Standard Proxy Research Articles

Improving the Accuracy of Bulk Fitness Assays by Correcting Barcode Processing Biases.

Measuring the fitnesses of genetic variants is a fundamental objective in evolutionary biology. A standard approach for measuring microbial fitnesses in bulk involves labeling a library of genetic variants with unique sequence barcodes, competing the labeled strains in batch culture, and using deep sequencing to track changes in the barcode abundances over time. However, idiosyncratic properties of barcodes can induce nonuniform amplification or uneven sequencing coverage that causes some barcodes to be over- or under-represented in samples. This systematic bias can result in erroneous read count trajectories and misestimates of fitness. Here, we develop a computational method, named REBAR (Removing the Effects of Bias through Analysis of Residuals), for inferring the effects of barcode processing bias by leveraging the structure of systematic deviations in the data. We illustrate this approach by applying it to two independent data sets, and demonstrate that this method estimates and corrects for bias more accurately than standard proxies, such as GC-based corrections. REBAR mitigates bias and improves fitness estimates in high-throughput assays without introducing additional complexity to the experimental protocols, with potential applications in a range of experimental evolution and mutation screening contexts.

Socio-Economic Infrastructure and Standard of Living in Nigeria

This study investigated the effect of socio-economic infrastructure on the standard of living in Nigeria for the period 1981–2021. The study used per capita income as a proxy for standard of living, while investments in health, education, telecommunications, and electric power supply were used as infrastructure. The exchange rate entered the model as a control variable. Annual time series data were obtained from secondary sources including the CBN annual statistical bulletin, and World Bank development indicators. The Eview10 Statistical Software was employed to analyze the data empirically. Due to the stationarity condition of the time series data, the study adopted the autoregressive distributed lag (ARDL) model to ascertain its objectives. The study revealed that, in the short run, the coefficient of electric power supply has a positive effect on standard of living and is significant, while in the long run, the coefficient of telecommunication infrastructure has a positive influence on standard of living and is significant. The study concludes that the place of power supply and communication cannot be undermined as Nigeria plans for sustainable economic growth and development. Therefore, it was recommended that there be a deliberate attempt to improve the quality of health care and education. Secondly, the federal government should see the provision of electric power and the reduction in airtime and internet data as the main drivers of the standard of living in Nigeria.

Effect of Formal Education on Standard of Living in Nigeria

This study investigates the relationship between formal education and the standard of living in Nigeria by analyzing the impact of government expenditure on education and school enrolment on the country's GDP per capita as a proxy for standard of living. Using 30 years of annual time series data and employing the ordinary least square (OLS) method, the study evaluates the time series properties of the variables with Augmented DickeyFuller (ADF) and Philip Peron unit root tests, and tests hypotheses using Ftests and t-tests. The findings reveal that school enrolment and government expenditure on education jointly explain a significant portion (93.33%) of the variation in GDP per capita, highlighting the vital role of education in driving economic growth and improving the standard of living in Nigeria. Specifically, higher enrolment rates in secondary and tertiary education exhibit positive and significant effects on GDP per capita, indicating that investments in higher education lead to increased productivity, higher incomes, and improved economic outcomes and living standards. However, a notable finding shows that government expenditure on education has a negative and insignificant effect (-27.45) on GDP per capita, calling for further exploration into the effectiveness and allocation of education spending for sustainable economic growth. As a result, several recommendations are proposed, including prioritizing investment in secondary and tertiary education to enhance individuals' skills and job opportunities, improving education quality and access, optimizing government spending on education, fostering collaboration between the public and private sectors in education, and combining education initiatives with poverty alleviation programs to address root causes of poverty and improve living standards for vulnerable populations, contributing to Nigeria's long-term economic development and prosperity.

The Term Structure of Monetary Policy Uncertainty

This paper studies the transmission of Federal Reserve communication to financial markets and the economy using new measures of the term structure of policy rate uncertainty. High-frequency movements in the term structure of interest rate uncertainty around FOMC announcements cannot be summarized by a single measure but, instead, are two dimensional. We characterize these two dimensions as the Level and Slope factors of the term structure of interest rate uncertainty. These two monetary policy uncertainty factors help to explain changes in Treasury yields and forward real interest rates following FOMC announcements, even after accounting for changes in the expected path of policy rates. Finally, compared to high-frequency instruments derived from interest rate futures, our policy uncertainty factors provide stronger first-stage instruments and imply FOMC forward guidance has been more effective in stimulating economic activity in a standard proxy SVAR.

The effect of school quality on house prices in the global south: evidence from South Africa

Purpose This paper aims to investigate the effects of school quality (SQ) on residential property prices in Johannesburg, South Africa. Previous studies have empirically examined the quality of private and public schools without a standard proxy that is accepted in the literature. As a result, this paper extends the literature to the global south by the effect that SQ has on residential property price changes in the local markets of the City of Johannesburg. Design/methodology/approach The research adopts the hedonic pricing model to evaluate and quantify the impact that the structural attributes such as erf size; number of bedrooms and bathrooms; and SQ measured by pass rates, sport rankings and quality of facilities have on house prices. A total of 2,763 property transactions covering the Kensington and Observatory areas of the City of Johannesburg over the period 2010 and 2020 were obtained from the deeds registry and used for the empirical analysis. Findings The study finds that SQ has a positive impact on house prices. When the average pass rate of the model school increases by 1%, all other things being equal, house prices also increase by 1.8%. This suggests that people who live closer to the model school are willing to pay more when the school performance improves. The 1.8% premium this study attributes to a 1% increase in school performance is however generally low when compared to some findings in the literature suggesting that there may be some other important factors that households consider when purchasing their home. Originality/value The main contribution is uncovering the relationship between the SQ and residential property prices in the local markets, using Kensington and Observatory in Johannesburg as sampled areas. Due to the presence of reliable and quality of data sets, such studies are not many in the global south and a study of this nature in South Africa is notably not existing in the literature.

Macroeconomic uncertainty and vector autoregressions

A procedure to estimate measures of macroeconomic uncertainty and compute the effects of uncertainty shocks based on standard VARs is proposed. Uncertainty and its effects are estimated using a single model so to ensure internal consistency. Under suitable assumptions, the procedure is equivalent to using the square of the VAR forecast error as an external instrument in a proxy SVAR. The procedure allows to add orthogonality constraints to the standard proxy SVAR identification scheme. The method is applied to a US data set; results show that macroeconomic uncertainty is responsible of a large fraction of business-cycle fluctuations while financial uncertainty plays a modest role.

A Method for Estimating Individual Socioeconomic Status of Twitter Users

The rise of social media has opened countless opportunities to explore social science questions with new data and methods. However, research on socioeconomic inequality remains constrained by limited individual-level socioeconomic status (SES) measures in digital trace data. Following Bourdieu, we argue that the commercial and entertainment accounts Twitter users follow reflect their economic and cultural capital. Adapting a political science method for inferring political ideology, we use correspondence analysis to estimate the SES of 3,482,652 Twitter users who follow the accounts of 339 brands in the United States. We validate our estimates with data from the Facebook Marketing application programming interface, self-reported job titles on users’ Twitter profiles, and a small survey sample. The results show reasonable correlations with the standard proxies for SES, alongside much weaker or nonsignificant correlations with other demographic variables. The proposed method opens new opportunities for innovative social research on inequality on Twitter and similar online platforms.

Detecting the Auroral Oval through CSES-01 Electric Field Measurements in the Ionosphere

We present the results of a systematic study of the ionospheric electric field in the Auroral Oval (AO) region in the southern hemisphere. We exploit one year of electric field measurements taken by the Electric Field Detector (EFD) on board the Chinese Seismo-Electromagnetic Satellite-01 (CSES-01), flying at around 500 km altitude in a sun-synchronous orbit. We exploit the high temporal resolution of the EFD to devise a new technique for the detection of CSES-01 crossing of the AO using electric field measurements only. This new technique combines a Median-Weighted Local Variance Measure with Fast Iterative Filtering to automatically isolate high levels of electromagnetic activity caused by, e.g., particle precipitation and Field Aligned Currents (FACs) at auroral latitudes. We validate this new method against other standard proxies, such as the single-FAC product from the Swarm mission and the auroral radiance emission measured by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) units on board the Defense Meteorological Satellite Program (DMSP) constellation. Furthermore, we identify ∼3000 orbits (out of a dataset of ∼10,000) where CSES-01 crosses the AO boundary under conditions of high geomagnetic activity. This dataset represents the first step in the systematic study of the auroral electric field, with many potential applications to space weather, thanks to the large amount of continuous observations of the ionosphere by CSES-01 and the forthcoming CSES-02 mission.

A 1000‐Year Record of Temperature From Isotopic Analysis of the Deep Critical Zone in Central China

AbstractTemperature proxies for paleoclimate reconstruction have been made typically via ice cores, tree rings, stalagmites, and lake sediments. While extremely useful, these proxies can be limited spatially. Here we sampled a 98 m “soil core” from Loess Plateau of China and examined the relationship between pore water isotopic values and hydroclimate history. We extracted soil pore water for δ18O, δ2H, and 3H and measured chloride concentration. The 3H‐peak at 6 m and chloride mass balance were used to turn depth into calendar year. A 1000 year span was revealed. δ18O and δ2H values between 14–50 m were anomalously low—bracketing well the Little Ice Age period from 1420 to 1870. The identification was consistent with other standard proxies in the region and showed the same temporal dynamics of temperature anomalies. Our study shows the potential of stable isotopes of soil water for paleoclimate reconstruction in deep soils.

Assessing Flexibility of Solution Strategy: Strategy Shifting as a Measure of Cognitive Reserve.

This series of experiments explores whether flexibility in strategy shifting might function as an expression of cognitive reserve (CR). A reasoning task was designed using matrix reasoning stimuli that each required 1 of 2 specific solution strategies: logicoanalytic and visuospatial. It was formatted as a task-switching paradigm, assessing the ability to switch between solution strategies as measured by switch costs. Study 1 was done on Amazon Mechanical Turk and included an assessment of CR proxies. Study 2 used participants who had been studied extensively with neuropsychological assessments and structural neuroimaging. Study 1 found that switch costs increased with aging. In addition, a relationship between switch costs and CR proxies was noted, suggesting a relationship between the flexibility of strategy shifting and CR. The results of Study 2 again indicated that age negatively affected strategy-shifting flexibility, but that individuals with higher CR as measured with standard proxies performed better. The flexibility measure accounted for additional variance in cognitive performance over that explained by cortical thickness, suggesting that it may contribute to CR. Overall, the results are consistent with the idea that flexibility in strategy shifting might be 1 cognitive process that underlies cognitive reserve.

Identifying structural VARs from sparse narrative instruments: Dynamic effects of US macroprudential policies

SummaryWe study identification in Bayesian proxy VARs for instruments that consist of sparse qualitative observations indicating the signs of shocks in specific periods. We propose the Fisher discriminant regression and a non‐parametric sign concordance criterion as two alternative methods for achieving correct inference in this case. The former represents a minor deviation from a standard proxy VAR, whereas the non‐parametric approach builds on set identification. Our application to US macroprudential policies finds persistent declines in credit volumes and house prices together with moderate declines in GDP and inflation and a widening of corporate bond spreads after a tightening of capital requirements or mortgage underwriting standards.

Hashing Fuzzing: Introducing Input Diversity to Improve Crash Detection

The utility of a test set of program inputs is strongly influenced by its diversity and its size. Syntax coverage has become a standard proxy for diversity. Although more sophisticated measures exist, such as proximity of a sample to a uniform distribution, methods to use them tend to be type dependent. We use r-wise hash functions to create a novel, semantics preserving, testability transformation for C programs that we call HashFuzz. Use of HashFuzz improves the diversity of test sets produced by instrumentation-based fuzzers. We evaluate the effect of the HashFuzz transformation on eight programs from the Google Fuzzer Test Suite using four state-of-the-art fuzzers that have been widely used in previous research. We demonstrate pronounced improvements in the performance of the test sets for the transformed programs across all the fuzzers that we used. These include strong improvements in diversity in every case, maintenance or small improvement in branch coverage – up to 4.8 perent improvement in the best case, and significant improvement in unique crash detection numbers – between 28 to 97 perent increases compared to test sets for untransformed programs.

Sunlight-driven nitrate loss records Antarctic surface mass balance

Standard proxies for reconstructing surface mass balance (SMB) in Antarctic ice cores are often inaccurate or coarsely resolved when applied to more complicated environments away from dome summits. Here, we propose an alternative SMB proxy based on photolytic fractionation of nitrogen isotopes in nitrate observed at 114 sites throughout East Antarctica. Applying this proxy approach to nitrate in a shallow core drilled at a moderate SMB site (Aurora Basin North), we reconstruct 700 years of SMB changes that agree well with changes estimated from ice core density and upstream surface topography. For the under-sampled transition zones between dome summits and the coast, we show that this proxy can provide past and present SMB values that reflect the immediate local environment and are derived independently from existing techniques.

Abstract 4089: Time to treatment discontinuation and time to next treatment as proxies of real-world progression-free survival in breast cancer patients

Abstract Background: There is no standardized real-world proxy for progression-free survival (PFS), although it is a key treatment response metric in clinical trials. Real-world PFS (rwPFS) has been curated from clinician-documented progression in unstructured electronic health records (EHRs), a time and resource intensive approach, that is not readily accessible in claims or structured EHRs. Alternatively, time to treatment discontinuation (rwTTD) and time to next treatment (rwTTNT) are used as treatment-based scalable proxies of disease progression. We compared clinician-documented rwPFS to rwTTD and rwTTNT. Methods: The study included patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced or metastatic breast cancer (A/MBC) who initiated first line treatment with palbociclib plus an aromatase inhibitor (1L) between 2015 and 2019 in US community health systems. Demographics, clinical characteristics, and outcomes were extracted from EHRs. rwPFS was captured through EHR-documented confirmation by two clinicians of disease progression based on imaging and/or pathology results. rwPFS, rwTTD and rwTTNT were defined as the time from 1L initiation until the date of clinician-confirmed progression, 1L discontinuation, or 2L initiation, respectively. Patients were censored at the first of: (1) death, (2) date of last contact, (3) study end date, (4) or at 2L for rwPFS. Results: The study included 241 patients with median age 66 at A/MBC diagnosis, among whom 85% were postmenopausal and 57% were de novo A/MBC. During study follow-up (median 22.4 months), 86 (36%) patients had a clinician-confirmed progression (rwPFS events); 130 (54%) discontinued 1L (rwTTD events), and 96 (40%) initiated 2L (rwTTNT events). With clinician-confirmed progression as the “gold standard”, rwTTD had higher sensitivity (90% vs 71%) but lower specificity (66% vs 77%) than rwTTNT. Patient’s choice, hospice referral, and toxicity were common reasons for treatment discontinuation apart from disease progression. The 12, 24, and 48-month survival estimates were closer between rwPFS (0.78, 0.64, 0.51) and rwTTNT (0.80, 0.63, 0.47), than rwTTD (0.69, 0.51, 0.37). Median rwPFS (39 months, 95% confidence interval [95% CI]: 30-NA) and rwTTNT (32 months, 95% CI: 29-46) were also more alike (log-rank p = 0.90) than median rwPFS and rwTTD (24 months, 95% CI: 18-30; log-rank p=0.02). The correlation between rwPFS and rwTTNT was 0.72 (95% CI: 0.56-0.83), compared to 0.73 (95% CI: 0.57-0.84) between rwPFS and rwTTD. Results were similar in sensitivity analyses where death was part of rwPFS, rwTTNT, and rwTTD events rather than a censoring event. Conclusions: Our results suggest that rwTTNT may be a more adequate at-scale proxy for rwPFS than rwTTD. Studies should assess the generalizability of these findings to other tumor types and treatment settings. Citation Format: Monika A. Izano, Mahder Teka, Colden Johanson, Jeanna Wallenta Law, Ronda Broome, Daniele Morgan, Amy Stone, Mary Tran, Thomas D. Brown, Chenan Zhang. Time to treatment discontinuation and time to next treatment as proxies of real-world progression-free survival in breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4089.

Mogamulizumab for Previously Treated Mycosis Fungoides and Sézary Syndrome: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE) invited the manufacturer (Kyowa Kirin) of mogamulizumab (Poteligeo®), as part of the single technology appraisal process, to submit evidence for its clinical and cost-effectiveness for previously treated mycosis fungoides (MF) and Sézary syndrome (SS). Kleijnen Systematic Reviews Ltd, in collaboration with Maastricht University Medical Centre, was commissioned to act as the independent evidence review group (ERG). This paper summarises the company submission (CS), presents the ERG’s critical review of the clinical and cost-effectiveness evidence in the CS, highlights the key methodological considerations and describes the development of the NICE guidance by the Appraisal Committee. Based on a systematic literature review, one randomised controlled trial, MAVORIC, was identified showing favourable results in patients with MF and SS. However, MAVORIC compared mogamulizumab to vorinostat, which is not standard care in the NHS, and there is uncertainty due to the study design, specifically crossover of patients. Based on a “naïve comparison of results from the vorinostat arm of the MAVORIC study and the physician’s choice arm (methotrexate or bexarotene i.e. United Kingdom [UK] standard treatments) of the ALCANZA study as well as comparison to Phase II bexarotene data”, the company considered vorinostat to be “a reasonable proxy for current standard of care in the NHS”. The ERG considered, based on the limited data available, that the comparability of vorinostat (MAVORIC) and physician’s choice (ALCANZA) could not be established. In response to the Appraisal Consultation Document, the company provided an unanchored matched adjusted indirect comparison (MAIC) of mogamulizumab with UK standard care by analysing Hospital Episode Statistics (HES) data. However, given the high risk of bias of an unanchored MAIC, these results needed to be regarded with a considerable degree of caution. The economic analysis suffered from uncertainty because there was no trial evidence on the comparator in the England and Wales National Health Service (NHS), and it was unclear to what extent the trial (MAVORIC) comparator (vorinostat) was comparable to standard care, referred to as established clinical management (ECM) in the NHS. The evidence for overall survival had not reached maturity and was confounded by treatment switching, for which different crossover adjustment methods produced large variations in life years. Caregiver utilities were applied in the analysis, but there was a lack of guidance on their application and whether these were indicated in this appraisal. After consultation, the company updated the economic analysis with the MAIC. Incremental cost-effectiveness ratios comparing mogamulizumab against ECM were (depending on whether the HES or MAVORIC comparison were used) £31,030 or £32,634 per quality-adjusted life years (QALYs) gained according to the company’s base case and £38,274 or £80,555 per QALY gained according to the ERG’s base case. NICE did not recommend mogamulizumab for treating MF or SS in adults who have had at least one previous systemic treatment. This decision was subsequently appealed, and an appeal decision has been reached.

Reducing the Risk of Transmission of Critical Antimicrobial Resistance Determinants From Contaminated Pork Products to Humans in South-East Asia.

Antimicrobial resistance (AMR) is a critical challenge worldwide as it impacts public health, especially via contamination in the food chain and in healthcare-associated infections. In relation to farming, the systems used, waste management on farms, and the production line process are all determinants reflecting the risk of AMR emergence and rate of contamination of foodstuffs. This review focuses on South East Asia (SEA), which contains diverse regions covering 11 countries, each having different levels of development, customs, laws, and regulations. Routinely, here as elsewhere antimicrobials are still used for three indications: therapy, prevention, and growth promotion, and these are the fundamental drivers of AMR development and persistence. The accuracy of detection of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARG) depends on the laboratory standards applicable in the various institutes and countries, and this affects the consistency of regional data. Enterobacteriaceae such as Escherichia coli and Klebsiella pneumoniae are the standard proxy species used for indicating AMR-associated nosocomial infections and healthcare-associated infections. Pig feces and wastewater have been suspected as one of the hotspots for spread and circulation of ARB and ARG. As part of AMR surveillance in a One Health approach, clonal typing is used to identify bacterial clonal transmission from the production process to consumers and patients – although to date there have been few published definitive studies about this in SEA. Various alternatives to antibiotics are available to reduce antibiotic use on farms. Certain of these alternatives together with improved disease prevention methods are essential tools to reduce antimicrobial usage in swine farms and to support global policy. This review highlights evidence for potential transfer of resistant bacteria from food animals to humans, and awareness and understanding of AMR through a description of the occurrence of AMR in pig farm food chains under SEA management systems. The latter includes a description of standard pig farming practices, detection of AMR and clonal analysis of bacteria, and AMR in the food chain and associated environments. Finally, the possibility of using alternatives to antibiotics and improving policies for future strategies in combating AMR in a SEA context are outlined.

Product of return and lagged shock, representativeness, dynamic overconfidence and return predictability

Motivated by the representativeness heuristic and dynamic overconfidence, we introduce a new proxy (product of return and lagged shock) for return predictability. We further propose a novel time-varying parameter moving average (MA) model, where time-varying MA coefficient is a linear function of past values of the standardized proxy. For monthly S&P 500 stock returns, the proposed model significantly improves out-of-sample predictability, indicating that the proxy is helpful for return predictability. Our forecast also outperforms most of 14 traditional predictors in Welch and Goyal (2008). More importantly, we find that the proxy has a significant positive effect on time-varying MA coefficient, providing empirical evidence for the representativeness in aggregate stock market. Finally, the proxy with two positive shocks (good outcomes) has a much stronger positive effect on MA coefficient than that of two negative or opposite outcomes. Thus, the investors give a higher weight on the lagged shock in face of the proxy with two good outcomes, indicating the dynamic overconfidence (Daniel and Hirshleifer, 2015).

Firm Informativeness, Information Environment, and Accounting Quality in Emerging Countries

Using standard proxies for accounting quality, with a focus on earnings persistence and earnings management, we examine how the association between firm-level informativeness and accounting quality varies according to the quality of the country-level information environment. Our sample comprises over 15,000 publicly traded firms from 21 countries included in the Morgan Stanley Capital International (MSCI) Emerging Markets Index, between the years 2000 and 2016. Using novel proxies that aggregate several firm- or country-level characteristics associated with lower information asymmetry or higher-quality information environment, we find that in emerging markets with weaker information environments, the positive association between firm-level informativeness and accounting quality is more pronounced, suggesting that greater firm-level informativeness may partially compensate for weaker country-level institutions. Consistent with the substitution effect, we also document that the positive association between firm-level informativeness and stock market performance is greater in emerging countries with weaker information environments.

From Macroeconomic Shocks to Credit Spreads

We identify the response of corporate bond credit spreads to three exogenous macroeconomic shocks: oil supply, investment-specific technology, and government spending. The response is large, significant, and close to a mirror image of the response of macroeconomic activity. The counter-cyclicality of credit spreads is mostly driven by time-varying credit risk premia, which translates into significant predictability in corporate bond returns. Standard proxies for equity risk premia exhibit similar responses, providing external validity to this argument. As causal evidence linking large, infrequent macro-shocks to credit risk premia is scarce and recent work mostly focuses on the real effects of credit market fluctuations, our findings contribute to understanding the joint dynamics of credit markets and the macroeconomy.

Compiled records of atmospheric CO2 concentrations and stable carbon isotopes to reconstruct climate and derive plant ecophysiological indices from tree rings

The stable carbon isotopic composition (δ13C) measured in tree rings is a standard proxy for paleoclimate reconstructions and is increasingly being used as a paleophysiological proxy. To fully exploit the potential of tree ring δ13C proxy, atmospheric CO2 concentration and δ13C (δ13CO2) data are required to correct tree ring δ13C from the declining trend of δ13CO2 due to fossil fuel burning since 1850 CE, and to derive physiological parameters using biochemical models that link photosynthesis to δ13C. These atmospheric data are available from direct measurements or can be inferred from indirect proxies such as ice cores covering the Common Era (CE) at variable temporal resolutions. For almost two decades, tree-ring researchers have relied on a dataset derived from fitted linear regressions of ice core measurements available through the seminal McCarroll and Loader (2004) article for the 1850−2003 CE period. However, new calibrations and compilations of ice core data and direct measurements are now available as part of Earth System Modelling efforts which remain overlooked by the tree ring research community.Here, we present an overview of the new and freely available datasets and provide recommendations for their use in ecophysiology and paleoclimate research, that we expect will stimulate cross-disciplinary collaborations.