Hidden multiple comparisons increase forensic error rates.

When wires are cut, the tool produces striations on the cut surface; as in other forms of forensic analysis, these striation marks are used to connect the evidence to the source that created them. Here, we argue that the practice of comparing two wire cut surfaces introduces complexities not present in better-investigated forensic examination of toolmarks such as those observed on bullets, as wire comparisons inherently require multiple distinct comparisons, increasing the expected false discovery rate. We call attention to the multiple comparison problem in wire examination and relate it to other situations in forensics that involve multiple comparisons, such as database searches.

Empirical Bayes small area prediction under a zero-inflated lognormal model with correlated random area effects.

Many variables of interest in agricultural or economical surveys have skewed distributions and can equal zero. Our data are measures of sheet and rill erosion called Revised Universal Soil Loss Equation - 2 (RUSLE2). Small area estimates of mean RUSLE2 erosion are of interest. We use a zero-inflated lognormal mixed effects model for small area estimation. The model combines a unit-level lognormal model for the positive RUSLE2 responses with a unit-level logistic mixed effects model for the binary indicator that the response is nonzero. In the Conservation Effects Assessment Project (CEAP) data, counties with a higher probability of nonzero responses also tend to have a higher mean among the positive RUSLE2 values. We capture this property of the data through an assumption that the pair of random effects for a county are correlated. We develop empirical Bayes (EB) small area predictors and a bootstrap estimator of the mean squared error (MSE). In simulations, the proposed predictor is superior to simpler alternatives. We then apply the method to construct EB predictors of mean RUSLE2 erosion for South Dakota counties. To obtain auxiliary variables for the population of cropland in South Dakota, we integrate a satellite-derived land cover map with a geographic database of soil properties. We provide an R Shiny application called viscover (available at https://lyux.shinyapps.io/viscover/) to visualize the overlay operations required to construct the covariates. On the basis of bootstrap estimates of the mean square error, we conclude that the EB predictors of mean RUSLE2 erosion are superior to direct estimators.

Severe fever with thrombocytopenia virus glycoproteins are targeted by neutralizing antibodies and can use DC-SIGN as a receptor for pH-dependent entry into human and animal cell lines.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a novel bunyavirus that recently emerged in China. Infection with SFTSV is associated with case-fatality rates of up to 30%, and neither antivirals nor vaccines are available at present. Development of antiviral strategies requires the elucidation of virus-host cell interactions. Here, we analyzed host cell entry of SFTSV. Employing lentiviral and rhabdoviral vectors, we found that the Gn/Gc glycoproteins (Gn/Gc) of SFTSV mediate entry into a broad range of human and animal cell lines, as well as human macrophages and dendritic cells. The Gn/Gc proteins of La Crosse virus (LACV) and Rift Valley Fever Virus (RVFV), other members of the bunyavirus family, facilitated entry into an overlapping but not identical range of cell lines, suggesting that SFTSV, LACV, and RVFV might differ in their receptor requirements. Entry driven by SFTSV Gn/Gc was dependent on low pH but did not require the activity of the pH-dependent endosomal/lysosomal cysteine proteases cathepsins B and L. Instead, the activity of a cellular serine protease was required for infection driven by SFTSV and LACV Gn/Gc. Sera from convalescent SFTS patients inhibited SFTSV Gn/Gc-driven host cell entry in a dose-dependent fashion, demonstrating that the vector system employed is suitable to detect neutralizing antibodies. Finally, the C-type lectin DC-SIGN was found to serve as a receptor for SFTSV Gn/Gc-driven entry into cell lines and dendritic cells. Our results provide initial insights into cell tropism, receptor usage, and proteolytic activation of SFTSV and will aid in the understanding of viral spread and pathogenesis.

The spike protein of the emerging betacoronavirus EMC uses a novel coronavirus receptor for entry, can be activated by TMPRSS2, and is targeted by neutralizing antibodies.

The novel human coronavirus EMC (hCoV-EMC), which recently emerged in Saudi Arabia, is highly pathogenic and could pose a significant threat to public health. The elucidation of hCoV-EMC interactions with host cells is critical to our understanding of the pathogenesis of this virus and to the identification of targets for antiviral intervention. Here we investigated the viral and cellular determinants governing hCoV-EMC entry into host cells. We found that the spike protein of hCoV-EMC (EMC-S) is incorporated into lentiviral particles and mediates transduction of human cell lines derived from different organs, including the lungs, kidneys, and colon, as well as primary human macrophages. Expression of the known coronavirus receptors ACE2, CD13, and CEACAM1 did not facilitate EMC-S-driven transduction, suggesting that hCoV-EMC uses a novel receptor for entry. Directed protease expression and inhibition analyses revealed that TMPRSS2 and endosomal cathepsins activate EMC-S for virus-cell fusion and constitute potential targets for antiviral intervention. Finally, EMC-S-driven transduction was abrogated by serum from an hCoV-EMC-infected patient, indicating that EMC-S-specific neutralizing antibodies can be generated in patients. Collectively, our results indicate that hCoV-EMC uses a novel receptor for protease-activated entry into human cells and might be capable of extrapulmonary spread. In addition, they define TMPRSS2 and cathepsins B and L as potential targets for intervention and suggest that neutralizing antibodies contribute to the control of hCoV-EMC infection.

An algorithm for forensic toolmark comparisons.

Forensic toolmark analysis traditionally relies on subjective human judgment, leading to inconsistencies and lack of transparency. The multitude of variables, including angles and directions of mark generation, further complicates comparisons. To address this, we first generate a dataset of 3D toolmarks from various angles and directions using consecutively manufactured slotted screwdrivers. By using PAM clustering, we find that there is clustering by tool rather than angle or direction. Using Known Match and Known Non-Match densities, we establish thresholds for classification. Fitting Beta distributions to the densities, we allow for the derivation of likelihood ratios for new toolmark pairs. With a cross-validated sensitivity of 98 % and specificity of 96 %, our approach enhances the reliability of toolmark analysis. This approach is applicable to slotted screwdrivers, and for screwdrivers that are made with a similar production method. With data collection of other tools and factors, it could be applied to compare toolmarks of other types. This empirically trained, open-source solution offers forensic examiners a standardized means to objectively compare toolmarks, potentially decreasing the number of miscarriages of justice in the legal system.

Impact of ETIF deletion on safety and immunogenicity of equine herpesvirus type 1-vectored vaccines.

Heterologous gene transfer by viral vector systems is often limited by factors such as preexisting immunity, toxicity, low packaging capacity, or weak immunogenic potential. A novel viral vector system derived from equine herpesvirus type 1 (EHV-1) not only overcomes some of these obstacles but also promotes the robust expression of a delivered transgene and the induction of antigen-specific immune responses. Regarding an enhanced safety profile, we assessed the impact of the gene encoding the sole essential tegument protein, ETIF, on the replication and immunogenicity of recombinant EHVs. The deletion of ETIF severely attenuates replication in permissive RK13 cells and a human lung epithelial cell line but without influencing transgene expression. Whereas the intranasal administration of a recombinant luciferase EHV in BALB/c mice resulted in transgene expression in nasal cavities and lungs for 5 to 6 days, the ETIF deletion limited expression to 2 days and resulted in 30-fold-less luminescence. Attenuated replication was accompanied by a decreased capacity to induce CD8(+) T cells against a delivered HIV Gag transgene in BALB/c mice following repeated intranasal application. However, a single subcutaneous immunization with a gag DNA vaccine primed specific T cells for substantial expansion by two subsequent intranasal booster immunizations with either the gag recombinant ETIF mutant or the parental virus. In addition to inducing Gag-specific serum antibodies, this prime-boost strategy clearly outperformed three sequential immunizations with the parental or EHV-ΔETIF virus or repeated DNA vaccination by inducing substantial specific secretory IgA (sIgA) titers.

Differential downregulation of ACE2 by the spike proteins of severe acute respiratory syndrome coronavirus and human coronavirus NL63.

The human coronaviruses (CoVs) severe acute respiratory syndrome (SARS)-CoV and NL63 employ angiotensin-converting enzyme 2 (ACE2) for cell entry. It was shown that recombinant SARS-CoV spike protein (SARS-S) downregulates ACE2 expression and thereby promotes lung injury. Whether NL63-S exerts a similar activity is yet unknown. We found that recombinant SARS-S bound to ACE2 and induced ACE2 shedding with higher efficiency than NL63-S. Shedding most likely accounted for the previously observed ACE2 downregulation but was dispensable for viral replication. Finally, SARS-CoV but not NL63 replicated efficiently in ACE2-positive Vero cells and reduced ACE2 expression, indicating robust receptor interference in the context of SARS-CoV but not NL63 infection.

The soy isoflavones for reducing bone loss study: 3-yr effects on pQCT bone mineral density and strength measures in postmenopausal women.

Soy isoflavones exert inconsistent bone density-preserving effects, but the bone strength-preserving effects in humans are unknown. Our double-blind randomized controlled trial examined 2 soy isoflavone doses (80 or 120mg/d) vs placebo tablets on volumetric bone mineral density (vBMD) and strength (by means of peripheral quantitative computed tomography) in healthy postmenopausal women (46-63yr). We measured 3-yr changes in cortical BMD (CtBMD), cortical thickness (CtThk), periosteal circumference (PC), endosteal circumference (EC), and strength-strain index (SSI) at 1/3 midshaft femur (N=171), and trabecular BMD (TbBMD), PC, and SSI at 4% distal tibia (N=162). We found no treatment effect on femur CtThk, PC, or EC, or tibia TbBMD or PC. The strongest predictors (negative) of tibia TbBMD and SSI and femur CtBMD were timepoint and bone resorption; whole-body fat mass was protective of SSI. As time since last menstrual period (TLMP) increased (p=0.012), 120-mg/d dose was protective of CtBMD. The strongest predictors of femur SSI were timepoint, bone resorption, and TLMP (protective). Isoflavone tablets were negative predictors of SSI, but 80-mg/d dose became protective as bone turnover increased (p=0.011). Soy isoflavone treatment for 3yr was modestly beneficial for midshaft femur vBMD as TLMP increased and for midshaft femur SSI as bone turnover increased.

Clustering microarray data to determine normalization method.

Most of the scientific journals require published microarray experiments to meet Minimum Information About a Microarray Experiment (MIAME) standards. This ensures that other researchers have the necessary information to interpret the results or reproduce them. Required MIAME information includes raw experimental data, processed data, and data processing procedures. However, the normalization method is often reported inaccurately or not at all. It may be that the scaling factor is not even known except to experienced users of the normalization software. We propose that using a seeded clustering algorithm, researchers can identify or verify previously unknown or doubtful normalization information. For that, we generate descriptive statistics (mean, variance, quantiles, and moments) for normalized expression data from gene chip experiments available in the ArrayExpress database and cluster chips based on these statistics. To verify that clustering grouped chips by normalization method, we normalize raw data for chips chosen from experiments in ArrayExpress using multiple methods. We then generate the same descriptive statistics for the normalized data and cluster the chips using these statistics. We use this dataset of known pedigree as seeding data to identify normalization methods used in unknown or doubtful situations.

Interactive Web-based Data Visualization and Analysis Tool for Synthetizing on-farm Research Networks Data.

The on-farm research network concept enables a group of farmers to test new agricultural management practices under local conditions with support from local researchers or agronomists. Different on-farm trials based on the same experimental design are conducted over several years and sites to test the effectiveness of different innovative management practices aimed at increasing crop productivity and profitability. As a larger amount of historical trial data are being accumulated, data of all the trials require analyses and summarization. Summaries of on-farm trials are usually presented to farmers as individual field reports, which are not optimal for the dissemination of results and decision making. A more practical communication method is needed to enhance result communication and decision making. R Shiny is a new rapidly developing technology for turning R data analyses into interactive web applications. For the first time for on-farm research networks, we developed and launched an interactive web tool called ISOFAST using R Shiny. ISOFAST simultaneously reports all trial results about the same management practice to simplify interpretation of multi-site and multi-year summaries. We used a random-effects model to synthetize treatment differences at both the individual trial and network levels and generate new knowledge for farmers and agronomists. The friendly interface enables users to explore trial summaries, access model outputs, and perform economic analysis at their fingertips. This paper describes a case-study to illustrate how to use the tool and make agronomic management decisions based on the on-farm trial data. We also provided technical details and guidance for developing a similar interactive visualization tool customized for on-farm research network. ISOFAST is currently available at https://analytics.iasoybeans.com/cool-apps/ISOFAST/.