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Establishing a new environmental governance model driven by the dual wheels of pollution control (PC) system and carbon reduction (CR) system is an efficient approach for addressing multiple ecological challenges. However, given the broad connotations of pollution control and carbon reduction (PCCR), studies that comprehensively quantify their synergistic effects are scarce. This paper develops a coupling coordination indicator system for PCCR grounded in the concepts of “source emission reduction” and “end-of-pipe treatment”. Subsequently, a modified coupling coordination degree (CCD) model is used to calculate the CCD of PCCR in China from 2011 to 2021. The distribution patterns, transition probabilities, and driving mechanisms of the CCD of PCCR are explored using kernel density estimation, Markov chains, and geographically and temporally weighted regression (GTWR). The findings indicate that a preliminary model for coordinated development in PCCR has been established. However, regional disparities in PCCR, a persistent and dynamically evolving feature, manifested a spatial pattern of “higher in the east, lower in the west”. The kernel density distribution curves of the CCD of PCCR in the four major regions showed varying distances of rightward shifts. The absolute differences in the CCD of PCCR in the eastern, western, and northeastern regions narrowed, whereas those in the central region widened. Additionally, a pronounced trend of multipolar differentiation in the CCD of PCCR was evident in the eastern region. Nationally, and particularly in the central region, a pattern of bipolar differentiation gradually formed, while in the western and northeastern regions, the distribution curves transitioned from bimodal or multimodal to unimodal. The development trends of the CCD of PCCR across Chinese provinces were relatively stable, exhibiting a “rich-get-richer” club convergence phenomenon. Overall, the drivers displayed zonal or patch-like spatial differentiation characteristics. Green innovation, digital economy, energy intensity, and human capital drivers showed a clear east–west zonal distribution. This paper provides methodological support for quantitatively evaluating the synergistic effects of PCCR, and its findings offer a reference for regions to develop differentiated PCCR synergy governance strategies.

Abstract The study examines the digital finance (DF) and regional sustainable development (RSD) across 90 cities within six major city clusters in China over the period from 2011 to 2020. By constructing an evaluation index system for DF and RSD, we employed the entropy value method to assess their levels, and the coupling coordination degree (CCD) model to evaluate their interplay. Our analysis extended to temporal and spatial disparities, distribution dynamics, and the convergence of CCD through kernel density estimation, Markov chain analysis, $$\sigma$$ σ -convergence, and $$\beta$$ β -convergence techniques. The results indicate a consistent upward trend in CCD, yet it remains at a low level with pronounced regional disparities and temporal characteristics. The kernel density distribution’s central tendency has shifted rightward progressively, albeit with a decelerating pace annually. The Markov transition probability matrix suggests a stable CCD across various levels, hinting at “club convergence”. Furthermore, both $$\sigma$$ σ -convergence and $$\beta$$ β -convergence analyses reveal significant convergence trends in CCD, enhanced by economic growth factors. Using the Quadratic Assignment Procedure (QAP) method, we found that regional economic growth disparities significantly influence the CCD’s regional variances.

The Pilot Free Trade Zone (PFTZ) policy represents a significant step in China’s institutional innovation and broader opening-up, crucial for fostering green and high-quality economic growth. The existing literature has conducted in-depth studies on the economic effects, energy conservation, emission reduction and green innovation of PFTZs, but the effect on green technology innovation efficiency (GTIE) remains underexplored. Institutional innovation in the PFTZs will profoundly affect regional green development, and green innovation, and will certainly affect the regional GTIE. Based on this, this paper uses the city-level data of prefecture-level cities in China from 2005 to 2020 to empirically test the impact of PFTZ establishment on GTIE. First, the Super-SBM model was applied to evaluate the GTIE across 281 Chinese cities. Then, taking the establishment of PFTZs as a quasi-natural experiment, the multi-stage differentially differential model is constructed to empirically assess PFTZ policy’s impact on GTIE. The findings indicate that PFTZs can significantly enhance the GTIE. This improvement is facilitated through four pathways: the digital economy, the high-tech industries agglomeration, innovation agglomeration, and talent agglomeration. The results offer strategies for balancing external openness with environmental protection in developing countries and furnish empirical support for creating high-quality development frameworks.

Abstract In this paper, a novel simulation-based evolutionary method is presented for designing parameter-free MEMS structures with maximum degrees of freedom. This novel design method enabled semiautomatic structure evolution by weighing the attributes of each segment of the structure and yielded an optimal design after multiple iterations. The proposed method was utilized to optimize the pressure-sensitive diaphragm of a piezoresistive pressure sensor (PPS). Finite element method (FEM) simulations revealed that, in comparison to conventional diaphragms without islands and with square islands, the optimized diaphragm increased the stress by 10% and 16% and reduced the nonlinearity by 57% and 77%, respectively. These improvements demonstrate the value of this method. Characterization of the fabricated PPS revealed a high sensitivity of 8.8 mV V−1 MPa−1 and a low nonlinearity of 0.058% FS at 20 °C, indicating excellent sensor performance.

PDR positioning is currently the core issue of autonomous positioning, there is a problem of high noise and interference in dynamic measurement using PDR (Pedestrian Dead Reckoning) MEMS (Micro-Electro-Mechanical System) device, which is often a low precision multi-source integration sensor. Two new models of improved spectral subtraction (ISS) and PDRS (PDR-Spectral subtraction) spectral subtraction are constructed in this paper according to the spectrum features of the periodic noise generated from personnel stepping in PDR positioning. It is proposed a two-stage noise reduction method of spectrum subtraction-Wiener filtering for obtaining the static magnetic sequence of personnel path and reducing the real-time noise in PDR positioning, which main mechanism is to use the step power spectrum as the background noise for primary noise reduction, secondary Wiener filtering noise reduction according to the correlation between the denoised signal and the reference signal. A self-made MEMS-based positioning device HBEQ-1 and a high-precision magnetometer FVM-400 were used to collect dynamic and static magnetic value from the test area, and a spectral subtraction-Wiener two-stage noise reduction test was carried out. The experimental results show that the improved ISS spectral subtraction and PDRS spectral subtraction are effective in denoising the dynamic magnetic measurement, but there is still a certain deviation between the peak value and the amplitude of the denoised signal. After secondary noise reduction by Wiener filtering, the signal morphology similarity of magnetic curve and the reference reached 0.7975, and the matched path values of the dynamic magnetic value reached around 12000–13000. It showed that the denoising effect is good and the waveform of denoised signal and the reference signal is similar, but there is spatial stretching of the overall magnetic sequence. It is shown that the spectral subtraction-Wiener noise reduction method cannot eliminate the inertial delay bias generated by personnel walking, the processing does not distort the magnetic signal, maintains spatial characteristics of the static magnetic sequence of personnel path, which is an excellent model for noise reduction of dynamic magnetic measurements in PDR positioning.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, β-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute β-convergence, and conditional β-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

Collaborative efforts to reduce pollution and carbon emissions are a notable feature of the current era. Achieving the “pollution reduction” and “carbon reduction” dual-driven new development model is the inevitable requirement and significant practical measure for building a new development pattern and realizing a comprehensive green transformation of economic and social development. The synergistic effects between pollution reduction and carbon reduction (PRCR) have been demonstrated. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of PRCR have not received enough attention. Therefore, the evaluation index system was constructed based on the scientific connotation of PRCR, and the CCD of PRCR in cities along the Yellow River Basin (YRB) from 2009 to 2018 was measured quantitatively by constructing the coupling coordination model in this paper. In addition, we comprehensively investigated its spatial pattern, distribution characteristics, and evolution trend using ESDA, Kernel density estimation, and Markov chain. The primary findings can be summarized as: (1) PRCR levels and their CCD fluctuated and increased in the YRB, with “east-high and west-low” spatial differentiation characteristics, and the coupling phenomenon of “pollution reduction is hindered and carbon reduction is lagging”. (2) There is a phenomenon of “spatial club” clustering in the coordination degree of PRCR in the YRB, with most cities in the downstream areas belonging to the type of high-high clustering, while the middle and upstream areas had the opposite type. (3) The CCD of PRCR in the whole and upper reaches of the YRB have transformed from low-level divergence to high-level convergence. (4) Spatial geographic factors have a significant spillover effect on the evolution of the CCD of PRCR, and there is a phenomenon of the “Matthew effect”. This paper provides a comprehensive framework for analyzing the synergistic effects between PRCR, and the research findings can also provide insights for other regions.

IntroductionThe retina is the “window” of the central nervous system. Previous studies discovered that retinal thickness degenerates through the pathological process of the Alzheimer’s disease (AD) continuum. Hippocampal atrophy is one of the typical clinical features and diagnostic criteria of AD. Former studies have described retinal thinning in normal aging subjects and AD patients, yet the association between retinal thickness and hippocampal atrophy in AD is unclear. The optical coherence tomography (OCT) technique has access the non-invasive to retinal images and magnetic resonance imaging can outline the volume of the hippocampus. Thus, we aim to quantify the correlation between these two parameters to identify whether the retina can be a new biomarker for early AD detection.MethodsWe systematically searched the PubMed, Embase, and Web of Science databases from inception to May 2023 for studies investigating the correlation between retinal thickness and hippocampal volume. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the study quality. Pooled correlation coefficient r values were combined after Fisher’s Z transformation. Moderator effects were detected through subgroup analysis and the meta-regression method.ResultsOf the 1,596 citations initially identified, we excluded 1,062 studies after screening the titles and abstract (animal models, n = 99; irrelevant literature, n = 963). Twelve studies met the inclusion criteria, among which three studies were excluded due to unextractable data. Nine studies were eligible for this meta-analysis. A positive moderate correlation between the retinal thickness was discovered in all participants of with AD, mild cognitive impairment (MCI), and normal controls (NC) (r = 0.3469, 95% CI: 0.2490–0.4377, I2 = 5.0%), which was significantly higher than that of the AD group (r = 0.1209, 95% CI:0.0905–0.1510, I2 = 0.0%) (p < 0.05). Among different layers, the peripapillary retinal nerve fiber layer (pRNFL) indicated a moderate positive correlation with hippocampal volume (r = 0.1209, 95% CI:0.0905–0.1510, I2 = 0.0%). The retinal pigmented epithelium (RPE) was also positively correlated [r = 0.1421, 95% CI:(−0.0447–0.3192), I2 = 84.1%]. The retinal layers and participants were the main overall heterogeneity sources. Correlation in the bilateral hemisphere did not show a significant difference.ConclusionThe correlation between RNFL thickness and hippocampal volume is more predominant in both NC and AD groups than other layers. Whole retinal thickness is positively correlated to hippocampal volume not only in AD continuum, especially in MCI, but also in NC.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, CRD42022328088.

Type I interferons (IFNs) initiate immune responses to viral infections. Their effects are mediated by the type I IFN receptor, IFNAR, comprised of two subunits: IFNAR1 and IFNAR2. One or both chains of the sheep IFNAR were disrupted in fetal fibroblast lines using CRISPR/Cas9 and 12 lambs were produced by somatic cell nuclear transfer (SCNT). Quantitative reverse transcription-polymerase chain reaction for IFN-stimulated gene expression showed that IFNAR deficient sheep fail to respond to IFN-alpha. Furthermore, fibroblast cells from an IFNAR2−/− fetus supported significantly higher levels of Zika virus (ZIKV) replication than wild-type fetal fibroblast cells. Although many lambs have died from SCNT related problems or infections, one fertile IFNAR2−/− ram lived to over 4 years of age, remained healthy, and produced more than 80 offspring. Interestingly, ZIKV infection studies failed to demonstrate a high level of susceptibility. Presumably, these sheep compensated for a lack of type I IFN signaling using the type II, IFN-gamma and type III, IFN-lambda pathways. These sheep constitute a unique model for studying the pathogenesis of viral infection. Historical data supports the concept that ruminants utilize a novel type I IFN, IFN-tau, for pregnancy recognition. Consequently, IFNAR deficient ewes are likely to be infertile, making IFNAR knockout sheep a valuable model for studying pregnancy recognition. A breeding herd of 32 IFNAR2+/− ewes, which are fertile, has been developed for production of IFNAR2−/− sheep for both infection and reproduction studies.

Abstract Background There is now ample evidence suggesting that extracorporeal shock wave therapy (ESWT) can improve hip mobility and reduce pain in patients with osteonecrosis of the femoral head (ONFH). The ability of ESWT to cure bone marrow edema syndrome (BMES) in patients with ONFH, 12 weeks after the initial course of ESWT, needs to be verified further and more relevant clinical research-based evidence should be consolidated. This study aimed to evaluate the efficacy of ESWT for BMES caused by ONFH. Methods This retrospective cohort study included 67 patients with BMES caused by ONFH who were participating in a rehabilitation program as outpatients. Before and after ESWT, the area of femoral bone marrow edema was evaluated by magnetic resonance imaging (MRI), and the Harris score and Charnley score were evaluated as hip pain and function indicators. Results After ESWT, MRI revealed that the area of bone marrow edema decreased from 984.6 ± 433.2 mm2 to 189.7 ± 214.4 mm2 (P < 0.0001). The Harris score increased from 42.2 ± 9.1 to 77.7 ± 10.8 points (P < 0.0001). The Charnley score increased from 7.3 ± 1.4 to 12.0 ± 1.7 (P < 0.0001). ESWT was effective in treating BMES in 98.5% of the cases. Conclusions This study demonstrated that ESWT can effectively treat BMES caused by ONFH and can aid in pain relief and functional recovery in patients with ONFH. Thus, ESWT should be included in the classic physical therapy regimen for patients with ONFH and BMES.

Objective: To explore the evolvement and new trends in the use of Shuanghuanglian injection (SHLI). Methods: China National Knowledge Infrastructure (CNKI), PubMed, and Embase were extensively searched using the search terms “Shuanghuanglian injection” and “Shuanghuanglian fenzhen” to retrieve articles relevant to SHLI (1992–2020). Retrieved articles were further investigated by two authors to exclude those unrelated to SHLI. The bibliographical references of the included articles were exported as raw data and then treated using the CiteSpace tool to visualize the mapping of the SHLI research domain. Essential clusters and highly frequent keywords were quantified for further analysis. The clusters were automatically labeled by the algorithm of tf∗idf for objective analysis. Basic bibliometric features, including article types and yearly trend in article numbers were also determined and discussed. Results: The modules of the keywords of interest presented clear boundaries with a high modularity score (Q = 0.73). High-confidence clusters were identified, including bioactivity fingerprint (S = 0.99), equal pupils (S = 0.91), drug preparation department (S = 0.87), difficulty in respiration (S = 0.85), peristalsis (0.88), and Danshen powder injection (S = 0.94). The characteristic keywords in terms of frequency and burstiness were Shuanghuanglian powder for injection (F = 235, B = 5.22), SHLI (F = 112, B = 11.39), and adverse drug reactions (ADRs; F = 104, B = 7.35). Conclusion: In the field of SHLI study, there are five major topic categories: bioactivity fingerprint; ADR mechanism and cause detection; proper preparation; clinical evidence accumulation; and efficacy in diseases with no effective treatment and combination usage. The trend for using modern methodologies from a science-based perspective to study SHLI will continue to exist. The causes of multi-factorial ADRs may be an important topic for future studies.

A Tm,Ho:YAP laser at cryogenic temperature is demonstrated for the first time with simultaneous emission at 2000 nm and 2119 nm. The feasibility of switching wavelength and achieving balanced output powers at two widely separated wavelengths has been confirmed by investigating the temperature dependence of the laser spectra. The optimal temperature for balanced output evidently diminishes as the pump power density increases, thereby manifesting a rate of change quantified at 1.19 K/W. At the optimal temperature of 43.1 K, the optical-to-optical conversion efficiency of the Tm,Ho:YAP simultaneous dual-wavelength laser (SDWL) with a pump power of 11.8 W is 12.7%, corresponding to a slope efficiency of 15.8%.

We explored changes in pregnancy-specific glycoprotein 9 (PSG9) levels in the serum of patients with preeclampsia and the effects and underlying mechanisms of PSG9 effects on calcium (Ca2+) homeostasis and nitric oxide (NO) release in human umbilical vein endothelial cells (HUVECs). Western blotting was used to detect protein expression levels, and an NO fluorescence probe was used to examine NO production. Intracellular Ca2+ concentrations were measured using a Ca2+-sensitive fluorescent dye under a fluorescence microscope. Compared with those in healthy pregnant women, serum PSG9 levels were significantly decreased in patients with preeclampsia. PSG9 (0.1 μg/mL) treatment of HUVECs significantly enhanced the expression levels of store-operated calcium entry (SOCE) channel proteins Orai1 and Orai2, but not Orai3, and of endothelial nitric oxide synthase (eNOS) and NO production. Pretreatment with an inhibitor of SOCE (BTP2) abolished PSG9-enhanced Orai1, Orai2, and eNOS expression levels and NO production in HUVECs. The mechanisms underlying SOCE that were PSG9 enhanced in HUVECs appear to involve the Ca2+/eNOS/NO signaling pathway. These findings suggest that serum PSG9 levels may be a potential biomarker for monitoring the occurrence or development of preeclampsia in pregnancy and that PSG9 may be a potential therapeutic target for the treatment of preeclampsia.

Objective: To explore the glucuronic acid metabolism of acacetin in human liver and intestinal microsomes to better characterize human uridine 5′-diphospho (UDP)-glucuronosyltransferase (UGT) isoforms. In addition, interspecies comparisons were performed to identify the most appropriate experimental animal model for an in vivo study. Methods: Liquid chromatography tandem mass spectrometry (LC-MS/MS) and nuclear magnetic resonance (NMR) were used to confirm the successful biosynthesis of acacetin-7-O-glucuronide. Human isoforms of UGT and isozyme-specific chemical inhibitors were used for recombinant assays. Acacetin glucuronidation kinetics were assessed by combining acacetin with recombinant human UGT isoforms or with microsomes from humans or experimental animals. Kinetic differences between species were assessed in vitro using the same approach. Results: We identified multiple UGT isoforms that facilitated acacetin glucuronidation, and found that UGT1A1 was the major isoform that catalyzed this process. Acacetin-7-O-glucuronide formation exhibited clear substrate inhibition kinetics when combined with recombinant UGTs or with liver/intestinal microsomes derived from humans, monkeys, rats, mice, dogs, or pigs. Intrinsic metabolic clearance values of human intestinal microsomes were two-fold greater than those of human liver microsomes. Among the evaluated species, the Km value of dog microsomes (0.86 μM) was greatest in acacetin glucuronidation, while mice exhibited the highest CLint value, 5.05 mL/min/mg. The CLint values of microsomes derived from monkeys and minipigs were 1.99 mL/min/mg and 2.12 mL/min/mg, respectively, exhibiting similar intrinsic metabolic clearance activity to that observed in humans. Conclusion: Monkey may represent a suitable model for experimental studies of acacetin pharmacokinetics owing to a high sequence homology of UGT1A1 and similar UGT1A1 glucuronidation activity to humans. Keywords: Acacetin, UDP-glucuronosyltransferases, Human liver microsomes, Glucuronidation, Species differences

Since the ecological protection and high-quality development of the Yellow River Basin (YRB) in China have become a primary national strategy, the low-carbon economy is crucial. To formulate effective emission mitigation policies for the YRB, we need to comprehensively understand the characteristics of the spatial agglomeration of the carbon emissions intensity in the YRB and its regional heterogeneity. Therefore, based on the relevant data from 2005 to 2017, we first scientifically measure the carbon emissions intensity of 57 cities along the YRB. Then, we analyze the spatial agglomeration characteristics and long-term transfer trends of carbon emission intensity using exploratory spatial data analysis methods and Markov chains. Finally, the Dagum Gini coefficient and the variation coefficient method are used to study the regional differences and differential evolution convergence of the carbon emissions intensity in the YRB. The results show that the carbon emissions intensity of the YRB has dropped significantly with the spatial distribution characteristics “high in the west and low in the east”, and there is a significant spatial autocorrelation phenomenon. In addition, the probability of a shift in urban carbon intensity is low, leading to a “club convergence” and a “Matthew effect” in general and across regions. Inter-regional differences have always been the primary source of spatial differences in carbon emissions intensity in the YRB, and the intra-regional differences in carbon emissions intensity in the lower YRB show a significant convergence phenomenon. The research results may provide a reference for the regional coordinated development of a low-carbon economy in the YRB, and serve to guide the win-win development model of ecological environment protection and economic growth in the YRB.

Background Osteosarcoma (OS) is the most common malignant bone tumor with high mortality in children and adolescents. REG γ is overexpressed and plays oncogenic roles in various types of human cancers. However, the expression and potential roles of REG γ in osteosarcoma are elusive. This study aims at exploring possible biological functions of REG γ in the pathogenesis of osteosarcoma and its underlying mechanism. Methods Quantitativereverse transcription-polymerase chain reaction (qRT-PCR), western blotting andimmunohistochemistry (IHC)were performed to detect the expression levels of REG γ in OS tissues and cell lines. Then, the effects of REG γ expression on OS cell proliferation in vitro were analyzed by Cell Counting Kit-8 (CCK-8), ethylene deoxyuridine (EdU), colony formation, flow cytometry. The protein levels of apoptosis and cell-cycle related proteins were evaluated using western blotting. Results In present study, we found for the first time that REG γ is overexpressed in osteosarcoma tissues and cell lines and knockdown of REG γ significantly inhibits cell proliferation and induces apoptosis and cell cycle arrest in osteosarcoma cells. Furthermore, we observed that p21, caspase-3 and cleaved caspase-3 are increased while the expression of cycinD1 and bcl-2 are decreased after REG γ depletion in osteosarcoma cells. In conclusion, REG γ may be involved in the proliferation of osteosarcoma and serve as a novel therapeutic target in patients with osteosarcoma.

Objective: To investigate the action mechanism of Rhizoma Atractylodis (Atractylodes lancea (Thunb.) Dc.) and Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.), a two-herb ancient traditional Chinese medicine used to treat type 2 diabetes mellitus, using molecular docking. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was searched for compounds in the two herbs and oral bioavailability and drug-likeness values were used to select compounds. The target proteins were selected based on a survey of the literature and related databases, and three receptors closely related to type 2 diabetes were chosen: insulin receptor, peroxisome proliferator activated receptor and dipeptidyl peptidase-IV. Molecular docking was performed using the CDocker module in Discovery Studio software. The interactions between targets and ligands were observed and analyzed, including the mode of action. Results: Nineteen compounds from the herbal pair interacted with the insulin receptor, the peroxisome proliferator activated receptor and dipeptidyl peptidase-IV. Among them, 10 compounds bound successfully with all three targets, one compound bound with two targets, and eight compounds bound with one target. According to CDocker Interaction Energy, most compounds from the herbal pair had good binding activities with receptors and nine compounds had even higher scores than those of the original ligands. These data indicate that these compounds may be active in reducing blood glucose levels for the treatment of type 2 diabetes. Conclusion: Multiple compounds in the Rhizoma Atractylodis-Rhizoma Atractylodis Macrocephalae herbal pair can affect multiple human targets related to type 2 diabetes. Keywords: Herbal pair, Pharmacological mechanism, Molecular docking, Type 2 diabetes mellitus

In this paper, a piezoresistive pressure sensor based on silicon on insulator (SOI) was presented, which was composed of an SOI layer with sensing elements and a glass cap for a hermetic package. Different from its conventional counterparts, the position and thickness of the four piezoresistors was optimized based on numerical simulation, which suggests that two piezoresistors at the center while the other two at the edge of the pressure-sensitive diaphragm and a thickness of 2 μm can produce the maximum sensitivity and the minimum nonlinearity. Due to the use of silicon rather than metal for electrical connections, the piezoresistive pressure sensor was fabricated in a highly simplified process. From the experimental results, the fabricated piezoresistive pressure sensor demonstrated a high sensitivity of 37.79 mV·V−1·MPa−1, a high full-scale (FS) output of 472.33 mV, a low hysteresis of 0.09% FS, a good repeatability of 0.03% FS and a good accuracy of 0.06% FS at 20 °C. A temperature coefficient of sensitivity of 0.44 mV·MPa−1·°C−1 and a low zero drift were also shown at different temperatures. The piezoresistive pressure sensor developed in this study may function as an enabling tool in pressure measurements.

Objective: To uncover and identify the hot topic and frontier of Chinese medicines treatment of type 2 diabetes mellitus (T2DM). Methods: Web of Science TM was searched for published articles for Chinese medicines treatment of T2DM ranging from January 1st, 2002 to July 6th, 2016. Knowledge maps of the international Chinese medicines treatment of T2DM are visualized by using document co-occurrence analysis and word frequency analysis (Institution and Journal), co-citation clustering analysis (Co-reference), keyword co-occurrence clustering analysis with CiteSpac III, a tool of scientometrics. Results: Universidad Nacional Autonoma de Mexico is the institution with the highest number of published papers that had been cited in this field, while China has four institutions among the top 10. The journal of the highest frequency of co-cited journal was Diabetes Care, a core one in the field. Keywords co-occurrence network was composed of 185 nodes, 541 lines, and divided into 10 clusters. Co-citation network of co-reference was composed of 407 nodes, 1199 lines, and divided into 20 clusters. Using Chinese medicine to improve insulin resistance and Chinese medicine research on blood glucose control are the hot topics. The frontier contains two aspects: new drugs development and application of intestinal insulin treatment and development and use of traditional Chinese medicine antidiabetic plants. Conclusion: Institutions from China still plays a major role in TCM-focused T2DM studies. The effect of TCM herbs on insulin resistance is the hot topic of the domain. Developing new TCM herbal medicine that regulates incretin effect is the domain frontier. Research on the Chinese medicines treatment of T2DM needs more high-quality evidence to support, and its mechanism requires further exploration.

Objective: To propose and test a new approach based on community detection in the field of social computing for uncovering consensuses and treatment principles in traditional Chinese medicine (TCM). Methods: Three Chinese databases (CNKI, VIP, and Wan Fang Data) were searched for published articles on TCM treatment of diabetic nephropathy (DN) from their inception until September 31, 2014. Zheng classification and herb data were extracted from included articles and used to construct a Zheng classification and treatment of diabetic nephropathy (DNZCT) network with nodes denoting Zhengs and herbs and edges denoting corresponding treating relationships among them. Community detection was applied to the DNZCT and detected community structures were analyzed. Results: A network of 201 nodes and 743 edges were constructed and six communities were detected. Nodes clustered in the same community captured the same semantic topic; different communities had unique characteristics, and indicated different treatment principles. Large communities usually represented similar points of view or consensuses on common Zheng diagnoses and herb prescriptions; small communities might help to indicate unusual Zhengs and herbs. Conclusion: The results suggest that the community detection-based approach is useful and feasible for uncovering consensuses and treatment principles of DN treatment in TCM, and could be used to address other similar problems in TCM.

Background and objective Lung cancer is the leading cause of cancer-related death in men and women. It is also the most common cause of brain metastases. A brain metastasis model is difficult to be established because of the presence of the blood-brain barrier (BBB) and the lack of optimal methods for detecting brain metastasis in nude mice. Thus, the establishment of a Chinese lung adenocarcinoma cell line and its animal model with brain metastasis potency and in vivo research is of great significance. Methods CPA-Yang1 cells were obtained from a patient with human lung adenocarcinoma by lentiviral vector-mediated transfection of green fluorescence protein. Intracardiac inoculation of the cells was performed in nude mice, and brain metastatic lesions were detected using micro 18F FDG-PET/CT scanners, small animal in vivo imaging system for fluorescence, radionuclide and X ray fused imaging, magnetic resonance imaging (MRI) with sense body detection, and resection. The samples were divided into two parts for cell culture and histological diagnosis. The process was repeated in vivo and in vitro for four cycles to obtain a novel cell clone, CPA-Yang1-BR. Results A novel cell clone, CPA-Yang1-BR, was obtained with a brain metastatic rate of 50%. The use of MRI for the detection of brain metastases has obvious advantages. Conclusion An experimental Chinese lung adenocarcinoma cell clone (CPA-Yang1-BR) and its animal model with brain metastasis potency in nude mice were established. MRI with sense body or micro MRI may be used as a sensitive, accurate, and noninvasive method to detect experimental brain metastases in intact live immunodeficient mice. The results of this study may serve as a technical platform for brain metastases from lung adenocarcinoma.

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

The golden Syrian hamster is the model of choice or the only rodent model for studying many human diseases. However, the lack of gene targeting tools in hamsters severely limits their use in biomedical research. Here, we report the first successful application of the CRISPR/Cas9 system to efficiently conduct gene targeting in hamsters. We designed five synthetic single-guide RNAs (sgRNAs)--three for targeting the coding sequences for different functional domains of the hamster STAT2 protein, one for KCNQ1, and one for PPP1R12C--and demonstrated that the CRISPR/Cas9 system is highly efficient in introducing site-specific mutations in hamster somatic cells. We then developed unique pronuclear (PN) and cytoplasmic injection protocols in hamsters and produced STAT2 knockout (KO) hamsters by injecting the sgRNA/Cas9, either in the form of plasmid or mRNA, targeting exon 4 of hamster STAT2. Among the produced hamsters, 14.3% and 88.9% harbored germline-transmitted STAT2 mutations from plasmid and mRNA injection, respectively. Notably, 10.4% of the animals produced from mRNA injection were biallelically targeted. This is the first success in conducting site-specific gene targeting in hamsters and can serve as the foundation for developing other genetically engineered hamster models for human disease.

OBJECTIVE: The aim of the present study was to explore the potential for hematoporphyrin monomethyl ether-Sonodynamic Therapy (HMME-SDT) treatment of hypertrophic scars within rabbit ears. METHODS: 60 white rabbits were randomly divided into five groups: (1) untreated controls, (2) lesioned, (3) lesioned + HMME, (4) lesioned + US (Ultrasound), and (5) lesioned +HMME-SDT. After induction of a lesion upon the ears of the rabbits, hypertrophic scars were assessed at 14, 28, 42 and 56 days post-lesion +/- treatment. Assessments consisted of visual inspection in the change of the skin, scar formation pathological morphology by hematoxylin and eosin (HE) staining technique with optical microscopy, calculation of a hypertrophic index, fibroblastic density measures, and observation of collagen changes in the scar tissue by Van Gieson's (VG)Stain along with calculation of collagen area density. RESULTS: With continued HMME-SDT treatment there was a gradual improvement in all parameters over the duration of the experiment. The lesion-induced scars of rabbits receiving HMME-SDT treatment were soft, the size was reduced, hyperplasia was flat and the color pale. The fibroblasts and collagens were reduced and the collagens were light red, sparse and orderly. The hypertrophic index was reduced, since the fibroblastic density was lowered and collagen area density was decreased. CONCLUSION: HMME is an effective sonosensitizer and the combination of HMME-SDT treatment can exert significant benefits in reducing the formation of hypertrophic scars.