PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorization.

Inferring gene regulatory networks (GRNs) from single-cell data is challenging due to heuristic limitations. Existing methods also lack estimates of uncertainty. Here we present Probabilistic Matrix Factorization for Gene Regulatory Network Inference (PMF-GRN). Using single-cell expression data, PMF-GRN infers latent factors capturing transcription factor activity and regulatory relationships. Using variational inference allows hyperparameter search for principled model selection and direct comparison to other generative models. We extensively test and benchmark our method using real single-cell datasets and synthetic data. We show that PMF-GRN infers GRNs more accurately than current state-of-the-art single-cell GRN inference methods, offering well-calibrated uncertainty estimates.

Association of Genetic polymorphisms of EDN1 gene and Endothelin-1 level in patients with type 2 diabetes mellitus in the Jordanian population.

Endothelin-1 (ET-1) is one of the most potent vasoconstrictors, encoded by the endothelin-1 (EDN1) gene. It has been shown to play an important role in different diseases including Diabetes Mellitus (DM). Various single nucleotide polymorphisms (SNPs) in the EDN1 gene are related to microvascular complications of type 2 diabetes mellitus (T2DM) such as retinopathy, neuropathy and nephropathy. This study aims to determine the association between two selected EDN1 gene polymorphisms (rs2071942 G > A, rs5370 G > T) and T2DM in the Jordanian population, also to measure the level of ET-1 in T2DM. The samples were collected from the National Center of Diabetes, Endocrinology, and Genetics- Amman, Jordan, including 97 patients with T2DM and 80 healthy individuals. PCR-RFLP was used for SNPs genotyping. ET-1 level was determined using IQELISA kits. The univariate analysis for both SNPs didn't show statistically significant differences in the genotype or allele frequencies among T2DM cases as well as in controls. The same results were obtained regarding ET-1 concentration. The subgroup analysis by sex showed that the genotype and allelic frequencies of rs5370, rs2071942 G/A polymorphisms were not significantly different in males and females. Multivariate Analysis adjusted for various confounders didn't express statistical significance difference for occurrences of both SNPs. However, height and gender showed to be significant risk factors for occurrences of heterozygote alleles in both SNPs. On the other hand, the duration of diabetes has appeared to be related to the recessive allele in rs5370.

Perceived challenges in implementing halal standards by halal certifying bodies in the United States.

Islamic dietary laws inform halal standards, defining which foods are halal (lawful and permissible). Many halal foods are produced in non-Muslim majority countries increasing the likelihood they might be haram (prohibited). Halal certification is one way to operationalize halal standards, hence protecting Muslim consumers. At present there is no unified halal standard guiding halal certification. The aim of this study was to determine the perceived challenges in implementing halal standards in the United States. Semi-structured in-depth interviews were done with a representative from 6 of the 11 halal certifying bodies (HCBs) in the United States. All reported their role was to verify food safety records for compliance with government regulations but not to monitor food safety practices. Two main issues-forged halal certificates and expired halal logos were identified as significant issues. Three HCBs stated there is no problem with having multiple halal standards, but all believed it is necessary to have one universal halal standard with minimum standards followed by everyone. The findings of this study can be beneficial to the U.S. halal industry as it highlights the challenges and issues they face.

Targeted Treatment of Adults with Relapsed or Refractory Diffuse Large B-Cell Lymphoma (DLBCL): Tafasitamab in Context.

The outcomes of Relapsed/Refractory (R/R) Diffuse Large B-cell lymphoma have been historically poor. The recent development of several novel therapies including CD19 directed agents has improved the prognosis of this disease significantly. Chimeric antigen receptor (CAR) T-cell therapy has drastically changed the treatment of R/R DLBCL, but it is still associated with significant barriers and limited access. Tafasitamab (an anti-CD19 engineered monoclonal antibody), in addition to lenalidomide, has shown significant efficacy with exceptionally durable responses in patients with R/R DLBCL who are ineligible for autologous stem cell transplantation (ASCT). Tafasitamab-lenalidomide and certain other therapies (ie, antibody-drug conjugates and bispecific antibodies) are important treatment options for patients who are ineligible for CAR-T due to co-morbidities or lack of access, and patients with rapid progression of disease who are unable to wait for manufacturing of CAR-T. This review will thus discuss currently approved and recently studied targeted treatment options for patients with R/R DLBCL with an emphasis on CAR-T alternative options, particularly Tafasitamab-lenalidomide.

Impact of Thiotepa-Based Autologous Hematopoietic Cell Transplantation in Primary Central Nervous System Lymphoma in First Complete Remission: A University of California Hematologic Malignancies Consortium Retrospective Analysis.

BACKGROUND: The choice between nonmyeloablative chemotherapy (NMA-C) or autologous hematopoietic cell transplantation (autoHCT) as consolidation in primary central nervous system lymphoma (PCNSL), and timing of autoHCT differs among centers. We aimed to clarify these points. METHODS: We retrospectively analyzed PCNSL adult patients who received consolidation in CR1 or underwent autoHCT during their treatment course. Cohort A included those who underwent autoHCT in CR1, cohort B included those who underwent NMA-C in CR1, and cohort C included patients who underwent autoHCT in CR2+. We compared cohorts A and B, and cohorts A and C. The primary endpoint was overall survival (OS), and secondary endpoints were progression-free survival (PFS), treatment-related mortality (TRM) and cumulative incidence of relapse (CIR). RESULTS: 36 patients were included in cohort A, 30 in cohort B, and 14 in cohort C. The 5-year OS for cohorts A vs B and vs C were 90.7% vs 62.8% (P = .045) and vs 77.9% (P = .32), respectively. The 5-year PFS from diagnosis for cohorts A vs B was 87.8% vs 37.3% (P < .001). The 5-year PFS from autoHCT for cohorts A vs C was 87.6% vs 58.4% (P = .023). The 5-year TRM and CIR in cohorts A vs B was 9.4% vs 9.5% (P = .674), and 2.9% vs 53.2% (P < .001), respectively. The 5-year TRM and CIR in cohorts A vs C from the time of autoHCT was 9.5% vs 22.1% (P = .188), and 2.9% vs 19.5% (P = .104), respectively. CONCLUSION: Despite the limitations, thiotepa-based autoHCT in CR1 appears to improve outcomes in eligible patients with PCNSL.

Molecular Detection of Salmonella spp. and E. coli non-O157:H7 in Two Halal Beef Slaughterhouses in the United States.

The aim of this study was to estimate the prevalence of pathogenic bacteria on halal beef carcasses and environmental surfaces in two halal beef slaughterhouses in the United States. To evaluate halal beef slaughter operations, 144 beef carcass samples (pre- and post-evisceration), and 24 environmental site samples (slaughter hall floor, brisket saw, and offal's table) were collected in two halal beef slaughterhouses during June to September 2017. All carcass and environmental samples were analyzed for the presence of Salmonella spp., Escherichia coli O157:H7, and shiga toxin-producing E. coli (non-O157 STEC). Results revealed that Salmonella spp. was isolated and confirmed for the presence of invA gene in 5/36 samples (13.8%) and 5/36 samples (13.8%) at pre-evisceration in plants A and B, respectively. Salmonella spp. was isolated in 2/9 samples (5.6%) of plants A and was not detected in any sample at post-evisceration process. E. coli O157:H7 was not detected in any sample collected from plant A and B. E. coli non-O157 was isolated and confirmed for the presence of virulence genes in 4/36 samples (11.1%) and 2/36 samples (5.5%) at post-evisceration in plants A and B, respectively. Salmonella spp. was detected based on the presence of the Salmonella invA gene in the slaughter hall floor (4/4) and the offal's table (2/4) samples using multiplex polymerase chain reaction (mPCR). In plant B, Salmonella spp. was also confirmed in the slaughter hall floor (2/4) and brisket saw (2/4) samples. On the other hand, one isolate of E. coli O157:H7 and one non-O157 STEC were obtained from the slaughter hall floor of plant A. The E. coli O157:H7 isolate was positive for stx1, stx2, eaeA, and EHEC-hly genes. Two isolates of non-O157 STEC (2/4) were detected in the environmental site samples, one from the slaughter hall floor, and one from an offal's table sample of plant B. These data can be used to inform food safety interventions targeting halal meat operations in the southeastern United States.

An Anomaly Intrusion Detection for High-Density Internet of Things Wireless Communication Network Based Deep Learning Algorithms.

Telecommunication networks are growing exponentially due to their significant role in civilization and industry. As a result of this very significant role, diverse applications have been appeared, which require secured links for data transmission. However, Internet-of-Things (IoT) devices are a substantial field that utilizes the wireless communication infrastructure. However, the IoT, besides the diversity of communications, are more vulnerable to attacks due to the physical distribution in real world. Attackers may prevent the services from running or even forward all of the critical data across the network. That is, an Intrusion Detection System (IDS) has to be integrated into the communication networks. In the literature, there are numerous methodologies to implement the IDSs. In this paper, two distinct models are proposed. In the first model, a custom Convolutional Neural Network (CNN) was constructed and combined with Long Short Term Memory (LSTM) deep network layers. The second model was built about the all fully connected layers (dense layers) to construct an Artificial Neural Network (ANN). Thus, the second model, which is a custom of an ANN layers with various dimensions, is proposed. Results were outstanding a compared to the Logistic Regression algorithm (LR), where an accuracy of 97.01% was obtained in the second model and 96.08% in the first model, compared to the LR algorithm, which showed an accuracy of 92.8%.

Masked graph modeling for molecule generation.

De novo, in-silico design of molecules is a challenging problem with applications in drug discovery and material design. We introduce a masked graph model, which learns a distribution over graphs by capturing conditional distributions over unobserved nodes (atoms) and edges (bonds) given observed ones. We train and then sample from our model by iteratively masking and replacing different parts of initialized graphs. We evaluate our approach on the QM9 and ChEMBL datasets using the GuacaMol distribution-learning benchmark. We find that validity, KL-divergence and Fréchet ChemNet Distance scores are anti-correlated with novelty, and that we can trade off between these metrics more effectively than existing models. On distributional metrics, our model outperforms previously proposed graph-based approaches and is competitive with SMILES-based approaches. Finally, we show our model generates molecules with desired values of specified properties while maintaining physiochemical similarity to the training distribution.

MRI signs of intrauterine fetal demise.

Intrauterine fetal demise (IUFD) is an uncommon but serious event that may occasionally be encountered on fetal MRI. Compared to the more florid signs of fetal demise which has occurred some time ago, recent IUFD is associated with more subtle findings that may be missed or misinterpreted. The two main MRI sequences used in imaging the fetus are T2-like two-dimensional balanced steady-state free-precession (SSFP), a white blood sequence, or T2-weighted single-shot fast spin-echo (SSFSE), a black blood sequence. The most reliable and specific signs of a recent IUFD are a constricted heart with poorly delineated cardiac chambers and signal abnormality in the heart and aorta, which will have different features depending on the MRI sequence used. Secondary signs of IUFD include global brain ischemia, abnormal globes, effusions, body wall edema and umbilical cord thrombosis. Unlike fetal ultrasound examinations where cardiac activity is routinely assessed, fetal MRI requires careful scrutiny of the fetal heart for assessment of fetal life.

Outpatient clinic-wide psychological screening for children and adolescents with type 1 diabetes in Qatar: An initiative for integrative healthcare in the Gulf region.

OBJECTIVE: To identify culturally appropriate psychological screening measures for children and adolescents with type 1 diabetes in Qatar, determine rates of depressive and anxiety symptoms in a clinical sample, and examine associations between screening measures, demographic variables, medical characteristics, and diabetes treatment outcomes, specifically HbA1c. METHODS: A total of 150 participants with type 1 diabetes aged 10-17 were recruited. Participants were Arabic or English speaking and of Qatari and non-Qatari nationality. Participants completed the Mood and Feelings Questionnaire (child and parent proxy form), the Spence Children's Anxiety Scale, and the Pediatric Quality of Life, Diabetes version (child and parent proxy form). Glycosylated hemoglobin (HbA1c) on the date of the testing was recorded. RESULTS: Approximately ten percent (10.2%) of children and adolescents scored above the cutoff score of 27 indicating clinically significant depressive symptoms, and 12.8% of parents rated their child above the respective cutoff score of 21 for the parent proxy form. Further, 36% of the sample reported clinically significant anxiety symptoms, scoring above the cutoff score of 50. Parent report on their child's quality of life predicted HbA1c (F[6, 140] = 5.42, p = 0.000); B = -0.05, p = 0.002). CONCLUSIONS: Rates of depressive and anxiety symptoms are comparable to those observed in western countries. Thus, systematic screening for depression and anxiety in children and adolescents with type 1 diabetes should be implemented in Qatar. This will help inform decisions to refer to mental health services and thus provide more integrated care, possibly improving treatment outcomes.

Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.

The analysis of single-cell genomics data presents several statistical challenges, and extensive efforts have been made to produce methods for the analysis of this data that impute missing values, address sampling issues and quantify and correct for noise. In spite of such efforts, no consensus on best practices has been established and all current approaches vary substantially based on the available data and empirical tests. The k-Nearest Neighbor Graph (kNN-G) is often used to infer the identities of, and relationships between, cells and is the basis of many widely used dimensionality-reduction and projection methods. The kNN-G has also been the basis for imputation methods using, e.g., neighbor averaging and graph diffusion. However, due to the lack of an agreed-upon optimal objective function for choosing hyperparameters, these methods tend to oversmooth data, thereby resulting in a loss of information with regard to cell identity and the specific gene-to-gene patterns underlying regulatory mechanisms. In this paper, we investigate the tuning of kNN- and diffusion-based denoising methods with a novel non-stochastic method for optimally preserving biologically relevant informative variance in single-cell data. The framework, Denoising Expression data with a Weighted Affinity Kernel and Self-Supervision (DEWÄKSS), uses a self-supervised technique to tune its parameters. We demonstrate that denoising with optimal parameters selected by our objective function (i) is robust to preprocessing methods using data from established benchmarks, (ii) disentangles cellular identity and maintains robust clusters over dimension-reduction methods, (iii) maintains variance along several expression dimensions, unlike previous heuristic-based methods that tend to oversmooth data variance, and (iv) rarely involves diffusion but rather uses a fixed weighted kNN graph for denoising. Together, these findings provide a new understanding of kNN- and diffusion-based denoising methods. Code and example data for DEWÄKSS is available at https://gitlab.com/Xparx/dewakss/-/tree/Tjarnberg2020branch.

SDHB and SDHA Immunohistochemistry in Canine Pheochromocytomas.

Pheochromocytomas (PCs) are tumors arising from the chromaffin cells of the adrenal glands and are the most common tumors of the adrenal medulla in animals. In people, these are highly correlated to inherited gene mutations in the succinate dehydrogenase (SDH) pathway; however, to date, little work has been done on the genetic basis of these tumors in animals. In humans, immunohistochemistry has proven valuable as a screening technique for SDH mutations. Human PCs that lack succinate dehydrogenase B (SDHB) immunoreactivity have a high rate of mutation in the SDH family of genes, while human PCs lacking succinate dehydrogenase A (SDHA) immunoreactivity have mutations in the SDHA gene. To determine if these results are similar for dogs, we performed SDHA and SDHB immunohistochemistry on 35 canine formalin-fixed, paraffin-embedded (FFPE) PCs. Interestingly, there was a loss of immunoreactivity for both SDHA and SDHB in four samples (11%), suggesting a mutation in SDHx including SDHA. An additional 25 (71%) lacked immunoreactivity for SDHB, while retaining SDHA immunoreactivity. These data suggest that 29 out of the 35 (82%) may have an SDH family mutation other than SDHA. Further work is needed to determine if canine SDH immunohistochemistry on PCs correlates to genetic mutations that are similar to human PCs.

Molecular Geometry Prediction using a Deep Generative Graph Neural Network.

A molecule's geometry, also known as conformation, is one of a molecule's most important properties, determining the reactions it participates in, the bonds it forms, and the interactions it has with other molecules. Conventional conformation generation methods minimize hand-designed molecular force field energy functions that are often not well correlated with the true energy function of a molecule observed in nature. They generate geometrically diverse sets of conformations, some of which are very similar to the lowest-energy conformations and others of which are very different. In this paper, we propose a conditional deep generative graph neural network that learns an energy function by directly learning to generate molecular conformations that are energetically favorable and more likely to be observed experimentally in data-driven manner. On three large-scale datasets containing small molecules, we show that our method generates a set of conformations that on average is far more likely to be close to the corresponding reference conformations than are those obtained from conventional force field methods. Our method maintains geometrical diversity by generating conformations that are not too similar to each other, and is also computationally faster. We also show that our method can be used to provide initial coordinates for conventional force field methods. On one of the evaluated datasets we show that this combination allows us to combine the best of both methods, yielding generated conformations that are on average close to reference conformations with some very similar to reference conformations.

Development of a Novel Loading Device for Studying Magnesium Degradation under Compressive Load for Implant Applications.

Medical implants play a key role in treating bone fractures. Permanent implants are currently used for immobilization of fractures and bearing physiological loads during bone healing. After bone has healed, these implants, if not removed, often cause complications in the long run; and secondary surgeries for removing them pose additional discomfort and expenses for patients. Magnesium (Mg)-based bioresorbable implants, can potentially eliminate the need for additional surgeries by degrading safely over time in the human body. When studying the degradation behaviors of Mg-based implants in vitro, it is important to simulate physiological conditions in vivo closely, including loading. Considering that implants often carry physiological loads in vivo and mechanical stresses affect the degradation rate of Mg, a novel loading device was designed and manufactured for studying Mg degradation under load over a long period of time in a simulated body fluid in vitro. Degradation of Mg rods were investigated by immersing in a revised simulated body fluid (rSBF) for two weeks while a consistent compressive load was applied using the loading device. The results showed that the loading device provided a consistent load of 500 ± 45 N during the two weeks of immersion. Mg rods showed a significant faster degradation rate under the applied load, as demonstrated by a higher mass loss of the sample, a higher pH increase and Mg2+ ion release in the rSBF.

Limb-girdle muscular dystrophies: where next after six decades from the first proposal (Review).

Limb-girdle muscular dystrophies (LGMD) are a heterogeneous group of disorders, which has led to certain investigators disputing its rationality. The mutual feature of LGMD is limb-girdle affection. Magnetic resonance imaging (MRI), perioral skin biopsies, blood-based assays, reverse­protein arrays, proteomic analyses, gene chips and next generation sequencing are the leading diagnostic techniques for LGMD and gene, cell and pharmaceutical treatments are the mainstay therapies for these genetic disorders. Recently, more highlights have been shed on disease biomarkers to follow up disease progression and to monitor therapeutic responsiveness in future trials. In this study, we review LGMD from a variety of aspects, paying specific attention to newly evolving research, with the purpose of bringing this information into the clinical setting to aid the development of novel therapeutic strategies for this hereditary disease. In conclusion, substantial progress in our ability to diagnose and treat LGMD has been made in recent decades, however enhancing our understanding of the detailed pathophysiology of LGMD may enhance our ability to improve disease outcome in subsequent years.

Limb-girdle muscular dystrophy subtypes: First-reported cohort from northeastern China.

The relative frequencies of different subtypes of limb-girdle muscular dystrophies vary widely among different populations. We estimated the percentage of limb-girdle muscular dystrophy subtypes in Chinese people based on 68 patients with limb-girdle muscular dystrophy from the Myology Clinic, Neurology Department, First Hospital of Jilin University, China. A diagnosis of calpainopathy was made in 12 cases (17%), and dysferlin deficiency in 10 cases (15%). Two biopsies revealed α-sarcoglycan deficiency (3%), and two others revealed a lack of caveolin-3 (3%). A diagnosis of unclassified limb-girdle muscular dystrophy was made in the remaining patients (62%). The appearances of calpain 3- and dysferlin-deficient biopsies were similar, though rimmed vacuoles were unique to dysferlinopathy, while inflammatory infiltrates were present in both these limb-girdle muscular dystrophy type 2D biopsies. Macrophages were detected in seven dysferlinopathy biopsies. The results of this study suggest that the distribution of limb-girdle muscular dystrophy subtypes in the Han Chinese population is similar to that reported in the West. The less necrotic, regenerating and inflammatory appearance of limb-girdle muscular dystrophy type 2A, but with more lobulated fibers, supports the idea that calpainopathy is a less active, but more chronic disease than dysferlinopathy. Unusual features indicated an extended limb-girdle muscular dystrophy disease spectrum. The use of acid phosphatase stain should be considered in suspected dysferlinopathies. To the best of our knowledge, this is the first report to define the relative proportions of the various forms of limb-girdle muscular dystrophy in China, based on protein testing.

Learning and memory performances in adolescent users of alcohol and marijuana: interactive effects.

OBJECTIVE: Lifetime alcohol hangover and withdrawal symptoms in youth have been shown to predict poorer recall of verbal and nonverbal information, as well as reduced visuospatial skills. Some evidence has suggested that negative effects of alcohol on the brain may be buffered in part by potential neuroprotective properties of cannabinoids. We hypothesized that a history of more alcohol hangover symptoms would predict worse performances on measures of verbal and visual memory, and that this relationship would be moderated by marijuana involvement. METHOD: Participants were 130 adolescents (65 with histories of heavy marijuana use, and 65 non-marijuana-using controls), ranging in age from 15.7 to 19.1 years. Neuropsychological tests for visual and verbal memory and interviews assessing lifetime and recent substance use, hangover/withdrawal symptoms, and abuse and dependence criteria were administered. RESULTS: Regression models revealed that greater alcohol hangover symptoms predicted worse verbal learning (p < .05) and memory (p < .05) (California Verbal Learning Test, Second Edition) scores for non-marijuana users, but alcohol hangover symptoms were not linked to performance among marijuana users. Alcohol hangover symptoms did not predict visual memory in either group. CONCLUSIONS: Results confirm previous studies linking adolescent heavy drinking to reduced verbal learning and memory performance. However, this relationship is not seen in adolescents with similar levels of alcohol involvement who also are heavy users of marijuana.

Neurocognitive correlates of white matter quality in adolescent substance users.

BACKGROUND: Progressive myelination during adolescence implicates an increased vulnerability to neurotoxic substances and enduring neurocognitive consequences. This study examined the cognitive manifestations of altered white matter microstructure in chronic marijuana and alcohol-using (MJ+ALC) adolescents. METHODS: Thirty-six MJ+ALC adolescents (ages 16-19) and 36 demographically similar controls were evaluated with diffusion tensor imaging (Bava et al., 2009) and neurocognitive tests. Regions of group difference in fractional anisotropy (FA) and mean diffusivity (MD) were analyzed in relation to cognitive performance. RESULTS: In users, lower FA in temporal areas related to poorer performance on attention, working memory, and speeded processing tasks. Among regions where users had higher FA than controls, occipital FA was positively associated with working memory and complex visuomotor sequencing, whereas FA in anterior regions was negatively associated with verbal memory performance. CONCLUSIONS: Findings suggest differential influences of white matter development on cognition in MJ+ALC using adolescents than in non-using peers. Neuroadaptation may reflect additive and subtractive responses to substance use that are complicated by competing maturational processes.

Age differences in visual path integration.

Previous research has demonstrated age-related decline in spatial navigation skills. However, spatial navigation is a complex ability that requires the integration of many component processes that may show differential susceptibility to aging. In particular, successful navigation depends on the accurate computation of distance and direction from self-generated movements through the environment, known as path integration. In the present study, we utilized virtual environments (VE) to investigate age-related differences in participants' ability to determine linear distances, angular rotations, and angular displacement exclusively from visual input. Results indicated that for shorter lengths, distances can be gauged from visual input alone with relative equivalence between older and younger participants. As distances increased, however, older individuals were less accurate. There were no age differences in estimating angular rotations. Requiring simultaneous integration of distance and rotation (in a triangle completion homing task) resulted in robust age-differences independent of the absolute amount of displacement. For older adults, accuracy in the triangle completion task was highly related to their rotation accuracy while returning to the point of origin, and less so to their distance accuracy. This study demonstrated age-related deficits in the ability to perform visual return-to-origin tasks and suggests one way in which elderly navigation performance may be compromised.

Neuropsychological performance and sleep disturbance following traumatic brain injury.

OBJECTIVE: To examine the relation between sleep disturbance and neurocognitive ability among persons with traumatic brain injury (TBI). DESIGN: Correlational research evaluating demographic and neuropsychological predictors of sleep disturbance using multiple regression analysis and analysis of variance. PARTICIPANTS: Eighty-seven patients with mild to severe TBI admitted to a comprehensive outpatient neurorehabilitation program. MAIN OUTCOME MEASURES: Sleep disturbance assessed using the Pittsburgh Sleep Quality Index. RESULTS: Hierarchical regression analysis revealed that performance on selected measures of cognitive functioning significantly improved prediction of sleep disturbance, accounting for 14% of variance beyond that accounted for by injury severity and gender. The total model accounted for 31% of the variance in Pittsburgh Sleep Quality Index scores. Patients with mild TBI reported more sleep disturbance (P < .01) than did patients with severe TBI. CONCLUSIONS: Sleep disturbance among patients with TBI may be associated with a particular constellation of neuropsychological abilities. These issues are discussed in relation to prior findings that indicate the involvement of additional neuropsychiatric factors associated with sleep disturbance in mild TBI.