Habitat escalated adaptive therapy (HEAT): a phase 2 trial utilizing radiomic habitat-directed and genomic-adjusted radiation dose (GARD) optimization for high-grade soft tissue sarcoma.

BACKGROUND: Soft tissue sarcomas (STS), have significant inter- and intra-tumoral heterogeneity, with poor response to standard neoadjuvant radiotherapy (RT). Achieving a favorable pathologic response (FPR ≥ 95%) from RT is associated with improved patient outcome. Genomic adjusted radiation dose (GARD), a radiation-specific metric that quantifies the expected RT treatment effect as a function of tumor dose and genomics, proposed that STS is significantly underdosed. STS have significant radiomic heterogeneity, where radiomic habitats can delineate regions of intra-tumoral hypoxia and radioresistance. We designed a novel clinical trial, Habitat Escalated Adaptive Therapy (HEAT), utilizing radiomic habitats to identify areas of radioresistance within the tumor and targeting them with GARD-optimized doses, to improve FPR in high-grade STS. METHODS: Phase 2 non-randomized single-arm clinical trial includes non-metastatic, resectable high-grade STS patients. Pre-treatment multiparametric MRIs (mpMRI) delineate three distinct intra-tumoral habitats based on apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) sequences. GARD estimates that simultaneous integrated boost (SIB) doses of 70 and 60 Gy in 25 fractions to the highest and intermediate radioresistant habitats, while the remaining volume receives standard 50 Gy, would lead to a > 3 fold FPR increase to 24%. Pre-treatment CT guided biopsies of each habitat along with clip placement will be performed for pathologic evaluation, future genomic studies, and response assessment. An mpMRI taken between weeks two and three of treatment will be used for biological plan adaptation to account for tumor response, in addition to an mpMRI after the completion of radiotherapy in addition to pathologic response, toxicity, radiomic response, disease control, and survival will be evaluated as secondary endpoints. Furthermore, liquid biopsy will be performed with mpMRI for future ancillary studies. DISCUSSION: This is the first clinical trial to test a novel genomic-based RT dose optimization (GARD) and to utilize radiomic habitats to identify and target radioresistance regions, as a strategy to improve the outcome of RT-treated STS patients. Its success could usher in a new phase in radiation oncology, integrating genomic and radiomic insights into clinical practice and trial designs, and may reveal new radiomic and genomic biomarkers, refining personalized treatment strategies for STS. TRIAL REGISTRATION: NCT05301283. TRIAL STATUS: The trial started recruitment on March 17, 2022.

In vivo single-cell high-dimensional mass cytometry analysis to track the interactions between Klebsiella pneumoniae and myeloid cells.

In vivo single-cell approaches have transformed our understanding of the immune populations in tissues. Mass cytometry (CyTOF), that combines the resolution of mass spectrometry with the ability to conduct multiplexed measurements of cell molecules at the single cell resolution, has enabled to resolve the diversity of immune cell subsets, and their heterogeneous functionality. Here we assess the feasibility of taking CyTOF one step further to immuno profile cells while tracking their interactions with bacteria, a method we term Bac-CyTOF. We focus on the pathogen Klebsiella pneumoniae interrogating the pneumonia mouse model. Using Bac-CyTOF, we unveil the atlas of immune cells of mice infected with a K. pneumoniae hypervirulent strain. The atlas is characterized by a decrease in the populations of alveolar and monocyte-derived macrophages. Conversely, neutrophils, and inflammatory monocytes are characterized by an increase in the subpopulations expressing markers of less active cells such as the immune checkpoint PD-L1. These are the cells infected. We show that the type VI secretion system (T6SS) contributes to shape the lung immune landscape. The T6SS governs the interaction with monocytes/macrophages by shifting Klebsiella from alveolar macrophages to interstitial macrophages and limiting the infection of inflammatory monocytes. The lack of T6SS results in an increase of cells expressing markers of active cells, and a decrease in the subpopulations expressing PD-L1. By probing Klebsiella, and Acinetobacter baumannii strains with limited ability to survive in vivo, we uncover that a heightened recruitment of neutrophils, and relative high levels of alveolar macrophages and eosinophils and the recruitment of a characteristic subpopulation of neutrophils are features of mice clearing infections. We leverage Bac-CyTOF-generated knowledge platform to investigate the role of the DNA sensor STING in Klebsiella infections. sting-/- infected mice present features consistent with clearing the infection including the reduced levels of PD-L1. STING absence facilitates Klebsiella clearance.

A complex receptor locus confers responsiveness to necrosis and ethylene-inducing like peptides in Brassica napus.

Brassica crops are susceptible to diseases which can be mitigated by breeding for resistance. MAMPs (microbe-associated molecular patterns) are conserved molecules of pathogens that elicit host defences known as pattern-triggered immunity (PTI). Necrosis and Ethylene-inducing peptide 1-like proteins (NLPs) are MAMPs found in a wide range of phytopathogens. We studied the response to BcNEP2, a representative NLP from Botrytis cinerea, and showed that it contributes to disease resistance in Brassica napus. To map regions conferring NLP response, we used the production of reactive oxygen species (ROS) induced during PTI across a population of diverse B. napus accessions for associative transcriptomics (AT), and bulk segregant analysis (BSA) on DNA pools created from a cross of NLP-responsive and non-responsive lines. In silico mapping with AT identified two peaks for NLP responsiveness on chromosomes A04 and C05 whereas the BSA identified one peak on A04. BSA delimited the region for NLP-responsiveness to 3 Mbp, containing ~245 genes on the Darmor-bzh reference genome and four co-segregating KASP markers were identified. The same pipeline with the ZS11 genome confirmed the highest-associated region on chromosome A04. Comparative BLAST analysis revealed unannotated clusters of receptor-like protein (RLP) homologues on ZS11 chromosome A04. However, no specific RLP homologue conferring NLP response could be identified. Our results also suggest that BR-SIGNALLING KINASE1 may be involved with modulating the NLP response. Overall, we demonstrate that responsiveness to NLP contributes to disease resistance in B. napus and define the associated genomic location. These results can have practical application in crop improvement.

Objective and subjective measures of air pollution and self-rated health: the evidence from Chile.

PURPOSE: The literature exploring individual differences in self-rated health has grown fast in recent years. Self-rated health (SRH) is a good indicator of general health status. This empirical study explores the association between outdoor air pollution and SRH in Chile. This type of analysis is infrequent in Latin America. METHODS: We used objective and subjective air pollution measures. The first corresponds to PM2.5, and the latter to the perception of a high level of air pollution. Drawing on data from two independent and repeated nationwide surveys over the period 2006-2017 at the individual level in Chile, we performed repeated cross-sectional analyses for each year of survey application. Ordered Logit (OL) and Logit (L) multivariate models were used to investigate the association between SRH and air pollution measures, considering other socioeconomic and demographic covariates. RESULTS: We found that the higher is the level of air pollution, the lower the SRH in Chile, regardless of whether air pollution is physically measured or perceived by respondents. The results were consistent over the years in the sign and significance of regression coefficients using two surveys and two forms of the outcome variable. CONCLUSIONS: Our findings add evidence that air pollution is a relevant determinant of SRH. In addition, they show that subjective measures of air pollution can be as reliable as physical measures in the analysis of the association between air pollution and human health.

Near-Infrared Light Activated Formulation for the Spatially Controlled Release of CRISPR-Cas9 Ribonucleoprotein for Brain Gene Editing.

The CRISPR/Cas9 system has emerged as a promising platform for gene editing; however, the lack of an efficient and safe delivery system to introduce it into cells continues to hinder clinical translation. Here, we report a rationally designed gene-editing nanoparticle (NP) formulation for brain applications: an sgRNA:Cas9 ribonucleoprotein complex is immobilized on the NP surface by oligonucleotides that are complementary to the sgRNA. Irradiation of the formulation with a near-infrared (NIR) laser generates heat in the NP, leading to the release of the ribonucleoprotein complex. The gene-editing potential of the formulation was demonstrated in vitro at the single-cell level. The safety and gene editing of the formulation were also demonstrated in the brains of reporter mice, specifically in the subventricular zone after intracerebral administration and in the olfactory bulb after intranasal administration. The formulation presented here offers a new strategy for the spatially controlled delivery of the CRISPR system to the brain.

Role of Nb2O5 Crystal Phases on the Photocatalytic Conversion of Lignin Model Molecules and Selectivity for Value-Added Products.

The photocatalytic conversion in aqueous media of phenol and guaiacol as a lignin model compound using Nb2O5 with different crystal phases was studied. Nb2O5 particles were synthesized using hydrothermal methods, where it was observed that changes in the solvent control their morphology and crystal phase. Different photocatalytic behavior of Nb2O5 was observed with the selected model compounds, indicating that its selection directly impacts the resulting conversion and selectivity rates as well as the reaction pathway, highlighting the relevance of model molecule selection. Photocatalytic conversion of phenol showed conversion rate (C%) up to 25 % after 2 h irradiation and high selectivity (S%) to pyrogallol (up to 50 %). Orthorhombic Nb2O5 spheres favored conversion through free hydroxyl radicals while monoclinic rods did not convert phenol. Guaiacol photocatalytic oxidation showed high conversion rate but lower selectivity. Orthorhombic and monoclinic Nb2O5 favored the formation of resorcinol with S % ~0.43 % (C % ~33 %) and ~13 % (C % ~27 %) respectively. The mixture of both phases enhanced the guaiacol conversion rate to ~55 % with ~17 % of selectivity to salicylaldehyde. The use of radical scavengers provided information to elucidate the reaction pathway for these model compounds, showing that different reaction pathways may be obtained for the same photocatalyst if the model compound is changed.

Differentiating action from inaction: Longitudinal relations among impulsive personality traits, internalizing symptoms, and drinking behavior.

BACKGROUND: Impulsive personality traits are strong, consistent risk factors for heavy drinking, and modern theories suggest that impulsive traits may also confer risk for internalizing symptoms. However, it remains unclear which specific impulsive traits are linked with heavy drinking versus internalizing symptoms, and whether heavy drinking and internalizing symptoms are mechanisms of risk for negative alcohol consequences in impulsive individuals. METHOD: Data are from a longitudinal study of young adults (N = 448, Mage = 22.27, 43.5 % female) assessed at baseline (T1), 6 months (T2), and one year later (T3). Longitudinal path models tested whether T1 impulsive traits (i.e., lack of premeditation, lack of perseverance, sensation seeking, positive urgency, negative urgency) were indirectly associated with T3 negative alcohol consequences through heavy T2 drinking and T2 internalizing symptoms (i.e., depression, anxiety, stress). Separate models were tested for positive and negative urgency given strong correlations between these measures. RESULTS: Across models, T1 lack of premeditation indirectly predicted more T3 negative alcohol consequences through heavy T2 drinking. When tested separately, T1 negative urgency indirectly predicted more T3 negative consequences through higher T2 stress and depressive (but not anxiety) symptoms, and T1 positive urgency predicted higher T2 anxiety symptoms, but T2 anxiety was unrelated to T3 negative consequences. Across models, T1 sensation seeking indirectly predicted less T3 negative consequences through decreased T2 depression. CONCLUSIONS: Distinct impulsive traits prospectively predicted heavy drinking and internalizing symptoms, both of which conferred risk for negative alcohol consequences. Findings underscore the importance of targeted interventions based on personality and suggest that decreases in drinking may be more effective prevention for those who lack premeditation, whereas decreases in internalizing, particularly depression/stress, may be critical for those high in negative urgency.

Urinary concentration of Cathepsin D as a relievable marker of preeclampsia.

BACKGROUND: The early and accurate diagnosis of preeclampsia is crucial to avoid serious complications for both the mother and baby. However, the current diagnostic methods are limited, and there is a need for new diagnostic biomarkers. Previous studies have shown that cathepsin D (CTD) participates in the pathophysiology of preeclampsia and is present in urine samples, making it a potential biomarker for the disease. This study aimed to compare urinary and serum levels of CTD in preeclamptic and normotensive women and analyze its potential role as a diagnostic biomarker in preeclampsia. METHODS: The study included thirty-nine patients with preeclampsia and twelve normotensive pregnant women as controls. Biomarkers were determined using Multiplex Assay kit, and serum prolactin (Prl) and urinary TNF-α levels were also evaluated. Statistical analysis was conducted using the Mann-Whitney U test. RESULTS: We found that urinary and serum CTD levels were significantly higher in the preeclampsia group than in the normotensive group, suggesting that CTD could be a diagnostic biomarker for preeclampsia. No significant differences were found in the levels of serum prolactin or urinary TNF-α between the two groups. CONCLUSIONS: The study provides evidence that non-invasive biological samples such as urine can be used to improve new therapeutic strategies for the early management of preeclampsia.

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities.

This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support "Learning Health Systems" with them. Initially, the authors elaborate on these challenges after separating them according to their mitigation strategies: those that need innovative approaches, time, or future technological capabilities and those that require a conceptual reappraisal from a critical perspective. Then, a novel opportunity to support "Learning Health Systems" by integrating hidden information extracted by ML models from digitalized histopathology slides with other healthcare big data is presented.

Contaminants of emerging concern: Occurrence, analytical techniques, and removal with electrochemical advanced oxidation processes with special emphasis in Latin America.

The occurrence of contaminants of emerging concern (CECs) in environmental systems is gradually more studied worldwide. However, in Latin America, the presence of contaminants of emerging concern, together with their environmental and toxicological impacts, has recently been gaining wide interest in the scientific community. This paper presents a critical review about the source, fate, and occurrence of distinct emerging contaminants reported during the last two decades in various countries of Latin America. In recent years, Brazil, Chile, and Colombia are the main countries that have conducted research on the presence of these pollutants in biological and aquatic compartments. Data gathered indicated that pharmaceuticals, pesticides, and personal care products are the most assessed CECs in Latin America, being the most common compounds the followings: atrazine, acenaphthene, caffeine, carbamazepine, ciprofloxacin, diclofenac, diuron, estrone, losartan, sulfamethoxazole, and trimethoprim. Most common analytical methodologies for identifying these compounds were HPLC and GC coupled with mass spectrometry with the potential to characterize and quantify complex substances in the environment at low concentrations. Most CECs' monitoring and detection were observed near to urban areas which confirm the out-of-date wastewater treatment plants and sanitization infrastructures limiting the removal of these pollutants. Therefore, the implementation of tertiary treatment should be required. In this tenor, this review also summarizes some studies of CECs removal using electrochemical advanced oxidation processes that showed satisfactory performance. Finally, challenges, recommendations, and future perspectives are discussed.

Harlequin ichthyosis, prenatal diagnosis: the ultrasound recognition.

Harlequin ichthyosis (HI) is an extremely rare disease with a prevalence of less than 1/300 000 live newborns and no more than 100 cases reported worldwide. It corresponds to a genodermatoses autosomal recessive inheritance, typically, with postnatal recognition due to the complexity of prenatal diagnosis. Advances in prenatal genetic testing allow sequencing of the affected gene and confirmation of the diagnosis after recognition of ultrasound markers. The prenatal acknowledgement of the disease significantly marks the course of the pregnancy; considering the perinatal high risk and neonatal mortality, this entity can be classified as lethal. Taking into account the legislation of each country, the possibility of pregnancy termination should be considered as an acceptable option. We present a case of prenatally diagnosed HI in the first ultrasound evaluation by the Maternal Fetal Medicine unit at 29 weeks of gestation, in which after counselling to the parents, the interruption of the gestation was decided.

A Preliminary Investigation into Search and Matching for Tumor Discrimination in World Health Organization Breast Taxonomy Using Deep Networks.

Breast cancer is one of the most common cancers affecting women worldwide. It includes a group of malignant neoplasms with a variety of biological, clinical, and histopathologic characteristics. There are more than 35 different histologic forms of breast lesions that can be classified and diagnosed histologically according to cell morphology, growth, and architecture patterns. Recently, deep learning, in the field of artificial intelligence, has drawn a lot of attention for the computerized representation of medical images. Searchable digital atlases can provide pathologists with patch-matching tools, allowing them to search among evidently diagnosed and treated archival cases, a technology that may be regarded as computational second opinion. In this study, we indexed and analyzed the World Health Organization breast taxonomy (Classification of Tumors fifth ed.) spanning 35 tumor types. We visualized all tumor types using deep features extracted from a state-of-the-art deep-learning model, pretrained on millions of diagnostic histopathology images from the Cancer Genome Atlas repository. Furthermore, we tested the concept of a digital "atlas" as a reference for search and matching with rare test cases. The patch similarity search within the World Health Organization breast taxonomy data reached >88% accuracy when validating through "majority vote" and >91% accuracy when validating using top n tumor types. These results show for the first time that complex relationships among common and rare breast lesions can be investigated using an indexed digital archive.

Impact of First Wave of COVID-19 Pandemic on Mortality at Emergency Department in Older Patients with COVID and Non-COVID Diagnoses.

INTRODUCTION: Mortality in emergency departments (EDs) is not well known. This study aimed to assess the impact of the first-wave pandemic on deaths accounted in the ED of older patients with COVID and non-COVID diseases. METHODS: We used data from the Emergency Department and Elderly Needs (EDEN) cohort (pre-COVID period) and from the EDEN-COVID cohort (COVID period) that included all patients ≥65 years seen in 52 Spanish EDs from April 1 to 7, 2019, and March 30 to April 5, 2020, respectively. We recorded patient characteristics and final destination at ED. We compared older patients in the pre-COVID period, with older patients with non-COVID and with COVID-19. ED-mortality (before discharge or hospitalization) is the prior outcome and is expressed as an adjusted odds ratio (aOR) with 95% interval confidence. RESULTS: We included 23,338 older patients from the pre-COVID period (aged 78.3 [8.1] years), 6,715 patients with non-COVID conditions (aged 78.9 [8.2] years) and 3,055 with COVID (aged 78.3 [8.3] years) from the COVID period. Compared to the older patients, pre-COVID period, patients with non-COVID and with COVID-19 were more often male, referred by a doctor and by ambulance, with more comorbidity and disability, dementia, nursing home, and more risk according to qSOFA, respectively (p < 0.001). Compared to the pre-COVID period, patients with non-COVID and with COVID-19 were more often to be hospitalized from ED (24.8% vs. 44.3% vs. 79.1%) and were more often to die in ED (0.6% vs. 1.2% vs. 2.2%), respectively (p < 0.001). Compared to the pre-COVID period, aOR for age, sex, comorbidity and disability, ED mortality in elderly patients cared in ED during the COVID period was 2.31 (95% confidence interval [CI]: 1.76-3.06), and 3.75 (95% CI: 2.77-5.07) for patients with COVID. By adding the variable qSOFA to the model, such OR were 1.59 (95% CI: 1.11-2.30) and 2.16 (95% CI: 1.47-3.17), respectively. CONCLUSIONS: During the early first pandemic wave of COVID-19, more complex and life-threatening older with COVID and non-COVID diseases were seen compared to the pre-COVID period. In addition, the need for hospitalization and the ED mortality doubled in non-COVID and tripled in COVID diagnosis. This increase in ED mortality is not only explained by the complexity or severity of the elderly patients but also because of the system's overload.

Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review.

Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was to assess the performance of externally validated ML models based on histopathology images for diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer. A systematic search of MEDLINE, EMBASE, CINAHL, IEEE, MICCAI, and SPIE conferences was performed for studies published between January 2010 and February 2022. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed, and the results were narratively described. Of the 2011 non-duplicated citations, 8 journal articles and 2 conference proceedings met inclusion criteria. Three studies externally validated ML models for diagnosis, 4 for classification, 2 for prognosis, and 1 for both classification and prognosis. Most studies used Convolutional Neural Networks and one used logistic regression algorithms. For diagnostic/classification models, the most common performance metrics reported in the EV were accuracy and area under the curve, which were greater than 87% and 90%, respectively, using pathologists' annotations/diagnoses as ground truth. The hazard ratios in the EV of prognostic ML models were between 1.7 (95% CI, 1.2-2.6) and 1.8 (95% CI, 1.3-2.7) to predict distant disease-free survival; 1.91 (95% CI, 1.11-3.29) for recurrence, and between 0.09 (95% CI, 0.01-0.70) and 0.65 (95% CI, 0.43-0.98) for overall survival, using clinical data as ground truth. Despite EV being an important step before the clinical application of a ML model, it hasn't been performed routinely. The large variability in the training/validation datasets, methods, performance metrics, and reported information limited the comparison of the models and the analysis of their results. Increasing the availability of validation datasets and implementing standardized methods and reporting protocols may facilitate future analyses.

Immunohistochemistry Biomarkers-Guided Image Search for Histopathology.

Medical practitioners use a number of diagnostic tests to make a reliable diagnosis. Traditionally, Haematoxylin and Eosin (H&E) stained glass slides have been used for cancer diagnosis and tumor detection. However, recently a variety of immunohistochemistry (IHC) stained slides can be requested by pathologists to examine and confirm diagnoses for determining the subtype of a tumor when this is difficult using H&E slides only. Deep learning (DL) has received a lot of interest recently for image search engines to extract features from tissue regions, which may or may not be the target region for diagnosis. This approach generally fails to capture high-level patterns corresponding to the malignant or abnormal content of histopathology images. In this work, we are proposing a targeted image search approach, inspired by the pathologists' workflow, which may use information from multiple IHC biomarker images when available. These IHC images could be aligned, filtered, and merged together to generate a composite biomarker image (CBI) that could eventually be used to generate an attention map to guide the search engine for localized search. In our experiments, we observed that an IHC-guided image search engine can retrieve relevant data more accurately than a conventional (i.e., H&E-only) search engine without IHC guidance. Moreover, such engines are also able to accurately conclude the subtypes through majority votes.

Composite Biomarker Image for Advanced Visualization in Histopathology.

Immunohistochemistry (IHC) biomarkers are essential tools for reliable cancer diagnosis and subtyping. It requires cross-staining comparison among Whole Slide Images (WSIs) of IHCs and hematoxylin and eosin (H&E) slides. Currently, pathologists examine the visually co-localized areas across IHC and H&E glass slides for a final diagnosis, which is a tedious and challenging task. Moreover, visually inspecting different IHC slides back and forth to analyze local co-expressions is inherently subjective and prone to error, even when carried out by experienced pathologists. Relying on digital pathology, we propose "Composite Biomarker Image" (CBI) in this work. CBI is a single image that can be composed using different filtered IHC biomarker images for better visualization. We present a CBI image produced in two steps by the proposed solution for better visualization and hence more efficient clinical workflow. In the first step, IHC biomarker images are aligned with the H&E images using one coordinate system and orientation. In the second step, the positive or negative IHC regions from each biomarker image (based on the pathologists' recommendation) are filtered and combined into one image using a fuzzy inference system. For evaluation, the resulting CBI images, from the proposed system, were evaluated qualitatively by the expert pathologists. The CBI concept helps the pathologists to identify the suspected target tissues more easily, which could be further assessed by examining the actual WSIs at the same suspected regions.

Overview of Benchtop Models for Comparison of Surgical Treatments for Benign Prostatic Hyperplasia.

PURPOSE OF REVIEW: Benign prostatic hyperplasia (BPH) is a disease of the lower urinary tract which often requires surgical treatment. Recently, there has been a deluge of new treatment options, rarely validated or compared to current treatments on a benchtop model. The purpose of this review is to examine the literature and report which benchtop models are currently being used, which therapies have been tested on them, and what outcomes are being studied on each model. RECENT FINDINGS: There are various benchtop models to choose from, each with their unique benefits and drawbacks. Perfused porcine kidney models are used to assess bleeding on the benchtop, ex-vivo human prostate helps to see specific interactions of devices with the prostatic tissue, and all other models have evaluated tissue ablation rates and depth of coagulation. There are currently no synthetic or non-animal tissues being used for this purpose, and surgical techniques such as enucleation, water-jet ablation, prostate stents, and water vapor thermal therapy have no representation in these benchtop tests. Benchtop testing serves an important role in the evaluation and comparison of surgical treatments for BPH. This testing allows these therapies to be objectively compared to one another, helping novel medical devices in their path to market and urologists make treatment decisions. Future directions may include further validation of the animal models currently being used and development of synthetic models which mimic the prostate on the benchtop.

Designing Cell Delivery Peptides and SARS-CoV-2-Targeting Small Interfering RNAs: A Comprehensive Bioinformatics Study with Generative Adversarial Network-Based Peptide Design and In Vitro Assays.

Nucleic acid technologies with designed intracellular delivery systems are some of the most promising therapies of the future. Small interfering (si)RNAs inhibit gene expression and protein synthesis and may complement current vaccines with faster design and production. Although successful delivery remains an issue, delivery peptides may help to fill this gap. Here, we address this issue by applying bioinformatic approaches to design new putative cell delivery peptides and siRNAs for COVID-19 variants and other related viral diseases. Of the 29,880 RNA sequences analyzed, 62 were identified in silico as able to target the virus mRNA sequence, and from the 9,984 peptide sequences analyzed, 10 were selected as delivery peptides. From the latter, we further performed in vitro studies of the two best-ranked peptides and compared them with the broadly used TAT delivery peptide. One of them, seq5, displayed better internalization results with about double intensity signal compared to TAT after a 1 h incubation time in GFP-HeLa cells. This peptide has, thus, the features of a delivery peptide and could be used for cargo intracellular delivery.

An online database for einkorn wheat to aid in gene discovery and functional genomics studies.

Diploid A-genome wheat (einkorn wheat) presents a nutrition-rich option as an ancient grain crop and a resource for the improvement of bread wheat against abiotic and biotic stresses. Realizing the importance of this wheat species, reference-level assemblies of two einkorn wheat accessions were generated (wild and domesticated). This work reports an einkorn genome database that provides an interface to the cereals research community to perform comparative genomics, applied genetics and breeding research. It features queries for annotated genes, the use of a recent genome browser release, and the ability to search for sequence alignments using a modern BLAST interface. Other features include a comparison of reference einkorn assemblies with other wheat cultivars through genomic synteny visualization and an alignment visualization tool for BLAST results. Altogether, this resource will help wheat research and breeding. Database URL  https://wheat.pw.usda.gov/GG3/pangenome.

Grade of Primary Cutaneous Leiomyosarcoma Dictates Risk for Metastatic Spread and Disease-Specific Mortality.

BACKGROUND AND OBJECTIVES: Primary cutaneous leiomyosarcoma (cLMS), a rare, typically intradermal tumor, has previously been reported to exhibit an indolent course of disease with zero-to-low risk of local recurrence or distant metastasis. This study seeks to evaluate recurrence and survival of cLMS patients through study of its clinicopathologic and treatment characteristics. METHODS: All patients included underwent resection of primary cLMS at this institution between 2006 and 2019. A retrospective cohort study analysis of clinicopathologic characteristics, treatment, recurrence, and overall survival was performed. Data was assessed through descriptive statistics and outcome measures assessed by Cox proportional models and log-rank tests. RESULTS: Eighty-eight patients with cLMS were evaluated. The majority were men (n = 68, 77%) and Caucasian (n = 85, 97%), with median age at diagnosis of 66 years (range 20-96). 65% of tumors were located on the extremities, with a median size of 1.3 cm (range .3-15). Assessment revealed low (n = 41, 47%), intermediate (n = 29, 33%), and high (n = 18, 20%) grade tumors, demonstrating extension into subcutaneous tissue in 38/60 (60%), with 3 patients exhibiting extension into muscle (3%). All underwent resection as primary treatment with median 1 cm margins (range .5-2). With median follow-up of 27.5 months (IQR 8-51; range 1-131), no low-grade cases had recurrence or death while there was a recurrence rate of 19.1% (9/47) and death rate of 8.5% (4/47) in intermediate- to high-grade cases. CONCLUSIONS: Primary tumor resection of cLMS provides excellent local control for low-grade tumors as no low-grade cases experienced recurrence. For patients with intermediate- to high-grade tumors, there is potential for local recurrence, distant metastasis, and death, and therefore surveillance following treatment is encouraged.