Preparation and characterization of poly(vinylidene fluoride) composite membranes blended with nano-crystalline cellulose

AbstractPoly(vinylidene fluoride) (PVDF) composite membranes blended with nano-crystalline cellulose (NCC) for ultrafiltration were prepared by a Loeb–Sourirajan (L–S) phase inversion process. The effects of NCC concentration on the membrane performances were investigated. Surface chemical compositions, surface and cross-section morphologies, degree of crystallinity and the thermal stability of the membranes were characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermal gravimetric analysis (TGA) respectively. The mechanical properties of the membranes were also investigated. All the experimental results indicated that the properties of the composite membranes were improved due to the addition of NCC. The pure water flux of composite membranes can reach 230.8L/(m2h) and increase up to 47.5% compared with pure PVDF membranes. At the same time, the rejection ratio of a bovine serum albumin solution (1g/L) was up to 92.5%. The porosity and the mean pore size of the composite membranes were 65% and 49nm, respectively. Due to the addition of NCC, the degree of crystallinity was increased to 52.1% resulting in the enhanced mechanical properties. A typical asymmetric structure, which was composed of sponge-like dense layer and finger-like microporous support layer, was observed in SEM images of composite membranes

OptIForest: Optimal Isolation Forest for Anomaly Detection

Anomaly detection plays an increasingly important role in various fields for critical tasks such as intrusion detection in cybersecurity, financial risk detection, and human health monitoring. A variety of anomaly detection methods have been proposed, and a category based on the isolation forest mechanism stands out due to its simplicity, effectiveness, and efficiency, e.g., iForest is often employed as a state-of-the-art detector for real deployment. While the majority of isolation forests use the binary structure, a framework LSHiForest has demonstrated that the multi-fork isolation tree structure can lead to better detection performance. However, there is no theoretical work answering the fundamentally and practically important question on the optimal tree structure for an isolation forest with respect to the branching factor. In this paper, we establish a theory on isolation efficiency to answer the question and determine the optimal branching factor for an isolation tree. Based on the theoretical underpinning, we design a practical optimal isolation forest OptIForest incorporating clustering based learning to hash which enables more information to be learned from data for better isolation quality. The rationale of our approach relies on a better bias-variance trade-off achieved by bias reduction in OptIForest. Extensive experiments on a series of benchmarking datasets for comparative and ablation studies demonstrate that our approach can efficiently and robustly achieve better detection performance in general than the state-of-the-arts including the deep learning based methods.Comment: This paper has been accepted by International Joint Conference on Artificial Intelligence (IJCAI-23

Privacy-preserving distributed service recommendation based on locality-sensitive hashing

With the advent of IoT (Internet of Things) age, considerable web services are emerging rapidly in service communities, which places a heavy burden on the target users’ service selection decisions. In this situation, various techniques, e.g., collaborative filtering (i.e., CF) is introduced in service recommendation to alleviate the service selection burden. However, traditional CF-based service recommendation approaches often assume that the historical user-service quality data is centralized, while neglect the distributed recommendation situation. Generally, distributed service recommendation involves inevitable message communication among different parties and hence, brings challenging efficiency and privacy concerns. In view of this challenge, a novel privacy-preserving distributed service recommendation approach based on Locality-Sensitive Hashing (LSH), i.e., DistSRLSH is put forward in this paper. Through LSH, DistSRLSH can achieve a good tradeoff among service recommendation accuracy, privacy-preservation and efficiency in distributed environment. Finally, through a set of experiments deployed on WS-DREAM dataset, we validate the feasibility of our proposal in handling distributed service recommendation problems

Crop Yield and Temperature Changes in North China during 601–900 AD

Depending on the descriptions of crop yield and social response to crop failure/harvest from Chinese historical documents, we classified the crop yield of North China during 601–900 AD into six categories and quantified each category to be the crop yield grades. We found that the regional mean crop yield had a significant (P<0.01) negative trend at the rate of −0.24% per decade. The interannual, multiple-decadal, and century-scale variability accounted for ~47%, ~30%, and ~20% of the total variations of crop yield, respectively. The interannual variability was significantly (P<0.05) persistent across the entire period. The multiple-decadal variability was more dominant after 750 AD than that before 750 AD, while the century-scale variability was more dominant before 750 AD than that after 750 AD. The variations of crop yield could be partly explained by temperature changes. On one hand, the declining trend of crop yield cooccurred with the climate cooling trend from 601 to 900 AD; on the other hand, the crop yield was positively correlated with temperature changes at 30-year resolution with the correlation coefficient of 0.59 (P<0.1). These findings supported that high (low) crop yield occurred in the warming (cooling) climate

Evaluation of potential reference genes for quantitative RT-PCR analysis in spotted sea bass (Lateolabrax maculatus) under normal and salinity stress conditions

The aim of this study was to select the most suitable reference genes for quantitative real-time polymerase chain reaction (qRT-PCR) of spotted sea bass (Lateolabrax maculatus), an important commercial marine fish in Pacific Asia, under normal physiological and salinity stress conditions. A total of 9 candidate reference genes (HPRT, GAPDH, EF1A, TUBA, RPL7, RNAPol II, B2M, ACTB and 18S rRNA) were analyzed by qRT-PCR in 10 tissues (intestine, muscle, stomach, brain, heart, liver, gill, kidney, pectoral fins and spleen) of L. maculatus. Four algorithms, geNorm, NormFinder, BestKeeper, and comparative ΔCt method, were used to evaluate the expression stability of the candidate reference genes. The results showed the 18S rRNA was most stable in different tissues under normal conditions. During salinity stress, RPL7 was the most stable gene according to overall ranking and the best combination of reference genes was RPL7 and RNAPol II. In contrast, GAPDH was the least stable gene which was not suitable as reference genes. The study showed that different algorithms might generate inconsistent results. Therefore, the combination of several reference genes should be selected to accurately calibrate system errors. The present study was the first to select reference genes of L. maculatus by qRT-PCR and provides a useful basis for selecting the appropriate reference gene in L. maculatus. The present study also has important implications for gene expression and functional genomics research in this species or other teleost species

Non-Esterified Fatty Acids Over-Activate the TLR2/4-NF-Κb Signaling Pathway to Increase Inflammatory Cytokine Synthesis in Neutrophils from Ketotic Cows

Background/Aims: Dairy cows with clinical ketosis display a negative energy balance and high blood concentrations of non-esterified fatty acids (NEFAs), the latter of which is an important pathological factor of ketosis in cows. The aims of this study were to investigate the inflammatory status of ketotic cows and to determine whether and through what underlying mechanism high levels of NEFAs induce an inflammatory response. Methods: Proinflammatory factors and the nuclear factor kappa B (NF-κB) signaling pathway were evaluated in neutrophils from clinical ketotic and control cows, using methods including western blotting, quantitative real-time polymerase chain reaction, and enzyme-linked immunosorbent assay. In vitro, the effects of NEFAs on the NF-κB signaling pathway in cow neutrophils were also evaluated using the above experimental techniques. Results: Ketotic cows displayed low blood concentrations of glucose and high blood NEFA and β-hydroxybutyrate concentrations. Importantly, Toll-like receptor 2 (TLR2) and TLR4 expression and IκBα and NF-κB p65 phosphorylation levels in neutrophils (PMNs) were significantly higher in ketotic cows than in control cows, indicating over-activation of the TLR2/4-induced NF-κB inflammatory pathway in PMNs in ketotic cows. The blood concentrations of the inflammatory cytokines interleukin-6 (IL-6), IL-1β, and tumor necrosis factor-α (TNF-α) were also significantly increased in ketotic cows. Interestingly, we found that NEFAs were positively correlated with proinflammatory cytokines. In vitro, after pharmacological inhibition of TLR2 and TLR4 expression in cow neutrophils, TLR2 and TLR4 expression was significantly decreased, and the phosphorylation level of NF-κB p65 was also reduced. Cow neutrophils were treated with different concentrations of NEFAs and pyrrolidine dithiocarbamate (PDTC; an NF-κB inhibitor). High concentrations of NEFAs (0.5 and 1 mM) significantly increased TLR2 and TLR4 expression, IκBα and NF-κB p65 phosphorylation levels, NF-κB p65 transcriptional activity, and IL-6, IL-1β, and TNF-α synthesis in cow neutrophils. The inhibition of NF-κB by PDTC suppressed the NEFA-induced synthesis of proinflammatory cytokines. Conclusions: High concentrations of NEFAs can over-activate the TLR2/4-mediated NF-κB signaling pathway to induce the over-production of proinflammatory cytokines, thereby increasing inflammation in cows with clinical ketosis

Physical and mental health impairments experienced by operating surgeons and camera-holder assistants during laparoscopic surgery: a cross-sectional survey

IntroductionSurgeons may experience physical and mental health problems because of their jobs, which may lead to chronic muscle damage, burnout, or even withdrawal. However, these are often ignored in camera-holder assistants during laparoscopic surgery. We aimed to analyze the differences between operating surgeons and camera-holder assistants.MethodsFrom January 1, 2022, to December 31, 2022, a cross-sectional survey was conducted to evaluate the muscle pain, fatigue, verbal scolding, and task load for operating surgeons and camera-holder assistants. The Nordic Musculoskeletal Questionnaire, the Space Administration Task Load Index, and the Surgical Task Load Index (SURG-TLX) were combined in the questionnaire.Results2,184 operations were performed by a total of 94 operating surgeons and 220 camera assistants. 81% of operating surgeons and 78% of camera-holder assistants reported muscle pain/discomfort during the procedure. The most affected anatomic region was the shoulders for operating surgeons, and the lower back for camera-holder assistants. Intraoperative fatigue was reported by 41.7% of operating surgeons and 51.7% of camera-holder assistants. 55.2% of camera-holder assistants reported verbal scolding from the operating surgeons, primarily attributed to lapses in laparoscope movement coordination. The SURG-TLX results showed that the distributions of mental, physical, and situational stress for operating surgeons and camera-holder assistants were comparable.ConclusionLike operating surgeons, camera-holder assistants also face similar physical and mental health impairments while performing laparoscopic surgery. Improvements to the working conditions of the camera-holder assistant should not be overlooked

COVID-19 vaccination willingness among people living with HIV in Shijiazhuang, China: a cross-sectional survey

ObjectivesThe COVID-19 pandemic imposed an enormous disease and economic burden worldwide. SARS-CoV-2 vaccination is essential to containing the pandemic. People living with HIV (PLWH) may be more vulnerable to severe COVID-19 outcomes; thus, understanding their vaccination willingness and influencing factors is helpful in developing targeted vaccination strategies.MethodsA cross-sectional study was conducted between 15 June and 30 August 2022 in Shijiazhuang, China. Variables included socio-demographic characteristics, health status characteristics, HIV-related characteristics, knowledge, and attitudes toward COVID-19 vaccination and COVID-19 vaccination status. Multivariable logistic regression was used to confirm factors associated with COVID-19 vaccination willingness among PLWH.ResultsA total of 1,428 PLWH were included, with a 90.48% willingness to receive the COVID-19 vaccination. PLWH were more unwilling to receive COVID-19 vaccination for those who were female or had a fair/poor health status, had an allergic history and comorbidities, were unconvinced and unsure about the effectiveness of vaccines, were unconvinced and unsure about the safety of vaccines, were convinced and unsure about whether COVID-19 vaccination would affect ART efficacy, or did not know at least a type of domestic COVID-19 vaccine. Approximately 93.00% of PLWH have received at least one dose of the COVID-19 vaccine among PLWH, and 213 PLWH (14.92%) reported at least one adverse reaction within 7 days.ConclusionIn conclusion, our study reported a relatively high willingness to receive the COVID-19 vaccination among PLWH in Shijiazhuang. However, a small number of PLWH still held hesitancy; thus, more tailored policies or guidelines from the government should be performed to enhance the COVID-19 vaccination rate among PLWH

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease. SIGNIFICANCE: In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.publishedVersionPeer reviewe