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BackgroundIndirect cardiomyocyte damage-related hyperinflammatory response is one of the key mechanisms in COVID-19-induced fulminant myocarditis. In addition to the clinical benefit of using cytokines absorption hemofiltration, the effectiveness of instituting veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support for cardiac compromise has been reported. However, current literature enunciates a paucity of available data on the effectiveness of these novel modalities.Case PresentationWe reported a 9-year-old boy with recurrent COVID-19 infection-causing fulminant myocarditis, who was treated successfully by using novel modalities of oXiris® hemofilter continuous venovenous hemofiltration (CVVH) and VA-ECMO. The patient made a full recovery without any sequelae.ConclusionWe conclude that the novel highly-absorptive hemofilter CVVH and VA-ECMO may be effective treatment modalities in managing SARS-CoV-2-induced fulminant myocarditis. Our report highlights the need for further well-designed investigations to confirm this extrapolation.

Introduction Avascular necrosis of the femoral head (ANFH) is a phenomenon vascular supply disruption lead to death of bone cells around the femoral head. The disease is a severe health issue all over the world. Within 2 years about 80 % to 85 % of symptomatic cases will result in collapse of the femoral head. Recovery of hip function after total hip arthroplasty (THA) may be influenced by many factors that vary among different racial/ethnic groups. Most findings in this field have been from Western developed nations, and not much information from developing Asian countries is available. This study aimed to determine the six-month functional outcome and patient–related factors that predict functional recovery in patients with avascular necrosis of the femoral head (ANFH) undertaking total hip arthroplasty (THA). Methods Between January 2022 and December 2023 there were 143 patients participating in this prospective study. Demographic, medical history and clinical findings were collected from their medical records. The six‑month functional outcome was evaluated using the Harris hip score (HHS). The mean age of the participants was 55.90 ± 11.49 years, and the majority (86.7 %) were male. Most patients had excellent (43.4 %) or good outcome (51.7 %). Discussion Our study had some limitations: the length of the follow-up after surgery is short (6 months), that hospital-related factors like the type and volume of the hospital have not been analyzed. Nonetheless, previous observations suggest that most of the improvement in physical function occurs during the first six months following surgery and remains the same for a long time. However, our sample has typical demographic and clinical characteristics of patients with THA for ANFH, suggesting that determinants of the 6-month functional outcome in the current study could apply to other patients undergoing this surgery. Results The determinants of excellent outcome were a higher preoperative HHS (odds ratio (OR): 4.369, 95 % confidence interval (CI) =1.854 – 10.299; p < 0.001) and absence of comorbidity (OR: 2.440, 95 % CI = 1.071 – 5.557, p = 0.034). No demographic (age, gender, body mass index), medical history (using of steroids, alcohol consumption or smoking), or any other clinical parameter (stage or side of the affected hip, time until surgery) had a significant influence on functional outcome. Conclusion Earlier surgery during functional decline and better management of comorbidity may help improve THA outcomes for patients with avascular necrosis of the femoral head.

Introduction To investigate clinical, laboratory findings and identify pre-operative variables associated with increased waiting time to surgery (WTS) and length of hospital stay (LOS) among hip fracture patients. Material and methods This prospective study is conducted between April 2020 and April 2021. Patients’ information was collected from medical records and subjected to analysis using a univariate and multivariate model. Results The study included 118 patients in a mean age of 79.5 years, and the majority were female (68.6 %). Overall, 66.9 % of the patients had at least one comorbidity. Almost all (95.8 %) patients had fractures due to a low-impact fall and an intertrochanteric fracture was the predominant type (61.9 %). The most abnormal laboratory findings at admission were elevated C-reactive protein (CRP) levels (94.9 %) followed by decreased mineral density (85.1 %), anaemia (81.4 %), electrolyte abnormalities (69.4 %) and hypoalbuminemia (66.1 %). The mean of WTS among 115 patients undergoing surgical treatment was 52.1 ± 47 hours and no patient-related factors had a significant influence on WTS. The mean hospital LOS was 15.9 ± 4.7 days. Marked elevation of CRP level (OR = 3.317, p = 0.042), type of surgery (OR = 4.413, p = 0.005) and WTS (OR = 4.602, p = 0.001) were independent predictors of prolonged LOS. Conclusion Most patients with hip fractures are elderly and suffer from many comorbidities and laboratory abnormalities. No patient-related factors are predictors of WTS but the elevation of CRP, type of surgery and time of waiting to surgery influence the LOS.

Abstract In this paper we investigate how the modularity of model and real-world social networks affect their robustness and the efficacy of node attack (removal) strategies based on node degree (ID) and node betweenness (IB). We build Barabasi–Albert model networks with different modularity by a new ad hoc algorithm that rewire links forming networks with community structure. We traced the network robustness using the largest connected component (LCC). We find that when model networks present absent or low modular structure ID strategy is more effective than IB to decrease the LCC. Conversely, in the case the model network present higher modularity, the IB strategy becomes the most effective to fragment the LCC. In addition, networks with higher modularity present a signature of a 1st order percolation transition and a decrease of the LCC with one or several abrupt changes when nodes are removed, for both strategies; differently, networks with non-modular structure or low modularity show a 2nd order percolation transition networks when nodes are removed. Last, we investigated how the modularity of the network structure evaluated by the modularity indicator (Q) affect the network robustness and the efficacy of the attack strategies in 12 real-world social networks. We found that the modularity Q is negatively correlated with the robustness of the real-world social networks for both the node attack strategies, especially for the IB strategy (p-value

Abstract This work aims to test the effectiveness of newly developed DFT-1/2 functional in calculating the electronic and optical properties of inorganic lead halide perovskites CsPbBr3. Herein, from DFT-1/2 we have obtained the direct band gap of 2.36 eV and 3.82 eV for orthorhombic bulk and 001-surface, respectively. The calculated energy band gap is in qualitative agreement with the experimental findings. The bandgap of ultra-thin film of CsPbBr3 is found to be 3.82 eV, which is more than the expected range 1.23-3.10 eV. However, we have found that the bandgap can be reduced by increasing the surface thickness. Thus, the system under investigation looks promising for optoelectronic and photocatalysis applications, due to the bandgap matching and high optical absorption in UV–Vis (Ultra violet and visible spectrum) range of electro-magnetic(em) radiation.

This study presents the source apportionment of PM2.5 performed by positive matrix factorization (PMF) on data presented here which were collected at urban (Institute of Atmospheric Physics – IAP) and rural (Pinggu – PG) sites in Beijing as part of the Atmospheric Pollution and Human Health in a Chinese megacity (APHH-Beijing) field campaigns. The campaigns were carried out from 9 November to 11 December 2016 and from 22 May to 24 June 2017. The PMF analysis included both organic and inorganic species, and a seven-factor output provided the most reasonable solution for the PM2.5 source apportionment. These factors are interpreted as traffic emissions, biomass burning, road dust, soil dust, coal combustion, oil combustion, and secondary inorganics. Major contributors to PM2.5 mass were secondary inorganics (IAP: 22 %; PG: 24 %), biomass burning (IAP: 36 %; PG: 30 %), and coal combustion (IAP: 20 %; PG: 21 %) sources during the winter period at both sites. Secondary inorganics (48 %), road dust (20 %), and coal combustion (17 %) showed the highest contribution during summer at PG, while PM2.5 particles were mainly composed of soil dust (35 %) and secondary inorganics (40 %) at IAP. Despite this, factors that were resolved based on metal signatures were not fully resolved and indicate a mixing of two or more sources. PMF results were also compared with sources resolved from another receptor model (i.e. chemical mass balance – CMB) and PMF performed on other measurements (i.e. online and offline aerosol mass spectrometry, AMS) and showed good agreement for some but not all sources. The biomass burning factor in PMF may contain aged aerosols as a good correlation was observed between biomass burning and oxygenated fractions (r2= 0.6–0.7) from AMS. The PMF failed to resolve some sources identified by the CMB and AMS and appears to overestimate the dust sources. A comparison with earlier PMF source apportionment studies from the Beijing area highlights the very divergent findings from application of this method.

Abstract Hanoi, Vietnam, is usually ranked as one of the most polluted capital cities in terms of air quality, particularly PM2.5. However, there has not been enough data to determine the main source of this pollution. In this study, we utilized the rare opportunity of the COVID-19 social distancing to assess the contribution of traffic emission to PM2.5 and CO levels when traffic volume was reduced significantly in Hanoi. Hourly PM2.5 and CO concentrations were measured from nine urban and traffic monitoring stations during pre-, soft, hard, and post-social distancing periods. As a result, we observed large reductions in both PM2.5 and CO levels during social distancing periods. PM2.5 concentrations were 14–18% lower during the social distancing than before this period, while CO concentrations had a more considerable drop by 28–41%. It is known that meteorological conditions can have significant effects on the ambient levels of air pollutants. To overcome this challenge, weather normalized concentrations of those pollutants were estimated using the random forest model, a machine learning technique. The normalized weather concentrations showed smaller reductions by 7–10% for PM2.5 and 5–11% for CO, indicating the presence of favorable weather conditions for better air quality during the social distancing period. In further analysis, the apparent improvement of air quality in Hanoi during the social distancing period was in line with reducing traffic emissions while emissions from coal-fired power plants remained relatively stable.

Fine particles were sampled from 9 November to 11 December 2016 and 22 May to 24 June 2017 as part of the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) field campaigns in urban Beijing, China. Inorganic ions, trace elements, organic carbon (OC), elemental carbon (EC), and organic compounds, including biomarkers, hopanes, polycyclic aromatic hydrocarbons (PAHs), n-alkanes, and fatty acids, were determined for source apportionment in this study. Carbonaceous components contributed on average 47.2 % and 35.2 % of total reconstructed PM2.5 during the winter and summer campaigns, respectively. Secondary inorganic ions (sulfate, nitrate, ammonium; SNA) accounted for 35.0 % and 45.2 % of total PM2.5 in winter and summer. Other components including inorganic ions (K+, Na+, Cl−), geological minerals, and trace metals only contributed 13.2 % and 12.4 % of PM2.5 during the winter and summer campaigns. Fine OC was explained by seven primary sources (industrial and residential coal burning, biomass burning, gasoline and diesel vehicles, cooking, and vegetative detritus) based on a chemical mass balance (CMB) receptor model. It explained an average of 75.7 % and 56.1 % of fine OC in winter and summer, respectively. Other (unexplained) OC was compared with the secondary OC (SOC) estimated by the EC-tracer method, with correlation coefficients (R2) of 0.58 and 0.73 and slopes of 1.16 and 0.80 in winter and summer, respectively. This suggests that the unexplained OC by the CMB model was mostly associated with SOC. PM2.5 apportioned by the CMB model showed that the SNA and secondary organic matter were the two highest contributors to PM2.5. After these, coal combustion and biomass burning were also significant sources of PM2.5 in winter. The CMB results were also compared with results from the positive matrix factorization (PMF) analysis of co-located aerosol mass spectrometer (AMS) data. The CMB model was found to resolve more primary organic aerosol (OA) sources than AMS-PMF, but the latter could apportion secondary OA sources. The AMS-PMF results for major components, such as coal combustion OC and oxidized OC, correlated well with the results from the CMB model. However, discrepancies and poor agreements were found for other OC sources, such as biomass burning and cooking, some of which were not identified in AMS-PMF factors.

Carbonaceous aerosol is a dominant component of fine particles in Beijing. However, it is challenging to apportion its sources. Here, we applied a newly developed method which combined radiocarbon (14C) with organic tracers to apportion the sources of fine carbonaceous particles at an urban (IAP) and a rural (PG) site of Beijing. PM2.5 filter samples (24 h) were collected at both sites from 10 November to 11 December 2016 and from 22 May to 24 June 2017. 14C was determined in 25 aerosol samples (13 at IAP and 12 at PG) representing low pollution to haze conditions. Biomass burning tracers (levoglucosan, mannosan, and galactosan) in the samples were also determined using gas chromatography–mass spectrometry (GC-MS). Higher contributions of fossil-derived OC (OCf) were found at the urban site. The OCf / OC ratio decreased in the summer samples (IAP: 67.8 ± 4.0 % in winter and 54.2 ± 11.7 % in summer; PG: 59.3 ± 5.7 % in winter and 50.0 ± 9.0 % in summer) due to less consumption of coal in the warm season. A novel extended Gelencsér (EG) method incorporating the 14C and organic tracer data was developed to estimate the fossil and non-fossil sources of primary and secondary OC (POC and SOC). It showed that fossil-derived POC was the largest contributor to OC (35.8 ± 10.5 % and 34.1 ± 8.7 % in wintertime for IAP and PG, 28.9 ± 7.4 % and 29.1 ± 9.4 % in summer), regardless of season. SOC contributed 50.0 ± 12.3 % and 47.2 ± 15.5 % at IAP and 42.0 ± 11.7 % and 43.0 ± 13.4 % at PG in the winter and summer sampling periods, respectively, within which the fossil-derived SOC was predominant and contributed more in winter. The non-fossil fractions of SOC increased in summer due to a larger biogenic component. Concentrations of biomass burning OC (OCbb) are resolved by the extended Gelencsér method, with average contributions (to total OC) of 10.6 ± 1.7 % and 10.4 ± 1.5 % in winter at IAP and PG and 6.5 ± 5.2 % and 17.9 ± 3.5 % in summer, respectively. Correlations of water-insoluble OC (WINSOC) and water-soluble OC (WSOC) with POC and SOC showed that although WINSOC was the major contributor to POC, a non-negligible fraction of WINSOC was found in SOC for both fossil and non-fossil sources, especially during winter. In summer, a greater proportion of WSOC from non-fossil sources was found in SOC. Comparisons of the source apportionment results with those obtained from a chemical mass balance model were generally good, except for the cooking aerosol.

Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µg m−3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.

Abstract Knowledge of hygroscopic properties is essential to prediction of the role of aerosol in cloud formation and lung deposition. Our objective was to introduce a new approach to classify and predict the hygroscopic growth factors (Gfs) of specific atmospheric sub-micrometre particle types in a mixed aerosol based on measurements of the ensemble hygroscopic growth factors and particle number size distribution (PNSD). Based on a non-linear regression model between aerosol source contributions from PMF applied to the PNSD data set and the measured Gf values (at 90% relative humidity) of ambient aerosols, the estimated mean Gf values for secondary inorganic, mixed secondary, nucleation, urban background, fresh, and aged traffic-generated particle classes at a diameter of 110 nm were found to be 1.51, 1.34, 1.12, 1.33, 1.09 and 1.10, respectively. It is found possible to impute (fill) missing HTDMA data sets using a Random Forest regression on PNSD and meteorological conditions.

This study investigates the chemical composition of PM2.5 collected at a central location in Beijing, China, during winter 2016 and summer 2017. The samples were characterised using direct-infusion negative-nano-electrospray-ionisation ultrahigh-resolution mass spectrometry to elucidate the composition and the potential primary and secondary sources of the organic fraction. The samples from the two seasons were compared with those from a road-tunnel site and an urban background site in Birmingham, UK, analysed in the course of an earlier study using the same method. There were strong differences in aerosol particle composition between the seasons, particularly regarding (poly-)aromatic compounds, which were strongly enhanced in winter, likely due to increased fossil fuel and biomass burning for heating. In addition to the seasonal differences, compositional differences between high- and low-pollution conditions were observed, with the contribution of sulfur-containing organic compounds strongly enhanced under high-pollution conditions. There was a correlation of the number of sulfur-containing molecular formulae with the concentration of particulate sulfate, consistent with a particle-phase formation process.

Depolymerization of lignin is an important step to obtain a lignin monomer for the synthesis of functional chemicals. In the context of more lignin produced from biomass and pulp industry, converting real lignin with low purity is still required more studies. In this study, the influence of solvent composition and reaction parameters such as binary solvents ratio, time, and temperature, the solvent-to-lignin ratio on the depolymerization of rice straw lignin was investigated carefully. Essential lignin-degraded products including liquid product (LP), char (solid), and gas were obtained, and their yields were directly influenced by reaction conditions. Results show that the maximum lignin conversion rate of 92% and LP yield of 66% was under the condition of 275°C, 30 min, 75 : 1 (mL solvent/1 g lignin), and ethanol 50%. Gas chromatography-mass spectroscopy (GC-MS) analysis was used for the analysis of the depolymerization products and identified 11 compounds which are mainly phenolic compounds such as 2-ethylphenol, 3-ethylphenol, phenol, methyl 2,4,6-trimethylbenzoate. The structure changes of LP and char in various conditions were analyzed using Fourier-transform infrared (FTIR).

Organic matter is a major component of PM2.5 in megacities. In order to understand the detailed characteristics of organic compounds (≥ C6) at a molecular level on non-haze and haze days, we determined more than 300 organic compounds in the PM2.5 from an urban area of Beijing collected in November–December 2016 using two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-ToF-MS). The identified organic compounds have been classified into groups, and quantitative methods were used to calculate their concentrations. Primary emission sources make significant contributions to the atmospheric organic compounds, and six groups (including n-alkanes, polycyclic aromatic hydrocarbons – PAHs, levoglucosan, branched alkanes, n-alkenes and alkyl-benzenes) account for 66 % of total identified organic compound mass. In addition, PAHs and oxygenated PAHs (O-PAHs) were abundant amongst the atmospheric organic compounds on both haze and non-haze days. The most abundant hydrocarbon groups were observed with a carbon atom range of C19–C28. In addition, the total concentration of unidentified compounds present in the chromatogram was estimated in the present study. The total identified compounds account for approximately 47 % of total organic compounds (≥ C6) in the chromatogram on both the non-haze and haze days. The total mass concentrations of organic compounds (≥ C6) in the chromatogram were 4.0 and 7.4 µg m−3 on the non-haze and haze days, respectively, accounting for 26.4 % and 18.5 % of organic matter, respectively, on those days estimated from the total organic carbon concentration. Ratios of individual compound concentrations between haze and non-haze days do not give a clear indication of the degree of oxidation, but the overall distribution of organic compounds in the chromatogram provides strong evidence that the organic aerosol is less GC volatile and hence more highly oxidized on haze days.

Abstract The development of sex-specific genetic assays in a species provides both a method for identifying the system of sex determination and a valuable tool to address questions of conservation and management importance. In this study, we focused on the identification of single nucleotide polymorphisms (SNPs) that differentiate genetic sex in burbot Lota lota. Burbot are the only true freshwater representative of the cod family and a species of conservation and management importance throughout Eurasia and North America. To identify sex-specific SNPs, we utilized restriction site-associated DNA sequencing (RADseq) to interrogate thousands of SNPs in burbot samples of known phenotypic sex. We discovered 170,569 biallelic SNPs, none of which fit the pattern expected under female heterogamety. However, we identified 22 SNPs that fit the pattern expected under male heterogamety (males heterozygous XY, females fixed XX) and, from these, developed two genetic assays that robustly (~ 97% genotyping success) and accurately (> 99% correct) sexed burbot samples. These sex-specific genetic assays will benefit growing conservation aquaculture programs for this species and allow future assessments of sex-specific migration, growth, and mortality.