Association of 24-hour movement guideline adherence, mental health and quality of life in young adults: the role of e-Health literacy.

Background: The spread of Covid-19 and resultant infection prevention strategies have disturbed the life routine of Chinese young adults, led to reduced physical activity (PA), prolonged screen time (ST) and inadequate sleep duration (SP), and made immense influence on their mental health (MH) and quality of life (QoL). E-Health literacy (EHL) can enable citizens to use available online information to respond to the highly complex information environment and make appropriate health decisions. Objective: This study aims to examine associations between adhering to 24-h movement (24HM) guidelines and MH and QoL among young adults, as well as to identify any mediating or moderating role of EHL in these associations. Methods: 1742 young adults (20.03 ± 1.54 years old, 68.6% females) from north and south China completed self-report measures of 24HM (PA, ST and SP), health indicators (MH and QoL), EHL and demographic information through an online survey between 4 Apr and 16 Jun 2022. Generalized linear mixed models were applied for data analysis. Results: Results showed that adhering to PA, ST and SP guidelines were all positively connected with QoL while MH was associated with adhering ST or SP guidelines. Adhering to more of 24HM guidelines was linked to better MH and QoL. EHL significantly mediated the association of guideline adherence and QoL and moderate that of guideline adherence and MH. Conclusion: This is the first study to investigate the role of EHL on the associations between 24HM and MH as well as QoL during the Covid-19. The findings may contribute to further empirical research or intervention that aims to promote MH or QoL among young adults more effectively or provide valuable references for developing relevant strategies or policy of health promotion or public health events in China.

Assessing the impact of Australia's mass vaccination campaigns over the Delta and Omicron outbreaks.

BACKGROUND: The Australian Government implemented a national vaccination campaign against COVID-19 beginning February 22, 2021. The roll-out was criticised for being delayed relative to many high-income countries, but high levels of vaccination coverage were belatedly achieved. The large-scale Omicron outbreak in January 2022 resulted in a massive number of cases and deaths, although mortality would have been far higher if not for vigorous efforts to rapidly vaccinate the entire population. The impact of the vaccination coverage was assessed over this extended period. METHODS: We considered NSW, as the Australian jurisdiction with the highest quality data for our purposes and which still reflected the national experience. Weekly death rates were derived among individuals aged 50+ with respect to vaccine status between August 8, 2021 and July 9, 2022. We evaluated deaths averted by the vaccination campaign by modelling alternative counterfactual scenarios based on a simple data-driven modelling methodology presented by Jia et al. (2023). FINDINGS: Unvaccinated individuals had a 7.7-fold greater mortality rate than those who were fully vaccinated among people aged 50+, which rose to 11.2-fold in those who had received a booster dose. If NSW had fully vaccinated its ~2.9 million 50+ residents earlier (by July 28, 2021), only 440 of the total 3,495 observed 50+ deaths would have been averted. Up to July 9, 2022, the booster campaign prevented 1,860 deaths. In the absence of a vaccination campaign, ~21,250 COVID-19 50+ deaths (conservative estimate) could have been expected in NSW i.e., some 6 times the actual total. We also find the methodology of Jia et al. (2023) can sometimes significantly underestimate that actual number. INTERPRETATION: The Australian vaccination campaign was successful in reducing mortality over 2022, relative to alternative hypothetical vaccination scenarios. The success was attributable to the Australian public's high levels of engagement with vaccination in the face of new SARS-COV-2 variants, and because high levels of vaccination coverage (full and booster) were achieved in the period shortly before the major Omicron outbreak of 2022.

One-Component Cationic Lipids for Systemic mRNA Delivery to Splenic T Cells.

Unlocking the full potential of mRNA immunotherapy necessitates targeted delivery to specific cell subsets in the spleen. Four-component lipid nanoparticles (LNPs) utilized in numerous clinical trials are primarily limited in hepatocyte and muscular targeting, highlighting the imperative demand for targeted and simplified non-liver mRNA delivery systems. Herein, we report the rational design of one-component ionizable cationic lipids to selectively deliver mRNA to the spleen and T cells with high efficacy. Unlike the tertiary amine-based ionizable lipids involved in LNPs, the proposed cationic lipids rich in secondary amines can efficiently deliver mRNA both in vitro and in vivo as the standalone carriers. Furthermore, these vectors facilitate efficacious mRNA delivery to the T cell subsets following intravenous administration, demonstrating substantial potential for advancing immunotherapy applications. This straightforward strategy extends the utility of lipid family for extrahepatic mRNA delivery, offering new insights into vector development beyond LNPs to further the field of precise mRNA therapy.

Targeting materials and strategies for RNA delivery.

RNA-based therapeutics have shown great promise in various medical applications, including cancers, infectious diseases, and metabolic diseases. The recent success of mRNA vaccines for combating the COVID-19 pandemic has highlighted the medical value of RNA drugs. However, one of the major challenges in realizing the full potential of RNA drugs is to deliver RNA into specific organs and tissues in a targeted manner, which is crucial for achieving therapeutic efficacy, reducing side effects, and enhancing overall treatment efficacy. Numerous attempts have been made to pursue targeting, nonetheless, the lack of clear guideline and commonality elucidation has hindered the clinical translation of RNA drugs. In this review, we outline the mechanisms of action for targeted RNA delivery systems and summarize four key factors that influence the targeting delivery of RNA drugs. These factors include the category of vector materials, chemical structures of vectors, administration routes, and physicochemical properties of RNA vectors, and they all notably contribute to specific organ/tissue tropism. Furthermore, we provide an overview of the main RNA-based drugs that are currently in clinical trials, highlighting their design strategies and tissue tropism applications. This review will aid to understand the principles and mechanisms of targeted delivery systems, accelerating the development of future RNA drugs for different diseases.

Rational Design of Abasic Site-Containing DNA Triplexes To Bind Small Molecules with Low Nanomolar Dissociation Constants.

De novo design of functional biomacromolecules is of great interest to a wide range of fundamental science and technological applications, including understanding life evolution and biomacromolecular structures, developing novel catalysts, inventing medicines, and exploring high-performance materials. However, it is an extremely challenging task and its success is very limited. It requires a deep understanding of the relationships among the primary sequences, the 3D structures, and the functions of biomacromolecules. Herein, we report a rational, de novo design of a DNA aptamer that can bind melamine with high specificity and high affinity (dissociation constant Kd = 4.4 nM). The aptamer is essentially a DNA triplex, but contains an abasic site, to which the melamine binds. The aptamer-ligand recognition involves hydrogen-bonding, π-π stacking, and electrostatic interactions. This strategy has been further tested by designing aptamers to bind to guanosine. It is conceivable that such a rational strategy, with further development, would provide a general framework for designing functional DNA molecules.

Impact of Platelet-Rich Fibrin Combined with Silver Nanoparticle Dressing on Healing Time and Therapeutic Efficacy of Chronic Refractory Wounds.

Introduction: Objective • This study aimed to investigate the clinical value of combining platelet-rich fibrin (PRF) with nano silver (AgNP) dressing in the treatment of chronic refractory wounds. Introduction: Methods • A total of 120 patients with chronic refractory wounds were selected from our hospital between January 2020 and January 2022. The patients were randomly divided into the control group and the study group, with 60 cases in each group. The control group received basic treatment combined with AgNP dressing, while the study group received PRF combined with AgNP dressing. A comparison was made between the two groups in terms of wound healing time, hS-CRP levels, VISUAL analogue scale (VAS) scores, procalcitonin (PCT) levels, clinical efficacy, and complications. Introduction: Results • Before treatment, there were no significant differences in hS-CRP, VAS, and PCT levels between the two groups (P > .05). However, after treatment, the study group showed significantly lower hS-CRP, VAS, and PCT levels compared to the control group (P < .05). The study group also exhibited a shorter wound healing time, a higher rate of excellent and good curative effect (95.00% vs 81.67%) compared to the control group (χ2 = 5.175, P < .05), and a lower incidence of wound complications (6.67% vs 21.67%) compared to the control group (χ2 = 4.386, P < .05). Introduction: Conclusions • The combination of PRF and AgNP dressing can effectively alleviate pain and local inflammation in patients with chronic refractory wounds, improve the wound healing rate, shorten the healing time, and reduce the risk of complications such as infection spread.

The Value of Continuous Closed Negative Pressure Drainage Combined with Antibacterial Biofilm Dressing in Postoperative Wound Healing for Severe Pancreatitis.

Objective: To investigate the application value of continuous vacuum sealing drainage (VSD) combined with antibacterial biofilm hydraulic fiber dressing in wound healing after surgery for severe acute pancreatitis (SAP). Methods: A total of 82 SAP patients who underwent minimally invasive surgery in our hospital from March 2021 to September 2022 were randomly divided into two groups using a random number table method. Each group consisted of 41 cases. Both groups received surgical treatment, with the control group receiving VSD treatment and the observation group receiving VSD treatment combined with antibacterial biofilm hydraulic fiber dressing. The postoperative recovery efficiency, preoperative and postoperative wound area reduction rate, pressure ulcer healing score (PUSH), serum biological indicators (white blood cell count (WBC), C-reactive protein (CRP), procalcitonin (PCT)), and the rate of wound-related adverse reactions were compared between the two groups. Results: There was no statistical difference between the two groups in the time to resume eating (P > .05). However, the wound healing time and hospitalization days in the observation group were significantly shorter than those in the control group (P < .05). After 7 and 14 days of treatment, the wound area reduction rate in the observation group was significantly higher than in the control group, and the PUSH score was significantly lower than in the control group (P < .05). WBC, CRP, and PCT levels in the observation group were lower than in the control group (P < .05). The incidence of wound-related adverse reactions in the observation group (12.20%) was significantly lower than that in the control group (34.15%) (P < .05). Conclusions: The application of VSD combined with antibacterial biofilm hydraulic fiber dressing in the postoperative wound healing of SAP has a significant effect. It improves wound healing efficiency, reduces pressure ulcer scores, decreases inflammation indicators, and lowers the incidence of adverse reactions. While further research is needed to determine its impact on infection and inflammation prevention, this treatment approach shows promise for clinical application.

The emotional facial recognition performance of Chinese patients with schizophrenia: An event-related potentials study.

Background: Patients with schizophrenia have deficits in identifying and recognizing emotional facial expressions. Aim: This study aimed to explore the event-related potential (ERP) responses of patients with schizophrenia (SZ) and healthy controls (HC) using the Chinese Facial Affective Picture System (CFAPS). Methods: This study included 30 SZs and 31 HCs. We asked them to complete the task based on the oddball paradigm, in which three emotional faces (happy, fearful, and neutral) were used as target stimuli. Additionally, the amplitude and latency of the N170 component and the P300 component were recorded synchronously. Results: Compared with HCs, SZs had significantly smaller amplitudes of N170 and P300 to all facial expressions. The pairwise comparison revealed that fearful faces could trigger a significantly larger P300 amplitude in HCs than neutral faces, while the such a difference was not found in SZs. Conclusion: These findings indicated that SZs had a noticeable deficiency in the structural coding of face recognition and available attentional resources.

Resolving the enigma of Iquitos and Manaus: A modeling analysis of multiple COVID-19 epidemic waves in two Amazonian cities.

The two nearby Amazonian cities of Iquitos and Manaus endured explosive COVID-19 epidemics and may well have suffered the world's highest infection and death rates over 2020, the first year of the pandemic. State-of-the-art epidemiological and modeling studies estimated that the populations of both cities came close to attaining herd immunity (>70% infected) at the termination of the first wave and were thus protected. This makes it difficult to explain the more deadly second wave of COVID-19 that struck again in Manaus just months later, simultaneous with the appearance of a new P.1 variant of concern, creating a catastrophe for the unprepared population. It was suggested that the second wave was driven by reinfections, but the episode has become controversial and an enigma in the history of the pandemic. We present a data-driven model of epidemic dynamics in Iquitos, which we also use to explain and model events in Manaus. By reverse engineering the multiple epidemic waves over 2 y in these two cities, the partially observed Markov process model inferred that the first wave left Manaus with a highly susceptible and vulnerable population (≈40% infected) open to invasion by P.1, in contrast to Iquitos (≈72% infected). The model reconstructed the full epidemic outbreak dynamics from mortality data by fitting a flexible time-varying reproductive number [Formula: see text] while estimating reinfection and impulsive immune evasion. The approach is currently highly relevant given the lack of tools available to assess these factors as new SARS-CoV-2 virus variants appear with different degrees of immune evasion.

Two waves of COIVD-19 in Brazilian cities and vaccination impact.

BACKGROUNDS: Brazil has suffered two waves of Coronavirus Disease 2019 (COVID-19). The second wave, coinciding with the spread of the Gamma variant, was more severe than the first wave. Studies have not yet reached a conclusion on some issues including the extent of reinfection, the infection fatality rate (IFR), the infection attack rate (IAR) and the effects of the vaccination campaign in Brazil, though it was reported that confirmed reinfection was at a low level. METHODS: We modify the classical Susceptible-Exposed-Infectious-Recovered (SEIR) model with additional class for severe cases, vaccination and time-varying transmission rates. We fit the model to the severe acute respiratory infection (SARI) deaths, which is a proxy of the COVID-19 deaths, in 20 Brazilian cities with the large number of death tolls. We evaluate the vaccination effect by a contrast of "with" vaccination actual scenario and "without" vaccination in a counterfactual scenario. We evaluate the model performance when the reinfection is absent in the model. RESULTS: In the 20 Brazilian cities, the model simulated death matched the reported deaths reasonably well. The effect of the vaccination varies across cities. The estimated median IFR is around 1.2%. CONCLUSION: Overall, through this modeling exercise, we conclude that the effects of vaccination campaigns vary across cites and the reinfection is not crucial for the second wave. The relatively high IFR could be due to the breakdown of medical system in many cities.

Multiple COVID-19 Waves and Vaccination Effectiveness in the United States.

(1) Background: The coronavirus 2019 (COVID-19) pandemic has caused multiple waves of cases and deaths in the United States (US). The wild strain, the Alpha variant (B.1.1.7) and the Delta variant (B.1.617.2) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were the principal culprits behind these waves. To mitigate the pandemic, the vaccination campaign was started in January 2021. While the vaccine efficacy is less than 1, breakthrough infections were reported. This work aims to examine the effects of the vaccination across 50 US states and the District of Columbia. (2) Methods: Based on the classic Susceptible-Exposed-Infectious-Recovered (SEIR) model, we add a delay class between infectious and death, a death class and a vaccinated class. We compare two special cases of our new model to simulate the effects of the vaccination. The first case expounds the vaccinated individuals with full protection or not, compared to the second case where all vaccinated individuals have the same level of protection. (3) Results: Through fitting the two approaches to reported COVID-19 deaths in all 50 US states and the District of Columbia, we found that these two approaches are equivalent. We calculate that the death toll could be 1.67-3.33 fold in most states if the vaccine was not available. The median and mean infection fatality ratio are estimated to be approximately 0.6 and 0.7%. (4) Conclusions: The two approaches we compared were equivalent in evaluating the effectiveness of the vaccination campaign in the US. In addition, the effect of the vaccination campaign was significant, with a large number of deaths averted.

Extraction method development for nanoplastics from oyster and fish tissues.

Nanoplastics are now found in some environmental media and consumer products. However, very limited data on nanoplastics are available for one of the main human consumption sources of microplastics: seafood. Unlike microplastics, a method for extracting nanoplastics from seafood is still lacking. Herein, a combination of common extraction techniques including enzymatic digestion, sequential membrane filtration, centrifugal concentration, and purification (dialysis and sodium dodecylsulfate (SDS) incubation), was developed to extract nanoplastics from oyster and fish tissues. Corolase with subsequent lipase treatment achieved the highest digestion efficiencies (88- 89%) for non-homogenized tissues compared to other proteases and additional cellulase or H2O2 treatment. With the exception of polyethylene terephthalate (PET), enzymatic digestion did not change the morphology or structure of polyvinyl chloride (PVC), polyethylene (PE), or polystyrene (PS) nanoplastic particles, and the subsequent extraction procedures had good recoveries of 71- 110% for fluorescence-labeled 76-nm PVC and 100- and 750-nm PS, as validated by a Nanoparticle Tracking Analysis (NTA). Few of the 1011 digested residual particles of 150- 300 nm in diameter per oyster or per serving of fish tissue were left in the method blank. Consequently, this efficient approach could be used as a pretreatment protocol for current potential nanoplastic detection methods.

The Disease Severity and Clinical Outcomes of the SARS-CoV-2 Variants of Concern.

With the continuation of the pandemic, many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have appeared around the world. Owing to a possible risk of increasing the transmissibility of the virus, severity of the infected individuals, and the ability to escape the antibody produced by the vaccines, the four SARS-CoV-2 variants of Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) have attracted the most widespread attention. At present, there is a unified conclusion that these four variants have increased the transmissibility of SARS-CoV-2, but the severity of the disease caused by them has not yet been determined. Studies from June 1, 2020 to October 15, 2021 were considered, and a meta-analysis was carried out to process the data. Alpha, Beta, Gamma, and Delta variants are all more serious than the wild-type virus in terms of hospitalization, ICU admission, and mortality, and the Beta and Delta variants have a higher risk than the Alpha and Gamma variants. Notably, the random effects of Beta variant to the wild-type virus with respect to hospitalization rate, severe illness rate, and mortality rate are 2.16 (95% CI: 1.19-3.14), 2.23 (95% CI: 1.31-3.15), and 1.50 (95% CI: 1.26-1.74), respectively, and the random effects of Delta variant to the wild-type virus are 2.08 (95% CI: 1.77-2.39), 3.35 (95% CI: 2.5-4.2), and 2.33 (95% CI: 1.45-3.21), respectively. Although, the emergence of vaccines may reduce the threat posed by SARS-CoV-2 variants, these are still very important, especially the Beta and Delta variants.

Water-absorption-trough dewatering machine for estimation of organic carbon in moist soil.

Quantitative estimation of soil organic carbon (SOC) is essential for the study of the C cycle and global C storage. Soil spectroscopic technology provides a cost-effective and time-efficient method for SOC quantification and has been successfully used to determine SOC storage. However, the SOC estimation accuracy remains limited by other soil properties, particularly soil water. In this study, we proposed a new deep learning algorithm named the Water Absorption Trough Dewatering Machine (WATDM) to improve estimations of SOC from soil reflectance spectra and reduce the effect of soil water. Soil water and reflectance spectral data of soil samples were measured using spectrometry. Based on the soil water contents derived from the water absorption troughs around 1900 nm, the optimal WATDM model was obtained and treated as the final model of the WATDM method, which performed better than a multiple linear regression model based on moist soil samples. The findings of this study indicate that the WATDM method can improve the estimation accuracy of SOC content by reducing the effect of soil water and can be used as a valuable new methodology within the spectroscopic estimation of soil properties.

Water-based measured-value fuzzification improves the estimation accuracy of soil organic matter by visible and near-infrared spectroscopy.

Visible and near-infrared (Vis-NIR) reflectance spectroscopy continues to emerge as a rapid and effective approach for estimating several soil physical and chemical properties including soil organic matter (SOM), but its accuracy is restricted by many factors including soil water. This study proposed the water-based measured-value fuzzification (WMF) method to decrease the influence of soil water, and combined with the partial least squares regression (PLSR) to develop SOM models. Vis-NIR spectral data was measured by an ASD FieldSpec 3 spectrometer. After WMF analysis, the PLSR method was used to develop SOM models. By comparison with the PLSR model, the WMF-PLSR model produced markedly better results (root mean square error of validation [RMSEV] = 2.776 g/kg, mean relative error of validation [MREV] = 8.111%, and ratio of performance to interquartile range [RPIQv] = 4.729). With these, the WMF method combined with PLSR shows the potential for estimating SOM content and expands the range of observation methods.

The Effects of the Transforming Growth Factor-ß1 (TGF-ß1) Signaling Pathway on Cell Proliferation and Cell Migration are Mediated by Ubiquitin Specific Protease 4 (USP4) in Hypertrophic Scar Tissue and Primary Fibroblast Cultures.

BACKGROUND Hypertrophic scar results from an abnormal repair response to trauma in the skin and involves fibroblasts proliferation with increased collagen deposition. Transforming growth factor-ß1 (TGF-ß1) and TGF-ß receptor type I (TGF-ßR1) are involved in tissue repair and are increased by ubiquitin-specific protease 4 (USP4). This study aimed to investigate the effects of TGF-ßR1 and USP4 in human tissue samples of hypertrophic scar and on cell proliferation and cell migration in primary fibroblast cultures in vitro. MATERIAL AND METHODS Skin excision tissue samples with adjacent normal skin were obtained from 15 patients with hypertrophic scar, which provided tissue sections and primary fibroblast culture for analysis. Immunohistochemistry detected the expression of USP4 and TGF-ßR1 in tissue sections. MicroRNA (miRNAs) expression levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR). Western blot was performed to measure protein expression levels. Cultured skin fibroblasts were investigated using immunofluorescence staining. Fibroblast proliferation, apoptosis, and migration were measured with the Cell Counting Kit-8 (CCK-8) assay, flow cytometry, and a wound-healing assay, respectively. RESULTS The expression of USP4 and TGF-ßR1 in hypertrophic scar were increased compared with normal skin. Fibroblasts cultured from hypertrophic scar tissue showed increased expression of of USP4 and TGF-ßR1. Fibroblast transfection with USP4 short-interfering RNA (siRNA) resulted in reduced fibroblast proliferation and migration, and increased apoptosis. Downregulation of USP4 inhibited the expression of TGF-ßR1 protein and increased the expression levels of Smad7 protein. CONCLUSIONS USP4 regulated the proliferation, migration, and apoptosis of hypertrophic scar fibroblasts by regulating the TGF-ß1 signaling pathway.

Overexpression of miR-133a-3p inhibits fibrosis and proliferation of keloid fibroblasts by regulating IRF5 to inhibit the TGF-ß/Smad2 pathway.

AIM: Keloid is a benign dermal tumor with excessive hyperplasia and deposition of collagen. As a common tumor suppressor gene, miR-133a-3p has not been studied in keloid. This study will delve into the specific mechanism of miR-133a-3p in keloid. METHODS: Normal skin fibroblasts and keloid fibroblasts (KFs) were first isolated from patients' normal skin and keloid, and cells were identified by morphological observation and immunofluorescence. The expressions of miR-133a-3p and extracellular matrix (ECM)-associated markers (Collagen I, III and α smooth muscle activin) were detected by Quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). Cell viability and apoptosis of KFs were examined by Cell Counting Kit-8 assay, flow cytometry, and Caspase-3 colorimetry. TargetScan predicted target gene for miR-133a-3p was verified by luciferase assay, qRT-PCR and Western Blot (WB). WB was used to study protein expression of TGFBR1, phosphorylated -Smad2 (p-Smad2) and Smad2. Finally, a series of rescue experiments were performed to verify the intervention of target genes on miR-133a-3p. RESULTS: MiR-133a-3p was lowly expressed in keloid tissue and KFs. Overexpression of miR-133a-3p inhibited the expression of ECM-associated markers, reduced KFs viability, and promoted apoptosis. It was verified that interference regulator 5 (IRF5) is miR-133a-3p target gene. The rescue experiments showed that IRF5 reversed the effect of miR-133a-3p mimic on inhibiting fibrosis, and reversed the effects on promoting apoptosis and reducing cell proliferation. CONCLUSION: Overexpressed miR-133a-3p inhibits fibrosis by down-regulating IRF5 and thus inhibiting the TGF-ß/Smad2 pathway. And it also promotes KFs apoptosis and reduces proliferation.

MicroRNA-138 Suppresses Adipogenic Differentiation in Human Adipose Tissue-Derived Mesenchymal Stem Cells by Targeting Lipoprotein Lipase.

PURPOSE: Adipogenic differentiation of adipose tissue-derived mesenchymal stem cells (AMSCs) is critical to many disease-related disorders, such as obesity and diabetes. Studies have demonstrated that miRNA-138 (miR-138) is closely involved in adipogenesis. However, the mechanisms affected by miR-138 remain unclear. This work aimed to investigate interactions between miR-138 and lipoprotein lipase (LPL), a key lipogenic enzyme, in AMSCs. MATERIALS AND METHODS: Human AMSCs (hAMSCs) isolated from human abdomen tissue were subjected to adipogenic differentiation medium. Quantitative real-time polymerase chain reaction and Western blot assay were applied to measure the expressions of miR-138, LPL, and the two adipogenic transcription factors cytidine-cytidine-adenosine-adenosine-thymidine enhancer binding protein alpha (C/EBPα) and peroxisome proliferator-activated receptor gamma (PPARγ). The relationship between miR-138 and LPL was predicted utilizing the miRTarBase database and validated by dual luciferase reporter assay. RESULTS: Showing increases in C/EBPα and PPARγ expression levels, hAMSCs were induced into adipogenic differentiation. During adipogenesis of hAMSCs, miR-138 expression was significantly downregulated. Overexpression of miR-138 by transfection inhibited hAMSCs adipogenic differentiation in vitro. Mechanically, LPL was a target of miR-138. LPL expression was upregulated during adipogenesis of hAMSCs, and this upregulation was reversed by miR-138 overexpression. Functionally, silencing of LPL by transfection exerted similar inhibition of the expressions of C/EBPα and PPARγ. Meanwhile, LPL ectopic expression was able to partly abolish the suppressive effect of miR-138 overexpression on adipogenic differentiation of hAMSCs. CONCLUSION: Upregulation of miR-138 inhibits adipogenic differentiation of hAMSCs by directly downregulating LPL.

[Study on Automatic Identification of Aerosols Boundary Layer Height with Local Optimum Model Based on Lidar Data].

The atmospheric aerosols have significant influence on human health, the environment and the climate system. The atmospheric boundary layer (ABL) reflects processes of the near-surface atmosphere and concentration of pollutants. Ground-based laser radar can monitor the vertical distribution of atmospheric aerosols stably and continuously. It provides dynamic information for timing observations of the ABL and environmental forecasting, if aerosols can be monitored and evaluated using lidar technology. There is a gap in the study of ABL observations during the presence of a residual layer and aerosol intrusion, as well as deficiencies in the accuracy and poor computational efficiency of the gradient method. This paper combines the physical meaning of the latter method with characteristics of a lidar timing chart and local optimum model, which based on space-time proximity. Then a polarization-Mie scattering lidar system is used to observe the vertical distribution of aerosols over time at Taihu observation site, which is in a newly developed area of the city of Wuxi, Jiangsu Province, China. Observation and analysis is carried out for two cases in terms of pollution at the end of 2012. Then corresponding estimation model was built with gradient method and local optimum model based on range-corrected signals. In the case of steady weather and mixed pollution, results of the gradient method and local optimum model were very similar. However, the gradient method has more error in the case of pollution intrusion with the residual layer. The local optimum model based on the space-time proximity theory considers vertical eigenvalues and horizontal correlations, thereby greatly reducing the effects of low clouds, signal interference, weak signals, bi-layered aerosols, and residual layer condition. Compared with the gradient method, the local optimum model had a smaller O(n) and greater stability in computer automatic identification. ABL identification in the case with the residual layer and aerosol intrusion was solved with use of lidar technology and the local optimum model. The accuracy and computational efficiency problems of the gradient method were resolved using automatic operation.