Comprehensive review of emerging contaminants: Detection technologies, environmental impact, and management strategies.

Emerging contaminants (ECs) are a diverse group of unregulated pollutants increasingly present in the environment. These contaminants, including pharmaceuticals, personal care products, endocrine disruptors, and industrial chemicals, can enter the environment through various pathways and persist, accumulating in the food chain and posing risks to ecosystems and human health. This comprehensive review examines the chemical characteristics, sources, and varieties of ECs. It critically evaluates the current understanding of their environmental and health impacts, highlighting recent advancements and challenges in detection and analysis. The review also assesses existing regulations and policies, identifying shortcomings and proposing potential enhancements. ECs pose significant risks to wildlife and ecosystems by disrupting animal hormones, causing genetic alterations that diminish diversity and resilience, and altering soil nutrient dynamics and the physical environment. Furthermore, ECs present increasing risks to human health, including hormonal disruptions, antibiotic resistance, endocrine disruption, neurological effects, carcinogenic effects, and other long-term impacts. To address these critical issues, the review offers recommendations for future research, emphasizing areas requiring further investigation to comprehend the full implications of these contaminants. It also suggests increased funding and support for research, development of advanced detection technologies, establishment of standardized methods, adoption of precautionary regulations, enhanced public awareness and education, cross-sectoral collaboration, and integration of scientific research into policy-making. By implementing these solutions, we can improve our ability to detect, monitor, and manage ECs, reducing environmental and public health risks.

Association between physical activity and functional movement screening among university students in an adaptive physical course.

BACKGROUND: Physical activity (PA) holds profound implications for the holistic development of college students. However, students with chronic diseases or physical disabilities experience significantly limited PA during adaptive sports. OBJECTIVE: This study aims to investigate the relationship between physical activity and Functional Movement Screening (FMS) among university students who participate in the adaptive physical course. METHODS: 36 university students (from the adaptive physical course) completed the International Physical Activity Questionnaire-Long Form (IPAQ-L). Body measurements and FMS were assessed. Correlation analysis and t-tests were used to determine relationships and differences between various indicators. A two-way analysis of variance was used to investigate potential variations in FMS scores based on gender and weight status. RESULTS: The results show that gender, PA, and BMI significantly influence FMS scores in students participating in adaptive physical courses. FMS score is significantly negatively correlated with BMI and significantly positively correlated with PA. The FMS score for males, as well as the scores for Trunk Stability Push-Up and Rotary Stability, are significantly higher than those for females. CONCLUSION: University students in adaptive physical courses can benefit from increased PA and FMS scores. Improving functional movement and enhancing physical activity are crucial for promoting overall health in this population.

Confidence-aware multi-modality learning for eye disease screening.

Multi-modal ophthalmic image classification plays a key role in diagnosing eye diseases, as it integrates information from different sources to complement their respective performances. However, recent improvements have mainly focused on accuracy, often neglecting the importance of confidence and robustness in predictions for diverse modalities. In this study, we propose a novel multi-modality evidential fusion pipeline for eye disease screening. It provides a measure of confidence for each modality and elegantly integrates the multi-modality information using a multi-distribution fusion perspective. Specifically, our method first utilizes normal inverse gamma prior distributions over pre-trained models to learn both aleatoric and epistemic uncertainty for uni-modality. Then, the normal inverse gamma distribution is analyzed as the Student's t distribution. Furthermore, within a confidence-aware fusion framework, we propose a mixture of Student's t distributions to effectively integrate different modalities, imparting the model with heavy-tailed properties and enhancing its robustness and reliability. More importantly, the confidence-aware multi-modality ranking regularization term induces the model to more reasonably rank the noisy single-modal and fused-modal confidence, leading to improved reliability and accuracy. Experimental results on both public and internal datasets demonstrate that our model excels in robustness, particularly in challenging scenarios involving Gaussian noise and modality missing conditions. Moreover, our model exhibits strong generalization capabilities to out-of-distribution data, underscoring its potential as a promising solution for multimodal eye disease screening.

Desorption Characteristics of CH4-C2H6 Mixed Gas in Heavy Hydrocarbon-Rich Coal Seams.

The gas desorption characteristics of coal are closely related to the gas content of the coal seam. The gas in heavy hydrocarbon-rich coal seams contains CH4 and C2H6 heavy hydrocarbons. However, most current research on the gas desorption characteristics of coal seams focuses on CH4 analysis, ignoring the influence of the C2H6 heavy hydrocarbon gas. To accurately determine the gas content of a heavy hydrocarbon-rich coal seam, methods based on CH4 analysis are inadequate and the desorption characteristics of CH4-C2H6 mixed gas must be clarified. This work experimentally and theoretically studies the desorption characteristics of single-component gas and CH4-C2H6 mixed gas from coal samples. The results show that increasing the adsorption-equilibrium pressure was found to increase the desorption quantity and desorption speed of single-component gas and increase the desorption quantity, desorption ratio, and diffusion coefficient of mixed gas. Under the same adsorption-equilibrium pressure, the desorption quantity and rate of single-component CH4 gas exceeded those of C2H6. The quantity and speed of mixed gas desorption increased with rising CH4 concentration and decreased with rising C2H6 concentration. The change in the mixed gas concentration during desorption reflects the distribution characteristics of light hydrocarbon components on the outer surface and heavy hydrocarbon components on the inner surface of coal. From the desorption characteristics of mixed gas, desorption models of mixed gas were obtained at different concentrations, laying a theoretical foundation for accurate determinations of gas contents in heavy hydrocarbon-rich coal seams.

Leveraging genomic signatures of oral microbiome-associated antibiotic resistance genes for diagnosing pancreatic cancer.

Growing evidence has increasingly suggested a potential linkage between the oral microbiome and various diseases, including pancreatic ductal adenocarcinoma (PDAC). However, the utilization of gene-level information derived from the oral microbiome for diagnosing PDAC remains unexplored. In this study, we sought to investigate the novel potential of leveraging genomic signatures associated with antibiotic resistance genes (ARGs) within the oral microbiome for the diagnosis of PDAC. By conducting an analysis of oral microbiome samples obtained from PDAC patients, we successfully identified specific ARGs that displayed distinct sequence abundance profiles correlated with the presence of PDAC. In the healthy group, three ARGs were found to be enriched, whereas 21 ARGs were enriched in PDAC patients. Remarkably, these ARGs from oral microbiome exhibited promising diagnostic capabilities for PDAC (AUROC = 0.79), providing a non-invasive and early detection method. Our findings not only provide novel modal data for diagnosing PDAC but also shed light on the intricate interplay between the oral microbiome and PDAC.

HPLC and LC-MS/MS-Based Quantitative Characterization of Related Substances Associated with Sotalol Hydrochloride.

In total, three related substances (RS) associated with sotalol hydrochloride (STHCl) were herein identified with a novel gradient high-performance liquid chromatography (HPLC) protocol. Further characterization of these substances was then performed via liquid chromatography-mass spectroscopy (LC-MS/MS) and nuclear magnetic resonance (NMR) approaches. For these analyses, commercial STHCl samples were used for quantitative HPLC studies and the degradation of STHCl under acidic (1M HCl), alkaline (1M NaOH), oxidative (30% H2O2), photolytic (4500 Lx), and thermal stress conditions (100 °C) was assessed. This approach revealed this drug to be resistant to acidic, alkaline, and high-temperature conditions, whereas it was susceptible to light and oxidation as confirmed through long-term experiments. The putative mechanisms governing RS formation were also explored, revealing that RS3 was derived from the manufacturing process, whereas RS2 was generated via oxidation and RS1 was generated in response to light exposure. The cytotoxicity of these RS compounds was then assessed using MTT assays and acute toxicity test. Overall, this study provides details regarding the characterization, isolation, quantification, and toxicological evaluation of STHCl and associated RS compounds together with details regarding the precise, specific, and reliable novel HPLC technique, thus providing the requisite information necessary to ensure STHCl purity and safety.

Chemical composition and antioxidant activity of petroleum ether fraction of Rosmarinus officinalis.

The presented study examines the chemical composition and antioxidant activity of the petroleum ether fraction of Rosmarinus officinalis (PEF-RO), which was obtained via 75 % ethanol extraction followed by petroleum ether extraction. The obtained fractions were analyzed by gas chromatography-mass spectrometry (GC-MS). The in vitro antioxidant activity of PEF-RO was investigated using various assays, including 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2'-azinobis-(3-ethylbenzthiazoline-6-sulfonate (ABTS) free radical scavenging, and ferric reducing antioxidant power (FRAP) method. A total of 82 chemical components were successfully identified, totaling 10.06 % of PEF-RO content. The identified components consisted of 24 hydrocarbons, 14 ketones, 16 alcohols, 4 phenols, 14 esters, and 10 other compounds. Notably, verbenone (2.4377 %), vitamin A (0.6854 %), trans-geraniol (0.5998 %), linolenic acid (0.5713 %), and 1,8-eucalyptol (0.5323 %) were the most abundant compounds, and there are many trace components in PEF-RO. PEF-RO's IC50 values of DPPH and ABTS free radical scavenging were determined as 0.36 mg/mL and 0.19 mg/mL, respectively. FRAP-method was employed to measure the total antioxidant energy of PEF-RO, which displayed good antioxidant activity. The obtained data provides the foundation for the comprehensive development and utilization of Rosmarinus officinalis.

Red Tide Detection Method Based on Improved U-Net Model-Taking GOCI Data in East China Sea as an Example.

In the coastal areas of China, the eutrophication of seawater leads to the continuous occurrence of red tide, which has caused great damage to Marine fisheries and aquatic resources. Therefore, the detection and prediction of red tide have important research significance. The rapid development of optical remote sensing technology and deep-learning technology provides technical means for realizing large-scale and high-precision red tide detection. However, the difficulty of the accurate detection of red tide edges with complex boundaries limits the further improvement of red tide detection accuracy. In view of the above problems, this paper takes GOCI data in the East China Sea as an example and proposes an improved U-Net red tide detection method. In the improved U-Net method, NDVI was introduced to enhance the characteristic information of the red tide to improve the separability between the red tide and seawater. At the same time, the ECA channel attention mechanism was introduced to give different weights according to the influence of different bands on red tide detection, and the spectral characteristics of different channels were fully mined to further extract red tide characteristics. A shallow feature extraction module based on Atrous Spatial Pyramid Convolution (ASPC) was designed to improve the U-Net model. The red tide feature information in a multi-scale context was fused under multiple sampling rates to enhance the model's ability to extract features at different scales. The problem of limited accuracy improvement in red tide edge detection with complex boundaries is solved via the fusion of deep and shallow features and multi-scale spatial features. Compared with other methods, the method proposed in this paper achieves better results and can detect red tide edges with complex boundaries, and the accuracy, precision, recall, and F1-score are 95.90%, 97.15%, 91.53%, and 0.94, respectively. In addition, the red tide detection experiments in other regions with relatively concentrated distribution also prove that the method has good applicability.

Steroidal Alkaloids from the Roots of Veratrum mengtzeanum Loes. with Their Anti-Inflammatory Activities.

The phytochemical investigation of Veratrum mengtzeanum Loes. roots resulted in the isolation and characterization of two novel, namely Mengtzeanines A (1), Mengtzeanines B (2), and eight known steroidal alkaloids (3-10). Their structural properties were assessed though extensive spectroscopic techniques. All constituents 1-10 were analyzed for suppression of NO formation in LPS-induced RAW264.7 macrophages. Among them, constituent 6 (Verazine) showed inhibition against LPS-induced NO production (IC50 = 20.41 µM). Additionally, compound 6 could inhibit the secretion of IL1ß, IL6, and TNFα, and downregulate the productions of iNOS and COX2 in LPS-induced RAW264.7 macrophages. Further experiments revealed that 6 exhibited a potent anti-inflammatory level in LPS-stimulated RAW264.7 macrophages via inhibiting NF-κB, and triggering of Keap1/Nrf2/HO-1 axis, implying that compound 6 may be a promising candidate for treating inflammatory disorders.

Interaction and Metabolic Function of Microbiota during the Washed Processing of Coffea arabica.

Coffee fermentation is crucial for flavor and aroma, as microorganisms degrade mucilage and produce metabolites. This study aimed to provide a basis for understanding the impact of microorganisms on Coffea arabica from Yunnan, China, during washed processing. The microbial community structure and differentially changed metabolites (DCMs) of C. arabica beans during washed processing were analyzed. The results indicated that the top five predominant microorganisms at the genera level were Achromobacter, Tatumella, Weissella, Streptococcus, and Trichocoleus for bacteria and Cystofilobasidium, Hanseniaspora, Lachancea, Wickerhamomyces, and Aspergillus for fungi. Meanwhile, the relative content of 115 DCMs in 36 h samples decreased significantly, compared to non-fermentation coffee samples (VIP > 1, p < 0.05, FC < 0.65), and the relative content of 28 DCMs increased significantly (VIP > 1, p < 0.05, FC > 1.5). Furthermore, 17 DCMs showed a strong positive correlation with microorganisms, and 5 DCMs had a strong negative correlation (p < 0.05, |r| > 0.6). Therefore, the interaction and metabolic function of microbiota play a key role in the formation of coffee flavor, and these results help in clarifying the fermentation mechanisms of C. arabica and in controlling and improving the quality of coffee flavor.

Integrating Metabolomics and Proteomics Technologies Provides Insights into the Flavor Precursor Changes at Different Maturity Stages of Arabica Coffee Cherries.

The metabolic modulation of major flavor precursors during coffee cherry ripening is critical for the characteristic coffee flavor formation. However, the formation mechanism of flavor precursors during coffee cherry ripening remains unknown. In the present study, a colorimeter was employed to distinguish different maturity stages of coffee cherry based on the coffee cherry skin colors, and proteomics and metabolomics profiles were integrated to comprehensively investigate the flavor precursor dynamics involved in Arabica coffee cherry ripening. The data obtained in the present study provide an integral view of the critical pathways involved in flavor precursor changes during coffee cherry ripening. Moreover, the contributions of critical events in regulating the development of flavor precursors during the four ripening stages of coffee cherries, including the biosynthesis and metabolism pathways of organic acids, amino acids, flavonoids, and sugars, are discussed. Overall, a total of 456 difference express metabolites were selected, and they were identified as being concentrated in the four maturity stages of coffee cherries; furthermore, 76 crucial enzymes from the biosynthesis and metabolism of sugars, organic acids, amino acids, and flavonoids contributed to flavor precursor formation. Among these enzymes, 45 difference express proteins that could regulate 40 primary amino acids and organic acids flavor precursors were confirmed. This confirmation indicates that the metabolic pathways of amino acids and organic acids played a significant role in the flavor formation of Arabica coffee cherries during ripening. These results provide new insights into the protease modulation of flavor precursor changes in Arabica coffee cherry ripening.

A meta-analysis of short-term and long-term effects of indocyanine green fluorescence imaging in hepatectomy for liver cancer.

OBJECTIVES: This meta-analysis aimed to compare the short-term and long-term effects of indocyanine green fluorescence imaging in hepatectomy for liver cancer. METHODS: The databases PubMed, Embase, Scopus, Cochrane Library, Web of Science, ScienceDirect, and major scientific websites were screened up to January 2023. Randomized controlled trials and observational studies comparing fluorescence navigation-assisted and fluorescence-free navigation-assisted hepatectomy for liver cancer were included. Our meta-analysis comprises overall results and 2 subgroup analyses based on surgery type (laparoscopy and laparotomy). These estimates are presented as mean differences (MD) or odds ratio (OR) estimates with 95% CIs. RESULTS: We analyzed 16 studies that included 1260 patients with liver cancer. Our results showed that fluorescent navigation-assisted hepatectomy were significantly more shorter than fluorescence-free navigation-assisted hepatectomy in the following parameters: operative time [MD = -16.19; 95% CI: -32.27 to -0.11; p = 0.050], blood loss [MD = -107.90; 95% CI: -160.46 to -55.35; p < 0.001], blood transfusion [OR = 0.5; 95% CI: 0.35 to 0.72; p = 0.0002], hospital stay [MD = -1.60; 95% CI: -2.33 to -0.87; p < 0.001], and postoperative complications [OR = 0.59; 95% CI: 0.42 to 0.82; p = 0.002], The one-year disease-free survival rate [OR = 2.87; 95% CI: 1.64 to 5.02; p = 0.0002] was higher in the fluorescent navigation-assisted hepatectomy group. CONCLUSIONS: Indocyanine green fluorescence imaging has good clinical value and can improve the short-term and long-term results of hepatectomy for liver cancer.

Comparison of chemical compositions, antioxidant activities, and acetylcholinesterase inhibitory activities between coffee flowers and leaves as potential novel foods.

This study aimed to compare chemical compositions, antioxidant activities, and acetylcholinesterase inhibitory activities of coffee flowers (ACF) and coffee leaves (ACL) with green coffee beans (ACGB) of Coffea Arabica L. The chemical compositions were determined by employing high-performance liquid chromatography-mass spectroscopy (HPLC-MS) and gas chromatography-mass spectroscopy (GC-MS) techniques. Antioxidant effects of the components were evaluated using DPPH and ABTS radical scavenging assays, and the ferric reducing antioxidant power (FRAP) assay. Their acetylcholinesterase inhibitory activities were also evaluated. The coffee sample extracts contained a total of 214 components identified by HPLC-MS and belonged to 12 classes (such as nucleotides and amino acids and their derivatives, tannins, flavonoids, alkaloids, benzene, phenylpropanoids, and lipids.), where phenylpropanoids were the dominant component (>30%). The contents of flavonoids, alkaloids, saccharides, and carboxylic acid and its derivatives in ACF and ACL varied significantly (p < .05) compared to similar components in ACGB. Meanwhile, 30 differentially changed chemical compositions (variable importance in projection [VIP] > 1, p < .01 and fold change [FC] > 4, or <0.25), that determine the difference in characteristics, were confirmed in the three coffee samples. Furthermore, among 25 volatile chemical components identified by GC-MS, caffeine, n-hexadecanoic acid, 2,2'-methylenebis[6-(1,1-dimethylethyl)-4-methyl-phenol], and quinic acid were common in these samples with caffeine being the highest in percentage. In addition, ACL showed the significantly highest (p < .05) DPPH radical scavenging capacity with IC50 value of 0.491 ± 0.148 mg/ml, and acetylcholinesterase inhibitory activity with inhibition ratio 25.18 ± 2.96%, whereas ACF showed the significantly highest (p < .05) ABTS radical scavenging activity with 36.413 ± 1.523 mmol trolox/g Ex. The results suggested that ACL and ACF had potential values as novel foods in the future.

Artificial intelligence-assisted determination of available sites for palatal orthodontic mini implants based on palatal thickness through CBCT.

OBJECTIVES: To develop an artificial intelligence (AI) system for automatic palate segmentation through CBCT, and to determine the personalized available sites for palatal mini implants by measuring palatal bone and soft tissue thickness according to the AI-predicted results. MATERIALS AND METHODS: Eight thousand four hundred target slices (from 70 CBCT scans) from orthodontic patients were collected, labelled by well-trained orthodontists and randomly divided into two groups: a training set and a test set. After the deep learning process, we evaluated the performance of our deep learning model with the mean Dice similarity coefficient (DSC), average symmetric surface distance (ASSD), sensitivity (SEN), positive predictive value (PPV) and mean thickness percentage error (MTPE). The pixel traversal method was proposed to measure the thickness of palatal bone and soft tissue, and to predict available sites for palatal orthodontic mini implants. Then, an example of available sites for palatal mini implants from the test set was mapped. RESULTS: The average DSC, ASSD, SEN, PPV and MTPE for the segmented palatal bone tissue were 0.831%, 1.122%, 0.876%, 0.815% and 6.70%, while that for the palatal soft tissue were 0.741%, 1.091%, 0.861%, 0.695% and 12.2%, respectively. Besides, an example of available sites for palatal mini implants was mapped according to predefined criteria. CONCLUSIONS: Our AI system showed high accuracy for palatal segmentation and thickness measurement, which is helpful for the determination of available sites and the design of a surgical guide for palatal orthodontic mini implants.

Comparative study of five anti-lipopolysaccharide factor genes in Litopenaeus vannamei.

Anti-lipopolysaccharide factors (ALFs) are a family of common innate immune effectors in crustaceans, and they exhibit broad spectrum antimicrobial activity. In this study, we identified and characterized five novel ALF genes (designated as LvALF1-5) from the Pacific white shrimp (Litopenaeus vannamei) to investigate their potential immune functions. The amino acid sequence alignments showed that LvALFs contained two conserved cysteine residues, a hydrophobic N-terminal region, and the conserved signature sequence W(T/K)CPG(S)WT(A). They all shared high similarity with previously reported ALFs and were clearly novel members of the ALF family. The mRNA transcripts of LvALFs were most highly expressed in hemocytes and the hepatopancreas. After shrimp were stimulated with Vibrio parahaemolyticus or white spot syndrome virus, expression of the LvALFs was significantly induced in hemocytes and the hepatopancreas with various expression profiles. Recombinant proteins of LvALFs exhibited potent bacteriostatic activity in vitro. Together, these results suggest that LvALF1-5 participate in the immune response of Pacific white shrimp against invading pathogens.

Recent advances (2019-2021) of capillary electrophoresis-mass spectrometry for multilevel proteomics.

Multilevel proteomics aims to delineate proteins at the peptide (bottom-up proteomics), proteoform (top-down proteomics), and protein complex (native proteomics) levels. Capillary electrophoresis-mass spectrometry (CE-MS) can achieve highly efficient separation and highly sensitive detection of complex mixtures of peptides, proteoforms, and even protein complexes because of its substantial technical progress. CE-MS has become a valuable alternative to the routinely used liquid chromatography-mass spectrometry for multilevel proteomics. This review summarizes the most recent (2019-2021) advances of CE-MS for multilevel proteomics regarding technological progress and biological applications. We also provide brief perspectives on CE-MS for multilevel proteomics at the end, highlighting some future directions and potential challenges.

Source characterization of volatile organic compounds in urban Beijing and its links to secondary organic aerosol formation.

Volatile organic compounds (VOCs) are precursors for ozone and secondary organic aerosol (SOA) formation, thereby playing a vital role in atmospheric chemistry and urban air quality. To characterize the relationship between VOCs and SOA, organics both in gas and particulate phases were concurrently measured in urban Beijing. The VOCs and organic aerosol (OA) were apportioned into factors with different oxidation levels by applying the factorization analysis on their detailed mass spectra. Six factors of VOCs were identified, including four primary VOCs (PVOC) factors and two secondary VOCs (SVOC) factors. The PVOC factors dominated the total VOCs when the air mass originated in the cleaner northern areas, while SVOC factors dominated for polluted southern air masses. The normalized concentrations of PVOC and primary OA factors showed consistent diurnal variations regardless of air mass directions, owing to the relatively stable local emissions during the experimental period. This contrasted with the secondary factors due to more complex transformation processes. The traffic-related VOCs and solid fuel combustion VOCs negatively correlated with SOA, implying that they may have contributed to the SOA formation through photooxidation. The VOCs in lower oxidation levels were found to have poor correlations with the less oxidized SOA, whereas they correlated strongly to the more oxidized SOA. This implied that the less oxidized SOA may be in a transition state, where its production and loss rates were balanced. These served as products of VOCs oxidation and reactants of more oxidized SOA formation, playing important roles on the VOC to SOA transformation. The identified VOC emission sources and their photochemical production of SOA should be considered in air quality policy planning.

Effects of hygroscopicity on aerosol optical properties and direct radiative forcing in Beijing: Based on two-year observations.

The influence of relative humidity on aerosol properties and the direct radiative forcing of PM10 and PM1 were investigated in Beijing from January 2018 to December 2019. The annual mean scattering hygroscopic growth factor at RH = 80 % [f(80 %)] of PM10 and PM1 were 1.60 ± 0.24 and 1.58 ± 0.22, respectively. The variation of aerosol hygroscopic growth factors of PM10 and PM1 aerosols was similar, which is mainly due to the fact that aerosol scattering in Beijing is dominated by fine particles. The seasonal mean f(80 %) of PM10 from spring to winter were 1.66 ± 0.23, 1.71 ± 0.25, 1.51 ± 0.20, 1.49 ± 0.16, respectively, which were higher in spring and summer, and lower in autumn and winter. The diurnal variation of f(80 %) was relatively higher from 12:00 to 18:00, which could be related to the formation of secondary aerosols by photochemical reactions. f(80 %) shows a strong positive relationship with both the scattering Angström exponent (SAE) and the single scattering albedo (ω0) under dry conditions; therefore, the scattering hygroscopic growth factor could be estimated using these two parameters. The upscatter fraction (ß) and single scattering albedo, which are the key aerosol optical properties for the calculation of direct radiative forcing, are also RH-dependent. As RH increases, the upscatter fraction (backscatter fraction) decreases and ω0 increases. The aerosol radiative forcing at RH 80 % was 1.48 times as that in the dry state. The sensitivity experiment showed that the variation in the scattering coefficient with relative humidity had the greatest influence on radiation forcing, followed by ß and ω0. The seasonal variation of ΔF(80 %)/ΔF(dry) coincides with that of the aerosol hygroscopic growth factor. Our study suggests that understanding the influence of relative humidity on aerosol properties and direct radiative forcing is important for accurately estimating the radiative forcing of aerosols.

Atmospheric Particle Hygroscopicity and the Influence by Oxidation State of Organic Aerosols in Urban Beijing.

A hygroscopic tandem differential mobility analyser (H-TDMA) was used to observe the size-resolved hygroscopic characteristics of submicron particles in January and April 2018 in urban Beijing. The probability distribution of the hygroscopic growth factor (HGF-PDF) in winter and spring usually showed a bimodal pattern, with more hygroscopic mode (MH) being more dominant. The seasonal variation in particle hygroscopicity was related to the origin of air mass, which received polluted southerly air masses in spring and clean northwesterly air masses in winter. Particles showed stronger hygroscopic behaviour during heavy pollution episodes (HPEs) with elevated concentrations of secondary aerosols, especially higher mass fraction of nitrate, which were indicated using the PM2.5 (particulate matter with diameter below 2.5 µm) mass concentration normalised by CO mass concentration. The hygroscopic parameter (κ) values were calculated using H-TDMA (κhtdma) and chemical composition (κchem). The closure study showed that κchem was overestimated in winter afternoon when compared with κhtdma, because the organic particle hygroscopic parameter (κorg) was overestimated in the calculations. It was influenced by the presence of a high concentration of hydrocarbon-like organic aerosol (HOA) with a weak water uptake ability. A positive relationship was observed between κorg and the ratio of oxygenated organic aerosol (OOA) and HOA, thereby indicating that the strong oxidation state enhanced the hygroscopicity of the particles. This study revealed the effect of local emission sources and secondary aerosol formation processes on particle hygroscopicity, which is of great significance for understanding the pollution formation mechanism in the North China Plain.

Surgical Strategies Affect the Long-Term Prognosis of Patients with Hepatocellular Carcinoma Adjacent to the Left Branch of the Portal Vein.

Purpose: When hepatocellular carcinoma (HCC) is closely associated with the left branch of the portal vein, there is still controversy regarding the surgical approach. Methods: This study enrolled 330 HCC patients with tumors adjacent to the left branch of the portal vein. Among them, 85 patients underwent left hemihepatectomy (LH), while the remaining 235 underwent liver lobectomy (LL), which included left medial segmentectomy or left lateral sectionectomy. Perioperative complications, time to recurrence and overall survival (OS) were compared using propensity score matching. Results: LH resulted in a lower 5-year recurrence rate and higher 5-year OS rate than LL (56.5% vs 74.0%, p=0.002; 67.4% vs 53.5%, p=0.029). The LL group showed a higher tendency for early recurrence (ER) and intrahepatic recurrence (IR). The cumulative IR rates at 1- 3-, and 5-years for the LH group and the LL group were 17.0%, 36.7%, 45.1% and 33.8%, 57.1%, 63.7%, respectively, with a p-value of 0.007. There was no statistically significant difference in the cumulative ER rates between the two groups at 1-, 3-, and 5- years. Furthermore, the LH group and the LL group had similar perioperative complications, and no cases of liver failure occurred. Conclusion: LH, compared to LL, reduced the IR rate and ER rate in HCC patients with tumor adjacent to the left branch of the portal vein. It improved the OS outcome of the patients, and there was no significant difference in perioperative complications between the two groups.