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Using the dual-pathway framework (Beach et al., 2022a), we tested a Neuro-immune Network (NIN) hypothesis: i.e., that chronically elevated inflammatory processes may have delayed (i.e., incubation) effects on young adult substance use, leading to negative health outcomes. In a sample of 449 participants in the Family and Community Health Study who were followed from age 10 to age 29, we examined a non-self-report index of young adult elevated alcohol consumption (EAC). By controlling self-reported substance use at the transition to adulthood, we were able to isolate a significant delayed (incubation) effect from childhood exposure to danger to EAC (β = −.157, p = .006), which contributed to significantly worse aging outomes. Indirect effects from danger to aging outcomes via EAC were: GrimAge (IE = .010, [.002, .024]), Cardiac Risk (IE = −.004, [−.011, −.001]), DunedinPACE (IE = .002, [.000, .008]). In exploratory analyses we examined potential sex differences in effects, showing slightly stronger incubation effects for men and slightly stronger effects of EAC on aging outcomes for women. Results support the NIN hypothesis that incubation of immune pathway effects contributes to elevated alcohol consumption in young adulthood, resulting in accelerated aging and elevated cardiac risk outcomes via health behavior.
Diagnosis in psychiatry faces familiar challenges. Validity and utility remain elusive, and confusion regarding the fluid and arbitrary border between mental health and illness is increasing. The mainstream strategy has been conservative and iterative, retaining current nosology until something better emerges. However, this has led to stagnation. New conceptual frameworks are urgently required to catalyze a genuine paradigm shift.
Methods
We outline candidate strategies that could pave the way for such a paradigm shift. These include the Research Domain Criteria (RDoC), the Hierarchical Taxonomy of Psychopathology (HiTOP), and Clinical Staging, which all promote a blend of dimensional and categorical approaches.
Results
These alternative still heuristic transdiagnostic models provide varying levels of clinical and research utility. RDoC was intended to provide a framework to reorient research beyond the constraints of DSM. HiTOP began as a nosology derived from statistical methods and is now pursuing clinical utility. Clinical Staging aims to both expand the scope and refine the utility of diagnosis by the inclusion of the dimension of timing. None is yet fit for purpose. Yet they are relatively complementary, and it may be possible for them to operate as an ecosystem. Time will tell whether they have the capacity singly or jointly to deliver a paradigm shift.
Conclusions
Several heuristic models have been developed that separately or synergistically build infrastructure to enable new transdiagnostic research to define the structure, development, and mechanisms of mental disorders, to guide treatment and better meet the needs of patients, policymakers, and society.
Investigations are conducted on the effect of wall proximity on the flow around a cylinder under an axial magnetic field, using the electrical potential probe technology to measure the velocity of liquid metal flow. The study focused on the impact of the inlet velocity of the fluid, the magnetic field and wall proximity on the characteristics of velocity fields, particularly on the vortex-shedding mode. Based on different magnitudes of the magnetic field and the distance from the cylinder to the duct wall, three types of vortex-shedding modes are identified, (I) shear layer oscillation state, (II) quasi-two-dimensional vortex-shedding states and (III) transition of the magnetohydrodynamic to hydrodynamic Kármán street. The transitions between these modes are analysed in detail. The experimental results show that the weak wall-proximity effect leads to the formation of the Kármán vortex street, while a reverse Kármán vortex street and secondary vortices emerge under a strong wall-proximity effect. It is noticed that the Kelvin–Helmholtz instability drives vortex shedding under regime I, leading to an increase in the Strouhal number (St) with stronger magnetic fields. Additionally, under a strong axial magnetic field, the wall-proximity effect (‘Shercliff layer effect’) promotes the instability of shear layers on both sides of the cylinder. These unique coupling effects are validated by variations in modal coefficients and energy proportions under different vortex-shedding regimes using the proper orthogonal decomposition method.
Exploring the neural basis related to different mood states is a critical issue for understanding the pathophysiology underlying mood switching in bipolar disorder (BD), but research has been scarce and inconsistent.
Methods
Resting-state functional magnetic resonance imaging data were acquired from 162 patients with BD: 33 (hypo)manic, 64 euthymic, and 65 depressive, and 80 healthy controls (HCs). The differences of large-scale brain network functional connectivity (FC) between the four groups were compared and correlated with clinical characteristics. To validate the generalizability of our findings, we recruited a small longitudinal independent sample of BD patients (n = 11). In addition, we examined topological nodal properties across four groups as exploratory analysis.
Results
A specific strengthened pattern of network FC, predominantly involving the default mode network (DMN), was observed in (hypo)manic patients when compared with HCs and bipolar patients in other mood states. Longitudinal observation revealed an increase in several network FCs in patients during (hypo)manic episode. Both samples evidenced an increase in the FC between the DMN and ventral attention network, and between the DMN and limbic network (LN) related to (hypo)mania. The altered network connections were correlated with mania severity and positive affect. Bipolar depressive patients exhibited decreased FC within the LN compared with HCs. The exploratory analysis also revealed an increase in degree in (hypo)manic patients.
Conclusions
Our findings identify a distributed pattern of large-scale network disturbances in the unique context of (hypo)mania and thus provide new evidence for our understanding of the neural mechanism of BD.
Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to prespecify study design and analysis plans; it addresses a wide range of guidance within a single framework. By supporting the transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on prespecified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers; three companion papers demonstrate applications of the Causal Roadmap for specific use cases.
In March 2018, the US Food and Drug Administration (FDA), US Centers for Disease Control and Prevention, California Department of Public Health, Los Angeles County Department of Public Health and Pennsylvania Department of Health initiated an investigation of an outbreak of Burkholderia cepacia complex (Bcc) infections. Sixty infections were identified in California, New Jersey, Pennsylvania, Maine, Nevada and Ohio. The infections were linked to a no-rinse cleansing foam product (NRCFP), produced by Manufacturer A, used for skin care of patients in healthcare settings. FDA inspected Manufacturer A's production facility (manufacturing site of over-the-counter drugs and cosmetics), reviewed production records and collected product and environmental samples for analysis. FDA's inspection found poor manufacturing practices. Analysis by pulsed-field gel electrophoresis confirmed a match between NRCFP samples and clinical isolates. Manufacturer A conducted extensive recalls, FDA issued a warning letter citing the manufacturer's inadequate manufacturing practices, and federal, state and local partners issued public communications to advise patients, pharmacies, other healthcare providers and healthcare facilities to stop using the recalled NRCFP. This investigation highlighted the importance of following appropriate manufacturing practices to minimize microbial contamination of cosmetic products, especially if intended for use in healthcare settings.
Since 2009, mid-upper arm circumference (MUAC) has become an accepted measure for screening children for acute malnutrition and determining eligibility for services to manage acute malnutrition. Use of MUAC has increased the reach and enhanced the quality of community-based management of acute malnutrition services. Increasingly, MUAC is also used to assess nutritional status and eligibility for nutrition support among adolescents and adults, including pregnant and lactating women and HIV and TB clients. However, globally recognised cut-offs have not been established to classify malnutrition among adults using MUAC. Therefore, different countries and programmes use different MUAC cut-offs to determine eligibility for programme services. Patient monitoring guidelines provided by WHO for country adaptation to support the integrated management of adult illness do not include MUAC, in part because guidance does not exist about what MUAC cut-off should trigger further action.
To determine if a global mid-upper arm circumference (MUAC) cut-off can be established to classify underweight in adults (men and non-pregnant women).
Design:
We conducted an individual participant data meta-analysis (IPDMA) to explore the sensitivity (SENS) and specificity (SPEC) of various MUAC cut-offs for identifying underweight among adults (defined as BMI < 18·5 kg/m2). Measures of diagnostic accuracy were determined every 0·5 cm across MUAC values from 19·0 to 26·5 cm. A bivariate random effects model was used to jointly estimate SENS and SPEC while accounting for heterogeneity between studies. Various subgroup analyses were performed.
Setting:
Twenty datasets from Africa, South Asia, Southeast Asia, North America and South America were included.
Participants:
All eligible participants from the original datasets were included.
Results:
The total sample size was 13 835. Mean age was 32·6 years and 65 % of participants were female. Mean MUAC was 25·7 cm, and 28 % of all participants had low BMI (<18·5 kg/m2). The area under the receiver operating characteristic curve for the pooled dataset was 0·91 (range across studies 0·61–0·98). Results showed that MUAC cut-offs in the range of ≤23·5 to ≤25·0 cm could serve as an appropriate screening indicator for underweight.
Conclusions:
MUAC is highly discriminatory in its ability to distinguish adults with BMI above and below 18·5 kg/m2. This IPDMA is the first step towards determining a global MUAC cut-off for adults. Validation studies are needed to determine whether the proposed MUAC cut-off of 24 cm is associated with poor functional outcomes.
Over the last two decades application of the clinical staging model in mental health has been advocated to improve diagnosis, intervention, prediction of illness trajectory and, ultimately, outcomes. The model offers a substantive advance for mental health care as it goes beyond traditional fixed categories to incorporate a stepwise continuum to guide much more appropriate treatment planning and prognosis. In this chapter, an overview of this advanced type of clinical staging is provided. With its focus on the continuum of mental illness, and underlying differential trajectories of illness progression that are not well captured by current categorical diagnostic practice, staging addresses the key limitations of traditional diagnostic categorical systems. It proposes that effective, safe and timely stage-specific treatments can be implemented to inhibit and delay illness onset and progression. It also enables biomarkers to be analysed according not only to syndrome but also stage. The model is supported by a number of clinical, longitudinal and neurobiological studies. Whilst clinical staging has clear and immediate potential benefits, further research investigating risk and protective factors and treatment outcomes across different stages and the creation of tools that clinicians can routinely use will determine the ultimate utility and value of the model.
There is increasing evidence of an association between depressive symptoms and mild cognitive impairment (MCI) in cross-sectional studies, but the longitudinal association between depressive symptoms and risk of MCI onset is less clear. The authors investigated whether baseline symptom severity of depression was predictive of time to onset of symptoms of MCI.
Method:
These analyses included 300 participants from the BIOCARD study, a cohort of individuals who were cognitively normal at baseline (mean age = 57.4 years) and followed for up to 20 years (mean follow-up = 2.5 years). Depression symptom severity was measured using the Hamilton Depression Scale (HAM-D). The authors assessed the association between dichotomous and continuous HAM-D and time to onset of MCI within 7 years versus after 7 years from baseline (reflecting the mean time from baseline to onset of clinical symptoms in the cohort) using Cox regression models adjusted for gender, age, and education.
Results:
At baseline, subjects had a mean HAM-D score of 2.2 (SD = 2.8). Higher baseline HAM-D scores were associated with an increased risk of progression from normal cognition to clinical symptom onset ≤ 7 years from baseline (p = 0.043), but not with progression > 7 years from baseline (p = 0.194). These findings remained significant after adjustment for baseline cognition.
Conclusions:
These results suggest that low levels of depressive symptoms may be predictive of clinical symptom onset within approximately 7 years among cognitively normal individuals and may be useful in identifying persons at risk for MCI due to Alzheimer’s disease.
There is a growing body of literature describing the characteristics of patients who plan for the end of life, but little research has examined how caregivers influence patients' advance care planning (ACP). The purpose of this study was to examine how patient and caregiver characteristics are associated with advance directive (AD) completion among patients diagnosed with a terminal illness. We defined AD completion as having completed a living will and/or identified a healthcare power of attorney.
Method:
A convenience sample of 206 caregiver–patient dyads was included in the study. All patients were diagnosed with an advanced life-limiting illness. Trained research nurses administered surveys to collect information on patient and caregiver demographics (i.e., age, sex, race, education, marital status, and individual annual income) and patients' diagnoses and completion of AD. Multivariate logistic regression was employed to model predictors for patients' AD completion.
Results:
Over half of our patient sample (59%) completed an AD. Patients who were older, diagnosed with amyotrophic lateral sclerosis, and with a caregiver who was Caucasian or declined to report an income level were more likely to have an AD in place.
Significance of results:
Our results suggest that both patient and caregiver characteristics may influence patients' decisions to complete an AD at the end of life. When possible, caregivers should be included in advance care planning for patients who are terminally ill.
Despite substantial research, uncertainty remains about the clinical and etiological heterogeneity of major depression (MD). Can meaningful and valid subtypes be identified and would they be stable cross-culturally?
Method.
Symptoms at their lifetime worst depressive episode were assessed at structured psychiatric interview in 6008 women of Han Chinese descent, age ⩾30 years, with recurrent DSM-IV MD. Latent class analysis (LCA) was performed in Mplus.
Results.
Using the nine DSM-IV MD symptomatic A criteria, the 14 disaggregated DSM-IV criteria and all independently assessed depressive symptoms (n = 27), the best LCA model identified respectively three, four and six classes. A severe and non-suicidal class was seen in all solutions, as was a mild/moderate subtype. An atypical class emerged once bidirectional neurovegetative symptoms were included. The non-suicidal class demonstrated low levels of worthlessness/guilt and hopelessness. Patterns of co-morbidity, family history, personality, environmental precipitants, recurrence and body mass index (BMI) differed meaningfully across subtypes, with the atypical class standing out as particularly distinct.
Conclusions.
MD is a clinically complex syndrome with several detectable subtypes with distinct clinical and demographic correlates. Three subtypes were most consistently identified in our analyses: severe, atypical and non-suicidal. Severe and atypical MD have been identified in multiple prior studies in samples of European ethnicity. Our non-suicidal subtype, with low levels of guilt and hopelessness, may represent a pathoplastic variant reflecting Chinese cultural influences.
The symptoms of major depression (MD) are clinically diverse. Do they form coherent factors that might clarify the underlying nature of this important psychiatric syndrome?
Method
Symptoms at lifetime worst depressive episode were assessed at structured psychiatric interview in 6008 women of Han Chinese descent, age ⩾30 years with recurrent DSM-IV MD. Exploratory factor analysis (EFA) and confirmatoryfactor analysis (CFA) were performed in Mplus in random split-half samples.
Results
The preliminary EFA results were consistently supported by the findings from CFA. Analyses of the nine DSM-IV MD symptomatic A criteria revealed two factors loading on: (i) general depressive symptoms; and (ii) guilt/suicidal ideation. Examining 14 disaggregated DSM-IV criteria revealed three factors reflecting: (i) weight/appetite disturbance; (ii) general depressive symptoms; and (iii) sleep disturbance. Using all symptoms (n = 27), we identified five factors that reflected: (i) weight/appetite symptoms; (ii) general retarded depressive symptoms; (iii) atypical vegetative symptoms; (iv) suicidality/hopelessness; and (v) symptoms of agitation and anxiety.
Conclusions
MD is a clinically complex syndrome with several underlying correlated symptom dimensions. In addition to a general depressive symptom factor, a complete picture must include factors reflecting typical/atypical vegetative symptoms, cognitive symptoms (hopelessness/suicidal ideation), and an agitated symptom factor characterized by anxiety, guilt, helplessness and irritability. Prior cross-cultural studies, factor analyses of MD in Western populations and empirical findings in this sample showing risk factor profiles similar to those seen in Western populations suggest that our results are likely to be broadly representative of the human depressive syndrome.
Previous studies support Beck's cognitive model of vulnerability to depression. However, the relationship between his cognitive triad and other clinical features and risk factors among those with major depression (MD) has rarely been systematically studied.
Method
The three key cognitive symptoms of worthlessness, hopelessness and helplessness were assessed during their lifetime worst episode in 1970 Han Chinese women with recurrent MD. Diagnostic and other risk factor information was assessed at personal interview. Odds ratios (ORs) were calculated by logistic regression.
Results
Compared to patients who did not endorse the cognitive trio, those who did had a greater number of DSM-IV A criteria, more individual depressive symptoms, an earlier age at onset, a greater number of episodes, and were more likely to meet diagnostic criteria for melancholia, postnatal depression, dysthymia and anxiety disorders. Hopelessness was highly related to all the suicidal symptomatology, with ORs ranging from 5.92 to 6.51. Neuroticism, stressful life events (SLEs) and a protective parental rearing style were associated with these cognitive symptoms.
Conclusions
During the worst episode of MD in Han Chinese women, the endorsement of the cognitive trio was associated with a worse course of depression and an increased risk of suicide. Individuals with high levels of neuroticism, many SLEs and high parental protectiveness were at increased risk for these cognitive depressive symptoms. As in Western populations, symptoms of the cognitive trio appear to play a central role in the psychopathology of MD in Chinese women.
The influence of fluid droplet properties on the droplet-on-demand jetting of a Newtonian model fluid (water–isopropanol–ethylene glycol ternary system) has been studied. The composition of the fluid was adjusted to investigate how the Ohnesorge number ($\mathit{Oh}$) influences droplet formation (morphology and speed) by a microfabricated short-channel shear-mode piezoelectric transducer. The fluid space for satellite-free single droplet formation was indeed found to be bound by upper and lower $\mathit{Oh}$ limits, but these shift approximately linearly with the piezo pulse voltage amplitude ${V}_{o} $, which has a stronger influence on jetting characteristics than pulse length. Therefore the jettable fluid space can be depicted on a ${V}_{o} {{\ndash}}\mathit{Oh}$ diagram. Satellite-free droplets of the model fluid can be jetted over a wide $\mathit{Oh}$ range, at least 0.025 to 0.5 (corresponding to $Z= {\mathit{Oh}}^{\ensuremath{-} 1} $ of 40 to 2), by adjusting ${V}_{o} $ appropriately. Air drag was found to dominate droplet flight, as may be expected. This can be accurately modelled to yield droplet formation time, which turned out to be $20\text{{\ndash}} 30~\lrm{\ensuremath{\mu}} \mathrm{s} $ under a wide range of jetting conditions. The corresponding initial droplet speed was found to vary linearly with ${V}_{o} $, with a fluid-dependent threshold but a fluid-independent slope, and a minimum speed of about $2~\mathrm{m} ~{\mathrm{s} }^{\ensuremath{-} 1} $. This suggests the existence of iso-velocity lines that run substantially parallel to the lower jetting boundary in the ${V}_{o} {{\ndash}}\mathit{Oh}$ diagram.
The NGVS is mapping the Virgo Cluster with a depth making possible to detect very low surface brightness (LSB) structures, such as faint dwarf galaxies. To extract these from just above the sky noise and make statistical studies of their properties, we use the software MARSIAA (MARkovian Software for Image Analysis in Astronomy). This segmentation software uses a Markovian approach to classify pixels and identify low-surface brightness structures.