Morphological control of bundled actin networks subject to fixed-mass depletion.

Depletion interactions are thought to significantly contribute to the organization of intracellular structures in the crowded cytosol. The strength of depletion interactions depends on physical parameters such as the depletant number density and the depletant size ratio. Cells are known to dynamically regulate these two parameters by varying the copy number of proteins of a wide distribution of sizes. However, mammalian cells are also known to keep the total protein mass density remarkably constant, to within 0.5% throughout the cell cycle. We thus ask how the strength of depletion interactions varies when the total depletant mass is held fixed, a.k.a. fixed-mass depletion. We answer this question via scaling arguments, as well as by studying depletion effects on networks of reconstituted semiflexible actin in silico and in vitro. We examine the maximum strength of the depletion interaction potential U∗ as a function of q, the size ratio between the depletant and the matter being depleted. We uncover a scaling relation U∗ ∼ qζ for two cases: fixed volume fraction φ and fixed mass density ρ. For fixed volume fraction, we report ζ < 0. For the fixed mass density case, we report ζ > 0, which suggests that the depletion interaction strength increases as the depletant size ratio is increased. To test this prediction, we prepared our filament networks at fixed mass concentrations with varying sizes of the depletant molecule poly(ethylene glycol) (PEG). We characterize the depletion interaction strength in our simulations via the mesh size. In experiments, we observe two distinct actin network morphologies, which we call weakly bundled and strongly bundled. We identify a mass concentration where different PEG depletant sizes lead to weakly bundled or strongly bundled morphologies. For these conditions, we find that the mesh size and intra-bundle spacing between filaments across the different morphologies do not show significant differences, while the dynamic light scattering relaxation time and storage modulus between the two states do show significant differences. Our results demonstrate the ability to tune actin network morphology and mechanics by controlling depletant size and give insights into depletion interaction mechanisms under the fixed-depletant-mass constraint relevant to living cells.

Assembling Inorganic Nanocrystal Gels.

Inorganic nanocrystal gels retain distinct properties of individual nanocrystals while offering tunable, network-structure-dependent characteristics. We review different mechanisms for assembling gels from colloidal nanocrystals including (1) controlled destabilization, (2) direct bridging, (3) depletion, as well as linking mediated by (4) coordination bonding or (5) dynamic covalent bonding, and we highlight how each impacts gel properties. These approaches use nanocrystal surface chemistry or the addition of small molecules to mediate inter-nanocrystal attractions. Each method offers advantages in terms of gel stability, reversibility, or tunability and presents new opportunities for the design of reconfigurable materials and fueled assemblies.

Colloidal Nanocrystal Gels from Thermodynamic Principles.

Gels assembled from solvent-dispersed nanocrystals are of interest for functional materials because they promise the opportunity to retain distinctive properties of individual nanocrystals combined with tunable, structure-dependent collective behavior. By incorporating stimuli-responsive components, these materials could also be dynamically reconfigured between structurally distinct states. However, nanocrystal gels have so far been formed mostly through irreversible aggregation, which has limited the realization of these possibilities. Meanwhile, gelation strategies for larger colloidal microparticles have been developed using reversible physical or chemical interactions. These approaches have enabled the experimental navigation of theoretically predicted phase diagrams, helping to establish an understanding of how thermodynamic behavior can guide gel formation in these materials. However, the translation of these principles to the nanoscale poses both practical and fundamental challenges. The molecules guiding assembly can no longer be safely assumed to be vanishingly small compared to the particles nor large compared to the solvent.In this Account, we discuss recent progress toward the assembly of tunable nanocrystal gels using two strategies guided by equilibrium considerations: (1) reversible chemical bonding between functionalized nanocrystals and difunctional linker molecules and (2) nonspecific, polymer-induced depletion attractions. The effective nanocrystal attractions, mediated in both approaches by a secondary molecule, compete against stabilizing repulsions to promote reversible assembly. The structure and properties of the nanocrystal gels are controlled microscopically by the design of the secondary molecule and macroscopically by its concentration. This mode of control is compelling because it largely decouples nanocrystal synthesis and functionalization from the design of interactions that drive assembly. Statistical thermodynamic theory and computer simulation have been applied to simple models that describe the bonding motifs in these assembling systems, furnish predictions for conditions under which gelation is likely to occur, and suggest strategies for tuning and disassembling the gel networks. Insights from these models have guided experimental realizations of reversible gels with optical properties in the infrared range that are sensitive to the gel structure. This process avoids time-consuming and costly trial-and-error experimental investigations to accelerate the development of nanocrystal gel assemblies.These advances highlight the need to better understand interactions between nanocrystals, how interactions give rise to gel structure, and properties that emerge. Such an understanding could suggest new approaches for creating stimuli-responsive and dissipative assembled materials whose properties are tunable on demand through directed reconfiguration of the underlying gel microstructure. It may also make nanocrystal gels amenable to computationally guided design using inverse methods to rapidly optimize experimental parameters for targeted functionalities.

Treatment Response of Transcranial Magnetic Stimulation in Intellectually Capable Youth and Young Adults with Autism Spectrum Disorder: A Systematic Review and Meta-Analysis.

To examine current clinical research on the use of transcranial magnetic stimulation (TMS) in the treatment of pediatric and young adult autism spectrum disorder in intellectually capable persons (IC-ASD). We searched peer-reviewed international literature to identify clinical trials investigating TMS as a treatment for behavioral and cognitive symptoms of IC-ASD. We identified sixteen studies and were able to conduct a meta-analysis on twelve of these studies. Seven were open-label or used neurotypical controls for baseline cognitive data, and nine were controlled trials. In the latter, waitlist control groups were often used over sham TMS. Only one study conducted a randomized, parallel, double-blind, and sham controlled trial. Favorable safety data was reported in low frequency repetitive TMS, high frequency repetitive TMS, and intermittent theta burst studies. Compared to TMS research of other neuropsychiatric conditions, significantly lower total TMS pulses were delivered in treatment and neuronavigation was not regularly utilized. Quantitatively, our multivariate meta-analysis results report improvement in cognitive outcomes (pooled Hedges' g = 0.735, 95% CI = 0.242, 1.228; p = 0.009) and primarily Criterion B symptomology of IC-ASD (pooled Hedges' g = 0.435, 95% CI = 0.359, 0.511; p < 0.001) with low frequency repetitive TMS to the dorsolateral prefrontal cortex. The results of our systematic review and meta-analysis data indicate that TMS may offer a promising and safe treatment option for pediatric and young adult patients with IC-ASD. However, future work should include use of neuronavigation software, theta burst protocols, targeting of various brain regions, and robust study design before clinical recommendations can be made.

How Frequent Is Switching From an Initial Stimulant Family to the Alternative One in the Clinical Setting?: A Pilot Study of 49 Consecutively Referred Medication-Naive Adults With Attention-Deficit/Hyperactivity Disorder.

PURPOSE/BACKGROUND: This study aimed to evaluate the frequency of needing to switch the initial treatment of a stimulant to the alternative family in newly referred, medication-naive adults with attention-deficit/hyperactivity disorder (ADHD) initiating treatment with stimulants. METHODS/PROCEDURES: Subjects were 49 unmedicated adults (18-45 years old) with Diagnostic and Statistical Manual of Disorders (Fifth Edition) ADHD who initiated treatment with a stimulant. Before the clinical assessment with an expert clinician, participants completed the Adult Self-Report, Behavior Rating Inventory of Executive Function-Adult Version, Emotional Dysregulation Subscale of the Barkley Current Behavior Scale-Self-report, and Mind Wandering Questionnaire. The rate of switching was examined using information from the electronic medical record for up to three clinical follow-up visits. Comparisons were made between those who did and did not need to switch on baseline demographic and clinical characteristics. FINDINGS/RESULTS: Sixty-seven percent of ADHD patients were initially prescribed a methylphenidate product, and 33%, an amphetamine product. Forty-one percent of ADHD patients needed to switch from their initially prescribed stimulant family within 90 days of initiating treatment because of poor tolerability. Whereas the rate of switching was significantly higher in those initially prescribed methylphenidate, the rate of patients who required changes in formulation (long- to short-acting and vice versa) or additional antianxiety or antidepressant treatment ("strugglers") was higher in those taking amphetamine. Switchers were more impaired on the Adult Self-Report Intrusive scale, whereas nonswitchers were more impaired on the Behavior Rating Inventory of Executive Function Inhibit and Task Monitor scales. However, these findings were small and of unclear clinical significance. IMPLICATIONS/CONCLUSIONS: Forty-one percent of medication-naive adults with ADHD initiating stimulant treatment required a switch from the initially prescribed stimulant family to the alternative one because of poor tolerability. Switching could not be adequately predicted by baseline demographic or clinical characteristics. These findings call for improved efforts to help identify predictors of response to stimulant treatment in adults with ADHD to avoid unnecessary delays in identifying a safe and effective treatment for these patients.

Rates of switching stimulants in consecutively referred medication naïve adults with ADHD.

OBJECTIVE: To evaluate the frequency and correlates of needing to switch the initial treatment with a stimulant medication to the alternative family in newly referred, untreated adults with ADHD initiating treatment. METHODS: Subjects were consecutively referred unmedicated adults with DSM-5 ADHD who initiated stimulant treatment. Before assessment with an expert clinician, participants completed a battery of self-report measures to assess psychopathology, executive functioning, emotional dysregulation, and mind wandering. The rate of switching was examined using information from electronic medical records for up to three clinical follow-up visits. Those who did and did not need to switch were compared on baseline demographic and clinical characteristics. RESULTS: Twenty-four percent (N = 21/86) of ADHD patients needed to switch from their initially prescribed stimulant family within 60 days of initiating treatment due to poor tolerability. While the rate of switching was significantly higher in those initially prescribed MPH, the rate of patients requiring changes in formulation or additional antianxiety or antidepressant treatment was higher in those taking AMPH. There were some hints about predictive risk factors for switching by the presence of emotional dysregulation and depressive symptoms, depending on age and sex. CONCLUSIONS: These findings call for improved efforts to help identify predictors of response to stimulant treatment in adults with ADHD to avoid unnecessary delays in identifying safe and effective treatments for these patients.

Universal Gelation of Metal Oxide Nanocrystals via Depletion Attractions.

Nanocrystal gelation provides a powerful framework to translate nanoscale properties into bulk materials and to engineer emergent properties through the assembled microstructure. However, many established gelation strategies rely on chemical reactions and specific interactions, e.g., stabilizing ligands or ions on the nanocrystals' surfaces, and are therefore not easily transferable. Here, we report a general gelation strategy via nonspecific and purely entropic depletion attractions applied to three types of metal oxide nanocrystals. The gelation thresholds of two compositionally distinct spherical nanocrystals agree quantitatively, demonstrating the adaptability of the approach for different chemistries. Consistent with theoretical phase behavior predictions, nanocrystal cubes form gels at a lower polymer concentration than nanocrystal spheres, allowing shape to serve as a handle to control gelation. These results suggest that the fundamental underpinnings of depletion-driven assembly, traditionally associated with larger colloidal particles, are also applicable at the nanoscale.

Surface-Enhanced Infrared Absorption Spectroscopy by Resonant Vibrational Coupling with Plasmonic Metal Oxide Nanocrystals.

Coupling between plasmonic resonances and molecular vibrations in nanocrystals (NCs) offers a promising approach for detecting molecules at low concentrations and discerning their chemical identities. Metallic NC superlattices can enhance vibrational signals under far-field detection by generating a myriad of intensified electric field hot spots between the NCs. Yet, their effectiveness is limited by the fixed electron concentration dictated by the metal composition and inefficient hot spot creation due to the large mode volume. Doped metal oxide NCs, such as tin-doped indium oxide (ITO), could overcome these limitations by enabling broad tunability of resonance frequencies in the mid-infrared range through independent variation of size and doping concentration. This study investigates the potential of close-packed ITO NC monolayers for surface-enhanced infrared absorption by quantifying trends in the coupling between their plasmon modes and various molecular vibrations. We show that maximum vibrational signal intensity occurs in monolayers composed of larger, more highly doped NCs, where the plasmon resonance peak lies at higher frequency than the molecular vibration. Using finite element and mutual polarization methods, we establish that near-field enhancement is stronger on the low-frequency side of the plasmon resonance and for more strongly coupled plasmonic NCs, thus rationalizing the design rules we experimentally uncovered. Our results can guide the development of optimal metal oxide NC-based superstructures for sensing target molecules or modifying their chemical properties through vibrational coupling.

Wavelength Tunable Infrared Perfect Absorption in Plasmonic Nanocrystal Monolayers.

The ability to efficiently absorb light in ultrathin (subwavelength) layers is essential for modern electro-optic devices, including detectors, sensors, and nonlinear modulators. Tailoring these ultrathin films' spectral, spatial, and polarimetric properties is highly desirable for many, if not all, of the above applications. Doing so, however, often requires costly lithographic techniques or exotic materials, limiting scalability. Here we propose, demonstrate, and analyze a mid-infrared absorber architecture leveraging monolayer films of nanoplasmonic colloidal tin-doped indium oxide nanocrystals (ITO NCs). We fabricate a series of ITO NC monolayer films using the liquid-air interface method; by synthetically varying the Sn dopant concentration in the NCs, we achieve spectrally selective perfect absorption tunable between wavelengths of two and five micrometers. We achieve monolayer thickness-controlled coupling strength tuning by varying NC size, allowing access to different coupling regimes. Furthermore, we synthesize a bilayer film that enables broadband absorption covering the entire midwave IR region (λ = 3-5 µm). We demonstrate a scalable platform, with perfect absorption in monolayer films only hundredths of a wavelength in thickness, enabling strong light-matter interaction, with potential applications for molecular detection and ultrafast nonlinear optical applications.

Neural and Cognitive Predictors of Stimulant Treatment Efficacy in Medication-Naïve ADHD Adults: A Pilot Diffusion Tensor Imaging Study.

OBJECTIVE: Stimulant medications are the main treatment for Attention Deficit Hyperactivity Disorder (ADHD), but overall treatment efficacy in adults has less than a 60% response rate. This study aimed to identify neural and cognitive markers predictive of longitudinal improvement in response to stimulant treatment in drug-naïve adults with ADHD. METHOD: We used diffusion tensor imaging (DTI) and executive function measures with 36 drug-naïve adult ADHD patients in a prospective study design. RESULTS: Structural connectivity (measured by fractional anisotropy, FA) in striatal regions correlated with ADHD clinical symptom improvement following stimulant treatment (amphetamine or methylphenidate) in better medication responders. A significant positive correlation was also found between working memory performance and stimulant-related symptom improvement. Higher pre-treatment working memory scores correlated with greater response. CONCLUSION: These findings provide evidence of pre-treatment neural and behavioral markers predictive of longitudinal treatment response to stimulant medications in adults with ADHD.

Growth Trajectories in Stimulant-Treated Children Ages 6 to 12: An Electronic Medical Record Analysis.

OBJECTIVE: The aim of this study was to evaluate growth trajectories in stimulant-exposed and stimulant-unexposed children using electronic medical record data from a large health care organization attending to moderating effects of the magnitude of exposure to stimulants, sex, and race. METHODS: Weight, height, body mass index (BMI), prescription, and sociodemographic information were extracted from the electronic medical records of a large health care organization. Included were children who were 6 to 12 years at the time they were receiving stimulants with a concurrent growth assessment (index assessment) plus 1 to 4 years of additional growth assessments thereafter. Non-attention-deficit/hyperactivity disorder (ADHD) children who were unexposed to stimulants were age and sex matched to those exposed. Stimulant exposure was examined as the total number of months with stimulant prescriptions, percentage of follow-up time exposed to stimulants, and cumulative stimulant dose. RESULTS: Our sample consisted of 323 children exposed to stimulants with available growth data and 1615 unexposed children. Small but significant decreases in height trajectories were found over time in exposed children compared with those unexposed. Weight and BMI trajectories decreased in the first year of follow-up with stabilization and increased thereafter. Growth trajectory effects were largest in girls (height, weight, and BMI), White children (weight), and children with more total stimulant exposure (weight). CONCLUSION: This comprehensive analysis of an ecologically informative sample attending to key covariates of the magnitude of exposure to stimulants, sex, and race extends previous findings, showing that effects on growth trajectories are small and do not appear to pose a significant clinical concern for most children with ADHD treated with stimulants from childhood onto adolescent years.

Further Evidence of an Association Between a Positive Child Behavior Checklist-Bipolar Profile and a Diagnosis of Pediatric Bipolar Disorder: A Meta-Analysis.

Background: Previous research has found that a unique profile of the Child Behavior Checklist comprising of aggregate elevations of the Attention, Anxiety/Depression and Aggression scales (A-A-A profile, CBCL-Bipolar (BP) profile, CBCL-Dysregulation profile (DP); henceforth CBCL-BP/DP profile) is associated with a clinical diagnosis of pediatric bipolar (BP) disorder. Objective: The main aim of the study is to evaluate the strength of the association between the CBCL-BP/DP profile and the clinical diagnosis of pediatric BP disorder through a meta-analysis. Methods: A literature search was performed to identify studies that examined the association between a positive CBCL-BP/DP profile and a clinical diagnosis of pediatric BP disorder. The meta-analyses first examined studies assessing the rates of a positive CBCL-BP/DP profile in youth with BP disorder versus those with 1) ADHD, anxiety/depression, or disruptive behavior disorders (DBDs), and 2) non-bipolar controls. The second analysis evaluated studies examining the rates of pediatric BP disorder in youth with and without a positive CBCL-BP/DP profile. Results: Eighteen articles met our inclusion and exclusion criteria, and fifteen articles had adequate data for meta-analysis. Results showed that BP youth were at significantly increased odds of having a positive CBCL-BP/DP profile compared to those with other psychiatric disorders (i.e., ADHD, anxiety/depression, or DBDs) (pooled OR=4.34, 95% CI=2.82, 8.27; p<0.001) and healthy control groups (pooled OR=34.77, 95% CI=2.87, 420.95; p=0.005). Further, meta-analysis results showed that youth with a positive CBCL-BP/DP profile were at significantly increased odds of having a BP disorder diagnosis compared to those without (pooled OR=4.25, 95% CI=2.12, 8.52; p<0.001). Conclusion: Our systematic review and meta-analysis of the extant literature provides strong support for the association between the CBCL-BP/DP profile and pediatric BP disorder.

Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study.

Attention deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder, is the most frequent comorbid condition seen in children with autism spectrum disorder (ASD). This high comorbidity between ADHD and ASD worsens symptom manifestations and complicates disease treatment and prognosis. It remains unclear whether individuals suffering with both ADHD and ASD, compared to individuals with ADHD only, share overlapping neural correlates associated with ADHD neuropathology, or exhibit a distinct neuropathological profile. Answering this question is critical to the understanding of treatment outcomes for the challenging comorbid ADHD symptoms. To identify the shared and the differentiated neural correlates of the comorbidity mechanisms of ADHD with ASD, we use diffusion tensor imaging (DTI) to characterize white-matter microstructure integrity in youth diagnosed with ADHD+ASD and youth with ADHD-only (excluding both the diagnosis and symptoms of ASD) compared with a healthy control group. Results show that the ADHD-only cohort exhibits impaired microstructural integrity (lower fractional anisotropy, FA) in the callosal-cingulum (CC-CG) tracts compared to the control cohort. The ADHD+ASD comorbid cohort shows impaired FA in an overlapping region within the CC-CG tracts and, additionally, shows impaired FA in the frontolimbic tracts including the uncinate fasciculus and anterior thalamic radiation. Across all participants, FA in the CC-CG showed a significantly negative relationship with the degree of ADHD symptom severity. Findings of this study suggest a specific role of CC-CG underlying ADHD neuropathology and symptom manifestations, and when comorbid with ASD a shared ADHD profile with a shift toward an anterior-brain, frontal impact. Results of this study may facilitate future targeted therapeutics and assist in diagnostic precision for individuals suffering with differing levels of comorbid ADHD with ASD, and ultimately contribute to improve prognostication and outcomes for these two highly prevalent and comorbid neurodevelopmental disorders.

Examining the impact of ADHD polygenic risk scores on ADHD and associated outcomes: A systematic review and meta-analysis.

Early identification of attention-deficit/hyperactivity disorder (ADHD) is critical for mitigating the many negative functional outcomes associated with its diagnosis. Because of the strong genetic basis of ADHD, the use of polygenic risk scores (PRS) could potentially aid in the early identification of ADHD and associated outcomes. Therefore, a systematic search of the literature on the association between ADHD and PRS in pediatric populations was conducted. All articles were screened for a priori inclusion and exclusion criteria, and, after careful review, 33 studies were included in our systematic review and 16 studies with extractable data were included in our meta-analysis. The results of the review were categorized into three common themes: the associations between ADHD-PRS with 1) the diagnosis of ADHD and ADHD symptoms 2) comorbid psychopathology and 3) cognitive and educational outcomes. Higher ADHD-PRS were associated with increased odds of having a diagnosis (OR = 1.37; p<0.001) and more symptoms of ADHD (ß = 0.06; p<0.001). While ADHD-PRS were associated with a persistent diagnostic trajectory over time in the systematic review, the meta-analysis did not confirm these findings (OR = 1.09; p = 0.62). Findings showed that ADHD-PRS were associated with increased odds for comorbid psychopathology such as anxiety/depression (OR = 1.16; p<0.001) and irritability/emotional dysregulation (OR = 1.14; p<0.001). Finally, while the systematic review showed that ADHD-PRS were associated with a variety of negative cognitive outcomes, the meta-analysis showed no significant association (ß = 0.08; p = 0.07). Our review of the available literature suggests that ADHD-PRS, together with risk factors, may contribute to the early identification of children with suspected ADHD and associated disorders.

JUE Insight: Measuring movement and social contact with smartphone data: a real-time application to COVID-19.

Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. These data cover broad sections of the US population and exhibit pre-pandemic patterns similar to conventional survey data. We develop and make publicly available a location exposure index that summarizes county-to-county movements and a device exposure index that quantifies social contact within venues. We also investigate the reliability of smartphone movement data during the pandemic.

Disentangling the heterogeneity of emotional dysregulation in referred youth using the Child Behavior Checklist attending to age and sex effects.

PURPOSE: To assess the utility of the Child Behavior Checklist (CBCL) to identify meaningful subtypes of emotional dysregulation in an outpatient pediatric psychiatry clinic. METHODS: The sample consisted of 417 newly referred youth 6-18 years of age. Parents completed the CBCL and rating scales measuring executive function deficits, social functioning, and quality of life. Patients were stratified into subtypes of emotional dysregulation and compared on clinical correlates based on the A-A-A profile consisting of the CBCL Anxious/Depressed, Aggressive Behavior, and Attention Problems (A-A-A) scales. RESULTS: 67% of youth had emotional dysregulation (CBCL A-A-A T-score ≥ 180) and of these, 39% had a positive CBCL-Bipolar (BP) profile (A-A-A T-score ≥ 210), 24% had depression without the BP profile (CBCL Anxious/Depressed and/or Withdrawn/Depressed T-scores ≥70 and A-A-A T-score ≥ 180 and ã€ˆ210), and 37% had emotional impulsivity (A-A-A T-score ≥ 180 and <210) with normal CBCL Anxious/Depressed and Withdrawn/Depressed T-scores. Patients with the CBCL-BP profile were significantly more impaired on all measures of social and executive functioning compared to the other two groups. LIMITATIONS: Since our findings relied on the CBCL, other instruments may have led to different results. Because we included youth from a single clinic, largely Caucasian and referred, our findings may not generalize to other ethnic groups or settings. CONCLUSIONS: The CBCL can aid in the identification of subtypes of emotional dysregulation affecting youth seeking mental health services.

Transcranial Photobiomodulation in Adults with High-Functioning Autism Spectrum Disorder: Positive Findings from a Proof-of-Concept Study.

Objective: To assess the efficacy and safety of transcranial photobiomodulation (tPBM) in adults with autism spectrum disorder (ASD). Methods: Adults with high-functioning-ASD, between 18 and 59 years of age, were enrolled to receive twice a week tPBM for 8 weeks in an open-label single group design. ASD symptom severity was assessed at baseline, midpoint, and end-point, by clinician-, self-, and informant-rated measures. Treatment response was defined as a ≥30% reduction in Social Responsiveness Scale-2nd Edition (SRS-2) total score and ASD Clinical Global Impression-Improvement score ≤2. Any possible adverse events were recorded at each visit. Paired-samples t-test analyses were performed. Results: Eleven participants were enrolled, and 10 participants (9 males; 30.0 ± 11.9 years) completed the study. One participant withdrew consent before baseline. All 10 completers were included in efficacy and safety analyses. Five participants (50%) met responder criteria at end-point. Overall, 8-week tPBM was associated with significant reduction in SRS-2 total scores at end-point (SRS-2: -30.6 ± 23, p < 0.001) particularly in Social Awareness (-3.0 ± 1.9, p < 0.001), Social Communication (-10.3 ± 6, p < 0.001), Social Motivation (-5.0 ± 2.4, p < 0.001), and Restricted/Repetitive Behaviors (-7.4 ± 4.1, p < 0.001). There were statistically significant improvements at end-point in Global Assessment of Functioning scores (+12.8 ± 4.2, p < 0.001) and Quality of Life Enjoyment and Satisfaction Questionnaire scores (+6.0 ± 7.9, p = 0.02). Three participants experienced transient, mild side effects (insomnia, headache, and warmth at treatment application site). No adverse events required changes in tPBM protocol. Adherence rate was 98%. Conclusions: tPBM is a safe and feasible treatment approach that has the potential to treat core features of ASD. Further research is necessary and warranted. ClinicalTrials.gov Identifier: NCT03724552.

Can machine learning identify childhood characteristics that predict future development of bipolar disorder a decade later?

Early identification of bipolar disorder may provide appropriate support and treatment, however there is no current evidence for statistically predicting whether a child will develop bipolar disorder. Machine learning methods offer an opportunity for developing empirically-based predictors of bipolar disorder. This study examined whether bipolar disorder can be predicted using clinical data and machine learning algorithms. 492 children, ages 6-18 at baseline, were recruited from longitudinal case-control family studies. Participants were assessed at baseline, then followed-up after 10 years. In addition to sociodemographic data, children were assessed with psychometric scales, structured diagnostic interviews, and cognitive and social functioning assessments. Using the Balanced Random Forest algorithm, we examined whether the diagnostic outcome of full or subsyndromal bipolar disorder could be predicted from baseline data. 45 children (10%) developed bipolar disorder at follow-up. The model predicted subsequent bipolar disorder with 75% sensitivity, 76% specificity, and an Area Under the Receiver Operating Characteristics of 75%. Predictors best differentiating between children who did or did not develop bipolar disorder were the Child Behavioral Checklist Externalizing and Internalizing behaviors, the Child Behavioral Checklist Total t-score, problematic school functions indexed through the Child Behavioral Checklist School Competence scale, and the Child Behavioral Checklist Anxiety/Depression and Aggression scales. Our study provides the first quantitative model to predict bipolar disorder. Longitudinal prediction may help clinicians assess children with emergent psychopathology for future risk of bipolar disorder, an area of clinical and scientific importance. Machine learning algorithms could be implemented to alert clinicians to risk for bipolar disorder.

Can polygenic risk scores help identify pediatric bipolar spectrum and related disorders?: A systematic review.

The genetic basis of mood disorders can, theoretically, provide diagnostic information in scenarios of clinical uncertainty. Therefore, we examined the available body of knowledge on the association between polygenic risk scores for bipolar disorder (BP-PRSs) and pediatric bipolar spectrum and related disorders. We performed a literature search through PubMed in March of 2020. The following variables were extracted from relevant studies: population age, study sample size, source of polygenic risk scores, source of data, the primary goal of the study, the assessments used during the course of the study, and the main findings/outcomes of each study. BP-PRSs were associated with deficits in executive functioning and the diagnosis of attention deficit/hyperactivity disorder (ADHD). Three studies included in our analysis directly compared major depressive disorder (MDD)-PRSs to BP-PRSs in youth. Results showed that MDD-PRSs, and not BP-PRSs, were associated with ADHD symptoms, internalizing problems, and social problems. ADHD-PRSs were associated with conduct problems, depressive symptomatology, and externalizing disorders symptoms. Findings revealed that ADHD-PRSs were more clearly associated with emotional reactivity, emotional dysregulation, and irritability-frequent correlates of pediatric BP disorder. These findings suggest that ADHD-PRSs may have an important contribution to the development of mood related problems in youth.

Differentiating bipolar disorder from unipolar depression in youth: A systematic literature review of neuroimaging research studies.

Differentiating bipolar disorder from unipolar depression is one of the most difficult clinical questions posed in pediatric psychiatric practices, as misdiagnosis can lead to severe repercussions for the affected child. This study aimed to examine the existing literature that investigates brain differences between bipolar and unipolar mood disorders in children directly, across all neuroimaging modalities. We performed a systematic literature search through PubMed, PsycINFO, Embase, and Medline databases with defined inclusion and exclusion criteria. Nine research studies were included in the systematic qualitative review, including three structural MRI studies, five functional MRI studies, and one MR spectroscopy study. Relevant variables were extracted and brain differences between bipolar and unipolar mood disorders in children as well as healthy controls were qualitatively analyzed. Across the nine studies, our review included 228 subjects diagnosed with bipolar disorder, 268 diagnosed with major depressive disorder, and 299 healthy controls. Six of the reviewed studies differentiated between bipolar and unipolar mood disorders. Differentiation was most commonly found in the anterior cingulate cortex (ACC), insula, and dorsal striatum (putamen and caudate) brain areas. Despite its importance, the current neuroimaging literature on this topic is scarce and presents minimal generalizability.