M2 tumor-associated macrophage promoted DNA methylation in lung cancer metastasis via intensifying EZH2.

This study aimed to explore the interaction between the tumor-associated macrophage (TAM) and enhancer of zeste homolog 2 (EZH2) in tumor microenvironment of lung cancer are obscure. M2 type of TAM was induced by interleukin-4 (IL-4) and interleukin-13 (IL-13) in RAW264.7 cells. Subsequently, the co-culture system of the M2 RAW264.7 treating LLC-1 cells were constructed to evaluate the cell proliferation, migration and invasion abilities. On top of that, the M2 RAW264.7 was injected into the LLC-1 cells-bearing mice. Tumor growth and the number of metastatic nodes were observed. Moreover, DNA methylation, EZH2 expression, target genes of EZH2 and the M2 type TAM-related markers were detected in vivo and in vitro . Further experiments of EZH2 function in lung cancer were carried out by the addition of EZH2 inhibitor (GSK126) and si-EZH2. M2 type of TAM was induced with IL-4 and IL-13 with increased expression of CD206, CD68, CD163 and Arg1. Following co-culture with M2 type TAM, the proliferative, invasive, migrative abilities, tumor growth and metastasis, and the DNA methylation, EZH2 level were strengthened whereas the target genes of EZH2, including p21, CDKN2A, CDKN2B were reduced in LLC-1 cells and LLC-1 cell-bearing mice. Of note, GSK126 and si-EZH2 offset the M2 type TAM's effects, and inhibited the LLC-1 cell metastasis, DNA methylation and tumor growth. M2 type TAM promoted DNA methylation in LLC-1 cells and LLC-1 cell-bearing mice, which is related to the intensified EZH2.

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approach. We retrospectively gathered medical data from 13 440 pediatric patients slated for surgery from 2018 to 2021. Following data preprocessing, we utilized random forests, logistic regression, linear support vector machines, gradient boosting trees, and extreme gradient boosting trees to predict these abrupt cancellations. The efficacy of these models was assessed through performance metrics. The analysis revealed that key factors influencing last-minute cancellations included the impact of the coronavirus disease 2019 pandemic, average wind speed, average rainfall, preanesthetic assessments, and patient age. The extreme gradient boosting algorithm outperformed other models in predicting cancellations, boasting an area under the curve value of 0.923 and an accuracy of 0.841. This algorithm yielded superior sensitivity (0.840), precision (0.837), and F1 score (0.838) relative to the other models. These insights underscore the potential of machine learning, informed by EMRs and meteorological data, in forecasting last-minute surgical cancellations. The extreme gradient boosting algorithm holds promise for clinical deployment to curtail healthcare expenses and avert adverse patient-family experiences.

Cytocompatibility of Ti3C2Tx MXene with Red Blood Cells and Human Umbilical Vein Endothelial Cells and the Underlying Mechanisms.

Two-dimensional (2D) nanomaterials have been widely used in biomedical applications because of their biocompatibility. Considering the high risk of exposure of the circulatory system to Ti3C2Tx, we studied the cytocompatibility of Ti3C2Tx MXene with red blood cells (RBCs) and human umbilical vein endothelial cells (HUVECs) and showed that Ti3C2Tx had excellent compatibility with the two cell lines. Ti3C2Tx at a concentration as high as 200 µg/mL caused a negligible percent hemolysis of 0.8%. By contrast, at the same treatment concentration, graphene oxide (GO) caused a high percent hemolysis of 50.8%. Scanning electron microscopy revealed that RBC structures remained intact in the Ti3C2Tx treatment group, whereas those in the GO group completely deformed, sunk, and shrunk, which resulted in the release of cell contents. This difference can be largely ascribed to the distinct surficial properties of the two nanosheets. In specific, the fully covered surface-terminating -O and -OH groups leading to Ti3C2Tx had a very hydrophilic surface, thereby hindering its penetration into the highly hydrophobic interior of the cell membrane. However, the strong direct van der Waals attractions coordinated with hydrophobic interactions between the unoxidized regions of GO and the lipid hydrophobic tails can still damage the integrity of the cell membranes. In addition, the sharp and keen-edged corners of GO may also facilitate its relatively strong cell membrane damage effects than Ti3C2Tx. Thus, the excellent cell membrane compatibility of Ti3C2Tx nanosheets and their ultraweak capacity to provoke excessive ROS generation endowed them with much better compatibility with HUVECs than GO nanosheets. These results indicate that Ti3C2Tx has much better cytocompatibility than GO and provide a valuable reference for the future biomedical applications of Ti3C2Tx.

The influence of media use degree on public depressive symptoms: mediating role of big five personality.

BACKGROUND: Mixed results have been found regarding the relationship between media use degree and depressive symptoms. The purpose of this study is to explore the relationship between media use degree, big five personality and depressive symptoms with a mediation model. METHOD: This was a cross-sectional study. With 9-item Patient Health Questionnaire (PHQ-9), 10-item Big Five Inventory (BFI-10) and self-designed media usage scale, 11,031 participants aged 12 and above in 120 cities in China were collected. Pearson correlation analysis and regression analysis were performed on the data. The Process plug-in was used to construct the mediation model and explore the relationship among media use degree, big five personality and depressive symptoms. The nonparametric percentile Bootstrap method was used to test the mediating effect of personality traits. RESULTS: The degree of media use was positively correlated with depressive symptoms (r = 0.20, P < 0.001), and big five personality played a mediating role between the degree of media use and depressive symptoms. Among five traits, extroversion (r=-0.12, P < 0.001), conscientiousness (r=-0.23, P < 0.001), openness (r=-0.03, P < 0.01) and agreeableness (r=-0.22, P < 0.001) were negatively correlated with depressive symptoms, and neuroticism (r = 0.25, P < 0.001) were positively correlated with depressive symptoms. In addition, extraversion (-0.004, -0.001), conscientiousness (-0.015, -0.008), agreeableness (-0.008, -0.001) and neuroticism (-0.015, -0.007) in big five personality played a mediating role between media use and depressive symptoms. CONCLUSION: The degree of media use positively predicted depressive symptoms, and excessive media use may bring risks to mental health. People with high neuroticism, low agreeableness, low conscientiousness and low extroversion are more likely to suffer from depressive symptoms.

Potential role of glutathione S-transferase P1 gene polymorphism and metabolic syndrome in lower urinary tract symptoms attributed to benign prostatic hyperplasia.

OBJECTIVE: The aim of the study is to investigate the effects of glutathione S-transferase P1 (GSTP1) gene polymorphism and metabolic syndrome (MS) on lower urinary tract symptoms (LUTS) attributed to benign prostatic hyperplasia (BPH). METHODS: This study included 195 patients diagnosed with LUTS secondary to BPH as case group, divided into simple BPH group (S-BPH group) and combined with MS group (MS-BPH group). Control group included 200 healthy elderly men without LUTS. Use peripheral blood samples detected the GSTP1 gene polymorphism (Ile 105 Val A → G polymorphism) by polymerase chain reaction-restriction fragment length polymorphism. Recorded age, GSTP1 gene polymorphism, international prostate symptom score (IPSS), prostate volume (PV), residual urine volume (RV), maximal urinary flowrate (Qmax), and prostate-specific antigen (PSA) to statistical analysis. RESULTS: Pairwise compared between control group, S-BPH group and MS-BPH, the PV (P < 0.001), PSA (P < 0.001), RV (P < 0.001), Qmax (P < 0.001), IPSS (P < 0.001), frequencies of GSTP1 gene (P < 0.05) were shown significant different, and MS-BPH group had larger PV, and more severe LUTS. In case group, variation genotypes (GSTP1 A/G + G/G) always had larger PV, higher PSA and IPSS, more RV and lower Qmax than homozygote (GSTP1 A/A) and the comparison were significant different (P < 0.05). Variation genotypes were positively correlated with PV (ß = 0.092, P < 0.001), RV (ß = 0.228, P = 0.004), IPSS (ß = 0.274, P = 0.038), PSA (ß = 1.243, P < 0.001) and negatively correlated with Qmax (ß = -0.362, P = 0.025). CONCLUSION: In patients with BPH, GSTP1 variation genotypes and MS might be potential risk factors for faster progression of benign prostatic enlargement and LUTS, which might increase the surgical rate. TRIAL REGISTRATION: ChiCTR-IPR-14005580.

Identification of pediatric respiratory diseases using a fine-grained diagnosis system.

Respiratory diseases, including asthma, bronchitis, pneumonia, and upper respiratory tract infection (RTI), are among the most common diseases in clinics. The similarities among the symptoms of these diseases precludes prompt diagnosis upon the patients' arrival. In pediatrics, the patients' limited ability in expressing their situation makes precise diagnosis even harder. This becomes worse in primary hospitals, where the lack of medical imaging devices and the doctors' limited experience further increase the difficulty of distinguishing among similar diseases. In this paper, a pediatric fine-grained diagnosis-assistant system is proposed to provide prompt and precise diagnosis using solely clinical notes upon admission, which would assist clinicians without changing the diagnostic process. The proposed system consists of two stages: a test result structuralization stage and a disease identification stage. The first stage structuralizes test results by extracting relevant numerical values from clinical notes, and the disease identification stage provides a diagnosis based on text-form clinical notes and the structured data obtained from the first stage. A novel deep learning algorithm was developed for the disease identification stage, where techniques including adaptive feature infusion and multi-modal attentive fusion were introduced to fuse structured and text data together. Clinical notes from over 12000 patients with respiratory diseases were used to train a deep learning model, and clinical notes from a non-overlapping set of about 1800 patients were used to evaluate the performance of the trained model. The average precisions (AP) for pneumonia, RTI, bronchitis and asthma are 0.878, 0.857, 0.714, and 0.825, respectively, achieving a mean AP (mAP) of 0.819. These results demonstrate that our proposed fine-grained diagnosis-assistant system provides precise identification of the diseases.

A Continuous Blood Pressure Estimation Method Using Photoplethysmography by GRNN-Based Model.

Compared with diastolic blood pressure (DBP) and systolic blood pressure (SBP), the blood pressure (BP) waveform contains richer physiological information that can be used for disease diagnosis. However, most models based on photoplethysmogram (PPG) signals can only estimate SBP and DBP and are susceptible to noise signals. We focus on estimating the BP waveform rather than discrete BP values. We propose a model based on a generalized regression neural network to estimate the BP waveform, SBP and DBP. This model takes the raw PPG signal as input and BP waveform as output. The SBP and DBP are extracted from the estimated BP waveform. In addition, the model contains encoders and decoders, and their role is to be responsible for the conversion between the time domain and frequency domain of the waveform. The prediction results of our model show that the mean absolute error is 3.96 ± 5.36 mmHg for SBP and 2.39 ± 3.28 mmHg for DBP, the root mean square error is 5.54 for SBP and 3.45 for DBP. These results fulfill the Association for the Advancement of Medical Instrumentation (AAMI) standard and obtain grade A according to the British Hypertension Society (BHS) standard. The results show that the proposed model can effectively estimate the BP waveform only using the raw PPG signal.

Adversarial active learning for the identification of medical concepts and annotation inconsistency.

OBJECTIVE: Named entity recognition (NER) is a principal task in the biomedical field and deep learning-based algorithms have been widely applied to biomedical NER. However, all of these methods that are applied to biomedical corpora use only annotated samples to maximize their performances. Thus, (1) large numbers of unannotated samples are relinquished and their values are overlooked. (2) Compared with other types of active learning (AL) algorithms, generative adversarial learning (GAN)-based AL methods have developed slowly. Furthermore, current diversity-based AL methods only compute similarities between a pair of sentences and cannot evaluate distribution similarities between groups of sentences. Annotation inconsistency is one of the significant challenges in the biomedical annotation field. Most existing methods for addressing this challenge are statistics-based or rule-based methods. (3) They require sufficient expert knowledge and complex designs. To address challenges (1), (2), and (3) simultaneously, we propose innovative algorithms. METHODS: GAN is introduced in this paper, and we propose the GAN-bidirectional long short-term memory-conditional random field (GAN-BiLSTM-CRF) and the GAN-bidirectional encoder representations from transformers-conditional random field (GAN-BERT-CRF) models, which can be considered an NER model, an AL model, and a model identifying error labels. BiLSTM-CRF or BERT-CRF is defined as the generator and a convolutional neural network (CNN)-based network is considered the discriminator. (1) The generator employs unannotated samples in addition to annotated samples to maximize NER performance. (2) The outputs of the CRF layer and the discriminator are used to select unlabeled samples for the AL task. (3) The discriminator discriminates the distribution of error labels from that of correct labels, identify error labels, and address the annotation inconsistency challenge. RESULTS: The corpus from the 2010 i2b2/VA NLP challenge and the Chinese CCKS-2017 Task 2 dataset are adopted for experiments. Compared to the baseline BiLSTM-CRF and BERT-CRF, the GAN-BiLSTM-CRF and GAN-BERT-CRF models achieved significant improvements on the precision, recall, and F1 scores in terms of NER performance. Learning curves in AL experiments show the comparative results of the proposed models. Furthermore, the trained discriminator can identify samples with incorrect medical labels in both simulation and real-word experimental environments. CONCLUSION: The idea of introducing GAN contributes significant results in terms of NER, active learning, and the ability to identify incorrect annotated samples. The benefits of GAN will be further studied.

[Hospital Networked Medical Equipment Safety Management].

With the continuous improvement and wide application of hospital information, more and more medical equipment is integrated into the hospital information systems, which brings new work contents and challenges for the traditional clinical engineers. This paper reviews and evaluates the current situation of networked medical equipment in the hospital. By applying the ISO 80001 and the MDS2(Manufacturer Disclosore Statement for Medical Device Security), the paper puts forward the measures and suggestions for the security management of networked medical equipment.

Ultra-high-speed PLIF imaging for simultaneous visualization of multiple species in turbulent flames.

In order to obtain more detailed characteristics and information in highly turbulent flames, for a better understanding of the transient behavior of eddies in such flames, a measurement technique with sufficient temporal resolution is requested. However, the probing of species distributions relevant in combustion (e.g. OH, CH2O) with ultra-high-speed laser diagnostics still remains a challenge. Nd:YAG clusters commercially available can generate only 4-8 pulses, although with high laser energy. Systems based on a diode-pumped solid-state Nd:YAG laser combined with a dye laser produce only about 100 µJ pulse energy at ultra-high repetition rates (≥50 kHz). Even more comprehensive information on the flame structure can be gained if simultaneous recording of multi-species is performed. In the present work, the development of the first ultra-high-speed diagnostic technique capable of simultaneous probing of hydroxyl radicals and formaldehyde distributions at a repetition rate of 50 kHz is outlined. This has been achieved by employing a burst laser pumped optical parametric oscillator system for the simultaneous detection of CH2O excited at 355 nm and OH-radicals excited at 283 nm, where the interference of scattering laser light can be avoided. The applicability of the proposed technique was demonstrated in a highly turbulent jet flame. Moreover, the presented improvement in terms of the number of consecutive images recorded with ultra-high-speed planar laser induced fluorescence imaging is significant. Due to the high temporal resolution, the movement of CH2O pocket enclosed by OH at the flame tip can be clearly captured. The transport velocity of the CH2O pocket was calculated and found to be in good agreement with previous LDV results.

Scutellarin Alleviates Diabetic Retinopathy via the Suppression of Nucleotide-Binding Oligomerization Domain (NOD)-Like Receptor Pyrin Domain Containing Protein 3 Inflammasome Activation.

PURPOSE: Diabetic retinopathy, a prevalent complication of diabetes, represents the leading cause of vision loss and blindness among middle-aged and elderly populations. Recent research has demonstrated the ameliorating effects of scutellarin on diabetes-associated complications such as diabetic retinopathy and type 2 diabetic cardiomyopathy. However, investigations into its protective impact and underlying mechanisms on diabetic retinopathy are scant. This study aims to explore the therapeutic potential of scutellarin in diabetic retinopathy treatment. METHODS: Diabetic retinopathy was induced in rats through intraperitoneal injections of streptozotocin (STZ, 60 mg/kg) administered daily for three consecutive days. Following this, diabetic retinopathy rats received daily intragastric administration of scutellarin (40 mg/kg) for 42 days. RESULTS: Our findings suggest that scutellarin alleviates histological damage in the retinal tissues of streptozotocin-challenged rats. Furthermore, scutellarin effectively enhances total retinal thickness and increases the number of ganglion cell layer (GCL) cells in the retinal tissues of streptozotocin-treated rats. Scutellarin also demonstrated anti-inflammatory and antioxidant effects in the retinal tissues of STZ-induced rats, as indicated by reduced levels of tumor necrosis factor-α, interleukin-1ß, and interleukin-6, and elevated levels of glutathione peroxidase, superoxide dismutase, and catalase. Additionally, scutellarin effectively inhibited the expression of NOD-like receptor pyrin domain containing protein 3 inflammasome-related markers in the retinal tissues of streptozotocin-administered rats. CONCLUSIONS: Collectively, our results indicate that scutellarin significantly reduces streptozotocin-induced retinal inflammation, an effect that may be partially attributed to the suppression of NLRP3 inflammasome activation.

The association between renal pelvis urine density and the risk of severe infectious complications in patient with symptom-free hydronephrosis after shock wave lithotripsy: a multi-center prospective study.

Finding reliable and easy-to-obtain predictors of severe infectious complications after shock wave lithotripsy (SWL) is a major clinical need, particular in symptom-free hydronephrosis. Therefore, we aim to prospectively investigate the predictive value of Hounsfield units (HU) in renal pelvis urine for the risk of severe infectious complications in patients with ureteral stones and symptom-free hydronephrosis after SWL. This multi-center prospective study was conducted from June 2020 to December 2023. The HU of renal pelvis urine was measured by non-enhanced computed tomography. The severe infectious complications included systemic inflammatory response syndrome, sepsis, and septic shock. Binary logistic regression models assessed the odds ratios (ORs) and 95% confidence intervals (CIs). Finally, 1,436 patients with ureteral stones were enrolled in this study. 8.9% (128/1,436) of patients experienced severe infectious complications after SWL treatment. After adjusting confounding variables, compared with the patients in the lowest renal pelvis urine density quartile, the OR (95% CI) for the highest quartile was 32.36 (13.32, 78.60). There was a positive linear association between the HU value of renal pelvis urine and the risk of severe infectious complications after SWL (P for trend < 0.001). Furthermore, this association was also observed stratified by age, gender, BMI, stone size, stone location and hydronephrosis grade (all P for interaction > 0.05). Additionally, the nonlinear association employed by restricted cubic splines is not statistically significant (nonlinear P = 0.256). The AUROC and 95%CI of renal pelvis urine density were 0.895 (0.862 to 0.927, P value < 0.001). The cut-off value was 12.0 HU with 78.59% sensitivity and 85.94% specificity. This multi-center prospective study demonstrated a positive linear association between HU in renal pelvis urine and the risk of severe infectious complications in patients with ureteral stones and symptom-free hydronephrosis after SWL, regardless of age, gender, BMI, stone size, stone location, and hydronephrosis grade. These findings might be helpful in the SWL treatment decision-making process.

Atractylenolide II combined with Interferon-γ synergistically ameliorates colorectal cancer progression in vivo and in vitro by blocking the NF-kB p65/PD-L1 pathway.

Purpose: Atractylodes macrocephala Koidz is a widely used classical traditional Chinese herbal medicine, that has shown remarkable efficacy in cancers. Colorectal cancer (CRC) is the most common malignant tumor globally. Interferon (IFN)-γ, a prominent cytokine involved in anti-tumor immunity that has cytostatic, pro-apoptotic, and immune-stimulatory properties for the detection and removal of transformed cells. Atractylenolides-II (AT-II) belongs to the lactone compound that is derived from Atractylodes macrocephala Koidz with anti-cancer activity. However, whether AT-II combined with IFN-γ modulates CRC progression and the underlying mechanisms remain unclear. The present study aimed to elucidate the efficacy and pharmaceutical mechanism of action of AT-II combined with IFN-γ synergistically against CRC by regulating the NF-kB p65/PD-L1 signaling pathway. Methods: HT29 and HCT15 cells were treated with AT-II and IFN-γ alone or in combination and cell viability, migration, and invasion were then analyzed using Cell Counting Kit-8 (CCK-8) and Transwell assays, respectively. Furthermore, the underlying mechanism was investigated through western blot assay. The role of AT-II combined with IFN-γ on tumor growth and lung metastases was estimated in vivo. Finally, the population of lymphocytes in tumor tissues of lung metastatic C57BL/6 mice and the plasma cytokine levels were confirmed by flow cytometry and enzyme-linked immunosorbent assay (ELISA). Results: AT-II or the combination IFN-γ significantly inhibited the growth and migration abilities of CRC cells in vitro and in vivo. The biological mechanisms behind the beneficial effects of AT-II combined with IFN-γ were also measured and inhibition of p38 MAPK, FAK, Wnt/ß-catenin, Smad, and NF-kB p65/PD-L1 pathways was observed. Moreover, AT-II combined with IFN-γ significantly inhibited HCT15 xenograft tumor growth and lung metastases in C57BL/6 mice, which was accompanied by lymphocyte infiltration into the tumor tissues and inflammatory response inactivation. Conclusions: The results showed that the AT-II in combination with IFN-γ could be used as a potential strategy for tumor immunotherapy in CRC. More importantly, the mechanism by which AT-II suppressed CRC progressions was by inhibiting the NF-kB p65/PD-L1 signal pathway.

Continuous age- and sex-specific reference ranges of liver enzymes in Chinese children and application in pediatric non-alcoholic fatty liver disease.

BACKGROUND: Alanine aminotransferase (ALT) is widely used to screen patients with hepatic diseases. However, the current reference ranges (< 50 U/L) were developed by laboratories and have not been validated in populations with a large number of healthy individuals. METHODS: This study collected venous blood and anthropometric data from a total of 13,287 healthy children aged 3 months to 18 years who underwent routine physical examinations in the Department of Pediatric Healthcare. We applied the least mean square algorithm to establish age- and sex-related reference percentiles of serum levels of transaminases. For validation, we recruited 4276 children and adolescents with obesity/overweight who underwent evaluation and metabolic tests in the hospital. Using receiver operating characteristic curves, we determined age- and sex-specific upper limit percentiles of liver enzymes for fatty liver diseases. RESULTS: This study revealed a significant correlation between serum transaminase levels and age and sex (P < 0.01). These transaminase levels exhibited age- and sex-specific patterns. Among individuals in the non-alcoholic fatty liver disease (NAFLD) cohort, elevated ALT levels displayed a positive association with clinical markers of disease severity, including homeostatic model assessment of insulin resistance, waist-hip ratio, and serum uric acid levels (P < 0.01). According to the receiver operating characteristic curves, ALT levels at the 92.58th percentile for boys and the 92.07th percentile for girls yielded the highest accuracy and specificity. CONCLUSIONS: This study provides age- and sex-specific reference ranges for ALT, aspartate aminotransferase, and γ-glutamyltransferase in Chinese children and adolescents, making it the largest population study to date. Furthermore, the study establishes a precise upper limit for ALT levels, facilitating their use in NAFLD screening. Video Abstract.

Artesunate Alleviates Hyperoxia-Induced Lung Injury in Neonatal Mice by Inhibiting NLRP3 Inflammasome Activation.

Bronchopulmonary dysplasia (BPD) is a chronic respiratory disease in preterm infants that may cause persistent lung injury. Artesunate exhibits excellent anti-inflammatory in lung injury caused by various factors. This study aimed to investigate the effect of the artesunate on hyperoxia-induced lung injury in neonatal mice and its mechanism. A BPD model of hyperoxic lung injury in neonatal mice was established after hyperoxia (75% oxygen) exposure for 14 days, and part of the mice received intraperitoneal injections of the artesunate. H&E staining was used to observe the pathology of lung tissue, and the degree of oxidative stress in the lung tissue was determined by commercial kits. The levels of inflammatory cytokines in the serum and lung tissues of neonatal mice were detected by an enzyme-linked immunosorbent assay. Immunohistochemical experiments were performed to further evaluate the expression of IL-1ß. The real-time quantitative polymerase chain reaction was used to determine the mRNA level of the NLRP3 inflammasome. The western blot assay was used to measure the levels of NLRP3 inflammasome and NF-κB pathway-related proteins. Artesunate ameliorated weight loss and lung tissue injury in neonatal mice induced by hyperoxia. The level of malondialdehyde was decreased, while the activity of superoxide dismutase and the level of glutathione increased after artesunate treatment. Artesunate reduced the level of inflammation cytokines TNF-α, IL-6, and IL-1ß in the serum and lung. Moreover, artesunate inhibited the mRNA expression and protein levels of NLRP3, ASC, and caspase-1, as well as the phosphorylation of the NF-κB and IκBα. Our findings suggest that artesunate treatment can attenuate hyperoxia-induced lung injury in BPD neonatal mice by inhibiting the activation of NLRP3 inflammasome and the phosphorylation of the NF-κB pathway.

Total Glucosides of Paeony Ameliorate Myocardial Injury in Chronic Heart Failure Rats by Suppressing PARP-1.

Total glucosides of paeony (TGP) have a potential protective effect on chronic heart failure (CHF) rats, but the mechanism remains unclear. PARP inhibition prevents the decrease in myocardial contractility. Therefore, we aim to investigate the effects and mechanisms of TGP on CHF and the role of PARP-1 in CHF. Left anterior descending ligation rats and adriamycin-treated H9C9 cells were used as CHF models, and captopril as a positive control for in vivo experiments. We found that TGP alleviated myocardial remodeling and improved cardiac morphology and function. TGP also reduced myocardial apoptosis and autophagy, decreased inflammatory factor release, and inhibited the PARP-1 and NF-κB proteins. Through cell transfection, we found that PAPR-1 knockdown inhibited NF-κB nuclear translocation. Additionally, TGP inhibited apoptosis, autophagy, and inflammation in CHF cells, while PARP-1 overexpression partially antagonized them. In conclusion, TGP has the potential to improve CHF and PARP-1 may be a potential target.

The potential effect of salvianolic acid B against rat ischemic brain injury in combination with mesenchymal stem cells.

BACKGROUND: Mesenchymal stem cells (MSCs) and Salvianolic acid B (SAB) are known to exert potent anti-inflammatory and anti-oxidative properties. But the effect of SAB and MSCs combination treatment on the cerebral ischemia/reperfusion injury (CI/RI) is not clear. METHODS: After the CI/RI animal model established, rats were administered with MSCs and SAB individually or combination treatment. To evaluate the therapeutic potential, behavioral tests, TTC staining, Hematoxylin-eosin (HE) staining, and immunofluorescence assays were performed to evaluate the neuroprotection and endogenous neurogenesis. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining and enzyme linked immunosorbent assay (ELISA) were performed to evaluate the anti-apoptosis and anti-inflammatory effect. Meanwhile, the expression of the TLR4/NF-ĸB/MYD88 signal pathway-related proteins was evaluated by Western blot. RESULTS: MSCs and SAB individually or combination treatment have protective effect in CI/RI rats. More importantly, the rats with the combination treatment showed a better behavioral recovery, neurogenesis and smaller infarct size compared with the rats administered with MSCs or SAB individually. Further research showed that the combination treatment decreased CI/RI induced inflammatory cytokines and oxidative stress, including inhibiting the production of IL-1ß, IL-6, TNF-α, decreasing the levels of malondialdehyde (MDA), and increased the activity of superoxide dismutase (SOD). In addition, the neuroprotection effect of SAB and MSCs combination was achieved through the regulation of TLR4/NF-κB/MyD88 signaling pathway related proteins, including inhibition the protein levels of TLR4, MYD88, p-NF-κB p65, TRAF6-and action of SIRT1 in brain tissues. CONCLUSION: The present study indicated that the MSCs and SAB combination treatment had better protective effect against rat ischemic brain injury. The combination of SAB and MSCs may provide a potent and promising strategy for the treatment of ischemic stroke and is worthy for further development.

Pressure Drop Performance of Porous Composites Based on Cotton Cellulose Nanofiber and Aramid Nanofiber for Cigarette Filter Rod.

Porous composites have been widely used in the adsorption and catalysis field due to their special structure, abundant sites, and light weight. In this work, an environmentally friendly porous composite was successfully prepared via a facile freeze-drying method, in which cotton cellulose nanofiber (CCNF) was adopted as the main framework to construct the connected flue structure, and aramid nanofiber (ANF) was used as a reinforcer to enhance its thermal property. As-prepared porous materials retained a regulated inter-connected hole structure and controllable porosity after ice template evolution and possessed improved resistance to thermal collapse with the introduction of a small amount of aramid nanofiber, as evaluated and verified by FTIR, SEM, and TGA measurements. With the increased addition of cotton cellulose nanofiber and aramid nanofiber, the porous composites exhibited decreased porosity and increased pressure drop performance. For the CCNF/ANF-5 sample, the pressure drop was 1867 Pa with a porosity of 7.46 cm3/g, which best met the required pressure drop value of 1870 Pa. As-prepared porous composite with adjustable interior structure and enhanced thermal property could be a promising candidate in the tobacco field.

Analyzing and Forecasting Pediatric Fever Clinic Visits in High Frequency Using Ensemble Time-Series Methods After the COVID-19 Pandemic in Hangzhou, China: Retrospective Study.

BACKGROUND: The COVID-19 pandemic has significantly altered the global health and medical landscape. In response to the outbreak, Chinese hospitals have established 24-hour fever clinics to serve patients with COVID-19. The emergence of these clinics and the impact of successive epidemics have led to a surge in visits, placing pressure on hospital resource allocation and scheduling. Therefore, accurate prediction of outpatient visits is essential for informed decision-making in hospital management. OBJECTIVE: Hourly visits to fever clinics can be characterized as a long-sequence time series in high frequency, which also exhibits distinct patterns due to the particularity of pediatric treatment behavior in an epidemic context. This study aimed to build models to forecast fever clinic visit with outstanding prediction accuracy and robust generalization in forecast horizons. In addition, this study hopes to provide a research paradigm for time-series forecasting problems, which involves an exploratory analysis revealing data patterns before model development. METHODS: An exploratory analysis, including graphical analysis, autocorrelation analysis, and seasonal-trend decomposition, was conducted to reveal the seasonality and structural patterns of the retrospective fever clinic visit data. The data were found to exhibit multiseasonality and nonlinearity. On the basis of these results, an ensemble of time-series analysis methods, including individual models and their combinations, was validated on the data set. Root mean square error and mean absolute error were used as accuracy metrics, with the cross-validation of rolling forecasting origin conducted across different forecast horizons. RESULTS: Hybrid models generally outperformed individual models across most forecast horizons. A novel model combination, the hybrid neural network autoregressive (NNAR)-seasonal and trend decomposition using Loess forecasting (STLF), was identified as the optimal model for our forecasting task, with the best performance in all accuracy metrics (root mean square error=20.1, mean absolute error=14.3) for the 15-days-ahead forecasts and an overall advantage for forecast horizons that were 1 to 30 days ahead. CONCLUSIONS: Although forecast accuracy tends to decline with an increasing forecast horizon, the hybrid NNAR-STLF model is applicable for short-, medium-, and long-term forecasts owing to its ability to fit multiseasonality (captured by the STLF component) and nonlinearity (captured by the NNAR component). The model identified in this study is also applicable to hospitals in other regions with similar epidemic outpatient configurations or forecasting tasks whose data conform to long-sequence time series in high frequency exhibiting multiseasonal and nonlinear patterns. However, as external variables and disruptive events were not accounted for, the model performance declined slightly following changes in the COVID-19 containment policy in China. Future work may seek to improve accuracy by incorporating external variables that characterize moving events or other factors as well as by adding data from different organizations to enhance algorithm generalization.

Development of lung segmentation method in x-ray images of children based on TransResUNet.

Background: Chest x-ray (CXR) is widely applied for the detection and diagnosis of children's lung diseases. Lung field segmentation in digital CXR images is a key section of many computer-aided diagnosis systems. Objective: In this study, we propose a method based on deep learning to improve the lung segmentation quality and accuracy of children's multi-center CXR images. Methods: The novelty of the proposed method is the combination of merits of TransUNet and ResUNet. The former can provide a self-attention module improving the feature learning ability of the model, while the latter can avoid the problem of network degradation. Results: Applied on the test set containing multi-center data, our model achieved a Dice score of 0.9822. Conclusions: This novel lung segmentation method proposed in this work based on TransResUNet is better than other existing medical image segmentation networks.