CYP3A Mediates an Unusual C(sp2)-C(sp3) Bond Cleavage via Ipso-Addition of Oxygen in Drug Metabolism.

Mammalian cytochrome P450 drug-metabolizing enzymes rarely cleave carbon-carbon (C-C) bonds and the mechanisms of such cleavages are largely unknown. We identified two unusual cleavages of non-polar, unstrained C(sp2)-C(sp3) bonds in the FDA-approved tyrosine kinase inhibitor pexidartinib that are mediated by CYP3A4/5, the major human phase I drug metabolizing enzymes. Using a synthetic ketone, we rule out the Baeyer-Villiger oxidation mechanism that is commonly invoked to address P450-mediated C-C bond cleavages. Our studies in 18O2 and H2 18O enriched systems reveal two unusual distinct mechanisms of C-C bond cleavage: one bond is cleaved by CYP3A-mediated ipso-addition of oxygen to a C(sp2) site of N-protected pyridin-2-amines, and the other occurs by a pseudo-retro-aldol reaction after hydroxylation of a C(sp3) site. This is the first report of CYP3A-mediated C-C bond cleavage in drug metabolism via ipso-addition of oxygen mediated mechanism. CYP3A-mediated ipso-addition is also implicated in the regioselective C-C cleavages of several pexidartinib analogs. The regiospecificity of CYP3A-catalyzed oxygen ipso-addition under environmentally friendly conditions may be attractive and inspire biomimetic or P450-engineering methods to address the challenging task of C-C bond cleavages.

Should Pediatric Surgical Oncologists Receive Training in Vascular Surgery ? A Practice Survey Report From the International Society of Paediatric Surgical Oncology (IPSO).

BACKGROUND: Is vascular training in paediatric surgical oncology considered desirable ? METHODS: A voluntary survey of work practice was undertaken with the surgeon membership of The International Society Of Paediatric Surgical Oncology (IPSO) using a structured designed questionnaire. RESULTS: A total of 149 IPSO surgeon members completed the survey. 57% (N = 84) of surgeons surveyed had no specific training in vascular surgery. 43% surgeons (N = 63) stated they had acquired some skills in residency training and/or with transplantation surgery. 65% (N = 96) of respondent surgeons stated that vascular surgical training must be incorporated into pediatric surgical oncology training and 27% (N = 40) agreed that it was considered desirable. 89% (N = 133) of surgeon respondents had encountered major vascular injury during work practice while operating on pediatric solid tumors. Vascular injury repairs were undertaken and attempted by pediatric surgeons though expert assistance of vascular surgeons proved crucially essential in many instances. Emergent operations included patch repairs, vessel ligation techniques and insertion of vascular graft prostheses. Interventional radiology services to arrest life-threatening hemorrhage were also reportedly utilized by respondents. CONCLUSION: Vascular injuries have significant potential for devastating patient outcomes including never event 'mortality'. The IPSO surgeon survey highlights that there are visible 'gaps' in skills training. Training to be a pediatric oncology surgeon must incorporate acquisition of skill sets proficiency in vascular surgery.

International Society of Paediatric Surgical Oncology (IPSO): A Short History, Developments, and Current Status.

The International Society of Paediatric Surgical Oncology (IPSO) was officially inaugurated in 1991 through the creativeness and inspiration of a collective dynamic group of paediatric surgeons committed to advancing childhood cancer. This article traces the origins and birth of IPSO tracking its modern day development to a growing world community of paediatric surgeon oncology members. LEVEL OF EVIDENCE: 5.

Accessing Pyridines via a Nitrene Internalization Process.

Pyridines are valuable pharmacophores, and their access via direct and selective transmutation of carbon atom with desired nitrogen could become crucial in drug discovery processes. However, only scarce examples can be found when it comes C-to-N-transmutation reactions of aromatics that could lead to the facile synthesis of pyridines or other azaarenes. In this context, Levin and co-workers recently disclosed a process leading to pyridines from the corresponding aryl azides via the regioselective nitrene internalization process. Notably, the transformation did not lead to any further modification of the rest of the aromatic skeleton. This innovative work enabled selectively accessing various pyridine derivatives through direct nitrogen scan operations on benzene derivatives, which were otherwise not feasible.

Design of innovation ability evaluation model based on IPSO-LSTM in intelligent teaching.

Guided by the development of an innovative economy, students' innovative education has also become the focus of talent training. This research aims to realize the intelligent evaluation of students' innovation ability. In this article, we proposed an innovation ability framework that integrates students' psychological state and innovation evaluation indicators. Firstly, the qualitative description of psychological data is quantified using the Delphi method. Secondly, this article proposes an improved particle swarm optimization-long short-term memory (IPSO-LSTM) model to achieve high-precision evaluation and classification of innovation capabilities. The classification accuracy of this model for excellent, general and failed innovation capabilities is up to 95.3%. Finally, the characteristic contribution analysis of psychological and innovative ability characteristics is carried out. The results show that the evaluation of creative ability contributes more than 50% to the psychological aspects of excellent students. This shows the importance of psychological status on creative ability and provides a theoretical basis for integrating innovative education and psychological education in the future.

Synthesis and biological evaluation of benzofuran piperazine derivatives as potential anticancer agents.

This work describes about the synthesis and evaluation of substituted benzofuran piperazines as potential anticancer agents. The synthesized candidates have been evaluated for their cell proliferation inhibition properties in six murine and human cancer cell lines. In vitro evaluation of apoptosis and cell cycle analysis with the lead candidate 1.19 reveals that necrosis might be an important pathway for the candidate compounds to cause cell death. Further, in vivo evaluation of the lead compound shows that this candidate is well tolerated in healthy mice. Additionally, an in vivo anticancer efficacy study in mice using a MDA-MB-231 xenograft model with the lead compound provides good anti-cancer efficacy.

Catalytic ipso-Nitration of Organosilanes Enabled by Electrophilic N-Nitrosaccharin Reagent.

Nitroaromatic compounds represent one of the essential classes of molecules that are widely used as feedstock for the synthesis of intermediates, the preparation of nitro-derived pharmaceuticals, agrochemicals, and materials on both laboratory and industrial scales. We herein disclose the efficient, mild, and catalytic ipso-nitration of organotrimethylsilanes, enabled by an electrophilic N-nitrosaccharin reagent and allows chemoselective nitration under mild reaction conditions, while exhibiting remarkable substrate generality and functional group compatibility. Additionally, the reaction conditions proved to be orthogonal to other common functionalities, allowing programming of molecular complexity via successive transformations or late-stage nitration. Detailed mechanistic investigation by experimental and computational approaches strongly supported a classical electrophilic aromatic substitution (SE Ar) mechanism, which was found to proceed through a highly ordered transition state.

Regioselective SmI2-Mediated Radical ipso-Substitution Cyclization for the Construction of Pyrrolophenanthridinone Skeletons: The Synthesis of Amaryllidaceae Alkaloids.

Here, we report a regioselective, samarium(II) diiodide mediated intramolecular radical ipso-substitution cyclization. Through the use of a methoxy group as a leaving group, it was possible to regulate the regioselectivity of the reaction by changing the temperature and additives. We applied the developed reaction to the synthesis of four Amaryllidaceae alkaloids and have shown that the present reaction successfully overcomes regioselectivity issues encountered with other cyclization methods.

An IPSO-FW-WSVM Method for Stock Trading Signal Forecasting.

Trading signal detection is a very popular yet challenging research topic in the financial investment area. This paper develops a novel method integrating piecewise linear representation (PLR), improved particle swarm optimization (IPSO) and a feature-weighted support vector machine (FW-WSVM) to analyze the nonlinear relationships between trading signals and the stock data hidden in historical data. First, PLR is applied to generate numerous trading points (valleys or peaks) based on the historical data. These turning points' prediction is formulated as a three-class classification problem. Then, IPSO is utilized to find the optimal parameters of FW-WSVM. Lastly, we conduct a series of comparative experiments between IPSO-FW-WSVM and PLR-ANN on 25 stocks with 2 different investment strategies. The experiment results show that our proposed method achieves higher prediction accuracy and profitability, which indicates the IPSO-FW-WSVM method is effective in the prediction of trading signals.

Surface Nanoarchitectonics of Boron Nitride Nanosheets for Highly Efficient and Sustainable ipso-Hydroxylation of Arylboronic Acids.

One of the important industrial processes commonly employed in the pharmaceutical, explosive, and plastic manufacturing industries is ipso-hydroxylation of arylboronic acids. In this work, a straightforward, metal-free methodology for the synthesis of phenols from arylboronic acids has been demonstrated using hydroxyl functionalized boron nitride (BN-OH) nanosheets. The functionalized hydroxyl groups on the BN nanosheets act as the active sites for the hydroxylation reaction to take place. The detailed optimization of reaction parameters was done in order to attain high catalytic efficiency, and the reactions were conducted in water, which eliminates the use of toxic solvents. The as-synthesized catalysts exhibited excellent recyclability and reusability in addition to high product yields and good turnover numbers. The green metrics parameters were also evaluated for the model reaction to examine the sustainable nature of the developed protocol. The use of BN-OH catalysts for the ipso-hydroxylation reactions under base-free and metal-free conditions using environmentally benign solvents is utmost desired for industrial processes and can pave a way toward sustainable organic catalysis.

Visible-Light-Induced Diradical-Mediated ipso-Cyclization towards Double Dearomative [2+2]-Cycloaddition or Smiles-Type Rearrangement.

When mono-radical ipso-cyclization of aryl sulfonamides tend to undergo Smiles-type rearrangement through aromatization-driven C-S bond cleavage, diradical-mediated cyclization must perform in a distinct reaction pathway. It is interesting meanwhile challenging to tune the rate of C-S bond cleavage to achieve a chemically divergent reaction of (hetero) aryl sulfonamides in a visible-light induced energy transfer (EnT) reaction pathway involving diradical species. Herein a chemically divergent reaction based on the designed indole-tethered (hetero)arylsulfonamides is reported which involves a diradical-mediated ipso-cyclization and a controllable cleavage of an inherent C-S bond. The combined experimental and computational results have revealed that the cleavage of the C-S bond in these substrates can be controlled by tuning the heteroaryl moieties: a) If the (hetero)aryl is thienyl, furyl, phenanthryl, etc., the radical coupling of double dearomative diradicals (DDDR) precedes over C-S bond cleavage to afford cyclobutene fused indolines by double dearomative [2+2]-cycloaddition; b) if the (hetero)aryl is phenyl, naphthyl, pyridyl, indolyl etc., the cleavage of C-S bond in DDDR is favored over radical coupling to afford biaryl products.

Comparison between human liver microsomes and the fungus Cunninghamella elegans for biotransformation of the synthetic cannabinoid JWH-424 having a bromo-naphthyl moiety analysed by high-resolution mass spectrometry.

PURPOSE: JWH-424, (8-bromo-1-naphthyl)(1-pentyl-1H-indol-3-yl)methanone, is a synthetic cannabinoid, which is a brominated analogue of JWH-018, one of the best-known synthetic cannabinoids. Despite the structural similarity to JWH-018, little is known about JWH-424 including its metabolism. The aim of the study was to compare human liver microsomes (HLM) and the fungus Cunninghamella elegans as the metabolism catalysts for JWH-424 to better understand the characteristic actions of the fungus in the synthetic cannabinoid metabolism. METHODS: JWH-424 was incubated with HLM for 1 h and Cunninghamella elegans for up to 72 h. The HLM incubation mixtures were diluted with methanol and fungal incubation mixtures were extracted with dichloromethane and reconstituted in methanol before analyses by liquid chromatography-high-resolution mass spectrometry (LC-HRMS). RESULTS: HLM incubation resulted in production of ten metabolites through dihydrodiol formation, hydroxylation, and/or ipso substitution of the bromine with a hydroxy group. Fungal incubation led to production of 23 metabolites through carboxylation, dihydrodiol formation, hydroxylation, ketone formation, glucosidation and/or sulfation. CONCLUSIONS: Generally, HLM models give good predictions of human metabolites and structural analogues are metabolised in a similar fashion. However, major hydroxy metabolites produced by HLM were those hydroxylated at naphthalene instead of pentyl moiety, the major site of hydroxylation for JWH-018. Fungal metabolites, on the other hand, had undergone hydroxylation mainly at pentyl moiety. The metabolic disagreement suggests the necessity to verify the human metabolites in authentic urine samples, while H9 and H10 (hydroxynaphthalene), H8 (ipso substitution), F22 (hydroxypentyl), and F17 (dihydroxypentyl) are recommended for monitoring of JWH-424 in urinalysis.

CEEMDAN-IPSO-LSTM: A Novel Model for Short-Term Passenger Flow Prediction in Urban Rail Transit Systems.

Urban rail transit (URT) is a key mode of public transport, which serves for greatest user demand. Short-term passenger flow prediction aims to improve management validity and avoid extravagance of public transport resources. In order to anticipate passenger flow for URT, managing nonlinearity, correlation, and periodicity of data series in a single model is difficult. This paper offers a short-term passenger flow prediction combination model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and long-short term memory neural network (LSTM) in order to more accurately anticipate the short-period passenger flow of URT. In the meantime, the hyperparameters of LSTM were calculated using the improved particle swarm optimization (IPSO). First, CEEMDAN-IPSO-LSTM model performed the CEEMDAN decomposition of passenger flow data and obtained uncoupled intrinsic mode functions and a residual sequence after removing noisy data. Second, we built a CEEMDAN-IPSO-LSTM passenger flow prediction model for each decomposed component and extracted prediction values. Third, the experimental results showed that compared with the single LSTM model, CEEMDAN-IPSO-LSTM model reduced by 40 persons/35 persons, 44 persons/35 persons, 37 persons/31 persons, and 46.89%/35.1% in SD, RMSE, MAE, and MAPE, and increase by 2.32%/3.63% and 2.19%/1.67% in R and R2, respectively. This model can reduce the risks of public health security due to excessive crowding of passengers (especially in the period of COVID-19), as well as reduce the negative impact on the environment through the optimization of traffic flows, and develop low-carbon transportation.

Metal free, one pot 1,6-Conjugate Addition of Diol on para-Quinone Methide followed by ipso cyclization: An Approach to Spiro 1,4-Dioxane cyclohexadienone Derivatives.

A novel one-pot transition metal-free and Brönsted acid mediated 1,6-conjugate addition of bisnuleophilic diol on biselectrophilc para-quinone methide followed by ipso cyclization assisted by NBS has been developed under mild reaction conditions, offers a new approach to synthesize spiro 1,4-dioxane cyclohexadienone derivatives. This strategy features broad substrate scope of p-QMs with high functional group tolerance and good yields of spirocyclic scaffolds (60-92 %). N-Bromo succinimide an important role in an ipso spirocyclization with high efficiency.

An innovative forecasting model to predict wind energy.

In recent years, the global wind power construction is accelerating. Although wind power is a clean energy without pollution, its volatility and irregularity have a great impact on wind power integration. Therefore, scholars pay more and more attention to the ultra-short-term prediction of wind speed. At present, the popular wind speed prediction model usually combines wind speed decomposition algorithm, machine learning algorithm, and intelligent optimization algorithm. The general wind speed decomposition algorithm cannot use the information contained in the factors affecting wind speed. Besides, the current popular optimization algorithms, such as gray wolf optimization algorithm, have strong convergence and better optimization effect, but their structure is complex and their operation complexity is large. And the PSO algorithm has simple structure and fast operation speed. To solve the above problems, a novel combination prediction model is proposed in this paper. This model uses VMD to decompose the wind speed into high-frequency signal and low-frequency signal and then uses principal component analysis and spectral clustering to extract and classify the influencing factors. In addition, aiming at the problem of slow convergence speed in the later stage of PSO iteration, an adaptive improved PSO is proposed. Finally, this paper also designs a rolling train method to adjust the size of training samples. Through four experiments of wind speed series in two periods, it is proved that the combined prediction model proposed in this paper has the following advantages: the model fully extracts the information of wind speed and influencing factors; the improved PSO algorithm has better optimization effect; rolling training method effectively improves the prediction ability of the model; the combined forecasting model has good adaptability and competitiveness.

Multi-Sensor Fusion by CWT-PARAFAC-IPSO-SVM for Intelligent Mechanical Fault Diagnosis.

A new method of multi-sensor signal analysis for fault diagnosis of centrifugal pump based on parallel factor analysis (PARAFAC) and support vector machine (SVM) is proposed. The single-channel vibration signal is analyzed by Continuous Wavelet Transform (CWT) to construct the time-frequency representation. The multiple time-frequency data are used to construct the three-dimension data matrix. The 3-level PARAFAC method is proposed to decompose the data matrix to obtain the six features, which are the time domain signal (mode 3) and frequency domain signal (mode 2) of each level within the three-level PARAFAC. The eighteen features from three direction vibration signals are used to test the data processing capability of the algorithm models by the comparison among the CWT-PARAFAC-IPSO-SVM, WPA-PSO-SVM, WPA-IPSO-SVM, and CWT-PARAFAC-PSO-SVM. The results show that the multi-channel three-level data decomposition with PARAFAC has better performance than WPT. The improved particle swarm optimization (IPSO) has a great improvement in the complexity of the optimization structure and running time compared to the conventional particle swarm optimization (PSO.) It verifies that the proposed CWT-PARAFAC-IPSO-SVM is the most optimal hybrid algorithm. Further, it is characteristic of its robust and reliable superiority to process the multiple sources of big data in continuous condition monitoring in the large-scale mechanical system.

Performance Degradation Prediction Using LSTM with Optimized Parameters.

Predicting the degradation of mechanical components, such as rolling bearings is critical to the proper monitoring of the condition of mechanical equipment. A new method, based on a long short-term memory network (LSTM) algorithm, has been developed to improve the accuracy of degradation prediction. The model parameters are optimized via improved particle swarm optimization (IPSO). Regarding how this applies to the rolling bearings, firstly, multi-dimension feature parameters are extracted from the bearing's vibration signals and fused into responsive features by using the kernel joint approximate diagonalization of eigen-matrices (KJADE) method. Then, the between-class and within-class scatter (SS) are calculated to develop performance degradation indicators. Since network model parameters influence the predictive accuracy of the LSTM model, an IPSO algorithm is used to obtain the optimal prediction model via the LSTM model parameters' optimization. Finally, the LSTM model, with said optimal parameters, was used to predict the degradation trend of the bearing's performance. The experiment's results show that the proposed method can effectively identify the trends of degradation and performance. Moreover, the predictive accuracy of this proposed method is greater than that of the extreme learning machine (ELM) and support vector regression (SVR), which are the algorithms conventionally used in degradation modeling.

Quantitative 1H-NMR analysis reveals steric and electronic effects on the substrate specificity of benzoate dioxygenase in Ralstonia eutropha B9.

The cis-dihydroxylation of arenes by Rieske dearomatizing dioxygenases (RDDs) represents a powerful tool for the production of chiral precursors in organic synthesis. Here, the substrate specificity of the RDD benzoate dioxygenase (BZDO) in Ralstonia eutropha B9 whole cells was explored using quantitative 1H nuclear magnetic resonance spectroscopy (q1H-NMR). The specific activity, specific carbon uptake, and regioselectivity of the dihydroxylation reaction were evaluated in resting cell cultures for a panel of 17 monosubstituted benzoates. Two new substrates of this dioxygenase system were identified (2-methyl- and 3-methoxybenzoic acid) and the corresponding cis-diol metabolites were characterized. Higher activities were observed for benzoates with smaller substituents, predominantly at the 3-position. Elevated activities were also observed in substrates bearing greater partial charge at the C-2 position of the benzoate ring. The regioselectivity of the reaction was directly measured using q1H-NMR and found to have positive correlation with increasing substituent size. These results widen the pool of cis-diol metabolites available for synthetic applications and offer a window into the substrate traits that govern specificity for BZDO.

Coordination Polymers as a Functional Material for the Selective Molecular Recognition of Nitroaromatics and ipso-Hydroxylation of Arylboronic Acids.

We report the synthesis and structural characterization of two coordination polymers (CPs), namely; [{Zn(L)(DMF)4 } ⋅ 2BF4 ]α (1) and [{Cd(L)2 (Cl)2 } ⋅ 2H2 O]α (2) (where L=N2 ,N6 -di(pyridin-4-yl)naphthalene-2,6-dicarboxamide). Crystal packing of 1 reveals the existence of channels running along the b- and c-axis filled by the ligated DMF and lattice anions, respectively. Whereas, crystal packing of 2 reveals that the metallacycles of each 1D chain are intercalating into the groove of adjacent metallacycles resulting in the stacking of 1D loop-chains to form a sheet-like architecture. In addition, both 1 and 2 were exploited as multifunctional materials for the detection of nitroaromatic compounds (NACs) as well as a catalyst in the ipso-hydroxylation of aryl/heteroarylboronic acids. Remarkably, 1 and 2 showed high fluorescence stability in an aqueous medium and displayed a maximum 88% and 97% quenching efficiency for 4-NPH, respectively among all the investigated NACs. The mechanistic investigation of NACs recognition suggested that the fluorescence quenching occurred via electron as well as energy transfer process. Furthermore, the ipso-hydroxylation of aryl/heteroarylboronic acids in presence of 1 and 2 gave up to 99% desired product yield within 15 min in our established protocol. In both cases, 1 and 2 are recyclable upto five cycles without any significant loss in their efficiency.

Improved particle swarm optimized deep convolutional neural network with super-pixel clustering for multiple sclerosis lesion segmentation in brain MRI imaging.

A central nervous system (CNS) disease affecting the insulating myelin sheaths around the brain axons is called multiple sclerosis (MS). In today's world, MS is extensively diagnosed and monitored using the MRI, because of the structural MRI sensitivity in dissemination of white matter lesions with respect to space and time. The main aim of this study is to propose Multiple Sclerosis Lesion Segmentation in Brain MRI imaging using Optimized Deep Convolutional Neural Network and Super-pixel Clustering. Three stages included in the proposed methodology are: (a) preprocessing, (b) segmentation of super-pixel, and (c) classification of super-pixel. In the first stage, image enhancement and skull stripping is done through performing a preprocessing step. In the second stage, the MS lesion and Non-MS lesion regions are segmented through applying SLICO algorithm over each slice of the volume. In the fourth stage, a CNN training and classification is performed using this segmented lesion and non-lesion regions. To handle this complex task, a newly developed Improved Particle Swarm Optimization (IPSO) based optimized convolutional neural network classifier is applied. On clinical MS data, the approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods.