Testing perceivers’ accuracy and accuracy awareness when forming personality impressions from faces

People spontaneously judge others’ personality based on their facial appearance and these impressions guide many important decisions. Although the consequences of personality impressions are well documented, studies on the accuracy of personality impressions have yielded mixed results. Moreover, relatively little is known about people’s accuracy awareness (i.e., whether they are aware of their judgment accuracy). Even if accuracy is generally low, awareness of accuracy would allow people to rely on their impressions in the right situations. In two studies (one preregistered), we estimated perceivers’ accuracy and accuracy awareness when forming personality impressions based on facial photographs. Our studies have three crucial advantages as compared to previous studies (a) by incentivizing accuracy and accuracy awareness, (b) by relying on substantially larger samples of raters (nStudy 1 = 223, nStudy 2 = 423) and targets (kStudy 1 = 140, kStudy 2 = 1,260 unique pairs with 280 unique targets), and (c) by conducting Bayesian analyses to also quantify evidence for the null hypothesis. Our findings suggest that face-based personality impressions are not accurate, that perceivers lack insight into their (in)accuracy, and that most people overestimate their accuracy

Using Effective Subnetworks to Predict Selected Properties of Gene Networks

BACKGROUND: Difficulties associated with implementing gene therapy are caused by the complexity of the underlying regulatory networks. The forms of interactions between the hundreds of genes, proteins, and metabolites in these networks are not known very accurately. An alternative approach is to limit consideration to genes on the network. Steady state measurements of these influence networks can be obtained from DNA microarray experiments. However, since they contain a large number of nodes, the computation of influence networks requires a prohibitively large set of microarray experiments. Furthermore, error estimates of the network make verifiable predictions impossible. METHODOLOGY/PRINCIPAL FINDINGS: Here, we propose an alternative approach. Rather than attempting to derive an accurate model of the network, we ask what questions can be addressed using lower dimensional, highly simplified models. More importantly, is it possible to use such robust features in applications? We first identify a small group of genes that can be used to affect changes in other nodes of the network. The reduced effective empirical subnetwork (EES) can be computed using steady state measurements on a small number of genetically perturbed systems. We show that the EES can be used to make predictions on expression profiles of other mutants, and to compute how to implement pre-specified changes in the steady state of the underlying biological process. These assertions are verified in a synthetic influence network. We also use previously published experimental data to compute the EES associated with an oxygen deprivation network of E.coli, and use it to predict gene expression levels on a double mutant. The predictions are significantly different from the experimental results for less than of genes. CONCLUSIONS/SIGNIFICANCE: The constraints imposed by gene expression levels of mutants can be used to address a selected set of questions about a gene network

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation

Metabolic Engineering of Pseudomonas putida KT2440 for enhanced rhamnolipid production

The production of chemicals and fuels is mainly based on fossil resources. The reduced availability of these resources and thus the increasing prices for crude oil as well as the resulting pollution of the environment require alternative strategies to be developed. One approach is the employment of microorganisms for the production of platform molecules using renewable resources as substrate. Biosurfactants, such as rhamnolipids, are an example for such products as they can be naturally produced by microorganisms and are biodegradable in contrast to chemical surfactants. The bio-based production of chemicals has to be efficient and sustainable to become competitive on the market. Several strategies can be applied to increase the efficiency of a microbial cell factory, e.g., streamlining the chassis. Here, we show the heterologous production of rhamnolipids with the non-pathogenic Pseudomonas putida KT2440 with the aim of increasing the yield. P. putida KT2440 is a well-characterized microorganism and its genome is sequenced and well annotated. Thus, the targeted removal of genes is possible and can lead to a reduction of the metabolic burden and by-product formation, which can result in a higher yield. Furthermore, the efficient supply of precursors is an important factor for optimized production processes. Rhamnolipids are amphiphilic molecules containing rhamnose and ß-hydroxy fatty acids. These precursors are synthesized by two pathways, the fatty acid de novo synthesis and the rhamnose pathway. We performed gene deletions to avoid the synthesis of by-products, like pyoverdine, exopolysaccharides, and large surface proteins and energy consuming devices as the flagellum. Most of the genome-reduced mutants reached a higher yield compared to the strain with wildtype background. With the best chassis, the yield could be increased by 35%. Furthermore, we conducted the overexpression of genes for precursor supply, either plasmid-based or genomically integrated. In this regard, the genes for the phosphoglucomutase, the complete rhamnose-synthesis pathway operon, and different enzymes in the pathway for acetyl-CoA synthesis were targeted. Various combinations were tested, and the highest yield reached was 51% higher compared to the initial rhamnolipid producer. Finally, a genome-reduced mutant was equipped with the overexpression modules and the rhamnolipid titer was increased from approximately 590 mg/L for the wildtype background to 960 mg/L, which represents a 63% increase. In conclusion, we were able to enhance the yield of rhamnolipids per glucose using metabolic engineering

Two years follow-up study of the pain-relieving effect of gold bead implantation in dogs with hip-joint arthritis

Seventy-eight dogs with pain from hip dysplasia participated in a six-month placebo-controlled, double-blinded clinical trial of gold bead implantation. In the present, non-blinded study, 73 of these dogs were followed for an additional 18 months to evaluate the long-term pain-relieving effect of gold bead implantation. The recently-published results of the six month period revealed that 30 of the 36 dogs (83%) in the gold implantation group showed significant improvement (p = 0.02), included improved mobility and reduction in the signs of pain, compared to the placebo group (60% improvement). In the long-term two-year follow-up study, 66 of the 73 dogs had gold implantation and seven dogs continued as a control group. The 32 dogs in the original placebo group had gold beads implanted and were followed for a further 18 months. A certified veterinary acupuncturist used the same procedure to insert the gold beads as in the blinded study, and the owners completed the same type of detailed questionnaires. As in the blinded study, one investigator was responsible for all the assessments of each dog. The present study revealed that the pain-relieving effect of gold bead implantation observed in the blinded study continued throughout the two-year follow-up period

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach

Risk for pelvic metastasis and role of pelvic lymphadenectomy in node-positive vulvar cancer - results from the AGO-VOP.2 QS vulva study

Simple Summary In node-positive vulvar squamous cell cancer, questions of when and how to perform pelvic lymphadenectomy (LAE) as well as the optimal extent of pelvic treatment in general have been surrounded by considerable controversy. In Germany, systematic pelvic LAE is currently recommended as a staging procedure in patients at risk for pelvic nodal involvement in order to prevent morbidity caused by pelvic radiotherapy (RT) in patients without histologically-confirmed pelvic involvement. However, the population at risk for pelvic metastases remains insufficiently described, resulting in the potential overtreatment of a considerable proportion of patients with groin-positive disease. This applies to the indication to perform surgical staging but also to adjuvant RT of the pelvis without previous pelvic staging. Our study aims to describe the risk for pelvic lymph node metastasis with regard to positive groin nodes and to clarify the indication criteria for pelvic treatment in node-positive vulvar cancer. Abstract The need for pelvic treatment in patients with node-positive vulvar cancer (VSCC) and the value of pelvic lymphadenectomy (LAE) as a staging procedure to plan adjuvant radiotherapy (RT) is controversial. In this retrospective, multicenter analysis, 306 patients with primary node-positive VSCC treated at 33 gynecologic oncology centers in Germany between 2017 and 2019 were analyzed. All patients received surgical staging of the groins; nodal status was as follows: 23.9% (73/306) pN1a, 23.5% (72/306) pN1b, 20.4% (62/306) pN2a/b, and 31.9% (97/306) pN2c/pN3. A total of 35.6% (109/306) received pelvic LAE; pelvic nodal involvement was observed in 18.5%. None of the patients with nodal status pN1a or pN1b and pelvic LAE showed pelvic nodal involvement. Taking only patients with nodal status ≥pN2a into account, the rate of pelvic involvement was 25%. In total, adjuvant RT was applied in 64.4% (197/306). Only half of the pelvic node-positive (N+) patients received adjuvant RT to the pelvis (50%, 10/20 patients); 41.9% (122/291 patients) experienced recurrent disease or died. In patients with histologically-confirmed pelvic metastases after LAE, distant recurrences were most frequently observed (7/20 recurrences). Conclusions: A relevant risk regarding pelvic nodal involvement was observed from nodal status pN2a and higher. Our data support the omission of pelvic treatment in patients with nodal status pN1a and pN1b

Ki-67 expression is superior to mitotic count and novel proliferation markers PHH3, MCM4 and mitosin as a prognostic factor in thick cutaneous melanoma

<p>Abstract</p> <p>Background</p> <p>Tumor cell proliferation is a predictor of survival in cutaneous melanoma. The aim of the present study was to evaluate the prognostic impact of mitotic count, Ki-67 expression and novel proliferation markers phosphohistone H3 (PHH3), minichromosome maintenance protein 4 (MCM4) and mitosin, and to compare the results with histopathological variables.</p> <p>Methods</p> <p>202 consecutive cases of nodular cutaneous melanoma were initially included. Mitotic count (mitosis per mm²) was assessed on H&E sections, and Ki-67 expression was estimated by immunohistochemistry on standard sections. PHH3, MCM4 and mitosin were examined by staining of tissue microarrays (TMA) sections.</p> <p>Results</p> <p>Increased mitotic count and elevated Ki-67 expression were strongly associated with increased tumor thickness, presence of ulceration and tumor necrosis. Furthermore, high mitotic count and elevated Ki-67 expression were also associated with Clark's level of invasion and presence of vascular invasion. High expression of PHH3 and MCM4 was correlated with high mitotic count, elevated Ki-67 expression and tumor ulceration, and increased PHH3 frequencies were associated with tumor thickness and presence of tumor necrosis. Univariate analyses showed a worse outcome in cases with elevated Ki-67 expression and high mitotic count, whereas PHH3, MCM4 and mitosin were not significant. Tumor cell proliferation by Ki-67 had significant prognostic impact by multivariate analysis.</p> <p>Conclusions</p> <p>Ki-67 was a stronger and more robust prognostic indicator than mitotic count in this series of nodular melanoma. PHH3, MCM4 and mitosin did not predict patient survival.</p

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

The Transcriptome of the Nosocomial Pathogen Enterococcus faecalis V583 Reveals Adaptive Responses to Growth in Blood

gains access to the bloodstream and establishes a persistent infection is not well understood.. infections