Precision Medicine in Rheumatic Diseases: Unlocking the Potential of Antibody-Drug Conjugates.

In the era of precision medicine, antibody-drug conjugates (ADCs) have emerged as a cutting-edge therapeutic strategy. These innovative compounds combine the precision of monoclonal antibodies with the potent cell-killing or immune-modulating abilities of attached drug payloads. This unique strategy not only reduces off-target toxicity but also enhances the therapeutic effectiveness of drugs. Beyond their well established role in oncology, ADCs are now showing promising potential in addressing the unmet needs in the therapeutics of rheumatic diseases. Rheumatic diseases, a diverse group of chronic autoimmune diseases with varying etiologies, clinical presentations, and prognoses, often demand prolonged pharmacological interventions, creating a pressing need for novel, efficient, and low-risk treatment options. ADCs, with their ability to precisely target the immune components, have emerged as a novel therapeutic strategy in this context. This review will provide an overview of the core components and mechanisms behind ADCs, a summary of the latest clinical trials of ADCs for the treatment of rheumatic diseases, and a discussion of the challenges and future prospects faced by the development of next-generation ADCs. SIGNIFICANCE STATEMENT: There is a lack of efficient and low-risk targeted therapeutics for rheumatic diseases. Antibody-drug conjugates, a class of cutting-edge therapeutic drugs, have emerged as a promising targeted therapeutic strategy for rheumatic disease. Although there is limited literature summarizing the progress of antibody-drug conjugates in the field of rheumatic disease, updating the advancements in this area provides novel insights into the development of novel antirheumatic drugs.

Mid1 promotes synovitis in rheumatoid arthritis via ubiquitin-dependent post-translational modification.

INTRODUCTION: Current anti-rheumatic drugs are primarily modulating immune cell activation, yet their effectiveness remained suboptimal. Therefore, novel therapeutics targeting alternative mechanisms, such as synovial activation, is urgently needed. OBJECTIVES: To explore the role of Midline-1 (Mid1) in synovial activation. METHODS: NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were used to establish a subcutaneous xenograft model. Wild-type C57BL/6, Mid1-/-, Dpp4-/-, and Mid1-/-Dpp4-/- mice were used to establish a collagen-induced arthritis model. Cell viability, cell cycle, qPCR and western blotting analysis were used to detect MH7A proliferation, dipeptidyl peptidase-4 (DPP4) and Mid1 levels. Co-immunoprecipitation and proteomic analysis identified the candidate protein of Mid1 substrates. Ubiquitination assays were used to determine DPP4 ubiquitination status. RESULTS: An increase in Mid1, an E3 ubiquitin ligase, was observed in human RA synovial tissue by GEO dataset analysis, and this elevation was confirmed in a collagen-induced mouse arthritis model. Notably, deletion of Mid1 in a collagen-induced arthritis model completely protected mice from developing arthritis. Subsequent overexpression and knockdown experiments on MH7A, a human synoviocyte cell line, unveiled a previously unrecognized role of Mid1 in synoviocyte proliferation and migration, the key aspects of synovial activation. Co-immunoprecipitation and proteomic analysis identified DPP4 as the most significant candidate of Mid1 substrates. Mechanistically, Mid1 promoted synoviocyte proliferation and migration by inducing ubiquitin-mediated proteasomal degradation of DPP4. DPP4 deficiency led to increased proliferation, migration, and inflammatory cytokine production in MH7A, while reconstitution of DPP4 significantly abolished Mid1-induced augmentation of cell proliferation and activation. Additionally, double knockout model showed that DPP4 deficiency abolished the protective effect of Mid1 defect on arthritis. CONCLUSION: Overall, our findings suggest that the ubiquitination of DPP4 by Mid1 promotes synovial cell proliferation and invasion, exacerbating synovitis in RA. These results reveal a novel mechanism that controls synovial activation, positioning Mid1 as a promising target for therapeutic intervention in RA.

A novel adaptive filter with a heart-rate-based reference signal for esophageal pressure signal denoising.

Esophageal pressure (Peso) is one of the most common and minimally invasive methods used to assess the respiratory and lung mechanics in patients receiving mechanical ventilation. However, the Peso measurement is contaminated by cardiogenic oscillations (CGOs), which cannot be easily eliminated in real-time. The field of study dealing with the elimination of CGO from Peso signals is still in the early stages of its development. In this study, we present an adaptive filtering-based method by constructing a reference signal based on the heart rate and sine function to remove CGOs in real-time. The proposed technique is tested using clinical data acquired from 20 patients admitted to the intensive care unit. Lung compliance ( QUOTE ) and esophageal pressure swings (△Pes) are used to evaluate the performance and efficiency of the proposed technique. The CGO can be efficiently suppressed when the constructional reference signal contains the fundamental, and second and third harmonic frequencies of the heart rate signal. The analysis of the data of 8 patients with controlled mechanical ventilation reveals that the standard deviation/mean of the QUOTE is reduced by 28.4-79.2% without changing the QUOTE and the △Pes measurement is more accurate, with the use of our proposed technique. The proposed technique can effectively eliminate the CGOs from the measured Peso signals in real-time without requiring additional equipment to collect the reference signal.

Self-Assembly of Cluster-Mediated 3D Catenanes with Size-Specific Recognition Behavior.

Although interlocked three-dimensional molecules display unique properties associated with their spatial structures, their synthesis and study of their host-guest properties remain challenging. We report the formation of a novel [2]catenane, [Et4N]@[(Tp*WS3Cu3Cl)2(cis-bpype)3]2(OTf)5 ([Et4N][1](OTf)5), by self-assembly of the cluster node [Tp*WS3Cu3Cl]+ and the organic linker (Z)-1,2-diphenyl-1,2-bis(4-(pyridin-4-yl)phenyl)ethene (cis-bpype). Single-crystal X-ray and NMR analyses established that [1]4+ is formed by the interpenetration of two cluster-organic cages. Unique cation-in-cation host-guest complexes were observed with this catenane. The crystalline, empty catenane was formed by taking advantage of the electrostatic repulsion-induced weak binding of the host. Encapsulation experiments also reveal that the empty catenane can adaptively encapsulate cations such as [Et4N]+ and [Pr4N]+ in the cross cavity but is unable to encapsulate [Bu4N]+ and [Me4N]+, although the size of the latter is compatible with that of the cavity. Theoretical calculations and volume analysis allow to unravel the ingenious role of catenane structures and the interplay between electrostatic repulsion and attractive noncovalent interactions for size-specific recognition behavior in host-guest systems involving species with similar electric charges.

Batch Similarity Based Triplet Loss Assembled into Light-Weighted Convolutional Neural Networks for Medical Image Classification.

In many medical image classification tasks, there is insufficient image data for deep convolutional neural networks (CNNs) to overcome the over-fitting problem. The light-weighted CNNs are easy to train but they usually have relatively poor classification performance. To improve the classification ability of light-weighted CNN models, we have proposed a novel batch similarity-based triplet loss to guide the CNNs to learn the weights. The proposed loss utilizes the similarity among multiple samples in the input batches to evaluate the distribution of training data. Reducing the proposed loss can increase the similarity among images of the same category and reduce the similarity among images of different categories. Besides this, it can be easily assembled into regular CNNs. To appreciate the performance of the proposed loss, some experiments have been done on chest X-ray images and skin rash images to compare it with several losses based on such popular light-weighted CNN models as EfficientNet, MobileNet, ShuffleNet and PeleeNet. The results demonstrate the applicability and effectiveness of our method in terms of classification accuracy, sensitivity and specificity.

A comprehensive analysis of subclass-specific IgG glycosylation in colorectal cancer progression by nanoLC-MS/MS.

Colorectal cancer is associated with changed IgG glycosylation, but the alteration in specific subclasses of IgG is unknown. Initially, we optimized five common IgG glycopeptide enrichment methods to acquire a comprehensive profile of IgG glycopeptides. However, an incomplete tryptic digestion of IgG occurred when using an ordinary protease to protein ratio, which significantly impacted the final statistical analysis. Herein, we introduced a two-step enzymatic digestion, enabling the complete digestion of IgG glycopeptides and further improving the detection intensity of the target glycopeptides. In order to rapidly process and automatically integrate the MS data, we developed a simple and effective code using MATLAB. Following statistical analysis, we observed that IgG1_H3N4F1 and IgG1_H3N4 were substantially increased in CRC, while IgG1_H5N5F1, IgG1_H5N4F1S1 and IgG2_H5N4F1 were markedly decreased. A further evaluation of the diagnostic performance showed that they all achieved a fair performance in discriminating the patients from the normal. In terms of the glycan features, it was demonstrated that the CRC progression was associated with increased agalactosylation, and the decreased digalactosylation and galactosylation per antenna on the diantenna glycans of IgG1 and IgG2. Concurrently, the decreased sialylation of IgG1 was strongly correlated with CRC. Moreover, an analysis of tumor-specific glycosylation showed that the alterations of IgG glycosylation were more significant in colon cancer, and no obvious difference was observed between colon and rectal cancer. This study comprehensively optimized the glycopeptide enrichment methods, evaluated the enzymatic digestion effect, and explored the association between CRC progression and subclass-specific glycosylation.

Safety and use of pulmonary function tests: a retrospective study from a single center over seven years' clinical practice.

BACKGROUND: To promote the utilization of pulmonary function tests (PFT) through analyzing the data of PFT during the past seven years in one large teaching hospital in China. METHODS: Through a retrospective analysis, the allocation of full-time staff in PFT room, the demographic characteristics of patients, cost-effectiveness of PFT, positive rate and failure rate of PFT, adverse events were analyzed. RESULTS: 1) From 2012 to 2018, the numbers of PFT showed the trend of escalation year by year. The proportion of patients receiving PFT rose from 29.0/10,000 in 2012 to 34.7/10,000 in 2018. The best allocation of PFT room was 20-25/ person / day. 2) The number of PFT provided by Department of Pulmonary and Critical Care Medicine (PCCM) accounted for 97.2, 97.1, 97.3, 97.8, 97.8, 98.0, and 98.2% of the total cases of outpatient PFT in the same year. The top three departments in the inpatient department were Department of Thoracic Surgery, Department of General Surgery, and Department of Urinary Surgery, the total cases of PFT in these three departments accounted for 65.1, 64.4, 62.1, 63.5, 62.4, 65.3 and 69.1% of the total cases of inpatient PFT in the same year. 3) Data from 2018 showed that the revenue from PFT was about 3.7 million Chinese Yuan, and that the salary of personnel and expenditure on machine maintenance and wear were about 800,000 Chinese Yuan. 4) 58.2% of the patients who had undergone PFT had ventilatory dysfunction. 5) The average failure rate of PFT in the past seven years was 1.91%. 6) The main adverse events of PFT examination were dizziness, amaurosis, limb numbness, lip numbness and falls. The incidence rates were 0.49, 0.42, 0.41, 0.39, 0.44, 0.48, and 0.45% respectively, with an average of 0.44%. CONCLUSIONS: The number of PFT showed an upward trend in the past seven years, and the optimal staffing of PFT room was 20-25 cases per person per day. The positive rate of pulmonary dysfunction was 58.2%. The failure rate of PFT and the incidence of adverse events were very low, suggesting it is a simple and safe clinical examination. It's worthy of further popularization and promotion.

H19 promotes non-small-cell lung cancer (NSCLC) development through STAT3 signaling via sponging miR-17.

LncRNAs can exhibit crucial roles in the development of multiple cancers, including non-small cell lung cancer (NSCLC). Currently, we investigated the role of lncRNA H19 in NSCLC. In our study, it was found that H19 was upregulated in A549 and H1299 cells compared to normal lung epithelial BEAS-2B cells. Meanwhile, we observed that miR-17 was downregulated in NSCLC cell lines. Inhibited H19 can suppress the growth, migration, and invasion of NSCLC cells and bioinformatics search was performed to predict the correlation between H19 and miR-17. Overexpression of miR-17 was able to inhibit the progression of NSCLC cells while reversely miR-17 inhibitors reversed this process. In addition, signal transducers and activators of transcription (STAT3), as an mRNA target of miR-17, was presented in our research. Moreover, we discovered that H19 demonstrated its biological functions via regulating miR-17 and STAT3 in vitro. Silencing H19 greatly increased STAT3 expression by sponging miR-19 in vitro. It was hypothesized that H19 may serve as a competing endogenous RNA (ceRNA) to modulate STAT3 by attaching miR-17 in lung cancer. In summary, our findings indicated that H19/miR-17/STAT3 axis participated in NSCLC development. H19 could be regarded as a significant prognostic biomarker in NSCLC progression.

Long noncoding RNA LINC00961 inhibits cell proliferation and induces cell apoptosis in human non-small cell lung cancer.

Long noncoding RNAs (LncRNAs) have been identified in multiple human cancer types, including lung cancer. An increasing number of studies have indicated that lncRNAs can function as important gene regulators. However, the biological mechanism of LINC00961 in lung cancerremains poorly understood. In our current study, we recognized lncRNA LINC00961, and we observed that it was significantly reduced in human non-small cell lung cancer (NSCLC) tissues. LINC00961 was elevated by infecting LV-LINC00961, while decreased by LV-shLINC00961 in H226 and A549 cells. Furthermore, it was shown that LINC00961 overexpression greatly inhibited lung cancer cell proliferation, whereas downregulated LINC00961 induced cell proliferation. In addition, further experiments showed that restoration of LINC00961 could dramatically increase apoptotic ratios of NSCLC H226 and A549 cells, and knockdown of LINC00961 exhibited an opposite effect. Moreover, Western blot analysis showed that upregulation of LINC00961 repressed proliferating cell nuclear antigen expression and increased Bax expression, indicating that it acts as an important pro-apoptosis gene. Conversely, inhibition of LINC00961 induced proliferating cell nuclear antigen expression and restrained Bax protein levels. Taking these together, LINC00961 might play a tumor suppressive role in NSCLC progression, and it could serve as a novel prognostic biomarker in NSCLC diagnosis and treatment.

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

Inhibition of hepatitis C virus by an M1GS ribozyme derived from the catalytic RNA subunit of Escherichia coli RNase P.

BACKGROUND: Hepatitis C virus (HCV) is a human pathogen causing chronic liver disease in about 200 million people worldwide. However, HCV resistance to interferon treatment is one of the important clinical implications, suggesting the necessity to seek new therapies. It has already been shown that some forms of the catalytic RNA moiety from E. coli RNase P, M1 RNA, can be introduced into the cytoplasm of mammalian cells for the purpose of carrying out targeted cleavage of mRNA molecules. Our study is to use an engineering M1 RNA (i.e. M1GS) for inhibiting HCV replication and demonstrates the utility of this ribozyme for antiviral applications. RESULTS: By analyzing the sequence and structure of the 5' untranslated region of HCV RNA, a putative cleavage site (C67-G68) was selected for ribozyme designing. Based on the flanking sequence of this site, a targeting M1GS ribozyme (M1GS-HCV/C67) was constructed by linking a custom guide sequence (GS) to the 3' termini of catalytic RNA subunit (M1 RNA) of RNase P from Escherichia coli through an 88 nt-long bridge sequence. In vitro cleavage assays confirmed that the engineered M1GS ribozyme cleaved the targeted RNA specifically. Moreover, ~85% reduction in the expression levels of HCV proteins and >1000-fold reduction in viral growth were observed in supernatant of cultured cells that transfected the functional ribozyme. In contrast, the HCV core expression and viral growth were not significantly affected by a "disabled" ribozyme (i.e. M1GS-HCV/C67*). Moreover, cholesterol-conjugated M1GS ribozyme (i.e. Chol-M1GS-HCV/C67) showed almost the same bioactivities with M1GS-HCV/C67, demonstrating the potential to improve in vivo pharmacokinetic properties of M1GS-based RNA therapeutics. CONCLUSION: Our results provide direct evidence that the M1GS ribozyme can function as an antiviral agent and effectively inhibit gene expression and multiplication of HCV.

[Determination of the in vitro antiviral activity of an engineered M1GS ribozyme that targets to the core gene of hepatitis C virus].

OBJECTIVE: Hepatitis C virus (HCV) is one of the major pathogens that lead to viral hepatitis. At present, Interferon treatment in combination with ribavirin is the first line clinical therapeutic approach. However, the responses are usually poor and the viral infection reoccurs. Therefore, exploring new antiviral agents and therapies is under urgent needs. METHODS: The sequence and structure of the core coding region of HCV genome were analyzed through the two computer software, DNAMAN and RNA Structure. The cytosine 52 nt downstream of the AUG initiation triplet was identified as the optimal target cleavage site. Based on the flanking sequence of this assumed cleavage site, a guide sequence (GS) was designed and covalently linked to the 3 prime terminus of the M1 RNA, which is catalytic subunit of the RNase P derived from Escherichia coli using PCR. We named this new targeting ribozyme M1GS-HCV/C52 and it antiviral activities were analyzed in cultured cells. RESULTS: In the in vitro cleavage assay, M1GS-HCV/C52 ribozyme could effectively cleave the HCV target RNA into two fragments at the specific cleavage site. Moreover, comparing to the blank control, this engineered M1GS ribozyme could reduce the core protein expression of more than 80% in the HCV-infected host cell and lead to a 1500-fold reduction of HCV RNA copies in the culture supernatant. An another M1GS ribozyme, M1GS-HCV/C52*, which has the same guide sequence but does not contain a 24nt-long bridge sequence, did not exhibit apparent inhibition for the expression of HCV core gene and viral proliferation in our paralleled assay. CONCLUSION: We successfully constructed an M1GS ribozyme showing affective and specific cleavage of target viral RNA. Further results showed that the engineering ribozyme had notably antiviral activity in cultured cells, thus provided a new promising approach for clinical anti-HCV therapeutic strategy.

Determinants of gastric cancer screening attendance in Southeastern China: a cross-sectional study.

OBJECTIVES: This study aimed to identify the determinants of gastric cancer screening attendance among individuals aged 40 years in a region with high gastric cancer in China. DESIGN: An anonymous, cross-sectional survey was conducted between October 2021 and March 2022. SETTING: A self-administered online survey was conducted in Fujian Province in Southeastern China. PARTICIPANTS: People aged 40 years living in five selected cities in Fujian Province with no history of cancer. MAIN OUTCOME MEASURES: Gastric cancer screening attendance was measured with the question 'Have you ever been screened for gastric cancer in the past'. RESULTS: In total, 2547 complete responses were obtained. The mean age of respondents was 47.72±7.20 years, and 59.8% were men. A total of 42.6% of participants reported that they had undergone gastric cancer screening. The result of multivariable logistic regression analysis showed that participants with a first-degree relative affected with gastric cancer (OR=2.02, 95% CI: 1.58 to 2.59) and high perceived susceptibility of gastric cancer (OR=2.03, 95% CI: 1.58 to 2.59) were the strongest facilitators for screening attendance. Other factors positively associated with screening attendance were age 51-60 years (OR=1.69, 95% CI: 1.31 to 2.18), living in urban regions (OR=1.27, 95% CI: 1.05 to 1.55), friends/neighbours/colleagues with gastric cancer (OR=1.30, 95% CI: 1.07 to 1.58), history of chronic gastric disease (OR=1.90, 95% CI: 1.57 to 2.30), perceived high cost (OR=1.28, 95% CI: 1.01 to 1.61) and physician recommendation (OR=1.71, 95% CI: 1.36 to 2.16). On the other hand, factors negatively associated with screening attendance included perceived barriers, namely screening is only necessary when symptoms present (OR=0.71, 95% CI: 0.58 to 0.87) and perceived appointment for gastroscopy screening is difficult and time-consuming (OR=0.75, 95% CI: 0.60 to 0.94). No significant association was found between knowledge level and participation in screening. CONCLUSION: This study highlights important individual-level factors and barriers to gastric cancer screening. Strategies targeting under-screened populations and eliminating patient-perceived barriers to gastric cancer screening are essential.

Medical Image Classification Using Light-weight CNN with Spiking Cortical Model Based Attention Module.

In the field of disease diagnosis where only a small dataset of medical images may be accessible, the light-weight convolutional neural network (CNN) has become popular because it can help to avoid the over-fitting problem and improve computational efficiency. However, the feature extraction capability of the light-weight CNN is inferior to that of the heavy-weight counterpart. Although the attention mechanism provides a feasible solution to this problem, the existing attention modules, such as the squeeze and excitation module and the convolutional block attention module, have insufficient non-linearity, thereby influencing the ability of the light-weight CNN to discover the key features. To address this issue, we have proposed a spiking cortical model based global and local (SCM-GL) attention module. The SCM-GL module analyzes the input feature maps in parallel and decomposes each map into several components according to the relation between pixels and their neighbors. The components are weighted summed to obtain a local mask. Besides, a global mask is produced by discovering the correlation between the distant pixels in the feature map. The final attention mask is generated by combining the local and global masks, and it is multiplied by the original map so that the important components can be highlighted to facilitate accurate disease diagnosis. To appreciate the performance of the SCM-GL module, this module and some mainstream attention modules have been embedded into the popular light-weight CNN models for comparison. Experiments on the classification of brain MR, chest X-ray, and osteosarcoma image datasets demonstrate that the SCM-GL module can significantly improve the classification performance of the evaluated light-weight CNN models by enhancing the ability of discovering the suspected lesions and it is generally superior to state-of-the-art attention modules in terms of accuracy, recall, specificity and F1 score.

Health-Related Quality of Life and Influencing Factors in Coronary Heart Disease Based on the Scale QLICD-CHD (V2.0): A Cross-Sectional Study.

Purpose: Coronary heart disease (CHD) is difficult to cure, so more attention should be paid to improving patients' health-related quality of life (HRQoL). This paper focuses on identifying factors that affect HRQoL. Patients and Methods: Overall, 189 in-patients with coronary heart disease were investigated at the Affiliated Hospital of Guangdong Medical University between 2015 and 2016. The scale Quality of Life Instruments for Chronic Diseases-Coronary heart disease (QLICD-CHD V2.0) was used to evaluate HRQoL and collect demographic information. Medical records were applied to collect patients' clinical indicators. A simple correlation analysis, Student's t-test, and a one-way analysis of variance were first performed to filter factors that might associate with HRQoL, and multiple linear regression was applied to finally identify related factors. Results: Findings from multiple linear regression showed that the total score was related to family economy, treatment, indirect bilirubin, and albumin with regression coefficient B=5.209, -6.615, 0.378, and 0.548, respectively. The physical functions were related to treatment, albumin, globular proteins, chloride, and red blood cell count with B=-9.031, 1.000, 0.612, 1.320, and 5.161, respectively. The psychological function was in association with family economy, clinical course, serum phosphorus, and percentage of lymphocyte population with B=7.487, 6.411, -16.458, and 0.090, respectively. The social function was associated with family economy, blood urea nitrogen, serum creatinine, and platelet distribution width with B=7.391, 1.331, -0.060, and -0.929, respectively. The special module was in association with treatment, indirect bilirubin, and serum calcium with B=-7.791, 0.414, and 23.017, respectively. Conclusion: Clinical indicators including albumin, globular proteins, chloride, red blood cell count, serum phosphorus, percentage of lymphocyte population, blood urea nitrogen, serum creatinine, platelet distribution width, indirect bilirubin, and serum calcium, as well as socio-demographic factors including the family economy, clinical course, and treatment, may affect coronary heart disease patients' HRQoL.

[Classification of plastics with laser-induced breakdown spectroscopy based on principal component analysis and artificial neural network model].

The classification of seven kinds of plastic (ABS, PET, PP, PS, PVC, HDPE and PMMA) with the laser-induced breakdown spectroscopy based on artificial neural network model was investigated in the present paper. One hundred seventy LIBS spectra for each type of plastic were collected. Firstly, all 1 190 plastics LIBS spectra were studied with principal component analysis. The first five principal components (PC) totally explain 78.4% of the original spectrum information. Therefore, the scores of five PCs of 130 LIBS spectra for each kind of plastic were chosen as the training set to build a back-propagation artificial network model. And the other 40 LIBS spectra of each sample were used as the testing set for the trained model. The classification accuracy was 97.5%. Experimental results demonstrate that plastics can be classified by using principal component analysis and artificial neural network (BP) method.

[Activation of JNK induces apoptosis to autophagy conversion and enhances the survival of oxygen-glycogen deprived rat neurons].

Objective To investigate the efficacy and mechanism of c-Jun N-terminal kinase (JNK) in boosting survival of oxygen glucose deprivation (OGD) rat neurons. Methods The cortex neurons from fetal rats were primarily cultured to prepare a model of OGD neurons in vitro, and the characteristic endpoints were filtered to intervene with JNK inducer anisomycin (AN), respectively. The cells were randomly divided into control group, solvent control group (a same volume of solvent DMSO was added into the culture medium of the OGD neuron), AN group (OGD neurons were treated with JNK inducer AN for 5 hours at the end of OGD). After that, Western blotting and immunofluorescence cytometry were respectively performed to detect the protein expressions in OGD neurons, including beclin 1, microtubule-associated protein 1 light chain 3 (LC3), B cell lymphoma 2 (Bcl2), caspase-3, P62, ubiquitin, cathepsin B and lysosomal associated membrane protein 1 (LAMP1). The cell activity was evaluated by CCK-8 assay, and the axon length was measured by IPP software. Results Activation of JNK significantly promoted the expressions of beclin 1, LC3, and Bcl2, and markedly reduced the content of beclin 1-Bcl2 complex and attenuated the expressions of P62 and ubiquitin. Meanwhile, the expressions of cathepsin B and LAMP1 were not obviously altered. In this way, the survival rate of OGD neurons was improved. Conclusion Activation of JNK exerts a neuroprotective effect by facilitating dissociation of beclin 1-Bcl2 and inducing a switch from apoptosis to autophagy in OGD neurons.

New wine in old bottles: current progress on P5 ATPases.

P5 ATPases are evolutionarily conserved P-type transporters. Despite their important roles in the endoplasmic reticulum (ER) and in lysosomes, the substrate specificities and transporting mechanisms of P5 ATPases have remained mysterious. Recently, several studies have provided genetic, biochemical, and structural evidence to help elucidate the physiological functions and substrates of P5 ATPases. Here, we summarize this progress and discuss the potential transport mechanisms of the P5 ATPases-in particular, P5A ATPase-for further study.

Neural network compensation control of magnetic levitation ball position based on fuzzy inference.

Aiming at the problem of poor transient performance of the control system caused by the control uncertainty of the undertrained neural network, a neural network compensation control method based on fuzzy inference is proposed in this paper. The method includes three control substructures: fuzzy inference block, neural network control block and basic control block. The fuzzy inference block adaptively adjusts the neural network compensation control quantity according to the control error and the error rate of change, and adds a dynamic adjustment factor to ensure the control quality at the initial stage of network learning or at the moment of signal transition. The neural network control block is composed of an identifier and a controller with the same network structure. After the identifier learns the dynamic inverse model of the controlled object online, its training parameters are dynamically copied to the controller for real-time compensation control. The basic control block uses a traditional PID controller to provide online learning samples for the neural network control block. The simulation and experimental results of the position control of the magnetic levitation ball show that the proposed method significantly reduces the overshoot and settling time of the control system without sacrificing the steady-state accuracy of neural network compensation control, and has good transient and steady-state performance and strong robustness simultaneously.