CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis.

Objective: We aimed to evaluate the diagnostic effectiveness of computed tomography (CT)-based radiomics for predicting lymph node metastasis (LNM) in patients diagnosed with esophageal cancer (EC). Methods: The present study conducted a comprehensive search by accessing the following databases: PubMed, Embase, Cochrane Library, and Web of Science, with the aim of identifying relevant studies published until July 10th, 2023. The diagnostic accuracy was summarized using the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC). The researchers utilized Spearman's correlation coefficient for assessing the threshold effect, besides performing meta-regression and subgroup analysis for the exploration of possible heterogeneity sources. The quality assessment was conducted using the Quality Assessment of Diagnostic Accuracy Studies-2 and the Radiomics Quality Score (RQS). Results: The meta-analysis included six studies conducted from 2018 to 2022, with 483 patients enrolled and LNM rates ranging from 27.2% to 59.4%. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC, along with their corresponding 95% CI, were 0.73 (0.67, 0.79), 0.76 (0.69, 0.83), 3.1 (2.3, 4.2), 0.35 (0.28, 0.44), 9 (6, 14), and 0.78 (0.74, 0.81), respectively. The results demonstrated the absence of significant heterogeneity in sensitivity, while significant heterogeneity was observed in specificity; no threshold effect was detected. The observed heterogeneity in the specificity was attributed to the sample size and CT-scan phases (P < 0.05). The included studies exhibited suboptimal quality, with RQS ranging from 14 to 16 out of 36. However, most of the enrolled studies exhibited a low-risk bias and minimal concerns relating to applicability. Conclusion: The present meta-analysis indicated that CT-based radiomics demonstrated a favorable diagnostic performance in predicting LNM in EC. Nevertheless, additional high-quality, large-scale, and multicenter trials are warranted to corroborate these findings. Systematic Review Registration: Open Science Framework platform at https://osf.io/5zcnd.

The impacts of knowledge and attitude on behavior of antibiotic use for the common cold among the public and identifying the critical behavioral stage: based on an expanding KAP model.

BACKGROUND: This study aims to explore the impacts of knowledge and attitude on the behavior of antibiotic use during the treatment of the common cold based on the expanding KAP model, and then identify the critical behavioral stage. METHODS: A cross-sectional study was conducted on 815 public from 21 community health centers (CHCs) in Chongqing, China. Based on the expanding KAP model, a self-administered questionnaire was designed to measure knowledge, attitude, multi-stage behavior, and perceived threat, in which multi-stage behavior was divided into pre-use antibiotic behavior, during-use antibiotic behavior, and post-use antibiotic behavior. A structural equation model was used to examine the model fit and the direct, indirect, mediating effects, and moderating effect of the variables. RESULTS: The expanding KAP showed good model fit indices with χ²/df = 0.537, RMSEA = 0.033, CFI = 0.973, GFI = 0.971, NFI = 0.934, TLI = 0.979. Knowledge had a positive effect on attitude (ß = 0.503, p < 0.05), pre-use antibiotic behavior (ß = 0.348, p < 0.05), during-use antibiotic behavior (ß = 0.461, p < 0.001), and post-use antibiotic behavior (ß = 0.547, p < 0.001). Attitude had a positive effect on during-use antibiotic behavior (ß = 0.296, p < 0.001), and post-use antibiotic behavior (ß = 0.747, p < 0.001). The mediating effect of attitude was positive among knowledge, during-use antibiotic behavior (ß = 0.149, p < 0.05), and post-use antibiotic behavior (ß = 0.376, p < 0.001). Perceived threat also had a positive moderating effect between knowledge and post-use antibiotic behavior (ß = 0.021, p < 0.001). CONCLUSIONS: Knowledge, attitude and perceived threat had different effects on different stages of antibiotic behavior. The critical behavioral stage prioritized the post-use antibiotic behavior and during-use antibiotic behavior over pre-use antibiotic behavior.

Decision-making process of breastfeeding behavior in mothers with gestational diabetes mellitus based on health belief model.

BACKGROUND: Gestational diabetes mellitus (GDM) threatens GDM mothers and their offspring's health and breastfeeding is one of the most effective ways to decrease the risk. However, the prevalence of breastfeeding among GDM mothers is far from optimal and how GDM mothers develop their feeding behavior is still unclear. Thus, this study aimed to explore the formation of GDM mothers' breastfeeding behaviors based on the health belief model (HBM). METHODS: A questionnaire survey was conducted on 324 GDM mothers who have given birth within 6 months from January 1 to February 6, 2022. According to HBM, GDM mothers' knowledge, the perceived threat from GDM, the perceived value of breastfeeding, self-efficacy, social support and GDM mothers' breastfeeding behavior were measured. Exclusive breastfeeding (EBF) was defined as an infant who received only breast milk in the past 24 h before the survey. Structural equation modeling (SEM) was applied to explore how GDM mothers form their breastfeeding behaviors based on HBM. RESULTS: The prevalence of EBF among GDM mothers was 33.95%. GDM mothers had limited knowledge of GDM (average 63.14% correct answer to 7 questions), especially poor on the long-term effect of GDM (39.81%) and protective effect of breastfeeding (34.57%-45.99%). Although GDM mothers showed high perceived benefits (Mean: 3.35, SD: 0.46), high self-efficacy (Mean: 3.43, SD: 0.97) and high level of social support for breastfeeding (Mean: 3.74, SD: 0.74), the various barriers (Mean: 2.20, SD: 0.47) hindered their success in EBF. The SEM results showed that a higher level of social support and more self-efficacy of breastfeeding resulted in a higher likelihood of EBF, while the higher level of knowledge of GDM, perceived higher barriers and benefits of breastfeeding and higher susceptibility to GDM consequences led to less EBF. CONCLUSION: To promote EBF, physicians' education, emphasizing the protective effect of breastfeeding and how to correct breastfeeding, is highly recommended. In addition, social support for GDM mothers is also important to reduce their barriers to breastfeeding and help enhance self-efficacy in breastfeeding.

The public's antibiotic use behavioural patterns and their determinants for upper respiratory tract infections: a latent class analysis based on consumer behaviour model in China.

Background: The irrational use of antibiotics among the public is a major contributor to antimicrobial resistance (AMR), which is a serious global threat. Prior studies have demonstrated that there are different behavioural patterns regarding antibiotic use among the public, and targeted interventions for subgroups with different behavioural patterns may be more effective. Thus, this study aimed to identify the public's behavioural patterns of antibiotic use for upper respiratory tract infections (URTIs) and their influencing factors. Methods: A cross-sectional survey was conducted among the general population in Chongqing, China. Consumer decision-making (Consumer Behaviour Model, CBM) was used to assess the public's behaviours regarding antibiotic use, including need recognition, information searching, alternative evaluation, obtaining antibiotics, antibiotic consumption, and postuse evaluation. Furthermore, a latent class analysis was used to identify the underlying behavioural patterns among the public. The identified behavioural patterns of antibiotic use were further linked with individuals' capacity, opportunity, and motivation factors of antibiotic use based on a multinominal logistic regression to explore possible determinants. Results: A total of 815 respondents were enrolled in the study. The public's irrational use of antibiotics was prevalent, including antibiotic self-medication (39.63%), nonprescription antibiotic purchasing (59.02%), and early stopping of antibiotic prescriptions (76.56%). Participants had inadequate knowledge of antibiotics (Mean = 2.33, SD = 1.71), reported high availability to antibiotics (Mean = 7.13, SD = 2.41), held strong belief in antibiotic effectiveness (Mean = 10.29, SD = 2.71), and demonstrated a high perceived threat of AMR (Mean = 12.30, SD = 3.20). Four behavioural patterns regarding antibiotic use for URTIs were identified, namely, "antibiotic self-medicators" (n = 165, 20.25%), "formal health care seekers" (n = 216, 26.50%), "various treatment users" (n = 198, 24.20%), and "self-medication without antibiotics" (n = 236, 28.96%). Individuals' self-efficacy of antibiotic use, belief in antibiotic effectiveness, awareness of antibiotic side effects, perceived antibiotic availability, social influence, and demographics (age, education, medical insurance, and having a medical background) were significantly associated with the public's different behavioural patterns of antibiotic use for URTIs. Conclusion: This study calls for collaborative efforts among the public, physicians, policy makers, and the implementation of precise and multifaceted interventions to effectively reduce irrational use of antibiotics in the public. Such interventions include identifying subgroups within the public to provide more targeted education about antibiotics and the management of URTIs, reinforcing the regulation of antibiotic dispensing, and improving physicians' rational antibiotic prescriptions.

The vicious cycle of the public's irrational use of antibiotics for upper respiratory tract infections: A mixed methods systematic review.

Background: The public's irrational use of antibiotics for upper respiratory tract infections (URTIs) is prevalent worldwide. This study aims to synthesize evidence on how people use antibiotics to treat URTIs, its prevalence and determinants. Methods: A mixed methods systematic review was conducted using a convergent segregated approach. Relevant studies were searched from PubMed, Cochrane Library, Embase, and Web of Science. A qualitative analysis was initiated, exploring the public's antibiotic use experience for URTIS based on the Consumer Behavior Model (CBM). This was followed by a quantitative synthesis, tapping into the prevalence and predictors of public behavior in antibiotic usage for URTIs. The segregated syntheses complemented each other and were further integrated. Results: A total of 86 studies were included: 48 quantitative, 30 qualitative, eight mixed methods studies. The included studies were conducted in Europe (n = 29), Asia (n = 27) and North America (n = 21), assessing the behaviors of patients (n = 46), their parents or caregivers (n = 31), or both (n = 9). Eleven themes emerged covering the six CBM stages: need recognition, information searching, alternative evaluation, antibiotic obtaining, antibiotic consumption, and post-consumption evaluation. The six stages reinforce each other, forming a vicious cycle. The high prevalence of the public's irrational use of antibiotics for URTIs is evident despite the high heterogeneity of the studies (ranging from 0.0 to 92.7%). The perceived seriousness of illness and misbelief in antibiotics were identified consistently across the studies as the major motivation driving the public's irrational use of antibiotics for URTIs. However, individual capacity (e.g., knowledge) and opportunity (e.g., contextual restriction) in reducing antibiotic use have mixed effect. Conclusion: Systemic interventions concerning both supply and demand sides are warranted. The public needs to be educated about the appropriate management of URTIs and health care providers need to re-shape public attitudes toward antibiotic use for URTIs through communication and prescribing practices. Systematic review registration: https://www.crd.york.ac.uk/prospero, identifier: CRD42021266407.

How breastfeeding behavior develops in women with gestational diabetes mellitus: A qualitative study based on health belief model in China.

Background: Gestational diabetes mellitus (GDM) is a condition in which women develop hyperglycemia during pregnancy, and is associated with long-term health burden on both mother and their offspring, such as future type 2 diabetes mellitus (T2DM). Although breastfeeding was expected to mitigate metabolic sequelae for both mothers and their newborns, the prevalence of breastfeeding in GDM mothers are sub-optimal worldwide. Objective: To explore the experience of disease among mothers with GDM and how they develop feeding behaviors. Methods: This study was conducted in three branches of an integrated tertiary hospital in the central area of China. Mothers who were diagnosed with GDM, had no other complications, and gave birth before no more than 6 months were approached based on a purposive sampling. GDM mothers' experience of the disease and breastfeeding were collected via in-depth interviews. A theory-driven thematic analysis based on Health Belief Model (HBM) was applied for data analysis. Inductive reasoning was used to identify emerging themes which were not included in HBM. Results: 16 GDM mothers were included in the current study, with nine using breastfeeding, six mixed feeding and one artificial feeding, respectively. Nine themes were identified, including: 1) GDM diagnosis and severity; 2) information searching and GDM knowledge;3) GDM management; 4) perceived susceptibility of future diabetes;5) perceived severity of future diabetes;6) perceived benefits of breastfeeding;7) perceived barriers of breastfeeding;8) decision making process of feeding and social support. Generally, mothers with GDM lack reliable sources of information, considered the disease as a minor and transient illness during pregnancy, and failed to realize the long-term risk of GDM and the protective effect of breastfeeding to themselves and their babies. They rarely considered GDM in their feeding decision. Instead, the formation of feeding behaviors depends on the balance between the benefits and barriers of breastfeeding as well as the level of social support. Conclusion: To promote breastfeeding, a multi-facet intervention targeted on healthcare providers (HCPs), GDM mothers and their networks was important to help GDM mothers better and correctly understand the disease and breastfeeding, and increase their capacity of breastfeeding.

Intraparticle Double-Scattering-Decoded Sonogenetics for Augmenting Immune Checkpoint Blockade and CAR-T Therapy.

Genetically arming new chimeric antigen receptors (CARs) on T cells is a prevalent method to fulfill CAR-T immunotherapy. However, this approach fails to completely address the poor infiltration, complex immunosuppressive tumor microenvironment (ITM), and insufficient immune cells, which are recognized as the three dominant hurdles to discouraging the trafficking and persistence of CAR-T and immune checkpoint blockade (ICB) immunotherapies against solid tumors. To address the three hurdles, a sonoimmunity-engineered nanoplatform is designed in which a rattle-type-structured carrier enables intraparticle-double-scattering to generate massive reactive oxygen species (ROS) during the sonodynamic process. Abundant ROS accumulation can directly kill tumor cells, release antigens, and activate systematic immune responses for expanding effector T or CAR-T cells, while alleviating ITM via immunosuppressive macrophage polarization and reduction in pro-tumorigenic cytokine secretion. Furthermore, the co-loaded phosphodiesterase-5 inhibitors release nitric oxide (NO) to impel vascular normalization and open the infiltration barrier (IB) for allowing more T cells to enter into the tumor. Systematic experiments demonstrate the feasibility of such intraparticle-double-scattering-decoded sonogenetics in the sonoimmunity-engineered nanoplatforms for expanding effector T or CAR-T cells, thereby promoting their infiltration into tumors and alleviating ITM. These compelling actions lead to excellent CAR-T and ICB immunotherapies against solid tumors with repressed tumor metastasis.

Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks.

PURPOSE: Computed tomography (CT) images can display internal organs of patients and are particularly suitable for preoperative surgical diagnoses. The increasing demands for computer-aided systems in recent years have facilitated the development of many automated algorithms, especially deep convolutional neural networks, to segment organs and tumors or identify diseases from CT images. However, performances of some systems are highly affected by the amount of training data, while the sizes of medical image data sets, especially three-dimensional (3D) data sets, are usually small. This condition limits the application of deep learning. METHODS: In this study, given a practical clinical data set that has 3D CT images of 20 patients with renal carcinoma, we designed a pipeline employing transfer learning to alleviate the detrimental effect of the small sample size. A dual-channel fine segmentation network (FS-Net) was constructed to segment kidney and tumor regions, with 210 publicly available 3D images from a competition employed during the training phase. We also built discriminative classifiers to classify the benign and malignant tumors based on the segmented regions, where both handcrafted and deep features were tested. RESULTS: Our experimental results showed that the Dice values of segmented kidney and tumor regions were 0.9662 and 0.7685, respectively, which were better than those of state-of-the-art methods. The classification model using radiomics features can classify most of the tumors correctly. CONCLUSIONS: The designed FS-Net was demonstrated to be more effective than simply fine-tuning on the practical small size data set given that the model can borrow knowledge from large auxiliary data without diluting the signal in primary data. For the small data set, radiomics features outperformed deep features in the classification of benign and malignant tumors. This work highlights the importance of architecture design in transfer learning, and the proposed pipeline is anticipated to provide a reference and inspiration for small data analysis.

Abundance and Metabolism Disruptions of Intratumoral Microbiota by Chemical and Physical Actions Unfreeze Tumor Treatment Resistance.

Intratumoral or intestinal microbiota correlates with tumorigenesis and progression, and microbiota regulation for reinforcing various anti-tumor approaches is of significant importance, which, however, suffers from no precise regulation method and unclear underlying mechanism. Herein, a microbiome metabolism-engineered phototherapy strategy is established, wherein Nb2 C/Au nanocomposite and the corresponding phototherapy are harnessed to realize "chemical" and "physical" bacterial regulations. Flora analysis and mass spectrometry (MS) and metabonomics combined tests demonstrate that the synergistic microbiota regulations can alter the abundance, diversity of intratumoral microbiome, and disrupt metabolic pathways of microbiome and tumor microenvironment, wherein the differential singling pathways and biosynthetic necessities or metabolites that can affect tumor progression are identified. As well, anti-TNFα is introduced to unite with bacterial regulation to synergistically mitigate bacterial-induced inflammation, which, along with the metabolism disruptions of intratumoral microbiota and tumor microenvironment, unfreezes tumor resistance and harvests significantly-intensified phototherapy-based anti-tumor outcomes against 4T1 and CT26 tumors. The clear underlying principles of microbiome-regulated tumorigenesis and the established microbiome metabolism regulation method provide distinctive insights into tumor therapy, and can be also extended to other gut microbiome-associated lesions interference.

Coping With Diagnostic Uncertainty in Antibiotic Prescribing: A Latent Class Study of Primary Care Physicians in Hubei China.

Background: Misuse of antibiotics is prevalent worldwide and primary care is a major contributor. Although a clear diagnosis is fundamental for rational antibiotic use, primary care physicians often struggle with diagnostic uncertainty. However, we know little about how physicians cope with this situation and its association with antibiotic prescribing. Methods: A total of 583 primary care physicians were surveyed using the Dealing with Uncertainty Questionnaire. Their prescriptions (n = 949,181) over the year 2018 were retrieved retrospectively. Two categories of behavioral patterns of participants were identified based on latent class analyses (high vs. low openness and collaborativeness) in responding to diagnostic uncertainty. Multi-level logistic regression models were established to determine the associations between these behavioral patterns and antibiotic prescribing (overall and broad-spectrum antibiotics) for illness without an indication for antibiotics and those with a conditional indication for antibiotics, respectively, after adjustment for variations of patient (level one) and physician (level two) characteristics. Results: Most physicians reported open communications with their patients (80.96%), collected further information (85.08%), and referred patients to specialists (68.95%) in dealing with diagnostic uncertainly. More than half (56.95%) sought help from colleagues. Less than 20% acted on intuition or adopted a "wait and see" strategy. About 40% participants (n = 238) were classified into the group of low openness and collaborativeness in coping with diagnostic uncertainty. They were more likely to prescribe antibiotics for the recorded illness without an indication for antibiotics (AOR = 1.013 for all antibiotics, p = 0.024; AOR = 1.047 for broad-spectrum antibiotics, p < 0.001), as well as for the recorded illness with a conditional indication for antibiotics (AOR = 1.226 for all antibiotic, p < 0.001; AOR = 1.257 for broad-spectrum antibiotics, p < 0.001). Conclusion: Low tolerance with diagnostic uncertainty is evident in primary care. Inappropriate and over antibiotic prescribing is shaped by physicians' coping methods of diagnostic uncertainty. Physicians' openness and collaborativeness in responding to diagnostic uncertainty is associated with lower antibiotic prescribing in primary care. Interventions targeting on better management of diagnostic uncertainty may offer a promising approach in reducing antibiotic use in primary care.

Current hydrogel advances in physicochemical and biological response-driven biomedical application diversity.

Hydrogel is a type of versatile platform with various biomedical applications after rational structure and functional design that leverages on material engineering to modulate its physicochemical properties (e.g., stiffness, pore size, viscoelasticity, microarchitecture, degradability, ligand presentation, stimulus-responsive properties, etc.) and influence cell signaling cascades and fate. In the past few decades, a plethora of pioneering studies have been implemented to explore the cell-hydrogel matrix interactions and figure out the underlying mechanisms, paving the way to the lab-to-clinic translation of hydrogel-based therapies. In this review, we first introduced the physicochemical properties of hydrogels and their fabrication approaches concisely. Subsequently, the comprehensive description and deep discussion were elucidated, wherein the influences of different hydrogels properties on cell behaviors and cellular signaling events were highlighted. These behaviors or events included integrin clustering, focal adhesion (FA) complex accumulation and activation, cytoskeleton rearrangement, protein cyto-nuclei shuttling and activation (e.g., Yes-associated protein (YAP), catenin, etc.), cellular compartment reorganization, gene expression, and further cell biology modulation (e.g., spreading, migration, proliferation, lineage commitment, etc.). Based on them, current in vitro and in vivo hydrogel applications that mainly covered diseases models, various cell delivery protocols for tissue regeneration and disease therapy, smart drug carrier, bioimaging, biosensor, and conductive wearable/implantable biodevices, etc. were further summarized and discussed. More significantly, the clinical translation potential and trials of hydrogels were presented, accompanied with which the remaining challenges and future perspectives in this field were emphasized. Collectively, the comprehensive and deep insights in this review will shed light on the design principles of new biomedical hydrogels to understand and modulate cellular processes, which are available for providing significant indications for future hydrogel design and serving for a broad range of biomedical applications.

Nanobiotechnology-enabled energy utilization elevation for augmenting minimally-invasive and noninvasive oncology thermal ablation.

Depending on the local or targeted treatment, independence on tumor type and minimally-invasive and noninvasive feature, various thermal ablation technologies have been established, but they still suffer from the intractable paradox between safety and efficacy. It has been extensively accepted that improving energy utilization efficiency is the primary means of decreasing thermal ablation power and shortening ablation time, which is beneficial for concurrently improving both treatment safety and treatment efficiency. Recent efforts have been made to receive a significant advance in various thermal methods including non-invasive high-intensity focused ultrasound, minimally-invasive radiofrequency and microwave, and non-invasive and minimally-invasive photothermal ablation, and so on. Especially, various nanobiotechnologies and design methodologies were employed to elevate the energy utilization efficiency for acquiring unexpected ablation outcomes accompanied with tremendously reduced power and time. More significantly, some combined technologies, for example, chemotherapy, photodynamic therapy (PDT), gaseous therapy, sonodynamic therapy (SDT), immunotherapy, chemodynamic therapy (CDT), or catalytic nanomedicine, were used to assist these ablation means to repress or completely remove tumors. We discussed and summarized the ablation principles and energy transformation pathways of the four ablation means, and reviewed and commented the progress in this field including newly developed technology or new material types with a highlight on nanobiotechnology-inspired design principles, and provided the deep insights into the existing problems and development direction. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Oncostatin M promotes hepatic progenitor cell activation and hepatocarcinogenesis via macrophage-derived tumor necrosis factor-α.

Hepatocellular carcinoma (HCC) usually occurs at the late stage of chronic liver injury. Oncostatin M (OSM) is a tumor-associated cytokine highly expressed in cirrhosis and HCC patients; however, its role in hepatocarcinogenesis has not been clearly elucidated. In this study, we investigated the effect of OSM on HCC occurrence in a rat model of N-diethylnitrosamine-induced HCC. OSM overexpression significantly increased the number of tumor nodules and shortened the overall survival of the rats. Notably, OSM promoted HPC activation in vivo but did not directly regulate the proliferation of the HPC cell line in vitro. Further, OSM induced tumor necrosis factor-α (TNF-α) secretion and CD68+ macrophage accumulation, which were positively correlated with HPC activation. Additionally, TNF-α or macrophage depletion inhibited the promoting effect of OSM on hepatocarcinogenesis and HPC activation. Furthermore, OSM expression in the peritumoral tissues of HCC was positively correlated with poor overall survival of patients. In conclusion, OSM plays an important role in hepatocarcinogenesis by regulating the liver inflammation environment. Hence, OSM could be used as a potential target for HCC prevention and therapy or as an indicator of HCC prognosis.

Bone marrow mesenchymal stem cells promote prostate cancer cell stemness via cell-cell contact to activate the Jagged1/Notch1 pathway.

BACKGROUND: Mesenchymal stem cells (MSCs) play a crucial role in cancer development and tumor resistance to therapy in prostate cancer, but the influence of MSCs on the stemness potential of PCa cells by cell-cell contact remains unclear. In this study, we investigated the effect of direct contact of PCa cells with MSCs on the stemness of PCa and its mechanisms. METHODS: First, the flow cytometry, colony formation, and sphere formation were performed to determine the stemness of PCaMSCs, and the expression of stemness-related molecules (Sox2, Oct4, and Nanog) was investigated by western blot analysis. Then, we used western blot and qPCR to determine the activity levels of two candidate pathways and their downstream stemness-associated pathway. Finally, we verified the role of the significantly changed pathway by assessing the key factors in this pathway via in vitro and in vivo experiments. RESULTS: We established that MSCs promoted the stemness of PCa cells by cell-cell contact. We here established that the enhanced stemness of PCaMSCs was independent of the CCL5/CCR5 pathway. We also found that PCaMSCs up-regulated the expression of Notch signaling-related genes, and inhibition of Jagged1-Notch1 signaling in PCaMSCs cells significantly inhibited MSCs-induced stemness and tumorigenesis in vitro and in vivo. CONCLUSIONS: Our results reveal a novel interaction between MSCs and PCa cells in promoting tumorigenesis through activation of the Jagged1/Notch1 pathway, providing a new therapeutic target for the treatment of PCa.

Influence of Electric Current and Magnetic Flow on Firing Patterns of Pre-Bötzinger Complex Model.

The dynamics of neuronal firing activity is vital for understanding the pathological respiratory rhythm. Studies on electrophysiology show that the magnetic flow is an essential factor that modulates the firing activities of neurons. By adding the magnetic flow to Butera's neuron model, we investigate how the electric current and magnetic flow influence neuronal activities under certain parametric restrictions. Using fast-slow decomposition and bifurcation analysis, we show that the variation of external electric current and magnetic flow leads to the change of the bistable structure of the system and hence results in the switch of neuronal firing pattern from one type to another.

The General Population's Inappropriate Behaviors and Misunderstanding of Antibiotic Use in China: A Systematic Review and Meta-Analysis.

The general population has increasingly become the key contributor to irrational antibiotic use in China, which fuels the emergence of antibiotic resistance. This study aimed to estimate the prevalence of the general population's irrational use behaviors of antibiotics and identify the potential reasons behind them. A systematic review and meta-analysis were performed concerning four main behaviors relevant to easy access and irrational use of antibiotics and common misunderstandings among the population about antibiotics. Four databases were searched, and studies published before 28 February 2021 were retrieved. Medium and high-level quality studies were included. Random effects meta-analysis was performed to calculate the prevalence of the general population's irrational behaviors and misunderstandings relevant to antibiotic use. A total of 8468 studies were retrieved and 78 met the criteria and were included. The synthesis showed the public can easily obtain unnecessary antibiotics, with an estimated 37% (95% CI: 29-46) of the population demanding antibiotics from physicians and 47% (95% CI: 38-57) purchasing non-prescription antibiotics from pharmacies. This situation is severe in the western area of China. People also commonly inappropriately use antibiotics by not following antibiotic prescriptions (pooled estimate: 48%, 95% CI: 41-55) and preventatively use antibiotics for non-indicated diseases (pooled estimate: 35%, 95% CI: 29-42). Misunderstanding of antibiotic use was also popular among people, including incorrect antibiotic recognition, wrong antibiotic use indication, inappropriate usage, and ignorance of potential adverse outcomes. Over-and inappropriate use of antibiotics is evident in China and a multifaceted antibiotic strategy targeted at the general population is urgently required.

Mesenchymal Stem Cell-Secreted Exosome Promotes Chemoresistance in Breast Cancer via Enhancing miR-21-5p-Mediated S100A6 Expression.

Emerging evidence has shown the role of mesenchymal stem cell-derived exosome (MSC-exo) in inducing resistance of cancer cells to chemotherapy. However, it remains unclear whether the change of MSC-exo in response to chemotherapy also contributes to chemoresistance. In this study, we investigated the effect of a standard-of-care chemotherapeutic agent, doxorubicin (Dox), on MSC-exo and its contribution to the development of Dox resistance in breast cancer cells (BCs). We found that the exosome secreted by Dox-treated MSCs (Dt-MSC-exo) induced a higher degree of Dox resistance in BCs when compared with non-treated MSC-exo. By analysis of the MSC-exo-induced transcriptome change in BCs, we identified S100A6, a chemoresistant gene, as a top-ranked gene induced by MSC-exo in BCs, which was further enhanced by Dt-MSC-exo. Furthermore, we found that Dox induced the expression of miR-21-5p in MSCs and MSC-exo, which was required for the expression of S100A6 in BCs. Importantly, silencing of miR-21-5p expression in MSCs and MSC-exo abolished the resistance of BCs to Dox, indicating an exosomal miR-21-5p-regulated S100A6 in chemoresistance. Our study thus uncovered a novel mechanistic insight into the role of MSC-secreted exosome in the development of chemoresistance in the tumor microenvironment.

Leptin promotes bone metastasis of breast cancer by activating the SDF-1/CXCR4 axis.

Obesity is associated with an increased risk of tumorigenesis, and increased leptin levels can promote tumor metastasis. However, the effects of leptin on bone metastasis in breast cancer are not fully understood. Here, we examined leptin receptor expression and bone metastasis in tissue samples from 96 breast cancer patients. In addition, we investigated the effects of leptin on the metastatic capacity of breast cancer cells invitro using a transwell assays. The results indicated that higher leptin receptor levels in breast cancer cells are associated with increased incidence of bone metastasis in breast cancer patients. Additionally, leptin promoted migration and invasion of breast cancer cells. The SDF-1/CXCR4 axis activated by leptin also promoted bone metastasis of breast cancer. Finally, increased CXCR4 expression was accompanied by high leptin receptor expression in bone metastatic tissues from breast cancer patients. These results indicate that leptin induces bone metastasis of breast cancer by activating the SDF-1/CXCR4 axis.

Correction to: Application of shear wave elastography and B-mode ultrasound in patellar tendinopathy after extracorporeal shockwave therapy.

In the original publication of the article the Fig. 1 has been removed, as the authors did not obtain the appropriate permission from the rights holder to use the image in this article.

Aspirin alleviates hepatic fibrosis by suppressing hepatic stellate cells activation via the TLR4/NF-κB pathway.

Hepatic fibrosis arises from a sustained wound-healing response to chronic liver injury. Because the occurrence and development of hepatic fibrosis is always associated with chronic inflammation, controlling inflammation within the liver may be an effective means of controlling the development and progression of hepatic fibrosis. Aspirin is a non-steroidal anti-inflammatory drug used to relieve both inflammatory symptoms and pain. The results of our study showed that aspirin significantly attenuated hepatic inflammation and fibrosis. Aspirin effectively inhibited the activation and proliferation of hepatic stellate cells (HSCs), which led to downregulation of inflammatory factors, including IL-6 and TNF-α in those cells. Aspirin also downregulated expression of Toll-like receptor-4 (TLR4) on HSCs, as well as its downstream mediators, MyD88 and NF-κB. The results of our study demonstrate aspirin's potential to inhibit the development of hepatic fibrosis and the molecular mechanism by which it acts. They suggest aspirin may be an effective therapeutic agent for the treatment of hepatic fibrosis.