Targeting microbiota-immune-synaptic plasticity to explore the effect of tea polyphenols on improving memory in the aged type 2 diabetic rat model.

OBJECTIVES: The study aimed to explore whether TP could improve memory in the aged type 2 diabetic rat model by regulating microbiota-immune-synaptic plasticity axis. METHODS: The experiment was divided into two parts. Firstly, to investigate the effects of TP on the physiopathology of the aged T2DM model rats, rats were randomly divided into the Normal control group, the aged group, the Aged T2DM model group, the TP 75, 150, 300 mg/kg groups, the 150 mg/kg Piracetam group and the 3 mg/kg Rosiglitazone group. Then, to further verify whether TP improved memory in aged T2DM rat model by regulating intestinal flora, the fecal microbiota transplantation (FMT) from the rats in the 300 mg/kg TP group into the rats in the aged T2DM model group was carried out. Effects on gut microbiota, colonic integrity (epithelial tight junction proteins), and endotoxemia (serum LPS) were examined, along with synaptic structure, synaptic plasticity-related structural proteins and inflammation signaling of the hippocampus in our study. RESULTS: Our results demonstrated that TP alleviated memory impairments in the aged T2DM rat model. The specific outcomes were as follows: TP 300 mg/kg corrected the gut dysbacteriosis, alleviated intestinal permeability reduction and peripheral/central inflammation, inhibited the TLR4/NF-κB signaling pathway. Meanwhile, TP improved the synaptic plasticity in the hippocampus of the aged T2DM model rats, whose expressions of SYN, PSD 95, NMDAR1 and GluR1 in hippocampus were significantly up-regulated. Surprisingly, rats of the FMT group displayed the same changes. DISCUSSION: TP improves the memory in aged T2DM rat model. The mechanism may be related to the alteration of gut flora, which can inhibit hippocampal TLR4/NF-κB signaling to attenuate neuroinflammation, then improve synaptic plasticity. The study proposes that TP interventions aimed at manipulating the gut microbiota may hold great potential as an effective approach for preventing and treating this disease.

[Tea polyphenols improves depression-like behavior in aged type 2diabetes rats by regulating microglia polarization].

OBJECTIVE: To investigate the effect of tea polyphenols(TP) on improving depression-like behavior in aged type 2 diabetes(T2DM) model rats. METHODS: A total of 40 8-week-old SD male rats were randomly divided into the control group(n=10) and the modeling group(n=30) according to the body weight. The rats in the modeling group were fed with high-glucose and high-fat diet and treated with 50 mg/kg D-galactose by intraperitoneal injection daily until the end of the experiment, while the rats in the control group were fed with the standard diet and treated with an equal volume of saline by intraperitoneal injection. After 4 weeks, the rats in the modeling group were injected with 25 mg/kg STZ, meanwhile the rats in the control group were injected with an equal volume of citric acid buffer. The level of fasting blood glucose(FBG) was measured on the 14~(th) day. When FBG≥16.7 mmol/L, the rats were identified as successful model of the T2DM rats. Then, the model rats were randomly divided into the model group, 150, 300 mg/kg TP groups(n=10, respectively), and the rats were given intragastric intervention for 8 weeks. The levels of the FBG were detected, and the depression-like behavior of rats was assessed by the open field test(OFT) and forced swimming test(FST). The density of microglia in hippocampus CA1 region was assessed by immunofluorescence staining, and protein expressions of P53, Iba1, iNOS, Arg-1 and BDNF were determined by western blot. RESULTS: Compared with the control group, the levels of FBG in the rats of the model group were obviously increased(P<0.01). In the OFT, the frequencies of rearing and grooming in the rats of model group markedly was decreased, while in the FST, the immobility time extensively was increased(P<0.01). The density of microglia in hippocampus CA1 region was increased(P<0.01). The expressions of P53, Iba1 and iNOS were increased, and the expressions of Arg-1 and BDNF were decreased(P<0.01). Additionally, compared with the model group, in the OFT, the frequencies of rearing and grooming were increased in the rats in 150 and 300 mg/kg TP group(P<0.01). The density of microglia in hippocampus CA1 region was decreased(P<0.01). The expressions of P53, Iba1 and iNOS were down-regulated, and the expression of BDNF was up-regulated(P<0.01). Additionally, compared with the model group, the levels of FBG was decreased in the rats in the 300 mg/kg TP group(P<0.01). The immobility time was decreased in the FST(P<0.01). The expression of Arg-1 was down-regulated(P<0.01). CONCLUSION: TP can improve depression-like behavior in aged T2DM model rats, and its mechanism may be related to regulate microglia M1/M2 polarization and up-regulate expression of BDNF in hippocampus.

Transpapillary Stenting Improves Treatment Outcomes in Patients Undergoing Endoscopic Transmural Drainage of Ductal Disruption-Associated Pancreatic Fluid Collections.

INTRODUCTION: Endoscopic transmural drainage (TMD) has been accepted as the preferred therapy for symptomatic pancreatic fluid collections (PFCs). Recurrence of PFCs presents a unique challenge in patients with disrupted pancreatic duct (PD). We aimed to evaluate whether transpapillary drainage (TPD) provides additional benefits to TMD in patients with PD disruption. METHODS: This was a multicenter retrospective study. Consecutive patients who underwent TMD, TPD, or combined drainage (CD) of PFCs were included. The primary outcome was to compare PFC recurrence among different groups. The secondary outcomes were the technical success rate, length of hospital stay, and procedure-related complications. RESULTS: A total of 153 patients, which consists of 57 patients with pancreatic pseudocysts and 96 patients with walled-off necrosis, were included. PFC recurrence was more common in patients with PD disruption than those with an intact main duct (19% vs 1.4%, P < 0.001). PD disruption was identified as a major risk factor of PFC recurrence by univariable and multivariable analyses. The recurrence rate of CD was significantly lower than TMD only or TPD only (6.5% vs 15.4% vs 22.7%, P < 0.01). The length of hospital stay of CD was significantly shorter than TMD only or TPD only (5 [3.0-9.0] vs 7.0 [5.0-12.0] vs 9 [7.0-16.0], P < 0.001). Dual-modality drainage did not increase procedure-related complications compared with TMD only (13.0% vs 12.8%, P > 0.05). Partial PD disruption was bridged in 87.3% cases while complete PD disruption was reconnected in 55.2% cases. Although statistically not significant, the clinical success rate in walled-off necrosis cases with actively bridged ducts was much higher than those with passively bridged ducts (76.9% vs 40%). DISCUSSION: Transpapillary pancreatic duct stenting seems to improve the efficacy of endoscopic TMD of pancreatic duct disruption-associated PFCs by reducing the recurrence rate and shortening the length of hospital stay.

The Wet Suction Technique Enhances the Diagnostic Efficacy and Aspirate Quality of EUS-FNA for Solid Lesions: A Multicenter Retrospective Study in China.

GOALS: To comprehensively compare the wet suction technique with the conventional dry suction technique for endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) in solid lesions. BACKGROUND: Optimal suction techniques for EUS-FNA remain uncertain when approaching solid lesions. STUDY: We performed a retrospective study of EUS-FNA at 3 medical centers in China. A total of 203 patients were enrolled who received 2 passes of EUS-FNA with 22-G needles. If the first pass underwent dry suction, the second pass was wet suction. Otherwise, the order of suction technique is opposite. Diagnostic accuracy, sample quality (including cellularity and blood contamination), and sample quantity (including specimen adequacy, the maximum intact specimen length, and the total specimen length) were compared between wet-suction and dry-suction techniques. RESULTS: The patients included 143 pancreatic lesions and 60 nonpancreatic lesions. Compared with the dry suction technique, the wet suction technique yielded a significantly higher diagnostic accuracy (85.22% vs. 72.41%, P =0.002), better specimen adequacy score and cellularity score ( P <0.0001), and lower blood contamination score ( P <0.0001). In the subgroup analysis, wet suction provided significantly higher diagnostic accuracy in pancreatic cancer without chronic pancreatitis ( P <0.05), and better cellularity score and specimen adequacy score, lower blood contamination score, and longer maximum intact specimen length and total specimen length in various lesions than that in dry suction. CONCLUSIONS: The wet suction technique resulted in significantly higher diagnostic accuracy in pancreatic cancer without chronic pancreatitis, and better cellularity and histologic specimen in most of solid lesions.

Omnidirectional Haptic Stimulation System via Pneumatic Actuators for Presence Presentation.

Recently, remote meetings and work-from-home have become more common, reducing the opportunities for face-to-face communication. To facilitate communication among remote workers, researchers have focused on virtual space technology and spatial augmented reality technology. Although these technologies can enhance immersiveness in collaborative work, they face the challenge of fostering a sense of physical contact. In this work, we aimed to foster a sense of presence through haptic stimulation using pneumatic actuators. Specifically, we developed a choker-type wearable device that presents various pressure patterns around the neck; the pattern presented depends on the message the device must convey. Various combinations of haptic presentation are achieved by pumping air to the multiple pneumatic actuators attached to the choker. In addition, we conducted experiments involving actuators of different shapes to optimize the haptic presentation. When linked with a smartphone, the proposed device can present pressure patterns to indicate incoming calls and notifications, to give warning about an obstacle that one who is texting might miss while walking, and to provide direction to a pedestrian. Furthermore, the device can be used in a wide range of applications, from those necessary in daily living to those that enhance one's experience in the realm of entertainment. For example, haptic feedback that synchronizes with the presence of a singer or with the rhythm of a song one listens to or with a performer's movements during a stage performance will immerse users in an enjoyable experience.

Circular RNA circ_0047744 suppresses the metastasis of pancreatic ductal adenocarcinoma by regulating the miR-21/SOCS5 axis.

There is increasing evidence that circular RNAs (circRNAs) can serve as microRNA (miRNA) sponges to regulate metastasis of multiple tumors, including pancreatic ductal adenocarcinoma (PDAC). However, the role of the circRNA/miRNA regulatory network in metastasis of PDAC has not been elucidated. The purpose of this study is to explore the role of circ_0047744/miR-21/SOCS5 in the metastasis of PDAC. We found that circRNA_0047744 was weakly expressed in PDAC tissues and cell lines. The expression of circ_0047744 was negatively correlated with lymph node metastasis and positively correlated with overall survival in PDAC patients. Functionally, the overexpression of circ_0047744 suppressed cell migration and invasion in vitro and in vivo. Mechanistically, circ_0047744 could regulate SOCS5 expression by acting as a sponge of miR-21 to inhibit migration and invasion of PDAC cells. Our study demonstrates that circ_0047744 acts as an anti-oncogene to inhibit PDAC metastasis by regulating the miR-21/SOCS5 axis, indicating that circ_0047744 may be a potential novel therapeutic target for PDAC patients.

Proteo-chemometrics interaction fingerprints of protein-ligand complexes predict binding affinity.

MOTIVATION: Reliable predictive models of protein-ligand binding affinity are required in many areas of biomedical research. Accurate prediction based on current descriptors or molecular fingerprints (FPs) remains a challenge. We develop novel interaction FPs (IFPs) to encode protein-ligand interactions and use them to improve the prediction. RESULTS: Proteo-chemometrics IFPs (PrtCmm IFPs) formed by combining extended connectivity fingerprints (ECFPs) with the proteo-chemometrics concept. Combining PrtCmm IFPs with machine-learning models led to efficient scoring models, which were validated on the PDBbind v2019 core set and CSAR-HiQ sets. The PrtCmm IFP Score outperformed several other models in predicting protein-ligand binding affinities. Besides, conventional ECFPs were simplified to generate new IFPs, which provided consistent but faster predictions. The relationship between the base atom properties of ECFPs and the accuracy of predictions was also investigated. AVAILABILITY: PrtCmm IFP has been implemented in the IFP Score Toolkit on github (https://github.com/debbydanwang/IFPscore). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Towards optimal conversion efficiency of Brillouin random fiber lasers in a half-open linear cavity.

We proposed and demonstrated an unprecedented high-efficiency Brillouin random fiber laser (BRFL) by fiber length optimization in a half-open linear cavity. In terms of the trade-off between Brillouin gain saturation and weak distributed Rayleigh feedback strength, optimal laser efficiency associated to proper fiber length in a BRFL was theoretically predicted. As a proof-of-concept, a unidirectional-pumped BRFL with a half-open linear cavity was experimentally conducted, in which a fiber Bragg grating at one end of gain fiber served as a high-reflection mirror while Rayleigh scattering enabled distributed feedback for random lasing resonance. Results show that the optimal fiber length of ∼3.4 km in the BRFL offers sufficient Rayleigh scattered random feedback whilst alleviating the Brillouin gain saturation to a large extent. Consequently, an optimal laser efficiency of 77.0% in the BRFL was experimentally demonstrated, which reaches the state-of-the-art high record. Laser characteristics, including the linewidth, statistics and frequency jitter were also systematically investigated. It is believed that such efficient BRFL could provide a promising platform for inspiring new explorations of laser physics as well as potentials in long-haul coherent communication and fiber-optic sensing.

Temporal event searches based on event maps and relationships.

To satisfy a user's need to find and understand the whole picture of an event effectively and efficiently, in this paper we formalize the problem of temporal event searches and propose a framework of event relationship analysis for search events based on user queries. We define three kinds of event relationships: temporal, content dependence, and event reference, that can be used to identify to what extent a component event is dependent on another in the evolution of a target event (i.e., the query event). The search results are organized as a temporal event map (TEM) that serves as the whole picture about an event's evolution or development by showing the dependence relationships among events. Based on the event relationships in the TEM, we further propose a method to measure the degrees of importance of events, so as to discover the important component events for a query, as well as the several algebraic operators involved in the TEM, that allow users to view the target event. Experiments conducted on a real data set show that our method outperforms the baseline method Event Evolution Graph (EEG), and it can help discover certain new relationships missed by previous methods and even by human annotators.

A bibliometric analysis of natural language processing in medical research.

BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great significance to conduct a deep analysis to understand the recent development of NLP-empowered medical research field. However, limited study examining the research status of this field could be found. Therefore, this study aims to quantitatively assess the academic output of NLP in medical research field. METHODS: We conducted a bibliometric analysis on NLP-empowered medical research publications retrieved from PubMed in the period 2007-2016. The analysis focused on three aspects. Firstly, the literature distribution characteristics were obtained with a statistics analysis method. Secondly, a network analysis method was used to reveal scientific collaboration relations. Finally, thematic discovery and evolution was reflected using an affinity propagation clustering method. RESULTS: There were 1405 NLP-empowered medical research publications published during the 10 years with an average annual growth rate of 18.39%. 10 most productive publication sources together contributed more than 50% of the total publications. The USA had the highest number of publications. A moderately significant correlation between country's publications and GDP per capita was revealed. Denny, Joshua C was the most productive author. Mayo Clinic was the most productive affiliation. The annual co-affiliation and co-country rates reached 64.04% and 15.79% in 2016, respectively. 10 main great thematic areas were identified including Computational biology, Terminology mining, Information extraction, Text classification, Social medium as data source, Information retrieval, etc. CONCLUSIONS: A bibliometric analysis of NLP-empowered medical research publications for uncovering the recent research status is presented. The results can assist relevant researchers, especially newcomers in understanding the research development systematically, seeking scientific cooperation partners, optimizing research topic choices and monitoring new scientific or technological activities.

The Effects of Berberine on Concanavalin A-Induced Autoimmune Hepatitis (AIH) in Mice and the Adenosine 5'-Monophosphate (AMP)-Activated Protein Kinase (AMPK) Pathway.

BACKGROUND Berberine, a herbal extract, has been reported to protect against inflammatory disorders. The adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway can be activated by berberine and inhibited by the synthetic, reversible AMP-competitive inhibitor, Compound C. The aim of this study was to investigate the effects of berberine on concanavalin A (Con A)-induced autoimmune hepatitis (AIH) in mice via the AMPK pathway. MATERIAL AND METHODS BALB/c mice were treated with berberine, with or without Compound C, followed by treatment with Con A. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were measured. Liver tissue histology was performed to evaluate hepatic injury and AIH. Cytokine levels in serum and hepatic tissue were measured by enzyme-linked immunoassay (ELISA) and used quantitative polymerase chain reaction (qPCR). Levels of phosphorylated acetyl coenzyme-A carboxylase (ACC), representing AMPK activation, were detected by Western blotting. RESULTS Serum ALT and AST levels were significantly reduced by berberine (100 and 200 mg/kg/day) in mice with Con A-induced hepatitis. Berberine also reduced Con A-induced hepatocyte swelling, cell death, and infiltration of leukocytes. Serum levels of tumor necrosis factor (TNF)-alpha, interferon (IF)-gamma, interleukin (IL)-2, and IL-1beta were reduced by berberine pre-treatment; levels of serum IL-10, an anti-inflammatory cytokine, was elevated. These protective effects of berberine on Con-A-induced AIH were reversed by treatment with Compound C. CONCLUSIONS In a murine model of Con A-induced AIH, berberine treatment reduced hepatic injury via activation of the AMPK pathway. Further studies are recommended to determine the potential therapeutic role for berberine in AIH.

The collaborative search by tag-based user profile in social media.

Recently, we have witnessed the popularity and proliferation of social media applications (e.g., Delicious, Flickr, and YouTube) in the web 2.0 era. The rapid growth of user-generated data results in the problem of information overload to users. Facing such a tremendous volume of data, it is a big challenge to assist the users to find their desired data. To attack this critical problem, we propose the collaborative search approach in this paper. The core idea is that similar users may have common interests so as to help users to find their demanded data. Similar research has been conducted on the user log analysis in web search. However, the rapid growth and change of user-generated data in social media require us to discover a brand-new approach to address the unsolved issues (e.g., how to profile users, how to measure the similar users, and how to depict user-generated resources) rather than adopting existing method from web search. Therefore, we investigate various metrics to identify the similar users (user community). Moreover, we conduct the experiment on two real-life data sets by comparing the Collaborative method with the latest baselines. The empirical results show the effectiveness of the proposed approach and validate our observations.

Technology-enhanced higher education: Text mining and bibliometrics.

Objectives: Research on technology-enhanced higher education (TEHE) has been active and influential in educational technology. The study had three objectives: (1) to recognize the tendencies in the field and the contributing countries/regions/institutions, (2) to visualize scientific collaborations, and (3) to reveal important research topics, their developmental tendencies, correlations, and distributions across contributing countries/regions/institutions. Methods: We collected 609 papers in relation to TEHE from 2004 to 2022 and analyzed them using text mining and bibliometric methods. Specifically, we focused on determining article trends, identifying contributing institutions/countries/regions, visualizing scientific collaborations through social network analysis, and revealing the important topics and their conceptual evolutions over time using topic models, Mann-Kendall trend test, hierarchical clustering, and Sankey visualization. Results: Regarding the first objective, TEHE articles have grown consistently and will continue to expand. This growth was due to the contributions of Spanish universities and institutions from other countries/regions such as the USA, the UK, Australia, Germany, China, and Turkey. Regarding the second objective, the exploration of regional and institutional collaborations through social networks revealed that geographically adjacent institutions tended to foster close collaborations, particularly among those sharing similar research interests. Nevertheless, more cross-regional collaborations are needed to advance TEHE research. Regarding the third objective, the analysis of topics highlighted research hotspots and emerging themes such as Massive Online Open Courses, AI and big data in education, Gamification and engagement, Learning effectiveness and strategies, Social networks and discussion forums, COVID-19 and online learning, and Plagiarism detection and learning analytics. Conclusions: This bibliometric study comprehensively analyzed the research landscape of TEHE research regarding contributors, collaborations, and research topics, and offers a glimpse into what the future may hold. It can be used as a guide for contributors to the field to identify the current research hotspots and emerging themes.

Study on the factors affecting the mechanical properties of antler under quasi-static compression.

In the natural environment, antlers have a significant mechanical structure that protects the deer head from injury. In this paper, the mechanical properties of antlers were evaluated through quasi-static compression tests and microstructural observation of samples from antlers, and the relationship between the sampling position, load direction, and microstructure and their mechanical properties were investigated. Compression experiments confirmed that the tines had the strongest mechanical properties, followed by the main beams and finally the brow tines. The mechanical properties of the test specimens subjected to axial compression were higher than those of lateral compression. The axial load test of the longitudinal sample of the tine of the antler has the best mechanical properties. Its specific energy absorption is 51.33 J/g, the peak crushing force is 1.26 kN, and the mean crushing force is 1.47 kN. There are many tubular structures in the transverse sections of antlers, and the distribution of fibers in the vertical direction is laminar with alternating rows forming a helical structure. Tubular structures were found to be prevalent in some of the better biomechanical structures by comparison. Numerical modeling simulations to describe the effect of tubular structures on the mechanical properties of antlers. The simulation results show that the increase in the size of the tubular structure improves its energy absorption within the variation of a 20% increase in the size of the long and short axis. These findings provide a theoretical and experimental basis for the design of energy-absorbing structures. RESEARCH HIGHLIGHTS: In this paper, transverse and longitudinal samples were taken from the main beam, tine, and brow tine of antlers, and axial and lateral compression were carried out, respectively. In this paper, quasi-static compression experiments were carried out on antler samples to study the effects of sampling position, loading direction, and microstructure on antler mechanical properties. By means of microstructure observation and numerical modeling, it is determined that the size of the antler Havel tube has an effect on its mechanical properties.

UCL-Dehaze: Toward Real-World Image Dehazing via Unsupervised Contrastive Learning.

While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known domain shift problem. From a different yet new perspective, this paper explores contrastive learning with an adversarial training effort to leverage unpaired real-world hazy and clean images, thus alleviating the domain shift problem and enhancing the network's generalization ability in real-world scenarios. We propose an effective unsupervised contrastive learning paradigm for image dehazing, dubbed UCL-Dehaze. Unpaired real-world clean and hazy images are easily captured, and will serve as the important positive and negative samples respectively when training our UCL-Dehaze network. To train the network more effectively, we formulate a new self-contrastive perceptual loss function, which encourages the restored images to approach the positive samples and keep away from the negative samples in the embedding space. Besides the overall network architecture of UCL-Dehaze, adversarial training is utilized to align the distributions between the positive samples and the dehazed images. Compared with recent image dehazing works, UCL-Dehaze does not require paired data during training and utilizes unpaired positive/negative data to better enhance the dehazing performance. We conduct comprehensive experiments to evaluate our UCL-Dehaze and demonstrate its superiority over the state-of-the-arts, even only 1,800 unpaired real-world images are used to train our network. Source code is publicly available at https://github.com/yz-wang/UCL-Dehaze.

Targeting ERS-mitophagy in hippocampal neurons to explore the improvement of memory by tea polyphenols in aged type 2 diabetic rats.

Increasing evidence demonstrated that mitophagy and endoplasmic reticulum stress (ERS) was closely associated with memory decline in elderly type 2 diabetes mellitus (T2DM). Tea polyphenols (TP), an excellent natural antioxidant, has been reported to have neuroprotective properties in aging and diabetes, but the underlying mechanisms are still not fully understood. This study targets ERS-mitophagy in hippocampal neurons to investigate the improvement effect of memory in aged T2DM rats by TP. Rats were randomly divided into the control group, the aged group, the aged T2DM model group, the TP 75, 150, 300 mg/kg groups. TP 300 mg/kg ameliorated mitophagy by decreasing the levels of p-mTOR (S2448), P62 and HSP60 and increasing the levels of PINK1 and Parkin, the ratio of LC3Ⅱ/LC3Ⅰ, co-localization of LC3 and HSP60 and the number of autophagosomes and autolysosomes. TP 300 mg/kg attenuated ERS by downregulating the levels of p-PERK, p-eIF2α, ATF4, GRP78 and restoring the ER structure. To further verify epigallocatechin gallate (EGCG), which is the main active component of TP, enhanced mitophagy by inhibiting ERS, PC12 cells were pretreated with ERS activator tunicamycin (TM) or ERS inhibitor 4-phenylbutyric acid (4-PBA). The results showed that the improvement of mitophagy by EGCG was inhibited by TM and promoted by 4-PBA. Collectively, ERS-mitophagy in hippocampal neurons plays a key role in the improvement of memory by TP in aged T2DM rats. This study will provide a new perspective and strategy for the prevention of memory decline in elderly with T2DM.

Identification of a potential prognostic model combining pyroptosis-related gene with immune microenvironment for pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a fatal tumor with grave prognosis. Pyroptosis, a programmed cell death, is involved in tumorigenesis. However, a few studies have elucidated the functions of pyroptosis in PDAC. METHODS: The mRNA expression profiles were downloaded from the TCGA and GEO databases. Univariate and LASSO Cox regression analyses were used to screen out differentially expressed genes (DEGs) and construct the pyroptosis-related genes (PRGs) risk model. The efficiency of model was examined by Kaplan-Meier curve, ROC curve, and nomogram. Univariate and multivariate Cox regression analyses were utilized to assess whether the risk model could be used as an independent prognostic factor. The biological function was analyzed by GO, KEGG, and GSEA enrichment analysis. qRT-PCR and immunohistochemical staining detected gene expression. RESULTS: Totally 9 PRGs with differential expression were identified between normal and PDAC tissues. Then, according to PRGs, we filtered out three key DEGs and constructed the prognostic risk model. Kaplan-Meier curve, ROC curve, and nomogram indicated that the prognostic risk model had high survival prediction efficiency. Meanwhile, the risk model had also shown to be an independent prognostic factor. Further functional enrichment analysis showed that cell adhesion, PI3K-AKT signaling pathway, and dysregulated immune status may be associated with PDAC development. External validation of the model was carried out in the GEO cohort, and the results were similar to that in the TCGA cohort. Finally, the expression of three genes was verified by qRT-PCR and immunohistochemical staining. CONCLUSION: The prognostic risk model established in this study can give a good prediction of the prognosis of PDAC patients, which might provide insights into clinical treatments and prognostic prediction of PDAC.

GeoDualCNN: Geometry-Supporting Dual Convolutional Neural Network for Noisy Point Clouds.

We propose a geometry-supporting dual convolutional neural network (GeoDualCNN) for both point cloud normal estimation and denoising. GeoDualCNN fuses the geometry domain knowledge that the underlying surface of a noisy point cloud is piecewisely smooth with the fact that a point normal is properly defined only when local surface smoothness is guaranteed. Centered around this insight, we define the homogeneous neighborhood (HoNe) which stays clear of surface discontinuities, and associate each HoNe with a point whose geometry and normal orientation is mostly consistent with that of HoNe. Thus, we not only obtain initial estimates of the point normals by performing PCA on HoNes, but also for the first time optimize these initial point normals by learning the mapping from two proposed geometric descriptors to the ground-truth point normals. GeoDualCNN consists of two parallel branches that remove noise using the first geometric descriptor (a homogeneous height map, which encodes the point-position information), while preserving surface features using the second geometric descriptor (a homogeneous normal map, which encodes the point-normal information). Such geometry-supporting network architectures enable our model to leverage previous geometry expertise and to benefit from training data. Experiments with noisy point clouds show that GeoDualCNN outperforms the state-of-the-art methods in terms of both noise-robustness and feature preservation.

Effects of different timing selections of labor analgesia for primiparae on parturition and neonates.

OBJECTIVE: To explore the effects of labor analgesia for primiparae with different stages of cervical dilation on parturition and neonates. MATERIALS AND METHODS: In the past three years, 530 cases of primiparae who had delivered in the Second People's Hospital of Hefei and were eligible for a vaginal trial of parturition were enrolled as the research subjects. Of these, 360 puerperae had labor analgesia, and the remaining 170 were taken as the control group. Those given labor analgesia were divided into three groups based on the different stages of cervical dilation at that time. There were 160 cases in Group I (cervical dilation <3 cm), 100 cases in Group II (cervical dilation of 3-4 cm), and 100 cases in Group III (cervical dilation of 4-6 cm). The labor and neonatal outcomes were compared among the four groups. RESULTS: The first, second, and total stages of labor in the three groups receiving labor analgesia were all longer than in the control group, and the differences were statistically significant (p < 0.05 in all). Group I had the longest duration of each stage and the total stage of labor. The differences in labor stages and the total stage of labor were not statistically significant between Group II and Group III (P > 0.05). In the three groups with labor analgesia, the usage rate of oxytocin was higher than in the control group, and the differences were statistically significant (P < 0.05). The differences in the incidence of postpartum hemorrhage, the incidence of postpartum urine retention, and the episiotomy rate were not statistically significant among the four groups (P > 0.05). The differences in the neonatal Apgar score were not statistically significant among the four groups (P > 0.05). CONCLUSION: Labor analgesia might prolong the stages of labor but does not affect the neonatal outcomes. It would be optimal to conduct labor analgesia when cervical dilation reaches 3-4 cm.

Mimosa Kinetic Façade: Bio-Inspired Ventilation Leveraging the Mimosa Pudica Mechanism for Enhanced Indoor Air Quality.

In light of pressing global health concerns, the significance of indoor air quality in densely populated structures has been emphasized. This research introduces the Mimosa kinetic façade, an innovative design inspired by the adaptive responsiveness of the Mimosa plant to environmental stimuli. Traditional static architectural façades often hinder natural ventilation, leading to diminished air quality with potential health and cognitive repercussions. The Mimosa kinetic façade addresses these challenges by enhancing effective airflow and facilitating the removal of airborne contaminants. This study evaluates the façade's impact on quality of life and its aesthetic contribution to architectural beauty, utilizing the biomimicry design spiral for a nature-inspired approach. Computational simulations and physical tests were conducted to assess the ventilation capacities of various façade systems, with a particular focus on settings in Bangkok, Thailand. The study revealed that kinetic façades, especially certain patterns, provided superior ventilation compared to static ones. Some patterns prioritized ventilation, while others optimized human comfort during extended stays. Notably, the most effective patterns of the kinetic façade inspired by the Mimosa demonstrated a high air velocity reaching up to 12 m/s, in contrast to the peak of 2.50 m/s in single-sided façades (traditional façades). This highlights the kinetic façade's potential to rapidly expel airborne particles from indoor spaces, outperforming traditional façades. The findings underscore the potential of specific kinetic façade patterns in enhancing indoor air quality and human comfort, indicating a promising future for kinetic façades in architectural design. This study aims to achieve an optimal balance between indoor air quality and human comfort, although challenges remain in perfecting this equilibrium.