SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study.

Background: The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection. Methods: In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥ 1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time. Results: Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels. Conclusions: Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

Pan-cancer analysis of the role of α2C-adrenergic receptor (ADRA2C) in human tumors and validation in glioblastoma multiforme models.

Background: Several studies have reported the relationship between α2C-adrenergic receptor (ADRA2C) and both neoplastic and non-neoplastic diseases. However, a comprehensive pan-cancer analysis is currently lacking. Methods: Utilizing the RNA sequencing (RNA-seq) datasets from The Cancer Genome Atlas (TCGA) database, the roles of ADRA2C in human pan-cancer were analyzed through a variety of bioinformatics approaches, including R programming language and single-cell sequencing data analysis, et al. Besides, cell migration assay and immunochemistry were employed to further validate the role of ADRA2C in glioblastoma multiforme (GBM) cell lines and GBM mouse model. Results: A total of 33 cancer types were involved in this study. It was revealed that the expression level of ADRA2C varied across different clinical stages in patients with breast invasive carcinoma (BRCA), esophageal adenocarcinoma (ESCA), kidney renal papillary cell carcinoma (KIRP) and lung squamous cell carcinoma (LUSC). Meanwhile, it was found that ADRA2C may play roles in prognosis of adrenocortical carcinoma (ACC), glioblastoma multiforme and lower grade glioma (GBM-LGG), and uveal melanoma (UVM). Functional enrichment analysis suggested that ADRA2C expression level was highly correlated with neuronal system-related pathways. Moreover, ADRA2C may be a promising diagnostic marker for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), GBM, GBMLGG, kidney chromophobe (KICH), and KIRP. Additionally, ADRA2C expression level was correlated with the levels of several infiltrating cells and immune checkpoint genes. Besides, the single-cell sequencing data analysis indicated that ADRA2C played a role in multiple tumor development processes in GBM, retinoblastoma (RB), and UVM. Finally, in vitro and in vivo experiments confirmed that the expression level of ADRA2C may be associated with glioma cell migration, apoptosis, and invasion. Conclusion: ADRA2C exhibited to play a notable role in several cancer types, suggesting that ADRA2C could serve as a promising biomarker or target for cancer diagnosis, prognosis, and treatment, particularly for GBM.

Effects of anions on the electrospray ionization of proteins in strong acids.

The effect of anions on the positive electrospray ionization (ESI) of proteins in different strong acids with varying pH values from 3 to 1 is studied using high-pressure ESI. Reducing the pH from ∼2 to 1 caused a drastic shift in charge state from a high-charge-state distribution (HCSD) to a narrow low-charge-state distribution (LCSD). The shift in charge state was consistent with the circular dichroism result that showed a conformational change due to the "acid-induced folding" of proteins from an unfolding state to a compact molten globule state. Acids of different anions produced noticeable differences in the average charge for HCSD and LCSD. For HCSD, the average charge was lower than the value typically observed using formic and acetic acids. As for LCSD, the average charge was lower than the "native" charge. The high abundance of acid anion that induces the protein compaction was believed to play a role in charge reduction. The effectiveness of anions to "refold" a highly unfolded protein to a compact state and the propensity to reduce the charge of HCSD for proteins appeared to follow the selectivity series of anions towards the stationary phase in ion chromatography. However, the propensity of anions to reduce the charge for LCSD follows quite an opposite trend. The presence of ammonium salt in the acidic solution was found to increase the charge of LCSD. The simple mass spectrum with a narrow distribution of charge state obtained with perchloric acid at pH 1 was demonstrated to facilitate the counting of basic sites.

Modulating amacrine cell-derived dopamine signaling promotes optic nerve regeneration and preserves visual function.

As part of the central nervous system, the optic nerve, composed of axons from retinal ganglion cells (RGCs), generally fails to regenerate on its own when injured in adult mammals. An innovative approach to promoting optic nerve regeneration involves manipulating the interactions between amacrine cells (ACs) and RGCs. Here, we identified a unique AC subtype, dopaminergic ACs (DACs), that responded early after optic nerve crush by down-regulating neuronal activity and reducing retinal dopamine (DA) release. Activating DACs or augmenting DA release with levodopa demonstrated neuroprotective effects and modestly enhanced axon regeneration. Within this context, we pinpointed the DA receptor D1 (DRD1) as a critical mediator of DAC-derived DA and showed that RGC-specific Drd1 overexpression effectively overcame subtype-specific barriers to regeneration. This strategy markedly boosted RGC survival and axon regeneration after crush and preserved vision in a glaucoma model. This study unveils the crucial role of DAC-derived DA signaling in optic nerve regeneration, holding promise for therapeutic insights into neural repair.

Establishment and validation of a nomogram for dropout intention in Chinese early year medical undergraduates.

BACKGROUND: The attrition rate of Chinese medical students is high. This study utilizes a nomogram technique to develop a predictive model for dropout intention among Chinese medical undergraduates based on 19 individual and work-related characteristics. METHOD: A repeated cross-sectional study was conducted, enrolling 3536 medical undergraduates in T1 (August 2020-April 2021) and 969 participants in T2 (October 2022) through snowball sampling. Demographics (age, sex, study phase, income, relationship status, history of mental illness) and mental health factors (including depression, anxiety, stress, burnout, alcohol use disorder, sleepiness, quality of life, fatigue, history of suicidal attempts (SA), and somatic symptoms), as well as work-related variables (career choice regret and reasons, workplace violence experience, and overall satisfaction with the Chinese healthcare environment), were gathered via questionnaires. Data from T1 was split into a training cohort and an internal validation cohort, while T2 data served as an external validation cohort. The nomogram's performance was evaluated for discrimination, calibration, clinical applicability, and generalization using receiver operating characteristic curves (ROC), area under the curve (AUC), calibration curves, and decision curve analysis (DCA). RESULT: From 19 individual and work-related factors, five were identified as significant predictors for the construction of the nomogram: history of SA, career choice regret, experience of workplace violence, depressive symptoms, and burnout. The AUC values for the training, internal validation, and external validation cohorts were 0.762, 0.761, and 0.817, respectively. The nomogram demonstrated reliable prediction and discrimination, with adequate calibration and generalization across both the training and validation cohorts. CONCLUSION: This nomogram exhibits reasonable accuracy in foreseeing dropout intentions among Chinese medical undergraduates. It could guide colleges, hospitals, and policymakers in pinpointing students at risk, thus informing targeted interventions. Addressing underlying factors such as depressive symptoms, burnout, career choice regret, and workplace violence may help reduce the attrition of medical undergraduates. TRIAL REGISTRATION: This is an observational study. There is no Clinical Trial Number associated with this manuscript.

An S-methyltransferase that produces the climate-active gas dimethylsulfide is widespread across diverse marine bacteria.

Hydrogen sulfide (H2S), methanethiol (MeSH) and dimethylsulfide (DMS) are abundant sulfur gases with roles in biogeochemical cycling, chemotaxis and/or climate regulation. Catabolism of the marine osmolyte dimethylsulfoniopropionate (DMSP) is a major source of DMS and MeSH, but both also result from S-methylation of H2S via MddA, an H2S and MeSH S-methyltransferase whose gene is abundant in soil but scarce in marine environments. Here we identify the S-adenosine methionine (SAM)-dependent MeSH and H2S S-methyltransferase 'MddH', which is widespread in diverse marine bacteria and some freshwater and soil bacteria. mddH is predicted in up to ~5% and ~15% of seawater and coastal sediment bacteria, respectively, which is considerably higher than mddA. Furthermore, marine mddH transcript levels are similar to those for the most abundant DMSP lyase gene dddP. This study implies that the importance of H2S and MeSH S-methylation pathways in marine environments is significantly underestimated.

Interfacial charge demulsification endowed dual-network photocatalytic hydrogen-bonded PVA@agarose membranes for oil-water separation.

Hydrogel materials with hydrophilic cross-linked network exhibit remarkable super-wettability, enabling their widespread application in oily wastewater treatment. However, the single and loose structure lacks sufficient strength and porosity to resist long-term degradation. Herein, a structural synergistic molecular strategy was reported to introduce reinforcing phase structures and interfacial active sites into the polymer networks for long-term oil-water emulsion separation. The carbon skeleton was uniformly interspersed through the strongly hydrogen-bonded polymer chains via covalent bonds, resulting in a hydrogel network with high mechanical strength and exceptional flow conductivity, which maintained a separation flux of 1233 L m-2 h-1 after 20 separation cycles under gravitational force. Dense negative charges on the surface disrupted the internal charge stability of the oil-water emulsion, leading to remarkable demulsification with a separation efficiency exceeding 99 %. Simultaneously, the strong redox reaction of the photoheterojunction effectively removed organic dyes under visible light, enhancing the overall antifouling performance. This study provided a feasible strategy at the molecular level for optimizing the suitability of hydrogels for oil-water emulsion separation.

Unveiling the Catalytic Roles of DsBBS1 and DsBBS2 in the Bibenzyl Biosynthesis of Dendrobium sinense.

Dendrobium sinense, an endemic medicinal herb in Hainan Island, is rich in bibenzyl compounds. However, few studies have explored the molecular mechanisms of bibenzyl biosynthesis. This study presents a comprehensive analysis of DsBBS1 and DsBBS2 function in D. sinense. A molecular docking simulation revealed high-resolution three-dimensional structural models with minor domain orientation differences. Expression analyses of DsBBS1 and DsBBS2 across various tissues indicated a consistent pattern, with the highest expression being found in the roots, implying that they play a pivotal role in bibenzyl biosynthesis. Protein expression studies identified optimal conditions for DsBBS2-HisTag expression and purification, resulting in a soluble protein with a molecular weight of approximately 45 kDa. Enzyme activity assays confirmed DsBBS2's capacity to synthesize resveratrol, exhibiting higher Vmax and lower Km values than DsBBS1. Functional analyses in transgenic Arabidopsis demonstrated that both DsBBS1 and DsBBS2 could complement the Atchs mutant phenotype. The total flavonoid content in the DsBBS1 and DsBBS2 transgenic lines was restored to wild-type levels, while the total bibenzyl content increased. DsBBS1 and DsBBS2 are capable of catalyzing both bibenzyl and flavonoid biosynthesis in Arabidopsis. This study provides valuable insights into the molecular mechanisms underlying the biosynthesis of bibenzyl compounds in D. sinense.

Highly Defective Zirconium-Based Metal-Organic Frameworks for the Efficient Adsorption and Detection of Sugar Phosphates in the Biological Sample.

Enrichment and quantification of sugar phosphates (SPx) in biological samples were of great significance in biological medicine. In this work, a series of zirconium-based metal-organic frameworks (MOFs) with different degrees of defects, namely, HP-UiO-66-NH2-X, were synthesized using acetic acid as a modulator and were utilized as high-capacity adsorbents for the adsorption of SPx in biological samples. The results indicated that the addition of acetic acid altered the morphology of HP-UiO-66-NH2-X, with corresponding changes in pore size (3.99-9.28 nm) and specific surface area (894.44-1142.50 m2·g-1). HP-UiO-66-NH2-10 showed the outstanding performance by achieving complete adsorption of all four SPx using only 80 µg of the adsorbent. The excellent adsorption efficiency of HP-UiO-66-NH2-10 was also obtained with a wide pH range and short adsorption time (10 min). Adsorption experiments demonstrated that the adsorption process involved chemical adsorption and multilayer adsorption. By utilizing X-ray photoelectron spectroscopy and density functional theory to explain the adsorption mechanism, it was found that various interactions (including coordination, hydrogen bonding, and electrostatic interactions) collectively contributed to the exceptional adsorption capability of HP-UiO-66-NH2-10. Those results indicated that the defect strategy not only increased the specific surface area and pore size, providing additional adsorption sites, but also reduced the adsorption energy between HP-UiO-66-NH2-10 and SPx. Moreover, HP-UiO-66-NH2-10 showed a low limit of detection (0.001-0.01 ng·mL-1), high precision (<13.77%), and accuracy (80.10-111.83%) in serum, liver, and cells, good stability, high selectivity (SPx/glucose, 1:100 molar ratio), and high adsorption capacity (292 mg·g-1 for SPx). The practical detection of SPx from human serum was also verified, prefiguring the great potentials of defective zirconium-based MOFs for the enrichment and detection of SPx in the biological medicine.

Hepatocellular Carcinoma in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Importance: In the US, hepatocellular carcinoma (HCC) has been the most rapidly increasing cancer since 1980, and metabolic dysfunction-associated steatotic liver disease (MASLD) is expected to soon become the leading cause of HCC. Objective: To develop a prediction model for HCC incidence in a cohort of patients with MASLD. Design, Setting, and Participants: This prognostic study was conducted among patients aged at least 18 years with MASLD, identified using diagnosis of MASLD using International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes; natural language processing of radiology imaging report text, which identified patients who had imaging evidence of MASLD but had not been formally diagnosed; or the Dallas Steatosis Index, a risk equation that identifies individuals likely to have MASLD with good precision. Patients were enrolled from Kaiser Permanente Northern California, an integrated health delivery system with more than 4.6 million members, with study entry between January 2009 and December 2018, and follow-up until HCC development, death, or study termination on September 30, 2021. Statistical analysis was performed during February 2023 and January 2024. Exposure: Data were extracted from the electronic health record and included 18 routinely measured factors associated with MASLD. Main Outcome and Measures: The cohort was split (70:30) into derivation and internal validation sets; extreme gradient boosting was used to model HCC incidence. HCC risk was divided into 3 categories, with the cumulative estimated probability of HCC 0.05% or less classified as low risk; 0.05% to 0.09%, medium risk; and 0.1% or greater, high risk. Results: A total of 1 811 461 patients (median age [IQR] at baseline, 52 [41-63] years; 982 300 [54.2%] female) participated in the study. During a median (range) follow-up of 9.3 (5.8-12.4) years, 946 patients developed HCC, for an incidence rate of 0.065 per 1000 person-years. The model achieved an area under the curve of 0.899 (95% CI, 0.882-0.916) in the validation set. At the medium-risk threshold, the model had a sensitivity of 87.5%, specificity of 81.4%, and a number needed to screen of 406. At the high-risk threshold, the model had a sensitivity of 78.4%, a specificity of 90.1%, and a number needed to screen of 241. Conclusions and Relevance: This prognostic study of more than 1.8 million patients with MASLD used electronic health record data to develop a prediction model to discriminate between individuals with and without incident HCC with good precision. This model could serve as a starting point to identify patients with MASLD who may need intervention and/or HCC surveillance.

Dispersive solid-phase extraction based on zirconium metal-organic framework coupled with gas chromatography-mass spectrometry for determining sugar phosphates in biological samples.

BACKGROUND: Sugar phosphates (SPx) play important role in the metabolism of the organism. SPx such as glycerate 3-phosphate, fructose 6-phosphate and glucose 6-phosphate in biological samples have the poor stability, similar structure and low abundance, which make their separation and detection more challenging. METHOD: UiO-66-NH2 and ZrO2 coated SiO2(SBA-15) hard-core-shell adsorbents (UiO-66-NH2@SBA-15 and ZrO2@SBA-15) were synthesized, which were further used for dispersive solid-phase extraction for enriching the SPx in biological samples. The protocol was developed by UiO-66-NH2@SBA-15 and ZrO2@SBA-15 coupled with gas chromatography-mass spectrometry for the detection of trace SPx. The univariate experiment and response surface methodology were used to optimize the adsorption and desorption conditions. RESULTS: The adsorbents showed excellent adsorption capacity and specificity towards SPx, which were proved by adsorption and selective experiments. Under the optimized conditions, there were good linearity within the range of 5.0-5000.0 ng mL-1, low limits of detection (0.001-1.0 ng mL-1), low limits of quantification (0.005-5.0 ng mL-1) and good precision (relative standard deviation less than 14.7 % for intra-day and inter-day). The satisfactory recoveries (89.1-113.8 %) and precision (0.5-14.6 %) were obtained when the sorbents were used to extract SPx from serum, saliva and cell samples. Moreover, UiO-66-NH2@SBA-15 was applied to the quantitative analysis of SPx from gastric cancer patients, because of a higher adsorption capacity (169.5-196.1 mg g-1). CONCLUSIONS: UiO-66-NH2@SBA-15 showed great potential in the extraction of SPx in biological samples, which was beneficial to find out the metabolic change of SPx and explain the pathogenesis of the disease.

LncRNA LINC01278 Regulates the Prognosis and Related Mechanisms of Gastric Cancer by Targeting miR-129-5p.

Gastric cancer, a prevalent malady within the digestive tract, has a complex pathological mechanism and numerous patients. The regulation of gastric cancer process by long non-coding RNA (lncRNA) presented new prospects for the study of its molecular mechanism and the treatment of patients. The abnormal expressed genes in gastric cancer were screened by GSE193109 dataset. The correlation between LINC01278 and the likelihood of survival in patients suffering from gastric cancer was investigated by Kaplan-Meier survival curve and multivariate Cox analysis. LINC01278 in gastric cancer tissue samples and cells was verified via RT-qPCR. The cell counting kit-8 (CCK-8) and transwell assay were selected to detect the growth activity of gastric cancer cells. The association between LINC01278 and miR-129-5p was validated through luciferase reporter assay and RNA-binding protein immunoprecipitation (RIP) assay. Correlation analysis of clinical features revealed an association between LINC01278 and the prognosis in gastric cancer patients. LINC01278 was actively expressed in gastric cancer, which exerts a tumor-promoting effect. Silencing LINC01278 suppressed the biological function of tumor cells through spongiform miR-129-5p. LINC01278 has the potential to serve as a novel biomarker, offering new avenues of research for the prognosis and treatment of gastric cancer.

Advances in immune regulation of the G protein-coupled estrogen receptor.

Estrogen and related receptors have been shown to have a significant impact on human development, reproduction, metabolism and immune regulation and to play a critical role in tumor development and treatment. Traditionally, the nuclear estrogen receptors (nERs) ERα and ERß have been thought to be involved in mediating the estrogenic effects. However, our group and others have previously demonstrated that the G protein-coupled estrogen receptor (GPER) is the third independent ER, and estrogen signaling mediated by GPER is known to play an important role in normal physiology and a variety of abnormal diseases. Interestingly, recent studies have progressively revealed GPER involvement in the maintenance of the normal immune system, abnormal immune diseases, and inflammatory lesions, which may be of significant clinical value primarily in the immunotherapy of tumors. In this article, we review current advances in GPER-related immunomodulators and provide a theoretical basis and potential clinical targets to ameliorate immune-related diseases and immunotherapy for tumors.

Data imbalance in cardiac health diagnostics using CECG-GAN.

Heart disease is the world's leading cause of death. Diagnostic models based on electrocardiograms (ECGs) are often limited by the scarcity of high-quality data and issues of data imbalance. To address these challenges, we propose a conditional generative adversarial network (CECG-GAN). This strategy enables the generation of samples that closely approximate the distribution of ECG data. Additionally, CECG-GAN addresses waveform jitter, slow processing speeds, and dataset imbalance issues through the integration of a transformer architecture. We evaluated this approach using two datasets: MIT-BIH and CSPC2020. The experimental results demonstrate that CECG-GAN achieves outstanding performance metrics. Notably, the percentage root mean square difference (PRD) reached 55.048, indicating a high degree of similarity between generated and actual ECG waveforms. Additionally, the Fréchet distance (FD) was approximately 1.139, the root mean square error (RMSE) registered at 0.232, and the mean absolute error (MAE) was recorded at 0.166.

Temperature dependence of the rain-gas and snow-gas partition coefficients for nearly a thousand chemicals.

Compared to the particle-gas partition coefficients (KPG), the rain-gas (KRG) and snow-gas (KSG) partition coefficients are also essential in studying the environmental behavior and fate of chemicals in the atmosphere. While the temperature dependence for the KPG have been extensively studied, the study for KRG and KSG are still lacking. Adsorption coefficients between water surface-air (KIA) and snow surface-air (KJA), as well as partition coefficients between water-air (KWA) and octanol-air (KOA) are vital in calculating KRG and KSG. These four basic adsorption and partition coefficients are also temperature-dependent, given by the well-known two-parameters Antoine equation logKXY = AXY + BXY/T, where KXY is the adsorption or partition coefficients, AXY and BXY are Antoine parameters (XY stand for IA, JA, WA, and OA), and T is the temperature in Kelvin. In this study, the parameters AXY and BXY are calculated for 943 chemicals, and logKXY can be estimated at any ambient temperature for these chemicals using these Antoine parameters. The results are evaluated by comparing these data with published experimental and modeled data, and the results show reasonable accuracy. Based on these coefficients, temperature-dependence of logKRG and logKSG is studied. It is found that both logKRG and logKSG are linearly related to 1/T, and Antoine parameters for logKRG and logKSG are also estimated. Distributions of the 943 chemicals in the atmospheric phases (gas, particle, and rain/snow), are illustrated in a Chemical Space Map. The findings reveal that, at environmental temperatures and precipitation days, the dominant state for the majority of chemicals is the gaseous phase. All the AXY and BXY values for logKSG, logKRG, and basic adsorption and partition coefficients, both modeled by this study and collected from published work, are systematically organized into an accessible dataset for public utilization.

Carbon Nanofiber Membranes Loaded with MXene@g-C3N4: Preparation and Photocatalytic Property.

In this study, a Ti3C2 MXene@g-C3N4 composite powder (TM-CN) was prepared by the ultrasonic self-assembly method and then loaded onto a carbon nanofiber membrane by the self-assembly properties of MXene for the treatment of organic pollutants in wastewater. The characterization of the TM-CN and the C-TM-CN was conducted via X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectrometer (FTIR) to ascertain the successful modification. The organic dye degradation experiments demonstrated that introducing an appropriate amount of Ti3C2 MXene resulted in the complete degradation of RhB within 60 min, three times the photocatalytic efficiency of a pure g-C3N4. The C-TM-CN exhibited the stable and outstanding photocatalytic degradation of the RhB solution over a wide range of pH values, indicating the characteristics of the photodegradation of organic pollutants in a wide range of aqueous environments. Furthermore, the results of the cyclic degradation experiments demonstrated that the C-TM-CN composite film maintained a degradation efficiency of over 85% after five cycles, thereby confirming a notable improvement in its cyclic stability. Consequently, the C-TM-CN composite film exhibits excellent photocatalytic performance and is readily recyclable, making it an auspicious eco-friendly material in water environment remediation.

Pollution characteristics, source apportionment and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity of China.

Polycyclic aromatic hydrocarbons (PAHs) have the capability for solar radiation absorption related to climate forcing. Herein, pollution characteristics and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity were comprehensively investigated. The mean concentrations of Σ18PAHs in all the 11 particle size ranges were 3.95 ± 4.77 × 104 pg/m3 and 2.17 ± 1.54 × 103 pg/m3 in heating period (HP) and non-heating period (NHP), respectively. Except for most PAHs with 2 and 3 benzene rings in NHP, most other PAHs showed a unimodal distribution pattern with the peak at 0.56-1.0 µm in both periods, which was caused by PAH emission sources. The PAH-related climate forcing was mainly caused by the solar radiation absorptions at ∼325 (∼330) nm and ∼365 nm. In general, the absorption intensities were higher in HP than NHP. The absorption intensity in the particle size range of 0.56-1.0 µm was the highest, and benzo[e]pyrene was the dominant contributor. In colder periods in HP, higher PAH concentrations caused more intensive PAH-related climate forcing. This study provided new insights for pollution characteristics and absorption spectra of size-resolved PAHs in atmospheric particles, which will be useful for better understanding PAH-related climate forcing.

Seasonal variations and sources of atmospheric EPFRs in a megacity in severe cold region: Implications for the influence of strong coal and biomass combustion.

Environmentally persistent free radicals (EPFRs) can pose exposure risks by inducing the generation of reactive oxygen species. As a new class of pollutants, EPFRs have been frequently detected in atmospheric particulate matters. In this study, the seasonal variations and sources of EPFRs in a severe cold region in Northeastern China were comprehensively investigated, especially for the high pollution events. The geomean concentration of EPFRs in the total suspended particle was 6.58 × 1013 spins/m3 and the mean level in winter was one order of magnitude higher than summer and autumn. The correlation network analysis showed that EPFRs had significantly positive correlation with carbon component, K+ and PAHs, indicating that EPFRs were primarily emitted from combustion and pyrolysis process. The source appointment by the Positive Matrix Factorization (PMF) model indicated that the dominant sources in the heating season were coal combustion (48.4%), vehicle emission (23.1%) and biomass burning (19.4%), while the top three sources in the non-heating season were others (41.4%), coal combustion (23.7%) and vehicle emissions (21.2%). It was found that the high EPFRs in cold season can be ascribed to the extensive use of fossil fuel for heating demand; while the high EPFRs occurred in early spring were caused by the large-scale opening combustion of biomass. In summary, this study provided important basic information for better understanding the pollution characteristics of EPFRs, which suggested that the implementation of energy transformation and straw utilization was benefit for the control of EPFRs in severe cold region.

Rapid detection of furanyl fentanyl in complex matrices using Leidenfrost desorption-assisted low-temperature arc plasma ionization mass spectrometry.

The abuse of illicit drugs poses serious threats to the physical and mental health of users, as well as to the overall safety and welfare of society. In this work, we present a newly developed technique for drug detection based on mass spectrometry. This technique combines Leidenfrost desorption with low-temperature arc plasma ionization mass spectrometry. This method is applicable for detecting furanyl fentanyl in complex matrices. Key advantages of this technique include minimal sample fragmentation and high sensitivity for detection. The Leidenfrost desorption plays a pivotal role in this methodology, as it spontaneously concentrates analyte molecules during the gradual evaporation of the solvent. Eventually, these concentrated molecules are redistributed at their highest concentrations, resulting in exceptionally high sensitivity. In the course of our investigation, we achieved a remarkable detection limit of 10 pg mL-1 for furanyl fentanyl in pure water. Moreover, the characteristic ion peaks of furanyl fentanyl can be distinctly identified within complex matrices such as wine, beverages, urine, and lake water. This innovative drug detection technology offers several advantages, including a simple setup, cost-effectiveness, rapid detection, high sensitivity, and minimal sample pretreatment.

Responses of assembled structures of block polyelectrolytes to electrostatic interaction strength.

In this paper, the responses of assembled behaviors of block polyelectrolytes (PEs) to the strength of electrostatic interactions are studied through molecular dynamic simulations. The results show that the assembled structures closely depend on the electrostatic strength. It should be noted that PE coacervation can outweigh the nucleation of hydrophobic blocks and invert the micelle structures at strong electrostatic strengths, leading to the formation of inverted micelles of PE cores and hydrophobic coronas. In the poor solvent condition for neutral block, diverse anisotropic micelles are presented; candy-like conventional micelles of hydrophobic cores and PE patches coexist with inverted candy-like micelles of PE cores and hydrophobic patches and with Janus micelles of semi-neutral aggregate and semi-PE cluster in the presence of divalent and trivalent counterions. The formation of conventional or inverted micelle is largely determined by the type of micellar fusion, which results from the nucleation competition between electrostatic correlation and hydrophobic interaction. The merge of micelles mediated by hydrophobic attraction leads to conventional hydrophobic cores, and the fusion induced by electrostatic correlations results in PE cores micelles. At strong electrostatic strengths, the PE chains exhibit rich conformations at trivalent counterions, ranging from a fully collapsed state to a rod-like state, and parallel alignment of PE chains is found.