A liposome encapsulated methylene blue-mediated electrochemical and UV-visible dual mode split-type immunoassay for the detection of 17ß-estradiol.

Herein, we fabricated an electrochemical (EC) and UV-visible absorption (UV-vis) dual mode split-type immunoassay for the detection of 17ß-estradiol (E2), which was mediated by liposome encapsulated methylene blue (MB@lip). MB molecule acted as the probe in the EC and UV-vis absorption dual mode detections, and its release was controlled by liposome. The competitive immune recognition was conducted between the E2 in the sample and E2 conjugated bovine serum protein (E2-BSA) adsorbed on the 96-wells plate in combining with E2 antibody labeled with MB@lip (E2-Ab/MB@lip). MB molecule could be released from the resulting immune composite of E2-BSA/E2-Ab/MB@lip in the presence of Triton X-100, and quantified by UV-vis and EC methods. The three-dimensional cross-linked reduced graphene oxide/Ti3C2 (3D-rGO/Ti3C2) aerogel was prepared through hydrothermal method, then complexed with the electroactive anthraquinone (AQ) and used as the electrode modified material. The AQ/3D-rGO/Ti3C2 composite had high surface area and provided abundant adsorption sites for MB, and the displacement/competitive behavior between AQ and MB could dexterously achieve the ratiometric EC detection of E2. In addition, the inherent blue color of MB allowed it to be analyzed by UV-vis absorption method. The proposed dual mode detection method exhibited broad linear ranges of 0.1 pg mL-1 to 50 ng mL-1 (by UV-vis) and 0.03 pg mL-1 to 50 ng mL-1 (by EC) for E2 detection, and the detection limits were 0.023 pg mL-1 (S/N = 3) and 8.0 fg mL-1 (S/N = 3), respectively. Moreover, the proposed immunoassay exhibited good practicability and was applied to monitor E2 in milk and serum successfully.

Harnessing machine learning for EEG signal analysis: Innovations in depth of anaesthesia assessment.

Anaesthesia, crucial to surgical practice, is undergoing renewed scrutiny due to the integration of artificial intelligence in its medical use. The precise control over the temporary loss of consciousness is vital to ensure safe, pain-free procedures. Traditional methods of depth of anaesthesia (DoA) assessment, reliant on physical characteristics, have proven inconsistent due to individual variations. In response, electroencephalography (EEG) techniques have emerged, with indices such as the Bispectral Index offering quantifiable assessments. This literature review explores the current scope and frontier of DoA research, emphasising methods utilising EEG signals for effective clinical monitoring. This review offers a critical synthesis of recent advances, specifically focusing on electroencephalography (EEG) techniques and their role in enhancing clinical monitoring. By examining 117 high-impact papers, the review delves into the nuances of feature extraction, model building, and algorithm design in EEG-based DoA analysis. Comparative assessments of these studies highlight their methodological approaches and performance, including clinical correlations with established indices like the Bispectral Index. The review identifies knowledge gaps, particularly the need for improved collaboration for data access, which is essential for developing superior machine learning models and real-time predictive algorithms for patient management. It also calls for refined model evaluation processes to ensure robustness across diverse patient demographics and anaesthetic agents. The review underscores the potential of technological advancements to enhance precision, safety, and patient outcomes in anaesthesia, paving the way for a new standard in anaesthetic care. The findings of this review contribute to the ongoing discourse on the application of EEG in anaesthesia, providing insights into the potential for technological advancement in this critical area of medical practice.

Treatment of hemolymphangioma by robotic surgery: A case report.

BACKGROUND: Hemolymphangioma of the jejunum is rare and lacks clinical specificity, and can manifest as gastrointestinal bleeding, abdominal pain, and intestinal obstruction. Computed tomography, magnetic resonance imaging, and other examinations show certain characteristics of the disease, but lack accuracy. Although capsule endoscopy and enteroscopy make up for this deficiency, the diagnosis also still requires pathology. CASE SUMMARY: A male patient was admitted to the hospital due to abdominal distension and abdominal pain, but a specific diagnosis by computed tomography examination was not obtained. Partial resection of the small intestine was performed by robotic surgery, and postoperative pathological biopsy confirmed the diagnosis of hemolymphangioma. No recurrence in the follow-up examination was observed. CONCLUSION: Robotic surgery is an effective way to treat hemolymphangioma through minimally invasive techniques under the concept of rapid rehabilitation.

Anthropogenic impacts and quantitative sources of nitrate in a rural-urban canal using a combined PMF, δ15N/δ18O-NO3-, and MixSIAR approach.

Nitrate (NO3-) pollution in irrigation canals is of great concern because it threatens canal water use; however, little is known about it at present. Herein, a combination of positive matrix factorization (PMF), isotope tracers, and Mixing Stable Isotope Analysis in R (MixSIAR) was developed to identify anthropogenic impacts and quantitative sources of NO3- in a rural-urban canal in China. The NO3- concentration (0.99-1.93 mg/L) of canal water increased along the flow direction and was higher than the internationally recognized eutrophication risk value in autumn and spring. The inputs of the Fuhe River, NH4+ fertilizer, soil nitrogen, manure & sewage, and rainfall were the main driving factors of canal water NO3- based on principal component analysis and PMF, which was supported by evidence from δ15N/δ18O-NO3-. According to the chemical and isotopic analyses, nitrogen transformation was weak, highlighting the potential of δ15N/δ18O-NO3- to trace NO3- sources in canal water. The MixSIAR and PMF results with a <15% divergence emphasized the predominance of the Fuhe River (contributing >50%) and anthropogenic impacts (NH4+ fertilizer plus manure & sewage, >37%) on NO3- in the entire canal, reflecting the effectiveness of the model analysis. According to the MixSIAR model, (1) higher NO3- concentration in canal water was caused by the general enhancement of human activities in spring and (2) NO3- source contributions were associated with land-use patterns. The high contributions of NH4+ fertilizer and manure & sewage showed inverse spatial variations, suggesting the necessity of reducing excessive fertilizer use in the agricultural area and controlling blind wastewater release in the urban area. These findings provide valuable insights into NO3- dynamics and fate for sustainable management of canal water resources. Nevertheless, long-term chemical and isotopic monitoring with alternative modeling should be strengthened for the accurate evaluation of canal NO3- pollution in future studies.

An electrochemically fabricated ZIF-67/[HOEMIM]BF4 coating for the solid-phase microextraction and detection of polycyclic aromatic hydrocarbons.

Coatings are considered to play a crucial role in solid-phase microextraction (SPME). In this work, a novel coating named ZIF-67/[HOEMIM]BF4 was fabricated through in situ potentiostatic electrodeposition in methanol solutions containing ZIF-67 precursors and 1-(2'-hydroxyethyl)-3-methylimidazolium tetrafluoroborate ([HOEMIM]BF4). Compared with the traditional solvothermal method, this method reduced the synthesis time and enabled ZIF-67 to grow directly on the surface of stainless-steel wire, effectively simplifying the preparation process and improving the coating reproducibility. Owing to the inherent characteristics such as high porosity and high thermal and mechanical stability, and the impressive morphological regulation and extraction function of [HOEMIM]BF4, the developed coating exhibited a prolonged service life and a better extraction capacity for trace polycyclic aromatic hydrocarbons (PAHs) compared to single ZIF-67 and commercial fibers. Under the optimal conditions, the linear range of the ZIF-67/[HOEMIM]BF4-based SPME-GC method was 0.01-500 µg L-1, and the detection limit was 0.27-5.2 ng L-1. When applied in the determination of PAHs in a real water sample, recoveries between 85.6-117.3% were obtained, indicating the potential of ZIF-67/[HOEMIM]BF4 in the high efficiency SPME and GC analysis of PAHs.

Silt-size sediment provenance of the Jianggang radial sand ridges in the southwestern Yellow Sea identified by geochemistry of quartz and K-feldspar.

In this paper, the geochemistry of K-feldspar and quartz, combined with MixSIAR and MDS models, was applied to illustrate the provenance of silt-size sediments in the Jianggang RSRs of the Yellow Sea, which profoundly affect the circulation of organic matter. The geochemical distributions revealed an apparent shoreward migration for sediments in the western offshore compared to eastern offshore. The models showed that the onshore RSRs silt-size sediments were mainly from the Yangtze River Mouth and Old Yellow River Delta, with contributions of 43.5 ± 15.3 % and 48.4 ± 13.9 %, respectively. While the offshore RSRs sediments were primarily from the Yangtze River Mouth (61.9 ± 18.0 %). Meanwhile, the transport patterns of silt-size sediments were proposed for the first time. The load calculation further showed that the expansion rate of local coast in 2023-2043 will be lower than in 1997-2017. Therefore, it was recommended to take actions for coastal development.

A magnetic porous carbon material derived from an MIL-101(Fe) complex for efficient magnetic solid phase extraction of fluoroquinolone antibiotics.

Extraction and determination of trace hazardous components from complex matrices continue to attract public attention. In this work, magnetic porous carbon (MPC) was prepared for efficient magnetic solid phase extraction (MSPE) of fluoroquinolone (FQ) antibiotics in food and water samples. To prepare the MPC, an Fe-based metal-organic framework (MIL-101(Fe)) was grown on a network of graphene oxide and multi-walled carbon nanotubes through a hydrothermal method, and then a carbonization process under a nitrogen atmosphere was carried out to obtain the MPC with high specific surface area and good magnetism. Four target FQs including ciprofloxacin (CIP), enrofloxacin (ENO), lomefloxacin (LOM) and ofloxacin (OFX) were enriched using the as-prepared MPC and determined by coupled high-performance liquid chromatography. Under the optimal conditions, the established MSPE-HPLC-UV detection method exhibited a linear range of 0.5-800 µg L-1 and detection limits of 0.11-0.18 µg L-1 with relative standard deviations (RSDs) of 0.5-4.8%. When applied in the determination of the above four FQs in real samples such as lake water, milk and pork, good recoveries between 85.2 and 103.7% were obtained, and the RSDs were less than 4.8%. This work indicates that the MPC material can be a good adsorption material and has good application prospects in antibiotics enrichment and/or removal from complex samples.

Pollution source identification of nitrogen and phosphorus in the lower West Main Canal, the Ganfu Plain irrigation district (South China).

The degradation of surface water quality has been a widespread concern around the world. However, irrigation canal water does not attract much attention although it is important to agriculture and population. In this study, a 5-year water quality monitoring of surface water was conducted in the lower West Main Canal of the Ganfu Plain irrigation district to identify the levels and pollution sources of nitrogen and phosphorus.Over 75% of samples had total phosphorus (TP) concentrations of > 0.02 mg/L, and all samples had total nitrogen (TN) concentrations of > 0.2 mg/L, indicating a risk of eutrophication. The concentrations of NO3--N and NH4+-N averagely occupied 57% and 18% of TN, respectively. PCA analysis showed that phosphorus and nitrogen in canal water were associated with meteorological factors, urban life and surface runoff, agricultural cultivation, livestock-poultry breeding, and water-sediment interaction in the wet season, whereas they were affected by meteorological factors, industrial effluent, urban domestic sewage, and livestock-poultry breeding in the dry season. Absolute principal component score-multiple linear regression (APCS-MLR) model results revealed that (1) agricultural cultivation plus livestock-poultry breeding contributed 43.2% of TP in canal water in the wet season, while livestock-poultry breeding contributed 52.9% in the dry season, and (2) domestic sewage plus surface runoff contributed 29.4% of TN in the wet season, while livestock-poultry breeding contributed 45.9% in the dry season. The unidentified sources had significant contributions of > 20% for almost all variables. So further investigations are required for determining unidentified sources, and anthropogenic pollution control is imperative for canal water quality protection.

A novel epileptic seizure prediction method based on synchroextracting transform and 1-dimensional convolutional neural network.

BACKGROUND AND OBJECTIVE: Epilepsy is a serious brain disorder affecting more than 50 million people worldwide. If epileptic seizures can be predicted in advance, patients can take measures to avoid unfortunate consequences. Important approaches for epileptic seizure predictions are often signal transformation and classification using electroencephalography (EEG) signals. A time-frequency (TF) transformation, such as the short-term Fourier transform (STFT), has been widely used over many years but curtailed by the Heisenberg uncertainty principle. This research focuses on decomposing epileptic EEG signals with a higher resolution so that an epileptic seizure can be predicted accurately before its episodes. METHODS: This study applies a synchroextracting transformation (SET) and singular value decomposition (SET-SVD) to improve the time-frequency resolution. The SET is a more energy-concentrated TF representation than classical TF analysis methods. RESULTS: The pre-seizure classification method employing a 1-dimensional convolutional neural network (1D-CNN) reached an accuracy of 99.71% (the CHB-MIT database) and 100% (the Bonn University database). The experiments on the CHB-MIT show that the accuracy, sensitivity and specificity from the SET-SVD method, compared with the results of the STFT, are increased by 8.12%, 6.24% and 13.91%, respectively. In addition, a multi-layer perceptron (MLP) was also used as a classifier. Its experimental results also show that the SET-SVD generates a higher accuracy, sensitivity and specificity by 5.0%, 2.41% and 11.42% than the STFT, respectively. CONCLUSIONS: The results of two classification methods (the MLP and 1D-CNN) show that the SET-SVD has the capacity to extract more accurate information than the STFT. The 1D-CNN model is suitable for a fast and accurate patient-specific EEG classification.

Pb and O isotopic characteristics of single minerals in the Jianggang radial sand ridges of the southwestern Yellow Sea: Implications for provenance and pathways of silt-size sediments.

Understanding the sediment provenance of the Jianggang radial sand ridges (RSRs) along the Jiangsu coast in the southwestern Yellow Sea is crucial for sustainable coastal development and land resource management. In this study, the provenance and transport patterns of silt-size sediments in the Jianggang RSRs were explored using Quartz oxygen (O) and K-feldspar lead (Pb) isotopic compositions and their large ion lithophile elements (LILEs) concentrations. The Pb-O isotopic compositions and concentrations of most LILEs in RSRs sediments were between those of the Yangtze River Mouth (YTZ), Old Yellow River Delta (OYR), and Modern Yellow River Mouth (MYR). The Pb-O isotopic compositions and typical elemental ratios were similar between the onshore and northwest offshore RSRs sediments, implying shoreward transport of offshore silt-size sediments. Through multidimensional scaling and graphic methods, it was found that the sediments of onshore and offshore RSRs originate mainly from the YTZ and OYR. Furthermore, the MixSIAR model showed that the contributions of the YTZ to onshore and offshore RSRs reached 33 ± 4 % and 36 ± 3 %, respectively. Followed by the OYR with contributions of 36 ± 3 % and 25 ± 8 %, respectively, and the contributions of the MYR and Korean Peninsula were <21 % and 8 %, respectively. Meanwhile, contributions from the Northern Chinese Deserts (approximately 10 %) deserved attention. Through the distribution of indicators, the transport patterns of silt-size sediments were proposed and compared with those of other fractions for the first time. According to the correlation analysis, the change in the area of central Jiangsu coast was mostly affected by terrestrial river supply and coastal mariculture. Therefore, it was necessary to control the scale of river reservoir construction and strengthen mariculture for sustainable land development and management. In future, comprehensive interdisciplinary and large temporal-spatial scales are suggested to further understand the coastal development.

Sensitive dual-mode detection of carbendazim by molecularly imprinted electrochemical sensor based on biomass-derived carbon-loaded gold nanoparticles.

A dual-mode electrochemical sensor was fabricated for carbendazim (CBD) detection. Biomass-derived carbon loaded gold nanoparticles (AuNPs/BC) were firstly coated on a glassy carbon electrode (GCE), and then molecularly imprinted polymer (MIP) of o-aminophenol was prepared on the resulting AuNPs/BC/GCE through electrochemical method in the presence of CBD. The AuNPs/BC had excellent conductivity, large surface and good electrocatalysis, while the imprinted film presented good recognition. Thus, the obtained MIP/AuNPs/BC/GCE exhibited sensitive current response to CBD. Furthermore, the sensor displayed good impedance response to CBD. Hence, a dual-mode detection platform for CBD was established. Under optimum conditions, the linear response ranges were as wide as 1.0 nM - 15 µM (by differential pulse voltammetry, DPV) and 1.0 nM - 10 µM (by electrochemical impedance spectroscopy, EIS), and the detection limits for these two methods were as low as 0.30 nM (S/N = 3) and 0.24 nM (S/N = 3), respectively. The sensor also had high selectivity, stability and reproducibility. The sensor was applied to detect CBD in spiked real samples, including cabbage, peach, apple and lake water, and the recoveries were 85.8-108% (by DPV) and 91.4-110% (by EIS); the relative standard deviations (RSD) were 3.4-5.3% (by DPV) and 3.7-5.1% (by EIS), respectively. The results were consistent with that obtained by high-performance liquid chromatography. Therefore, this sensor is a simple and effective tool for CBD detection, and it has good application potential.

Effects of vaccines on clinical characteristics of convalescent adult patients infected with SARS-CoV-2 Omicron variant: A retrospective study.

Introduction: The protective effect of SARS-CoV-2 vaccines has become a global focus due to Omicron variant pandemic. The effects of various SARS-CoV-2 vaccines are diverse. However, studies on the effect of domestic vaccines on clinical characteristics in convalescent adult patients infected with the Omicron variant are lacking. Methods: In this retrospective, single-center cohort study, the effect of three domestic vaccines on clinical characteristics of convalescent adult patients infected with the Omicron variant was investigated in the initial largest outbreak of the Omicron variant infection between January and February 2022 in Tianjin, China. The primary endpoint was COVID-19 severity and the secondary endpoints were re-positive results on nucleic acid tests, liver and kidney function, and inflammation levels during recovery. Results: A total of 320 adult patients infected with the Omicron variant were enrolled, including 296 post-vaccination and 24 unvaccinated patients. The median age of the unvaccinated patients was higher than that of vaccinated patients, but no significant difference was detected in the sex composition ratio between the different groups. Binary logistic regression results suggested that Sinopharm and Sinovac vaccine was an independent protective factor for relieving the severity of the Omicron variant infection. Regrettably, the vaccines did not showed any protective effect on the liver and kidney function of convalescent adult patients. Three domestic vaccines significantly relieved inflammation and increased the SARS-CoV-2-specific antibody levels. Furthermore, Sinovac and CanSino vaccines had a better immune stimulation effect on increasing T lymphocytes levels in convalescent adult patients. In addition, three domestic vaccines have protective effects on preventing re-detectable positive (RP) result in convalescent adult patients. Conclusion: Although the three domestic vaccines cannot prevent the infection of the Omicron variant, it has a significant protective effect in adult patients. This study supports the policy of accelerating to vaccination worldwide combat the evolving and mutating SARS-CoV-2. Discussion: Omicron spreads faster and might escape antibodies more readily than previous variants, increasing the cases of reinfection and breakthrough infections in vaccinated people. Although vaccinated people are likely to have a much lower risk of severe disease from Omicron infection, many issues still need to be considered. Concerns about lower vaccine efficacy because of new variants might have changed our understanding of the COVID-19 endgame, disabusing the world of the notion that global vaccination is by itself adequate for controlling SARS-CoV-2 infection. The current data showed that vaccination with three domestic SARS-CoV-2 vaccines alleviates the disease severity of adult patients with COVID-19, reduces the inflammation level and the RP rate of convalescent adult patients, and enhances body's defense against the virus in convalescent adult patients. Moreover, our study has highlighted that a combination prevention approach of vaccination and public health measures would be an effective strategy.

Clinical and immunological features of convalescent pediatric patients infected with the SARS-CoV-2 Omicron variant in Tianjin, China.

COVID-19 has spread surprisingly fast worldwide, and new variants continue to emerge. Recently, the World Health Organization acknowledged a new mutant strain "Omicron", with children were accounting for a growing share of COVID-19 cases compared with other mutant strains. However, the clinical and immunological characteristics of convalescent pediatric patients after Omicron infection were lacking. In this study, we comparatively analyzed the clinical data from pediatric patients with adult patients or healthy children and the effects of SARS-CoV-2 vaccine on the clinical and immune characteristics in convalescent pediatric patients. Our results indicated that convalescent pediatric patients had unique clinical and immune characteristics different from those of adult patients or healthy children, and SARS-CoV-2 vaccination significantly affected on the clinical and immune characteristics and the prevention of nucleic acid re-detectable positive (RP) in convalescent patients. Our study further deepens the understanding of the impact of Omicron on the long-term health of pediatric patients and provides a valuable reference for the prevention and treatment of children infected with Omicron.

Clinical characteristics and risks of the convalescent COVID-19 patients with re-detectable positive RNA test: a 430 patients with Omicron infected cross-sectional survey in Tianjin, China.

BACKGROUND: The outbreak of severe acute respiratory syndrome coronavirus (SARS-CoV-2) Omicron variant occurred in Tianjin, China, at the beginning of 2022. In the present study, we identified risk factors that may affect positive (RP) RNA re-testing in recovered patients infected with Omicron variants during recovery in hospital. METHODS: We retrospectively analyzed the medical records of 425 patients with Omicron variant infection admitted to our medical center from January 21, 2022 to February 24, 2022, based on the recurrence of RT-PCR positive results for SARS-CoV-2 after cure and discharge. Patients were divided into re-tested positive (RP) and non-re-detectable positive patients (NRP) groups, and clinical data from both groups were analyzed to investigate the characteristics and risk factors of RP patients. RESULTS: Univariate analysis showed significant differences in age, vaccination rate and dose, partial signs and symptoms, most co-existing disorders, and levels of CRP and IL-6 between the RP and NRP groups (all P < 0.05), while multifactorial logistic regression analysis showed that vaccination status and levels of IL-6 were independent risk factors for RP patients. CONCLUSION: Our results suggested that clinicians should assess the probability of "re-positive" nucleic acid tests after discharge, taking the following indicators into account: pre-admission underlying diseases, unvaccinated status, and high levels of CRP and IL-6. Post-discharge isolation and follow-up should also be strengthened.

The isotopic composition of organic carbon, nitrogen and provenance of organic matter in surface sediment from the Jiangsu tidal flat, southwestern Yellow Sea.

The Jiangsu tidal flat is a significant organic matter reservoir, but quantitative studies of organic matter sources are scarce. In this study, total organic carbon (TOC) and total nitrogen (TN) concentrations and δ13Corg and δ15Ntotal values of surface sediment from Jiangsu tidal flat were investigated for their distributions, influencing factors, and sources of organic matter. TOC and TN were high in the center of study area and correlated well with grain size, indicating hydrodynamic influence on organic matter. High TOC/TN and low δ13Corg and δ15Ntotal in estuaries were characteristic of C3 plants, soil, and fertilizer sources, suggesting source effect on the distribution of organic matter. The MixSIAR model revealed that marine sources were dominant with a contribution reaching 56.9 %, followed by uniform of C3 plants, soil and fertilizer, while domestic sewage was least prominent. This study enriched theories of the biogeochemical cycle and ecological protection in the southwestern Yellow Sea.

A novel empirical wavelet SODP and spectral entropy based index for assessing the depth of anaesthesia.

The requirement for anaesthesia during modern surgical procedures is unquestionable to ensure a safe experience for patients with successful recovery. Assessment of the depth of anaesthesia (DoA) is an important and ongoing field of research to ensure patient stability during and post-surgery. This research addresses the limitations of current DoA indexes by developing a new index based on electroencephalography (EEG) signal analysis. Empirical wavelet transformation (EWT) methods are employed to extract wavelet coefficients before statistical analysis. The features Spectral Entropy and Second Order Difference Plot are extracted from the wavelet coefficients. These features are used to train a new index, SSEDoA, utilising a Support Vector Machine (SVM) with a linear kernel function. The new index accurately assesses the DoA to illustrate the transition between different anaesthetic stages. Testing was undertaken with nine patients and an additional four patients with low signal quality. Across the nine patients we tested, an average correlation of 0.834 was observed with the Bispectral (BIS) index. The analysis of the DoA stage transition exhibited a Choen's Kappa of 0.809, indicative of a high agreement.

Signature Based on Six Autophagy-related Genes to Predict Prognosis of Head and Neck Squamous Cell Carcinoma.

OBJECTIVE: The present study aimed to develop an autophagy-related gene prognostic prediction model to provide survival risk prediction for head and neck squamous cell carcinoma (HNSCC) patients. METHODS: The K-mean cluster analysis was performed on HNSCC samples based on the expression values of 210 autophagy-related genes for candidate signature gene selection. LASSO Cox regression analysis was generated using the potential genes and the risk score was calculated from the prognosis model. The risk score was processed as an independent prognostic indicator to construct the nomogram model. The immune status including immune cell infiltration ratio and checkpoints of patients with HNSCC in high- and low-risk groups was also explored. RESULTS: LASSO Cox regression analysis was performed on the selected autophagy-related genes. According to the lambda value corresponding to the number of different genes in the LASSO Cox analysis, six genes (GABARAPL2, SAR1A, ST13, GAPDH, FADD and LAMP1) were finally chosen. The risk score based on the genes was generated, which was an independent prognostic marker for HNSCC. The prognostic prediction model (nomogram) was further optimized by the independent prognostic factors (risk score), which can better predict the prognosis and survival of patients. With the risk score and prognosis model, eight types of immune cells and six key immune checkpoints (CTLA4, PD1, IDO1, TDO2, LAG3, TIGIT) displayed expression specificity. CONCLUSION: This study identified several potential prognostic biomarkers and established an autophagy-related prognostic prediction model for HNSCC, which provides a valuable reference for future clinical research.

Characteristics of airborne bacterial communities and antibiotic resistance genes under different air quality levels.

Pathogenic bacteria and antibiotic resistance genes (ARGs) in bioaerosols are major threats to human health. In this study, the microbial community structure and ARG distribution characteristics of airborne bacteria in total suspended particulates (TSP) and PM2.5 were investigated under different air quality levels in Xinxiang, Central China. The results revealed that with the deterioration of air quality, the concentrations of airborne bacteria in both TSP and PM2.5 decreased; however, the relative amounts of pathogenic bacteria increased. The predominant genera in pathogenic bacteria of Bacillus, Sphingomonas, Corynebacterium, Rhodococcus, and Staphylococcus were identified in both TSP and PM2.5. Although the airborne bacteria concentrations and absolute abundances of ARGs in TSP were higher than those in PM2.5 under identical air quality conditions, the bacterial community structure and relative amounts of pathogenic bacteria were similar. In addition, the relationship between environmental factors of ions, metal elements, and meteorological parameters and the community structures of airborne bacteria and pathogenic bacteria were also analyzed. The effects of soluble ions and metal elements on several dominant genera of total bacteria and pathogenic bacteria differed, probably due to the strong tolerance of pathogenic bacteria to harsh atmospheric environments Different subtypes of ARGs showed various distribution characteristics with variations in air quality. The deterioration of air quality can inhibit the dissemination of ARGs, as the minimum values of all ARGs and class 1 integrase intI1 were observed under Severely Polluted conditions. This study provides a comprehensive understanding of the effect of air pollution levels on the airborne bacteria community composition and ARG distribution.

A Novel Permutation Entropy-Based EEG Channel Selection for Improving Epileptic Seizure Prediction.

The key research aspects of detecting and predicting epileptic seizures using electroencephalography (EEG) signals are feature extraction and classification. This paper aims to develop a highly effective and accurate algorithm for seizure prediction. Efficient channel selection could be one of the solutions as it can decrease the computational loading significantly. In this research, we present a patient-specific optimization method for EEG channel selection based on permutation entropy (PE) values, employing K nearest neighbors (KNNs) combined with a genetic algorithm (GA) for epileptic seizure prediction. The classifier is the well-known support vector machine (SVM), and the CHB-MIT Scalp EEG Database is used in this research. The classification results from 22 patients using the channels selected to the patient show a high prediction rate (average 92.42%) compared to the SVM testing results with all channels (71.13%). On average, the accuracy, sensitivity, and specificity with selected channels are improved by 10.58%, 23.57%, and 5.56%, respectively. In addition, four patient cases validate over 90% accuracy, sensitivity, and specificity rates with just a few selected channels. The corresponding standard deviations are also smaller than those used by all channels, demonstrating that tailored channels are a robust way to optimize the seizure prediction.

A novel spectral entropy-based index for assessing the depth of anaesthesia.

Anaesthesia is a state of temporary controlled loss of awareness induced for medical operations. An accurate assessment of the depth of anaesthesia (DoA) helps anesthesiologists to avoid awareness during surgery and keep the recovery period short. However, the existing DoA algorithms have limitations, such as not robust enough for different patients and having time delay in assessment. In this study, to develop a reliable DoA measurement method, pre-denoised electroencephalograph (EEG) signals are divided into ten frequency bands (α, ß1, ß2, ß3, ß4, ß, ßγ, γ, δ and θ), and the features are extracted from different frequency bands using spectral entropy (SE) methods. SE from the beta-gamma frequency band (21.5-38.5 Hz) and SE from the beta frequency band show the highest correlation (R-squared value: 0.8458 and 0.7312, respectively) with the most popular DoA index, bispectral index (BIS). In this research, a new DoA index is developed based on these two SE features for monitoring the DoA. The highest Pearson correlation coefficient by comparing the BIS index for testing data is 0.918, and the average is 0.80. In addition, the proposed index shows an earlier reaction than the BIS index when the patient goes from deep anaesthesia to moderate anaesthesia, which means it is more suitable for the real-time DoA assessment. In the case of poor signal quality (SQ), while the BIS index exhibits inflexibility with cases of poor SQ, the new proposed index shows reliable assessment results that reflect the clinical observations.