Reviving Bistable Perception in Patients With Depression by Decreasing the Overestimation of Prior Precision.

Slower perceptual alternations, a notable perceptual effect observed in psychiatric disorders, can be alleviated by antidepressant therapies that affect serotonin levels in the brain. While these phenomena have been well documented, the underlying neurocognitive mechanisms remain to be elucidated. Our study bridges this gap by employing a computational cognitive approach within a Bayesian predictive coding framework to explore these mechanisms in depression. We fitted a prediction error (PE) model to behavioral data from a binocular rivalry task, uncovering that significantly higher initial prior precision and lower PE led to a slower switch rate in patients with depression. Furthermore, serotonin-targeting antidepressant treatments significantly decreased the prior precision and increased PE, both of which were predictive of improvements in the perceptual alternation rate of depression patients. These findings indicated that the substantially slower perception switch rate in patients with depression was caused by the greater reliance on top-down priors and that serotonin treatment's efficacy was in its recalibration of these priors and enhancement of PE. Our study not only elucidates the cognitive underpinnings of depression, but also suggests computational modeling as a potent tool for integrating cognitive science with clinical psychology, advancing our understanding and treatment of cognitive impairments in depression.

Orienting role of the putative human posterior infero-temporal area in visual attention.

The dorsal attention network (DAN) is a network of brain regions essential for attentional orienting, which includes the lateral intraparietal area (LIP) and frontal eye field (FEF). Recently, the putative human dorsal posterior infero-temporal area (phPITd) has been identified as a new node of the DAN. However, its functional relationship with other areas of the DAN and its specific role in visual attention remained unclear. In this study, we analyzed a large publicly available neuroimaging dataset to investigate the intrinsic functional connectivities (FCs) of the phPITd with other brain areas. The results showed that the intrinsic FCs of the phPITd with the areas of the visual network and the DAN were significantly stronger than those with the ventral attention network (VAN) areas and areas of other networks. We further conducted individual difference analyses with a sample size of 295 participants and a series of attentional tasks to investigate which attentional components each phPITd-based DAN edge predicts. Our findings revealed that the intrinsic FC of the left phPITd with the LIPv could predict individual ability in attentional orienting, but not in alerting, executive control, and distractor suppression. Our results not only provide direct evidence of the phPITd's functional relationship with the LIPv, but also offer a comprehensive understanding of its specific role in visual attention.

Depression and hepatobiliary diseases: a bidirectional Mendelian randomization study.

Background: More and more evidence suggests a close association between depression and hepatobiliary diseases, but its causal relationship is not yet clear. Method: Using genome-wide association studies (GWAS) to summarize data, independent genetic variations associated with depression were selected as instrumental variables. Firstly, we designed a univariate Mendelian randomization (UVMR) analysis with two samples and simultaneously conducted reverse validation to evaluate the potential bidirectional causal relationship between depression and various hepatobiliary diseases. Secondly, we conducted a multivariate Mendelian randomization (MVMR) analysis on diseases closely related to depression, exploring the mediating effects of waist to hip ratio, hypertension, and daytime nap. The mediating effects were obtained through MVMR. For UVMR and MVMR, inverse variance weighted method (IVW) is considered the most important analytical method. Sensitivity analysis was conducted using Cochran'Q, MR Egger, and Leave-one-out methods. Results: UVMR analysis showed that depression may increase the risk of non-alcoholic fatty liver disease (OR, 1.22; 95% CI, 1.03-1.46; p=0.0248) in liver diseases, while depression does not increase the risk of other liver diseases; In biliary and pancreatic related diseases, depression may increase the risk of cholelithiasis (OR, 1.26; 95% CI, 1.05-1.50; p=0.0120), chronic pancreatitis (OR, 1.61; 95% CI, 1.10-2.35; p=0.0140), and cholecystitis (OR, 1.23; 95% CI, 1.03-1.48; p=0.0250). In addition, through reverse validation, we found that non-alcoholic fatty liver disease, cholelithiasis, chronic pancreatitis, cholecystitis, or the inability to increase the risk of depression (p>0.05). The waist to hip ratio, hypertension, and daytime nap play a certain role in the process of depression leading to non-alcoholic fatty liver disease, with a mediating effect of 35.8%. Conclusion: Depression is a susceptibility factor for non-alcoholic fatty liver disease, and the causal effect of genetic susceptibility to depression on non-alcoholic fatty liver disease is mediated by waist-hip ratio, hypertension, and daytime nap.

Identification and preliminary validation of differently expressed genes as candidate biomarkers associated with atherosclerosis.

OBJECTIVE: Atherosclerosis (AS) is the primary cause of deadly cardio-cerebro vascular diseases globally. This study aims to explore the key differentially expressed genes (DEGs), potentially serving as predictive biomarkers for AS. METHODS: Microarray datasets were retrieved from the GEO database for DEGs and DE-miRNAs identification. Then biological function of DEGs were elucidated based on gene ontology (GO) and KEGG pathway enrichment analysis. The protein-protein interaction (PPI) network and DEGs-DE-miRNAs network were constructed, with emphasis on hub DEGs selection and their interconnections. Additionally, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic precision of hub DEGs for AS. More importantly, an AS Syrian Golden hamster model was established to validate the expression levels of hub DEGs in AS. RESULTS: A total of 203 DEGs and 10 DE-miRNAs were screened, with six genes were chosen as hub DEGs. These DEGs were significantly enriched in AS-related biological processes and pathways, such as immune and inflammatory response, cellular response to IL-1 and TNF, positive regulation of angiogenesis, Type I diabetes mellitus, Cytokine-cytokine receptor interaction, TLR signaling pathway. Also, these DEGs and DE-miRNAs formed a closely-interacted DE-miRNAs - DEGs - KEGG pathway network. Besides, hub DEGs presented promising diagnostic potential for AS (AUC: 0.781 âˆ¼ 0.887). In addition, the protein expression levels of TNF-α, CXCL8, CCL4, IL-1ß, CCL3 and CCR8 were significantly increased in AS group Syrian Golden hamsters. CONCLUSION: The identified candidate genes TNF, CXCL8, CCL4, IL1B, CCL3 and CCR8 may have the potential to serve as prognostic biomarker in diagnosing AS.

Dihydromyricetin reverses capecitabine-induced peripheral myelin dysfunction through modulation of oxidative stress.

Previous clinical reports have shown that capecitabine, an oral prodrug of 5-fluorouracil (5-Fu), can induce peripheral neuropathy, resulting in numbness, paresthesia and hypoesthesia. However, the mechanism through which capecitabine causes peripheral nerve injury remains unclear. Here, we demonstrate that systemic administration of capecitabine leads to myelin abnormalities in the peripheral nerves of mice, which are possibly attributed to the death of Schwann cells, the myelinating cells in the peripheral nervous system. Furthermore, our results show that 5-Fu induces significant oxidative stress in Schwann cells by inhibiting the expression of the anti-oxidative protein DJ-1, leading to a decrease in Schwann cell markers. We found that the anti-oxidant dihydromyricetin (DMY) reverses 5-Fu-induced Schwann cell death and oxidative stress and alleviates capecitabine-induced myelin abnormalities. Taken together, our data indicate that capecitabine induces peripheral myelin dysfunction by regulating DJ-1-mediated oxidative stress in Schwann cells and reveal DMY as a potential therapeutic strategy for capecitabine-induced peripheral neuropathy.

The distinct development of stimulus and response serial dependence.

Serial dependence (SD) is a phenomenon wherein current perceptions are biased by the previous stimulus and response. This helps to attenuate perceptual noise and variability in sensory input and facilitates stable ongoing perceptions of the environment. However, little is known about the developmental trajectory of SD. This study investigates how the stimulus and response biases of the SD effect develop across three age groups. Conventional analyses, in which previous stimulus and response biases were assessed separately, revealed significant changes in the biases over time. Previous stimulus bias shifted from repulsion to attraction, while previous response bias evolved from attraction to greater attraction. However, there was a strong correlation between stimulus and response orientations. Therefore, a generalized linear mixed-effects (GLME) analysis that simultaneously considered both previous stimulus and response, outperformed separate analyses. This revealed that previous stimulus and response resulted in two distinct biases with different developmental trajectories. The repulsion bias of previous stimulus remained relatively stable across all age groups, whereas the attraction bias of previous response was significantly stronger in adults than in children and adolescents. These findings demonstrate that the repulsion bias towards preceding stimuli is established early in the developing brain (at least by around 10 years old), while the attraction bias towards responses is not fully developed until adulthood. Our findings provide new insights into the development of the SD phenomenon and how humans integrate two opposing mechanisms into their perceptual responses to external input during development.

Chemical Rules for Stacked Kagome and Honeycomb Topological Semimetals.

The chemical rules for predicting and understanding topological states in stacked kagome and honeycomb lattices are studied in both analytical and numerical ways. Starting with a minimal five-band tight-binding model, all the topological states are sorted into five groups, which are determined by the interlayer and intralayer hopping parameters. Combined with the model, an algorithm is designed to obtain a series of experimentally synthesized topological semimetals with kagome and honeycomb layers, i.e., IAMX family (IA = Alkali metal element, M = Rare earth metal element, X = Carbon group element), in the inorganic crystal structure database. A follow-up high-throughput calculation shows that IAMX family materials are all nodal-line semimetals and they will be Weyl semimetals after taking spin-orbit coupling into consideration. To have further insights into the topology of the IAMX family, a detailed chemical rule analysis is carried out on the high-throughput calculations, including the lattice constants of the structure, intralayer and interlayer couplings, bond strengths, electronegativity, and so on, which are consistent with the tight-binding model. This study provides a way to discover and modulate topological properties in stacked kagome and honeycomb crystals and offers candidates for studying topology-related properties like topological superconductors and axion insulators.

Peripheral Mechanisms of Mechanical Itch.

Mechanical itch, which is defined as an itch sensation caused by innocuous mechanical force, may warn of the potential risk in the skin. The increased mechanosensitivity in sensory neurons may cause scratch-induced itch and promote the transition from acute itch to chronic itch. Recent studies have not only expanded our knowledge about the neuronal circuits in the CNS but have also highlighted the importance of the peripheral epithelia-immune-neuronal crosstalk in the development of mechanical itch. In this review, we will summarize related findings about the molecular and cellular mechanisms of mechanical itch in the skin.

A strategy for quality evaluation of complex herbal preparations based on multi-color scale and efficacy-oriented high-performance thin-layer chromatography characteristic fingerprint combined with chemometric method: Sanwujiao Pills as an example.

To rapidly evaluate the quality of complex herbal preparations, a new strategy was proposed based on multi-color scale and efficacy-oriented high-performance thin-layer chromatography (HPTLC) characteristic fingerprint combined with chemometric method. Firstly, effective components were screened through high-performance liquid chromatography with ultraviolet detection and evaporative light-scattering (HPLC-UV-ELSD), using multi-wavelength fusion combined with network pharmacology and molecular docking techniques. Subsequently, guided by the effective components, the targeted HPTLC characteristic fingerprint was established by multi-color scale scanning. Finally, combined with the chemometric method, the consistency of the preparation quality was evaluated, the marker components leading to quality differences were screened, and the quality control limit was established. Sanwujiao Pills (SWJPs) is a herbal preparation composed of six herbs for treating rheumatoid arthritis (RA). Through this strategy, four HPTLC characteristic fingerprints were established, they were derived from five herbs and guided by eight effective components in SWJPs. Through similarity, clustering heatmap, principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA), the quality distinctions among the 12 batches of SWJPs were determined. These batches were categorized into two groups based on their production time, and eight components affecting the quality of the preparation were identified. Meanwhile, the quality control threshold for SWJPs was determined based on Hotelling's T2 and DModX methods. This strategy aims to rapidly evaluate the quality of complex herbal preparations by HPTLC and extends the application of HPTLC fingerprint chromatography for identifying herbal medicine species and activity-related quality detection. The proposed strategy is also helpful for the quality control of other complex herbal preparations.

Visual impairment and blindness caused by retinal diseases: A nationwide register-based study.

Background: Retinal disorders cause substantial visual burden globally. Accurate estimates of the vision loss due to retinal diseases are pivotal to inform optimal eye health care planning and allocation of medical resources. The purpose of this study is to describe the proportion of visual impairment and blindness caused by major retinal diseases in China. Methods: A nationwide register-based study of vitreoretinal disease covering all 31 provinces (51 treating centres) of mainland China. A total of 28 320 adults diagnosed with retinal diseases were included. Participants underwent standardised ocular examinations, which included best-corrected visual acuity (BCVA), dilated-fundus assessments, and optical coherence tomography. Visual impairment and blindness are defined using BCVA according to the World Health Organization (WHO) (visual impairment: <20/63-≥20/400; blindness: <20/400) and the United States (visual impairment: <20/40-≥20/200; blindness: <20/200) definitions. The risk factors of vision loss were explored by logistic regression analyses. Results: Based on the WHO definitions, the proportions for unilateral visual impairment and blindness were 46% and 18%, respectively, whereas those for bilateral visual impairment and blindness were 31% and 3.3%, respectively. Diabetic retinopathy (DR) accounts for the largest proportion of patients with visual impairment (unilateral visual impairment: 32%, bilateral visual impairment: 60%) and blindness (unilateral blindness: 35%; bilateral blindness: 64%). Other retinal diseases that contributed significantly to vision loss included age-related macular degeneration, myopic maculopathy, retinal vein occlusion, and rhegmatogenous retinal detachment and other macular diseases. Women (bilateral vision loss: P = 0.011), aged patients (unilateral vision loss: 45-64 years: P < 0.001, ≥65 years: P < 0.001; bilateral vision loss: 45-64 years: P = 0.003, ≥65 years: P < 0.001 (reference: 18-44 years)) and those from Midwest China (unilateral and bilateral vision loss: both P < 0.001) were more likely to suffer from vision loss. Conclusions: Retinal disorders cause substantial visual burden among patients with retinal diseases in China. DR, the predominant retinal disease, is accountable for the most prevalent visual disabilities. Better control of diabetes and scaled-up screenings are warranted to prevent DR. Specific attention should be paid to women, aged patients, and less developed regions.

The role of distractors in rapid serial visual presentation reveals the mechanism of attentional blink by EEG-based univariate and multivariate analyses.

Attentional blink pertains to the performance of participants with a severe decline in identifying the second target presented after the first target reported correctly within 200-500 ms in a rapid serial visual presentation. The current study was conducted to investigate the neural mechanism of the effect of the distractor (D1) that immediately follows first target to attentional blink by altering whether D1 was substituted with a blank with electroencephalography recording. The results showed that D1 interfered with the attentional enhancement and working memory encoding in both single-target rapid serial visual presentation task and dual-target rapid serial visual presentation task, which were mainly manifested in delayed and attenuated P3a and diminished P3b of first target. Single-trial analysis indicated that first target and second target will compete with each other for working memory encoding resources in short lag, but not in the long lag. In addition, D1 interfered with the working memory encoding of second target under short lag rather than long lag in the dual-target rapid serial visual presentation task. These results suggested that attentional blink can be attributed to the limited working memory encoding resource, whereas the amount of available resources is subject to modulation by attention. The D1 hinders the attention enhancement of first target, thereby exacerbating attentional blink.

One-step ethylene purification from ternary mixtures by an ultramicroporous material with synergistic binding centers.

Developing advanced porous materials with industrial potential to separate multicomponent gas mixtures that are structurally similar is a crucial but challenging task. Here, we report the efficient one-step separation of ethylene (C2H4) from acetylene (C2H2) and carbon dioxide (CO2) using an ultramicroporous metal-organic framework UTSA-16. The synergistic effect of the polarized carboxyl groups and coordinated water molecules in its pore channel enables the material to have high uptakes for C2H2 and CO2 due to electrostatic potential matching, as well as excellent separation selectivity against C2H4. Breakthrough experiments suggest that UTSA-16 can efficiently separate 99.9% pure C2H4 from ternary mixtures with a high productivity of 403 L kg-1. Moreover, the preparation cost of UTSA-16 is significantly lower than other related adsorbents by 40-2000 times, indicating its unique potential for industrial applications.

Leading basic modes of spontaneous activity drive individual functional connectivity organization in the resting human brain.

Spontaneous activity of the human brain provides a window to explore intrinsic principles of functional organization. However, most studies have focused on interregional functional connectivity. The principles underlying rich repertoires of instantaneous activity remain largely unknown. We apply a recently proposed eigen-microstate analysis to three resting-state functional MRI datasets to identify basic modes that represent fundamental activity patterns that coexist over time. We identify five leading basic modes that dominate activity fluctuations. Each mode exhibits a distinct functional system-dependent coactivation pattern and corresponds to specific cognitive profiles. In particular, the spatial pattern of the first leading basis mode shows the separation of activity between the default-mode and primary and attention regions. Based on theoretical modelling, we further reconstruct individual functional connectivity as the weighted superposition of coactivation patterns corresponding to these leading basic modes. Moreover, these leading basic modes capture sleep deprivation-induced changes in brain activity and interregional connectivity, primarily involving the default-mode and task-positive regions. Our findings reveal a dominant set of basic modes of spontaneous activity that reflect multiplexed interregional coordination and drive conventional functional connectivity, furthering the understanding of the functional significance of spontaneous brain activity.

High strength, anti-freezing and conductive silkworm excrement cellulose-based ionic hydrogel with physical-chemical double cross-linked for pressure sensing.

Recently, ionic conductive hydrogels have attracted extensive attention in the field of flexible pressure sensors due to their mechanical flexibility and high conductivity. However, the trade-off between the high electrical and mechanical properties of ionic conductive hydrogels and the loss of mechanical and electrical properties of traditional high water content hydrogels at low temperature are still the main hurdles in this area. Herein, a rigid Ca-rich silkworm excrement cellulose (SECCa) extracted from silkworm breeding waste was prepared. SEC-Ca was combined with the flexible hydroxypropyl methylcellulose (HPMC) molecules through hydrogen bonding and double ionic bonds of Zn2+ and Ca2+ to obtain the physical network SEC@HPMC-(Zn2+/Ca2+). Then, the covalently cross-linked network of polyacrylamide (PAAM) and the physical network were cross-linked by hydrogen bonding to obtain the physical-chemical double cross-linked hydrogel (SEC@HPMC-(Zn2+/Ca2+)/PAAM). The hydrogel showed excellent compression properties (95 %, 4.08 MPa), high ionic conductivity (4.63 S/m at 25 °C) and excellent frost resistance (possessing ionic conductivity of 1.20 S/m at -70 °C). Notably, the hydrogel can monitor pressure changes in a wide temperature range (-60-25 °C) with high sensitivity, stability and durability. This newly fabricated hydrogel-based pressure sensors can be deemed of great prospects for large-scale application of pressure detection at ultra-low temperatures.

A connectome-based neuromarker of nonverbal number acuity and arithmetic skills.

The approximate number system (ANS) is vital for survival and reproduction in animals and is crucial for constructing abstract mathematical abilities in humans. Most previous neuroimaging studies focused on identifying discrete brain regions responsible for the ANS and characterizing their functions in numerosity perception. However, a neuromarker to characterize an individual's ANS acuity is lacking, especially one based on whole-brain functional connectivity (FC). Here, based on the resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from a large sample, we identified a distributed brain network (i.e. a numerosity network) using a connectome-based predictive modeling (CPM) analysis. The summed FC strength within the numerosity network reliably predicted individual differences in ANS acuity regarding behavior, as measured using a nonsymbolic number-comparison task. Furthermore, in an independent dataset of the Human Connectome Project (HCP), we found that the summed FC strength within the numerosity network also specifically predicted individual differences in arithmetic skills, but not domain-general cognitive abilities. Therefore, our findings revealed that the identified numerosity network could serve as an applicable neuroimaging-based biomarker of nonverbal number acuity and arithmetic skills.

The brain network underlying attentional blink predicts symptoms of attention deficit hyperactivity disorder in children.

Attention deficit hyperactivity disorder (ADHD) is a chronic neuropsychiatric disease that can markedly impair educational, social, and occupational function throughout life. Behavioral deficits may provide clues to the underlying neurological impairments. Children with ADHD exhibit a larger attentional blink (AB) deficit in rapid serial visual presentation (RSVP) tasks than typically developing children, so we examined whether brain connectivity in the neural network associated with AB can predict ADHD symptoms and thus serve as potential biomarkers of the underlying neuropathology. We first employed a connectome-based predictive model analysis of adult resting-state functional magnetic resonance imaging data to identify a distributed brain network for AB. The summed functional connectivity (FC) strength within the AB network reliably predicted individual differences in AB magnitude measured by a classical dual-target RSVP task. Furthermore, the summed FC strength within the AB network predicted individual differences in ADHD Rating Scale scores from an independent dataset of pediatric patients. Our findings suggest that the individual AB network could serve as an applicable neuroimaging-based biomarker of AB deficit and ADHD symptoms.

BmRRS1 Protein Inhibits the Proliferation of Baculovirus Autographa californica Nucleopolyhedrovirus in Silkworm, Bombyx mori.

The study of functional genes involved in baculovirus infection is vital for its wide application in pest biocontrol. This study utilized the Autographa californica nucleopolyhedrovirus (AcMNPV) and silkworm as models to elucidate the role of BmRRS1, which has been found to exhibit notable differential expression between resistant and susceptible silkworm strains. The results showed that it was evolutionarily conserved in selected species. Among different tissues, it was expressed at the highest level in the gonads, followed by the hemolymph and silk glands; among the different developmental stages, it was the highest in the second instar, followed by the pupae and adults. Moreover, its vital role in suppressing AcMNPV infection was verified by the decreased expression of lef3 and vp39 protein after overexpression of BmRRS1 as well as by the increased expression of the viral gene lef3 and the viral protein vp39 after siRNA treatment against BmRRS1 expression in BmN cells. Additionally, the direct interaction between BmRRS1 and AcMNPV was detected by the GST pull-down assay. Finally, the homologue of BmRRS1 in Spodoptera frugiperda was found to be involved in larval resistance to AcMNPV. In a word, BmRRS1 plays a vital role in AcMNPV resistance in silkworms, and this might be related to the direct interaction with AcMNPV. The results of this study provide a potential target for protecting silkworm larvae from virus infection and controlling agricultural and forestry pests.

Fibroblast growth factor 10 protects against particulate matter-induced lung injury by inhibiting oxidative stress-mediated pyroptosis via the PI3K/Akt/Nrf2 signaling pathway.

Particulate matter (PM) is a major environmental contaminant that causes and worsens respiratory diseases. Fibroblast growth factor 10 (FGF10), a paracrine fibroblast growth factor that specifically stimulates repair and regeneration after injury, has been shown to protect against PM-induced lung injury. However, the underlying mechanisms are still unclear. In this study, the protective effects of FGF10 were investigated using a PM-induced lung injury mouse model in vivo and BEAS-2B cells in vitro. According to the findings, FGF10 treatment alleviated PM-induced oxidative damage and pyroptosis in vivo and in vitro. Mechanistically, FGF10 activated antioxidative Nrf2 signaling. Inhibition of PI3K signaling with LY294002 or Nrf2 signaling with ML385 revealed that FGF10-mediated lung protection was mediated by the PI3K/Akt/Nrf2 pathway. These results collectively indicate that FGF10 inhibits oxidative stress-mediated pyroptosis via the PI3K/Akt/Nrf2 pathway, suggesting a possible therapy for PM-induced lung injury.

Dynamic analysis of the microbial communities and metabolome of healthy banana rhizosphere soil during one growth cycle.

Background: The banana-growing rhizosphere soil ecosystem is very complex and consists of an entangled network of interactions between banana plants, microbes and soil, so identifying key components in banana production is difficult. Most of the previous studies on these interactions ignore the role of the banana plant. At present, there is no research on the the micro-ecological environment of the banana planting growth cycle. Methods: Based on high-throughput sequencing technology and metabolomics technology, this study analyzed the rhizosphere soil microbial community and metabolic dynamics of healthy banana plants during one growth cycle. Results: Assessing the microbial community composition of healthy banana rhizosphere soil, we found that the bacteria with the highest levels were Proteobacteria, Chloroflexi, and Acidobacteria, and the dominant fungi were Ascomycota, Basidiomycota, and Mortierellomycota. The metabolite profile of healthy banana rhizosphere soil showed that sugars, lipids and organic acids were the most abundant, accounting for about 50% of the total metabolites. The correlation network between fungi and metabolites was more complex than that of bacteria and metabolites. In a soil environment with acidic pH, bacterial genera showed a significant negative correlation with pH value, while fungal genera showed no significant negative correlation with pH value. The network interactions between bacteria, between fungi, and between bacteria and fungi were all positively correlated. Conclusions: Healthy banana rhizosphere soil not only has a stable micro-ecology, but also has stable metabolic characteristics. The microorganisms in healthy banana rhizosphere soil have mutually beneficial rather than competitive relationships.

Establishing a novel model of malignant airway stenosis in rabbit.

Background: Malignant central airway stenosis is a life-threatening condition. However, treatment of malignant airway stenosis remains challenging. There is currently a severe lack of an excellent animal model of malignant airway stenosis to facilitate treatment approaches. This is the first study to establish a rabbit model of malignant airway stenosis for bronchoscopic interventional studies. Materials and methods: New Zealand White rabbits were used in this study, randomly divided into group A (18 rabbits) and group B (6 rabbits). A VX2 fragment suspension was injected into the submucosal layer of rabbits' airway by bronchoscopy. Bronchoscopic examinations were performed once a week after VX2 tumor implantation to observe tumor growth and the degree of airway stenosis. Randomly, three rabbits were generally dissected after a weekly bronchoscopic examination in group A. The rabbits that reached grade III airway stenosis underwent stent implantation in group B. Results: A total of 24 rabbits were successfully implanted with the VX2 fragment suspension in the airway without significant adverse events, and the success rate of the tumor growth was 100%. The degree of airway stenosis reaching grade III took 2 to 3 weeks after implantation of the VX2 tumor. The median survival time of rabbit models without stent implantation and rabbits with stent implantation was 32.5 and 32.0 days, respectively. Conclusions: The implanting method is safe and effective for the establishment of a rabbit model of malignant airway stenosis. When the tumor grows to 2 to 3 weeks, the rabbit model is available for stent implantation. We recommend the models for more preclinical animal studies on bronchoscopic interventional treatments.