Catalytic Asymmetric Synthesis of Vicinal Quaternary Stereocenters Enabled by Alkylation of α,α-Disubstituted Aldehydes with 3-Bromooxindoles.

An organocatalytic enantioselective alkylation of α,α-disubstituted aldehydes with 3-bromooxindoles is reported. Enantioenriched oxindoles with vicinal quaternary stereocenters are accessed by an asymmetric conjugate addition process of branched aldehydes with o-azaxylylene intermediates (indol-2-ones). Key to the success of highly diastereo- and enantioselective transformations is the combined use of a triphenylsilyl-protected ß-amino alcohol catalyst derived from the spiropyrrolidine scaffold and 3,5-dinitrobenzoic acid. This study also presents a rare example of aldehyde alkylation with the formation of consecutive quaternary stereocenters.

CT radiomics based on the peritumoral adipose region of gastric adenocarcinoma for preoperative prediction of lymph node metastasis.

PURPOSE: To construct and validate CT radiomics model based on the peritumoral adipose region of gastric adenocarcinoma to preoperatively predict lymph node metastasis (LNM). METHODS AND METHODS: 293 consecutive gastric adenocarcinoma patients receiving radical gastrectomy with lymph node dissection in two medical institutions were stratified into a development set (from Institution A, n = 237), and an external validation set (from Institution B, n = 56). Volume of interest of peritumoral adipose region was segmented on preoperative portal-phase CT images. The least absolute shrinkage and selection operator method and stepwise logistic regression were used to select features and build radiomics models. Manual classification was performed according to routine CT characteristics. A classifier incorporating the radiomics score and CT characteristics was developed for predicting LNM. Area under the receiver operating characteristic curve (AUC) was used to show discrimination between tumors with and without LNM, and the calibration curves and Brier score were used to evaluate the predictive accuracy. Violin plots were used to show the distribution of radiomics score. RESULTS: AUC values of radiomics model to predict LNM were 0.938, 0.905, and 0.872 in the training, internal test, and external validation sets, respectively, higher than that of manual classification (0.674, all P values < 0.01). The radiomics score of the positive LNM group were higher than that of the negative group in all sets (both P-values < 0.001). The classifier showed no improved predictive power compared with the radiomics signature alone with AUC values of 0.916 and 0.872 in the development and external validation sets, respectively. Multivariate analysis showed that radiomics score was an independent predictor. CONCLUSIONS: Radiomics model based on peritumoral adipose region could be a useful approach for preoperative LNM prediction in gastric adenocarcinoma.

Disfunction of dorsal raphe nucleus-hippocampus serotonergic-HTR3 transmission results in anxiety phenotype of Neuroplastin 65-deficient mice.

Anxiety disorders are the most common psychiatric condition, but the etiology of anxiety disorders remains largely unclear. Our previous studies have shown that neuroplastin 65 deficiency (NP65-/-) mice exhibit abnormal social and mental behaviors and decreased expression of tryptophan hydroxylase 2 (TPH2) protein. However, whether a causal relationship between TPH2 reduction and anxiety disorders exists needs to be determined. In present study, we found that replenishment of TPH2 in dorsal raphe nucleus (DRN) enhanced 5-HT level in the hippocampus and alleviated anxiety-like behaviors. In addition, injection of AAV-NP65 in DRN significantly increased TPH2 expression in DRN and hippocampus, and reduced anxiety-like behaviors. Acute administration of exogenous 5-HT or HTR3 agonist SR57227A in hippocampus mitigated anxiety-like behaviors in NP65-/- mice. Moreover, replenishment of TPH2 in DRN partly repaired the impairment of long-term potentiation (LTP) maintenance in hippocampus of NP65-/- mice. Finally, we found that loss of NP65 lowered transcription factors Lmx1b expression in postnatal stage and replenishment of NP65 in DRN reversed the decrease in Lmx1b expression of NP65-/- mice. Together, our findings reveal that NP65 deficiency induces anxiety phenotype by downregulating DRN-hippocampus serotonergic-HTR3 transmission. These studies provide a novel and insightful view about NP65 function, suggesting an attractive potential target for treatment of anxiety disorders.

A Systematic Review and Meta-Analysis of MRI Radiomics for Predicting Microvascular Invasion in Patients with Hepatocellular Carcinoma.

BACKGROUND: The prediction power of MRI radiomics for microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) remains uncertain. OBJECTIVE: To investigate the prediction performance of MRI radiomics for MVI in HCC. METHODS: Original studies focusing on preoperative prediction performance of MRI radiomics for MVI in HCC, were systematically searched from databases of PubMed, Embase, Web of Science and Cochrane Library. Radiomics quality score (RQS) and risk of bias of involved studies were evaluated. Meta-analysis was carried out to demonstrate the value of MRI radiomics for MVI prediction in HCC. Influencing factors of the prediction performance of MRI radiomics were identified by subgroup analyses. RESULTS: 13 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement were eligible for this systematic review and meta-analysis. The studies achieved an average RQS of 14 (ranging from 11 to 17), accounting for 38.9% of the total points. MRI radiomics achieved a pooled sensitivity of 0.82 (95%CI: 0.78 - 0.86), specificity of 0.79 (95%CI: 0.76 - 0.83) and area under the summary receiver operator characteristic curve (AUC) of 0.88 (95%CI: 0.84 - 0.91) to predict MVI in HCC. Radiomics models combined with clinical features achieved superior performances compared to models without the combination (AUC: 0.90 vs 0.85, P < 0.05). CONCLUSION: MRI radiomics has the potential for preoperative prediction of MVI in HCC. Further studies with high methodological quality should be designed to improve the reliability and reproducibility of the radiomics models for clinical application. The systematic review and meta-analysis was registered prospectively in the International Prospective Register of Systematic Reviews (No. CRD42022333822).

Computed tomography-based nomogram of Siewert type II/III adenocarcinoma of esophagogastric junction to predict response to docetaxel, oxaliplatin and S-1.

BACKGROUND: Neoadjuvant chemotherapy (NAC) has become the standard care for advanced adenocarcinoma of esophagogastric junction (AEG), although a part of the patients cannot benefit from NAC. There are no models based on baseline computed tomography (CT) to predict response of Siewert type II or III AEG to NAC with docetaxel, oxaliplatin and S-1 (DOS). AIM: To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS. METHODS: One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS, and were randomly and consecutively assigned to the training cohort (TC) (n = 94) and the validation cohort (VC) (n = 34). Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors (version 1.1) criteria. Possible prognostic factors associated with responses after DOS treatment including Siewert classification, gross tumor volume (GTV), and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age. Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS. A nomogram was established based on independent factors to predict the response. The predictive performance of the nomogram was evaluated by Concordance index (C-index), calibration and receiver operating characteristics curve in the TC and VC. RESULTS: Univariate analysis showed that Siewert type (52/55 vs 29/39, P = 0.005), pretherapeutic cT stage (57/62 vs 24/32, P = 0.028), GTV (47.3 ± 27.4 vs 73.2 ± 54.3, P = 0.040) were significantly associated with response to DOS in the TC. Multivariate analysis of the TC also showed that the pretherapeutic cT stage, GTV and Siewert type were independent predictive factors related to response to DOS (odds ratio = 4.631, 1.027 and 7.639, respectively; all P < 0.05). The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC (C-index: 0.838 and 0.824), with area under the receiver operating characteristic curve of 0.838 and 0.824, respectively. The calibration curves showed that the practical and predicted response to DOS effectively coincided. CONCLUSION: A novel nomogram developed with pretherapeutic cT stage, GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.

Contrast-enhanced CT radiomics features to preoperatively identify differences between tumor and proximal tumor-adjacent and tumor-distant tissues of resectable esophageal squamous cell carcinoma.

BACKGROUND: Esophagectomy is the main treatment for esophageal squamous cell carcinoma (ESCC), and patients with histopathologically negative margins still have a relatively higher recurrence rate. Contrast-enhanced CT (CECT) radiomics might noninvasively obtain potential information about the internal heterogeneity of ESCC and its adjacent tissues. This study aimed to develop CECT radiomics models to preoperatively identify the differences between tumor and proximal tumor-adjacent and tumor-distant tissues in ESCC to potentially reduce tumor recurrence. METHODS: A total of 529 consecutive patients with ESCC from Centers A (n = 447) and B (n = 82) undergoing preoperative CECT were retrospectively enrolled in this study. Radiomics features of the tumor, proximal tumor-adjacent (PTA) and proximal tumor-distant (PTD) tissues were individually extracted by delineating the corresponding region of interest (ROI) on CECT and applying the 3D-Slicer radiomics module. Patients with pairwise tissues (ESCC vs. PTA, ESCC vs. PTD, and PTA vs. PTD) from Center A were randomly assigned to the training cohort (TC, n = 313) and internal validation cohort (IVC, n = 134). Univariate analysis and the least absolute shrinkage and selection operator were used to select the core radiomics features, and logistic regression was performed to develop radiomics models to differentiate individual pairwise tissues in TC, validated in IVC and the external validation cohort (EVC) from Center B. Diagnostic performance was assessed using area under the receiver operating characteristics curve (AUC) and accuracy. RESULTS: With the chosen 20, 19 and 5 core radiomics features in TC, 3 individual radiomics models were developed, which exhibited excellent ability to differentiate the tumor from PTA tissue (AUC: 0.965; accuracy: 0.965), the tumor from PTD tissue (AUC: 0.991; accuracy: 0.958), and PTA from PTD tissue (AUC: 0.870; accuracy: 0.848), respectively. In IVC and EVC, the models also showed good performance in differentiating the tumor from PTA tissue (AUCs: 0.956 and 0.962; accuracy: 0.956 and 0.937), the tumor from PTD tissue (AUCs: 0.990 and 0.974; accuracy: 0.952 and 0.970), and PTA from PTD tissue (AUCs: 0.806 and 0.786; accuracy: 0.760 and 0.786), respectively. CONCLUSION: CECT radiomics models could differentiate the tumor from PTA tissue, the tumor from PTD tissue, and PTA from PTD tissue in ESCC.

MRI-Based Radiomics and Delta-Radiomics Models of the Patella Predict the Radiographic Progression of Osteoarthritis: Data From the FNIH OA Biomarkers Consortium.

RATIONALE AND OBJECTIVES: To analyse the MRI-based radiomics and delta-radiomics features to establish radiomics models for predicting the radiographic progression of osteoarthritis (OA). MATERIALS AND METHODS: The data used in this research come from the dataset of the FNIH Biomarker Consortium Project within the Osteoarthritis Initiative (OAI). 565 participants randomly divided into training and validation groups at a 7:3 ratio. The training cohort consisted of 395 participants and included 202 cases. The validation cohort consisted of 170 participants and included 87 cases. Least absolute shrinkage and selection operator (LASSO) was used for feature selection. Support vector machine (SVM) was used to establish radiomics models and clinical and biomarker models for predicting the radiographic progression of OA. The predictive ability of the model was evaluated by the area under the curve (AUC). RESULTS: The baseline, 24 M, Delta, and two combination radiomics models (Baseline and Delta, 24 M and Delta) all showed good predictive performance in the training and validation cohorts, with the combination model exhibiting the best performance. In the training cohort, the AUCs were 0.851 (95% CI: 0.812-0.890), 0.825 (95% CI: 0.784-0.865), 0.804 (95% CI: 0.761-0.847), 0.892 (95% CI: 0.860-0.924) and 0.884 (95% CI: 0.851-0.917), respectively. The AUCs in the validation cohort were 0.741 (95% CI: 0.667-0.814), 0.786 (95% CI: 0.716-0.856), 0.745 (95% CI: 0.671-0.819), 0.781 (95% CI: 0.711-0.851) and 0.802 (95% CI: 0.736-0.869), respectively. As compared, the clinical and biomarker models have AUC < 0.74. The DeLong test showed that the predictive performance of the radiomics models in the training and validation cohorts was significantly better than that of the clinical and biomarker models (P < 0.001). CONCLUSION: The MRI-based radiomics models of the patella all showed good predictive performance performed better than the clinical and biomarker models in predicting the radiographic progression of OA. Delta radiomics can improve the predictive performance of the single time model, the combined model of 24 M and Delta provided the best predictive performance.

An improved model based on quantitative features of right liver lobe, maximum varices, and portal vein system measured on magnetic resonance imaging to predict oesophagogastric variceal haemorrhage secondary to hepatitis B-related cirrhosis.

Background: In patients with hepatitis B-related cirrhosis, it is important to predict those at high-risk of oesophagogastric variceal haemorrhage (OVH) to decide upon prophylactic treatment. Our published model developed with right liver lobe volume and diameters of portal vein system did not incorporate maximum variceal size as a factor. This study thus aimed to develop an improved model based on right liver lobe volume, diameters of maximum oesophagogastric varices (OV) and portal vein system obtained at magnetic resonance imaging (MRI) to predict OVH. Methods: Two hundred and thirty consecutive individuals with hepatitis B-related cirrhosis undergoing abdominal enhanced MRI were randomly grouped into training (n=160) and validation sets (n=70). OVH was confirmed in 51 and 23 participants in the training and validation sets during 2-year follow-up period, respectively. Spleen, total liver, right lobe, caudate lobe, left lateral lobe, and left medial lobe volumes, together with diameters of maximum OV and portal venous system were measured on MRI. In the training set, univariate analyses and binary logistic regression analyses were conducted to determine independent predictors. The performance of the model for predicting OVH constructed based on independent predictors from the training set was evaluated with receiver operating characteristic (ROC) analysis and validated in the validation set. Results: The model for predicting OVH was established based on right liver lobe volume and diameters of the maximum OV, left gastric vein, and portal vein [odds ratio (OR) =0.991, 2.462, 1.434, and 1.582, respectively; all P values <0.05]. The logistic regression model equation [-0.009 × right liver lobe volume + 0.901 × maximum OV diameter (MOVD) + 0.361 × left gastric vein diameter (LGVD) + 0.459 × portal vein diameter (PVD) - 7.842] with a cutoff value of -0.656 for predicting OVH obtained excellent performance with an area under ROC curve (AUC) of 0.924 [95% confidence interval (CI): 0.878-0.971]. The Delong test showed negative statistical difference in the model performance between the training and validation sets, with a P value >0.99. Conclusions: The model could help well screen those patients at high risk of OVH for timely intervention and avoiding the fatal complications.

Photoinduced reductive Reformatsky reaction of α-haloesters and aldehydes or ketones by cooperative dual-metal catalysis.

A photoinduced reductive Reformatsky reaction by cooperative dual-metal catalysis is described. This methodology enables the implementation of this venerable reaction in environmentally friendly conditions, obviating the need for a stoichiometric amount of metals. A broad range of synthetically useful ß-hydroxy esters can be efficiently prepared in moderate to high yields using this protocol.

CT Features of Recurrent Acute Pancreatitis: Early Phase Versus Late Phase.

OBJECTIVES: The aim of this study was to investigate the computed tomography (CT) features of recurrent acute pancreatitis (RAP) in the early phase and late phase. METHODS: Recurrent acute pancreatitis data were obtained over the past 5 years. Recurrent acute pancreatitis patients were divided into 2 groups according to the time from RAP onset to performing CT examination: the early phase (first week) and late phase (after the first week) based on the 2012 revised Atlanta classification (RAC). Evaluation and comparison of patients' demographic data, RAC, CT findings, CT severity index (CTSI) score, and extrapancreatic inflammation on CT (EPIC) score were conducted in the 2 groups. RESULTS: Hypertriglyceridemia was the most common cause of RAP in 679 of 686 patients (positive CT rate: 98.98%). Among 679 CT-positive patients, interstitial edematous pancreatitis and necrotizing pancreatitis accounted for 61.71% (419/679) and 38.29% (260/679), respectively. The CTSI and EPIC scores were higher in the late phase than in the early phase (both P 's < 0.05). The proportion of moderately severe and severe RAP patients based on RAC was higher in the late phase than in the early phase ( P < 0.05). Early-stage EPIC score was more accurate than CTSI and Acute Physiology and Chronic Health Evaluation (APACHE) II scores in predicting clinically severe RAP (EPIC vs CTSI; EPIC vs APACHE II, both P 's < 0.05). CONCLUSIONS: Recurrent acute pancreatitis is more severe in the late phase than in the early phase. The EPIC score is more indicative of clinically severe RAP than CTSI and APACHE II scores in the early phase of RAP.

Catalytic Asymmetric Polycyclization of Tertiary Enamides with Silyl Enol Ethers: Total Synthesis of (-)-Cephalocyclidin A.

A catalytic enantioselective polycyclization of tertiary enamides with terminal silyl enol ethers has been developed by virtue of Cu(OTf)2 catalysis with a novel spiropyrroline-derived oxazole (SPDO) ligand. This tandem reaction offers an effective approach to assemble bicyclic and tricyclic N-heterocycles bearing both aza- and oxa-quaternary stereogenic centers, which are primal subunits in a range of natural alkaloids. Strategic application of this methodology and a late-stage radical cyclization as key steps have been showcased in the concise total synthesis of (-)-cephalocyclidin A.

Au-Catalyzed Asymmetric Polyene Cyclization and Its Application in the Total Synthesis of (+)-2-Ketoferruginol, (+)-Fleuryinol B, (+)-Salviol, and (-)-Erythroxylisin A.

A catalytic asymmetric 1,3-acyloxy shift/polyene cyclization cascade has been achieved with good enantioselectivities under the catalysis of the chiral Au(I) reagent. The synthetic utility of this method has been showcased by the catalytic asymmetric total syntheses of (+)-2-ketoferruginol, (+)-fleuryinol B, and (+)-salviol. Notably, the first enantioselective total synthesis of (-)-erythroxylisin A has also been realized in 15 steps.