Search

Skull growth involves the expansion of both the flat calvarial bones of the skull and the fibrous marginal zones, termed sutures, between them. This process depends on co‐ordinated proliferation of mesenchymal‐derived progenitor cells within the sutures, and their differentiation to osteoblasts which produce the bone matrix required to expand the size of the bony plates. Defects lead to premature closure of these sutures, termed craniosynostosis, resulting in heterogeneous head shape differences due to restricted growth of one or more sutures. The impact on the individual depends on how many and which sutures are affected and the severity of the effect. Several genetic loci are responsible, including a wide range of variants in the gene for the interleukin 11 receptor (IL11RA, OMIM#600939). Recent work from Kespohl and colleagues provides new insights into how some of these variants influence IL‐11R function; we discuss their influences on IL‐11R structure and IL‐11 function as a stimulus of osteoblast differentiation. [ABSTRACT FROM AUTHOR]

Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected individuals to severe adverse effects. Though the importance of controlling hypertension is clear, the multitude of therapeutic regimens and patient factors that affect the success of blood pressure control makes it difficult to predict the likelihood to predict whether a patient's blood pressure will be controlled. This project endeavors to investigate whether machine learning can accurately predict the control of a patient's hypertension within 12 months of a clinical encounter. To build the machine learning model, a retrospective review of the electronic medical records of 350,008 patients 18 years of age and older between January 1, 2015 and June 1, 2022 was performed to form model training and testing cohorts. The data included in the model included medication combinations, patient laboratory values, vital sign measurements, comorbidities, healthcare encounters, and demographic information. The mean age of the patient population was 65.6 years with 161,283 (46.1%) men and 275,001 (78.6%) white. A sliding time window of data was used to both prohibit data leakage from training sets to test sets and to maximize model performance. This sliding window resulted in using the study data to create 287 predictive models each using 2 years of training data and one week of testing data for a total study duration of five and a half years. Model performance was combined across all models. The primary outcome, prediction of blood pressure control within 12 months demonstrated an area under the curve of 0.76 (95% confidence interval; 0.75–0.76), sensitivity of 61.52% (61.0–62.03%), specificity of 75.69% (75.25–76.13%), positive predictive value of 67.75% (67.51–67.99%), and negative predictive value of 70.49% (70.32–70.66%). An AUC of 0.756 is considered to be moderately good for machine learning models. While the accuracy of this model is promising, it is impossible to state with certainty the clinical relevancy of any clinical support ML model without deploying it in a clinical setting and studying its impact on health outcomes. By also incorporating uncertainty analysis for every prediction, the authors believe that this approach offers the best-known solution to predicting hypertension control and that machine learning may be able to improve the accuracy of hypertension control predictions using patient information already available in the electronic health record. This method can serve as a foundation with further research to strengthen the model accuracy and to help determine clinical relevance. [ABSTRACT FROM AUTHOR]

Emotional engagement when recollecting a trauma memory is considered a key element of effective trauma-focused therapy. Research has shown that reduced physiological reactivity during trauma recall is associated with worse treatment outcomes for posttraumatic stress disorder (PTSD), but this has yet to be examined in a cognitively oriented treatment. This study examined whether pretreatment heart rate (HR) reactivity during trauma recall predicts PTSD symptom improvement and treatment dropout during Cognitive Processing Therapy (CPT) for PTSD. Participants were 142 women with PTSD secondary to interpersonal violence enrolled in one of two clinicals trials. HR reactivity reflected the mean increase in HR after listening to two 30-s scripts of the trauma memory prior to treatment. Linear mixed-effects models showed the effect of HR reactivity on change in total PTSD symptoms was not significant, but lower HR reactivity predicted less improvement in reexperiencing and avoidance and was associated with increased dropout. Findings suggest pretreatment physiological reactivity to the trauma memory may be a prognostic indicator of some elements of treatment response in CPT. Results tentatively support the importance of emotional activation during trauma recall in cognitive treatment of PTSD, though more research is needed to clarify how low HR reactivity impacts treatment. • Women with PTSD (n = 142) received 12 sessions of cognitive processing therapy (CPT). • Prior to treatment, heart rate reactivity (HRR) during trauma recall was measured. • Lower HRR predicted less improvement in reexperiencing and avoidance during CPT. • Lower HRR also predicted greater study and treatment dropout. • No association between pretreatment HRR and total PTSD symptom change was found. [ABSTRACT FROM AUTHOR]

Selenophosphate synthetase (SEPHS) plays an essential role in selenium metabolism. Two mammalian SEPHS paralogues, SEPHS1 and SEPHS2, share high sequence identity and structural homology with SEPHS. Here, we report nine individuals from eight families with developmental delay, growth and feeding problems, hypotonia, and dysmorphic features, all with heterozygous missense variants in SEPHS1. Eight of these individuals had a recurrent variant at amino acid position 371 of SEPHS1 (p.Arg371Trp, p.Arg371Gln, and p.Arg371Gly); seven of these variants were known to be de novo. Structural modeling and biochemical assays were used to understand the effect of these variants on SEPHS1 function. We found that a variant at residue Trp352 results in local structural changes of the C-terminal region of SEPHS1 that decrease the overall thermal stability of the enzyme. In contrast, variants of a solvent-exposed residue Arg371 do not impact enzyme stability and folding but could modulate direct protein-protein interactions of SEPSH1 with cellular factors in promoting cell proliferation and development. In neuronal SH-SY5Y cells, we assessed the impact of SEPHS1 variants on cell proliferation and ROS production and investigated the mRNA expression levels of genes encoding stress-related selenoproteins. Our findings provided evidence that the identified SEPHS1 variants enhance cell proliferation by modulating ROS homeostasis. Our study supports the hypothesis that SEPHS1 plays a critical role during human development and provides a basis for further investigation into the molecular mechanisms employed by SEPHS1. Furthermore, our data suggest that variants in SEPHS1 are associated with a neurodevelopmental disorder. SEPHS1 is in the selenocysteine biosynthetic pathway. We report nine individuals from eight families with developmental delay, growth and feeding problems, hypotonia, and dysmorphic features, all with heterozygous missense variants in SEPHS1. Our findings provide insight into the molecular pathogenesis of this neurodevelopmental disorder. [ABSTRACT FROM AUTHOR]

Tripartite ATP-independent periplasmic (TRAP) transporters are secondary-active transporters that receive their substrates via a soluble-binding protein to move bioorganic acids across bacterial or archaeal cell membranes. Recent cryo-electron microscopy (cryo-EM) structures of TRAP transporters provide a broad framework to understand how they work, but the mechanistic details of transport are not yet defined. Here we report the cryo-EM structure of the Haemophilus influenzae N-acetylneuraminate TRAP transporter (HiSiaQM) at 2.99 Å resolution (extending to 2.2 Å at the core), revealing new features. The improved resolution (the previous HiSiaQM structure is 4.7 Å resolution) permits accurate assignment of two Na+ sites and the architecture of the substrate-binding site, consistent with mutagenic and functional data. Moreover, rather than a monomer, the HiSiaQM structure is a homodimer. We observe lipids at the dimer interface, as well as a lipid trapped within the fusion that links the SiaQ and SiaM subunits. We show that the affinity (KD) for the complex between the soluble HiSiaP protein and HiSiaQM is in the micromolar range and that a related SiaP can bind HiSiaQM. This work provides key data that enhances our understanding of the 'elevator-with-an-operator' mechanism of TRAP transporters. [ABSTRACT FROM AUTHOR]