Radical Three-Component Nitro Spiro-Cyclization of Unsaturated Sulfonamides/Amides to Access NO2-Featured 4-Azaspiro[4.5]decanes.

Free radical three-component nitration/spirocyclization of unsaturated sulfonamides/amides with tert-butyl nitrite was developed for the construction of diverse NO2-revised 4-azaspiro[4.5]decanes. This tandem system featured metal-free participation, simple operation, good selectivity/yields, and a green/low-cost O source. Meanwhile, one nitro-containing complex molecule and a scaled-up operation were performed well to test the synthetic potential of the cascade reaction. Isotopic labeling, radical inhibition experiments, and DFT analysis were carried out to gain insight into the reaction process.

Metal-free radical bicyclization/chloroalkylarylation of 1,6-enynes with chloroalkanes.

Free radical initiated bicyclization of 1,6-enynes with chloralkanes, is achieved via selective activation of the C(sp3)-H bond of the chloralkane, resulting in diverse polychlorinated/chlorinated polyheterocycles. Two kinds of transformations and a scaled-up experiment were performed to test the synthetic importance of the organic chlorides. Finally, a range of radical inhibition operations and radical clock tests were explored to support the reaction process.

Predicting occult lymph node metastasis in solid-predominantly invasive lung adenocarcinoma across multiple centers using radiomics-deep learning fusion model.

BACKGROUND: In solid-predominantly invasive lung adenocarcinoma (SPILAC), occult lymph node metastasis (OLNM) is pivotal for determining treatment strategies. This study seeks to develop and validate a fusion model combining radiomics and deep learning to predict OLNM preoperatively in SPILAC patients across multiple centers. METHODS: In this study, 1325 cT1a-bN0M0 SPILAC patients from six hospitals were retrospectively analyzed and divided into pathological nodal positive (pN+) and negative (pN-) groups. Three predictive models for OLNM were developed: a radiomics model employing decision trees and support vector machines; a deep learning model using ResNet-18, ResNet-34, ResNet-50, DenseNet-121, and Swin Transformer, initialized randomly or pre-trained on large-scale medical data; and a fusion model integrating both approaches using addition and concatenation techniques. The model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS: All patients were assigned to four groups: training set (n = 470), internal validation set (n = 202), and independent test set 1 (n = 227) and 2 (n = 426). Among the 1325 patients, 478 (36%) had OLNM (pN+). The fusion model, combining radiomics with pre-trained ResNet-18 features via concatenation, outperformed others with an average AUC (aAUC) of 0.754 across validation and test sets, compared to aAUCs of 0.715 for the radiomics model and 0.676 for the deep learning model. CONCLUSION: The radiomics-deep learning fusion model showed promising ability to generalize in predicting OLNM from CT scans, potentially aiding personalized treatment for SPILAC patients across multiple centers.

Recent advances in radical thiocyanation cyclization or spirocyclization reactions.

Organic thiocyanates are valuable biological moities and drug-building blocks. They can also transform effectively into thioethers, thiols, alkynyl thioethers, and thiocarbamates in synthetic chemistry. With respect to the merits of thiocyanates, many chemists and our research team have developed diverse strategies to access SCN-revised heterocycles/spirocycles via an effective radical cyclization process. Hence, this review article first describes the importance/application of thiocyanates. Subsequently, it summarizes the reaction conditions, substrate scopes, and plausible mechanism, respectively, of the excellent work stated above.

An uncertainty-aware self-training framework with consistency regularization for the multilabel classification of common computed tomography signs in lung nodules.

Background: Computed tomography (CT) signs of lung nodules play an important role in indicating lung nodules' malignancy, and accurate automatic classification of these signs can help doctors improve their diagnostic efficiency. However, few relevant studies targeting multilabel classification (MLC) of nodule signs have been conducted. Moreover, difficulty in obtaining labeled data also restricts this avenue of research to a large extent. To address these problems, a multilabel automatic classification system for nodule signs is proposed, which consists of a 3-dimensional (3D) convolutional neural network (CNN) and an efficient new semi-supervised learning (SSL) framework. Methods: Two datasets were used in our experiments: Lung Nodule Analysis 16 (LUNA16), a public dataset for lung nodule classification, and a private dataset of nodule signs. The private dataset contains 641 nodules, 454 of which were annotated with 6 important signs by radiologists. Our classification system consists of 2 main parts: a 3D CNN model and an SSL method called uncertainty-aware self-training framework with consistency regularization (USC). In the system, supervised training is performed with labeled data, and simultaneously, an uncertainty-and-confidence-based strategy is used to select pseudo-labeled samples for unsupervised training, thus jointly realizing the optimization of the model. Results: For the MLC of nodule signs, our proposed 3D CNN achieved satisfactory results with a mean average precision (mAP) of 0.870 and a mean area under the curve (AUC) of 0.782. In semi-supervised experiments, compared with supervised learning, our proposed SSL method could increase the mAP by 7.6% (from 0.730 to 0.806) and the mean AUC by 8.1% (from 0.631 to 0.712); it thus efficiently utilized the unlabeled data and achieved superior performance improvement compared to the recently advanced methods. Conclusions: We realized the optimal MLC of lung nodule signs with our proposed 3D CNN. Our proposed SSL method can also offer an efficient solution for the insufficiency of labeled data that may exist in the MLC tasks of 3D medical images.

Photoinduced Tandem Cyanomethylation/Cyclization of Unsaturated Compounds: Access to Cyanomethylated 7- or 5-Membered N-Heterocycles.

A cyanomethylation/cyclization of aryl acetylenes/ethylenes with bromoacetonitrile was finished in a photopromoted condition, which offers an efficient and mild protocol for the preparation of cyanomethylated 7- or 5-membered N-heterocycles with good yields. Meanwhile, trichloroacetonitrile was also compatible with this radical pathway. In addition, a variety of single-crystal X-ray diffraction measurements, scaled-up operations to 1 mmol, functional group transformations of final products, light on/off experiments, and even radial inhibition studies were smoothly performed in this tandem system.

Nitro-Spirocyclization of Biaryl Ynones with tert-Butyl Nitrite: Access to NO2-Substituted Spiro[5,5]trienones.

A metal/peroxide-free involved simple cascade 6-exo-trig spirocyclization of tert-butyl nitrite with biaryl ynones has been finished, which resulted in various NO2-modified spiro[5,5]trienones with good regioselectivity/yields. A variety of scaled-up experiments, reduction/epoxidation operations, and mechanistic studies were performed to verify the merits and spirocyclization process of this radical system. Finally, the structure of the spirocycles was confirmed by single-crystal X-ray diffraction.

Correction: Iron-promoted free radical cascade difunctionalization of unsaturated benzamides with silanes.

Correction for 'Iron-promoted free radical cascade difunctionalization of unsaturated benzamides with silanes' by Yaxin Ge et al., Chem. Commun., 2020, 56, 12656-12659, https://doi.org/10.1039/D0CC05213B.

Free Radical Promoted Trifluoromethylthiolation of Alkynes to Access SCF3-Containing Dibenzazepines or Dioxodibenzothiazepines.

Persulfate-promoted radical cascade trifluoromethylthiolation of aryl acetylenes with AgSCF3 provides a simple reaction system for the synthesis of SCF3-substituted dibenzazepines or dioxodibenzothiazepines with good Z/E selectivity. The single-crystal X-ray diffraction data confirms the structures of the final products. A series of scaled-up experiments, further transformations, and radical inhibition experiments were operated in the reaction system.

MRI-based radiomics signature for identification of invisible basal cisterns changes in tuberculous meningitis: a preliminary multicenter study.

OBJECTIVE: To develop and evaluate a radiomics signature based on magnetic resonance imaging (MRI) from multicenter datasets for identification of invisible basal cisterns changes in tuberculous meningitis (TBM) patients. METHODS: Our retrospective study enrolled 184 TBM patients and 187 non-TBM controls from 3 Chinese hospitals (training dataset, 158 TBM patients and 159 non-TBM controls; testing dataset, 26 TBM patients and 28 non-TBM controls). nnU-Net was used to segment basal cisterns in fluid-attenuated inversion recovery (FLAIR) images. Subsequently, radiomics features were extracted from segmented basal cisterns in FLAIR and T2-weighted (T2W) images. Feature selection was carried out in three steps. Support vector machine (SVM) and logistic regression (LR) classifiers were applied to construct the radiomics signature to directly identify basal cisterns changes in TBM patients. Finally, the diagnostic performance was evaluated by the receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA). RESULTS: The segmentation model achieved the mean Dice coefficients of 0.920 and 0.727 in the training and testing datasets, respectively. The SVM model with 7 T2WI-based radiomics features achieved best discrimination capability for basal cisterns changes with an AUC of 0.796 (95% CI, 0.744-0.847) in the training dataset, and an AUC of 0.751 (95% CI, 0.617-0.886) with good calibration in the testing dataset. DCA confirmed its clinical usefulness. CONCLUSION: The T2WI-based radiomics signature combined with deep learning segmentation could provide a fully automatic, non-invasive tool to identify invisible changes of basal cisterns, which has the potential to assist in the diagnosis of TBM. KEY POINTS: • The T2WI-based radiomics signature was useful for identifying invisible basal cistern changes in TBM. • The nnU-Net model achieved acceptable results for the auto-segmentation of basal cisterns. • Combining radiomics and deep learning segmentation provided an automatic, non-invasive approach to assist in the diagnosis of TBM.

Cryo-EM structure of AMP-PNP-bound human mitochondrial ATP-binding cassette transporter ABCB7.

ATP-binding cassette subfamily B member 7 (ABCB7) is localized in the inner membrane of mitochondria, playing a critical role in iron metabolism. Here, we determined the structure of the nonhydrolyzable ATP analog adenosine-5'-(ß-γ-imido) triphosphate (AMP-PNP) bound human ABCB7 at 3.3 Å by single-particle electron cryo-microscopy (cryo-EM). The AMP-PNP-bound human ABCB7 shows an inverted V-shaped homodimeric architecture with an inward-facing open conformation. One AMP-PNP molecule and Mg2+ were identified in each nucleotide-binding domain (NBD) of the hABCB7 monomer. Moreover, four disease-causing missense mutations of human ABCB7 have been mapped to the structure, creating a hotspot map for X-linked sideroblastic anemia and ataxia disease. Our results provide a structural basis for further understanding the transport mechanism of the mitochondrial ABC transporter.

Radiomics nomogram analysis of T2-fBLADE-TSE in pulmonary nodules evaluation.

OBJECTIVES: To develop and validate a radiomics nomogram for differentiating between malignant pulmonary nodules and benign nodules. METHODS: 56 benign and 51 malignant nodules from 96 patients were analyzed using manual segmentation of the T2-fBLADE-TSE, while the nodules signal intensity (SIlesion), lesion muscle ratio (LMR) and nodule size were all measured and recorded. The maximum relevance and minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select nonzero coefficients and develop the model in pulmonary nodules diagnosis. The radiomics nomogram was also developed. The clinical prediction value was determined by the decision curve analysis (DCA). RESULTS: The nodule size, SIlesion and LMR of the benign group were 1.78 ± 0.57 cm, 227.50 ± 81.39 and 2.40 ± 1.27 respectively, in contrast to the 2.00 ± 0.64 cm, 232.87 ± 82.21 and 2.17 ± 0.91, respectively, in the malignant group (P = 0.09, 0.60 and 0.579). A total of 13 radiomics features were retained. The Rad-score of the benign nodules group was lower than that of the malignant nodules group (P < 0.001 & 0.049, training & test set). The AUC of radiomics signature for nodules diagnosis was 0.82 (95% CI, 0.73-0.91) in the training set and 0.71 (95% CI, 0.51-0.90) in the test set. A nomogram, consisting of 13 radiomics features and nodule size, produced good prediction in the training set (AUC, 0.82; 95% CI, 0.73-0.91), which was significantly better than that of T2-based quantitative parameters (AUC, 0.62; 95% CI, 0.50-0.75, P = 0.003). In the test set, the performance of radiomics nomogram (AUC, 0.70; 95% CI, 0.51-0.90) was also better than that of T2-based quantitative parameters (AUC, 0.46; 95% CI, 0.25-0.67) (P = 0.145). The DCA showed that radiomics nomogram and T2-based quantitative parameter had overall net benefits, while the performance of nomogram was better. CONCLUSION: We constructed and validated a T2-fBLADE-TSE-based radiomics nomogram that can help to differentiate between malignant pulmonary nodules and benign nodules.

Preliminary study of 3 T-MRI native T1-mapping radiomics in differential diagnosis of non-calcified solid pulmonary nodules/masses.

BACKGROUND: Cumulative CT radiation damage was positively correlated with increased tumor risks. Although it has recently been known that non-radiation MRI is alternative for pulmonary imaging. There is little known about the value of MRI T1-mapping in the diagnosis of pulmonary nodules. This article aimed to investigate the value of native T1-mapping-based radiomics features in differential diagnosis of pulmonary lesions. METHODS: 73 patients underwent 3 T-MRI examination in this prospective study. The 99 pulmonary lesions on native T1-mapping images were segmented twice by one radiologist at indicated time points utilizing the in-house semi-automated software, followed by extraction of radiomics features. The inter-class correlation coefficient (ICC) was used for analyzing intra-observer's agreement. Dimensionality reduction and feature selection were performed via univariate analysis, and least absolute shrinkage and selection operator (LASSO) analysis. Then, the binary logical regression (LR), support vector machine (SVM) and decision tree classifiers with the input of optimal features were selected for differentiating malignant from benign lesions. The receiver operative characteristics (ROC) curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated. Z-test was used to compare differences among AUCs. RESULTS: 107 features were obtained, of them, 19.5% (n = 21) had relatively good reliability (ICC ≥ 0.6). The remained 5 features (3 GLCM, 1 GLSZM and 1 shape features) by dimensionality reduction were useful. The AUC of LR was 0.82(95%CI: 0.67-0.98), with sensitivity, specificity and accuracy of 70%, 85% and 80%. The AUC of SVM was 0.82(95%CI: 0.67-0.98), with sensitivity, specificity and accuracy of 70, 85 and 80%. The AUC of decision tree was 0.69(95%CI: 0.49-0.87), with sensitivity, specificity and accuracy of 50, 85 and 73.3%. CONCLUSIONS: The LR and SVM models using native T1-mapping-based radiomics features can differentiate pulmonary malignant from benign lesions, especially for uncertain nodules requiring long-term follow-ups.

Free Radical-Promoted Monochloroalkylarylation of Alkenes with Chloralkanes.

Free radical-initiated cascade cyclization of unactivated alkenes with chloralkanes, which undergoes selective activation of the α-C(sp3)-H bond of chloralkanes, provides a protocol for the synthesis of chlorinated heterocycles or polycyclic compounds. A series of radical inhibition experiments, radical capture operations, and radical clock tests were studied in this system.

Expression, purification and microscopic characterization of human ATP-binding cassette sub-family B member 7 protein.

The ATP-binding cassette sub-family B member 7 (ABCB7) is a membrane transport protein located on the inner membrane of mitochondria, which could be involved in the transport of heme from the mitochondria to the cytosol. ABCB7 also plays a central role in the maturation of cytosolic iron-sulfur (Fe/S) cluster-containing proteins, and mutations can cause a series of mitochondrial defects. X-linked sideroblastic anemia and ataxia (XLSA-A) is a rare cause of early onset ataxia, which may be overlooked due to the usually mild asymptomatic anemia. The genetic defect has been identified as a mutation in the ABCB7 gene at Xq12-q13. Here, we report the expression, purification and the 2D projections derived from negatively stained electron micrographs of recombinant H. sapiens ABCB7 (hABCB7), paving the way from an atomic structure determination of ABCB7.

Clinical Features of COVID-19 Patients in Xiaogan City.

On February 6, 2020, Xiaogan City became the second most seriously affected city with coronavirus disease 2019 (COVID-19), outside Wuhan district, Hubei Province, China. The objectives are to study the clinical features of COVID-19 patients and assess the relationship between the severity of COVID-19, age, and C-reactive protein (CRP) levels. The retrospective data of 134 COVID-19 patients hospitalized in 3 hospitals of Xiaogan City, between February 1 and March 1, 2020, was collected. This study documented COVID-19 patients. Clinical data in terms of body temperature, history of travel, and direct contact with COVID-19 patients, and incubation period was collected. Out of the 134 patients, only 5 required intensive care. Moreover, 2 patients succumbed during this period. The median age of patients was 45 (33-56) years. The most common symptoms at the onset of disease were fever (66.4%), cough (33, 6%), and sore throat (14.7%). Amongst the medicines used, antiviral agents (92.3%) followed by the traditional Chinese medicine (89.5%) were most commonly used. In both the crude and adjusted (I to III) models, odds ratio and its 95% confidence interval for both age and CRP levels were > 1. Moreover, the smooth curve fitting graph reflected that the severity of COVID-19 was positively correlated with both age and CRP levels (all P value < 0.05). The signs and symptoms of COVID-19 patients were fairly moderate. The health care professionals treating the COVID-19 patients should be aware of the increased likelihood of progression to severe COVID-19 in elderly patients and those with high CRP levels.

Iron-promoted free radical cascade difunctionalization of unsaturated benzamides with silanes.

Iron salt/peroxide promoted cascade difunctionalization of unsaturated benzamides with silanes has been reported. It provides a convenient, highly selective, and efficient protocol for the synthesis of various silylated dihydroisoquinolinones and 1,3-isoquinolinediones. In particular, the present methodology only gives cyclization products in good isolated yields under the typical conditions.

A pilot study of native T1-mapping for focal pulmonary lesions in 3.0 T magnetic resonance imaging: size estimation and differential diagnosis.

BACKGROUND: To investigate the accuracy of size estimation and potential diagnosis efficacy of native T1-mapping in focal pulmonary lesion, compared to T1-star 3D-volumetric interpolated breath-hold sequence (VIBE), T2-fBLADE turbo-spin echo (TSE), and computed tomography (CT). METHODS: Thirty-nine patients with CT-detected focal pulmonary lesions underwent thoracic 3.0-T magnetic resonance imaging (MRI) using axial free-breathing 3D T1-star VIBE, respiratory triggered T2-fBLADE TSE, breath-hold T1-Turbo fast low angle shot (FLASH) and T1-FLASH 3D. Native T1-mapping images were generated by T1-FLASH 3D with B1-filed correction by T1-Turbo FLASH. The intraclass correlation coefficient (ICC) and Bland-Altman plots were used to evaluate intra-observer agreement and inter-method reliability of diameter measurements. Native T1-values were measured and compared among the malignancy, tuberculosis, non-tuberculosis benign groups using Mann-Whitney U tests. RESULTS: Forty-five focal pulmonary lesions were displayed by CT, native T1-mapping, T1-star VIBE, and T2-fBLADE TSE. T1-mapping-based diameter measurements yielded an intra-observer ICC of 0.995. Additionally, inter-method measurements were highly consistent (T1-mapping & T1-star VIBE: ICC 0.982, T1-mapping & T2-fBLADE TSE: ICC 0.978, T1-mapping & CT: ICC 0.972). For lesions <3.00 cm, T1-mapping intra-observer (ICC 0.982) and inter-method diameter measurements were also highly consistent (T1-mapping & CT: ICC 0.823). Native T1-values of malignant tumors were lower than those of the non-tuberculosis benign lesions (P=0.003). Native T1-values of tuberculosis were lower than those of the non-tuberculosis benign lesions (P=0.002). Native T1-values showed no statistically significant differences between malignant tumors and tuberculosis (P=0.059). CONCLUSIONS: Native T1-mapping enable accurate and reliable diameter measurement. Native T1-values potentially differentiate malignant tumors or tuberculosis from non-tuberculosis benign lesions.

Effect of combination antiretroviral therapy on the clinical manifestations, radiological characteristics, and disease severity of HIV-associated Talaromyces marneffei infection.

The objective of this study was to evaluate whether combination antiretroviral therapy (cART) has an effect on the clinical manifestations, radiological characteristics, and disease severity of human immunodeficiency virus (HIV)-associated Talaromyces marneffei infection. The clinical manifestations, chest computed tomography (CT) images, and disease severity were compared between 14 patients with culture-confirmed T. marneffei infections who received cART and 38 patients who did not receive cART. Clinical manifestations included high fever (>38°C), cough, shortness of breath, chills, and skin rash. Chest CT scans were evaluated for the presence of ground-glass opacities, consolidation, miliary nodules, nodules, masses, cavitation, pericardial effusion, pleural effusion, mediastinal lymphadenitis, and the distribution of parenchymal abnormalities. Disease severity was estimated by clinical manifestations and chest CT findings. Fever (>38°C), cough, shortness of breath, and chills were significantly less frequent in patients who received cART than in those who did not receive cART (P < 0.05). The frequencies of miliary nodules, mediastinal lymphadenitis, and the proportion of diffuse lesions were significantly lower in patients who received cART than in those who did not receive cART (P < 0.05). The disease severity was significantly decreased in patients who received cART compared with patients who did not receive cART (P < 0.001). T. marneffei-infected patients who received cART had fewer clinical manifestations and decreased disease severity compared with those who did not receive this treatment. The use of cART is associated with modified chest CT characteristics in HIV-associated T. marneffei infections.

COVID-19 and Liver Dysfunction: Current Insights and Emergent Therapeutic Strategies.

The outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has attracted increasing worldwide attention. Cases of liver damage or dysfunction (mainly characterized by moderately elevated serum aspartate aminotransferase levels) have been reported among patients with COVID-19. However, it is currently uncertain whether the COVID-19-related liver damage/dysfunction is due mainly to the viral infection per se or other coexisting conditions, such as the use of potentially hepatotoxic drugs and the coexistence of systemic inflammatory response, respiratory distress syndrome-induced hypoxia, and multiple organ dysfunction. Based on the current evidence from case reports and case series, this review article focuses on the demographic and clinical characteristics, potential mechanisms, and treatment options for COVID-19-related liver dysfunction. This review also describes the geographical and demographic distribution of COVID-19-related liver dysfunction, as well as possible underlying mechanisms linking COVID-19 to liver dysfunction, in order to facilitate future drug development, prevention, and control measures for COVID-19.