Mycobacterium vaccae attenuates airway inflammation by inhibiting autophagy and activating PI3K/Akt signaling pathway in OVA-induced allergic airway inflammation mouse model.

PURPOSE: The etiology of asthma remains elusive, with no known cure. Based on accumulating evidence, autophagy, a self-degradation process that maintains cellular metabolism and homeostasis, participates in the development of asthma. Mycobacterium vaccae vaccine (M. vaccae), an immunomodulatory agent, has previously been shown to effectively alleviate airway inflammation and airway remodeling. However, its therapeutic effect on asthma via the regulation of autophagy remains unknown. Therefore, this study aimed to investigate the impact of M. vaccae in attenuating asthma airway inflammation via autophagy-mediated pathways. METHODS: Balb/c mice were used to generate an ovalbumin (OVA)-immunized allergic airway model and were subsequently administered either M. vaccae or M. vaccae + rapamycin (an autophagy activator) prior to each challenge. Next, airway inflammation, mucus secretion, and airway remodeling in mouse lung tissue were assessed via histological analyses. Lastly, the expression level of autophagy proteins LC3B, Beclin1, p62, and autolysosome was determined both in vivo and in vitro, along with the expression level of p-PI3K, PI3K, p-Akt, and Akt in mouse lung tissue. RESULTS: The findings indicated that aerosol inhalation of M. vaccae in an asthma mouse model has the potential to decrease eosinophil counts, alleviate airway inflammation, mucus secretion, and airway remodeling through the inhibition of autophagy. Likewise, M. vaccae could reduce the levels of OVA-specific lgE, IL-5, IL-13, and TNF-α in asthma mouse models by inhibiting autophagy. Furthermore, this study revealed that M. vaccae also suppressed autophagy in IL-13-stimulated BEAS-2B cells. Moreover, M. vaccae may activate the PI3K/Akt signaling pathway in the lung tissue of asthmatic mice. CONCLUSION: In summary, the present study suggests that M. vaccae may contribute to alleviating airway inflammation and remodeling in allergic asthma by potentially modulating autophagy and the PI3K/Akt signaling pathway. These discoveries offer a promising avenue for the development of therapeutic interventions targeting allergic airway inflammation.

Cardiac glycosides with cytotoxic activity from the seeds of Thevetia peruviana.

Phytochemical investigation on the extract of the seeds of Thevetia peruviana resulted in the isolation of six new cardiac glycosides, namely theveperosides A-F (1-6), including a rare 19-nor-cardenolide (1), together with seven known analogues (7-13). The chemical structures of these compounds were determined based on detailed spectroscopic analysis. The cytotoxic activities of 1-13 were evaluated against MCF-7, HCT-116, HeLa, and HepG2 cancer cell lines, and their structure-activity relationships (SARs) were investigated. Compound 3 exhibited the significant cytotoxic effects with IC50 values ranging from 0.032 to 0.055 µΜ, which could induce HepG2 cells apoptosis in a dose-dependent manner.

Study of tree shrew biology and models: A booming and prosperous field for biomedical research.

The tree shrew ( Tupaia belangeri) has long been proposed as a suitable alternative to non-human primates (NHPs) in biomedical and laboratory research due to its close evolutionary relationship with primates. In recent years, significant advances have facilitated tree shrew studies, including the determination of the tree shrew genome, genetic manipulation using spermatogonial stem cells, viral vector-mediated gene delivery, and mapping of the tree shrew brain atlas. However, the limited availability of tree shrews globally remains a substantial challenge in the field. Additionally, determining the key questions best answered using tree shrews constitutes another difficulty. Tree shrew models have historically been used to study hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, myopia, and psychosocial stress-induced depression, with more recent studies focusing on developing animal models for infectious and neurodegenerative diseases. Despite these efforts, the impact of tree shrew models has not yet matched that of rodent or NHP models in biomedical research. This review summarizes the prominent advancements in tree shrew research and reflects on the key biological questions addressed using this model. We emphasize that intensive dedication and robust international collaboration are essential for achieving breakthroughs in tree shrew studies. The use of tree shrews as a unique resource is expected to gain considerable attention with the application of advanced techniques and the development of viable animal models, meeting the increasing demands of life science and biomedical research.

[Impact of Land Use Change on Carbon Storage in Urban Agglomerations in the Guanzhong Plain].

It is important to study the impact of land use change on terrestrial ecosystem carbon stocks in urban agglomerations for the optimization of land use structure and sustainable development in urban agglomerations. Based on the patch-generating land use simulation (PLUS) model and integrated valuation of ecosystem services and trade-offs (InVEST) model, a simulation was developed that predicted the land use change and carbon stock of the Guanzhong Plain urban agglomeration in 2040 under different scenarios and further analyzed the impact of land use change on carbon stock. The results showed that:① The land use types of the Guanzhong Plain urban agglomeration were mainly cultivated land, forest land, and grassland, which accounted for more than 90 % of the total study area. ② From 2000 to 2020, the carbon stock in the Guanzhong Plain showed a continuous downward trend, with cropland, woodland, and grassland being the main sources of carbon stock in the Guanzhong Plain, and the overall carbon stock declined by 15.12×106 t, with the spatial distribution presenting the distribution characteristics of "high in the north and south and low in the middle." ③ By 2040, the carbon stock would decrease the most under the urban development scenario, with a total reduction of 27.08×106 t, and the least under the ecological development scenario, with a total reduction of 4.14×106t. The research results can provide data support for the high-quality development and rational land use planning of the Guanzhong Plain urban agglomeration.

How do "words poorly expressed emotion" affect mental health? The mediating role of affect labelling effect.

Previous studies have found that people with high negative emotional granularity(NEG) tend to have better health levels. It is generally believed that this is due to the selection and application of explicit emotion regulation strategies that affect mental health. However, no research has yet examined a more fundamental process, the role of affect labelling, an implicit emotion regulation strategy. This study focuses on the aforementioned issues and uses the experience sampling method to categorise participants into groups with high and low NEG. Using an affect labelling paradigm with ERP(event-related potential) technology, the study measures the effects of affect labelling in participants. Furthermore, it assesses the mental health levels of the participants through questionnaires to explore whether the affect labelling effect serves as a mediator between NEG and mental health. The results show that: (1) The high-NEG group exhibited significantly lower LPP wave amplitudes under affect labelling compared to under non-affect labelling, whereas the low-NEG group did not show significant differences. The results indicate that only the high-NEG group can produce the affect labelling effect. (2) The affect labelling effect mediates the relationship between NEG and mental health, meaning that NEG predicts mental health through the affect labelling effect.

Explainable machine learning for early predicting treatment failure risk among patients with TB-diabetes comorbidity.

The present study aims to assess the treatment outcome of patients with diabetes and tuberculosis (TB-DM) at an early stage using machine learning (ML) based on electronic medical records (EMRs). A total of 429 patients were included at Chongqing Public Health Medical Center. The random-forest-based Boruta algorithm was employed to select the essential variables, and four models with a fivefold cross-validation scheme were used for modeling and model evaluation. Furthermore, we adopted SHapley additive explanations to interpret results from the tree-based model. 9 features out of 69 candidate features were chosen as predictors. Among these predictors, the type of resistance was the most important feature, followed by activated partial throm-boplastic time (APTT), thrombin time (TT), platelet distribution width (PDW), and prothrombin time (PT). All the models we established performed above an AUC 0.7 with good predictive performance. XGBoost, the optimal performing model, predicts the risk of treatment failure in the test set with an AUC 0.9281. This study suggests that machine learning approach (XGBoost) presented in this study identifies patients with TB-DM at higher risk of treatment failure at an early stage based on EMRs. The application of a convenient and economy EMRs based on machine learning provides new insight into TB-DM treatment strategies in low and middle-income countries.

Mycobacterium vaccae alleviates allergic airway inflammation and airway hyper-responsiveness in asthmatic mice by altering intestinal microbiota.

Host immunity can influence the composition of the gut microbiota and consequently affect disease progression. Previously, we reported that a Mycobacterium vaccae vaccine could ameliorate allergic inflammation in asthmatic mice by regulating inflammatory immune processes. Here, we investigated the anti-inflammatory effects of M. vaccae on allergic asthma via gut microbiota modulation. An ovalbumin (OVA)-induced asthmatic murine model was established and treated with M. vaccae. Gut microbiota profiles were determined in 18 BALB/c mice using 16S rDNA gene sequencing and metabolomic profiling was performed using liquid chromatography quadrupole time-of-flight mass spectrometry. Mycobacterium vaccae alleviated airway hyper-reactivity and inflammatory infiltration in mice with OVA-induced allergic asthma. The microbiota of asthmatic mice is disrupted and that this can be reversed with M. vaccae. Additionally, a total of 24 differential metabolites were screened, and the abundance of PI(14:1(9Z)/18:0), a glycerophospholipid, was found to be correlated with macrophage numbers (r = 0.52, p = 0.039). These metabolites may affect chemokine (such as macrophage chemoattractant protein-1) concentrations in the serum, and ultimately affect pulmonary macrophage recruitment. Our data demonstrated that M. vaccae might alleviate airway inflammation and hyper-responsiveness in asthmatic mice by reversing imbalances in gut microbiota. These novel mechanistic insights are expected to pave the way for novel asthma therapeutic strategies.

Non­diagnostic electromagnetic navigation bronchoscopy biopsy: Predictive factors and final diagnoses.

The present study aimed to explore the final diagnosis of pulmonary nodules with an initial non-diagnostic result on electromagnetic navigation bronchoscopy (ENB) biopsy and the predictive factors for a non-diagnostic result. A total of 198 nodules from 194 patients that were suspected to be malignant tumors were included in the present study. The initial biopsy pathology results were divided into two groups: The diagnostic group and the non-diagnostic group. The diagnostic group was defined as a successful initial biopsy to obtain a diagnosis, including malignant and benign diagnoses. The non-diagnostic group was defined as a non-specific benign diagnosis, normal lung tissue or an unsuccessful biopsy. Among the 198 nodules, 139 (70.2%) were in the diagnostic group and 59 (29.8%) were in the non-diagnostic group. Predictive factors for a non-diagnostic biopsy included nodule size ≤1.5 cm [odds ratio (OR), 2.05; 95% confidence interval (CI), 1.03-4.09], non-solid nodules (OR, 2.71; 95% CI, 1.33-5.64) and nodules in the left lung (OR, 2.50; 95% CI, 1.27-4.92). Of the 59 non-diagnostic biopsies, 46 were finally confirmed to be malignant by surgery. Notably, non-diagnostic biopsies with non-solid nodules (OR, 7.64; 95% CI, 3.11-18.76) were more likely to be malignant. In conclusion, the predictive factors for a non-diagnostic biopsy were nodule size ≤1.5 cm and non-solid nodules. It was not rare for patients to finally be diagnosed with a malignancy in the non-diagnostic group. Therefore, care should be taken when the results of an ENB are non-diagnostic to prevent misdiagnosis.

[QMEC-based Analysis of the Soil Microbial Functional Potentials across Different Tibetan Plateau Glacier Forelands].

Soil microorganisms dominate the biogeochemical cycles of elements in glacier forelands, which continue to expand due to the climate warming. We analyzed the soil microbial functional characteristics among three types of glacier forelands on the Tibetan Plateau: Yulong Glacier (Y), a temperate glacier; Tianshan Urumqi Glacier No.1 (T), a sub-continental glacier; and Laohugou Glacier No.12 (L), a continental glacier. Here, soil microbial functional genes were quantified using quantitative microbial element cycling technology (QMEC). We found that, in the three glacier forelands, the abundances of soil microbial functional genes related to hemicellulose degradation and reductive acetyl-CoA pathway were highest compared with other carbon-related functional genes. The main nitrogen cycling genes were involved in ammonification. The functional genes of the phosphorus cycle and sulfur cycle were related to organic phosphate mineralization and sulfur oxidation. Furthermore, the soils of the temperate glacier foreland with better hydrothermal conditions had the most complex microbial functional gene structure and the highest functional potentials, followed by those of the soils of continental glacier foreland with the driest environment. These significant differences in soil microbial functional genes among the three types of glacier forelands verified the impacts of geographic difference on microbial functional characteristics, as well as providing a basis for the study of soil microbial functions and biogeochemical cycles in glacier forelands.

Dosage selection and effect evaluation of sodium pentobarbital in tree shrew anesthesia.

To achieve surgical anesthesia in animal experimentation, it is important to select the appropriate anesthetic dose. However, few studies have investigated the reasonable anesthetic dose in tree shrew (Tupaia belangeri). The aim of the study was to review the literature to determine the most commonly used anesthetic dose in tree shrew and to calculate the reasonable equivalent dose between tree shrew and rat based on the body surface area conversion. Two groups of 10 adult tree shrews each were anesthetized with 1% sodium pentobarbital through intraperitoneal injection separately at doses of 62 mg/kg (equivalent dose) and 40 mg/kg (reported dose). Anesthetic depth and times were assessed in addition to vital signs. The results showed that the dosage was quite different across studies, ranging from 15 mg/kg to 80 mg/kg, with 40 mg/kg being the most frequently reported dose. However, the group of tree shrews anesthetized with the commonly reported dose were unable to meet the requirements of surgery. In contrast, the equivalent dose (62 mg/kg, intraperitoneal injection with sodium pentobarbital) calculated by body surface area conversion could achieve an anesthetic time of 44.28 ± 3.95 min with no serious or fatal effects. During anesthetic monitoring, we found that sodium pentobarbital had an inhibitory effect on the blood pressure, pulse rate, respiratory rate and rectal temperature in tree shrews, especially on the respiratory rate. Thus, our study indicated that the use of the equivalent dose of sodium pentobarbital was effective in anesthetizing tree shrews.