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Density functional theory (DFT) has been a cornerstone in computational science, providing powerful insights into structure-property relationships for molecules and materials through first-principles quantum-mechanical (QM) calculations. However, the advent of atomistic machine learning (ML) is reshaping the landscape by enabling large-scale dynamics simulations and high-throughput screening at DFT-equivalent accuracy with drastically reduced computational cost. Yet, the development of general-purpose atomistic ML models as surrogates for QM calculations faces several challenges, particularly in terms of model capacity, data efficiency, and transferability across chemically diverse systems. This work introduces a novel extension of the polarizable atom interaction neural network (namely, XPaiNN) to address these challenges. Two distinct training strategies have been employed, one direct-learning and the other Δ-ML on top of a semiempirical QM method. These methodologies have been implemented within the same framework, allowing for a detailed comparison of their results. The XPaiNN models, in particular the one using Δ-ML, not only demonstrate competitive performance on standard benchmarks, but also demonstrate the effectiveness against other ML models and QM methods on comprehensive downstream tasks, including noncovalent interactions, reaction energetics, barrier heights, geometry optimization and reaction thermodynamics, etc. This work represents a significant step forward in the pursuit of accurate and efficient atomistic ML models of general-purpose, capable of handling complex chemical systems with transferable accuracy.

Bioluminescence of bacteria is widely applied in biological imaging, environmental toxicant detection, and many other situations. Understanding the spectral tuning mechanism not only helps explain the diversity of colors observed in nature but also provides principles for bioengineering new color variants for practical applications. In this study, time-dependent density functional theory (TD-DFT) and quantum mechanics and molecular mechanics (QM/MM) calculations have been employed to understand the fluorescence spectral tuning mechanism of bacterial luciferase with a focus on the electrostatic effect. The spectrum can be tuned by both a homogeneous dielectric environment and oriented external electric fields (OEEFs). Increasing the solvent polarity leads to a redshift of the fluorescence emission maximum, λ F , accompanied by a substantial increase in density. In contrast, applying an OEEF along the long axis of the isoalloxazine ring ( X -axis) leads to a significant red- or blue-shift in λ F , depending on the direction of the OEEF, yet with much smaller changes in intensity. The effect of polar solvents is directionless, and the red-shifts can be attributed to the larger dipole moment of the S 1 state compared with that of the S 0 state. However, the effect of OEEFs directly correlates with the difference dipole moment between the S 1 and S 0 states, which is directional and is determined by the charge redistribution upon deexcitation. Moreover, the electrostatic effect of bacterial luciferase is in line with the presence of an internal electric field (IEF) pointing in the negative X direction. Finally, the key residues that contribute to this IEF and strategies for modulating the spectrum through site-directed point mutations are discussed.

Glioblastoma (GBM), a prevalent and aggressive brain tumor, poses significant treatment challenges due to its rapid progression and the difficulty in achieving complete surgical resection. The current treatment regime, primarily surgery followed by radiotherapy and chemotherapy, offers limited success, with a five-year survival rate of less than 10 %. For addressing the challenges faced in the treatment of GBM, an approach using a biopolymer implant constructed with dynamic reversible covalent bonds, was designed to achieve controlled and constant-rate release of chemotherapy drug (Temozolomide, TMZ), immune adjuvant (Resiquimod, R848) and checkpoint inhibitor (5-carboxy-8-hydroxyquinoline, IOX1). The safety evaluation demonstrated the biocompatibility of the implants, with no significant inflammatory response or adverse effects on various systemic organs. In vivo antitumor study showed that the local delivery of drug combination via this implant significantly inhibited tumor recurrence of orthotopic GBM. Immune analysis revealed that the combination of the three drugs effectively activated systemic antitumor immune responses and induced memory effects. The synergistic mechanism of the drug combination was further validated by RNA whole sequencing. The innovative approach of combining chemotherapy and immunotherapy in biopolymer immune implants for GBM treatment showed promising and opens new avenues for treating GBM, particularly in addressing postoperative recurrence. STATEMENT OF SIGNIFICANCE: Our research introduces a pioneering approach in treating orthotopic brain glioblastoma (GBM), characterized by inevitable tumor recurrence, poor immune infiltration and the restrictive nature of the blood-brain barrier. To break the impasse of ineffective treatment for GBM, the innovative use of dynamically reversible covalent bonds in polymer matrix ensures the controlled, stable and sustained release of drug combinations of the chemotherapeutic agent temozolomide, immune adjuvants and checkpoint inhibitors, which maintains the optimal concentration in the tumor, overcoming problems associated with conventional chemotherapy such as systemic toxicity and low tumor targeting. Empirical evidence from in vivo experiments on the rat GBM model demonstrates significant outcomes: 90 % tumor size reduction and prolonged survival with over 70 % tumor cure rate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.)

Neuro-symbolic artificial intelligence has garnered considerable attention amid increasing industry demands for high-performance neural networks that are interpretable and adaptable to previously unknown problem domains with minimal reconfiguration. However, implementing neuro-symbolic hardware is challenging due to the complexity in symbolic knowledge representation and calculation. We experimentally demonstrated a memristor-based neuro-fuzzy hardware based on TiN/TaO x /HfO x /TiN chips that is superior to its silicon-based counterpart in terms of throughput and energy efficiency by using array topological structure for knowledge representation and physical laws for computing. Intrinsic memristor variability is fully exploited to increase robustness in knowledge representation. A hybrid in situ training strategy is proposed for error minimizing in training. The hardware adapts easier to a previously unknown environment, achieving ~6.6 times faster convergence and ~6 times lower error than deep learning. The hardware energy efficiency is over two orders of magnitude greater than field-programmable gate arrays. This research greatly extends the capability of memristor-based neuromorphic computing systems in artificial intelligence.

Motivated by comparing the distribution of longitudinal quality of life (QoL) data among different treatment groups from a cancer clinical trial, we propose a semiparametric test statistic for the homogeneity of the distributions of multigroup longitudinal measurements, which are bounded in a closed interval with excess observations taking the boundary values. Our procedure is based on a three-component mixed density ratio model and a composite empirical likelihood for the longitudinal data taking values inside the interval. A nonparametric bootstrap method is applied to calculate the p-value of the proposed test. Simulation studies are conducted to evaluate the proposed procedure, which show that the proposed test is effective in controlling type I errors and more powerful than the procedure which ignores the values on the boundaries. It is also robust to the model mispecification than the parametric test. The proposed procedure is also applied to compare the distributions of the scores of Physical Function subscale and Global Heath Status between the patients randomized to two treatment groups in a cancer clinical trial.

Identification of a subgroup of patients who may be sensitive to a specific treatment is an important problem in precision medicine. This article considers the case where the treatment effect is assessed by longitudinal measurements, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. Recently, a linear mixed threshold regression model has been proposed but it assumes the longitudinal measurements are normally distributed. In many applications, longitudinal measurements, such as quality of life data obtained from answers to questions on a Likert scale, may be restricted in a fixed interval because of the floor and ceiling effects and, therefore, may be skewed. In this article, a threshold longitudinal Tobit quantile regression model is proposed and a computational approach based on alternating direction method of multipliers algorithm is developed for the estimation of parameters in the model. In addition, a random weighting method is employed to estimate the variances of the parameter estimators. The proposed procedures are evaluated through simulation studies and applications to the data from clinical trials., (© 2023 John Wiley & Sons Ltd.)

Adenine DNA glycosylase (MutY) is a monofunctional glycosylase, removing adenines (A) misinserted opposite 8-oxo-7,8-dihydroguanine (OG), a common product of oxidative damage to DNA. Through multiscale calculations, we decipher a detailed adenine excision mechanism of MutY that is consistent with all available experimental data, involving an initial protonation step and two nucleophilic displacement steps. During the first displacement step, N-glycosidic bond cleavage is accompanied by the attack of the carboxylate group of residue Asp144 at the anomeric carbon (C1'), forming a covalent glycosyl-enzyme intermediate to stabilize the fleeting oxocarbenium ion. After departure of the excised base, water nucleophiles can be recruited to displace Asp144, completing the catalytic cycle with retention of stereochemistry at the C1' position. The two displacement reactions are found to mostly involve the movement of the oxocarbenium ion, occurring with large charge reorganization and thus sensitive to the internal electric field (IEF) exerted by the polar protein environment. Intriguingly, we find that the negatively charged carboxylate group is a good nucleophile for the oxocarbenium ion, yet an unactivated water molecule is not, and that the electric field catalysis strategy is used by the enzyme to enable its unique double-displacement reaction mechanism. A strong IEF, pointing toward 5' direction of the substrate sugar ring, greatly facilitates the second displacement reaction at the expense of elevating the barrier of the first one, thereby allowing both reactions to occur. These findings not only increase our understanding of the strategies used by DNA glycosylases to repair DNA lesions, but also have important implications for how internal/external electric field can be applied to modulate chemical reactions.

Many methods have been developed to study nonparametric function-on-function regression models. Nevertheless, there is a lack of model selection approach to the regression function as a functional function with functional covariate inputs. To study interaction effects among these functional covariates, in this article, we first construct a tensor product space of reproducing kernel Hilbert spaces and build an analysis of variance (ANOVA) decomposition of the tensor product space. We then use a model selection method with the L1 criterion to estimate the functional function with functional covariate inputs and detect interaction effects among the functional covariates. The proposed method is evaluated using simulations and stroke rehabilitation data.

The mechanical properties of crystalline materials are influenced by their deformation behavior, which is associated with their microstructural characteristics. Specifically, crystallographic orientation greatly affects the microscale plastic deformation of individual grains. In this study, experiments and finite element simulations of Berkovich nanoindentations are conducted to investigate the impact of crystallographic orientation in polycrystalline copper. A crystal plasticity constitutive model is developed for copper materials, which accurately captures their indentation mechanical response. The results showed that the indentation behavior of polycrystalline copper exhibits a high degree of anisotropy due to significant variation in slip systems for different crystallographic orientations. This results in different mechanical responses of individual grains and distinct material pileup morphologies on the indented surface. Additionally, the study revealed that crystallographic orientation plays a critical role in determining the indentation size effect. These findings have important implications for the design of materials where plasticity is a crucial factor., (© 2023 IOP Publishing Ltd.)

The Wuerzburg bleb classification system (WBCS) is an established tool for evaluating filtering blebs, while anterior segment optical coherence tomography (ASOCT) provides detailed information on inner bleb structure. The present study aimed to investigate the clinical value of ASOCT-assisted WBCS following trabeculectomy (TRAB). The present prospective, observational study included eyes that underwent TRAB. Bleb assessments using the WBCS were based on the image acquired by ASOCT. The WBCS scores were assessed at postoperative week 2 and postoperative month (POM) 1, 2, 3, 6 and 12. The surgical outcomes at 1 year were determined as success or failure. Spearman's analysis explored the correlation of WBCS scores with intraocular pressure (IOP) and surgical outcome. A total of 32 eyes from 32 patients were included in the present study. The WBCS total score significantly correlated with IOP at POM 1, 2, 3, 6 and 12 (P<0.05). For single parameters, microcysts demonstrated a good correlation with IOP at POM 1, 2, 3, 6 and 12 (P<0.05). The WBCS total score correlated well with surgical outcome at POM 2, 3, 6 and 12 (P≤0.005). Microcysts, vascularity and encapsulation significantly correlated with surgical outcomes (P<0.05). The results of the present study suggest that ASOCT-assisted WBCS is a simple and effective measurement system for blebs after TRAB in clinical practice, which correlates well with IOP and surgical outcomes. Blebs with a higher WBCS total score and microcysts score in the early postoperative period, such as at POM 2 and 3, are less likely to have surgical failure in the long term., Competing Interests: The authors declare that they have no competing interests., (Copyright: © Sun et al.)

P450 TleB catalyzes the oxidative cyclization of the dipeptide N -methylvalyl-tryptophanol into indolactam V through selective intramolecular C-H bond amination at the indole C4 position. Understanding its catalytic mechanism is instrumental for the engineering or design of P450-catalyzed C-H amination reactions. Using multiscale computational methods, we show that the reaction proceeds through a diradical pathway, involving a hydrogen atom transfer (HAT) from N1-H to Cpd I, a conformational transformation of the substrate radical species, and a second HAT from N13-H to Cpd II. Intriguingly, the conformational transformation is found to be the key to enabling efficient and selective C-N coupling between N13 and C4 in the subsequent diradical coupling reaction. The underlined conformational transformation is triggered by the first HAT, which proceeds with an energy-demanding indole ring flip and is followed by the facile approach of the N13-H group to Cpd II. Detailed analysis shows that the internal electric field (IEF) from the protein environment plays key roles in the transformation process, which not only provides the driving force but also stabilizes the flipped conformation of the indole radical. Our simulations provide a clear picture of how the P450 enzyme can smartly modulate the selective C-N coupling reaction. The present findings are in line with all available experimental data, highlighting the crucial role of substrate dynamics in controlling this highly valuable reaction.

Background: Patients with low-grade glioma (LGG) have wildly varying average lifespans. However, no effective way exists for identifying LGG patients at high risk. Cuproptosis is a recently described form of cell death associated with the abnormal aggregation of lipid acylated proteins. Few investigations have been conducted on cuproptosis-associated genes and LGG thus far. The purpose of this research is to establish a predictive model for cuproptosis-related genes in order to recognise LGG populations at high risk., Methods: We analyzed 926 LGGs from 2 public datasets, all of which were RNA sequencing datasets. On the basis of immune scores, the LGG population was split into different risk categories with X-tile. LASSO and Cox regressions were employed to filter cuproptosis-associated genes and construct prediction models. The accuracy of the predictive models was measured by using TCGA internal validation set and the CGGA external validation set. In addition, LGG immune cell infiltration was viewed using CIBERSORT and ssGSEA algorithms and correlation analysis was done with cuproptosis-related genes. Finally, immune escape capacity in LGG low- and high-risk groups was evaluated using the TIDE method., Results: The prediction model constructed by four cuproptosis-related genes was used to identify high-risk populations in LGG. It performed well in training and all validation sets (AUC values: 0.915, 0.894, and 0.774). Meanwhile, we found that FDX1 and ATP7A in the four cuproptosis-related genes were positively correlated with immune response, while GCSH and ATP7B were opposite. In addition, the high immune score group had a lower TIDE score, indicating that their immune escape capacity was weak., Conclusion: High-risk individuals in LGG can be reliably identified by the model based on cuproptosis-related genes. Furthermore, cuproptosis is closely related to tumor immune microenvironment, which gives a novel approach to treating LGG., Competing Interests: The author(s) declare(s) that they have no conflicts of interest., (Copyright © 2023 Ping Chen et al.)

More and more individuals are paying attention to the research on the emotional information found in micro-blog comments. TEXTCNN is growing rapidly in the short text space. However, because the training model of TEXTCNN model itself is not very extensible and interpretable, it is difficult to quantify and evaluate the relative importance of features and themselves. At the same time, word embedding can't solve the problem of polysemy at one time. This research suggests a microblog sentiment analysis method based on TEXTCNN and Bayes that addresses this flaw. First, the word embedding vector is obtained by word2vec tool, and based on the word vector, the ELMo word vector integrating contextual features and different semantic features is generated by ELMo model. Second, the local features of ELMo word vector are extracted from multiple angles by using the convolution layer and pooling layer of TEXTCNN model. Finally, the training task of emotion data classification is completed by combining Bayes classifier. On the Stanford Sentiment Classification Corpus data set SST (Stanford Sentiment Classification Corpus Data bank), the experimental findings demonstrate that the model in this paper is compared with TEXTCNN, LSTM, and LSTM-TEXTCNN models. The Accuracy, Precision, Recall, and F1-score of the experimental results of this research have all greatly increased. Their values are respectively 0.9813, 0.9821, 0.9804 and 0.9812, which are superior to other comparison models and can be effectively used for emotional accurate analysis and identification of events in microblog emotion analysis., Competing Interests: Conflict of interestIt is stated by the authors that they have no competing interests., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

The non-heme iron ergothioneine synthase (EgtB) is a sulfoxide synthase that catalyzes oxidative C-S bond formation in the synthesis of ergothioneine, which plays roles against oxidative stress in cells. Despite extensive experimental and computational studies of the catalytic mechanisms of EgtB, the root causes for the selective C-S bond formation remain elusive. Using quantum mechanics/molecular mechanics (QM/MM) calculations, we show herein that a coordination switch of the sulfoxide intermediate is involved in the catalysis of the non-heme iron EgtB. This coordination switch from the S to the O atom is driven by the S/π electrostatic interactions, which efficiently promotes the observed stereoselective C-S bond formation while bypassing cysteine dioxygenation. The present mechanism is in agreement with all available experimental data, including regioselectivity, stereoselectivity and KIE results. This match underscores the critical role of coordination switching in the catalysis of non-heme enzymes., (© 2022 Wiley-VCH GmbH.)

According to the actual situation of gun-launched UAV intercepting "Low-slow-small" target and the specific maneuverability of gun-launched UAV, an enhanced real proportion guidance law (RTPN) guidance interception method is designed. The traditional RTPN method does not consider the saturation overload limit and the capture region of arbitrary maneuvering target. In addition, aiming at the measurement error and the dynamic response delay of the gun-launched UAV during the interception, the EKF data fusion track prediction algorithm is proposed. Simulation results show that the proposed method can effectively solve the problem.

The 2-oxoglutarate (2OG)-dependent non-heme enzyme FtmOx1 catalyzes the endoperoxide biosynthesis of verruculogen. Although several mechanistic studies have been carried out, the catalytic mechanism of FtmOx1 is not well determined owing to the lack of a reliable complex structure of FtmOx1 with fumitremorgin B. Herein we provide the X-ray crystal structure of the ternary complex FtmOx1⋅2OG⋅fumitremorgin B at a resolution of 1.22 Å. Our structures show that the binding of fumitremorgin B induces significant compression of the active pocket and that Y68 is in close proximity to C26 of the substrate. Further MD simulation and QM/MM calculations support a CarC-like mechanism, in which Y68 acts as the H atom donor for quenching the C26-centered substrate radical. Our results are consistent with all available experimental data and highlight the importance of accurate complex structures in the mechanistic study of enzymatic catalysis., (© 2021 Wiley-VCH GmbH.)

Regression models with a functional response and functional covariate have received significant attention recently. While various nonparametric and semiparametric models have been developed, there is an urgent need for model selection and diagnostic methods. In this article, we develop a unified framework for estimation and model selection in nonparametric function-on-function regression. We propose a general nonparametric functional regression model with the model space constructed through smoothing spline analysis of variance (SS ANOVA). The proposed model reduces to some of the existing models when selected components in the SS ANOVA decomposition are eliminated. We propose new estimation procedures under either L 1 or L 2 penalty and show that the combination of the SS ANOVA decomposition and L 1 penalty provides powerful tools for model selection and diagnostics. We establish consistency and convergence rates for estimates of the regression function and each component in its decomposition under both the L 1 and L 2 penalties. Simulation studies and real examples show that the proposed methods perform well. Technical details and additional simulation results are available in online supplementary materials.

Nitrogen heterocycles are key and prevalent motifs in drugs. Evolved variants of cytochrome P450 BM3 (CYP102A1) from Bacillus megaterium employ high-valent oxo-iron(iv) species to catalyze the synthesis of imidazolidine-4-ones via an intramolecular C-H amination. Herein, we use multi-scale simulations, including classical molecular dynamics (MD) simulations, quantum mechanical/molecular mechanical (QM/MM) calculations and QM calculations, to reveal the molecular mechanism of the intramolecular C-H amination of the pyrrolidine derivative of lidocaine bearing cyclic amino moieties catalyzed by the variant RP/FV/EV of P450 BM3 , which bears five mutations compared to wild type. Our calculations show that overall catalysis includes both the enzymatic transformation in P450 and non-enzymatic transformation in water solution. The enzymatic transformation involves the exclusive hydroxylation of the C-H bond of the pyrrolidine derivative of lidocaine, leading to the hydroxylated intermediate, during which the substrate radical would be bypassed. The following dehydration and C-N coupling reactions are found to be much favored in aqueous situation compared to that in the non-polar protein environment. The present findings expand our understanding of the P450-catalyzed C(sp 3 )-H amination reaction., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Cancer vaccines are made from tumor-specific antigens, which are then injected back into the body to activate immune responses for cancer immunotherapy. Despite the high specificity and therapeutic efficiency, the vaccine has huge challenges such as complex preparation process, expensiveness and limited durational effects. Herein, a strategy to develop in situ cancer vaccines by enhancing the immunomodulatory effects for immunogenic cell death (ICD) is presented. First, amorphous iron oxide-packaged oxaliplatin (AIOoxp) nanoprodrugs with a high drug loading efficiency of 12.9% were prepared. By utilizing tumor microenvironment (TME) as an endogenous stimulus, this inorganic nanoprodrug can effectively realize TME-responsive combined treatments of chemotherapy and chemodynamic therapy (CDT), and thus achieve dual and precise ICD induction. Further, in vivo immunopotentiation performances further prove that this enhanced ICD effect is able to efficiently promote the maturity of dendritic cells (DCs), T cell activation and correlative cytokine secretion. Furthermore, the obtained nanoprodrugs not only reduce systemic toxicities of Oxp and achieve T1/T2 magnetic resonance imaging (MRI), but also dramatically inhibit tumor growth and lung metastasis. We believe that the design of in situ cancer vaccines by enhancing the ICD effects will inspire future studies on cancer vaccines.

Long-range electron transfer (ET) in metalloenzymes is a general and fundamental process governing O 2 activation and reduction. Lytic polysaccharide monooxygenases (LPMOs) are key enzymes for the oxidative cleavage of insoluble polysaccharides, but their reduction mechanism by cellobiose dehydrogenase (CDH), one of the most commonly used enzymatic electron donors, via long-range ET is still an enigma. Using multiscale simulations, we reveal that interprotein ET between CDH and LPMO is mediated by the heme propionates of CDH and solvent waters. We also show that oxygen binding to the copper center of LPMO is coupled with the long-range interprotein ET. This process, which is spin-regulated and enhanced by the presence of O 2 , directly leads to LPMO-Cu II -O 2 - , bypassing the formation of the generally assumed LPMO-Cu I species. The uncovered ET mechanism rationalizes experimental observations and might have far-reaching implications for LPMO catalysis as well as the O 2 - or CO-binding-enhanced long-range ET processes in other metalloenzymes., (© 2020 Wiley-VCH GmbH.)

Cytochrome P450 monooxygenases (P450s) are versatile biocatalysts used in natural products biosynthesis, xenobiotic metabolisms, and biotechnologies. In P450s, the electrons required for O 2 activation are supplied by NAD(P)H through stepwise electron transfers (ETs) mediated by redox partners. While much is known about the machinery of the catalytic cycle of P450s, the mechanisms of long-range ET are largely unknown. Very recently, the first crystal structure of full-length P450 TT was solved. This enables us to decipher the interdomain ET mechanism between the [2Fe-2S]-containing ferredoxin and the heme, by use of molecular dynamics simulations. In contrast to the "distal" conformation characterized in the crystal structure where the [2Fe-2S] cluster is ∼28 Å away from heme-Fe, our simulations demonstrated a "proximal" conformation of [2Fe-2S] that is ∼17 Å [and 13.7 Å edge-to-edge] away from heme-Fe, which may enable the interdomain ET. Key residues involved in ET pathways and interdomain complexation were identified, some of which have already been verified by recent mutation studies. The conformational transit of ferredoxin between "distal" and "proximal" was found to be controlled mostly by the long-range electrostatic interactions between the ferredoxin domain and the other two domains. Furthermore, our simulations show that the full-length P450 TT utilizes a flexible ET pathway that resembles either P450 Scc or P450 cam . Thus, this study provides a uniform picture of the ET process between reductase domains and heme domain.

Redox stimulus responsive drug delivery systems have been widely investigated and proved to be promising prospects for efficient cancer therapy due to the abnormal high level of reactive oxygen species and glutathione in tumor microenvironment. Herein, three paclitaxel dimers (named as PTX 2 -R, R = S, Se and Te) bridged with alkyl sulfide, selenide or telluride are synthesized. These dimers can self-assemble into stable uniform nanoparticles (named as PTX 2 -R NPs, R = S, Se and Te) with impressively high drug loading. As expected, sulfur/selenium/tellurium bonds exhibit different redox responsiveness, thereby affecting the drug release and cytotoxicity. Of note, tellurium bridged paclitaxel dimer shows ultra-sensitivity to hydrogen peroxide, which rapidly cleaves into two paclitaxel under the subsequent dithiothreitol stimulation. Our findings provide deep insight into the redox sensitivity of chalcogenide elements and offer the rational design strategies to biologically redox condition for programmed drug release., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Inc. All rights reserved.)

This Perspective discusses oriented external-electric-fields (OEEF), and other electric-field types, as "smart reagents", which enable in principle control over wide-ranging aspects of reactivity and structure. We discuss the potential of OEEFs to control nonredox reactions and impart rate-enhancement and selectivity. An OEEF along the "reaction axis", which is the direction whereby electronic reorganization converts reactants' to products' bonding, will accelerate reactions, control regioselectivity, induce spin-state selectivity, and elicit mechanistic crossovers . Simply flipping the direction of the OEEF will lead to inhibition . Orienting the OEEF off the reaction axis enables control over stereoselectivity, enantioselectivity, and product selectivity . For polar/polarizable reactants, the OEEF itself will act as tweezers , which orient the reactants and drive their reaction. OEEFs also affect bond-dissociation energies and dissociation modes (covalent vs ionic), as well as alteration of molecular geometries and supramolecular aggregation. The "key" to gaining access to this toolbox provided by OEEFs is microscopic control over the alignment between the molecule and the applied field. We discuss the elegant experimental methods which have been used to verify the theoretical predictions and describe various alternative EEF sources and prospects for upscaling OEEF catalysis in solvents. We also demonstrate the numerous ways in which the OEEF effects can be mimicked by use of (designed) local-electric fields (LEFs) , i.e., by embedding charges or dipoles into molecules . LEFs and OEEFs are shown to be equivalent and to obey the same ground rules. Outcomes are exemplified for Diels-Alder cycloadditions, oxidative addition of bonds by transition-metal complexes, H-abstractions by oxo-metal species, ionic cleavage of halogen bonds, methane activation, etc.

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process-such as the active-learning methods found in the machine-learning literature-will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method., (© 2019 The International Biometric Society.)

The manuscript studies the enantioselectivity and stereoselectivity of Diels-Alder (DA) cycloadditions between cyclopentadiene (CPD) and a variety of dienophiles (ranging from halo-ethenes to cyano-ethenes), under oriented external electric fields (OEEFs). Applying OEEFs oriented in the X/ Y directions, perpendicular to the reaction axis ( Z), will achieve complete isomeric and enantiomeric discrimination of the products. Unlike the Z-OEEF, which involves charge-transfer from the diene to the dienophile, and thereby brings about catalysis due to increased intramolecular bonding, an OEEF along X, aligned parallel to the C1-C4 atoms of CPD, will lead to R/ S enantiomeric discrimination by means of intramolecular-bond polarization. A Y field will discriminate endo/exo stereoisomers in a similar mechanism. The XY field-combination will resolve both R/S and endo/exo. The resolution is complete and can be achieved at will by flipping the direction of the field along the X and Y axes. The preconditions for achieving the enantiomeric and isomeric discrimination are discussed and require fixing of the CPD onto a surface. In so doing the chiral discrimination is achieved by dipole-moment selection rules, such that the field filters out one of the enantiomers, which is highly raised in energy by dipole selection. The dependence of the discrimination on the polarity of the dienophiles leads to a predictive trend.

Intracranial aneurysm (IA) is a severe clinical condition of primary concern and currently, there is no effective therapeutic reagent. The present study aimed to investigate the molecular mechanism of IA via bioinformatic analysis. Various gene expression profiles (GSE26969) were downloaded from the Gene Expression Omnibus database, including 3 IA and 3 normal superficial temporal artery samples. Firstly, the limma package in R language was used to identify differentially expressed genes (DEGs; P‑value <0.01 and |log2 FC|≥1). Secondly, the database for annotation, visualization and integrated discovery software was utilized to perform pathway and functional enrichment analyses (false discovery rate ≤0.05). Finally, protein‑protein interaction (PPI) network and sub‑network clustering analyses were performed using the biomolecular interaction network database and ClusterONE software, respectively. Following this, a transcription factor regulatory network was identified from the PPI network. A total of 1,124 DEGs were identified, of which 989 were upregulated and 135 downregulated. Pathway and functional enrichment analyses revealed that the DEGs primarily participated in RNA splicing, functioning of the spliceosome, RNA processing and the mRNA metabolic process. Following PPI network analysis, 1 hepatocyte nuclear factor (HNF) 4A (transcription factor)‑centered regulatory network and 5 DEG‑centered sub‑networks were identified. On analysis of the transcription factor regulatory network, 6 transcription factors (HNF6, HNF4A, E2F4, YY1, H4 and H31T) and a regulatory pathway (HNF6‑HNF4‑E2F4) were identified. The results of the present study suggest that activating transcription factor‑5, Jun proto‑oncogene, activator protein‑1 transcription factor subunit, HNF6, HNF4 and E2F4 may participate in IA progression via vascular smooth muscle cell apoptosis, inflammation, vessel wall remodeling and damage and the tumor necrosis factor‑β signaling pathway. However, further experimental studies are required to validate these predictions.

The present study aimed to elucidate the potential mechanism of cyclin-dependent kinase 2 (CDK2) in neuroblastoma progression and to identify the candidate genes associated with neuroblastoma with CDK2 silencing. The microarray data of GSE16480 were obtained from the gene expression omnibus database. This dataset contained 15 samples: Neuroblastoma cell line IMR32 transfected with CDK2 shRNA at 0, 8, 24, 48 and 72 h (n=3 per group; total=15). Significant clusters associated with differentially expressed genes (DEGs) were identified using fuzzy C‑Means algorithm in the Mfuzz package. Gene ontology and pathway enrichment analysis of DEGs in each cluster were performed, and a protein‑protein interaction (PPI) network was constructed. Additionally, functional annotation of DEGs in clusters was performed for the detection of transcription factors and tumor‑associated genes. A total of 4 clusters with significant change tendency and 1,683 DEGs were identified. The hub nodes of the PPI network constructed by DEGs in Cluster 1, Cluster 2, Cluster 3 and Cluster 4 were MDM2 oncogene, E3 ubiquitin protein ligase (MDM2), cyclin‑dependent kinase 1 (CDK1), proteasome (prosome, macropain) 26S subunit, non‑ATPase, 14 (PSMD14) and translocator protein (18 kDa) (TSPO) respectively. These genes were significantly enriched in the p53 signaling pathway, cell cycle, proteasome and systemic lupus erythematosus pathways. MDM2, CDK1, PSMD14 and TSPO may be key target genes of CDK2. CDK2 may have key functions in neuroblastoma progression by regulating the expression of these genes.

Gene expression data were analysed using bioinformatic tools to demonstrate molecular mechanisms underlying the glioma CpG island methylator phenotype (CIMP). A gene expression data set (accession no. GSE30336) was downloaded from Gene Expression Omnibus, including 36 CIMP+ and 16 CIMP- glioma samples. Differential analysis was performed for CIMP+ vs. CIMP‑ samples using the limma package in R. Functional enrichment analysis was subsequently conducted for differentially expressed genes (DEGs) using Database for Annotation, Visualization and Integration Discovery. Protein‑protein interaction (PPI) networks were constructed for upregulated and downregulated genes with information from STRING. MicroRNAs (miRNAs) targeting DEGs were also predicted using WebGestalt. A total of 439 DEGs were identified, including 214 upregulated and 198 downregulated genes. The upregulated genes were involved in extracellular matrix organisation, defence and immune response, collagen fibril organisation and regulation of cell motion and the downregulated genes in cell adhesion, sensory organ development, regulation of system process, neuron differentiation and membrane organisation. A PPI network containing 134 nodes and 314 edges was constructed from the upregulated genes, whereas a PPI network consisting of 85 nodes and 80 edges was obtained from the downregulated genes. miRNAs regulating upregulated and downregulated genes were predicted, including miRNA‑124a and miRNA‑34a. Numerous key genes associated with glioma CIMP were identified in the present study. These findings may advance the understanding of glioma and facilitate the development of appropriate therapies.

BACKGROUND This study aimed to identify more potential genes and miRNAs associated with the pathogenesis of intracranial aneurysms (IAs). MATERIAL AND METHODS The dataset of GSE36791 (accession number) was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened for in the blood samples from patients with ruptured IAs and controls, followed by functional and pathway enrichment analyses. In addition, gene co-expression network was constructed and significant modules were extracted from the network by WGCNA R package. Screening for miRNAs that could regulate DEGs in the modules was performed and an analysis of regulatory relationships was conducted. RESULTS A total of 304 DEGs (167 up-regulated and 137 down-regulated genes) were screened for in blood samples from patients with ruptured IAs compared with those from controls. Functional enrichment analysis showed that the up-regulated genes were mainly associated with immune response and the down-regulated DEGs were mainly concerned with the structure of ribosome and translation. Besides, six functional modules were significantly identified, including four modules enriched by up-regulated genes and two modules enriched by down-regulated genes. Thereinto, the blue, yellow, and turquoise modules of up-regulated genes were all linked with immune response. Additionally, 16 miRNAs were predicted to regulate DEGs in the three modules associated with immune response, such as hsa-miR-1304, hsa-miR-33b, hsa-miR-125b, and hsa-miR-125a-5p. CONCLUSIONS Several genes and miRNAs (such as miR-1304, miR-33b, IRS2 and KCNJ2) may take part in the pathogenesis of IAs.

Gliomas are serious primary brain tumors. The aim of the present study was to identify potential key genes associated with the progression of gliomas. The GSE31262 gene expression profile data, which included 9 glioblastoma stem cells (GSCs) samples and 5 neural stem cell samples from adult humans, were downloaded from Gene Expression Omnibus (GEO) database. limma package was used to identify differentially expressed genes (DEGs). Based on STRING database and Pearson Correlation Coefficient (PCC), a co-expression network was constructed to comprehensively understand the interactions between DEGs, and function analysis of genes in the network was conducted. Furthermore, the DEGs that were associated with prognosis were analyzed. A total of 431 DEGs were identified, including 98 upregulated DEGs and 333 downregulated DEGs. Genes including PDZ binding kinase, topoisomerase (DNA) II α ( TOP2A ), cyclin dependent kinase ( CDK ) 1, cell division cycle 6 and NIMA related kinase 2 had a relatively high degree in the co-expression network. A set of genes including cyclin D1, CDK1 and CDK2 were significantly enriched in the cell cycle and p53 signaling pathway. Additionally, 69 DEGs were identified as genes involved in glioblastoma prognosis, such as CDK2 and TOP2A . The genes that had a higher degree and were associated with cell cycle and p53 signaling pathway may play pivotal roles in the progress of glioblastoma.

In this work, a glutamic acid linked paclitaxel (PTX) dimer (Glu-PTX 2 ) with high PTX content of 88.9wt% was designed and synthesized. Glu-PTX 2 could self-assemble into nanoparticles (Glu-PTX 2 NPs) in aqueous solution to increase the water solubility of PTX. Glu-PTX 2 NPs were characterized by electron microscopy and dynamic light scattering, exhibiting spherical morphology and favorable structural stability in aqueous media. Glu-PTX 2 NPs could be internalized by cancer cells as revealed by confocal laser scanning microscopy and exert potent cytotoxicity. It is envisaged that Glu-PTX 2 NPs would be an alternative formulation for PTX, and such amino acid linked drug dimers could also be applied to other therapeutic agents., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Guided bone regeneration (GBR) is one such treatment that reconstructs neo-bone tissue by using a barrier membrane to prevent the invasion of soft tissue and to create a space for guiding new bone growth into the bone defect. Herein, we report a novel functionally graded bilayer membrane (FGBM) for GBR application. To fabricate the novel membrane, the composites of poly(lactic-co-glycolic acid) and nano-hydroxyapatite were prepared by phase inversion for the dense layer and by electrospinning for another porous layer, and their corresponding properties were evaluated including surface morphology, mechanics, degradability, cell barrier function, and in vitro osteogenic bioactivity. The results showed that PLGA with 5% nHA in dense layer could meet the requirement of mechanical strength and have excellent barrier function even on condition of post-degradation. Furthermore, PLGA with 30% nHA in porous layer could achieve the good physical and chemical properties. In addition, 30% nHA incorporation would enhance the in vitro mineralization, and have superior capabilities of cell adhesion, proliferation and differentiation compared to other groups. Therefore, the designed FGBM could potentially serve as a barrier for preferential tissue ingrowth and achieve a desirable therapeutic result for bone tissue regeneration.

Porcine circovirus type 2 (PCV2) causes increased mortality and poor growth or weight loss in apparently healthy swine. Therefore, methods to detect PCV2-specific antibodies in swine serum are important for prevention, diagnosis, and control of PCV2-associated diseases (PCVAD). In this study, PCV2 virus-like particles (VLPs) were used to develop a rapid, simple and economical indirect enzyme-linked immunosorbent assay to detect (with high sensitivity) PCV2-specific antibodies in swine serum. The PCV2 capsid protein (Cap) was overexpressed in E. coli after optimizing the cap gene. Subsequently, the soluble Cap was rapidly purified in one step by automated fast protein liquid chromatography (FPLC). The purified PCV2 Cap was shown by transmission electron microscopy and gel filtration chromatography to be capable of self-assembling into VLPs in vitro. Using the purified VLPs as antigens, optimal operating conditions for the VLP ELISA were determined. The concentration of PCV2 VLPs was 1 µg/ml per well, and the dilution factors for swine serum and horseradish peroxidase (HRP)-labeled goat anti-pig antibody were 1:150 and 1:4000, respectively. Out of 241 serum samples tested with this assay, 83.4 % were found to be positive. Importantly, the VLP ELISA had a total coincidence rate of 97.4 % (74/76) compared to an Ingezim PCV2 ELISA IgG assay. In summary, this rapid, inexpensive VLP ELISA has the potential to greatly facilitate large-scale investigations of PCV2-associated serotypes.

Virus-like particles (VLPs) can be used as transfer vehicles carrying foreign proteins or antigen epitopes to produce chimeric VLPs for bivalent or multivalent vaccines. Based on the crystal structure of porcine circovirus type 2 (PCV2) capsid protein (Cap), in addition to alignment of the Cap sequences collected from various isolates of PCV2 and PCV1, we predicted that Loop CD of the PCV2 Cap should tolerate insertion of foreign epitopes, and furthermore that such an insertion could be presented on the surface of PCV2 VLPs. To validate this, the GP5 epitope B of porcine reproductive and respiratory syndrome virus (PRRSV) was inserted into Loop CD of the PCV2 Cap. The 3D structure of the recombinant PCV2 Cap (rCap) was simulated by homology modeling; it appeared that the GP5 epitope B was folded as a relatively independent unit, separated from the PCV2 Cap backbone. Furthermore, based on transmission electron microscopy, the purified PCV2 rCap self-assembled into chimeric VLPs which entered PK-15 cells. In addition, PCV2 chimeric VLPs induced strong humoral (neutralizing antibodies against PCV2 and PRRSV) and cellular immune responses in mice. We concluded that the identified insertion site in the PCV2 Cap had great potential to develop PCV2 VLPs-based bivalent or multivalent vaccines; furthermore, it would also facilitate development of a nano-device to present a functional peptide on the surface of the VLPs that could be used for therapeutic purposes., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Porcine circovirus type 2 (PCV2) is the pivotal pathogen causing porcine circovirus-associated diseases. In this study, 62 PCV2 isolates were identified from seven farms in southern China from 2013 to 2015 and phylogenetic trees were reconstructed based on whole-genome sequences or the cap gene. In this investigation, PCV2b was the main genotype in circulation throughout these farms. Furthermore, an emerging mutant (PCV2b-1C), isolated from PCV2-vaccinated farms, was the predominant strain prevalent on these farms. In addition, we isolated a new cluster that may represent evolution of the virus through recombination of PCV2b-1A/1B and PCV2b-1C. Finally, we discuss evidence that antigenicity and surface structure variation of the capsid resulted from mutation of the C-terminal loop (Loop CT) of the PCV2b-1C Cap in silico.

As medical research and technology advance, there are always new biomarkers found and predictive models proposed for improving the diagnostic performance of diseases. Therefore, in addition to the existing biomarkers and predictive models, how to assess new biomarkers becomes an important research problem. Many classification performance measures, which are usually based on the performance on the whole cut-off values, were applied directly to this type of problems. However, in a medical diagnosis, some cut-off points are more important, such as those points within the range of high specificity. Thus, as the partial area under the ROC curve to the area under ROC curve, we study the partial integrated discriminant improvement (pIDI) for evaluating the predictive ability of a newly added marker at a prespecified range of cut-offs. Theoretical property of estimate of the proposed measure is reported. The performance of this new measure is then compared with that of the partial area under an ROC curve. The numerical results use synthesized are presented, and a liver cancer dataset is used for demonstration purposes., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Porcine circovirus 2 (PCV2) strain 102 belongs to the PCV2b-1C subtype, and its sole structural protein (Cap) exhibits high homology with that of other PCV2b isolates reported in South Korea, China, and the United States. Strain 102 contains a new mutation (R37H) in the domain of the nuclear localization signal (NLS) of the Cap., (Copyright © 2015 Zhu et al.)

Background: MicroRNAs (miRNAs) are a group of small noncoding RNAs that take part in diverse biological processes by suppressing target gene expression. Relatively few miRNAs have been studied in detail, especially miR-503, and hence the biological relevance of majority remains to be uncovered. Whether altered expression of miRNA-503 affects the immunity response to radiotherapy has yet to be addressed., Results: In the present study, we applied ionizing radiation with a dose of either 0.1 Gy or 5 Gy to irradiate U937 cells to confirm CD40 as a miR-503 target, which was identified using a bioimformatics tool. In high dose (5 Gy) ionizing-irradiated U937 cells, expression of miR-503 was up regulated while the expression of CD40 gene was down regulated. Using the transfection of the miR-503 gene into U937 cells and Luciferase assay, we confirmed that miR-503 suppressed the expression of CD40, and was a negtive regulator of CD40., Conclusions: To our knowledge, we are the first to describe involvement of miR-503 in radiobiological effect at a molecular level. This initial finding suggested the evidence that ionizing radiation could alter the expression of miR-503 and its target gene CD40, and may be very important to shed light on a possible mechanism regarding regulation of immune responses to irradiation.

Rather than viewing receiver operating characteristic (ROC) curves directly to compare the performances of diagnostic methods, the whole and the partial areas under the ROC curve (area under the ROC curve [AUC] and partial area under the ROC curve [pAUC]) are 2 of the most popularly used summaries of the curve. Moreover, when high specificity is a prerequisite, as in some medical diagnostics, pAUC is preferable. In this paper, we propose a wrapper-type algorithm to select the best linear combination of markers that has high sensitivity within a confined specificity range. The markers selected by the proposed algorithm are different from those selected by AUC-based algorithms and therefore provide different information for further studies. Most notably, for example, within the given range of specificity, the markers selected by the proposed algorithm always have higher individual sensitivities than those selected by other AUC-based methods. This characteristic makes the proposed method a good addition to existing methods. Without assuming the underlying distributions of markers, we prove that the pAUC obtained with the proposed algorithm is a strongly consistent estimate of the true pAUC and then illustrate its performance with numerical studies using synthesized data and 2 real examples. The results are compared with those obtained by its AUC-based counterpart. We found that the classification performance of the final classifier based on the selected markers is very competitive.

Objective: We studied the antiviral activity of probiotics and possible mechanism thereof., Methods: With hemagglutination in vitro and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) of chicken embryo fibroblast (CEF), the hemagglutination titers and virus inhibition rate were respectively determined to evaluate the impact of probiotics on Newcastle Disease Virus (NDV)., Results: Five probiotics and their metabolites could reduce the viral titer of NDV, but the two pathogenic bacteria and their metabolites could not. These results indicated that probiotics may destruct the structure of NDV directly and this effect was strain-specific. Probiotics could inhibit the replication rate of NDV significantly in a dose-dependent manner (P<0.01). The inhibitory rate increased when the cells were pre-treated with probiotics, which indicated that the probiotics might block NDV adsorbing to the cells. The fact that addition of probiotics and NDV at the same time reduced the cytopathic effect (CPE) of cells suggested that probiotics could destruct the viral structure directly; the lower inhibitory rate of viral replication when cells infected with NDV before addition of probiotics to the cells suggested that the probiotics worked hardly after the cells were infected., Conclusion: Probiotics can not only destruct the virus, but also block the virus infection of the cells and inhibit the viral proliferation in the cells.

By means of "emulsion-electrospinning", both hydrophobic and hydrophilic drugs, paclitaxel (PTX) and doxorubicin hydrochloride (DOX), were successfully loaded into PEG-PLA nanofiber mats to realize multi-drug delivery. The release behaviors of both the drugs from the same fiber mats were ascribed to their solubility properties and distribution status in the fibers. Due to its high hydrophilicity, DOX was easy to diffuse out from the fibers, and its release rate was always faster than that of hydrophobic PTX. Moreover, the release rate of PTX was accelerated by DOX's release from the same drug-loaded fibers. In vitro cytotoxicity against rat Glioma C6 cells indicated that the dual drug combination showed a higher inhibition and apoptosis against C6 cells than a single drug-loaded system, which suggests the promise for multi-drug delivery on combination therapy.

Background and Aim: To screen for serum biomarkers of HBV-related hepatocellular carcinoma (HCC) and HBV-related liver cirrhosis (LC) in an attempt to seek a new method for differential diagnosis of HCC and LC using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) techniques., Methods: Using SELDI-TOF-MS, serum proteins/peptide profiles on the immobilized metal ion affinity capture (IMAC) protein chips were obtained from 29 HCC patients and 30 LC patients. Discriminant analysis was carried out to establish new diagnostic methods using protein/peptide peaks with or without alpha-fetoprotein (AFP)., Results: Forty-five protein/peptide peaks changed much more in the HCC group than they did in the LC group. Discriminant analysis using the Wilcoxon rank-sum test showed high sensitivity and specificity in distinguishing HCC from LC. The most significantly differentiating peak, 3892, offered 69.0% sensitivity, 83.3% specificity and 80% positive predictive value in distinguishing HCC and LC. Interestingly, six HCC patients with negative serum AFP were confirmed by peak 3892. The combination of multi-protein peaks (m/z = 9297, 29 941) with AFP offered an 82.8% sensitivity, 93.3% specificity and 92.3% positive predictive value, which was much better than AFP alone (P = 0.013)., Conclusions: Special proteins/peptides of serum may differentiate HBV-related HCC and HBV-related LC, indicating that SELDI-TOF-MS may be useful to distinguish HCC from LC with the proper discriminant analytical method. SELDI peak 3892 may be a complementary diagnostic marker to positive AFP for HCC and a potential marker for the diagnosis of AFP-negative HCC as well.

Motivation: Protein expression profiling for differences indicative of early cancer holds promise for improving diagnostics. Due to their high dimensionality, statistical analysis of proteomic data from mass spectrometers is challenging in many aspects such as dimension reduction, feature subset selection as well as construction of classification rules. Search of an optimal feature subset, commonly known as the feature subset selection (FSS) problem, is an important step towards disease classification/diagnostics with biomarkers., Methods: We develop a parsimonious threshold-independent feature selection (PTIFS) method based on the concept of area under the curve (AUC) of the receiver operating characteristic (ROC). To reduce computational complexity to a manageable level, we use a sigmoid approximation to the empirical AUC as the criterion function. Starting from an anchor feature, the PTIFS method selects a feature subset through an iterative updating algorithm. Highly correlated features that have similar discriminating power are precluded from being selected simultaneously. The classification rule is then determined from the resulting feature subset., Results: The performance of the proposed approach is investigated by extensive simulation studies, and by applying the method to two mass spectrometry data sets of prostate cancer and of liver cancer. We compare the new approach with the threshold gradient descent regularization (TGDR) method. The results show that our method can achieve comparable performance to that of the TGDR method in terms of disease classification, but with fewer features selected., Availability: Supplementary Material and the PTIFS implementations are available at http://staff.ustc.edu.cn/~ynyang/PTIFS., Supplementary Information: Supplementary data are available at Bioinformatics online.