Large field-of-view pine wilt disease tree detection based on improved YOLO v4 model with UAV images.

Introduction: Pine wilt disease spreads rapidly, leading to the death of a large number of pine trees. Exploring the corresponding prevention and control measures for different stages of pine wilt disease is of great significance for its prevention and control. Methods: To address the issue of rapid detection of pine wilt in a large field of view, we used a drone to collect multiple sets of diseased tree samples at different times of the year, which made the model trained by deep learning more generalizable. This research improved the YOLO v4(You Only Look Once version 4) network for detecting pine wilt disease, and the channel attention mechanism module was used to improve the learning ability of the neural network. Results: The ablation experiment found that adding the attention mechanism SENet module combined with the self-designed feature enhancement module based on the feature pyramid had the best improvement effect, and the mAP of the improved model was 79.91%. Discussion: Comparing the improved YOLO v4 model with SSD, Faster RCNN, YOLO v3, and YOLO v5, it was found that the mAP of the improved YOLO v4 model was significantly higher than the other four models, which provided an efficient solution for intelligent diagnosis of pine wood nematode disease. The improved YOLO v4 model enables precise location and identification of pine wilt trees under changing light conditions. Deployment of the model on a UAV enables large-scale detection of pine wilt disease and helps to solve the challenges of rapid detection and prevention of pine wilt disease.

Antiglomerular basement membrane antibody type rapidly progressive glomerulonephritis with seizures: Two cases and literature review.

BACKGROUND: Rapidly progressive glomerulonephritis (RPGN) is clinically manifestations as a rapidly progressive renal failure and pathologically as crescentic and necrotizing lesions with infiltration of inflammatory cells in the glomeruli. Uremic encephalopathy (UE) usually develops in patients who are suffering from acute or chronic renal failure. OBJECTIVE: The purpose of this article is to provide reference for clinical diagnosis and treatment of renal disease complicated with seizures. Patients Two cases of anti-glomerular basement membrane type rapidly progressive glomerulonephritis complicated with seizures were reported. MATERIALS & METHODS: In case 1, a 40-year-old woman was hospitalized for the treatment of nausea, anorexia, and fever. On admission, she presented with elevated serum inflammatory indicators, moderate anemia, and advanced acute kidney injury requiring hemodialysis. Her anti-glomerular basement membrane (GBM) antibody in serum and renal tissues was found to be extremely high. She was finally diagnosed with anti-GBM disease. She was treated with a combination of corticosteroid pulse therapy, oral cyclophosphamide and prednisolone, and plasma exchange, while continued to require maintenance hemodialysis for end-stage kidney disease. During treatment, she suddenly suffered blindness, seizure, and consciousness disturbance. She was diagnosed as posterior reversible leukoencephalopathy syndrome by magnetic resonance imaging (MRI). The posterior reversible leukoencephalopathy syndrome subsided quickly after control of her hypertension and reinforcement of immunosuppressive treatment. In case 2, the patient also developed epileptic symptoms on the basis of GBM disease, and was given treatment similar to that of Case 1, so that the epileptic symptoms were controlled. RESULT: Reversible posterior leukoencephalopathy syndrome, especially when accompanied by cerebral hemorrhage, may lead to irreversible and lethal neurological abnormalities, and nephrologists should, therefore, be aware of the potential risk of reversible posterior leukoencephalopathy syndrome in patients with anti-GBM disease. We can discuss the current two cases in the light of the previous literature.

Volumes of hippocampal subfields suggest a continuum between schizophrenia, major depressive disorder and bipolar disorder.

Objective: There is considerable debate as to whether the continuum of major psychiatric disorders exists and to what extent the boundaries extend. Converging evidence suggests that alterations in hippocampal volume are a common sign in psychiatric disorders; however, there is still no consensus on the nature and extent of hippocampal atrophy in schizophrenia (SZ), major depressive disorder (MDD) and bipolar disorder (BD). The aim of this study was to verify the continuum of SZ - BD - MDD at the level of hippocampal subfield volume and to compare the volume differences in hippocampal subfields in the continuum. Methods: A total of 412 participants (204 SZ, 98 MDD, and 110 BD) underwent 3 T MRI scans, structured clinical interviews, and clinical scales. We segmented the hippocampal subfields with FreeSurfer 7.1.1 and compared subfields volumes across the three diagnostic groups by controlling for age, gender, education, and intracranial volumes. Results: The results showed a gradual increase in hippocampal subfield volumes from SZ to MDD to BD. Significant volume differences in the total hippocampus and 13 of 26 hippocampal subfields, including CA1, CA3, CA4, GC-ML-DG, molecular layer and the whole hippocampus, bilaterally, and parasubiculum in the right hemisphere, were observed among diagnostic groups. Medication treatment had the most effect on subfields of MDD compared to SZ and BD. Subfield volumes were negatively correlated with illness duration of MDD. Positive correlations were found between subfield volumes and drug dose in SZ and MDD. There was no significant difference in laterality between diagnostic groups. Conclusion: The pattern of hippocampal volume reduction in SZ, MDD and BD suggests that there may be a continuum of the three disorders at the hippocampal level. The hippocampus represents a phenotype that is distinct from traditional diagnostic strategies. Combined with illness duration and drug intervention, it may better reflect shared pathophysiology and mechanisms across psychiatric disorders.

Facial emotion perception abilities are related to grey matter volume in the culmen of cerebellum anterior lobe in drug-naïve patients with first-episode schizophrenia.

Impaired capability for understanding and interpreting the expressions on other people's faces manifests itself as a core feature of schizophrenia, contributing to social dysfunction. With the purpose of better understanding of the neurobiological basis of facial emotion perception deficits in schizophrenia, we investigated facial emotion perception abilities and regional structural brain abnormalities in drug-naïve patients with first-episode schizophrenia, and then examined the correlation between them. Fifty-two drug-naive patients with first-episode schizophrenia and 29 group-matched healthy controls were examined for facial emotion perception abilities assessed with the Facial Emotion Categorization and performed magnetic resonance imaging. The Facial Emotion Categorization data were inserted into a logistic function model so as to calculate shift point and slope as outcome measurements. Voxel-based morphometry was applied to investigate regional grey matter volume (GMV) alterations. The relationship between facial emotion perception and GMV was explored in patients using voxel-wise correlation analysis within brain regions that showed a significant GMV alterations in patients compared with controls. The schizophrenic patients performed differently on Facial Emotion Categorization tasks from the controls and presented a higher shift point and a steeper slope. Relative to the controls, patients showed GMV reductions in the superior temporal gyrus, middle occipital gyrus, parahippocampa gyrus, posterior cingulate, the culmen of cerebellum anterior lobe, cerebellar tonsil, and the declive of cerebellum posterior lobe. Importantly, abnormal performance on Facial Emotion Categorization was found correlated with GMV alterations in the culmen of cerebellum anterior lobe in schizophrenia. This study suggests that reduced GMV in the culmen of cerebellum anterior lobe occurs in first-episode schizophrenia, constituting a potential neuropathological basis for the impaired facial emotion perception in schizophrenia.

An Exergoeconomic Analysis of a Gas-Type Industrial Drying System of Black Tea.

The performance evaluation and optimization of an energy conversion system design of an energy intensive drying system applied the method of combining exergy and economy is a theme of global concern. In this study, a gas-type industrial drying system of black tea with a capacity of 100 kg/h is used to investigate the exergetic and economic performance through the exergy and exergoeconomic methodology. The result shows that the drying rate of tea varies from the maximum value of 3.48 gwater/gdry matter h to the minimum 0.18 gwater/gdry matter h. The highest exergy destruction rate is found for the drying chamber (74.92 kW), followed by the combustion chamber (20.42 kW) in the initial drying system, and 51.83 kW and 21.15 kW in the redrying system. Similarly, the highest cost of the exergy destruction rate is found for the drying chamber (18.497 USD/h), followed by the combustion chamber (5.041 USD/h) in the initial drying system, and 12.796 USD/h and 5.222 USD/h in the redrying system. Furthermore, we analyzed the unit exergy rate consumed and the unit exergy cost of water removal in different drying sections of the drying system, and determined the optimal ordering of each component. These results mentioned above indicate that, whether from an energy or economic perspective, the component improvements should prioritize the drying chamber. Accordingly, minimizing exergy destruction and the cost of the exergy destruction rate can be considered as a strategy for improving the performance of energy and economy. Overall, the main results provide a more intuitive judgment for system improvement and optimization, and the exergy and exergoeconomic methodology can be commended as a method for agricultural product industrial drying from the perspective of exergoeconomics.

Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm.

The application of agricultural robots can liberate labor. The improvement of robot sensing systems is the premise of making it work. At present, more research is being conducted on weeding and harvesting systems of field robot, but less research is being conducted on crop disease and insect pest perception, nutritional element diagnosis and precision fertilizer spraying systems. In this study, the effects of the nitrogen application rate on the absorption and accumulation of nitrogen, phosphorus and potassium in sweet maize were determined. Firstly, linear, parabolic, exponential and logarithmic diagnostic models of nitrogen, phosphorus and potassium contents were constructed by spectral characteristic variables. Secondly, the partial least squares regression and neural network nonlinear diagnosis model of nitrogen, phosphorus and potassium contents were constructed by the high-frequency wavelet sensitivity coefficient of binary wavelet decomposition. The results show that the neural network nonlinear diagnosis model of nitrogen, phosphorus and potassium content based on the high-frequency wavelet sensitivity coefficient of binary wavelet decomposition is better. The R2, MRE and NRMSE of nn of nitrogen, phosphorus and potassium were 0.974, 1.65% and 0.0198; 0.969, 9.02% and 0.1041; and 0.821, 2.16% and 0.0301, respectively. The model can provide growth monitoring for sweet corn and a perception model for the nutrient element perception system of an agricultural robot, while making preliminary preparations for the realization of intelligent and accurate field fertilization.

Performance of Exergetic, Energetic and Techno-Economic Analyses on a Gas-Type Industrial Drying System of Black Tea.

The purpose of this research work is to perform detailed exergetic, energetic and techno-economic analysis of the black tea drying process in the gas-type industrial dryer. Exergy-energy and techno-economic methodology was applied to investigate the heat loss, exergetic and energetic performance, exergy efficiency, improvement potential rate, sustainability index and techno-economic performance of a drying system. The results showed that the heat loss of exhaust air in the late drying process played a main contributing role in the heat loss and exergy loss of the whole drying system. Therefore, the exergy efficiency of the initial drying period and the redrying period varied from 38.08% to 65.09% and 24.76% to 26.97%, respectively. In addition, the improvement potential rate and sustainability index of the whole system varied from 6.93 kW to 12.94 kW and 1.33 to 2.86, respectively. The improvement potential obtained in the present work indicated that the drying operation is greatly in need of exergy performance improvement. Finally, the net present value and payback period obtained from techno-economic analysis were 179,442.03 USD and 5.3 years, the result is useful for investors or contractors to refer to and make investment decisions.

Fabrication and Performance of Graphene Flexible Pressure Sensor with Micro/Nano Structure.

Laser-induced graphene (LIG) has been widely used in flexible sensors due to its excellent mechanical properties and high conductivity. In this paper, a flexible pressure sensor prepared by bionic micro/nanostructure design and LIG mass fraction regulation is reported. First, prepared LIG and conductive carbon paste (CCP) solutions were mixed to obtain a conductive polymer. After the taro leaf structure was etched on the surface of the aluminum alloy plate by Nd:YAG laser processing, the conductive polymer was evenly coated on the template. Pressure sensors were packaged with a stencil transfer printing combined with an Ecoflex flexible substrate. Finally, the effects of different laser flux and the proportion of LIG in the composite on the sensitivity of the sensor are discussed. The results show that when the laser flux is 71.66 J·cm-2 and the mass fraction of LIG is 5%, the sensor has the best response characteristics, with a response time and a recovery time of 86 ms and 101 ms, respectively, with a sensitivity of 1.2 kPa-1 over a pressure range of 0-6 kPa, and stability of 650 cycle tests. The LIG/CCP sensor with a bionic structure demonstrates its potential in wearable devices.

Genetic diversity and population structure analysis in a large collection of white clover (Trifolium repens L.) germplasm worldwide.

White clover is an important temperate legume forage with high nutrition. In the present study, 448 worldwide accessions were evaluated for the genetic variation and polymorphisms using 22 simple sequence repeat (SSR) markers. All the markers were highly informative, a total of 341 scored bands were amplified, out of which 337 (98.83%) were polymorphic. The PIC values ranged from 0.89 to 0.97 with an average of 0.95. For the AMOVA analysis, 98% of the variance was due to differences within the population and the remaining 2% was due to differences among populations. The white clover accessions were divided into different groups or subgroups based on PCoA, UPGMA, and STRUCTURE analyses. The existence of genetic differentiation between the originally natural and introduced areas according to the PCoA analysis of the global white clover accessions. There was a weak correlation between genetic relationships and geographic distribution according to UPGMA and STRUCTURE analyses. The results of the present study will provide the foundation for future breeding programs, genetic improvement, core germplasm collection establishment for white clover.

Two independent mouse lines carrying the Nav1.7 I228M gain-of-function variant display dorsal root ganglion neuron hyperexcitability but a minimal pain phenotype.

ABSTRACT: Small-fiber neuropathy (SFN), characterized by distal unmyelinated or thinly myelinated fiber loss, produces a combination of sensory dysfunction and neuropathic pain. Gain-of-function variants in the sodium channel Nav1.7 that produce dorsal root ganglion (DRG) neuron hyperexcitability are present in 5% to 10% of patients with idiopathic painful SFN. We created 2 independent knock-in mouse lines carrying the Nav1.7 I228M gain-of-function variant, found in idiopathic SFN. Whole-cell patch-clamp and multielectrode array recordings show that Nav1.7 I228M knock-in DRG neurons are hyperexcitable compared with wild-type littermate-control neurons, but despite this, Nav1.7 I228M mice do not display mechanical or thermal hyperalgesia or intraepidermal nerve fiber loss in vivo. Therefore, although these 2 Nav1.7 I228M knock-in mouse lines recapitulate the DRG neuron hyperexcitability associated with gain-of-function mutations in Nav1.7, they do not recapitulate the pain or neuropathy phenotypes seen in patients. We suggest that the relationship between hyperexcitability in sensory neurons and the pain experienced by these patients may be more complex than previously appreciated and highlights the challenges in modelling channelopathy pain disorders in mice.

Research Progress of Graphene-Based Flexible Humidity Sensor.

Graphene is a new type of carbon material with a flexible, two-dimensional structure. Due to the excellent stability of its lattice structure and its mechanical flexibility, graphene-based materials can be applied in flexible humidity sensors. At present, the application of graphene-based flexible humidity sensors in the fields of medical care and environmental monitoring is attracting widespread attention. In this review, the basic properties of graphene oxide (GO) and reduced graphene oxide (rGO) as moisture-sensitive materials and methods for their preparation were introduced. Moreover, three methods for improving the performance of moisture-sensitive materials were discussed. The working principle of different types of graphene-based humidity sensors were introduced. The progress in the research on graphene-based flexible humidity sensors in four respects: Human respiration, skin moisture, human sweat, and environmental humidity were discussed. Finally, the future research, following the development trends and challenges, to develop the potential of integrated, graphene-based flexible humidity sensors were discussed.

Fingerprint identification of white clover cultivars based on SSR molecular markers.

White clover (Trifolium repens L.) is an important perennial legume forage with high productivity and quality. To strengthen the basic research on the genetic characteristics, fingerprint identification and adaptability of white clover germplasm resources, Simple sequence repeat (SSR) molecular markers were applied to 10 white clover cultivars to assess the genetic diversity and related lines of white clover at the molecular level in order to lay a theoretical foundation for the selection of high-quality seeds and cultivars of white clover. A total of 120 different bands were amplified by 29 pairs of SSR primers with good polymorphism, of which 103 (89.5%) were polymorphic. Meanwhile, the PIC of each primer was 0.181-0.588, with an average of 0.329. Analysis of molecular variance revealed that 57% of the genetic variation occurred within cultivars and 43% occurred among cultivars. The results of cluster analysis and the principal coordinate analysis revealed that the parental relationships of the 10 cultivars, with the 'Purple' cultivar very distantly related to the other 9 cultivars and the closest parental relationship between 'Ladino' and 'Sulky'. The fingerprints constructed by three representative primers (gtrs679, gtrs319, and gtrs678) have a strong identification ability. In summary, the SSR markers had good polymorphism and could be used for DNA fingerprint analysis of white clover cultivars.

Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques.

Pine wilt disease (PWD) caused by pine wood nematode (PWN, Bursaphelenchus xylophilus) originated in North America and has since spread to Asia and Europe. PWN is currently a quarantine object in 52 countries. In recent years, pine wilt disease has caused considerable economic losses to the pine forest production industry in China, as it is difficult to control. Thus, one of the key strategies for controlling pine wilt disease is to identify epidemic points as early as possible. The use of hyperspectral cameras mounted on drones is expected to enable PWD monitoring over large areas of forest, and hyperspectral images can reflect different stages of PWD. The trend of applying hyperspectral techniques to the monitoring of pine wilt disease is analyzed, and the corresponding strategies to address the existing technical problems are proposed, such as data collection of early warning stages, needs of using unmanned aerial vehicles (UAVs), and establishment of models after preprocessing.

Abnormalities of regional homogeneity and its correlation with clinical symptoms in Naïve patients with first-episode schizophrenia.

Several resting-state neuroimaging studies have indicated abnormal regional homogeneity (ReHo) in chronic schizophrenia; however, little work has been conducted to investigate naïve patients with first-episode schizophrenia (FES). Even less investigated is the association between ReHo measures and clinical symptom severity in naïve patients with FES. The current study evaluated ReHo alterations in whole brain, and assessed the correlations between ReHo measures and clinical variables in naïve patients with FES. Forty-four naïve patients with FES and 26 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Group-level analysis was utilized to analyze the ReHo differences between FES and HC in a voxel-by-voxel manner. Severity of symptoms was evaluated using a five-factor model of the Positive and Negative Syndrome Scale (PANSS). The correlation between the severity of symptoms and ReHo map was examined in patients using voxel-wise correlation analyses within brain areas that showed a significant ReHo alteration in patients compared with controls. Compared with the healthy control group, the FES group showed a significant decrease in ReHo values in the left medial frontal gyrus (MFG), right precentral gyrus, left superior temporal gyrus (STG), left left middle temporal gyrus (MTG), left thalamus, and significant increase in ReHo values in the left MFG, left inferior parietal lobule (IPL), left precuneus, and right lentiform nucleus (LN). In addition, the correlation analysis showed the PANSS total score negatively correlated with ReHo in the right precentral gyrus and positively correlated with ReHo in the left thalamus, the positive factor positively correlated with ReHo in the right thalamus, the disorganized/concrete factor positively correlated with ReHo in left posterior cingulate gyrus (PCG), the excited factor positively correlated with ReHo in the left precuneus, and the depressed factor negatively correlated with ReHo in the right postcentral gyrus and positively correlated with ReHo in the right thalamus. Our results indicate that widespread ReHo abnormalities occurred in an early stage of schizophrenic onset, suggesting a potential neural basis for the pathogenesis and symptomatology of schizophrenia.

Higher serum VGF protein levels discriminate bipolar depression from major depressive disorder.

Misdiagnosis between major depressive disorder (MDD) and bipolar depression (BD) is quite common. Our previous study found significantly lower serum VGF (non-acronymic) in MDD patients. However, it is unclear whether same changes occur in BD patients. Therefore, we aimed to investigate the relationship between serum VGF levels in BD and MDD patients. General information, scores of 17-item Hamilton Depression Rating Scale (HDRS), and fasting blood samples of all participants including 30 MDD patients, 20 BD patients, and 30 healthy controls (HC) were collected. Serum VGF levels were measured by Enzyme-linked immunosorbent assay kits. Pearson correlation analysis was used to analyze correlations between serum VGF levels and clinical information. Receiver operating characteristic (ROC) curve and likelihood ratios (LRs) were used to analyze the differential potential of serum VGF. Serum VGF levels were significantly lower in MDD patients but higher in BD patients compared with HC (both PTukey < 0.01). No correlation was found between serum VGF levels and any data of subjects. The optimal cutoff for serum VGF in discriminating BD patients from MDD patients was ≥1093.85 pg/ml (AUC = 0.990, sensitivity of 95%, specificity of 100% and accuracy of 95%). LRs further confirmed the differential efficiency of serum VGF in distinguishing BD and MDD patients with +LR of infinity and -LR of 0. The results suggest that serum VGF level changed significantly in MDD and BD patients and serum VGF may be an indicator for differentiating BD patients from MDD patients.

The Novel Activity of Carbamazepine as an Activation Modulator Extends from NaV1.7 Mutations to the NaV1.8-S242T Mutant Channel from a Patient with Painful Diabetic Neuropathy.

Neuropathic pain in patients carrying sodium channel gain-of-function mutations is generally refractory to pharmacotherapy. However, we have shown that pretreatment of cells with clinically achievable concentration of carbamazepine (CBZ; 30 µM) depolarizes the voltage dependence of activation in some NaV1.7 mutations such as S241T, a novel CBZ mode of action of this drug. CBZ reduces the excitability of dorsal root ganglion (DRG) neurons expressing NaV1.7-S241T mutant channels, and individuals carrying the S241T mutation respond to treatment with CBZ. Whether the novel activation-modulating activity of CBZ is specific to NaV1.7, and whether this pharmacogenomic approach can be extended to other sodium channel subtypes, are not known. We report here the novel NaV1.8-S242T mutation, which corresponds to the NaV1.7-S241T mutation, in a patient with neuropathic pain and diabetic peripheral neuropathy. Voltage-clamp recordings demonstrated hyperpolarized and accelerated activation of NaV1.8-S242T. Current-clamp recordings showed that NaV1.8-S242T channels render DRG neurons hyperexcitable. Structural modeling shows that despite a substantial difference in the primary amino acid sequence of NaV1.7 and NaV1.8, the S242 (NaV1.8) and S241 (NaV1.7) residues have similar position and orientation in the domain I S4-S5 linker of the channel. Pretreatment with a clinically achievable concentration of CBZ corrected the voltage dependence of activation of NaV1.8-S242T channels and reduced DRG neuron excitability as predicted from our pharmacogenomic model. These findings extend the novel activation modulation mode of action of CBZ to a second sodium channel subtype, NaV1.8.

CD24 is a Potential Biomarker for Prognosis in Human Breast Carcinoma.

BACKGROUND/AIMS: CD24 is a highly glycosylated mucin-like antigen on the cell surface, which has recently emerged as a novel oncogene and metastasis promoter. We performed bioinformatics analysis to investigate whether CD24 can serve as a prognostic indicator in breast cancer. METHODS: CD24 expression was assessed using SAGE Genie tools and Oncomine analysis. The PrognoScan database, Kaplan-Meier Plotter, and bc-GenExMiner were used to identify the prognostic roles of CD24 in breast cancer. RESULTS: We found that CD24 was more frequently overexpressed in breast cancer than in normal breast tissue and correlated with worse prognosis. Meanwhile, high CD24 expression was associated with increased risk of HER2, basal-like, triple-negative breast cancer, and higher Scarff-Bloom-Richardson grade. Data mining in multiple big databases confirmed a positive correlation between CD24 mRNA expression and SDC1 mRNA expression in breast cancer tissue. CONCLUSIONS: Our findings suggest that CD24 overexpression is more common in breast cancer than in corresponding normal tissue. In addition, CD24 and SDC1 can serve as prognostic indicators for breast cancer. However, large-scale and comprehensive research is needed to further confirm these results.

Nonmuscle myosin II isoforms interact with sodium channel alpha subunits.

Sodium channels play pivotal roles in health and diseases due to their ability to control cellular excitability. The pore-forming α-subunits (sodium channel alpha subunits) of the voltage-sensitive channels (i.e., Nav1.1-1.9) and the nonvoltage-dependent channel (i.e., Nax) share a common structural motif and selectivity for sodium ions. We hypothesized that the actin-based nonmuscle myosin II motor proteins, nonmuscle myosin heavy chain-IIA/myh9, and nonmuscle myosin heavy chain-IIB/myh10 might interact with sodium channel alpha subunits to play an important role in their transport, trafficking, and/or function. Immunochemical and electrophysiological assays were conducted using rodent nervous (brain and dorsal root ganglia) tissues and ND7/23 cells coexpressing Nav subunits and recombinant myosins. Immunoprecipitation of myh9 and myh10 from rodent brain tissues led to the coimmunoprecipitation of Nax, Nav1.2, and Nav1.3 subunits, but not Nav1.1 and Nav1.6 subunits, expressed there. Similarly, immunoprecipitation of myh9 and myh10 from rodent dorsal root ganglia tissues led to the coimmunoprecipitation of Nav1.7 and Nav1.8 subunits, but not Nav1.9 subunits, expressed there. The functional implication of one of these interactions was assessed by coexpressing myh10 along with Nav1.8 subunits in ND7/23 cells. Myh10 overexpression led to three-fold increase ( P < 0.01) in the current density of Nav1.8 channels expressed in ND7/23 cells. Myh10 coexpression also hyperpolarized voltage-dependent activation and steady-state fast inactivation of Nav1.8 channels. In addition, coexpression of myh10 reduced ( P < 0.01) the offset of fast inactivation and the amplitude of the ramp currents of Nav1.8 channels. These results indicate that nonmuscle myosin heavy chain-IIs interact with sodium channel alpha subunits subunits in an isoform-dependent manner and influence their functional properties.

Combined serum levels of multiple proteins in tPA-BDNF pathway may aid the diagnosis of five mental disorders.

Mental disorders are severe, disabling conditions with unknown etiology and are commonly misdiagnosed when clinical symptomology criteria are solely used. Our previous work indicated that combination of serum levels of multiple proteins in tissue plasminogen activator (tPA)-brain-derived neurotrophic factor (BDNF) pathway improved accuracy of diagnosis of major depressive disorder (MDD). Here, we measured serum levels of tPA, plasminogen activator inhibitor-1 (PAI-1), BDNF, precursor-BDNF (proBDNF), tropomyosin-related kinase B (TrkB) and neurotrophin receptor p75 (p75NTR) in patients with paranoid schizophrenia (SZ, n = 34), MDD (n = 30), bipolar mania (BM, n = 30), bipolar depression (BD, n = 22), panic disorder (PD, n = 30), and healthy controls (HCs, n = 30) by Enzyme-linked immunosorbent assay kits. We used receiver operating characteristic (ROC) curve to analyze diagnostic potential of these proteins. We found, compared with HCs, that serum tPA and proBDNF were lower in SZ, BM and BD; TrkB was lower in SZ and BD; and p75NTR was declined in SZ and BM. ROC analysis showed that combined serum level of tPA, PAI-1, BDNF, proBDNF, TrkB and p75NTR was better than any single protein in accuracy of diagnosis and differentiation, suggesting that the combination of multiple serum proteins levels in tPA-BDNF pathway may have a potential for a diagnostic panel in mental disorders.

Diagnostic accuracy of ELISA for detecting serum Midkine in cancer patients.

Midkine (MK) has been reported as the potential novel diagnostic biomarker for cancer in several studies, but their results were controversial. Therefore, we performed a diagnostic meta-analysis to assess the diagnostic value of serum MK in cancer patients. A systematic electronic and manual search was performed for relevant literatures through several databases up to June 1, 2017. The quality of the studies included in the meta-analysis was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. All analyses were conducted using stata12.0 software. Ten studies collectively included 1119 cancer patients and 1441 controls met the eligible criteria. The summary estimates were: sensitivity 0.78 (95% CI = 0.68-0.85), specificity 0.83 (95% CI = 0.72-0.90), positive likelihood ratio 4,54 (95% CI = 2.64-7.80), negative likelihood 0.27 (95% CI = 0.18-0.40), diagnostic odds ratio 16.79 (95% CI = 7.17-39.33), and area under the curve 0.87 (95% CI = 0.84-0.89). Publication bias was suggested by Deeks' funnel plot asymmetry test (P = 0.92). According to our results, serum MK has greater diagnostic value in diagnosing cancer, however, more reliable studies in larger cohort should be conducted to evaluate the diagnostic accuracy of serum MK.