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Abstract Background Ingestion and aspiration of orthodontic devices are rare occurrences, typically associated with components such as expansion keys, archwire segments, dislodged fixed appliances (including brackets, buccal tubes, and bands), as well as fractured metal or plastic appliances. This article describes the clinical diagnosis and treatment process of a case of accidental ingestion of a fractured piece of orthodontic aligner. Case presentation A 31-year-old female under orthodontic treatment by aligners accidentally ingested a fractured piece of the aligner. The special difficulty of this case is that the transparent orthodontic aligner has a low radiopacity. At the beginning, no foreign body was found in the commonly used soft tissue window, causing difficulty in its location until greyscale was adjusted to lung window. The 2-centimeter fractured piece was taken out under anesthesia and endoscopic surgery. Conclusion Materials with low radiopacity should be read with a lower grayscale range. Fractured orthodontic appliances with low retention force should not continue to be worn until consultation with attending doctor.

Abstract Background Multiple enhancers co-regulating the same gene is prevalent and plays a crucial role during development and disease. However, how multiple enhancers coordinate the same gene expression across various cell types remains largely unexplored at genome scale. Results We develop a computational approach that enables the quantitative assessment of enhancer specificity and selectivity across diverse cell types, leveraging enhancer-promoter (E-P) interactions data. We observe two well-known gene regulation patterns controlled by enhancer clusters, which regulate the same gene either in a limited number of cell types (Specific pattern, Spe) or in the majority of cell types (Conserved pattern, Con), both of which are enriched for super-enhancers (SEs). We identify a previously overlooked pattern (Variable pattern, Var) that multiple enhancers link to the same gene, but rarely coexist in the same cell type. These three patterns control the genes associating with distinct biological function and exhibit unique epigenetic features. Specifically, we discover a subset of Var patterns contains Shared enhancers with stable enhancer-promoter interactions in the majority of cell types, which might contribute to maintaining gene expression by recruiting abundant CTCF. Conclusions Together, our findings reveal three distinct E-P regulation patterns across different cell types, providing insights into deciphering the complexity of gene transcriptional regulation.

IntroductionThe study aims to predict tooth extraction decision based on four machine learning methods and analyze the feature contribution, so as to shed light on the important basis for experts of tooth extraction planning, providing reference for orthodontic treatment planning.MethodsThis study collected clinical information of 192 patients with malocclusion diagnosis and treatment plans. This study used four machine learning strategies, including decision tree, random forest, support vector machine (SVM) and multilayer perceptron (MLP) to predict orthodontic extraction decisions on clinical examination data acquired during initial consultant containing Angle classification, skeletal classification, maxillary and mandibular crowding, overjet, overbite, upper and lower incisor inclination, vertical growth pattern, lateral facial profile. Among them, 30% of the samples were randomly selected as testing sets. We used five-fold cross-validation to evaluate the generalization performance of the model and avoid over-fitting. The accuracy of the four models was calculated for the training set and cross-validation set. The confusion matrix was plotted for the testing set, and 6 indicators were calculated to evaluate the performance of the model. For the decision tree and random forest models, we observed the feature contribution.ResultsThe accuracy of the four models in the training set ranges from 82% to 90%, and in the cross-validation set, the decision tree and random forest had higher accuracy. In the confusion matrix analysis, decision tree tops the four models with highest accuracy, specificity, precision and F1-score and the other three models tended to classify too many samples as extraction cases. In the feature contribution analysis, crowding, lateral facial profile, and lower incisor inclination ranked at the top in the decision tree model.ConclusionAmong the machine learning models that only use clinical data for tooth extraction prediction, decision tree has the best overall performance. For tooth extraction decisions, specifically, crowding, lateral facial profile, and lower incisor inclination have the greatest contribution.

[Introduction] The "carbon peak and neutrality" strategy has put forward a new path for China's energy development, which restricts the use of traditional fossil energy, and promotes the Chinese government to increase its support for the development of the new energy industry. Photovoltaic, as a new energy which is the most accessible and has the widest coverage, has become the first choice to solve the current energy and environmental problems. However, if we want to increase its market scale and realize the vigorous development of photovoltaic industry, it is necessary to find out and solve the pain points and difficulties of the current stage. [Method] China's policy on the whole photovoltaic industry chain was combed and analyzed to explore the shortcomings of the photovoltaic industry incentive policy. Based on the data from 33 sample enterprises in the A-share market from 2000 to 2021, the DEA model was built and the integrated innovation benefits and scale benefits of China's PV industry under the guidance of policy were explored. And using the panel regression analysis method, the different impacts of different regional policies on the innovation capacity of the upstream, middle and downstream enterprises of the PV industry. were explored. [Result] The research shows that the policy subsidies have a more significant impact on the innovation benefits of upstream photovoltaic enterprises, which is positively correlated with the development of enterprises in the eastern region. While in the western region, the opposite is the case, and there are certain regional differences. [Conclusion] It is necessary to improve the preferential policy strength in the photovoltaic technology innovation level, and carry out a reasonable industry chain planning and layout in combination with the regional advantages.

Abstract Boron is an essential trace element with roles in growth, development, and physiological functions; however, its mechanism of action is still unclear. In this study, the regulatory roles of the PI3K/Akt signaling pathway on boron-induced changes in barrier function, proliferation, and apoptosis in rat intestinal epithelial cells were evaluated. Occludin levels, the proportion of cells in the G2/M phase, cell proliferation rate, and mRNA and protein expression levels of PCNA were higher, while the proportions of cells in the G0/G1 and S phases, apoptosis rate, and caspase-3 mRNA and protein expression levels were lower in cells treated with 0.8 mmol/L boron than in control IEC-6 cells (P

Abstract Kesterite is an earth‐abundant energy material with high predicted power conversion efficiency, making it a sustainable and promising option for photovoltaics. However, a large open circuit voltage Voc deficit due to non‐radiative recombination at intrinsic defects remains a major hurdle, limiting device performance. Incorporating Ge into the kesterite structure emerges as an effective approach for enhancing performance by manipulating defects and morphology. Herein, how different amounts of Ge affect the kesterite growth pathways through the combination of advanced microscopy characterization techniques are systematically investigated. The results demonstrate the significance of incorporating Ge during the selenization process of the CZTSSe thin film. At high temperature, the Ge incorporation effectively delays the selenization process due to the formation of a ZnSe layer on top of the metal alloys through decomposition of the Cu‐Zn alloy and formation of Cu‐Sn alloy, subsequently forming of Cu‐Sn‐Se phase. Such an effect is compounded by more Ge incorporation that further postpones kesterite formation. Furthermore, introducing Ge mitigates detrimental “horizontal” grain boundaries by increasing the grain size on upper layer. The Ge incorporation strategy discussed in this study holds great promise for improving device performance and grain quality in CZTSSe and other polycrystalline chalcogenide solar cells.

It has become an emerging idea for fitness apps to be gamified to intrinsically and extrinsically motivate user’s usage intention or behavior. For the long-term success of gamified fitness apps, understanding what and how various motivations affect continued use is critical. A combination of qualitative and quantitative methodologies was used to explore two research questions concerning gamified fitness applications. Specifically, the research questions focused on understanding the impacts of intrinsic and extrinsic motivations on continued usage. Additionally, the study aimed to investigate whether extrinsic motivations enhance or diminish the influence of intrinsic motivations. Results from qualitative study identified three intrinsic motivations (self-development, self-control and hedonic motivation) and two extrinsic motivations (social recognition and financial reward) in gamified fitness apps. Results from quantitative study indicated that intrinsic motivations (formed by self-development, self-control and hedonic motivation), financial reward and social recognition could significantly improve intention for continued use; and further, both financial reward and social recognition could crowd-in intrinsic motivations. This research offers insights into the phenomenon of motivation crowding effects on the intention to continue using gamified fitness apps.

Abstract Flexible photovoltaics have been and will be increasingly in demand in modern and future society in various applications. Searching for ideal flexible photovoltaic technologies that can perfectly meet these expanding demands has long been an active branch of photovoltaic research. Flexible kesterite Cu2ZnSn(S,Se)4 (CZTSSe) has emerged in recent years owning to its great potential to be an abundant, low-cost, stable, and high-efficiency ‘green’ photovoltaic material that can be widely deployed with the lowest detrimental environmental impact. Here, we review the recent progress with flexible kesterite solar cells in thin-film and monograin technologies, discuss the key challenges and strategies associated with the flexible substrates, and finally provide the future perspectives on further pushing the efficiency toward commercial-competitive levels.

METTL3 catalyzes mRNA m6A deposition. The authors identify an acetylation-mediated regulation of METTL3 subcellular localization and compartment-specific functions, a process that is fine-tuned by anti-inflammatory and pro-inflammatory signals, which ultimately determine breast cancer metastasis.

Summary: T helper type 2 (Th2) cytokine-activated M2 macrophages contribute to inflammation resolution and wound healing. This study shows that IL-4-primed macrophages exhibit a stronger response to lipopolysaccharide stimulation while maintaining M2 signature gene expression. Metabolic divergence between canonical M2 and non-canonical proinflammatory-prone M2 (M2INF) macrophages occurs after the IL-4Rα/Stat6 axis. Glycolysis supports Hif-1α stabilization and proinflammatory phenotype of M2INF macrophages. Inhibiting glycolysis blunts Hif-1α accumulation and M2INF phenotype. Wdr5-dependent H3K4me3 mediates the long-lasting effect of IL-4, with Wdr5 knockdown inhibiting M2INF macrophages. Our results also show that the induction of M2INF macrophages by IL-4 intraperitoneal injection and transferring of M2INF macrophages confer a survival advantage against bacterial infection in vivo. In conclusion, our findings highlight the previously neglected non-canonical role of M2INF macrophages and broaden our understanding of IL-4-mediated physiological changes. These results have immediate implications for how Th2-skewed infections could redirect disease progression in response to pathogen infection.

The coronavirus disease 2019 (COVID-19) pandemic is still ongoing, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continuing to evolve and accumulate mutations. While various bioinformatics tools have been developed for SARS-CoV-2, a well-curated mutation-tracking database integrated with in silico evaluation for molecular diagnostic assays is currently unavailable. To address this, we introduce CovidShiny, a web tool that integrates mutation profiling, in silico evaluation, and data download capabilities for genomic sequence-based SARS-CoV-2 assays and data download. It offers a feasible framework for surveilling the mutation of SARS-CoV-2 and evaluating the coverage of the molecular diagnostic assay for SARS-CoV-2. With CovidShiny, we examined the dynamic mutation pattern of SARS-CoV-2 and evaluated the coverage of commonly used assays on a large scale. Based on our in silico analysis, we stress the importance of using multiple target molecular diagnostic assays for SARS-CoV-2 to avoid potential false-negative results caused by viral mutations. Overall, CovidShiny is a valuable tool for SARS-CoV-2 mutation surveillance and in silico assay design and evaluation.

Abstract Background Super-enhancers are clusters of enhancer elements that play critical roles in the maintenance of cell identity. Current investigations on super-enhancers are centered on the established ones in static cell types. How super-enhancers are established during cell differentiation remains obscure. Results Here, by developing an unbiased approach to systematically analyze the evolving landscape of super-enhancers during cell differentiation in multiple lineages, we discover a general trend where super-enhancers emerge through three distinct temporal patterns: conserved, temporally hierarchical, and de novo. The three types of super-enhancers differ further in association patterns in target gene expression, functional enrichment, and 3D chromatin organization, suggesting they may represent distinct structural and functional subtypes. Furthermore, we dissect the enhancer repertoire within temporally hierarchical super-enhancers, and find enhancers that emerge at early and late stages are enriched with distinct transcription factors, suggesting that the temporal order of establishment of elements within super-enhancers may be directed by underlying DNA sequence. CRISPR-mediated deletion of individual enhancers in differentiated cells shows that both the early- and late-emerged enhancers are indispensable for target gene expression, while in undifferentiated cells early enhancers are involved in the regulation of target genes. Conclusions In summary, our analysis highlights the heterogeneity of the super-enhancer population and provides new insights to enhancer functions within super-enhancers.

Uniaxial trackers are widely employed as the frame for solar photovoltaic (PV) panel installation. However, when used in sloping terrain scenarios such as mountain and hill regions, it is essential to apply a solar-tracking strategy with the sloping factors considered, to eliminate the shading effects between arrays and reduce the electricity production loss due to terrain changes. Based on a uniaxial tracker on the sloping terrain of a PV farm located in Ningxia, this study established a uniaxial solar-tracking strategy for sloping terrain by integrating a spatial projection model with a dynamic shadow assessment method. In the proposed strategy, the optimal tilt angle of the PV array and related desirable adjustment are identified taking into consideration major parameters such as the shadow area ratio S and the average solar irradiance intensity G. A tool underpinned by Matlab Simulink has also been developed to realize the proposed solar-tracking strategy. With the input of a simulated ramp signal β and the dynamically changed time parameters, the tracking angle of PV arrays over the simulated duration is accurately predicted, followed by a series of experimental validations conducted on the winter solstice and a typical sunny day (15 September). Moreover, the study also explored the terrain impacts on solar tracking by comparing the sloping terrain and flat terrain applications. The analytic and experimental results indicate that (a) the maximum value of the G(β) function could serve as the input to identify the optimal tracking angle; (b) the application of the flat terrain tracking (FTT) strategy in sloping terrain would result in a reduction of average solar irradiance intensity harvested by the PV arrays with varying degrees; (c) in the context of an east–west −7° sloping terrain, compared with the FTT strategy, the sloping terrain tracking (STT) strategy enabled anti-shading tracking, and then increased the daily PV electricity yield by 0.094 kWh/kWp, which is around 1.48% of the daily energy production; (d) given a measurement with annual scale, the STT strategy could cause a 1.26% increase in the energy harvesting with a flat uniaxial PV array on a −7° slope terrain, achieving an annual increase of 25.16 kWh/kWp. The experimental comparative analysis validated the precision of the proposed solar-tracking model, which has far-reaching significance for achieving automatic solar-tracking of PV modules, as well as improving the capacity and efficiency of PV systems.

Summary: Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer, with a 10% five-year survival rate. However, little is known about its origin and the mechanisms governing its emergence. Our study characterized ADPC and NEPC in prostate tumors from 7 patients using scRNA-seq. First, we identified two NEPC gene expression signatures representing different phases of trans-differentiation. New marker genes we identified may be used for clinical diagnosis. Second, integrative analyses combining expression and subclonal architecture revealed different paths by which NEPC diverges from the original ADPC, either directly from treatment-naïve tumor cells or from specific intermediate states of treatment-resistance. Third, we inferred a hierarchical transcription factor (TF) network underlying the progression, which involves constitutive regulation by ASCL1, FOXA2, and selective regulation by NKX2-2, POU3F2, and SOX2. Together, these results defined the complex expression profiles and advanced our understanding of the genetic and transcriptomic mechanisms leading to NEPC differentiation.

Abstract When colorectal subepithelial lesions occur in ovarian carcinoma patients, EUS‐FNA may help to diagnose colorectal metastasis, thereby guiding clinicians to select appropriate treatment and improve the overall outcome.

M-banking usage has attracted great attention from literature in recent years. The goal of this study is to provide new insights into m-banking usage by investigating the motivations for m-banking usage and how these motivations can drive different levels of m-banking usage respectively. A quantitative dominant mixed-methods design is applied in this study. First, a qualitative study through interviews is conducted to identify the motivations for m-banking usage. Five m-banking motivations are identified from the qualitative study, namely convenience, cost saving, information gaining, word-of-mouth and decision-making quality. Second, a quantitative study through survey is conducted to test the effects of motivations on different levels of m-banking usage. In general, results indicate that different levels of m-banking usage could be driven by different m-banking motivations.

The threats of climatic change on life, health, and the environment have been regarded by the joint consensus of scholars in the recent decades. With the advancement of global green development, green finance has paved the way for the government to respond to the challenges of climate change by providing mature financial services, appropriate financing, investment, and project funds related to environmental protection. In this context, green finance was proposed, and the relationship between green finance, renewable energy, and carbon emissions in the BRICS countries from 2000 to 2018 was further studied based on the quantile regression model. The presence of cross-sectional dependence in panel results is tested through CD and LM methods. The findings show the negative effect of green finance and non-fossil energy consumption on CO2 emissions. Furthermore, economic growth, trade openness, energy consumption, and foreign direct investment increase the CO2 emissions. Finally, the research results confirm that green finance is the best financial strategy to reduce carbon dioxide emissions.

Energy and environmental concepts have been extensively studied in the past. However, these studies often lacked integrated analysis of energy, monetary, public, and ecological aspects to assess energy and environmental issues. This article provides analyzation of the G7 nations’ qualitative, social, cultural, and health achievement in the energy poverty indexes. These include the energy economics and climate change of energy poverty, by using DEA like a composite indicator. The G7 countries’ combined energy consumption is equal to 34% of the world’s total, whereas the GDP is 50% of the global total. As a result, this article develops a comprehensive series of energy, financial, societal, and environmental indicators that are up to date. Such indicators are utilized to assess energy financial, societal, and EPI using a mathematical composite indicator. Canada has the greatest EPII score, indicating that it can deal better than the other G7 countries with energy independence, productivity expansion, and social impact, and France’s and Italy’s the second tier. While Japan has a 0.50 EPI grade and the United States will have the lowest, the G7 countries are growing faster. Finally, we propose a policy framework for enhancing the research area. The energy, societal, and EPI were created by combining these elements. In terms of energy independence, economic growth, and sustainability practices, Canada beats the other G7 countries according to the data. France and Italy are in the 2nd and 3rd places, respectively. Despite having a higher level of economic development than the G7 countries, Japan has a 0.50 Environmental Performance Index rating, whereas the United States has a minimum average Environmental Performance Index rating. Finally, in order to improve the study’s subject, we propose a policy framework.

Abstract Genomic amplification of OTUD7B is frequently found across human cancers. But its role in tumorigenesis is poorly understood. Lysine‐specific demethylase 1 (LSD1) is known to execute epigenetic regulation by forming corepressor complex with CoREST/histone deacetylases (HDACs). However, the molecular mechanisms by which cells maintain LSD1/CoREST complex integrity are unknown. Here, it is reported that LSD1 protein undergoes K63‐linked polyubiquitination. OTUD7B is responsible for LSD1 deubiquitination at K226/277 residues, resulting in dynamic control of LSD1 binding partner specificity and cellular homeostasis. OTUD7B deficiency increases K63‐linked ubiquitination of LSD1, which disrupts LSD1/CoREST complex formation and targets LSD1 for p62‐mediated proteolysis. Consequently, OTUD7B deficiency impairs genome‐wide LSD1 occupancy and enhances the methylation of H3K4/H3K9, therefore profoundly impacting global gene expression and abrogating breast cancer metastasis. Moreover, physiological fluctuation of OTUD7B modulates cell cycle‐dependent LSD1 oscillation, ensuring the G1/S transition. Both OTUD7B and LSD1 proteins are overpresented in high‐grade or metastatic human breast cancer, while dysregulation of either protein is associated with poor survival and metastasis. Thus, OTUD7B plays a unique partner‐switching role in maintaining the integrity of LSD1/CoREST corepressor complex, LSD1 turnover, and breast cancer metastasis.

Abstract Individuals with Trisomy 21 (T21) exhibit numerous hematological abnormalities, including reductions in numbers of circulating B and T lymphocytes. To elucidate molecular mechanisms underlying these phenotypes, we differentiated human isogenic disomic and trisomic pluripotent cells, and observed that trisomic cells showed defects in B cell, but not T cell differentiation. Global gene expression of differentiated, trisomic B cells revealed reduced expression of genes encoding endothelin signaling components, namely the Endothelin Receptor B (EDNRB), and its ligand Endothelin1 (EDN1). Depletion of EDNRB mRNA in cord blood-derived CD34+ cells led to defective B cell differentiation, supporting a hypothesis that low EDNRB expression in T21 contributes to intrinsic lymphoid defects. Further evidence for the role of the EDNRB pathway in B cell differentiation was obtained through CRISPR/Cas9 gene targeting in disomic and trisomic iPS cells. Knockout of EDNRB in both cell backgrounds reduced the capacity for B cell differentiation. Collectively, this work identifies downregulation of EDNRB as a causative factor for impaired B lymphocyte generation in trisomic cells, which may contribute to defects in immune function associated with T21. Furthermore, a novel role for endothelin signaling in regulation of B cell development has been identified.

Super-enhancers (SEs) are important regulatory elements for gene expression, but their intrinsic properties remain poorly understood. Here the authors analyse Hi-C and ChIP-seq data and find that a significant fraction of SEs are hierarchically organized, containing both hub and non-hub enhancers.

Exploring the cohort behavior of local governments in green governance from the perspective of knowledge management can help promote the implementation of new development concepts. This article firstly explains the differentiation logic of local governments’ green governance cohort behavior based on the SECI expansion model. Secondly, by constructing a dynamic evolutionary game model, the conditions for the formation of positive and negative cohorts are analyzed. Finally, corresponding countermeasures are proposed. The results show that under the effect of knowledge management, the explicit and tacit knowledge, such as green governance ability and willingness of local government transform into each other, finally differentiates into four kinds of peer behavior states. Willingness stimulation, learning effect perception, complementary knowledge stock, knowledge synergy income, cooperation value-added income, punishment and reputation loss increase, which promotes local government green governance into a positive-peer state. Knowledge learning effect only exists in the early and middle stages of green governance, while the knowledge spillover effect has a more significant impact in the later stage of green governance; a higher gap between explicit knowledge and tacit knowledge, and a lower level of tacit knowledge and explicit knowledge, are conducive to the formation of positive-peer status.

In order to explore the impact of a manufacturer’s or retailer’s undertaking corporate social responsibility (CSR) and different power structures on their joint green marketing decisions and profits in the green supply chain, this paper establishes green supply chain optimization models under six different decision-making scenarios according to two different CSR bearers and three different power structures. Based on the main assumptions of a linear product demand function and CSR measured by consumer surplus, this paper solves the equilibrium solutions of the manufacturer and the retailer through game theory. The results show that: First, the difference in the degree of CSR undertaken by manufacturers and retailers leads to a difference in the ranking of optimal strategies of both parties under the three power structures. Second, under the same power structure, compared with undertaking CSR by oneself, when the other party undertakes CSR, the level of the product’s green degree, the level of green promotion, the party’s own profit, and the profit of the other party are all higher. Third, regardless of the power structure, manufacturers and retailers undertaking CSR is conducive to improving the level of product greenness, increasing green promotion, lowering the retail price, increasing consumers’ willingness to buy green products, and ultimately helping to increase the profits of manufacturers and retailers.

The impact of chromatin structure on gene expression makes it integral to our understanding of developmental and disease processes. Here, the authors introduce a hierarchical hidden Markov model to systematically annotate chromatin states at multiple length scales, and demonstrate its utility for the elucidation of the role of chromatin structure in gene expression.

As a renewable energy source, wind energy harvesting provides a desirable solution to address the environmental concerns associated with energy production to satisfy the increasingly global demand. Over the years, the penetration of wind turbines has experienced a rapid growth, however, the impacts of turbine noise correspondingly become a major concern in wind energy harvesting. Recent studies indicate that the noise emitted by turbine operating could increase the risk of nuisance, which might further affect the well-being of local residents. However, the main factors affecting turbine noise assessment and to what extent they contribute to the assessment are still unclear. In this study, a survey-based approach is developed to identify these major factors and to explore the interactions between the factors and assessment results. Principal component analysis method was adapted to extract key factors; followed by reliability assessment, validity analysis, descriptive assessment, and correlation analysis were conducted to test the robust of the proposed methodology, as well as to examine the interactions between variables. Regression analysis was finally employed to measure the impacts on results contributed by the key factors. Findings of this study indicate that key factors including physical conditions, control capacity, and subjective opinions are of significant impact on residents’ response to wind turbine noise, while the factor of subjective opinions contributes predominately to the assessment results. Further validations also indicate that the proposed approach is robust and can be extensively applied in survey-based assessments for other fields.

B cell CLL/lymphoma 11A (BCL11A) is a transcription factor and regulator of hemoglobin switching that has emerged as a promising therapeutic target for sickle cell disease and thalassemia. In the hematopoietic system, BCL11A is required for B lymphopoiesis, yet its role in other hematopoietic cells, especially hematopoietic stem cells (HSCs) remains elusive. The extensive expression of BCL11A in hematopoiesis implicates context-dependent roles, highlighting the importance of fully characterizing its function as part of ongoing efforts for stem cell therapy and regenerative medicine. Here, we demonstrate that BCL11A is indispensable for normal HSC function. Bcl11a deficiency results in HSC defects, typically observed in the aging hematopoietic system. We find that downregulation of cyclin-dependent kinase 6 (Cdk6), and the ensuing cell-cycle delay, correlate with HSC dysfunction. Our studies define a mechanism for BCL11A in regulation of HSC function and have important implications for the design of therapeutic approaches to targeting BCL11A.

Development of polymer-based composites with simultaneously high thermal conductivity and breakdown strength has attracted considerable attention owing to their important applications in both electronic and electric industries. In this work, boron nitride (BN) nanofibers (BNNF) are successfully prepared as fillers, which are used for epoxy composites. In addition, the BNNF in epoxy composites are aligned by using a film casting method. The composites show enhanced thermal conductivity and dielectric breakdown strength. For instance, after doping with BNNF of 2 wt%, the thermal conductivity of composites increased by 36.4% in comparison with that of the epoxy matrix. Meanwhile, the breakdown strength of the composite with 1 wt% BNNF is 122.9 kV/mm, which increased by 6.8% more than that of neat epoxy (115.1 kV/mm). Moreover, the composites have maintained a low dielectric constant and alternating current conductivity among the range of full frequency, and show a higher thermal decomposition temperature and glass-transition temperature. The composites with aligning BNNF have wide application prospects in electronic packaging material and printed circuit boards.

Vapour-phase and solid-phase epitaxy are used for thickening of a solid-phase crystallised silicon seed layer on glass. Cross-sectional transmission microscope images confirm that a transfer of crystallographic information has taken place from the seed layer into the epilayers. X-ray diffraction, scanning electron microscopy, and transmission electron microscopy reveal that the density of planar defects (mainly on {111} plains) in the vapour-phase epitaxial sample is much higher than in the solid-phase epitaxial sample. These planar defects can act as recombination centres for free-charge carriers. Consequently, PC1D modelled minority carrier diffusion length in the vapour-phase grown epilayer is 50% shorter than that in the solid-phase grown epilayer. As a result, a solar cell grown by solid-phase epitaxy achieves open circuit voltage of 468 mV, short circuit current of 9.17 mA/cm2, and photovoltaic conversion efficiency at 2.75% which are all higher than those of the solar cell grown by vapour-phase epitaxy on the same seed layer, 400 mV, 7.28 mA/cm2, 1.69%, respectively. It proves that solid-phase epitaxy is more suitable for the solar cell growth on the solid-phase crystallised silicon seed layer than vapour-phase epitaxy.

Identifying drug-drug interactions (DDIs) is a major challenge in drug development. Previous attempts have established formal approaches for pharmacokinetic (PK) DDIs, but there is not a feasible solution for pharmacodynamic (PD) DDIs because the endpoint is often a serious adverse event rather than a measurable change in drug concentration. Here, we developed a metric "S-score" that measures the strength of network connection between drug targets to predict PD DDIs. Utilizing known PD DDIs as golden standard positives (GSPs), we observed a significant correlation between S-score and the likelihood a PD DDI occurs. Our prediction was robust and surpassed existing methods as validated by two independent GSPs. Analysis of clinical side effect data suggested that the drugs having predicted DDIs have similar side effects. We further incorporated this clinical side effects evidence with S-score to increase the prediction specificity and sensitivity through a Bayesian probabilistic model. We have predicted 9,626 potential PD DDIs at the accuracy of 82% and the recall of 62%. Importantly, our algorithm provided opportunities for better understanding the potential molecular mechanisms or physiological effects underlying DDIs, as illustrated by the case studies.

Periodontitis is a common chronic inflammatory disease, which leads to alveolar bone resorption. Healthy and functional alveolar bone, which can support the teeth and enable their movement, is very important for orthodontic treatment. Myricetin inhibited osteoclastogenesis by suppressing the expression of some genes, signaling pathways, and cytokines. This study aimed to investigate the effects of myricetin on alveolar bone loss in an ovariectomized (OVX) mouse model of periodontitis as well as in vitro osteoclast formation and bone resorption. Twenty-four healthy eight-week-old C57BL/J6 female mice were assigned randomly to four groups: phosphate-buffered saline (PBS) control (sham) OVX + ligature + PBS (vehicle), and OVX + ligature + low or high (2 or 5 mg∙kg−1∙day−1, respectively) doses of myricetin. Myricetin or PBS was injected intraperitoneally (i.p.) every other day for 30 days. The maxillae were collected and subjected to further examination, including micro-computed tomography (micro-CT), hematoxylin and eosin (H&E) staining, and tartrate-resistant acid phosphatase (TRAP) staining; a resorption pit assay was also performed in vitro to evaluate the effects of myricetin on receptor activator of nuclear factor κ-B ligand (RANKL)-induced osteoclastogenesis. Myricetin, at both high and low doses, prevented alveolar bone resorption and increased alveolar crest height in the mouse model and inhibited osteoclast formation and bone resorption in vitro. However, myricetin was more effective at high dose than at low dose. Our study demonstrated that myricetin had a positive effect on alveolar bone resorption in an OVX mouse model of periodontitis and, therefore, may be a potential agent for the treatment of periodontitis and osteoporosis.

Extreme altitude can induce a range of cellular and systemic responses. Although it is known that hypoxia underlies the major changes and that the physiological responses include hemodynamic changes and erythropoiesis, the molecular mechanisms and signaling pathways mediating such changes are largely unknown. To obtain a more complete picture of the transcriptional regulatory landscape and networks involved in extreme altitude response, we followed four climbers on an expedition up Mount Xixiabangma (8,012 m), and collected blood samples at four stages during the climb for mRNA and miRNA expression assays. By analyzing dynamic changes of gene networks in response to extreme altitudes, we uncovered a highly modular network with 7 modules of various functions that changed in response to extreme altitudes. The erythrocyte differentiation module is the most prominently up-regulated, reflecting increased erythrocyte differentiation from hematopoietic stem cells, probably at the expense of differentiation into other cell lineages. These changes are accompanied by coordinated down-regulation of general translation. Network topology and flow analyses also uncovered regulators known to modulate hypoxia responses and erythrocyte development, as well as unknown regulators, such as the OCT4 gene, an important regulator in stem cells and assumed to only function in stem cells. We predicted computationally and validated experimentally that increased OCT4 expression at extreme altitude can directly elevate the expression of hemoglobin genes. Our approach established a new framework for analyzing the transcriptional regulatory network from a very limited number of samples.

Background: New hemoglobin (Hb) variants are constantly being updated as assays are developed and the testing population expands. Here, we report a novel Hb variant, named Hb Guigang. Methods: Hemoglobin (Hb) analysis was analyzed by capillary electrophoresis (CE) and high-performance liquid chromatography (HPLC). Glycated hemoglobin was performed by CE and HPLC. Routine genetic analysis was done with Gap-PCR and PCR-reverse dot-blot hybridization. The hemoglobin variant was identified by Sanger sequencing. Results: CE of three cases showed the presence of Hb variants in Zone 5 and Zone 12, respectively. HPLC indicated an elevated P3 peak, suggesting the possible presence of the Hb variant. Hb A1c was measured by CE and HPLC, and the results were 6.7% and 4.76%, respectively. Sanger sequencing confirmed an AAG˃AAT mutation at codon 90 of the HBA1 gene. This mutation was reported for the first time, and we named it Hb Guigang based on the proband’s place of residence. Conclusions: Hb Guigang with normal hematological parameters was separated and quantified by CE, whereas HPLC suggested that Hb Guigang co-eluted with the P3 peaks and could not be quantified. [ABSTRACT FROM AUTHOR]

Background: Klinefelter syndrome is a common sex chromosome abnormality in males, characterized by an extra X chromosome compared to normal males. Glucose-6-phosphate dehydrogenase deficiency (G6PD) is an X-linked incomplete dominant defect disorder. In this study, we reported the unexpected detection of Klinefelter syndrome in a patient with G6PD. Methods: G6PD enzyme activity was measured by immunoenzyme assay, and genetic analysis was performed using a fluorescent PCR melting curve method (PCR-melting curve). Sex chromosome number abnormalities were detected by multiplex ligation-dependent probe amplification (MLPA). The patient also underwent peripheral blood chromosome karyotype analysis. Results: The patient's G6PD and 6PGD enzyme activities were 21.34 U/L and 22.85 U/L, respectively, and their ratio was below the reference range (0.93). The PCR-melting curve displayed a c.1388 heterozygous mutation in this boy, and the Sanger sequencing provided the same results. MLPA results suggested the presence of approximately two copies of the X-chromosome in the boy. Finally, chromosome karyotype analysis confirmed that the boy had Klinefelter syndrome with a karyotype of 47, XXY. Conclusions: Klinefelter syndrome was accidentally detected during G6PD genetic analysis in a male. X-chromosomes can interfere with the results of G6PD genetic analysis and should be noted. [ABSTRACT FROM AUTHOR]