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.

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.

A Field Deployable Real-Time Loop-Mediated Isothermal Amplification Targeting Five Copy nrdB Gene for the Detection of 'Candidatus Liberibacter asiaticus' in Citrus.

Huanglongbing (HLB) is one of the most destructive diseases in citrus, which imperils the sustainability of citriculture worldwide. The presumed causal agent of HLB, 'Candidatus Liberibacter asiaticus' (CLas) is a non-culturable phloem-limited α-proteobacterium transmitted by Asian citrus psyllids (ACP, Diaphorina citri Kuwayama). A widely adopted method for HLB diagnosis is based on quantitative real-time polymerase chain reaction (qPCR). Although HLB diagnostic qPCR provides high sensitivity and good reproducibility, it is limited by time-consuming DNA preparation from plant tissue or ACP and the requirement of proper lab instruments including a thermal cycler to conduct qPCR. In an attempt to develop a quick assay that can be deployed in the field for CLas detection, we developed a real-time loop-mediated isothermal amplification (rt-LAMP) assay by targeting the CLas five copy nrdB gene. The rt-LAMP assay using various plant sample types and psyllids successfully detected the nrdB target as low as ~2.6 Log10 copies. Although the rt-LAMP assay was less sensitive than laboratory-based qPCR (detection limit ~10 copies), the data obtained with citrus leaf and bark and ACP showed that the rt-LAMP assay has >96% CLas detection rate, compared to that of laboratory-based qPCR. However, the CLas detection rate in fibrous roots was significantly decreased compared to qPCR due to low CLas titer in some root DNA sample. We also demonstrated that the rt-LAMP assay can be used with a crude leaf DNA extract which is fully deployable in the field for quick and reliable HLB screening.

Analysis of Polymeric Immunoglobulin Receptor Expression in Olive Flounder (Paralichthys olivaceus) against Viral Hemorrhagic Septicemia Virus.

Polymeric immunoglobulin receptor (pIgR) mediates the transfer of polymeric immunoglobulin to protect organisms and is one of the most important mucosal effectors. In this study, the developmental stage- and tissue-specific expression of pIgR were observed before virus inoculation in olive flounder. pIgR was gradually expressed until the formation of immune tissue, exhibiting high expression in the late juvenile period; thereafter, pIgR expression gradually decreased and exhibited high expression in the spleen and skin. Moreover, pIgR expression after viral hemorrhagic septicemia virus infection was high in the kidney and spleen tissues at high density and low at low density. The results of this study can provide a basis for future studies on breeding density, virus expression, and immune system studies in fish.

High water temperature-mediated immune gene expression of olive flounder, Paralichthys olivaceus according to pre-stimulation at high temperatures.

Increased ocean temperature due to global warming affects the health and immunity of fish. In this study, juvenile Paralichthys olivaceus were exposed to high temperature after pre-heat (Acute: Acute heat shock at 32 °C, AH-S: Acquired heat shock at 28 °C & short recovery (2 h) and heat shock at 32 °C, AH-L: acquired heat shock at 28 °C and long recovery (2 days), AH-LS: acquired heat shock at 28 °C & long (2 days) + short (2 h) recovery). Heat shock after pre-heat significantly upregulated various immune-related genes, including interleukin 8 (IL-8), c-type lysozyme (c-lys), immunoglobulin M (IgM), Toll-like receptor 3 (tlr3), major histocompatibility complex IIα (mhcIIα) and cluster of differentiation 8α (cd8α) in the liver and brain of P. olivaceus. This study showed pre-exposure to high temperatures below the critical temperature can activate fish immunity and increase tolerance to high temperatures.

The complete chloroplast genome sequence of the medicinal plant, Dracocephalum rupestre (Lamiaceae).

Dracocephalum rupestre (tribe Mentheae; Lamiaceae) is a perennial herb from Korea and China with high ornamental and medicinal value. Here, we report its complete chloroplast genome to provide insight into the phylogenetic relationships of Dracocephalum. The genome is 151,230 bp long, with two inverted repeat regions (25,643 bp each) that separate a large single-copy region (82,536 bp) and a small single-copy region (17,408 bp). It contains 133 genes that encode 88 proteins, eight rRNAs, and 37 tRNAs. The maximum-likelihood phylogenetic analysis strongly supported Dracocephalum monophyly, showing that the genus forms a sister group with the subtribe Menthinae in the tribe Mentheae.

Evaluation of race/ethnicity-specific survival machine learning models for Hispanic and Black patients with breast cancer.

OBJECTIVES: Survival machine learning (ML) has been suggested as a useful approach for forecasting future events, but a growing concern exists that ML models have the potential to cause racial disparities through the data used to train them. This study aims to develop race/ethnicity-specific survival ML models for Hispanic and black women diagnosed with breast cancer to examine whether race/ethnicity-specific ML models outperform the general models trained with all races/ethnicity data. METHODS: We used the data from the US National Cancer Institute's Surveillance, Epidemiology and End Results programme registries. We developed the Hispanic-specific and black-specific models and compared them with the general model using the Cox proportional-hazards model, Gradient Boost Tree, survival tree and survival support vector machine. RESULTS: A total of 322 348 female patients who had breast cancer diagnoses between 1 January 2000 and 31 December 2017 were identified. The race/ethnicity-specific models for Hispanic and black women consistently outperformed the general model when predicting the outcomes of specific race/ethnicity. DISCUSSION: Accurately predicting the survival outcome of a patient is critical in determining treatment options and providing appropriate cancer care. The high-performing models developed in this study can contribute to providing individualised oncology care and improving the survival outcome of black and Hispanic women. CONCLUSION: Predicting the individualised survival outcome of breast cancer can provide the evidence necessary for determining treatment options and high-quality, patient-centred cancer care delivery for under-represented populations. Also, the race/ethnicity-specific ML models can mitigate representation bias and contribute to addressing health disparities.

Co-Occurrence Analysis of Citrus Root Bacterial Microbiota under Citrus Greening Disease.

Candidatus Liberibacter asiaticus (CLas) is associated with Citrus Huanglongbing (HLB), a devastating disease in the US. Previously, we conducted a two-year-long monthly HLB survey by quantitative real-time PCR using root DNA fractions prepared from 112 field grapefruit trees grafted on sour orange rootstock. Approximately 10% of the trees remained CLas-free during the entire survey period. This study conducted 16S metagenomics using the time-series root DNA fractions, monthly prepared during twenty-four consecutive months, followed by microbial co-occurrence network analysis to investigate the microbial factors contributing to the CLas-free phenotype of the aforementioned trees. Based on the HLB status and the time when the trees were first diagnosed as CLas-positive during the survey, the samples were divided into four groups, Stage H (healthy), Stage I (early), II (mid), and III (late) samples. The 16S metagenomics data using Silva 16S database v132 revealed that HLB compromised the diversity of rhizosphere microbiota. At the phylum level, Actinobacteria and Proteobacteria were the predominant bacterial phyla, comprising >93% of total bacterial phyla, irrespective of HLB status. In addition, a temporal change in the rhizosphere microbe population was observed during a two-year-long survey, from which we confirmed that some bacterial families differently responded to HLB disease status. The clustering of the bacterial co-occurrence network data revealed the presence of a subnetwork composed of Streptomycetaceae and bacterial families with plant growth-promoting activity in Stage H and III samples. These data implicated that the Streptomycetaceae subnetwork may act as a functional unit against HLB.

Multilayer Perceptron-Based Real-Time Intradialytic Hypotension Prediction Using Patient Baseline Information and Heart-Rate Variation.

Intradialytic hypotension (IDH) is a common side effect that occurs during hemodialysis and poses a great risk for dialysis patients. Many studies have been conducted so far to predict IDH, but most of these could not be applied in real-time because they used only underlying patient information or static patient disease information. In this study, we propose a multilayer perceptron (MP)-based IDH prediction model using heart rate (HR) information corresponding to time-series information and static data of patients. This study aimed to validate whether HR differences and HR slope information affect real-time IDH prediction in patients undergoing hemodialysis. Clinical data were collected from 80 hemodialysis patients from 9 September to 17 October 2020, in the artificial kidney room at Yeungnam University Medical Center (YUMC), Daegu, South Korea. The patients typically underwent hemodialysis 12 times during this period, 1 to 2 h per session. Therefore, the HR difference and HR slope information within up to 1 h before IDH occurrence were used as time-series input data for the MP model. Among the MP models using the number and data length of different hidden layers, the model using 60 min of data before the occurrence of two layers and IDH showed maximum performance, with an accuracy of 81.5%, a true positive rate of 73.8%, and positive predictive value of 87.3%. This study aimed to predict IDH in real-time by continuously supplying HR information to MP models along with static data such as age, diabetes, hypertension, and ultrafiltration. The current MP model was implemented using relatively limited parameters; however, its performance may be further improved by adding additional parameters in the future, further enabling real-time IDH prediction to play a supporting role for medical staff.

Peripherally Inserted Central Catheter by Interventional Nephrologists: Experiences from a Single Center.

Purpose: As the number of patients with chronic kidney disease increases, nephrologist activities are gradually expanding. This study evaluated the safety and success of peripherally inserted central catheter (PICC) performed by nephrologists. Patients and Methods: We retrospectively analyzed the medical records of a medical center. All patients underwent a PICC procedure by two nephrologists. The reasons for catheter removal were classified as accidental removal; treatment termination; catheter occlusion; vessel thrombosis; catheter-related infection, or patient death. Overall catheter complications were defined as catheter occlusion, vessel thrombosis, or catheter-related infection. Results: A total of 335 catheterizations among 286 patients were performed. Overall, catheter removal was required during follow-up in 251 of 335 cases. The catheter was removed in 48 out of 251 (19.1%) cases with catheter-related complications. In univariate and multivariate analyses, diabetes mellitus was associated with catheter-related infection. The catheter survival rates were 85.3% at 1 month. In univariate and multivariate analyses, diabetes mellitus and fluoroscopy-guided insertion were associated with favorable catheter survival. Conclusion: The results of our study showed high success and low complication rates for PICC insertion by nephrologists. These findings indicate that interventional nephrologists already skilled in other procedures can expand their field of activity and profit.

Host-derived chimeric peptides clear the causative bacteria and augment host innate immunity during infection: A case study of HLB in citrus and fire blight in apple.

Bacterial diseases cause severe losses in the production and revenue of many fruit crops, including citrus and apple. Huanglongbing (HLB) in citrus and fire blight in apple are two deadly diseases without any cure. In this article, we introduce a novel therapy for HLB and fire blight by enhancing the innate immunity of the host plants. Specifically, we constructed in silico a library of chimeras containing two different host peptides with observed or predicted antibacterial activity. Subsequently, we performed bactericidal and toxicity tests in vitro to select a few non-toxic chimeras with high antibacterial activity. Finally, we conducted ex planta studies to show that not only do the chimeras clear the causative bacteria from citrus leaves with HLB and from apple leaves with fire blight but they also augment the host's innate immunity during infection. This platform technology can be extended to design host-derived chimeras against multiple pathogenic bacteria that cause diseases in plants and animals of agricultural importance and in humans.

Sensing Techniques for Organochlorides through Intermolecular Interaction with Bicyclic Amidines.

Toxic organochloride molecules are widely used in industry for various purposes. With their high volatility, the direct detection of organochlorides in environmental samples is challenging. Here, a new organochloride detection mechanism using 1,5-diazabicyclo[4.3.0]non-5-ene (DBN) is introduced to simplify a sensing method with higher detection sensitivity. Three types of organochloride compounds-trichloroethylene (TCE), dichloromethane (DCM), and dichlorodiphenyltrichloroethane (DDT)-were targeted to understand DCM conjugation chemistry by using nuclear magnetic resonance (NMR) and liquid chromatography with a mass spectrometer (LC-MS). 13C-NMR spectra and LC-MS data indicated that DBN can be labeled on these organochloride compounds by chlorine-nitrogen interaction. Furthermore, to demonstrate the organochloride sensing capability, the labeling yield and limit of detection were determined by a colorimetric assay as well as micellar electrokinetic chromatography (MEKC). The interaction with DBN was most appreciable for TCE, among other organochlorides. TCE was detected at picomolar levels, which is two orders of magnitude lower than the maximum contaminant level set by the United States Environmental Protection Agency. MEKC, in conjunction with this DBN-labeling method, enables us to develop a field-deployable sensing platform for detecting toxic organochlorides with high sensitivity.