Platelet Membrane Coated Cu9S8-SNAP for Targeting NIR-II Mild Photothermal Enhanced Chemodynamic/Gas Therapy of Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is a highly aggressive and uncommon subtype of breast cancer with a poor prognosis. It is crucial to prioritise the creation of a nanotherapeutic method that is highly selective and actively targeting TNBC. This study explores a new nanosystem, Cu9S8-SNAP@PM (C-S@P), composed of Cu9S8-SNAP coated with a platelet membrane (PM). The purpose of this nanosystem is to cure TNBC using multimodal therapy. The utilisation of PM-coated nanoparticles (NPs) enables active targeting, leading to the efficient accumulation of C-S@P within the tumour. The Cu9S8 component within these NPs serves the potential to exert photothermal therapy (PTT) and chemodynamic therapy (CDT). Simultaneously, the S-Nitroso-N-Acetylvanicillamine (SNAP) component enables nitric oxide (NO) gas therapy (GT). Furthermore, when exposed to NIR-II laser light, Cu9S8 not only increases the temperature of the tumour area for PTT, but also boosts CDT and stimulates the release of NO through thermal reactions to improve the effectiveness of GT. Both in vitro and in vivo experimental results validate that C-S@P exhibits minimal side effects and represents a multifunctional nano-drug targeted at tumors for efficient treatment. This approach promises significant potential for TNBC therapy and broader applications in oncology.

Fan-in/fan-out for heterogeneous 19-core fibers based on metasurfaces with nonuniform phase plates.

In space-division-multiplexed transmission systems, it is essential to realize fan-in/fan-out devices that connect the cores between multicore fibers and single-mode fibers. In this Letter, we propose a metasurface-based fan-in/fan-out device with nonuniform phase plates for heterogeneous 19-core fibers across the full C band. Our results show that an average insertion loss of 0.85 dB and a maximum crosstalk of -25.5 dB can be achieved at 1550 nm. Across the C band, the insertion loss and crosstalk are better than 2.78 dB and -19.96 dB, respectively. The proposed concept can flexibly handle various fiber configurations without additional complexity.

Using pose estimation to identify regions and points on natural history specimens.

A key challenge in mobilising growing numbers of digitised biological specimens for scientific research is finding high-throughput methods to extract phenotypic measurements on these datasets. In this paper, we test a pose estimation approach based on Deep Learning capable of accurately placing point labels to identify key locations on specimen images. We then apply the approach to two distinct challenges that each requires identification of key features in a 2D image: (i) identifying body region-specific plumage colouration on avian specimens and (ii) measuring morphometric shape variation in Littorina snail shells. For the avian dataset, 95% of images are correctly labelled and colour measurements derived from these predicted points are highly correlated with human-based measurements. For the Littorina dataset, more than 95% of landmarks were accurately placed relative to expert-labelled landmarks and predicted landmarks reliably captured shape variation between two distinct shell ecotypes ('crab' vs 'wave'). Overall, our study shows that pose estimation based on Deep Learning can generate high-quality and high-throughput point-based measurements for digitised image-based biodiversity datasets and could mark a step change in the mobilisation of such data. We also provide general guidelines for using pose estimation methods on large-scale biological datasets.

The greener the living environment, the better the health? Examining the effects of multiple green exposure metrics on physical activity and health among young students.

The sedentary and less active lifestyle of modern college students has a significant impact on the physical and mental well-being of the college community. Campus Green Spaces (GSs) are crucial in promoting physical activity and improving students' health. However, previous research has focused on evaluating campuses as a whole, without considering the diverse spatial scenarios within the campus environment. Accordingly, this study focused on the young people's residential scenario in university and constructed a framework including a comprehensive set of objective and subjective GSs exposure metrics. A systematic, objective exposure assessment framework ranging from 2D (GSs areas), and 2.5D (GSs visibility) to 3D (GSs volume) was innovatively developed using spatial analysis, deep learning technology, and unmanned aerial vehicle (UAV) measurement technology. Subjective exposure metrics incorporated GSs visiting frequency, GSs visiting duration, and GSs perceived quality. Our cross-sectional study was based on 820 university students in Nanjing, China. Subjective measures of GSs exposure, physical activity, and health status were obtained through self-reported questionnaires. The Generalized Linear Model (GLM) was used to evaluate the associations between GSs exposure, physical activity, and perceived health. Physical activity and social cohesion were considered as mediators, and path analysis based on Structural Equation Modeling (SEM) was used to disentangle the mechanisms linking GSs exposure to the health status of college students. We found that (1) 2D indicator suggested significant associations with health in the 100m buffer, and the potential underlying mechanisms were: GSs area → Physical activity → Social cohesion → Physical health → Mental health; GSs area → Physical activity → Social cohesion → Mental health. (2) Subjective GSs exposure indicators were more relevant in illustrating exposure-response relationships than objective ones. This study can clarify the complex nexus and mechanisms between campus GSs, physical activity, and health, and provide a practical reference for health-oriented campus GSs planning.

Effects of job demands, job resources, personal resources on night-shift alertness of ICU shift nurses: a cross­sectional survey study based on the job demands-resources model.

BACKGROUND: A positive work environment can enhance nursing safety and patient satisfaction while alleviating nurse stress. Conversely, a poor work environment can harm nurses' physical and mental health and compromise the quality of care, particularly in the high-intensity and shift-based setting of the ICU. OBJECTIVES: Based on the Job demands-resources (JD-R) model, this study examined the effects of job demands and job resources in the work environment, as well as personal resources, on the night-shift alertness of ICU shift nurses. METHODS: This cross-sectional correlational exploratory study, conducted from July to September 2022, recruited 291 ICU shift nurses from a hospital in Beijing, China. The Copenhagen Psychosocial Questionnaire (COPSOQ), the Self-resilience scale, the General Self-Efficacy Scale (GSES), and the Psychomotor Vigilance Task (PVT) were used to subjectively and objectively measure the job demands, job resources, personal resources, and night-shift alertness. SPSS 26.0 and Mplus 8.3 were used to analyze the data and construct the structural equation model. RESULTS: The night-shift reaction time was 251.0 ms (Median), indicating a relatively high level of alertness. Job demands were negatively correlated with both job resources (r=-0.570, P < 0.001) and personal resources (r=-0.462, P < 0.001), while a positive correlation existed between job resources and personal resources (r = 0.554, P < 0.001). The results show that increased job demands can lead to higher levels of nurse strain (ß = 0.955, P < 0.001), whereas job resources were found that it can decrease strain (ß=-0.477, P = 0.047). Adequate job resources can enhance motivation directly (ß = 0.874, P < 0.001), subsequently reducing reaction time (ß=-0.148, P = 0.044) and improving night-shift alertness among ICU shift nurses. CONCLUSION: Enhancing ICU shift nurses' work motivation through bolstering job resources can boost night-shift alertness. However, it is noteworthy that, in this study, neither strain nor individual resources significantly influenced nurses' night-shift alertness. This may be attributed to the complexity of the ICU environment and individual differences. Future research should explore the relationship between these factors and nurses' work alertness.

LncRNA expression signature identified using genome-wide transcriptomic profiling to predict lymph node metastasis in patients with stage T1 and T2 gastric cancer.

BACKGROUND: Lymph node (LN) status is vital to evaluate the curative potential of relatively early gastric cancer (GC; T1-T2) treatment (endoscopic or surgery). Currently, there is a lack of robust and convenient methods to identify LN metastasis before therapeutic decision-making. METHODS: Genome-wide expression profiles of long noncoding RNA (lncRNA) in primary T1 gastric cancer data from The Cancer Genome Atlas (TCGA) was used to identify lncRNA expression signature capable of detecting LN metastasis of GC and establish a 10-lncRNA risk-prediction model based on deep learning. The performance of the lncRNA panel in diagnosing LN metastasis was evaluated both in silico and clinical validation methods. In silico validation was conducted using TCGA and Asian Cancer Research Group (ACRG) datasets. Clinical validation was performed on T1 and T2 patients, and the panel's efficacy was compared with that of traditional tumor markers and computed tomography (CT) scans. RESULTS: Profiling of genome-wide RNA expression identified a panel of lncRNA to predict LN metastasis in T1 stage gastric cancer (AUC = 0.961). A 10-lncRNA risk-prediction model was then constructed, which was validated successfully in T1 and T2 datasets (TCGA, AUC = 0.852; ACRG, AUC = 0.834). Thereafter, the clinical performance of the lncRNA panel was validated in clinical cohorts (T1, AUC = 0.812; T2, AUC = 0.805; T1 + T2, AUC = 0.764). Notably, the panel demonstrated significantly better performance compared with CT and traditional tumor markers. CONCLUSIONS: The novel 10-lncRNA could diagnose LN metastasis robustly in relatively early gastric cancer (T1-T2), with promising clinical potential.

NIR diagnostic imaging of triple-negative breast cancer and its lymph node metastasis for high-efficiency hypoxia-activated multimodal therapy.

BACKGROUND: Triple-negative breast cancer (TNBC) possesses special biological behavior and clinicopathological characteristics, which is highly invasive and propensity to metastasize to lymph nodes, leading to a worse prognosis than other types of breast cancer. Thus, the development of an effective therapeutic method is significant to improve the survival rate of TNBC patients. RESULTS: In this work, a liposome-based theranostic nanosystem (ILA@Lip) was successfully prepared by simultaneously encapsulating IR 780 as the photosensitizer and lenvatinib as an anti-angiogenic agent, together with banoxantrone (AQ4N) molecule as the hypoxia-activated prodrug. The ILA@Lip can be applied for the near-infrared (NIR) fluorescence diagnostic imaging of TNBC and its lymph node metastasis for multimodal therapy. Lenvatinib in ILA@Lip can inhibit angiogenesis by cutting oxygen supply, thereby leading to enhanced hypoxia levels. Meanwhile, large amounts of reactive oxygen species (ROS) were produced while IR 780 was irradiated by an 808 nm laser, which also rapidly exhausted oxygen in tumor cells to worsen tumor hypoxia. Through creating an extremely hypoxic in TNBC, the conversion of non-toxic AQ4N to toxic AQ4 was much more efficiency for hypoxia-activated chemotherapy. Cytotoxicity assay of ILA@Lip indicated excellent biocompatibility with normal cells and tissues, but showed high toxicity in hypoxic breast cancer cells. Also, the in vivo tumors treated by the ILA@Lip with laser irradiation were admirably suppressed in both subcutaneous tumor model and orthotopic tumor models. CONCLUSION: Utilizing ILA@Lip is a profound strategy to create an extremely hypoxic tumor microenvironment for higher therapeutic efficacy of hypoxia-activated chemotherapy, which realized collective suppression of tumor growth and has promising potential for clinical translation.

Optogenetic engineered umbilical cord MSC-derived exosomes for remodeling of the immune microenvironment in diabetic wounds and the promotion of tissue repair.

BACKGROUND: Angiogenesis and tissue repair in chronic non-healing diabetic wounds remain critical clinical problems. Engineered MSC-derived exosomes have significant potential for the promotion of wound healing. Here, we discuss the effects and mechanisms of eNOS-rich umbilical cord MSC exosomes (UCMSC-exo/eNOS) modified by genetic engineering and optogenetic techniques on diabetic chronic wound repair. METHODS: Umbilical cord mesenchymal stem cells were engineered to express two recombinant proteins. Large amounts of eNOS were loaded into UCMSC-exo using the EXPLOR system under blue light irradiation. The effects of UCMSC-exo/eNOS on the biological functions of fibroblasts and vascular endothelial cells in vitro were evaluated. Full-thickness skin wounds were constructed on the backs of diabetic mice to assess the role of UCMSC-exo/eNOS in vascular neogenesis and the immune microenvironment, and to explore the related molecular mechanisms. RESULTS: eNOS was substantially enriched in UCMSCs-exo by endogenous cellular activities under blue light irradiation. UCMSC-exo/eNOS significantly improved the biological functions of cells after high-glucose treatment and reduced the expression of inflammatory factors and apoptosis induced by oxidative stress. In vivo, UCMSC-exo/eNOS significantly improved the rate of wound closure and enhanced vascular neogenesis and matrix remodeling in diabetic mice. UCMSC-exo/eNOS also improved the inflammatory profile at the wound site and modulated the associated immune microenvironment, thus significantly promoting tissue repair. CONCLUSION: This study provides a novel therapeutic strategy based on engineered stem cell-derived exosomes for the promotion of angiogenesis and tissue repair in chronic diabetic wounds.

A Vectorial Current Density Imaging Method Based on Magnetic Gradient Tensor.

Magnetic current imaging is deemed an emerging powerful technique for visualizing electrical currents in electronic devices. However, the existing magnetic-field-based Fourier Transform back-evolution method is limited by its mono-function of imaging the magnitude of current density in devices under test, and subject to background noise distortion. Here, we developed a novel vectorial current density imaging method based on the detection of the magnetic field gradient generated by current carrying conductors. A closed form solution of current density inversion was analytically derived and numerically verified. Experiments were conducted by scanning tri-axial fluxgate sensor over different shapes of electrical wires. The results show that a current density resolution of 24.15 mA/mm2, probe-to-sample separation of 2 mm, and spatial resolution of 0.69 mm were achieved over a maximum scanning area of 300 mm × 300 mm. Such a method is verified to be capable of simultaneously imaging both magnitude and directions of current density, which is a promising technique for in situ noninvasive inspection for the power electronic and semiconductor industry.

Interactive effects of ambient air pollution and sunshine duration on the risk of intrahepatic cholestasis of pregnancy.

INTRODUCTION: While the associations among ambient pollutants and various pregnancy complications are well documented, the effect of ambient pollutants on intrahepatic cholestasis of pregnancy (ICP) has not been examined. This study aimed to explore the effects of ambient pollutants and sunshine duration on ICP. METHODS: The study enrolled 169,971 pregnant women who delivered between 2015 and 2020 in two hospitals. The associations between ICP and exposure to ambient pollutants and sunshine duration, averaged throughout different periods (including the 3 months before conception, 1st trimester and 2nd trimester), were estimated using a generalized linear model. The interaction effects of ambient pollutants and sunshine duration on ICP were estimated. RESULTS: The fitted curves for ICP incidence were similar to the temporal trends of PM2.5, PM10, SO2, CO and NO2 but not that of O3. The risk of ICP was significantly elevated following a 10-µg/m3 increase in PM2.5 (aOR [adjusted odds ratio] = 1.057, 95% CI [confidence interval]: 1.017-1.099) and PM10 (aOR = 1.043, 95% CI: 1.013-1.074) and a 1-h decrease in sunshine duration (aOR = 1.039, 95% CI: 1.011-1.068) during the 3 months before conception. In the second trimester, a 1-µg/m3 increase in the concentration of SO2 was associated with an increased risk of ICP (aOR = 1.011, 95% CI: 1.001-1.021). Increased concentrations of PM2.5 and PM10 had interactive effects with reduced sunshine duration during the 3 months before conception on increasing the risk of ICP. CONCLUSIONS: Exposure to PM2.5 and PM10 during the 3 months before conception and exposure to SO2 in the second trimester were associated with an increased ICP risk. Reduced sunshine duration had an interactive effect with increased concentrations of PM2.5 and PM10 during the 3 months before conception on the occurrence of ICP.

Association between prenatal exposure to ambient air pollutants and postpartum depressive symptoms: A multi-city cohort study.

BACKGROUND: Women are vulnerable to depression during postpartum period. While several studies have shown associations between ambient air pollution exposure and depression in general population, there was few studies focused on the effect of various air pollutants on postpartum depression (PPD). OBJECTIVE: This study is designed to explore the association between prenatal exposure to air pollutants and PPD, and to reveal the potential vulnerable exposure time point. METHODS: The study enrolled 10,209 pregnant women who delivered between October 2019 and February 2021 in 5 participating hospitals from 3 cities in China. Edinburgh Postnatal Depression Scale (EPDS) was administered at 6 weeks postpartum to identify PPD symptoms. Associations between PPD symptoms and exposure levels in PM2.5, PM10, SO2, CO, NO2, and O3 averaged over the whole pregnancy and each trimester were estimated using logistic regression models after adjusting for potential confounding factors. Distributed lag models (DLMs) were used to determine the relevant associations in each gestational week. RESULTS: The risk for developing PPD symptoms was significant following a 10 µg/m3 increase in PM10 (aOR = 1.47, 95%CI:1.36-1.59), NO2 (aOR = 1.63, 95%CI:1.44-1.85), and 0.1 mg/m3 increase in CO (aOR = 2.31, 95%CI: 1.99-2.69) during the whole pregnancy. Similar results were also found in exposure during each trimester of pregnancy. Besides, SO2 exposure during the second trimester was a major risk factor for developing PPD symptoms (aOR = 1.10, 95%CI:1.03-1.18). Consistent effects were also observed in DLMs, except for PM2.5 and O3, which showed no significant sensitive windows throughout pregnancy period. CONCLUSION: Exposure to PM10, CO, NO2, and SO2 in pregnancy is associated with increased risks of developing depression at 6 weeks postpartum. Our findings reveal the importance of air pollution control for preventing maternal mental health disorders among the public.

PHF21A expression as a biomarker of hepatocellular carcinoma progression and prognosis.

Previous studies have shown that PHF21A is associated with the initiation and progression of various tumors. However, its role in hepatocellular carcinoma (HCC) is still unclear. Thus, this study aimed to determine the expression and clinical significance of PHF21A in HCC. PHF21A expression in 201 liver cancer samples and 129 adjacent normal tissues was detected by immunohistochemistry. The correlation between PHF21A expression and the clinicopathological features and prognosis of HCC was verified in 70 other liver tissue microarray samples. The relationship between PHF21A expression and HCC immune cell infiltration was explored via the Tumor Immune Estimation Resource (TIMER). The mechanism underlying the effect of PHF21A on HCC progression was analyzed by gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis. Immunohistochemical staining showed that PHF21A expression in HCC tissue was significantly lower than that in adjacent nontumor liver tissue and was associated with patient sex, tumor size, metastasis, and Edmondson grade (p<0.05). Kaplan-Meier analysis demonstrated that low PHF21A expression was associated with a poor prognosis, and Cox regression analysis showed that PHF21A was an independent predictor of prognosis. TIMER analysis showed that PHF21A is positively correlated with tumor immune cell infiltration levels. Functional annotation indicated that PHF21A is involved in important pathways, including transcriptional deregulation pathways in cancer. Finally, in vitro experiments confirmed the low expression of PHF21A in HCC cells. PHF21A affects the progression and prognosis of HCC, suggesting that PHF21A may play an important role in monitoring and preventing the development of HCC.

Association between abnormal body mass index and pregnancy outcomes in patients following frozen embryo transfer: a systematic review and meta-analysis.

BACKGROUND: There has been increasing interest in the relationship between body mass index(BMI) and pregnancy outcomes, especially in women undergoing frozen embryo transfer(FET). Several observational studies have been published, but so far with conflicting results. METHODS: A systematic review and meta-analysis was conducted according to PRISMA guidelines. Pubmed, Embase, Cochrane Library, Clinicaltrails.gov and Web of Science databases were searched based on established search strategy from inception through January 2021. RESULTS: Twelve studies were eligible. In women following FET, high BMI (BMI ≥ 23 kg/m2) was associated with an impaired live birth rate (LBR, OR: 0.89, 95% CI: 0.82-0.96, P = 0.002), but wasn't associated with the implantation rate or the clinical pregnancy rate. Subgroup analysis revealed higher LBR for women didn't complicated by polycystic ovary syndrome (PCOS, OR: 0.96, 95% CI: 0.85-1.08, P = 0.46) and women with blastocyst transferred (OR: 0.89, 95% CI: 0.68-1.16, P = 0.40). LBR did not differ between the low BMI group (BMI < 18.5 kg/m2) and the normal weight group. CONCLUSIONS: Our study showed that high BMI in women is negatively associated with LBR in FET cycles, whereas low BMI isn't. The results of subgroup analysis implied a need for women with a high BMI to get individualized weight management and treatment. Further evidence is still required to optimize preconception health and develop Nutritional and exercise guidelines.

Perinatal outcomes of neonates born from different endometrial preparation protocols after frozen embryo transfer: a retrospective cohort study.

BACKGROUND: Previous studies have focused on pregnancy outcomes after frozen embryo transfer (FET) performed using different endometrial preparation protocols. Few studies have evaluated the effect of endometrial preparation on pregnancy-related complications. This study was designed to explore the association between different endometrial preparation protocols and adverse obstetric and perinatal complications after FET. METHODS: We retrospectively included all FET cycles (n = 12,950) in our hospital between 2010 and 2017, and categorized them into three groups, natural cycles (NC), hormone replacement therapy (HRT) and ovarian stimulation (OS) protocols. Pregnancy-related complications and subsequent neonatal outcomes were compared among groups. RESULTS: Among all 12,950 FET cycles, the live birth rate was slightly lower for HRT cycles than for NC (HRT vs. NC: 28.15% vs. 31.16%, p < 0.001). The pregnancy loss rate was significantly higher in OS or HRT cycles than in NC (HRT vs. NC: 17.14% vs. 10.89%, p < 0.001; OS vs. NC: 16.44% vs. 10.89%, p = 0.001). Among 3864 women with live birth, preparing the endometrium using OS or HRT protocols increased the risk of preeclampsia, and intrahepatic cholestasis of pregnancy (ICP) in both singleton and multiple deliveries. Additionally, OS and HRT protocols increased the risk of low birth weight (LBW) and small for gestational age (SGA) in both singletons and multiples after FET. CONCLUSION: Compared with HRT or OS protocols, preparing the endometrium with NC was associated with the decreased risk of pregnancy-related complications, as well as the decreased risk of LBW and SGA after FET.

PRAP: Pan Resistome analysis pipeline.

BACKGROUND: Antibiotic resistance genes (ARGs) can spread among pathogens via horizontal gene transfer, resulting in imparities in their distribution even within the same species. Therefore, a pan-genome approach to analyzing resistomes is necessary for thoroughly characterizing patterns of ARGs distribution within particular pathogen populations. Software tools are readily available for either ARGs identification or pan-genome analysis, but few exist to combine the two functions. RESULTS: We developed Pan Resistome Analysis Pipeline (PRAP) for the rapid identification of antibiotic resistance genes from various formats of whole genome sequences based on the CARD or ResFinder databases. Detailed annotations were used to analyze pan-resistome features and characterize distributions of ARGs. The contribution of different alleles to antibiotic resistance was predicted by a random forest classifier. Results of analysis were presented in browsable files along with a variety of visualization options. We demonstrated the performance of PRAP by analyzing the genomes of 26 Salmonella enterica isolates from Shanghai, China. CONCLUSIONS: PRAP was effective for identifying ARGs and visualizing pan-resistome features, therefore facilitating pan-genomic investigation of ARGs. This tool has the ability to further excavate potential relationships between antibiotic resistance genes and their phenotypic traits.

Quantitative and sensitive detection of lipase using a liquid crystal microfiber biosensor based on the whispering-gallery mode.

In this study, we demonstrate a quantitative and sensitive strategy for monitoring the lipase concentration using a liquid crystal (LC) microfiber biosensor based on the whispering-gallery mode (WGM). An LC 4-cyano-4'-pentylbiphenyl (5CB) microfiber was doped with glycerol trioleate (GT) and used as both an optical microcavity and a sensing element. The self-assembled monolayer of a surfactant was formed at the LC/aqueous solution interface by the enzymatic reaction between lipase and GT, which resulted in the reorientation of the 5CB molecules from a planar to a homeotropic configuration. Interestingly, the structural change of the 5CB microfiber can be sensitively captured by the WGMs and quantitatively characterized by the wavelength shift. With this method, lipase with concentrations as low as 0.01 µg mL-1 in aqueous solution can be detected within 200 seconds, which is lower than the optimal value based on LC materials reported so far. In addition, our biodetection system is highly selective for lipase. We believe that the proposed biosensor has high potential for the detection of biochemical molecules.

[Drug-target protein interaction prediction based on AdaBoost algorithm].

The drug-target protein interaction prediction can be used for the discovery of new drug effects. Recent studies often focus on the prediction of an independent matrix filling algorithm, which apply a single algorithm to predict the drug-target protein interaction. The single-model matrix-filling algorithms have low accuracy, so it is difficult to obtain satisfactory results in the prediction of drug-target protein interaction. AdaBoost algorithm is a strong multiple classifier combination framework, which is proved by the past researches in classification applications. The drug-target interaction prediction is a matrix filling problem. Therefore, we need to adjust the matrix filling problem to a classification problem before predicting the interaction among drug-target protein. We make full use of the AdaBoost algorithm framework to integrate several weak classifiers to improve performance and make accurate prediction of drug-target protein interaction. Experimental results based on the metric datasets show that our algorithm outperforms the other state-of-the-art approaches and classical methods in accuracy. Our algorithm can overcome the limitations of the single algorithm based on machine learning method, exploit the hidden factors better and improve the accuracy of prediction effectively.

[Design of Portable Spirometer Based on Internet of Things of Medicine].

A kind of portable device for detecting common lung function parameters is mentioned in this paper. Using the singlechip microcomputer as the master control block to collect and process the data from high-accuracy gas pressure sensor, through the way of parametric calibration and linear interpolation to test and calculate the Forced Vital Capacity (FVC), Peak Expiratory Flow (PEF), Forced Expiratory Volume in one second (FEV1), and FEV1/FVC. Meanwhile, the detected parameters can be uploaded to the intelligent mobile terminal through the wireless transmission module. The device is able to show expiratory volume-time curve and the final parameters clearly, the error of measurement is less than 5%. In addition, that device is small and convenient, not only is good for clinical application, but also can be used for family in a house.

Assembly, Morphology, Diffusivity, and Indentation of Hydrogel-Supported Lipid Bilayers.

Recognizing the limitations of solid-supported lipid bilayers to reproduce the behavior of cell membranes, including bendability, transmembrane protein inclusion, and virus entry, this study describes a novel biomimetic system for cell membranes with the potential to overcome these and other limitations. The developed strategy utilizes a hydrogel with tunable mechanical behavior that resembles those of living cells as the soft support for the phospholipid bilayer, while a polyelectrolyte multilayer film serves as an intermediate layer to facilitate the self-assembly of the lipid bilayer on the soft cushion. Quartz crystal microbalance studies show that, upon coming into contact with the polyelectrolyte film, vesicles fuse and rupture to yield a robust lipid bilayer. Fluorescence recovery after photobleaching confirms the formation of a membrane, while atomic force microscopy shows a low adhesion between the indenting probe and the bilayer. More importantly, in comparison to the solid-supported lipid bilayer, the response of this biomimetic system to nanoindentation demonstrates its increased mechanical stability and bendability when assembled on a soft cushion. Hence, the developed hydrogel-supported lipid bilayers can mimic biomechanical properties of cell membranes, which will enable scientists to study and to understand biophysicochemical interactions between cell membranes and extracellular entities.

The m6A demethylase FTO targets POLQ to promote ccRCC cell proliferation and genome stability maintenance.

BACKGROUND AND AIM: As the first identified m6A demethylase, FTO has been implicated in the progression of various cancers. However, the specific mechanism of FTO in clear cell renal cell carcinoma (ccRCC) remains incompletely understood. In this study, we aimed to explore the potential molecular mechanisms influencing the progression of ccRCC. METHODS: We initially assessed the expression of FTO in tumor and adjacent tissues using TCGA database, RT-qPCR, and Western blot. We then conducted CCK-8, cell cycle analysis, and colony formation assay to investigate the impact of FTO on ccRCC cell proliferation. MeRIP-seq and RNA-seq were employed to identify potential downstream targets of FTO in ccRCC, and these findings were further validated through dual-luciferase reporter assays and MeRIP-qPCR. Then, DNA damage and cell death were assessed separately through gammaH2AX immunofluorescence detection and the LIVE/DEAD Fixable Dead Cell Stain assay, respectively. Subsequently, we identified downstream pathways influenced by FTO's regulation of POLQ through TCGA database analysis and GSEA enrichment analysis. Validation was carried out through Western blot. RESULTS: FTO is highly expressed in ccRCC tissues and cell lines. Furthermore, ROC curve demonstrates that FTO contributes to the diagnosis of ccRCC. FTO modulates m6A modification, consequently influencing the expression of POLQ, thus facilitating cell proliferation and maintaining genome stability in ccRCC. CONCLUSION: FTO could potentially serve as a diagnostic marker for ccRCC. FTO promotes the progression of ccRCC by regulating m6A modification, making the inhibition of FTO a potential novel therapeutic strategy in ccRCC.