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Nucleation and growth of aerosol particles from atmospheric vapors constitutes a major source of global cloud condensation nuclei (CCN). The fraction of newly formed particles that reaches CCN sizes is highly sensitive to particle growth rates, especially for particle sizes <10 nm, where coagulation losses to larger aerosol particles are greatest. Recent results show that some oxidation products from biogenic volatile organic compounds are major contributors to particle formation and initial growth. However, whether oxidized organics contribute to particle growth over the broad span of tropospheric temperatures remains an open question, and quantitative mass balance for organic growth has yet to be demonstrated at any temperature. Here, in experiments performed under atmospheric conditions in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN), we show that rapid growth of organic particles occurs over the range from −25 ∘C to 25 ∘C. The lower extent of autoxidation at reduced temperatures is compensated by the decreased volatility of all oxidized molecules. This is confirmed by particle-phase composition measurements, showing enhanced uptake of relatively less oxygenated products at cold temperatures. We can reproduce the measured growth rates using an aerosol growth model based entirely on the experimentally measured gas-phase spectra of oxidized organic molecules obtained from two complementary mass spectrometers. We show that the growth rates are sensitive to particle curvature, explaining widespread atmospheric observations that particle growth rates increase in the single-digit-nanometer size range. Our results demonstrate that organic vapors can contribute to particle growth over a wide range of tropospheric temperatures from molecular cluster sizes onward.
High-frequency changes in interest rates around FOMC announcements are a standard method of measuring monetary policy shocks. However, some recent studies have documented puzzling effects of these shocks on private-sector forecasts of GDP, unemployment, or inflation that are opposite in sign to what standard macroeconomic models would predict. This evidence has been viewed as supportive of a „Fed information effect“ channel of monetary policy, whereby an FOMC tightening (easing) communicates that the economy is stronger (weaker) than the public had expected.
The authors show that these empirical results are also consistent with a „Fed response to news“ channel, in which incoming, publicly available economic news causes both the Fed to change monetary policy and the private sector to revise its forecasts. They provide substantial new evidence that distinguishes between these two channels and strongly favors the latter; for example, regressions that include the previously omitted public macroeconomic news, high-frequency stock market responses to Fed announcements, and a new survey that they conduct of individual Blue Chip forecasters all indicate that the Fed and private sector are simply responding to the same public news, and that there is little if any role for a „Fed information effect“.
Background: There are several ways to conduct a job task analysis in medical work environments including pencil-paper observations, interviews and questionnaires. However these methods implicate bias problems such as high inter-individual deviations and risks of misjudgement. Computer-based observation helps to reduce these problems. The aim of this paper is to give an overview of the development process of a computer-based job task analysis instrument for real-time observations to quantify the job tasks performed by physicians working in different medical settings. In addition reliability and validity data of this instrument will be demonstrated.
Methods: This instrument was developed in consequential steps. First, lists comprising tasks performed by physicians in different care settings were classified. Afterwards content validity of task lists was proved. After establishing the final task categories, computer software was programmed and implemented in a mobile personal computer. At least inter-observer reliability was evaluated. Two trained observers recorded simultaneously tasks of the same physician.
Results: Content validity of the task lists was confirmed by observations and experienced specialists of each medical area. Development process of the job task analysis instrument was completed successfully. Simultaneous records showed adequate interrater reliability.
Conclusion: Initial results of this analysis supported the validity and reliability of this developed method for assessing physicians' working routines as well as organizational context factors. Based on results using this method, possible improvements for health professionals' work organisation can be identified.
RP1 (synonym: MAPRE2, EB2) is a member of the microtubule binding EB1 protein family, which interacts with APC, a key regulatory molecule in the Wnt signalling pathway. While the other EB1 proteins are well characterized the cellular function and regulation of RP1 remain speculative to date. However, recently RP1 has been implicated in pancreatic cancerogenesis. CK2 is a pleiotropic kinase involved in adhesion, proliferation and anti-apoptosis. Overexpression of protein kinase CK2 is a hallmark of many cancers and supports the malignant phenotype of tumor cells. In this study we investigate the interaction of protein kinase CK2 with RP1 and demonstrate that CK2 phosphorylates RP1 at Ser236 in vitro. Stable RP1 expression in cell lines leads to a significant cleavage and down-regulation of N-cadherin and impaired adhesion. Cells expressing a Phospho-mimicking point mutant RP1-ASP236 show a marked decrease of adhesion to endothelial cells under shear stress. Inversely, we found that the cells under shear stress downregulate endogenous RP1, most likely to improve cellular adhesion. Accordingly, when RP1 expression is suppressed by shRNA, cells lacking RP1 display significantly increased cell adherence to surfaces. In summary, RP1 phosphorylation at Ser236 by CK2 seems to play a significant role in cell adhesion and might initiate new insights in the CK2 and EB1 family protein association.
The authors estimate perceptions about the Fed's monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions is time-varying and cyclical: high during tightening episodes but low during easings. Forecasters update their perceptions about the policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that forecasters have imperfect information about the rule. The perceived rule impacts asset prices crucial for monetary policy transmission, driving how interest rates respond to macroeconomic news and explaining term premia in long-term interest rates.
Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees’ decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of a system discontinuance. Following cognitive theories, the provision of ML-based predictions can adversely affect the development of decision-making skills that come to light when people lose access to the system. The purpose of this study is to put this assertion to the test. Using a novel experiment specifically tailored to deal with organizational obstacles and endogeneity concerns, we show that the initial provision of ML decision aids can latently prevent the development of decision-making skills which later becomes apparent when the system gets discontinued. We also find that the degree to which individuals 'blindly' trust observed predictions determines the ultimate performance drop in the post-discontinuance phase. Our results suggest that making it clear to people that ML decision aids are imperfect can have its benefits especially if there is a reasonable danger of (temporary) system discontinuances.
Background: Unlike metastatic colorectal cancer (CRC) there are to date few reports concerning the predictive value of molecular biomarkers on the clinical outcome in stage II/III CRC patients receiving adjuvant chemotherapy. Aim of this study was to assess the predictive value of proteins related with the EGFR- and VEGFR- signalling cascades in these patients.
Methods: The patients' data examined in this study were from the collective of the 5-FU/FA versus 5-FU/FA/irinotecan phase III FOGT-4 trial. Tumor tissues were stained by immunohistochemistry for VEGF-C, VEGF-D, VEGFR-3, Hif-1 α, PTEN, AREG and EREG expression and evaluated by two independent, blinded investigators. Survival analyses were calculated for all patients receiving adjuvant chemotherapy in relation to expression of all makers above.
Results: Patients with negative AREG and EREG expression on their tumor had a significant longer DFS in comparison to AREG/EREG positive ones (p< 0.05). The benefit on DFS in AREG-/EREG- patients was even stronger in the group that received 5-FU/FA/irinotecan as adjuvant treatment (p=0.002). Patients with strong expression of PTEN profited more in terms of OS under adjuvant treatment containing irinotecan (p< 0.05). Regarding markers of the VEGFR- pathway we found no correlation of VEGF-C- and VEGFR-3 expression with clinical outcome. Patients with negative VEGF-D expression had a trend to live longer when treated with 5-FU/FA (p=0.106). Patients who were negative for Hif-1 α, were disease-free in more than 50% at the end of the study and showed significant longer DFS-rates than those positive for Hif-1 α (p=0.007). This benefit was even stronger at the group treated with 5-FU/FA/irinotecan (p=0.026). Finally, AREG-/EREG-/PTEN+ patients showed a trend to live longer under combined treatment combination.
Conclusions: The addition of irinotecan to adjuvant treatment with 5-FU/FA does not provide OS or DFS benefit in patients with stage II/III CRC. Nevertheless, AREG/EREG negative, PTEN positive and Hif-1 α negative patients might profit significantly in terms of DFS from a treatment containing fluoropyrimidines and irinotecan. Our results suggest a predictive value of these biomarkers concerning adjuvant chemotherapy with 5-FU/FA +/− irinotecan in stage II/III colorectal cancer.
Background: Lithium has proven suicide preventing effects in the long-term treatment of patients with affective disorders. Clinical evidence from case reports indicate that this effect may occur early on at the beginning of lithium treatment. The impact of lithium treatment on acute suicidal thoughts and/or behavior has not been systematically studied in a controlled trial. The primary objective of this confirmatory study is to determine the association between lithium therapy and acute suicidal ideation and/or suicidal behavior in inpatients with a major depressive episode (MDE, unipolar and bipolar disorder according to DSM IV criteria). The specific aim is to test the hypothesis that lithium plus treatment as usual (TAU), compared to placebo plus TAU, results in a significantly greater decrease in suicidal ideation and/or behavior over 5 weeks in inpatients with MDE.
Methods/Design: We initiated a randomized, placebo-controlled multicenter trial. Patients with the diagnosis of a moderate to severe depressive episode and suicidal thoughts and/or suicidal behavior measured with the Sheehan-Suicidality-Tracking Scale (S-STS) will be randomly allocated to add lithium or placebo to their treatment as usual. Change in the clinician administered S-STS from the initial to the final visit will be the primary outcome.
Discussion: There is an urgent need to identify treatments that will acutely decrease suicidal ideation and/or suicidal behavior. The results of this study will demonstrate whether lithium reduces suicidal ideation and behavior within the first 5 weeks of treatment.
Introduction: Bipolar disorder (BD) is characterized by recurrent episodes of depression and mania and affects up to 2% of the population worldwide. Patients suffering from bipolar disorder have a reduced life expectancy of up to 10 years. The increased mortality might be due to a higher rate of somatic diseases, especially cardiovascular diseases. There is however also evidence for an increased rate of diabetes mellitus in BD, but the reported prevalence rates vary by large.
Material and Methods: 85 bipolar disorder patients were recruited in the framework of the BiDi study (Prevalence and clinical features of patients with Bipolar Disorder at High Risk for Type 2 Diabetes (T2D), at prediabetic state and with manifest T2D) in Dresden and Würzburg. T2D and prediabetes were diagnosed measuring HBA1c and an oral glucose tolerance test (oGTT), which at present is the gold standard in diagnosing T2D. The BD sample was compared to an age-, sex- and BMI-matched control population (n = 850) from the Study of Health in Pomerania cohort (SHIP Trend Cohort).
Results: Patients suffering from BD had a T2D prevalence of 7%, which was not significantly different from the control group (6%). Fasting glucose and impaired glucose tolerance were, contrary to our hypothesis, more often pathological in controls than in BD patients. Nondiabetic and diabetic bipolar patients significantly differed in age, BMI, number of depressive episodes, and disease duration.
Discussion: When controlled for BMI, in our study there was no significantly increased rate of T2D in BD. We thus suggest that overweight and obesity might be mediating the association between BD and diabetes. Underlying causes could be shared risk genes, medication effects, and lifestyle factors associated with depressive episodes. As the latter two can be modified, attention should be paid to weight changes in BD by monitoring and taking adequate measures to prevent the alarming loss of life years in BD patients.
Protein signatures of oxidative stress response in a patient specific cell line model for autism
(2014)
Background: Known genetic variants can account for 10% to 20% of all cases with autism spectrum disorders (ASD). Overlapping cellular pathomechanisms common to neurons of the central nervous system (CNS) and in tissues of peripheral organs, such as immune dysregulation, oxidative stress and dysfunctions in mitochondrial and protein synthesis metabolism, were suggested to support the wide spectrum of ASD on unifying disease phenotype. Here, we studied in patient-derived lymphoblastoid cell lines (LCLs) how an ASD-specific mutation in ribosomal protein RPL10 (RPL10[H213Q]) generates a distinct protein signature. We compared the RPL10[H213Q] expression pattern to expression patterns derived from unrelated ASD patients without RPL10[H213Q] mutation. In addition, a yeast rpl10 deficiency model served in a proof-of-principle study to test for alterations in protein patterns in response to oxidative stress.
Methods: Protein extracts of LCLs from patients, relatives and controls, as well as diploid yeast cells hemizygous for rpl10, were subjected to two-dimensional gel electrophoresis and differentially regulated spots were identified by mass spectrometry. Subsequently, Gene Ontology database (GO)-term enrichment and network analysis was performed to map the identified proteins into cellular pathways.
Results: The protein signature generated by RPL10[H213Q] is a functionally related subset of the ASD-specific protein signature, sharing redox-sensitive elements in energy-, protein- and redox-metabolism. In yeast, rpl10 deficiency generates a specific protein signature, harboring components of pathways identified in both the RPL10[H213Q] subjects' and the ASD patients' set. Importantly, the rpl10 deficiency signature is a subset of the signature resulting from response of wild-type yeast to oxidative stress.
Conclusions: Redox-sensitive protein signatures mapping into cellular pathways with pathophysiology in ASD have been identified in both LCLs carrying the ASD-specific mutation RPL10[H213Q] and LCLs from ASD patients without this mutation. At pathway levels, this redox-sensitive protein signature has also been identified in a yeast rpl10 deficiency and an oxidative stress model. These observations point to a common molecular pathomechanism in ASD, characterized in our study by dysregulation of redox balance. Importantly, this can be triggered by the known ASD-RPL10[H213Q] mutation or by yet unknown mutations of the ASD cohort that act upstream of RPL10 in differential expression of redox-sensitive proteins.
There is a need for diagnostic biomarkers of epilepsy and status epilepticus to support clinical examination, electroencephalography and neuroimaging. Extracellular microRNAs may be potentially ideal biomarkers since some are expressed uniquely within specific brain regions and cell types. Cerebrospinal fluid offers a source of microRNA biomarkers with the advantage of being in close contact with the target tissue and sites of pathology. Here we profiled microRNA levels in cerebrospinal fluid from patients with temporal lobe epilepsy or status epilepticus, and compared findings to matched controls. Differential expression of 20 microRNAs was detected between patient groups and controls. A validation phase included an expanded cohort and samples from patients with other neurological diseases. This identified lower levels of miR-19b in temporal lobe epilepsy compared to controls, status epilepticus and other neurological diseases. Levels of miR-451a were higher in status epilepticus compared to other groups whereas miR-21-5p differed in status epilepticus compared to temporal lobe epilepsy but not to other neurological diseases. Targets of these microRNAs include proteins regulating neuronal death, tissue remodelling, gliosis and inflammation. The present study indicates cerebrospinal fluid contains microRNAs that can support differential diagnosis of temporal lobe epilepsy and status epilepticus from other neurological and non-neurological diseases.
Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. BD shows substantial clinical and genetic overlap with other psychiatric disorders, in particular schizophrenia (SCZ). The genes underlying this etiological overlap remain largely unknown. A recent SCZ genome wide association study (GWAS) by the Psychiatric Genomics Consortium identified 128 independent genome-wide significant single nucleotide polymorphisms (SNPs). The present study investigated whether these SCZ-associated SNPs also contribute to BD development through the performance of association testing in a large BD GWAS dataset (9747 patients, 14278 controls). After re-imputation and correction for sample overlap, 22 of 107 investigated SCZ SNPs showed nominal association with BD. The number of shared SCZ-BD SNPs was significantly higher than expected (p = 1.46x10-8). This provides further evidence that SCZ-associated loci contribute to the development of BD. Two SNPs remained significant after Bonferroni correction. The most strongly associated SNP was located near TRANK1, which is a reported genome-wide significant risk gene for BD. Pathway analyses for all shared SCZ-BD SNPs revealed 25 nominally enriched gene-sets, which showed partial overlap in terms of the underlying genes. The enriched gene-sets included calcium- and glutamate signaling, neuropathic pain signaling in dorsal horn neurons, and calmodulin binding. The present data provide further insights into shared risk loci and disease-associated pathways for BD and SCZ. This may suggest new research directions for the treatment and prevention of these two major psychiatric disorders.
Incentives, self-selection, and coordination of motivated agents for the production of social goods
(2021)
We study, theoretically and empirically, the effects of incentives on the self-selection and coordination of motivated agents to produce a social good. Agents join teams where they allocate effort to either generate individual monetary rewards (selfish effort) or contribute to the production of a social good with positive effort complementarities (social effort). Agents differ in their motivation to exert social effort. Our model predicts that lowering incentives for selfish effort in one team increases social good production by selectively attracting and coordinating motivated agents. We test this prediction in a lab experiment allowing us to cleanly separate the selection effect from other effects of low incentives. Results show that social good production more than doubles in the low- incentive team, but only if self-selection is possible. Our analysis highlights the important role of incentives in the matching of motivated agents engaged in social good production.
Risk stratification for bipolar disorder using polygenic risk scores among young high-risk adults
(2020)
Objective: Identifying high-risk groups with an increased genetic liability for bipolar disorder (BD) will provide insights into the etiology of BD and contribute to early detection of BD. We used the BD polygenic risk score (PRS) derived from BD genome-wide association studies (GWAS) to explore how such genetic risk manifests in young, high-risk adults. We postulated that BD-PRS would be associated with risk factors for BD.
Methods: A final sample of 185 young, high-risk German adults (aged 18–35 years) were grouped into three risk groups and compared to a healthy control group (n = 1,100). The risk groups comprised 117 cases with attention deficit hyperactivity disorder (ADHD), 45 with major depressive disorder (MDD), and 23 help-seeking adults with early recognition symptoms [ER: positive family history for BD, (sub)threshold affective symptomatology and/or mood swings, sleeping disorder]. BD-PRS was computed for each participant. Logistic regression models (controlling for sex, age, and the first five ancestry principal components) were used to assess associations of BD-PRS and the high-risk phenotypes.
Results: We observed an association between BD-PRS and combined risk group status (OR = 1.48, p < 0.001), ADHD diagnosis (OR = 1.32, p = 0.009), MDD diagnosis (OR = 1.96, p < 0.001), and ER group status (OR = 1.7, p = 0.025; not significant after correction for multiple testing) compared to healthy controls.
Conclusions: In the present study, increased genetic risk for BD was a significant predictor for MDD and ADHD status, but not for ER. These findings support an underlying shared risk for both MDD and BD as well as ADHD and BD. Improving our understanding of the underlying genetic architecture of these phenotypes may aid in early identification and risk stratification.
The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
The formation of secondary particles in the atmosphere accounts for more than half of global cloud condensation nuclei. Experiments at the CERN CLOUD (Cosmics Leaving OUtdoor Droplets) chamber have underlined the importance of ions for new particle formation, but quantifying their effect in the atmosphere remains challenging. By using a novel instrument setup consisting of two nano-particle counters, one of them equipped with an ion filter, we were able to further investigate the ion-related mechanisms of new particle formation. In autumn 2015, we carried out experiments at CLOUD on four systems of different chemical compositions involving monoterpenes, sulfuric acid, nitrogen oxides, and ammonia. We measured the influence of ions on the nucleation rates under precisely controlled and atmospherically relevant conditions. Our results indicate that ions enhance the nucleation process when the charge is necessary to stabilize newly formed clusters, i.e. in conditions where neutral clusters are unstable. For charged clusters that were formed by ion-induced nucleation, we were able to measure, for the first time, their progressive neutralization due to recombination with oppositely charged ions. A large fraction of the clusters carried a charge at 1.2 nm diameter. However, depending on particle growth rates and ion concentrations, charged clusters were largely neutralized by ion–ion recombination before they grew to 2.2 nm. At this size, more than 90 % of particles were neutral. In other words, particles may originate from ion-induced nucleation, although they are neutral upon detection at diameters larger than 2.2 nm. Observations at Hyytiälä, Finland, showed lower ion concentrations and a lower contribution of ion-induced nucleation than measured at CLOUD under similar conditions. Although this can be partly explained by the observation that ion-induced fractions decrease towards lower ion concentrations, further investigations are needed to resolve the origin of the discrepancy.
In current discussions on large language models (LLMs) such as GPT, understanding their ability to emulate facets of human intelligence stands central. Using behavioral economic paradigms and structural models, we investigate GPT’s cooperativeness in human interactions and assess its rational goal-oriented behavior. We discover that GPT cooperates more than humans and has overly optimistic expectations about human cooperation. Intriguingly, additional analyses reveal that GPT’s behavior isn’t random; it displays a level of goal-oriented rationality surpassing human counterparts. Our findings suggest that GPT hyper-rationally aims to maximize social welfare, coupled with a strive of self-preservation. Methodologically, our esearch highlights how structural models, typically employed to decipher human behavior, can illuminate the rationality and goal-orientation of LLMs. This opens a compelling path for future research into the intricate rationality of sophisticated, yet enigmatic artificial agents.
How does group identity affect belief formation? To address this question, we conduct a series of online experiments with a representative sample of individuals in the US. Using the setting of the 2020 US presidential election, we find evidence of intergroup preference across three distinct components of the belief formation cycle: a biased prior belief, avoid-ance of outgroup information sources, and a belief-updating process that places greater (less) weight on prior (new) information. We further find that an intervention reducing the salience of information sources decreases outgroup information avoidance by 50%. In a social learn-ing context in wave 2, we find participants place 33% more weight on ingroup than outgroup guesses. Through two waves of interventions, we identify source utility as the mechanism driving group effects in belief formation. Our analyses indicate that our observed effects are driven by groupy participants who exhibit stable and consistent intergroup preferences in both allocation decisions and belief formation across all three waves. These results suggest that policymakers could reduce the salience of group and partisan identity associated with a policy to decrease outgroup information avoidance and increase policy uptake.