The neurostructural consequences of glaucoma and their overlap with disorders exhibiting emotional dysregulations: A voxel-based meta-analysis and tripartite system model.

BACKGROUND: Glaucoma, a progressive neurodegenerative disorder leading to irreversible blindness, is associated with heightened rates of generalized anxiety and depression. This study aims to comprehensively investigate brain morphological changes in glaucoma patients, extending beyond visual processing areas, and explores potential overlaps with alterations observed in anxiety and depression. METHODS: A comparative meta-analysis was conducted, using case-control studies of brain structural integrity in glaucoma patients. We aimed to identify regions with gray matter volume (GMV) changes, examine their role within distinct large-scale networks, and assess overlap with generalized anxiety disorder (GAD) and major depressive disorder (MDD). RESULTS: Glaucoma patients exhibited significant GMV reductions in visual processing regions (lingual gyrus, thalamus). Notably, volumetric reductions extended beyond visual systems, encompassing the left putamen and insula. Behavioral and functional network decoding revealed distinct large-scale networks, implicating visual, motivational, and affective domains. The insular region, linked to pain and affective processes, displayed reductions overlapping with alterations observed in GAD. LIMITATIONS: While the study identified significant VBM changes, the inclusion of studies from both the glaucoma and GAD cohorts is limited due to the lack of independent studies meeting our inclusion criteria. CONCLUSION: The study proposes a tripartite brain model for glaucoma, connecting visual processing changes to the lingual gyrus and suggesting additional alterations in the putamen and insular regions tied to emotional or motivational functions. These neuroanatomical changes extend beyond the visual system, implying broader implications for brain structure and potential pathological developments, providing insights into the overall neurological consequences of this visually focused disorder.

Demographic Correlates of Endometriosis Diagnosis Among United States Women Aged 15-50.

OBJECTIVE: To compare demographic characteristics for women with and without a diagnosis of endometriosis. DESIGN: Data were collected from the National Survey of Family Growth - a publicly available survey designed and administered by the Centers for Disease Control, which uses a nationally-representative sample of the United States population. Univariate data were reported as survey-weighted percentages and means, and were analyzed using chi-square, t-tests, and logistic regression. Analyses accounted for complex survey design. SETTING: United States PARTICIPANTS: Interviews were conducted with 6,141 female respondents, aged 15-50, between 2017 and 2019. INTERVENTIONS: Data were collected through in-person interviews. RESULTS: Nationally, 5.7% reported a diagnosis of endometriosis (95% CI 4.6-6.9%). Those with endometriosis were older, with a mean age of 39 (95% CI 38.1-39.9), compared to 31.7 (95% CI 31.2-32.2) among those without (p < 0.0005). Endometriosis diagnosis was significantly associated with race. Compared to non-Hispanic White women, Hispanic women had an adjusted odds ratio (aOR) of 0.37 (95% CI 0.21-0.65) for diagnosis of endometriosis, and non-Hispanic Black women had an aOR of 0.54 (95% CI 0.35-0.84). We also observed a difference in diagnosis by health insurance: compared to those with private insurance or Medi-Gap coverage, those with Medicare or military insurance had an aOR for endometriosis diagnosis of 2.49 (95% CI 1.36-4.55). Finally, compared to those with less than a high school education, those who had completed high school or greater had an aOR for endometriosis diagnosis of 2.84 (95% CI 1.15-6.99). CONCLUSION: These disparities in endometriosis diagnosis suggest that intersecting barriers may preclude certain groups from accessing timely endometriosis diagnosis and management. Further studies are warranted to explore these hypothesis-generating data, and to identify and address specific barriers to equitable endometriosis diagnosis and management.

The impact of delayed diagnosis and treatment due to COVID-19 on Australian thyroid cancer patients: a qualitative interview study.

OBJECTIVES: The study aims to investigate the perceptions of patients with thyroid cancer on the potential impact of diagnosis and treatment delays during the COVID-19 pandemic. DESIGN: This study involved qualitative semi-structured telephone interviews. The interviews were transcribed verbatim, analysed using the thematic framework analysis method and reported using the Consolidated Criteria for Reporting Qualitative Research. SETTING: Participants in the study were treated and/or managed at hospital sites across New South Wales and Victoria, Australia. PARTICIPANTS: 17 patients with thyroid cancer were interviewed and included in the analysis (14 females and 3 males). RESULTS: The delays experienced by patients ranged from <3 months to >12 months. The patients reported about delays to diagnostic tests, delays to surgery and radioactive iodine treatment, perceived disease progression and, for some, the financial burden of choosing to go through private treatment to minimise the delay. Most patients also reported not wanting to experience delays any longer than they did, due to unease and anxiety. CONCLUSIONS: This study highlights an increased psychological burden in patients with thyroid cancer who experienced delayed diagnosis and/or treatment during COVID-19. The impacts experienced by patients during this time may be similar in the case of other unexpected delays and highlight the need for regular clinical review during delays to diagnosis or treatment.

Recommendations for pharmacogenetic testing in clinical practice guidelines in the US.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Pharmacogenetic testing can identify patients who may benefit from personalized drug treatment. However, clinical uptake of pharmacogenetic testing has been limited. Clinical practice guidelines recommend biomarker tests that the guideline authors deem to have demonstrated clinical utility, meaning that testing improves treatment outcomes. The objective of this narrative review is to describe the current status of pharmacogenetic testing recommendations within clinical practice guidelines in the US. SUMMARY: Guidelines were reviewed for pharmacogenetic testing recommendations for 21 gene-drug pairs that have well-established drug response associations and all of which are categorized as clinically actionable by the Clinical Pharmacogenetics Implementation Consortium. The degree of consistency within and between organizations in pharmacogenetic testing recommendations was assessed. Relatively few clinical practice guidelines that provide a pharmacogenetic testing recommendation were identified. Testing recommendations for HLA-B*57:01 before initiation of abacavir and G6PD before initiation of rasburicase, both of which are included in drug labeling, were mostly consistent across guidelines. Gene-drug pairs with at least one clinical practice guideline recommending testing or stating that testing could be considered included CYP2C19-clopidogrel, CYP2D6-codeine, CYP2D6-tramadol, CYP2B6-efavirenz, TPMT-thiopurines, and NUDT15-thiopurines. Testing recommendations for the same gene-drug pair were often inconsistent between organizations and sometimes inconsistent between different guidelines from the same organization. CONCLUSION: A standardized approach to evaluating the evidence of clinical utility for pharmacogenetic testing may increase the inclusion and consistency of pharmacogenetic testing recommendations in clinical practice guidelines, which could benefit patients and society by increasing clinical use of pharmacogenetic testing.

Urgent versus elective surgical disparities among American Indian and Alaska Native patients.

BACKGROUND: American Indian and Alaska Native (AIAN) health issues are understudied despite documentation of lower-than-average life expectancy. Urgent surgery is associated with higher rates of postsurgical complications and postoperative death. We assess whether American Indian and Alaska Native (AIAN) patients in Washington State are at greater risk of requiring urgent rather than elective surgery compared with non-Hispanic Whites (NHW). METHODS: We accessed data for the period 2009-2014 from the Washington State Comprehensive Hospital Abstract Reporting System (CHARS) database, which captures all statewide hospital admissions, to examine three common surgeries that are performed both urgently and electively: hip replacements, aortic valve replacements, and spinal fusions. We extracted patient race, age, insurance status, comorbidity, admission type, and procedures performed. We then constructed multivariable logistic regression models to identify factors associated with use of urgent surgical care. RESULTS: AIAN patients had lower mean age at surgery for all three surgeries compared with NHW patients. AIAN patients were at higher risk for urgent surgery for hip replacements (OR = 1.49, 95% CI 1.19-1.88), spinal fusions (OR = 1.39, 95% CI 1.04-1.87), and aortic valve replacements (OR = 2.06, 95% CI 1.12-3.80). CONCLUSION: AIAN patients were more likely to undergo urgent hip replacement, spinal fusion, and aortic valve replacement than NHW patients. AIAN patients underwent urgent surgery at younger ages. Medicaid insurance conferred higher risks for urgent surgery across all surgeries studied. Further research is warranted to more clearly identify the factors contributing to disparities among AIAN patients undergoing urgent surgery.

Development of low back pain curriculum content standards for entry-level clinical training.

BACKGROUND: The management of low back pain (LBP) is highly variable and patients often receive management that is not recommended and/or miss out on recommended care. Clinician knowledge and behaviours are strongly influenced by entry-level clinical training and are commonly cited as barriers to implementing evidence-based management. Currently there are no internationally recognised curriculum standards for the teaching of LBP content to ensure graduating clinicians have the appropriate knowledge and competencies to assess and manage LBP. We formed an international interdisciplinary working group to develop curriculum content standards for the teaching of LBP in entry-level clinical training programs. METHODS: The working group included representatives from 11 countries: 18 academics and clinicians from healthcare professions who deal with the management of LBP (medicine, physiotherapy, chiropractic, osteopathy, pharmacology, and psychology), seven professional organisation representatives (medicine, physiotherapy, chiropractic, spine societies), and one healthcare consumer. A literature review was performed, including database and hand searches of guidelines and accreditation, curricula, and other policy documents, to identify gaps in current LBP teaching and recommended entry-level knowledge and competencies. The steering group (authors) drafted the initial LBP Curriculum Content Standards (LBP-CCS), which were discussed and modified through two review rounds with the working group. RESULTS: Sixty-two documents informed the draft standards. The final LBP-CCS consisted of four broad topics covering the epidemiology, biopsychosocial contributors, assessment, and management of LBP. For each topic, key knowledge and competencies to be achieved by the end of entry-level clinical training were described. CONCLUSION: We have developed the LBP-CCS in consultation with an interdisciplinary, international working group. These standards can be used to inform or benchmark the content of curricula related to LBP in new or existing entry-level clinical training programs.

Longitudinal impact of a residency-based postplacental levonorgestrel intrauterine device insertion program: Expulsion rates in years 1, 2, and 3.

OBJECTIVE: To evaluate expulsion rates in the first 3 years of an academic postplacental levonorgestrel intrauterine device (LNG-IUD) insertion program. STUDY DESIGN: Retrospective case series, January 2016 to December 2018. We measured LNG-IUD expulsion rates by 12 weeks postpartum. RESULTS: Of 235 LNG-IUD insertions, in years 1, 2, and 3, expulsion rates were 11/39 (28%), 9/94 (10%), and 15/102 (15%) (p = 0.03). After vaginal delivery, manual insertion was associated with a higher expulsion rate than ring-forceps (10/28 [36%] vs 17/105 [16%], p = 0.04). CONCLUSIONS: LNG-IUD expulsion rates decreased after program year 1, suggesting program maturity may be associated with a lower expulsion risk.

Patient experiences of an online consultation system: a qualitative study in English primary care post-COVID-19.

BACKGROUND: Online consultation systems (OCSs) allow patients to contact their healthcare teams online. Since 2020 they have been rapidly rolled out in primary care following policy initiatives and the COVID-19 pandemic. In-depth research of patients' experiences using OCSs is lacking. AIM: Explore patients' experiences of using an OCS. DESIGN AND SETTING: Qualitative study in English GP practices using the Patchs OCS (www.Patchs.ai) from March 2020 to July 2022. METHOD: Thematic analysis of 25 patient interviews and 21 467 written comments from 11 851 patients who used the OCS from nine and 240 GP practices, respectively. RESULTS: Patients cited benefits of using the OCS as speed, flexibility, and efficiency. Nevertheless, some patients desired a return to traditional consultation methods. GP practices often did not clearly advertise the OCS or use it as patients expected, which caused frustration. Patients reported advantages of having a written record of consultations and the opportunity to communicate detailed queries in free text. Views differed on how the OCS influenced clinical safety and discussions of sensitive topics. Patients who struggled to communicate in traditional consultations often preferred using the OCS, and male patients reported being more likely to use it. CONCLUSION: Globally, this is the largest in-depth study of patient experiences of an OCS. It contributes new knowledge that the patient experience of using OCSs can be influenced by previously unreported patient characteristics and the conditions they consult about. Further, it contributes recommendations on the design and implementation of the OCS in practice.

Comparing Predictive Performance of Time Invariant and Time Variant Clinical Prediction Models in Cardiac Surgery.

Clinical prediction models are increasingly used across healthcare to support clinical decision making. Existing methods and models are time-invariant and thus ignore the changes in populations and healthcare practice that occur over time. We aimed to compare the performance of time-invariant with time-variant models in UK National Adult Cardiac Surgery Audit data from Manchester University NHS Foundation Trust between 2009 and 2019. Data from 2009-2011 were used for initial model fitting, and data from 2012-2019 for validation and updating. We fitted four models to the data: a time-invariant logistic regression model (not updated), a logistic model which was updated every year and validated it in each subsequent year, a logistic regression model where the intercept is a function of calendar time (not updated), and a continually updating Bayesian logistic model which was updated with each new observation and continuously validated. We report predictive performance over the complete validation cohort and for each year in the validation data. Over the complete validation data, the Bayesian model had the best predictive performance.

Encoding a magic state with beyond break-even fidelity.

To run large-scale algorithms on a quantum computer, error-correcting codes must be able to perform a fundamental set of operations, called logic gates, while isolating the encoded information from noise1-8. We can complete a universal set of logic gates by producing special resources called magic states9-11. It is therefore important to produce high-fidelity magic states to conduct algorithms while introducing a minimal amount of noise to the computation. Here we propose and implement a scheme to prepare a magic state on a superconducting qubit array using error correction. We find that our scheme produces better magic states than those that can be prepared using the individual qubits of the device. This demonstrates a fundamental principle of fault-tolerant quantum computing12, namely, that we can use error correction to improve the quality of logic gates with noisy qubits. Moreover, we show that the yield of magic states can be increased using adaptive circuits, in which the circuit elements are changed depending on the outcome of mid-circuit measurements. This demonstrates an essential capability needed for many error-correction subroutines. We believe that our prototype will be invaluable in the future as it can reduce the number of physical qubits needed to produce high-fidelity magic states in large-scale quantum-computing architectures.

Users' views on the use of a smartwatch app to collect daily symptom data in individuals with multiple long-term conditions (Multimorbidity): A qualitative study.

Introduction: Long-term conditions are a major burden on health systems. One way to facilitate more research and better clinical care among patients with long-term conditions is to collect accurate data on their daily symptoms (patient-generated health data) using wearable technologies. Whilst evidence is growing for the use of wearable technologies in single conditions, there is less evidence of the utility of frequent symptom tracking in those who have more than one condition. Aims: To explore patient views of the acceptability of collecting daily patient-generated health data for three months using a smartwatch app. Methods: Watch Your Steps was a longitudinal study which recruited 53 patients to track over 20 symptoms per day for a 90-day period using a study app on smartwatches. Semi-structured interviews were conducted with a sub-sample of 20 participants to explore their experience of engaging with the app. Results: In a population of older people with multimorbidity, patients were willing and able to engage with a patient-generated health data app on a smartwatch. It was suggested that to maintain engagement over a longer period, more 'real-time' feedback from the app should be available. Participants did not seem to consider the management of more than one condition to be a factor in either engagement or use of the app, but the presence of severe or chronic pain was at times a barrier. Conclusion: This study has provided preliminary evidence that multimorbidity was not a major barrier to engagement with patient-generated health data via a smartwatch symptom tracking app.

Approximating Projections of Conformational Boltzmann Distributions with AlphaFold2 Predictions: Opportunities and Limitations.

Protein thermodynamics is intimately tied to biological function and can enable processes such as signal transduction, enzyme catalysis, and molecular recognition. The relative free energies of conformations that contribute to these functional equilibria evolved for the physiology of the organism. Despite the importance of these equilibria for understanding biological function and developing treatments for disease, computational and experimental methods capable of quantifying the energetic determinants of these equilibria are limited to systems of modest size. Recently, it has been demonstrated that the artificial intelligence system AlphaFold2 can be manipulated to produce structurally valid protein conformational ensembles. Here, we extend these studies and explore the extent to which AlphaFold2 contact distance distributions can approximate projections of the conformational Boltzmann distributions. For this purpose, we examine the joint probability distributions of inter-residue contact distances along functionally relevant collective variables of several protein systems. Our studies suggest that AlphaFold2 normalized contact distance distributions can correlate with conformation probabilities obtained with other methods but that they suffer from peak broadening. We also find that the AlphaFold2 contact distance distributions can be sensitive to point mutations. Overall, we anticipate that our findings will be valuable as the community seeks to model the thermodynamics of conformational changes in large biomolecular systems.

Distinct neurofunctional alterations during motivational and hedonic processing of natural and monetary rewards in depression - a neuroimaging meta-analysis.

Reward processing dysfunctions are considered a candidate mechanism underlying anhedonia and apathy in depression. Neuroimaging studies have documented that neurofunctional alterations in mesocorticolimbic circuits may neurally mediate these dysfunctions. However, common and distinct neurofunctional alterations during motivational and hedonic evaluation of monetary and natural rewards in depression have not been systematically examined. Here, we capitalized on pre-registered neuroimaging meta-analyses to (1) establish general reward-related neural alterations in depression, (2) determine common and distinct alterations during the receipt and anticipation of monetary v. natural rewards, and, (3) characterize the differences on the behavioral, network, and molecular level. The pre-registered meta-analysis (https://osf.io/ay3r9) included 633 depressed patients and 644 healthy controls and revealed generally decreased subgenual anterior cingulate cortex and striatal reactivity toward rewards in depression. Subsequent comparative analyses indicated that monetary rewards led to decreased hedonic reactivity in the right ventral caudate while natural rewards led to decreased reactivity in the bilateral putamen in depressed individuals. These regions exhibited distinguishable profiles on the behavioral, network, and molecular level. Further analyses demonstrated that the right thalamus and left putamen showed decreased activation during the anticipation of monetary reward. The present results indicate that distinguishable neurofunctional alterations may neurally mediate reward-processing alterations in depression, in particular, with respect to monetary and natural rewards. Given that natural rewards prevail in everyday life, our findings suggest that reward-type specific interventions are warranted and challenge the generalizability of experimental tasks employing monetary incentives to capture reward dysregulations in everyday life.

Boosting interpersonal emotion regulation through facial imitation: functional neuroimaging foundations.

Empathic function, which is primarily manifested by facial imitation, is believed to play a pivotal role in interpersonal emotion regulation for mood reinstatement. To explore this association and its neural substrates, we performed a questionnaire survey (study l) to identify the relationship between empathy and interpersonal emotion regulation; and a task-mode fMRI study (study 2) to explore how facial imitation, as a fundamental component of empathic processes, promotes the interpersonal emotion regulation effect. Study 1 showed that affective empathy was positively correlated with interpersonal emotion regulation. Study 2 showed smaller negative emotions in facial imitation interpersonal emotion regulation (subjects imitated experimenter's smile while followed the interpersonal emotion regulation guidance) than in normal interpersonal emotion regulation (subjects followed the interpersonal emotion regulation guidance) and Watch conditions. Mirror neural system (e.g. inferior frontal gyrus and inferior parietal lobe) and empathy network exhibited greater activations in facial imitation interpersonal emotion regulation compared with normal interpersonal emotion regulation condition. Moreover, facial imitation interpersonal emotion regulation compared with normal interpersonal emotion regulation exhibited increased functional coupling from mirror neural system to empathic and affective networks during interpersonal emotion regulation. Furthermore, the connectivity of the right orbital inferior frontal gyrus-rolandic operculum lobe mediated the association between the accuracy of facial imitation and the interpersonal emotion regulation effect. These results show that the interpersonal emotion regulation effect can be enhanced by the target's facial imitation through increased functional coupling from mirror neural system to empathic and affective neural networks.

Trust toward humans and trust toward artificial intelligence are not associated: Initial insights from self-report and neurostructural brain imaging.

The present study examines whether self-reported trust in humans and self-reported trust in [(different) products with built-in] artificial intelligence (AI) are associated with one another and with brain structure. We sampled 90 healthy participants who provided self-reported trust in humans and AI and underwent brain structural magnetic resonance imaging assessment. We found that trust in humans, as measured by the trust facet of the personality inventory NEO-PI-R, and trust in AI products, as measured by items assessing attitudes toward AI and by a composite score based on items assessing trust toward products with in-built AI, were not significantly correlated. We also used a concomitant dimensional neuroimaging approach employing a data-driven source-based morphometry (SBM) analysis of gray-matter-density to investigate neurostructural associations with each trust domain. We found that trust in humans was negatively (and significantly) correlated with an SBM component encompassing striato-thalamic and prefrontal regions. We did not observe significant brain structural association with trust in AI. The present findings provide evidence that trust in humans and trust in AI seem to be dissociable constructs. While the personal disposition to trust in humans might be "hardwired" to the brain's neurostructural architecture (at least from an individual differences perspective), a corresponding significant link for the disposition to trust AI was not observed. These findings represent an initial step toward elucidating how different forms of trust might be processed on the behavioral and brain level.

Structural-functional connectivity deficits of callosal-white matter-cortical circuits in schizophrenia.

Schizophrenia is increasingly recognized as a disorder with altered integration between large-scale functional networks and cortical-subcortical pathways. This spatial long-distance information communication must be associated with white matter (WM) fiber bundles. With accumulating evidence that WM functional signals reflect the intrinsic neural activities, how the deep callosal organization modulates cortical functional activities through WM remains unclear in schizophrenia. Using a data-driven method, we identified nine WM and gray matter (GM) functional networks, and then parcellated corpus callosum into distinct sub-regions. Combining functional connectivity and fiber tracking analysis, we estimated the structural and functional connectivity changes of callosal-WM-cortical circuits in schizophrenia. We observed higher structural and functional connectivity between corpus callosum, WM and GM functional networks involving visual network (visual processing), executive control network (executive controls), ventral attention network (processing of salience), and limbic network (emotion processing) in schizophrenia compared to healthy controls. We also found nine abnormal pathways of callosal-WM-cortical circuits involving the above networks and default mode network (self-related thought). These results highlight the role of connectivity deficits in callosal-WM-cortical circuits may play in understanding the delusions, hallucinations and cognitive impairment of schizophrenia.

Time-resolved live-cell spectroscopy reveals EphA2 multimeric assembly.

Ephrin type-A receptor 2 (EphA2) is a receptor tyrosine kinase that initiates both ligand-dependent tumor-suppressive and ligand-independent oncogenic signaling. We used time-resolved, live-cell fluorescence spectroscopy to show that the ligand-free EphA2 assembles into multimers driven by two types of intermolecular interactions in the ectodomain. The first type entails extended symmetric interactions required for ligand-induced receptor clustering and tumor-suppressive signaling that inhibits activity of the oncogenic extracellular signal-regulated kinase (ERK) and protein kinase B (AKT) protein kinases and suppresses cell migration. The second type is an asymmetric interaction between the amino terminus and the membrane proximal domain of the neighboring receptors, which supports oncogenic signaling and promotes migration in vitro and tumor invasiveness in vivo. Our results identify the molecular interactions that drive the formation of the EphA2 multimeric signaling clusters and reveal the pivotal role of EphA2 assembly in dictating its opposing functions in oncogenesis.

Comparative analysis of group information-guided independent component analysis and independent vector analysis for assessing brain functional network characteristics in autism spectrum disorder.

Introduction: Group information-guided independent component analysis (GIG-ICA) and independent vector analysis (IVA) are two methods that improve estimation of subject-specific independent components in neuroimaging studies. These methods have shown better performance than traditional group independent component analysis (GICA) with respect to intersubject variability (ISV). Methods: In this study, we compared the patterns of community structure, spatial variance, and prediction performance of GIG-ICA and IVA-GL, respectively. The dataset was obtained from the publicly available Autism Brain Imaging Data Exchange (ABIDE) database, comprising 75 healthy controls (HC) and 102 Autism Spectrum Disorder (ASD) participants. The greedy rule was used to match components from IVA-GL and GIG-ICA in order to compare the similarities between the two methods. Results: Robust correspondence was observed between the two methods the following networks: cerebellum network (CRN; |r| = 0.7813), default mode network (DMN; |r| = 0.7263), self-reference network (SRN; |r| = 0.7818), ventral attention network (VAN; |r| = 0.7574), and visual network (VSN; |r| = 0.7503). Additionally, the Sensorimotor Network demonstrated the highest similarity between IVA-GL and GIG-ICA (SOM: |r| = 0.8125). Our findings revealed a significant difference in the number of modules identified by the two methods (HC: p < 0.001; ASD: p < 0.001). GIG-ICA identified significant differences in FNC between HC and ASD compared to IVA-GL. However, in correlation analysis, IVA-GL identified a statistically negative correlation between FNC of ASD and the social total subscore of the classic Autism Diagnostic Observation Schedule (ADOS: pi = -0.26, p = 0.0489). Moreover, both methods demonstrated similar prediction performances on age within specific networks, as indicated by GIG-ICA-CRN (R2 = 0.91, RMSE = 3.05) and IVA-VAN (R2 = 0.87, RMSE = 3.21). Conclusion: In summary, IVA-GL demonstrated lower modularity, suggesting greater sensitivity in estimating networks with higher intersubject variability. The improved age prediction of cerebellar-attention networks underscores their importance in the developmental progression of ASD. Overall, IVA-GL may be appropriate for investigating disorders with greater variability, while GIG-ICA identifies functional networks with distinct modularity patterns.

High-Threshold Quantum Computing by Fusing One-Dimensional Cluster States.

We propose a measurement-based model for fault-tolerant quantum computation that can be realized with one-dimensional cluster states and fusion measurements only; basic resources that are readily available with scalable photonic hardware. Our simulations demonstrate high thresholds compared with other measurement-based models realized with basic entangled resources and 2-qubit fusion measurements. Its high tolerance to noise indicates that our practical construction offers a promising route to scalable quantum computing with quantum emitters and linear-optical elements.

Contraception and Abortion Care for People Living With HIV: A Clinical Guide for Reproductive Health Practitioners.

People capable of pregnancy are disproportionately affected by HIV. Family planning needs and services are often unmet in this population, and clinical care guidelines regarding contraceptive options and abortion care are not well elucidated. Individuals living with HIV often face unique barriers in accessing contraception and abortion services due to internalized stigma, medically complex care (eg, drug-drug interactions, adverse effects of antiretroviral therapy), and distrust of health care providers. There is also a lack of clarity among reproductive health, primary, and infectious disease care providers on best-practice contraceptive counseling and contraceptive care for individuals living with HIV, given limited opportunities to enhance expertise in reproductive infectious disease. In this review, we summarize existing and updated evidence and clinical considerations regarding contraceptive counseling and abortion care in this population.