Corrigendum: Pre-transplant crossmatch-negative donor-specific anti-HLA antibody predicts acute antibody-mediated rejection but not long-term outcomes in kidney transplantation: an analysis of the Korean Organ Transplantation Registry.

[This corrects the article DOI: 10.3389/fimmu.2024.1420351.].

Advancing equity in breast cancer care: natural language processing for analysing treatment outcomes in under-represented populations.

OBJECTIVE: The study aimed to develop natural language processing (NLP) algorithms to automate extracting patient-centred breast cancer treatment outcomes from clinical notes in electronic health records (EHRs), particularly for women from under-represented populations. METHODS: The study used clinical notes from 2010 to 2021 from a tertiary hospital in the USA. The notes were processed through various NLP techniques, including vectorisation methods (term frequency-inverse document frequency (TF-IDF), Word2Vec, Doc2Vec) and classification models (support vector classification, K-nearest neighbours (KNN), random forest (RF)). Feature selection and optimisation through random search and fivefold cross-validation were also conducted. RESULTS: The study annotated 100 out of 1000 clinical notes, using 970 notes to build the text corpus. TF-IDF and Doc2Vec combined with RF showed the highest performance, while Word2Vec was less effective. RF classifier demonstrated the best performance, although with lower recall rates, suggesting more false negatives. KNN showed lower recall due to its sensitivity to data noise. DISCUSSION: The study highlights the significance of using NLP in analysing clinical notes to understand breast cancer treatment outcomes in under-represented populations. The TF-IDF and Doc2Vec models were more effective in capturing relevant information than Word2Vec. The study observed lower recall rates in RF models, attributed to the dataset's imbalanced nature and the complexity of clinical notes. CONCLUSION: The study developed high-performing NLP pipeline to capture treatment outcomes for breast cancer in under-represented populations, demonstrating the importance of document-level vectorisation and ensemble methods in clinical notes analysis. The findings provide insights for more equitable healthcare strategies and show the potential for broader NLP applications in clinical settings.

Pre-transplant crossmatch-negative donor-specific anti-HLA antibody predicts acute antibody-mediated rejection but not long-term outcomes in kidney transplantation: an analysis of the Korean Organ Transplantation Registry.

Background: Pre-transplant donor-specific anti-human leukocyte antigen antibody (HLA-DSA) is a recognized risk factor for acute antibody-mediated rejection (ABMR) and allograft failure. However, the clinical relevance of pre-transplant crossmatch (XM)-negative HLA-DSA remains unclear. Methods: We investigated the effect of XM-negative HLA-DSA on post-transplant clinical outcomes using data from the Korean Organ Transplantation Registry (KOTRY). This study included 2019 living donor kidney transplant recipients from 40 transplant centers in South Korea: 237 with HLA-DSA and 1782 without HLA-DSA. Results: ABMR developed more frequently in patients with HLA-DSA than in those without (5.5% vs. 1.5%, p<0.0001). Multivariable analysis identified HLA-DSA as a significant risk factor for ABMR (odds ratio = 3.912, 95% confidence interval = 1.831-8.360; p<0.0001). Furthermore, the presence of multiple HLA-DSAs, carrying both class I and II HLA-DSAs, or having strong HLA-DSA were associated with an increased incidence of ABMR. However, HLA-DSA did not affect long-term clinical outcomes, such as allograft function and allograft survival, patient survival, and infection-free survival. Conclusion: Pre-transplant XM-negative HLA-DSA increased the risk of ABMR but did not affect long-term allograft outcomes. HLA-incompatible kidney transplantation in the context of XM-negative HLA-DSA appears to be feasible with careful monitoring and ensuring appropriate management of any occurrence of ABMR. Furthermore, considering the characteristics of pre-transplant XM-negative HLA-DSA, the development of a more detailed and standardized desensitization protocol is warranted.

Chromosome-Scale, De Novo, Phased Genome Assemblies of Three Australian Limes: Citrus australasica, C. inodora, and C. glauca.

Huanglongbing (HLB) is a severe citrus disease worldwide. Wild Australian limes like Citrus australasica, C. inodora, and C. glauca possess beneficial HLB resistance traits. Individual trees of the three taxa were extensively used in a breeding program for over a decade to introgress resistance traits into commercial-quality citrus germplasm. We generated high-quality, phased, de novo genome assemblies of the three Australian limes using PacBio long-read sequencing. The genome assembly sizes of the primary and alternate haplotypes were determined for C. australasica (337 Mb/335 Mb), C. inodora (304 Mb/299 Mb), and C. glauca (376 Mb/379 Mb). The nine chromosome-scale scaffolds included 86-91% of the genome sequences generated. The integrity and completeness of the assembled genomes were estimated to be at 97.2-98.8%. Gene annotation studies identified 25,461 genes in C. australasica, 27,665 in C. inodora, and 30,067 in C. glauca. Genes belonging to 118 orthogroups were specific to Australian lime genomes compared to other citrus genomes analyzed. Significantly fewer canonical resistance (R) genes were found in C. inodora and C. glauca (319 and 449, respectively) compared to C. australasica (576), C. clementina (579), and C. sinensis (651). Similar patterns were observed for other gene families associated with potential HLB resistance, including Phloem protein 2 (PP2) and Callose synthase (CalS) genes predicted in the Australian lime genomes. The genomic information on Australian limes developed in the present study will help understand the genetic basis of HLB resistance.

Spatial Dynamics of Demersal Fish Assemblages off the Korean Coast in the East Sea.

This study assessed variations in demersal fish assemblages with respect to the study site and water depth. Seasonal samplings from May 2018 to March 2019 were conducted along the northern (Ayajin, Goseong) and southern (Hupo, Uljin) sites of the East Sea off the Korean coast, using commercial gill nets. Samples were collected at depths of ~50, ~80, ~150 m across the study sites, with concurrent monitoring of water column structures. A total of 73 species and 6250 specimens were collected. Distinctive fish species compositions were observed according to the study site and depth. Although Glyptocephalus stelleri was the most abundant fish species in both Ayajin and Hupo, Gadus macrocephalus, Icelus cataphractus, and Alcichthys elongatus were most predominant in Ayajin, whereas Cleisthenes pinetorum, Hippoglossoides dubius, and Gymnocanthus herzensteini were more prevalent in Hupo. In terms of depth layer, in Ayajin, G. stelleri dominated in both intermediate and deeper layers, with Hemilepidotus gilberti, A. elongatus, Enophrys diceraus common in shallower depths. Conversely, in Hupo, G. stelleri, C. pinetorum, and A. nadeshnyi dominated across all depth layers, whereas Dasycottus setiger and G. herzensteini dominated in deeper and shallower depths, respectively. Significant influences of the study site and water depth on fish assemblage structures were observed due to variations in water temperature at the seasonal thermocline boundary.

Experience of Implementing Deep Learning-Based Automatic Contouring in Breast Radiation Therapy Planning: Insights From Over 2000 Cases.

PURPOSE: This study evaluated the impact and clinical utility of an auto-contouring system for radiation therapy treatments. METHODS AND MATERIALS: The auto-contouring system was implemented in 2019. We evaluated data from 2428 patients who underwent adjuvant breast radiation therapy before and after the system's introduction. We collected the treatment's finalized contours, which were reviewed and revised by a multidisciplinary team. After implementation, the treatment contours underwent a finalization process that involved manual review and adjustment of the initial auto-contours. For the preimplementation group (n = 369), auto-contours were generated retrospectively. We compared the auto-contours and final contours using the Dice similarity coefficient (DSC) and the 95% Hausdorff distance (HD95). RESULTS: We analyzed 22,215 structures from final and corresponding auto-contours. The final contours were generally larger, encompassing more slices in the superior or inferior directions. Among organs at risk (OAR), the heart, esophagus, spinal cord, and contralateral breast demonstrated significantly increased DSC and decreased HD95 postimplementation (all P < .05), except for the lungs, which presented inaccurate segmentation. Among target volumes, CTVn_L2, L3, L4, and the internal mammary node showed increased DSC and decreased HD95 postimplementation (all P < .05), although the increase was less pronounced than the OAR outcomes. The analysis also covered factors contributing to significant differences, pattern identification, and outlier detection. CONCLUSIONS: In our study, the adoption of an auto-contouring system was associated with an increased reliance on automated settings, underscoring its utility and the potential risk of automation bias. Given these findings, we underscore the importance of considering the integration of stringent risk assessments and quality management strategies as a precautionary measure for the optimal use of such systems.

Diversity of 'Candidatus Liberibacter asiaticus' Strains in Texas Revealed by Prophage Sequence Analyses.

Prophages/phages are important components of the genome of 'Candidatus Liberibacter asiaticus' (CLas), an unculturable alphaproteobacterium associated with citrus huanglongbing (HLB) disease. Phage variations have significant contributions to CLas strain diversity research, which provide critical information for HLB management. In this study, prophage variations among selected CLas strains from southern Texas were studied. The CLas strains were collected from three different CLas inhabitant environments: citrus leaf, citrus root, and Asian citrus psyllid (ACP), the vector of CLas. Regardless of the different habitats and time span, more than 80% of CLas strains consistently had both Type 1 and Type 2 prophages, the same prophage type profile as in CLas strains from Florida but different to those reported in California and China. Further studies were performed on prophage type diversity. Analyses on Type 1-specific PCR amplicon sequences (encoding an endolysin protein) revealed the presence of two groups: Type 1-A, clustered around prophage SC1 originating from Florida, and Type 1-B, clustered with prophage P-SGCA5-1 originating in California. Type 1-B strains were mostly from ACP of nearby citrus orchards. On the other hand, analyses on Type 2-specific PCR amplicon sequences (encoding a putative hypothetical protein) showed a single group clustering around prophage SC2 originated from Florida, although a different Type 2 prophage has been reported in California. The presence of two distinct Type 1 prophage groups suggested the possibility of two different CLas introductions in southern Texas. The results from this study provide an initial baseline of information on genomic and population diversity of CLas in Texas.

Efficacy of Radiomics in Predicting Oncologic Outcome of Liver-Directed Combined Radiotherapy in Locally Advanced Hepatocellular Carcinoma.

PURPOSE: We investigated whether radiomic features extracted from three-phase dynamic contrast-enhanced computed tomography (CECT) can be used to predict clinical outcomes, including objective treatment response (OR) and in-field failure-free survival rate (IFFR), in patients with hepatocellular carcinoma (HCC) who received liver-directed combined radiotherapy (LD-CRT). METHODS: We included 409 patients, and they were randomly divided into training (n = 307) and validation (n = 102) cohorts. For radiomics models, we extracted 116 radiomic features from the region of interest on the CECT images. Significant clinical prognostic factors are identified to predict the OR and IFFR in the clinical models. We developed clinical models, radiomics models, and a combination of both features (CCR model). RESULTS: Among the radiomic models evaluated for OR, the OR-PVP-Peri-1cm model showed favorable predictive performance with an area under the curve (AUC) of 0.647. The clinical model showed an AUC of 0.729, whereas the CCR model showed better performance (AUC 0.759). For the IFFR, the IFFR-PVP-Peri-1cm model showed an AUC of 0.673, clinical model showed 0.687, and the CCR model showed 0.736. We also developed and validated a prognostic nomogram based on CCR models. CONCLUSION: In predicting the OR and IFFR in patients with HCC undergoing LD-CRT, CCR models performed better than clinical and radiomics models. Moreover, the constructed nomograms based on these models may provide valuable information on the prognosis of these patients.

Identification of the Plant Family Caryophyllaceae in Korea Using DNA Barcoding.

Caryophyllaceae is a large angiosperm family, with many species being utilized as ornamental or medicinal plants in Korea, in addition to several endangered species that are managed by the government. In this study, we used DNA barcoding for the accurate identification of Korean Caryophyllaceae. A total of 78 taxa (n = 215) were sequenced based on three chloroplast regions (rbcL, matK, and psbA-trnH) and nuclear ribosomal internal transcribed spacers (ITS). In the neighbor-joining tree, a higher accuracy of identification was generally observed when using ITS (>73%) rather than chloroplast regions (<62%). The highest resolution was found for rbcL + ITS (77.6%), although resolution varied according to the genus. Among the genera that included two and more species, five genera (Eremogone, Minuartia, Pseudostellaria, Sagina, and Stellaria) were successfully identified. However, the species of five other genera (Cerastium, Gypsophila, Dianthus, Silene, and Spergularia) showed relatively low resolutions (0-61.1%). In the cases of Cerastium, Dianthus, and Silene, ambiguous taxonomic relationships among unidentified species may have been a factor contributing to such low resolutions. However, in contrast to these results, Gypsophila and Spergularia have been identified well in previous studies. Our findings indicate the need of taxonomic reconsideration in Korea.

First report of L1 cell adhesion molecule (L1CAM) in flat fish (Starry flounder): Molecular features and expression analysis.

In this study, the starry flounder L1 cell adhesion molecule (L1CAM) sequence was obtained using next-generation sequencing, and the integrity of the sequence was verified by cloning and sequencing. First, the amino acid sequence was predicted using the cDNA sequence, and the gene was then identified through multiple sequence alignment analysis with related sequences and phylogenetic analysis. Thus, homogeneity was confirmed. The expression level of PsL1CAM (Platichthys stellatus L1CAM) mRNA in healthy starry flounder was detected in all tissues used in the experiment, and tissue- and gene-specific expression levels were confirmed. In addition, as a result of mRNA expression analysis after artificial infection with viral hemorrhagic septicemia virus (VHSV) and Streptococcus parauberis PH0710, significant expression changes and characteristics were confirmed following infection with VHSV and S. parauberis PH0710. After artificial infection with VHSV, the expression level of PsL1CAM mRNA was significantly upregulated in almost all major tissues of the starry flounder, whereas it was significantly downregulated in mucosal-associated lymphoid tissues, such as the gills and intestine. Infection with S. parauberis PH0710 significantly upregulated the expression of PsL1CAM mRNA in almost all major tissues of the starry flounder, whereas it was significantly downregulated in the heart after infection. Our results indicate that PsL1CAM may be involved in the host immune response to starry flounders.