Deep convolutional neural network model ResNeSt for discrimination of papillary thyroid carcinomas and benign nodules in thyroid nodules diagnosed as atypia of undetermined significance.

Background: A deep convolutional neural network (DCNN) model was employed for the differentiation of thyroid nodules diagnosed as atypia of undetermined significance (AUS) according to the 2023 Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). The aim of this study was to investigate the efficiency of ResNeSt in improving the diagnostic accuracy of fine-needle aspiration (FNA) biopsy. Methods: Fragmented images were used to train and test DCNN models. A training dataset was built from 1,330 samples diagnosed as papillary thyroid carcinoma (PTC) or benign nodules, and a test dataset was built from 173 samples diagnosed as AUS. ResNeSt was trained and tested to provide a differentiation. With regard to AUS samples, the characteristics of the cell nuclei were compared using the Wilcoxon test. Results: The ResNeSt model achieved an accuracy of 92.49% (160/173) on fragmented images and 84.78% (39/46) from a patient wise viewpoint in discrimination of PTC and benign nodules in AUS nodules. The sensitivity and specificity of ResNeSt model were 95.79% and 88.46%. The κ value between ResNeSt and the pathological results was 0.847 (P<0.001). With regard to the cell nuclei of AUS nodules, both area and perimeter of malignant nodules were larger than those of benign ones, which were 2,340.00 (1,769.00, 2,807.00) vs. 1,941.00 (1,567.50, 2,455.75), P<0.001 and 190.46 (167.64, 208.46) vs. 171.71 (154.95, 193.65), P<0.001, respectively. The grayscale (0 for black, 255 for white) of malignant lesions was lower than that of benign ones, which was 37.52 (31.41, 46.67) vs. 45.84 (31.88, 57.36), P <0.001, indicating nuclear staining of malignant lesions were deeper than benign ones. Conclusions: In summary, the DCNN model ResNeSt showed great potential in discriminating thyroid nodules diagnosed as AUS. Among those nodules, malignant nodules showed larger and more deeply stained nuclei than benign nodules.

Thermostable vacuum foam dried Newcastle disease vaccine: Process optimization and pilot-scale study.

Vacuum foam drying (VFD) has been shown to improve the thermostability and long-term shelf life of Newcastle Disease Virus (NDV). This study optimized the VFD process to improve the shelf life of NDV at laboratory-scale and then tested the optimized conditions at pilot-scale. The optimal NDV to T5 formulation ratio was determined to be 1:1 or 3:2. Using the 1:1 virus to formulation ratio, the optimal filling volumes were determined to be 13-17% of the vial capacity. The optimized VFD process conditions were determined to be at a shelf temperature of 25℃ with a minimum overall drying time of 44 h. The vaccine samples prepared using these optimized conditions at laboratory-scale exhibited virus titer losses of ≤ 1.0 log10 with residual moisture content (RMC) below 3%. Furthermore, these samples were transported for 97 days around China at ambient temperature without significant titer loss, thus demonstrating the thermostability of the NDV-VFD vaccine. Pilot-scale testing of the NDV-VFD vaccine at optimized conditions showed promising results for up-scaling the process as the RMC was below 3%. However, the virus titer loss was slightly above 1.0 log10 (approximately 1.1 log10). Therefore, the NDV-VFD process requires further optimization at pilot scale to obtain a titer loss of ≤ 1.0 log10. Results from this study provide important guidance for possible industrialization of NDV-VFD vaccine in the future. KEY POINTS: • The process optimization and scale-up test of thermostable NDV vaccine prepared through VFD is reported for the first time in this study. • The live attenuated NDV-VFD vaccine maintained thermostability for 97 days during long distance transportation in summer without cold chain conditions. • The optimized NDV-VFD vaccine preparations evaluated at pilot-scale maintained acceptable levels of infectivity after preservation at 37℃ for 90 days, which demonstrated the feasibility of the vaccine for industrialization.

An investigation of the prevalence and diversity of Anisakis in China: marine food safety implications.

Anisakis can cause Anisakiasis in humans if raw or undercooked fish is consumed. Symptoms of infection may include vomiting, acute abdominal symptoms, or allergies. In this study, we collected 187 commercially available marine fish from the Yellow Sea, East China Sea, and South China Sea. Among them, 79 were found positive containing 520 Anisakis worms. The average prevalence rate was found 42% in this investigation. Ninety-two worms from different sea areas were selected and analyzed for identification, revealing the presence of five different species, which are Anisakis pegreffii, Hysterothylacium aduncum, Hysterothylacium zhoushanense, Hysterothylacium amoyense, and Hysterothylacium sp. In the meta-analysis, three databases: PubMed, CNKI, and BaiduXueshu were searched for surveys on the prevalence of Anisakis in Chinese waters from January 2000 to December 2023. A total of 26 studies were included in this analysis of which 25 publications were retrieved from different databases and one being the present study. The pooled prevalence of Anisakis was 45% among commercially available marine fish. Variances in the prevalence of Anisakis were noted among the four seas, with the highest rates in the East China Sea and the Bohai Sea, reaching 53% [0.38; 0.68] and 49% [0.36; 0.62], respectively. The Prevalence of Anisakis infection was significantly higher in astern parts such as Liaoning, Shanghai, and Zhejiang. Analysis of the host fish subgroups revealed that the orders of Anguilliformes, Scombriformes, and Gadiformes had high rates of infection. These findings suggest a significant prevalence of Anisakis, posing an increasing risk of infection for individuals. This study provides impactful information for implementing preventative measures against Anisakis.

Decreased GATA3 levels cause changed mouse cutaneous innate lymphoid cell fate, facilitating hair follicle recycling.

In mice, skin-resident type 2 innate lymphoid cells (ILC2s) exhibit some ILC3-like characteristics. However, the underlying mechanism remains elusive. Here, we observed lower expression of the ILC2 master regulator GATA3 specifically in cutaneous ILC2s (cILC2s) compared with canonical ILC2s, in line with its functionally divergent role in transcriptional control in cILC2s. Decreased levels of GATA3 enabled the expansion of RORγt fate-mapped (RORγtfm+) cILC2s after postnatal days, displaying certain similarities to ILC3s. Single-cell trajectory analysis showed a sequential promotion of the RORγtfm+ cILC2 divergency by RORγt and GATA3. Notably, during hair follicle recycling, these RORγtfm+ cILC2s accumulated around the hair follicle dermal papilla (DP) region to facilitate the process. Mechanistically, we found that GATA3-mediated integrin α3ß1 upregulation on RORγtfm+ cILC2s was required for their positioning around the DP. Overall, our study demonstrates a distinct regulatory role of GATA3 in cILC2s, particularly in promoting the divergence of RORγtfm+ cILC2s to facilitate hair follicle recycling.

A Nomogram Prediction Model for Persistent Pulmonary Hypertension of the Newborn in Neonates Hospitalized for the First Time After Birth.

OBJECTIVE: Persistent pulmonary hypertension of the newborn (PPHN) is one of the critical neonatal diseases associated with high morbidity and mortality. This study attempted to conduct a nomogram prediction model for performing early identification of PPHN and providing effective information for clinical practice. METHODS: A total of 456 newborns who first admitted to the hospital after birth were included in the analysis, including 138 newborns with PPHN and 318 newborns without PPHN (as controls). The optimal predictive variables selection was performed based on LASSO (least absolute shrinkage and selection operator) regression and multivariate logistic regression. Using the selected variables, a nomogram prediction model was developed. To validate the model, the model was assessed using the receiver operating characteristic curve, calibration plot, and clinical impact curve. RESULTS: Six predictors, namely, gestational age, neonatal respiratory distress syndrome, the levels of hemoglobin and creatine kinase-MB, gestational thyroid dysfunction, and Pao2, were identified by LASSO and multivariate logistic regression analysis from the original 30 variables studied. The constructed model, using these predictors, exhibited favorable predictive ability for PPHN, with an area under the receiver operating characteristic of 0.897 (sensitivity = 0.876, specificity = 0.785) in the training set and 0.871 (sensitivity = 0.902, specificity = 0.695) in the validation set, and was well calibrated, as indicated by the PHosmer-Lemeshow test values of 0.233 and 0.876 for the training and validation sets, respectively. CONCLUSIONS: The model included gestational age, neonatal respiratory distress syndrome, the levels of hemoglobin and creatine kinase-MB, gestational thyroid dysfunction, and Pao2 had good prediction performance for predicting PPHN among newborns first admitted to the hospital after birth.

Modulation of the rat intestinal microbiota in the course of Anisakis pegreffii infection.

Background: Anisakis are globally distributed, marine parasitic nematodes that can cause human health problems, including symptoms such as vomiting, acute diarrhea, and allergic reactions. As parasitic nematodes that primarily affect the patient's digestive tract, intestinal helminths can interact directly with the host microbiota through physical contact, chemicals, or nutrient competition. It is widely accepted that the host microbiota plays a crucial role in the regulation of immunity. Materials and methods: Nematodes collected from the abdominal cavity of marine fish were identified by molecular biology and live worms were artificially infected in rats. Infection was determined by indirect ELISA based on rat serum and worm extraction. Feces were collected for 16S rDNA-based analysis of microbiota diversity. Results: Molecular biology identification based on ITS sequences identified the collected nematodes as A. pegreffii. The success of the artificial infection was determined by indirect ELISA based on serum and worm extraction from artificially infected rats. Microbiota diversity analysis showed that a total of 773 ASVs were generated, and PCoA showed that the infected group was differentiated from the control group. The control group contained five characterized genera (Prevotellaceae NK3B31 group, Turicibacter, Clostridium sensu stricto 1, Candidatus Stoquefichus, Lachnospira) and the infected group contained nine characterized genera (Rodentibacter, Christensenella, Dubosiella, Streptococcus, Anaeroplasma, Lactococcus, Papillibacter, Desulfovibrio, Roseburia). Based on the Wilcoxon test, four processes were found to be significant: bacterial secretion system, bacterial invasion of epithelial cells, bacterial chemotaxis, and ABC transporters. Conclusion: This study is the first to analyze the diversity of the intestinal microbiota of rats infected with A. pegreffii and to determine the damage and regulation of metabolism and immunity caused by the infection in the rat gut. The findings provide a basis for further research on host-helminth-microbe correlationships.

[Correlation between intestinal toxicity and composition changes of toxic parts from Euphorbia ebracteolata before and after Terminalia chebula soup processing].

This study aims to explore the correlation between intestinal toxicity and composition changes of Euphorbia ebracteolata before and after Terminalia chebula soup(TCS) processing. Intragastric administration was performed on the whole animal model. By using fecal water content, inflammatory causes, and pathological damage of different parts of the intestinal tract of mice as indexes, the differences in intestinal toxicity of dichloromethane extraction of raw E. ebracteolata(REDE), dichloromethane extraction of TCS, and dichloromethane extraction of E. ebracteolata after simulated TCS processing(STREDE) were compared, so as to investigate the effect of TCS processing on the intestinal toxicity of E. ebracteolata. At the same time, the component databases of E. ebracteolata and T. chebula were constructed, and the composition changes of diterpenoids, tannins, and phenolic acids in the three extracted parts were analyzed by HPLC-TOF-MS. HPLC was used to compare the content of four diterpenoids including ent-11α-hydroxyabicta-8(14), 13(15)-dien-16, 12-olide(HAO), jolkinolide B(JNB), fischeria A(FA), and jolkinolide E(JNE) in the E. ebracteolata before and after processing and the residue of container wall after processing, so as to investigate the effect of TCS processing on the content and structure of the diterpenoids. The results showed that the REDE group could significantly increase the fecal water content and the release levels of TNF-α and IL-1ß from each intestinal segment, and intestinal tissue damage was accompanied by significant infiltration of inflammatory cells. However, compared with the REDE group, the intestinal tissue damage in the STREDE group was alleviated, and the infiltration of inflammatory cells decreased. The intestinal toxicity significantly decreased. Mass spectrometry analysis showed that there was no significant difference in the content of diterpenoids of REDE before and after simulated TCS processing, but a large number of tannins and phenolic acids were added. The results of HPLC showed that the content of four diterpenoids of E. ebracteo-lata decreased to varying degrees after TCS processing, ranging from-0.35% to-19.74%, and the decreased part mainly remained in the container wall, indicating that the structure of toxic diterpenoids of E. ebracteolata was not changed after TCS processing. The antagonistic effect of tannic and phenolic acids in the TCS may be the main reason for the reduced intestinal toxicity of E. ebracteolata after TCS processing. The TCS processing for E. ebracteolata is scientific.

Polystyrene nanoplastics exert cardiotoxicity through the Notch and Wnt pathways in zebrafish (Danio rerio).

The ubiquity of micro(nano)plastics has raised significant concerns among people. Their accumulation in the cardiovascular system necessitates attention to their cardiotoxicity. However, research on the cardiotoxicity of micro(nano)plastics remains scarce. Our study exposed zebrafish embryos to four different concentrations (0, 1, 10, 100 µg/mL) of polystyrene nanoplastics (PSNPs) for a period of 7 days. The results indicated that PSNPs noticeably decreased the hatching and survival rates of zebrafish and also induced cardiac developmental abnormalities. The mRNA level analysis revealed significant upregulations of heart development-related genes nkx2.5, cmlc-2, and myh-7 in response to PSNPs. Additionally, PSNPs significantly up-regulated the mRNA level associated with the Notch signaling pathway (notch-1a, jag-1a, and her-7) while remarkably suppressing the expression of the Wnt signaling pathway gene (wnt-3a). Further research showed that PSNPs significantly increased the expression of endoplasmic reticulum stress genes atf-6 and chop, while noticeably inhibiting mitochondrial copy numbers. Moreover, PSNPs were found to decrease calcium ion level and superoxide dismutase (SOD) activity in zebrafish larvae. Additionally, prolonged exposure to PSNPs for 7 days exacerbated abnormalities in various indicators compared to a 4-day exposure. In conclusion, our study demonstrates that PSNPs induce oxidative stress in zebrafish larvae, thereby activating endoplasmic reticulum stress and inhibiting mitochondrial activity, ultimately disrupting the Notch and Wnt signaling pathways. These disruptions result in abnormalities in cardiac developmental genes, ultimately leading to cardiac developmental abnormalities in zebrafish. The present research contributes to a novel understanding of the cardiotoxicity of PSNPs.

Risk/benefit trade-off of habitual physical activity and air pollution on mortality: A large-scale prospective analysis in the UK Biobank.

BACKGROUND: Previous observational studies have indicated associations of physical activity (PA) and air pollution with mortality. A few studies have evaluated air pollution and PA interactions for health. Still, the trade-off between the harmful effects of air pollution exposure and the protective effects of PA remains controversial and unclear. OBJECTIVE: This study aimed to investigate the joint association of air pollution and PA with mortality risks. METHODS: This prospective cohort study included 322,092 participants from 2006 to 2010 and followed up to 2021 in the UK Biobank study. The concentrations of air pollutants (2006-2010), including particulate matter (PM) with diameters <=2.5 mm (PM2.5), <=10 mm (PM10), and between 2.5 and 10 mm (PM2.5-10), and nitrogen oxides (NO2 and NOx) were obtained. Information on PA measured by the International Physical Activity Questionnaire short form (2006-2010) and wrist-worn accelerometer (2013-2015) were collected. All-cause and cause-specific mortalities were recorded. Cox proportional hazard models were used to investigate the associations of air pollution exposure and PA with mortality risks. The additive and multiplicative interactions were also examined. RESULTS: During a mean follow-up of 11.83 years, 16629 deaths were recorded. Compared with participants reporting low PA, higher PA was negatively associated with all-cause [hazard ratio (HR), 0.74; 95% CI, 0.71-0.78], cancer (HR, 0.85; 95% CI, 0.80-0.90), CVD (HR, 0.79; 95% CI, 0.71-0.87), and respiratory disease-specific mortality (HR, 0.51; 95% CI, 0.44-0.60). Exposure to PM2.5 (HR, 1.05; 95% CI, 1.00-1.09) and NOx (HR, 1.06; 95% CI, 1.02-1.10) was connected with increased all-cause mortality risk, and significant PM2.5-associated elevated risks for CVD mortality and NOx-associated elevated risks for respiratory disease mortality were observed. No obvious interaction between PA and PM2.5 or NOx exposure was detected. CONCLUSIONS: Our study provides additional evidence that higher PA and lower air pollutant levels are independently connected with reduced mortality risk. The benefits of PA are not significantly affected by long-term air pollution exposure, indicating PA can be recommended to prevent mortality regardless of air pollution levels. Our findings highlight the importance of public health policies and interventions facilitating PA and reducing air pollution in reducing mortality risks and maximizing health benefits. Future investigation is urgently needed to identify these findings in areas with severe air pollution conditions.

Stacking and ridge regression-based spectral ensemble preprocessing method and its application in near-infrared spectral analysis.

Spectral preprocessing techniques can, to a certain extent, eliminate irrelevant information, such as current noise and stray light from spectral data, thereby enhancing the performance of prediction models. However, current preprocessing techniques mostly attempt to find the best single preprocessing method or their combination, overlooking the complementary information among different preprocessing methods. These preprocessing techniques fail to maximize the utilization of useful information in spectral data and restrict the performance of prediction models. This study proposed a spectral ensemble preprocessing method based on the rapidly developing ensemble learning methods in recent years and the ridge regression (RR) model, named stacking preprocessing ridge regression (SPRR), to address the aforementioned issues. Different from conventional ensemble learning methods, the proposed SPRR method applied multiple different preprocessing techniques to the original spectral data, generating multiple preprocessed datasets. These datasets were then individually inputted into RR base models for training. Ultimately, RR still served as the meta-model, integrating the output results of each RR base model through stacking. This approach not only produced diversity in base models but also achieved higher accuracy and lower computational complexity by using a single type of base model. On the apple spectral dataset collected by our team, correlation analysis showed significant complementary information among the data produced by different preprocessing techniques. This provided robust theoretical support for the proposed SPRR method. By introducing the currently popular averaging ensemble preprocessing method in a comparative experiment, the results of applying the proposed SPRR method to six datasets (apple, meat, wheat, olive oil, tablet, and corn) demonstrated that compared to the single preprocessing method and averaging ensemble preprocessing method, SPRR yielded the best accuracy and reliability for all six datasets. Furthermore, under the same conditions of the training and test datasets, the proposed SPRR method demonstrated better performance than the four commonly used ensemble preprocessing methods.

Mesenchymal stem cell-derived extracellular vesicles relieve endothelial cell senescence via recovering CTRP9 upon repressing miR-674-5p in atherosclerosis.

Background: The senescence of endothelial cells is of great importance involving in atherosclerosis (AS) development. Recent studies have proved the protective role of mesenchymal stem cell-derived extracellular vesicles in AS, herein, we further desired to unvei their potential regulatory mechanisms in endothelial cell senescence. Methods: Senescence induced by H2O2 in primary mouse aortic endothelial cells (MAECs) was evaluated by SA-ß-gal staining. Targeted molecule expression was detected by qRT-PCR and Western blotting. The biological functions of MAECs were determined by CCK-8, flow cytometry, transwell, and tube formation assays. Oxidative injury was assessed by LDH, total and lipid ROS, LPO and MDA levels. The proliferation of adipose-derived mesenchymal stem cell (ADSCs) was analyzed by EdU assay. Effect of ADSCs-derived extracellular vesicles (ADSC-EVs) on AS was investigated in HFD-fed ApoE-/- mice. Results: miR-674-5p was up-regulated, while C1q/TNF-related protein 9 (CTRP9) was down-regulated in H2O2-induced senescent MAECs. CTRP9 was demonstrated as a target gene of miR-674-5p. miR-674-5p inhibition restrained senescence, oxidative stress, promoted proliferation, migration, and angiogenesis of H2O2-stimulated MAECs via enhancing CTRP9 expression. Moreover, treatment with ADSC-EVs inhibited H2O2-induced senescence and dysfunction of MAECs through regulating miR-674-5p/CTRP9 axis. In the in vivo AS mouse model, ADSC-EVs combination with miR-674-5p silencing slowed down AS progression via up-regulation of CTRP9. Conclusion: ADSC-EVs repressed endothelial cell senescence and improved dysfunction via promotion of CTRP9 expression upon miR-674-5p deficiency during AS progression, which might provide vital evidence for ADSC-EVs as a promising therapy for AS.

Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer.

Colorectal cancer (CRC) is the third most diagnosed cancer and the second deadliest cancer worldwide representing a major public health problem. In recent years, increasing evidence has shown that microRNA (miRNA) can control the expression of targeted human messenger RNA (mRNA) by reducing their abundance or translation, acting as oncogenes or tumor suppressors in various cancers, including CRC. Due to the significant up-regulation of oncogenic miRNAs in CRC, elucidating the underlying mechanism and identifying dysregulated miRNA targets may provide a basis for improving current therapeutic interventions. In this paper, we proposed Gra-CRC-miRTar, a pre-trained nucleotide-to-graph neural network framework, for identifying potential miRNA targets in CRC. Different from previous studies, we constructed two pre-trained models to encode RNA sequences and transformed them into de Bruijn graphs. We employed different graph neural networks to learn the latent representations. The embeddings generated from de Bruijn graphs were then fed into a Multilayer Perceptron (MLP) to perform the prediction tasks. Our extensive experiments show that Gra-CRC-miRTar achieves better performance than other deep learning algorithms and existing predictors. In addition, our analyses also successfully revealed 172 out of 201 functional interactions through experimentally validated miRNA-mRNA pairs in CRC. Collectively, our effort provides an accurate and efficient framework to identify potential miRNA targets in CRC, which can also be used to reveal miRNA target interactions in other malignancies, facilitating the development of novel therapeutics.

Reaction Environment Regulation for Electrocatalytic CO2 Reduction in Acids.

The electrocatalytic CO2 reduction reaction (CO2RR) is a sustainable route for converting CO2 into value-added fuels and feedstocks, advancing a carbon-neutral economy. The electrolyte critically influences CO2 utilization, reaction rate and product selectivity. While typically conducted in neutral/alkaline aqueous electrolytes, the CO2RR faces challenges due to (bi)carbonate formation and its crossover to the anolyte, reducing efficiency and stability. Acidic media offer promise by suppressing these processes, but the low Faradaic efficiency, especially for multicarbon (C2+) products, and poor electrocatalyst stability persist. The effective regulation of the reaction environment at the cathode is essential to favor the CO2RR over the competitive hydrogen evolution reaction (HER) and improve long-term stability. This review examines progress in the acidic CO2RR, focusing on reaction environment regulation strategies such as electrocatalyst design, electrode modification and electrolyte engineering to promote the CO2RR. Insights into the reaction mechanisms via in situ/operando techniques and theoretical calculations are discussed, along with critical challenges and future directions in acidic CO2RR technology, offering guidance for developing practical systems for the carbon-neutral community.

LncRNA PART1 Attenuates Myocardial Ischemia-Reperfusion Injury by Regulating TFAP2C/DUSP5 Axis via miR-302a-3p.

BACKGROUND AND OBJECTIVES: Myocardial ischemia-reperfusion injury (MIRI) refers to the damage of cardiac function caused by restoration of blood flow perfusion in ischemic myocardium. However, long non-coding RNA prostate androgen regulated transcript 1 (PART1)'s role in MIRI remain unclear. METHODS: Immunofluorescence detected LC3 expression. Intermolecular relationships were verified by dual luciferase reporter assay. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, flow cytometry and transferase-mediated dUTP nick-end labeling (TUNEL) assays analyzed cell viability and apoptosis. The release of lactate dehydrogenase was tested via enzyme-linked immunosorbent assay (ELISA). Left anterior descending coronary artery surgery induced a MIRI mouse model. Infarct area was detected by 2,3,5-triphenyltetrazolium chloride staining. Hematoxylin and eosin staining examined myocardial injury. ELISA evaluated myocardial marker (creatine kinase MB) level. RESULTS: PART1 was decreased in hypoxia/reoxygenation (H/R) induced AC16 cells and MIRI mice. PART1 upregulation attenuated the increased levels of Bax, beclin-1 and the ratio of LC3II/I, and enhanced the decrease of Bcl-2 and p62 expression in H/R-treated cells. PART1 upregulation alleviated H/R-triggered autophagy and apoptosis via miR-302a-3p. Mechanically, PART1 targeted miR-302a-3p to upregulate transcription factor activating enhancer-binding protein 2C (TFAP2C). TFAP2C silencing reversed the protected effects of miR-302a-3p inhibitor on H/R treated AC16 cells. We further established TFAP2C combined to dual-specificity phosphatase 5 (DUSP5) promoter and activated DUSP5. TFAP2C upregulation suppressed H/R-stimulated autophagy and apoptosis through upregulating DUSP5. Overexpressed PART1 reduced myocardial infarction area and attenuated MIRI in mice. CONCLUSION: PART1 improved the autophagy and apoptosis in H/R-exposed AC16 cells through miR-302a-3p/TFAP2C/DUSP5 axis, which might provide novel targets for MIRI treatment.

Simulation of Natural Convection with Sinusoidal Temperature Distribution of Heat Source at the Bottom of an Enclosed Square Cavity.

The lattice Boltzmann method is employed in the current study to simulate the heat transfer characteristics of sinusoidal-temperature-distributed heat sources at the bottom of a square cavity under various conditions, including different amplitudes, phase angles, initial positions, and angular velocities. Additionally, a machine learning-based model is developed to accurately predict the Nusselt number in such a sinusoidal temperature distribution of heat source at the bottom of a square cavity. The results indicate that (1) in the phase angle range from 0 to π, Nu basically shows a decreasing trend with an increase in phase angle. The decline in Nu at an accelerated rate is consistently observed when the phase angle reaches 4π/16. The corresponding Nu decreases as the amplitude increases at the same phase angle. (2) The initial position of the sinusoidal-temperature-distributed heat source Lc significantly impacts the convective heat transfer in the cavity. Moreover, the decline in Nu was further exacerbated when Lc reached 7/16. (3) The optimal overall heat transfer effect was achieved when the angular velocity of the non-uniform heat source reached π. As the angular velocity increases, the local Nu in the square cavity exhibits a gradual and oscillatory decline. Notably, it is observed that Nu at odd multiples of π surpasses that at even multiples of π. Furthermore, the current work integrates LBM with machine learning, enabling the development of a precise and efficient prediction model for simulating Nu under specific operational conditions. This research provides valuable insights into the application of machine learning in the field of heat transfer.

Nitrogen-Based Gas Molecule Adsorption on a ReSe2 Monolayer via Single-Atom Doping: A First-Principles Study.

Two-dimensional materials have shown immense promise for gas-sensing applications due to their remarkable surface-to-volume ratios and tunable chemical properties. However, despite their potential, the utilization of ReSe2 as a gas-sensing material for nitrogen-containing molecules, including NO2, NO, and NH3, has remained unexplored. The choice of doping atoms in ReSe2 plays a pivotal role in enhancing the gas adsorption and gas-sensing capabilities. Herein, the adsorption properties of nitrogen-containing gas molecules on metal and non-metal single-atom (Au, Pt, Ni, P, and S)-doped ReSe2 monolayers have been evaluated systematically via ab initio calculations based on density functional theory. The findings strongly suggest that intrinsic ReSe2 has better selectivity toward NO2 than toward NO and NH3. Moreover, our results provide compelling evidence that all of the dopants, with the exception of S, significantly enhance both the adsorption strength and charge transfer between ReSe2 and the investigated molecules. Notably, P-decorated ReSe2 showed the highest adsorption energy for NO2 and NO (-1.93 and -1.52 eV, respectively) with charge transfer above 0.5e, while Ni-decorated ReSe2 exhibited the highest adsorption energy for NH3 (-0.76 eV). In addition, on the basis of transition theory, we found that only Au-ReSe2 and Ni-ReSe2 can serve as reusable chemiresisitve gas sensors for reliable detection of NO and NH3, respectively. Hence, our findings indicate that gas-sensing applications can be significantly improved by utilizing a single-atom-doped ReSe2 monolayer.

The role of transcription factor FOXA1/C2/M1/O3/P1/Q1 in breast cancer.

Breast cancer is a common malignancy with the highest mortality rate among women worldwide. Its incidence is on the rise year after year, accounting for more than one-tenth of new cancers worldwide. Increasing evidence suggests that forkhead box (FOX) transcription factors play an important role in the occurrence and development of breast cancer. However, little is known about the relationship between the expression, prognostic value, function, and immune infiltration of FOX transcription factors in tumor microenvironment. We used bioinformatics to investigate expression and function of FOX factor in breast cancer. Our results revealed the expression levels of FOXA1 and FOXM1 were significantly higher in breast cancer tissues than in normal tissues. The high expression of mRNA in FOXA1 (P < .05), FOXM1 (P < .01), and FOXP1 (P < .05) groups was related to tumor stage. Survival analysis results showed that increased FOXP1 mRNA levels were significantly associated with overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS) in all patients with breast cancer (P < .05). Patients with the FOXA1 high-expression group had better RFS and DMFS than the low-expression group (P < .05), while patients with FOXM1 high-expression group had worse RFS, OS, and DMFS than the low-expression group (P < .05). Meanwhile, mutation analysis showed that genetic alterations in FOX transcription factors were significantly associated with shorter OS and progression-free survival (P < .05), but not with disease-free survival (P = .710) in patients with breast cancer. FOXP1, FOXA1, and FOXM1 may be used as potential biomarkers to predict the prognosis of patients with breast cancer. Functional enrichment indicated that FOX was mainly involved in cell division, cell senescence, cell cycle, and prolactin signaling pathway. In patients with breast cancer, FOXC2 expression was negatively correlated with the infiltration of B cells and positively correlated with the infiltration of neutrophils and dendritic cells. However, FOXM1 was negatively correlated with the infiltration of CD8 + T cells and macrophages and positively correlated with the infiltration of neutrophils and dendritic cells. These findings provided novel insights into the screening of prognostic biomarkers of the FOX family in breast cancer and laid a foundation for further research on the immune infiltration of the FOX transcription factor family members in tumors.

Regulable high-contrast mechanofluorochromic enhancement behaviour based on substituent effects.

Herein, a facile strategy was established to build mechanoresponsive luminogens with high sensitivity to substituents and positional effects. Even in slightly different structures, distinct optical phenomena, including fluorescence efficiency and mechano-responsive properties, were clearly present. Outstanding mechanical-induced emission enhancement (5-100 times) properties and reversibility makes for promising applications in pressure sensors and OLEDs.

Transcriptomic and intervention evidence reveals domestic dogs as a promising model for anti-inflammatory investigation.

Domestic dogs have great potential to expand our understanding of the determinants of aging. To understand the aging pattern of domestic dogs and evaluate whether they can be used as an aging model, we performed RNA sequencing on white blood cells from domestic dogs aged 1-9 years and treated aged dogs with classical antiaging approaches. We obtained 30 RNA sequencing libraries and identified 61 age-associated genes with dynamic changes, the majority of which were related to metabolism and immune function, which may be predominant biomarkers for aging in dogs. We next treated aged dogs with canine mesenchymal stem cells (cMSCs), nicotinamide mononucleotide, and rapamycin to determine whether and how they responded to the antiaging interventions. The results showed that these treatments can significantly reduce the level of inflammatory factors (IL-6 and TNF-α). MSCs effectively improved the heart functions of aged dogs. Three key potential age-related genes (PYCR1, CCRL2, and TOX) were reversed by MSC treatment, two of which (CCRL2 and TOX) are implicated in immunity. Overall, we profiled the transcriptomic pattern of domestic dogs and revealed that they may be a good model of aging, especially in anti-inflammatory investigations.