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Abstract The diagnosis of prostate cancer using histopathology is reliant on the accurate interpretation of prostate tissue sections. Current standards rely on the assessment of Haematoxylin and Eosin (H&E) staining, which can be difficult to interpret and introduce inter-observer variability. Here, we present a digital pathology atlas and online resource of prostate cancer tissue micrographs for both H&E and the reinterpretation of samples using a novel set of three biomarkers as an interactive tool, where clinicians and scientists can explore high resolution histopathology from various case studies. The digital pathology prostate cancer atlas when used in conjunction with the biomarkers, will assist pathologists to accurately grade prostate cancer tissue samples.

Abstract In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston’s proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})

This study aimed to evaluate the effectiveness of a computer-assisted ultrasound analysis of senile dogs cataractous lens and identify its correlation to phacoemulsification surgical parameters. Simultaneous A- and B- mode ultrasonic evaluation of the lens was performed on 15 dogs with cataract. A computer-assisted image analysis was used to objectively calculate the lens echogenicity. Following ultrasonographic examination the cataracts were removed by phacoemulsification and the ultrasonographic and phacoemulsification findings were compared to identify possible correlations. Lens echogenicity obtained by the computer-assisted ultrasonographic analysis correlated to the phacoemulsification time, such that the whiter the ultrasound image, the longer was the phacoemulsification time. The B-mode ultrasonography was helpful for the prediction of lens opacity location, but not predictive of lens hardness.

Abstract Background Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate cancer has been reported to increase proliferation and invasion. The exact role of AZGP1 in prostate cancer progression remains elusive. Method AZGP1 knockout and overexpressing prostate cancer cells were generated using a lentiviral system. The effects of AZGP1 under- or over-expression in prostate cancer cells were evaluated by in vitro cell proliferation, migration, and invasion assays. Heterozygous AZGP1± mice were obtained from European Mouse Mutant Archive (EMMA), and prostate tissues from homozygous knockout male mice were collected at 2, 6 and 10 months for histological analysis. In vivo xenografts generated from AZGP1 under- or over-expressing prostate cancer cells were used to determine the role of AZGP1 in prostate cancer tumor growth, and subsequent proteomics analysis was conducted to elucidate the mechanisms of AZGP1 action in prostate cancer progression. AZGP1 expression and microvessel density were measured in human prostate cancer samples on a tissue microarray of 215 independent patient samples. Result Neither the knockout nor overexpression of AZGP1 exhibited significant effects on prostate cancer cell proliferation, clonal growth, migration, or invasion in vitro. The prostates of AZGP1−/− mice initially appeared to have grossly normal morphology; however, we observed fibrosis in the periglandular stroma and higher blood vessel density in the mouse prostate by 6 months. In PC3 and DU145 mouse xenografts, over-expression of AZGP1 did not affect tumor growth. Instead, these tumors displayed decreased microvessel density compared to xenografts derived from PC3 and DU145 control cells, suggesting that AZGP1 functions to inhibit angiogenesis in prostate cancer. Proteomics profiling further indicated that, compared to control xenografts, AZGP1 overexpressing PC3 xenografts are enriched with angiogenesis pathway proteins, including YWHAZ, EPHA2, SERPINE1, and PDCD6, MMP9, GPX1, HSPB1, COL18A1, RNH1, and ANXA1. In vitro functional studies show that AZGP1 inhibits human umbilical vein endothelial cell proliferation, migration, tubular formation and branching. Additionally, tumor microarray analysis shows that AZGP1 expression is negatively correlated with blood vessel density in human prostate cancer tissues. Conclusion AZGP1 is a negative regulator of angiogenesis, such that loss of AZGP1 promotes angiogenesis in prostate cancer. AZGP1 likely exerts heterotypical effects on cells in the tumor microenvironment, such as stromal and endothelial cells. This study sheds light on the anti-angiogenic characteristics of AZGP1 in the prostate and provides a rationale to target AZGP1 to inhibit prostate cancer progression.

Abstract Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on 2603 histological images of prostate tissue stained with hematoxylin and eosin. We analyzed various factors influencing tumor grade discordance between the vPatho system and six human pathologists. Our results demonstrated that vPatho achieved comparable performance in prostate cancer detection and tumor volume estimation, as reported in the literature. The concordance levels between vPatho and human pathologists were examined. Notably, moderate to substantial agreement was observed in identifying complementary histological features such as ductal, cribriform, nerve, blood vessel, and lymphocyte infiltration. However, concordance in tumor grading decreased when applied to prostatectomy specimens (κ = 0.44) compared to biopsy cores (κ = 0.70). Adjusting the decision threshold for the secondary Gleason pattern from 5 to 10% improved the concordance level between pathologists and vPatho for tumor grading on prostatectomy specimens (κ from 0.44 to 0.64). Potential causes of grade discordance included the vertical extent of tumors toward the prostate boundary and the proportions of slides with prostate cancer. Gleason pattern 4 was particularly associated with this population. Notably, the grade according to vPatho was not specific to any of the six pathologists involved in routine clinical grading. In conclusion, our study highlights the potential utility of AI in developing a digital twin for a pathologist. This approach can help uncover limitations in AI adoption and the practical application of the current grading system for prostate cancer pathology.

Abstract Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC–MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies.

The recent emergence of SARS-CoV-2 in 2019 has highlighted the necessity of antiviral therapeutics for current and future emerging coronaviruses. Recently, the traditional herbal medicines baicalein, baicalin, and andrographolide have shown inhibition against the main protease of SARS-CoV-2. This provides a promising new direction for COVID-19 therapeutics, but it remains unknown whether these three substances inhibit other human coronaviruses. In this study, we describe the development of novel chimeric mouse hepatitis virus (MHV) reporters that express firefly luciferase (FFL) and the 3CLpro proteases of human coronaviruses HKU1 and OC43. These chimeric viruses were used to determine if the phytochemicals baicalein, baicalin, and andrographolide are inhibitory against human coronavirus strains HKU1 and OC43. Our data show that both baicalein and baicalin exhibit inhibition towards the chimeric MHV strains. However, andrographolide induces cytotoxicity and failed to demonstrate selective toxicity towards the viruses. This study reports the development and use of a safe replicating reporter platform to investigate potential coronavirus 3CLpro inhibitors against common-cold human coronavirus strains HKU1 and OC43.

BACKGROUND: Prompt treatment of acute exacerbations (AEs) in chronic obstructive pulmonary disease (COPD) improves quality of life and reduces the use of health care resources. Although patient self-management through an individualized action plan (AP) can help with early initiation of therapy, its use is critically dependent on the patient recognizing the features of an exacerbation.

The Dark Energy Spectroscopic Instrument (DESI) survey will measure spectroscopic redshifts for millions of galaxies across roughly $14,000 \, \mathrm{deg}^2$ of the sky. Cross-correlating targets in the DESI survey with complementary imaging surveys allows us to measure and analyze shear distortions caused by gravitational lensing in unprecedented detail. In this work, we analyze a series of mock catalogs with ray-traced gravitational lensing and increasing sophistication to estimate systematic effects on galaxy-galaxy lensing estimators such as the tangential shear $\gamma_{\mathrm{t}}$ and the excess surface density $\Delta\Sigma$. We employ mock catalogs tailored to the specific imaging surveys overlapping with the DESI survey: the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS). Among others, we find that fiber incompleteness can have significant effects on galaxy-galaxy lensing estimators but can be corrected effectively by up-weighting DESI targets with fibers by the inverse of the fiber assignment probability. Similarly, we show that intrinsic alignment and lens magnification are expected to be statistically significant given the precision forecasted for the DESI year-1 data set. Our study informs several analysis choices for upcoming cross-correlation studies of DESI with DES, HSC, and KiDS.

IntroductionEffective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms.MethodsWe investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables.ResultsSnap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

Abstract Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

Abstract Background Patients diagnosed with low-risk prostate cancer (PCa) are confronted with a difficult decision regarding whether to undergo definitive treatment or to pursue an active surveillance protocol. This is potentially further complicated by the possibility that patients and physicians may place different value on factors that influence this decision. We conducted a qualitative investigation to better understand patient and physician perceptions of factors influencing treatment decisions for low-risk PCa. Methods Semi-structured interviews were conducted among 43 racially and ethnically diverse patients diagnosed with low-risk PCa, who were identified through a population-based cancer registry, and 15 physicians who were selected to represent a variety of practice settings in the Greater San Francisco Bay Area. Results Patients and physicians both described several key individual (e.g., clinical) and interpersonal (e.g., healthcare communications) factors as important for treatment decision-making. Overall, physicians’ perceptions largely mirrored patients’ perceptions. First, we observed differences in treatment preferences by age and stage of life. At older ages, there was a preference for less invasive options. However, at younger ages, we found varying opinions among both patients and physicians. Second, patients and physicians both described concerns about side effects including physical functioning and non-physical considerations. Third, we observed differences in expectations and the level of difficulty for clinical conversations based on information needs and resources between patients and physicians. Finally, we discovered that patients and physicians perceived patients’ prior knowledge and the support of family/friends as facilitators of clinical conversations. Conclusions Our study suggests that the gap between patient and physician perceptions on the influence of clinical and communication factors on treatment decision-making is not large. The consensus we observed points to the importance of developing relevant clinical communication roadmaps as well as high quality and accessible patient education materials.

Purpose: Obtaining prior authorization (PA) before treatment is becoming increasingly burdensome in oncology, especially in radiation oncology. Here, we describe the impact of a strategic novel operational PA redesign to shorten authorization time and to improve patient access to cancer care at a large United States academic proton therapy center. We ask whether such a redesign may be replicable and adoptable across oncology centers. Materials and Methods: Our PA redesign strategy was based on a 3-tiered approach. Specifically, we (1) held payors accountable to legally backed timelines, (2) leveraged expertise on insurance policies and practices, and (3) updated the submission, appeal writing, and planning procedures for PA. Metrics were compared at the following 3 time points: 6 months before, at phase-in, and at 6 months after intervention. Results: In analyzing the impact of improving PA access to care, the percentage of approvals for commercial proton beam therapy improved by an absolute 30.6% postintervention (P < .001). The proportion of commercially insured patients treated with proton beam therapy also increased by 6.2%, and the number of new starts rose by 11.7 patients/mo. Overall patient census increased by 13 patients/d. Median authorization time was 1 week, and 90% of surveyed providers reported reduced PA burden and improved patient care. Conclusion: This is the first validated, comprehensive operational strategy to improve access to cancer therapy while reducing the burden of PA. This novel approach may be helpful for addressing barriers to PA in medical and surgical oncology because the redesign is predicated on laws that regulate PA across disciplines.

Nausea and vomiting during pregnancy (NVP), particularly its severe form, Hyperemesis gravidarum (HG), affects up to 70% of pregnancies and significantly impacts the quality of life for those with the condition as well as generates a great economic burden, with annual costs exceeding $1.7 billion in the United States. Despite the available treatments targeting neurotransmitters like serotonin and dopamine, many patients experience inadequate relief and suffer from severe side effects, including headaches and dizziness. Recent research has underscored the role of GDF15, a protein mainly produced by the placenta and linked to NVP symptoms. This protein, part of the TGF-β superfamily, has been implicated in appetite and weight regulation and is altered in those with HG due to specific genetic mutations. Addressing the challenges of delivering effective treatments, current innovations focus on targeting GDF15 to reduce symptoms while ensuring fetal safety. Promising therapeutic strategies include non-IgG immunotherapies, small peptide and molecule antagonists, and novel administration methods such as transdermal patches. These approaches aim to optimize dosage and reduce adverse effects. The effective development and testing of these treatments necessitate advanced animal models that closely resemble human pregnancy physiology, highlighting the need for further research and funding. This ongoing research holds significant potential to improve the clinical outcomes for HG patients and decrease the economic impact on healthcare systems, urging a dedicated response from the scientific and medical communities to advance these promising treatments.

While systemic shortcomings in meeting the needs of individuals with progressive chronic illnesses at the end of life have been well documented, there is growing interest in improving both care and quality of life for persons with advanced chronic obstructive pulmonary disease (COPD). For instance, the American Thoracic Society has issued an official statement on palliative care for patients with respiratory diseases, affirming that the prevention, relief, reduction and soothing of symptoms “without affecting a cure” must become an integral component of standard care. A recent Medline search located 1015 articles related to palliative or end-of-life care for people with COPD published between 2001 and 2008, compared with only 336 articles published before 2001. To address the needs of Canadian patients, an interdisciplinary consensus meeting, funded by the Canadian Institutes of Health Research and supported by the Canadian Thoracic Society, the Canadian Respiratory Health Professionals and the Canadian Lung Association was convened in Toronto, Ontario, on November 22, 2008, to begin examining the quality of end-of-life care for individuals with COPD in Canada. The present report summarizes the background to and outcomes of this consensus meeting.

Influenza A virus (IAV) infection in pregnancy resembles a preeclamptic phenotype characterised by vascular dysfunction and foetal growth retardation. Given that low dose aspirin (ASA) is safe in pregnancy and is used to prevent preeclampsia, we investigated whether ASA or NO-conjugated aspirin, NCX4016, resolve vascular inflammation and function to improve offspring outcomes following IAV infection in pregnant mice. Pregnant mice were intranasally infected with a mouse adapted IAV strain (Hkx31; 104 plaque forming units) and received daily treatments with either 200µg/kg ASA or NCX4016 via oral gavage. Mice were then culled and the maternal lungs and aortas collected for qPCR analysis, and wire myography was performed on aortic rings to assess endothelial and vascular smooth muscle functionality. Pup and placentas were weighed and pup growth rates and survival assessed. IAV infected mice had an impaired endothelial dependent relaxation response to ACh in the aorta, which was prevented by ASA and NCX4016 treatment. ASA and NCX4016 treatment prevented IAV dissemination and inflammation of the aorta as well as improving the pup placental ratios in utero, survival and growth rates at post-natal day 5. Low dose ASA is safe to use during pregnancy for preeclampsia and this study demonstrates that ASA may prove a promising treatment for averting the significant vascular complications associated with influenza infection during pregnancy.

Purpose: Male breast cancer treatment involves multimodality therapy, including radiation therapy; nevertheless, few men have received proton therapy (PT) for it. Further, heart disease is an established leading cause of death in men, and radiation therapy heart dose correlates with cardiac toxicity, highlighting the need for cardiac-sparing radiation techniques. Thus, we provide a descriptive analysis of PT in a male breast cancer cohort. Patients and Methods: Men who received PT for localized breast cancer between 2012 and 2022 were identified from a prospective database. Toxicities were prospectively recorded by using the Common Terminology Criteria for Adverse Events (CTCAE), version 4.0. Results: Five male patients were identified. All had estrogen receptor (ER)–positive, Her2neu-negative disease and received adjuvant endocrine therapy. One had genetic testing positive for BRCA2, one had a variant of unknown significance (VUS) in the APC gene, and one had a VUS in MSH2. Median age was 73 years (range, 41–80). Baseline comorbidities included obesity (n = 1), diabetes (n = 1), hypertension (n = 4), history of deep vein thrombosis (n = 1), personal history of myocardial infarction (n = 3; 1 with a pacemaker), and a history of lung cancer (n = 1). All received PT to the left chest wall and comprehensive regional lymphatics. One received passive-scattering PT, and 4 received pencil beam scanning. One patient received a boost to the mastectomy incision via electrons. Median heart dose was 1 GyRBE (range, 0–1.0), median 0.1-cm3 dose to the left anterior descending artery was 7.5 GyRBE (range, 0–14.2), and median follow-up was 2 years (range, 0.75–6.5); no patient experienced a new cardiac event, and all remain free from breast cancer recurrence and progression. Conclusion: In a small case series for a rare diagnosis, PT to the chest wall and regional lymphatics, including internal mammary nodes, resulted in low cardiac exposure, high local regional disease control rates, and minimal toxicity. Proton therapy should be considered for treating men with breast cancer to achieve cardiac sparing.

We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω _M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q _0 < 0 in ΛCDM) with over 5 σ confidence. We find $({{\rm{\Omega }}}_{{\rm{M}}},w)=({0.264}_{-0.096}^{+0.074},-{0.80}_{-0.16}^{+0.14})$ in flat w CDM. For flat w _0 w _a CDM, we find $({{\rm{\Omega }}}_{{\rm{M}}},{w}_{0},{w}_{a})=({0.495}_{-0.043}^{+0.033},-{0.36}_{-0.30}^{+0.36},-{8.8}_{-4.5}^{+3.7})$ , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω _M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

Introduction: Prostate cancer is a highly heterogeneous disease, presenting varying levels of aggressiveness and response to treatment. Angiogenesis is one of the hallmarks of cancer, providing oxygen and nutrient supply to tumors. Micro vessel density has previously been correlated with higher Gleason score and poor prognosis. Manual segmentation of blood vessels (BVs) In microscopy images is challenging, time consuming and may be prone to inter-rater variabilities. In this study, an automated pipeline is presented for BV detection and distribution analysis in multiplexed prostate cancer images.Methods: A deep learning model was trained to segment BVs by combining CD31, CD34 and collagen IV images. In addition, the trained model was used to analyze the size and distribution patterns of BVs in relation to disease progression in a cohort of prostate cancer patients (N = 215).Results: The model was capable of accurately detecting and segmenting BVs, as compared to ground truth annotations provided by two reviewers. The precision (P), recall (R) and dice similarity coefficient (DSC) were equal to 0.93 (SD 0.04), 0.97 (SD 0.02) and 0.71 (SD 0.07) with respect to reviewer 1, and 0.95 (SD 0.05), 0.94 (SD 0.07) and 0.70 (SD 0.08) with respect to reviewer 2, respectively. BV count was significantly associated with 5-year recurrence (adjusted p = 0.0042), while both count and area of blood vessel were significantly associated with Gleason grade (adjusted p = 0.032 and 0.003 respectively).Discussion: The proposed methodology is anticipated to streamline and standardize BV analysis, offering additional insights into the biology of prostate cancer, with broad applicability to other cancers.

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum. Supplementary information: you can download the chains here or create your own chains with CosmoSIS here.

Abstract Breast tissue enhances on contrast MRI and is called background parenchymal enhancement (BPE). Having high BPE has been associated with an increased risk of breast cancer. We examined the relationship between BPE and the amount of fibroglandular tissue on MRI (MRI-FGT) and breast cancer risk factors. This was a cross-sectional study of 415 women without breast cancer undergoing contrast-enhanced breast MRI at Memorial Sloan Kettering Cancer Center. All women completed a questionnaire assessing exposures at the time of MRI. Prevalence ratios (PR) and 95% confidence intervals (CI) describing the relationship between breast cancer risk factors and BPE and MRI-FGT were generated using modified Poisson regression. In multivariable-adjusted models a positive association between body mass index (BMI) and BPE was observed, with a 5-unit increase in BMI associated with a 14% and 44% increase in prevalence of high BPE in pre- and post-menopausal women, respectively. Conversely, a strong inverse relationship between BMI and MRI-FGT was observed in both pre- (PR = 0.66, 95% CI 0.57, 0.76) and post-menopausal (PR = 0.66, 95% CI 0.56, 0.78) women. Use of preventive medication (e.g., tamoxifen) was associated with having low BPE, while no association was observed for MRI-FGT. BPE is an imaging marker available from standard contrast-enhanced MRI, that is influenced by endogenous and exogenous hormonal exposures in both pre- and post-menopausal women.

We explore the influence of radio-mode feedback on the properties of the cool circumgalactic medium (CGM). To this end, we assemble a statistical sample of approximately 30,000 radio galaxies with background quasars by combining optical spectroscopic measurements of luminous red galaxies and quasars from the year 1 data set of the Dark Energy Spectroscopic Instrument and radio sources from the LOw-Frequency ARray Two-metre Sky Survey (LoTSS) DR2 catalog and the Very Large Array Sky Survey (VLASS) quick-look catalog. Galaxies with similar optical properties but with no radio counterparts in LoTSS and VLASS are selected as the control group. We measure the cool CGM properties of radio galaxies and their control samples traced by Mg ii absorption lines, including covering fraction, rest equivalent width, and gas kinematics. Our results show no significant difference in the properties of gas around radio galaxies and their control sample, indicating that the operating radio-mode feedback of massive galaxies does not produce detectable effects on the properties of the cool CGM. Finally, we show that the CGM of radio galaxies contains a nonnegligible amount of cool gas with approximately 10 ^10 M _⊙ . This abundance can place a stringent constraint on the radio-mode feedback models.

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%−40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Highly multiplexed, fiber-fed spectroscopy is enabling surveys of millions of stars and galaxies. The performance of these surveys depends on accurately positioning fibers in the focal plane to capture target light. We describe a technique to measure the positioning accuracy of fibers by dithering fibers slightly around their ideal locations. This approach also enables measurement of the total system throughput and point-spread function delivered to the focal plane. We then apply this technique to observations from the Dark Energy Survey Instrument (DESI), and demonstrate that DESI positions fibers to within 0.″08 of their targets (5% of a fiber diameter) and achieves a system throughput within about 7% of expectations.

We present a case of serious and progressive neuropathy shortly following the administration of the herpes zoster subunit (HZ/su) vaccine, otherwise known as Shingrix. The progressive neuropathy occurred a week following the vaccination and progressed until discharge 16 days post-admittance. The patient’s mild symptoms persist. The development of neuropathy following HZ/su administration is exceedingly rare, with an attributable risk of three cases per million vaccines administered. A black box warning was issued for this indication, although diagnosis and treatment were not confirmed for this patient. Reporting cases like this is crucial for a comprehensive understanding of vaccine risks and to characterize the underlying etiology of these serious adverse events.

Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is nontrivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5 Yr (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift differences between the true and matched hosts of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Δ w ) due to including SNe with incorrect host galaxy matches. For SN Ia–only simulations, we find Δ w = 0.0013 ± 0.0026 with constraints from the cosmic microwave background. Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Δ w ranges from 0.0009 to 0.0032, depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty on w from the DES-SN5YR sample of ∼0.03. We conclude that the bias on w from host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts.

Extremely metal-poor galaxies (XMPGs) at relatively low redshift are excellent laboratories for studying galaxy formation and evolution in the early universe. Much effort has been spent on identifying them from large-scale spectroscopic surveys or spectroscopic follow-up observations. Previous work has identified a few hundred XMPGs. In this work, we obtain a large sample of 223 XMPGs at z < 1 from the early data of the Dark Energy Spectroscopic Instrument (DESI). The oxygen abundance is determined using the direct T _e method based on the detection of the [O iii ] λ 4363 line. The sample includes 95 confirmed XMPGs based on the oxygen abundance uncertainty; the remaining 128 galaxies are regarded as XMPG candidates. These XMPGs are only 0.01% of the total DESI observed galaxies. Their coordinates and other properties are provided in the paper. The most XMPGs have an oxygen abundance of ∼1/34 Z _⊙ , a stellar mass of about 1.5 × 10 ^7 M _⊙, and a star formation rate of 0.22 M _⊙ yr ^−1 . The two most XMPGs present distinct morphologies suggesting different formation mechanisms. The local environmental investigation shows that XMPGs preferentially reside in relatively low-density regions. Many of them fall below the stellar mass–metallicity relations (MZRs) of normal star-forming galaxies. From a comparison of the MZR with theoretical simulations, it appears that XMPGs are good analogs to high-redshift star-forming galaxies. The nature of these XMPG populations will be further investigated in detail with larger and more complete samples from the ongoing DESI survey.

We report results from a systematic wide-area search for faint dwarf galaxies at heliocentric distances from 0.3 to 2 Mpc using the full 6 yr of data from the Dark Energy Survey (DES). Unlike previous searches over the DES data, this search specifically targeted a field population of faint galaxies located beyond the Milky Way virial radius. We derive our detection efficiency for faint, resolved dwarf galaxies in the Local Volume with a set of synthetic galaxies and expect our search to be complete to M _V ∼ (−7, −10) mag for galaxies at D = (0.3, 2.0) Mpc. We find no new field dwarfs in the DES footprint, but we report the discovery of one high-significance candidate dwarf galaxy at a distance of ${2.2}_{-0.12}^{+0.05}\,\mathrm{Mpc}$ , a potential satellite of the Local Volume galaxy NGC 55, separated by 47′ (physical separation as small as 30 kpc). We estimate this dwarf galaxy to have an absolute V -band magnitude of $-{8.0}_{-0.3}^{+0.5}\,\mathrm{mag}$ and an azimuthally averaged physical half-light radius of ${2.2}_{-0.4}^{+0.5}\,\mathrm{kpc}$ , making this one of the lowest surface brightness galaxies ever found with $\mu =32.3\,\mathrm{mag}\,{\mathrm{arcsec}}^{-2}$ . This is the largest, most diffuse galaxy known at this luminosity, suggesting possible tidal interactions with its host.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg ^2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg ^2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg ^2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

We address the problem of optimally identifying all kilonovae detected via gravitational-wave emission in the upcoming LIGO/Virgo/KAGRA observing run, O4, which is expected to be sensitive to a factor of ∼7 more binary neutron star (BNS) alerts than previously. Electromagnetic follow-up of all but the brightest of these new events will require >1 m telescopes, for which limited time is available. We present an optimized observing strategy for the DECam during O4. We base our study on simulations of gravitational-wave events expected for O4 and wide-prior kilonova simulations. We derive the detectabilities of events for realistic observing conditions. We optimize our strategy for confirming a kilonova while minimizing telescope time. For a wide range of kilonova parameters, corresponding to a fainter kilonova compared to GW170817/AT 2017gfo, we find that, with this optimal strategy, the discovery probability for electromagnetic counterparts with the DECam is ∼80% at the nominal BNS gravitational-wave detection limit for O4 (190 Mpc), which corresponds to an ∼30% improvement compared to the strategy adopted during the previous observing run. For more distant events (∼330 Mpc), we reach an ∼60% probability of detection, a factor of ∼2 increase. For a brighter kilonova model dominated by the blue component that reproduces the observations of GW170817/AT 2017gfo, we find that we can reach ∼90% probability of detection out to 330 Mpc, representing an increase of ∼20%, while also reducing the total telescope time required to follow up events by ∼20%.

Fat mass and obesity-associated (FTO) protein, the first m6A demethylase identified in 2011, regulates multiple aspects of RNA biology including splicing, localization, stability, and translation. Accumulating data show that FTO is involved in numerous physiological processes and is implicated in multiple cancers including renal cell carcinoma (RCC). However, the exact role of FTO in RCC remains controversial. Some studies demonstrated that decreased FTO expression was associated with aggressive clinical features and shorter overall survival in clear cell RCC (ccRCC) patients, while others found that FTO inhibition selectively reduced the growth and survival of VHL-deficient ccRCC cells in vitro and in vivo. Here, we review the evidence supporting either a promoting or suppressive role of FTO in kidney cancers, the mechanisms of action of FTO, and recent progress in developing FTO inhibitors.