy functional assessments were qualitatively and quantitatively analysed in the context of neglect type and severity as reported by the OCS Cancellation Task. Overall, neglect patients had more references to having difficulty initiating tasks, finding items, exhibiting spatial inattention, and having difficulty using both arms than patients without neglect. The proportion of theme references did not differ significantly across patients with egocentric and allocentric neglect. The quantitative severity of egocentric neglect was acted as a significant predictor of reference occurrence over and above stroke severity within difficulty finding items, spatial inattention, body inattention, and upper limb use.This study expands on previous findings by identifying real-world functional impairments differentiating patients with and without neglect. This data provides novel insight into the impact of neglect on functional abilities.

A disease severity scale for the evaluation of vaccine and other preventive or therapeutic interventions for travellers' diarrhoea.

BACKGROUND: Travellers' diarrhoea (TD) is the most common travel-related illness with an estimated 10 million people afflicted annually. Outcome measures to assess the efficacy of primary and secondary TD interventions were historically based on diarrhoea frequency with ≥1 associated gastrointestinal symptom. Furthermore, efficacy determination is often made on the presence or absence of TD, rather than on TD illness severity. Current severity classifications are based on subjective consideration of impact of illness on activity. We sought to develop a standardized scoring system to characterize TD severity to potentially apply as a secondary outcome in future field studies. METHODS: Data on multiple signs and symptoms were obtained from a previously published multisite TD treatment trial conducted by the US Department of Defense (TrEAT TD). Correlation, regression and multiple correspondence analyses were performed to assess impact on activity and a TD severity score was established. RESULTS: Numerous signs and symptoms were associated with impaired function, with malaise and nausea most strongly associated [odds ratio (OR) 5.9-44.3, P < 0.0001 and OR 2.8-37.1, P < 0.0001, respectively). Based on co-varying symptomatology, a TD severity score accounting for diarrhoea frequency in addition to several signs and symptoms was a better predictor of negative impact on function than any single sign/symptom (X2 = 127.16, P < 0.001). Additionally, there was a significant difference (P < 0.0001) in the mean TD severity score between those with acute watery diarrhoea (3.9 ± 1.9) and those with dysentery or acute febrile illness (6.2 ± 2.0). CONCLUSIONS: The newly developed disease severity score better predicted a negative impact on activity due to TD than did any single sign or symptom. Incorporating multiple parameters into the TD severity score better captures illness severity and moves the field towards current recommendations for TD management by considering symptoms with high functional impact. Further validation of this score is needed in non-military travellers and other settings.

A Subtle Profile With a Significant Impact: Language and Communication Difficulties for Autistic Females Without Intellectual Disability.

The presentation of autism in females is poorly understood, which is thought to contribute to missed or later- age diagnosis, especially for those without intellectual disability. Dedicated research into social and behavioral differences has indicated a specific female phenotype of autism. However, less has been done to explore language and communication profiles, despite known sex/gender differences in typically developing populations. This article provides a synthesis of recent work from this small but emerging field. It focuses on a series of four preliminary and explorative studies conducted by the authors and embeds this within the wider literature. Findings suggest a specific profile of language and communication strengths and weaknesses for autistic females without intellectual disability (compared to autistic males and typically developing females). Furthermore, despite the relatively subtle presentation of difficulties (compared to autistic males), the impact on functionality, social inter-relations and emotional well-being, appears to be equitable and significant. The discussion highlights the need for further empirical research and proposes areas for investigation. Implications for clinical practice include the need for better recognition, testing and provision of interventions dedicated to the language and communication difficulties for autistic females. This has relevance for diagnostic, mental health and speech and language therapy services.

An inferred functional impact map of genetic variants in rice.

Interpreting the functional impacts of genetic variants (GVs) is an important challenge for functional genomic studies in crops and next-generation breeding. Previous studies in rice (Oryza sativa) have focused mainly on the identification of GVs, whereas systematic functional annotation of GVs has not yet been performed. Here, we present a functional impact map of GVs in rice. We curated haplotype information for 17 397 026 GVs from sequencing data of 4726 rice accessions. We quantitatively evaluated the effects of missense mutations in coding regions in each haplotype based on the conservation of amino acid residues and obtained the effects of 918 848 non-redundant missense GVs. Furthermore, we generated high-quality chromatin accessibility (CA) data from six representative rice tissues and used these data to train deep convolutional neural network models to predict the impacts of 5 067 405 GVs for CA in regulatory regions. We characterized the functional properties and tissue specificity of the GV effects and found that large-effect GVs in coding and regulatory regions may be subject to selection in different directions. Finally, we demonstrated how the functional impact map could be used to prioritize causal variants in mapping populations. This impact map will be a useful resource for accelerating gene cloning and functional studies in rice, and can be freely queried in RiceVarMap V2.0 (http://ricevarmap.ncpgr.cn).

A systematic view of computational methods for identifying driver genes based on somatic mutation data.

Abnormal changes of driver genes are serious for human health and biomedical research. Identifying driver genes, exactly from enormous genes with mutations, promotes accurate diagnosis and treatment of cancer. A lot of works about uncovering driver genes have been developed over the past decades. By analyzing previous works, we find that computational methods are more efficient than traditional biological experiments when distinguishing driver genes from massive data. In this study, we summarize eight common computational algorithms only using somatic mutation data. We first group these methods into three categories according to mutation features they apply. Then, we conclude a general process of nominating candidate cancer driver genes. Finally, we evaluate three representative methods on 10 kinds of cancer derived from The Cancer Genome Atlas Program and five Chinese projects from the International Cancer Genome Consortium. In addition, we compare results of methods with various parameters. Evaluation is performed from four perspectives, including CGC, OG/TSG, Q-value and QQQuantile-Quantileplot. To sum up, we present algorithms using somatic mutation data in order to offer a systematic view of various mutation features and lay the foundation of methods based on integration of mutation information and other types of data.

Depression, health comorbidities, cognitive symptoms and their functional impact: Not just a geriatric problem.

OBJECTIVE: To compare the prevalence of cognitive symptoms and their functional impact by age group accounting for depression and number of other health conditions. METHODS: We analyzed data from the 2011 Behavioral Risk Factor Surveillance System, a population-based, cross-sectional telephone survey of US adults. Twenty-one US states asked participants (n = 131, 273) about cognitive symptoms (worsening confusion or memory loss in the past year) and their functional impact (interference with activities and need for assistance). We analyzed the association between age, depression history and cognitive symptoms and their functional impact using logistic regression and adjusted for demographic characteristics and other health condition count. RESULTS: There was a significant interaction between age and depression (p < 0.0001). In adults reporting depression, the adjusted odds of cognitive symptoms in younger age groups (<75 years) were comparable or greater to those in the oldest age group (≥75 years) with a peak in the middle age (45-54 years) group (OR 1.9 (95% Confidence Interval: 1.4-2.5). In adults without depression, adults <75 years had a significantly lower adjusted odds of cognitive symptoms compared to the oldest age group with the exception of the middle-aged group where the difference was not statistically significant. Over half of adults under age 65 with depression reported that cognitive symptoms interfered with life activities compared to 35.7% of adults ≥65 years. CONCLUSIONS: Cognitive symptoms are not universally higher in older adults; middle-aged adults are also particularly vulnerable. Given the adverse functional impact associated with cognitive symptoms in younger adults, clinicians should assess cognitive symptoms and their functional impact in adults of all ages and consider treatments that impact both cognition and functional domains.