MOF-Based Membranes for Remediated Application of Water Pollution.

Membrane separation plays a crucial role in the current increasingly complex energy environment. Membranes prepared by metal-organic framework (MOF) materials usually possess unique advantages in common, such as uniform pore size, ultra-high porosity, enhanced selectivity and throughput, and excellent adsorption property, which have been contributed to the separation fields. In this comprehensive review, we summarize various designs and synthesized strategies of free-standing MOF and composite MOF-based membranes for water treatment. Special emphases are given not only on the effects of MOF on membrane performance, removal efficiencies, and elimination mechanisms, but also on the importance of MOF-based membranes for the applications of oily and micro-pollutant removal, adsorption, separation, and catalysis. The challenges and opportunities in the future for the industrial implementation of MOF-based membranes are also discussed.

Tree shrews as a new animal model for systemic sclerosis research.

Objective: Systemic sclerosis (SSc) is a chronic systemic disease characterized by immune dysregulation and fibrosis for which there is no effective treatment. Animal models are crucial for advancing SSc research. Tree shrews are genetically, anatomically, and immunologically closer to humans than rodents. Thus, the tree shrew model provides a unique opportunity for translational research in SSc. Methods: In this study, a SSc tree shrew model was constructed by subcutaneous injection of different doses of bleomycin (BLM) for 21 days. We assessed the degree of inflammation and fibrosis in the skin and internal organs, and antibodies in serum. Furthermore, RNA sequencing and a series of bioinformatics analyses were performed to analyze the transcriptome changes, hub genes and immune infiltration in the skin tissues of BLM induced SSc tree shrew models. Multiple sequence alignment was utilized to analyze the conservation of selected target genes across multiple species. Results: Subcutaneous injection of BLM successfully induced a SSc model in tree shrew. This model exhibited inflammation and fibrosis in skin and lung, and some developed esophageal fibrosis and secrum autoantibodies including antinuclear antibodies and anti-scleroderma-70 antibody. Using RNA sequencing, we compiled skin transcriptome profiles in SSc tree shrew models. 90 differentially expressed genes (DEGs) were identified, which were mainly enriched in the PPAR signaling pathway, tyrosine metabolic pathway, p53 signaling pathway, ECM receptor interaction and glutathione metabolism, all of which are closely associated with SSc. Immune infiltration analysis identified 20 different types of immune cells infiltrating the skin of the BLM-induced SSc tree shrew models and correlations between those immune cells. By constructing a protein-protein interaction (PPI) network, we identified 10 hub genes that were significantly highly expressed in the skin of the SSc models compared to controls. Furthermore, these genes were confirmed to be highly conserved in tree shrews, humans and mice. Conclusion: This study for the first time comfirmed that tree shrew model of SSc can be used as a novel and promising experimental animal model to study the pathogenesis and translational research in SSc.

Development and validation of a new diagnostic prediction model of ENHO and NOX4 for early diagnosis of systemic sclerosis.

Objective: Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by fibrosis. The challenge of early diagnosis, along with the lack of effective treatments for fibrosis, contribute to poor therapeutic outcomes and high mortality of SSc. Therefore, there is an urgent need to identify suitable biomarkers for early diagnosis of SSc. Methods: Three skin gene expression datasets of SSc patients and healthy controls were downloaded from Gene Expression Omnibus (GEO) database (GSE130955, GSE58095, and GSE181549). GSE130955 (48 early diffuse cutaneous SSc and 33 controls) were utilized to screen differentially expressed genes (DEGs) between SSc and normal skin samples. Least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) were performed to identify diagnostic genes and construct a diagnostic prediction model. The results were further validated in GSE58095 (61 SSc and 36 controls) and GSE181549 (113 SSc and 44 controls) datasets. Receiver operating characteristic (ROC) curves were applied for assessing the level of diagnostic ability. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to verify the diagnostic genes in skin tissues of out cohort (10 SSc and 5 controls). Immune infiltration analysis were performed using CIBERSORT algorithm. Results: A total of 200 DEGs were identified between SSc and normal skin samples. Functional enrichment analysis revealed that these DEGs may be involved in the pathogenesis of SSc, such as extracellular matrix remodeling, cell-cell interactions, and metabolism. Subsequently, two critical genes (ENHO and NOX4) were identified by LASSO and SVM-RFE. ENHO was found down-regulated while NOX4 was up-regulated in skin of SSc patients and their expression levels were validated by above three datasets and our cohort. Notably, these differential expressions were more pronounced in patients with diffuse cutaneous SSc than in those with limited cutaneous SSc. Next, we developed a novel diagnostic model for SSc using ENHO and NOX4, which demonstrated strong predictive power in above three cohorts and in our own cohort. Furthermore, immune infiltration analysis revealed dysregulated levels of various immune cell subtypes within early SSc skin specimens, and a negative correlation was observed between the levels of ENHO and Macrophages M1 and M2, while a positive correlation was observed between the levels of NOX4 and Macrophages M1 and M2. Conclusion: This study identified ENHO and NOX4 as novel biomarkers that can be serve as a diagnostic prediction model for early detection of SSc and play a potential role in the pathogenesis of the disease.

Evolution of the thermostability of actin-depolymerizing factors enhances the adaptation of pollen germination to high temperature.

Double fertilization in many flowering plants (angiosperms) often occurs during the hot summer season, but the mechanisms that enable angiosperms to adapt specifically to high temperatures are largely unknown. The actin cytoskeleton is essential for pollen germination and the polarized growth of pollen tubes, yet how this process responds to high temperatures remains unclear. Here, we reveal that the high thermal stability of 11 Arabidopsis (Arabidopsis thaliana) actin-depolymerizing factors (ADFs) is significantly different: ADFs that specifically accumulate in tip-growing cells (pollen and root hairs) exhibit high thermal stability. Through ancestral protein reconstruction, we found that subclass II ADFs (expressed specifically in pollen) have undergone a dynamic wave-like evolution of the retention, loss, and regeneration of thermostable sites. Additionally, the sites of AtADF7 with high thermal stability are conserved in ADFs specific to angiosperm pollen. Moreover, the high thermal stability of ADFs is required to regulate actin dynamics and turnover at high temperatures to promote pollen germination. Collectively, these findings suggest strategies for the adaptation of sexual reproduction to high temperature in angiosperms at the cell biology level.

Changes in Stress-Strain Index in School-Aged Children: A 3-Year Longitudinal Study.

Purpose: To determine three-year change of the corneal biomechanical parameter stress-strain index (SSI) in schoolchildren aged 7- 9 years and their correlation with refractive error and axial length (AL). Methods: This is a prospective cohort study. Data of the AL, refractive error, and corneal biomechanical parameter SSI were collected at baseline and a 3-year follow-up for 217 schoolchildren. SSI, AL, and refractive error were measured via corneal visualization Scheimpflug technology (Corvis ST), IOLMaster biometry, and cycloplegic refraction. Three years of changes in SSI and its association with refractive error and AL were analyzed. Participants were divided into persistent nonmyopia (PNM), newly developed myopia (NDM), and persistent myopia (PM). The three-year difference in SSI among the three groups was analyzed. Results: After three years of follow-up, the corneal biomechanical parameter SSI decreased in all participants (P < 0.01). There was a negative correlation between the change in SSI and the change in AL (r = -0.205, P=0.002) and a positive correlation between the change in refractive error (r = 0.183, P=0.007). After three years of follow-up, there was a decrease in the SSI for the NDM, PM, and PNM participants, with a median change of -0.05 for PNM and -0.13 and -0.09 for the NDM and PM, respectively. There was a significant decrease in corneal biomechanical properties for NDM patients compared with PNM patients (P < 0.01). Conclusion: In 7- to 9-year-old schoolchildren, SSI decreased after three years of the longitudinal study, and the change in SSI was correlated with the change in AL and refractive error. There was a rapid decrease in corneal biomechanical properties among newly developed myopic patients.

The new insights into autophagy in thyroid cancer progression.

In recent decades, the incidence of thyroid cancer keeps growing at a shocking rate, which has aroused increasing concerns worldwide. Autophagy is a fundamental and ubiquitous biological event conserved in mammals including humans. Basically, autophagy is a catabolic process that cellular components including small molecules and damaged organelles are degraded for recycle to meet the energy needs, especially under the extreme conditions. The dysregulated autophagy has indicated to be involved in thyroid cancer progression. The enhancement of autophagy can lead to autophagic cell death during the degradation while the produced energies can be utilized by the rest of the cancerous tissue, thus this influence could be bidirectional, which plays either a tumor-suppressive or oncogenic role. Accordingly, autophagy can be suppressed by therapeutic agents and is thus regarded as a drug target for thyroid cancer treatments. In the present review, a brief description of autophagy and roles of autophagy in tumor context are given. We have addressed summary of the mechanisms and functions of autophagy in thyroid cancer. Some potential autophagy-targeted treatments are also summarized. The aim of the review is linking autophagy to thyroid cancer, so as to develop novel approaches to better control cancer progression.

[A novel method for electroencephalography background analysis in neonates with hypoxic-ischemic encephalopathy]. / åº”ç”¨äºŽæ–°ç”Ÿå„¿ç¼ºæ°§ç¼ºè¡€æ€§è„‘ç— çš„è„‘ç”µèƒŒæ™¯åˆ†æžæ–°æ–¹æ³•.

OBJECTIVES: To explore a new method for electroencephalography (EEG) background analysis in neonates with hypoxic-ischemic encephalopathy (HIE) and its relationship with clinical grading and head magnetic resonance imaging (MRI) grading. METHODS: A retrospective analysis was performed for the video electroencephalography (vEEG) and amplitude-integrated electroencephalography (aEEG) monitoring data within 24 hours after birth of neonates diagnosed with HIE from January 2016 to August 2022. All items of EEG background analysis were enrolled into an assessment system and were scored according to severity to obtain the total EEG score. The correlations of total EEG score with total MRI score and total Sarnat score (TSS, used to evaluate clinical gradings) were analyzed by Spearman correlation analysis. The total EEG score was compared among the neonates with different clinical gradings and among the neonates with different head MRI gradings. The receiver operating characteristic (ROC) curve and the area under thecurve (AUC) were used to evaluate the value of total EEG score in diagnosing moderate/severe head MRI abnormalities and clinical moderate/severe HIE, which was then compared with the aEEG grading method. RESULTS: A total of 50 neonates with HIE were included. The total EEG score was positively correlated with the total head MRI score and TSS (rs=0.840 and 0.611 respectively, P<0.001). There were significant differences in the total EEG score between different clinical grading groups and different head MRI grading groups (P<0.05). The total EEG score and the aEEG grading method had an AUC of 0.936 and 0.617 respectively in judging moderate/severe head MRI abnormalities (P<0.01) and an AUC of 0.887 and 0.796 respectively in judging clinical moderate/severe HIE (P>0.05). The total EEG scores of ≤6 points, 7-13 points, and ≥14 points were defined as mild, moderate, and severe EEG abnormalities respectively, which had the best consistency with clinical grading and head MRI grading (P<0.05). CONCLUSIONS: The new EEG background scoring method can quantitatively reflect the severity of brain injury and can be used for the judgment of brain function in neonates with HIE.

Long-term effects of mnemonic training in healthy older adults: A meta-analysis.

Mnemonic training can improve episodic memory function, the most aging-sensitive functional domain in older adults. However, it remains unclear whether memory training gains can be maintained over time. In this meta-analysis, we aimed to investigate the long-term effects (pretest to follow-up) of mnemonic training in improving memory among older adults. Eligible studies were randomized controlled trials of mnemonic training with follow-up assessments (ranging from 0.5 to 32 months, median follow-up duration = 4 months) in healthy older adults (aged ≥ 50 years) without known cognitive impairment. Twenty-one studies, with a total of 4,149 participants, were identified. The three-level meta-analyses indicated that the immediate (pre- to post-test) and long-term effect sizes on episodic memory were 0.408 and 0.418 (Hedges'g, ps < .001), respectively. In addition, the results revealed significant immediate effect (g = 0.362, p < .01) and long-term effect (g = 0.227, p < .01) on subjective memory. It is recommended that future studies incorporate more real-world outcomes and multiple follow-ups and boosters to determine training effects on everyday functioning over time. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Separation of memory span and learning rate: Evidence from behavior and spontaneous brain activity in older adults.

It is unclear how the ability to initially acquire information in a first learning trial relates to learning rate in subsequent repeated trials. The separation of memory span and learning rate is an important psychological dilemma that remains unaddressed. Given the potential effects of aging on memory and learning, this study investigated the separation of memory span and learning rate from behavior and spontaneous brain activity in older adults. We enrolled a total of 758 participants, including 707 healthy older adults and 51 mild cognitive impairment (MCI) patients. Sixty-five participants out of 707 completed resting-state functional magnetic resonance imaging (fMRI) scanning. Behaviorally, memory span and learning rate were not correlated with each other in the paired-associative learning test (PALT) but were negatively correlated in the auditory verbal learning test (AVLT). This indicated that the relationship between memory span and learning rate for item memory might be differentially affected by aging. Interaction analysis confirmed that these two capacities were differentially affected by test type (associative memory vs. item memory). Additionally, at three progressive brain activity indexes (ALFF, ReHo, and DC), the right brain regions (right inferior temporal gyrus and right middle frontal gyrus) were more negatively correlated with memory span, whereas, the left precuneus was more positively correlated with learning rate. Regarding pathological aging, none of the correlations between memory span and learning rate were significant in either PALT or AVLT in MCI. This study provides novel evidence for the dissociation of memory span and learning rate at behavioral and brain activity levels, which may have useful applications in detecting cognitive deficits or conducting cognitive interventions.

Identification of immune-related diagnostic markers in primary Sjögren's syndrome based on bioinformatics analysis.

Background: Primary Sjögren's syndrome (pSS) is a relatively common diffuse connective tissue disease that often invades exocrine glands, such as the lacrimal and salivary glands, and manifests as dry eyes and dry mouth. At present, the molecular mechanism of pSS is not clear. This study was designed to explore the internal mechanism of pSS from the gene level and screen out the immune-related diagnostic markers of pSS. Methods: The gene expression profiles GSE84844, GSE7451, and GSE40611 were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified with R software. Then, the DEGs were intersected with the immune genes obtained from the ImmPort database to acquire differentially expressed immune-related genes (DEIRGs), and functional enrichment analyses were performed. The DEIRGs were screened through the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm to obtain the optimal immune-related genes (IRGs). Expression levels of the optimal IRGs were verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to obtain the key genes. Next, gene chips GSE7451 and GSE40611, from other tissues, were selected as the training sets to verify the sensitivity and specificity of the diagnosis of the key genes by receiver operating characteristic (ROC) analysis. Results: A total of 54 DEIRGs were obtained. The functional enrichment analysis results showed that they play an important role in immune and inflammatory responses. Nine optimal IRGs were screened from the DEIRGs by the LASSO logistic regression algorithm. After qRT-PCR verification, eight out of nine optimal IRGs (IL-18, JAK2, TBK1, EED, TNFSF10, TNFSF13B, CYSLTR1, and ICOS) were significantly highly expressed in pSS patients and were defined as key genes. ROC analysis identified that TNFSF13B and CYSLTR1 had high sensitivity and specificity. Finally, the lack of previous research on EED and CYSLTR1 in pSS suggests that these IRGs may be regarded as new gateways to explore the diagnosis and pathogenesis of pSS. Conclusions: The key DEIRGs play a decisive role during the occurrence and development of pSS.

Boundary-aware context neural network for medical image segmentation.

Medical image segmentation can provide a reliable basis for further clinical analysis and disease diagnosis. With the development of convolutional neural networks (CNNs), medical image segmentation performance has advanced significantly. However, most existing CNN-based methods often produce unsatisfactory segmentation masks without accurate object boundaries. This problem is caused by the limited context information and inadequate discriminative feature maps after consecutive pooling and convolution operations. Additionally, medical images are characterized by high intra-class variation, inter-class indistinction and noise, extracting powerful context and aggregating discriminative features for fine-grained segmentation remain challenging. In this study, we formulate a boundary-aware context neural network (BA-Net) for 2D medical image segmentation to capture richer context and preserve fine spatial information, which incorporates encoder-decoder architecture. In each stage of the encoder sub-network, a proposed pyramid edge extraction module first obtains multi-granularity edge information. Then a newly designed mini multi-task learning module for jointly learning segments the object masks and detects lesion boundaries, in which a new interactive attention layer is introduced to bridge the two tasks. In this way, information complementarity between different tasks is achieved, which effectively leverages the boundary information to offer strong cues for better segmentation prediction. Finally, a cross feature fusion module acts to selectively aggregate multi-level features from the entire encoder sub-network. By cascading these three modules, richer context and fine-grain features of each stage are encoded and then delivered to the decoder. The results of extensive experiments on five datasets show that the proposed BA-Net outperforms state-of-the-art techniques.

POSTAR3: an updated platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins.

RNA-binding proteins (RBPs) play key roles in post-transcriptional regulation. Accurate identification of RBP binding sites in multiple cell lines and tissue types from diverse species is a fundamental endeavor towards understanding the regulatory mechanisms of RBPs under both physiological and pathological conditions. Our POSTAR annotation processes make use of publicly available large-scale CLIP-seq datasets and external functional genomic annotations to generate a comprehensive map of RBP binding sites and their association with other regulatory events as well as functional variants. Here, we present POSTAR3, an updated database with improvements in data collection, annotation infrastructure, and analysis that support the annotation of post-transcriptional regulation in multiple species including: we made a comprehensive update on the CLIP-seq and Ribo-seq datasets which cover more biological conditions, technologies, and species; we added RNA secondary structure profiling for RBP binding sites; we provided miRNA-mediated degradation events validated by degradome-seq; we included RBP binding sites at circRNA junction regions; we expanded the annotation of RBP binding sites, particularly using updated genomic variants and mutations associated with diseases. POSTAR3 is freely available at http://postar.ncrnalab.org.

An Improved Shape from Focus Method for Measurement of Three-Dimensional Features of Fuel Nozzles.

The precise three-dimensional measurement of fuel nozzles is of great significance to assess the manufacturing accuracy and improve the spray and atomization performance. This paper proposes an improved fast shape from focus (SFF) method for three-dimensional measurement of key features of fuel nozzles. In order to ensure the measurement accuracy and efficiency of the SFF, the dispersion of the measured points from a standard flat plane was used to select the optimal combination of the focus measure operator, window size and sampling step size. In addition, an approximate method for the focus measure interval is proposed to improve the measurement efficiency, which uses the peak region of the central pixel to replace the peak region of other pixels. The results show that the proposed method decreased the average computation time of the focus measure by 79.19% for the cone section and by 38.30% for the swirl slot. Compared with a reference laser scanning microscope, the measurement error in length is within 10 µm and the error in angle is within a maximum 0.15°.

Correlation of electroencephalogram background evolution with the degree of brain injury in neonates with hypoxic-ischemic encephalopathy. / æ–°ç”Ÿå„¿ç¼ºæ°§ç¼ºè¡€æ€§è„‘ç— è„‘ç”µèƒŒæ™¯æ¼”å˜ä¸Žè„‘æŸä¼¤ç¨‹åº¦çš„ç›¸å ³æ€§ç ”ç©¶.

OBJECTIVES: To study the correlation of electroencephalogram (EEG) background evolution with the degree of brain injury in neonates with hypoxic-ischemic encephalopathy (HIE). METHODS: A retrospective analysis was performed for 56 neonates with HIE who underwent continuous video electroencephalogram (cVEEG) and brain magnetic resonance imaging (MRI) examinations. According to clinical symptoms, they were divided into a mild group with 3 neonates, a moderate group with 36 neonates, and a severe group with 17 neonates. EEG background grading and MRI score were determined for each group to analyze the correlation of EEG background evolution with the degree of brain injury. RESULTS: Compared with the moderate group, the severe group had significantly lower gestational age and Apgar score at 5 minutes after birth, a significantly higher resuscitation score, significantly lower base excess in umbilical cord blood or blood gas within 1 hour, a significantly higher proportion of neonates on mechanical ventilation, and a significantly higher incidence rate of short-term adverse outcomes (P<0.05). For the neonates in the mild and moderate groups, MRI mainly showed no brain injury (67%, 2/3) and watershed injury (67%, 16/24) respectively, and EEG showed mild abnormality in 62% (13/21) of the neonates on the 3rd day after birth. For the neonates in the severe group, MRI mainly showed basal ganglia/thalamus + brainstem injury (24%, 4/17) and whole brain injury (71%, 12/17), and EEG showed moderate or severe abnormalities on the 3rd day after birth. EEG background grading was correlated with clinical grading, MRI score, and short-term outcome on days 1, 2, 3 and 7-14 after birth (P<0.01). The highest correlation coefficient between EEG grading and MRI score was observed on the 3rd day after birth (rs=0.751, P<0.001), and the highest correlation coefficients between EEG grading and clinical grading (rs=0.592, P=0.002) and between EEG grading and short-term outcome (rs=0.737, P<0.001) were observed 7-14 days after birth. Among the neonates with severe abnormal EEG, the neonates without brain electrical activity had the highest MRI score, followed by those with status epileptics and persistent low voltage (P<0.05). CONCLUSIONS: There is a good correlation between EEG background grading and degree of brain injury in neonates with HIE, which can help to evaluate the degree and prognosis of brain injury in the early stage.

Plaque Elasticity and Intraplaque Neovascularisation on Carotid Artery Ultrasound: A Comparative Histological Study.

OBJECTIVE: Plaque elasticity and intraplaque neovascularisation are strongly suggestive of vulnerable plaque. This study aimed to investigate the relationship between intraplaque neovascularisation and plaque elasticity, and to compare the ultrasound findings with histopathological changes. METHODS: Patients enrolled in this study presented with symptomatic carotid stenosis (> 70%) and later underwent both pre-operative ultrasonography and endarterectomy. Contrast enhanced ultrasound (CEUS) and shear wave elastography (SWE) were used to measure the neovascularisation and elasticity of the plaque, respectively. After removal, plaques were histologically assessed to determine the microvessel density (MVD), matrix metalloproteinase (MMP)-9 expression, and type I/type III collagen ratio using immunohistochemistry staining and morphometry. A correlation analysis was used to establish the relationship among the aforementioned quantitative parameters. Inter- and intra-observer consistency evaluations were performed using the intraclass correlation coefficient and Bland-Altman plots. RESULTS: Ninety-four symptomatic patients with 98 plaques were included. The area under the curve (AUC) of the carotid plaque detected using CEUS correlated with its shear wave velocity (SWV) (r = -.714; p < .001), MVD (r = .842; p < .001), collagen type I/III ratio (r = -.833; p < .001), and MMP-9 (r = .738; p < .001). SWE was positively correlated with the type I/III collagen ratio (r = .805; p < .001). The overall interexaminer consistency of the SWE was acceptable (r = .638; p < .001). The interobserver correlation coefficient of the AUC, time to peak (TP), mean transit time (MTT), and SWV were .719, .756, .733, and .686, respectively. The intra-observer variability values of the AUC, TP, MTT, and SWV were .826, .845, .633, and .748, respectively. CONCLUSION: SWE and CEUS can comprehensively evaluate the vulnerability of the carotid plaque by assessing the elasticity of the plaque and neovascularisation within it. The negative correlation between the intraplaque neovascularisation and elasticity, further validated by histological findings, suggests that the more abundant the neovascularisation, the less elasticity.

Ultrasound-Targeted Microbubble Destruction Mediates Gene Transfection for Beta-Cell Regeneration and Glucose Regulation.

Ultrasound-targeted microbubble destruction (UTMD) mediates gene transfection with high biosafety and thus has been promising toward treatment of type 1 diabetes. However, the potential application of UTMD in type 2 diabetes (T2D) is still limited, due to the lack of systematic design and dynamic monitoring. Herein, an efficient gene delivery system is constructed by plasmid deoxyribonucleic acid (DNA) encoding glucagon-like peptide 1 (GLP-1) in ultrasound-induced microbubbles, toward treatment of T2D in macaque. The as designed UTMD afforded enhancement of cell membrane penetration and GLP-1 expression in macaque, which is characterized by ultrasound-guided biopsy to monitor the dynamic process of islet cells for 6 months. Also, improvement of pancreatic beta cell regeneration, and regulation of plasma glucose in macaque with T2D is achieved. The approach would serve as promising alternatives for the treatment of T2D.

Bacterial Peptidoglycan Fragments Differentially Regulate Innate Immune Signaling.

The human innate immune system responds to both pathogen and commensal bacteria at the molecular level using bacterial peptidoglycan (PG) recognition elements. Traditionally, synthetic and commercially accessible PG monosaccharide units known as muramyl dipeptide (MDP) and N-glycolyl MDP (ng-MDP) have been used to probe the mechanism of innate immune activation of pattern recognition receptors, such as NOD-like receptors. However, bacterial PG is a dynamic and complex structure, with various chemical modifications and trimming mechanisms that result in the production of disaccharide-containing elements. These molecules pose as attractive targets for immunostimulatory screening; however, studies are limited because of their synthetic accessibility. Inspired by disaccharide-containing compounds produced from the gut microbe Lactobacillus acidophilus, a robust and scalable chemical synthesis of PG-based disaccharide ligands was implemented. Together with a monosaccharide PG library, compounds were screened for their ability to stimulate proinflammatory genes in bone-marrow-derived macrophages. The data reveal distinct gene induction patterns for monosaccharide and disaccharide PG units, suggesting that PG innate immune signaling is more complex than a one activator-one pathway program, as biologically relevant fragments induce transcriptional programs to different degrees. These disaccharide molecules will serve as critical immunostimulatory tools to more precisely define specialized innate immune regulatory mechanisms that distinguish between commensal and pathogenic bacteria residing in the microbiome.

Enhanced leaching of manganese from low-grade pyrolusite using ball milling and electric field.

In this study, electric field and ball milling were used to leach Mn2+ from low-grade pyrolusite (LGP). The effects of current density, reaction time, reaction temperature, ball-to-powder weight ratio, and ball milling time on the leaching efficiency of Mn2+ from LGP as well as the leaching mechanism were systematically studied. The results showed that the combined use of electric field and ball milling enhanced the leaching of Mn2+ from LGP. The leaching efficiency of Mn2+ reached 97.79% under the optimum conditions of LGP-to-pyrite mass ratio of 1:0.18, current density of 30 mA/cm2, LGP-to-H2SO4 mass ratio of 1:0.4, liquid-to-solid ratio of 5:1, ball-to-powder weight ratio of 1:1, ball milling time of 2 h, temperature of 80 °C, and leaching duration of 120 min. This value was 25.95% higher than that attained without ball milling and 41.45% higher than that attained when neither ball milling nor electric field was employed. Pyrite was fully oxidized to generate additional SO42- and Fe3+, and was further hydrolyzed to form jarosite (KFe3(SO4)2(OH)6) and hydronium jarosite (Fe3(SO4)2(OH)5·2H2O) via ball milling and electric field application. Moreover, the electric field changed the surface charge distribution of the mineral particles and promoted collisions between them as well as the collapse of the crystal lattice, further improving the leaching efficiency of Mn2+ from LGP. This study provided a new method for leaching Mn from LGP.

Social Neighborhood Graph and Multigraph Fusion Ranking for Multifeature Image Retrieval.

A single feature is hard to describe the content of images from an overall perspective, which limits the retrieval performances of single-feature-based methods in image retrieval tasks. To fully describe the properties of images and improve the retrieval performances, multifeature fusion ranking-based methods are proposed. However, the effectiveness of multifeature fusion in image retrieval has not been theoretically explained. This article gives a theoretical proof to illustrate the role of independent features in improving the retrieval results. Based on the theoretical proof, the original ranking list generated with a single feature greatly influences the performances of multifeature fusion ranking. Inspired by the principle of three degrees of influence in social networks, this article proposes a reranking method named k -nearest neighbors' neighbors' neighbors' graph (N3G) to improve the original ranking list by a single feature. Furthermore, a multigraph fusion ranking (MFR) method motivated by the group relation theory in social networks for multifeature ranking is also proposed, which considers the correlations of all images in multiple neighborhood graphs. Evaluation experiments conducted on several representative data sets (e.g., UK-bench, Holiday, Corel-10K, and Cifar-10) validate that N3G and MFR outperform the other state-of-the-art methods.

Checkpoint therapeutic target database (CKTTD): the first comprehensive database for checkpoint targets and their modulators in cancer immunotherapy.

BACKGROUND: Checkpoint targets play a key role in tumor-mediated immune escape and therefore are critical for cancer immunotherapy. Unfortunately, there is a lack of bioinformatics resource that compile all the checkpoint targets for translational research and drug discovery in immuno-oncology. METHODS: To this end, we developed checkpoint therapeutic target database (CKTTD), the first comprehensive database for immune checkpoint targets (proteins, miRNAs and LncRNAs) and their modulators. A scoring system was adopted to filter more relevant targets with high confidence. In addition, a few biological databases such as Oncomine, Drugbank, miRBase and Lnc2Cancer database were integrated into CKTTD to provide an in-depth information. Moreover, we computed and provided ligand-binding site information for all the targets which may support bench scientists for drug discovery efforts. RESULTS: In total, CKTTD compiles 105 checkpoint protein targets, 53 modulators (small-molecules and antibody), 30 miRNAs and 18 LncRNAs in cancer immunotherapy with validated experimental evidences curated from 10 649 literatures via an enhanced text-mining system. CONCLUSIONS: In conclusion, the CKTTD may serve as a useful platform for the research of cancer immunotherapy and drug discovery. The CKTTD database is freely available to public at http://www.ckttdb.org/.