What eye and hand movements tell us about expectations towards argument order: An eye- and mouse-tracking study in German

Previous research on real-time sentence processing in German has shown that listeners use the morphological marking of accusative case on a sentence-initial noun phrase to not only interpret the current argument as the object and patient, but also to predict a plausible agent. So far, less is known about the use of case marking to predict the semantic role of upcoming arguments after the subject/agent has been encountered. In the present study, we examined the use of case marking for argument interpretation in transitive as well as ditransitive structures. We aimed to control for multiple factors that could have influenced processing in previous studies, including the animacy of arguments, world knowledge, and the perceptibility of the case cue. Our results from eye- and mouse-tracking indicate that the exploitation of the first case cue that enables the interpretation of the unfolding sentence is influenced by (i) the strength of argument order expectation and (ii) the perceptual salience of the case cue. PsycINFO code: 2720 Linguistics & Language & Speech.

Next-generation sequencing and comprehensive data reassessment in 263 adult patients with neuromuscular disorders: insights into the gray zone of molecular diagnoses

BACKGROUND

Neuromuscular disorders (NMDs) are heterogeneous conditions with a considerable fraction attributed to monogenic defects. Despite the advancements in genomic medicine, many patients remain without a diagnosis. Here, we investigate whether a comprehensive reassessment strategy improves the diagnostic outcomes.

METHODS

We analyzed 263 patients with NMD phenotypes that underwent diagnostic exome or genome sequencing at our tertiary referral center between 2015 and 2023. We applied a comprehensive reassessment encompassing variant reclassification, re-phenotyping and NGS data reanalysis. Multivariable logistic regression was performed to identify predictive factors associated with a molecular diagnosis.

RESULTS

Initially, a molecular diagnosis was identified in 53 cases (20%), while an additional 23 (9%) had findings of uncertain significance. Following comprehensive reassessment, the diagnostic yield increased to 23%, revealing 44 distinct monogenic etiologies. Reasons for newly obtained molecular diagnoses were variant reclassifications in 7 and NGS data reanalysis in 3 cases including one recently described disease-gene association (DNAJB4). Male sex reduced the odds of receiving a molecular diagnosis (OR 0.42; 95%CI 0.21-0.82), while a positive family history (OR 5.46; 95%CI 2.60-11.76) and a myopathy phenotype (OR 2.72; 95%CI 1.11-7.14) increased the likelihood. 7% were resolved through targeted genetic testing or classified as acquired etiologies.

CONCLUSION

Our findings reinforce the use of NGS in NMDs of suspected monogenic origin. We show that a comprehensive reassessment enhances diagnostic accuracy. However, one needs to be aware that genetic diagnoses are often made with uncertainty and can even be downgraded based on new evidence.

A decadal atmospheric ammonia reanalysis product in China

Atmospheric ammonia has great environmental implications due to its important role in ecosystem and nitrogen cycle, as well as contribution to formation of secondary particles. China is recognized as a hotspot of NH3 pollution owing to agricultural and livestock intensification. In the quest to achieve a comprehensive understanding of atmospheric ammonia load and to quantify its environmental impacts in China, relying solely either on existing measurements or on model simulations falls short. Their limitations, either in spatial coverage and integrity or in data quality, fails to meet the needs. Available reanalysis products exhibit a marked deficiency in ammonia data. We therefore aim to propose an integrated ammonia reanalysis product in China, adeptly melding satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI) NH3 retrievals with chemical transport model simulation, capitalizing on the robust Ensemble Kalman Filter (EnKF) data assimilation methodology. The product is validated in high quality via the comparison against independent measurements from ground monitoring stations. Spanning a decade from 2013 to 2022, our reanalysis uncovers not just the spatial intricacies of NH3 concentrations but also their temporal dynamics. Our findings pinpointed the spatial disparities in atmospheric ammonia intensities, highlighting regional hotspots in the NCP, SCB, and Northeast China, and identified annual and seasonal patterns. Our research provides crucial insights for shaping future NH3 pollution prevention and control strategies in China.

Thermal stress information as a tourism-oriented climate product: Performance analysis for selected urban destinations in Romania and Italy

The study addresses the characteristics of a climate service targeting tourists and discusses the evaluation of its products with a particular focus on the thermal stress information. Furthermore, an assessment of the impact of input data on the accuracy and relevance of the thermal stress product is presented. The thermal stress is expressed through UTCI (Universal Thermal Climate Index) and it is computed from UERRA regional reanalysis and E-OBS gridded dataset, for summer season during 2011-2018. The analysis targets 10 cities with different characteristics located in Romania and Italy. It focuses on the impact of three temperature-related input data (instantaneous temperature at 12:00 UTC, daily maximum and daily mean temperature) on the thermal stress intensity. The results show that differences up to 4 days in the pronounced thermal stress category may appear when employing daily maximum temperature compared to the use 12:00 UTC instantaneous temperature, while the use of daily mean temperature leads to strong underestimation of thermal stress in this category. The findings are of interest in defining the technical choices of products to be incorporated in a climate service for tourism in order to assure a good user uptake.

Phenotype-driven reanalysis reveals five novel pathogenic variants in 40 exome-negative families with Charcot-Marie-Tooth Disease

BACKGROUND

To identify genetic causes in 40 whole exome sequencing (WES)-negative Charcot-Marie-Tooth (CMT) families and provide a summary of the clinical and genetic features of the diagnosed patients.

METHODS

The clinical information and sequencing data of 40 WES-negative families out of 131 CMT families were collected, and phenotype-driven reanalysis was conducted using the Exomiser software.

RESULTS

The molecular diagnosis was regained in 4 families, increasing the overall diagnosis rate by 3.0%. One family with adolescent-onset pure CMT1 was diagnosed [POLR3B: c.2810G>A (p.R937Q)] due to the novel genotype-phenotype association. One infantile-onset, severe CMT1 family with deep sensory disturbance was diagnosed by screening the BAM file and harbored c.1174C>T (p.R392*) and 875_927delinsCTGCCCACTCTGCCCACTCTGCCCACTCTG (p.V292Afs53) of PRX. Two families were diagnosed due to characteristic phenotypes, including an infantile-onset ICMT family with renal dysfunction harboring c.213_233delinsGAGGAGCA (p.S72Rfs34) of INF2 and an adolescent-onset CMT2 family with optic atrophy harboring c.560C>T (p.P187L) and c.616A>G (p.K206E) of SLC25A46. According to the American College of Medical Genetics and Genomics (ACMG) guidelines, the variants of POLR3B and SLC25A46 were classified as likely pathogenic, and the variants of INF2 and PRX were pathogenic. All these variants were first reported worldwide except for p.R392* of PRX.

CONCLUSIONS

We identified five novel pathogenic variants in POLR3B, PRX, INF2, and SLC25A46, which broaden their phenotypic and genotypic spectrums. Regular phenotype-driven reanalysis is a powerful strategy for increasing the diagnostic yield of WES-negative CMT patients, and long-term follow-up and screening BAM files for contiguous deletion and missense variants are both essential for reanalysis.

Reanalysis of whole-exome sequencing (WES) data of children with neurodevelopmental disorders in a standard patient care context

This study aims to inform future genetic reanalysis management by evaluating the yield of whole-exome sequencing (WES) reanalysis in standard patient care in the Netherlands. Single-center data of 159 patients with a neurodevelopmental disorder (NDD), in which WES analysis and reanalysis were performed between January 1, 2014, and December 31, 2021, was retrospectively collected. Patients were included if they were under the age of 18 years at initial analysis and if this initial analysis did not result in a diagnosis. Demographic, phenotypic, and genotypic characteristics of patients were collected and analyzed. The primary outcomes of our study were (i) diagnostic yield at reanalysis, (ii) reasons for detecting a new possibly causal variant at reanalysis, (iii) unsolicited findings, and (iv) factors associated with positive result of reanalysis. In addition, we conducted a questionnaire study amongst the 7 genetic department in the Netherlands creating an overview of used techniques, yield, and organization of WES reanalysis. The single-center data show that in most cases, WES reanalysis was initiated by the clinical geneticist (65%) or treating physician (30%). The mean time between initial WES analysis and reanalysis was 3.7 years. A new (likely) pathogenic variant or VUS with a clear link to the phenotype was found in 20 initially negative cases, resulting in a diagnostic yield of 12.6%. In 75% of these patients, the diagnosis had clinical consequences, as for example, a screening plan for associated signs and symptoms could be devised. Most (32%) of the (likely) causal variants identified at WES reanalysis were discovered due to a newly described gene-disease association. In addition to the 12.6% diagnostic yield based on new diagnoses, reclassification of a variant of uncertain significance found at initial analysis led to a definite diagnosis in three patients. Diagnostic yield was higher in patients with dysmorphic features compared to patients without clear dysmorphic features (yield 27% vs. 6%; p = 0.001).

CONCLUSIONS

Our results show that WES reanalysis in patients with NDD in standard patient care leads to a substantial increase in genetic diagnoses. In the majority of newly diagnosed patients, the diagnosis had clinical consequences. Knowledge about the clinical impact of WES reanalysis, clinical characteristics associated with higher yield, and the yield per year after a negative WES in larger clinical cohorts is warranted to inform guidelines for genetic reanalysis. These guidelines will be of great value for pediatricians, pediatric rehabilitation specialists, and pediatric neurologists in daily care of patients with NDD.

WHAT IS KNOWN

• Whole exome sequencing can cost-effectively identify a genetic cause of intellectual disability in about 30-40% of patients. • WES reanalysis in a research setting can lead to a definitive diagnosis in 10-20% of previously exome negative cases.

WHAT IS NEW

• WES reanalysis in standard patient care resulted in a diagnostic yield of 13% in previously exome negative children with NDD. • The presence of dysmorphic features is associated with an increased diagnostic yield of WES reanalysis.

Validation and calibration of aerosol optical depth and classification of aerosol types based on multi-source data over China

A refined classification of aerosol types is essential to identify and control air pollution sources. This study focused on improving the resolution and accuracy of aerosol optical depth (AOD) and further refining the classification of aerosol types in China. We validated the accuracy of the AOD acquired using the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) and Copernicus Atmosphere Monitoring Service (CAMS) by comparing it with that acquired using from the Aeronet Robotic Network (AERONET). We simulated the AOD with high spatial resolution and accuracy based on the extremely randomized trees (ERT), adaptive boosting (AdaBoost), and gradient boosting decision trees (GBDT) models and identified aerosol types based on the Angstrom Exponent (AE) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the calibrated AOD. The results showed that CAMS overestimates AOD (21.4 %) and MERRA2 underestimates AOD (-17.3 %). Among the three machine learning models, the ERT model performed best, with a determination coefficient (R2) of 0.825 and the root-mean-square error (RMSE) of 0.174. Biomass burning/urban-industrial aerosols dominated China, with the largest contributions to southern, eastern, and central China in spring and summer. Clean continental aerosols contributed the most to southwestern China in fall and winter, whereas desert dust aerosols contributed the most to northwestern and eastern China in spring.

Reanalysis of Chromosomal Microarray Data Using a Smaller Copy Number Variant Call Threshold Identifies Four Cases with Heterozygous Multiexon Deletions of ARID1B, EHMT1, and FOXP1 Genes

Introduction

Chromosomal microarray (CMA) is a highly accurate and established method for detecting copy number variations (CNVs) in clinical genetic testing. CNVs are important etiological factors for disorders such as intellectual disability, developmental delay, and multiple congenital anomalies. Recently developed analytical methods have facilitated the identification of smaller CNVs. Therefore, reanalyzing CMA data using a smaller CNV calling threshold may yield useful information. However, this method was left to the discretion of each institution.

Methods

We reanalyzed the CMA data of 131 patients using a smaller CNV call threshold: 50 kb 50 probes for gain and 25 kb 25 probes for loss. We interpreted the reanalyzed CNVs based on the most recently available information. In the reanalysis, we filtered the data using the Clinical Genome Resource dosage sensitivity gene list as an index to quickly and efficiently check morbid genes.

Results

The number of copy number loss was approximately 20 times greater, and copy number gain was approximately three times greater compared to those in the previous analysis. We detected new likely pathogenic CNVs in four participants: a 236.5 kb loss within ARID1B, a 50.6 kb loss including EHMT1, a 46.5 kb loss including EHMT1, and an 89.1 kb loss within the FOXP1 gene.

Conclusion

The method employed in this study is simple and effective for CMA data reanalysis using a smaller CNV call threshold. Thus, this method is efficient for both ongoing and repeated analyses. This study may stimulate further discussion of reanalysis methodology in clinical laboratories.

An Australian convective wind gust climatology using Bayesian hierarchical modelling

To quantify the hazard or risks associated with severe convective wind gusts, it is necessary to have a reliable and spatially complete climatology of these events. The coupling of observational and global reanalysis (ERA-Interim) data over the period 2005-2015 is used here to facilitate the development of a spatially complete convective wind gust climatology for Australia. This is done through the development of Bayesian Hierarchical models that use both weather station-based wind gust observations and seasonally averaged severe weather indices (SWI), calculated using reanalysis data, to estimate seasonal gust frequencies across the country while correcting for observational biases specifically, the sparse observational network to record events. Different SWI combinations were found to explain event counts for different seasons. For example, combinations of Lifted Index and low level wind shear were found to generate the best results for autumn and winter. While for spring and summer, the composite Microburst Index and the combination of most unstable CAPE and 0-1 km wind shear were found to be most successful. Results from these models showed a minimum in event counts during the winter months, with events that do occur mainly doing so along the southwest coast of Western Australia or along the coasts of Tasmania and Victoria. Summer is shown to have the largest event counts across the country, with the largest number of gusts occurring in northern Western Australia extending east into the Northern Territory with another maximum over northeast New South Wales. Similar trends were found with an extended application of the models to the period 1979-2015 when utilizing only reanalysis data as input. This implementation of the models highlights the versatility of the Bayesian hierarchical modelling approach and its ability, when trained, to be used in the absence of observations.

Spatiotemporal evolution of global long-term patterns of soil moisture

Surface soil moisture (SM) is essential for existence of biotic lifeform and geophysical processes. However, with increasing global warming due to climatic changes, its spatiotemporal evolution is uncertain and largely unknown. In this study we detected long-term (40 years; 1981-2020) SM patterns of global vegetated areas through spatial timeseries clustering using the state-of-the-art ERA5-Land dataset. In addition, we also analyzed long-term patterns of precipitation (P), evapotranspiration (bare soil evaporation (BSe) and vegetation transpiration (VT)), and normalized difference vegetation index (NDVI). Our results indicate that surface SM (0-7 cm depth) of about 48 % and 9 % of the global vegetated area is showing drying and wetting pattern over the past 40 years, respectively. The detected soil drying, and wetting patterns were largely consistent across different soil depth, with 90 % and 80 % pattern similarity of surface soil layer with 2^nd soil layer (7-28 cm) and 3^rd soil layer (28-100 cm), respectively. About 80 % of areas with drying soil pattern also showed increasing evapotranspiration and/or decreasing precipitation. Specifically, decreasing P, increasing BSe and VT pattern were detected for 11 % of the soil drying pattern area. Similarly, increasing BSe and VT pattern, only decreasing P and only increasing VT pattern were detected for 17 %, 25 % and 12 % of soil drying areas, respectively. Both decreasing precipitation and increasing evapotranspiration patterns showed about 40 % similarity with decreasing soil moisture patterns. Across different landcover types, broadleaved forests, and cropland areas showed largest drying pattern. Under the future global warming scenario, the global soil water is expected to decrease as evapotranspiration would increase with inconsistent trend of global precipitation change. Our findings are of utmost importance for global soil water resource conservation and management.

MADIA - Meteorological variables for agriculture: A dataset for the Italian area

The MADIA gridded dataset provides the dekadal series of the main agro-meteorological variables derived from ERA5 hourly surface data, across Italy for the period 1981-2021, and their respective 1981-2010 and 1991-2020 climate normals, also including absolute minimum and maximum and the main quantiles. Temporal and spatial resolutions are 10-day and 0.25 degrees respectively and the dataset is annotated with standard metadata. The dataset was obtained by: (1) estimating the daily time series of minimum, average and maximum air temperature, minimum and maximum air relative humidity, wind speed, surface solar radiation downwards, precipitation and reference evapotranspiration according to the FAO Penman-Monteith method; (2) summarising them to 10-day series as accumulated values for precipitation and evapotranspiration and mean values for the other variables. The MADIA dataset is provided in both NetCDF and csv format. A complementary vector file is provided which reports for every cell the fractions covered of the total area of each administrative unit considered to derive statistics for Italy on the European Nomenclature of Territorial Units for Statistics levels (NUTS 2 and 3). Other potential dataset reuses are the estimation of bioclimatic indices and statistical downscaling of climate scenarios.

Musical Garden Paths: Evidence for Syntactic Revision Beyond the Linguistic Domain

While theoretical and empirical insights suggest that the capacity to represent and process complex syntax is crucial in language as well as other domains, it is still unclear whether specific parsing mechanisms are also shared across domains. Focusing on the musical domain, we developed a novel behavioral paradigm to investigate whether a phenomenon of syntactic revision occurs in the processing of tonal melodies under analogous conditions as in language. We present the first proof-of-existence for syntactic revision in a set of tonally ambiguous melodies, supporting the relevance of syntactic representations and parsing with language-like characteristics in a nonlinguistic domain. Furthermore, we find no evidence for a modulatory effect of musical training, suggesting that a general cognitive capacity, rather than explicit knowledge and strategies, may underlie the observed phenomenon in music.

Diagnostic performance of automated, streamlined, daily updated exome analysis in patients with neurodevelopmental delay

Background

The diagnostic yield of whole-exome sequencing (WES) varies from 30%–50% among patients with mild to severe neurodevelopmental delay (NDD)/intellectual disability (ID). Routine retrospective reanalysis of undiagnosed patients has increased the total diagnostic yield by 10–15%. Here, we performed proband-only WES of 1065 patients with NDD/ID and applied a prospective, daily reanalysis automated pipeline to patients without clinically significant variants to facilitate diagnoses.

Methods

The study included 1065 consecutive patients from 1056 nonconsanguineous unrelated families from 10 multimedical centers in South Korea between April 2018 and August 2021. WES data were analyzed daily using automatically updated databases with variant classification and symptom similarity scoring systems.

Results

At the initial analysis, 402 patients from 1056 unrelated families (38.0%, 402/1,056 families) had a positive genetic diagnosis. Daily prospective, automated reanalysis resulted in the identification of 34 additional diagnostic variants in 31 patients (3%), which increased our molecular diagnostic yield to 41% (433/1056 families). Among these 31 patients, 26 were diagnosed with 23 different diseases that were newly discovered after 2019. The time interval between the first analysis and the molecular diagnosis by reanalysis was 1.2 ± 0.9 years, which was shorter in the patients enrolled during the latter part of the study period.

Conclusion

Daily updated databases and reanalysis systems enhance the diagnostic performance in patients with NDD/ID, contributing to the rapid diagnosis of undiagnosed patients by applying the latest molecular genetic information.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00464-x.

Retrospective analysis of a clinical exome sequencing cohort reveals the mutational spectrum and identifies candidate disease-associated loci for BAFopathies

PURPOSE

BRG1/BRM-associated factor (BAF) complex is a chromatin remodeling complex that plays a critical role in gene regulation. Defects in the genes encoding BAF subunits lead to BAFopathies, a group of neurodevelopmental disorders with extensive locus and phenotypic heterogeneity.

METHODS

We retrospectively analyzed data from 16,243 patients referred for clinical exome sequencing (ES) with a focus on the BAF complex. We applied a genotype-first approach, combining predicted genic constraints to propose candidate BAFopathy genes.

RESULTS

We identified 127 patients carrying pathogenic variants, likely pathogenic variants, or de novo variants of unknown clinical significance in 11 known BAFopathy genes. Those include 34 patients molecularly diagnosed using ES reanalysis with new gene-disease evidence (n = 21) or variant reclassifications in known BAFopathy genes (n = 13). We also identified de novo or predicted loss-of-function variants in 4 candidate BAFopathy genes, including ACTL6A, BICRA (implicated in Coffin-Siris syndrome during this study), PBRM1, and SMARCC1.

CONCLUSION

We report the mutational spectrum of BAFopathies in an ES cohort. A genotype-driven and pathway-based reanalysis of ES data identified new evidence for candidate genes involved in BAFopathies. Further mechanistic and phenotypic characterization of additional patients are warranted to confirm their roles in human disease and to delineate their associated phenotypic spectrums.

Artificial intelligence (AI)-assisted exome reanalysis greatly aids in the identification of new positive cases and reduces analysis time in a clinical diagnostic laboratory

PURPOSE

Artificial intelligence (AI) and variant prioritization tools for genomic variant analysis are being rapidly developed for use in clinical diagnostic testing. However, their clinical utility and reliability are currently limited. Therefore, we performed a validation of a commercial AI tool (Moon) and a comprehensive reanalysis of previously collected clinical exome sequencing cases using an open-source variant prioritization tool (Exomiser) and the now-validated AI tool to test their feasibility in clinical diagnostics.

METHODS

A validation study of Moon was performed with 29 positive cases determined by previous manual analysis. After validation, reanalysis was performed on 80 previously manually analyzed nondiagnostic exome cases using Moon. Finally, a comparison between Moon and Exomiser was completed regarding their ability to identify previously completed positive cases and to identify new positive cases.

RESULTS

Moon correctly selected the causal variant(s) in 97% of manually analyzed positive cases and identified 7 new positive cases. Exomiser correctly identified the causal gene in 85% of positive cases and agreed with Moon by ranking the new gene in its top 10 list 43% of the time.

CONCLUSION

The use of AI in diagnostic laboratories greatly enhances exome sequencing analysis by reducing analysis time and increasing the diagnostic rate.

Novel variants in OSGEP leading to Galloway-Mowat syndrome by altering its subcellular localization

Galloway-Mowat syndrome (GAMOS) is an extremely rare clinically heterogeneous autosomal or X-linked inherited recessive disease characterized by early-onset steroid-resistant nephrotic syndrome (SRNS), microcephaly and neurological impairment. In this study, two siblings mainly presenting with decreased head circumference, hypotonia, gross motor delay, and dysmorphic features were initially detected without pathogenic variants by karyotyping, SNP-array and WES. After a 3 year's follow-up, the proband manifested additional proteinuria, hematuria and "deeper sulci" with a sign of brain atrophy. By reanalysis on the proband's previous WES data, two novel compound heterozygous variants of OSGEP (c.133dupA; c.608C > T) were identified. Furthermore, functional studies showed that the variants reduced the expression of OSGEP protein and activated the DNA damage response (DDR) signaling in the lymphoblastoid cell lines (LCLs) obtained from the patient. The analysis of protein localization with confocal microscopy revealed that the EGFP-tagged/HA-tagged mutant OSGEP proteins were abnormal aggregation or retained inside the cytosol, respectively. Our study not only expanded the pathogenic variant spectrum of OSGEP but also carried on regular follow-up for kidney involvement and established a strategy for evaluation on the function of mutant OSGFP by subcellular localization assay.

Re-analysis of suspected DWI blood samples for ethanol: A Texas case study

The gradual loss of ethanol over time in stored blood specimens under a variety of conditions has been well documented. An analysis of over 160 blood specimens from suspected impaired drivers was recently accomplished with the knowledge that the samples had previously been analyzed. These two analyses were performed independently, using different methods and instrumentation and by different individuals. Although in most cases there were two tubes available in each case, the tube used for the initial analysis was also used for the second analysis. Reported results from both laboratories were obtained and evaluated retrospectively. Over an average interval of approximately 13 months (range 34-1002 days), the average change of ethanol concentrations was a loss of 0.006 g/dL, with a maximum loss of 0.023 g/dL, and a maximum increase of 0.004 g/dL. The median difference was a loss of 0.005 g/dL. The percentage of samples that reported second concentrations equal to or less than the original reported concentrations (to the thousandths decimal place) was 96.4%. No correlation was observed between the net loss and the initial BAC value, but the amount of time between analyses did impact the extent of the loss of ethanol as determined by the second analysis. Our results indicate a smaller loss of ethanol, and hence stronger correlation between analytical events, than what has been experienced in similar work. Based on our analysis and review of previously opened and analyzed blood specimens, a previously opened blood tube can yield a strong correlation to the original analysis and may therefore be appropriate if a second tube is not available or compromised in some way.

Bias-corrected monthly precipitation data over South Siberia for 1979-2019

Bias-Corrected Precipitation data over South Siberia (CPSS) contains monthly precipitation data for the area within the coordinates 50-65 N, 60-120 E for the period from January 1979 to December 2019. CPSS data were combined from monthly total precipitation data from ERA5 reanalysis European Centre for Medium-Range Weather Forecasts and precipitation data records from ground weather stations. The ERA5 data were scaled according to the derived scale coefficient. The linear scaling coefficient for each month and weather station were calculated and extrapolated to the study area using the ordinary kriging method. Data spatial resolution is 0.25° in the latitude and 0.25° in the longitude. CPSS reproduces the spatial variability of precipitation more precisely than can be done from the weather station observation network. The CPSS dataset will be useful for the study of extreme precipitation events and allow for more accurate hydrologic risk assessment at a regional level based on climate model results.

Evaluation of the ERA5 reanalysis-based Universal Thermal Climate Index on mortality data in Europe

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 - the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) - as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

Genetic health professionals' experiences with initiating reanalysis of genomic sequence data

Despite the increased diagnostic yield associated with genomic sequencing (GS), a sizable proportion of patients do not receive a genetic diagnosis at the time of the initial GS analysis. Systematic data reanalysis leads to considerable increases in genetic diagnosis rates yet is time intensive and leads to questions of feasibility. Few policies address whether laboratories have a duty to reanalyse and it is unclear how this impacts clinical practice. To address this, we interviewed 31 genetic health professionals (GHPs) across Europe, Australia and Canada about their experiences with data reanalysis and variant reinterpretation practices after requesting GS for their patients. GHPs described a range of processes required to initiate reanalysis of GS data for their patients and often practices involved a combination of reanalysis initiation methods. The most common mechanism for reanalysis was a patient-initiated model, where they instruct patients to return to the genetic service for clinical reassessment after a period of time or if new information comes to light. Yet several GHPs expressed concerns about patients' inabilities to understand the need to return to trigger reanalysis, or advocate for themselves, which may exacerbate health inequities. Regardless of the reanalysis initiation model that a genetic service adopts, patients' and clinicians' roles and responsibilities need to be clearly outlined so patients do not miss the opportunity to receive ongoing information about their genetic diagnosis. This requires consensus on the delineation of these roles for clinicians and laboratories to ensure clear pathways for reanalysis and reinterpretation to be performed to improve patient care.

Reanalysis of residential radon surveys in China from 1980 to 2019

A study on the published historic data of the residential radon concentration was carried out in order to provide a systematic retrospect and the confluent analysis of the investigations from 1980 to 2019 in China. A new database was established by collecting the results of nearly all radon surveys reported in China. A total of 129 surveys on residential radon, covering 147 cities with the sampling size of 72,295 were collected into the data pool for secondary analysis. The results from different decades confirmed the rapid increase trend of residential radon concentration in China. The geographical coverage, the sampling density and the geographic distribution of sampling sites of these surveys were discussed. The analysis on the local data sequences indicated the average increasing rate of residential radon concentration for 28 Chinese cities was estimated to be 0.80 Bq·m^-3·a^-1 in last 40 years. The results in this study provided the overall expression of the radon investigations in China and were expected to be benefit to the radon-related studies in the future.

Reanalysis and integration of public microarray datasets reveals novel host genes modulated in leprosy

Due to multiple hypothesis testing with often limited sample size, microarrays and other-omics technologies can sometimes produce irreproducible findings. Complementary to better experimental design, reanalysis and integration of gene expression datasets may help overcome reproducibility issues by identifying consistent differentially expressed genes from independent studies. In this work, after a systematic search, nine microarray datasets evaluating host gene expression in leprosy were reanalyzed and the information was integrated to strengthen evidence of differential expression for several genes. Our results are relevant in prioritizing genes and pathways for further investigation, whether in functional studies or in biomarker discovery. Reanalysis of individual datasets revealed several differentially expressed genes (DEGs) in accordance with original reports. Then, five integration methods (P value and effect size based) were tested. In the end, random-effects model and ratio association were selected as the main methods to pinpoint DEGs. Overall, classic pathways were found corroborating previous findings and validating this approach. Also, we identified some novel DEG involved especially with skin development processes (AQP3, AKR1C3, CYP27B1, LTB, VDR) and keratinocyte biology (CSTA, DSG1, KRT14, KRT5, PKP1, IVL), both still poorly understood in leprosy context. In addition, here we provide aggregated evidence towards some gene candidates that should be prioritized in further leprosy research, as they are likely important in immunopathogenesis. Altogether, these data are useful in better understanding host responses to the disease and, at the same time, provide a list of potential host biomarkers that could be useful in complementing leprosy diagnosis based on transcriptional levels.

Heat wave trends in Southeast Asia during 1979-2018: The impact of humidity

In tropics, especially Southeast Asia (SEA), heat wave (HW) research is seriously scarce although several global studies have projected this region to be greatly susceptible to increasing HW events under climate change scenarios. Using the recently released ERA5 reanalysis data, we find that in most parts of SEA, HWs are becoming more frequent, longer-lasting and stronger, no matter using dry-bulb or wet-bulb temperatures to define HW. The increasing trends of HW characteristics based on minimum temperatures are larger than those based on maximum temperatures, suggesting an alarming situation of anomalously warm night. HW characteristics based on wet-bulb temperatures show higher increasing rates in the IndoChina Peninsula and Malay Peninsula than those based on dry-bulb temperatures. Nearly all HW characteristics are significantly correlated with El Niño index, but Indian Ocean Dipole only significantly impacts HW characteristics based on wet-bulb temperature in Java. Results derived from other reanalysis products exhibit general agreement with those from ERA5, lending support to the findings reported herein. This study highlights the different role of humidity in changing HW trends in different regions of SEA, and calls for attention to the associated risk of increasing nighttime temperatures during HWs.

Comparison of temperature-mortality associations using observed weather station and reanalysis data in 52 Spanish cities

BACKGROUND

Most studies use temperature observation data from weather stations near the analyzed region or city as the reference point for the exposure-response association. Climatic reanalysis data sets have already been used for climate studies, but are not yet used routinely in environmental epidemiology.

METHODS

We compared the mortality-temperature association using weather station temperature and ERA-5 reanalysis data for the 52 provincial capital cities in Spain, using time-series regression with distributed lag non-linear models.

RESULTS

The shape of temperature distribution is very close between the weather station and ERA-5 reanalysis data (correlation from 0.90 to 0.99). The overall cumulative exposure-response curves are very similar in their shape and risks estimates for cold and heat effects, although risk estimates for ERA-5 were slightly lower than for weather station temperature.

CONCLUSIONS

Reanalysis data allow the estimation of the health effects of temperature, even in areas located far from weather stations or without any available.

Development of a combined empirical index for a 5-day forecast of heavy precipitation over the Bernese Alps

The Bernese Alps are a region that is very prone for the initiation of thunderstorms. In fact, the flow and convergence of air and water vapor from the Swiss Plateau to the Swiss Alps is frequently favouring the formation of isolated rainfall events, which then may cause loss and damage in settlements. Due to the complex topography of the Bernese Alps, the forecasting and nowcasting of heavy convective precipitation remain challenging. A critical need therefore exists for the development of new forecasting tools so as to improve the predictability of convective precipitation events, also with the aim to alert first responders and to subsequently reduce damage. This study aims at developing an empirical index for the forecasting of heavy precipitation events in the Bernese Alps by using two reanalysis datasets, ECMWF's ERA-Interim and NASA's MERRA-2; in addition, the ICON-EU model is employed here to test and verify the index for the 2018 summer period. Our approach is based on the calculation of several convective indices as well as on the assessment of their relative forecast skills using a dichotomous scheme. The Heavy Precipitation Index (HPI) is then defined by combining the best performing combination of convective indices. HPI is aimed at forecasting heavy precipitation events over the Bernese Alps. We show that the combination of several indices, including DCI or KI, have a better capability to forecast heavy precipitation in the Bernese Alps than has the commonly used CAPE. Therefore, HPI should be seen as a pre-alert index when it comes to assist first responders in situations of crisis and in the process of decision making.

Inferential reproduction analysis demonstrated that "paracetamol for acute low back pain" trial conclusions were reproducible

OBJECTIVES

The aim of this study was to reanalyze and reinterpret data obtained in Paracetamol in Acute Low Back Pain (PACE), the first large randomized controlled trial evaluating the efficacy of paracetamol in acute low back pain, to assess the inferential reproducibility of the original conclusions.

STUDY DESIGN AND SETTING

Mixed effects models were used to reanalyze pain intensity (primary outcome; 11-point Numeric Rating Scale) and physical functioning, health-related quality of life, sleep quality, and time until recovery (as secondary outcomes), according to the intention-to-treat principle. The original authors of the PACE study were not involved in the development of the methods for this reanalysis.

RESULTS

The reproduction analyses indicated no effect of treatment on pain intensity and confidence intervals excluded clinically worthwhile effects (adjusted main effect for regular paracetamol vs. placebo 0.00 [-0.02, 0.01; P = 0.85]; adjusted main effect for paracetamol as-needed vs. placebo 0.00 [-0.02, 0.01; P = 0.92]). Similar results were obtained for all secondary outcomes.

CONCLUSION

This study indicates that the conclusions of the PACE trial are inferentially reproducible, even when using a different analytical approach. This reinforces the notion that the management of acute low back pain should focus on providing patients advice and reassurance without the addition of paracetamol.

Robinow Syndrome and Brachydactyly: An Interplay of High-Throughput Sequencing and Deep Phenotyping in a Kindred

We report a family with a spectrum of short stature, craniofacial dysmorphism, and digital anomalies in a father and 2 daughters, with the youngest (proband) displaying a severe phenotype. Clinically, autosomal dominant Robinow syndrome (ADRS) was diagnosed. Whole-exome sequencing identified a heterozygous pathogenic BMP2 variant in the father and his daughters. The phenotype of short stature, facial dysmorphism, and skeletal anomalies with or without cardiac anomalies related to BMP2 haploinsufficiency has some facial and digital resemblance to ADRS. Although this variant segregated in the affected members, it failed to explain the severe phenotype of the proband. A reanalysis of the girl's raw data confirmed 2 disorders: a de novo likely pathogenic DVL1 variant implicated in ADRS and the familial BMP2 variant. A close interplay of high-throughput sequencing and deep phenotyping unraveled the complexities of the blended phenotype in the proband.

Shared neural resources of rhythm and syntax: An ALE meta-analysis

A growing body of evidence has highlighted behavioral connections between musical rhythm and linguistic syntax, suggesting that these abilities may be mediated by common neural resources. Here, we performed a quantitative meta-analysis of neuroimaging studies using activation likelihood estimate (ALE) to localize the shared neural structures engaged in a representative set of musical rhythm (rhythm, beat, and meter) and linguistic syntax (merge movement, and reanalysis) operations. Rhythm engaged a bilateral sensorimotor network throughout the brain consisting of the inferior frontal gyri, supplementary motor area, superior temporal gyri/temporoparietal junction, insula, intraparietal lobule, and putamen. By contrast, syntax mostly recruited the left sensorimotor network including the inferior frontal gyrus, posterior superior temporal gyrus, premotor cortex, and supplementary motor area. Intersections between rhythm and syntax maps yielded overlapping regions in the left inferior frontal gyrus, left supplementary motor area, and bilateral insula-neural substrates involved in temporal hierarchy processing and predictive coding. Together, this is the first neuroimaging meta-analysis providing detailed anatomical overlap of sensorimotor regions recruited for musical rhythm and linguistic syntax.

Impact of land use and land cover transitions and climate on evapotranspiration in the Lake Naivasha Basin, Kenya

The Lake Naivasha Basin in Kenya has experienced significant land use cover changes (LUCC) that has been hypothesized to have altered the hydrological regime in recent decades. While it is generally recognized that LUCC will impact evapotranspiration (ET), the precise nature of such impact is not very well understood. This paper describes how land use conversions among grassland and croplands have influenced ET in the Lake Naivasha Basin for the period 2003 to 2012. MODIS data products were used in combination with the European Centre for Medium-Range Weather Forecasts (ECMWF) data sets to model ET using the Surface Energy Balance System (SEBS). The results indicate that conversions from grassland to cropland accounted for increases in ET of up to 12% while conversion from cropland back to grasslands (abandonment) reduced ET by ~4%. This suggests that recently cultivated agricultural lands could increase local water demands, while abandonment of the farms could decrease the water loss and eventually increase the water availability. Also, recovery of ET following re-conversion from cropland to grassland might be impeded due to delayed recovery of soil properties since parts of the catchment are continuously being transformed with no ample time given for soil recovery. The annual ET over the 10 years shows an estimated decline from 724 mm to 650 mm (~10%). This decline is largely explained by a reduction in net radiation, an increase in actual vapour pressure whose net effect also led to decrease in the surface-air temperature difference. These findings suggest that in order to better understand LUCC effects on water resources of Lake Naivasha, it is important to take into account the effect of LUCC and climate because large scale changes of vegetation type from grassland to cropland substantially will increase evapotranspiration with implications on the water balance.

A high-resolution hydro power time-series model for energy systems analysis: Validated with Chinese hydro reservoirs

We expand the renewable technology model palette and present a validated high resolution hydro power time series model for energy systems analysis. Among the weather-based renewables, hydroelectricity shows unique storage-like flexibility, which is particularly important given the high variability of wind and solar power. Often limited by data availability or computational performance, a high resolution, globally applicable and validated hydro power time series model has not been available. For a demonstration, we focus on 41 Chinese reservoir-based hydro stations as a demo, determine their upstream basin areas, estimate their inflow based on gridded surface runoff data and validate their daily inflow time series in terms of both flow volume and potential power generation. Furthermore, we showcase an application of these time series with hydro cascades in energy system long term investment planning. Our method's novelty lies in:

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it is based on highly resolved spatial-temporal datasets;

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both data and algorithms used here are globally applicable;

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it includes a hydro cascade model that can be integrated into energy system simulations.

Increased diagnostic yield by reanalysis of data from a hearing loss gene panel

Background

Congenital hearing loss affects approximately 1–2 infants out of every 1000, with 50% of the cases resulting from genetic factors. Targeted gene panels have been widely used for genetic diagnosis of hearing loss. This study aims to reveal new diagnoses via reanalyzing historical data of a multigene panel, and exam the reasons for new diagnoses.

Methods

A total of 210 samples were enlisted, including clinical reports and sequencing data of patients with congenital/prelingual hearing loss who were referred to clinical genetic testing from October 2014 to June 2017. All variants listed on the original clinical reports were reinterpreted according to the standards and guidelines recommended by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). Expanded analysis of raw data were performed in undiagnosed cases.

Results

Re-analysis resulted in nine new diagnoses, improving the overall diagnostic rate from 39 to 43%. New diagnoses were attributed to newly published clinical evidence in the literature, adoption of new interpretation guidelines and expanded analysis range.

Conclusion

This work demonstrates benefits of reanalysis of targeted gene panel data, indicating that periodical reanalysis should be performed in clinical practice.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0531-6) contains supplementary material, which is available to authorized users.

Climatology and dynamics of the link between dry intrusions and cold fronts during winter. Part I: global climatology

Cold fronts are a primary feature of the day-to-day variability of weather in the midlatitudes, and feature in conceptual extratropical cyclone models alongside the dry intrusion airstream. Here the climatological frequency and spatial distribution of the co-occurrence of these two features are quantified, and the differences in cold front characteristics (intensity, size, and precipitation) when a dry intrusion is present or not are calculated. Fronts are objectively identified in the ECMWF ERA-Interim dataset for the winter seasons in each hemisphere and split into three sub-types: central fronts (within a cyclone area); trailing fronts (outwith the cyclone area but connected to a central front); and isolated fronts (not connected to a cyclone). These are then associated with dry intrusions identified using Lagrangian trajectory analysis. Trailing fronts are most likely to be associated with a DI in both hemispheres, and this occurs more frequently in the western parts of the major storm track regions. Isolated fronts are linked to DIs more frequently on the eastern ends of the storm tracks, and in the subtropics. All front types, when co-occurring with a DI, are stronger in terms of their temperature gradient, are much larger in area, and typically have higher average precipitation. Therefore, climatologically the link with DIs increases the impact of cold fronts. There are some differences in the statistics of the precipitation for trailing and isolated fronts that are further investigated in Part II of this study from the front-centred perspective.

Estimating policy-relevant health effects of ambient heat exposures using spatially contiguous reanalysis data

BACKGROUND

Regional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes.

METHODS

We assessed the effect of multi-day lag exposure for maximum near-surface air temperature (T_max) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression.

RESULTS

We observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in T_max on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria.

CONCLUSION

Reanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

Evaluation of physical parameterizations for atmospheric river induced precipitation and application to long-term reconstruction based on three reanalysis datasets in Western Oregon

Dynamically downscaled precipitation is often used for evaluating sub-daily precipitation behavior on a watershed-scale and for the input to hydrological modeling because of its increasing accuracy and spatiotemporal resolution. Despite these advantages, physical parameterizations in regional models and systematic biases due to the dataset used for boundary conditions greatly influence the quality of downscaled precipitation data. The present paper aims to evaluate the performance and the sensitivities of physical parameterizations of the Weather Research and Forecasting (WRF) model to simulate extreme precipitation associated with atmospheric rivers (ARs) over the Willamette watershed in Oregon. Also investigated was whether the optimized WRF configuration for extreme events can be used for long-term reconstruction using different boundary condition datasets. Three reanalysis datasets, the Twentieth Century Reanalysis version 2c (20CRv2c), the European Center for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA20C), and the Climate Forecast System Reanalysis (CFSR), which have different spatial resolutions and dataset periods, were used to simulate precipitation at 4 km resolution. Sensitivity analyses showed that AR precipitation is most sensitive to the microphysics parameterization. Among 13 microphysics schemes investigated, the Goddard and the Stony-Brook University schemes performed the best regardless of the choice of reanalysis. Reconstructed historical precipitation with the optimized configuration showed better accuracies during the wet season than the dry season. With respect to simulations with CFSR, it was found that the optimized configuration for AR precipitation can be used for long-term reconstruction with small biases. However, systematic biases in the reanalysis datasets may still lead to uncertainties in downscaling precipitation in a different season with a single configuration.

Using reanalysis in crop monitoring and forecasting systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980-2010 under potential and water-limited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.

Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment

The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation from Remotely Sensed Information using Artificial Neural Networks), TRMM (Tropical Rainfall Measuring Mission), and AgMERRA (The Modern-Era Retrospective Analysis for Research and Applications) precipitation products to apply as input data for CSM-CERES-Wheat crop growth simulation model to predict rainfed wheat yield. Daily precipitation output from various sources for 7 years (2000-2007) was obtained and compared with corresponding ground-observed precipitation data for 16 ground stations across the northeast of Iran. Comparisons of ground-observed daily precipitation with corresponding data recorded by different sources of datasets showed a root mean square error (RMSE) of less than 3.5 for all data. AgMERRA and APHRODITE showed the highest correlation (0.68 and 0.87) and index of agreement (d) values (0.79 and 0.89) with ground-observed data. When daily precipitation data were aggregated over periods of 10 days, the RMSE values, r, and d values increased (30, 0.8, and 0.7) for AgMERRA, APHRODITE, PERSIANN, and TRMM precipitation data sources. The simulations of rainfed wheat leaf area index (LAI) and dry matter using various precipitation data, coupled with solar radiation and temperature data from observed ones, illustrated typical LAI and dry matter shape across all stations. The average values of LAI_max were 0.78, 0.77, 0.74, 0.70, and 0.69 using PERSIANN, AgMERRA, ground-observed precipitation data, APHRODITE, and TRMM. Rainfed wheat grain yield simulated by using AgMERRA and APHRODITE daily precipitation data was highly correlated (r² ≥ 70) with those simulated using observed precipitation data. Therefore, gridded data have high potential to be used to supply lack of data and gaps in ground-observed precipitation data.

Grand Theft Auto is a "Sandbox" Game, but There are Weapons, Criminals, and Prostitutes in the Sandbox: Response to Ferguson and Donnellan (2017)

In this issue, (Ferguson, C. J., & Donnellan, B. D., Journal of Youth and and Adolescence, published online 21 June 2017) criticize one of our studies (Gabbiadini, A., Riva, P., Andrighetto, L., Volpato, C., & Bushman, B. J., PLoS ONE, 11: 1-14, 2016) that found violent sexist video games can reduce empathy for female violence victims in male players who identify with violent male game characters, and do so by increasing masculine beliefs. Their main criticism is a "straw person" argument built on a claim that we never made (i.e., a direct effect of sexist-violent video games on empathy). They also made several other criticisms of our article. We appreciate the opportunity to respond to their criticisms in this article. We also point out some flaws in their reanalysis. Despite their criticisms, the core contributions of our original article remain intact.

Statistical heartburn: an attempt to digest four pizza publications from the Cornell Food and Brand Lab

Background

We present the results of a reanalysis of four articles from the Cornell Food and Brand Lab based on data collected from diners at an Italian restaurant buffet.

Method

We calculated whether the means, standard deviations, and test statistics were compatible with the sample size. Test statistics and p values were recalculated. We also applied deductive logic to see whether the claims made in each article were compatible with the claims made in the others. We have so far been unable to obtain the data from the authors of the four articles.

Results

A thorough reading of the articles and careful reanalysis of the results revealed a wide range of problems. The sample sizes for the number of diners in each condition are incongruous both within and between the four articles. In some cases, the degrees of freedom of between-participant test statistics are larger than the sample size, which is impossible. Many of the computed F and t statistics are inconsistent with the reported means and standard deviations. In some cases, the number of possible inconsistencies for a single statistic was such that we were unable to determine which of the components of that statistic were incorrect. Our Appendix reports approximately 150 inconsistencies in these four articles, which we were able to identify from the reported statistics alone.

Conclusions

We hope that our analysis will encourage readers, using and extending the simple methods that we describe, to undertake their own efforts to verify published results, and that such initiatives will improve the accuracy and reproducibility of the scientific literature. We also anticipate that the editors of the journals that published these four articles may wish to consider whether any corrective action is required.

Data on cardiovascular and pulmonary diseases among smokers of menthol and non-menthol cigarettes compiled from the National Health and Nutrition Examination Survey (NHANES), 1999-2012

This Data in Brief contains results from three different survey logistic regression models comparing risks of self-reported diagnoses of cardiovascular and pulmonary diseases among smokers of menthol and non-menthol cigarettes. Analyses employ data from National Health and Nutrition Examination Survey (NHANES) cycles administered between 1999 and 2012, combined and in subsets. Raw data may be downloaded from the National Center for Health Statistics. Results were not much affected by which covariates were included in the models, but depended strongly on the NHANES cycles included in the analysis. All three models returned elevated risk estimates for three endpoints when they were run in individual NHANES cycles (congestive heart failure in 2001-02; hypertension in 2003-04; and chronic obstructive pulmonary disease in 2005-06), and all three models returned null results for these endpoints when data from 1999-2012 were combined.

Reanalyzing Head et al. (2015): investigating the robustness of widespread p-hacking

Head et al. (2015) provided a large collection of p-values that, from their perspective, indicates widespread statistical significance seeking (i.e., p-hacking). This paper inspects this result for robustness. Theoretically, the p-value distribution should be a smooth, decreasing function, but the distribution of reported p-values shows systematically more reported p-values for .01, .02, .03, .04, and .05 than p-values reported to three decimal places, due to apparent tendencies to round p-values to two decimal places. Head et al. (2015) correctly argue that an aggregate p-value distribution could show a bump below .05 when left-skew p-hacking occurs frequently. Moreover, the elimination of p = .045 and p = .05, as done in the original paper, is debatable. Given that eliminating p = .045 is a result of the need for symmetric bins and systematically more p-values are reported to two decimal places than to three decimal places, I did not exclude p = .045 and p = .05. I conducted Fisher's method .04 < p < .05 and reanalyzed the data by adjusting the bin selection to .03875 < p ≤ .04 versus .04875 < p ≤ .05. Results of the reanalysis indicate that no evidence for left-skew p-hacking remains when we look at the entire range between .04 < p < .05 or when we inspect the second-decimal. Taking into account reporting tendencies when selecting the bins to compare is especially important because this dataset does not allow for the recalculation of the p-values. Moreover, inspecting the bins that include two-decimal reported p-values potentially increases sensitivity if strategic rounding down of p-values as a form of p-hacking is widespread. Given the far-reaching implications of supposed widespread p-hacking throughout the sciences Head et al. (2015), it is important that these findings are robust to data analysis choices if the conclusion is to be considered unequivocal. Although no evidence of widespread left-skew p-hacking is found in this reanalysis, this does not mean that there is no p-hacking at all. These results nuance the conclusion by Head et al. (2015), indicating that the results are not robust and that the evidence for widespread left-skew p-hacking is ambiguous at best.

Stroke risk among menthol versus non-menthol cigarette smokers in the United States: Analysis of the National Health and Nutrition Examination Survey (NHANES)

Though available evidence is relatively consistent in showing no additional health effects among smokers due to menthol in cigarettes, two studies reported conflicting results for stroke risk using different subsets of NHANES data. We investigated reasons for the differences in these reports by analyzing NHANES cycles conducted between 1999 and 2012, combined and in subsets. Adjusted odds ratios (AOR) and 95% confidence intervals (CI) from three different survey logistic regression models compare risk of reported stroke diagnoses among menthol and non-menthol cigarette smokers. Depending on timeframe, about 1150 to 8000 U.S. adults (aged ≥ 20 years) who smoked on ≥ 1 of the last 30 days had complete data for cigarette type and all covariates included in each model. Results were not much affected by which covariates were included in the models, but depended strongly on the NHANES cycles included in the analysis. Using NHANES 1999-2012 data combined, AORs and 95% CIs for stroke comparing menthol with non-menthol cigarette smokers were 0.95 (95% CI: 0.65, 1.37), 0.85 (95% CI: 0.59, 1.23) or 0.86 (95% CI: 0.59, 1.25). Collectively, findings illustrate the need for fully reporting research and analytical methods, especially when analyses are meant to develop evidence intended for regulatory decision-making.

Evaluation of eight high spatial resolution gridded precipitation products in Adige Basin (Italy) at multiple temporal and spatial scales

This study provides a comprehensive evaluation of eight high spatial resolution gridded precipitation products in Adige Basin located in Italy within 45-47.1°N. The Adige Basin is characterized by a complex topography, and independent ground data are available from a network of 101 rain gauges during 2000-2010. The eight products include the Version 7 TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis 3B42 product, three products from CMORPH (the Climate Prediction Center MORPHing technique), i.e., CMORPH_RAW, CMORPH_CRT and CMORPH_BLD, PCDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record), PGF (Global Meteorological Forcing Dataset for land surface modelling developed by Princeton University), CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and GSMaP_MVK (Global Satellite Mapping of Precipitation project Moving Vector with Kalman-filter product). All eight products are evaluated against interpolated rain gauge data at the common 0.25° spatial resolution, and additional evaluations at native finer spatial resolution are conducted for CHIRPS (0.05°) and GSMaP_MVK (0.10°). Evaluation is performed at multiple temporal (daily, monthly and annual) and spatial scales (grid and watershed). Evaluation results show that in terms of overall statistical metrics the CHIRPS, TRMM and CMORPH_BLD comparably rank as the top three best performing products, while the PGF performs worst. All eight products underestimate and overestimate the occurrence frequency of daily precipitation for some intensity ranges. All products tend to show higher error in the winter months (December-February) when precipitation is low. Very slight difference can be observed in the evaluation metrics and aspects between at the aggregated 0.25° spatial resolution and at the native finer resolutions (0.05°) for CHIRPS and (0.10°) for GSMaP_MVK products. This study has implications for precipitation product development and the global view of the performance of various precipitation products, and provides valuable guidance when choosing alternative precipitation data for local community.

The Lair: a resource for exploratory analysis of published RNA-Seq data

Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is difficult to use in practice. We introduce a series of tools for processing and analyzing RNA-Seq data in the Sequence Read Archive, that together have allowed us to build an easily extendable resource for analysis of data underlying published papers. Our system makes the exploration of data easily accessible and usable without technical expertise. Our database and associated tools can be accessed at The Lair: http://pachterlab.github.io/lair .

Estimating daily air temperature across the Southeastern United States using high-resolution satellite data: A statistical modeling study

Accurate estimates of spatio-temporal resolved near-surface air temperature (Ta) are crucial for environmental epidemiological studies. However, values of Ta are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature (Ts) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite Ts to estimate high resolution (1km×1km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts-Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R(2) of 0.952 indicated excellent model performance. When satellite Ts were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate Ta. The daily Ta estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R(2) of 0.969 and a mean squared prediction error (RMSPE) of 1.376°C was achieved. Our results demonstrate that Ta can be reliably predicted using this Ts-based prediction model, even in a large geographical area with topography and weather patterns varying considerably.

The need to revisit published data: A concept and framework for complementary proteomics

Tandem proteomic strategies based on large-scale and high-resolution mass spectrometry have been widely applied in various biomedical studies. However, protein sequence databases and proteomic software are continuously updated. Proteomic studies should not be ended with a stable list of proteins. It is necessary and beneficial to regularly revise the results. Besides, the original proteomic studies usually focused on a limited aspect of protein information and valuable information may remain undiscovered in the raw spectra. Several studies have reported novel findings by reanalyzing previously published raw data. However, there are still no standard guidelines for comprehensive reanalysis. In the present study, we proposed the concept and draft framework for complementary proteomics, which are aimed to revise protein list or mine new discoveries by revisiting published data.

Thematic role assignment in the posterior parietal cortex: A TMS study

Verbs denote relations between entities acting a role in an event. Thematic roles are essential to the correct use of verbs and involve both semantic and syntactic aspects. We used repetitive Transcranial Magnetic Stimulation (rTMS) to study the involvement of three different left parietal sites in the understanding of thematic roles. In a sentence-to-picture matching task, twelve participants were asked to judge whether or not a given picture matched with a written sentence. Pictures represented simple reversible actions, and sentences were in the active or passive diathesis. Whereas both active and passive sentences require the correct encoding of thematic roles, passives also imply thematic reanalysis, as the canonical order of thematic roles is systematically reversed. The experiment was divided in three sessions. In each session a different parietal site (anterior, middle, posterior) was stimulated at 5 Hz in an event-related fashion, time-locked to the presentation of visual stimuli. Results showed increased accuracy for passive sentences following posterior parietal stimulation. The effect appeared to be (a) TMS-related, as no effect was observed in a control, no-TMS experiment with eighteen new participants; (b) independent from semantic processes involved in word-picture association, as no TMS-related effects were observed in a picture-word matching task. We interpret the results as showing that the posterior parietal site is specifically involved in the assignment of thematic roles, in particular when the correct interpretation of a sentence requires reanalysis of temporarily encoded thematic roles, as in passive reversible sentences.

Identification of Molecular Signatures from Different Vaccine Adjuvants in Chicken by Integrative Analysis of Microarray Data

The present study compared the differential functions of two groups of adjuvants, Montanide incomplete Seppic adjuvant (ISA) series and Quil A, cholesterol, dimethyl dioctadecyl ammonium bromide, and Carbopol (QCDC) formulations, in chicken by analyzing published microarray data associated with each type of vaccine adjuvants. In the biological function analysis for differentially expressed genes altered by two different adjuvant groups, ISA series and QCDC formulations showed differential effects when chickens were immunized with a recombinant immunogenic protein of Eimeria. Among the biological functions, six categories were modified in both adjuvant types. However, with respect to “Response to stimulus”, no biological process was modified by the two adjuvant groups at the same time. The QCDC adjuvants showed effects on the biological processes (BPs) including the innate immune response and the immune response to the external stimulus such as toxin and bacterium, while the ISA adjuvants modified the BPs to regulate cell movement and the response to stress. In pathway analysis, ISA adjuvants altered the genes involved in the functions related with cell junctions and the elimination of exogenous and endogenous macromolecules. The analysis in the present study could contribute to the development of precise adjuvants based on molecular signatures related with their immunological functions.

Comparing the skill of different reanalyses and their ensembles as predictors for daily air temperature on a glaciated mountain (Peru)

It is well known from previous research that significant differences exist amongst reanalysis products from different institutions. Here, we compare the skill of NCEP-R (reanalyses by the National Centers for Environmental Prediction, NCEP), ERA-int (the European Centre of Medium-range Weather Forecasts Interim), JCDAS (the Japanese Meteorological Agency Climate Data Assimilation System reanalyses), MERRA (the Modern Era Retrospective-Analysis for Research and Applications by the National Aeronautics and Space Administration), CFSR (the Climate Forecast System Reanalysis by the NCEP), and ensembles thereof as predictors for daily air temperature on a high-altitude glaciated mountain site in Peru. We employ a skill estimation method especially suited for short-term, high-resolution time series. First, the predictors are preprocessed using simple linear regression models calibrated individually for each calendar month. Then, cross-validation under consideration of persistence in the time series is performed. This way, the skill of the reanalyses with focus on intra-seasonal and inter-annual variability is quantified. The most important findings are: (1) ERA-int, CFSR, and MERRA show considerably higher skill than NCEP-R and JCDAS; (2) differences in skill appear especially during dry and intermediate seasons in the Cordillera Blanca; (3) the optimum horizontal scales largely vary between the different reanalyses, and horizontal grid resolutions of the reanalyses are poor indicators of this optimum scale; and (4) using reanalysis ensembles efficiently improves the performance of individual reanalyses.