Chinese self-report version of biological rhythms interview for assessment in neuropsychiatry (C-BRIAN-SR) - psychometric properties and prospective follow-up in patients with non-seasonal depression.

This study examined the psychometric properties and longitudinal changes of the self-reporting Traditional Chinese version of Biological Rhythms Interview for Assessment in Neuropsychiatry (C-BRIAN-SR) among healthy controls (HC) and patients with major depressive episode (MDE). Eighty patients with a current MDE and 80 HC were recruited. Assessments were repeated after two weeks in HC, and upon the discharge of MDE patients to examine the prospective changes upon remission of depression. The C-BRIAN-SR score was significantly higher in the MDE than HC group. The concurrent validity was supported by a positive correlation between scores of C-BRIAN-SR, Insomnia Severity Index and the Hospital Anxiety Depression Scale. C-BRIAN-SR negatively correlated MEQ in the MDE group (r = .30, p = 0.009), suggesting higher rhythm disturbances were associated with a tendency toward eveningness. A moderate test-retest reliability was found (r = .61, p < 0.001). A cut-off of 38.5 distinguished MDE subjects from HC with 82.9% of sensitivity and 81.0% of specificity. C-BRIAN-SR score normalized in remitted MDE patients but remained higher in the non-remitted. The C-BRIAN-SR is a valid and reliable scale for measuring the biological rhythms and may assist in the screening of patients with MDE.

Network Bursts in 3D Neuron Clusters Cultured on Microcontact-Printed Substrates.

Microcontact printing (CP) is widely used to guide neurons to form 2D networks for neuroscience research. However, it is still difficult to establish 3D neuronal cultures on the CP substrate even though 3D neuronal structures are able to recapitulate critical aspects of native tissue. Here, we demonstrate that the reduced cell-substrate adhesion caused by the CP substrate could conveniently facilitate the aggregate formation of large-scale 3D neuron cluster networks. Furthermore, based on the quantitative analysis of the calcium activity of the resulting cluster networks, the effect of cell seeding density and local restriction of the CP substrate on network dynamics was investigated in detail. The results revealed that cell aggregation degree, rather than cell number, could take on the main role of the generation of synchronized network-wide calcium oscillation (network bursts) in the 3D neuron cluster networks. This finding may provide new insights for easy and cell-saving construction of in vitro 3D pathological models of epilepsy, and into deciphering the onset and evolution of network bursts in developmental nerve systems.

A life-threatening bleeding prediction model for immune thrombocytopenia based on personalized machine learning: a nationwide prospective cohort study.

Rare but critical bleeding events in primary immune thrombocytopenia (ITP) present life-threatening complications in patients with ITP, which severely affect their prognosis, quality of life, and treatment decisions. Although several studies have investigated the risk factors related to critical bleeding in ITP, large sample size data, consistent definitions, large-scale multicenter findings, and prediction models for critical bleeding events in patients with ITP are unavailable. For the first time, in this study, we applied the newly proposed critical ITP bleeding criteria by the International Society on Thrombosis and Hemostasis for large sample size data and developed the first machine learning (ML)-based online application for predict critical ITP bleeding. In this research, we developed and externally tested an ML-based model for determining the risk of critical bleeding events in patients with ITP using large multicenter data across China. Retrospective data from 8 medical centers across the country were obtained for model development and prospectively tested in 39 medical centers across the country over a year. This system exhibited good predictive capabilities for training, validation, and test datasets. This convenient web-based tool based on a novel algorithm can rapidly identify the bleeding risk profile of patients with ITP and facilitate clinical decision-making and reduce the occurrence of adversities.

Degradation of Levofloxacin by a green zero-valent iron-loaded carbon composite activating peroxydisulfate system: Reactivity, products and mechanism.

In this study, a green zero-valent iron-loaded carbon composite (ZVI-SCG) was synthesized using coffee grounds and FeCl3 solution through two-steps method, and the synthesized ZVI-SCG was used in the activation of peroxydisulfate (PDS) to degrade Levofloxacin (LEX). Results revealed that ZVI-SCG exhibited a great potential for LEX removal by adsorption and catalytic degradation in the ZVI-SCG/PDS system, and 99% of LEX was removed in the ZVI-SCG/PDS system within 60 min. ZVI-SCG/PDS system showed a high reactivity toward LEX degradation under realistic environmental conditions. Also, the ZVI-SCG/PDS system could effectively degrade several quinolone antibiotics including gatifloxacin, ciprofloxacin and LEX in single and simultaneous removal modes. A potential reaction mechanism of LEX degradation by ZVI-SCG/PDS system was proposed, SO4•-, HO•, O2•- and 1O2 involved in radical and non-radical pathways took part in catalytic degradation of LEX by ZVI-SCG/PDS system, but HO• might be the main reactive species for LEX degradation. The possible degradation pathway of LEX was also proposed based on the identified ten intermediate products, LEX degradation was successfully achieved through decarboxylation, opening ring and hydroxylation processes. The potential toxicity of LEX and its oxidation products decreased significantly after treatment. This study provides a promising strategy of water treatment for the antibiotics-containing wastewater.

Development and validation of an interpretable machine learning model-Predicting mild cognitive impairment in a high-risk stroke population.

Background: Mild cognitive impairment (MCI) is considered a preclinical stage of Alzheimer's disease (AD). People with MCI have a higher risk of developing dementia than healthy people. As one of the risk factors for MCI, stroke has been actively treated and intervened. Therefore, selecting the high-risk population of stroke as the research object and discovering the risk factors of MCI as early as possible can prevent the occurrence of MCI more effectively. Methods: The Boruta algorithm was used to screen variables, and eight machine learning models were established and evaluated. The best performing models were used to assess variable importance and build an online risk calculator. Shapley additive explanation is used to explain the model. Results: A total of 199 patients were included in the study, 99 of whom were male. Transient ischemic attack (TIA), homocysteine, education, hematocrit (HCT), diabetes, hemoglobin, red blood cells (RBC), hypertension, prothrombin time (PT) were selected by Boruta algorithm. Logistic regression (AUC = 0.8595) was the best model for predicting MCI in high-risk groups of stroke, followed by elastic network (ENET) (AUC = 0.8312), multilayer perceptron (MLP) (AUC = 0.7908), extreme gradient boosting (XGBoost) (AUC = 0.7691), and support vector machine (SVM) (AUC = 0.7527), random forest (RF) (AUC = 0.7451), K-nearest neighbors (KNN) (AUC = 0.7380), decision tree (DT) (AUC = 0.6972). The importance of variables suggests that TIA, diabetes, education, and hypertension are the top four variables of importance. Conclusion: Transient ischemic attack (TIA), diabetes, education, and hypertension are the most important risk factors for MCI in high-risk groups of stroke, and early intervention should be performed to reduce the occurrence of MCI.

YAP1 as a Novel Negative Biomarker of Immune Checkpoint Inhibitors for EGFR-Mutant Non-Small-Cell Lung Cancer.

Background: Immune checkpoint inhibitors (ICIs) have become a standard care in non-small-cell lung cancer (NSCLC). However, its application to epidermal growth factor receptor (EGFR)-mutant NSCLC patients is confronted with drug resistance. This study aimed to clarify the potential role of Yes1-associated transcriptional regulator (YAP1) in ICIs treatment for EGFR-mutant NSCLC population. Methods: All the clinical data of NSCLC were downloaded from Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) for GSE11969 and GSE72094. Based on YAP1 expression, all the NSCLC patients including the EGFR-mutant and EGFR-wildtype (WT) patients were divided into two groups, YAP1_High and YAP1_Low. Using cBioPortal, genetic alterations were analyzed for identification of immunogenicity in EGFR-mutant NSCLC. MR analysis was used to analyze the hub gene of EGFR. The infiltration of immune cells and the expression of the identified tumor-associated antigens were identified with TIMER. By graph learning-based dimensionality reduction analysis, the immune landscape was visualized. Moreover, survival analysis was performed to verify the predictive value of YAP1 in ICIs treatment for EGFR-mutant NSCLC population using Ren's research data (NCT03513666). Results: YAP1 was a poor prognostic factor of EGFR-mutant NSCLC population rather than lung adenocarcinoma (LUAD) patients. MR analysis revealed that the EGFR gene regulated YAP1 expression. YAP1 was identified as a hub gene closely associated with immunosuppressive microenvironment and poor prognosis in EGFR-mutant NSCLC population in TCGA LUAD. Tumors with YAP1_High showed an immune-"cold" and immunosuppressive phenotype, whereas those with YAP1_Low demonstrated an immune-"hot" and immunoactive phenotype. More importantly, it was verified that YAP1_High subpopulation had a significantly shorter progression-free survival (PFS) and overall survival (OS) after ICIs treatment in EGFR-mutant NSCLC patients in the clinical trial. Conclusions: YAP1 mediates immunosuppressive microenvironment and poor prognosis in EGFR-mutant NSCLC population. YAP1 is a novel negative biomarker of ICIs treatment in EGFR-mutant NSCLC population. Clinical Trials. This trial is registered with NCT03513666.

Correlation of preclinical and clinical biomarkers with efficacy and toxicity of cancer immunotherapy.

Immune checkpoint inhibitors (ICIs) have revealed significant clinical values in different solid tumors and hematological malignancy, changing the landscape for the treatment of multiple types of cancer. However, only a subpopulation of patients has obvious tumor response and long-term survival after ICIs treatment, and many patients may experience other undesirable clinical features. Therefore, biomarkers are critical for patients to choose exact optimum therapy. Here, we reviewed existing preclinical and clinical biomarkers of immunotherapeutic efficacy and immune-related adverse events (irAEs). Based on efficacy prediction, pseudoprogression, hyperprogressive disease, or irAEs, these biomarkers were divided into cancer cell-derived biomarkers, tumor microenvironment-derived biomarkers, host-derived biomarkers, peripheral blood biomarkers, and multi-modal model and artificial intelligence assessment-based biomarkers. Furthermore, we describe the relation between ICIs efficacy and irAEs. This review provides the overall perspective of biomarkers of immunotherapeutic outcome and irAEs prediction during ICIs treatment.

pan-ECM: live brain extracellular matrix imaging with protein-reactive dye.

The brain extracellular matrix (ECM), consisting of proteins and glycosaminoglycans, is a critical scaffold in the development, homeostasis, and disorders of the central nervous system (CNS) and undergoes remodeling in response to environmental cues. Live imaging of brain ECM structure represents a native view of the brain ECM but, until now, remains challenging due to the lack of a robust fluorescent labeling approach. Here, we developed a pan-ECM method for labeling the entire (Greek: pan) brain ECM network by screening and delivering a protein-reactive dye into the brain. pan-ECM enables imaging of ECM compartments in live brain tissue, including the interstitial matrix, basement membrane (BM), and perineuronal nets (PNNs), and even the ECM in glioblastoma and stroke mouse brains. This approach provides access to the structure and dynamics of the ECM and enhances our understanding of the complexities of the brain ECM and its contribution to brain health and disease.

An Overview of In Vitro Biological Neural Networks for Robot Intelligence.

In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot control, etc. This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems, with a particular focus on those related to robot intelligence. In this work, we first introduce the necessary biological background to understand the 2 characteristics of the BNNs: nonlinear computing capacity and network plasticity. Then, we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects: from robots to BNNs and from BNNs to robots. Next, we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity (computing capacity-dependent) or depend also on the network plasticity (network plasticity-dependent), which are then expounded respectively, with a focus on those related to the realization of robot intelligence. Finally, the development trends and challenges of the BNN-based neurorobotic systems are discussed.

Differences in urban heat island and its driving factors between central and new urban areas of Wuhan, China.

Urban heat island (UHI) is one of the important effects of urbanization on built environment. Land surface temperature data was taken from moderate-resolution imaging spectroradiometer (MODIS) to investigate the long-term spatiotemporal patterns of UHI in Wuhan during 2001~2018 and, the UHI intensity changes of built-up land in 13 administrative regions in Wuhan were analyzed. Furthermore, 34 spatial error models and 34 ordinary least squares models were established and compared. Spatial error models showed good fitting effect, which were used to determine the influence of normalized difference vegetation index (NDVI), normalized difference building index (NDBI), and social-economic factors (population and nighttime light) on UHI intensity in central urban area and new urban area. The explanatory power changes of these four indicators during 2001~2018 were explored as well. The average UHI intensity in 2014~2018 has increased by about 0.45 °C compared to that in 2001~2005. NDBI is the most dominant factor contributing to the increase in temperature. The impact of NDVI on UHI intensity changes from negative to positive, and the impact of NDBI on UHI intensity in central urban area is weakened during 2001-2018. Social-economic factors have a greater impact on new urban area than on central urban area. These findings show the effects and the explanatory power changes of driving factors during 18 years, which can provide a better understanding of the formation and development of UHI and support for the future urban planning of Wuhan.

Correction to: Decreased sustained attention, processing speed and verbal learning memory in patients with insomnia in Chinese young and middle-aged adults: a cross-sectional study.

[This corrects the article DOI: 10.1007/s41105-020-00262-0.].

A Stretching Force Control-Based Cyclic Loading Method for the Evaluation of Mechanical Properties of Gelation Methacrylate (GelMA) Microfibers.

Microfluidic spun gelation mechacrylate (GelMA) microfiber has been widely utilized as a promising bioink for 3D bioprinting. However, its weak and easily tuned mechanical properties are still difficult to precisely evaluate, due to the lack of an effective stretching method. In this paper, we propose a force-control-based cyclic loading method for rapidly evaluating the elastic modulus: the E of the microfibers with different GelMA concentrations. A two-tube manipulation system is used to stretch microfiber with a non-destructive process. Based on the model reference adaptive control strategy, the stress response can be fitted into a sinusoidal wave when a small sinusoidal strain is automatically applied onto the microfiber. Afterwards, the maximum tensile stress and tensile stain is obtained to determine the E. Moreover, different stress amplitudes and frequencies are applied to form different stress-strain loops with almost same E. Compared with a frequently-used constant force loading method, the proposed method shows an obvious advantage in measurement accuracy, especially for low-concentration GelMA microfiber. Furthermore, the reasonableness of the measured E for different GelMA concentrations is confirmed by 3D cell culture experiments, and the results show the proposed method has great application potential to investigate the interaction between cell and fibrous bioink substrate.

A clamp-free micro-stretching system for evaluating the viscoelastic response of cell-laden microfibers.

Viscoelastic hydrogel microfibers have extensive applications in tissue engineering and regenerative medicine, however, their viscoelasticity is still difficult to be directly characterized because microfiber-specific measuring system is lacking for quantitative studies. In this paper, we develop a two-probe micro-stretching system to quantitatively investigate viscoelasticity of the microfiber by evaluating the storage and loss modulus: E' and E″. A liquid bridge-based fixation method enables single microfiber to be easily fixed to be stably stretched by a two-probe actuator. Afterward, multi-frequency stretching force loading is automatically implemented based on real-time force control, and the resulting stress and strain in the frequency spectrum are measured to evaluate the E' and E″ of pure GelMA, alginate-GelMA composite and GelMA core-alginate shell microfibers. The measured E' and E″ are verified by the response of NIH/3T3 fibroblast cells to the composite microfibers with different alginate concentrations. Moreover, benefiting from the low-damaged stretching process, our system can also detect the difference of the E' and E″ between two cellular processes including growth and differentiation of the aligned mesenchymal stem cells in the same one core-shell microfiber. These results all show that our proposed system provides a valuable reference tool for biomaterials design, the study of cell-matrix interaction and disease etiology from the perspective of mechanics.

The PARP1 Inhibitor Niraparib Represses DNA Damage Repair and Synergizes with Temozolomide for Antimyeloma Effects.

Purpose: Poly(ADP-ribose) polymerase 1 (PARP1) is necessary for single-strand break (SSB) repair by sensing DNA breaks and facilitating DNA repair through poly ADP-ribosylation of several DNA-binding and repair proteins. Inhibition of PARP1 results in collapsed DNA replication fork and double-strand breaks (DSBs). Accumulation of DSBs goes beyond the capacity of DNA repair response, ultimately resulting in cell death. This work is aimed at assessing the synergistic effects of the DNA-damaging agent temozolomide (TMZ) and the PARP inhibitor niraparib (Nira) in human multiple myeloma (MM) cells. Materials and Methods: MM RPMI8226 and NCI-H929 cells were administered TMZ and/or Nira for 48 hours. CCK-8 was utilized for cell viability assessment. Cell proliferation and apoptosis were detected flow-cytometrically. Immunofluorescence was performed for detecting γH2A.X expression. Soft-agar colony formation assay was applied to evaluate the antiproliferative effect. The amounts of related proteins were obtained by immunoblot. The combination index was calculated with the CompuSyn software. A human plasmacytoma xenograft model was established to assess the anti-MM effects in vivo. The anti-MM activities of TMZ and/or Nira were evaluated by H&E staining, IHC, and the TUNEL assay. Results: The results demonstrated that cotreatment with TMZ and Nira promoted DNA damage, cell cycle arrest, and apoptotic death in cultured cells but also reduced MM xenograft growth in nude mice, yielding highly synergistic effects. Immunoblot revealed that TMZ and Nira cotreatment markedly increased the expression of p-ATM, p-CHK2, RAD51, and γH2A.X, indicating the suppression of DNA damage response (DDR) and elevated DSB accumulation. Conclusion: Inhibition of PARP1 sensitizes genotoxic agents and represents an important therapeutic approach for MM. These findings provide preliminary evidence for combining PARP1 inhibitors with TMZ for MM treatment.

[Pharmacokinetic behavior and brain tissue distribution of paeoniflorin combined with normal and toxic doses of strychnine in rats after percutaneous administration].

This study aims to establish a rapid and sensitive UPLC-MS/MS method for simultaneously determining the content of strychnine and paeoniflorin in plasma and brain tissue of rats, and compare the pharmacokinetic behavior and brain tissue distribution of paeoniflorin combined with normal and toxic doses of strychnine in rats after percutaneous administration. Compared with those in the toxic-dose strychnine group, the AUC_(0-t), AUC_(0-∞), and C_(max) of strychnine decreased by 51.51%, 45.68%, and 46.03%, respectively(P<0.01), and the corresponding values of paeoniflorin increased by 91.41%, 102.31%, and 169.32%, respectively(P<0.01), in the compatibility group. Compared with the normal-dose strychnine group, the compatibility group showed insignificantly decreased C_(max), AUC_(0-t), and AUC_(0-∞) of strychnine, increased C_(max) and T_(max) of paeoniflorin(P<0.01), 66.88% increase in AUC_(0-t), and 70.55% increase in AUC_(0-∞) of paeoniflorin. In addition, the brain tissue concentration of strychnine decreased and that of paeoniflorin increased after compatibility. The combination of paeoniflorin with normal dose and toxic dose of strychnine can inhibit the percutaneous absorption of strychnine, and greatly promote the percutaneous penetration of paeoniflorin, whereas the interaction mechanism remains to be explored. The UPLC-MS/MS method established in this study is easy to operate and has good precision. It is suitable for in vivo study of pharmacokinetic behavior and brain tissue distribution of paeoniflorin and strychnine after percutaneous administration in rats, which provides reference for the safe and rational clinical use of strychnine and the combined use of drugs, and lays a solid foundation for the development of external preparations containing Strychni Semen.

Bio-inspired engineering of a perfusion culture platform for guided three-dimensional nerve cell growth and differentiation.

Collagen provides a promising environment for 3D nerve cell culture; however, the function of perfusion culture and cell-growth guidance is difficult to integrate into such an environment to promote cell growth. In this paper, we develop a bio-inspired design method for constructing a perfusion culture platform for guided nerve cell growth and differentiation in collagen. Based on the anatomical structure of peripheral neural tissue, a biomimetic porous structure (BPS) is fabricated by two-photon polymerization of IP-Visio. The micro-capillary effect is then utilized to facilitate the self-assembly of cell encapsulated collagen into the BPS. 3D perfusion culture can be rapidly implemented by inserting the cell-filled BPS into a pipette tip connected with syringe pumps. Furthermore, we investigate the nerve cell behavior in the BPS. 7-channel aligned cellular structures surrounded with a Schwann cell layer can be stably formed after a long-time perfusion culture. Differentiation of PC12 cells and mouse neural stem cells shows 3D neurite outgrowth alignment and elongation in collagen. The calcium activities of differentiated PC12 cells are visualized for confirming the preliminary formation of cell function. These results demonstrate that the proposed bio-inspired 3D cell culture platform with the advantages of miniaturization, structure complexity and perfusion has great potential for future application in the study of nerve regeneration and drug screening.

[Effects of long-term straw returning on distribution of aggregates and nitrogen, phosphorus, and potassium in paddy]. / é•¿æœŸç§¸ç§†è¿˜ç”°å¯¹æ°´ç¨»åœŸå›¢èšä½“åŠæ°®ç£·é’¾åˆ†é çš„å½±å“.

In order to understand the composition and stability of soil aggregate in paddy filed, as well as the changes of soil aggregate-associated nitrogen (N), phosphorus (P) and potassium (K) after straw addition combined with chemical fertilization, soil samples were collected from a 34-year positioning experiment with three treatments, including no chemical fertilizer (CK), chemical fertilizer only (NPK), and straw addition plus chemical fertilizer (NPKS). The composition of water-stable aggregates at the soil layers of 0-20 cm and 20-40 cm were analyzed with the wet sieving method, as well as the distribution characteristics, contribution rate and activation rate of soil aggregate-associated N, P, and K. Results showed that the fractions of >2 mm and 0.25-1 mm aggregates dominated the soil water-stable aggregates in paddy field, while the contribution of <0.053 mm aggregates was lowest. Compared with CK, NPKS treatment increased the contents of >2 mm and 1-2 mm aggregates at the layers of 0-20 and 20-40 cm, and reduced the contents of 0.053-0.25 mm and <0.053 mm. Similar result in NPK treatment was observed at the layer of 0-20 cm. Compared with tat under the NPK treatment, mean weight diameter (MWD) and geometric mean diameter (GMD) increased by 3.9%-15.5% and 6.3%-41.7% in NPKS treatment, respectively. However, the unstable aggregate index (ELT) reduced by 5.7%-28.7% in the NPKS treatment. NPKS significantly increased the contents of total N (TN), available P (AP), and available K (AK) in soil aggregates, especially in the >0.25 mm aggregates. There were no significant diffe-rences about alkali-hydrolysable N (AN) and total K (TK) between NPK and NPKS treatments. The nutrient contribution of soil aggregates in paddy field was affected by aggregate composition. NPKS significantly increased the contribution of AN, AP, and AK within >1 mm aggregates. In all, straw addition combined with chemical fertilizer could increase the stability of soil aggregates at the layers of 0-20 cm and 20-40 cm, and increase the contents of soil aggregate-associated N, P and K, especially for the >1 mm aggregates. Our results provided insights into ensuring soil quality and sustainable development of resources in paddy field by adjusting the ratio of soil C to N.

Celecoxib Blocks Vasculogenic Mimicry via an Off-Target Effect to Radiosensitize Lung Cancer Cells: An Experimental Study.

The resistance to radiotherapy in lung cancer can be attributed to vasculogenic mimicry (VM) to some extent. Celecoxib (CXB), a selective inhibitor of cyclooxygenase-2 (COX-2), is reported as a radiosensitizer in non-small cell lung cancer (NSCLC). However, whether CXB can regulate VM formation via an off-target effect to radiosensitize NSCLC remains unclear. This study aimed to elucidate the mechanism underlying the radiosensitizing effect of CXB on NSCLC, i.e., whether CXB can inhibit VM formation via binding to newly identified targets other than COX-2. CXB radiosensitivity assay was performed in BALB/c mice bearing H460 xenografts and C57 mice bearing Lewis lung cancer (LLC) xenografts, which were divided into the control, CXB, irradiation (IR) treatment, and IR plus CXB groups. VM formation was observed using 3D Matrigel, periodic acid solution (PAS) staining, and immunofluorescence staining. The potential off-targets of CXB were screened using Protein Data Bank (PDB) database, MGLTools 1.5.6, and AutoDock Vina 1.1.2 and confirmed by Western blotting, enzyme activity assay, and RNA interference in vitro experiments and by immunohistochemistry in vivo experiments. CXB treatment almost eliminated the enhancement of VM formation by IR in vitro and in vivo, partially due to COX-2 inhibition. Four potential off-targets were predicted by molecular docking. Among them, aminopeptidase N (APN) and integrin alpha-V (ITAV) were remarkably inhibited in protein expression and enzyme activity in vitro or in vivo, consistent with the remarkable reduction of VM formation in H460 xenografts in BALB/c mice. In conclusion, CXB dramatically blocked VM through inhibiting newly identified off-targets APN and ITAV, other than COX-2, then radiosensitizing NSCLC.

Improvement of Definite Diagnosis of Familial Hypercholesterolemia Using an Expanding Genetic Analysis.

Background: The deeper understanding of the complex hereditary basis of familial hypercholesterolemia (FH) has raised the rationale of genetic testing, which has been underutilized in clinical practice. Objectives: The present study aimed to explore the variant spectrum of FH in an expanding manner and compare its diagnostic performance. Methods: A total of 169 Chinese individuals (124 index cases and 45 relatives) with clinical definite/probable FH were consecutively enrolled. Next-generation sequencing was performed for genetic analysis of 9 genes associated with hypercholesterolemia (major genes: LDLR, APOB, and PCSK9; minor genes: LDLRAP1, LIPA, STAP1, APOE, ABCG5, and ABCG8) including the evaluations of small-scale variants and large-scale copy number variants (CNVs). Results: Among the 169 clinical FH patients included, 98 (58.0%) were men. A total of 85 (68.5%) index cases carried FH-associated variants. The proportion of FH caused by small-scale variants in LDLR, APOB, and PCSK9 genes was 62.1% and then increased by 6.5% when other genes and CNVs were further included. Furthermore, the variants in LDLR, APOB, and PCSK9 genes occupied 75% of all FH-associated variants. Of note, there were 8 non-LDLR CNVs detected in the present study. Conclusions: LDLR, APOB, and PCSK9 genes should be tested in the initial genetic screening, although variants in minor genes also could explain phenotypic FH, suggesting that an expanding genetic testing may be considered to further explain phenotypic FH.