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•Magnetic Fe3O4-PSS@ZIF-67 composites with core-shell structure were prepared.•Fe3O4-PSS@ZIF-67 exhibited highly adsorption capacity for MO.•Fe3O4-PSS@ZIF-67 exhibited excellent ...selective adsorption of MO from mixture solution.•Adsorption kinetic and mechanism were studied.
Efficacious and convenient removal of organic dye contaminants from wastewater is a challenge for public health and ecosystem protection. Here we fabricate a novel type of Fe3O4@MOFs (Metal-organic frameworks) magnetic porous composite materials. ZIF-67 (Zeolitic imidazolate framework-67) nano-crystals as an attractive subfamily of MOF was selected to fabricate Fe3O4-PSS@ZIF-67 composites (defined as MZIF-67). MZIF-67 composites are core-shell structure, for which the aggregation core of Fe3O4 nanoparticles is coated with petal-like ZIF-67 crystals, in which Co2+ firstly combines with SO32− provided by PSS (poly (styrenesulfonate, sodium salt)) to form nucleation. MZIF-67 composites perform well on methyl orange (MO) adsorption, which could be attributed to the highly porosity and the nature of Lewis base of coordinated Co2+ centrals. The results show that the equilibrium adsorption capacity for MO is up to 738mg·g−1 (when pH=8.0, contact time is 7h, adsorbent dose is 5mg and initial MO concentration is 400mg·L−1). In addition, MZIF-67 composites could selectively separate MO from the mixture solution of MO and MB (methylene blue). The removal rate of MO is up to 92%. The concentration ratio of MO/MB is 0.04. And the separation efficiency is up to 96%. The results suggest MZIF-67 composites could be a good candidate for treatment of dye-bearing wastewater.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Soils is a crucial reservoir influencing mercury (Hg) emissions and soil-air exchange dynamics, partially modulated by microbial reducers aiding Hg reduction. Yet, the extent to which microbial ...engagements contribute to soil Hg volatilization remains largely unknown. Here, we characterized Hg-reducing bacterial communities in natural and anthropogenically perturbed soil environments and quantified their contribution to soil Hg(0) volatilization. Our results revealed distinct Hg-reducing bacterial compositions alongside elevated mercuric reductase (merA) gene abundance and diversity in soils adjacent to chemical factories compared to less-impacted ecosystems. Notably, solely industry-impacted soils exhibited increased merA gene abundance along Hg gradients, indicating microbial adaption to Hg selective pressure through quantitative changes in Hg reductase and genetic diversity. Microcosm studies demonstrated that glucose inputs boosted microbial involvement and induced 2–8 fold increments in cumulative Hg(0) volatilization in industry-impacted soils. Microbially-mediated Hg reduction contributed to 41.6% of soil Hg(0) volatilization in industry-impacted soils under 25% water-holding capacity and glucose input conditions over a 21-day incubation period. Alcaligenaceae, Moraxellaceae, Nitrosomonadaceae and Shewanellaceae were identified as potential contributors to Hg(0) volatilization in the soil. Collectively, our study provides novel insights into microbially-mediated Hg reduction and soil-air exchange processes, with important implications for risk assessment and management of industrial Hg-contaminated soils.
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•Soils adjacent to chemical factories show pronounced emission potential of legacy Hg.•Hg pollution selects unique Hg-reducing bacteria in industry-impacted soils.•The merA abundance increases along Hg gradients in industry-impacted soils.•Labile carbon inputs boost microbial contribution to Hg(0) volatilization.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•TTC loaded nanosystems including PLA NPs, SLNs, and NLCs were constructed.•TTC NLCs exhibited the most prominent in vivo efficiency in analgesic time and pain control.•TTC NLCs is ...the promising system for the long-term anesthesia.
Local anesthetics (LAs) are drugs that promote the reversible blocking of neural transmission by inhibiting the excitation conduction process in peripheral nerves. Tetracaine (TTC) is one of the most common topical anesthetics used in general practice and was applied to provide long-term anesthesia. In this research, poly(L-lactide) nanoparticles (PLA NPs), solid lipid nanoparticles (SLNs), and nanostructured lipid carriers (NLCs) were utilized to construct TTC loaded nanosystems. The mean sizes, drug loading efficiency, cytotoxicity, skin permeation ability, and anesthetic analgesic effect were evaluated and compared in vitro and in vivo. The average particle sizes of blank PLA NPs, SLNs, and NLCs were 93.2, 100.9 and 110.4 nm, respectively. At all the concentrations, PLA NPs, SLNs, and NLCs showed a moderate effect on cell viability. TTC NLCs exhibited the most prominent in vivo efficiency in improving the skin permeation, analgesic time and pain control intensity. Other experiments proved that TTC PLA NPs showed advantages in serum stability and TTC SLNs illustrated the best in vitro permeation efficiency. These three kinds of nano-systems had their own superiority in some respects. Conclusion could be made that in this study, TTC NLCs is the promising system for the long-term anesthesia.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The early detection and differential diagnosis of respiratory infections increase the chances for successful control of COVID-19 disease. The nucleic acid RT-PCR test is regarded as the current ...standard for molecular diagnosis. However, the maximal specificity confirmation target ORF1ab gene is considered to be less sensitive than other targets in clinical application. In addition, recent evidence indicated that the initial missed diagnosis of asymptomatic patients with SARS-CoV-2 and discharged patients with "re-examination positive" might be due to low viral load, and the ability of rapid mutation of SARS-CoV-2 also increases the rate of false-negative results. Moreover, the mixed sample nucleic acid detection is helpful in seeking out the early community transmission of SARS-CoV-2 rapidly, but the detection kit needs ultra-high detection sensitivity. Herein, the lowest detection concentration of different nucleic acid detection kits was evaluated and compared to provide direct evidence for the selection of kits for mixed sample detection or make recommendations for the selection of validation kit, which is of great significance for the prevention and control of the current epidemic and the discharge criteria of low viral load patients.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
The high-strain dynamic test method possesses the attributes of speed, efficiency, and environmentally-friendly, low-carbon characteristics. To study the reliability of the high-strain ...dynamic test method in detecting the bearing capacity of pile foundation in permafrost regions, 4 test piles, each with a length of 15 m and a diameter of 1.0 m, were poured based on the actual bridge construction project in the permafrost region of Daxing'an Mountains in China. Based on the temperature data between the piles and soil, the refreezing state of the pile foundation was comprehensively judged. Subsequently, the static method was employed to assess the friction resistance values and single pile bearing capacity of each soil layer on the pile side under different freezing states before and after the pile foundation refreezing. Building upon these findings, the restrictive parameters for soil elastic limit
$$q_{(i)}$$
q
(
i
)
, soil resistance
$$R_{U} (i)$$
R
U
(
i
)
and other parameters in the pile-soil model of high-strain dynamic test method are clarified. The test and analysis results indicate that under the condition that the ground temperature of frozen soil is about − 1.9 °C, the pile-soil refreezing takes about 120 days, and the pile-soil refreezing is a slow process; In CAPWAPC calculation program, after the values of soil parameters were constrained by the results of static-load test, the calculated curve is in satisfactory agreement with the measured curve, and the parameters of the pile-soil model are reliable, which can be used for the rapid detection of the ultimate bearing capacity of piles in permafrost regions; In the process of pile-soil refreezing, the change of temperature field affects the freezing strength between pile and soil, the process of pile-soil refreezing is positively correlated with the increase of pile foundation bearing capacity.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Osteoporosis and cardiovascular diseases (CVDs) are 2 major public health problems. Osteoporosis and CVDs may be linked but the association between lipid profile and osteoporosis is still ...controversial. The purpose of this study was to examine the associations of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) with osteoporosis.
Using inpatients' and outpatients' electronic medical records (EMR) and dual X-ray absorptiometry (DXA) database stored at The Second Hospital of Jilin University, we included 481 individuals with complete and valid lipid and bone mineral density (BMD) data in 2017. Serum samples were used to measure TC, LDL-C, HDL-C and TG. Femoral neck and total hip BMD were measured by DXA; osteoporosis was defined as femoral neck or total hip T-score ≤ -2.5. Multivariable logistic regression models were used to test the associations of TC, LDL-C, HDL-C and TG with osteoporosis.
The mean age for included individuals was 62.7 years (SD = 8.6 years); 60.1 % of them were female. Each standard deviation (SD) increase in TC (Odds Ratio OR: 1.48; 95 % Confidence Interval CI: 1.06-2.07) and TG (OR: 1.67; 95 % CI: 1.16-2.39) were associated with increased risk of osteoporosis; LDL-C and HDL-C levels were not associated with osteoporosis. Age, sex and body mass index (BMI) did not interact with the relationships of TC and TG with osteoporosis (all P > 0.10).
Higher TC and TG levels were associated with greater risk of osteoporosis in this cross-sectional study.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
The aim of this study was to explore the relationship between serum uric acid (SUA) and the triglyceride-glucose (TyG) index, which is a more effective indicator of insulin resistance. The ...study participants included 1700 children and adolescents with short stature who were recruited at the Affiliated Hospital of Jining Medical University in China between March 2013 and April 2021. A positive association between SUA levels and the TyG index was detected by univariate analysis (
p
< 0.001). Furthermore, a nonlinear relationship was detected between SUA and the TyG index, whose point was 6.55 mg/dL. There was a positive association between SUA and the TyG index when the SUA level was greater than 6.55 mg/dL (β 0.17, 95% CI: 0.07, 0.27;
P
< 0.001). However, we did not observe a significant relationship between SUA and the TyG index when the SUA level was less than 6.55 mg/dL (β 0.02, 95% CI: − 0.01, 0.05;
P
= 0.091). In addition, a stratified analysis was performed to appraise changes in this relationship for different sexes. The relationship between SUA and the TyG index in males and females is consistent with that in the general population, showing a nonlinear relationship. However, the inflection points of SUA level were significantly higher in males than in females, and the inflection points were approximately 6.72 and 5.88 mg/dL, respectively. This study revealed a nonlinear relationship between SUA and the TyG index in children with short stature. The nonlinear relationship remained in gender stratification analysis, but the inflection point of SUA level was higher in men. Further studies are needed to establish a causal relationship between SUA levels and the TyG index in children with short stature.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Sorafenib is the unique recommended molecular-targeted drug for advanced hepatocellular carcinoma, but its clinical use is limited due to cardiotoxicity. As sorafenib is an efficient ferroptosis ...inducer, the pathogenesis of this compound to ferroptosis-mediated cardiotoxicity is worth further study. Mice were administered 30 mg/kg sorafenib intraperitoneally for 2 weeks to induce cardiac dysfunction and Ferrostatin-1 (Fer-1) was used to reduce ferroptosis of mice with sorafenib-induced cardiotoxicity. Sorafenib reduced levels of anti-ferroptotic markers involving Slc7a11 and glutathione peroxidase 4 (GPX4), increased malonaldehyde malondialdehyde, apart from causing obvious mitochondria damage, which was alleviated by Fer-1.
In vitro
experiments showed that Fer-1 inhibited lipid peroxidation and injury of H9c2 cardiomyoblasts induced by sorafenib. Both
in vitro
and
in vivo
experiments confirmed that the expression of Slc7a11 was down regulated in sorafenib-induced cardiotoxicity, which can be partially prevented by treatment with Fer-1. Overexpression of Slc7a11 protected cells from ferroptosis, while knock-down of Slc7a11 made cardiomyoblasts sensitive to ferroptosis caused by sorafenib. Finally, by comparing data from the GEO database, we found that the expression of ATF3 was significantly increased in sorafenib treated human cardiomyocytes. In addition, we demonstrated that ATF3 suppressed Slc7a11 expression and promoted ferroptosis. Based on these findings, we concluded that ATF3/Slc7a11 mediated ferroptosis is one of the key mechanisms leading to sorafenib-induced cardiotoxicity. Targeting ferroptosis may be a novel therapeutic approach for preventing sorafenib-induced cardiotoxicity in the future.
Visible-infrared person re-identification (VIPR) has great potential for intelligent transportation systems for constructing smart cities, but it is challenging to utilize due to the huge modal ...discrepancy between visible and infrared images. Although visible and infrared data can appear to be two domains, VIPR is not identical to domain adaptation as it can massively eliminate modal discrepancies. Because VIPR has complete identity information on both visible and infrared modalities, once the domain adaption is overemphasized, the discriminative appearance information on the visible and infrared domains would drain. For that, we propose a novel margin-based modal adaptive learning (MMAL) method for VIPR in this paper. On each domain, we apply triplet and label smoothing cross-entropy functions to learn appearance-discriminative features. Between the two domains, we design a simple yet effective marginal maximum mean discrepancy (M3D) loss function to avoid an excessive suppression of modal discrepancies to protect the features' discriminative ability on each domain. As a result, our MMAL method could learn modal-invariant yet appearance-discriminative features for improving VIPR. The experimental results show that our MMAL method acquires state-of-the-art VIPR performance, e.g., on the RegDB dataset in the visible-to-infrared retrieval mode, the rank-1 accuracy is 93.24% and the mean average precision is 83.77%.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Most pharmaceutical formulation developments are complex and ideal formulations are generally obtained after extensive experimentation. Machine learning is increasingly advancing many aspects in ...modern society and has achieved significant success in multiple subjects. Current research demonstrated that machine learning can be adopted to build up high-accurate predictive models in drugs/cyclodextrins (CDs) systems. Molecular descriptors of compounds and experimental conditions were employed as inputs, while complexation free energy as outputs. Results showed that the light gradient boosting machine provided significantly improved predictive performance over random forest and deep learning. The mean absolute error was 1.38 kJ/mol and squared correlation coefficient was 0.86. The evaluation of relative importance of molecular descriptors further demonstrated the key factors affecting molecular interactions in drugs/CD systems. In the specific ketoprofen–CD systems, machine learning model showed better predictive performance than molecular modeling calculation, while molecular simulation could provide structural, dynamic and energetic information. The integration of machine learning and molecular simulation could produce synergistic effect for interpreting and predicting pharmaceutical formulations. In conclusion, the developed predictive models were able to quickly and accurately predict the solubilizing capacity of CD systems. Current research has taken an important step toward the application of machine learning in pharmaceutical formulation design.
Current research presented an alternative to traditionally trial-and-error experimentation for drug–CD formulation development. It revealed that the integration of experimental determinations, molecular modeling calculation and data-driven machine learning techniques could provide a new solution for highly efficient and accurate formulation development in the future. Display omitted
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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