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The excessive and frequent use of insecticides has led to serious problems with insecticide residues, impacting nontarget organisms such as the parasitoid Encarsia formosa. This study examined the growth, development, and enzyme activity of E. formosa exposed to spirotetramat at LC10, LC30, and LC50. The regression equation for the toxicity of spirotetramat toward E. formosa was Y = 5.25X-11.07. After exposure to spirotetramat, the survival rates of E. formosa sharply decreased, which occurred earlier than those in the control batch. Although the maximum daily parasitism quantity of E. formosa increased and the average parasitism number, enumerated from the 1st to the 5th day, was 53.97 after being exposed to spirotetramat at LC10, the life span of its F1 generation adults was only 8.47 days, which was significantly shorter than that in the control batch. After being exposed to spirotetramat at LC50, the average parasitism number of E. formosa was 63.30, and the developmental time of its F1 generation, enumerated from the 1st to the 5th day after exposure to spirotetramat, was significantly longer than that of the control batch. The activities of mixed function oxidase, acetylcholinesterase, carboxylesterase, and catalase increased significantly, and the rate of increase in enzyme activity was directly proportional to the increase in the concentration of spirotetramat. These results revealed that the parasitic ability of E. formosa decreased after exposure to spirotetramat at LC10, LC30, and LC50. This leads to a change in parasitoid control of pests, revealing the potential environmental threat of insecticide residues to nontarget organisms.
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Succinate dehydrogenase (SDH) has been considered an ideal target for discovering fungicides. To develop novel SDH inhibitors, in this work, 31 novel benzothiazol-2-ylthiophenylpyrazole-4-carboxamides were designed and synthesized using active fragment exchange and a link approach as promising SDH inhibitors. The findings from the tests on antifungal activity indicated that most of the synthesized compounds displayed remarkable inhibition against the fungi tested. Compound Ig N-(2-(((5-chlorobenzo[d]thiazol-2-yl)thio)methyl)phenyl)-3-(difluoromethyl)-1-methyl-1H-yrazole-4-carboxamide, with EC50 values against four kinds of fungi tested below 10 µg/mL and against Cercospora arachidicola even below 2 µg/mL, showed superior antifungal activity than that of commercial fungicide thifluzamide, and specifically compounds Ig and Im were found to show preventative potency of 90.6% and 81.3% against Rhizoctonia solani Kühn, respectively, similar to the positive fungicide thifluzamide. The molecular simulation studies suggested that hydrophobic interactions were the main driving forces between ligands and SDH. Encouragingly, we found that compound Ig can effectively promote the wheat seedlings and the growth of Arabidopsis thaliana. Our further studies indicated that compound Ig could stimulate nitrate reductase activity in planta and increase the biomass of plants.
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Inibidores Enzimáticos , Fungicidas Industriais , Pirazóis , Succinato Desidrogenase , Succinato Desidrogenase/antagonistas & inibidores , Succinato Desidrogenase/metabolismo , Fungicidas Industriais/farmacologia , Fungicidas Industriais/química , Fungicidas Industriais/síntese química , Relação Estrutura-Atividade , Inibidores Enzimáticos/farmacologia , Inibidores Enzimáticos/química , Inibidores Enzimáticos/síntese química , Pirazóis/farmacologia , Pirazóis/química , Pirazóis/síntese química , Rhizoctonia/efeitos dos fármacos , Rhizoctonia/crescimento & desenvolvimento , Simulação de Acoplamento Molecular , Benzotiazóis/química , Benzotiazóis/farmacologia , Proteínas Fúngicas/antagonistas & inibidores , Proteínas Fúngicas/metabolismo , Proteínas Fúngicas/química , Ascomicetos/efeitos dos fármacos , Ascomicetos/enzimologia , Estrutura MolecularRESUMO
Objective: To develop a CT-based nomogram to predict the response of advanced esophageal squamous cell carcinoma (ESCC) to neoadjuvant chemotherapy plus immunotherapy. Methods: In this retrospective study, 158 consecutive patients with advanced ESCC receiving contrast-enhanced CT before neoadjuvant chemotherapy plus immunotherapy were randomized to a training cohort (TC, n = 121) and a validation cohort (VC, n = 37). Response to treatment was assessed with response evaluation criteria in solid tumors. Patients in the TC were divided into the responder (n = 69) and non-responder (n = 52) groups. For the TC, univariate analyses were performed to confirm factors associated with response prediction, and binary analyses were performed to identify independent variables to develop a nomogram. In both the TC and VC, the nomogram performance was assessed by area under the receiver operating characteristic curve (AUC), calibration slope, and decision curve analysis (DCA). Results: In the TC, univariate analysis showed that cT stage, cN stage, gross tumor volume, gross volume of all enlarged lymph nodes, and tumor length were associated with the response (all P < 0.05). Binary analysis demonstrated that cT stage, cN stage, and tumor length were independent predictors. The independent factors were imported into the R software to construct a nomogram, showing the discriminatory ability with an AUC of 0.813 (95% confidence interval: 0.735-0.890), and the calibration curve and DCA showed that the predictive ability of the nomogram was in good agreement with the actual observation. Conclusion: This study provides an accurate nomogram to predict the response of advanced ESCC to neoadjuvant chemotherapy plus immunotherapy.
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BACKGROUND: The modified pancreatitis activity scoring system (mPASS) was proposed to assess the activity of acute pancreatitis (AP) while it doesn't include indicators that directly reflect pathophysiology processes and imaging characteristics. OBJECTIVES: To determine the threshold of admission mPASS and investigate radiomics and laboratory parameters to construct a model to predict the activity of AP. METHODS: AP inpatients at institution 1 were randomly divided into training and validation groups based on a 5:5 ratio. AP inpatients at Institution 2 were served as test group. The cutoff value of admission mPASS scores in predicting severe AP was selected to divide patients into high and low level of disease activity group. LASSO was used in screening features. Multivariable logistic regression was used to develop radiomics model. Meaningful laboratory parameters were used to construct combined model. RESULTS: There were 234 (48 years ± 10, 155 men) and 101 (48 years ± 11, 69 men) patients in two institutions. The threshold of admission mPASS score was 112.5 in severe AP prediction. The AUC of the radiomics model was 0.79, 0.72, and 0.76 and that of the combined model incorporating rad-score and white blood cell were 0.84, 0.77, and 0.80 in three groups for activity prediction. The AUC of the combined model in predicting disease without remission was 0.74. CONCLUSIONS: The threshold of admission mPASS was 112.5 in predicting severe AP. The model based on CECT radiomics has the ability to predict AP activity. Its ability to predict disease without remission is comparable to mPASS. CRITICAL RELEVANCE STATEMENT: This work is the first attempt to assess the activity of acute pancreatitis using contrast-enhanced CT radiomics and laboratory parameters. The model provides a new method to predict the activity and prognosis of AP, which could contribute to further management. KEY POINTS: Radiomics features and laboratory parameters are associated with the activity of acute pancreatitis. The combined model provides a new method to predict the activity and prognosis of AP. The ability of the combined model is comparable to the modified Pancreatitis Activity Scoring System.
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The integration of artificial intelligence (AI) into smart agriculture boosts production and management efficiency, facilitating sustainable agricultural development. In intensive agricultural management, adopting eco-friendly and effective pesticides is crucial to promote green agricultural practices. However, exploring new insecticides species is a difficult and time-consuming task that involves significant risks. Enhancing compound druggability in the lead discovery phase could considerably shorten the discovery cycle, accelerating insecticides research and development. The Insecticide Activity Prediction (IAPred) model, a novel classic artificial intelligence-based method for evaluating the potential insecticidal activity of unknown functional compounds, is introduced in this study. The IAPred model utilized 27 insecticide-likeness features from PaDEL descriptors and employed an ensemble of Support Vector Machine (SVM) and Random Forest (RF) algorithms using the hard-vote mechanism, achieving an accuracy rate of 86 %. Notably, the IAPred model outperforms current models by accurately predicting the efficacy of novel insecticides such as nicofluprole, overcoming the limitations inherent in existing insecticide structures. Our research presents a practical approach for discovering and optimizing novel insecticide lead compounds quickly and efficiently.
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Delírio , Fragilidade , Fraturas do Quadril , Complicações Pós-Operatórias , Humanos , Fraturas do Quadril/cirurgia , Delírio/etiologia , Delírio/epidemiologia , Fragilidade/complicações , Idoso , Estudos Prospectivos , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologia , Fatores de Risco , Idoso de 80 Anos ou mais , Idoso Fragilizado , Feminino , Masculino , Estudos de CoortesRESUMO
Bridged chiral biaryls are axially chiral compounds with a medium-sized ring connecting the two arenes. Compared with plentiful methods for the enantioselective synthesis of biaryl compounds, synthetic approaches for this subclass of bridged atropisomers are limited. Here we show an atroposelective synthesis of 1,3-diaxial bridged eight-membered terphenyl atropisomers through an Co/SPDO (spirocyclic pyrrolidine oxazoline)-catalyzed aerobic oxidative coupling/desymmetrization reaction of prochiral phenols. This catalytic desymmetric process is enabled by combination of an earth-abundant Co(OAc)2 and a unique SPDO ligand in the presence of DABCO (1,4-diaza[2.2.2]bicyclooctane). An array of diaxial bridged terphenyls embedded in an azocane can be accessed in high yields (up to 99%) with excellent enantio- (>99% ee) and diastereoselectivities (>20:1 dr).
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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.
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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.
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Adenocarcinoma , Tecido Adiposo , Metástase Linfática , Neoplasias Gástricas , Tomografia Computadorizada por Raios X , Humanos , Neoplasias Gástricas/diagnóstico por imagem , Neoplasias Gástricas/patologia , Neoplasias Gástricas/cirurgia , Masculino , Feminino , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/patologia , Adenocarcinoma/cirurgia , Tomografia Computadorizada por Raios X/métodos , Pessoa de Meia-Idade , Metástase Linfática/diagnóstico por imagem , Idoso , Tecido Adiposo/diagnóstico por imagem , Tecido Adiposo/patologia , Valor Preditivo dos Testes , Adulto , Gastrectomia , Estudos Retrospectivos , Reprodutibilidade dos Testes , Excisão de Linfonodo , RadiômicaRESUMO
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.
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Ansiedade , Núcleo Dorsal da Rafe , Hipocampo , Camundongos Knockout , Receptores 5-HT3 de Serotonina , Serotonina , Triptofano Hidroxilase , Animais , Núcleo Dorsal da Rafe/metabolismo , Hipocampo/metabolismo , Ansiedade/metabolismo , Serotonina/metabolismo , Camundongos , Masculino , Triptofano Hidroxilase/genética , Triptofano Hidroxilase/metabolismo , Triptofano Hidroxilase/deficiência , Receptores 5-HT3 de Serotonina/metabolismo , Receptores 5-HT3 de Serotonina/genética , Camundongos Endogâmicos C57BL , Fenótipo , Potenciação de Longa DuraçãoRESUMO
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).
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Carcinoma Hepatocelular , Neoplasias Hepáticas , Imageamento por Ressonância Magnética , Microvasos , Invasividade Neoplásica , Radiômica , Humanos , Carcinoma Hepatocelular/diagnóstico por imagem , Carcinoma Hepatocelular/patologia , Neoplasias Hepáticas/diagnóstico por imagem , Neoplasias Hepáticas/patologia , Imageamento por Ressonância Magnética/métodos , Microvasos/diagnóstico por imagem , Valor Preditivo dos Testes , Prognóstico , Curva ROC , Sensibilidade e EspecificidadeRESUMO
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.
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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.
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Neoplasias Esofágicas , Carcinoma de Células Escamosas do Esôfago , Humanos , Carcinoma de Células Escamosas do Esôfago/diagnóstico por imagem , Carcinoma de Células Escamosas do Esôfago/cirurgia , Neoplasias Esofágicas/diagnóstico por imagem , Neoplasias Esofágicas/cirurgia , Radiômica , Estudos Retrospectivos , Tomografia Computadorizada por Raios XRESUMO
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.