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Background: Both lung lobe segmentation and lung fissure segmentation are useful in the clinical diagnosis and evaluation of lung disease. It is often of clinical interest to quantify each lobe separately because many diseases are associated with specific lobes. Fissure segmentation is important for a significant proportion of lung lobe segmentation methods, as well as for assessing fissure completeness, since there is an increasing requirement for the quantification of fissure integrity. Methods: We propose a method for the fully automatic segmentation of pulmonary fissures on lung computed tomography (CT) based on U-Net and PAN models using a Derivative of Stick (DoS) filter for data preprocessing. Model ensembling is also used to improve prediction accuracy. Results: Our method achieved an F1 score of 0.916 for right-lung fissures and 0.933 for left-lung fissures, which are significantly higher than the standalone DoS results (0.724 and 0.666, respectively). We also performed lung lobe segmentation using fissure segmentation. The lobe segmentation algorithm shows results close to those of state-of-the-art methods, with an average Dice score of 0.989. Conclusions: The proposed method segments pulmonary fissures efficiently and have low memory requirements, which makes it suitable for further research in this field involving rapid experimentation.

Lymphovascular invasion (LVI) in lung cancer is a significant prognostic factor that influences treatment and outcomes, yet its reliable detection is challenging due to interobserver variability. This study aims to develop a deep learning model for LVI detection using whole slide images (WSIs) and evaluate its effectiveness within a pathologist's information system. Experienced pathologists annotated blood vessels and invading tumor cells in 162 WSIs of non-mucinous lung adenocarcinoma sourced from two external and one internal datasets. Two models were trained to segment vessels and identify images with LVI features. DeepLabV3+ model achieved an Intersection-over-Union of 0.8840 and an area under the receiver operating characteristic curve (AUC-ROC) of 0.9869 in vessel segmentation. For LVI classification, the ensemble model achieved a F1-score of 0.9683 and an AUC-ROC of 0.9987. The model demonstrated robustness and was unaffected by variations in staining and image quality. The pilot study showed that pathologists' evaluation time for LVI detecting decreased by an average of 16.95%, and by 21.5% in “hard cases”. The model facilitated consistent diagnostic assessments, suggesting potential for broader applications in detecting pathological changes in blood vessels and other lung pathologies.

Abstract 12-lead electrocardiogram (ECG) recordings can be collected in any clinic and the interpretation is performed by a clinician. Modern machine learning tools may make them automatable. However, a large fraction of 12-lead ECG data is still available in printed paper or image only and comes in various formats. To digitize the data, smartphone cameras can be used. Nevertheless, this approach may introduce various artifacts and occlusions into the obtained images. Here we overcome the challenges of automating 12-lead ECG analysis using mobile-captured images and a deep neural network that is trained using a domain adversarial approach. The net achieved an average 0.91 receiver operating characteristic curve on tested images captured by a mobile device. Assessment on image from unseen 12-lead ECG formats that the network was not trained on achieved high accuracy. We further show that the network accuracy can be improved by including a small number of unlabeled samples from unknown formats in the training data. Finally, our models also achieve high accuracy using signals as input rather than images. Using a domain adaptation approach, we successfully classified cardiac conditions on images acquired by a mobile device and showed the generalizability of the classification using various unseen image formats.

ABSTRACTThe tumor microenvironment (TME) in ovarian cancer (OC) is characterized by immune suppression, due to an abundance of suppressive immune cells populations. To effectively enhance the activity of immune checkpoint inhibition (ICI), there is a need to identify agents that target these immunosuppressive networks while promoting the recruitment of effector T cells into the TME. To this end, we sought to investigate the effect of the immunomodulatory cytokine IL12 alone or in combination with dual-ICI (anti-PD1 + anti-CTLA4) on anti-tumor activity and survival, using the immunocompetent ID8-VEGF murine OC model. Detailed immunophenotyping of peripheral blood, ascites, and tumors revealed that durable treatment responses were associated with reversal of myeloid cell-induced immune suppression, which resulted in enhanced anti-tumor activity by T cells. Single cell transcriptomic analysis further demonstrated striking differences in the phenotype of myeloid cells from mice treated with IL12 in combination with dual-ICI. We also identified marked differences in treated mice that were in remission compared to those whose tumors progressed, further confirming a pivotal role for the modulation of myeloid cell function to allow for response to immunotherapy. These findings provide the scientific basis for the combination of IL12 and ICI to improve clinical response in OC.

Presently we report a second example of a biochemical reaction sensitized remotely by excitons (electronic excited states) efficiently transferred along intermediate filaments (IFs) over macroscopic distances. IFs are excellent conductors of energy in the form of excitons, with the efficiency of ca. 0.53 reported in vitro. Excitons were generated by visible light and propagated along Müller cell (MC) intermediate filaments, about 100 μm long. These experiments used a capillary matrix filled by MC IFs extracted from porcine retina. Excitons induced efficient isomerization of 11-cis- to all-trans-retinal, with the reaction quantum yield φcis/trans = 0.347 obtained for 11-cis-retinal concentration of 1.0 × 10−3 M (0.284 g/L) using 546 nm light at 6.87 mW/cm2 power density. Exciton quantum yield φexc at 546 nm was also measured in function of radiation power density, with nonlinearity indicative of biphotonic processes. This is the first case of biphotonic processes occurring at such low light intensities with steady-state illumination. The present results support quantum mechanism of high-contrast vision of vertebrate eyes.

Mathematical models of non-small-cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with “omics” approaches will improve our understanding of the nature of non-small-cell lung cancer. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.

Titanium alloys are widely used in various industries. The most common and well-known titanium alloy is titanium alloy with aluminum and vanadium (Ti-6Al-4V). This alloy is used, for example, in the manufacture of aircraft engines. As part of the development of technologies and the emergence of the evolving requirements for materials, Ti-6Al-4V alloys with ultrafine grains less than 1 μm may become promising. This modification of the alloy has excellent strength characteristics, such as increased fatigue resistance. However, manufacturers are aware of the machinability problem of titanium alloys. To date, a sufficiently high level of understanding of this problem has already been achieved. But, there is practically no information about the machinability of ultrafine-grained alloys and their comparison, in this regard, with the usual coarse-grained version. This study presents the results of experimental studies on the influence of cutting parameters (cutting speed, V, m/min; feed rate, Fz, mm/rev) on the roughness and microstructure of the surface of Ti-6Al-4V samples with coarse-grained and ultrafine-grained structures produced via equal-channel angular pressing. It is shown that turning at a low cutting speed (V = 48 m/min) results in a better surface roughness, Ra, for the coarse-grained sample compared to its ultrafine-grained alloy counterpart. When the cutting speed is increased by 1.5 times (up to V = 72 m/min), on the contrary, the ultrafine-grained sample has a lower surface roughness, Ra, compared to the coarse-grained sample. The differences in the morphology and microstructure of the chips, depending on the microstructure type of the processed alloy, are discussed: the presence of plastic flow lines in the chip microstructure of the turned ultrafine-grained sample and the formation of shear bands, cleavages, and microcracks in the chips of the turned coarse-grained alloy.

Background Merkel cell carcinoma (MCC) often responds to PD-1 pathway blockade, regardless of tumor-viral status (~80% of cases driven by the Merkel cell polyomavirus (MCPyV)). Prior studies have characterized tumor-specific T cell responses to MCPyV, which have typically been CD8, but little is known about the T cell response to UV-induced neoantigens.Methods A patient in her mid-50s with virus-negative (VN) MCC developed large liver metastases after a brief initial response to chemotherapy. She received anti-PD-L1 (avelumab) and had a partial response within 4 weeks. Whole exome sequencing (WES) was performed to determine potential neoantigen peptides. Characterization of peripheral blood neoantigen T cell responses was evaluated via interferon-gamma (IFNγ) ELISpot, flow cytometry and single-cell RNA sequencing. Tumor-resident T cells were characterized by multiplexed immunohistochemistry.Results WES identified 1027 tumor-specific somatic mutations, similar to the published average of 1121 for VN-MCCs. Peptide prediction with a binding cut-off of ≤100 nM resulted in 77 peptides that were synthesized for T cell assays. Although peptides were predicted based on class I HLAs, we identified circulating CD4 T cells targeting 5 of 77 neoantigens. In contrast, no neoantigen-specific CD8 T cell responses were detected. Neoantigen-specific CD4 T cells were undetectable in blood before anti-PD-L1 therapy but became readily detectible shortly after starting therapy. T cells produced robust IFNγ when stimulated by neoantigen (mutant) peptides but not by the normal (wild-type) peptides. Single cell RNAseq showed neoantigen-reactive T cells expressed the Th1-associated transcription factor (T-bet) and associated cytokines. These CD4 T cells did not significantly exhibit cytotoxicity or non-Th1 markers. Within the pretreatment tumor, resident CD4 T cells were also Th1-skewed and expressed T-bet.Conclusions We identified and characterized tumor-specific Th1-skewed CD4 T cells targeting multiple neoantigens in a patient who experienced a profound and durable partial response to anti-PD-L1 therapy. To our knowledge, this is the first report of neoantigen-specific T cell responses in MCC. Although CD4 and CD8 T cells recognizing viral tumor antigens are often detectible in virus-positive MCC, only CD4 T cells recognizing neoantigens were detected in this patient. These findings suggest that CD4 T cells can play an important role in the response to anti-PD-(L)1 therapy.

The analysis of the microvasculature and the assessment of angiogenesis have significant prognostic value in various diseases, including cancer. The search for invasion into the blood and lymphatic vessels and the assessment of angiogenesis are important aspects of oncological diagnosis. These features determine the prognosis and aggressiveness of the tumor. Traditional manual evaluation methods are time consuming and subject to inter-observer variability. Blood vessel detection is a perfect task for artificial intelligence, which is capable of rapid analyzing thousands of tissue structures in whole slide images. The development of computer vision solutions requires the segmentation of tissue regions, the extraction of features and the training of machine learning models. In this review, we focus on the methodologies employed by researchers to identify blood vessels and vascular invasion across a range of tumor localizations, including breast, lung, colon, brain, renal, pancreatic, gastric and oral cavity cancers. Contemporary models herald a new era of computational pathology in morphological diagnostics.

The paper considers the problems of estimation and provision of efficiency of rotary-screw propulsion units (RSP) for snow and swamp-going amphibious vehicles. The performance curves of fully submerged Archimedes screws of RSP are presented with parameters typical for snow and swamp-going amphibious vehicles. These parameters were obtained from the results of computer simulation. For a wide range of performance modes, the impact of particular elements of Archimedes screws on the general efficiency of the propulsion unit is analysed. According to the results of analysis of data received, lines of further research will aim to increase the efficiency of RSP when moving afloat.

Mutations in IDH1 and IDH2 drive the development of gliomas. These genetic alterations promote tumor cell renewal, disrupt differentiation states, and induce stem-like properties. Understanding how this phenotypic reprogramming occurs remains an area of high interest in glioma research. Previously, we showed that IDH mutation results in the development of a CD24-positive cell population in gliomas. Here, we demonstrate that this CD24-positive population possesses striking stem-like properties at the molecular and phenotypic levels. We found that CD24 expression is associated with stem-like features in IDH-mutant tumors, a patient-derived gliomasphere model, and a neural stem cell model of IDH1-mutant glioma. In orthotopic models, CD24-positive cells display enhanced tumor initiating potency compared to CD24-negative cells. Furthermore, CD24 knockdown results in changes in cell viability, proliferation rate, and gene expression that closely resemble a CD24-negative phenotype. Our data demonstrate that induction of a CD24-positive population is one mechanism by which IDH-mutant tumors acquire stem-like properties. These findings have significant implications for our understanding of the molecular underpinnings of IDH-mutant gliomas.

Nitrogen-doped graphene quantum dots (NGQDs) have gained significant attention due to their various physical and chemical properties; however, there is a gap in the study of NGQDs’ magnetic properties. This work adds to the efforts of bridging the gap by demonstrating the room temperature paramagnetism in GQDs doped with Nitrogen up to 3.26 at.%. The focus of this experimental work was to confirm the paramagnetic behavior of metal free NGQDs resulting from the pyridinic N configuration in the GQDs host. Metal-free nitrogen-doped NGQDs were synthesized using glucose and liquid ammonia as precursors by microwave-assisted synthesis. This was followed by dialysis filtration. The morphology, optical, and magnetic properties of the synthesized NGQDs were characterized carefully through atomic force microscopy (AFM), transmission electron microscopy (TEM)), UV-VIS spectroscopy, fluorescence, X-ray photon spectroscopy (XPS), and vibrating sample magnetometer (VSM). The high-resolution TEM analysis of NGQDs showed that the NGQDs have a hexagonal crystalline structure with a lattice fringe of ~0.24 nm of (1120) graphene plane. The N1s peak using XPS was assigned to pyridinic, pyrrolic, graphitic, and oxygenated NGQDs. The magnetic study showed the room-temperature paramagnetic behavior of NGQDs with pyridinic N configuration, which was found to have a magnetization of 20.8 emu/g.

This is the first Russian translation of several theatre-related excerpts from John Northbrooke’s treatise against idle pastimes originally published in 1577. Little known as it is, Northbrooke’s treatise is important as the opening piece in the theatrical controversy that raged intermittently in England from the late 16th to mid-17th centuries. The publication also includes a historical and biographical introduction and commentary, which covers the glosses provided by Northbrooke.

Papain-like cysteine proteases (PLCPs) are widely expressed enzymes, the main function of which is low-specific-protein turnover in the acidic conditions of lysosomes. Additionally, these proteases provide specific functions in other compartments such as cytosol, nucleus, and extracellular space. The specificity of each protease to its substrates mainly depends on the patterns of the amino acids in the binding cleft. This specificity is highly regulated by media conditions and the presence of accessory proteins. In this study, we examined structural aspects, ensuring the pH-dependent substrate specificity of PLCPs. Experiments employing fluorogenic peptide substrates demonstrated that plant PLCPs and human cathepsins possess a pH-dependent specificity for the residue in the P1 position. X-ray crystallographic studies and molecular simulations allowed the overall structure determination of the enzymes to predict residues in the S1 binding pocket, which can form electrostatic contacts with the substrates. Sequence analysis established the variability of these residues among PLCPs. Based on the obtained data, we designed a peptide inhibitor for human cathepsin L and described its inhibitory potential. As a conclusion, we stated that the S1 binding pocket defines specific pH-dependent recognition of substrates by PLCPs, ensuring multiple physiological functions of these proteases. This work was supported by the Russian Science Foundation (grant No. 22-25-00648).

This article represents the fi rst ever attempt to examine the series of pamphlets on Pierce Penniless, the poor London intellectual, written by T. Nashe, T. Middleton, Anonymous and T. Dekker in 1592–1606, as a unifi ed collection. The three sequels, written more than a decade later than Nashe’s original pamphlet, off er various solutions to Pierce’s problem except the change in attitude to scholars he had been yearning for. The protagonist’s supplication to the devil brings it close to Marlowe’s Tragical history of Doctor Faustus, composed only a little earlier, and highlights the uncommon elements in both narratives. Both Faustus and Pierce begin with melancholic introspection, although their later choices are diff erent in that Faustus renounces the learning he had been involved in, whereas Pierce’s appeal to the devil is a gesture intended to restore the order that he thinks had been undermined by the ‘cormorants’. Both Marlowe’s dramatic and Nashe’s prosaic narratives can be seen in the light of contemporary debate on “mongrel tragicomedy” (as defi ned by Philip Sidney). Rather than “mingling kings and clowns”, playwrights and pamphletists examine the tragic aspects of satire and comic aspects of intellectual plea by focusing on an intellectual protagonist. The pamphlet, traditionally seen as a moralistic genre only, appears as a complex text with an important focus on theatricality and the theatre as a metaphor of life and the stage of justice. The appearance of the devil on stage as a “Prologue in its own play” in Middleton’s Black Booke, the journey of the Knight of the post to hell in Dekker’s pamphlets and the point-by-point response to Pierce set against the panicridden city in the anonymous sequel are shown to be informed by theatre and imbued with theatricality.

We present unique ultrastructural data on avian retinal cells. Presently and earlier (Zueva et al., 2016) we explored distribution of intermediate filaments (IFs) in retinal cells of the Pied flycatcher (Ficedula hypoleuca, Passeriformes, Aves) in the central foveolar zone. This retinal zone only contains single and double cone photoreceptors. Previously we found that continuous IFs span Müller cells (MC) lengthwise from the retinal inner limiting membrane (ILM) layer up to the outer limiting membrane (OLM) layer. Here we describe long cylindrical bundles of IFs (IFBs) inside the cone inner segments (CIS) adjoining the cone plasma membrane, with these IFBs following along the cone lengthwise, and surrounding the cone at equal spacing one from the other. Double cones form a combined unit, wherein they are separated by their respective plasma membranes. Double cones thus have a common external ring of IFBs, surrounding both cone components. In the layer of cilia, the IFBs that continue into the cone outer segment (COS) follow on to the cone apical tip along the direction of incident light, with single IFs separating from the IFB, touching, and sometimes passing in-between the light-sensitive lamellae of the COS. These new data support our previous hypothesis on the quantum mechanism of light energy propagation through the vertebrate retina (Zueva et al., 2016, 2019).

The majority of software vulnerabilities originate from buffer overflow. Techniques to eliminate buffer overflows and limit their damage include secure programming, source code audit, binary code audit, static and dynamic code generation features. Modern compilers implement compile-time and execution time protection schemes, that include variables reordering, inserting canary value, and separate stack for return addresses. Our research is targeted to finding the breaches in the compiler protection methods. We tested MSVC, gcc, and clang and found that two of these compilers have flaws that allow exploiting buffer overwrite under certain conditions.

Myoepithelial carcinoma (MECA) is a rare aggressive salivary gland cancer. Here, the authors analyze the genomic landscape of MECA and identify a high prevalence of oncogenic gene fusions, primarily PLAG1 fusions, highlighting TGFBR3-PLAG1 as a potential hallmark of MECA.

At the root of most fatal malignancies are aberrantly activated transcriptional networks that drive metastatic dissemination. Although individual metastasis-associated genes have been described, the complex regulatory networks presiding over the initiation and maintenance of metastatic tumors are still poorly understood. There is untapped value in identifying therapeutic targets that broadly govern coordinated transcriptional modules dictating metastatic progression. Here, we reverse engineered and interrogated a breast cancer-specific transcriptional interaction network (interactome) to define transcriptional control structures causally responsible for regulating genetic programs underlying breast cancer metastasis in individual patients. Our analyses confirmed established pro-metastatic transcription factors, and they uncovered TRIM25 as a key regulator of metastasis-related transcriptional programs. Further, in vivo analyses established TRIM25 as a potent regulator of metastatic disease and poor survival outcome. Our findings suggest that identifying and targeting keystone proteins, like TRIM25, can effectively collapse transcriptional hierarchies necessary for metastasis formation, thus representing an innovative cancer intervention strategy.

Prototyping and debugging of operating systems and drivers are very tough tasks because of hardware volatility, kernel panics, blue screens of death, long periods of time required to expose the bug, perturbation of the drivers by the debugger, and non-determinism of multi-threaded environment. This paper shows how the deterministic replay of the virtual machine execution can be used to reduce the impact of these factors to the process of debugging. We present an approach to reverse debugging which allows creating multi-target whole-system debugger. Using this debugger one can investigate the failures affecting behavior of virtual hardware and guest software. Our debugger is capable of replaying whole virtual machine execution with reproducing internal state of all virtual devices. Although reverse debugging was a subject of many previous researches, there is no widely available practical tool for debugging software on different platforms. We present reverse debugger as a practical tool, which was tested for Í386, x86-64, MIPS, and ARM platforms, for Windows and Linux guest operating systems. One can use this debugger to debug user-and kernel-level code, deterministic functional modelling of peripheral devices and hardware platforms. We show that this tool incurs 15-40% recording overhead, which allows using our tool for debugging time-sensitive applications. We presented reverse execution implementation as a set of patches. Some of the patches were already included into mainline QEMU.

Various types of 2D/2D prototype devices based on graphene (G) and boron nitride nanosheets (BNNS) were fabricated to study the charge tunneling phenomenon pertinent to vertical transistors for digital and high frequency electronics. Specifically, G/BNNS/metal, G/SiO2, and G/BNNS/SiO2 heterostructures were investigated under direct current (DC-bias) conditions at room temperature. Bilayer graphene and BNNS were grown separately and transferred subsequently onto the substrates to fabricate 2D device architectures. High-resolution transmission electron microscopy confirmed the bilayer graphene structure and few layer BNNS sheets having a hexagonal B3-N3 lattice. The current vs voltage I(V) data for the G/BNNS/Metal devices show Schottky barrier characteristics with very low forward voltage drop, Fowler-Nordheim behavior, and 10−4 Ω/sq. sheet resistance. This result is ascribed to the combination of fast electron transport within graphene grains and out-of-plane tunneling in BNNS that circumvents grain boundary resistance. A theoretical model based on electron tunneling is used to qualitatively describe the behavior of the 2D G/BNNS/metal devices.

We consider competition between layers in adaptive multiplex networks of phase oscillators, where adaptation principles (which cause intra-layer topology evolution) are inspired by real world homophily and homeostasis phenomena. Our model yields the emergence of both scale-free topologies and meso-scale structures in the layers, for an appropriate choice of the control parameters. We further report that the growth of the number of interacting layers leads to a decrease of the global order, due to inter-layer structural competition. However, the increase of the system’s scale can effect local synchronization between neighboring (or strongly coupled) nodes. Such unforeseen phenomena is connected with the nature of the competitive mechanism, which implies the rivalry for optimal structure within the whole system, a situation occurring in a variety of natural systems.

*These authors contributed equally to this work. Essential tremor (ET) is the most prevalent movement disorder affecting millions of people in the United States. Although a positive family history is one of the most important risk factors for ET, the genetic causes of ET remain unknown. In this study, whole exome sequencing and subsequent approaches were performed in a family with an autosomal dominant form of early-onset ET. Functional analyses including mutagenesis, cell culture, gene expression, enzyme-linked immunosorbent, and apoptosis assays were also performed. A disease-segregating mutation (p.Gly171Ala), absent in normal population, was identified in the SORT1 gene. The p.Gly171Ala mutation was shown not only to impair the expression of its encoding protein sortilin but also the mRNA levels of its binding partner p75 neurotrophin receptor that is known to be implicated in brain injury, neuronal apoptosis, and neurotransmission.

Expression profiling of clinically obtainable tumor specimens has been hindered by the need for microgram quantities of RNA. In vitro transcription (IVT)-based amplifications are most commonly used to amplify small quantities of RNA for microarray analysis. However, significant drawbacks exist with IVT-based amplification, and the need for alternative amplification methods remains. Herein, we validate whole transcriptome amplification (WTA), an exponential amplification technique that produces cDNA libraries and amplified target in 3 to 4 hours from nanogram quantities of total RNA using a combination of cDNA microarrays and quantitative polymerase chain reaction (PCR). We demonstrate that WTA material can serve as a “molecular archive” because a WTA cDNA library can be faithfully amplified through multiple rounds of PCR amplification, allowing it to serve as a bankable and distributable resource. To demonstrate applicability, WTA was combined with laser capture microdissection to profile frozen prostate tissues. Unlike most IVT-based and exponential amplification techniques, WTA does not depend on the presence of a poly-A tail. Thus, we demonstrate that WTA is compatible with artificially degraded RNA and RNA isolated from formalin-fixed paraffin-embedded tissues. Taken together, WTA represents a versatile approach to profile and archive cDNA from minute tumor samples and is compatible with partially degraded RNA.

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.

Obsessive compulsive disorder (OCD) is a syndrome characterized by recurrent and intrusive thoughts and ritualistic behaviors or mental acts that a person feels compelled to perform. Twin studies, family studies, and segregation analyses provide compelling evidence that OCD has a strong genetic component. The SLITRK1 gene encodes a developmentally regulated stimulator of neurite outgrowth and previous studies have implicated rare variants in this gene in disorders in the OC spectrum, specifically Tourette syndrome (TS) and trichotillomania (TTM). The objective of the current study was to evaluate rare genetic variation in SLITRK1 in risk for OCD and to functionally characterize associated coding variants. We sequenced SLITRK1 coding exons in 381 individuals with OCD as well as in 356 control samples and identified three novel variants in seven individuals. We found that the combined mutation load in OCD relative to controls was significant (p = 0.036). We identified a missense N400I change in an individual with OCD, which was not found in more than 1000 control samples (P