Search

Background:Ovarian cancer(OC) is the most lethal carcinoma among all gynecological malignancies.Based on the continued understanding of interaction relationships between immune components in tumor microenvironment (TME) and OC cells,immunotherapies have demonstrated to be dramatically effective in increasing survival rates.This research aims to construct a risk model and identify landmark genes which are of vital importance to improve the prognosis of OC. Methods:The gene expression data of 379 OC patients were extracted from The Cancer Genome Atlas(TCGA) database,and immune and stromal related genes were analyzed by difference analysis and weighted correlation network analysis (WGCNA).Subsequently,univariate and multivariate Cox regression analyses were used to build an risk model for OC.Kaplan-Meier survival curves were then taken to depict survival difference between high- and low-risk subgroups.Meanwhile,receiver operating characteristic (ROC) curves and the nomograms were applied to assess the accuracy and validity of the model.Finally,differentiation of immune cells,immune checkpoint molecules,and biological functions between high- and low-risk categories were identified to predict immunotherapy efficacy for OC.Results:GIMAP7,HTRA4,CCL5,ICOS,CD40LG,CD3G,VSIG4,CD2,ANKRD22 were obtained to construct the prognosis risk model;high risk score was an prognosis factor of poor survival rate of OC patients.Further ROC curve and nomogram analyses showed that this model exhibited excellent performance in predicting the 1-,3-,and 5-year survival rate.We obtained 17 functional immune cells,17 immune checkpoint molecules,several immune-related reactions,and GO items which might change the prognosis of OC patients.Conclusions:The 9-genes prognostic model may play critical roles as potential prognostic markers and offer personalized immunotherapy protocols for OC and may provide a theoretical foundation for new immunotherapy combinations.

MicroRNA (miRNA) is an endogenous single-stranded noncoding small RNA with a base length of 18-30, which widely exists in eukaryotic cells. It plays an important role in plant growth and development, metabolic biosynthesis and stress response. Mature miRNAs are evolutionarily conserved and have both sequential and tissue-specific expression. This paper summarizes the production, action mechanisms, main technologies, research progress and biological functions of miRNAs. miRNA research includes miRNA discovery (genetic screening, direct cloning, bioinformatics prediction and high-throughput sequencing) and biological function analysis (overexpression, the expression or inhibition of target gene mutants). It was found that most miRNAs are involved in plant secondary metabolism biosynthesis and have great potential as molecular breeding tools. The same biological process can be regulated by different miRNAs. Interestingly, the role of the same miRNA in different plants may behave in completely opposite manner, and the mode of action of each miRNA is also unique. Moreover, miRNA interaction and miRNA self-regulation will also be the developmental direction in the future. However, miRNA target recognition and functional verification are still major challenges for the future. This study will provide a reference for further exploration and verification the specific biological functions and related applications of miRNAs in plants.

Background Tertiary lymphoid structures (TLSs) are formed by the aggregation of tumour-infiltrating lymphocytes (TILs), which is driven by chemokines or cytokines in the tumour microenvironment. Studies have shown that TLSs are associated with good prognosis in patients with various solid tumours and can improve patient responses to immunotherapy. However, the role of TLSs in hepatocellular carcinoma (HCC) remains controversial, and the underlying molecular mechanism is unclear. Methods According to haematoxylin-eosin (HE) staining results, 150 HCC patients from Xijing Hospital were divided into TLS + and TLS- groups, and Kaplan–Meier (K-M) analysis was performed to assess their overall survival (OS) and recurrence-free survival (RFS). Spearman correlation analysis was used to calculate the correlation between LCK and TILs, and the molecular pathways of LCK regulating immunotherapy were clarified through enrichment analysis. Immune score was calculated based on the expression difference of LCK to evaluate the sensitivity of HCC patients to ICIs. Results The HE results showed that 61 (40.7%) of 150 HCC patients had TLSs, and 89 (59.3%) didn't. The K-M results showed that TLSs had no effect on the OS of HCC patients but significantly affected the RFS. Enrichment analysis showed that upregulation of LCK expression mainly regulated cytokine signalling pathway, the chemokine signalling pathway and T cell activation. Immune score showed that HCC patients with high expression of LCK had higher sensitivity to ICIs. Conclusion LCK may regulate the sensitivity of HCC patients to ICIs by affecting the related pathways of TLSs formation to improve the prognosis of patients.

Background Coiled-coil domain-containing protein 34 (CCDC34), which belongs to the CCDCs family, has been recently reported to be up-regulated in various kinds of tumors. However, its role in the development of hepatocellular carcinoma (HCC) still remains unclear. Materials and methods In this study, real-time polymerase chain reaction (RT-PCR) and Western blot analysis were performed to measure the mRNA and protein levels of CCDC34 in clinical samples. Kaplan-Meier method was used to analyze the relationship between CCDC34 and the prognosis in HCC patients. CCK-8 and colony formation assays were conducted to investigate CCDC34's effect on the cell proliferation, and Transwell assays were used to detect CCDC34's effect on the cell metastasis. Moreover, subcutaneous xenograft tumor model and lung metastasis model were applied to confirm the impact of CCDC34 on the HCC development. Lastly, RNA sequencing and Western blot analysis were performed to probe the underlying mechanism of CCDC34's effect on HCC. Results CCDC34 was significantly induced in HCC tissues, and the overexpression of CCDC34 predicted the poor outcomes among HCC patients. It was verified by the in vitro and in vivo experiments that CCDC34-knockdown potently inhibited the proliferation and metastasis of HCC cells. Subsequent results indicated that CCDC34 inhibition can affect the activation of protein kinase B (PKB or AKT) as well as epithelial-mesenchymal transition (EMT) process. Conclusion CCDC34 is significantly associated with HCC. It will become a promising prognostic biomarker and therapeutic target against HCC.

A centipede like thiocyanate-bridged multi-nuclear copper(I/II) complex, [Cu2L(CH3OH)(NCS)3]n, derived from 2-(((2-(dimethylamino)ethyl)imino)methyl)-5-fluorophenol (HL), was prepared and characterized by elemental analysis, IR and UV–vis spectra, as well as single crystal X-ray diffraction. The Cu1 ion in the +2 oxidation state is coordinated by the tridentate Schiff base ligand in a square pyramidal geometry, with the other two sites occupied by one N atom of the thiocyanate ligand and one methanol O atom. The Cu2 ion in the +1 oxidation state is coordinated by one N and three S atoms from four thiocyanate ligands, forming a tetrahedral geometry. The CuI ions are linked by thiocyanate ligands to form a one-dimensional chain with [CuI2(μ1,3,3-NCS)2] as the repeat unit. The [CuIIL(CH3OH)] moieties are linked to the chain through thiocyanate ligands. The complex has remarkable inhibitory activity on Jack bean urease with an IC50 value of 1.3 μmol L–1.

Nitrogen (N) is an indispensable element for plant growth and development. To understand the regulation of underlying carbon (C) and N metabolism in blackberry plants, we performed integrated analyses of the physiology, metabolome and transcriptome. Blackberry plants were subjected to no N, nitrate (NO

Blueberry belongs to the genus Vaccinium L. in the Ericaceae and is an economically important shrub that produces small berries that are rich in nutrients. There were differences in the appearance of blueberry leaves under different shade treatments. To explore the differences in metabolites in blueberry leaves under different shading treatments, nontargeted liquid chromatography–mass spectrometry (LC–MS) metabonomic analysis was performed. Different shade intensities resulted in significant differences in the contents of metabolites. A total of 6879 known metabolites were detected, including 750 significantly differentially expressed metabolites, including mainly lipids and lipid-like molecules and phenylpropanoid and polyketide superclass members. Based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, the flavone and flavonol biosynthesis pathways were the most significantly enriched. The results of this study provide a reference and scientific basis for the establishment of a high-quality and high-yield shaded blueberry cultivation system.

The conversion of CO

Due to the lack of effective and stable reference genes, studies on functional genes in Rubus, a genus of economically important small berry crops, have been greatly limited. To select the best internal reference genes of different types, we selected four representative cultivars of blackberry and raspberry (red raspberry, yellow raspberry, and black raspberry) as the research material and used RT-qPCR technology combined with three internal stability analysis software programs (geNorm, NormFinder, and BestKeeper) to analyze 12 candidate reference genes for the stability of their expression. The number of most suitable internal reference genes for different cultivars, tissues, and fruit developmental stages of Rubus was calculated by geNorm software to be two. Based on the results obtained with the three software programs, the most stable genes in the different cultivars were RuEEF1A and Ru18S. Finally, to validate the reliability of selected reference genes, the expression pattern of the RuCYP73A gene was analyzed, and the results highlighted the importance of appropriate reference gene selection. RuEEF1A and Ru18S were screened as reference genes for their relatively stable expression, providing a reference for the further study of key functional genes in blackberry and raspberry and an effective tool for the analysis of differential gene expression.

BACKGROUND Free fractions of different blackberry varieties' extracts are high in phenolic compounds with antioxidant activities. However, the phenolic profiles and antioxidant activities against peroxyl radicals of bound fractions of different blackberry varieties' extracts have not been previously reported. In addition, what the key antioxidant phenolic compounds are in free and bound fractions of blackberry extracts remain unknown. This study aimed to investigate the phenolic profiles and antioxidant activities of free and bound fractions of eight blackberry varieties' extracts and reveal the key antioxidant phenolic compounds by boosted regression trees. RESULTS Fifteen phenolics (three anthocyanins, four flavonols, three phenolic acids, two proanthocyanidins, and three ellagitannins) were identified in blackberry by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Ferulic acid, ellagic acid, procyanidin C1, kaempferol-O-hexoside, ellagitannins hex, and gallic acid were major bound phenolics. Bound fractions of eight blackberry varieties' extracts were high in phenolics and showed great antioxidant activity. Boosted regression trees analysis showed that cyanidin-3-O-glucoside and chlorogenic acid were the most significant compounds, contributing 48.4% and 15.9% respectively to the antioxidant activity of free fraction. Ferulic acid was the most significant antioxidant compound in bound fraction, with a contribution of 61.5%. Principal component analysis showed that Kiowa was the best among the eight varieties due to its phenolic profile and antioxidant activity. CONCLUSION It was concluded that blackberry varieties contained high amounts of bound phenolics, which confer health benefits through reducing oxidative stress. Ferulic acid was the key compound to explain the antioxidant activities of bound fractions. © 2021 Society of Chemical Industry.

A series of flume experiments were carried out to investigate the influence of tidal turbine rotor diameter to depth ratio on the hydrodynamic process of wake flow using two different diameter rotor discs of the same porosity. Time-varying velocities were measured by an Acoustic Doppler Velocimeter at 8 cross-sections over the distance of 10 diameters downstream, and the three-dimensional structures of wake flow and turbulence fields were obtained. Immediately downstream, the peak of velocity deficit occurred at the wake core and the value was greater for the large diameter-depth ratio. Strong wake turbulence was mainly located in the shear stress layer around wake core. However, the attenuation processes of wake hydrodynamics were different under two diameter-depth ratios. The momentum transfer was caused by Reynolds shear stress in both transverse and vertical directions. The vertical momentum transfer process was much more significant above the wake core than the lateral transfer process, but it decayed rapidly in near wake as the diameter-depth ratio enlarged. The experimental results provide detailed data to better understand the wake propagation processes behind rotor discs.

For selective hydrogenation of substrates that contain diversified unsaturated groups, it is difficult to address the dilemma between activity and selectivity. Herein, we developed Pt Fe nanowires with abundant high-index facets which created steric effect for improved selectivity without occupying or passivating active sites. During the selective hydrogenation of acetophenone, the turnover frequency number of Pt Fe nanowires was 97.7 min−1 at 70 °C, 5.7 times higher than that (17.2 min−1) of cubic counterparts. The selectivity for C = O groups over Pt Fe nanowires reached 91.7% at a conversion of 99.3%, whereas that over nanocubes was only 60.2% at a conversion of 98.4%. The high C O selectivity of Pt Fe nanowires was attributed to the steric effect, where the stepped surfaces composed of high-index facets selectively adsorbed C O bonds and inhibited the adsorption of aromatic rings.

Fruit flesh firmness plays a critical role in controlling blackberry (Rubus spp.) postharvest shelf life. This work aimed to identify the underlying characteristics in pericarp morphology, cell wall hydrolase activity and cell wall composition that account for flesh firmness in soft-fruited ‘Boysen’ and firm-fruited ‘Arapaho’ cultivars that have a similar ripening time of 39 days after flowering (DAF). The fruit firmness of both fruits decreased noticeably at the onset of color change, and this decrease hastened from 33 DAF to ripening despite considerable differences in their temporal changes. The evaluation of pericarp cellular morphology revealed that the disassembly of the cell wall in both fruits was likely initiated at 33 DAF, followed by extreme degradation at 39 DAF. Cell wall hydrolase activity assays indicated that increases in polygalacturonase (PG) and cellulase activity also dramatically occurred in the late softening stages of both fruits. Notably, appreciably higher levels of cellulase, and significant increases in pectin methylesterase (PME), α-L-arabinofuranosidase (α-L-Af) and xyloglucan endotransglycosylase (XET) were only detected in the late ripening stages of ‘Boysen’. In terms of cell wall components, the levels of cell wall material (CWM), cellulose and hemicellulose declined similarly during ripening in both fruits. Comparatively, lower levels of CWM, chelator soluble pectin (CSP), sodium carbonate soluble pectin (SSP), and hemicellulose as well as higher levels of water soluble pectin (WSP) were found in ‘Boysen’ than those in ‘Arapaho’ during maturation and ripening. Overall, the loss of fruit firmness during ripening in blackberry fruit is correlated closely with biochemical changes in cell wall fractions that involve hydrolytic processes, resulting in the breakdown of cell-wall polymers. The low firmness of ‘Boysen’, as determined by cell wall degradation, could be of particular relevance to the function of cell wall degrading enzymes and to the more drastic degradation of cell wall components than that in the firm cv. ‘Arapaho’.

Background Blackberry postharvest diseases are caused by fungal pathogens, and treatment of fruits with edible, natural products could reduce the postharvest losses and contribute to food sustainability. Based on the hypothesis that inhibition of fungal pathogens will significantly extend the shelf-life of food products, the effects of natural antifungal agents on fungal pathogens were tested. Results Two pathogenic fungal isolates, Aspergillus japonicus and Gilbertella persicaria, from infected blackberry fruits were identified morphologically using scanning electron microscopy and confirmed by DNA sequence analysis. The inhibitory effects and synergistic action of natural antifungal agents against the two fungal isolates were investigated. The results obtained demonstrated that the natamycin, chitosan and ferulic acid exhibited significant antifungal activities against the tested strains based on the calculated minimum inhibitory concentration. The best antifungal activity was obtained using a combination of ferulic acid and natamycin, which generated a total synergistic effect on both tested strains with a fractional inhibitory concentration index of 0.281. Application of the selected agents on postharvest blackberry fruits reduced the rot ratio and weight loss and also increased fruit firmness. In addition, the shelf-life of fresh blackberry fruits was extended up to 12-15 days at 4 °C and 90 ± 5% relative humidity. Conclusion The combined utilization of ferulic acid and natamycin showed synergistic antifungal activity against two pathogenic fungal isolates, and extended the shelf life of fresh blackberry fruits up to 12-15 days. © 2018 Society of Chemical Industry.

Based on the upper limit theorem of limit analysis and the Hoek-Brown failure criterion and considering the adverse influence of the seepage force, we established a stability analysis method of analyzing the water-resistant rock mass of a karst tunnel face, developed a critical safety thickness criterion for water inrush caused by the instability of the tunnel face, and conducted a sensitivity analysis of the main influencing parameters. We defined the safety coefficient (k) of the tunnel face’s resistance to water-inrush instability during the tunnel excavation process and analyzed the dynamic evolution characteristics of the tunnel face’s stability during the tunnel construction according to the safety coefficient. We used the method introduced in this paper to calculate the safe thickness of the water-resistant rock mass of the Xiema tunnel face in the first horizontal line of the Chongqing Expressway where it is adjacent to karst cavity 268. We compared these results with the calculation results of a method that did not consider the adverse influence of the karst water seepage force. The results showed that the safety thickness of the water-resistant rock mass calculated using the method proposed in this paper more accurately conformed to the actual situation of the project, which can more effectively ensure the construction safety of the tunnel segment adjacent to the anterior, concealed, high-pressure, water-rich karst cavity. The results of this study hold great significance for improving the predictability and targeted prevention of water-inrush disasters in karst tunnels.

Background: The prognosis of hepatocellular carcinoma (HCC) is not optimistic. Our study focused on present inflammatory markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), gamma-glutamyl transpeptidase-to-platelet ratio (GPR), aspartate aminotransferase-to-lymphocyte ratio (ALR) and fibrinogen-to-albumin ratio (FAR), and aimed to explore their optimal combination for the prognosis of HCC after resection.Methods: 347 HCC patients with curative resection were enrolled. The optimal cutoff values of the inflammatory markers were calculated using receiver operating characteristic (ROC) curve analysis, and used to divide patients into two groups whose differences were compared by Kaplan-Meier analysis. Cox univariate and multivariate analysis were used to analyze the independent prognostic inflammatory markers. c2 test was chosen to determine the relationship between independent prognostic inflammatory markers and clinicopathological features. We created the combined scoring models and evaluated them by Cox univariate and multivariate methods. The concordance index (C-index), Akaike information criterion (AIC) and likelihood ratio were calculated to compare the models. The selected optimal inflammatory markers and their combinations were tested in different stages of HCC by Kaplan-Meier analysis.Results: ALR and GPR were independent prognostic factors for DFS; ALR, PLR, and GPR were independent prognostic factors for OS. The proposed GPR and ALR-GPR-PLR score models were independent predictors for DFS and OS, respectively.Conclusion: The preoperative GPR and ALR-GPR-PLR score models were independent predictors for DFS and OS, respectively, and performed well in stratifying patients with HCC. The higher score in the model, the worse the prognosis was.

The study of rockburst criterion is the key to predict whether rockburst occurs or not. First of all, based on the energy principle and taking the rock strength and overall failure criterion as the benchmark, the rockburst proneness criterion of rock mass unit under compression and tension was established. The criterion took into account the integrity factors, mechanical factors, brittleness factors and energy storage factors in the process of rockburst inoculation, and three rockburst classification thresholds (2, 11 and 110) for four grades of none, weak, moderate and severe rockburst were proposed. Second, Taking the typical rockburst disaster as examples, the rationality of the existing classical rockburst criterions and the rockburst proneness criterion proposed in this paper were tested, and the results showed that this criterion had good engineering applicability. Finally, the numerical simulation analysis of rockburst disaster in 2# diversion tunnel of Jinping II hydropower station was carried out by using this criterion. The results were basically consistent with the actual situation, which verified the accuracy and effectiveness of the rockburst proneness criterion proposed in this paper. The research results can provide reference for the evaluation and prediction of rockburst disaster in deep underground engineering.

A well-designed heteroleptic ruthenium(ii) polypyridyl complex demonstrated stable target-specific in vitro Golgi apparatus imaging abilities in HeLa cell lines. After utilizing photodynamic therapy via UV excitation, the Ru-SL complex could be triggered to generate singlet oxygen (1O2) and red fluorescence signals. 1O2 was highly cytotoxic and could induce DNA damage and the disappearance of the Golgi apparatus. The red fluorescence signals disappeared gradually, suggesting that the live or dead state of the cells can be estimated from the fluorescence signal intensity.

A reactive power reserve prediction method for ev charging piles based on big data and optimized neural network is proposed. Firstly analyzes the big data environment on the influence of the reactive power reserve prediction method, put forward the electric vehicle charging pile, the concept of dynamic reactive power reserve, studied the factors impact on reactive power reserve, established the pulsating current and direct current (dc) reactive power reserve capacity correction of electric vehicle charging pile analysis, the mathematical model and particle swarm optimization neural network model is established, and put forward the reactive power reserve prediction scheme based on big data analysis. Finally, the proposed method is verified with grid data and compared with the predicted results of traditional artificial neural network. The results show that this method has high precision and can effectively reduce the time required for prediction, and improve the stability of the voltage of the power grid.

The concept of career planning is related to the development of students and is an important part of the values of college students.Therefore, career planning guidance is an important part of ideological and political education.Based on the theory of self-efficacy and based on the theory of self-efficacy, this article uses the course of “College Students’ Career Planning” as the main carrier to explore the guidance of college students’ career planning concepts.From the perspectives of freshmen’s mental health, it puts forward suggestions for college students’ career planning perspectives and corresponding course teaching.

Blackberry fruit is rich in anthocyanins, showing incomparable nutritional and health value. Anthocyanins are flavonoids that are downstream products of the flavonoid biosynthesis pathway. They are important secondary metabolites with antioxidant and anticancer functions. Therefore, we performed combined transcriptome and metabolome analyses of unripe and ripe blackberry fruits to identify the molecular mechanisms of flavonoid biosynthesis. Herein, we identified 997 differentially expressed metabolites (DEMs) in positive-ion mode, 411 DEMs in negative-ion mode, and 17,566 differentially expressed genes (DEGs). Eight DEMs and 16 DEGs were annotated to the flavonoid biosynthesis pathway. Four DEGs related to flavonoids (unigene 0028088, unigene 0039337, unigene 0063209, and unigene 0014842) were positively correlated with related flavonoid DEMs. Interestingly, 8 DEGs and 11 flavonoid-related DEMs showed significant negative correlations. This study lays a foundation for further research on the biosynthesis and metabolism of flavonoid, providing a reference for the future breeding and cultivation of excellent high-flavonoid germplasm resources and the blackberry-related pharmaceutical industry.

Background: Blueberry（Vaccinium Spp）is a popular healthy fruit all over the world. The health value of blueberry is mainly due to the fact that blueberry is rich in anthocyanins, which have a strong antioxidant capacity. However, due to the fact that blueberry is a non model plant, little is known about the structural genes and regulatory genes involved in the anthocyanin synthesis of blueberries. Previous studies have found that spraying abscisic acid at the late green stage of blueberry fruit can increase the content of anthocyanins. Based on the former results, the anthocyanin accumulation process of blueberry can be divided into six stages from late green stage to mature stage to analyze the anthocyanin synthesis mechanism. In order to identify the important genes in the anthocyanin synthesis process of blueberry, the transcriptome analysis was conducted to explore the key genes in blueberry anthocyanin synthesis process.Results: The results showed that ABA could increase the anthocyanin content of blueberry fruits during the veraison. The effect of ABA on blueberry fruit development was systematically analyzed by KEGG and GO. All structural genes and transcription factors (MYB, bHLH and WD40) involved in anthocyanin pathway were identified and their spatiotemporal expression patterns were analyzed. The expression of CHS, CHI, DFR and LDOX / ANS in ABA treated fruits was higher in S5-S6, which was consistent with the change of anthocyanins in fruits.In general, six MYB transcription factors, one bHLH transcription factor and four WD40 transcription factors under treatment were found to have significant changes in transcripts during fruit ripening. Conclusions: Our results suggest that VcMYBA should play a major role in the regulation of anthocyanin synthesis in ABA signaling. This result preliminarily explained the mechanism of ABA increasing anthocyanin content and improves the efficiency of industrial use of blueberry anthocyanins.

Background Hainan Island, located in the South China Sea and separated from the Leizhou Peninsula by Qiongzhou Strait, is the second largest island after Taiwan in China. With the expansion of Han Chinese and the gradual formation of “South Hlai and North Han”, nowadays, Hainan Hlai is the second largest population after Han Chinese in Hainan Island. Ha Hlai, distributed in southwest and southern Hainan Island, is the dominant branch of Hlai and speaks Ha localism. Methods We utilized the Huaxia™ Platinum PCR Amplification System (including 23 autosomal STRs and 2 sex‐linked markers) to obtain the first STR profiling batch of 657 Ha Hlai individuals (497 males and 160 females). In order to explore the genetic relationships between the studied Ha Hlai and other reference populations with different language families, population genetic analyses, including PCA, MDS, STRUCTURE, and phylogenetic analysis, were conducted based upon the raw data and allelic frequencies of the polymorphic autosomal STR markers. Results In total, 271 distinct alleles were observed at the 23 STR loci. The number of diverse alleles ranged from 7 at TPOX locus to 23 at FGA locus, and the allelic frequencies varied from 0.0008 to 0.5533. In addition, the CPE and CPD were 1‐7.39 × 10−10 and 1‐3.13 × 10−28, respectively. The phylogenetic analyses indicated that Ha Hlai is a Tai‐Kadai language‐speaking and relatively isolated population which has a close genetic and geographical relationship with Hainan Hlai, and M95 is the dominant haplogroup in Ha Hlai (56.18%). Conclusion The 23 autosomal STR genetic markers were highly polymorphic as well as potentially useful for forensic applications in Hainan Ha Hlai population. The phylogenetic analyses demonstrated that small geographic scale gene flows could not be ignored and the shaping of the unique gene pool for each population was the combination effects of geographic, language, and cultural isolations., The first batch of 23 autosomal STR profiles of Ha Hlai, one important branch of Hainan Li (Hlai), were obtained and reported by genotyping 657 Ha Hlai individuals (497 males and 160 females) utilizing the Huaxia™ Platinum PCR Amplification System. The analyses and comparisons of all these allelic frequencies and forensic statistical parameters demonstrated that the 23 autosomal STR genetic markers included in Huaxia™ Platinum PCR Amplification System were highly polymorphic as well as potentially useful for forensic applications in Hainan Ha Hlai population. Ha Hlai is a Tai‐Kadai language‐speaking and relatively isolated population which has a relatively close relationship with Hainan Hlai, and the haplogroup M95 is the dominant haplogroup in Ha Hlai (56.18%), which demonstrated that the relatively small geographic scale gene flows, especially for the multi‐ethnic mixed areas, could not be ignored and the shaping of the unique gene pool for each population the co‐effects of geographic, language, and cultural isolations.

Artificial neural networks are a dominant force in our modern era of data-driven artificial intelligence. The adaptive neuro fuzzy inference system (ANFIS) is a neural network based on fuzzy logic versus a more traditional premise like convolution. Advantages of ANFIS include the ability to encode and potentially understand machine learned neural information in the pursuit of explainable, interpretable, and ultimately trustworthy artificial intelligence. However, real-world data is almost always imperfect, e.g., incomplete or noisy, and ANFIS is not naturally robust. Specifically, ANFIS is susceptible to over inflated uncertainty, poor antecedent (fuzzy set) data alignment, degenerate optimization conditions, and hard to interpret logic, to name a few factors. Herein, we explore the use of possibilistic clustering to identify outliers, specifically typicality degrees, to increase the robustness of ANFIS; or any fuzzy logic neuron/network. Experiments are presented that demonstrate the need and quality of the proposed solutions in the pursuit of robust interpretable machine learned neuro fuzzy logic solutions.

The use of photoelectrochemical (PEC) sensors, with their outstanding advantages of remarkable sensitivity, inherent miniaturization, portability and easy integration, is becoming a promising analytical detection technique. The rational design of PEC materials and convenient establishment of PEC analysis platforms have given this technique tremendous popularity in both analytical and medical communities for biomolecule detection. However, most of the current efforts in the development of PEC analysis have been made with ultraviolet and visible light (UV-vis) as light source, which are detrimental to biomolecules because of their high energy. On the contrary, near-infrared (NIR) light is biocompatible and is available for in vivo detection. Herein, a prototype of NIR light-responsive PEC analysis platform is first proposed with defect-engineered TiO

Examining most streaming clustering algorithms leads to the understanding that they are actually incremental classification models. They model existing and newly discovered structures via summary information that we call footprints. Incoming data is normally assigned a crisp label (into one of the structures) and that structure's footprint is incrementally updated. There is no reason that these assignments need to be crisp. In this paper, we propose a new streaming classification algorithm that uses Neural Gas prototypes as footprints and produces a possibilistic label vector (of typicalities) for each incoming vector. These typicalities are generated by a modified possibilistic k-nearest neighbor algorithm. The approach is tested on synthetic and real image datasets. We compare our approach to three other streaming classifiers based on the Adaptive Random Forest, Very Fast Decision Rules, and the DenStream algorithm with excellent results.

There is increasing interest in the “Internet of Things” (IoT) and the development of wearable intelligent devices with human–machine interfaces (HMIs). Flexible touch panels have received wide attention because they are intuitive HMIs. However, most existing flexible touch panels can only detect a single touch or rely on massive electrodes and complex sensor arrays for multi-touch detection. Herein, a long service life (>5 months), wearable, and Multifunctional HMI (MHMI) with only two electrodes is reported for various applications. An anti-drying, transparent, ion-conducting, and tough organohydrogel with satisfactory stretchability (>450%) and long life is developed as a sensing material. A parallel mutual inspection detection structure based on ion conductors is designed to detect single or multiple touches accurately and sensitively. This structure comprises a pair of organohydrogel strips in a horizontal or spiral form embedded in a flexible substrate to construct one-dimensional (1D) or two-dimensional (2D) MHMIs. The 1D- and 2D-MHMIs can be used as linear controllers and 2D movement controllers, respectively. The multi-touch recognition function endows the MHMIs with greater operability by programmatically implementing multi-device switching and multi-function selection in a versatile and effective manner. Therefore, the devices have great potential for use in the IoT-related applications.

Older adults have experienced greater isolation and mental health concerns during the COVID-19 pandemic. In long-term care (LTC) settings, residents have been particularly impacted due to strict lockdown policies. Little is known about how these policies have impacted older adults. This study leveraged existing research with embedded sensors installed in LTC settings, and analyzed sensor data of residents (N=30) two months pre/post the onset of the U.S. COVID-19 pandemic (1/13/20 to 3/13/20, 03/14/20 to 5/13/20). Data from three sensors (bed sensors, depth sensors, and motion sensors) were analyzed for each resident using paired t-tests, which generated information on the resident’s pulse, respiration, sleep, gait, and motion in entering/exiting their front door, living rooms, bedrooms, and bathrooms. A 14.4% decrease was observed in front door motion in the two months post-onset of the pandemic, as well as a 2.4% increase in average nighttime respiration, and a 7.6% increase in nighttime bed restlessness. Over half of our sample (68%) had significant differences (p

The remote sensing and control of biomimetic robot fishes is an important but challenging task because the available underwater acoustic communication cannot accommodate their size, power consumption, and price. Hence, we propose a power-efficient, low-complexity time reversal pulse position modulation communication scheme, which partitions the available bandwidth of a transducer into several different sub-bands using different linear frequency modulated (LFM) pulses. The information is reflected by the position of the LFM pulses with different start and end frequencies for adjacent symbols. In the receiver, the Doppler factor is obtained by cross-correlating two hyperbolic frequency modulation signals transmitted before and after the modulated signal, and the channel response is estimated by match filtering the sync preamble. Furthermore, time reversal and bandpass filtering are performed to mitigate intrasymbol and intersymbol interferences caused by the multipath effects of underwater acoustic channels, respectively. The effectiveness and robustness of the proposed communication scheme are confirmed experimentally.

The AC electrokinetic technology, such as AC electroosmosis, induced-charged electroosmosis, dielectrophoresis, etc., can precisely manipulate trace fluids and has been widely used in lab on a chip. However, the power supplies used in AC electrokinetic experiments are mostly function generators or other large-scare instruments, which is an obstacle to portability. Encouragingly, triboelectric nanogenerator (TENG) with the characteristics of portable, green, and simple structure is a potential opportunity for AC electrokinetic microfluidic operation. We have designed a self-powered AC electrokinetic microfluidic system based on vertical contact-separation mode TENG for the first time. The TENG, as a power supply, costs only 2 cents and maintains excellent output performance after millions of working cycles. Through the combination of TENG and microfluidic chip, this system successfully realizes AC electroosmotic flow and induced-charged electroosmotic flow in the microchannel and completes the effective mixing of two fluids at low frequencies (

Blackberry and raspberry flavonoid compounds, including anthocyanins, are known for their nutritional and health benefits. Five representative Rubus fruits (blackberry, red raspberry, yellow raspberry, black raspberry, Rubus hybrid ‘Young’ fruit) were examined. The yellow raspberry ‘Colde Summit’ had the brightest color. The Rubus hybrid ‘Young’ had the highest brix and ‘Colde Summit’ the lowest solidity-acid ratio. In total, 2118 and 1089 known metabolites were identified from five representative Rubus fruits by LC-MS in positive and negative ion modes. Isoquinoline alkaloid biosynthesis was the most enriched pathway in the biosynthesis of other secondary metabolites, followed by flavonoid and anthocyanin biosynthesis. Fewer pathways differed between red raspberry and yellow raspberry than among other Rubus fruits. Significant differences among groups occurred in cyanidin-3-sambubioside content in the anthocyanin pathway, which may be predominantly responsible for color differences. This study provides a theoretical basis for the comprehensive utilization and quality improvement of Rubus.

Hydrogenation of CO2 into fuels and useful chemicals could help to reduce reliance on fossil fuels. Although great progress has been made over the past decades to improve the activity of catalysts for CO2 hydrogenation, more efficient catalysts, especially those based on non-noble metals, are desired. Here we incorporate N atoms into Co nanosheets to boost the catalytic activity toward CO2 hydrogenation. For the hydrogenation of CO2, Co4N nanosheets exhibited a turnover frequency of 25.6 h−1 in a slurry reactor under 32 bar pressure at 150 °C, which was 64 times that of Co nanosheets. The activation energy for Co4N nanosheets was 43.3 kJ mol−1, less than half of that for Co nanosheets. Mechanistic studies revealed that Co4N nanosheets were reconstructed into Co4NH x , wherein the amido-hydrogen atoms directly interacted with the CO2 to form HCOO* intermediates. In addition, the adsorbed H2O* activated amido-hydrogen atoms via the interaction of hydrogen bonds. Hydrogenation of CO2 over heterogeneous catalysts can produce useful energy vectors such as methanol and formic acid. Here the authors show that the activity of unsupported cobalt catalysts can be markedly enhanced through incorporation of nitrogen atoms into the structure.

The blackberry (Rubus L.) is a berry fruit with high capacity for drought stress tolerance. In this study, the rooted clones of blackberry cv. ‘Kiowa’ growing in pots and produced by tissue culture were subjected to 14 days of drought stress for investigation of the physiological changes and leaf morphological characteristics. After the treatment, the leaf relative water content (RWC) on days 10 and 14 was significantly lower than that of the controls. Accordingly, the stress imposed an evident increase in the leaf electrolyte leakage. The superoxide dismutase activity under drought stress gradually decreased; meanwhile, the peroxidase activity displayed a higher level. At the elongation stage, both ascorbic acid (AsA) and glutathione (GSH) accumulation revealed a rising trend. Afterward, micromorphological observation revealed that with the increasing duration of stress, cellular morphology of the leaf epidermis endured a series of expansion changes. Moreover, the drought progression seemingly enhanced the stomatal length on day 7, and the stomatal width and opening on day 10, respectively. By day 14, the treated leaves demonstrated a striking increase in stomata density than before. Cell walls of the leaf epidermal and spongy tissue cells were thickened with prolonged drought. In particular, from day 10, the spongy tissue cells were clearly squeezed and filled with sclerenchyma. These results indicated that blackberry clones exhibited adaption to drought, which was reflected by the changes in leaf RWC, electrolyte leakage and antioxidative enzyme activities, the elevation of AsA and GSH concentrations and responses of leaf micromorphology.

The effects of increasing concentrations of cadmium (Cd) on the ultrastructure, Cd accumulation, nutrient elements contents, levels of chlorophyll pigments, hydrogen peroxide (H2O2), malondialdehyde (MDA), antioxidants, as well as the activities of antioxidant enzymes were investigated in the leaves of Hydrocharis dubia (Bl.) Backer. Cd exposure resulted in significant damage in chloroplasts and mitochondria, suggesting that Cd hastened the senescence of the tested plants. The accumulation of Cd was found to increase in a concentration dependent manner with a maximum of 1088 μg g−1 at 80 μM. The levels of Ca, P and Cu declined and the levels of Mg increased under all Cd concentrations, but K and Fe contents increased initially and decreased thereafter. Pigment content decreased with the rise of the Cd concentrations. H2O2 content enhanced gradually at all Cd concentrations. MDA content increased progressively up to 60 μM Cd, followed by a decline at higher concentration. The effect of Cd application on ascorbate (AsA) and reduced glutathione (GSH) contents was similar to that seen for H2O2 content. Peroxidase (POD) and catalase (CAT) activities first increased and then decreased, while superoxide dismutase (SOD) activity markedly decreased. Results suggest that Cd-induced oxidative damage in H. dubia is closely associated with the efficiency of its intrinsic antioxidant mechanisms, both the disorder of nutrient elements and the damage to the ultrastructure were indicative of general disarray in the cellular functions exerted by Cd.

The use of photoelectrochemical (PEC) sensors, with their outstanding advantages of remarkable sensitivity, inherent miniaturization, portability and easy integration, is becoming a promising analytical detection technique. The rational design of PEC materials and convenient establishment of PEC analysis platforms have given this technique tremendous popularity in both analytical and medical communities for biomolecule detection. However, most of the current efforts in the development of PEC analysis have been made with ultraviolet and visible light (UV-vis) as light source, which are detrimental to biomolecules because of their high energy. On the contrary, near-infrared (NIR) light is biocompatible and is available for in vivo detection. Herein, a prototype of NIR light-responsive PEC analysis platform is first proposed with defect-engineered TiO2 nanotube photonic crystals as photoelectrode and dopamine as target molecule. The coupled strategies of defect engineering for electronic structure modification and morphology design for photon manipulation open up a distinctive avenue to not only implement sensitive NIR PEC detection of dopamine but also have potential multi-target detection ability by integrating bio-recognition units, thus promoting NIR PEC analysis as a versatile analysis method.

For implementing sensitive and selective detection of biological molecules, the biosensors are been designed more and more complicated. The exploration of detection platform in a simple way without loss their sensitivity and selectivity is always a big challenge. Herein, a prototype of recognition biomolecule unit-free photoelectrochemical (PEC) sensing platform with self-cleaning activity is proposed with TiO2 nanotube photonic crystal (TiO2 NTPCs) materials as photoelectrode, and dopamine (DA) molecule as both sensitizer and target analyte. The unique adsorption between DA and TiO2 NTPCs induces the formation of charge transfer complex, which not only expends the optical absorption of TiO2 into visible light region, thus significantly boosts the PEC performance under illumination of visible light, but also implements the selective detection of DA on TiO2 photoelectrode. This simple but efficient PEC analysis platform presents a low detection limit of 0.15nm for detection of DA, which allows to realize the sensitive and selective determination of DA release from the mouse brain for its practical application after coupled with a microdialysis probe. The DA functionalized TiO2 NTPCs PEC sensing platform opens up a new PEC detection model, without using extra-biomolecule auxiliary, just with target molecule naturally adsorbed on the electrode for sensitive and selective detection, and paves a new avenue for biosensors design with minimalism idea.