Observer Bias Research Articles

Of hormones (well, not really!), behavior, and observer bias

Of hormones (well, not really!), behavior, and observer bias

Breast cancer patients are getting younger; reality or observer bias?

Breast cancer patients are getting younger; reality or observer bias?

Comprehensive evaluation of a new automatic scoring system for cleanliness assessment in video capsule endoscopy

AbstractA reliable, quick‐to‐assess, and automatic scoring system for cleanliness assessment in video capsule endoscopy (VCE) is presently not available. The present study proposes an approach to automatically assess the cleanliness in VCE frames as per the latest scoring system, that is, Korea‐Canada (KODA). First, a new multi‐label frame dataset containing medical scores of 28 VCE videos was generated through the proposed mobile‐based application called Artificial Intelligence‐KODA (AI‐KODA) score. The scores were saved automatically in real‐time through the application. The generated dataset was transformed into three datasets based on the scores, and each of the dataset was then randomly split into train:validate:test ratio of 60:20:20. Second, a comprehensive evaluation, interpretation, and benchmarking of the three classification tasks were performed with the help of eight transfer learning algorithms on NVIDIA RTX A5000 workstation. Thorough analysis indicates that AI‐KODA utilized with AI is reliable, quick‐to‐access, and free from observer bias. It promotes automatic scoring system for cleanliness assessment in VCE. The meta‐data is available here (link).

A 350 MHz Green Bank Telescope Survey of Unassociated Fermi LAT Sources: Discovery and Timing of 10 Millisecond Pulsars

We have searched for radio pulsations toward 49 Fermi Large Area Telescope (LAT) 1FGL Catalog γ-ray sources using the Green Bank Telescope at 350 MHz. We detected 18 millisecond pulsars (MSPs) in blind searches of the data; 10 of these were discoveries unique to our survey. 16 are binaries, with eight having short orbital periods P B < 1 day. No radio pulsations from young pulsars were detected, although three targets are coincident with apparently radio-quiet γ-ray pulsars discovered in LAT data. Here, we give an overview of the survey and present radio and γ-ray timing results for the 10 MSPs discovered. These include the only isolated MSP discovered in our survey and six short-P B binary MSPs. Of these, three have very-low-mass companions (M c ≪ 0.1 M ⊙) and hence belong to the class of black widow pulsars. Two have more massive, nondegenerate companions with extensive radio eclipses and orbitally modulated X-ray emission consistent with the redback class. Significant γ-ray pulsations have been detected from nine of the discoveries. This survey and similar efforts suggest that the majority of Galactic γ-ray sources at high Galactic latitudes are either MSPs or relatively nearby nonrecycled pulsars, with the latter having on average a much smaller radio/γ-ray beaming ratio as compared to MSPs. It also confirms that past surveys suffered from an observational bias against finding short-P B MSP systems.

Land Use Change Alters Soil Organic Carbon: Constrained Global Patterns and Predictors

AbstractLand use change (LUC) alters the global carbon (C) stock, but our estimation of the alteration remains uncertain and is a major impediment to predicting the global C cycle. The uncertainty is partly due to the limited number and geographical bias of observations, and limited exploration of its predictors. Here we generated a comprehensive global database of 5,980 observations from 790 articles. The number of sites evaluated is at least seven times larger than in previous meta‐analyses. Our constrained estimates of different LUC's effects on soil organic C (SOC) and their variations across global climates reveal underestimation/overestimation in previous estimates. Converting forests and grasslands to croplands reduced SOC by 24.5% ± 1.53% (−11.03 ± 1.06 Mg ha−1) and 22.7% ± 1.22% (−8.09 ± 0.67 Mg ha−1), while 28.0% ± 1.56% (4.46 ± 0.42 Mg ha−1) and 33.5% ± 1.68% (5.8 ± 0.38 Mg ha−1) increases, respectively, were obtained in the reverse processes. Converting forests to grasslands decreased SOC by 2.1% ± 1.22% (−1.13 ± 0.44 Mg ha−1), while the reverse process increased SOC by 18.6% ± 1.73% (3.31 ± 0.51 Mg ha−1). Modeled relative importance of 10 drivers of LUC's impact on SOC revealed that higher initial SOC (iSOC) does not solely determine SOC loss in SOC‐negative LUC scenarios as previously proposed. Across four decades, reconverting croplands to forests and grasslands recovered only 49.5% (6.1 ± 0.51 Mg ha−1) and 75.3% (7.0 ± 0.38 Mg ha−1) of the iSOC, respectively, indicating the need for protecting C‐rich ecosystems. Our global data set advances information on LUC's effect on SOC and can be valuable to constrain Earth system models to reliably estimate global SOC stocks and plan climate change mitigation strategies.

Using computer vision libraries to streamline nuclei quantification: A validation study

Valid analyses of cell function-based experiments depend on accuracy and reproducibility of the experimental protocol, often requiring normalization to cell count or other measures. The process of counting cells manually is laborious and susceptible to human error. Although cell counting programs exist, they are not preferred by all users, may be cost-prohibitive, and validation is minimal. Therefore, we aimed to validate an object visualization effciency tool that we developed to provide users with an alternative means of automated cell counting for the very specific, necessary, and widely performed task: quantifying nuclei to assess cell count in images. We hypothesized strong agreement between manual and automated counts. To ensure validation across cell densities, C2C12 myoblasts were seeded at 7.3x104 cells per cm2, proliferated for various timeframes (24, 48, and 72 hours; 6 wells across 2 plates per time point), and fixed with ice-cold methanol for 10 minutes. The nuclei were then stained using the fluorescent DNA stain, 4’,6-diamidino-2-phenylindole (DAPI), and 5 images per well were captured. The number of nuclei in each image were manually quantified by 2 separate raters (MC1 and MC2) using ImageJ, and with our automated program developed using computer vision libraries in Python (AI). To minimize risk for observer bias, AI counts and counts completed by each rater were kept separately until all 3 counts for each image were complete. To validate the program, we assessed interrater reliability between 1) MC1 and MC2 to ensure manual count agreement and 2) the average of MC1 and MC2 (MCavg) with AI to assess agreement between manual and AI counts. Spearman’s Rho (rs) was utilized to assess the strength of the association between counts across all images and separately for each quartile (Q) where Q1 had the fewest and Q4 had the most nuclei by manual counts. Nuclei per image ranged from 44 to 1166. Interrater reliability was nearly perfect between MC1 and MC2 (ICC=0.999) and between MCavg and AI (ICC=0.991). A significant, strong correlation was observed between AI and MCavg (rs=0.998, p&lt;0.001). This strong correlation between persisted regardless of cell density (MCavg vs AI: Q1: rs=.998, p&lt;0.001; Q2: rs=0.999, p&lt;0.001; Q3: rs=1.000, p&lt;0.001; Q4: rs=1.000, p&lt;0.001). The results indicate strong agreement between nuclei counts obtained manually and using our automated object recognition program, which remained consistent regardless of cell quantity, demonstrating the validity of this program. Therefore, the automated object recognition program analyzed in the present study can be considered an accurate, rapid, user-friendly, and inexpensive resource for quantifying nuclei to assess cell count across a range of cell densities. Use of this software will save the user valuable time during the critically important but often time-consuming task of quantifying nuclei. Danielle Levitt's start-up funding through Texas Tech University. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Breathe Easy, an automated respiratory data pipeline for waveform characteristic analysis

Whole body barometric flow through plethysmography is used to study respiratory output in rodent genetic and disease models. Turn-key commercial and custom systems are both used to gather multiple data streams for respiratory and metabolic parameters. Comprehensive and accurate data analysis is crucial to modelling congenital, pathogenic, and degenerative diseases. However, such studies produce large amounts of data that are time-consuming and diffcult to analyze. The investigator may use cumbersome hand annotation subject to observer bias or a series of software products to manage raw data, calculated data, statistical analysis, and graphing. Commercial software, however, is prohibitively expensive or bundled with turn-key systems limiting options for bespoke respiratory measurement systems. A lack of tools for high-throughput analysis of respiratory datasets remains a major challenge. Here, we present Breathe Easy, a novel open-source pipeline for processing raw recordings and associated metadata into operative outcomes, publication-worthy graphs, and robust statistical analyses including QQ and residual plots for assumption queries and data transformations. This pipeline uses a facile graphical user interface (GUI) for uploading data files, setting waveform feature thresholds, and defining experimental variables. After loading the GUI a, python-based program, Signal Analysis Selection and Segmentation Integration (SASSI) takes the user-settings and selects all quantitatively defined, quality breaths from each period of interest in the signal files. After SASSI, the STatistics and Graph Generator (STAGG) takes those breaths and performs linear mixed effects modeling based on user selections for each dependent variable of interest. Furthermore, our software can integrate non-respiratory experimental outcomes including quantified behavioral or gene expression data to test for breathing related associations. To validate breath selection and generate optimized default values, results from Breathe Easy were compared to manual selection by experts, which represents the current standard in the field. We show high quality breath selection and a significant reduction in quality of breaths that were rejected by the software. We also demonstrate Breathe Easy’s utility and capacity by examining a 2-year longitudinal study of an Alzheimer’s Disease mouse model to assess contributions of forebrain pathology in disordered breathing (600+ files; 1TB data). We show that, at least with this model of AD, there does not seem to be an association between forebrain pathology and respiratory outcomes. Breathe Easy offers a facile and highly customizable platform for automated handling and analysis of animal respiratory and metabolic data that sets the stage for high-throughput studies and machine learning approaches on large data sets. NIH: 1F32HL160073-01A1, R01HL130249 44617-S4. BCM McNair Scholar Program, March of Dimes Basil O'Connor Research Award, Parker B. Francis Fellowship, CJ Foundation for SIDS. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Low Contact Strategy to Measure Flutamide’s Effects on Territorial Aggression in C57BL/6J Male Mice

While numerous factors contribute to mouse behavior, biological drivers are paramount to many regulatory processes that undergird behavior. In particular, the sex hormone testosterone plays a key role in the regulation of aggression, physical activity, mating, and other behaviors known to be influenced by the presence of an experimenter. Due to this experimenter bias, strategies that minimize direct and frequent contact with research animals are needed to reduce any undesirable effects. The purpose of this research was to explore the effects of an androgen receptor antagonist (Flutamide) on territorial aggression in male C57BL/6J mice utilizing a low contact technique for chemical delivery. It was hypothesized that the introduction of an androgen receptor inhibiting substance under a low contact delivery strategy would result in effective reduction of the territorial aggression response in mice introduced to an unknown male mouse in the home cage environment, mimicking similar blunting responses characterized in previous work evaluating aggression in rodents. Silastic (Dow Corning, Midland, MI) implants were used as the lower contact delivery strategy for drug administration. This strategy allowed minimal contact with the experimental technician and eliminated the need for daily contact required for the commonly used injection strategies employed elsewhere. A series of aggression trials before, 24, 96, and 192 hours after Flutamide implantation were conducted in three groups of mice. Control mice (n=4) received 100% Cholesterol-containing implants, low exposure mice (n=5) received 80% Cholesterol/20% Flutamide-containing implants, and high exposure mice (n=5) received 100% Flutamide-containing implants. Each aggression trial consisted of introducing a foreign mouse to an experimental mouse’s home cage for an 8-minute period. The time to initial aggression and the total number of aggressions over the 8 minutes was quantified. The time to initial aggression was unaffected by flutamide administration throughout the study [F(26,91) =0.37, p=0.864]. The total number of aggressions were significantly affected by flutamide exposure [F(28,82) = 2.90, p=0.029]. Follow-up post hoc testing indicated a significant reduction in aggression in both the low and high dose groups 24 (low: p = 0.001; high = 0.001) and 96 (low: p = 0.009; high = 0.012) hours after implantation compared to the control at the same time points. The use of Silastic implants to deliver the anti-androgenic compound was a valuable technique that reduced research animal contact with experimental technicians. This technique can be modified for prolonged exposure by lengthening the implant or increasing the diameter of the Silastic tubing. This anti-androgen exposure methodology requiring less interaction reduces the confounding variables that impact mouse behavior and could prove beneficial to observe and study other androgen-related behaviors including physical activity and mating. All funding for this research was provided by the Union University Department of Biology. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

A3COSMOS and A3GOODSS: Continuum source catalogues and multi-band number counts

Context. Galaxy submillimetre number counts are a fundamental measurement in our understanding of galaxy evolution models. Most early measurements are obtained via single-dish telescopes with substantial source confusion, whereas recent interferometric observations are limited to small areas. Aims. We used a large database of ALMA continuum observations to accurately measure galaxy number counts in multiple (sub)millimetre bands, thus bridging the flux density range between single-dish surveys and deep interferometric studies. Methods. We continued the Automated Mining of the ALMA Archive in the COSMOS Field project (A3COSMOS) and extended it with observations from the GOODS-South field (A3GOODSS). The database consists of ∼4000 pipeline-processed continuum images from the public ALMA archive, yielding 2050 unique detected sources, including sources with and without a known optical counterpart. To infer galaxy number counts, we constructed a method to reduce the observational bias inherent to targeted pointings that dominate the database. This method comprises a combination of image selection, masking, and source weighting. The effective area was calculated by accounting for inhomogeneous wavelengths, sensitivities, and resolutions and for the spatial overlap between images. We tested and calibrated our method with simulations. Results. We derived the number counts in a consistent and homogeneous way in four different ALMA bands covering a relatively large area. The results are consistent with number counts retrieved from the literature within the uncertainties. In Band 7, at the depth of the inferred number counts, ∼40% of the cosmic infrared background is resolved into discrete sources. This fraction, however, decreases with increasing wavelength, reaching ∼4% in Band 3. Finally, we used the number counts to test models of dusty galaxy evolution, and find a good agreement within the uncertainties. Conclusions. By continuing the A3COSMOS and A3GOODSS archival effort, we obtained the deepest archive-based (sub)millimetre number counts measured to date over such a wide area. This database proves to be a valuable resource that, thanks to its substantial size, can be used for statistical analyses after having applied certain conservative restrictions.

Narrowly Banded Spectra with Peak Frequency around 1 GHz of FRB 20201124A: Implications for Energy Function and Radiation Physics

The radiation physics of fast radio bursts (FRBs) remains an open question. Current observations have discovered that narrowly banded bursts of FRB 20201124A are active in 0.4–2 GHz, and their spectral peak frequency ( νpobs ) is mostly toward ∼1 GHz. Utilizing a sample of 1268 bursts of FRB 20201124A detected with the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we show that the 1σ spectral regime of 71.4% of the events (in-band bursts) is within the FAST bandpass. The intrinsic burst energies ( EBWeobs ) and spectral widths ( σsobs ) are well measured by fitting the spectral profile with a Gaussian function. The derived EBWeobs and σsobs distributions are lognormal and centered at logEBWeobs/erg=37.2(σ=0.76) and logσsobs/GHz=−1.16(σ=0.17) . Our Monte Carlo simulation analysis infers its intrinsic ν p distribution as a normal function centered at ν p,c = 1.16 GHz (σ = 0.22) and its intrinsic energy function as Φ(E)∝E−0.60e−E/Ec with E c = 9.49 × 1037 erg. We compare these results with that of typical repeating FRBs 20121102A and 20190520B, which are active over a broad frequency range at several specific frequencies, and discuss possible observational biases on the estimation of the event rate and energy function. Based on these results, we argue that FRB 20201124A likely occurs in a fine-tuned plasma for maser radiation at a narrow frequency range, while FRB 20121102A and FRB 20190520B could involve clumpy plasma conditions that make maser emission around several specific frequencies in a broad range.

Generation of Low-inclination, Neptune-crossing Trans-Neptunian Objects by Planet Nine

The solar system’s distant reaches exhibit a wealth of anomalous dynamical structure, hinting at the presence of a yet-undetected, massive trans-Neptunian body—Planet Nine (P9). Previous analyses have shown how orbital evolution induced by this object can explain the origins of a broad assortment of exotic orbits, ranging from those characterized by high perihelia to those with extreme inclinations. In this work, we shift the focus toward a more conventional class of TNOs and consider the observed census of long-period, nearly planar, Neptune-crossing objects as a hitherto-unexplored probe of the P9 hypothesis. To this end, we carry out comprehensive N-body simulations that self-consistently model gravitational perturbations from all giant planets, the Galactic tide, as well as passing stars, stemming from initial conditions that account for the primordial giant planet migration and Sun's early evolution within a star cluster. Accounting for observational biases, our results reveal that the orbital architecture of this group of objects aligns closely with the predictions of the P9-inclusive model. In stark contrast, the P9-free scenario is statistically rejected at a ∼5σ confidence level. Accordingly, this work introduces a new line of evidence supporting the existence of P9 and further delineates a series of observational predictions poised for near-term resolution.

New experimental measurements of X-ray emissions induced by protons of several tens of MeV on elements with Z=22 to Z=79: Toward quantitative high-energy PIXE

K-shell X-ray production cross-sections measurement campaigns were carried out at the ARRONAX cyclotron with titanium, chromium, copper, molybdenum, silver and gold targets for different energies from 15 to 68 MeV. These measurements, carried out using three detectors (SDD, CdTe and HPGe), complete the database with 66 new values. Our different measurements agree with previously published data and are consistent for all three detectors, confirming the absence of experimental bias. The universal ionisation cross-section representation allows an optimisation of the data using a 3rd-order polynomial function. This function can be used for HE-PIXE quantification for elements with atomic numbers between 22 (Ti) and 79 (Au) in the studied energy region.

Deep‐learning‐powered data analysis in plankton ecology

ABSTRACTThe implementation of deep learning algorithms has brought new perspectives to plankton ecology. Emerging as an alternative approach to established methods, deep learning offers objective schemes to investigate plankton organisms in diverse environments. We provide an overview of deep‐learning‐based methods including detection and classification of phytoplankton and zooplankton images, foraging and swimming behavior analysis, and finally ecological modeling. Deep learning has the potential to speed up the analysis and reduce the human experimental bias, thus enabling data acquisition at relevant temporal and spatial scales with improved reproducibility. We also discuss shortcomings and show how deep learning architectures have evolved to mitigate imprecise readouts. Finally, we suggest opportunities where deep learning is particularly likely to catalyze plankton research. The examples are accompanied by detailed tutorials and code samples that allow readers to apply the methods described in this review to their own data.

Searching for precursor activity of Type IIn Supernovae

We conducted a search for luminous outbursts prior to the explosion of Type IIn supernovae (SNe IIn). We built a sample of 27 objects spectroscopically classified as SNe IIn and all located at $z&lt;0.015$. Using deep archival SN fields images ---taken up to nearly 20 years prior to the SN explosions themselves--- from transient surveys (PTF, ZTF, DES and CHASE) and major astronomical observatories (European Southern Observatory, ESO and National Optical Astronomy Observatory, NOAO), we found at least one outburst years to months before the explosion of seven SNe IIn, with the earliest precursor being 10 years prior to the explosion of SN 2019bxq. The maximum absolute magnitudes of the outbursts range between $-$11.5 mag and $-$15 mag, and the eruptive phases last for a few weeks to a few years. The $g-r$ colour measured for three objects during their outburst is relatively red, with $g-r$ ranging between 0.5 and 1.0 mag. This is similar to the colour expected during the eruptions of luminous blue variables. We note that the light curves of SNe with pre-SN outbursts have faster decline rates than those of the SNe that do not show pre-SN outbursts. SN 2011fh is remarkable, as it is still visible 12 years after the luminous SN-like event, indicating that the progenitor possibly survived, or that the interaction is still ongoing. We detect precursor activity in 29&lt;!PCT!&gt; of bona fide SNe IIn in our sample. However, a quantitative assessment of the observational biases affecting the sample suggests that this fraction is an underestimation of the intrinsic precursor occurrence rate.

Experimenter bias: exploring the interaction between participant’s and investigator’s gender/sex in VR

This study explores the effect of the experimenter’s gender/sex and its interaction with the participant’s gender/sex as potential contributors to the replicability crisis, particularly in the man-gendered domain of VR. 75 young men and women from Western France were randomly evaluated by either a man or a woman during a 13-min immersion in a first-person shooter game. Self-administered questionnaires were used to measure variables commonly assessed during VR experiments (sense of presence, cybersickness, video game experience, flow). MANOVAs, ANOVAs and post-hoc comparisons were used. Results indicate that men and women differ in their reports of cybersickness and video game experience when rated by men, whereas they report similar measures when rated by women. These findings are interpreted as consequences of the psychosocial stress triggered by the interaction between the two genders/sexes, as well as the gender conformity effect induced, particularly in women, by the presence of a man in a masculine domain. Corroborating this interpretation, the subjective measure of flow, which is not linked to video games and/or computers, does not seem to be affected by this experimental effect. Methodological precautions are highlighted, notably the brief systematic description of the experimenter, and future exploratory and confirmatory studies are outlined.Graphical abstract

P-values and confidence intervals for weighted log-rank tests under truncated binomial design based on clustered medical data

ABSTRACT The randomization design employed to gather the data is the basis for the exact distributions of the permutation tests. One of the designs that is frequently used in clinical trials to force balance and remove experimental bias is the truncated binomial design. The exact distribution of the weighted log-rank class of tests for censored cluster medical data under the truncated binomial design is examined in this paper. For p-values in this class, a double saddlepoint approximation is developed using the truncated binomial design. With the right censored cluster data, the saddlepoint approximation’s speed and accuracy over the normal asymptotic make it easier to invert the weighted log-rank tests and find nominal 95 % confidence intervals for the treatment effect.

Reducing Interference Bias in Online Marketplace Experiments Using Cluster Randomization: Evidence from a Pricing Meta-experiment on Airbnb

Online marketplace designers frequently run randomized experiments to measure the impact of proposed product changes. However, given that marketplaces are inherently connected, total average treatment effect (TATE) estimates obtained through individual-level randomized experiments may be biased because of violations of the stable unit treatment value assumption, a phenomenon we refer to as “interference bias.” Cluster randomization (i.e., the practice of randomizing treatment assignment at the level of “clusters” of similar individuals) is an established experiment design technique for countering interference bias in social networks, but it is unclear ex ante if it will be effective in marketplace settings. In this paper, we use a meta-experiment or “experiment over experiments” conducted on Airbnb to both provide empirical evidence of interference bias in online marketplace settings and assess the viability of cluster randomization as a tool for reducing interference bias in marketplace TATE estimates. Results from our meta-experiment indicate that at least 20% of the TATE estimate produced by an individual-level randomized evaluation of the platform fee increase we study is attributable to interference bias and eliminated through the use of cluster randomization. We also find suggestive, nonstatistically significant evidence that interference bias in seller-side experiments is more severe in demand-constrained geographies and that the efficacy of cluster randomization at reducing interference bias increases with cluster quality. This paper was accepted by Chris Forman, information systems. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2020.01157 .

Evaluation of Wintertime Precipitation Estimates and Forecasts in the Mountains of Colorado

Abstract Wintertime precipitation poses many observational and forecasting challenges, especially in the complex topography of the western United States where radar beam blockage and difficulty siting in situ observations yields more sparse observations than in the eastern United States. Uncertainty in western U.S. winter precipitation is known to be high, so much so that some studies have found model simulated precipitation to produce similar or better large-scale estimates of annual precipitation than gridded observational products during climatologically anomalous years. This study evaluates high-resolution gridded precipitation estimates from Multi-Radar Multi-Sensor (MRMS) and Stage IV as well as forecasts from NOAA’s High-Resolution Rapid Refresh (HRRR) model in the Colorado Rocky Mountains. Gridded precipitation estimates and forecasts are compared with in situ SNOTEL measurements for two seasons of wintertime precipitation. The influence of forecast length, lead time, and model elevation on seasonal precipitation predictions from the HRRR are investigated. Additional comparisons are made with the relatively dense network of observations deployed in Colorado’s East River Watershed during the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign. Gridded products and forecasts are found to underestimate cold-season precipitation by 25%–65% relative to in situ and aircraft measurements, with longer forecast periods and lead times (6–24 h) having smaller biases (25%–30%) than shorter forecast periods and lead times (55%–65%). The assessment of multiple years of observations indicates that these biases are related more to the data and methods used to create the gridded products and forecasts than to precipitation characteristics. Significance Statement In the mountainous western United States, it is very challenging to both observe and forecast wintertime precipitation, yet snowfall plays an important role in providing the region’s annual water supply. This study aims to increase our understanding of the biases in observations and forecasts of snowfall in the Colorado Rocky Mountains, which can in turn impact forecasts of water availability for the ensuing warm season. In this study we find high-resolution gridded precipitation estimates and forecasts to underestimate cold-season precipitation when compared with in situ observing stations, with longer-range forecasts (e.g., daily) being the least biased. These findings were consistent over two years of study and have broad implications for the hydrologic modeling and water management communities.

Large deformation diffeomorphic mapping of 3D shape variation reveals two distinct mandible and head capsule morphs in Atta vollenweideri leaf-cutter worker ants.

Ants are crucial ecosystem engineers, and their ecological success is facilitated by a division of labour among sterile "workers". In some ant lineages, workers have undergone further morphological differentiation, resulting in differences in body size, shape, or both. Distinguishing between changes in size and shape is not trivial. Traditional approaches based on allometry reduce complex 3D shapes into simple linear, areal, or volume metrics; modern approaches using geometric morphometrics typically rely on landmarks, introducing observer bias and a trade-off between effort and accuracy. Here, we use a landmark-free method based on large deformation diffeomorphic metric mapping (LDDMM) to assess the co-variation of size and 3D shape in the mandibles and head capsules of Atta vollenweideri leaf-cutter ants, a species exhibiting extreme worker size-variation. Body mass varied by more than two orders of magnitude, but a shape atlas created via LDDMM on μ-CT-derived 3D mesh files revealed only two distinct head capsule and mandibles shapes-one for the minims (body mass < 1 mg) and one for all other workers. We discuss the functional significance of the identified 3D shape variation, and its implications for the evolution of extreme polymorphism in Atta.

Comparative Effectiveness of Partial Gland Cryoablation Versus Robotic Radical Prostatectomy for Cancer Control

Background and objectiveThere is an absence of high-level evidence comparing oncologic endpoints for partial gland ablation, and most series used prostate-specific antigen (PSA) rather than biopsy endpoints. Our aim was to compare oncologic outcomes between partial gland cryoablation (PGC) and radical prostatectomy (RP) for prostate cancer. MethodsThis was a retrospective, single-center analysis of subjects treated with PGC (n = 98) or RP (n = 536) between January 2017 and December 2022 as primary treatment for intermediate-risk (Gleason grade group [GG] 2–3) prostate cancer. Oncologic endpoints included protocol surveillance biopsies after PGC in comparison to serial PSA testing after RP. The primary outcome was treatment failure, defined as a need for any salvage treatment or development of metastatic disease. Treatment failure and survival analyses were conducted using Cox proportional-hazard regression and Kaplan Meier survival curves. Key findings and limitationsAfter applying the inclusion/exclusion criteria, the PGC (n = 75) and RP (n = 298) groups were compared. PGC patients were significantly older (71 vs 64 yr; p < 0.001) but there were no differences in PSA, biopsy GG, or treatment year between the groups. The PGC group had higher rates of treatment failures at 24 mo (33% vs 11%; p < 0.001) and 48 mo (43% vs 14%; p < 0.001). One PGC patient (2.1%) and one RP patient (0.7%) had developed metastases by 48-mo follow-up (p = 0.4). On adjusted analysis, PGC was associated with a higher risk of treatment failure (hazard ratio 4.6, 95% confidence interval 2.7–7.9; p < 0.001). Limitations include observational biases associated with the retrospective study design. ConclusionsThis is the first comparative effectiveness study of cancer control outcomes for PGC versus RP. The results demonstrate an almost fivefold higher risk of treatment failure with PGC during short-term follow-up. Patient summaryWe compared cancer control outcomes for patients with intermediate-risk prostate cancer treated with partial prostate gland cryoablation versus radical prostatectomy. We found that partial gland cryoablation had an almost fivefold higher risk of treatment failure. Men with prostate cancer should be counseled regarding this difference in treatment failure.