Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.

Rapidly progressive necrotizing enterocolitis: Risk factors and a predictive model.

BACKGROUND: Rapidly progressive necrotizing enterocolitis (RP-NEC) is a particular subtype of NEC known for its rapid progression and high mortality rate. The objective of this study was to establish a predictive model for RP-NEC. METHODS: This was a retrospective single-center cohort study. Patients were newborn infants with NEC (Bell's stage ≥ IIB) admitted from January 1, 2016 to December 31, 2023. The primary outcome was RP-NEC defined as the need for surgical intervention and/or death within 48 hours of the onset of NEC. RESULTS: Totally 334 newborn infants were included, among which 82 (24.6%) were RP-NEC cases with a gestation age 34.1 (31.0, 37.0) weeks and birth weight 2100 (1413, 2800) g. Plasma sodium <135 mmol/L, C-reactive protein ≥10 mg/L, platelet count <100 × 109/L, lymphocyte count <1.5 × 109/L, pH <7.2 in blood gas, and ascites at NEC onset were identified as independent risk factors for RP-NEC. The model established presented an AUC value of 0.983 (95% CI 0.97-0.99). The calibration curve for validation was applied revealing a slope close to unity while the Hosmer-Lemeshow test yielded χ2 = 2.550 (p = 0.636). CONCLUSION: The predictive model established on the above 6 items of RP-NEC is highly promising. IMPACT: Currently, there is a paucity of research on this specific type of severe necrotizing enterocolitis (NEC) characterized by rapid progression. Our study was to investigate the risk factors associated with surgical intervention and/or death within 48 hours following onset in infants with NEC, establish a predictive model for infants with rapidly progressive NEC. The new data presented in this study was the ROC curve combining the above factors as well as hyponatremia.

Study on medical dispute prediction model and its clinical-application effectiveness based on machine learning.

BACKGROUND: Medical dispute is a global public health issue, which has been garnering increasing attention. In this study, we used machine learning (ML) method to establish a dispute prediction model and explored the clinical-application efficiency of this model in effectively reducing the occurrence of medical disputes. METHODS: Retrospective study of All disputes filed by Gansu Medical Mediation Committee from 2019 to 2021 and patients with the same hospital level as that of the dispute group and hospitalization year were randomly selected as the control group in 1:1 ratio. SPSS software was used for univariate feature selection of the 14 factors that may cause disputes, and factors with statistical differences were selected. The data were divided into training and test sets in a 7:3 ratio. Six ML models were selected, and Python was used to establish a dispute prediction model. The area under the curve (AUC) of the receiver operating characteristic curve (ROC), sensitivity, specificity, accuracy, precision, average precision (AP), and F1 score were used to characterize the fitting and accuracy of the models, while decision curve analysis (DCA) was used to evaluate their clinical utility. RESULTS: A total of 1189 patients in the dispute and control groups were extracted. Following 11 influencing factors were selected: the inpatient department, doctor title, patient age, patient gender, patient occupation, payment method, hospitalization days, hospitalization times, discharge method, blood transfusion volume, and hospitalization espenses. Compared to other models, the AUC (0.945, 95% CI 0.913-0.981), Sensitivity (0.887), Accuracy (0.887), AP (0.834), and F1 score (0.880) of the random forest model were higher than those of other models, while the DCA curve indicated its high clinical benefits. CONCLUSIONS: Inpatient department, hospitalization expenses, and discharge type are the primary influencing factors of dispute. Random forest exhibited high dispute prediction and clinical-application value and is expected to be promoted for offline dispute prediction.

In vitro drug screening models derived from different PC12 cell lines for exploring Parkinson's disease based on electrochemical signals of catecholamine neurotransmitters.

Gold nanostructures and a Nafion modified screen-printed carbon electrode (Nafion/AuNS/SPCE) were developed to assess the cell viability of Parkinson's disease (PD) cell models. The electrochemical measurement of cell viability was reflected by catecholamine neurotransmitter (represented by dopamine) secretion capacity, followed by a traditional tetrazolium-based colorimetric assay for confirmation. Due to the  capacity to synthesize, store, and release catecholamines as well as their unlimited homogeneous proliferation, and ease of manipulation, pheochromocytoma (PC12) cells were used for PD cell modeling. Commercial low-differentiated and highly-differentiated PC12 cells, and home-made nerve growth factor (NGF) induced low-differentiated PC12 cells (NGF-differentiated PC12 cells) were included in the modeling. This approach achieved sensitive and rapid determination of cellular modeling and intervention states. Notably, among the three cell lines, NGF-differentiated PC12 cells displayed the enhanced neurotransmitter secretion level accompanied with attenuated growth rate, incremental dendrites in number and length that were highly resemble with neurons. Therefore, it was selected as the PD-tailorable modeling cell line. In short, the electrochemical sensor can be used to sensitively determine the biological function of neuron-like PC12 cells with negligible destruction and to explore the protective and regenerative impact of various substances on nerve cell model.

Visual Feedback and Guided Balance Training in an Immersive Virtual Reality Environment for Lower Extremity Rehabilitation.

Balance training is essential for physical rehabilitation procedures, as it can improve functional mobility and enhance cognitive coordination. However, conventional balance training methods may have limitations in terms of motivation, real-time objective feedback, and personalization, which a virtual reality (VR) setup may better provide. In this work, we present an immersive VR training environment for lower extremity balance rehabilitation with real-time guidance and feedback. The VR training environment immerses the user in a 3D ice rink model where a virtual coach (agent) leads them through a series of balance poses, and the user controls a trainee avatar with their own movements. We developed two coaching styles: positive-reinforcement and autonomous-supportive, and two viewpoints of the trainee avatar: first-person and third-person. The proposed environment was evaluated in a user study with healthy, non-clinical participants (n = 16, 24.4 ± 5.7 years old, 9 females). Our results show that participants showed stronger performance in the positive-reinforcement style compared to the autonomous-supportive style. Additionally, in the third-person viewpoint, the participants exhibited more stability in the positive-reinforcement style compared to the autonomous-supportive style. For viewpoint, participants exhibited stronger performance in the first-person viewpoint compared to third-person in the autonomous-supportive style, while they were comparable in the positive-reinforcement style. We observed no significant effects on the foot height and number of mistakes. Furthermore, we report the analysis of user performance with balance training poses and subjective measures based on questionnaires to assess the user experience, usability, and task load. The proposed VR balance training could offer an interactive, adaptive, and engaging environment and open new potential research directions for lower extremity rehabilitation.

Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics.

INTRODUCTION: Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial. OBJECTIVES: We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach. METHODS: Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers. RESULTS: Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9. CONCLUSIONS: Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.

CCTδ colocalizes with actin and ß-tubulin: Insight into its involvement in the cytoskeleton formation of the intracellular parasite Nosema bombycis.

The chaperonin-containing t-complex polypeptide 1 (CCT) is a molecular chaperone protein that is widely present in eukaryotic cytoplasm and can assist in the folding of newly synthesized proteins. The CCT complex consists of eight completely different subunits, among which the δ subunit plays an extremely important role in the folding and assembly of cytoskeleton proteins as an individual or complex with other subunits. In this study, we identified the CCTδ in the microsporidian Nosema bombycis (NbCCTδ) for the first time. The NbCCTδ gene contains a complete ORF of 1497 bp in length that encodes a 498 amino acid polypeptide. NbCCTδ is expressed throughout the entire lifecycle of N. bombycis and rather higher in early stage of proliferation. Indirect immunofluorescence results showed that NbCCTδ was colocalized with actin and ß-tubulin during the proliferative and sporogonic phases of N. bombycis. RNA interference down-regulated the expression of the NbCCTδ gene. These results imply that NbCCTδ may participate in cytoskeleton formation and proliferation of N. bombycis.

Serum sCD14, PGLYRP2 and FGA as potential biomarkers for multidrug-resistant tuberculosis based on data-independent acquisition and targeted proteomics.

Multidrug-resistant tuberculosis (MDR-TB), defined as tuberculosis (TB) resistant to at least isoniazid and rifampicin, is a major concern of TB control worldwide. However, the diagnosis of MDR-TB remains a huge challenge to its prevention and control. To identify new diagnostic methods for MDR-TB, a mass spectrometry strategy of data-independent acquisition and parallel reaction monitoring was used to detect and validate differential serum proteins. The bioinformatic analysis showed that the functions of differential serum proteins between the MDR-TB group and the drug-sensitive tuberculosis group were significantly correlated to the complement coagulation cascade, surface adhesion and extracellular matrix receptor interaction, suggesting a disorder of coagulation in TB. Here, we identified three potential candidate biomarkers such as sCD14, PGLYRP2 and FGA, and established a diagnostic model using these three candidate biomarkers with a sensitivity of 81.2%, a specificity of 90% and the area under the curve value of 0.934 in receiver operation characteristics curve to diagnose MDR-TB. Our study has paved the way for a novel method to diagnose MDR-TB and may contribute to elucidate the mechanisms underlying MDR-TB.

Protective role of Astragaloside IV in chronic glomerulonephritis by activating autophagy through PI3K/AKT/AS160 pathway.

Astragaloside IV(AS-IV), a saponin purified from Astragalus membranaceus (Fisch.) Bge.var.mongholicus (Bge.) Hsiao, has been widely used in traditional Chinese medicine. However, the underlying mechanisms in treating chronic glomerular nephritis (CGN) have not been fully understood. The aim of the present study was to evaluate the potential mechanism of AS-IV on CGN. CGN rats were administrated with AS-IV at 10 mg·kg-1 ·d-1 (ASL) and 20 mg·kg-1 ·d-1 (ASH). Twenty four hour proteinuria, blood urea nitrogen (BUN), and serum creatinine (SCr) were detected. Hematoxylin-eosin (HE) and periodic acid-Schiff (PAS) staining were performed to evaluate the kidney lesion. Transmission electron microscope and GFP-RFP-LC3 transfection assay were used to monitor the effect of AS-IV on autophagy. IL-6 and IL-1ß were detected. The expression of CyclinD1, PI3K/AKT/AS160 pathway and autophagy related proteins were detected by Western Blot. The results demonstrated that AS-IV improved kidney function, ameliorated kidney lesion, and diminished inflammatory in CGN rats. Further, both in vivo and vitro study demonstrated that AS-IV inhibited the proliferation of mesangial cells. AS-IV further displayed a remarkable effect on inhibiting the activation of PI3K/AKT/AS160 pathway and improved the activation of autophagy in vivo and vitro. These results suggested that AS-IV is a potential therapeutic agent for CGN and merits further investigation.

Antibiotic contamination control mediated by manganese oxidizing bacteria in a lab-scale biofilter.

Antibiotic micro-pollution is usually found at the ng/L-level in drinking water sources or discharge water of wastewater treatment plants. In this study, a novel approach mediated by manganese oxidizing bacteria (MnOB) in a biofilter was developed to control the pollution. The results indicated that the biogenic manganese oxide (MnOx) produced during the oxidation of the feeding manganese ions could coat the surface of the filtering sand effecting the simultaneous removal of antibiotics. It was found that the removal of antibiotics is insured as long as the feeding manganese was well removed and was not influenced by the hydraulic loading. The growth rate of the MnOB group revealed that the antibiotic concentration at 50 and 100 ng/L promoted their activity, but it was inhibited at 500 and 1000 ng/L. The structure of the bacterial community was stable in the presence of antibiotics (50 ng/L), but their extracellular processes changed. The removal performance of the feeding manganese seemed to relate to the extracellular processes of the dominant bacterial genus. Moreover, the freshly formed MnOx was a buserite-like material that was rich in Mn(III) and Mn(IV) (94.1%), favoring the degradation. The biofilter did not generate additional antibiotic resistant genes in the presence of antibiotics.

A Visibly Observable, Programmable Supramolecular Logic Platform and Its Application in Smart Thiols Sensing.

Molecular computation is increasingly attractive as a tool for medical and biological research because of its programmability and controllability. Herein, a novel visibly observable supramolecular system that can execute multi-level logic functions on a uniform platform was constructed. By employing some programming factors, we succeeded in not only constructing a whole set of contrary logic pairs, but also building up a logic network that can implement advanced functions. Further, the platform is applied to sense thiols in specific environments. The developed method can efficiently filter signals of thiols in intracellular conditions and measure cysteine levels quantitatively in serum conditions. The visual readout makes the method particularly suitable for point-of-care testing. The supramolecule-based platform illustrates not only an incremental advance for the construction of programmable molecular logic systems, but also viable applications in intelligent thiol analysis.

Versatile and Homogeneous DNA Tetraplex Platform for Constructing Label-Free Logic Devices: From Design to Application.

The design of DNA-based logic circuits has become an active research field in DNA nanotechnology and holds great potential in intelligent bioanalysis. To date, although many DNA-based logic systems have been realized, the implementation of advanced logic functions is still challenging, especially with simple and homogeneous compositions. Herein, by integrating two DNA tetraplex structures (G-quadruplex and i-motif), a completely label-free logic platform with high scalability was established, with which a series of advanced functions were realized, including arithmetic (adders and subtractors) and nonarithmetic ones (majority and dual-transfer gates). Furthermore, the platform was also applied as an intelligent biosensor to coanalyze two cancer-related micro-RNAs with high sensitivities and specificities. Considering the excellent versatility, expandability, and biocompatibility, the platform may promote the development of DNA computing and hold great potential in multiparameter sensing and medical diagnosis.

Role of autophagy in inhibiting the proliferation of A549 cells by type III interferon.

Interferons (IFNs) have anti-viral and anti-tumour effects. Type III interferon, as a member of the recently discovered interferon family, has been proved to inhibit tumour proliferation and promote the apoptosis of various tumour cells. However, whether type III IFN could inhibit the proliferation of lung cancer was not clear. In this study, we found that interferon λ (IFN λ) could inhibit the proliferation of A549 cells and induce autophagy and apoptosis of A549 cells. IFN λ could promote the expression of autophagy gene Beclin1 and interfere the expression of autophagy gene Beclin1 with small interfering RNA, thus inhibiting the effect of type III interferon on anti-proliferation and promoting apoptosis of lung cancer cell. These results suggested that IFN λ could inhibit the proliferation of A549 cells by activating autophagy pathway, and IFN λ might be one of the potential therapeutic drugs for lung cancer.

Intelligent Sensors of Lead Based on a Reconfigurable DNA-Supramolecule Logic Platform.

The lead (Pb) hazard is not only in connection with the concentration of Pb2+ but also closely related to the ambience which affects its mobility and the synergistic toxicity with other ions. However, most of the existent methods focus highly on detecting Pb2+ concentration accurately but can seldom reflect the pollution-related information in actual samples, thereby limiting their pragmatic applications. In this work, a DNA-supramolecule logic platform was established, which can be configurated to implement three information process functions and act as three unique intelligent sensors of Pb. The demultiplexer that can split signal flow was used to determine Pb2+ in different pH conditions; the multiplexer that can alternate signal channels was applied to detect Pb2+ or Ag+ selectively; and the decoder that can extract information was utilized to test Pb2+ and the coexisted Ni2+ simultaneously. All three intelligent sensors based on the logic prototypes present practicable sensitivities and specificities. Considering its flexibility, scalability, and reconfigurability, we believe the logic platform may provide new solutions to process sophisticated information and implement intelligent analysis in environmental monitoring, biochemical detecting, and medical diagnosis.

Screening and identification of potential protein biomarkers for evaluating the efficacy of intensive therapy in pulmonary tuberculosis.

This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy.

Downregulation of Survivin Gene Expression Affects Ionizing Radiation Resistance of Human T98 Glioma Cells.

Survivin is a tumor-associated gene, which has been detected in a wide variety of human tumors. Previous research has shown that Survivin can affect hepatoma carcinoma cell radiosensitivity. However, little is known about the role of Survivin in ionizing radiation resistance in glioma cells. In this study, we aimed to identify the effects of Survivin on ionizing radiation resistance in glioma cell line T98. Our results showed that downregulation of Survivin gene expression and ionizing irradiation could both inhibit T98 cell proliferation by assays in vitro including CCK-8 and immunohistochemistry. The inhibitory effect of downregulation of Survivin combined with irradiation was the most significant compared with other groups. Results of Western blotting and flow cytometric analysis also showed that downregulation of Survivin combined with the irradiation group achieved the highest apoptosis rate. Experimental results in vivo by intracranial implanting into nude mice were consistent with those in vitro. These findings indicated that ionizing radiation resistance of human T98 glioma cells can be inhibited effectively after Survivin gene silencing.

Anti-Aging Effect of Chitosan Oligosaccharide on d-Galactose-Induced Subacute Aging in Mice.

Chitosan oligosaccharide (COS), a natural polysaccharide with good antioxidant and anti-inflammatory properties, is the depolymerized product of chitosan possessing various biological activities. The present study was designed to investigate the possible anti-aging effect of COS on the aging model mouse induced by d-galactose (d-gal) and explore the underlying mechanism. In the experiment, 48 male Kunming mice (KM mice) were randomly divided into the normal group, model group, positive group, and low-medium-high dose polysaccharide groups (300, 600, 1200 mg/kg/day). The results showed that COS, by intragastric gavage after subcutaneous injection of d-gal (250 mg/kg/day) into the neck of mice consecutively for eight weeks, gradually recovered the body weight, the activity of daily living, and organ indices of mice, as well as effectively ameliorated the histological deterioration of the liver and kidney in mice triggered by d-gal. To be specific, COS obviously improved the activities of antioxidant enzymes in liver and kidney of KM mice, including catalase (CAT), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD), as well as decreased malondialdehyde (MDA) levels when compared with those in model group mice. Furthermore, COS not only elevated the diminished levels of serum immunoglobulin G (IgG) and IgM induced by d-gal, but also significantly inhibited the d-gal-caused upregulation of serum alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), uric acid (UA) and creatinine (CREA) levels as compared with those of mice in the model group. These results demonstrate that COS has an obvious anti-aging activity in d-gal-induced subacute aging mice, the mechanism of which, to some extent, is associated with enhancing the antioxidant defenses, reducing oxidative stress, and improving the immune function of aging model mice.

Transcriptome data analysis of grass carp (Ctenopharyngodon idella) infected by reovirus provides insights into two immune-related genes.

Grass carp (Ctenopharyngodon idella) was one of the economically important freshwater fish in China. However, hemorrhagic disease caused by grass carp reovirus (GCRV) results in a tremendous loss in the process of grass carp cultivation. Transcriptome analysis could provide a comprehensive understanding of the molecular mechanisms involved in specific biological processes and diseases for the resistance to reovirus infection of grass carp. In this study, the raw data from NCBI (accession number: SRA099702) were analyzed, in which, 50 significant differentially expressed genes by routine transcriptome analysis and 84 notably differentially expressed genes by co-expression network method. KEGG analysis revealed that the pathway in hemorrhagic diseases in grass carp was similar to the influenza A induced pathway. The interferon-stimulated gene ISG15 and sacsin-like gene, which were up-regulated in data (SRA099702), were also up-regulated in data (SRP049081) from a similar assay. QPCR experiment was performed to validate these up-regulated genes. The ISG15 gene was shown to be the core gene in the co-expression network. The results would enhance our understanding of the antivirus system of grass carp infected by reovirus.

A systematic analysis of the resistance and sensitivity of HER2YVMA receptor tyrosine kinase mutant to tyrosine kinase inhibitors in HER2-positive lung cancer.

Human epidermal growth factor receptor 2 (HER2) has become a well-established target for the treatment of HER2-positive lung cancer. However, a frequently observed in-frame mutation that inserts amino acid quadruplex Tyr776-Val777-Met778-Ala779 at G776 (G776(YVMA)) in HER2 kinase domain can cause drug resistance and sensitivity, largely limiting the application of reversible tyrosine kinase inhibitors in lung cancer therapy. A systematic investigation of the intermolecular interactions between the HER2(YVMA) mutant and clinical small-molecule inhibitors would help to establish a complete picture of drug response to HER2 G776(YVMA) insertion in lung cancer, and to design new tyrosine kinase inhibitors with high potency and selectivity to target the lung cancer-related HER2(YVMA) mutant. Here, we combined homology modeling, ligand grafting, structure minimization, molecular simulation and binding affinity analysis to profile a number of tyrosine kinase inhibitors against the G776(YVMA) insertion in HER2. It is found that the insertion is far away from HER2 active pocket and thus cannot contact inhibitor ligand directly. However, the insertion is expected to induce marked allosteric effect on some regions around the pocket, including A-loop and hinges connecting between the N- and C-lobes of HER2 kinase domain, which may exert indirect influence to inhibitor binding. Most investigated inhibitors exhibit weak binding strength to both wild-type and mutant HER2, which can be attributed to steric hindrance that impairs ligand compatibility with HER2 active pocket. However, the cognate inhibitor lapatinib and the non-cognate inhibitor bosutinib were predicted to have low affinity for wild-type HER2 but high affinity for HER2(YVMA) mutant, which was confirmed by subsequent kinase assay experiments; the inhibitory potencies of bosutinib against wild-type and mutant HER2 were determined to be IC(50) > 1000 and =27 nM, respectively, suggesting that the bosutinib might be exploited as a selective inhibitor for mutant over wild-type HER2. Structural examination revealed that formation of additional non-bonded interactions such as hydrogen bonds and hydrophobic contacts with HER2 A-loop region due to G776(YVMA) insertion is the primary factor to improve bosutinib affinity upon the mutation.

Backplane aberration calibration of spatial light modulators using a phase-retrieval algorithm.

The calibration and correction of backplane aberration of a liquid-crystal spatial light modulator (LCSLM) are important for its proper functioning. To simplify the calibration procedurally, we study a random-illumination-phase-retrieval-based method. Our method improves the convergence of the phase-retrieval-based calibration and reduces the calibration complexity. However, the cross talk of the LCSLM deteriorates the calibration performance. We determined the relationship between the probability density function of the random phases and the light-intensity pattern and proposed an algorithm to compensate for the cross talk. We conducted a series of simulations to test the performance of the above-mentioned algorithms. The results show that our algorithms are effective and outperform other methods.