ABSTRACT
Predicting the strength of promoters and guiding their directed evolution is a crucial task in synthetic biology. This approach significantly reduces the experimental costs in conventional promoter engineering. Previous studies employing machine learning or deep learning methods have shown some success in this task, but their outcomes were not satisfactory enough, primarily due to the neglect of evolutionary information. In this paper, we introduce the Chaos-Attention net for Promoter Evolution (CAPE) to address the limitations of existing methods. We comprehensively extract evolutionary information within promoters using merged chaos game representation and process the overall information with modified DenseNet and Transformer structures. Our model achieves state-of-the-art results on two kinds of distinct tasks related to prokaryotic promoter strength prediction. The incorporation of evolutionary information enhances the model's accuracy, with transfer learning further extending its adaptability. Furthermore, experimental results confirm CAPE's efficacy in simulating in silico directed evolution of promoters, marking a significant advancement in predictive modeling for prokaryotic promoter strength. Our paper also presents a user-friendly website for the practical implementation of in silico directed evolution on promoters. The source code implemented in this study and the instructions on accessing the website can be found in our GitHub repository https://github.com/BobYHY/CAPE.
Subject(s)
Deep Learning , Promoter Regions, Genetic , Algorithms , Evolution, Molecular , Computer Simulation , Nonlinear Dynamics , Computational Biology/methodsABSTRACT
Chromatin spatial organization plays a crucial role in gene regulation. Recently developed and prospering multiplexed DNA FISH technologies enable direct visualization of chromatin conformation in the nucleus. However, incomplete data caused by limited detection efficiency can substantially complicate and impair downstream analysis. Here, we present SnapFISH-IMPUTE that imputes missing values in multiplexed DNA FISH data. Analysis on multiple published datasets shows that the proposed method preserves the distribution of pairwise distances between imaging loci, and the imputed chromatin conformations are indistinguishable from the observed conformations. Additionally, imputation greatly improves downstream analyses such as identifying enhancer-promoter loops and clustering cells into distinct cell types. SnapFISH-IMPUTE is freely available at https://github.com/hyuyu104/SnapFISH-IMPUTE .
Subject(s)
Chromatin , DNA , In Situ Hybridization, Fluorescence , In Situ Hybridization, Fluorescence/methods , Chromatin/genetics , DNA/genetics , Humans , Animals , SoftwareABSTRACT
BACKGROUND: The rupture of intracranial aneurysms (IAs) would result in subarachnoid hemorrhage with high mortality and disability. Predicting the risk of IAs rupture remains a challenge. METHODS: This paper proposed an effective method for classifying IAs rupture status by integrating a PointNet-based model and machine learning algorithms. First, medical image segmentation and reconstruction algorithms were applied to 3D Digital Subtraction Angiography (DSA) imaging data to construct three-dimensional IAs geometric models. Geometrical parameters of IAs were then acquired using Geomagic, followed by the computation of hemodynamic clouds and hemodynamic parameters using Computational Fluid Dynamics (CFD). A PointNet-based model was developed to extract different dimensional hemodynamic cloud features. Finally, five types of machine learning algorithms were applied on geometrical parameters, hemodynamic parameters, and hemodynamic cloud features to classify and recognize IAs rupture status. The classification performance of different dimensional hemodynamic cloud features was also compared. RESULTS: The 16-, 32-, 64-, and 1024-dimensional hemodynamic cloud features were extracted with the PointNet-based model, respectively, and the four types of cloud features in combination with the geometrical parameters and hemodynamic parameters were respectively applied to classify the rupture status of IAs. The best classification outcomes were achieved in the case of 16-dimensional hemodynamic cloud features, the accuracy of XGBoost, CatBoost, SVM, LightGBM, and LR algorithms was 0.887, 0.857, 0.854, 0.857, and 0.908, respectively, and the AUCs were 0.917, 0.934, 0.946, 0.920, and 0.944. In contrast, when only utilizing geometrical parameters and hemodynamic parameters, the accuracies were 0.836, 0.816, 0.826, 0.832, and 0.885, respectively, with AUC values of 0.908, 0.922, 0.930, 0.884, and 0.921. CONCLUSION: In this paper, classification models for IAs rupture status were constructed by integrating a PointNet-based model and machine learning algorithms. Experiments demonstrated that hemodynamic cloud features had a certain contribution weight to the classification of IAs rupture status. When 16-dimensional hemodynamic cloud features were added to the morphological and hemodynamic features, the models achieved the highest classification accuracies and AUCs. Our models and algorithms would provide valuable insights for the clinical diagnosis and treatment of IAs.
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The highly variable SARS-CoV-2 virus responsible for the COVID-19 pandemic frequently undergoes mutations, leading to the emergence of new variants that present novel threats to public health. The determination of these variants often relies on manual definition based on local sequence characteristics, resulting in delays in their detection relative to their actual emergence. In this study, we propose an algorithm for the automatic identification of novel variants. By leveraging the optimal natural metric for viruses based on an alignment-free perspective to measure distances between sequences, we devise a hypothesis testing framework to determine whether a given viral sequence belongs to a novel variant. Our method demonstrates high accuracy, achieving nearly 100% precision in identifying new variants of SARS-CoV-2 and HIV-1 as well as in detecting novel genera in Orthocoronavirinae. This approach holds promise for timely surveillance and management of emerging viral threats in the field of public health.
Subject(s)
Algorithms , COVID-19 , HIV-1 , SARS-CoV-2 , SARS-CoV-2/genetics , Humans , COVID-19/virology , COVID-19/epidemiology , HIV-1/genetics , MutationABSTRACT
ETHNOPHARMACOLOGICAL RELEVANCE: The plants in the genus Erigeron are known to exhibit antiviral activities, including those against the respiratory syncytial virus (RSV). In traditional medicine Erigeron annuus (L.) Pers (EA) has been used in the treatment of pulmonary diseases and acute infectious hepatitis. AIM OF THIS STUDY: The aim of this study is to determine the optimum extraction method to produce the most potent anti-RSV extract, elucidate its mode and mechanisms of antiviral activity in both in vitro and in vivo models, and identify the chemical structures of the bioactive compounds. MATERIALS AND METHODS: The whole plant of EA was extracted with ethyl acetate, methanol, ethanol, water, aqueous methanol (60, 80% and 100%) and aqueous ethanol (50, 75% and 95%) using maceration, reflux, and ultrasound-assisted extraction methods. The antiviral activities of the extracts were determined in vitro. The in vitro antiviral activities of the extracts were determined using Hep-2 cells. Four in vitro experiments were performed to determine the mode of antiviral activity of the most active extract, ethyl acetate fraction (EAE) of Erigeron annuus whole plant extract prepared by refluxing with 50% ethanol, by examining its ability to inactivate the virus directly, inhibit viral adsorption and penetration, inhibit viral replication and preventive effect. The effect of temperature and duration of treatment on these modes of action was also determined. The antiviral activity of the EAE was also assessed in vivo in a mouse model. The lung index, viral load, and lung tissue histology were measured. qRT-PCR and ELISA studies were performed to determine the expression of key genes (TLR-3 and TLR-4) and proteins (IL-2, IFN-γ, and TNF-α) related to RSV infection. The most active antiviral compound was isolated using chromatography techniques, and its chemical structure was identified through electrospray triple quadrupole mass spectroscopy and nuclear magnetic resonance spectroscopy. RESULTS: The EAE was the most active on RSV. In vitro experiments showed that the antiviral activity of EAE is via direct inactivation, inhibition of entry, and inhibition of the proliferation of the virus. In vivo experiments showed that the EAE effectively inhibited the proliferation of RSV in the lungs and alleviated the lung tissue lesions in RSV-infected mice. The antiviral activity of the EAE is mediated by downregulating the expression of TLR3 and TLR4 in the lung, upregulating the expression of IL-2 and IFN-γ, and downregulating the expression of TNF-α. Apigenin 7-O-methylglucuronide was found to be a major bioactive compound in EAE. CONCLUSIONS: The results of this study confirmed the antiviral activity of EA by inactivating, inhibiting the entry, and inhibiting the proliferation of RSV. The activity is mediated by regulating the immunity and inflammatory mediators. Apigenin 7-O-methylglucuronide is the bioactive compound present in EA.
Subject(s)
Antiviral Agents , Erigeron , Plant Extracts , Respiratory Syncytial Virus Infections , Antiviral Agents/pharmacology , Antiviral Agents/isolation & purification , Antiviral Agents/chemistry , Animals , Plant Extracts/pharmacology , Plant Extracts/chemistry , Humans , Erigeron/chemistry , Mice , Respiratory Syncytial Virus Infections/drug therapy , Respiratory Syncytial Virus Infections/virology , Mice, Inbred BALB C , Female , Virus Replication/drug effects , Cytokines/metabolismABSTRACT
Noble gases with inert chemical properties have rich bonding modes under high pressure. Interestingly, Xe and Xe form covalent bonds, originating from the theoretical simulation of the pressure-induced decomposition of XeF2, which has yet to be experimentally confirmed. Moreover, the structural phase transition and metallization of XeF2 under high pressure have always been controversial. Therefore, we conducted extensive experiments using a laser-heated diamond anvil cell technique to investigate the above issues of XeF2. We propose that XeF2 undergoes a structural phase transition and decomposition above 84.1 GPa after laser heating, and the decomposed product Xe2F contains Xe-Xe covalent bonds. Neither the pressure nor temperature alone could bring about these changes in XeF2. With our UV-vis absorption experiment, I4/mmm-XeF2 was metalized at 159 GPa. This work confirms the existence of Xe-Xe covalent bonds and provides insights into the controversy surrounding XeF2, enriching the research on noble gas chemistry under high pressure.
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Understanding the structural similarity between genomes is pivotal in classification and phylogenetic analysis. As the number of known genomes rockets, alignment-free methods have gained considerable attention. Among these methods, the natural vector method stands out as it represents sequences as vectors using statistical moments, enabling effective clustering based on families in biological taxonomy. However, determining an optimal metric that combines different elements in natural vectors remains challenging due to the absence of a rigorous theoretical framework for weighting different k-mers and orders. In this study, we address this challenge by transforming the determination of optimal weights into an optimization problem and resolving it through gradient-based techniques. Our experimental results underscore the substantial improvement in classification accuracy achieved by employing these optimal weights, reaching an impressive 92.73% on the testing set, surpassing other alignment-free methods. On one hand, our method offers an outstanding metric for virus classification, and on the other hand, it provides valuable insights into feature integration within alignment-free methods.
ABSTRACT
This Letter presents the fabrication and characterization of a chip-scale GaN optical device for measuring glycerol viscosity. The monolithically integrated GaN chip with a size of 1 × 1â mm2 comprises a light-emitting diode (LED) and a photodiode (PD) on a transparent sapphire substrate. The glycerol droplet applied to the device acts as a medium for coupling light from the LED to the PD. When a mechanical impulse is applied, the droplet undergoes a damped vibration that depends on its viscosity, causing a change in its shape and altering the path of light propagation. The viscosity of the glycerol sample can be determined by obtaining the rate of attenuation of the measured photocurrent signals. The proposed unit offers a fast time response in microseconds and requires only a small sample volume of 5â µl. The developed device is highly suitable for the practical measurement of glycerol viscosity due to its miniaturization, low cost, and ease of operation without the need for external optical components.
ABSTRACT
Influenza viruses present a significant threat to global health. The production of a universal vaccine is considered essential due to the ineffectiveness of current seasonal influenza vaccines against mutant strains. mRNA technology offers new prospects in vaccinology, with various candidates for different infectious diseases currently in development and testing phases. In this study, we encapsulated a universal influenza mRNA vaccine. The vaccine encoded influenza hemagglutinin (HA), nucleoprotein (NP), and three tandem repeats of matrix protein 2 (3M2e). Twice-vaccinated mice exhibited strong humoral and cell-mediated immune responses in vivo. Notably, these immune responses led to a significant reduction in viral load of the lungs in challenged mice, and also conferred protection against future wild-type H1N1, H3N2, or H5N1 influenza virus challenges. Our findings suggest that this mRNA-universal vaccine strategy for influenza virus may be instrumental in mitigating the impact of future influenza pandemics.
Subject(s)
Antibodies, Viral , Hemagglutinin Glycoproteins, Influenza Virus , Influenza A Virus, H3N2 Subtype , Influenza Vaccines , Mice, Inbred BALB C , Orthomyxoviridae Infections , Viral Matrix Proteins , mRNA Vaccines , Animals , Influenza Vaccines/immunology , Influenza Vaccines/administration & dosage , Influenza Vaccines/genetics , Mice , Orthomyxoviridae Infections/prevention & control , Orthomyxoviridae Infections/immunology , Orthomyxoviridae Infections/virology , Antibodies, Viral/immunology , mRNA Vaccines/immunology , Influenza A Virus, H3N2 Subtype/immunology , Influenza A Virus, H3N2 Subtype/genetics , Hemagglutinin Glycoproteins, Influenza Virus/immunology , Hemagglutinin Glycoproteins, Influenza Virus/genetics , Viral Matrix Proteins/immunology , Viral Matrix Proteins/genetics , Female , Influenza A Virus, H1N1 Subtype/immunology , Influenza A Virus, H1N1 Subtype/genetics , Influenza A Virus, H5N1 Subtype/immunology , Influenza A Virus, H5N1 Subtype/genetics , Vaccines, Synthetic/immunology , Vaccines, Synthetic/administration & dosage , Cross Protection/immunology , Viral Load , Lung/virology , Lung/immunology , Humans , Viroporin ProteinsABSTRACT
Combinatorial optimization (CO) has a broad range of applications in various fields, including operations research, computer science, and artificial intelligence. However, many of these problems are classified as nondeterministic polynomial-time (NP)-complete or NP-hard problems, which are known for their computational complexity and cannot be solved in polynomial time on traditional digital computers. To address this challenge, continuous-time Ising machine solvers have been developed, utilizing different physical principles to map CO problems to ground state finding. However, most Ising machine prototypes operate at speeds comparable to digital hardware and rely on binarizing node states, resulting in increased system complexity and further limiting operating speed. To tackle these issues, a novel device-algorithm co-design method is proposed for fast sub-optimal solution finding with low hardware complexity. On the device side, a piezoelectric lithium niobate (LiNbO3) microelectromechanical system (MEMS) oscillator network-based Ising machine without second-harmonic injection locking (SHIL) is devised to solve Max-cut and graph coloring problems. The LiNbO3 oscillator operates at speeds greater than 9 GHz, making it one of the fastest oscillatory Ising machines. System-wise, an innovative grouping method is used that achieves a performance guarantee of 0.878 for Max-cut and 0.658 for graph coloring problems, which is comparable to Ising machines that utilize binarization.
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BACKGROUND: The prevalence of mild cognitive impairment (MCI) is steadily increasing among elderly people with type 2 diabetes (T2DM). This study aimed to create and validate a predictive model based on a nomogram. METHODS: This cross-sectional study collected sociodemographic characteristics, T2DM-related factors, depression, and levels of social support from 530 older adults with T2DM. We used LASSO regression and multifactorial logistic regression to determine the predictors of the model. The performance of the nomogram was evaluated using calibration curves, receiver operating characteristics (ROC), and decision curve analysis (DCA). RESULTS: The nomogram comprised age, smoking, physical activity, social support, depression, living alone, and glycosylated hemoglobin. The AUC for the training and validation sets were 0.914 and 0.859. The DCA showed good clinical applicability. CONCLUSIONS: This predictive nomogram has satisfactory accuracy and discrimination. Therefore, the nomogram can be intuitively and easily used to detect MCI in elderly adults with T2DM.
Subject(s)
Cognitive Dysfunction , Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/complications , Male , Female , Aged , Cross-Sectional Studies , Risk Assessment/methods , Risk Factors , Nomograms , Social Support , Depression , Aged, 80 and overABSTRACT
BACKGROUND: To analyze the effects and pathways of factors such as psychological capital, family functioning, and sources of meaning in life on the level of self-management in elderly patients with chronic diseases and to provide a basis for the development of relevant nursing interventions in the future. METHODS: Convenience sampling was used to select elderly patients with chronic diseases who underwent medical checkups and consultations at three community hospitals in Jinzhou city from March 2023 to October 2023, and the self-designed General Information Questionnaire (GIS), Psychological Capital of the Elderly Scale (PCE), Family Functioning Index Questionnaire (APGAR), Sources of Meaning of Life Scale for Older Adults(SMSE), and Self-Management Behavior of Chronic Patients Scale (SMCS) were used. SPSS 26.0 was used for data entry, one-way analysis, Pearson correlation analysis, and multiple linear regression were used to analyze the data, and Amos 17.0 was used to construct the structural equation model. RESULTS: A total of 355 elderly patients with chronic diseases were included, and their self-management score was 74.75 ± 12.93, which was moderate. The results of the influencing factor analysis showed that the influencing factors of the self-management level of elderly chronic disease patients were age, years of illness, psychological capital, family functioning, and sources of meaning in life (p < 0.05). Path analysis revealed that sources of meaning in life were a partial mediator of the relationship between psychological capital and self-management, with an effect value of 0.166 (95% CI: 0.042,0.391), accounting for 37.6% of the total effect; life meaning was a partial mediator of family functioning and self-management level, with an effect value of 0.231 (95% CI: 0.040,0.452), accounting for 54.0% of the total effect. accounting for 54.0% of the total effect. CONCLUSION: The self-management of elderly patients with chronic diseases is intermediate. Healthcare professionals should actively implement holistic healthcare management measures from the family aspect to help patients understand the meaning of life and improve the level of patients' psychological capital to improve the self-management level of elderly patients with chronic diseases.
Subject(s)
Self-Management , Humans , Aged , Chronic Disease/therapy , Chronic Disease/psychology , Male , Female , Self-Management/methods , Self-Management/psychology , Middle Aged , Aged, 80 and over , Surveys and Questionnaires , China/epidemiology , Self Care/methodsABSTRACT
Chromosomal fusion is a significant form of structural variation, but research into algorithms for its identification has been limited. Most existing methods rely on synteny analysis, which necessitates manual annotations and always involves inefficient sequence alignments. In this paper, we present a novel alignment-free algorithm for chromosomal fusion recognition. Our method transforms the problem into a series of assignment problems using natural vectors and efficiently solves them with the Kuhn-Munkres algorithm. When applied to the human/gorilla and swamp buffalo/river buffalo datasets, our algorithm successfully and efficiently identifies chromosomal fusion events. Notably, our approach offers several advantages, including higher processing speeds by eliminating time-consuming alignments and removing the need for manual annotations. By an alignment-free perspective, our algorithm initially considers entire chromosomes instead of fragments to identify chromosomal structural variations, offering substantial potential to advance research in this field.
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Cell division cycle 42 (CDC42) regulates podocyte apoptosis to take part in the development and progression of diabetic nephropathy (DN), but currently the clinical evidence is limited. The aim of the present study was to investigate the capability of serum CDC42 expression level to estimate the development and progression of DN in patients with diabetes mellitus (DM). Patients with type 2 DM (n=306) were enrolled and divided into normoalbuminuria (n=185), microalbuminuria (n=72) and macroalbuminuria (n=49) groups based on the urinary albumin-to-creatinine ratio. Serum CDC42 was measured in all subjects using enzyme-linked immunosorbent assay. The median (interquartile range) CDC42 in patients with DM was 0.461 (0.314-0.690) ng/ml (range, 0.087-1.728 ng/ml). CDC42 was positively associated with the estimated glomerular filtration rate (P<0.001), but negatively correlated with body mass index, systolic blood pressure, hemoglobin A1c, serum creatine, serum uric acid and C reactive protein (all P<0.050). CDC42 levels were lowest in the macroalbuminuria group, followed by the microalbuminuria group, and were highest in the normoalbuminuria group (P<0.001). CDC42 indicated that it was a favorable estimator for the presence of albuminuria [area under the curve (AUC), 0.792; 95% confidence interval (CI), 0.736-0.848] and macroalbuminuria (AUC, 0.845; 95% CI, 0.775-0.915). By analyses in four different multivariate logistic regression models, increased CDC42 was independently associated with the presence of microalbuminuria (all P<0.001), macroalbuminuria (most P<0.001) and microalbuminuria + macroalbuminuria (all P<0.001). Serum CDC42 level negatively correlated with microalbuminuria and macroalbuminuria in patients with DM, suggesting its ability for estimating the development and progression of DN.
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BACKGROUND: Diabetic patients' oral health concerns are a reality for every diabetic patient in China. The attitudes of diabetic patients toward early identification of oral literacy influence oral literacy in diabetes patients. Diabetes patients' oral health literacy is critical for providing focused education and therapies. However, no instrument exists to measure oral health literacy in Chinese diabetic patients. In this study, the English version of the oral health literacy among people living with diabetes (OHLD) scale was cross-culturally validated to provide a reliable tool for assessing the oral health literacy of diabetic patients in China. OBJECTIVE: The oral literacy among people living with diabetes (OHLD) scale was Chineseized and its reliability and validity tested, and the OHLD scale was revised to test the reliability and validity of the Chinese version of the OHLD scale and to provide a tool for assessing the oral health literacy of diabetic patients in China. METHODS: A modified version of the Brislin translation model was used, cross-cultural adaptation was performed through expert consultation and pre-survey, and expert opinion was used to assess content validity to form the Chinese version of the Oral Health Literacy Scale for Diabetic Patients, which was administered to 420 diabetic patients in two tertiary hospitals in Liaoning Province from March to August 2023. The reliability of the scale was tested. SPSS 25.0 and AMOS 23.0 were used to analyze the data. RESULTS: The Chinese version of the OHLD scale consisted of three dimensions and 10 entries. Structure of the validity analysis: three factors were extracted from the exploratory factors with a cumulative variance contribution of 79.794%; Content validity results:An item's content validity index (I-CVI) was 0.857 to 1 at the entry level, and the content validity index of the scale (S-CVI) was 0.928 at the scale level. The results of the reliability analyses were: the Cronbach's alpha coefficient for the total scale was 0.908; the Cronbach's alpha coefficients for the factors and dimensions were 0.853 to 0.922; the split-half reliability was 0.827; and the test-retest reliability was 0.848. The results of the validation factor analysis showed that (χ2/df) was 1.430, the root mean square of the error of approximation (RMSEA) was 0.045, the comparative fit index (CFI) was 0.989, and the Tucker Lewis index (TLI) was 0.985, which showed that the model had an overall good fit. CONCLUSION: The Chinese version of the OHLD scale has good reliability and validity and can be used as a valid tool for assessing diabetes mellitus patients in China.
Subject(s)
Diabetes Mellitus , Health Literacy , Humans , Reproducibility of Results , Oral Health , Psychometrics , China , Surveys and QuestionnairesABSTRACT
Oncolytic viruses (OVs) are appealing anti-tumor agents. But it is limited in its effectiveness. In this study, we used combination therapy with immune checkpoint inhibitor to enhance the antitumor efficacy of OVs. Using reverse genetics technology, we rescued an oncolytic influenza virus with the name delNS1-GM-CSF from the virus. After identifying the hemagglutination and 50% tissue culture infectivedose (TCID50) of delNS1-GM-CSF, it was purified, and the viral morphology was observed under electron microscopy. Reverse transcription quantitative-polymerase chain reaction (RT-qPCR) was used to identify the level of GM-CSF expression in delNS1-GM-CSF, and the GM-CSF expression level was determined after infection with delNS1-GM-CSF by enzyme linked immunosorbent assay (ELISA). To study the tumor-killing effect of delNS1-GM-CSF, we utilized the hepatocellular carcinoma (HCC) tumor-bearing mouse model. To examine signaling pathways, we performed transcriptome sequencing on mouse tumor tissue and applied western blotting to confirm the results. Changes in T-cell infiltration in HCC tumors following treatment were analyzed using flow cytometry and immunohistochemistry. DelNS1-GM-CSF can target and kill HCCs without damaging normal hepatocytes. DelNS1-GM-CSF combined with programmed cell death 1 blockade therapy enhanced anti-tumor effects and significantly improved mouse survival. Further, we found that combination therapy had an antitumor impact via the janus kinase-signal transducer and activator of transcription (JAK2-STAT3) pathway as well as activated CD4+ and CD8+T cells. Interestingly, combined therapy also showed promising efficacy in distant tumors. DelNS1-GM-CSF is well targeted. Mechanistic investigation revealed that it functions through the JAK2-STAT3 pathway. Combination immunotherapies expected to be a novel strategy for HCC immunotherapy.
Subject(s)
Carcinoma, Hepatocellular , Influenza, Human , Liver Neoplasms , Oncolytic Virotherapy , Oncolytic Viruses , Mice , Animals , Humans , Oncolytic Viruses/genetics , Carcinoma, Hepatocellular/genetics , Carcinoma, Hepatocellular/therapy , Granulocyte-Macrophage Colony-Stimulating Factor/genetics , Liver Neoplasms/genetics , Liver Neoplasms/therapy , Immunotherapy/methods , Apoptosis , Cell Line, Tumor , Oncolytic Virotherapy/methodsABSTRACT
The piezoelectric thin film composed of single-crystal lithium niobate (LiNbO3) exhibits a remarkably high electromechanical coupling coefficient and minimal intrinsic losses, making it an optimal material for fabricating bulk acoustic wave resonators. However, contemporary first-order antisymmetric (A1) Lamb mode resonators based on LiNbO3 thin films face specific challenges, such as inadequate mechanical stability, limited power capacity, and the presence of multiple spurious modes, which restrict their applicability in a broader context. In this paper, we present an innovative design for A1 Lamb mode resonators that incorporates a support-pillar structure. Integration of support pillars enables the dissipation of spurious wave energy to the substrate, effectively mitigating unwanted spurious modes. Additionally, this novel approach involves anchoring the piezoelectric thin film to a supportive framework, consequently enhancing mechanical stability while simultaneously improving the heat dissipation capabilities of the core.
ABSTRACT
Thermoelectric devices (TEDs) show great potential for waste heat energy recycling and sensing. However, existing TEDs cannot be self-adapted to the complex quadratic surface, leading to significant heat loss and restricting their working scenario. Here, surface-conformable origami-TEDs (o-TEGs) are developed through programmable crease-designed origami substrates and the screen-printing TE legs. Compared with "π" structured TEDs, the origami design (with heat conductive materials) changed the heat-transferring direction of the laminated TE legs, resulting in an enhancement in enlarging ΔT/THot and Vout by 5.02 and 3.51 times. Four o-TEDs with different creases designs are fabricated to verify the heat recycling ability on plane and central quadratic surfaces. Demonstrating a high Vout density (up to 0.98 -2 at ΔT of 50 K) and good surface conformability, o-TEDs are further used in thermal touch panels attached to multiple surfaces, allowing information to be wirelessly transferred on a remote display via finger-writing.
ABSTRACT
Chromatin spatial organization plays a crucial role in gene regulation. Recently developed and prospering multiplexed DNA FISH technologies enable direct visualization of chromatin conformation in nucleus. However, incomplete data caused by limited detection efficiency can substantially complicate and impair downstream analysis. Here, we present SnapFISH-IMPUTE that imputes missing values in multiplexed DNA FISH data. Analysis on multiple published datasets shows that the proposed method preserves the distribution of pairwise distances between imaging loci, and the imputed chromatin conformations are indistinguishable from the observed conformations. Additionally, imputation greatly improves downstream analyses such as identifying enhancer-promoter loops and clustering cells into distinct cell types. SnapFISH-IMPUTE is freely available at https://github.com/hyuyu104/SnapFISH-IMPUTE.
ABSTRACT
Background: Oncolytic virus (OV) therapy has emerged as a promising novel form of immunotherapy. Moreover, an increasing number of studies have shown that the therapeutic efficacy of OV can be further improved by arming OVs with immune-stimulating molecules. Methods: In this study, we used reverse genetics to produce a novel influenza A virus, termed IAV-OX40L, which contained the immune-stimulating molecule OX40L gene in the influenza virus nonstructural (NS1) protein gene. The oncolytic effect of IAV-OX40L was explored on hepatocellular carcinoma (HCC)HCC cells in vitro and in vivo. Results: Hemagglutination titers of the IAV-OX40L virus were stably 27-28 in specific-pathogen-free chicken embryos. The morphology and size distribution of IAV-OX40L are similar to those of the wild-type influenza. Expression of OX40L protein was confirmed by Western blot and immunofluorescence. MTS assays showed that the cytotoxicity of IAV-OX40L was higher in HCC cells (HepG2 and Huh7) than in normal liver cells (MIHA) in a time- and dose-dependent manner in vitro. We found that intratumoral injection of IAV-OX40L reduced tumor growth and increased the survival rate of mice compared with PR8-treated controls in vivo. In addition, the pathological results showed that IAV-OX40L selectively destroyed tumor tissues without harming liver and lung tissues. CD4+ and CD8+ T cells of the IAV-OX40L group were significantly increased in the splenic lymphocytes of mice. Further validation confirmed that IAV-OX40L enhanced the immune response mainly by activating Th1-dominant immune cells, releasing interferon-γ and interleukin-2. Conclusion: Taken together, our findings demonstrate the novel chimeric influenza OV could provide a potential therapeutic strategy for combating HCC and improve the effectiveness of virotherapy for cancer therapy.