Fine mapping and analysis of a candidate gene controlling Phytophthora blight resistance in cucumber

Cucumber blight is a destructive disease. The best way to control this disease is resistance breeding. This study focuses on disease resistance gene mapping and molecular marker development. We used the resistant cucumber, JSH, and susceptible cucumber, B80, as parents to construct F2 populations. Bulked segregant analysis (BSA) combined with specific length amplified fragment sequencing (SLAF-seq) were used, from which we developed cleaved amplified polymorphic sequence (CAPs) markers to map the resistance gene. Resistance in F2 individuals showed a segregation ratio of resistance:susceptibility close to 3:1. The gene in JSH resistant cucumber was mapped to an interval of 9.25 kb, and sequencing results for the three genes in the mapped region revealed three mutations at base sites 225, 302, and 591 in the coding region of Csa5G139130 between JSH and B80, but no mutations in coding regions of Csa5G139140 and Csa5G139150. The mutations caused changes in amino acids 75 and 101 of the protein encoded by Csa5G139130, suggesting that Csa5G139130 is the most likely resistance candidate gene. We developed a molecular marker, CAPs-4, as a closely linked marker for the cucumber blight resistance gene. This is the first report on mapping of a cucumber blight resistance gene and will provideg a useful marker for molecular breeding of cucumber resistance to Phytophthora blight.

Small Mitochondria-Targeting Fluorophore with Multifunctional Therapeutic Activities against Prostate Cancer via the HIF1α/OATPs Pathway

Prostate cancer (PCa) is considered to be the most prevalent malignancy in males worldwide. Abiraterone is a 17α-hydroxylase/C17, 20-lyase (CYP17) inhibitor that has been approved for use in patients with prostate cancer. However, several negative aspects, such as drug resistance, toxicity, and lack of real-time monitoring of treatment responses, could appear with long-term use. Therefore, the development of anticancer agents with specific targeting to avoid side effects is imperative. Here, we used MHI-148, a type of heptamethine cyanine (HC) near-infrared fluorescence dye (NIRF), as a prototype structure to synthesize two theranostic agents, Abi-DZ-1 and Abi-783. The new compound Abi-DZ-1 retained the excellent photophysical characteristics and NIRF imaging property of MHI-148, and it could preferentially accumulate in prostate cancer cells but not in normal prostate epithelial cells via the HIF1α/organic anion-transporting polypeptides axis. NIRF imaging using Abi-DZ-1 selectively identified tumors in mice bearing PCa xenografts. Moreover, Abi-DZ-1 treatment significantly retarded the tumor growth in both a cell-derived xenograft model and a patient-derived tumor xenograft model. This finding demonstrated that Abi-DZ-1 may hold promise as a potential multifunctional theranostic agent for future tumor-targeted imaging and precision therapy. Constructing theranostic agents using the NIRF dye platform holds great promise in accurate therapy and intraoperative navigation.

Establishment of organoid models for pancreatic ductal adenocarcinoma and screening of individualized therapy strategy

BACKGROUND

Patients with pancreatic ductal adenocarcinoma (PDAC) who undergo surgical resection and receive effective chemotherapy have the best chance for long-term survival. Unfortunately, because of the heterogeneity of pancreatic cancer, it is difficult to find a personalized treatment strategy for patients. Organoids are ideal preclinical models for personalized medicine. Therefore, we explore the cultivation conditions and construction methods of PDAC organoid models to screen the individualized therapy strategy.

METHODS

Fresh PDAC tissues from surgical resection were collected and digested with digestive enzymes; then the tumor cells were embedded in Matrigel with a suitable medium to establish the PDAC organoid models. The genetic stability of the organoids was analyzed using whole exon sequencing; hematoxylin and eosin staining and immunohistochemistry of organoids were performed to analyze their consistency with the pathological morphology of the patient's tumor tissue; After 2 days of organoid culture, we selected four commonly used clinical chemotherapy drugs for single or combined treatment to analyze drug sensitivity.

RESULTS

Two cases of PDAC organoid models were successfully established, and the results of their pathological characteristics and exome sequencing were consistent with those of the patient's tumor tissue. Both PDAC organoids showed more sensitivity to gemcitabine and cisplatin, and the combined treatment was more effective than monotherapy.

CONCLUSION

Both organoids better retained the pathological characteristics, genomic stability, and heterogeneity with the original tumor. Individual PDAC organoids exhibited different sensitivities to the same drugs. Thus, this study provided ideal experimental models for screening individualized therapy strategy for patients with PDAC.

Prediction of toxicity outcomes following radiotherapy using deep learning-based models: A systematic review

PURPOSE

This study aims to perform a comprehensive systematic review of deep learning (DL) models in predicting RT-induced toxicity.

MATERIALS AND METHODS

A literature review was performed following the PRISMA guidelines. Systematic searches were performed in PubMed, Scopus, Cochrane and Embase databases from the earliest record up to September 2022. Related studies on deep learning models for radiotherapy toxicity prediction were selected based on predefined PICOS criteria.

RESULTS

Fourteen studies of radiotherapy-treated patients on different types of cancer [prostate (n=2), HNC (n=4), liver (n=2), lung (n=4), cervical (n=1), and oesophagus (n=1)] were eligible for inclusion in the systematic review. Information regarding patient characteristics and model development was summarized. Several approaches, such as ensemble learning, data augmentation, and transfer learning, that were utilized by selected studies were discussed.

CONCLUSION

Deep learning techniques are able to produce a consistent performance for toxicity prediction. Future research using large and diverse datasets and standardization of the study methodologies are required to improve the consistency of the research output.

Global burden of metabolic diseases: data from Global Burden of Disease 2000-2019. A cosortium of metabolic disease

Funding Acknowledgements

Type of funding sources: None.

Background

The growing prevalence of metabolic diseases is a major concern. We sought to examine the global trends and mortality of metabolic diseases using estimates from the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019.

Methods

Global estimates of prevalence, deaths, and disability-adjusted life year (DALYs) from 2000-2019 were examined for metabolic diseases (type 2 diabetes mellitus [T2DM], hypertension, and nonalcoholic fatty liver disease [NAFLD]). For metabolic risk factors (hyperlipidemia and obesity), estimates were limited to mortality and DALYs. Death rates was compared across sex, World Health Organisation regions and Socio-demographic Index (SDI) quintiles. Age-standardised prevalence and death rates were presented per 100,000 population with 95% uncertainty intervals (UI).

Findings

From 2000 to 2019, prevalence rates increased for all metabolic diseases, with the most pronounced increase in high SDI countries. In 2019, the mean (95%UI) age-standardised prevalence per 100,000 population was estimated to be 15,023 (13,493-16,764) for NAFLD, 5,283 (4,864–5,720) for T2DM and 234 (171-313) for hypertension. The highest age-standardised death rates were observed in obesity (62·59 [39·92-89·13]; males, 66·55 [39·76-97·21]; females. 58·14 [38·53-81·39]), followed by hyperlipidemia (56·51 [41·83-73·62]; males, 67·33 [50·78-86·43]; females, 46·50 [32·70-62·38]), T2DM (18·49 [17·18-19·66], males, 67·33 [50·78-86·43]; females, 46·50 [32·70-62·38]), hypertension (15·16 [11·20-16·75]; males, 14·95 [10·32-16·75]; females, 15·05 [11·51-17·09]) and NAFLD (2·09 [1·61-2·60]; males, 2·38 [1·82-3·02]; females, 1·82 [1·41-2·27]). Mortality rates decreased over time in hyperlipidemia (-154%), hypertension (-52%) and NAFLD (-52%), but not in T2DM and obesity. The highest mortality for metabolic diseases was found in Eastern Mediterranean, and low to low-middle SDI countries.

Conclusion

The global prevalence of metabolic diseases has risen over the past two decades regardless of SDI. Attention is needed to address the unchanging mortality rates attributed to metabolic disease and the regional, socioeconomic, and sex disparities in mortality from metabolic disease.

Screening of an individualized treatment strategy for an advanced gallbladder cancer using patient-derived tumor xenograft and organoid models

Gallbladder cancer is a highly aggressive malignancy with poor sensitivity to postoperative radiotherapy or chemotherapy; therefore, the development of individualized treatment strategies is paramount to improve patient outcomes. Both patient-derived tumor xenograft (PDX) and patient-derived tumor organoid (PDO) models derived from surgical specimens can better preserve the biological characteristics and heterogeneity of individual original tumors, display a unique advantage for individualized therapy and predicting clinical outcomes. In this study, PDX and PDO models of advanced gallbladder cancer were established, and the consistency of biological characteristics between them and primary patient samples was confirmed using pathological analysis and RNA-sequencing. Additionally, we tested the efficacy of chemotherapeutic drugs, targeted drugs, and immune checkpoint inhibitors using these two models. The results demonstrated that gemcitabine combined with cisplatin induced significant therapeutic effects. Furthermore, treatment with immune checkpoint inhibitors elicited promising responses in both the humanized mice and PDO immune models. Based on these results, gemcitabine combined with cisplatin was used for basic treatment, and immune checkpoint inhibitors were applied as a complementary intervention for gallbladder cancer. The patient responded well to treatment and exhibited a clearance of tumor foci. Our findings indicate that the combined use of PDO and PDX models can guide the clinical treatment course for gallbladder cancer patients to achieve individualized and effective treatment.

Reconstructed meta-analysis of percutaneous coronary intervention versus coronary artery bypass grafting for left main disease

Background

Randomized controlled trials (RCTs) comparing percutaneous coronary intervention (PCI) with drug-eluting stents and coronary artery bypass grafting (CABG) for patients with left main coronary artery disease (LMCAD) have reported conflicting results.

Objectives

We performed a systematic review from inception to 23 May 2021 and one-stage reconstructed individual-patient data meta-analysis (IPDMA) that included 10-year mortality outcomes.

Methods

The primary outcome was 10-year all-cause mortality. Secondary outcomes included myocardial infarction (MI), stroke and unplanned revascularization at 5 years. We did IPDMA using published Kaplan-Meier curves to provide individual data points in coordinates and numbers at risk were used to increase the calibration accuracy of the reconstructed data. Shared frailty model or, when proportionality assumptions were not met, a restricted mean survival time model were fitted to compare outcomes between treatment groups.

Results

Of 583 articles retrieved, 5 RCTs were included. A total of 4595 patients from these 5 RCTs were randomly assigned to PCI (N=2297) or CABG (N=2298). The cumulative 10-year all-cause mortality after PCI and CABG was 12.0% versus 10.6% respectively (HR 1.093, 95% CI: 0.925–1.292; p=0.296). PCI conferred similar time-to-MI (RMST ratio 1.006, 95% CI: 0.992–1.021, p=0.391) and stroke (RMST ratio 1.005, 95% CI: 0.998–1.013, p=0.133) at 5 years. Unplanned revascularization was more frequent following PCI compared with CABG (HR 1.807, 95% CI: 1.524–2.144, p<0.001) at 5 years.

Conclusion

This meta-analysis using reconstructed participant-level time-to-event data showed no statistically significant difference in cumulative 10-year all-cause mortality between PCI versus CABG in the treatment of LMCAD.

Funding Acknowledgement

Type of funding sources: None.

THIRD bedside ultrasound protocol for rapid diagnosis of undifferentiated shock: a prospective observational study

INTRODUCTION

It is clinically challenging to differentiate the pathophysiological types of shock in emergency situations. Here, we evaluated the ability of a novel bedside ultrasound protocol (Tamponade/tension pneumothorax, Heart, Inferior vena cava, Respiratory system, Deep venous thrombosis/aorta dissection [THIRD]) to predict types of shock in the emergency department.

METHODS

An emergency physician performed the THIRD protocol on all patients with shock who were admitted to the emergency department. All patients were closely followed to determine their final clinical diagnoses. The kappa index, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the initial diagnostic impression provided by the THIRD protocol, compared with each patient's final diagnosis.

RESULTS

In total, 112 patients were enrolled in this study. The kappa index between initial impression and final diagnosis was 0.81 (95% confidence interval=0.73-0.89; P<0.001). For hypovolaemic, cardiogenic, distributive, and obstructive types of shock, the sensitivities of the THIRD protocol were 100%, 100%, 93%, and 100%, respectively; the sensitivity for a 'mixed' shock aetiology was 86%. The negative predictive value of the THIRD protocol for all five types of shock was ≥96%.

CONCLUSION

Initial diagnostic judgements determined using the THIRD protocol showed favourable agreement with the final diagnosis in patients who presented with undifferentiated shock. The THIRD protocol has great potential for use as a bedside approach that can guide the rapid management of undifferentiated shock in emergency settings, particularly for patients with obstructive, hypovolaemic, or cardiogenic shock.

Functional assessment of military aircrew applicants in a hypobaric chamber

Background

Aircrew are exposed to environmental pressure changes. In the Republic of Singapore Air Force (RSAF), applicants assessed to be at intermediate risk of otic barotrauma undergo a hypobaric chamber assessment [“trial of chamber” (TOC)] to functionally evaluate their suitability for military aircrew vocations.

Aims

To identify factors associated with TOC failure among applicants with otorhinolaryngological conditions.

Methods

All applicants to RSAF aircrew vocations who were assessed to be at intermediate risk of otic barotrauma over a 3-yr period were identified using the RSAF Aeromedical Centre’s electronic database. Their medical records, as well as the TOC assessment records of the subset of applicants who underwent TOC, were reviewed for demographic data, clinical findings, and TOC outcomes.

Results

Of the 483 identified applicants, 374 (77%) had abnormal otoscopic findings, 103 (21%) had rhinitis symptoms, and 6 (1%) had previous ENT surgery. 123 (25%) underwent TOC, of which 20 (16%) failed. Holding other predictor variables constant, the odds of TOC failure increased by 0.79 per unit decrease in BMI (95% CI 0.63–0.99), and the odds of TOC failure increased by 0.93 per kg decrease in body weight (95% CI 0.87–1.00). An abnormal tympanogram was not a statistically significant predictor of TOC failure (OR 1.96, 95% CI 0.59–6.42). Of the 47 applicants who passed TOC and were eventually recruited, none subsequently developed otic barotrauma (mean follow-up, 3.3 yr ± 1.5 yr).

Conclusions

Applicants with lower weight and BMI are more likely to develop otic barotrauma with environmental pressure change. Tympanometry cannot be reliably used to identify applicants who would more likely pass TOC.

Lipocalin 2 may be a key factor regulating the chemosensitivity of pancreatic cancer to gemcitabine

Owing to the high heterogeneity of pancreatic cancer, patient-derived xenografts (PDX) can compensate for the defects of cell line-derived xenografts (CDX) and also better preserve the heterogeneity and tumor microenvironment of primary tumors. Further, gemcitabine, which is used for the treatment of various cancers, is prone to tumor drug resistance, and this limits its sustained efficacy. Therefore, in this study, our objective was to screen appropriate individual therapeutic drugs for pancreatic cancer. To this end, we established pancreatic cancer PDX models from different patients and screened gemcitabine sensitivity regulatory molecules via high-throughput transcriptome sequencing and bioinformatics analysis. Based on the results obtained, gemcitabine was identified as the most suitable chemotherapeutic drug in a variety of PDX models. Additionally, our results indicated that Lipocalin 2 (LCN 2) may play an important role in the sensitivity of pancreatic cancer to gemcitabine treatment. Thus, the study provides a new potential intervention target for the treatment of pancreatic cancer in clinical practice.

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PDX model plays an important role in the screening of chemotherapeutic agents for pancreatic cancer.

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Gemcitabine is the most suitable chemotherapeutic drug in a variety of PDX models of pancreatic cancer.

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Lcn2 may be involved in the sensitivity of gemcitabine in the treatment of pancreatic cancer and the change of Lipocalin 2 levels determines the gemcitabine therapeutic output.

Cystatin 2 leads to a worse prognosis in patients with gastric cancer

Despite the amazing progress in the treatment of gastric cancer (GC), it is still the third leading cause of cancer death in the world. This study explored the key genes that are related to the prognosis and pathogenesis of GC. Data from the cancer genome atlas (TCGA) and Oncomine were applied to evaluate the expression of cystatin 2 (CST2) in GC samples. Kaplan-Meier plotter was carried out to detect the overall survival of GC patients with different expression levels of CST2. Gene Set Enrichment Analysis (GSEA) was carried out to investigate the functions and pathways connected with CST2 expression. Quantitative real-time polymerase chain reaction (qPCR) and Western blot assays were used to assess CST2 expression. The biological properties of GC cells were assessed with the support of cell proliferation and Transwell assays. Important proteins involved in the regulation of CST2 in GC cell behaviors were evaluated by Western blot. Through analysis of the database, we found that CST2 expression was significantly upregulated in GC samples and actively related to GC patients' poor outcomes. Importantly, the analysis of GSEA showed that GST2 expression was closely connected with the proliferation and migration of cells, as well as the TGF-β1 signaling pathway. In addition, biological assays illustrated that over-expression of CST2 strengthened the activity and metastasis of GC cells. After the upregulation of CST2, the expression of cyclin D1, N-cadherin, vimentin, TGF-β1, and Smad4 increased, and E-cadherin expression decreased. Our findings revealed that over-expression of CST2 enhanced the growth, migration, and invasion of GC cells through modulating the epithelial-mesenchymal transition (EMT) and TGF-β1 signaling pathway, affording a possible biomarker for the treatment of GC.

Indeterminate pulmonary nodules are not associated with worse overall survival in Ewing Sarcoma

AIM

Lung metastases are a negative prognostic factor in Ewing sarcoma, however, the incidence and significance of sub-centimetre pulmonary nodules at diagnosis is unclear. The aims of this study were to (1): determine the incidence of indeterminate pulmonary nodules (IPNs) in patients diagnosed with Ewing sarcoma (2); establish the impact of IPNs on overall and metastasis-free survival and (3) identify patient, oncological and radiological factors that correlate with poorer prognosis in patients that present with IPNs on their staging chest CT.

MATERIALS & METHODS

Between 2008 and 2016, 173 patients with a first presentation of Ewing sarcoma of bone were retrospectively identified from an institutional database. Staging and follow-up chest CTs for all patients with IPN were reviewed by a senior radiologist. Clinical and radiologic course were examined to determine overall- and metastasis-free survival for IPN patients and to identify demographic, oncological or nodule-specific features that predict which IPN represent true lung metastases.

RESULTS

Following radiologic re-review, IPN were found in 8.7% of patients. Overall survival for IPN patients was comparable to those with a normal staging chest CT (2-year overall survival of 73.3% [95% CI 43.6-89] and 89.4% [95% CI 81.6-94], respectively; p = 0.34) and was significantly better than for patients with clear metastases (46.0% [95% CI 31.9-59]; p < 0.0001). Similarly, there was no difference in metastasis-free survival between 'No Metastases' and 'IPN' patients (p = 0.16). Lung metastases developed in 40% of IPN patients at a median 9.6 months. Reduction of nodule size on neoadjuvant chemotherapy was associated with worse overall survival in IPN patients (p = 0.0084).

CONCLUSION

IPN are not uncommon in patients diagnosed with Ewing sarcoma. In this study, we were unable to detect a difference in overall- or metastasis-free survival between patients with IPN at diagnosis and patients with normal staging chest CTs.

Heat and Work Along Individual Trajectories of a Quantum Bit

We use a near quantum limited detector to experimentally track individual quantum state trajectories of a driven qubit formed by the hybridization of a waveguide cavity and a transmon circuit. For each measured quantum coherent trajectory, we separately identify energy changes of the qubit as heat and work, and verify the first law of thermodynamics for an open quantum system. We further establish the consistency of these results by comparison with the master equation approach and the two-projective-measurement scheme, both for open and closed dynamics, with the help of a quantum feedback loop that compensates for the exchanged heat and effectively isolates the qubit.

Establishment and characterization of patient-derived xenografts for hormone-naïve and castrate-resistant prostate cancers to improve treatment modality evaluation

Prostate cancer (PC) is a heterogeneous disease characterized by variable morphological patterns. Thus, establishing a patient-derived xenograft (PDX) model that retains the key features of the primary tumor for each type of PC is important for appropriate evaluation. In this study, we established PDX models of hormone-naïve (D17225) and castration-resistant (B45354) PC by implanting fresh tumor samples, obtained from patients with advanced PC under the renal capsule of immune-compromised mice. Supplementation with exogenous androgens shortened the latent period of tumorigenesis and increased the tumor formation rate. The PDX models exhibited the same major genomic and phenotypic features of the disease in humans and maintained the main pathological features of the primary tumors. Moreover, both PDX models showed different outcomes after castration or docetaxel treatment. The hormone-naïve D17225 PDX model displayed a range of responses from complete tumor regression to overt tumor progression, and the development of castrate-resistant PC was induced after castration. The responses of the two PDX models to androgen deprivation and docetaxel were similar to those observed in patients with advanced PC. These new preclinical PC models will facilitate research on the mechanisms underlying treatment response and resistance.

Development of patient-derived xenograft models of prostate cancer for maintaining tumor heterogeneity

Prostate cancer (Pca) is a heterogeneous disease with multiple morphological patterns. Thus, the establishment of a patient-derived xenograft (PDX) model that retains key features of the primary tumor is of great significance. This review demonstrates the characteristics and advantages of the Pca PDX model and summarizes the main factors affecting the establishment of the model. Because this model well recapitulates the diverse heterogeneity observed in the clinic, it was extensively utilized to discover new therapeutic targets, screen drugs, and explore metastatic mechanisms. In the future, clinical phenotype and different stages of the Pca patient might be faithfully reflected by PDX model, which provides tremendous potential for understanding Pca biology and achieving individualized treatment.