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Study Design: This study is a scoping review. Objective: There is a broad variability in the definition of degenerative cervical myelopathy (DCM) and no standardized set of diagnostic criteria to date. Methods: We interrogated the Myelopathy.org database, a hand-indexed database of primary clinical studies conducted exclusively on DCM in humans between 2005-2021. The DCM inclusion criteria used in these studies were inputted into 3 topic modeling algorithms: Hierarchical Dirichlet Process (HDP), Latent Dirichlet Allocation (LDA), and BERtopic. The emerging topics were subjected to manual labeling and interpretation. Results: Of 1676 reports, 120 papers (7.16%) had well-defined inclusion criteria and were subjected to topic modeling. Four topics emerged from the HDP model: disturbance from extremity weakness and motor signs; fine-motor and sensory disturbance of upper extremity; a combination of imaging and clinical findings is required for the diagnosis; and "reinforcing" (or modifying) factors that can aid in the diagnosis in borderline cases. The LDA model showed the following topics: disturbance to the patient is required for the diagnosis; reinforcing factors can aid in the diagnosis in borderline cases; clinical findings from the extremities; and a combination of imaging and clinical findings is required for the diagnosis. BERTopic identified the following topics: imaging abnormality, typical clinical features, range of objective criteria, and presence of clinical findings. Conclusions: This review provides quantifiable data that only a minority of past studies in DCM provided meaningful inclusion criteria. The items and patterns found here are very useful for the development of diagnostic criteria for DCM. [ABSTRACT FROM AUTHOR]

Study Design: Delayed diagnosis of degenerative cervical myelopathy (DCM) is associated with reduced quality of life and greater disability. Developing diagnostic criteria for DCM has been identified as a top research priority. Objectives: This scoping review aims to address the following questions: What is the diagnostic accuracy and frequency of clinical symptoms in patients with DCM? Methods: A scoping review was conducted using a database of all primary DCM studies published between 2005 and 2020. Studies were included if they (i) assessed the diagnostic accuracy of a symptom using an appropriate control group or (ii) reported the frequency of a symptom in a cohort of DCM patients. Results: This review identified three studies that discussed the diagnostic accuracy of various symptoms and included a control group. An additional 58 reported on the frequency of symptoms in a cohort of patients with DCM. The most frequent and sensitive symptoms in DCM include unspecified paresthesias (86%), hand numbness (82%) and hand paresthesias (79%). Neck and/or shoulder pain was present in 51% of patients with DCM, whereas a minority had back (19%) or lower extremity pain (10%). Bladder dysfunction was uncommon (38%) although more frequent than bowel (23%) and sexual impairment (4%). Gait impairment is also commonly seen in patients with DCM (72%). Conclusion: Patients with DCM present with many different symptoms, most commonly sensorimotor impairment of the upper extremities, pain, bladder dysfunction and gait disturbance. If patients present with a combination of these symptoms, further neuroimaging is indicated to confirm the diagnosis of DCM. [ABSTRACT FROM AUTHOR]

Study Design: Delayed diagnosis of degenerative cervical myelopathy (DCM) is likely due to a combination of its subtle symptoms, incomplete neurological assessments by clinicians and a lack of public and professional awareness. Diagnostic criteria for DCM will likely facilitate earlier referral for definitive management. Objectives: This systematic review aims to determine (i) the diagnostic accuracy of various clinical signs and (ii) the association between clinical signs and disease severity in DCM? Methods: A search was performed to identify studies on adult patients that evaluated the diagnostic accuracy of a clinical sign used for diagnosing DCM. Studies were also included if they assessed the association between the presence of a clinical sign and disease severity. The QUADAS-2 tool was used to evaluate the risk of bias of individual studies. Results: This review identified eleven studies that used a control group to evaluate the diagnostic accuracy of various signs. An additional 61 articles reported on the frequency of clinical signs in a cohort of DCM patients. The most sensitive clinical tests for diagnosing DCM were the Tromner and hyperreflexia, whereas the most specific tests were the Babinski, Tromner, clonus and inverted supinator sign. Five studies evaluated the association between the presence of various clinical signs and disease severity. There was no definite association between Hoffmann sign, Babinski sign or hyperreflexia and disease severity. Conclusion: The presence of clinical signs suggesting spinal cord compression should encourage health care professionals to pursue further investigation, such as neuroimaging to either confirm or refute a diagnosis of DCM. [ABSTRACT FROM AUTHOR]

In this work, based on the degradation of rhodamine B (RhB) and rhodamine 6G (R6G) with the catalysis of MnO2 nanosheets (MnO2 NSs) under acidity condition, a colorimetric and fluorescence dual signal sensor array was developed for Baijiu discrimination. Rhodamine B and rhodamine 6G present characteristic UV-vis absorption peaks and fluorescence emission peaks at specific wavelength. MnO2 NSs could induce the degradation of rhodamine B and rhodamine 6G and weaken the intensity of UV-vis and fluorescence. In the presence of organic acids or Baijiu, the degradation of dyes accelerated and the optical signal could be further weakened. Owing to the various of acidity, the sensor array exhibited different responses to organic acids and Baijiu, resulting in unique fingerprint maps. With the method, 8 kinds of organic acids and formic acid-acetic acid mixture samples were successfully recognized. In addition, 12 kinds of Baijiu with different flavor types were identified with 100% accuracy. Notably, 5 other distilled liquors were also successfully discriminated with no misclassifications. The method not only reduces the amount of dyes, but also improves the specificity of the sensor array, demonstrating the potential application prospects of the dual signal sensor array in Baijiu industry. [ABSTRACT FROM AUTHOR]

The demand‐side DC electricity‐using equipment and newly integrated renewables are driving the transformation of power distribution and utilization mode. The building system based on DC technology is emerging as a promising option. In the low‐voltage DC building distribution and utilization system (LVDCBDUS), global energy optimization management and operational control arrangement are key components. To obtain exemplary achievements of those, two different DC building energy management system (DC BEMS) integration schemes are investigated according to the respective features and application‐required functions of various system networking structures. Centralized and decentralized control strategies are presented and discussed for buildings with AC–DC transformation and newly built LVDCBDUSs. On this basis, the centralized DC BEMS and operational control strategy are applied to the first multi‐scenario low‐carbon city‐based future building project—Shenzhen IBR Future Complex. The operation data are recorded and analysed. Problems encountered during the implementation are summarized, and requirements of converter equipment, new technologies and marketization are further discussed to promote the high‐quality development of the LVDCBDUS. [ABSTRACT FROM AUTHOR]

The endoplasmic reticulum membrane protein complex (EMC) plays a critical role in the synthesis of multipass membrane proteins. Genetic studies indicated that mutations in EMC1 gene were associated with retinal degeneration diseases; however, the role of EMC1 in photoreceptor has not been confirmed. Here, we show that Emc1 ablation in the photoreceptor cells of mice recapitulated the retinitis pigmentosa phenotypes, including an attenuated scotopic electroretinogram response and the progressive degeneration of rod cells and cone cells. Histopathological examination of tissues from rod‐specific Emc1 knockout mice revealed mislocalized rhodopsin and irregularly arranged cone cells at the age of 2 months. Further immunoblotting analysis revealed decreased levels of membrane proteins and endoplasmic reticulum chaperones in 1‐month‐old rod‐specific Emc1 knockout mice retinae, and this led us to speculate that the loss of membrane proteins is the main cause of the degeneration of photoreceptors. EMC1 most likely regulated the membrane protein levels at an earlier step in the biosynthetic process before the proteins translocated into the endoplasmic reticulum. The present study demonstrates the essential roles of Emc1 in photoreceptor cells, and reveals the mechanism through which EMC1 mutations are linked to retinitis pigmentosa. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summarizing the principles and processes of deep learning and traditional machine learning algorithms, analyzing the application of machine learning in TCM, reviewing the results of previous studies, this study proposed a promising future perspective based on the combination of machine learning, TCM theory, chemical compositions of natural products, and computational simulations based on molecules and chemical compositions. In the first place, machine learning will be utilized in the effective chemical components of natural products to target the pathological molecules of the disease which could achieve the purpose of screening the natural products on the basis of the pathological mechanisms they target. In this approach, computational simulations will be used for processing the data for effective chemical components, generating datasets for analyzing features. In the next step, machine learning will be used to analyze the datasets on the basis of TCM theories such as the superposition of syndrome elements. Finally, interdisciplinary natural product-syndrome research will be established by unifying the results of the two steps outlined above, potentially realizing an intelligent artificial intelligence diagnosis and treatment model based on the effective chemical components of natural products under the guidance of TCM theory. This perspective outlines an innovative application of machine learning in the clinical practice of TCM based on the investigation of chemical molecules under the guidance of TCM theory. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summarizing the principles and processes of deep learning and traditional machine learning algorithms, analyzing the application of machine learning in TCM, reviewing the results of previous studies, this study proposed a promising future perspective based on the combination of machine learning, TCM theory, chemical compositions of natural products, and computational simulations based on molecules and chemical compositions. In the first place, machine learning will be utilized in the effective chemical components of natural products to target the pathological molecules of the disease which could achieve the purpose of screening the natural products on the basis of the pathological mechanisms they target. In this approach, computational simulations will be used for processing the data for effective chemical components, generating datasets for analyzing features. In the next step, machine learning will be used to analyze the datasets on the basis of TCM theories such as the superposition of syndrome elements. Finally, interdisciplinary natural product-syndrome research will be established by unifying the results of the two steps outlined above, potentially realizing an intelligent artificial intelligence diagnosis and treatment model based on the effective chemical components of natural products under the guidance of TCM theory. This perspective outlines an innovative application of machine learning in the clinical practice of TCM based on the investigation of chemical molecules under the guidance of TCM theory. [ABSTRACT FROM AUTHOR]

Radioactive substances have been used in various aspects in daily life. However, high-energy radiation could cause environmental problems, which would damage the human body. Circular RNA (CircRNA) has great potential in the minimization of ionizing radiation damage. To find a potential diagnostic and therapeutic target for reducing the damage of ionizing radiation, we selected circRNA cleavage and polyadenylation specificity factor subunit 1 (circ-CPSF1) based on its up-regulated expression after X-ray radiation and explored its effect on response to ionizing radiation using Caenorhabditis elegans (C. elegans). Circ-CPSF1 was screened out and its up-regulated expression was verified. The measurement of lifespan and germ cell apoptosis showed that circ-CPSF1 RNAi treatment extended lifespan and reduced apoptotic germ cells. ROS levels were significantly reduced after the interference of circ-CPSF1 in C. elegans with radiation. Mitochondrial membrane potential assay showed that the suppression of circ-CPSF1 could alleviate mitochondrial damage after radiation. Relative genes expression showed the involvement of circ-CPSF1 in radiation mediated DNA damage response pathways and apoptosis pathways. In conclusion, circ-CPSF1 exerts deleterious effects on lifespan, eggs production and germ cell apoptosis of C. elegans through oxidative stress, the DNA damage response (DDR) pathway, and the core apoptotic pathway after ionizing radiation, indicating the potential of circ-CPSF1 to be an important therapeutic target of radiation damage. [ABSTRACT FROM AUTHOR]

Feruloyl esterase (FAE)-producing micro-organisms to obtain ferulic acid (FA) from natural substrates have good industrial prospects, and the synergistic effect of multiple bacteria can better improve the yield of FA. In this study, on the premise of the synergistic effect of FAE, hemicellulose, and cellulase, the key strain Klebsiella oxytoca Z28 with FAE was combined with CMCase and Xylanase-producing strains to produce FA. The combination of strains with higher FA production are Klebsiella oxytoca Z28, Klebsiella pneumoniae JZE, Bacillus velezensis G1, and their FA production can reach 109.67 μg/g, which is 15% higher than that of single bacteria. To explore the effects of temperature, Ph, inoculum amount, distillers grains concentration and fermentation time on the FAE activity of the combination of strains in the fermentation process, and determined that temperature, Ph, and fermentation time were the main influencing factors and optimized through orthogonal design. The optimized fermentation conditions are 34 °C, Ph 8.0, and fermentation days for 6 days, the FAE activity can reach 270.78 U/L, and the FA yield of the combined strain is 324.50 μg/g, which is 200% higher than that of single-strain fermentation. [ABSTRACT FROM AUTHOR]

Revealing the anatomical structures, functions, and distribution of vasculature via contrast agent (CA) enhanced magnetic resonance imaging (MRI) is crucial for precise medical diagnosis and therapy. The clinically used MRI CAs strongly rely on Gd‐chelates, which exhibit low T1 relaxivities and high risks of nephrogenic systemic fibrosis (NSF) for patients with renal dysfunction. It is extremely important to develop high‐performance and safe CAs for MRI. Herein, it is reported that ultra‐small NaGdF4 nanoparticles (UGNs) can serve as an excellent safe MRI CA via surface engineering with rationally designed novel hydrophilic block co‐polymer (BPn). By optimizing the polymer molecular weights, the polymer‐functionalized UGNs (i.e., UGNs‐BP14) are obtained to exhibit remarkably higher relaxivity (11.8 mm–1 s–1 at 3.0 T) than Gd‐DTPA (3.6 mm–1 s–1) due to their ultracompact and abundant hydrophilic surface coating. The high performance of UGNs‐BP14 enables us to sensitively visualize microvasculature with a small diameter of ≈0.17 mm for up to 2 h, which is the thinnest blood vessel and the longest time window for low field (1.0 T) MR angiography ever reported, and cannot be achieved by using the clinically used Gd‐DTPA under the same conditions. More importantly, renal clearable UGNs‐BP14 show lower risks of inducing NSF in comparison with Gd‐DTPA due to their negligible release of Gd3+ ions after modification with the novel hydrophilic block copolymer. The study presents a novel avenue for boosting imaging‐performance and systemic biosafety of UGNs as a robust MRI CA with great potential in precise diagnosis of vasculature‐related diseases. [ABSTRACT FROM AUTHOR]

As the major pipeline for transporting oxygen and nutrients to living tissues, well‐ordered and functional vasculature is vital to maintain the function of organisms. The cerebrovascular disorders induced by acute or chronic diseases, including traumatic brain injury (TBI), stroke, and brain tumors, could cause vascular cognitive impairment and even mortality. Due to the complication of these cerebrovascular diseases, early diagnosis and monitoring their pathological processes in real time in animal models could enlighten us with insights into early prevention and effective treatment. Over the last decade, the NIR‐II fluorescence imaging technology has been well developed in both nanofluorophores and imaging systems. For cerebrovascular disorders, the collaborative use of wide‐field imaging setup with NIR‐II nanoprobes enable arteriovenous staging, and calculation of blood flow velocity to distinguish ischemic area in TBI and stroke. The changes in molecular and cellular levels of TBI provide the guidance on the design of targeted and activatable NIR‐II nanoprobes for evaluating and monitoring the microenvironment variations. For the brain tumors, both targeted strategy and focus ultrasound sonication are efficient approaches for overcoming the blood‐brain‐barrier and brain‐tumor‐barrier for delivery of nanoprobes. Therefore, NIR‐II fluorescence imaging‐guided surgical navigation of brain tumors and resected lesions biopsy intraoperatively ensure the accuracy of surgery based on the precise definition of tumor margins. This review summarizes the recent advances in NIR‐II fluorescence imaging technology, which is mainly inclusive of well‐developed NIR‐II nanofluorophores and their applications in cerebrovascular diseases with address of its challenges and great potential in these aspects. [ABSTRACT FROM AUTHOR]

Background and purpose: With the increasing adoption of electronic records in the health system, machine learning‐enabled techniques offer the opportunity for greater computer‐assisted curation of these data for audit and research purposes. In this project, we evaluate the consistency of traditional curation methods used in routine clinical practice against a new machine learning‐enabled tool, MedCAT, for the extraction of the stroke comorbidities recorded within the UK's Sentinel Stroke National Audit Programme (SSNAP) initiative. Methods: A total of 2327 stroke admission episodes from three different National Health Service (NHS) hospitals, between January 2019 and April 2020, were included in this evaluation. In addition, current clinical curation methods (SSNAP) and the machine learning‐enabled method (MedCAT) were compared against a subsample of 200 admission episodes manually reviewed by our study team. Performance metrics of sensitivity, specificity, precision, negative predictive value, and F1 scores are reported. Results: The reporting of stroke comorbidities with current clinical curation methods is good for atrial fibrillation, hypertension, and diabetes mellitus, but poor for congestive cardiac failure. The machine learning‐enabled method, MedCAT, achieved better performances across all four assessed comorbidities compared with current clinical methods, predominantly driven by higher sensitivity and F1 scores. Conclusions: We have shown machine learning‐enabled data collection can support existing clinical and service initiatives, with the potential to improve the quality and speed of data extraction from existing clinical repositories. The scalability and flexibility of these new machine‐learning tools, therefore, present an opportunity to revolutionize audit and research methods. [ABSTRACT FROM AUTHOR]

The bamboo-wood composite container floor (BWCCF) plays an increasingly important role in the transportation area in recent years. However, the conventional mechanical testing methods are conducted in a time-consuming and resource-wasting way. Therefore, this study is aimed to provide a frugal and high-efficiency method to predict the concentrated load of BWCCF, by comparing models with two sets of parameters. First, three artificial neural network (ANN) models were developed by taking the characteristic parameters of the end face extracted by image processing as input and concentrated load as output. Then, the other three ANN models were presented by taking the vertical density profile (VDP) as input. Of the six models, the two ANN models constructed using all characteristic parameters of cross and vertical sections and all VDP parameters had the strongest generalization. The mean absolute percentage errors were determined as 3.393 and 6.196%, respectively, and the absolute percentage errors were all within 10.000%. The result indicates that the designed model has the potential to be a useful, reliable and effective tool for predicting concentrated load. [ABSTRACT FROM AUTHOR]

Atherosclerosis (AS) is a chronic progressive disease related to dyslipidemia, inflammation, and oxidative stress. Guanxinshutong capsule (GXST), a traditional Chinese medicine, has been widely used in treating coronary atherosclerotic heart disease, while its mechanism actions on AS are still not to be well addressed. Our present study is aimed to examine the effect of GXST on AS and elucidate the multitarget mechanisms of GXST on AS. Network pharmacology analysis was employed to screen the multitarget mechanisms of GXST on AS. ApoE−/− mice were used to validate these effects. Circulating lipid profile and oxidative stress-related factors were measured by the Elisa kit. Furthermore, the aortic trunk and aortic root were excised for oil red O staining, histopathological and immunohistochemical analysis. We first discovered that GXST was clued to exert synergistically antiatherosclerosis properties including lipid-lowering, anti-inflammation, and antioxidation through the computational prediction based on a network pharmacology simulation. Next, the validation experiments in atherosclerosis mice provided evidence that GXST significantly reduced atherosclerotic lesions, increased collagen deposition, and attenuated LV remodeling to some extent. Mechanistically, GXST modulated lipid profile, downregulated the level of inflammatory cytokines and NF-κBp65. GXST also reduced the activity of oxidative parameter MDA and upregulated the activities of antioxidant enzymes (SOD and GSH) compared with the AS model group. In conclusion, GXST intervention might attenuate atherosclerosis by mechanisms involving reducing lipid deposition, modulating oxidative stress and inflammatory responses, but a larger controlled trial is necessary for confirmation. [ABSTRACT FROM AUTHOR]

The endoplasmic reticulum (ER) membrane protein complex (EMC) is a conserved protein complex involved in inserting the transmembrane domain of membrane proteins into membranes in the ER. EMC3 is an essential component of EMC and is important for rhodopsin synthesis in photoreceptor cells. However, the in vivo function of Emc3 in bipolar cells (BCs) has not been determined. To explore the role of Emc3 in BCs, we generated a BC-specific Emc3 knockout mouse model (named Emc3 cKO) using the Purkinje cell protein 2 (Pcp2) Cre line. Although normal electroretinography (ERG) b-waves were observed in Emc3 cKO mice at 6 months of age, Emc3 cKO mice exhibited reduced b-wave amplitudes at 12 months of age, as determined by scotopic and photopic ERG, and progressive death of BCs, whereas the ERG a-wave amplitudes were preserved. PKCa staining of retinal cryosections from Emc3 cKO mice revealed death of rod BCs. Loss of Emc3 led to the presence of the synaptic protein mGLuR6 in the outer nuclear layer (ONL). Immunostaining analysis of presynaptic protein postsynaptic density protein 95 (PSD95) revealed rod terminals retracted to the ONL in Emc3 cKO mice at 12 months of age. In addition, deletion of Emc3 resulted in elevated glial fibrillary acidic protein, indicating reactive gliosis in the retina. Our data demonstrate that loss of Emc3 in BCs leads to decreased ERG response, increased astrogliosis and disruption of the retinal inner nuclear layer in mice of 12 months of age. Taken together, our studies indicate that Emc3 is not required for the development of BCs but is important for long-term survival of BCs. [ABSTRACT FROM AUTHOR]

The “tumor-seeking” role of bleomycin (BLM) disaccharide has been demonstrated to serve as a promising tool for cancer diagnosis and a potential ligand for targeted therapy. However, these practical applications are often hampered by the lack of BLM disaccharide. Herein, an efficient multi-gram synthesis of peracetylated BLM disaccharide 20 is achieved by a TMSOTF-mediated glycosidation coupling manner in 43.6% overall yield in terms of benzyl galactoside. The critical innovation of the synthetic strategy is that inexpensive benzyl galactoside was first adopted to prepare an l-gulose subunit 3 as a glycosyl acceptor, with a much shorter route in 73.0% yield, and a 3-O-carbamoyl-mannose donor 4 was achieved in 47.2% yield by lowering the amount of dibutyltin oxide, and merging aminolysis and selective deacetylation into a one-pot reaction. Next, the incorporation of BLM disaccharide into 10-hydroxycamptothecin (10-HCPT), a non-specific model compound, to form conjugate 1 could significantly improve the antitumor activity and display obvious selectivity toward cancerous and normal cells in comparison with 10-HCPT. Moreover, BLM disaccharide itself was non-cytotoxic, clearly indicating the importance and potential of BLM disaccharide in solving the targeted antitumor therapy of cytotoxic drugs. [ABSTRACT FROM AUTHOR]

The whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a cryptic species complex and widely distributed throughout tropical and subtropical regions. To understand the B. tabaci cryptic species diversity in China more comprehensively, in the year 2014 and 2016, a large-scale sampling was conducted from the famous biodiversity hotspot of China, Yunnan province. Mitochondrial cytochrome oxidase I gene sequences were used to identify new putative cryptic species. Phylogenetic analyses were performed using Bayesian methods to evaluate the position of new cryptic species in the context of the B. tabaci diversity in Asia. Two new cryptic species, China 5 and Asia V were identified. In total, 19 B. tabaci cryptic species are present in China, two invasive (MED and MEAM1) and 17 indigenous. A new sibling species of B. tabaci was first defined and reported. Based on the mtCOI sequences and haplotype network analyses, the genetic diversity of MED was far higher than MEAM1. We confirmed the exotic MED was originated from the western Mediterranean regions and first invaded into Yunnan, China. The genetic structures of other four indigenous species (Asia I, Asia II 1, Asia II 6, and China 1) with relatively wide distribution ranges in China were also discussed. [ABSTRACT FROM AUTHOR]

The occurrence and damage of Xylotrechus quadripes Chevr were investigated in different time points and micro environments in Simao south island river coffee test demonstration field. The results showed that X. quadripes mainly damaged 5-year-old coffee trees. X. quadripes occurred one generation per year in Simao region, and the larval stage lasted 296-322 d. The adult could be found in four seasons because of different development progress and overlapping generations. In different micro environments, X. quadripes were mainly distributed in mixed forests and the coffee land in sunny slope. The adult enjoyed sunshine on the coffee trees at noon. The natural enemy Prislauacus nigripea kieff was found to parasitize in the larvae of X. quadripes, which could control the population of X. quadripes. [ABSTRACT FROM AUTHOR]

Background: Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a newly discovered long intergenic noncoding RNA (lincRNA), has been reported to be aberrantly expressed in various cancers, and may serve as a novel potential biomarker for cancer prognosis. This meta-analysis was conducted to investigate the effects of MALAT1 on cancer prognosis and lymph node metastasis. Methods: A quantitative meta-analysis was performed using a systematic search of PubMed, Medline and Web of Science databases to identify eligible papers on prognostic value of MALAT1 in cancers. The pooled hazard ratios (HRs) or odds ratios (OR) with a 95 % confidence interval (95 % Cl) were calculated to evaluate its prognostic value. Results: A total of 2094 patients from 17 studies between 2003 and 2016 were included. The results revealed that elevated MALAT1 expression was significantly associated with poor overall survival (OS) in 11 types of cancers (HR = 1.91, 95 % CI 1.49-2.34). Furthermore, subgroup analysis indicated that region of study (Germany, Japan or China), cancer type (digestive system cancers, urinary system cancers or respiratory system cancers) and sample size (more or less than 100) did not alter the significant predictive value of MALAT1 in OS from various types of cancer. In addition, upregulation of MALAT1 expression was significantly associated with poor disease-free survival (HR = 2.29, 95 % CI 1.24-3.35), and recurrence-free survival (HR = 2.09, 95 % CI 0.81-3.37). The results showed that the incidence of lymph node metastasis was higher in high MALAT1 expression group than that in low MALAT1 expression group (OR = 1.67, 95 % CI 1.30-2.15). Conclusions: This meta-analysis revealed that elevated MALAT1 expression may serve as a novel predictive biomarker for poor survival and lymph node metastasis in different types of cancer. [ABSTRACT FROM AUTHOR]

Heavy metals not only adversely affect the quality of tobacco leaves, but also very adverse effects on human health. In order to find out the effective cultivation method of controlling heavy metal content in flue-cured tobacco, the content of four kinds of heavy metals in soil and tobacco leaves in different intercropping treatments was tested. The results showed that there were significant differences between the effects of interheavy metal content in tobacco leaves and play a very important and positive role in actual production. [ABSTRACT FROM AUTHOR]

Retinitis pigmentosa (RP) is a heterogenous group of inherited retinal degenerations caused by mutations in at least 50 genes. To identify genetic mutations underlying autosomal recessive RP (arRP), we performed whole-exome sequencing study on two consanguineous marriage Indian families (RP-252 and RP-182) and 100 sporadic RP patients. Here we reported novel mutation in FAM161A in RP-252 and RP-182 with two patients affected with RP in each family. The FAM161A gene was identified as the causative gene for RP28, an autosomal recessive form of RP. By whole-exome sequencing we identified several homozygous genomic regions, one of which included the recently identified FAM161A gene mutated in RP28-linked arRP. Sequencing analysis revealed the presence of a novel homozygous frameshift mutation p.R592FsX2 in both patients of family RP-252 and family RP-182. In 100 sporadic Indian RP patients, this novel homozygous frameshift mutation p.R592FsX2 was identified in one sporadic patient ARRP-S-I-46 by whole-exome sequencing and validated by Sanger sequencing. Meanwhile, this homozygous frameshift mutation was absent in 1000 ethnicity-matched control samples screened by direct Sanger sequencing. In conclusion, we identified a novel homozygous frameshift mutations of RP28-linked RP gene FAM161A in Indian population. [ABSTRACT FROM AUTHOR]

In order to ascertain the invasive mechanism and control strategy of the invasive Crofton weed, Ageratina adenophora, its ecological adaptability and population differentiation, the formation of single dominant population, displacement of native plants and sustainable management strategies were investigated. The present results helped to clarify and explain such issues as the adaptability post invasion, interaction and competition between inter- and intra-species and community resistance, thereby providing important references to researches on other invasive alien species. [ABSTRACT FROM AUTHOR]

In this article number 20200128, Zhen Li and co-workers have summarized the recent advances of the NIR-II fluorescence imaging technique, and addressed its significance in the early prevention and treatment of cerebral diseases inclusive of traumatic brain injury (TBI), stroke, and cerebroma. The advanced NIR-II fluorescence imaging system and nano-fluorophores enable the dynamic and visible evaluation of cerebral lesions from tissue, cellular and molecular levels. Cover Picture: NIR-II Fluorescence imaging for cerebrovascular diseases (View 6/2021). [Extracted from the article]

The bamboo–wood composite container floor (BWCCF) has been wildly utilized in transportation in recent years. However, most of the common approaches of mechanics detection are conducted in a time-consuming and resource wasting way. Therefore, this paper aims to provide a frugal and highly efficient method to predict the short-span shear stress, the modulus of rupture (MOR) and the modulus of elasticity (MOE) of the BWCCF. Artificial neural network (ANN) models were developed and support vector machine (SVM) models were constructed for comparative study by taking the characteristic parameters of image processing as input and the mechanical properties as output. The results show that the SVM models can output better values than the ANN models. In a prediction of the three mechanical properties by SVMs, the correlation coefficients (R) were determined as 0.899, 0.926, and 0.949, and the mean absolute percentage errors (MAPE) were obtained, 6.983%, 5.873%, and 4.474%, respectively. The performance measures show the strong generalization of the SVM models. The discoveries in this work provide new perspectives on the study of mechanical properties of the BWCCF combining machine learning and image processing. [ABSTRACT FROM AUTHOR]

Atropanthe sinensis Pascher (genus Atropanthe, family Solanaceae) is an endangered and medical important plant of China. Here, we report the complete plastome of A. sinensis, which was found to be 156,565 bp in length and encodes 114 annotated known unique genes, including 80 protein-coding genes, 4 ribosomal RNAs, and 30 transfer RNAs. Among them, 10 coding genes contained one intron each and two genes (clpP and ycf3) contained two introns each. The result of the phylogenetic analysis showed that genera Scopolia and Przewalskia were placed as sister groups to the Atropanthe. [ABSTRACT FROM AUTHOR]