The influence of modified Qing E Formula on the differential expression of serum exosomal miRNAs in postmenopausal osteoporosis patients.

Objective: Although guidelines support the efficacy of Modified Qing' E Formula (MQEF) in treating postmenopausal osteoporosis (PMOP), its underlying mechanisms remain incompletely understood. This retrospective investigation aims to elucidate MQEF's impact on serum exosomal miRNA expression in postmenopausal osteoporosis patients and to explore potential therapeutic mechanisms. Methods: Following ethical approval and registration, postmenopausal osteoporosis patients aged 50-85 years, meeting the diagnostic criteria were randomly selected and received MQEF decoction supplementary therapy. Serum samples were collected pre- and post-treatment, followed by isolation and sequencing of exosomal miRNAs. Differential miRNAs in serum exosomes were identified, and bioinformatics analysis was conducted to discern the principal exosomal miRNAs involved in MQEF's effects on PMOP and the associated signaling pathways. Results: Eighteen clinical blood samples were collected. A total of 282,185 target genes were detected across the three groups. 306 miRNAs exhibited altered expression in serum exosomes of PMOP patients, while MQEF intervention resulted in changes in 328 miRNAs. GO enrichment analysis revealed the immune and endocrine systems was pertained. KEGG enrichment analysis indicated associations between PMOP occurrence and MQEF treatment with cytokine interactions, oxidative phosphorylation, and the renin-angiotensin system. Intersectional analysis identified 17 miRNAs, including 2 consistent trends. miR-3188 as a potentially pivotal miRNA implicated in both PMOP occurrence and MQEF treatment. Conclusion: This study constitutes the first randomized, retrospective clinical exploration confirming that MQEF demonstrates regulatory influence over exosomal miRNA expression in PMOP patients' serum, its impact likely involves modulation of the immune and endocrine systems, as well as the renin-angiotensin system.

Neural stimulation and modulation with sub-cellular precision by optomechanical bio-dart.

Neural stimulation and modulation at high spatial resolution are crucial for mediating neuronal signaling and plasticity, aiding in a better understanding of neuronal dysfunction and neurodegenerative diseases. However, developing a biocompatible and precisely controllable technique for accurate and effective stimulation and modulation of neurons at the subcellular level is highly challenging. Here, we report an optomechanical method for neural stimulation and modulation with subcellular precision using optically controlled bio-darts. The bio-dart is obtained from the tip of sunflower pollen grain and can generate transient pressure on the cell membrane with submicrometer spatial resolution when propelled by optical scattering force controlled with an optical fiber probe, which results in precision neural stimulation via precisely activation of membrane mechanosensitive ion channel. Importantly, controllable modulation of a single neuronal cell, even down to subcellular neuronal structures such as dendrites, axons, and soma, can be achieved. This bio-dart can also serve as a drug delivery tool for multifunctional neural stimulation and modulation. Remarkably, our optomechanical bio-darts can also be used for in vivo neural stimulation in larval zebrafish. This strategy provides a novel approach for neural stimulation and modulation with sub-cellular precision, paving the way for high-precision neuronal plasticity and neuromodulation.

3D Printing of Metals with sub-10 µm Resolution.

The ability to manufacture 3D metallic architectures with microscale resolution is greatly pursued because of their diverse applications in microelectromechanical systems (MEMS) including microelectronics, mechanical metamaterials, and biomedical devices. However, the well-developed photolithography and emerging metal additive manufacturing technologies have limited abilities in manufacturing micro-scaled metallic structures with freeform 3D geometries. Here, for the first time, the high-fidelity fabrication of arbitrary metallic motifs with sub-10 µm resolution is achieved by employing an embedded-writing embedded-sintering (EWES) process. A paraffin wax-based supporting matrix with high thermal stability is developed, which permits the printed silver nanoparticle ink to be pre-sintered at 175 °C to form metallic green bodies. Via carefully regulating the matrix components, the printing resolution is tuned down to ≈7 µm. The green bodies are then embedded in a supporting salt bath and further sintered to realize freeform 3D silver motifs with great structure fidelity. 3D printing of various micro-scaled silver architectures is demonstrated such as micro-spring arrays, BCC lattices, horn antenna, and rotatable windmills. This method can be extended to the high-fidelity 3D printing of other metals and metal oxides which require high-temperature sintering, providing the pathways toward the design and fabrication of 3D MEMS with complex geometries and functions.

Opto-Thermal-Tension Mediated Precision Large-Scale Particle Manipulation and Flexible Patterning.

Large-scale particle manipulation with single-particle precision and further flexible patterning into functional structures is of huge potentials in many fields including bio-optoelectronic sensing, colloidal lithography, and wearable devices. However, it is very challenging for the precision manipulation and flexible patterning of particles on complicated curved and functional substrates. In this work, opto-thermal-tension (OTT) mediated precision large-scale particle manipulation and flexible patterning based on soap film are reported. Flexible manipulation and subsequent patterning of particles with single-particle resolution is realized by optothermal regulated surface tension on soap films. Reconfigurable patterning of particle structures with different shapes as well as large-scale ordered structures (up to 2000 particles) with particle sizes spanning two orders of magnitude (0.5-20 µm) is realized using this OTT mediation method. Importantly, due to the high flexibility of soap films, the patterned large-scale particle structures can be non-destructively transferred to curved and rough substrates, including rough iron pipe surface, leaf and skin surface. This OTT mediated method provides a new method for precision large-scale particle manipulation and flexible patterning with high versatility on complicated functional substrates, with great potentials for optoelectronic and biophotonic sensing and wearable device design on different curved and rough functional substrates.

SCPLPA: An miRNA-disease association prediction model based on spatial consistency projection and label propagation algorithm.

Identifying the association between miRNA and diseases is helpful for disease prevention, diagnosis and treatment. It is of great significance to use computational methods to predict potential human miRNA disease associations. Considering the shortcomings of existing computational methods, such as low prediction accuracy and weak generalization, we propose a new method called SCPLPA to predict miRNA-disease associations. First, a heterogeneous disease similarity network was constructed using the disease semantic similarity network and the disease Gaussian interaction spectrum kernel similarity network, while a heterogeneous miRNA similarity network was constructed using the miRNA functional similarity network and the miRNA Gaussian interaction spectrum kernel similarity network. Then, the estimated miRNA-disease association scores were evaluated by integrating the outcomes obtained by implementing label propagation algorithms in the heterogeneous disease similarity network and the heterogeneous miRNA similarity network. Finally, the spatial consistency projection algorithm of the network was used to extract miRNA disease association features to predict unverified associations between miRNA and diseases. SCPLPA was compared with four classical methods (MDHGI, NSEMDA, RFMDA and SNMFMDA), and the results of multiple evaluation metrics showed that SCPLPA exhibited the most outstanding predictive performance. Case studies have shown that SCPLPA can effectively identify miRNAs associated with colon neoplasms and kidney neoplasms. In summary, our proposed SCPLPA algorithm is easy to implement and can effectively predict miRNA disease associations, making it a reliable auxiliary tool for biomedical research.

Association between risk of preterm birth and long-term and short-term exposure to ambient carbon monoxide during pregnancy in chongqing, China: a study from 2016-2020.

BACKGROUND: Preterm birth (PTB) is an important predictor of perinatal morbidity and mortality. Previous researches have reported a correlation between air pollution and an increased risk of preterm birth. However, the specific relationship between short-term and long-term exposure to carbon monoxide (CO) and preterm birth remains less explored. METHODS: A population-based study was conducted among 515,498 pregnant women in Chongqing, China, to assess short-term and long-term effects of CO on preterm and very preterm births. Generalized additive models (GAM) were applied to evaluate short-term effects, and exposure-response correlation curves were plotted after adjusting for confounding factors. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using COX proportional hazard models to estimate the long-term effect. RESULTS: The daily incidence of preterm and very preterm birth was 5.99% and 0.41%, respectively. A positive association between a 100 µg/m³ increase in CO and PTB was observed at lag 0-3 days and 12-21 days, with a maximum relative risk (RR) of 1.021(95%CI: 1.001-1.043). The exposure-response curves (lag 0 day) revealed a rapid increase in PTB due to CO. Regarding long-term exposure, positive associations were found between a 100 µg/m3 CO increase for each trimester(Model 2 for trimester 1: HR = 1.054, 95%CI: 1.048-1.060; Model 2 for trimester 2: HR = 1.066, 95%CI: 1.060-1.073; Model 2 for trimester 3: HR = 1.007, 95%CI: 1.001-1.013; Model 2 for entire pregnancy: HR = 1.080, 95%CI: 1.073-1.088) and higher HRs of very preterm birth. Multiplicative interactions between air pollution and CO on the risk of preterm and very preterm birth were detected (P- interaction<0.05). CONCLUSIONS: Our findings suggest that short-term exposure to low levels of CO may have protective effects against preterm birth, while long-term exposure to low concentrations of CO may reduce the risk of both preterm and very preterm birth. Moreover, our study indicated that very preterm birth is more susceptible to the influence of long-term exposure to CO during pregnancy, with acute CO exposure exhibiting a greater impact on preterm birth. It is imperative for pregnant women to minimize exposure to ambient air pollutants.

Light-controlled soft bio-microrobot.

Micro/nanorobots hold exciting prospects for biomedical and even clinical applications due to their small size and high controllability. However, it is still a big challenge to maneuver micro/nanorobots into narrow spaces with high deformability and adaptability to perform complicated biomedical tasks. Here, we report a light-controlled soft bio-microrobots (called "Ebot") based on Euglena gracilis that are capable of performing multiple tasks in narrow microenvironments including intestinal mucosa with high controllability, deformability and adaptability. The motion of the Ebot can be precisely navigated via light-controlled polygonal flagellum beating. Moreover, the Ebot shows highly controlled deformability with different light illumination duration, which allows it to pass through narrow and curved microchannels with high adaptability. With these features, Ebots are able to execute multiple tasks, such as targeted drug delivery, selective removal of diseased cells in intestinal mucosa, as well as photodynamic therapy. This light-controlled Ebot provides a new bio-microrobotic tool, with many new possibilities for biomedical task execution in narrow and complicated spaces where conventional tools are difficult to access due to the lack of deformability and bio-adaptability.

Profiling DNA Cargos in Single Extracellular Vesicles via Hydrogel-Based Droplet Digital Multiple Displacement Amplification.

Due to the substantial heterogeneity among extracellular vesicle (EV) subpopulations, single-EV analysis has the potential to elucidate the mechanisms behind EV biogenesis and shed light on the myriad functions, leading to the development of novel diagnostics and therapeutics. While many studies have been devoted to reveal between-EV variations in surface proteins and RNAs, DNA cargos (EV-DNA) have received little attention. Here, we report a hydrogel-based droplet digital multiple displacement amplification approach for the comprehensive analysis of EV-DNA at the single-EV level. Single EVs are dispersed in thousands of hydrogel droplets and lysed for DNA amplification and identification. The droplet microfluidics strategy empowers the assay with single-molecule sensitivity and capability for absolute quantification of DNA-containing EVs. In particular, our findings indicate that 5-40% EVs are associated with DNA, depending on the cell of origin. Large EVs exhibit a higher proportion of DNA-containing EVs and a more substantial presence of intraluminal DNA, compared to small EVs. These DNA-containing EVs carry multiple DNA fragments on average. Furthermore, both double-stranded DNA and single-stranded DNA were able to be detected at the single-EV level. Utilizing this method, the abundance, distribution, and biophysical properties of EV-DNA in various EV populations are evaluated. The DNA level within EVs provides insight into the status of the originating cells and offers valuable information on the outcomes of anticancer treatments. The utilization of single-EV analysis for EV-DNA holds significant promise for early cancer detection and treatment response monitoring.

Can Moving More and Sitting Less Improve the Academic Engagement of Adolescents?- A Study Based on Junior High School Students in Shanghai, China.

Purpose: The purpose of this study was to examine the relationships between academic engagement and moderate-to-vigorous physical activity (MVPA), muscle-strengthening exercise (MSE) and sedentary behavior (SB) among adolescents, so as to provide evidence from the perspective of exercising for students to learn efficiently, teachers to improve classroom teaching, and schools to improve educational quality. Methods: A questionnaire survey was conducted in 12 junior high schools in Shanghai, China, which were selected by a multi-stage stratified cluster sampling method. Then, with the valid data of 2078 students collected from the survey. A data analysis was performed using SPSS Statistics 26.0. Multiple linear regression models were adopted to analyze the factors affecting adolescent academic engagement and to determine whether MVPA, MSE, and SB play roles in it. Results: (1) The differences in academic engagement depended on the exercise adherence to the recommended amount of MVPA, MSE, and screen-based SB. (2) In terms of the three independent variables of total time, MSE (ß = 0.206) and MVPA (ß = 0.175) showed a significant positive correlation with academic engagement, while SB (ß = -0.155) was negatively correlated with academic engagement. (3) From the linear regression model of eight combination groups divided by the exercise adherence to the recommended amount of MVPA, MSE and SB, the group that met none of the recommendations (ß = -0.235) showed a significant negative effect on academic engagement, while the groups that met any two or all three of the recommendations demonstrated strong positive correlations with academic engagement (P < 0.001). Conclusion: Increasing adolescents' muscle-strengthening exercise and moderate-to-vigorous physical activity and reducing sedentary behavior can effectively promote academic engagement. Therefore, adolescents are suggested to reach the recommended amounts of physical activity, muscle-strengthening exercise, and sedentary behavior so as to improve academic engagement more effectively.

Glycobiology in osteoclast differentiation and function.

Glycans, either alone or in complex with glycan-binding proteins, are essential structures that can regulate cell biology by mediating protein stability or receptor dimerization under physiological and pathological conditions. Certain glycans are ligands for lectins, which are carbohydrate-specific receptors. Bone is a complex tissue that provides mechanical support for muscles and joints, and the regulation of bone mass in mammals is governed by complex interplay between bone-forming cells, called osteoblasts, and bone-resorbing cells, called osteoclasts. Bone erosion occurs when bone resorption notably exceeds bone formation. Osteoclasts may be activated during cancer, leading to a range of symptoms, including bone pain, fracture, and spinal cord compression. Our understanding of the role of protein glycosylation in cells and tissues involved in osteoclastogenesis suggests that glycosylation-based treatments can be used in the management of diseases. The aims of this review are to clarify the process of bone resorption and investigate the signaling pathways mediated by glycosylation and their roles in osteoclast biology. Moreover, we aim to outline how the lessons learned about these approaches are paving the way for future glycobiology-focused therapeutics.

Socioeconomic status may affect association of vegetable intake with risk of ischemic cardio-cerebral vascular disease: a Mendelian randomization study.

Background: Previous studies found that increasing vegetable intake benefits are reduced after adjustment for socioeconomic factors. Using genetic variation as an instrumental variable for vegetable intake and socioeconomic status, we investigated the relationship between vegetable intake and ischemic cardio-cerebral vascular diseases and focused on whether socioeconomic status was a possible confounder. Methods: From three independent genome-wide association studies, we extracted instrumental variables reflecting raw and cooked vegetable intake, which were used to perform Mendelian randomization analysis. To evaluate the effects of socioeconomic factors on vegetable intake, univariate and multivariate Mendelian randomization analyses were performed using single nucleotide polymorphisms representing education attainment and household income reported in the literature. We also performed outlier assessment and a series of sensitivity analyses to confirm the results. Results: Genetically predicted raw and cooked vegetable intake were not associated with any ischemic cardio-cerebral vascular diseases and lipid components after Bonferroni correction. Univariate Mendelian randomized analysis revealed that raw vegetable intake was positively correlated with education attainment (ß = 0.04, p = 0.029) and household income (ß = 0.07, p < 0.001). Multivariate Mendelian randomized model showed a positive correlation between household income and raw vegetable intake (ß = 0.06, p = 0.004). Socioeconomic status was closely associated with eating habits and lifestyle related to the risk of cardiovascular diseases. Conclusion: Genetically determined raw and cooked vegetable intake was not associated with significant benefits in terms of ischemic cardio-cerebral vascular diseases while genetically determined socioeconomic status may have an impact on vegetable intake. Socioeconomic status, which was closely associated with other eating habits and lifestyle, may affect the association between vegetable intake and ischemic cardio-cerebral vascular diseases.

Butyrate Improves Porcine Endometrial Epithelial Cell Receptivity via Enhancing Acetylation of Histone H3K9.

SCOPE: Uterine receptivity is a major restriction of embryo implantation and survival, and the endometrial luminal epithelium serves as the transient gateway for uterine receptivity and embryo implantation. Butyrate is reported to promote the success of embryo implantation, but the effects and mechanism of butyrate on uterine receptivity are still unknown. METHODS AND RESULTS: Porcine endometrial epithelial cells (PEECs) are used as a model, and the cellular receptivity changes, metabolism, and gene expression profiles influenced by butyrate are analyzed. The study finds that butyrate improves receptive changes in PEECs, including inhibiting proliferation, exhibiting more pinocytosis on the cell surface, and increasing adhesiveness to porcine trophoblast cells. In addition, butyrate increases prostaglandin synthesis and markedly impacts purine metabolism, pyrimidine metabolism, and the FoxO signaling pathway. siRNA to inhibit the expression of FoxO1 and chromatin immunoprecipitation-sequencing (ChIP-seq) of H3K9ac are used to demonstrate that the H3K9ac/FoxO1/PCNA pathway can contribute to the effects of cell proliferation inhibition and uterine receptivity improvement induced by butyrate. CONCLUSION: The findings reveal that butyrate improves endometrial epithelial cell receptivity by enhancing the acetylation of histone H3K9, which shows nutritional regulation and therapeutic potential for poor uterine receptivity and difficulty in embryo implantation.

Acoustic Atomization-Induced Pumping Based on a Vibrating Sharp-Tip Capillary.

Pumping is an essential component in many microfluidic applications. Developing simple, small-footprint, and flexible pumping methods is of great importance to achieve truly lab-on-a-chip systems. Here, we report a novel acoustic pump based on the atomization effect induced by a vibrating sharp-tip capillary. As the liquid is atomized by the vibrating capillary, negative pressure is generated to drive the movement of fluid without the need to fabricate special microstructures or use special channel materials. We studied the influence of the frequency, input power, internal diameter (ID) of the capillary tip, and liquid viscosity on the pumping flow rate. By adjusting the ID of the capillary from 30 µm to 80 µm and the power input from 1 Vpp to 5 Vpp, a flow rate range of 3 to 520 µL/min can be achieved. We also demonstrated the simultaneous operation of two pumps to generate parallel flow with a tunable flow rate ratio. Finally, the capability of performing complex pumping sequences was demonstrated by performing a bead-based ELISA in a 3D-printed microdevice.

KATZNCP: a miRNA-disease association prediction model integrating KATZ algorithm and network consistency projection.

BACKGROUND: Clinical studies have shown that miRNAs are closely related to human health. The study of potential associations between miRNAs and diseases will contribute to a profound understanding of the mechanism of disease development, as well as human disease prevention and treatment. MiRNA-disease associations predicted by computational methods are the best complement to biological experiments. RESULTS: In this research, a federated computational model KATZNCP was proposed on the basis of the KATZ algorithm and network consistency projection to infer the potential miRNA-disease associations. In KATZNCP, a heterogeneous network was initially constructed by integrating the known miRNA-disease association, integrated miRNA similarities, and integrated disease similarities; then, the KATZ algorithm was implemented in the heterogeneous network to obtain the estimated miRNA-disease prediction scores. Finally, the precise scores were obtained by the network consistency projection method as the final prediction results. KATZNCP achieved the reliable predictive performance in leave-one-out cross-validation (LOOCV) with an AUC value of 0.9325, which was better than the state-of-the-art comparable algorithms. Furthermore, case studies of lung neoplasms and esophageal neoplasms demonstrated the excellent predictive performance of KATZNCP. CONCLUSION: A new computational model KATZNCP was proposed for predicting potential miRNA-drug associations based on KATZ and network consistency projections, which can effectively predict the potential miRNA-disease interactions. Therefore, KATZNCP can be used to provide guidance for future experiments.

Corrigendum to "Point-of-care testing for lysine concentration in swine serum via blue-emissive carbon dots entrapped microfluidic chip" [Animal Nutrition 12 (2023) 236-244].

[This corrects the article DOI: 10.1016/j.aninu.2022.08.017.].

Relationship between the Depth of Acetabuloplasty and Outcomes of Hip Arthroscopy in Patients with Global Pincer Femoroacetabular Impingement: Study with a Minimum Follow-Up Period of 2 Years.

OBJECTIVE: There has been no definite consensus on the ideal depth of acetabuloplasty, especially in cases of global pincer femoroacetabular impingement (FAI). This study aims to determine whether the depth of acetabuloplasty influences postoperative outcomes in cases of global pincer FAI. METHODS: Data were retrospectively collected from patients with global pincer FAI who underwent hip arthroscopy with a minimum follow-up period of 2 years from May 2014 to December 2018. Patients with global pincer FAI were subdivided into low or high resection depth groups based on whether the intraoperative acetabular rim was resected by more than 3 mm. Radiographic measurements; arthroscopic procedures; preoperative and postoperative PROs were recorded. Achievement of MCID and PASS was compared for the VAS, mHHS, HOS-ADL, and iHOT-12. A paired Student t-test was used to evaluate the significance of preoperative and postoperative PROs and two-tailed unpaired Student t-test was used to compare demographic data and PROs between different groups. MCID and PASS were evaluated using the chi-square test or the Fisher's exact test. RESULTS: A total of 41 hips with global pincer FAI (15 and 26 patients in low or high resection depth groups, respectively) were included in this study. Both groups showed significant postoperative improvements in the scores of all PROs (p < 0.001). Compared to the low resection depth group, the high resection depth group had a lower degree of improvement through hip arthroscopy, which manifested as lower postoperative mHHS scores (94.29 vs. 85.08, p = 0.006), higher VAS scores (0.93 vs. 2.54, p = 0.002), and lower improvements in VAS (-5.00 vs. -3.35, p = 0.028), HOS-ADL (34.99 vs. 23.90, p = 0.017) and iHOT-12 (39.89 vs. 29.27, p = 0.036). Patients in high resection depth group were less likely to achieve the MCID for the VAS score compared to low resection depth group in significant (73.3 vs. 26.9%, p = 0.004). CONCLUSIONS: For patients with global pincer, the outcomes in high resection depth group were slightly worse than the the low resection depth group. It is indicated that excessive resection of the acetabular rim during the procedure should be avoided.

LRP1B mutation is associated with tumor immune microenvironment and progression-free survival in lung adenocarcinoma treated with immune checkpoint inhibitors.

Background: Only a fraction of lung adenocarcinoma (LUAD) patients are eligible for immunotherapy. The identification of biomarkers for immunotherapy is crucial to improve patient outcomes. This study aims to systemically analyze LRP1B mutation and its association with the tumor immune microenvironment (TIME) and immunotherapy. Methods: A cohort of immune checkpoint inhibitors (ICIs)-treated LUAD patients was analyzed to assess the association of LRP1B mutation with immunotherapy prognosis. Another cohort of LUAD patients with genetic and transcriptomic data was also obtained from The Cancer Genome Atlas (TCGA). By investigating the ICIs and the TCGA-LUAD cohorts, we compared the differences in mutation profiles, immunogenicity, TIME, and DNA damage repair (DDR) mutations between the LRP1B-mutated and LRP1B wild-type groups. Additionally, we performed multiplex immunohistochemistry (mIHC) to validate the differences in the tumor microenvironment. Results: Our results revealed that LRP1B mutation is associated with multiple immune-related pathways. Analysis of TIME indicated that LUAD patients with LRP1B mutation expressed significant levels of genes involved in antigen presentation, cytotoxicity, chemokines, and pro-inflammatory mediators, whereas a few immune checkpoint genes were highly expressed in the LRP1B-mutated group as well. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) analysis indicated that LRP1B-mutated LUAD patients had higher infiltration of active immune cells. Multiplex IHC analysis showed that LRP1B-mutated LUAD patients had elevated programmed death ligand-1 (PD-L1) expression and immune cell infiltration. Patients with LRP1B mutation had higher tumor mutation burden, neoantigens, as well as more mutated genes in the DDR-related pathways. Finally, LRP1B-mutated LUAD patients showed a significant prolongation of progression-free survival (PFS) in the ICIs cohort and could be effectively predicted by our constructed nomogram. Conclusions: Our study suggests that LRP1B mutation is associated with higher immune cell infiltration and elevated immune gene expression in TIME and potentially serves as a prognostic biomarker for LUAD patients treated with ICIs.

Wake-Riding Effect-Inspired Opto-Hydrodynamic Diatombot for Non-Invasive Trapping and Removal of Nano-Biothreats.

Contamination of nano-biothreats, such as viruses, mycoplasmas, and pathogenic bacteria, is widespread in cell cultures and greatly threatens many cell-based bio-analysis and biomanufacturing. However, non-invasive trapping and removal of such biothreats during cell culturing, particularly many precious cells, is of great challenge. Here, inspired by the wake-riding effect, a biocompatible opto-hydrodynamic diatombot (OHD) based on optical trapping navigated rotational diatom (Phaeodactylum tricornutum Bohlin) for non-invasive trapping and removal of nano-biothreats is reported. Combining the opto-hydrodynamic effect and optical trapping, this rotational OHD enables the trapping of bio-targets down to sub-100 nm. Different nano-biothreats, such as adenoviruses, pathogenic bacteria, and mycoplasmas, are first demonstrated to be effectively trapped and removed by the OHD, without affecting culturing cells including precious cells such as hippocampal neurons. The removal efficiency is greatly enhanced via reconfigurable OHD array construction. Importantly, these OHDs show remarkable antibacterial capability, and further facilitate targeted gene delivery. This OHD serves as a smart micro-robotic platform for effective trapping and active removal of nano-biothreats in bio-microenvironments, and especially for cell culturing of many precious cells, with great promises for benefiting cell-based bio-analysis and biomanufacturing.

Three tyrosine kinase inhibitors cause cardiotoxicity by inducing endoplasmic reticulum stress and inflammation in cardiomyocytes.

BACKGROUND: Tyrosine kinase inhibitors (TKIs) are anti-cancer therapeutics often prescribed for long-term treatment. Many of these treatments cause cardiotoxicity with limited cure. We aim to clarify molecular mechanisms of TKI-induced cardiotoxicity so as to find potential targets for treating the adverse cardiac complications. METHODS: Eight TKIs with different levels of cardiotoxicity reported are selected. Phenotypic and transcriptomic responses of human cardiomyocytes to TKIs at varying doses and times are profiled and analyzed. Stress responses and signaling pathways that modulate cardiotoxicity induced by three TKIs are validated in cardiomyocytes and rat hearts. RESULTS: Toxicity rank of the eight TKIs determined by measuring their effects on cell viability, contractility, and respiration is largely consistent with that derived from database or literature, indicating that human cardiomyocytes are a good cellular model for studying cardiotoxicity. When transcriptomes are measured for selected TKI treatments with different levels of toxicity in human cardiomyocytes, the data are classified into 7 clusters with mainly single-drug clusters. Drug-specific effects on the transcriptome dominate over dose-, time- or toxicity-dependent effects. Two clusters with three TKIs (afatinib, ponatinib, and sorafenib) have the top enriched pathway as the endoplasmic reticulum stress (ERS). All three TKIs induce ERS in rat primary cardiomyocytes and ponatinib activates the IRE1α-XBP1s axis downstream of ERS in the hearts of rats underwent a 7-day course of drug treatment. To look for potential triggers of ERS, we find that the three TKIs induce transient reactive oxygen species followed by lipid peroxidation. Inhibiting either PERK or IRE1α downstream of ERS blocks TKI-induced cardiac damages, represented by the induction of cardiac fetal and pro-inflammatory genes without causing more cell death. CONCLUSIONS: Our data contain rich information about phenotypic and transcriptional responses of human cardiomyocytes to eight TKIs, uncovering potential molecular mechanisms in modulating cardiotoxicity. ER stress is activated by multiple TKIs and leads to cardiotoxicity through promoting expression of pro-inflammatory factors and cardiac fetal genes. ER stress-induced inflammation is a promising therapeutic target to mitigate ponatinib- and sorafenib-induced cardiotoxicity.

A pharmacokinetic model based on the SSA-1DCNN-Attention method.

To solve the problem of the lack of representativeness of the training set and the poor prediction accuracy due to the limited number of training samples when the machine learning method is used for the classification and prediction of pharmacokinetic indicators, this paper proposes a 1DCNN-Attention concentration prediction model optimized by the sparrow search algorithm (SSA). First, the SMOTE method is used to expand the small sample experimental data to make the data diverse and representative. Then a one-dimensional convolutional neural network (1DCNN) model is established, and the attention mechanism is introduced to calculate the weight of each variable for dividing the importance of each pharmacokinetic indicator by the output drug concentration. The SSA algorithm was used to optimize the parameters in the model to improve the prediction accuracy after data expansion. Taking the pharmacokinetic model of phenobarbital (PHB) combined with Cynanchum otophyllum saponins to treat epilepsy as an example, the concentration changes of PHB were predicted and the effectiveness of the method was verified. The results show that the proposed model has a better prediction effect than other methods.