[Correlation between preoperative MRI measurement of cross-sectional area of hamstring tendon and graft in anterior cruciate ligament reconstruction].

OBJECTIVE: To study the corretation between the cross-sectional area of hamstring tenden measured by MRI and gragt in anterior cruciate ligament rexonstruction. METHODS: MRI data of 50 patients who planned to undergo anterior cruciate ligament reconstruction from November 2021 to March 2022 were collected, including 32 males and 18 females, aged from 19 to 48 years old with an average of(31.1±8.7) years. Before the operation, the semitendinosus and gracilis tendons were measured and recorded by MRI, and then the anterior cruciate ligament was reconstructed under arthroscope. During the operation, gracilis and semitendinosus tendons were taken to prepare the final tendon to be transplanted, and the diameter of the prepared final graft was measured during the operation. Finally, the data were analyzed by statistical software. RESULTS: The cross sectional areas of semitendinosus tendon, gracilis tendon, semitendinosus tendon and gracilis tendon measured by MRI were significantly and positively correlated with the diameter of grafts required in anterior cruciate ligament surgery, the r values were 0.858, 0.728, 0.842(P<0.001), respectively. The area under curre (AUC), sensitivity, and specificity of the sum of the cross sectional areas of semitendinosus tendon and gracilis tendon were 0.925, 90.48%, and 85.71%, respectively. CONCLUSION: In patients undergoing anterior cruciate ligament reconstruction, preoperative MRI measurement has a strong statistical correlation with the diameter of hamstring muscle transplantation during operation. The sum of the cross sectional areas of semitendinosus tendon and gracilis tendon has a high predictive value for the diameter of grafts during anterior cruciate ligament reconstruction, and can predict the size of grafts during operation.

Computational spectrometer based on local feature-weighted spectral reconstruction.

The computational spectrometer enables the reconstruction of spectra from precalibrated information encoded. In the last decade, it has emerged as an integrated and low-cost paradigm with vast potential for applications, especially in portable or handheld spectral analysis devices. The conventional methods utilize a local-weighted strategy in feature spaces. These methods overlook the fact that the coefficients of important features could be too large to reflect differences in more detailed feature spaces during calculations. In this work, we report a local feature-weighted spectral reconstruction (LFWSR) method, and construct a high-accuracy computational spectrometer. Different from existing methods, the reported method learns a spectral dictionary via L 4-norm maximization for representing spectral curve features, and considers the statistical ranking of features. According to the ranking, weight features and update coefficients then calculate the similarity. What's more, the inverse distance weighted is utilized to pick samples and weight a local training set. Finally, the final spectrum is reconstructed utilizing the local training set and measurements. Experiments indicate that the reported method's two weighting processes produce state-of-the-art high accuracy.

Tuning-free and self-supervised image enhancement against ill exposure.

Complex lighting conditions and the limited dynamic range of imaging devices result in captured images with ill exposure and information loss. Existing image enhancement methods based on histogram equalization, Retinex-inspired decomposition model, and deep learning suffer from manual tuning or poor generalization. In this work, we report an image enhancement method against ill exposure with self-supervised learning, enabling tuning-free correction. First, a dual illumination estimation network is constructed to estimate the illumination for under- and over-exposed areas. Thus, we get the corresponding intermediate corrected images. Second, given the intermediate corrected images with different best-exposed areas, Mertens' multi-exposure fusion strategy is utilized to fuse the intermediate corrected images to acquire a well-exposed image. The correction-fusion manner allows adaptive dealing with various types of ill-exposed images. Finally, the self-supervised learning strategy is studied which learns global histogram adjustment for better generalization. Compared to training on paired datasets, we only need ill-exposed images. This is crucial in cases where paired data is inaccessible or less than perfect. Experiments show that our method can reveal more details with better visual perception than other state-of-the-art methods. Furthermore, the weighted average scores of image naturalness matrics NIQE and BRISQUE, and contrast matrics CEIQ and NSS on five real-world image datasets are boosted by 7%, 15%, 4%, and 2%, respectively, over the recent exposure correction method.

Contribution of Constituents in Rosemary-Magnolia Compound Essential Oil to Antibacterial, Antioxidant and Cytotoxicity Bioactivities Revealed by Grey Correlation Analysis.

The compound of essential oils (EOs) is a key approach to achieving the superimposed efficacy of plant EOs. In this article, grey correlation analysis was applied for the first time to explore the compound ratios and contribution between constituents and the bioactivity of the compound EOs. There were 12 active constituents shared in rosemary and magnolia EOs prepared by negative pressure distillation. With different proportions, these two EOs were blended and analyzed for the antioxidant, bacteriostatic and antitumor effects. According to the results of the inhibition circle, minimum bactericidal and inhibitory concentration, the most obvious inhibition effect of the compound EOs on different strains of bacteria was shown in Staphylococcus aureus. The results of antioxidant test showed that single EO from rosemary had the best antioxidant effect, and its EO content was directly proportional to the antioxidant effect. The cytotoxicity results showed that, there was a significant difference in the lethality of the compound EOs between tumor cells Mcf-7 (human breast cancer cells) and SGC-7901 cells (human gastric cancer cells). Furthermore, single EO from magnolia had an obvious inhibitory effect on the growth of Mcf-7 cells and SGC-7901 cells, and the cell lethality rate was as high as 95.19 % and 97.96 %, respectively. As the results of grey correlation analysis, the constituents with the maximal correlation of inhibitory effects on bacteria were as follows: S. aureus - Terpinolene (0.893), E. coli - Eucalyptol (0.901), B. subtilis - α-Pinene (0.823), B. cereus - Terpinolene (0.913) and Salmonella - α-Phellandrene (0.855). For the ABTS and DPPH scavenging effects, the constituents with the maximal correlation were (-)-Camphor (0.860) and ß-Pinene (0.780), respectively. In terms of the effects of the active constituents of compound EOs on the inhibitory activities of tumor cells Mcf-7 and SGC-7901, the three active constituents of γ-Terpinene, (R)-(+)-ß-Citronellol and (-)-Camphor were in the top three, and their correlation were Mcf-7 (0.833, 0.820, 0.795) and SGC-7901 (0.797, 0.766, 0.740). Our study determined the contribution degree of active constituents in the antibacterial, antioxidant, and antitumor bioactivities of rosemary-magnolia compound EOs, and also provided new insights for the research of EOs combination formulations.

Mitigating Modality Discrepancies for RGB-T Semantic Segmentation.

Semantic segmentation models gain robustness against adverse illumination conditions by taking advantage of complementary information from visible and thermal infrared (RGB-T) images. Despite its importance, most existing RGB-T semantic segmentation models directly adopt primitive fusion strategies, such as elementwise summation, to integrate multimodal features. Such strategies, unfortunately, overlook the modality discrepancies caused by inconsistent unimodal features obtained by two independent feature extractors, thus hindering the exploitation of cross-modal complementary information within the multimodal data. For that, we propose a novel network for RGB-T semantic segmentation, i.e. MDRNet + , which is an improved version of our previous work ABMDRNet. The core of MDRNet + is a brand new idea, termed the strategy of bridging-then-fusing, which mitigates modality discrepancies before cross-modal feature fusion. Concretely, an improved Modality Discrepancy Reduction (MDR + ) subnetwork is designed, which first extracts unimodal features and reduces their modality discrepancies. Afterward, discriminative multimodal features for RGB-T semantic segmentation are adaptively selected and integrated via several channel-weighted fusion (CWF) modules. Furthermore, a multiscale spatial context (MSC) module and a multiscale channel context (MCC) module are presented to effectively capture the contextual information. Finally, we elaborately assemble a challenging RGB-T semantic segmentation dataset, i.e., RTSS, for urban scene understanding to mitigate the lack of well-annotated training data. Comprehensive experiments demonstrate that our proposed model surpasses other state-of-the-art models on the MFNet, PST900, and RTSS datasets remarkably.

Therapeutic drug combinations against COVID-19 obtained by employing a collaborative filtering method.

The outbreak of coronavirus disease 2019 (COVID-19) has severely harmed human society and health. Because there is currently no specific drug for the treatment and prevention of COVID-19, we used a collaborative filtering algorithm to predict which traditional Chinese medicines (TCMs) would be effective in combination for the prevention and treatment of COVID-19. First, we performed drug screening based on the receptor structure prediction method, molecular docking using q-vina to measure the binding ability of TCMs, TCM formulas, and neo-coronavirus proteins, and then performed synergistic filtering based on Laplace matrix calculations to predict potentially effective TCM formulas. Combining the results of molecular docking and synergistic filtering, the new recommended formulas were analyzed by reviewing data platforms or tools such as PubMed, Herbnet, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the Guide to the Dispensing of Medicines for Clinical Evidence, and the Dictionary of Chinese Medicine Formulas, as well as medical experts' treatment consensus in terms of herbal efficacy, modern pharmacological studies, and clinical identification and typing of COVID-19 pneumonia, to determine the recommended solutions. We found that the therapeutic effect of a combination of six TCM formulas on the COVID-19 virus is the result of the overall effect of the formula rather than that of specific components of the formula. Based on this, we recommend a formula similar to that of Jinhua Qinggan Granules for the treatment of COVID-19 pneumonia. This study may provide new ideas and new methods for future clinical research. Classification: Biological Science.

Globulin and Albumin/Globulin Ratios as Potential Biomarkers for the Diagnosis of Acute and Chronic Peri-Prosthetic Joint Infections: A Retrospective Study.

Background: Peri-prosthetic joint infection (PJI) is the most serious complication after prosthetic joint replacement. However, the diagnosis of PJI remains challenging for clinicians because of the lack of a gold standard. The purpose of this study was to investigate the diagnostic significance of serum globulin, albumin/globulin, and other biomarkers in acute and chronic periprosthetic infections. Patients and Methods: A retrospective study of 162 patients with PJI and aseptic loosening between January 2016 and March 2021 at our institution was performed in three groups. There were 20 patients with acute infection in group A, 36 patients with chronic infection in group B, and 106 patients with aseptic loosening in group C. Globulin, albumin/globulin, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), platelet count (PLT), mean platelet volume (MPV), d-dimer, and platelet count/mean platelet volume ratio (PMR) levels were recorded. The area under the curve (AUC) was used to measure the diagnostic value of globulin and albumin/globulin with other biomarkers for PJI. Results: Compared with the aseptic loosening group, the acute and chronic PJI group had higher levels of CRP, ESR, d-dimer, globulin, PLT, and PMR (p < 0.01) and lower levels of albumin/globulin and MPV (p < 0.01). The optimal cutoff, AUC, sensitivity, and specificity of CRP, albumin/globulin, ESR, and globulin were: CRP, 8.3 mg/L, 0.903, 78.57%, and 88.68%; albumin/globulin, 1.31, 0.899, 91.07%, and 73.58%; ESR, 32 mm/h, 0.888, 75.%, and 85.85%; globulin, 29.5 g/L, 0.880, 91.07%, and 72.64%. Conclusions: Globulin and albumin/globulin have excellent diagnostic value for acute and chronic PJI and are promising potential biomarkers for the diagnosis of PJI. The diagnostic performance of albumin/globulin is superior to that of ESR and similar to that of CRP.

Middle-Level Feature Fusion for Lightweight RGB-D Salient Object Detection.

Most existing RGB-D salient object detection (SOD) models adopt a two-stream structure to extract the information from the input RGB and depth images. Since they use two subnetworks for unimodal feature extraction and multiple multi-modal feature fusion modules for extracting cross-modal complementary information, these models require a huge number of parameters, thus hindering their real-life applications. To remedy this situation, we propose a novel middle-level feature fusion structure that allows to design a lightweight RGB-D SOD model. Specifically, the proposed structure first employs two shallow subnetworks to extract low- and middle-level unimodal RGB and depth features, respectively. Afterward, instead of integrating middle-level unimodal features multiple times at different layers, we just fuse them once via a specially designed fusion module. On top of that, high-level multi-modal semantic features are further extracted for final salient object detection via an additional subnetwork. This will greatly reduce the network's parameters. Moreover, to compensate for the performance loss due to parameter deduction, a relation-aware multi-modal feature fusion module is specially designed to effectively capture the cross-modal complementary information during the fusion of middle-level multi-modal features. By enabling the feature-level and decision-level information to interact, we maximize the usage of the fused cross-modal middle-level features and the extracted cross-modal high-level features for saliency prediction. Experimental results on several benchmark datasets verify the effectiveness and superiority of the proposed method over some state-of-the-art methods. Remarkably, our proposed model has only 3.9M parameters and runs at 33 FPS.

Immunomodulatory mechanisms of abatacept: A therapeutic strategy for COVID-19.

Coronavirus disease 2019 (COVID-19) caused by coronavirus-2 (SARS-CoV-2) infection has rapidly spread throughout the world and become a major threat to human beings. Cytokine storm is a major cause of death in severe patients. Abatacept can suppress cytokines used as antirheumatic drugs in clinical applications. This study analyzed the molecular mechanisms of abatacept treatment for COVID-19. Differentially expressed genes (DEGs) were identified by analyzing expression profiling of abatacept treatment for rheumatoid arthritis (RA) patients and SARS-CoV-2 infection patients. We found that 59 DEGs were upregulated in COVID-19 patients and downregulated following abatacept treatment. Gene set enrichment analysis (GSEA) and Gene Ontology (GO) analysis showed that immune and inflammatory responses were potential regulatory mechanisms. Moreover, we verified 8 targeting genes and identified 15 potential drug candidates for the treatment of COVID-19. Our study illustrated that abatacept could be a promising property for preventing severe COVID-19, and we predicted alternative potential drugs for the treatment of SARS-CoV-2 infection.

The accuracy of D-dimer in the diagnosis of periprosthetic infections: a systematic review and meta-analysis.

BACKGROUND: Periprosthetic joint infection (PJI) is a devastating complication after total hip arthroplasty (THA) or total knee arthroplasty (TKA). It is scarce and contradicting evidence supporting the use of serum D-dimer to diagnose PJI in revision THA and TKA. This systematic review and meta-analysis aimed to investigate the accuracy of D-dimer in the diagnosis of periprosthetic infections. METHODS: The PubMed, Embase, Web of Science were systematically searched from the inception dates to August 15, 2020. We included all diagnostic studies of D-dimer in the diagnosis of periprosthetic infections. The literature's quality was evaluated by the QUADAS-2 tool, and Stata16 and Revman5.3 software carried out the meta-analysis. RESULTS: Of 115 citations identified by the search strategy, 10 studies (comprising 1756 participants) met the inclusion criteria. The literature quality assessment results show that most of the literature is low-risk bias literature. The combined sensitivity of D-dimer in diagnosing periprosthetic infections was 0.81 (95% confidence interval [CI] 0.71-0.88), combined specificity was 0.74 (95% CI 0.61-0.84), combined positive likelihood ratio was 3.1 (95% CI 2.0-5.0), combined negative likelihood ratio 0.26 (95% CI 0.16-0.41), combined diagnosis odds ratio 12 (95% CI 5-27), area under the Summary Receiver Operator Characteristic Curve (SROC) is 0.85 (95% CI 0.81-0.88). The data are statistically significant. CONCLUSION: D-dimer has a high diagnostic value in diagnosing PJI and has clinical significance in diagnosing periprosthetic infection. In addition, there are relatively few studies on the threshold of D-dimer, different sampling types, different laboratory detection methods, and different races, so more prospective trials with large samples, multi-centers, and scientific design should be carried out in the future.

Ultrahigh-security single-pixel semantic encryption.

Single-pixel encryption is a recently developed encryption technique enabling the ciphertext amount to be decreased. It adopts modulation patterns as secret keys and uses reconstruction algorithms for image recovery in the decryption process, which are time-consuming and can easily be illegally deciphered if the patterns are exposed. We report an image-free single-pixel semantic encryption technique that significantly enhances security. The technique extracts semantic information directly from the ciphertext without image reconstruction, which significantly reduces computing resources for end-to-end real-time decoding. Moreover, we introduce a stochastic mismatch between keys and ciphertext, with random measurement shift and dropout, which effectively enhances the difficulty of illegal deciphering. Experiments on the MNIST dataset validate that 78 coupling measurements (0.1 sampling rate) with stochastic shift and random dropout achieved 97.43% semantic decryption accuracy. In the worst situation, when all the keys are illegally obtained by unauthorized attackers, only 10.80% accuracy can be achieved (39.47% in an ergodic manner).

Engineering oxygen vacancies and surface chemical reconstruction of MOF-derived hierarchical CoO/Ni2P-Co2P nanosheet arrays for advanced aqueous zinc-ion batteries.

Aqueous zinc-ion batteries (ZIBs) are emerging as promising alternatives among various energy storage devices. However, the lack of research on cathode materials with both high capacity and electrochemical stability restricts widespread applications of ZIBs. Herein, surface chemical reconstruction and partial phosphorization strategies are employed to synthesize MOF-derived hierarchical CoO/Ni2P-Co2P nanosheet arrays on Ni foam substrates as cathodes for ZIBs. The unique hierarchical nanostructure and multiple components with exposed surfaces and rich oxygen vacancies accelerate charge transfer and ion diffusion, expose more active sites, and promote the accessibility between the active materials and electrolyte. The oxide/phosphide composites obtained by novel partial phosphorization achieve a common improvement of performance and stability. As expected, the CoO/Ni2P-Co2P electrode delivers a high specific capacity (370.4 mA h g-1 at 3 A g-1) and excellent rate performance (63.3% retention after a six-fold increase in the current density). Moreover, when employed as the cathode of the CoO/Ni2P-Co2P-30//Zn battery, the assembled battery exhibits a superior specific capacity (322.8 mA h g-1 at 2 A g-1), a long cycle life (104.9% retention after 6000 cycles), a favorable energy density (547.5 W h kg-1) and power density (9.7 kW kg-1). Therefore, this study provides a suitable candidate which meets the requirements of high-performance cathode materials for ZIBs.

Sensitive electrochemical aptasensor for determination of sulfaquinoxaline based on AuPd NPs@UiO-66-NH2/CoSe2 and RecJf exonuclease-assisted signal amplification.

The authors designed a sensitive label-free electrochemical aptasensor for the detection of sulfaquinoxaline (SQX), including the AuPd NPs@UiO-66-NH2/CoSe2 nanocomposites and RecJf exonuclease-assisted target recycle signal amplification strategy. AuPd NPs@UiO-66-NH2/CoSe2 nanocomposite with excellent conductivity and numerous active sites was successfully synthesized to provide a favorable sensing platform and load more double-strand DNA (dsDNA) on the electrode surface. The negatively charged phosphate group of the oligonucleotide and [Fe (CN)6] 3-/4- repel each other electrostatically, resulting in very low electrical signals. In the presence of SQX, its corresponding aptamer will be released from the double-stranded structure and then digested by RecJf exonuclease, which resulted in the SQX being released to initiate the next recycling to help amplify the DPV signal. Under the optimal conditions, the peak current has a linear relationship with the logarithmic of SQX concentration in the range of 1 pg/mL∼100 ng/mL and the obtained detection limit was 0.547 pg/mL. Furthermore, the contrasted aptasensor possess reliable specificity, reproducibility and stability toward SQX, and has been applied to detect SQX in pork samples with a satisfied recovery varied from 94.40% to 95.98%.

A competitive-type electrochemical immunosensor based on Ce-MOF@Au and MB-Au@Pt core-shell for nitrofuran metabolites residues detection.

A novel competitive-type electrochemical immunosensor based on square wave voltammetry (SWV) response was developed for the quantitative detection of 1-Aminohydantoin (AHD). To improve the conductivity of this immunosensor nanocomposites with good electrical conductivity were prepared as a signal amplification platform for the immunosensor by growing Au nanoparticles on the surface of Ce-based metal-organic framework (Ce-MOF). In addition, methylene blue (MB)-loaded Au@Pt and coating antigen (OVA-AHD) connected as a signal label. When the target was introduced, it competed with the coating antigen for the Ab, which led to a reduction in the number of signal probes bound to the Ab. The concentration of AHD can be determined by SWV detection of the MB signal loaded on the signal labels. Under optimal conditions, the wide linear range of 0.001-1000 µg /L and a low detection limit of 1.35 × 10-7 µg/L were achieved. Ultimately, the developed method displayed excellent specificity in practical applications, providing a promising probability to detect nitrofuran metabolites residues to guarantee food safety.

Constitutional morphological features and risk of hip osteoarthritis: a case-control study using standard radiographs.

OBJECTIVES: To evaluate the risk of association with hip osteoarthritis (OA) of 14 morphological features measured on standard antero-posterior pelvis radiographs. METHODS: A case-control study of 566 symptomatic unilateral hip OA cases and 1108 controls without hip OA, using the Genetics of OA and Lifestyle database. Unaffected hips of cases were assumed to reflect pre-OA morphology of the contralateral affected hip. ORs with 95% CI adjusted for confounding factors were calculated using logistic regression. Hierarchical clustering on principal component method was used to identify clusters of morphological features. Proportional risk contribution (PRC) of these morphological features in the context of other risk factors of hip OA was estimated using receiver operating characteristic analysis. RESULTS: All morphological features showed right-left symmetry in controls. Each feature was associated with hip OA after adjusting for age, gender and body mass index. Increased sourcil angle had the strongest association (OR: 6.93, 95% CI 5.16 to 9.32). Three clusters were identified. The PRC varied between individual features, as well as between clusters. It was 35% (95% CI 31% to 40%) for all 14 morphological features, compared to 21% (95% CI 19% to 24%) for all other well-established risk factors. CONCLUSIONS: Constitutional morphological variation strongly associates with hip OA development and may explain much of its heritability. Relevant morphological measures can be assessed readily on standard radiographs to help predict risk of hip OA. Prospective studies are required to provide further support for causality.

[Research progress of phase separation of intracellular biological macromolecules].

The phenomenon of phase separation of intracellular biological macromolecules is an emerging research field that has received great attention in recent years. As an aggregation and compartment mechanism of cell biochemical reactions, it widely exists in nature and participates in important physiological processes such as gene transcription and regulation, as well as influences organism's response to external stimuli. Disequilibrium of phase separation may lead to the occurrence of some major diseases. Researchers in cross-cutting fields are trying to examine dementia and other related diseases from a new perspective of phase separation, exploring its molecular mechanism and the potential possibility of intervention and treatment. This review intends to introduce the latest research progress in this field, summarize the major research directions, biochemical basis, its relationship with disease occurrence, and giving a future perspective of key problems to focus on.

[Limited open reduction and intramedullary fixation for the treatment of refractory femoral subtrochanteric fractures].

OBJECTIVE: To explore the surgical technique and clinical effect of limited open reduction and intramedullary fixation assisted with orthopedic traction bed for the treatment of femoral subtrochanteric fractures. METHODS: From July 2015 to October 2017, 12 patients with femoral subtrochanteric fractures were treated including 9 males and 3 females with an average age of 44 years old ranging from 33 to 67 years old. Among them, 10 cases were on the left trochanter and 2 on the right, and there were 8 cases of highly fall injury and 4 cases of traffic accident injury. All patients received operation at 2 to 5 days after injury. According to the Seinsheimer classification, 8 cases were type IIIA, 2 were type IIIB and 2 were type IV, and all cases were closed injury. The patients were placed on the orthopedic traction bed for trial closed reduction to maintain proper traction before operation. Under C-arm X-ray fluoroscopy, it was advisable to take the fracture end of the main bone block without obvious shortening and shifting. Then limited incision and lengthened InterTan intramedullary nailing were performed, and the Sanders traumatic hip score was used to evaluate the postoperative efficacy. RESULTS: All 12 patients were followed up from 6 to 24 months with an average of 12 months. All cases were received bone healing at 3 to 6 months with an average time of 4 months. According to the Sanders grades, the results were excellent in 9 cases, good in 2 cases and medium in 1 case. Infection, breakage of internal fixation loosening and adverse complications such as malunion were not appeared in all the cases. CONCLUSIONS: Limited open reduction assisted with traction bed can be effective to solve the problem of the intraoperative reduction in the complex subtrochanteric fractures, which could save operation time and decrease bleeding. Combined with intramedullary fixation, this method could acquire good counterpoint and stability for the fracture end, and provide a method for the treatment of refractory subtrochanteric fractures.

Pinning Controllers for Activation Output Tracking of Boolean Network Under One-Bit Perturbation.

This paper studies pinning controllers for activation output tracking (AOT) of Boolean network under one-bit perturbation, based on the semitensor product of matrices. First, the definition of AOT with respect to an activation number is presented, where the activation number means the number of active outputs whose logical variables are 1 s. Then, several criteria are established for AOT issue. Further, the impact of one-bit perturbation on AOT is studied, where one-bit perturbation means that only one logical function has one-bit change of its truth table by flipping the value from 1 to 0 or 0 to 1. In addition, if a one-bit perturbation is a valid perturbation on AOT, an output feedback pinning control is designed to recover AOT. The obtained results are effectively illustrated by a D. melanogaster segmentation polarity gene network and a reduced signal transduction network.

Nonisothermal decomposition and safety parameters of HNIW/TNT cocrystal.

To explore the thermal decomposition behavior and evaluate the thermal safety of the cocrystal 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (HNIW)/2,4,6-trinitrotoluene (TNT), its thermal and kinetic behaviors were studied by differential scanning calorimetry (DSC) technique. With the help of onset temperature (T e) and maximum peak temperature (T p) from the non-isothermal DSC curves of HNIW/TNT cocrystal at different heating rates (ß), the following were calculated: the value of specific heat capacity (C p) and the standard molar enthalpy of formation , the apparent activation energy (E K and E O) and pre-exponential constant (A K) of thermal decomposition reaction obtained by Kissinger's method and Ozawa's method, density (ρ) and thermal conductivity (λ), the decomposition heat (Q d, as half-explosion heat), Zhang-Hu-Xie-Li's formula, Smith's equation, Friedman's formula, Bruckman-Guillet's formula, Frank-Kamenetskii's formula and Wang-Du's formulas, the values (T e0 and T p0) of T e and T p corresponding to ß â†’ 0, thermal explosion temperature (T be and T bp), adiabatic time-to-explosion (t tiad), 50% drop height (H 50) for impact sensitivity, critical temperature of hot-spot initiation (T cr), thermal sensitivity probability density function [S(T)] vs. temperature (T) relation curves with radius of 1 m and ambient temperature of 300 K, the peak temperature corresponding to the maximum value of S(T) vs. T relation curve (T S(T)max), safety degree (SD) and critical ambient temperature (T acr) of thermal explosion. Results show that the kinetic equation describing the exothermic decomposition reaction of HNIW/TNT cocrystal is The following thermal safety parameters for the HNIW/TNT cocrystal are obtained: T e0 = 464.45 K; T p0 = 477.55 K; T be = 472.82 K; T bp = 485.89 K; t tiad = 4.40 s, 4.42 s, and 4.43 s for n = 0, 1, and 2, respectively; T cr = 531.90 K; H 50 = 19.46 cm; and the values of T acr, T S(T)max, SD and P TE are 469.69 K, 470.58 K, 78.57% and 21.43% for sphere; 465.70 K, 470.58 K, 78.17% and 21.83% for infinite cylinder; and 459.39 K, 464.26 K, 77.54% and 22.46% for infinite flat.

Cyclic Equibiaxial Tensile Strain Alters Gene Expression of Chondrocytes via Histone Deacetylase 4 Shuttling.

OBJECTIVES: This paper aims to investigate whether equibiaxial tensile strain alters chondrocyte gene expression via controlling subcellular localization of histone deacetylase 4 (HDAC4). MATERIALS AND METHODS: Murine chondrocytes transfected with GFP-HDAC4 were subjected to 3 h cyclic equibiaxial tensile strain (CTS, 6% strain at 0.25 Hz) by a Flexcell® FX-5000™ Tension System. Fluorescence microscope and western blot were used to observe subcellular location of HDAC4. The gene expression was analyzed by real-time RT-PCR. The concentration of Glycosaminoglycans in culture medium was quantified by bimethylmethylene blue dye; Collagen II protein was evaluated by western blot. Cells phenotype was identified by immunohistochemistry. Cell viability was evaluated by live-dead cell detect kit. Okadaic acid, an inhibitor of HDAC4 nuclear relocation, was used to further validate whether HDAC4 nuclear relocation plays a role in gene expression in response to tension stimulation. RESULTS: 87.5% of HDAC4 was located in the cytoplasm in chondrocytes under no loading condition, but it was relocated to the nucleus after CTS. RT-PCR analysis showed that levels of mRNA for aggrecan, collagen II, LK1 and SOX9 were all increased in chondrocytes subjected to CTS as compared to no loading control chondrocytes; in contrast, the levels of type X collagen, MMP-13, IHH and Runx2 gene expression were decreased in the chondrocytes subjected to CTS as compared to control chondrocytes. Meanwhile, CTS contributed to elevation of glycosaminoglycans and collagen II protein, but did not change collagen I production. When Okadaic acid blocked HDAC4 relocation from the cytoplasm to nucleus, the changes of the chondrocytes induced by CTS were abrogated. There was no chondrocyte dead detected in this study in response to CTS. CONCLUSIONS: CTS is able to induce HDAC4 relocation from cytoplasm to nucleus. Thus, CTS alters chondrocytes gene expression in association with the relocation of HDAC4 induced by CTS.