TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level.

Single-cell RNA sequencing (scRNA-seq) has significantly accelerated the experimental characterization of distinct cell lineages and types in complex tissues and organisms. Cell-type annotation is of great importance in most of the scRNA-seq analysis pipelines. However, manual cell-type annotation heavily relies on the quality of scRNA-seq data and marker genes, and therefore can be laborious and time-consuming. Furthermore, the heterogeneity of scRNA-seq datasets poses another challenge for accurate cell-type annotation, such as the batch effect induced by different scRNA-seq protocols and samples. To overcome these limitations, here we propose a novel pipeline, termed TripletCell, for cross-species, cross-protocol and cross-sample cell-type annotation. We developed a cell embedding and dimension-reduction module for the feature extraction (FE) in TripletCell, namely TripletCell-FE, to leverage the deep metric learning-based algorithm for the relationships between the reference gene expression matrix and the query cells. Our experimental studies on 21 datasets (covering nine scRNA-seq protocols, two species and three tissues) demonstrate that TripletCell outperformed state-of-the-art approaches for cell-type annotation. More importantly, regardless of protocols or species, TripletCell can deliver outstanding and robust performance in annotating different types of cells. TripletCell is freely available at https://github.com/liuyan3056/TripletCell. We believe that TripletCell is a reliable computational tool for accurately annotating various cell types using scRNA-seq data and will be instrumental in assisting the generation of novel biological hypotheses in cell biology.

Characterizing viral circRNAs and their application in identifying circRNAs in viruses.

Circular RNAs (circRNAs) are non-coding RNAs with a special circular structure produced formed by the reverse splicing mechanism, which play an important role in a variety of biological activities. Viruses can encode circRNA, and viral circRNAs have been found in multiple single-stranded and double-stranded viruses. However, the characteristics and functions of viral circRNAs remain unknown. Sequence alignment showed that viral circRNAs are less conserved than circRNAs in animal, indicating that the viral circRNAs may evolve rapidly. Through the analysis of the sequence characteristics of viral circRNAs and circRNAs in animal, it was found that viral circRNAs and animals circRNAs are similar in nucleic acid composition, but have obvious differences in secondary structure and autocorrelation characteristics. Based on these characteristics of viral circRNAs, machine learning algorithms were employed to construct a prediction model to identify viral circRNA. Additionally, analysis of the interaction between viral circRNA and miRNAs showed that viral circRNA is expected to interact with 518 human miRNAs, and preliminary analysis of the role of viral circRNA. And it has been also found that viral circRNAs may be involved in many KEGG pathways related to nervous system and cancer. We curated an online server, and the data and code are available: http://server.malab.cn/viral-CircRNA/.

Novel Organism Verification and Analysis (NOVA) study: identification of 35 clinical isolates representing potentially novel bacterial taxa using a pipeline based on whole genome sequencing.

BACKGROUND: Reliable species identification of cultured isolates is essential in clinical bacteriology. We established a new study algorithm named NOVA - Novel Organism Verification and Analysis to systematically analyze bacterial isolates that cannot be characterized by conventional identification procedures MALDI-TOF MS and partial 16 S rRNA gene sequencing using Whole Genome Sequencing (WGS). RESULTS: We identified a total of 35 bacterial strains that represent potentially novel species. Corynebacterium sp. (n = 6) and Schaalia sp. (n = 5) were the predominant genera. Two strains each were identified within the genera Anaerococcus, Clostridium, Desulfovibrio, and Peptoniphilus, and one new species was detected within Citrobacter, Dermabacter, Helcococcus, Lancefieldella, Neisseria, Ochrobactrum (Brucella), Paenibacillus, Pantoea, Porphyromonas, Pseudoclavibacter, Pseudomonas, Psychrobacter, Pusillimonas, Rothia, Sneathia, and Tessaracoccus. Twenty-seven of 35 strains were isolated from deep tissue specimens or blood cultures. Seven out of 35 isolated strains identified were clinically relevant. In addition, 26 bacterial strains that could only be identified at the species level using WGS analysis, were mainly organisms that have been identified/classified very recently. CONCLUSION: Our new algorithm proved to be a powerful tool for detection and identification of novel bacterial organisms. Publicly available clinical and genomic data may help to better understand their clinical and ecological role. Our identification of 35 novel strains, 7 of which appear to be clinically relevant, shows the wide range of undescribed pathogens yet to define.

Alveolar nitric oxide concentration plays an important role in identifying cough variant asthma and assessing asthma control in children.

OBJECTIVE: To study the value of alveolar nitric oxide concentration (CaNO) in the identification and disease control of cough variant asthma. METHODS: A retrospective study was conducted on cough variant asthma (CVA-Group), nonasthmatic cough (NAC-Group) and healthy control children (C-Group) aged 5-12 years. The exhaled nitric oxide and spirometry test results of the three groups were collected and compared. RESULTS: A total of 410 children were included in this study, including 190 in the CVA-Group, 183 in the NAC-Group, and 37 in the C-Group. The CaNO values of the CVA-Group [11.40 ppb (8.48-14.25)] were significantly higher than those of the NAC-Group and C-Group (all p values <.05). The MMEF %pred values of the CVA-Group [63.65 (56.28-73.58)] were significantly lower than those of the NAC-Group and C-Group (all p values <.05). FeNO50, JawNO and other spirometry indices (FVC %pred, FEV1%pred, FEV1/FVC %pred) showed no significant difference among the three groups. ROC curve analysis showed that the optimal cutoff point value of CaNO was 9.45 ppb, corresponding to 0.816 sensitivity and 0.736 specificity. Spearman correlation analysis showed a significant negative correlation between the CaNO measurement and CVA control score. CONCLUSIONS: CaNO can not only help identify CVA early in children aged 5-12 years with chronic cough but is also significantly negatively correlated with the CVA control score.

Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936.

BACKGROUND: The Lothian Birth Cohort 1936 (LBC1936) is a longitudinal study of ageing with well-characterised assessments, but until now, it has relied on self-report or proxies for dementia such as cognitive tests. Our aims were twofold: a) to describe a framework for identifying dementia in a cohort study. b) to report the age-specific incidence and prevalence of all-cause dementia and dementia subtypes in 865 individuals in the LBC1936. METHODS: Electronic Health Records (EHR) of all participants were reviewed, and relevant information was extracted to form case vignettes for everyone with any record of cognitive dysfunction. The EHR data sources include hospital and clinic letters, general practitioner and hospital referrals, prescribed medications, imaging and laboratory results. Death certificate data were obtained separately. Clinician assessments were performed when there was concern about a participant's cognition. A diagnosis of probable dementia, possible dementia, or no dementia was agreed upon by a consensus diagnostic review board, comprised of a multidisciplinary team of clinical dementia experts who reviewed case vignettes and clinician assessment letters. For those with probable dementia, a subtype was also determined, where possible. We compared the agreement between our newly ascertained dementia diagnoses with the existing self-reported dementia diagnoses. RESULTS: Self-reported dementia diagnoses were positive in only 17.8% of ascertained dementia diagnoses. The EHR review identified 163/865 (18.8%) individuals as having cognitive dysfunction. At the consensus diagnostic review board, 118/163 were diagnosed with probable all-cause dementia, a prevalence of 13.6%. Age-specific dementia prevalence increased with age from 0.8% (65-74.9 years) to 9.93% (85-89.9 years). Prevalence rates for women were higher in nearly all age groups. The most common subtype was dementia due to Alzheimer disease (49.2%), followed by mixed Alzheimer and cerebrovascular disease (17.0%), dementia of unknown or unspecified cause (16.1%), and dementia due to vascular disease (8.5%). CONCLUSIONS: We present a robust systematic framework and guide for other cohort teams wanting to ascertain dementia diagnoses. The newly ascertained dementia diagnosis provides vital data for further analyses of LBC1936 to allow exploration of lifecourse predictors of dementia.

Dominant infection of Cryptosporidium baileyi in broiler chickens in Zhejiang Province, China.

Cryptosporidium is a common enteric parasite in chickens. A total of 812 fecal specimens were collected from 11 broiler farms in Zhejiang Province, China, and analyzed by nested PCR amplification based on the small subunit ribosomal RNA (SSU rRNA) gene. The overall infection rate of Cryptosporidium was 6.3% (51/812), and five of 11 farms were Cryptosporidium positive. Broilers aged > 90 days accounted for the highest infection rate of 16.1% (6/56), followed by those aged 30-60 days (10.6%, 38/358) and 60-90 days (4/378, 1.1%). Two Cryptosporidium species were identified by sequence analysis, with the predominant species being C. baileyi (96.1%, 49/51) and the minor infection being C. meleagridis (3.9%, 2/51). Based on the 60-kDa glycoprotein (gp60) gene, two C. meleagridis-positive isolates were identified as one known subtype, IIIbA24G1R1. This study indicated the common occurrence of C. baileyi in broiler chickens in this region and low zoonotic transmission potential of Cryptosporidium to humans.

Evaluation and correlation of patient movement during online adaptive radiotherapy with CBCT and a surface imaging system.

PURPOSE: With the clinical implementation of kV-CBCT-based daily online-adaptive radiotherapy, the ability to monitor, quantify, and correct patient movement during adaptive sessions is paramount. With sessions lasting between 20-45 min, the ability to detect and correct for small movements without restarting the entire session is critical to the adaptive workflow and dosimetric outcome. The purpose of this study was to quantify and evaluate the correlation of observed patient movement with machine logs and a surface imaging (SI) system during adaptive radiation therapy. METHODS: Treatment machine logs and SGRT registration data log files for 1972 individual sessions were exported and analyzed. For each session, the calculated shifts from a pre-delivery position verification CBCT were extracted from the machine logs and compared to the SGRT registration data log files captured during motion monitoring. The SGRT calculated shifts were compared to the reported shifts of the machine logs for comparison for all patients and eight disease site categories. RESULTS: The average (±STD) net displacement of the SGRT shifts were 2.6 ± 3.4 mm, 2.6 ± 3.5 mm, and 3.0 ± 3.2 in the lateral, longitudinal, and vertical directions, respectively. For the treatment machine logs, the average net displacements in the lateral, longitudinal, and vertical directions were 2.7 ± 3.7 mm, 2.6 ± 3.7 mm, and 3.2 ± 3.6 mm. The average difference (Machine-SGRT) was -0.1 ± 1.8 mm, 0.2 ± 2.1 mm, and -0.5 ± 2.5 mm for the lateral, longitudinal, and vertical directions. On average, a movement of 5.8 ± 5.6 mm and 5.3 ± 4.9 mm was calculated prior to delivery for the CBCT and SGRT systems, respectively. The Pearson correlation coefficient between CBCT and SGRT shifts was r = 0.88. The mean and median difference between the treatment machine logs and SGRT log files was less than 1 mm for all sites. CONCLUSION: Surface imaging should be used to monitor and quantify patient movement during adaptive radiotherapy.

A Density-Based Multilevel Terrain-Adaptive Noise Removal Method for ICESat-2 Photon-Counting Data.

The photon point clouds collected by the high-sensitivity single-photon detector on the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) are utilized in various applications. However, the discretely distributed noise among the signal photons greatly increases the difficulty of signal extraction, especially the edge noise adjacent to signals. To detect signal photons from vegetation coverage areas at different slopes, this paper proposes a density-based multilevel terrain-adaptive noise removal method (MTANR) that identifies noise in a coarse-to-fine strategy based on the distribution of noise photons and is evaluated with high-precision airborne LiDAR data. First, the histogram-based successive denoising method was used as a coarse denoising process to remove distant noise and part of the sparse noise, thereby increasing the fault tolerance of the subsequent steps. Second, a rotatable ellipse that adaptively corrects the direction and shape based on the slope was utilized to search for the optimal filtering direction (OFD). Based on the direction, sparse noise removal was accomplished robustly using the Otsu's method in conjunction with the ordering points to identify the clustering structure (OPTICS) and provide a nearly noise-free environment for edge searching. Finally, the edge noise was removed by near-ground edge searching, and the signal photons were better preserved by the surface lines. The proposed MTANR was validated in four typical experimental areas: two in Baishan, China, and two in Taranaki, New Zealand. A comparison was made with three other representative methods, namely differential, regressive, and Gaussian adaptive nearest neighbor (DRAGANN), used in ATL08 products, local distance statistics (LDS), and horizontal ellipse-based OPTICS. The results demonstrated that the values of the F1 score for the signal photon identification achieved by the proposed MTANR were 0.9762, 0.9857, 0.9839, and 0.9534, respectively, which were higher than those of the other methods mentioned above. In addition, the qualitative and quantitative results demonstrated that MTANR outperformed in scenes with steep slopes, abrupt terrain changes, and uneven vegetation coverage.

Primary Site Identification of Soft-Tissue Mass: Things to Know in MRI Assessment.

The spectrum of soft-tissue mass is varied, including neoplastic and nonneoplastic/inflammatory lesions. However, soft-tissue tumors have similar imaging findings and, therefore, the diagnosis of soft-tissue mass is challenging. Although careful assessment of the internal characteristics on imaging can often narrow the differential diagnoses, the differential diagnosis may be out of the question if identification of the soft-tissue mass origin is missed. The purpose of this article is to review the imaging findings and the essential anatomy to identify the primary site of the soft-tissue mass, and discuss the associated potential pitfalls. In order not to fall into a pitfall, recognition of characteristic imaging findings indicating the origin of the soft-tissue mass and anatomical knowledge of the normal tissue distribution are necessary. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Culturally safe, high-quality breast cancer screening for transgender people: A scoping review protocol.

AIM: To develop evidence-based recommendations for provision of culturally safe, high-quality services for breast cancer screening for transgender people. DESIGN: The scoping review will follow the JBI methodological guidance for scoping reviews. METHODS: A search using MEDLINE (PubMed), Embase (Ovid), Scopus, the Cochrane Library, including the Cochrane Methodology Register, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and the World Health Organization, Australia Government Department of Health and Google Scholar will be undertaken. The review will include people of any age and ethnicity defined in the source of evidence as transgender. The review will include individuals who have used gender-affirming interventions or not and sources of evidence that report information relevant to the provision of culturally safe, high-quality breast cancer screening services for transgender people. English language sources of evidence published from database inception with information from any country will be eligible for inclusion. Sources will be screened for inclusion by three independent reviewers. Results will be extracted using a purpose-built tool and presented in relation to the review questions and objective in the final report using tables, figures and corresponding narrative. Project funding was approved by the Australian Government Department of Health in June 2020. DISCUSSION: There are a range of factors that impact on the equity of health access and outcomes for people who are not cisgender. Transgender people are at risk of breast cancer but there is relatively little evidence about how their risks may or may not differ substantially from cis-gendered individuals and little guidance for health providers to ensure inclusive, culturally safe, high-quality breast cancer screening services for both transgender males, transgender females and gender diverse people who may not identify as male or as female. IMPACT: It is important to provide culturally safe, high-quality services for breast cancer screening for transgender people.

Research on an Algorithm of Express Parcel Sorting Based on Deeper Learning and Multi-Information Recognition.

With the development of smart logistics, current small distribution centers have begun to use intelligent equipment to indirectly read bar code information on courier sheets to carry out express sorting. However, limited by the cost, most of them choose relatively low-end sorting equipment in a warehouse environment that is complex. This single information identification method leads to a decline in the identification rate of sorting, affecting efficiency of the entire express sorting. Aimed at the above problems, an express recognition method based on deeper learning and multi-information fusion is proposed. The method is mainly aimed at bar code information and three segments of code information on the courier sheet, which is divided into two parts: target information detection and recognition. For the detection of target information, we used a method of deeper learning to detect the target, and to improve speed and precision we designed a target detection network based on the existing YOLOv4 network, Experiments show that the detection accuracy and speed of the redesigned target detection network were much improved. Next for recognition of two kinds of target information we first intercepted the image after positioning and used a ZBAR algorithm to decode the barcode image after interception. The we used Tesseract-OCR technology to identify the intercepted three segments code picture information, and finally output the information in the form of strings. This deeper learning-based multi-information identification method can help logistics centers to accurately obtain express sorting information from the database. The experimental results show that the time to detect a picture was 0.31 s, and the recognition accuracy was 98.5%, which has better robustness and accuracy than single barcode information positioning and recognition alone.

Identifying Cancer genes by combining two-rounds RWR based on multiple biological data.

BACKGROUND: It's a very urgent task to identify cancer genes that enables us to understand the mechanisms of biochemical processes at a biomolecular level and facilitates the development of bioinformatics. Although a large number of methods have been proposed to identify cancer genes at recent times, the biological data utilized by most of these methods is still quite less, which reflects an insufficient consideration of the relationship between genes and diseases from a variety of factors. RESULTS: In this paper, we propose a two-rounds random walk algorithm to identify cancer genes based on multiple biological data (TRWR-MB), including protein-protein interaction (PPI) network, pathway network, microRNA similarity network, lncRNA similarity network, cancer similarity network and protein complexes. In the first-round random walk, all cancer nodes, cancer-related genes, cancer-related microRNAs and cancer-related lncRNAs, being associated with all the cancer, are used as seed nodes, and then a random walker walks on a quadruple layer heterogeneous network constructed by multiple biological data. The first-round random walk aims to select the top score k of potential cancer genes. Then in the second-round random walk, genes, microRNAs and lncRNAs, being associated with a certain special cancer in corresponding cancer class, are regarded as seed nodes, and then the walker walks on a new quadruple layer heterogeneous network constructed by lncRNAs, microRNAs, cancer and selected potential cancer genes. After the above walks finish, we combine the results of two-rounds RWR as ranking score for experimental analysis. As a result, a higher value of area under the receiver operating characteristic curve (AUC) is obtained. Besides, cases studies for identifying new cancer genes are performed in corresponding section. CONCLUSION: In summary, TRWR-MB integrates multiple biological data to identify cancer genes by analyzing the relationship between genes and cancer from a variety of biological molecular perspective.

Disparity level identification using the voxel-wise Gabor model of fMRI data.

Perceiving disparities is the intuitive basis for our understanding of the physical world. Although many electrophysiology studies have revealed the disparity-tuning characteristics of the neurons in the visual areas of the macaque brain, neuron population responses to disparity processing have seldom been investigated. Many disparity studies using functional magnetic resonance imaging (fMRI) have revealed the disparity-selective visual areas in the human brain. However, it is unclear how to characterize neuron population disparity-tuning responses using fMRI technique. In the present study, we constructed three voxel-wise encoding Gabor models to predict the voxel responses to novel disparity levels and used a decoding method to identify the new disparity levels from population responses in the cortex. Among the three encoding models, the fine-coarse model (FCM) that used fine/coarse disparities to fit the voxel responses to disparities outperformed the single model and uncrossed-crossed model. Moreover, the FCM demonstrated high accuracy in predicting voxel responses in V3A complex and high accuracy in identifying novel disparities from responses in V3A complex. Our results suggest that the FCM can better characterize the voxel responses to disparities than the other two models and V3A complex is a critical visual area for representing disparity information.

Establishment of an HPLC-based method to identify key proteases of proteins in vitro.

Given that the biological functions of proteins may decrease or even be lost due to degradation by proteases, it is of great significance to identify potential proteases that degrade protein drugs during systemic circulation. In this work, we describe a method based on high-performance liquid chromatography (HPLC) to identify key proteases that degrade therapeutic proteins in blood, including endopeptidases and exopeptidases. Here, the degradation of proteins was detected by competition with standard substrates of proteases and is shown as the relative residue rate. Four protein drugs were subjected to this method, and the results suggested that growth hormone was degraded by aminopeptidase N and kallikrein-related peptidase 5, pertuzumab was hardly degraded by the proteases, factor VII was degraded by carboxypeptidase B, neprilysin, dipeptidyl peptidase-4 and peptidyl dipeptidase A, and fibrinogen was degraded by carboxypeptidase B and kallikrein-related peptidase 5, findings consistent with the literature. The results were confirmed by microscale thermophoresis; additionally, activity detection in vitro substantiated that the degradation of factor VII decreased its activity. We demonstrate that this method can be used to identify key proteases of proteins with high accuracy, precision and durability.

Acceptability, feasibility and outcome of a screening programme for complicated grief in integrated primary and behavioural health care clinics.

BACKGROUND: Complicated grief, a syndrome of persistent grief diagnosed >6 months following the loss of someone close is expected to be included in the 11th revision of the International Classification of Diseases as a new diagnosis called prolonged grief disorder. Complicated grief is associated with impaired functioning and health comorbidity and does not respond to treatments for depression. Individuals may seek help in primary care where providers need to be familiar with the syndrome. OBJECTIVE: This study examines the acceptability, feasibility and outcome of a screening programme for complicated grief among diverse adults receiving behavioural health services in integrated primary care. METHODS: Behavioural health providers (n = 14) administered the Brief Grief Questionnaire and the Inventory of Complicated Grief during routine assessment and completed an acceptability survey. Descriptive statistics described rates of complicated grief symptoms and sample demographics, health and service use. RESULTS: Most providers (71%) reported the Brief Grief Questionnaire to be a moderate to very useful assessment instrument and the Inventory of Complicated Grief moderate to very useful for developing a treatment plan (57%). Of the 2425 patients screened, 1015 reported a loss over 6 months ago. Of these 1015, 28% (n = 282) screened positive on the Brief Grief Questionnaire and 22% (n = 228) endorsed symptoms of complicated grief (Inventory of Complicated Grief score ≥25), considered at high risk for needing clinical care. CONCLUSIONS: A screening programme for identifying complicated grief was acceptable to providers, feasible to implement and useful in identifying complicated grief in integrated primary care clinics.

Patient-centred education: How do learners' perceptions change as they experience clinical training?

The use of patient educators is one of many teaching strategies meant to foster principles of patient-centred care. We previously found that early patient educator exposure helped to shape the understanding of patient-centredness in pre-clerkship learners. We now expand on this work to evaluate whether there is persistence of initial perceptions and to explore general reflections on longer-term impacts of early patient educator exposures once learners are immersed in the clinical phase of their training. In this follow-up study, we conducted group interviews with a sample of learners who wrote reflections as part of their pre-clerkship patient educator experience. We explored how perspectives on patient educators changed over time, and determined which themes identified during pre-clerkship remained relevant to clinical trainees. Audio recordings were transcribed and analyzed thematically using a hybrid inductive and deductive analysis to construct a thematic framework derived through a method of constant comparison. We identified three new themes: "value of early clinical experience", "change in learners' perspectives", and "valuing and applying CanMEDS roles other than Medical Expert". Themes from pre-clerkship that remained relevant included: "patients' perspective humanizes disease", "patients' experiences with navigating the healthcare system", "learners' perceptions of the learning strategy", and "inaccuracies and inconsistencies in the learning experience." Many themes identified in pre-clerkship learners remain relevant in early clinical trainees. Further, insights from pre-clerkship experiences with patient educators evolve as learners experience clerkship with definite shifts in emphasis and new perspectives. This work illuminates the utility of patient educators for those considering this strategy for supporting the development of patient-centredness in undergraduate medical education.

Identification of the Virulence Factors of Candidatus Liberibacter asiaticus via Heterologous Expression in Nicotiana benthamiana using Tobacco Mosaic Virus.

Huanglongbing (HLB), also known as citrus greening, is the most destructive disease of citrus worldwide. HLB is associated with the non-culturable bacterium, Candidatus Liberibacter asiaticus (CaLas) in the United States. The virulence mechanism of CaLas is largely unknown, partly because of the lack of a mutant library. In this study, Tobacco mosaic virus (TMV) and Nicotiana benthamiana (N. benthamiana) were used for large-scale screening of the virulence factors of CaLas. Agroinfiltration of 60 putative virulence factors in N. benthamiana led to the identification of four candidates that caused severe symptoms in N. benthamiana, such as growth inhibition and cell death. CLIBASIA_05150 and CLIBASIA_04065C (C-terminal of CLIBASIA_04065) could cause cell death in the infiltrated leaves at five days post infiltration. Two low-molecular-weight candidates, CLIBASIA_00470 and CLIBASIA_04025, could inhibit plant growth. By converting start codon to stop codon or frameshifting, the four genes lost their harmful effects to N. benthamiana. It indicated that the four virulence factors functioned at the protein level rather than at the RNA level. The subcellular localization of the four candidates was determined by confocal laser scanning microscope. CLIBASIA_05150 located in the Golgi apparatus; CLIBASIA_04065 located in the mitochondrion; CLIBASIA_00470 and CLIBASIA_04025 distributed in cells as free GFP. The host proteins interacting with the four virulence factors were identified by yeast two-hybrid. The host proteins interacting with CLIBASIA_00470 and CLIBASIA_04025 were overlapping. Based on the phenotypes, the subcellular localization and the host proteins identified by yeast two-hybrid, CLIBASIA_00470 and CLIBASIA_04025, functioned redundantly. The hypothesis of CaLas virulence was proposed. CaLas affects citrus development and suppresses citrus disease resistance, comprehensively, in a complicated manner. Ubiquitin-mediated protein degradation might play a vital role in CaLas virulence. Deep characterization of the interactions between the identified virulence factors and their prey will shed light on HLB. Eventually, it will help in developing HLB-resistant citrus and save the endangered citrus industry worldwide.

The Washington University Central Neuroimaging Data Archive.

Since the early 2000's, much of the neuroimaging work at Washington University (WU) has been facilitated by the Central Neuroimaging Data Archive (CNDA), an XNAT-based imaging informatics system. The CNDA is uniquely related to XNAT, as it served as the original codebase for the XNAT open source platform. The CNDA hosts data acquired in over 1000 research studies, encompassing 36,000 subjects and more than 60,000 imaging sessions. Most imaging modalities used in modern human research are represented in the CNDA, including magnetic resonance (MR), positron emission tomography (PET), computed tomography (CT), nuclear medicine (NM), computed radiography (CR), digital radiography (DX), and ultrasound (US). However, the majority of the imaging data in the CNDA are MR and PET of the human brain. Currently, about 20% of the total imaging data in the CNDA is available by request to external researchers. CNDA's available data includes large sets of imaging sessions and in some cases clinical, psychometric, tissue, or genetic data acquired in the study of Alzheimer's disease, brain metabolism, cancer, HIV, sickle cell anemia, and Tourette syndrome.

To ask, or not to ask: the hesitation process described by district nurses encountering women exposed to intimate partner violence.

AIMS AND OBJECTIVES: To improve the understanding of district nurses' experiences of encountering women exposed to intimate partner violence. BACKGROUND: Intimate partner violence is a public health issue that influences all aspects of affected women's lives; it is thus of great relevance to identify intimate partner violence. District nurses in primary health care in Sweden encounter women of all ages and are therefore in a unique position to identify intimate partner violence and provide nursing care. However, studies indicate that several barriers have kept nurses from identifying intimate partner violence. Consequently deeper understanding of district nurses' encounters with women exposed to intimate partner violence is needed. DESIGN: A qualitative study using grounded theory method. METHODS: Interviews with 11 district nurses in primary health care in Sweden. RESULTS: The hesitation process is central in these encounters. Several barriers to asking and factors that facilitated asking impacted the hesitation process. Under the influence of these factors, district nurses moved from being unaware that identifying intimate partner violence was their professional responsibility, to becoming ambivalent about asking, to starting to prepare themselves to ask about intimate partner violence. The presence of factors that facilitated asking finally made district nurses feel prepared, and then they decided to ask women about intimate partner violence. CONCLUSIONS: The concept of managing the hesitation process could be used to be incorporated in continuing education and training. Barriers and facilitators concerning organisational factors found in this study may be specific to the Swedish health care system, but the concept of the hesitation process is applicable in similar contexts and perhaps to other issues about which it is difficult to ask. RELEVANCE TO CLINICAL PRACTICE: This study illuminates the importance of a supportive work environment in reducing district nurses' hesitation to ask about intimate partner violence and to propose continuing education, training and supervision for district nurses regarding intimate partner violence.