Integrating Virtual Surgical Planning and 3D-Printed Tools with Iliac Bone Grafts for Orbital and Zygomatic Reconstruction in Hemifacial Microsomia Patients.

Hemifacial Microsomia (HFM) is the second most common congenital craniofacial malformation syndrome, and the complexity of HFM makes its treatment challenging. The present study aimed to introduce a new approach of utilization of virtual surgical planning (VSP) and 3D-printed surgical adjuncts for maxillofacial reconstruction. Five HFM patients were included in this study. All participants were provided with a full VSP, including the design of osteotomy lines, the design and fabrication of 3D-printed cutting guides, fixation plates, and titanium mesh for implantation. With the assistance of 3D-printed cutting guides and fixation plates, the orbital deformities were corrected, and a 3D-printed titanium mesh combined with iliac cancellous bone graft was applied to reconstruct the zygomatic arch. The surgical accuracy, effectiveness, and bone absorption rate were evaluated. All patients completed the entirely digital treatment process without experiencing severe complications. The surgical adjuncts were effective in aligning the movement of the bone segments with the surgical plan, resulting in mean 3D deviations (1.0681 ± 0.15 mm) and maximum 3D deviations (3.1127 ± 0.44 mm). The image fusion results showed that the patients' postoperative position of the maxilla, zygoma, and orbital rim was consistent with the virtual surgical plan, with only a slight increase in the area of bone grafting. The postoperative measurements showed significant improvement in the asymmetry indices of Er (AI of Er: from 17.91 ± 3.732 to 5.427 ± 1.389 mm, p = 0.0001) and FZ (AI of FZ: from 7.581 ± 1.435 to 4.070 ± 1.028 mm, p = 0.0009) points. In addition, the observed bone resorption rate at the 6-month follow-up across the five patients was 45.24% ± 3.13%. In conclusion, the application of VSP and 3D-printed surgical adjuncts demonstrates significant value in enhancing the precision and effectiveness of surgical treatments for HFM. A 3D-printed titanium mesh combined with iliac cancellous bone graft can be considered an ideal alternative for the reconstruction of the zygomatic arch.

An explainable artificial intelligence framework for risk prediction of COPD in smokers.

BACKGROUND: Since the inconspicuous nature of early signs associated with Chronic Obstructive Pulmonary Disease (COPD), individuals often remain unidentified, leading to suboptimal opportunities for timely prevention and treatment. The purpose of this study was to create an explainable artificial intelligence framework combining data preprocessing methods, machine learning methods, and model interpretability methods to identify people at high risk of COPD in the smoking population and to provide a reasonable interpretation of model predictions. METHODS: The data comprised questionnaire information, physical examination data and results of pulmonary function tests before and after bronchodilatation. First, the factorial analysis for mixed data (FAMD), Boruta and NRSBoundary-SMOTE resampling methods were used to solve the missing data, high dimensionality and category imbalance problems. Then, seven classification models (CatBoost, NGBoost, XGBoost, LightGBM, random forest, SVM and logistic regression) were applied to model the risk level, and the best machine learning (ML) model's decisions were explained using the Shapley additive explanations (SHAP) method and partial dependence plot (PDP). RESULTS: In the smoking population, age and 14 other variables were significant factors for predicting COPD. The CatBoost, random forest, and logistic regression models performed reasonably well in unbalanced datasets. CatBoost with NRSBoundary-SMOTE had the best classification performance in balanced datasets when composite indicators (the AUC, F1-score, and G-mean) were used as model comparison criteria. Age, COPD Assessment Test (CAT) score, gross annual income, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), anhelation, respiratory disease, central obesity, use of polluting fuel for household heating, region, use of polluting fuel for household cooking, and wheezing were important factors for predicting COPD in the smoking population. CONCLUSION: This study combined feature screening methods, unbalanced data processing methods, and advanced machine learning methods to enable early identification of COPD risk groups in the smoking population. COPD risk factors in the smoking population were identified using SHAP and PDP, with the goal of providing theoretical support for targeted screening strategies and smoking population self-management strategies.

Three-dimensional printed titanium mesh combined with iliac cancellous bone in the reconstruction of mandibular defects secondary to ameloblastoma resection.

BACKGROUND: The reconstruction of large mandibular defects is a challenge, and free vascularized bone flaps are most commonly used. However, the precision and symmetry of this repair are deficient, and patients have a risk of vascular embolism, flap necrosis, and donor site complications. Therefore, to explore an ideal alternative in mandibular reconstruction with high surgical accuracy and low complications is indispensable. METHODS: Seven patients with recurrent or large-scope ameloblastoma were enrolled in this study. All patients were provided with a fully digital treatment plan, including the design of osteotomy lines, surgical guides, and three-dimensional printed titanium mesh for implantation. With the assistance of surgical guide, ameloblastomas were resected, and custom 3D printed titanium mesh combined with posterior iliac bone harvest was used in mandibular reconstruction. A comparison was made between the discrepant surgical outcomes and the intended surgical plan, as well as the average three-dimensional deviation of the mandible before and after the surgery. At the same time, the resorption rate of the implanted bone was evaluated. RESULTS: All patients completed the fully digital treatment process successfully without severe complications. Image fusion showed that the postoperative contour of the mandible was basically consistent with surgical planning, except for a slight increase in the inferior border of the affected side. The mean three-dimensional deviation of the mandible between the preoperative and postoperative periods was 0.78 ± 0.41 mm. The mean error between the intraoperative bone volume and the digital planning bone volume was 2.44%±2.10%. Furthermore, the bone resorption rates of the harvested graft 6 months later were 32.15%±6.95%. CONCLUSIONS: The use of digital surgical planning and 3D-printed templates can assist surgeons in performing surgery precisely, and the 3D-printed titanium mesh implant can improve the patient's facial symmetry. 3D printed titanium mesh combined with posterior iliac cancellous bone graft can be regarded as an ideal alternative in extensive mandibular reconstruction.

Facile Synthesis of Polymer-Reinforced Silica Aerogel Microspheres as Robust, Hydrophobic and Recyclable Sorbents for Oil Removal from Water.

With the rapid development of industry and the acceleration of urbanization, oil pollution has caused serious damage to water, and its treatment has always been a research hotspot. Compared with traditional adsorption materials, aerogel has the advantages of light weight, large adsorption capacity and high selective adsorption, features that render it ideal as a high-performance sorbent for water treatment. The objective of this research was to develop novel hydrophobic polymer-reinforced silica aerogel microspheres (RSAMs) with water glass as the precursor, aminopropyltriethoxysilane as the modifier, and styrene as the crosslinker for oil removal from water. The effects of drying method and polymerization time on the structure and oil adsorption capacity were investigated. The drying method influenced the microstructure and pore structure in a noteworthy manner, and it also significantly depended on the polymerization time. More crosslinking time led to more volume shrinkage, thus resulting in a larger apparent density, lower pore volume, narrower pore size distribution and more compact network. Notably, the hydrophobicity increased with the increase in crosslinking time. After polymerization for 24 h, the RSAMs possessed the highest water contact angle of 126°. Owing to their excellent hydrophobicity, the RSAMs via supercritical CO2 drying exhibited significant oil and organic liquid adsorption capabilities ranging from 6.3 to 18.6 g/g, higher than their state-of-the-art counterparts. Moreover, their robust mechanical properties ensured excellent reusability and recyclability, allowing for multiple adsorption-desorption cycles without significant degradation in performance. The novel sorbent preparation method is facile and inspiring, and the resulting RSAMs are exceptional in capacity, efficiency, stability and regenerability.

Diabetes mellitus early warning and factor analysis using ensemble Bayesian networks with SMOTE-ENN and Boruta.

Diabetes mellitus (DM) has become the third chronic non-infectious disease affecting patients after tumor, cardiovascular and cerebrovascular diseases, becoming one of the major public health issues worldwide. Detection of early warning risk factors for DM is key to the prevention of DM, which has been the focus of some previous studies. Therefore, from the perspective of residents' self-management and prevention, this study constructed Bayesian networks (BNs) combining feature screening and multiple resampling techniques for DM monitoring data with a class imbalance in Shanxi Province, China, to detect risk factors in chronic disease monitoring programs and predict the risk of DM. First, univariate analysis and Boruta feature selection algorithm were employed to conduct the preliminary screening of all included risk factors. Then, three resampling techniques, SMOTE, Borderline-SMOTE (BL-SMOTE) and SMOTE-ENN, were adopted to deal with data imbalance. Finally, BNs developed by three algorithms (Tabu, Hill-climbing and MMHC) were constructed using the processed data to find the warning factors that strongly correlate with DM. The results showed that the accuracy of DM classification is significantly improved by the BNs constructed by processed data. In particular, the BNs combined with the SMOTE-ENN resampling improved the most, and the BNs constructed by the Tabu algorithm obtained the best classification performance compared with the hill-climbing and MMHC algorithms. The best-performing joint Boruta-SMOTE-ENN-Tabu model showed that the risk factors of DM included family history, age, central obesity, hyperlipidemia, salt reduction, occupation, heart rate, and BMI.

Magnetic Domains and Their Power Spectral Densities in Non-Oriented Electrical Steel after Thermal Compression at Different Rates.

The magnetic domains of non-oriented electrical steel bearing cumulative thermal compressions made by a Gleeble 3500 Thermal System were observed using an atomic force microscope (AFM). The component forces, comprising the magnetic forces between the AFM probe and magnetic domains of the samples, along the freedom direction of the probe, were measured, and they formed the value fluctuation of the magnetic domains. The fluctuations of the magnetic domains were analyzed by examining the power spectral density (PSD) curves. The hysteresis curves of the samples were measured using a highly sensitive magnetic measurement system. An analysis of the magnetic force microscope (MFM) maps suggested that some magnetic domains were compressed into crushed and fragmented shapes, similar to the microstructure of deformed grains. Meanwhile, some were reconstructed within the thermal compressions, like dynamic recrystallization microstructures. Meaningfully, the MFM probe moved and deformed the proximal magnetic domains of tested samples within the region of its weak magnetic field. The peak positions of the magnetic domains with a high deformation rate were shifted and moved during the measuring processes by the weakly polarized probe. Both windward and leeward sides simultaneously expressed a slope towards each co-adjacent valley in the MFM maps and induced a statistical throbbing within a narrow band in the PSD curves. Thus, the MFM scanning mode was also analyzed and improved to obtain accurate MFM maps with low disturbances from the weak magnetic field of the probe. Swapping the order positions of the middle processes in the MFM scanning and adding a gliding step between them could offset the peak skewing of magnetic domains caused by the weakly polarized probe during MFM measurement process without incurring excessive replacement costs. Accumulative compression at a high rate (10 s-1) would crush magnetic domains into irregularly decreasing sizes with messy boundaries. This investigation provides an example of the complete relationships among deformations, magnetic domains, and magnetic properties.

Iron metabolism and ferroptosis in diabetic bone loss: from mechanism to therapy.

Osteoporosis, one of the most serious and common complications of diabetes, has affected the quality of life of a large number of people in recent years. Although there are many studies on the mechanism of diabetic osteoporosis, the information is still limited and there is no consensus. Recently, researchers have proven that osteoporosis induced by diabetes mellitus may be connected to an abnormal iron metabolism and ferroptosis inside cells under high glucose situations. However, there are no comprehensive reviews reported. Understanding these mechanisms has important implications for the development and treatment of diabetic osteoporosis. Therefore, this review elaborates on the changes in bones under high glucose conditions, the consequences of an elevated glucose microenvironment on the associated cells, the impact of high glucose conditions on the iron metabolism of the associated cells, and the signaling pathways of the cells that may contribute to diabetic bone loss in the presence of an abnormal iron metabolism. Lastly, we also elucidate and discuss the therapeutic targets of diabetic bone loss with relevant medications which provides some inspiration for its cure.

The application of a fully digital approach in the treatment of skeletal class III malocclusion: a preliminary study.

BACKGROUND: Skeletal malocclusion patients have facial malformations and occlusal dysfunctions that require orthodontic-orthognathic joint treatment, while the combination treatment takes time and requires close communication between surgeons and orthodontists. Thus, improving the efficiency and effectiveness of the combination treatment is necessary, and it is still a challenge. Now, digital technology provides us with an excellent alternative. Despite the widespread use of digital technology in orthognathic surgery simulation and clear aligner orthodontic therapy, it has not been fully integrated into the combined orthognathic and orthodontic treatment process, and the components remain independent. METHODS: A fully digital approach to seamlessly integrating various parts of the combined treatment through digital technology was investigated in this study in order to achieve an efficient transition. Five patients with skeletal Class III malocclusion were enrolled, and all made fully digital treatment plans at the beginning of actual implementation, which included the design of pre-surgical orthodontic, orthognathic surgery, and post-surgical orthodontic. Then, every aspect of the clinical operation was carried out in accordance with the fully digital routine. After the entire treatment process was completed, the skeleton and dentition discrepancy between virtual planning and the actual result was evaluated. RESULTS: All participants completed the fully digital treatment process, and no complication was observed. The linear deviation of the skeletal anatomy was less than 1 mm, and the angular deviation was less than 1 degree. Except in one case in the lower dentition, the deviation of the virtual dental design from the real alignment was less than 2 mm. Furthermore, with one exception of maxillary anterior-posterior dimension, the linear deviations of the skeleton were not statistically significant. Therefore, the simulation accuracy of the fully digital approach was clinically acceptable. CONCLUSIONS: The digital treatment approach is clinically feasible and has achieved satisfactory results. The discrepancy between virtual design of the entire digital process and actual post-treatment situation was acceptable in clinic. A fully digital approach was proved effective in the treatment of skeletal Class III malocclusion, with which the efficient transition of treatment procedures was realized.

Constitutive BAK/MCL1 complexes predict paclitaxel and S63845 sensitivity of ovarian cancer.

We previously found that preformed complexes of BAK with antiapoptotic BCL2 proteins predict BH3 mimetic sensitivities in lymphohematopoietic cells. These complexes have not previously been examined in solid tumors or in the context of conventional anticancer drugs. Here we show the relative amount of BAK found in preformed complexes with MCL1 or BCLXL varies across ovarian cancer cell lines and patient-derived xenografts (PDXs). Cells bearing BAK/MCL1 complexes were more sensitive to paclitaxel and the MCL1 antagonist S63845. Likewise, PDX models with BAK/MCL1 complexes were more likely to respond to paclitaxel. Mechanistically, BIM induced by low paclitaxel concentrations interacted preferentially with MCL1 and displaced MCL1-bound BAK. Further studies indicated that cells with preformed BAK/MCL1 complexes were sensitive to the paclitaxel/S63845 combination, while cells without BAK/MCL1 complexes were not. Our study suggested that the assessment of BAK/MCL1 complexes might be useful for predicting response to paclitaxel alone or in combination with BH3 mimetics.

Protein Palmitoylation Regulates Cell Survival by Modulating XBP1 Activity in Glioblastoma Multiforme.

Glioblastoma multiforme (GBM) almost invariably acquires an invasive phenotype, resulting in limited therapeutic options. Protein palmitoylation markedly affects tumorigenesis and malignant progression in GBM. The role of protein palmitoylation in GBM, however, has not been systematically reported. This study aimed to investigate the effect of protein palmitoylation on GBM cell survival and the cell cycle. In this study, most palmitoyltransferases were upregulated in GBM and its cell lines, and protein palmitoylation participated in signaling pathways controlling cell survival and the GBM cell cycle. Inhibition of protein palmitoylation with substrate-analog inhibitors, that is, 2-bromopalmitate, cerulenin, and tunicamycin, induced G2 cell cycle arrest and cell death in GBM cells through enhanced endoplasmic reticulum (ER) stress. These effects are primarily attributed to the palmitoylation inhibitors activating pro-apoptotic pathways and ER stress signals. Further analysis revealed was the accumulation of SUMOylated XBP1 (X-box binding protein 1) and its transcriptional repression, along with a reduction in XBP1 palmitoylation. Taken together, the present results indicate that protein palmitoylation plays an important role in the survival of GBM cells, further providing a potential therapeutic strategy for GBM.

Molecular subtyping of glioblastoma based on immune-related genes for prognosis.

Glioblastoma (GBM) is associated with an increasing mortality and morbidity and is considered as an aggressive brain tumor. Recently, extensive studies have been carried out to examine the molecular biology of GBM, and the progression of GBM has been suggested to be correlated with the tumor immunophenotype in a variety of studies. Samples in the current study were extracted from the ImmPort and TCGA databases to identify immune-related genes affecting GBM prognosis. A total of 92 immune-related genes displaying a significant correlation with prognosis were mined, and a shrinkage estimate was conducted on them. Among them, the 14 most representative genes showed a marked correlation with patient prognosis, and LASSO and stepwise regression analysis was carried out to further identify the genes for the construction of a predictive GBM prognosis model. Then, samples in training and test cohorts were incorporated into the model and divided to evaluate the efficiency, stability, and accuracy of the model to predict and classify the prognosis of patients and to identify the relevant immune features according to the median value of RiskScore (namely, Risk-H and Risk-L). In addition, the constructed model was able to instruct clinicians in diagnosis and prognosis prediction for various immunophenotypes.

Supervillin promotes tumor angiogenesis in liver cancer.

Tumor angiogenesis is a hallmark of liver cancer and is necessary for tumor growth and progression. Supervillin (SVIL) is highly expressed and implicated in several malignant processes of liver cancer. However, the functional relationships between SVIL and tumor angiogenesis in liver cancer have not yet been fully elucidated. The present study was based on bioinformatics analysis, patient tissue sample detection, three­dimensional simulated blood vessel formation, a series of cytological experiments and mouse models. The results demonstrated the important role of SVIL in the progression of malignant liver cancer and tumor angiogenesis, both in terms of vasculogenic mimicry (VM) and endothelium­dependent vessel (EDV) development. SVIL knockdown inhibited VM formation and induced tumor cell apoptosis via the VEGF­p38 signaling axis and through various VM­associated transcriptional factors, including vascular endothelial­cadherin, matrix metalloproteinase 9/12 and migration­inducing protein 7. SVIL may therefore be considered a potential tumor vascular biomarker and a promising therapeutic target for patients with liver cancer.

Metabolism of bioconjugate therapeutics: why, when, and how?

Bioconjugation of therapeutic agents has been used as a selective drug delivery platform for many therapeutic areas. Bioconjugates are prepared by the covalent linkage of active compounds (small or large molecule) to a carrier molecule (lipids, proteins, peptides, carbohydrates, and polymers) through a chemical linker. The linkage of the active component to a carrier molecule enhances the therapeutic window through a targeted delivery and by reducing toxicity. Bioconjugates also possess improved pharmacokinetic properties such as a long half-life, increased stability, and cleavage by intracellular enzymes/environment. However, premature cleavage of the bioconjugates and the resulting metabolites/catabolites may produce undesirable toxic effects and, hence, it is critical to understand cleavage mechanisms, metabolism of bioconjugates, and translatability to human in the discovery stages. This article provides a comprehensive overview of linker cleavage pathways and catabolism/metabolism of antibody-drug conjugates, glycoconjugates, polymer-drug conjugates, lipid-drug conjugates, folate-targeted small molecule-drug conjugates, and drug-drug conjugates.

Activation of JNK and p38 MAPK Mediated by ZDHHC17 Drives Glioblastoma Multiforme Development and Malignant Progression.

Rationale: Glioblastoma multiforme (GBM) almost invariably gain invasive phenotype with limited therapeutic strategy and ill-defined mechanism. By studying the aberrant expression landscape of gliomas, we find significant up-regulation of p-MAPK level in GBM and a potent independent prognostic marker for overall survival. DHHC family was generally expressed in glioma and closely related to the activation of MAPK signaling pathway, but its role and clinical significance in GBM development and malignant progression are yet to be determined. Method: Bioinformatics analysis, western blotting and immunohistochemistry (IHC) were performed to detect the expression of ZDHHC17 in GBM. The biological function of ZDHHC17 was demonstrated by a series of in vitro and in vivo experiments. Pharmacological treatment, flow cytometry, Transwell migration assay, Co- Immunoprecipitation and GST pulldown were carried out to demonstrate the potential mechanisms of ZDHHC17. Results: ZDHHC17 is up-regulated and coordinated with MAPK activation in GBM. Mechanistically, ZDHHC17 interacts with MAP2K4 and p38/JNK to build a signaling module for MAPK activation and malignant progression. Notably, the ZDHHC17-MAP2K4-JNK/p38 signaling module contributes to GBM development and malignant progression by promoting GBM cell tumorigenicity and glioma stem cell (GSC) self-renewal. Moreover, we identify a small molecule, genistein, as a specific inhibitor to disrupt ZDHHC17-MAP2K4 complex formation for GBM cell proliferation and GSC self-renewal. Moreover, genistein, identified herein as a lead candidate for ZDHHC17-MAP2K4 inhibition, demonstrated potential therapeutic effect in patients with ZDHHC17-expressing GBM. Conclusions: Our study identified disruption of a previously unrecognized signaling module as a target strategy for GBM treatment, and provided direct evidence of the efficacy of its inhibition in glioma using a specific inhibitor.

Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns.

DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.

Systematic Profiling of Alternative mRNA Splicing Signature for Predicting Glioblastoma Prognosis.

Emerging evidence suggests that alternative splicing (AS) is modified in cancer and is associated with cancer progression. Systematic analysis of AS signature in glioblastoma (GBM) is lacking and is greatly needed. We profiled genome-wide AS events in 498 GBM patients in TCGA using RNA-seq data, and splicing network and prognostic predictor were built by integrated bioinformatics analysis. Among 45,610 AS events in 10,434 genes, we detected 1,829 AS events in 1,311 genes, and 1,667 AS events in 1,146 genes that were significantly associated with overall survival and disease-free survival of GBM patients, respectively. Five potential feature genes, S100A4, ECE2, CAST, ASPH, and LY6K, were discovered after network mining as well as correlation analysis between AS and gene expression, most of which were related to carcinogenesis and development. Multivariate survival model analysis indicated that these five feature genes could classify the prognosis at AS event and gene expression level. This report opens up a new avenue for exploration of the pathogenesis of GBM through AS, thus more precisely guiding clinical treatment and prognosis judgment.

Specific Glioma Prognostic Subtype Distinctions Based on DNA Methylation Patterns.

DNA methylation is an important regulator of gene expression and may provide an important basis for effective glioma diagnosis and therapy. Here, we explored specific prognosis subtypes based on DNA methylation status using 653 gliomas from The Cancer Genome Atlas (TCGA) database. Five subgroups were distinguished by consensus clustering using 11,637 cytosines preceding a guanosine (CpGs) that significantly influenced survival. The specific DNA methylation patterns were correlated with age, tumor stage, and prognosis. Additionally, weighted gene co-expression network analysis (WGCNA) analysis of CpG sites revealed that 11 of them could distinguish the samples into high- and low-methylation groups and could classify the prognostic information of samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained from the test set and 12 glioma patients. Moreover, in vitro experiments revealed an inverse relationship between methylation level and migration ability or insensitivity to temozolomide (or radiotherapy) of glioma cells based on the final prognostic predictor. Thus, these results suggested that the model constructed in this study could provide guidance for clinicians regarding the prognosis of various epigenetic subtypes.

A Practical Perspective on the Evaluation of Small Molecule CNS Penetration in Drug Discovery.

The separation of the brain from blood by the blood-brain barrier and the bloodcerebrospinal fluid (CSF) barrier poses unique challenges for the discovery and development of drugs targeting the central nervous system (CNS). This review will describe the role of transporters in CNS penetration and examine the relationship between unbound brain (Cu-brain) and unbound plasma (Cu-plasma) or CSF (CCSF) concentration. Published data demonstrate that the relationship between Cu-brain and Cu-plasma or CCSF can be affected by transporter status and passive permeability of a drug and CCSF may not be a reliable surrogate for CNS penetration. Indeed, CCSF usually over-estimates Cu-brain for efflux substrates and it provides no additional value over Cu-plasma as the surrogate of Cu-brain for highly permeable non-efflux substrates. A strategy described here for the evaluation of CNS penetration is to use in vitro permeability, P-glycoprotein (Pgp) and breast cancer resistance protein efflux assays and Cu-brain/Cu-plasma in preclinical species. Cu-plasma should be used as the surrogate of Cu-brain for highly permeable non-efflux substrates with no evidence of impaired distribution into the brain. When drug penetration into the brain is impaired, we recommend using (total brain concentration * unbound fraction in the brain) as Cu-brain in preclinical species or Cu-plasma/in vitro Pgp efflux ratio if Pgp is the major limiting mechanism for brain penetration.

DHHC protein family targets different subsets of glioma stem cells in specific niches.

BACKGROUND: Glioblastomas (GBM) comprise different subsets that exhibit marked heterogeneity and plasticity, leading to a lack of success of genomic profiling in guiding the development of precision medicine approaches against these tumors. Accordingly, there is an urgent need to investigate the regulatory mechanisms for different GBM subsets and identify novel biomarkers and therapeutic targets relevant in the context of GBM-specific niches. The DHHC family of proteins is associated tightly with the malignant development and progression of gliomas. However, the role of these proteins in the plasticity of GBM subsets remains unclear. METHODS: This study utilized human glioma proneural or mesenchymal stem cells as indicated. The effects of DHHC proteins on different GBM subsets were investigated through in vitro and in vivo assays (i.e., colony formation assay, flow cytometry assay, double immunofluorescence, western blot, and xenograft model). Western blot, co-immunoprecipitation, and liquid chromatograph mass spectrometer-mass spectrometry assays were used to detect the protein complexes of ZDHHC18 and ZDHHC23 in various GBM subtypes, and explore the mechanism of DHHC proteins in targeting different subsets of GSCs in specific niches. RESULTS: ZDHHC18 and ZDHHC23 could target the glioma stem cells of different GBM subsets in the context of their specific niches and regulate the cellular plasticity of these subtypes. Moreover, mechanistic investigations revealed that ZDHHC18 and ZDHHC23 competitively interact with a BMI1 E3 ligase, RNF144A, to regulate the polyubiquitination and accumulation of BMI1. These events contributed to the transition of glioma stem cells in GBM and cell survival under the stressful tumor microenvironment. CONCLUSIONS: Our work highlights the role of DHHC proteins in the plasticity of GBM subsets and reveals that BMI1 represents a potential therapeutic target for human gliomas.