MicroRNAs as potential biomarkers for diagnosis of post-traumatic stress disorder.

Post-traumatic stress disorder is a mental disorder caused by exposure to severe traumatic life events. Currently, there are no validated biomarkers or laboratory tests that can distinguish between trauma survivors with and without post-traumatic stress disorder. In addition, the heterogeneity of clinical presentations of post-traumatic stress disorder and the overlap of symptoms with other conditions can lead to misdiagnosis and inappropriate treatment. Evidence suggests that this condition is a multisystem disorder that affects many biological systems, raising the possibility that peripheral markers of disease may be used to diagnose post-traumatic stress disorder. We performed a PubMed search for microRNAs (miRNAs) in post-traumatic stress disorder (PTSD) that could serve as diagnostic biomarkers and found 18 original research articles on studies performed with human patients and published January 2012 to December 2023. These included four studies with whole blood, seven with peripheral blood mononuclear cells, four with plasma extracellular vesicles/exosomes, and one with serum exosomes. One of these studies had also used whole plasma. Two studies were excluded as they did not involve microRNA biomarkers. Most of the studies had collected samples from adult male Veterans who had returned from deployment and been exposed to combat, and only two were from recently traumatized adult subjects. In measuring miRNA expression levels, many of the studies had used microarray miRNA analysis, miRNA Seq analysis, or NanoString panels. Only six studies had used real time polymerase chain reaction assay to determine/validate miRNA expression in PTSD subjects compared to controls. The miRNAs that were found/validated in these studies may be considered as potential candidate biomarkers for PTSD and include miR-3130-5p in whole blood; miR-193a-5p, -7113-5p, -125a, -181c, and -671-5p in peripheral blood mononuclear cells; miR-10b-5p, -203a-3p, -4488, -502-3p, -874-3p, -5100, and -7641 in plasma extracellular vesicles/exosomes; and miR-18a-3p and -7-1-5p in blood plasma. Several important limitations identified in the studies need to be taken into account in future studies. Further studies are warranted with war veterans and recently traumatized children, adolescents, and adults having PTSD and use of animal models subjected to various stressors and the effects of suppressing or overexpressing specific microRNAs.

MicroRNAs as potential diagnostic biomarkers for bipolar disorder.

Abnormal expression of microRNAs is connected to brain development and disease and could provide novel biomarkers for the diagnosis and prognosis of bipolar disorder. We performed a PubMed search for microRNA biomarkers in bipolar disorder and found 18 original research articles on studies performed with human patients and published from January 2011 to June 2023. These studies included microRNA profiling in blood- and brain-based materials. From the studies that had validated the preliminary findings, potential candidate biomarkers for bipolar disorder in adults could be miR-140-3p, -30d-5p, -330-5p, -378a-5p, -21-3p, -330-3p, -345-5p in whole blood, miR-19b-3p, -1180-3p, -125a-5p, let-7e-5p in blood plasma, and miR-7-5p, -23b-5p, -142-3p, -221-5p, -370-3p in the blood serum. Two of the studies had investigated the changes in microRNA expression of patients with bipolar disorder receiving treatment. One showed a significant increase in plasma miR-134 compared to baseline after 4 weeks of treatment which included typical antipsychotics, atypical antipsychotics, and benzodiazepines. The other study had assessed the effects of prescribed medications which included neurotransmitter receptor-site binders (drug class B) and sedatives, hypnotics, anticonvulsants, and analgesics (drug class C) on microRNA results. The combined effects of the two drug classes increased the significance of the results for miR-219 and -29c with miR-30e-3p and -526b* acquiring significance. MicroRNAs were tested to see if they could serve as biomarkers of bipolar disorder at different clinical states of mania, depression, and euthymia. One study showed that upregulation in whole blood of miR-9-5p, -29a-3p, -106a-5p, -106b-5p, -107, -125a-3p, -125b-5p and of miR-107, -125a-3p occurred in manic and euthymic patients compared to controls, respectively, and that upregulation of miR-106a-5p, -107 was found for manic compared to euthymic patients. In two other studies using blood plasma, downregulation of miR-134 was observed in manic patients compared to controls, and dysregulation of miR-134, -152, -607, -633, -652, -155 occurred in euthymic patients compared to controls. Finally, microRNAs such as miR-34a, -34b, -34c, -137, and -140-3p, -21-3p, -30d-5p, -330-5p, -378a-5p, -134, -19b-3p were shown to have diagnostic potential in distinguishing bipolar disorder patients from schizophrenia or major depressive disorder patients, respectively. Further studies are warranted with adolescents and young adults having bipolar disorder and consideration should be given to using animal models of the disorder to investigate the effects of suppressing or overexpressing specific microRNAs.

Autism spectrum disorder: difficulties in diagnosis and microRNA biomarkers.

We performed a PubMed search for microRNAs in autism spectrum disorder that could serve as diagnostic biomarkers in patients and selected 17 articles published from January 2008 to December 2023, of which 4 studies were performed with whole blood, 4 with blood plasma, 5 with blood serum, 1 with serum neural cell adhesion molecule L1-captured extracellular vesicles, 1 with blood cells, and 2 with peripheral blood mononuclear cells. Most of the studies involved children and the study cohorts were largely males. Many of the studies had performed microRNA sequencing or quantitative polymerase chain reaction assays to measure microRNA expression. Only five studies had used real-time polymerase chain reaction assay to validate microRNA expression in autism spectrum disorder subjects compared to controls. The microRNAs that were validated in these studies may be considered as potential candidate biomarkers for autism spectrum disorder and include miR-500a-5p, -197-5p, -424-5p, -664a-3p, -365a-3p, -619-5p, -664a- 3p, -3135a, -328-3p, and -500a-5p in blood plasma and miR-151a-3p, -181b-5p, -320a, -328, -433, -489, -572, -663a, -101-3p, -106b-5p, -19b-3p, -195-5p, and -130a-3p in blood serum of children, and miR-15b-5p and -6126 in whole blood of adults. Several important limitations were identified in the studies reviewed, and need to be taken into account in future studies. Further studies are warranted with children and adults having different levels of autism spectrum disorder severity and consideration should be given to using animal models of autism spectrum disorder to investigate the effects of suppressing or overexpressing specific microRNAs as a novel therapy.

Narrowing the Digital Divide: Framework for Creating Telehealth Equity Dashboards.

Telehealth presents both the potential to improve access to care and to widen the digital divide contributing to health care disparities and obliging health care systems to standardize approaches to measure and display telehealth disparities. Based on a literature review and the operational experience of clinicians, informaticists, and researchers in the Supporting Pediatric Research on Outcomes and Utilization of Telehealth (SPROUT)-Clinical and Translational Science Awards (CTSA) Network, we outline a strategic framework for health systems to develop and optimally use a telehealth equity dashboard through a 3-phased approach of (1) defining data sources and key equity-related metrics of interest; (2) designing a dynamic and user-friendly dashboard; and (3) deploying the dashboard to maximize engagement among clinical staff, investigators, and administrators.

Prognostic clinical prediction models for acute post-surgical pain in adults: a systematic review.

BACKGROUND: Acute post-surgical pain is managed inadequately in many patients undergoing surgery. Several prognostic risk prediction models have been developed to identify patients at high risk of developing moderate to severe acute post-surgical pain. The aim of this systematic review was to describe and evaluate the methodological conduct of these prediction models. METHODS: We searched MEDLINE, EMBASE and CINAHL for studies of prognostic risk prediction models for acute post-surgical pain using predetermined criteria. Prediction model performance was evaluated according to discrimination and calibration. Adherence to TRIPOD guidelines was assessed. Risk of bias and applicability was independently assessed by two reviewers using the prediction model risk of bias assessment tool. RESULTS: We included 14 studies reporting on 17 prediction models. The most common predictors identified in final prediction models included age; surgery type; sex or gender; anxiety or fear of surgery; pre-operative pain intensity; pre-operative analgesic use; pain catastrophising; and expected surgical incision size. Discrimination, measured by the area under receiver operating characteristic curves or c-statistic, ranged from 0.61 to 0.83. Calibration was only reported for seven models. The median (IQR [range]) overall adherence rate to TRIPOD items was 62 (53-66 [47-72])%. All prediction models were at high risk of bias. CONCLUSIONS: Effective prediction models could support the prevention and treatment of acute post-surgical pain; however, existing models are at high risk of bias which may affect their reliability to inform practice. Consideration should be given to the goals, timing of intended use and desired outcomes of a prediction model before development.

Full-field, frequency-domain comparison of simulated and measured human brain deformation.

We propose a robust framework for quantitatively comparing model-predicted and experimentally measured strain fields in the human brain during harmonic skull motion. Traumatic brain injuries (TBIs) are typically caused by skull impact or acceleration, but how skull motion leads to brain deformation and consequent neural injury remains unclear and comparison of model predictions to experimental data remains limited. Magnetic resonance elastography (MRE) provides high-resolution, full-field measurements of dynamic brain deformation induced by harmonic skull motion. In the proposed framework, full-field strain measurements from human brain MRE in vivo are compared to simulated strain fields from models with similar harmonic loading. To enable comparison, the model geometry and subject anatomy, and subsequently, the predicted and measured strain fields are nonlinearly registered to the same standard brain atlas. Strain field correlations (\(\:{C}_{v}\)), both global (over the brain volume) and local (over smaller sub-volumes), are then computed from the inner product of the complex-valued strain tensors from model and experiment at each voxel. To demonstrate our approach, we compare strain fields from MRE in six human subjects to predictions from two previously developed models. Notably, global \(\:{C}_{v}\) values are higher when comparing strain fields from different subjects (\(\:{C}_{v}\)~0.6-0.7) than when comparing strain fields from either of the two models to strain fields in any subject. The proposed framework provides a quantitative method to assess similarity (and to identify discrepancies) between model predictions and experimental measurements of brain deformation, and thus can aid in the development and evaluation of improved models of brain biomechanics.

Gene Expression Changes Associated With Recurrence After Gross Total Resection of Newly Diagnosed World Health Organization Grade 1 Meningioma.

BACKGROUND AND OBJECTIVE: Patients who undergo gross total resection (GTR) of Central Nervous System World Health Organization (WHO) grade 1 meningioma constitute a "low-risk" group, but some low-risk meningiomas can recur despite reassuring clinical and histological features. In this study, gene expression values in newly diagnosed WHO grade 1 meningiomas that had undergone GTR were evaluated for their association with recurrence. METHODS: This was a retrospective, international, multicenter cohort study that included WHO grade 1 meningiomas that underwent GTR, as first treatment, based on postoperative magnetic resonance imaging. Normalized gene expression values from a previously validated 34-gene panel were evaluated for their association with recurrence. Kaplan-Meier, multivariable Cox proportional hazard analyses, and K-means clustering were performed to assess the association of genes of interest with recurrence and identify molecular subgroups among clinically and histologically low-risk meningiomas. RESULTS: In total, 442 patients with WHO grade 1 meningiomas that underwent GTR and had available gene expression profiling data were included in the study. The median follow-up was 5.0 years (interquartile range 2.6-7.7 years), local recurrence occurred in 36 patients (8.1%), 5-year local freedom from recurrence was 90.5%, and median time to recurrence was 2.9 years (range 0.5-10.7 years). Eleven genes were associated with local recurrence, including lower expression of ARID1B, ESR1, LINC02593, PGR, and TMEM30B and higher expression of CDK6, CDKN2C, CKS2, KIF20A, PGK1, and TAGLN. Of these genes, PGK1 had the largest effect size. K-means clustering based on these 11 genes distinguished 2 molecular groups of clinically and histologically low-risk meningiomas with significant differences in local freedom from recurrence (hazard ratio 2.5, 95% CI 1.2-5.1, P = .016). CONCLUSION: Gene expression profiling may help to identify newly diagnosed WHO grade 1 meningiomas that have an elevated risk of recurrence despite GTR.

Prenatal Exposure to Bisphenol A and/or Diethylhexyl Phthalate Impacts Brain Monoamine Levels in Rat Offspring.

This study examines the sex-specific effects of gestational exposure (days 6-21) to endocrine-disrupting chemicals such as bisphenol A (BPA), diethylhexyl phthalate (DEHP), or their combination on brain monoamine levels that play an important role in regulating behavior. Pregnant Sprague-Dawley rats were orally administered saline, low doses (5 µg/kg BW/day) of BPA or DEHP, and their combination or a high dose (7.5 mg/kg BW/day) of DEHP alone or in combination with BPA during pregnancy. The offspring were subjected to a behavioral test and sacrificed in adulthood, and the brains were analyzed for neurotransmitter levels. In the paraventricular nucleus, there was a marked reduction in dopamine levels (p < 0.01) in male offspring from the BPA, DEHP, and B + D (HD) groups, which correlated well with their shock probe defensive burying times. Neurotransmitter changes in all brain regions examined were significant in female offspring, with DEHP (HD) females being affected the most, followed by the B + D groups. BPA and/or DEHP (LD) increased monoamine turnover in a region-specific manner in male offspring (p < 0.05). Overall, prenatal exposure to BPA, DEHP, or their combination alters monoamine levels in a brain region-specific, sex-specific, and dose-dependent manner, which could have implications for their behavioral and neuroendocrine effects.

Post-mortem changes of anisotropic mechanical properties in the porcine brain assessed by MR elastography.

Knowledge of the mechanical properties of brain tissue in vivo is essential to understanding the mechanisms underlying traumatic brain injury (TBI) and to creating accurate computational models of TBI and neurosurgical simulation. Brain white matter, which is composed of aligned, myelinated, axonal fibers, is structurally anisotropic. White matter in vivo also exhibits mechanical anisotropy, as measured by magnetic resonance elastography (MRE), but measurements of anisotropy obtained by mechanical testing of white matter ex vivo have been inconsistent. The minipig has a gyrencephalic brain with similar white matter and gray matter proportions to humans and therefore provides a relevant model for human brain mechanics. In this study, we compare estimates of anisotropic mechanical properties of the minipig brain obtained by identical, non-invasive methods in the live (in vivo) and dead animals (in situ). To do so, we combine wave displacement fields from MRE and fiber directions derived from diffusion tensor imaging (DTI) with a finite element-based, transversely-isotropic nonlinear inversion (TI-NLI) algorithm. Maps of anisotropic mechanical properties in the minipig brain were generated for each animal alive and at specific times post-mortem. These maps show that white matter is stiffer, more dissipative, and more anisotropic than gray matter when the minipig is alive, but that these differences largely disappear post-mortem, with the exception of tensile anisotropy. Overall, brain tissue becomes stiffer, less dissipative, and less mechanically anisotropic post-mortem. These findings emphasize the importance of testing brain tissue properties in vivo. Statement of Significance: In this study, MRE and DTI in the minipig were combined to estimate, for the first time, anisotropic mechanical properties in the living brain and in the same brain after death. Significant differences were observed in the anisotropic behavior of brain tissue post-mortem. These results demonstrate the importance of measuring brain tissue properties in vivo as well as ex vivo, and provide new quantitative data for the development of computational models of brain biomechanics.

Structural tuning of anisotropic mechanical properties in 3D-Printed hydrogel lattices.

We investigated the ability to tune the anisotropic mechanical properties of 3D-printed hydrogel lattices by modifying their geometry (lattice strut diameter, unit cell size, and unit cell scaling factor). Many soft tissues are anisotropic and the ability to mimic natural anisotropy would be valuable for developing tissue-surrogate "phantoms" for elasticity imaging (shear wave elastography or magnetic resonance elastography). Vintile lattices were 3D-printed in polyethylene glycol di-acrylate (PEGDA) using digital light projection printing. Two mechanical benchtop tests, dynamic shear testing and unconfined compression, were used to measure the apparent shear storage moduli (G') and apparent Young's moduli (E) of lattice samples. Increasing the unit cell size from 1.25 mm to 2.00 mm reduced the Young's and shear moduli of the lattices by 91% and 85%, respectively. Decreasing the strut diameter from 300 µm to 200 µm reduced the apparent shear moduli of the lattices by 95%. Increasing the geometric scaling ratio of the lattice unit cells from 1.00 × to 2.00 × increased mechanical anisotropy in shear (by a factor of 3.1) and in compression (by a factor of 2.9). Both simulations and experiments show that the effects of unit cell size and strut diameter are consistent with power law relationships between volume fraction and apparent elastic moduli. In particular, experimental measurements of apparent Young's moduli agree well with predictions of the theoretical Gibson-Ashby model. Thus, the anisotropic mechanical properties of a lattice can be tuned by the unit cell size, the strut diameter, and scaling factors. This approach will be valuable in designing tissue-mimicking hydrogel lattice-based composite materials for elastography phantoms and tissue engineered scaffolds.

Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography.

Magnetic resonance elastography (MRE) is a promising neuroimaging technique to probe tissue microstructure, which has revealed widespread softening with loss of structural integrity in the aging brain. Traditional MRE approaches assume mechanical isotropy. However, white matter is known to be anisotropic from aligned, myelinated axonal bundles, which can lead to uncertainty in mechanical property estimates in these areas when using isotropic MRE. Recent advances in anisotropic MRE now allow for estimation of shear and tensile anisotropy, along with substrate shear modulus, in white matter tracts. The objective of this study was to investigate age-related differences in anisotropic mechanical properties in human brain white matter tracts for the first time. Anisotropic mechanical properties in all tracts were found to be significantly lower in older adults compared to young adults, with average property differences ranging between 0.028-0.107 for shear anisotropy and between 0.139-0.347 for tensile anisotropy. Stiffness perpendicular to the axonal fiber direction was also significantly lower in older age, but only in certain tracts. When compared with fractional anisotropy measures from diffusion tensor imaging, we found that anisotropic MRE measures provided additional, complementary information in describing differences between the white matter integrity of young and older populations. Anisotropic MRE provides a new tool for studying white matter structural integrity in aging and neurodegeneration.

Effect of Human Head Shape on the Risk of Traumatic Brain Injury: A Gaussian Process Regression-Based Machine Learning Approach.

INTRODUCTION: Computational head injury models are promising tools for understanding and predicting traumatic brain injuries. However, most available head injury models are "average" models that employ a single set of head geometry (e.g., 50th-percentile U.S. male) without considering variability in these parameters across the human population. A significant variability of head shapes exists in U.S. Army soldiers, evident from the Anthropometric Survey of U.S. Army Personnel (ANSUR II). The objective of this study is to elucidate the effects of head shape on the predicted risk of traumatic brain injury from computational head injury models. MATERIALS AND METHODS: Magnetic resonance imaging scans of 25 human subjects are collected. These images are registered to the standard MNI152 brain atlas, and the resulting transformation matrix components (called head shape parameters) are used to quantify head shapes of the subjects. A generative machine learning model is used to generate 25 additional head shape parameter datasets to augment our database. Head injury models are developed for these head shapes, and a rapid injurious head rotation event is simulated to obtain several brain injury predictor variables (BIPVs): Peak cumulative maximum principal strain (CMPS), average CMPS, and the volume fraction of brain exceeding an injurious CMPS threshold. A Gaussian process regression model is trained between head shape parameters and BIPVs, which is then used to study the relative sensitivity of the various BIPVs on individual head shape parameters. We distinguish head shape parameters into 2 types: Scaling components ${T_{xx}}$, ${T_{yy}}$, and ${T_{zz}}$ that capture the breadth, length, and height of the head, respectively, and shearing components (${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$) that capture the relative skewness of the head shape. RESULTS: An overall positive correlation is evident between scaling components and BIPVs. Notably, a very high, positive correlation is seen between the BIPVs and the head volume. As an example, a 57% increase in peak CMPS was noted between the smallest and the largest investigated head volume parameters. The variation in shearing components ${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$ on average does not cause notable changes in the BIPVs. From the Gaussian process regression model, all 3 BIPVs showed an increasing trend with each of the 3 scaling components, but the BIPVs are found to be most sensitive to the height dimension of the head. From the Sobol sensitivity analysis, the ${T_{zz}}$ scaling parameter contributes nearly 60% to the total variance in peak and average CMPS; ${T_{yy}}$ contributes approximately 20%, whereas ${T_{xx}}$ contributes less than 5%. The remaining contribution is from the 6 shearing components. Unlike peak and average CMPS, the VF-CMPS BIPV is associated with relatively evenly distributed Sobol indices across the 3 scaling parameters. Furthermore, the contribution of shearing components on the total variance in this case is negligible. CONCLUSIONS: Head shape has a considerable influence on the injury predictions of computational head injury models. Available "average" head injury models based on a 50th-percentile U.S. male are likely associated with considerable uncertainty. In general, larger head sizes correspond to greater BIPV magnitudes, which point to potentially a greater injury risk under rapid neck rotation for people with larger heads.

Preoperative prolapse phenotype is predictive of surgical outcome with minimally invasive sacrocolpopexy.

BACKGROUND: The gold-standard treatment for advanced pelvic organ prolapse is sacrocolpopexy. However, the preoperative features of prolapse that predict optimal outcomes are unknown. OBJECTIVE: This study aimed to develop a clinical prediction model that uses preoperative scores on the Pelvic Organ Prolapse Quantification examination to predict outcomes after minimally invasive sacrocolpopexy for stages 2, 3, and 4 uterovaginal prolapse and vaginal vault prolapse. STUDY DESIGN: A 2-institution database of pre- and postoperative variables from 881 cases of minimally invasive sacrocolpopexy was analyzed. Data from patients were analyzed in the following 4 groups: stage 2 uterovaginal prolapse, stage 3 to 4 uterovaginal prolapse, stage 2 vaginal vault prolapse, and stage 3 to 4 vaginal vault prolapse. Unsupervised machine learning was used to identify clusters and investigate associations between clusters and outcome. The k-means clustering analysis was performed with preoperative Pelvic Organ Prolapse Quantification points and stratified by previous hysterectomy status. The "optimal" surgical outcome was defined as postoperative Pelvic Organ Prolapse Quantification stage <2. Demographic variables were compared by cluster with Student t and chi-square tests. Odds ratios were calculated to determine whether clusters could predict the outcome. Age at surgery, body mass index, and previous prolapse surgery were used for adjusted odds ratios. RESULTS: Five statistically distinct prolapse clusters (phenotypes C, A, A>P, P, and P>A) were found. These phenotypes reflected the predominant region of prolapse (apical, anterior, or posterior) and whether support was preserved in the nonpredominant region. Phenotype A (anterior compartment prolapse predominant, posterior support preserved) was found in all 4 groups of patients and was considered the reference in the analysis. In 111 patients with stage 2 uterovaginal prolapse, phenotypes A and A>P (greater anterior prolapse than posterior prolapse) were found, and patients with phenotype A were more likely than those with phenotype A>P to have an optimal surgical outcome. In 401 patients with stage 3 to 4 uterovaginal prolapse, phenotypes C (apical compartment predominant, prolapse in all compartments), A, and A>P were found, and patients with phenotype A>P were more likely than those with phenotype A to have ideal surgical outcome. In 72 patients with stage 2 vaginal vault prolapse, phenotypes A, A>P, and P (posterior compartment predominant, anterior support preserved) were found, and those with phenotype A>P were less likely to have an ideal outcome than patients with phenotype A. In 297 patients with stage 3 to 4 vaginal vault prolapse, phenotypes C, A, and P>A (prolapse greater in posterior than in anterior compartment) were found, but there were no significant differences in rate of ideal outcome between phenotypes. CONCLUSION: Five anatomic phenotypes based on preoperative Pelvic Organ Prolapse Quantification scores were present in patients with stages 2 and 3 to 4 uterovaginal prolapse and vaginal vault prolapse. These phenotypes are predictive of surgical outcome after minimally invasive sacrocolpopexy. Further work needs to confirm the presence and predictive nature of these phenotypes. In addition, whether the phenotypes represent a progression of prolapse or discrete prolapse presentations resulting from different anatomic and life course risk profiles is unknown. These phenotypes may be useful in surgical counseling and planning.

Site-directed genotype screening for elimination of antinutritional saponins in quinoa seeds identifies TSARL1 as a master controller of saponin biosynthesis selectively in seeds.

Climate change may result in a drier climate and increased salinization, threatening agricultural productivity worldwide. Quinoa (Chenopodium quinoa) produces highly nutritious seeds and tolerates abiotic stresses such as drought and high salinity, making it a promising future food source. However, the presence of antinutritional saponins in their seeds is an undesirable trait. We mapped genes controlling seed saponin content to a genomic region that includes TSARL1. We isolated desired genetic variation in this gene by producing a large mutant library of a commercial quinoa cultivar and screening the library for specific nucleotide substitutions using droplet digital PCR. We were able to rapidly isolate two independent tsarl1 mutants, which retained saponins in the leaves and roots for defence, but saponins were undetectable in the seed coat. We further could show that TSARL1 specifically controls seed saponin biosynthesis in the committed step after 2,3-oxidosqualene. Our work provides new important knowledge on the function of TSARL1 and represents a breakthrough for quinoa breeding.

Improving access to child abuse evaluations through innovation & telemedicine.

Many children and families do not have access to specialized pediatric health care, including child abuse pediatricians. Medical evaluations in cases of suspected child maltreatment including physical abuse, sexual abuse, and neglect are a critical component of the multidisciplinary team response to these concerns. We review the role of child abuse pediatricians in cases of suspected child maltreatment. We discuss the advantages and disadvantages of current models of care including co-location of child abuse specialists within children's advocacy centers, hospital-based medical evaluation programs and community-based clinics. We review barriers to universal and equitable access to specialized care. We then highlight the significance of telemedicine as an important tool for improving access to care for children who would not otherwise have access.

Shear wave speeds in a nearly incompressible fibrous material with two unequal fiber families.

The mechanical properties of soft biological tissues can be characterized non-invasively by magnetic resonance elastography (MRE). In MRE, shear wave fields are induced by vibration, imaged by magnetic resonance imaging, and inverted to estimate tissue properties in terms of the parameters of an underlying material model. Most MRE studies assume an isotropic material model; however, biological tissue is often anisotropic with a fibrous structure, and some tissues contain two or more families of fibers-each with different orientations and properties. Motivated by the prospect of using MRE to characterize such tissues, this paper describes the propagation of shear waves in soft fibrous material with two unequal fiber families. Shear wave speeds are expressed in terms of material parameters, and the effect of each parameter on the shear wave speeds is investigated. Analytical expressions of wave speeds are confirmed by finite element simulations of shear wave transmission with various polarization directions. This study supports the feasibility of estimating parameters of soft fibrous tissues with two unequal fiber families in vivo from local shear wave speeds and advances the prospects for the mechanical characterization of such biological tissues by MRE.

National Institute for Health and Care Excellence (NICE) guidance on monitoring and management of Barrett's oesophagus and stage I oesophageal adenocarcinoma.

Barrett's oesophagus is the only known precursor to oesophageal adenocarcinoma, a cancer with very poor prognosis. The main risk factors for Barrett's oesophagus are a history of gastro-oesophageal acid reflux symptoms and obesity. Men, smokers and those with a family history are also at increased risk. Progression from Barrett's oesophagus to cancer occurs via an intermediate stage, known as dysplasia. However, dysplasia and early cancer usually develop without any clinical signs, often in individuals whose symptoms are well controlled by acid suppressant medications; therefore, endoscopic surveillance is recommended to allow for early diagnosis and timely clinical intervention. Individuals with Barrett's oesophagus need to be fully informed about the implications of this diagnosis and the benefits and risks of monitoring strategies. Pharmacological treatments are recommended for control of symptoms, but not for chemoprevention. Dysplasia and stage 1 oesophageal adenocarcinoma have excellent prognoses, since they can be cured with endoscopic or surgical therapies. Endoscopic resection is the most accurate staging technique for early Barrett's-related oesophageal adenocarcinoma. Endoscopic ablation is effective and indicated to eradicate Barrett's oesophagus in patients with dysplasia. Future research should focus on improved accuracy for dysplasia detection via new technologies and providing more robust evidence to support pathways for follow-up and treatment.

Theoretical relationships between axoneme distortion and internal forces and torques in ciliary beating.

The axoneme is an intricate nanomachine responsible for generating the propulsive oscillations of cilia and flagella in an astonishing variety of organisms. New imaging techniques based on cryoelectron-tomography (cryo-ET) and subtomogram averaging have revealed the detailed structures of the axoneme and its components with sub-nm resolution, but the mechanical function of each component and how the assembly generates oscillations remains stubbornly unclear. Most explanations of oscillatory behavior rely on the dynamic regulation of dynein by some signal, but this may not be necessary if the system of dynein-driven slender filaments is dynamically unstable. Understanding the possibility of instability-driven oscillations requires a multifilament model of the axoneme that accounts for distortions of the axoneme as it bends. Active bending requires forces and bending moments that will tend to change the spacing and alignment of doublets. We hypothesize that components of the axoneme resist and respond to these loads in ways that are critical to beating. Specifically, we propose (i) that radial spokes provide torsional stiffness by resisting misalignment (as well as spacing) between the central pair and outer doublets, and (ii) that the kinematics of dynein arms affect the relationships between active forces and bending moments on deforming doublets. These proposed relationships enhance the ability of theoretical, multifilament models of axonemal beating to generate propulsive oscillatory waveforms via dynamic mechanical instability.