Evaluation of a 12-hole clock model for improving bronchoscopic skills in simulated normal and difficult airways among anesthesia residents: A randomized controlled study.

BACKGROUND: Simulation-based training is used to improve fiberoptic bronchoscopic skills for novices. We developed a nonanatomical task trainer (named 12-hole clock model) that focused on training manipulation of bronchoscopes. The aim of this study was to evaluate the training effect of this model on bronchoscopic skills and learning interests in simulated normal and difficult airways among anesthesia residents. METHODS: Forty-three anesthesia residents without experience in bronchoscopic intubation were randomly divided into control (n = 22) and intervention groups (n = 21). All participants received standard multimedia learning and a baseline test using a normal airway manikin. Then, the control and intervention groups engaged in 60 minutes of training via a traditional airway manikin or the clock model, respectively. After training, the participants completed bronchoscopic performance assessments in simulated normal and difficult airways, as well as an electronic questionnaire related to the course. RESULTS: During training, the total hands-on time of bronchoscopic practice recorded by trainees' themselves was longer in the intervention group than in the control group (1568 ±â€…478 seconds vs 497 ±â€…172 s, P < .0001). Posttraining, the time required to visualize the carina in simulated normal airways was longer in the intervention group than in the control group (22.0 [18.0, 29.0] vs 14.0 [10.8, 18.3], P < .0001), while it was shorter for simulated difficult airways (24.0 [16.0, 32.0] s vs 27.0 [21.0, 35.5] s, P = .0425). The survey results indicated that confidence in bronchoscopic intubation increased in both groups, without significant differences in satisfaction, acceptance, or perceived difficulty between the groups. However, the interest ratings were higher in the intervention group than in the control group. CONCLUSIONS: The 12-hole clock model is a simple and feasible method for improving bronchoscopic skills and promoting interest among trainees. TRIAL REGISTRATION: NCT05327842 at Clinicaltrials.gov.

A telomere-related gene risk model for predicting prognosis and treatment response in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a prevalent hematological malignancy among adults. Recent studies suggest that the length of telomeres could significantly affect both the risk of developing AML and the overall survival (OS). Despite the limited focus on the prognostic value of telomere-related genes (TRGs) in AML, our study aims at addressing this gap by compiling a list of TRGs from TelNet, as well as collecting clinical information and TRGs expression data through the Gene Expression Omnibus (GEO) database. The GSE37642 dataset, sourced from GEO and based on the GPL96 platform, was divided into training and validation sets at a 6:4 ratio. Additionally, the GSE71014 dataset (based on the GPL10558 platform), GSE12417 dataset (based on the GPL96 and GPL570 platforms), and another portion of the GSE37642 dataset (based on the GPL570 platform) were designated as external testing sets. Univariate Cox regression analysis identified 96 TRGs significantly associated with OS. Subsequent Lasso-Cox stepwise regression analysis pinpointed eight TRGs (MCPH1, SLC25A6, STK19, PSAT1, KCTD15, DNMT3B, PSMD5, and TAF2) exhibiting robust predictive potential for patient survival. Both univariate and multivariate survival analyses unveiled TRG risk scores and age as independent prognostic variables. To refine the accuracy of survival prognosis, we developed both a nomogram integrating clinical parameters and a predictive risk score model based on TRGs. In subsequent investigations, associations were emphasized not solely regarding the TRG risk score and immune infiltration patterns but also concerning the response to immune-checkpoint inhibitor (ICI) therapy. In summary, the establishment of a telomere-associated genetic risk model offers a valuable tool for prognosticating AML outcomes, thereby facilitating informed treatment decisions.

Small molecule NMD and MDM2 inhibitors synergistically trigger apoptosis in HeLa cells.

The nonsense-mediated mRNA decay (NMD) pathway and the p53 pathway, linked to tumorgenesis, are also promising targets for cancer treatment. NMD plays an important role in RNA quality control, while the p53 pathway is involved in cancer suppression. However, their individual and combined effects on cervical cancer are poorly understood. In this study, we evaluated the impacts of NMD inhibitor, Mouse double minute 2 homolog (MDM2) inhibitor, and their combination on cell apoptosis, cell cycle, and p53 target genes in human papillomavirus-18-positive HeLa cells. Our findings revealed that XR-2 failed to activate p53 or induce apoptosis in HeLa cells, whereas SMG1 (serine/threonine-protein kinase 1) inhibitor repressed cell proliferation at high concentrations. Notably, the combination of these 2 agents significantly inhibited cell proliferation, arrested the cell cycle, and triggered cell apoptosis. Mechanistically, MDM2 inhibitor and NMD inhibitor likely exert a synergistically through the truncated E6 protein. These results underscore the potential of employing a combination of MDM2 inhibitor and NMD inhibitor as a promising candidate for the clinical treatment of human papillomavirus-infected tumors.

Photoinduced decarboxylative germylation of α-fluoroacrylic acids: access to germylated monofluoroalkenes.

Herein, a novel strategy is presented for the photoinduced decarboxylative and dehydrogenative cross-coupling of a wide range of α-fluoroacrylic acids with hydrogermanes. This methodology provides an efficient and robust approach for producing various germylated monofluoroalkenes with excellent stereoselectivity within a brief photoirradiation period. The feasibility of this reaction has been demonstrated through gram-scale reaction, conversion of germylated monofluoroalkenes, and modification of complex organic molecules.

Temperature dependence of the rain-gas and snow-gas partition coefficients for nearly a thousand chemicals.

Compared to the particle-gas partition coefficients (KPG), the rain-gas (KRG) and snow-gas (KSG) partition coefficients are also essential in studying the environmental behavior and fate of chemicals in the atmosphere. While the temperature dependence for the KPG have been extensively studied, the study for KRG and KSG are still lacking. Adsorption coefficients between water surface-air (KIA) and snow surface-air (KJA), as well as partition coefficients between water-air (KWA) and octanol-air (KOA) are vital in calculating KRG and KSG. These four basic adsorption and partition coefficients are also temperature-dependent, given by the well-known two-parameters Antoine equation logKXY = AXY + BXY/T, where KXY is the adsorption or partition coefficients, AXY and BXY are Antoine parameters (XY stand for IA, JA, WA, and OA), and T is the temperature in Kelvin. In this study, the parameters AXY and BXY are calculated for 943 chemicals, and logKXY can be estimated at any ambient temperature for these chemicals using these Antoine parameters. The results are evaluated by comparing these data with published experimental and modeled data, and the results show reasonable accuracy. Based on these coefficients, temperature-dependence of logKRG and logKSG is studied. It is found that both logKRG and logKSG are linearly related to 1/T, and Antoine parameters for logKRG and logKSG are also estimated. Distributions of the 943 chemicals in the atmospheric phases (gas, particle, and rain/snow), are illustrated in a Chemical Space Map. The findings reveal that, at environmental temperatures and precipitation days, the dominant state for the majority of chemicals is the gaseous phase. All the AXY and BXY values for logKSG, logKRG, and basic adsorption and partition coefficients, both modeled by this study and collected from published work, are systematically organized into an accessible dataset for public utilization.

Consent and Educational Sensitive Exams on Anesthetized Patients: Experiences of Medical Students Across Canada.

OBJECTIVE: This study investigates experiences of medical students across Canada related to consent for educational sensitive (i.e., pelvic, rectal) exams under anesthesia (EUAs). METHODS: A bilingual online questionnaire was developed and distributed to medical students across Canada. RESULTS: Of 134 respondents, 63% had performed a pelvic EUA, 35% a rectal EUA, and 11% another sensitive EUA during their training. For those who had performed pelvic EUA, 28% were unsure if consent had taken place, 26% reported no specific consent, 20% reported specific consent, and 25% had mixed experiences of consent. For rectal EUAs, 48% reported no specific consent, 37% were unsure if consent had taken place, 13% reported that there had been specific consent, and 2% reported mixed experiences. Most respondents were uncomfortable (36%) or not sure if they were comfortable (32%) with how the consent process was handled for student pelvic EUAs; 31% were comfortable. In open-ended responses, respondents described a variety of experiences related to variability, discomfort, and authority. CONCLUSION: Non-consensual educational sensitive EUAs continue to take place in medical training across Canada, although practices of consent are highly variable. The majority of respondents reported being uncomfortable or unsure if they are comfortable with how consent for educational sensitive EUAs was practiced during their training, and some respondents struggled to express their discomfort given the power dynamics at play.

Identification of Pepper Leaf Diseases Based on TPSAO-AMWNet.

Pepper is a high-economic-value agricultural crop that faces diverse disease challenges such as blight and anthracnose. These diseases not only reduce the yield of pepper but, in severe cases, can also cause significant economic losses and threaten food security. The timely and accurate identification of pepper diseases is crucial. Image recognition technology plays a key role in this aspect by automating and efficiently identifying pepper diseases, helping agricultural workers to adopt and implement effective control strategies, alleviating the impact of diseases, and being of great importance for improving agricultural production efficiency and promoting sustainable agricultural development. In response to issues such as edge-blurring and the extraction of minute features in pepper disease image recognition, as well as the difficulty in determining the optimal learning rate during the training process of traditional pepper disease identification networks, a new pepper disease recognition model based on the TPSAO-AMWNet is proposed. First, an Adaptive Residual Pyramid Convolution (ARPC) structure combined with a Squeeze-and-Excitation (SE) module is proposed to solve the problem of edge-blurring by utilizing adaptivity and channel attention; secondly, to address the issue of micro-feature extraction, Minor Triplet Disease Focus Attention (MTDFA) is proposed to enhance the capture of local details of pepper leaf disease features while maintaining attention to global features, reducing interference from irrelevant regions; then, a mixed loss function combining Weighted Focal Loss and L2 regularization (WfrLoss) is introduced to refine the learning strategy during dataset processing, enhancing the model's performance and generalization capabilities while preventing overfitting. Subsequently, to tackle the challenge of determining the optimal learning rate, the tent particle snow ablation optimizer (TPSAO) is developed to accurately identify the most effective learning rate. The TPSAO-AMWNet model, trained on our custom datasets, is evaluated against other existing methods. The model attains an average accuracy of 93.52% and an F1 score of 93.15%, demonstrating robust effectiveness and practicality in classifying pepper diseases. These results also offer valuable insights for disease detection in various other crops.

Rapid detection of markers in green coffee beans with different primary processing treatments of Coffea arabica L. from Yunnan.

The characteristic flavor of Coffea arabica from Yunnan is largely attributed to the primary processing treatments through affecting the VOCs accumulation. Therefore, a rapid and comprehensive detection technique is needed to accurately recognize VOCs in green coffee beans with different pretreatment methods. Hence, we conducted volatile profiles and identified nine markers of three different primary processed green coffee beans from the major production areas in Yunnan with the combined of HS-SPME-GC-MS and PTR-TOF-MS. The relationships between the chemical composition and the content of VOCs in green coffee beans were elucidated. Among the markers, palmitic acid (F3), linoleic acid (F6), α-ethylidene phenylacetaldehyde (T4), and phytane (T8) contributed to the antioxidant activity of sun-exposed green coffee beans. In conclusion, the analytical technology presented here provided a general tool for an overall and rapid understanding of a detailed volatile profiles of green coffee beans in Yunnan.

Iron Overload-induced Ferroptosis as a Target for Protection against Obliterative Bronchiolitis after Orthotopic Tracheal Transplantation in Mice.

INTRODUCTION: The major complication of Obliterative Bronchiolitis (OB) is characterized by epithelial cell loss, fibrosis, and luminal occlusion of the terminal small airways, which limits the long-term survival of the recipient after lung transplantation. However, the underlying mechanisms are still not fully clarified. This research aims to investigate whether iron overload-induced ferroptosis is involved in OB development and provide a new target for OB prevention. MATERIALS AND METHODS: Allograft orthotopic tracheal transplantation in mice was applied in our study. Ferrostatin-1 and deferoxamine were administrated to inhibit ferroptosis and get rid of ferric iron, while iron dextran was used to induce an iron overload condition in the recipient. The histological examination, luminal occlusion rate, collagen deposition, iron level, ferroptosis marker (GPX4, PTGS2), and mitochondrial morphological changes of the graft were evaluated in mice. RESULTS: Our research indicated that ferroptosis and iron overload contribute to OB development, while ferroptosis inhibition and iron chelator could reverse the changes. Iron overload exacerbated OB development after orthotopic tracheal transplantation via promoting ferroptosis. CONCLUSION: Overall, this research demonstrated that iron overload-induced ferroptosis is involved in OB, which may be a potential therapeutic target for OB after lung transplantation.

Circ_0003945: an emerging biomarker and therapeutic target for human diseases.

Due to the rapid development of RNA sequencing techniques, a circular non-coding RNA (ncRNA) known as circular RNAs (circRNAs) has gradually come into focus. As a distinguished member of the circRNA family, circ_0003945 has garnered attention for its aberrant expression and biochemical functions in human diseases. Subsequent studies have revealed that circ_0003945 could regulate tumor cells proliferation, migration, invasion, apoptosis, autophagy, angiogenesis, drug resistance, and radio resistance through the molecular mechanism of competitive endogenous RNA (ceRNA) during tumorigenesis. The expression of circ_0003945 is frequently associated with some clinical parameters and implies a poorer prognosis in the majority of cancers. In non-malignant conditions, circ_0003945 also holds considerable importance in diseases pathogenesis. This review aims to recapitulate molecular mechanism of circ_0003945 and elucidates its potential as a diagnostic and therapeutic target in neoplasms and other diseases.

Targeting PKM2 signaling cascade with salvianic acid A normalizes tumor blood vessels to facilitate chemotherapeutic drug delivery.

Aberrant tumor blood vessels are prone to propel the malignant progression of tumors, and targeting abnormal metabolism of tumor endothelial cells emerges as a promising option to achieve vascular normalization and antagonize tumor progression. Herein, we demonstrated that salvianic acid A (SAA) played a pivotal role in contributing to vascular normalization in the tumor-bearing mice, thereby improving delivery and effectiveness of the chemotherapeutic agent. SAA was capable of inhibiting glycolysis and strengthening endothelial junctions in the human umbilical vein endothelial cells (HUVECs) exposed to hypoxia. Mechanistically, SAA was inclined to directly bind to the glycolytic enzyme PKM2, leading to a dramatic decrease in endothelial glycolysis. More importantly, SAA improved the endothelial integrity via activating the ß-Catenin/Claudin-5 signaling axis in a PKM2-dependent manner. Our findings suggest that SAA may serve as a potent agent for inducing tumor vascular normalization.

Self-Limiting Phase Transition Enabling Reversible Overstoichiometric Li Storage in Ni-Rich Cathodes.

Ni-rich cathodes are some of the most promising candidates for advanced lithium-ion batteries, but their available capacities have been stagnant due to the intrinsic Li+ storage sites. Extending the voltage window down can induce the phase transition from O3 to 1T of LiNiO2-derived cathodes to accommodate excess Li+ and dramatically increase the capacity. By setting the discharge cutoff voltage of LiNi0.6Co0.2Mn0.2O2 to 1.4 V, we can reach an extremely high capacity of 393 mAh g-1 and an energy density of 1070 Wh kg-1 here. However, the phase transition causes fast capacity decay and related structural evolution is rarely understood, hindering the utilization of this feature. We find that the overlithiated phase transition is self-limiting, which will transform into solid-solution reaction with cycling and make the cathode degradation slow down. This is attributed to the migration of abundant transition metal ions into lithium layers induced by the overlithiation, allowing the intercalation of overstoichiometric Li+ into the crystal without the O3 framework change. Based on this, the wide-potential cycling stability is further improved via a facile charge-discharge protocol. This work provides deep insight into the overstoichiometric Li+ storage behaviors in conventional layered cathodes and opens a new avenue toward high-energy batteries.

Brain tissue oxygen partial pressure monitoring and prognosis of patients with traumatic brain injury: a meta-analysis.

To assess whether monitoring brain tissue oxygen partial pressure (PbtO2) or employing intracranial pressure (ICP)/cerebral perfusion pressure (CCP)-guided management improves patient outcomes, including mortality, hospital length of stay (LOS), mean daily ICP and mean daily CCP during the intensive care unit(ICU)stay. We searched the Web of Science, EMBASE, PubMed, Cochrane Library, and MEDLINE databases until December 12, 2023. Prospective randomized controlled and cohort studies were included. A meta-analysis was performed for the primary outcome measure, mortality, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eleven studies with a total of 37,492 patients were included. The mortality in the group with PbtO2 was 29.0% (odds ratio: 0.73;95% confidence interval [CI]:0.56-0.96; P = 0.03; I = 55%), demonstrating a significant benefit. The overall hospital LOS was longer in the PbtO2 group than that in the ICP/CPP group (mean difference:2.03; 95% CI:1.03-3.02; P<0.0001; I = 39%). The mean daily ICP in the PbtO2 monitoring group was lower than that in the ICP/CPP group (mean difference:-1.93; 95% CI: -3.61 to -0.24; P = 0.03; I = 41%). Moreover, PbtO2 monitoring did not improve the mean daily CPP (mean difference:2.43; 95%CI: -1.39 to 6.25;P = 0.21; I = 56%).Compared with ICP/CPP monitoring, PbtO2 monitoring reduced the mortality and the mean daily ICP in patients with severe traumatic brain injury; however, no significant effect was noted on the mean daily CPP. In contrast, ICP/CPP monitoring alone was associated with a short hospital stay.

Emodin alleviates intestinal ischemia/reperfusion-induced lung injury by upregulating HO-1 expression via PI3K/AkT pathway.

BACKGROUND: Emodin, a natural anthraquinone derivative found in various Chinese medicinal herbs, has been proved to be an effective therapeutic agent in the treatment of many diseases. However, its effect on lung injury after intestinal ischemia/reperfusion injury remains unknown. This research was designed to investigate whether emodin protects against intestinal ischemia/reperfusion-induced lung injury and to elucidate the underlying molecular mechanisms in vivo and in vitro. METHODS: Intestinal ischemia/reperfusion injury was induced by occluding the superior mesenteric artery in mice, and mouse lung epithelial-12 cells were subjected to oxygen-glucose deprivation and reoxygenation to establish an in vitro model. RESULTS: Our data indicated that emodin treatment reduced intestinal ischemia/reperfusion-induced oxidative stress, inflammation and apoptosis in lung tissues and alleviated lung injury. However, the protective effects of emodin on intestinal ischemia/reperfusion-induced lung injury were reversed by the protein kinase B inhibitor triciribine or the heme oxygenase-1 inhibitor tin protoporphyrin IX. The protein kinase inhibitor triciribine also downregulated the expression of heme oxygenase-1. CONCLUSION: In conclusion, our data suggest that emodin treatment protects against intestinal ischemia/reperfusion-induced lung injury by enhancing heme oxygenase-1 expression via activation of the PI3K/protein kinase pathway. Emodin may act as a potential therapeutic agent for the prevention and treatment of lung injury induced by intestinal ischemia/reperfusion.

Profiling of carbonyl metabolic fingerprints in urine of Graves' disease patients based on atmospheric ionization mass spectrometry.

Graves' disease (GD) is considered among the organ autoimmune diseases and is somewhat linked to other autoimmune and secondary diseases. Commonly used detection methods rely on identifying characteristic clinical features and abnormal biochemical markers, but they have certain limitations and may be affected by patient medication. In this study, a desorption separation ionization (DSI) device coupled with a linear ion trap mass spectrometer is introduced for effective detection and screening of urine from GD patients. To enhance the sensitivity of MS analysis, derivatization reagent is utilized as a labeling method. The MS signal is used for metabolic profiling, through which differential metabolites and pathways are identified. Subsequently, processing the acquired spectra with a machine learning algorithm enables successful differentiation of GD patients and healthy individuals. This method is believed to provide versatile and powerful technical support for effective detection on the scene. Notably, this method offers the advantage of achieving early and rapid diagnosis of thyroid-related diseases.

Modelling the dynamic gas/particle partitioning process of semi-volatile organic compounds emitted from point sources: Quantitative analysis and impact assessment.

The deleterious impact of pollution point sources on the surrounding environment and human has long been a focal point of environmental research. When considering the local atmospheric dispersion of semi-volatile organic compounds (SVOCs) around the emission sites, it is essential to account the dynamic process for the gas/particle (G/P) partitioning, which involves the transition from an initial state to a steady state. In this study, we have developed a model that enables the prediction of the dynamic process for G/P partitioning of SVOCs, particularly considering the influence from emission. It is important to note that the dynamic processes of the concentrations of SVOCs in particle phase (CP) and in gas phase (CG) differ significantly. These differences arise due to the influence of two critical factors: particulate proportion of SVOCs in the emissions (ϕ0) and octanol-air partitioning coefficient (KOA). The validity of our model was assessed by comparing its predictions of the extremum value of the G/P partitioning quotient (KP) with the results obtained from the steady-state model. Remarkably, the characteristic time (tC), used to evaluate the timescale required for SVOCs to reach steady state, demonstrated different variations with KOA for CP and CG. Additionally, the values of tC were quite different for CP and CG, which were markedly influenced by ϕ0. For some SVOCs with high KOA values, it took approximately 35 h to reach steady state. Furthermore, it was found that the time to achieve 95 % of steady state (t95 ≈ 3tC) could reach approximately 105 h. This duration is sufficient for chemicals to disperse from their emission site to the surrounding areas. Therefore, it is crucial to consider the dynamic process of G/P partitioning in local atmospheric transport studies. Moreover, the influence of ϕ0 should be incorporated into future investigations examining the dynamic process of G/P partitioning.

Stranski-Krastanov Growth of Two-Dimensional Covalent Organic Framework Films.

Insights into the formation mechanisms of two-dimensional covalent organic frameworks (2D COFs) at both the in-plane and interlayer levels are essential for improving material quality and synthetic methodology. Here, we report the controllable preparation of 2D COF films via on-surface synthesis and investigate the growth mechanism using atomic force microscopy. Monolayer, bilayer, and layer-plus-island multilayer COF films were successfully constructed on hexagonal boron nitride in a controlled manner. The porphyrin-based COF films grow in the Stranski-Krastanov mode, i.e., a uniform bilayer COF film can be formed through layer-by-layer growth in the initial stage followed by island growth starting from the third layer. Furthermore, fluorescence quenching caused by π-π stacking interactions between 2D COF neighboring layers was revealed. These results provide new perspectives on the synthesis of high-quality 2D COF films with controllable thickness and morphology, paving the way for a diverse range of applications.

EHMT2-mediated transcriptional reprogramming drives neuroendocrine transformation in non-small cell lung cancer.

The transformation of lung adenocarcinoma to small cell lung cancer (SCLC) is a recognized resistance mechanism and a hindrance to therapies using epidermal growth factor receptor tyrosine kinase inhibitors (TKIs). The paucity of pretranslational/posttranslational clinical samples limits the deeper understanding of resistance mechanisms and the exploration of effective therapeutic strategies. Here, we developed preclinical neuroendocrine (NE) transformation models. Next, we identified a transcriptional reprogramming mechanism that drives resistance to erlotinib in NE transformation cell lines and cell-derived xenograft mice. We observed the enhanced expression of genes involved in the EHMT2 and WNT/ß-catenin pathways. In addition, we demonstrated that EHMT2 increases methylation of the SFRP1 promoter region to reduce SFRP1 expression, followed by activation of the WNT/ß-catenin pathway and TKI-mediated NE transformation. Notably, the similar expression alterations of EHMT2 and SFRP1 were observed in transformed SCLC samples obtained from clinical patients. Importantly, suppression of EHMT2 with selective inhibitors restored the sensitivity of NE transformation cell lines to erlotinib and delayed resistance in cell-derived xenograft mice. We identify a transcriptional reprogramming process in NE transformation and provide a potential therapeutic target for overcoming resistance to erlotinib.