An exocyst component, Sec5, is essential for ascospore formation in Bipolaris maydis

In this study, we identified Sec5 in Bipolaris maydis, a homologue of Sec5 in Saccharomyces cerevisiae and a possible exocyst component of the fungus. To examine how Sec5 affects the life cycle of B. maydis, we generated null mutant strains of the gene (Δsec5). The Δsec5 strains showed a strong reduction in hyphal growth and a slight reduction in pathogenicity. In sexual reproduction, they possessed the ability to develop pseudothecia. However, all ascospores were aborted in any of the asci obtained from crosses between Δsec5 and the wild-type. Our cytological study revealed that the abortion was caused by impairments of the post-meiotic stages in ascospore development, where ascospore delimitation and young spore elongation occur

Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray

Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of artificial intelligence (AI) to the chest X-ray (CXR) could identify elevated pulmonary artery pressure (PAP) and stratify the risk of heart failure hospitalization with PH. We retrospectively enrolled a total of 900 consecutive patients with suspected PH. We trained a convolutional neural network to identify patients with elevated PAP (> 20 mmHg) as the actual value of PAP. The endpoints in this study were admission or occurrence of heart failure with elevated PAP. In an independent evaluation set for detection of elevated PAP, the area under curve (AUC) by the AI algorithm was significantly higher than the AUC by measurements of CXR images and human observers (0.71 vs. 0.60 and vs. 0.63, all p < 0.05). In patients with AI predicted PH had 2-times the risk of heart failure with PH compared with those without AI predicted PH. This preliminary work suggests that applying AI to the CXR in high risk groups has limited performance when used alone in identifying elevated PAP. We believe that this report can serve as an impetus for a future large study

AI for Exercise-Induced Pulmonary Hypertension

Background: Stress echocardiography is an emerging tool used to detect exercise-induced pulmonary hypertension (EIPH). However, facilities that can perform stress echocardiography are limited by issues such as cost and equipment. Objective: We evaluated the usefulness of a deep learning (DL) approach based on a chest X-ray (CXR) to predict EIPH in 6-min walk stress echocardiography. Methods: The study enrolled 142 patients with scleroderma or mixed connective tissue disease with scleroderma features who performed a 6-min walk stress echocardiographic test. EIPH was defined by abnormal cardiac output (CO) responses that involved an increase in mean pulmonary artery pressure (mPAP). We used the previously developed AI model to predict PH and calculated PH probability in this cohort. Results: EIPH defined as ΔmPAP/ΔCO >3.3 and exercise mPAP >25 mmHg was observed in 52 patients, while non-EIPH was observed in 90 patients. The patients with EIPH had a higher mPAP at rest than those without EIPH. The probability of PH based on the DL model was significantly higher in patients with EIPH than in those without EIPH. Multivariate analysis showed that gender, mean PAP at rest, and the probability of PH based on the DL model were independent predictors of EIPH. A model based on baseline parameters (age, gender, and mPAP at rest) was improved by adding the probability of PH predicted by the DL model (AUC: from 0.65 to 0.74; p = 0.046). Conclusion: Applying the DL model based on a CXR may have a potential for detection of EIPH in the clinical setting

Deep learning approach for analyzing chest x-rays to predict cardiac events in heart failure

Background: A deep learning (DL) model based on a chest x-ray was reported to predict elevated pulmonary artery wedge pressure (PAWP) as heart failure (HF). Objectives: The aim of this study was to (1) investigate the role of probability of elevated PAWP for the prediction of clinical outcomes in association with other parameters, and (2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF. Methods: We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP. Readmission following HF and cardiac mortality were the primary endpoints. Results: Probability of elevated PAWP was associated with diastolic function by echocardiography. During a median follow-up period of 58 months, 57 individuals either died or were readmitted. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge was associated with event free survival, independent of elevated left atrial pressure (LAP) based on echocardiographic guidelines (p < 0.001). In sequential Cox models, a model based on clinical data was improved by elevated LAP (p = 0.005), and increased further by probability of elevated PAWP (p < 0.001). In contrast, the addition of pulmonary congestion interpreted by a doctor did not statistically improve the ability of a model containing clinical variables (compared p = 0.086). Conclusions: This study showed the potential of using a DL model on a chest x-ray to predict PAWP and its ability to add prognostic information to other conventional clinical prognostic factors in HF. The results may help to enhance the accuracy of prediction models used to evaluate the risk of clinical outcomes in HF, potentially resulting in more informed clinical decision-making and better care for patients

Cluster analysis after TAVR

Aims The aim of this study was to identify phenotypes with potential prognostic significance in aortic stenosis (AS) patients after transcatheter aortic valve replacement (TAVR) through a clustering approach. Methods and results This multi-centre retrospective study included 1365 patients with severe AS who underwent TAVR between January 2015 and March 2019. Among demographics, laboratory, and echocardiography parameters, 20 variables were selected through dimension reduction and used for unsupervised clustering. Phenotypes and outcomes were compared between clusters. Patients were randomly divided into a derivation cohort (n = 1092: 80%) and a validation cohort (n = 273: 20%). Three clusters with markedly different features were identified. Cluster 1 was associated predominantly with elderly age, a high aortic valve gradient, and left ventricular (LV) hypertrophy; Cluster 2 consisted of preserved LV ejection fraction, larger aortic valve area, and high blood pressure; and Cluster 3 demonstrated tachycardia and low flow/low gradient AS. Adverse outcomes differed significantly among clusters during a median of 2.2 years of follow-up (P < 0.001). After adjustment for clinical and echocardiographic data in a Cox proportional hazards model, Cluster 3 (hazard ratio, 4.18; 95% confidence interval, 1.76–9.94; P = 0.001) was associated with increased risk of adverse outcomes. In sequential Cox models, a model based on clinical data and echocardiographic variables (χ2 = 18.4) was improved by Cluster 3 (χ2 = 31.5; P = 0.001) in the validation cohort. Conclusion Unsupervised cluster analysis of patients after TAVR revealed three different groups for assessment of prognosis. This provides a new perspective in the categorization of patients after TAVR that considers comorbidities and extravalvular cardiac dysfunction

Is the Importance of Achieving Stable Disease Different between Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors and Cytotoxic Agents in the Second-Line Setting for Advanced Non-small Cell Lung Cancer?

BackgroundIt is controversial whether achieving stable disease leads to a survival benefit and whether the importance of achieving stable disease differs between cytotoxic agents and molecular targeted agents. To examine these questions, the authors retrospectively reviewed phase II and III studies in the second-line setting for advanced non-small cell lung cancer using epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) and cytotoxic agents separately.MethodsThe authors chose 45 trials for the chemotherapy group and nine for the EGFR TKI group by searching the PubMed database. All nine trials in the EGFR TKI group concern gefitinib and erlotinib.ResultsThe median survival time increased 0.0375 month with each 1% increase in stable disease rate (p = 0.039), and each 1% increase in response rate resulted in 0.0744 (p < 0.001) month of median survival time in the analysis combined with both cytotoxic agents and EGFR TKIs. Main and interaction terms for EGFR TKI treatment were not statistically significant. With respect to time to progression, only response rate showed a statistically significant relationship with survival.ConclusionsTo obtain response seems to be more important than to achieve stable disease for both cytotoxic agents and EGFR TKIs, although achieving stable disease is still valuable. The relationship between survival and response or stable disease appears similar for cytotoxic agents and EGFR TKIs

トウモロコシごま葉枯病菌における前胞子膜の形成および伸長に関する研究

京都大学新制・課程博士博士(農学)甲第23961号農博第2510号新制||農||1092(附属図書館)学位論文||R4||N5396(農学部図書室)京都大学大学院農学研究科地域環境科学専攻(主査)教授 田中 千尋, 教授 本田 与一, 教授 日本 典秀学位規則第4条第1項該当Doctor of Agricultural ScienceKyoto UniversityDGA

Suppression of Intersite Charge Transfer in Charge-Disproportionated Perovskite YCu3Fe4O12\mathrm{YCu_3Fe_4O_{12}}

A novel iron perovskite $YCu_{3}Fe_{4}O_{12}$ was synthesized under high pressure and high temperature of 15 GPa and 1273 K. Synchrotron X-ray and electron diffraction measurements have demonstrated that this compound crystallizes in the cubic $AA′_{3}B_{4}O_{12}$-type perovskite structure (space group Im3̅, No. 204) with a lattice constant of a = 7.30764(10) Å at room temperature. $YCu_{3}Fe_{4}O_{12}$ exhibits a charge disproportionation of $8Fe^{3.75+} \rightarrow 3Fe^{5+} + 5Fe^{3+}$, a ferrimagnetic ordering, and a metal-semiconductor-like transition simultaneously at 250 K, unlike the known isoelectronic compound $LaCu_{3}Fe_{4}O_{12}$ that currently shows an intersite charge transfer of $3Cu^{2+} + 4Fe^{3.75+} \rightarrow 3Cu^{3+} + 4Fe^{3+}$, an antiferromagnetic ordering, and a metal–insulator transition at 393 K. This finding suggests that intersite charge transfer is not the only way of relieving the instability of the $Fe^{3.75+}$ state in the $A^{3+}Cu^{2+}$$_{3}Fe^{3.75+}$$_{4}O_{12}$ perovskites. Crystal structure analysis reveals that bond strain, rather than the charge account of the $\mathit{A}$-site alone, which is enhanced by large $A{3+}$ ions, play an important role in determining which of intersite charge transfer or charge disproportionation is practical

Control of Bond-Strain-Induced Electronic Phase Transitions in Iron Perovskites

Unusual electronic phase transitions in the A-site ordered perovskites LnCu3Fe4O12 (Ln: trivalent lanthanide ion) are investigated. All LnCu3Fe4O12 compounds are in identical valence states of Ln3+Cu2+3Fe3.75+4O12 at high temperature. LnCu3Fe4O12 with larger Ln ions (Ln = La, Pr, Nd, Sm, Eu, Gd, Tb) show an intersite charge transfer transition (3Cu2+ + 4Fe3.75+ → 3Cu3+ + 4Fe3+) in which the transition temperature decreases from 360 to 240 K with decreasing Ln ion size. In contrast, LnCu3Fe4O12 with smaller Ln ions (Ln = Dy, Ho, Er, Tm Yb, Lu) transform into a charge-disproportionated (8Fe3.75+ → 5Fe3+ + 3Fe5+) and charge-ordered phase below ∼250–260 K. The former series exhibits metal-to-insulator, antiferromagnetic, and isostructural volume expansion transitions simultaneously with intersite charge transfer. The latter shows metal-to-semiconductor, ferrimagnetic, and structural phase transitions simultaneously with charge disproportionation. Bond valence calculation reveals that the metal–oxygen bond strains in these compounds are classified into two types: overbonding or compression stress (underbonding or tensile stress) in the Ln–O (Fe–O) bond is dominant in the former series, while the opposite stresses or bond strains are found in the latter. Intersite charge transfer transition temperatures are strongly dependent upon the global instability indices that represent the structural instability calculated from the bond valence sum, whereas the charge disproportionation occurs at almost identical temperatures, regardless of the magnitude of structural instability. These findings provide a new aspect of the structure–property relationship in transition metal oxides and enable precise control of electronic states by bond strains

Segmental distributions and consonant-vowel association patterns in Japanese infant- and adult-directed speech

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