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8% of total MP) and ⁎C-PVC (Ø 12.0% of total MP) were found, with the latter presumably originating from paint used for road markings. check details Truck tire tread, C-PE, C-PP, C-PS, C-PMMA, and C-PC were also frequently found, but in much lower abundance (Ø less then 6.4% of total MP). Differences in contamination levels could be plausibly related to the sampling locations.Nitrogen fertilization (NF) is one of the common practices to increase crop production worldwide over the past several decades. Nevertheless, unreasonable NF results in massive greenhouse gas (GHG) emissions, leading to climate change and global warming. Many studies have already reported the impact of NF on crop yield, global warming potential (GWP) and greenhouse gas intensity (GHGI), but the studies were limited to only some parameters. In this study, a total of 174 studies from 16 countries were collected and then a regression analysis was conducted to obtain the appropriate N fertilization rates that enhance crop yield while reducing GWP and GHGI. After that, a meta-analysis was performed to evaluate the effects of NF on crop yield, GHGI, GWP and GHG emissions and identify NF management strategies that benefit crop yield and maintain GWP. The results showed that the suitable N fertilization rate was 180, 150, 130 and 200 kg ha-1 for wheat, maize, rice and vegetables or industrial crops, respectively. Overall, NF resulted in positive effect size in crop yield (0.56) and negative effect size in GHGI (-0.14) compared to NNF. GWP showed positive effect size (0.37) due to an increase in N2O emissions (0.91) relative to NNF, which is higher than the increase of CH4 emissions (0.01) and CO2 emissions (0.22). It was recommended that split and banded application of urea or urea plus manure is employed for cereals (especially wheat) in the arid and semi-arid regions with medium-textured and neutral or alkaline soil.Rice is an important food crop that is susceptible to arsenic (As) contamination under paddy soil conditions depending on As uptake characteristics of the rice genotypes. Here we unveiled the significance of eighteen (fine and coarse) rice genotypes against As accumulation/tolerance, morphological and physiological response, and antioxidant enzymes-enabled defense pathways. Arsenic significantly affected rice plant morphological and physiological attributes, with relatively more impacts on fine compared to coarse genotypes. Grain, shoot, and root As uptake were lower in fine genotypes (0.002, 0.020, and 0.032 mg pot-1 DW, respectively) than that of coarse (0.031, 0.60, and 1.2 mg pot-1 DW, respectively). Various biochemical (pigment contents, hydrogen peroxide, lipid peroxidation) and defense (antioxidant enzymes) plant parameters indicated that the fine genotypes, notably Kainat and Basmati-385, possessed the highest As tolerance. Arsenic-induced risk indices exhibited greater hazard quotient (up to 1.47) and carcinogenic risk (up to 0.0066) for coarse genotypes compared to the fine ones, with the greatest risk for KSK-282. This study elaborates the pivotal role of genotypic variation among rice plants in As accumulation, which is crucial for mitigating the associated human health risk. Further research is required on molecular aspects, e.g., genetic sequencing, to examine rice genotypes variation in defense mechanisms to As contamination.The article by Andrew Huxley in this journal in 1957, "Muscle Structure and theories of Contraction" is much more than a standard review of a field. It is itself a major theoretical modelling achievement the first mathematical model of the contractile process in skeletal muscle. That model was based on careful microscopic analysis of the striation patterns in skeletal muscles. Cited 4456 times, it holds the record for this journal.

Lipids are involved in the interaction between viral infection and the host metabolic and immunological responses. Several studies comparing the lipidome of COVID-19-positive hospitalized patients vs. healthy subjects have already been reported. It is largely unknown, however, whether these differences are specific to this disease. The present study compared the lipidomic signature of hospitalized COVID-19-positive patients with that of healthy subjects, as well as with COVID-19-negative patients hospitalized for other infectious/inflammatory diseases.

We analyzed the lipidomic signature of 126 COVID-19-positive patients, 45 COVID-19-negative patients hospitalized with other infectious/inflammatory diseases and 50 healthy volunteers. A semi-targeted lipidomics analysis was performed using liquid chromatography coupled to mass spectrometry. Two-hundred and eighty-three lipid species were identified and quantified. Results were interpreted by machine learning tools.

We identified acylcarnitines, lysophosps study shows that COVID-19 infection shares many lipid alterations with other infectious/inflammatory diseases, and which differentiate them from the healthy population. The most notable alterations were observed in oxylipins, while alterations in bile acids and glycerophospholipis best distinguished between COVID-19-positive and COVID-19-negative patients. Our results highlight the value of integrating lipidomics with machine learning algorithms to explore the pathophysiology of COVID-19 and, consequently, improve clinical decision making.

Anesthesia assistance is commonly used for ERCP. General anesthesia (GA) may provide greater airway protection but may lead to hypotension. We aimed to compare GA versus sedation without planned intubation (SWPI) on the incidence of hypoxemia and hypotension. We also explored risk factors for conversion from SWPI to GA.

This observational study used data from the Multicenter Perioperative Outcomes Group. Adults with American Society of Anesthesiologists physical status class I to IV undergoing ERCP between 2006 and 2019 were included. We compared GA and SWPI on incidence of hypoxemia (oxygen saturation<90% for≥3 minutes) and hypotension (mean arterial pressure<65mm Hg for≥5 minutes) using joint hypothesis testing. The association between anesthetic approach and outcomes was assessed using logistic regression. The noninferiority delta for hypoxemia and hypotension was an odds ratio of 1.20. One approach was deemed better if it was noninferior on both outcomes and superior on at least 1 outcome. To explore risk factors associated with conversion from SWPI to GA, we constructed a logistic regression model.

Among 61,735 cases from 42 institutions, 38,830 (63%) received GA and 22,905 (37%) received SWPI. The GA group had 1.27 times (97.5% confidence interval, 1.19-1.35) higher odds of hypotension but .71 times (97.5% confidence interval, .63-.80) lower odds of hypoxemia. Neither group was noninferior to the other on both outcomes. Conversion from SWPI to GA occurred in 6.5% of cases and was associated with baseline comorbidities and higher institutional procedure volume.

GA for ERCP was associated with less hypoxemia, whereas SWPI was associated with less hypotension. Neither approach was better on the combined incidence of hypotension and hypoxemia.

GA for ERCP was associated with less hypoxemia, whereas SWPI was associated with less hypotension. Neither approach was better on the combined incidence of hypotension and hypoxemia.

Disposable gastroscopes have recently been developed to eliminate the risk of infection transmission from contaminated reusable gastroscopes. We compared the performance of disposable and reusable gastroscopes in patients undergoing gastroscopy.

Patients requiring gastroscopy were randomized to either the disposable or reusable digital gastroscope group. The primary endpoint was the success rate of photographing customary anatomic sites, with a noninferiority margin of -8%. Secondary endpoints were technical performance factors such as gastroscope imaging quality, maneuverability, gastroscopy completion rate, device failure/defect rate, operating time, and safety. Data were analyzed using the Newcombe-Wilson score method and Fisher exact 2-tailed t test.

Of 110 patients, 55 were treated using disposable gastroscopes and 55 using reusable gastroscopes. The success rate for capturing images of customary anatomic sites was 100% in both groups. The average imaging quality score was significantly lower (37.02 ± 3.09 vs 39.47 ± 1.92, P< .001) and the operating time significantly longer (P< .001) in the disposable gastroscope group. No significant differences in maneuverability, gastroscopy completion rate, device failure/defect rate, operating time, or safety were found between the 2 groups.

Given the overall safety profile and similar technical performance, disposable gastroscopes represent an alternative to reusable gastroscopes for routine examination, bedside first aid, and some certain circumstances.

Given the overall safety profile and similar technical performance, disposable gastroscopes represent an alternative to reusable gastroscopes for routine examination, bedside first aid, and some certain circumstances.New emerging nano-scale technologies like hydrogenated noncrystalline-silicon thin-film transistors (TFTs) and memristors, fabricated at low temperatures and over large areas, permit low-cost processing and 3D integration with CMOS cores. Here, we aim to propose a mathematical model which explains the memory-TFT threshold voltage shift due to the gate bias instability. Then, based on this mathematical approach, we propose a novel learning synapse composed of a voltage/flux driven memristor in parallel with a common-source memory-TFT with a memristive load. The proposed device realizes the triplet-based spike-timing-dependent plasticity rule (TSTDP) as a more realistic form of learning than the purely pair-based STDP (PSTDP). PSTDP is a synaptic learning rule which utilizes a constant-frequency pairing protocol to induce synaptic weight change and cannot explain the modification due to the frequency changes of spike pairs, and also the outcomes of triplet and quadruplet experiments. However, TSTDP improves the learning capabilities of the conventional PSTDP and reproduces the results of more electrophysiological experiments. In this paper, we apply various spike patterns like different-frequency and different-timing spike pairs, spike triplets, and quadruplets to the proposed device. Our simulations confirm a close match with the experimental data sets of real biological synapses.Alzheimer's disease (AD) is one of the most common dementia, and its pathogenesis has not been clarified. The failure of amyloid targeted therapy has led us to rethink the pathogenesis of AD. There is growing evidence that complex diseases usually involve the impairment of multiple biological functions, rather than focus on several single genes. Protein-protein interaction network (PPIN) has been recognized as an important tool for identifying and predicting disease biomarkers. It is a great challenge to design network-based classification method for identifying effective, stable and interpretable biomarkers to distinguish the disease phenotype based on gene expression profile data. In this study, we used graph Laplacian regularization method to introduce topology information of PPIN, which can reveal the damaged networks involved in disease from heterogeneous gene expression profile data and identify disease-related biomarkers. The results in three AD datasets showed that the biomarkers identified by our method can not only distinguish the sample categories more accurately, but also help researchers understand the biological meaning behind complex diseases.