A large deletion conferring pale green leaves of maize.

BACKGROUND: The structural basis of chloroplast and the regulation of chloroplast biogenesis remain largely unknown in maize. Gene mutations in these pathways have been linked to the abnormal leaf color phenotype observed in some mutants. Large scale structure variants (SVs) are crucial for genome evolution, but few validated SVs have been reported in maize and little is known about their functions though they are abundant in maize genomes. RESULTS: In this research, a spontaneous maize mutant, pale green leaf-shandong (pgl-sd), was studied. Genetic analysis showed that the phenotype of pale green leaf was controlled by a recessive Mendel factor mapped to a 156.8-kb interval on the chromosome 1 delineated by molecular markers gy546 and gy548. There were 7 annotated genes in this interval. Reverse transcription quantitative PCR analysis, SV prediction, and de novo assembly of pgl-sd genome revealed that a 137.8-kb deletion, which was verified by Sanger sequencing, might cause the pgl-sd phenotype. This deletion contained 5 annotated genes, three of which, including Zm00001eb031870, Zm00001eb031890 and Zm00001eb031900, were possibly related to the chloroplast development. Zm00001eb031870, encoding a Degradation of Periplasmic Proteins (Deg) homolog, and Zm00001eb031900, putatively encoding a plastid pyruvate dehydrogenase complex E1 component subunit beta (ptPDC-E1-ß), might be the major causative genes for the pgl-sd mutant phenotype. Plastid Degs play roles in protecting the vital photosynthetic machinery and ptPDCs provide acetyl-CoA and NADH for fatty acid biosynthesis in plastids, which were different from functions of other isolated maize leaf color associated genes. The other two genes in the deletion were possibly associated with DNA repair and disease resistance, respectively. The pgl-sd mutation decreased contents of chlorophyll a, chlorophyll b, carotenoids by 37.2%, 22.1%, and 59.8%, respectively, and led to abnormal chloroplast. RNA-seq revealed that the transcription of several other genes involved in the structure and function of chloroplast was affected in the mutant. CONCLUSIONS: It was identified that a 137.8-kb deletion causes the pgl-sd phenotype. Three genes in this deletion were possibly related to the chloroplast development, which may play roles different from that of other isolated maize leaf color associated genes.

Rapamycin facilitates differentiation of regulatory T cells via enhancement of oxidative phosphorylation.

We explored the interplay between energy metabolism and the impact of rapamycin (Rapa) on regulatory T cell (Treg) differentiation. Naïve CD4+ T cells were stimulated under Treg-polarizing conditions with or without Rapa. Rapa promoted Treg induction, as the expression of Foxp3 and Treg phenotypic markers were enhanced. Rapa disrupts glycolysis while favoring mitochondrial metabolism in induced Tregs (iTregs). Metabolic profiling showed reduced glycolytic metabolites in Rapa-treated iTregs, in line with the downregulation of glucose uptake and the expression of glycolytic enzymes. Conversely, Rapa increased the ratios of ATP/ADP and ATP/AMP, the production of mitochondrial ATP, and the expression of ATP5A. Treatment with oxidative phosphorylation inhibitors suppressed Foxp3 expression in Rapa-treated cells. Moreover, Rapa decreased oleic acid and palmitoleic acid levels and increased l-carnitine and acetylcarnitine levels and CPT1A expression in iTregs, indicative of augmented fatty acid oxidation. In conclusion, Rapa induces metabolic reprogramming in Tregs, affecting their differentiation.

Nanocomposites of graphene and zirconia for adsorption of organic-arsenic drugs: Performances comparison and analysis of adsorption behavior.

3-Nitro-4-hydroxy-phenylarsonic acid (3-NHPAA), an organic-arsenic compound, as one of widely used antibacterial veterinary drug, has greatly attracted the attention due to its potential threats on ecological environment. A series of the nanocomposites of zirconia nanoparticles with crystal phases (pure monoclinic, pure tetragonal and mixed phase (monoclinic + tetragonal)) anchored on reduced graphene oxide were produced through managing the concentration of triethanolamine solution and the reaction time. The effects of the crystal phases of the zirconia in the structure of the nanocomposites were played a key role in the adsorption performances of the 3-NHPAA. Experiment data identified the nanocomposites with monoclinic phase of zirconia excelled at the adsorption of the 3-NHPAA with a higher adsorption capacity up to 207.2 mg g-1. The uptake of the 3-NHPAA by the three nanocomposites was implemented within 60 min and highly pH-dependent which illustrated electrostatic attraction between them as a main mechanism during the adsorption process. A wider pH range (3.8-8.8) for the uptake of the 3-NHPAA by the nanocomposites with the monoclinic phase of zirconia was obtained compared with the nanocomposites containing tetragonal phase (3.8-5.9) or the mixed phase (3.8-7.1) of zirconia. The adsorption of the 3-NHPAA was well described by the pseudo-second order kinetic and Langmuir equations. The thermodynamic parameters suggested that the adsorption of the 3-NHPAA over the three nanocomposites was endothermic and spontaneous in nature. In summary, the nanocomposites of reduced graphene oxide and monoclinic phase of zirconia nanoparticles as an adsorbent were better to the adsorption of the 3-NHPAA.

Neuregulin-1 promotes mitochondrial biogenesis, attenuates mitochondrial dysfunction, and prevents hypoxia/reoxygenation injury in neonatal cardiomyocytes.

Neuregulin-1 (NRG-1)/erythroblastic leukaemia viral oncogene homologues (ErbB) pathway activation plays a crucial role in regulating the adaptation of the adult heart to physiological and pathological stress. In the present study, we investigate the effect of recombined human NRG-1 (rhNRG-1) on mitochondrial biogenesis, mitochondrial function, and cell survival in neonatal rat cardiac myocytes (NRCMs) exposed to hypoxia/reoxygenation (H/R). The results of this study showed that, in the H/R-exposed NRCMs, mitochondrial biogenesis was impaired, as manifested by the decrease of the expression of peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α) and mitochondrial membrane proteins, the inner membrane (Tim23), mitofusin 1 (Mfn1), and mitofusin 2 (Mfn2). RhNRG-1 pretreatment effectively restored the expression of PGC-1α and these membrane proteins, upregulated the expression of the anti-apoptosis proteins Bcl-2 and Bcl-xL, preserved the mitochondrial membrane potential, and attenuated H/R-induced cell apoptosis. Blocking PGC-1 expression with siRNA abolished the beneficial role of rhNRG-1 on mitochondrial function and cell survival. The results of the present study strongly suggest that NRG-1/ErbB activation enhances the adaption of cardiomyocytes to H/R injury via promoted mitochondrial biogenesis and improved mitochondrial homeostasis. SIGNIFICANCE OF THE STUDY: The results of this research revealed for the first time the relationship between neuregulin-1 (NRG-1)/erythroblastic leukaemia viral oncogene homologues (ErbB) activation and mitochondrial biogenesis in neonatal cardiomyocytes and verified the significance of this promoted mitochondrial biogenesis in attenuating hypoxia/reoxygenation injury. This finding may open a new field to further understand the biological role of NRG-1/ErbB signalling pathway in cardiomyocyte.

Celastrol mediates Th17 and Treg cell generation via metabolic signaling.

A T helper 17 (Th17) cell/regulatory T (Treg) cell imbalance is involved in many immune disorders and diseases. Celastrol, a Chinese herbal compound that has anti-inflammatory and immunosuppressive properties, has been indicated to suppress T cell proliferation and Th17 cell induction, while facilitating Forkhead box P3 (Foxp3) expression and Treg cell generation. In this study, we explored the impact and mechanism of celastrol on Th17 cell/induced Treg (iTreg) cell induction. CD4+CD25- T cells were purified, stimulated with anti-CD3 and anti-CD28 antibodies, and polarized in vitro to generate Th17 or iTreg cells in the presence or absence of celastrol. Initially, we determined that Interleukin (IL)-17 expression by celastrol-treated Th17 was significantly decreased compared with untreated cells; however, the frequency of Foxp3+ cells was increased in celastrol-treated cells. We verified that celastrol inhibited phospho-STAT3 expression in cultured Th17 cells and up-regulated phospho-STAT5 expression in iTreg cells. Furthermore, T cells treated with celastrol were more likely to participate in FAO metabolism instead of glycolysis. Celastrol suppressed the expression of glucose transporter, Glut1, and the rate-limiting enzyme, HK2, in addition to mTOR, HIF-1α, c-Myc and Akt expression in Th17 cells. Conversely, celastrol promoted FAO of lipids by up-regulating CPT1A and AMPKα expression in iTreg cells. Our results suggest that celastrol suppresses Th17 cell induction, while promoting the generation of iTreg cells. We found that celastrol inhibits glycolysis in Th17 cells and promotes FAO by iTreg cells, suggesting that celastrol could mediate the metabolism of Th17 and iTreg cells.

Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex.

Finger vein recognition has been considered one of the most promising biometrics for personal authentication. However, the capacities and percentages of finger tissues (e.g., bone, muscle, ligament, water, fat, etc.) vary person by person. This usually causes poor quality of finger vein images, therefore degrading the performance of finger vein recognition systems (FVRSs). In this paper, the intrinsic factors of finger tissue causing poor quality of finger vein images are analyzed, and an intensity variation (IV) normalization method using guided filter based single scale retinex (GFSSR) is proposed for finger vein image enhancement. The experimental results on two public datasets demonstrate the effectiveness of the proposed method in enhancing the image quality and finger vein recognition accuracy.

Efficient descriptor of histogram of salient edge orientation map for finger vein recognition.

Finger vein images are rich in orientation and edge features. Inspired by the edge histogram descriptor proposed in MPEG-7, this paper presents an efficient orientation-based local descriptor, named histogram of salient edge orientation map (HSEOM). HSEOM is based on the fact that human vision is sensitive to edge features for image perception. For a given image, HSEOM first finds oriented edge maps according to predefined orientations using a well-known edge operator and obtains a salient edge orientation map by choosing an orientation with the maximum edge magnitude for each pixel. Then, subhistograms of the salient edge orientation map are generated from the nonoverlapping submaps and concatenated to build the final HSEOM. In the experiment of this paper, eight oriented edge maps were used to generate a salient edge orientation map for HSEOM construction. Experimental results on our available finger vein image database, MMCBNU_6000, show that the performance of HSEOM outperforms that of state-of-the-art orientation-based methods (e.g., Gabor filter, histogram of oriented gradients, and local directional code). Furthermore, the proposed HSEOM has advantages of low feature dimensionality and fast implementation for a real-time finger vein recognition system.

Implications of the changes in serum neutrophil gelatinase-associated lipocalin and cystatin C in patients with chronic kidney disease.

AIM: Early intervention in patients with chronic kidney disease (CKD) significantly improves the prognosis. The present widely used markers of renal function, such as serum creatinine (sCr), fail to reflect early renal damage and predict the progression of disease. The authors aimed to evaluate whether neutrophil gelatinase-associated lipocalin (NGAL), a novel specific biomarker of acute kidney injury, could predict the progression of CKD. METHODS: We identified 92 patients with stage 2-4 CKD caused by primary chronic glomerulonephritis. The patients were followed for 2 years, the changes in NGAL levels in the progressive and non-progressive groups were compared. RESULTS: First, the serum NGAL levels of patients with stage 2-4 CKD were significantly increased compared with the control group. Second, based on Pearson correlation analysis, positive correlations existed between NGAL and cystatin C levels and between NGAL and sCr levels. Third, bounded by the progress of renal function, the area under the curve of serum NGAL was 0.872 (95% confidence interval, 0.786-0.933), which suggests a blood NGAL cut-off level of 246 ng/mL (sensitivity 85.19%, specificity 81.54%). Fourth, Kaplan-Meier survival curve analysis showed that the serum NGAL level was closely related to the end-point of renal function in patients with CKD. Fifth, Cox multivariate regression analysis showed that the estimated glomerular filtration rate and blood NGAL are associated with progression of CKD. CONCLUSION: Serum NGAL is an effective biomarker for detecting early-stage renal damage in CKD patients. Serum NGAL was significantly correlated with the severity of renal damage and the progression of renal function deterioration.

A high accuracy pedestrian detection system combining a cascade AdaBoost detector and random vector functional-link net.

In pedestrian detection methods, their high accuracy detection rates are always obtained at the cost of a large amount of false pedestrians. In order to overcome this problem, the authors propose an accurate pedestrian detection system based on two machine learning methods: cascade AdaBoost detector and random vector functional-link net. During the offline training phase, the parameters of a cascade AdaBoost detector and random vector functional-link net are trained by standard dataset. These candidates, extracted by the strategy of a multiscale sliding window, are normalized to be standard scale and verified by the cascade AdaBoost detector and random vector functional-link net on the online phase. Only those candidates with high confidence can pass the validation. The proposed system is more accurate than other single machine learning algorithms with fewer false pedestrians, which has been confirmed in simulation experiment on four datasets.

Expression of USP15, TßR-I and Smad7 in psoriasis.

The deubiquitinating enzyme ubiquitin specific peptidase 15 (USP15) is regarded as a regulator of TGFß signaling pathway. This process depends on Smad7, the inhibitory factor of the TGFß signal, and type I TGFß receptor (TßR-I), one of the receptors of TGFß. The expression level of USP15 seems to play vital roles in the pathogenesis of many neoplasms, but so far there has been no report about USP15 in psoriasis. In this study, immunohistochemical staining of USP15, TßR-I and Smad7 was performed in 30 paraffin-embedded psoriasis specimens and 10 normal specimens to investigate the expression of USP15, TßR-I and Smad7 in psoriasis and to explore the relevance among them. And USP15 small interfering RNA (USP15 siRNA) was used to transfect Hacat cells to detect the mRNA expression of TßR-I and Smad7. Of 30 cases of psoriasis in active stage, 28, 24 and 26 cases were positive for USP15, TßR-I and Smad7 staining, respectively. The positive rates of USP15 and Smad7 were significantly higher in psoriasis specimens than in normal skin specimens (44.1%±26.0% vs. 6.1%±6.6%, 47.2%±27.1% vs. 6.6%±7.1%), and positive rate of TßR-I (20.3%±22.2%) in psoriasis was lower than that in normal skin specimens (46.7%±18.2%). There was a significant positive correlation between USP15 and Smad7 expression, and significant negative correlations between USP15 and TßR-expression, an I d between TßR- and Smad7 expression I in psoriasis. After transfection of USP15 siRNA in Hacat cells, the expression of TßR-mRNA was up I -regulated and that of Smad7 was down-regulated. It is concluded that USP15 may play a role in the pathogenesis of psoriasis through regulating the TßR-I/Smad7 pathway and there may be other cell signaling pathways interacting with USP15 to take part in the development of psoriasis.

Automatic Segmentation of Bone Marrow Lesions on MRI Using a Deep Learning Method.

Bone marrow lesion (BML) volume is a potential biomarker of knee osteoarthritis (KOA) as it is associated with cartilage degeneration and pain. However, segmenting and quantifying the BML volume is challenging due to the small size, low contrast, and various positions where the BML may occur. It is also time-consuming to delineate BMLs manually. In this paper, we proposed a fully automatic segmentation method for BMLs without requiring human intervention. The model takes intermediate weighted fat-suppressed (IWFS) magnetic resonance (MR) images as input, and the output BML masks are evaluated using both regular 2D Dice similarity coefficient (DSC) of the slice-level area metric and 3D DSC of the subject-level volume metric. On a dataset with 300 subjects, each subject has a sequence of 36 IWFS MR images approximately. We randomly separated the dataset into training, validation, and testing sets with a 70%/15%/15% split at the subject level. Since not every subject or image has a BML, we excluded the images without a BML in each subset. The ground truth of the BML was labeled by trained medical staff using a semi-automatic tool. Compared with the ground truth, the proposed segmentation method achieved a Pearson's correlation coefficient of 0.98 between the manually measured volumes and automatically segmented volumes, a 2D DSC of 0.68, and a 3D DSC of 0.60 on the testing set. Although the DSC result is not high, the high correlation of 0.98 indicates that the automatically measured BML volume is strongly correlated with the manually measured BML volume, which shows the potential to use the proposed method as an automatic measurement tool for the BML biomarker to facilitate the assessment of knee OA progression.

A causal analysis of the relationship between exposure to sunlight and colorectal cancer risk: A Mendelian randomization study.

Several observational studies have found that exposure to sunlight reduces the risk of colorectal cancer (CRC). However, sun exposure remains ambiguous in its relationship to CRC. We carried out a Mendelian randomization (MR) study to explore the potential associations between them. We examined the exposure to sunlight summary statistics of the UK Biobank Consortium using a 2-sample MR analysis. Using data from the FinnGen consortium, we derived summary statistics for CRC. We conducted our analysis with various methods, incorporating inverse variance weighted (IVW) along with 4 other approaches. A Cochran Q statistic was used to measure the heterogeneity of instrumental variables (IVs). We screened 133 single nucleotide polymorphisms (SNPs) (time spent outdoors in summer), 41 SNPs (time spent outdoors in winter), and 35 SNPs (frequency of solarium/sunlamp use) representing sunlight exposure for MR analysis. All selected SNPs had an F-statistic >20, indicating that IVs did not weakly bias the results. The summer outdoor activity trait exhibited significant heterogeneity (Cochran Q statistic = 183.795, P = .002 < 0.05), but we found no horizontal polymorphisms or significant heterogeneity for the other exposure traits. According to IVW estimates, no causal association exists between time spent outdoors in summer and CRC (Odds Ratio, OR = 0.735, 95% confidence interval, CI = 0.494-1.017, P = .128 > 0.017). No causal relationship existed between time spent outdoors in winter and CRC, as indicated by Bonferroni-corrected adjusted p-values. The OR was 0.877 with a 95% CI of 0.334-2.299, and the P value was .789, more significant than the significance threshold of 0.017. The solarium/sunlamp use frequency was not associated with CRC (OR = 1.567, 95%CI = 0.243-10.119, P = .637 > .017). Also, an IVW with random effects was applied to determine the causal relationship between summer outdoor time and CRC. No causal association between summer outdoor time and CRC was found (OR = 0.735, 95% CI = 0.494-1.017, P = .128 > .017). Additionally, 4 additional analyses yielded similar results. The findings of our study suggest that exposure to sunlight may reduce CRC risk, but the causal relationship remains unsolved. There is no evidence to suggest that exposure to sunlight prevents CRC. Randomized, controlled trials are needed to determine whether sunlight exposure protects against CRC.

Mechanisms of cyclosporine-induced renal cell apoptosis: a systematic review.

BACKGROUND/AIMS: Chronic cyclosporine A (CsA) nephrotoxicity (CCN) is an important cause of chronic renal dysfunction with no effective clinical intervention. To further elucidate the mechanisms of renal cell apoptosis in CCN, all relevant in vivo studies on this subject were analyzed. METHODS: We searched for in vivo studies on the mechanisms of CsA-induced renal cell apoptosis in Medline (1966-July 2010), Embase (1980-July 2010) and ISI (1986-July 2010). The studies were evaluated for their quality according to a set of in vivo standards, data extracted according to PICOS, and then synthesized. RESULTS: Renal cell apoptosis was an important feature of CCN and an important factor of renal dysfunction. First, CsA could upregulate Fas/Fas ligand, downregulate Bcl-2/Bcl-XL, and increase caspase-1 and caspase-3. Second, it could induce oxidative stress and damage the antioxidant defense system. Third, it could increase endoplasmic reticulum stress protein in a dose- and time-dependent manner. Fourth, CsA could impair the urine concentration and decrease the expression of hypertonicity-induced genes. Fifth, CsA-induced renal cell apoptosis was significantly decreased by blocking the angiotensin II type 1 receptor using losartan. CONCLUSIONS: The in vivo mechanisms for CCN are more complex than those found in vitro. CsA can induce renal cell apoptosis using five pathways in vivo and activated caspases might be the ultimate intersection of these pathways and the common intracellular pathway mediating apoptosis. These data provide new potential points for intervention and need to be confirmed by further studies.

Over-expression of microRNA-494 up-regulates hypoxia-inducible factor-1 alpha expression via PI3K/Akt pathway and protects against hypoxia-induced apoptosis.

BACKGROUND: Hypoxia-inducible factor-1 alpha (HIF-1α) is one of the key regulators of hypoxia/ischemia. MicroRNA-494 (miR-494) had cardioprotective effects against ischemia/reperfusion (I/R)-induced injury, but its functional relationship with HIF-1α was unknown. This study was undertaken to determine if miR-494 was involved in the induction of HIF-1α. RESULTS: Quantitative RT-PCR showed that miR-494 was up-regulated to peak after 4 hours of hypoxia in human liver cell line L02. To investigate the role of miR-494, cells were transfected with miR-494 mimic or miR-negative control, followed by incubation under normoxia or hypoxia. Our results indicated that overexpression of miR-494 significantly induced the expression of p-Akt, HIF-1α and HO-1 determined by qRT-PCR and western blot under normoxia and hypoxia, compared to negative control (p < 0.05). While LY294002 treatment markedly abolished miR-494-inducing Akt activation, HIF-1α and HO-1 increase under both normoxic and hypoxic conditions (p < 0.05). Moreover, apoptosis detection using Annexin V indicated that overexpression of miR-494 significantly decreased hypoxia-induced apoptosis in L02 cells, compared to control (p < 0.05). MiR-494 overexpression also decreased caspase-3/7 activity by 1.27-fold under hypoxia in L02 cells. CONCLUSIONS: Overexpression of miR-494 upregulated HIF-1α expression through activating PI3K/Akt pathway under both normoxia and hypoxia, and had protective effects against hypoxia-induced apoptosis in L02 cells. Thus, these findings suggested that miR-494 might be a target of therapy for hepatic hypoxia/ischemia injury.

Robust finger vein ROI localization based on flexible segmentation.

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system.

IL-36 cytokine expression and its relationship with p38 MAPK and NF-κB pathways in psoriasis vulgaris skin lesions.

This study examined the correlation of the expression of interleukin-36 (IL-36), a novel member of interleukin-1 (IL-1) family, with p38 mitogen-activated protein kinase (p38 MAPK) and nuclear factor-kappa B (NF-κB) pathways in psoriasis vulgaris skin lesions. The expression levels of IL-36α, IL-36ß, IL-36Γ, phosphorylated p38 MAPK, and NF-κBp65 were detected in the skin tissues of 38 psoriasis patients and 17 healthy control subjects by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting. The cytokine expression levels were compared between the psoriasis group and the control group. A correlation analysis between cytokine proteins was performed in the psoriasis group. Results showed that the expression levels of IL-36a, IL-36ß, IL-36Γ, phosphorylated p38 MAPK and NF-κBp65 in the psoriasis group were significantly higher than those in the control group (P<0.001). In the psoriasis group, the IL-36 cytokine expression was positively correlated with phosphorylated p38 MAPK and NF-κBp65 expression (P<0.05). A significant positive correlation was also found between the phosphorylated p38 MAPK and NF-κBp65 expression (P<0.01). It was concluded that the increased IL-36 expression is correlated with p38 MAPK and NF-κB pathways in psoriasis vulgaris skin lesions. All the three factors may be jointly involved in the pathogenesis and local inflammatory response of psoriasis.

Exploring the Influence of Hepatitis B Immunoglobulin on the Immune Response to the Hepatitis B Vaccine in a Mouse Model.

Background: The extent to which maternal antibodies against the hepatitis B surface antigen (HBsAb) acquired transplacentally affect the immune responses to the hepatitis B vaccine (HBVac) in infants is still uncertain. Objective: To explore the impact of the HBsAb on the immune response to the HBVac in a mouse model. Methods: According to the doses of the HBVac (2, 5 µg) injected, 267 BALB/c mice were divided into two groups. Each group was subdivided into 3 subgroups based on the doses of the hepatitis B immunoglobulin (HBIG) (0, 25, 50 IU) administered. The HBsAb titers were detected 4 weeks after completing the HepB vaccination. Results: Among all the mice, 40 had an HBsAb titer <100 mIU/mL (non- or low-response to the HBVac). The rates of the HBsAb titer <100 mIU/mL in 0, 25 and 50 IU HBIG groups were 1.1%, 23.1%, and 20.7%, respectively. Multivariate logistic regression analysis showed that the risk factors for low- or non-response to the HBVac were injection with the HBIG, low HBVac dose, and hypodermic injection. The mean HBsAb titers (log10) reduced gradually in the 0, 25 and 50 IU HBIG groups (P<0.001). Conclusion: The HBIG administration has negative impacts on the peak level of the HBsAb and the rate of an effective immune response. This implies that the maternal HBsAb acquired transplacentally might inhibit the immune responses to the HBVac in infants.

Automatic Measuring of Finger Joint Space Width on Hand Radiograph using Deep Learning and Conventional Computer Vision Methods.

Hand osteoarthritis (OA) severity can be assessed visually through radiographs using semi-quantitative grading systems. However, these grading systems are subjective and cannot distinguish minor differences. Joint space width (JSW) compensates for these disadvantages, as it quantifies the severity of OA by accurately measuring the distances between joint bones. Current methods used to assess JSW require users' interaction to identify the joints and delineate initial joint boundary, which is time-consuming. To automate this process and offer a more efficient and robust measurement for JSW, we proposed two novel methods to measure JSW: 1) The segmentation-based (SEG) method, which uses traditional computer vision techniques to calculate JSW; 2) The regression-based (REG) method, which is a deep learning approach employing a modified VGG-19 network to predict JSW. On a dataset with 3,591 hand radiographs, 10,845 DIP joints were cut as regions of interest and served as input to the SEG and REG methods. The bone masks of the ROI images generated by a U-Net model were sent as input in addition to the ROIs. The ground truth of JSW was labeled by a trained research assistant using a semi-automatic tool. Compared with the ground truth, the REG method achieved a correlation coefficient of 0.88 and mean square error (MSE) of 0.02 mm on the testing set; the SEG method achieved a correlation coefficient of 0.42 and MSE of 0.15 mm. Results show the REG method has promising performance in automatic JSW measurement and in general, Deep Learning approaches can facilitate the automatic quantification of distance features in medical images.

Dendritic cells transduced with lentiviral vector targeting RelB gene using RNA interference induce hyporesponsiveness in memory CD4(+) T cells and naïve CD4(+) T cells.

The ability of DCs to induce immune tolerance depends on its maturation status. RelB plays a pivotal role in DCs differentiation. A therapeutic protocol of DCs-based not only induces hyporesponsiveness in T(N)s, but also in alloreactive T(M)s is required. Thus, it is urgent to assess modulatory effects of RelB-silenced DCs on T(M)s and T(N)s. In this study, we constructed lentiviral vector which could efficiently silenced the RelB in DCs (DCs-miR RelB) to keep them immature. These DCs induced antigen-specific hyporesponsiveness in CD4(+) T(N)s. In contrast, upon re-stimulation with mature DCs, CD4(+) T(M)s primed by DCs-miR RelB maintained hyporesponsiveness in terms of proliferation and cytokine production. And these may be associated with micro155 and micro181a expression levels in T(M)s and T(N)s. These results may help developing the DCs-based therapeutical protocols by inducing hyporesponsiveness in CD4(+) T(N)s and T(M)s.

A novel segmentation method for breast ultrasound images based on neutrosophic l-means clustering.

PURPOSE: Fully automatic and accurate breast lesion segmentation is an essential and challenging task. In this paper, the authors develop a novel, effective, and fully automatic method for breast ultrasound (BUS) image segmentation. METHODS: The segmentation method utilizes a novel phase feature to improve the image quality, and a novel neutrosophic clustering approach to detect the accurate lesion boundary. First, a region of interest is generated to cut off complex background. After speckle reduction, an enhancement algorithm based on phase in max-energy orientation (PMO) is developed to further improve the image quality. The PMO is a newly proposed 2D phase feature obtained by filtering the image in the frequency domain and calculating the phase accumulation in the orientation with maximum energy. Finally, the authors propose a novel clustering approach called neutrosophic l-means (NLM) to detect the lesion boundary. NLM is a generalized clustering method that can be used to solve other clustering problems as well. In this paper, NLM is used to segment images with vague boundaries, and to deal with uncertainty better. To evaluate the performance of the proposed method, the authors compare it with the traditional fuzzy c-means clustering, active contour, level set, and watershed-based segmentation methods, using a common database. Radiologist's manual delineations are used as the golden standards. Five assessment metrics are utilized to evaluate the performance from different aspects. Both accuracy and efficiency are analyzed. Sensitivity analysis is also conducted to test the robustness of the proposed method. RESULTS: Compared with the other methods, the proposed method generates the most similar boundaries to the radiologist's manual delineations (TP rate is 92.4%, FP rate is 7.2%, and similarity rate is 86.3%; Hausdorff distance is 22.5 pixels and mean absolute distance is 4.8 pixels), with efficient processing speed (averagely 9.8 s per image). Sensitivity analysis shows the robustness of the proposed method as well. CONCLUSIONS: The proposed method is a fully automatic segmentation method for BUS images that can generate accurate lesion boundaries even for complicated cases. The fast processing speed, robustness, and accuracy of the proposed method suggest its potential applications in clinics.