Preservation of Porcine Donation after Circulatory Death (DCD) Liver by Perfusion and Orthotopic Liver Transplantation.

Conventional static cold storage (SCS) exacerbates ischemic injury in the DCD liver, leading to severe complications for transplant recipients. To address this issue, clinical application of MP technology for donor liver preservation is underway. Simultaneously, efforts are focused on the development of various MP instruments, validated through relevant animal model experiments. Effective large animal trials play a pivotal role in clinical applications. However, challenges persist in the ex vivo preservation of DCD livers and the transplantation procedure in pigs. These hurdles encompass addressing the prolonged preservation of donor livers, conducting viability tests, alleviating ischemic injuries, and shortening the anhepatic phase. The use of a variable temperature-controlled MP device facilitates the prolonged preservation of DCD livers through sequential Dual Hypothermic Oxygenated Machine Perfusion (DHOPE) and Normothermic Machine Perfusion (NMP) modes. This protocol enhances the porcine OLTx model by improving the quality of DCD livers, optimizing the anastomosis technique, and reducing the duration of the anhepatic phase.

Transcriptome analysis suggested that lncRNAs regulate rapeseed seedlings in responding to drought stress by coordinating the phytohormone signal transduction pathways.

The growth, yield, and seed quality of rapeseed are negatively affected by drought stress. Therefore, it is of great value to understand the molecular mechanism behind this phenomenon. In a previous study, long non-coding RNAs (lncRNAs) were found to play a key role in the response of rapeseed seedlings to drought stress. However, many questions remained unanswered. This study was the first to investigate the expression profile of lncRNAs not only under control and drought treatment, but also under the rehydration treatment. A total of 381 differentially expressed lncRNA and 10,253 differentially expressed mRNAs were identified in the comparison between drought stress and control condition. In the transition from drought stress to rehydration, 477 differentially expressed lncRNAs and 12,543 differentially expressed mRNAs were detected. After identifying the differentially expressed (DE) lncRNAs, the comprehensive lncRNAs-engaged network with the co-expressed mRNAs in leaves under control, drought and rehydration was investigated. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of co-expressed mRNAs identified the most significant pathways related with plant hormones (expecially abscisic acid, auxin, cytokinins, and gibberellins) in the signal transduction. The genes, co-expressed with the most-enriched DE-lncRNAs, were considered as the most effective candidates in the water-loss and water-recovery processes, including protein phosphatase 2 C (PP2C), ABRE-binding factors (ABFs), and SMALL AUXIN UP-REGULATED RNAs (SAURs). In summary, these analyses clearly demonstrated that DE-lncRNAs can act as a regulatory hub in plant-water interaction by controlling phytohormone signaling pathways and provided an alternative way to explore the complex mechanisms of drought tolerance in rapeseed.

REEP3 is a potential diagnostic and prognostic biomarker correlated with immune infiltration in pancreatic cancer.

Receptor Expression-Enhancing Protein 3 (REEP3) serves as a pivotal enzyme crucial for endoplasmic reticulum (ER) clearance during mitosis and is implicated in the advancement of diverse malignancies. Nonetheless, the biological role and mechanisms of REEP3 in pancreatic cancer patients, along with its interplay with immune infiltration, remain inadequately elucidated. In this study, we initially analyzed the differential expression of REEP3 between pancreatic cancer tissues and normal pancreas tissues using the Cancer Genome Atlas (TCGA), GTEx and Gene Expression Omnibus (GEO) databases. Subsequently, we utilized Kaplan-Meier analysis, Cox regression and ROC curve to determine the predictive value of REEP3 for the clinical outcomes of pancreatic cancer patients. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), were conducted to explore the potential signaling pathways and biological functions associated with pancreatic cancer. Furthermore, we investigated the PPI network, miRNA, RBP and transcription factor interactions of REEP3 using databases such as GeneMania, STRING, StarBase, KnockTK, ENCODE, Jaspar and hTFtarget. Lastly, the "ssGSEA" algorithm and TIMER database were employed to investigate the correlation between REEP3 expression and immune infiltration as well as immune checkpoints. The expression of REEP3 in pancreatic cancer showed a significantly higher level compared to that in normal tissues. ROC curve analysis indicated that REEP3 holds substantial diagnostic potential for pancreatic cancer patients. Elevated REEP3 expression correlated with unfavorable outcomes in terms of both overall survival and relapse-free survival, establishing it as a notable adverse prognostic marker in pancreatic cancer. Moreover, both univariate and multivariate Cox regression analyses demonstrated that REEP3 maintained an independent association with overall survival. Functional enrichment analyses revealed pathways significantly linked to REEP3, including cytoplasmic translation, wound healing, viral processes, regulation of cellular component size and actin filament organization. Additionally, REEP3 expression displayed a significant positive correlation with CD8+ T cells, B cells, natural killer cells, dendritic cells and macrophages. REEP3 is a potential diagnostic, prognostic marker and immunotherapeutic target for pancreatic cancer.

Exploring the casual association between gut microbiome, circulating inflammatory cytokines and chronic pancreatitis: A Mendelian randomization analysis.

It has been established that gut dysbiosis contributed to the pathogenesis of digestive disorders. We aimed to explore the causal relationships between intestinal microbiota, circulating inflammatory cytokines and chronic pancreatitis (CP). Summary statistics of genome-wide association studies (GWAS) of intestinal microbiome was retrieved from the MiBioGen study and the GWAS data of 91 circulating inflammatory cytokines and CP were obtained from the GWAS catalog. The 2-sample bidirectional Mendelian randomization (MR) analysis was performed between gut microbiota, circulating inflammatory cytokines and CP, in which the inverse variance weighted (IVW) method was regarded as the primary analysis approach. To prove the reliability of the causal estimations, multiple sensitivity analyses were utilized. IVW results revealed that genetically predicted 2 genera, including Sellimonas and Eubacteriumventriosumgroup, and plasm C-C motif chemokine 23 (CCL23) level were positively associated with CP risk, while genus Escherichia Shigella, Eubacteriumruminantiumgroup and Prevotella9, and plasma Caspase 8, Adenosine Deaminase (ADA), and SIR2-like protein 2 (SIRT2) level, demonstrated an ameliorative effect on CP. Leave-one-out analysis confirmed the robustness of the aforementioned causal effects and no significant horizontal pleiotropy or heterogeneity of the instrumental variables was detected. However, no association was found from the identified genera to the CP-related circulating inflammatory cytokines. Besides, the reverse MR analysis demonstrated no causal relationship from CP to the identified genera and circulating inflammatory cytokines. Taken together, our comprehensive analyses offer evidence in favor of the estimated causal connections from the 5 genus-level microbial taxa and 4 circulating inflammatory cytokines to CP risk, which may help to reveal the underlying pathogenesis of CP.

An audio-semantic multimodal model for automatic obstructive sleep Apnea-Hypopnea Syndrome classification via multi-feature analysis of snoring sounds.

Introduction: Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a common sleep-related breathing disorder that significantly impacts the daily lives of patients. Currently, the diagnosis of OSAHS relies on various physiological signal monitoring devices, requiring a comprehensive Polysomnography (PSG). However, this invasive diagnostic method faces challenges such as data fluctuation and high costs. To address these challenges, we propose a novel data-driven Audio-Semantic Multi-Modal model for OSAHS severity classification (i.e., ASMM-OSA) based on patient snoring sound characteristics. Methods: In light of the correlation between the acoustic attributes of a patient's snoring patterns and their episodes of breathing disorders, we utilize the patient's sleep audio recordings as an initial screening modality. We analyze the audio features of snoring sounds during the night for subjects suspected of having OSAHS. Audio features were augmented via PubMedBERT to enrich their diversity and detail and subsequently classified for OSAHS severity using XGBoost based on the number of sleep apnea events. Results: Experimental results using the OSAHS dataset from a collaborative university hospital demonstrate that our ASMM-OSA audio-semantic multimodal model achieves a diagnostic level in automatically identifying sleep apnea events and classifying the four-class severity (normal, mild, moderate, and severe) of OSAHS. Discussion: Our proposed model promises new perspectives for non-invasive OSAHS diagnosis, potentially reducing costs and enhancing patient quality of life.

Fuzzy-set qualitative comparative analysis of factors affecting the use of e-cigarettes among college students in Guangdong province.

INTRODUCTION: In recent years, e-cigarettes as an emerging tobacco product have been favored by college students. Our study aims to explore the factors affecting the use of e-cigarettes among college students and to put forward feasible suggestions for effectively controlling the use of e-cigarettes among college students. METHODS: The participating students were from three undergraduate and three specialized colleges in Guangdong Province, surveyed from January to March 2022. The Fuzzy-set Qualitative Comparative Analysis (fsQCA) method was used to analyze the influence mechanism and path of five antecedents: self-efficacy, social environment, cognition, sales environment, and negative outcome expectation, on the use of e-cigarettes. The fsQCA used in this study is a novel research methodology that combines the strengths of qualitative and quantitative analyses, through which we can determine which conditions are essential to the outcomes that lead to e-cigarette use among college students, and which combinations of conditions are more important than others. RESULTS: The interaction of self-efficacy, social environment, cognition, sales environment, and negative outcome expectation, affected college students' use of e-cigarettes. Through the fsQCA method, it was found that self-efficacy alone constitutes a necessary condition for college students not to use e-cigarettes. There are four possible pathways for college students not to use e-cigarettes, with higher self-efficacy, correct cognition, and a healthy social environment influencing the most important combination of conditions for college students to use e-cigarettes. CONCLUSIONS: The use of e-cigarettes by students in Guangdong Province is the result of the synergistic effect of multiple factors. Tobacco control action suggestions focus on improving students' self-efficacy and paying attention to the combination of different factors to achieve more effective tobacco control.

Cathodic Deposition-Assisted Synthesis of Thin Glass MOF Films for High-Performance Gas Separations.

Glass metal-organic framework (MOF) films can be fabricated from their crystalline counterparts through a melt-quenching process and are prospective candidates for gas separation because of the elimination of the grain boundaries in crystalline MOF films. However, current techniques are limited to producing glass MOF films with a thickness of tens of micrometers, which leads to ultralow gas permeances. Here, we report a novel cathodic deposition-assisted synthesis of glass ZIF-62 films with a thickness as low as ~1 µm. Electrochemical analyses and deposition experiments suggest that the cathodic deposition can lead to pure crystalline ZIF-62 films with a controllable thickness of ~2 µm to ~15 µm. Accordingly, glass ZIF-62 films with a thickness of ~1 µm to ~10 µm can be obtained after a thermal treatment. The fabricated defect-free glass ZIF-62 film measuring 2 µm in thickness shows a remarkable CO2/N2 and CO2/CH4 selectivity of 31.4 and 33.4, respectively, with a CO2 permeance which is over 30 times higher than the best-performing glass ZIF-62 films in literature.

Insights into adsorbable organic halogen analysis: Two overlooked factors impacting water quality assessment.

Adsorbable organic halogen (AOX) represents the total amount of halogenated organics that can be adsorbed on activated carbon (AC) from samples. Measuring AOX is crucial for assessing water quality, and any erroneous estimation of AOX risks misleading decision-makers. This study demonstrated two overlooked factors that may introduce biases to AOX measurement. The first one relates to impurities in the gas transfer tubes of AOX combustion system and in the pressurized gas of AOX separation system, which resulted in significant fluctuations and high blank values (8.5-118.0 µg-Cl/L). The solutions of above issues are to warming up the combustor for several runs and replacing the pressurized air with argon gas in the separator, which could drop the blank AOX values to 9.1-10.0 µg-Cl/L. The second one involves coexisting chloride ion (Cl-) during AOX analysis, which interfered with AOX measurements (T. test, p < 0.05) even at low concentration levels (e.g., 10 mg/L Cl- in samples with 100 µg-Cl/L p-chlorophenol). Results show that AC captured 0.02-0.11 % of Cl-, resulting in 17.7-24.5 µg-Cl/L AOX responses in control samples containing 15-130 mg/L Cl- only. Furthermore, a significant mass imbalance of Cl- (3.58-8.39 %) during analysis process suggests a potential impact of residual Cl- on subsequent samples. By comparing synthetic and actual waters, samples with low dissolved organic carbon (DOC) were more susceptible to interference from Cl- on AOX measurement than those with high DOC. These findings underscore the pressing need to optimize existing AOX methods or develop alternative analytical methods to ensure accurate water quality assessment.

A Critical Review of Conventional and Modern Approaches to Develop Herbicide-Resistance in Rice.

Together with rice, weeds strive for nutrients and space in farmland, resulting in reduced rice yield and quality. Planting herbicide-resistant rice varieties is one of the effective ways to control weeds. In recent years, a series of breakthroughs have been made to generate herbicide-resistant germplasm, especially the emergence of biotechnological tools such as gene editing, which provides an inherent advantage for the knock-out or knock-in of the desired genes. In order to develop herbicide-resistant rice germplasm resources, gene manipulation has been conducted to enhance the herbicide tolerance of rice varieties through the utilization of techniques such as physical and chemical mutagenesis, as well as genome editing. Based on the current research and persisting problems in rice paddy fields, research on the generation of herbicide-resistant rice still needs to explore genetic mechanisms, stacking multiple resistant genes in a single genotype, and transgene-free genome editing using the CRISPR system. Current rapidly developing gene editing technologies can be used to mutate herbicide target genes, enabling targeted genes to maintain their biological functions, and reducing the binding ability of target gene encoded proteins to corresponding herbicides, ultimately resulting in herbicide-resistant crops. In this review article, we have summarized the utilization of conventional and modern approaches to develop herbicide-resistant cultivars in rice as an effective strategy for weed control in paddy fields, and discussed the technology and research directions for creating herbicide-resistant rice in the future.

G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction.

Developing new drugs is costly, time-consuming, and risky. Drug-target affinity (DTA), indicating the binding capability between drugs and target proteins, is a crucial indicator for drug development. Accurately predicting interaction strength between new drug-target pairs by analyzing previous experiments aids in screening potential drug molecules, repurposing them, and developing safe and effective medicines. Existing computational models for DTA prediction rely on strings or single-graph neural networks, lacking consideration of protein structure and molecular semantic information, leading to limited accuracy. Our experiments demonstrate that string-based methods may overlook protein conformations, causing a high root mean square error (RMSE) of 3.584 in affinity due to a lack of spatial context. Single graph networks also underperform on topology features, with a 6% lower confidence interval (CI) for activity classification. Absent semantic information also limits generalization across diverse compounds, resulting in 18% increment in RMSE and 5% in misclassifications within quantifications study, restricting potential drug discovery. To address these limitations, we propose G-K BertDTA, a novel framework for accurate DTA prediction incorporating protein features, molecular semantic features, and molecular structural information. In this proposed model, we represent drugs as graphs, with a GIN employed to learn the molecular topological information. For the extraction of protein structural features, we utilize a DenseNet architecture. A knowledge-based BERT semantic model is incorporated to obtain rich pre-trained semantic embeddings, thereby enhancing the feature information. We extensively evaluated our proposed approach on the publicly available benchmark datasets (i.e., KIBA and Davis), and experimental results demonstrate the promising performance of our method, which consistently outperforms previous state-of-the-art approaches. Code is available at https://github.com/AmbitYuki/G-K-BertDTA.

Integrated assessment of the pollution and risk of heavy metals in soils near chemical industry parks along the middle Yangtze River.

Industrialization in riparian areas of critical rivers has caused significant environmental and health impacts. Taking eight industrial parks along the middle Yangtze River as examples, this study proposes a multiple-criteria approach to investigate soil heavy metal pollution and associated ecological and health risks posed by industrial activities. Aiming at seven heavy metals, the results show that nickel (Ni), cadmium (Cd), and copper (Cu) exhibited the most significant accumulation above background levels. The comprehensive findings from Pearson correlation analysis, cluster analysis, principal component analysis, and industrial investigation uncover the primary sources of Cd, arsenic (As), mercury (Hg), and lead (Pb) to be chemical processing, while Ni and chromium (Cr) are predominantly derived from mechanical and electrical equipment manufacturing. In contrast, Cu exhibits a broad range of origins across various industrial processes. Soil heavy metals can cause serious ecological and carcinogenic health risks, of which Cd and Hg contribute to >70 % of the total ecological risk, and As contributes over 80 % of the total health risk. This study highlights the importance of employing multiple mathematical and statistical models in determining and evaluating environmental hazards, and may aid in planning the environmental remediation engineering and optimizing the industry standards.

Discovery of lung adenocarcinoma tumor antigens and ferroptosis subtypes for developing mRNA vaccines.

mRNA vaccines are becoming a feasible alternative for treating cancer. To develop mRNA vaccines against LUAD, potential antigens were identified and LUAD ferroptosis subtypes distinguished for selecting appropriate patients. The genome expression omnibus, cancer genome atlas (TCGA) and FerrDB were used to collect gene expression profiles, clinical information, and the genes involved in ferroptosis, respectively. cBioPortal was used to visualize and compare genetic alterations, GEPIA2 to calculate prognostic factors of the selected antigens, and TIMER to visualize the relationship between potential antigens and tumor immune cell infiltration. Consensus clustering analysis was utilized to identify ferroptosis subtypes and their prognostic value assessed by Log-rank and cox regression tests. The modules of ferroptosis-related gene screening were conducted by weight gene co-expression network analysis. The LUAD ferroptosis landscape was visualized through dimensionality reduction and graph learning. Six tumor antigens had obvious LUAD-mutations, positively correlated with different antigen-presenting cells, and might induce tumor cell ferroptosis. LUAD patients were stratified into three ferroptosis subtypes (FS1, FS2, and FS3) according to diverse molecular, cellular, and clinical characteristics. FS3 showed the highest tumor mutation burden and the most somatic mutations, deemed potential indicators of mRNA vaccine effectiveness. Moreover, different ferroptosis subtypes expressed distinct immune checkpoints and immunogenic cell death modulators. AGPS, NRAS, MTDH, PANX1, NOX4, and PPARD are potentially suitable for mRNA vaccinations against LUAD, specifically in patients with FS3 tumors. This study defines vaccination candidates and establishes a theoretical basis for LUAD mRNA vaccinations.

The antipsychotic drug pimozide promotes apoptosis through the RAF/ERK pathway and enhances autophagy in breast cancer cells.

The antipsychotic drug pimozide has been demonstrated to inhibit cancer. However, the precise anti-cancer mechanism of pimozide remains unclear. The purpose of this study was to investigate the effects of pimozide on human MCF-7 and MDA-MB-231 breast cancer cell lines, and the potential involvement in the RAF/ERK signaling. The effects of pimozide on cells were examined by 4,5-dimethylthiazol-2-yl-3,5-diphenylformazan, wound healing, colony formation, transwell assays, and caspase activity assay. Flow cytometry and acridine orange and ethidium bromide staining were performed to assess changes in cells. Transmission electron microscopy and monodansylcadaverine staining were used to observe autophagosomes. The cyclic adenosine monophosphate was evaluated using the FRET system. Immunohistochemistry, immunofluorescence, RNA interference, and western blot investigated the expression of proteins. Mechanistically, we focus on the RAF1/ERK signaling. We detected pimozide was docked to RAF1 by Schrodinger software. Pimozide down-regulated the phosphorylation of RAF1, ERK 1/2, Bcl-2, and Bcl-xl, up-regulated Bax, and cleaved caspase-9 to induce apoptosis. Pimozide might promote autophagy by up-regulating cAMP. The enhancement of autophagy increased the conversion of LC3-I to LC3-II and down-regulated p62 expression. But mTOR signaling was not involved in promoting autophagy. The knockdown of RAF1 expression induced autophagy and apoptosis in breast cancer cells, consistent with the results of pimozide or sorafenib alone. Blocked autophagy by chloroquine resulted in the impairment of pimozide-induced apoptosis. These data showed that pimozide inhibits breast cancer by regulating the RAF/ERK signaling pathway and might activate cAMP-induced autophagy to promote apoptosis and it may be a potential drug for breast cancer treatment.

Comparison of laparoscopic radiofrequency ablation with percutaneous radiofrequency ablation in the treatment of chronic hepatitis B-related hepatocellular carcinoma involving specific sites: A retrospective cohort study.

BACKGROUND: This study compared the effectiveness and safety of laparoscopic radiofrequency ablation (LRFA) and percutaneous radiofrequency ablation (PRFA) in the treatment of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) involving specific sites. METHODS: This retrospective cohort study included patients with HBV-related HCC involving specific sites treated with LRFA or PRFA between January 2012 and December 2020. The overall survival (OS), disease-free survival (DFS), and complications were compared between the LRFA and PRFA groups. The Cox proportional-hazards regression model was used to determine the factors affecting prognosis. RESULTS: This study included 109 patients: 69 in the LRFA group and 40 cases in the PRFA group. No significant differences were found in the 3-year OS rate between the two groups (73.7% vs. 70.0%, P = 0.514), but the LRFA group showed a higher 3-year DFS rate than the PRFA group (58.2% vs. 42.5%, P = 0.018). The RFA method was not associated with OS but was independently associated with DFS (LRPA vs. PRFA, HR = 2.078, P = 0.012). The common complications were ascites, pleural effusion, and fever in the two groups. The occurrence of complications in patients treated with LRFA or PRFA was similar (15.9% vs. 12.5%, P = 0.785). CONCLUSION: LRFA was associated with a better DFS in patients with HBV-related HCC involving specific sites. Thus, LRFA might have more advantages in treating liver cancer involving specific sites.

Twenty-four-hour urinary protein excretion in uncomplicated singleton pregnancy.

BACKGROUND: Twenty-four-hour urinary total protein excretion is an essential parameter used for evaluation of renal function and early detection of gestational complications. However, data on reference ranges of 24-hour urinary total protein excretion in normal pregnancy are scarce. OBJECTIVE: This study aimed to determine reference ranges for 24-hour urinary total protein excretion in a population with uncomplicated singleton pregnancies using a standard method for urinary total protein. In addition, the values of 24-hour urinary total protein were stratified by maternal age and prepregnancy body mass index. STUDY DESIGN: This study was based on a prospective cohort study in Shenzhen, China. The pregnant women were enrolled at their first prenatal clinical visit. All the participants were instructed to collect 24-hour urine samples during the following successive gestational periods: 6+0 to 13+6, 14+0 to 27+6, and 28+0 to 41+6 weeks. Total urinary protein excretion was analyzed by a colorimetric method. Ultimately, the study encompassed a total of 4844 pregnant women with uncomplicated pregnancies. The nonparametric percentile method was used to determine reference ranges for 24-hour urinary total protein excretion during different trimesters in women with uncomplicated pregnancies (excluding those with previous kidney disorders, gestational or chronic hypertension, preeclampsia, and pregestational diabetes mellitus, among others). RESULTS: The 24-hour urinary total protein levels expressed as medians and percentiles (5th, 95th) for each trimester were as follows: 72.0 (28.4, 165.0), 88.0 (34.0, 185.0), and 108.0 (37.5, 258.0) mg in the first, second, and third trimesters, respectively. A significant increase in 24-hour urinary total protein excretion was observed throughout pregnancy (all P values <.001). Moreover, 24-hour urinary total protein levels were higher in the older (≥35 years) than in the younger (<35 years) group from mid-gestation. Specifically, the median (interquartile range) 24-hour urinary total protein levels by age were 72.2 (50.6-100.0) vs 70.5 (50.5-100.0) mg, 85.8 (62.0-117.0) vs 96.0 (68.0-127.8) mg, and 106.6 (76.0-146.2) vs 114.7 (81.5-153.6) mg in the first, second, and third trimesters, respectively. In addition, 24-hour proteinuria was significantly increased in higher-weight (overweight or obese) subgroups compared with lower-weight (underweight or normal-weight) subgroups (all P values <.05). CONCLUSION: Our study provides reference values for 24-hour urinary total protein excretion with apparently uncomplicated pregnancies. Understanding these changes in low-risk pregnancies is essential for optimizing maternal management.

A modified Blumgart anastomosis with a simple and practicable procedure after laparoscopic pancreaticoduodenectomy: our center's experience.

BACKGROUND: Laparoscopic pancreaticoduodenectomy(LPD) has become the goal of lots of minimally invasive surgical centers in recent years. Postoperative pancreatic fistula(POPF) is still the barrier to attaining the above goal. Thus, improving anastomosis techniques to reduce the rate of POPF has been a hotspot of surgery. Blumgart pancreaticojejunostomy is considered one of the best anastomosis procedures, with low rates of POPF. However, the original Blumgart pancreaticojejunostomy method is not easy for laparoscopic operation. In consequence, we modified a Blumgart pancreaticojejunostomy technique with a simple and practicable procedure and applied to LPD. METHODS: We collected and retrospectively analyzed the perioperative clinical data of patients who underwent modified Blumgart anastomosis from February 2017 to September 2022. The above patients included 53 cases in open pancreaticojejunostomy(OPD) and 58 cases in LPD. After propensity score matching, 44 cases were included for comparison in each group. RESULTS: After propensity score matching, the average time for pancreaticojejunostomy was about 30 min in the LPD group. The Clinically relevant POPF(CR-POPF) rate was 9.1%. The length of postoperative hospitalization was 13.1 days. Compared with the OPD group, The CR-POPF rate in the LPD group are not significant differences. But the postoperative length of hospital stay was significantly shorter in the LPD group. Besides, there were no other severely postoperative complications between two groups. CONCLUSION: The modified Blumgart anastomosis technique applied to LPD in our Center not only has simple and convenient properties but also low rate of CR-POPF. And this method may be a good choice for surgeons to begin to carry out LPD.

Neural-SEIR: A flexible data-driven framework for precise prediction of epidemic disease.

Accurately modeling and predicting epidemic diseases is crucial to prevent disease transmission and reduce mortality. Due to various unpredictable factors, including population migration, vaccination, control efforts, and seasonal fluctuations, traditional epidemic models that rely on prior knowledge of virus transmission mechanisms may not be sufficient to forecast complex epidemics like coronavirus disease 2019(COVID-19). The application of traditional epidemiological models such as susceptible-exposed-infectious-recovered (SEIR) may face difficulties in accurately predicting such complex epidemics. Data-driven prediction approaches lack the ability to generalize and exhibit low accuracy on small datasets due to their reliance on large amounts of data without incorporating prior knowledge. To overcome this limitation, we introduce a flexible ensemble data-driven framework (Neural-SEIR) that "neuralizes" the SEIR model by approximating the core parameters through neural networks while preserving the propagation structure of SEIR. Neural-SEIR employs long short-term memory (LSTM) neural network to capture complex correlation features, exponential smoothing (ES) to model seasonal information, and prior knowledge from SEIR. By incorporating SEIR parameters into the neural network structure, Neural-SEIR leverages prior knowledge while updating parameters with real-world data. Our experimental results demonstrate that Neural-SEIR outperforms traditional machine learning and epidemiological models, achieving high prediction accuracy and efficiency in forecasting epidemic diseases.

Application of arterial infusion ports in hepatic arterial infusion chemotherapy and embolization for advanced hepatocellular carcinoma.

OBJECTIVES: To investigate the safety and feasibility of subcutaneous implantable infusion ports in repeated hepatic arterial infusion chemotherapy (HAIC) for advanced hepatocellular carcinoma (HCC) in China. METHODS: A total of 237 patients who were clinically diagnosed with advanced HCC (CNLC III a/III b) in our hospitals from December 2020 to October 2022 were retrospectively analyzed. The approaches of HAIC were divided into 2 groups: arterial infusion port implantation (group A) and one-time femoral artery catheterization (group B) based on the physicians' suggestion and the patients' intention. The comfort level (evaluated with the General Comfort Questionnaire), complications and average inpatient expenditure were compared between the 2 groups. RESULTS: 116 patients were finally enrolled in the study (group A: 69; group B: 47) and completed HAIC (FOLFOX-4 regimen) according to the dosing schedules (mean: 6±1 cycles). The comfort level of group A was greater than that of group B (p<0.05). The average inpatient expenditure of group A was lower than that of group B (5.4±2.4 vs 10.4±1.9 thousand yuan RMB/cycle, p<0.05). No patients developed port incision infection, hematoma or catheter-related thrombosis in group A, whereas four patients had groin hematomas, one had femoral artery dissection and four had deep vein thrombosis in group B. CONCLUSION: Hepatic arterial infusion chemotherapy via arterial infusion ports for advanced HCC decreased complications and medical expenditures and improved patient comfort levels compared with indwelling catheters.

Effects of various wet environments on the characteristics of the dust cake deposited on the surface of filter media.

The effect of wet environments on the dust cake of filter media was studied. The collapse angles of dust particles and the collapse angles between dust particles and filter media increase with increasing dust moisture content, relative humidity, and spray rate. The smallest growth rate of collapse was observed under dust moisture content, while the largest growth rate occurred under the spray rate condition. The collapse angles between dust particles and filter media of coated filter media were smaller compared to those of mechanical filter media under different wet environments. The dust cake drag coefficients of both filter media initially increase and then decrease with an increase in the dust moisture content, decrease with the acceleration of the relative humidity, and show a pattern of first decreasing and then increasing as the spray rate increases. The dust loading capacity of both filter media follows an opposite trend to that of the dust cake drag coefficients.

Thirdhand smoke beliefs, exposure status and associated factors among young people in China: A cross-sectional study.

INTRODUCTION: Thirdhand smoke is an emerging threat to global public health. There is no research on young people's exposure to thirdhand smoke in China. This study aims to investigate the exposure status and beliefs of thirdhand smoke among young Chinese people and provide a reference for policy regarding thirdhand smoke. METHODS: Data from the 2022 Chinese Resident Psychological and Behavioral Survey were used to select young people aged 15-24 years. A total of 11781 subjects were included in this study. Demographic information, beliefs about thirdhand smoke, and exposure status to thirdhand smoke were investigated. RESULTS: Among the participants, 47.8% reported being exposed to thirdhand smoke (males: 49.1%, females: 47.0%). Young people living in urban areas (AOR=0.84, 95% CI: 0.77-0.91, p<0.001) and those with a monthly family income >12000 RMB (AOR=0.81, 95% CI: 0.71-0.92, p=0.001) were less likely to be exposed to thirdhand smoke. Young people with junior high school education or higher, and current or former smokers, were more likely to be exposed to thirdhand smoke. There is room for improvement in the beliefs about thirdhand smoke among young people. CONCLUSIONS: Thirdhand smoke exposure is an issue that should be addressed in public health policy. Young people with low income and current or former smokers are populations that should be mainly focused on in public education and prevention work on thirdhand smoke.