Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Prevalence and Impact of Workplace Sexual Harassment Experienced by Medical Sonographers.

OBJECTIVE: To assess the prevalence and impact of sexual harassment among a nationwide sample of medical sonographers. METHODS: A survey was distributed anonymously to a convenience sample of medical sonographers via email contacts and sonographer-specific social media pages. Data were analyzed to determine respondent demographics, the prevalence of sexual harassment in the last 2 years, the type and severity of harassment experienced, demographics of perpetrators, personal and institutional responses to such experiences, and the impact of sexual harassment on sonographer physical and mental health and job satisfaction. RESULTS: Of the 220 sonographers (83% female) most (45%) were between 18 and 34 years and identified as white (81%). A total of 192 (87%) reported experiencing at least 1 incident of harassment within the last 2 years. Female respondents experienced higher harassment rates (76%) compared to males (50%, P = .02). The most common forms of harassment were verbal, including suggestive or sexist jokes (69%) and offensive sexist remarks (61%). Perpetrators were predominantly male (78%) and most commonly patients (89%) or their friends/family members (46%). The majority of respondents either ignored the harassing behavior (70%) or treated it like a joke (50%), with only a minority (12%) officially reporting incidents. Of those who reported, 44% were unsatisfied with their institution's response. Among respondents, 34% reported negative impacts of workplace sexual harassment, such as anxiety, depression, sleep loss, or adverse workplace consequences. DISCUSSION: Workplace sexual harassment is a common occurrence for sonographers and often leads to negative health and career outcomes. Further institutional policies to prevent harassment and mitigate its effects are needed.

Quantitative diffusion imaging and genotype-by-sex interactions in a rat model of Alexander disease.

PURPOSE: The clinical diagnosis and classification of Alexander disease (AxD) relies in part on qualitative neuroimaging biomarkers; however, these biomarkers fail to distinguish and discriminate different subtypes of AxD, especially in the presence of overlap in clinical symptoms. To address this gap in knowledge, we applied neurite orientation dispersion and density imaging (NODDI) to an innovative CRISPR-Cas9 rat genetic model of AxD to gain quantitative insights into the neural substrates and brain microstructural changes seen in AxD and to potentially identify novel quantitative NODDI biomarkers of AxD. METHODS: Multi-shell DWI of age- and sex-matched AxD and wild-type Sprague Dawley rats (n = 6 per sex per genotype) was performed and DTI and NODDI measures calculated. A 3 × 2 × 2 analysis of variance model was used to determine the effect of genotype, biological sex, and laterality on quantitative measures of DTI and NODDI across regions of interest implicated in AxD. RESULTS: There is a significant effect of genotype in the amygdala, hippocampus, neocortex, and thalamus in measures of both DTI and NODDI brain microstructure. A genotype by biological sex interaction was identified in DTI and NODDI measures in the corpus callosum, hippocampus, and neocortex. CONCLUSION: We present the first application of NODDI to the study of AxD using a rat genetic model of AxD. Our analysis identifies alterations in NODDI and DTI measures to large white matter tracts and subcortical gray nuclei. We further identified genotype by sex interactions, suggesting a possible role for biological sex in the neuropathogenesis of AxD.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN.

The design of novel protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. A new generation of deep learning methods promises to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Patient, Provider, and Practice Characteristics Predicting Use of Diagnostic Imaging in Primary Care: Cross-Sectional Data From the National Ambulatory Medical Care Survey.

OBJECTIVE: To determine imaging utilization rates in outpatient primary care visits and factors influencing likelihood of imaging use. METHODS: We used 2013 to 2018 National Ambulatory Medical Care Survey cross-sectional data. All visits to primary care clinics during the study period were included in the sample. Descriptive statistics on visit characteristics including imaging utilization were calculated. Logistic regression analyses evaluated the influence of a variety of patient-, provider-, and practice-level variables on the odds of obtaining diagnostic imaging, further subdivided by modality (radiographs, CT, MRI, and ultrasound). The data's survey weighting was accounted for to produce valid national-level estimates of imaging use for US office-based primary care visits. RESULTS: Using survey weights, approximately 2.8 billion patient visits were included. Diagnostic imaging was ordered at 12.5% of visits with radiographs the most common (4.3%) and MRI the least common (0.8%). Imaging utilization was similar or greater among minority patients compared with White, non-Hispanic patients. Physician assistants used imaging at higher rates than physicians, in particular CT at 6.5% of visits compared with 0.7% for doctors of medicine and doctors of osteopathic medicine (odds ratio 5.67, 95% confidence interval 4.07-7.88). CONCLUSION: Disparities in rates of imaging utilization for minorities seen in other health care settings were not present in this sample of primary care visits, supporting that access to primary care is a path to promote health equity. Higher rates of imaging utilization among advanced-level practitioners highlight an opportunity to evaluate imaging appropriateness and promote equitable, high-value imaging among all practitioners.

Particle retracking algorithm capable of quantifying large, local matrix deformation for traction force microscopy.

Deformation measurement is a key process in traction force microscopy (TFM). Conventionally, particle image velocimetry (PIV) or correlation-based particle tracking velocimetry (cPTV) have been used for such a purpose. Using simulated bead images, we show that those methods fail to capture large displacement vectors and that it is due to a poor cross-correlation. Here, to redeem the potential large vectors, we propose a two-step deformation tracking algorithm that combines cPTV, which performs better for small displacements than PIV methods, and newly-designed retracking algorithm that exploits statistically confident vectors from the initial cPTV to guide the selection of correlation peak which are not necessarily the global maximum. As a result, the new method, named 'cPTV-Retracking', or cPTVR, was able to track more than 92% of large vectors whereas conventional methods could track 43-77% of those. Correspondingly, traction force reconstructed from cPTVR showed better recovery of large traction than the old methods. cPTVR applied on the experimental bead images has shown a better resolving power of the traction with different-sized cell-matrix adhesions than conventional methods. Altogether, cPTVR method enhances the accuracy of TFM in the case of large deformations present in soft substrates. We share this advance via our TFMPackage software.

SLC13A5/sodium-citrate co-transporter overexpression causes disrupted white matter integrity and an autistic-like phenotype.

Endoplasmic reticulum-based N ɛ-lysine acetylation serves as an important protein quality control system for the secretory pathway. Dysfunctional endoplasmic reticulum-based acetylation, as caused by overexpression of the acetyl coenzyme A transporter AT-1 in the mouse, results in altered glycoprotein flux through the secretory pathway and an autistic-like phenotype. AT-1 works in concert with SLC25A1, the citrate/malate antiporter in the mitochondria, SLC13A5, the plasma membrane sodium/citrate symporter and ATP citrate lyase, the cytosolic enzyme that converts citrate into acetyl coenzyme A. Here, we report that mice with neuron-specific overexpression of SLC13A5 exhibit autistic-like behaviours with a jumping stereotypy. The mice displayed disrupted white matter integrity and altered synaptic structure and function. Analysis of both the proteome and acetyl-proteome revealed unique adaptations in the hippocampus and cortex, highlighting a metabolic response that likely plays an important role in the SLC13A5 neuron transgenic phenotype. Overall, our results support a mechanistic link between aberrant intracellular citrate/acetyl coenzyme A flux and the development of an autistic-like phenotype.

Increased expression of SLC25A1/CIC causes an autistic-like phenotype with altered neuron morphology.

N ε-lysine acetylation within the lumen of the endoplasmic reticulum is a recently characterized protein quality control system that positively selects properly folded glycoproteins in the early secretory pathway. Overexpression of the endoplasmic reticulum acetyl-CoA transporter AT-1 in mouse forebrain neurons results in increased dendritic branching, spine formation and an autistic-like phenotype that is attributed to altered glycoprotein flux through the secretory pathway. AT-1 overexpressing neurons maintain the cytosolic pool of acetyl-CoA by upregulation of SLC25A1, the mitochondrial citrate/malate antiporter and ATP citrate lyase, which converts cytosolic citrate into acetyl-CoA. All three genes have been associated with autism spectrum disorder, suggesting that aberrant cytosolic-to-endoplasmic reticulum flux of acetyl-CoA can be a mechanistic driver for the development of autism spectrum disorder. We therefore generated a SLC25A1 neuron transgenic mouse with overexpression specifically in the forebrain neurons. The mice displayed autistic-like behaviours with a jumping stereotypy. They exhibited increased steady-state levels of citrate and acetyl-CoA, disrupted white matter integrity with activated microglia and altered synaptic plasticity and morphology. Finally, quantitative proteomic and acetyl-proteomic analyses revealed differential adaptations in the hippocampus and cortex. Overall, our study reinforces the connection between aberrant cytosolic-to-endoplasmic reticulum acetyl-CoA flux and the development of an autistic-like phenotype.

18F-SynVesT-1 PET/MR Imaging of the Effect of Gut Microbiota on Synaptic Density and Neurite Microstructure: A Preclinical Pilot Study.

The gut microbiome profoundly influences brain structure and function. The gut microbiome is hypothesized to play a key role in the etiopathogenesis of neuropsychiatric and neurodegenerative illness; however, the contribution of an intact gut microbiome to quantitative neuroimaging parameters of brain microstructure and function remains unknown. Herein, we report the broad and significant influence of a functional gut microbiome on commonly employed neuroimaging measures of diffusion tensor imaging (DTI), neurite orientation dispersion and density (NODDI) imaging, and SV2A 18F-SynVesT-1 synaptic density PET imaging when compared to germ-free animals. In this pilot study, we demonstrate that mice, in the presence of a functional gut microbiome, possess higher neurite density and orientation dispersion and decreased synaptic density when compared to age- and sex-matched germ-free mice. Our results reveal the region-specific structural influences and synaptic changes in the brain arising from the presence of intestinal microbiota. Further, our study highlights important considerations for the development of quantitative neuroimaging biomarkers for precision imaging in neurologic and psychiatric illness.

Clinical translational neuroimaging of the antioxidant effect of N-acetylcysteine on neural microstructure.

PURPOSE: Oxidative stress and downstream effectors have emerged as important pathological processes that drive psychiatric illness, suggesting that antioxidants may have a therapeutic role in psychiatric disease. However, no imaging biomarkers are currently available to track therapeutic response. The purpose of this study was to examine whether advanced DWI techniques are able to sensitively detect the potential therapeutic effects of the antioxidant N-acetylcysteine (NAC) in a Disc1 svΔ2 preclinical rat model of psychiatric illness. METHODS: Male and female Disc1 svΔ2 rats and age-matched, sex-matched Sprague-Dawley wild-type controls were treated with a saline vehicle or NAC before ex vivo MRI acquisition at P50. Imaging data were fit to DTI and neurite orientation dispersion and density imaging models and analyzed for region-specific changes in quantitative diffusion metrics. Brains were further processed for cellular quantification of microglial density and morphology. All experiments were repeated for Disc1 svΔ2 rats exposed to chronic early-life stress to test how gene-environment interactions might alter effectiveness of NAC therapy. RESULTS: The DTI and neurite orientation dispersion and density imaging analyses demonstrated amelioration of early-life, sex-specific neural microstructural deficits with concomitant differences in microglial morphology across multiple brain regions relevant to neuropsychiatric illness with NAC treatment, but only in male Disc1 svΔ2 rats. Addition of chronic early-life stress reduced the ability of NAC to restore microstructural deficits. CONCLUSION: These findings provide evidence for a treatment pathway targeting endogenous antioxidant capacity, and the clinical translational utility of neurite orientation dispersion and density imaging microstructural imaging to sensitively detect microstructural alterations resulting from antioxidant treatment.

Good performance of bioimpedance in early pregnancy to predict preeclampsia.

INTRODUCTION: Preeclampsia (PE) affects 2-8% of pregnancies and is one of the main causes of maternal morbidity and mortality worldwide. Early identification of pregnant women at higher risk for PE would allow the use of interventions to reduce adverse maternal and perinatal outcomes. OBJECTIVE: To assess the ability of bioelectrical impedance analysis (BIA) in pregnancy to predict the development of PE. METHODS: This prospective cohort involved healthy nulliparas who underwent BIA at 17-20 weeks gestation and were followed until delivery. We used univariate and multivariate logistic regression to assess the ability of BIA measures to predict the occurrence of PE. We used an adjusted regression model to estimate the probability of developing PE, the Hosmer-Lemeshow test to assess the adequacy of the final model, and ROC curves to assess the sensitivity and specificity of different BIA measures in the prediction of PE. RESULTS: Twelve (6.1%) of the 196 participants developed PE. In the final multivariate model, the following BIA measures were associated with the occurrence of PE: extracellular water/intracellular water ≤ 0.618, skeletal muscle mass ≥ 25 Kg, and body fat percentage ≥ 44%. The combination of these three measures had a predictive accuracy of 83.7%, a sensitivity of 83.3%, a specificity of 83.7%, and a negative predictive value of 98.7% for PE. CONCLUSION: BIA done on nulliparous women at 17-20 weeks gestation has a good accuracy and high negative predictive value for the risk of developing PE.

Outpatient ocular brachytherapy: The USC Experience.

PURPOSE: Ocular brachytherapy is a standard-of-care surgical procedure for globe salvage in the treatment of uveal melanoma. The procedure involves the placement and subsequent removal of a radioactive plaque several days later. At many locations, patients are admitted on an inpatient basis until plaque removal due to radiation safety concerns. However, patients may be discharged to home after plaque insertion, and subsequently return to the medical facility for plaque removal. This study aimed to evaluate the safety and systematic financial benefit of the outpatient ocular brachytherapy program at "?>the University of Southern California (USC) Roski Eye Institute for 30 years. METHODS AND MATERIALS: A single-institution retrospective record review was performed on all 275 patients who underwent brachytherapy for ocular tumors between January 1, 1989 and December 31, 2019 to assess for occurrences of reportable radiation and/or patients safety events. The treatment protocols at our institution are described. Data on hospital-adjusted expenses per inpatient day from the American Hospital Association's 2018 Annual Survey were used as a proxy for costs to patients and the health care system to perform a cost-benefit analysis comparing outpatient versus inpatient brachytherapy. RESULTS: Of the 275 plaque procedures over a 30-year period that were reviewed, there were no internally or externally reportable patient or radiation safety events. There were no adverse events related to patient transportation to the hospital, the patient not returning for plaque removal, operative issues in removing the plaque on time due to cancelled or delayed cases, or loss of radioactive material. Additionally, our cost-benefit analysis estimates that outpatient brachytherapy reduced costs for USC's patients in 2018 by an average of $24,722 per patient treated with ocular brachytherapy. CONCLUSIONS: With appropriate measures, outpatient ocular brachytherapy allows patients to safely return home with the added benefit of decreased financial burden for both patients and the broader health care system.

Structural and Biochemical Insights into the Inhibition of Human Acetylcholinesterase by G-Series Nerve Agents and Subsequent Reactivation by HI-6.

The recent use of organophosphate nerve agents in Syria, Malaysia, Russia, and the United Kingdom has reinforced the potential threat of their intentional release. These agents act through their ability to inhibit human acetylcholinesterase (hAChE; E.C. 3.1.1.7), an enzyme vital for survival. The toxicity of hAChE inhibition via G-series nerve agents has been demonstrated to vary widely depending on the G-agent used. To gain insight into this issue, the structures of hAChE inhibited by tabun, sarin, cyclosarin, soman, and GP were obtained along with the inhibition kinetics for these agents. Through this information, the role of hAChE active site plasticity in agent selectivity is revealed. With reports indicating that the efficacy of reactivators can vary based on the nerve agent inhibiting hAChE, human recombinatorially expressed hAChE was utilized to define these variations for HI-6 among various G-agents. To identify the structural underpinnings of this phenomenon, the structures of tabun, sarin, and soman-inhibited hAChE in complex with HI-6 were determined. This revealed how the presence of G-agent adducts impacts reactivator access and placement within the active site. These insights will contribute toward a path of next-generation reactivators and an improved understanding of the innate issues with the current reactivators.

Mapping Sex-Specific Neurodevelopmental Alterations in Neurite Density and Morphology in a Rat Genetic Model of Psychiatric Illness.

Neurite orientation dispersion and density imaging (NODDI) is an emerging magnetic resonance (MR) diffusion-weighted imaging (DWI) technique that permits non-invasive quantitative assessment of neurite density and morphology. NODDI has improved our ability to image neuronal microstructure over conventional techniques such as diffusion tensor imaging (DTI) and is particularly suited for studies of the developing brain as it can measure and characterize the dynamic changes occurring in dendrite cytoarchitecture that are critical to early brain development. Neurodevelopmental alterations to the diffusion tensor have been reported in psychiatric illness, but it remains unknown whether advanced DWI techniques such as NODDI are able to sensitively and specifically detect neurodevelopmental changes in brain microstructure beyond those provided by DTI. We show, in an extension of our previous work with a Disc1 svΔ2 rat genetic model of psychiatric illness, the enhanced sensitivity and specificity of NODDI to identify neurodevelopmental and sex-specific changes in brain microstructure that are otherwise difficult to observe with DTI and further corroborate observed changes in brain microstructure to differences in sex-specific systems-level animal behavior. Together, these findings inform the potential application and clinical translational utility of NODDI in studies of brain microstructure in psychiatric illness throughout neurodevelopment and further, the ability of advanced DWI methods such as NODDI to examine the role of biological sex and its influence on brain microstructure in psychiatric illness.

Distinct microRNA profiles for complete hydatidiform moles at risk of malignant progression.

BACKGROUND: MicroRNAs are small noncoding RNAs with important regulatory functions. Although well-studied in cancer, little is known about the role of microRNAs in premalignant disease. Complete hydatidiform moles are benign forms of gestational trophoblastic disease that progress to gestational trophoblastic neoplasia in up to 20% of cases; however, there is no well-established biomarker that can predict the development of gestational trophoblastic neoplasia. OBJECTIVE: This study aimed to investigate possible differences in microRNA expression between complete moles progressing to gestational trophoblastic neoplasia and those regressing after surgical evacuation. STUDY DESIGN: Total RNA was extracted from fresh frozen tissues from 39 complete moles collected at the time of uterine evacuation in Brazil. In the study, 39 cases achieved human chorionic gonadotropin normalization without further therapy, and 9 cases developed gestational trophoblastic neoplasia requiring chemotherapy. Total RNA was also extracted from 2 choriocarcinoma cell lines, JEG-3 and JAR, and an immortalized normal placenta cell line, 3A-subE. MicroRNA expression in all samples was quantified using microRNA sequencing. Hits from the sequencing data were validated using a quantitative probe-based assay. Significantly altered microRNAs were then subjected to target prediction and gene ontology analyses to search for alterations in key signaling pathways. Expression of potential microRNA targets was assessed by quantitative real-time polymerase chain reaction and western blot. Finally, potential prognostic protein biomarkers were validated in an independent set of formalin-fixed paraffin-embedded patient samples from the United States (15 complete moles progressing to gestational trophoblastic neoplasia and 12 that spontaneously regressed) using quantitative immunohistochemistry. RESULTS: In total, 462 microRNAs were identified in all samples at a threshold of <1 tag per million. MicroRNA sequencing revealed a distinct set of microRNAs associated with gestational trophoblastic neoplasia. Gene ontology analysis of the most altered transcripts showed that the leading pathway was related to response to ischemia (P<.001). Here, 2 of the top 3 most significantly altered microRNAs were mir-181b-5p (1.65-fold; adjusted P=.014) and mir-181d-5p (1.85-fold; adjusted P=.014), both of which have been shown to regulate expression of BCL2. By quantitative real-time polymerase chain reaction, BCL2 messenger RNA expression was significantly lower in the complete moles progressing to gestational trophoblastic neoplasia than the regressing complete moles (-4.69-fold; P=.018). Reduced expression of BCL2 was confirmed in tissue samples by western blot. Immunohistochemistry in the independent patient samples revealed significantly lower cytoplasmic expression of BCL2 in the villous trophoblasts from cases destined for progression to gestational trophoblastic neoplasia compared with those that regressed, both with respect to staining intensity (optic density 0.110±0.102 vs 0.212±0.036; P<.001) and to the percentage of positive cells (16%±28% vs 49.4%±28.05%; P=.003). CONCLUSION: Complete moles progressing to gestational trophoblastic neoplasia are associated with a distinct microRNA profile. miR-181 family members and BCL2 may be prognostic biomarkers for predicting gestational trophoblastic neoplasia risk.

Microglial Density Alters Measures of Axonal Integrity and Structural Connectivity.

Diffusion tensor imaging (DTI) has fundamentally transformed how we interrogate diseases and disorders of the brain in neuropsychiatric illness. DTI and recently developed multicompartment diffusion-weighted imaging (MC-DWI) techniques, such as NODDI (neurite orientation dispersion and density imaging), measure diffusion anisotropy presuming a static neuroglial environment; however, microglial morphology and density are highly dynamic in psychiatric illness, and how alterations in microglial density might influence intracellular measures of diffusion anisotropy in DTI and MC-DWI brain microstructure is unknown. To address this question, DTI and MC-DWI studies of murine brains depleted of microglia were performed, revealing significant alterations in axonal integrity and fiber tractography in DTI and in commonly used MC-DWI models. With accumulating evidence of the role of microglia in neuropsychiatric illness, our findings uncover the unexpected contribution of microglia to measures of axonal integrity and structural connectivity and provide unanticipated insights into the potential influence of microglia in diffusion imaging studies of neuropsychiatric disease.

Women's multisite microbial modulation during pregnancy.

The composition of female microbiome varies with age, physiological and socio-behavior conditions. Also, changes in microbiome composition are observed as pregnancy progresses, especially in the vaginal site. Together with the physiological adaptations of gestation, changes in microbiome composition seem to be fundamental for proper fetal development. This study aimed at simultaneously evaluating the vaginal, gut, and oral microbiome of healthy pregnant women, and comparing it with those observed in healthy non-pregnant women of reproductive age. In a cross-sectional study, vaginal, oral and gut samples were collected from 42 pregnant and 18 non-pregnant women, and the microbiome composition was evaluated by 16S rRNA sequencing, using Illumina platform. In the pregnant group, we observed a positive correlation between Eubacterium and Akkermansia in the gut samples; between Eubacterium and Ruminococcus in the vaginal samples; and between Streptococcus and Gemella in the oral samples. Notwithstanding, we observed a negative correlation between Lactobacillus and Atopobium and between Lactobacillus and Gardnerella in vaginal microbiome. Prevotella was the only genus found in all three sites studied; however, there was no signal of bacterial influence between sites during pregnancy. These results suggest that in addition to hormonal and immunological variations during healthy pregnancy, the female body also undergoes microbiome modulation in multiple sites in order to maintain an eubiotic status.

Metabolic Changes in Synaptosomes in an Animal Model of Schizophrenia Revealed by 1H and 1H,13C NMR Spectroscopy.

Synaptosomes are isolated nerve terminals that contain synaptic components, including neurotransmitters, metabolites, adhesion/fusion proteins, and nerve terminal receptors. The essential role of synaptosomes in neurotransmission has stimulated keen interest in understanding both their proteomic and metabolic composition. Mass spectrometric (MS) quantification of synaptosomes has illuminated their proteomic composition, but the determination of the metabolic composition by MS has been met with limited success. In this study, we report a proof-of-concept application of one- and two-dimensional nuclear magnetic resonance (NMR) spectroscopy for analyzing the metabolic composition of synaptosomes. We utilize this approach to compare the metabolic composition synaptosomes from a wild-type rat with that from a newly generated genetic rat model (Disc1 svΔ2), which qualitatively recapitulates clinically observed early DISC1 truncations associated with schizophrenia. This study demonstrates the feasibility of using NMR spectroscopy to identify and quantify metabolites within synaptosomal fractions.

Neonatal Near Miss among Newborns of Women with Type 1 Diabetes Mellitus.

OBJECTIVE: To investigate the frequency of neonatal near miss (NNM) and associate it with maternal morbidity in newborns of women with type 1 diabetes mellitus (T1DM). METHODS: This was a cross-sectional retrospective study from a secondary analysis of data retrieved from medical records of pregnant women with T1DM cared at a Brazilian university hospital between 2005 and 2015. Maternal near miss (MNM) and potentially life-threatening conditions (PTLC) were classified according to the World Health Organization criteria. NNM was classified according to the Pan American Health Organization Neonatal Near Miss Working Group criteria. Association of maternal morbidity with NNM was assessed using chi-square test. RESULTS: There were 122 newborns (NB) among 137 T1DM pregnancies. Thirty-seven NB presented NNM-incidence of 303 NNM per 1000 live births (37/122). NNM was associated with MNM (P < 0.001, OR (95% CI): 17.15 (1.85-159.12)). PLTC did not increase the odds of NNM (P=0.07; OR (95% CI): 2.1281 (0.92-4.91)). Seven newborns died, six of them from pregnancies without severe maternal morbidity. 71% of the neonatal death (5/7) occurred in malformed neonates. CONCLUSION: MNM was associated with NNM among women with T1DM, and PLTC, paradoxically, did not increase NNM.