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Coronavirus disease (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is currently spreading globally. To overcome the COVID-19 pandemic, preclinical evaluations of vaccines and therapeutics using K18-hACE2 and CAG-hACE2 transgenic mice are ongoing. However, a comparative study on SARS-CoV-2 infection between K18-hACE2 and CAG-hACE2 mice has not been published. In this study, we compared the susceptibility and resistance to SARS-CoV-2 infection between two strains of transgenic mice, which were generated in FVB background mice. K18-hACE2 mice exhibited severe weight loss with definitive lethality, but CAG-hACE2 mice survived; and differences were observed in the lung, spleen, cerebrum, cerebellum, and small intestine. A higher viral titer was detected in the lungs, cerebrums, and cerebellums of K18-hACE2 mice than in the lungs of CAG-hACE2 mice. Severe pneumonia was observed in histopathological findings in K18-hACE2, and mild pneumonia was observed in CAG-hACE2. Atrophy of the splenic white pulp and reduction of spleen weight was observed, and hyperplasia of goblet cells with villi atrophy of the small intestine was observed in K18-hACE2 mice compared to CAG-hACE2 mice. These results indicate that K18-hACE2 mice are relatively susceptible to SARS-CoV-2 and that CAG-hACE2 mice are resistant to SARS-CoV-2. Based on these lineage-specific sensitivities, we suggest that K18-hACE2 mouse is suitable for highly susceptible model of SARS-CoV-2, and CAG-hACE2 mouse is suitable for mild susceptible model of SARS-CoV-2 infection.

This study aimed to investigate the predictive efficacy of positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) for the pathological response of advanced breast cancer to neoadjuvant chemotherapy (NAC). The breast PET/MRI image deep learning model was introduced and compared with the conventional methods. PET/CT and MRI parameters were evaluated before and after the first NAC cycle in patients with advanced breast cancer [n = 56; all women; median age, 49 (range 26–66) years]. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained with the corresponding baseline values (SUV0, MTV0, and TLG0, respectively) and interim PET images (SUV1, MTV1, and TLG1, respectively). Mean apparent diffusion coefficients were obtained from baseline and interim diffusion MR images (ADC0 and ADC1, respectively). The differences between the baseline and interim parameters were measured (ΔSUV, ΔMTV, ΔTLG, and ΔADC). Subgroup analysis was performed for the HER2-negative and triple-negative groups. Datasets for convolutional neural network (CNN), assigned as training (80%) and test datasets (20%), were cropped from the baseline (PET0, MRI0) and interim (PET1, MRI1) images. Histopathologic responses were assessed using the Miller and Payne system, after three cycles of chemotherapy. Receiver operating characteristic curve analysis was used to assess the performance of the differentiating responders and non-responders. There were six responders (11%) and 50 non-responders (89%). The area under the curve (AUC) was the highest for ΔSUV at 0.805 (95% CI 0.677–0.899). The AUC was the highest for ΔSUV at 0.879 (95% CI 0.722–0.965) for the HER2-negative subtype. AUC improved following CNN application (SUV0:PET0 = 0.652:0.886, SUV1:PET1 = 0.687:0.980, and ADC1:MRI1 = 0.537:0.701), except for ADC0 (ADC0:MRI0 = 0.703:0.602). PET/MRI image deep learning model can predict pathological responses to NAC in patients with advanced breast cancer.

Flowering in Arabidopsis thaliana is controlled by multiple pathways, including the photoperiod pathway and the FLOWERING LOCUS C (FLC)-dependent pathway. Here, we report that a pair of related jumonji-class transcription factors, EARLY FLOWERING 6 (ELF6) and RELATIVE OF EARLY FLOWERING 6 (REF6), play divergent roles in the regulation of Arabidopsis flowering. ELF6 acts as a repressor in the photoperiod pathway, whereas REF6, which has the highest similarity to ELF6, is an FLC repressor. Ectopic expression studies and expression pattern analyses show that ELF6 and REF6 have different cellular roles and are also regulated differentially despite their sequence similarities. Repression of FLC expression by REF6 accompanies histone modifications in FLC chromatin, indicating that the transcriptional regulatory activity of this class of proteins includes chromatin remodeling. This report demonstrates the in vivo functions of this class of proteins in higher eukaryotes.

Emerging evidence suggests that the mammalian target of rapamcyin (mTOR) pathway is associated with radio-resistance in cancer treatment. We hypothesised that phosphorylated ribosomal S6 kinase 1 (p-S6K1), a major downstream regulator of the mTOR pathway, may play a role in predicting radio-resistance. Therefore, we evaluated the association of p-S6K1 expression with radio-resistance in breast cancer cell lines and patients. During median follow-up of 33 (range, 0.1–111) months for 1770 primary breast cancer patients who underwent surgery, patients expressing p-S6K1 showed worse 10-year loco-regional recurrence-free survival (LRFS) compared to that of p-S6K1-negative patients after radiotherapy (93.4% vs. 97.7%, p  = 0.015). Multivariate analysis revealed p-S6K1 expression as a predictor of radio-resistance (hazard ratio 7.9, 95% confidence interval 1.1–58.5, p  = 0.04). In vitro , CD44 high /CD24 low MCF7 cells with a radioresistant phenotype expressed higher levels of p-S6K1 than control MCF7 cells. Furthermore, the combination of radiation with treatment of everolimus, an mTOR-S6K1 pathway inhibitor, sensitised CD44 high /CD24 low MCF7 cells to a greater extent than MCF7 cells. This study provides in vivo and in vitro evidence for p-S6K1 expression status as an important marker for predicting the resistance to radiotherapy and as a possible target for radio-sensitization in breast cancer patients.

Background Chemo-endocrine therapy can lead to various side effects associated with ovarian dysfunction. Predicting menstrual recovery is necessary to discuss the treatment-related issues regarding fertility and premature menopause with patients. Methods In the ASTRRA trial, patients who resumed ovarian function within 2 years after chemotherapy were randomized to receive tamoxifen for 5 years or OFS with tamoxifen for 2 years. With these 1298 patients, we developed a model that predicts when menstrual recovery will occur within a 3-year period after chemotherapy using variables including age, body mass index, chemotherapy regimen and duration, and serum estradiol and follicle-stimulating hormone levels. Results The data of 957 patients were used to develop the prediction model, and those of 341 patients were used for validation. In the development group, menstruation resumed in 450 patients (47.0%) within 5 years. In multivariable analysis, younger age (< 35 vs. 45, HR 7.85, 95% CI 4.63–13.30, p  < 0.0001), anthracycline-based chemotherapy without taxane (vs. with taxane, HR 1.81, 95% CI 1.37–2.38, p  < 0.0001), and chemotherapy duration (≤ 90 days vs. > 90 days, HR 1.32, 95% CI 1.01–1.72, p  = 0.045) correlated with menstrual recovery. Using combined age, regimen, and duration of chemotherapy, we developed a simplified scoring system to estimate recovery chances and used a concordance index of 0.679 overall and 0.744 at 3 years for validation. Conclusion This model predicted timing and probability of menstrual recovery, based on their individual age, type and duration of chemotherapy in premenopausal women diagnosed with breast cancer who received tamoxifen after chemotherapy.

Doil Choi and colleagues report the genome sequence of the hot pepper, Capsicum annuum , as well as the resequencing of two cultivated peppers and a wild species, Capsicum chinense . Comparative genomic analysis across Solanaceae provides insights into genome expansion, pungency, ripening and disease resistance in hot peppers. Hot pepper ( Capsicum annuum ), one of the oldest domesticated crops in the Americas, is the most widely grown spice crop in the world. We report whole-genome sequencing and assembly of the hot pepper (Mexican landrace of Capsicum annuum cv. CM334) at 186.6× coverage. We also report resequencing of two cultivated peppers and de novo sequencing of the wild species Capsicum chinense . The genome size of the hot pepper was approximately fourfold larger than that of its close relative tomato, and the genome showed an accumulation of Gypsy and Caulimoviridae family elements. Integrative genomic and transcriptomic analyses suggested that change in gene expression and neofunctionalization of capsaicin synthase have shaped capsaicinoid biosynthesis. We found differential molecular patterns of ripening regulators and ethylene synthesis in hot pepper and tomato. The reference genome will serve as a platform for improving the nutritional and medicinal values of Capsicum species.

Background Coronavirus disease 2019 (COVID-19) continues to impact populations globally, raising concerns about immunity levels and risks to high-risk groups despite the lifting of the global health emergency in May 2023. While studies have tracked seroprevalence, few have comprehensively assessed long-term antibody persistence and COVID-19 risk, particularly regarding immunity changes due to vaccination and infection. This study aimed to estimate the population prevalence of SARS-CoV-2-specific antibodies, including anti-spike (anti-S) and anti-nucleocapsid (anti-N) antibodies, and to assess the risk of newly confirmed COVID-19 infections in Korea in December 2022. We conducted a follow-up survey and blood testing of 9,945 participants in the Korea Seroprevalence Study of Monitoring of SARS-CoV-2 Antibody Retention and Transmission (K-SEROSMART) Wave 1. Methods The K-SEROSMART Wave 2 study employed a staged approach through public health centers nationwide, using mobile web, telephone, and face-to-face surveys. The follow-up survey (Wave 2) was conducted between December 6 and 27, 2022, four months after the initial survey (Wave 1) conducted in August 2022. Participants self-reported sociodemographic characteristics and health status and provided blood samples for the analysis of anti-spike (anti-S) and anti-nucleocapsid (anti-N) antibodies via electrochemiluminescence immunoassay. Population prevalence estimates were weighted for demographic data. Multivariate Cox proportional hazards regression was used to assess the relationship between anti-S antibody titers from Wave 1 and new COVID-19 cases, adjusting for age and sex. Results A total of 7,528 individuals participated, yielding a follow-up rate of 74.9%. The population-adjusted prevalence rates of anti-S and anti-N antibodies were 98.5% and 70.0%, respectively. The percentage of newly confirmed COVID-19 cases was significantly higher in individuals with anti-S antibody titers below 2,000 U/mL, 2,000–3,999 U/mL, 4,000–5,999 U/mL, 6,000–7,999 U/mL, and 8,000–9,999 U/mL than in those with titers above 18,000 U/mL (hazard ratio [HR] = 9.9, 95% confidence interval [CI] = 7.2–13.5; HR = 8.1, 95% CI = 5.8–11.3; HR = 7.1, 95% CI = 5.0–10.1; HR = 4.2, 95% CI = 2.8–6.3; HR = 2.0, 95% CI = 1.2–3.3, respectively). Conclusions This study demonstrated the feasibility of conducting a seroepidemiological cohort survey on COVID-19 using a nationally representative sample. Additionally, this study quantified anti-S antibody titer levels that are associated with reduced risk of new infections within a community.

ABSTRACT Objective To develop deep learning–based cardiac chamber enlargement-detection algorithms for left atrial (DLCE-LAE) and ventricular enlargement (DLCE-LVE), on chest radiographs Methods For training and internal validation of DLCE-LAE and -LVE, 5,045 chest radiographs (CRs; 2,463 normal and 2,393 LAE) and 1,012 CRs (456 normal and 456 LVE) matched with the same-day echocardiography were collected, respectively. External validation was performed using 107 temporally independent CRs. Reader performance test was conducted using the external validation dataset by five cardiothoracic radiologists without and with the results of DLCE. Classification performance of DLCE was evaluated and compared with those of the readers and conventional radiographic features, including cardiothoracic ratio, carinal angle, and double contour. In addition, DLCE-LAE was tested on 5,277 CRs from a healthcare screening program cohort. Results DLCE-LAE showed areas under the receiver operating characteristics curve (AUROCs) of 0.858 on external validation. On reader performance test, DLCE-LAE showed better results than pooled radiologists (AUROC 0.858 vs. 0.651; p < .001) and significantly increased their performance when used as a second reader (AUROC 0.651 vs. 0.722; p < .001). DLCE-LAE also showed a significantly higher AUROC than conventional radiographic findings (AUROC 0.858 vs. 0.535–0.706; all p s < .01). In the healthcare screening cohort, DLCE-LAE successfully detected 71.0% (142/200) CRs with moderate-to-severe LAE (93.5% [29/31] of severe cases), while yielding 11.8% (492/4,184) false-positive rate. DLCE-LVE showed AUROCs of 0.966 and 0.594 on internal and external validation, respectively. Conclusion DLCE-LAE outperformed and improved cardiothoracic radiologists’ performance in detecting LAE and showed promise in screening individuals with moderate-to-severe LAE in a healthcare screening cohort. Key Points • Our deep learning algorithm outperformed cardiothoracic radiologists in detecting left atrial enlargement on chest radiographs. • Cardiothoracic radiologists improved their performance in detecting left atrial enlargement when aided by the algorithm. • On a healthcare-screening cohort, our algorithm detected 71.0% (142/200) radiographs with moderate-to-severe left atrial enlargement while yielding 11.8% (492/4,184) false-positive rate.

Objective This study was designed to investigate the mammography and ultrasound findings of triple-negative breast cancer and to compare the results with characteristics of ER-positive/PR-negative/HER2-negative breast cancer and ER-negative/PR-negative/HER2-positive breast cancer. Methods From January 2007 to October 2008, mammography and ultrasound findings of 245 patients with pathologically confirmed triple-negative ( n  = 87), ER-positive/PR-negative/HER2-negative ( n  = 93) or ER-negative/PR-negative/HER2-positive breast cancers ( n  = 65) were retrospectively reviewed. We also reviewed pathological reports for information on the histological type, histological grade and the status of the biological markers. Results Triple-negative breast cancers showed a high histological grade. On mammography, triple-negative breast cancers usually presented with a mass (43/87, 49%) or with focal asymmetry (19/87, 22%), and were less associated with calcifications. On ultrasound, the cancers were less frequently seen as non-mass lesions (12/87, 14%), more likely to have circumscribed margins (43/75, 57%), were markedly hypoechoic (36/75, 57%) and less likely to show posterior shadowing (4/75, 5%). Among the three types of breast cancers, ER-negative/PR-negative/HER2-positive breast cancers most commonly had associated calcifications (52/65, 79%) on mammography and were depicted as non-mass lesions (21/65, 32%) on ultrasound. Conclusion Our results suggest that the imaging findings might be useful in diagnosing triple-negative breast cancer.