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This study extracted historical water level data from 12 National Oceanographic and Atmospheric Administration tide gauge stations, spanning the period from the early 20th century to 2022 from central Maine to southern Florida, in order to determine if temporal and spatial trends existed in the frequency and magnitude of storms along the US Atlantic Ocean coast. We used the Storm Erosion Potential Index (SEPI) to identify and quantify storms. We then use the timing and magnitude of those storms to determine the cumulative effect of storm clustering and large-magnitude storms on sandy beaches using the cumulative storm impact index (CSII) empirical model. The results from this study showed (1) no appreciable increase in storm frequency at any of the stations (except for sheltered stations susceptible to storm tide augmentation), (2) statistically significant but modest increases in storm magnitudes over time for 8 of the 12 tidal stations, (3) regional differences in storm magnitudes (SEPI) and cumulative storm impacts (CSII) characteristic of more frequent extratropical storms (temporal clustering) in the north and less frequent tropical storms in the south, and (4) a 4- to 10-year recovery period for regional beach recovery.

Community colleges across the United States are increasingly linguistically diverse, with populations that often include immigrant students who have grown up with a language other than English but have spent a significant part of their childhood in the U.S. and as such received a substantial part of their -K-12 education there. In this paper, we analyze perceived second language (L2) effects in essays written by multilingual "resident," i.e., immigrant, students enrolled in pre-credit bearing developmental and ESL writing courses. Focusing on a predominant set of grammatical patterns identified in previous research, this study compares the writings of L2 resident students to those of monolingual and international L2 students. Findings reveal that the age of arrival to the U.S. impacts grammatical patterns, with L2 resident students arriving after age 12 displaying residual grammatical L2 acquisition effects, as contrasted with earlier arrivals, whose writings resemble monolingual students' more closely. As familiarity with "standard" English patterns is unfortunately often viewed by community college instructors as indicative of "academic" writing ability, we argue that these findings indicate a need for community colleges to consider students' linguistic histories and their effects in order to interpret resident L2 students' writing skills correctly and to provide appropriate linguistic support for resident L2 students across the curriculum. Professional development that emphasizes critical language awareness is needed so that instructors can better understand and support linguistic diversity in their classrooms.

Abstract High dose-rate brachytherapy is a treatment technique for gynecologic cancers where intracavitary applicators are placed within the patient’s pelvic cavity. To ensure accurate radiation delivery, localization of the applicator at the time of insertion is vital. This study proposes a novel method for acquiring, registering, and fusing three-dimensional (3D) trans-abdominal and 3D trans-rectal ultrasound (US) images for visualization of the pelvic anatomy and applicators during gynecologic brachytherapy. The workflow was validated using custom multi-modal pelvic phantoms and demonstrated during two patient procedures. Experiments were performed for three types of intracavitary applicators: ring-and-tandem, ring-and-tandem with interstitial needles, and tandem-and-ovoids. Fused 3D US images were registered to magnetic resonance (MR) and computed tomography (CT) images for validation. The target registration error (TRE) and fiducial localization error (FLE) were calculated to quantify the accuracy of our fusion technique. For both phantom and patient images, TRE and FLE across all modality registrations (3D US versus MR or CT) resulted in mean ± standard deviation of 4.01 ± 1.01 mm and 0.43 ± 0.24 mm, respectively. This work indicates proof of concept for conducting further clinical studies leveraging 3D US imaging as an accurate, accessible alternative to advanced modalities for localizing brachytherapy applicators.

ABSTRACT: Transfer of Salmonella to internal organs of broilers over a 35 d grow-out period was evaluated. A total of 360 one-day old chicks were placed in 18 floor pens of 3 groups with 6 replicate pens each. On d 0, broilers were orally challenged with a cocktail of Salmonella (equal population of marked serovars; nalidixic acid-resistant S. Typhimurium, rifampicin-resistant S. Infantis, and kanamycin-resistant S. Reading) to have 3 groups: L (low; ∼2 log CFU/bird); M (medium; ∼5 log CFU/bird); and H (High; ∼8 log CFU/bird). On d 2, 7 and 35, 4 birds/pen were euthanized and ceca, liver, and spleen samples were collected aseptically. Gizzard samples (4/pen) were collected on d 35. The concentration of Salmonella in liver and spleen were transformed to binary outcomes (positive and negative) and fitted in glm function of R using cecal Salmonella concentrations (log CFU/g) and inoculation doses (L, M, and H) as inputs. On d 2, H group showed greater (P ≤ 0.05) cecal colonization of all 3 serovars compared to L and M groups. However, M group showed greater (P ≤ 0.05) colonization of all 3 serovars in the liver and spleen compared to L group. Salmonella colonization increased linearly in the ceca and quadratically in the liver and spleen with increasing challenge dose (P ≤ 0.05). On d 35, L group had greater (P ≤ 0.05) S. Infantis colonization in the ceca and liver compared to M and H groups (P ≤ 0.05). Moreover, within each group on d 35, the concentration of S. Reading was greater than those of S. Typhimurium and S. Infantis for all 3 doses in the ceca and high dose in the liver and gizzard (P ≤ 0.05). Salmonella colonization diminished in the ceca, liver, and spleen during grow-out from d 0 to d 35 (P ≤ 0.05). On d 35, birds challenged with different doses of Salmonella cocktail showed a similar total Salmonella spp. population in the ceca (ca. 3.14 log CFU/g), liver (ca. 0.54 log CFU/g), spleen (ca. 0.31 log CFU/g), and gizzard (ca. 0.42 log CFU/g). Estimates from the fitted logistic model showed that one log CFU/g increase in cecal Salmonella concentration will result in an increase in relative risk of liver and spleen being Salmonella-positive by 4.02 and 3.40 times (P ≤ 0.01), respectively. Broilers from H or M group had a lower risk (28 and 23%) of being Salmonella-positive in the liver compared to the L group when the cecal Salmonella concentration is the same (P ≤ 0.05). Oral challenge of broilers with Salmonella spp. with various doses resulted in linear or quadratic increases in Salmonella colonization in the internal organs during early age and these populations decreased during grow-out (d 35). This research can provide guidance on practices to effectively mitigate the risk of Salmonella from chicken parts and enhance public health.

Abstract In brain, the striatum is a heterogenous region involved in reward and goal-directed behaviors. Striatal dysfunction is linked to psychiatric disorders, including opioid use disorder (OUD). Striatal subregions are divided based on neuroanatomy, each with unique roles in OUD. In OUD, the dorsal striatum is involved in altered reward processing, formation of habits, and development of negative affect during withdrawal. Using single nuclei RNA-sequencing, we identified both canonical (e.g., dopamine receptor subtype) and less abundant cell populations (e.g., interneurons) in human dorsal striatum. Pathways related to neurodegeneration, interferon response, and DNA damage were significantly enriched in striatal neurons of individuals with OUD. DNA damage markers were also elevated in striatal neurons of opioid-exposed rhesus macaques. Sex-specific molecular differences in glial cell subtypes associated with chronic stress were found in OUD, particularly female individuals. Together, we describe different cell types in human dorsal striatum and identify cell type-specific alterations in OUD.

Our paper, "Relationship between self-efficacy measured by the TSES scale and teacher participation in PDS activity," focuses on the collaboration between 19 professional development schools [PDSs] with whom Notre Dame of Maryland University has a partnership. The researchers surveyed in-service teachers in those 19 schools to determine if the collaboration was systemic and to investigate as to whether teacher self-efficacy was related to the likelihood that teachers would participate in PDS sponsored activities. With the use of the Teacher's Sense of Self-Efficacy Scale (TSES), the researchers found the higher the in-service teacher's self-efficacy; the greater the likelihood that they would participate in PDS sponsored activities.

The available medical literature on lung function and corresponding clinical characteristics among symptomatic survivors of Corona Virus Disease 2019 (long COVID) is sparse. Primary physicians referred patients who manifested persistent dyspnea months after their index case of infection to a designated clinic. Patients underwent symptom-driven, quality-of-life, physical, and focused respiratory [pulmonary function tests and computed tomography (CT) of the chest] evaluations and were followed over time. In this paper, we present our findings. Patients with abnormal CT imaging were more likely to be of advanced age and to have been hospitalized during their COVID-19 infection. Forced exhaled volume in the first second, forced vital capacity (FVC), total lung capacity, and diffusion capacity of carbon monoxide measurements were found to be significantly lower in patients with abnormal CT imaging. Multivariate regression of clinical characteristics uncovered a significant association between FVC, body mass index, history of hospitalization, and diabetes mellitus. In conclusion, longer-term studies will help further our understanding of the risk factors, disease course, and prognosis of long COVID patients.

Abstract Breast cancer screening has substantially reduced mortality across screening populations. However, a clinical need persists for more accessible, cost-effective, and robust approaches for increased-risk and diverse patient populations, especially those with dense breasts where screening mammography is suboptimal. We developed and validated a cost-effective, portable, patient-dedicated three-dimensional (3D) automated breast ultrasound (ABUS) system for point-of-care breast cancer screening. The 3D ABUS system contains a wearable, rapid-prototype 3D-printed dam assembly, a compression assembly, and a computer-driven 3DUS scanner, adaptable to any commercially available US machine and transducer. Acquisition is operator-agnostic, involves a 40-second scan time, and provides multiplanar 3D visualization for whole-breast assessment. Geometric reconstruction accuracy was evaluated with a 3D grid phantom and tissue-mimicking breast phantoms, demonstrating linear measurement and volumetric reconstruction errors

Since the first half of the twentieth century, evolutionary theory has been dominated by the idea that mutations occur randomly with respect to their consequences1. Here we test this assumption with large surveys of de novo mutations in the plant Arabidopsis thaliana. In contrast to expectations, we find that mutations occur less often in functionally constrained regions of the genome-mutation frequency is reduced by half inside gene bodies and by two-thirds in essential genes. With independent genomic mutation datasets, including from the largest Arabidopsis mutation accumulation experiment conducted to date, we demonstrate that epigenomic and physical features explain over 90% of variance in the genome-wide pattern of mutation bias surrounding genes. Observed mutation frequencies around genes in turn accurately predict patterns of genetic polymorphisms in natural Arabidopsis accessions (r = 0.96). That mutation bias is the primary force behind patterns of sequence evolution around genes in natural accessions is supported by analyses of allele frequencies. Finally, we find that genes subject to stronger purifying selection have a lower mutation rate. We conclude that epigenome-associated mutation bias2 reduces the occurrence of deleterious mutations in Arabidopsis, challenging the prevailing paradigm that mutation is a directionless force in evolution.

Obtaining a complete good-quality sequence and annotation for the long double-stranded DNA genome of the African swine fever virus (ASFV) from next-generation sequencing (NGS) technology has proven difficult, despite the increasing availability of reference genome sequences and the increasing affordability of NGS. A gap analysis conducted by the global African swine fever research alliance (GARA) partners identified that a standardized, automatic pipeline for NGS analysis was urgently needed, particularly for new outbreak strains. Whilst there are several diagnostic and research labs worldwide that collect isolates of the ASFV from outbreaks, many do not have the capability to analyze, annotate, and format NGS data from outbreaks for submission to NCBI, and some publicly available ASFV genomes have missing or incorrect annotations. We developed an automated, standardized pipeline for the analysis of NGS reads that directly provides users with assemblies and annotations formatted for their submission to NCBI. This pipeline is freely available on GitHub and has been tested through the GARA partners by examining two previously sequenced ASFV genomes; this study also aimed to assess the accuracy and limitations of two strategies present within the pipeline: reference-based (Illumina reads) and de novo assembly (Illumina and Nanopore reads) strategies.

African swine fever (ASF) is a deadly hemorrhagic disease of domestic and wild swine that was first described in the early 20th century after the introduction of European pigs to Kenya. The etiological agent, the African swine fever virus (ASFV), is a large DNA virus within the Asfarviridae family that is broadly categorized epidemiologically into genotypes based on the nucleotide sequence of B646L, the gene encoding the major capsid protein p72. ASF outbreaks in Africa have been linked historically to 25 genotypes by p72 nucleotide analysis and, recently, to 6 genotypes by amino acid comparison, whereas global outbreaks of ASF outside of Africa have only been linked to 2 genotypes: genotype I, which led to an outbreak in Europe during the 1960s that later spread to South America, and genotype II, responsible for the current pandemic that began in Georgia in 2007 and has since spread to Europe, Asia, and Hispaniola. Here, we present an analysis of the genome of ASFV Spencer, an isolate that was collected in 1951 near Johannesburg, South Africa. While nucleotide analysis of Spencer indicates the p72 coding sequence is unique, differentiating from the closest reference by five nucleotides, the predicted amino acid sequence indicates that it is 100% homologous to contemporary genotype 1. Full genome analysis reveals it is more similar to Mkuzi1979 and encodes genes that share similarity with either genotype 1 or genotype 2 outbreak strains.

The African swine fever virus (ASFV) is an often deadly disease in swine and poses a threat to swine livestock and swine producers. With its complex genome containing more than 150 coding regions, developing effective vaccines for this virus remains a challenge due to a lack of basic knowledge about viral protein function and protein–protein interactions between viral proteins and between viral and host proteins. In this work, we identified ASFV-ASFV protein–protein interactions (PPIs) using artificial intelligence-powered protein structure prediction tools. We benchmarked our PPI identification workflow on the Vaccinia virus, a widely studied nucleocytoplasmic large DNA virus, and found that it could identify gold-standard PPIs that have been validated in vitro in a genome-wide computational screening. We applied this workflow to more than 18,000 pairwise combinations of ASFV proteins and were able to identify seventeen novel PPIs, many of which have corroborating experimental or bioinformatic evidence for their protein–protein interactions, further validating their relevance. Two protein–protein interactions, I267L and I8L, I267L__I8L, and B175L and DP79L, B175L__DP79L, are novel PPIs involving viral proteins known to modulate host immune response.

Introduction 334 I. Artificial Intelligence: Technical Perspectives and Artificial Intelligence's Benefits 337 A. Background to Artificial Intelligence in Healthcare 337 B. The Benefits of Artificial Intelligence in Healthcare 338 II. [...]

Though the Professional Development School (PDS) model assumes that student teachers will be placed in cohorts as opposed to singletons during their student teaching experience in PDSs, little research is available to validate what the 'magic' number in those cohorts should be. In the state where the researchers' Institute for Higher Education resides, it is "required" that at least 5 interns be placed in the same PDS at the "same time" during their student teaching experience. If five is the critical mass needed to secure a quality student teaching experience, the researchers questioned what the impact might be on student teachers who are placed in cohorts of fewer than five. To answer this question, the researchers surveyed teacher candidates placed in various cohort sizes at PDSs over a 4-year period to determine (a) the extent to which the number of student teachers placed simultaneously in a PDS affects the quality of the experience for the student teacher, and (b) the student teacher's perceived ability to affect student achievement. Using the "Standards for Maryland Professional Development Schools" as a framework to identify characteristics that promote quality student teaching experiences and to develop the survey questions, the researchers found that regardless of cohort size, there were few significant differences in the interns' perceptions of the quality of their experiences or their perceived ability to address student achievement in the schools in which they were placed.

Abstract Intracardiac flow hemodynamic patterns have been considered to be an early sign of diastolic dysfunction. In this study we investigated right ventricular (RV) diastolic dysfunction between patients with pulmonary arterial hypertension (PAH) and pulmonary hypertension with chronic lung disease (PH‐CLD) via 4D‐Flow cardiac MRI (CMR). Patients underwent prospective, comprehensive CMR for function and size including 4D‐Flow CMR protocol for intracardiac flow visualization and analysis. RV early filling phase and peak atrial phase vorticity (E‐vorticity and A‐vorticity) values were calculated in all patients. Patients further underwent comprehensive Doppler and tissue Doppler evaluation for the RV diastolic dysfunction. In total 13 patients with PAH, 15 patients with PH‐CLD, and 10 control subjects underwent the 4D‐Flow CMR and echocardiography evaluation for RV diastolic dysfunction. Reduced E‐vorticity differentiated PAH and PH‐CLD from healthy controls (both p

Carotid total plaque area (TPA) is an important contributing measurement to the evaluation of stroke risk. Deep learning provides an efficient method for ultrasound carotid plaque segmentation and TPA quantification. However, high performance of deep learning requires datasets with many labeled images for training, which is very labor-intensive. Thus, we propose an image reconstruction-based self-supervised learning algorithm (IR-SSL) for carotid plaque segmentation when few labeled images are available. IR-SSL consists of pre-trained and downstream segmentation tasks. The pre-trained task learns region-wise representations with local consistency by reconstructing plaque images from randomly partitioned and disordered images. The pre-trained model is then transferred to the segmentation network as the initial parameters in the downstream task. IR-SSL was implemented with two networks, UNet++ and U-Net, and evaluated on two independent datasets of 510 carotid ultrasound images from 144 subjects at SPARC (London, Canada) and 638 images from 479 subjects at Zhongnan hospital (Wuhan, China). Compared to the baseline networks, IR-SSL improved the segmentation performance when trained on few labeled images (n = 10, 30, 50 and 100 subjects). For 44 SPARC subjects, IR-SSL yielded Dice-similarity-coefficients (DSC) of 80.14–88.84%, and algorithm TPAs were strongly correlated (r=0.962−0.993, p < 0.001) with manual results. The models trained on the SPARC images but applied to the Zhongnan dataset without retraining achieved DSCs of 80.61–88.18% and strong correlation with manual segmentation (r=0.852−0.978, p < 0.001). These results suggest that IR-SSL could improve deep learning when trained on small labeled datasets, making it useful for monitoring carotid plaque progression/regression in clinical use and trials.