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OBJECTIVES: To determine real-life quantitative changes in OCT biomarkers in a large set of treatment naive patients in a real-life setting undergoing anti-VEGF therapy. For this purpose, we devised a novel deep learning based semantic segmentation algorithm providing the first benchmark results for automatic segmentation of 11 OCT features including biomarkers for neovascular age-related macular degeneration (nAMD). METHODS: Training of a Deep U-net based semantic segmentation ensemble algorithm for state-of-the-art semantic segmentation performance which was used to analyze OCT features prior to, after 3 and 12 months of anti-VEGF therapy. RESULTS: High F1 scores of almost 1.0 for neurosensory retina and subretinal fluid on a separate hold-out test set with unseen patients. The algorithm performed worse for subretinal hyperreflective material and fibrovascular PED, on par with drusenoid PED, and better in segmenting fibrosis. In the evaluation of treatment naive OCT scans, significant changes occurred for intraretinal fluid (mean: 0.03 µm3 to 0.01 µm3, p < 0.001), subretinal fluid (0.08 µm3 to 0.01 µm3, p < 0.001), subretinal hyperreflective material (0.02 µm3 to 0.01 µm3, p < 0.001), fibrovascular PED (0.12 µm3 to 0.09 µm3, p = 0.02) and central retinal thickness C0 (225.78 µm3 to 169.40 µm3). The amounts of intraretinal fluid, fibrovascular PED, and ERM were predictive of poor outcome. CONCLUSIONS: The segmentation algorithm allows efficient volumetric analysis of OCT scans. Anti-VEGF provokes most potent changes in the first 3 months while a gradual loss of RPE hints at a progressing decline of visual acuity. Additional research is required to understand how these accurate OCT predictions can be leveraged for a personalized therapy regimen.
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Differential item functioning (DIF) is a common challenge when examining latent traits in large scale surveys. In recent work, methods from the field of machine learning such as model-based recursive partitioning have been proposed to identify subgroups with DIF when little theoretical guidance and many potential subgroups are available. On this basis, we propose and compare recursive partitioning techniques for detecting DIF with a focus on measurement models with multiple latent variables and ordinal response data. We implement tree-based approaches for identifying subgroups that contribute to DIF in multidimensional latent variable modeling and propose a robust, yet scalable extension, inspired by random forests. The proposed techniques are applied and compared with simulations. We show that the proposed methods are able to efficiently detect DIF and allow to extract decision rules that lead to subgroups with well fitting models.
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BACKGROUND: Optical coherence tomography and electroretinography studies have revealed structural and functional retinal alterations in individuals with schizophrenia spectrum disorders (SSDs). However, it remains unclear which specific retinal layers are affected; how the retina, brain, and clinical symptomatology are connected; and how alterations of the visual system are related to genetic disease risk. METHODS: Optical coherence tomography, electroretinography, and brain magnetic resonance imaging were applied to comprehensively investigate the visual system in a cohort of 103 patients with SSDs and 130 healthy control individuals. The sparse partial least squares algorithm was used to identify multivariate associations between clinical disease phenotype and biological alterations of the visual system. The association of the revealed patterns with individual polygenic disease risk for schizophrenia was explored in a post hoc analysis. In addition, covariate-adjusted case-control comparisons were performed for each individual optical coherence tomography and electroretinography parameter. RESULTS: The sparse partial least squares analysis yielded a phenotype-eye-brain signature of SSDs in which greater disease severity, longer duration of illness, and impaired cognition were associated with electrophysiological alterations and microstructural thinning of most retinal layers. Higher individual loading onto this disease-relevant signature of the visual system was significantly associated with elevated polygenic risk for schizophrenia. In case-control comparisons, patients with SSDs had lower macular thickness, thinner retinal nerve fiber and inner plexiform layers, less negative a-wave amplitude, and lower b-wave amplitude. CONCLUSIONS: This study demonstrates multimodal microstructural and electrophysiological retinal alterations in individuals with SSDs that are associated with disease severity and individual polygenic burden.
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PURPOSE: To evaluate the long-term outcomes of patients with non-infectious uveitis treated with 0.19 mg fluocinolone acetonide insert (FAi) for up to 36 months in clinical practice. METHODS: A retrospective study conducted at a single uveitis center. RESULTS: Fifty eyes of 39 patients were included. Mean best corrected visual acuity (BCVA) and central retinal thickness (CRT) remained stable until month 36 after FAi implantation (61.04 vs. 70.25 letters and 370.8 vs. 332.5 µm, respectively). The recurrence rate was 34% (17 eyes) after 36 months, of which 82% (14 eyes) received high-dose corticosteroids before FAi. Mean intraocular pressure (IOP) remained unchanged (13.38 vs. 15.74 mmHg), while most phakic eyes (13 of 14 eyes) required cataract surgery. CONCLUSIONS: We show that FAi effectively prevents recurrences of non-infectious uveitis for up to three years in clinical practice, comparable with randomized clinical trials. Patients who received high-dose corticosteroids before FAi have an increased risk for early recurrence and should be considered for scheduled re-treatment.
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BACKGROUND: Humanitarian crises and armed conflicts lead to a greater prevalence of poor population mental health. Following the 1 February 2021 military coup in Burma, the country's civilians have faced humanitarian crises that have probably caused rising rates of mental disorders. However, a dearth of data has prevented researchers from assessing the extent of the problem empirically. AIMS: To better understand prevalence of depressive and anxiety disorders among the Burmese adult population after the February 2021 military coup. METHOD: We fielded an online non-probability survey of 7720 Burmese adults aged 18 and older during October 2021 and asked mental health and demographic questions. We used the Patient Health Questionnaire-4 to measure probable depression and anxiety in respondents. We also estimated logistic regressions to assess variations in probable depression and anxiety across demographic subgroups and by level of trust in various media sources, including those operated by the Burmese military establishment. RESULTS: We found consistently high rates of probable anxiety and depression combined (60.71%), probable depression (61%) and probable anxiety (58%) in the sample overall, as well as across demographic subgroups. Respondents who 'mostly' or 'completely' trusted military-affiliated media sources (about 3% of the sample) were significantly less likely than respondents who did not trust these sources to report symptoms of anxiety and depression (AOR = 0.574; 95% CI 0.370-0.889), depression (AOR = 0.590; 95% CI 0.383-0.908) or anxiety (AOR = 0.609; 95% CI 0.390-0.951). CONCLUSIONS: The widespread symptoms of anxiety and depression we observed demonstrate the need for both continuous surveillance of the current situation and humanitarian interventions to address mental health needs in Burma.
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The study of a fluorescent indolin-3-one derivative is reported that, as opposed to its previously described congeners, selectively undergoes photoactivated ring-opening in apolar solvents. The excited state involved in this photoisomerization was partially deactivated by the formation of singlet oxygen. Cell studies revealed lipid droplet accumulation and efficient light-induced cytotoxicity.
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Oxigênio Singlete , SolventesRESUMO
Subduction transports volatiles between Earth's mantle, crust, and atmosphere, ultimately creating a habitable Earth. We use isotopes to track carbon from subduction to outgassing along the Aleutian-Alaska Arc. We find substantial along-strike variations in the isotopic composition of volcanic gases, explained by different recycling efficiencies of subducting carbon to the atmosphere via arc volcanism and modulated by subduction character. Fast and cool subduction facilitates recycling of ~43 to 61% sediment-derived organic carbon to the atmosphere through degassing of central Aleutian volcanoes, while slow and warm subduction favors forearc sediment removal, leading to recycling of ~6 to 9% altered oceanic crust carbon to the atmosphere through degassing of western Aleutian volcanoes. These results indicate that less carbon is returned to the deep mantle than previously thought and that subducting organic carbon is not a reliable atmospheric carbon sink over subduction time scales.
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Introduction: Treatment of severe mental illness (SMI) symptoms, especially negative symptoms and cognitive dysfunction in schizophrenia, remains a major unmet need. There is good evidence that SMIs have a strong genetic background and are characterized by multiple biological alterations, including disturbed brain circuits and connectivity, dysregulated neuronal excitation-inhibition, disturbed dopaminergic and glutamatergic pathways, and partially dysregulated inflammatory processes. The ways in which the dysregulated signaling pathways are interconnected remains largely unknown, in part because well-characterized clinical studies on comprehensive biomaterial are lacking. Furthermore, the development of drugs to treat SMIs such as schizophrenia is limited by the use of operationalized symptom-based clusters for diagnosis. Methods: In line with the Research Domain Criteria initiative, the Clinical Deep Phenotyping (CDP) study is using a multimodal approach to reveal the neurobiological underpinnings of clinically relevant schizophrenia subgroups by performing broad transdiagnostic clinical characterization with standardized neurocognitive assessments, multimodal neuroimaging, electrophysiological assessments, retinal investigations, and omics-based analyzes of blood and cerebrospinal fluid. Moreover, to bridge the translational gap in biological psychiatry the study includes in vitro investigations on human-induced pluripotent stem cells, which are available from a subset of participants. Results: Here, we report on the feasibility of this multimodal approach, which has been successfully initiated in the first participants in the CDP cohort; to date, the cohort comprises over 194 individuals with SMI and 187 age and gender matched healthy controls. In addition, we describe the applied research modalities and study objectives. Discussion: The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive dysfunction, and treatment-resistant symptoms in general are still difficult to treat.
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The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data types and recipients, we argue that established social norms shape the acceptance of novel practices of data collection and use. To investigate the willingness to share health data, we conducted a preregistered vignette experiment. The scenarios experimentally varied the vignette dimensions by data type, recipient, and research purpose. While some findings contradict our hypotheses, the results indicate that all three dimensions affected respondents' data sharing decisions. Additional analyses suggest that institutional and social trust, privacy concerns, technical affinity, altruism, age, and device ownership influence the willingness to share health data.
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COVID-19 , Pandemias , Humanos , Prontuários Médicos , Biomarcadores , Disseminação de InformaçãoRESUMO
BACKGROUND: Schizophrenia spectrum disorders (SSDs) are presumed to be associated with retinal thinning. However, evidence is lacking as to whether these retinal alterations reflect a disease-specific process or are rather a consequence of comorbid diseases or concomitant microvascular impairment. METHODS: The study included 126 eyes of 65 patients with SSDs and 143 eyes of 72 healthy controls. We examined macula and optic disc measures by optical coherence tomography (OCT) and OCT angiography (OCT-A). Additive mixed models were used to assess the impact of SSDs on retinal thickness and perfusion and to explore the association of retinal and clinical disease-related parameters by controlling for several ocular and systemic covariates (age, sex, spherical equivalent, intraocular pressure, body mass index, diabetes, hypertension, smoking status, and OCT signal strength). RESULTS: OCT revealed significantly lower parafoveal macular, macular ganglion cell-inner plexiform layer (GCIPL), and macular retinal nerve fiber layer (RNFL) thickness and thinner mean and superior peripapillary RNFL in SSDs. In contrast, the applied OCT-A investigations, which included macular and peripapillary perfusion density, macular vessel density, and size of the foveal avascular zone, did not reveal any significant between-group differences. Finally, a longer duration of illness and higher chlorpromazine equivalent doses were associated with lower parafoveal macular and macular RNFL thickness. CONCLUSIONS: This study strengthens the evidence for disease-related retinal thinning in SSDs.
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Disco Óptico , Esquizofrenia , Humanos , Tomografia de Coerência Óptica/métodos , Esquizofrenia/complicações , Esquizofrenia/diagnóstico por imagem , Células Ganglionares da Retina , Pressão IntraocularRESUMO
PURPOSE: To evaluate the effectiveness of 0.19-mg fluocinolone acetonide implant (FAi) for preventing inflammatory relapses in noninfectious uveitis with posterior segment involvement in standard clinical practice. Further, to assess the value of remission induction therapy with intraocular and periorbital administered high-dose corticosteroids before FAi. METHODS: A retrospective cohort study in a tertiary referral center specialized in uveitis management. The primary study outcomes were the best-corrected visual acuity (BVCA) and central retinal thickness (CRT) within a 12-month observation period. The secondary outcomes were intraocular pressure (IOP) and intraocular inflammation. The main safety measures were IOP increase and cataract formation. RESULTS: In total, 76 eyes of 57 patients received FAi. Locally administered high-dose corticosteroids were applied in 68.4% of all eyes before FAi. BCVA remained stable within the 12-month observation period (63.21 vs. 62.95, difference 0.26 letters; 95% CI: - 6.31 to 6.84; p > 0.9). Significant CRT reduction upon FAi was sustained after 12 months (362.7 vs. 309.1 µm, difference 53.57 µm; 95% CI: 1.55 to 105.6; p = 0.04). Intraocular inflammation was reduced until 9 months of follow-up (0.82 vs. 0.3, difference 0.53; 95% CI: 0.11 to 0.95; p = 0.007). A mean IOP increase (13.68 vs. 15.6; difference - 1.92; 95% CI: - 3.85 to 0.004; p = 0.0507) and cataract development (20% of all phakic eyes) were noted. CONCLUSION: We observed similar levels of FAi effectiveness for the treatment of noninfectious uveitis in standard clinical practice compared to previous randomized clinical trials. Moreover, remission induction therapy before FAi can benefit patients with increased baseline uveitis activity.
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Catarata , Uveíte Posterior , Uveíte , Humanos , Glucocorticoides , Estudos Retrospectivos , Implantes de Medicamento/uso terapêutico , Recidiva Local de Neoplasia , Fluocinolona Acetonida , Uveíte/diagnóstico , Uveíte/tratamento farmacológico , Uveíte/induzido quimicamente , Pressão Intraocular , Inflamação , Catarata/complicações , Catarata/diagnóstico , Resultado do Tratamento , Uveíte Posterior/diagnóstico , Uveíte Posterior/tratamento farmacológicoRESUMO
Prediction algorithms are regularly used to support and automate high-stakes policy decisions about the allocation of scarce public resources. However, data-driven decision-making raises problems of algorithmic fairness and justice. So far, fairness and justice are frequently conflated, with the consequence that distributive justice concerns are not addressed explicitly. In this paper, we approach this issue by distinguishing (a) fairness as a property of the algorithm used for the prediction task from (b) justice as a property of the allocation principle used for the decision task in data-driven decision-making. The distinction highlights the different logic underlying concerns about fairness and justice and permits a more systematic investigation of the interrelations between the two concepts. We propose a new notion of algorithmic fairness called error fairness which requires prediction errors to not differ systematically across individuals. Drawing on sociological and philosophical discourse on local justice, we present a principled way to include distributive justice concerns into data-driven decision-making. We propose that allocation principles are just if they adhere to well-justified distributive justice principles. Moving beyond the one-sided focus on algorithmic fairness, we thereby make a first step toward the explicit implementation of distributive justice into data-driven decision-making.
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Human perceptions of fairness in (semi-)automated decision-making (ADM) constitute a crucial building block toward developing human-centered ADM solutions. However, measuring fairness perceptions is challenging because various context and design characteristics of ADM systems need to be disentangled. Particularly, ADM applications need to use the right degree of automation and granularity of data input to achieve efficiency and public acceptance. We present results from a large-scale vignette experiment that assessed fairness perceptions and the acceptability of ADM systems. The experiment varied context and design dimensions, with an emphasis on who makes the final decision. We show that automated recommendations in combination with a final human decider are perceived as fair as decisions made by a dominant human decider and as fairer than decisions made only by an algorithm. Our results shed light on the context dependence of fairness assessments and show that semi-automation of decision-making processes is often desirable.
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In Space, cosmic radiation is a strong, ubiquitous form of energy with constant flux, and the ability to harness it could greatly enhance the energy-autonomy of expeditions across the solar system. At the same time, radiation is the greatest permanent health risk for humans venturing into deep space. To protect astronauts beyond Earth's magnetosphere, advanced shielding against ionizing as well as non-ionizing radiation is highly sought after. In search of innovative solutions to these challenges, biotechnology appeals with suitability for in situ resource utilization (ISRU), self-regeneration, and adaptability. Where other organisms fail, certain microscopic fungi thrive in high-radiation environments on Earth, showing high radioresistance. The adaptation of some of these molds to areas, such as the Chernobyl Exclusion Zone has coined the terms positive "radiotropism" and "radiotrophy", reflecting the affinity to and stimulation by radiation, and sometimes even enhanced growth under ionizing conditions. These abilities may be mediated by the pigment melanin, many forms of which also have radioprotective properties. The expectation is that these capabilities are extendable to radiation in space. To study its growth in space, an experiment cultivating Cladosporium sphaerospermum Penzig ATCC® 11289™ aboard the International Space Station (ISS) was conducted while monitoring radiation beneath the formed biomass in comparison to a no-growth negative control. A qualitative growth advantage in space was observable. Quantitatively, a 1.21 ± 0.37-times higher growth rate than in the ground control was determined, which might indicate a radioadaptive response to space radiation. In addition, a reduction in radiation compared to the negative control was discernable, which is potentially attributable to the fungal biomass.
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The gold-standard approaches for gleaning statistically valid conclusions from data involve random sampling from the population. Collecting properly randomized data, however, can be challenging, so modern statistical methods, including propensity score reweighting, aim to enable valid inferences when random sampling is not feasible. We put forth an approach for making inferences based on available data from a source population that may differ in composition in unknown ways from an eventual target population. Whereas propensity scoring requires a separate estimation procedure for each different target population, we show how to build a single estimator, based on source data alone, that allows for efficient and accurate estimates on any downstream target data. We demonstrate, theoretically and empirically, that our target-independent approach to inference, which we dub "universal adaptability," is competitive with target-specific approaches that rely on propensity scoring. Our approach builds on a surprising connection between the problem of inferences in unspecified target populations and the multicalibration problem, studied in the burgeoning field of algorithmic fairness. We show how the multicalibration framework can be employed to yield valid inferences from a single source population across a diverse set of target populations.
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Direct control of protein interactions by chemically induced protein proximity holds great potential for both cell and synthetic biology as well as therapeutic applications. Low toxicity, orthogonality and excellent cell permeability are important criteria for chemical inducers of proximity (CIPs), in particular for in vivo applications. Here, we present the use of the agrochemical mandipropamid (Mandi) as a highly efficient CIP in cell culture systems and living organisms. Mandi specifically induces complex formation between a sixfold mutant of the plant hormone receptor pyrabactin resistance 1 (PYR1) and abscisic acid insensitive (ABI). It is orthogonal to other plant hormone-based CIPs and rapamycin-based CIP systems. We demonstrate the applicability of the Mandi system for rapid and efficient protein translocation in mammalian cells and zebrafish embryos, protein network shuttling and manipulation of endogenous proteins.
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Amidas/farmacologia , Ácidos Carboxílicos/farmacologia , Fungicidas Industriais/farmacologia , Ácido Abscísico/metabolismo , Animais , Dimerização , Peixe-Zebra/embriologiaRESUMO
BACKGROUND: Guidelines and recommendations from public health authorities related to face masks have been essential in containing the COVID-19 pandemic. We assessed the prevalence and correlates of mask usage during the pandemic. METHODS: We examined a total of 13,723,810 responses to a daily cross-sectional online survey in 38 countries of people who completed from April 23, 2020 to October 31, 2020 and reported having been in public at least once during the last 7 days. The outcome was individual face mask usage in public settings, and the predictors were country fixed effects, country-level mask policy stringency, calendar time, individual sociodemographic factors, and health prevention behaviors. Associations were modeled using survey-weighted multivariable logistic regression. RESULTS: Mask-wearing varied over time and across the 38 countries. While some countries consistently showed high prevalence throughout, in other countries mask usage increased gradually, and a few other countries remained at low prevalence. Controlling for time and country fixed effects, sociodemographic factors (older age, female gender, education, urbanicity) and stricter mask-related policies were significantly associated with higher mask usage in public settings. Crucially, social behaviors considered risky in the context of the pandemic (going out to large events, restaurants, shopping centers, and socializing outside of the household) were associated with lower mask use. CONCLUSION: The decision to wear a face mask in public settings is significantly associated with sociodemographic factors, risky social behaviors, and mask policies. This has important implications for health prevention policies and messaging, including the potential need for more targeted policy and messaging design.