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Among outpatients with coronavirus disease 2019 (COVID-19) due to the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) δ (delta) variant who did and did not receive 2 vaccine doses at 7 days after symptom onset, there was no difference in viral shedding (cycle threshold difference 0.59, 95% CI, −4.68 to 3.50; P = .77) with SARS-CoV-2 cultured from 2 (7%) of 28 and 1 (4%) of 26 outpatients, respectively.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Returning genomic research results to family members raises complex questions. Genomic research on life-limiting conditions such as cancer, and research involving storage and reanalysis of data and specimens long into the future, makes these questions pressing. This author group, funded by an NIH grant, published consensus recommendations presenting a framework. This follow-up paper offers concrete guidance and tools for implementation. The group collected and analyzed relevant documents and guidance, including tools from the Clinical Sequencing Exploratory Research (CSER) Consortium. The authors then negotiated a consensus toolkit of processes and documents. That toolkit offers sample consent and notification documents plus decision flow-charts to address return of results to family of living and deceased participants, in adult and pediatric research. Core concerns are eliciting participant preferences on sharing results with family and on choice of a representative to make decisions about sharing after participant death.
Identifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention.
In total 287 participants aged 12–30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes.
At baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of ‘conversion’ to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania.
This study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.
The debate about how to manage individual research results and incidental findings in genetic and genomic research has focused primarily on what information, if any, to offer back to research participants. However, increasing controversy surrounds the question of whether researchers have any responsibility to offer a participant’s results (defined here to include both individual research results and incidental findings) to the participant’s relatives, including after the participant’s death. This question arises in multiple contexts, including when researchers discover a result with potentially important health implications for genetic relatives, when a participant’s relatives ask a researcher whether any research results about the participant have implications for their own health or reproductive planning, when a participant’s relative asks whether any of the participant’s results have implications for a child’s health, and when the participant is deceased and the participant’s relatives seek information about the participant’s genetic results in order to address their own health or reproductive concerns.
Background: Ependymomas are rare tumors of the central nervous system whose management is controversial. This population-based study of adults and children with ependymoma aims to (1) identify clinical and treatment-related factors that impact survival and (2) determine if postoperative radiotherapy (RT) can improve survival of patients with subtotal resection (STR) to levels similar to patients who had gross total resection (GTR). Methods: This retrospective population-based study evaluated 158 patients with ependymoma diagnosed between 1975-2007 in Alberta, Canada. Results: Younger patients (<7 years of age) were more likely to be diagnosed with grade III tumors compared with adults in whom grade I tumors were more common (p=0.003). Adults were more likely to have spinally located tumors compared to young children whose tumors were typically found in the brain. Overall, young children with ependymoma were more likely to die than older children or adults (p=0.001). An equivalent number of patients underwent GTR as compared with STR (48% vs 45%, respectively). Overall, older age, spinal tumor location, lower grade, and GTR were associated with improved progression free survival but only GTR was associated with significant improvement in overall survival. Median survival after STR and RT was 82 months compared with 122 months in patients who had GTR (p=0.0022). Conclusions: This is the first Canadian population-based analysis of patients with ependymoma including adults and children. Extent of resection appears to be the most important factor determining overall survival. Importantly, the addition of RT to patients initially treated with STR does not improve survival to levels similar to patients receiving GTR.
Although genetic epidemiological studies have confirmed increased rates of major depressive disorder among the relatives of people with bipolar affective disorder, no report has compared the clinical characteristics of depression between these two groups.
To compare clinical features of depressive episodes across participants with major depressive disorder and bipolar disorder from within bipolar disorder pedigrees, and assess the utility of a recently proposed probabilistic approach to distinguishing bipolar from unipolar depression. A secondary aim was to identify subgroups within the relatives with major depression potentially indicative of ‘genetic’ and ‘sporadic’ subgroups.
Patients with bipolar disorder types 1 and 2 (n = 246) and patients with major depressive disorder from bipolar pedigrees (n = 120) were assessed using the Diagnostic Interview for Genetic Studies. Logistic regression was used to identify distinguishing clinical features and assess the utility of the probabilistic approach. Hierarchical cluster analysis was used to identify subgroups within the major depressive disorder sample.
Bipolar depression was characterised by significantly higher rates of psychomotor retardation, difficulty thinking, early morning awakening, morning worsening and psychotic features. Depending on the threshold employed, the probabilistic approach yielded a positive predictive value ranging from 74% to 82%. Two clusters within the major depressive disorder sample were found, one of which demonstrated features characteristic of bipolar depression, suggesting a possible ‘genetic’ subgroup.
A number of previously identified clinical differences between unipolar and bipolar depression were confirmed among participants from within bipolar disorder pedigrees. Preliminary validation of the probabilistic approach in differentiating between unipolar and bipolar depression is consistent with dimensional distinctions between the two disorders and offers clinical utility in identifying patients who may warrant further assessment for bipolarity. The major depressive disorder clusters potentially reflect genetic and sporadic subgroups which, if replicated independently, might enable an improved phenotypic definition of underlying bipolarity in genetic analyses.
Gregory S. Schultz, Department of Obstetrics and Gynecology, University of Florida, Gainesville, Florida, USA,
Gloria A. Chin, Department of Surgery, University of Florida, Gainesville, Florida, USA,
Lyle Moldawer, Department of Surgery, University of Florida, Gainesville, Florida, USA,
Robert F. Diegelmann, Department of Biochemistry, Medical College of Virginia, Richmond, Virginia, USA
Acute wounds normally heal in an orderly and efficient manner, and progress smoothly through the four distinct, but overlapping phases of wound healing: haemostasis, inflammation, proliferation and remodelling (Figure 23.1). In contrast, chronic wounds will similarly begin the healing process, but will have prolonged inflammatory, proliferative, or remodelling phases, resulting in tissue fibrosis and in non-healing ulcers. The process of wound healing is complex and involves a variety of specialized cells, such as platelets, macrophages, fibroblasts, epithelial and endothelial cells. These cells interact with each other and with the extracellular matrix. In addition to the various cellular interactions, healing is also influenced by the action of proteins and glycoproteins, such as cytokines, chemokines, growth factors, inhibitors, and their receptors. Each stage of wound healing has certain milestones that must occur in order for normal healing to progress. In order to identify the differences inherent in chronic wounds that prevent healing, it is important to review the process of healing in normal wounds
PHASES OF ACUTE WOUND HEALING
Haemostasis occurs immediately following an injury. To prevent exsanguination, vasoconstriction occurs and platelets undergo activation, adhesion and aggregation at the site of injury. Platelets become activated when exposed to extravascular collagen (such as type I collagen), which they detect via specific integrin receptors, cell surface receptors that mediate a cell's interactions with the extracellular matrix. Once in contact with collagen, platelets release the soluble mediators (growth factors and cyclic AMP) and adhesive glycoproteins, which signal them to become sticky and aggregate.
This paper describes the analysis and the design of an integrated antenna on 0.13 µm SiGe BICMOS technology. A non-resonant dipole antenna integrated on SiGe is electromagnetically coupled to a radiating element reported on a printed circuit board (PCB) substrate. This integrated solution, also compatible with system in package (SIP) concept, provides significant improvements with respect to direct System On Chip (SoC) integration. The main objective of this SIP antenna lies on the optimization of integrated millimeter wave front-ends modules, considering the immediate antenna environment (especially the lossy substrate and technological dielectric/metallic levels), in order to achieve performances compatible with short range radar specifications at 79–81 GHz. One solution, using a RT/Rogers Duroid 6006 PCB (er = 6, thickness h = 127 µm), is presented, providing a 2.93 dBi gain, and 45% radiation efficiency antenna.
The UV spectra predicted by LTE line-blanketed model atmosphere calculations are used to obtain a preliminary calibration of FWHM vs. v for UV lines, which is then used to determine the values of v sin i for four O-type stars in the Small Magellanic Cloud.
A short form of the Minnesota Multiphasic Personality Inventory was administered to 146 clinical patients who were assigned to one of four groups: Group I, tinnitus only; Group II, hearing loss and tinnitus, tinnitus primary; Group III, hearing loss and tinnitus, hearing loss primary; and Group IV, hearing loss only. The purpose of the study was to determine whether there were measurable characteristics unique to the tinnitus patient. Elevations were noted for all four groups on Scales 8, 6, 3, and 2, showing significant differences between the groups who suffered from tinnitus as opposed to those whose primary complaint was hearing loss. The tinnitus patients, especially those with only tinnitus, had social adjustment problems that were not evidenced for patients with impaired hear-ing. Indications are that the patient with an inveterate hearing loss is better able to cope with tinnitus than the patient who is suddenly and unaccountably afflicted with tinnitus.