Association between Pre-operative Body Mass Index and Surgical Infection in Perihilar Cholangiocarcinoma Patients Treated with Curative Resection: A Multi-center Study.

Background: The objective of this study was to investigate the association between pre-operative body mass index (BMI) and surgical infection in perihilar cholangiocarcinoma (pCCA) patients treated with curative resection. Methods: Consecutive pCCA patients were enrolled from four tertiary hospitals between 2008 and 2022. According to pre-operative BMI, the patients were divided into three groups: low BMI (≤18.4 kg/m2), normal BMI (18.5-24.9 kg/m2), and high BMI (≥25.0 kg/m2). The incidence of surgical infection among the three groups was compared. Multivariable logistic regression models were used to determine the independent risk factors associated with surgical infection. Results: A total of 371 patients were enrolled, including 283 patients (76.3%) in the normal BMI group, 30 patients (8.1%) in the low BMI group, and 58 patients (15.6%) in the high BMI group. The incidence of surgical infection was significantly higher in the patients in the low BMI and high BMI groups than in the normal BMI group. The multivariable logistic regression model showed that low BMI and high BMI were independently associated with the occurrence of surgical infection. Conclusions: The pCCA patients with a normal BMI treated with curative resection could have a lower risk of surgical infection than pCCA patients with an abnormal BMI.

Integration of single-cell and bulk RNA sequencing data reveals that CYTOR is a potential prognostic and immunotherapeutic response marker for skin cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is a highly malignant tumor that is prone to immune escape and distant metastasis. Immunotherapy is considered to be the best treatment for patients with SKCM. However, not all patients benefit from it. We observed a significant differential expression of the lncRNA CYTOR in patients with SKCM based on single-cell and bulk RNA sequencing data mining results. The results showed that compared to normal tissue lncRNA CYTOR expression was significantly upregulated in SKCM tissue. Subsequently, we validated this finding in clinical samples, and we also found that the expression of lncRNA CYTOR in SKCM was higher as it progressed. lncRNA CYTOR was differentially expressed in patients who responded to immunotherapy, suggesting that it may serve as a biomarker to predict the efficacy of SKCM immunotherapy. In-depth analysis revealed that lncRNA CYTOR expression was strongly correlated with immune cell infiltration, immune response, and immune checkpoint expression. Meanwhile, our experiments revealed that CYTOR affects SKCM cell invasion and clone formation and is associated with the activation of the EMT pathway. In summary, our findings illustrate, for the first time, the value of CYTOR as a potential prognostic and immunotherapeutic response marker in SKCM.

Tip60-FOXO regulates JNK signaling mediated apoptosis in Drosophila.

The JNK signaling pathway plays crucial roles in various physiological processes, including cell proliferation, differentiation, migration, apoptosis, and stress response. Dysregulation of this pathway is closely linked to the onset and progression of numerous major diseases, such as developmental defects and tumors. Identifying and characterizing novel components of the JNK signaling pathway to enhance and refine its network hold significant scientific and clinical importance for the prevention and treatment of associated cancers. This study utilized the model organism Drosophila and employed multidisciplinary approaches encompassing genetics, developmental biology, biochemistry, and molecular biology to investigate the interplay between Tip60 and the JNK signaling pathway, and elucidated its regulatory mechanisms. Our findings suggest that loss of Tip60 acetyltransferase activity results in JNK signaling pathway activation and subsequent induction of JNK-dependent apoptosis. Genetic epistasis analysis reveals that Tip60 acts downstream of JNK, paralleling with the transcription factor FOXO. The biochemical results confirm that Tip60 can bind to FOXO and acetylate it. Introduction of human Tip60 into Drosophila effectively mitigates apoptosis induced by JNK signaling activation, underscoring conserved regulatory role of Tip60 in the JNK signaling pathway from Drosophila to humans. This study further enhances our understanding of the regulatory network of the JNK signaling pathway. By revealing the role and mechanism of Tip60 in JNK-dependent apoptosis, it unveils new insights and potential therapeutic avenues for preventing and treating associated cancers.

Arsenic Trioxide Suppresses Angiogenesis in Non-small Cell Lung Cancer via the Nrf2-IL-33 Signaling Pathway.

BACKGROUND: Non-Small Cell Lung Cancer (NSCLC) ranks as a leading cause of cancer-related mortality, necessitating the urgent search for cost-effective and efficient anti-NSCLC drugs. Our preliminary research has demonstrated that arsenic trioxide (ATO) significantly inhibits NSCLC angiogenesis, exerting anti-tumor effects. In conjunction with existing literature reports, the Nrf2-IL-33 pathway is emerging as a novel mechanism in NSCLC angiogenesis. OBJECTIVE: This study aimed to elucidate whether ATO can inhibit NSCLC angiogenesis through the Nrf2-IL-33 pathway. METHODS: Immunohistochemistry was employed to assess the expression of Nrf2, IL-33, and CD31 in tumor tissues from patients with NSCLC. DETA-NONOate was used as a nitric oxide (NO) donor to mimic high levels of NO in the tumor microenvironment. Western blot, quantitative real-time PCR, and enzyme-linked immunosorbent assay were utilized to evaluate the expression of Nrf2 and IL-33 in the NCI-H1299 cell line. Subcutaneous xenograft models were established in nude mice by implanting NCI-H1299 cells to assess the anti-tumor efficacy of ATO. RESULTS: High expression levels of Nrf2 and IL-33 were observed in tumor samples from patients with NSCLC, and Nrf2 expression positively correlated with microvascular density in NSCLC. In vitro, NO (released from 1mM DETA-NONOate) promoted activation of the Nrf2-IL-33 signaling pathway in NCI-H1299 cells, which was reversed by ATO. Additionally, both Nrf2 deficiency and ATO treatment significantly attenuated NOinduced IL-33 expression. In vivo, both ATO and the Nrf2 inhibitor ML385 demonstrated significant inhibitory effects on angiogenesis tumor growth. CONCLUSION: Nrf2-IL-33 signaling is usually activated in NSCLC and positively correlates with tumor angiogenesis. ATO effectively disrupts the activation of the Nrf2-IL-33 pathway in NSCLC and thus inhibits angiogenesis, suggesting its potential as an anti-angiogenic agent for use in the treatment of NSCLC.

Gp93 inhibits unfolded protein response-mediated c-Jun N-terminal kinase activation and cell invasion.

In eukaryotes, Hsp90B1 serves as a vital chaperonin, facilitating the accurate folding of proteins. Interestingly, Hsp90B1 exhibits contrasting roles in the development of various types of cancers, although the underlying reasons for this duality remain enigmatic. Through the utilization of the Drosophila model, this study unveils the functional significance of Gp93, the Drosophila ortholog of Hsp90B1, which hitherto had limited reported developmental functions. Employing the Drosophila cell invasion model, we elucidated the pivotal role of Gp93 in regulating cell invasion and modulating c-Jun N-terminal kinase (JNK) activation. Furthermore, our investigation highlights the involvement of the unfolded protein response-associated IRE1/XBP1 pathway in governing Gp93 depletion-induced, JNK-dependent cell invasion. Collectively, these findings not only uncover a novel molecular function of Gp93 in Drosophila, but also underscore a significant consideration pertaining to the testing of Hsp90B1 inhibitors in cancer therapy.

Extracorporeal closed-loop respiratory regulation for patients with respiratory difficulty using a soft bionic robot.

OBJECTIVE: Respiratory regulation is critical for patients with respiratory dysfunction. Clinically used ventilators can lead to long-term dependence and injury. Extracorporeal assistance approaches such as iron-lung devices provide a noninvasive alternative, however, artificial actuator counterparts have not achieved marvelous biomimetic ventilation as human respiratory muscles. Here, we propose a bionic soft exoskeleton robot that can achieve extracorporeal closed-loop respiratory regulation by emulating natural human breath. METHODS: For inspiration, a soft vacuum chamber is actuated to produce negative thoracic pressure and thus expand lung volume by pulling the rib cage up and outward through use of external negative pressure. For expiration, a soft origami array under positive pressure pushes the abdominal muscles inward and the diaphragm upward. To achieve in vitro measurement of respiratory profile, we describe a wireless respiratory monitoring device to measure respiratory profiles with high accuracy, validated by quantitative comparisons with spirometer as gold-standard reference. By constructing a human-robot coupled respiratory mechanical model, a model-based proportional controller is designed for continuous tracking of the target respiratory profile. RESULTS: In experiments with ten healthy participants and ten patients with respiratory difficulty, the robot can adjust its assistive forces in real time and drive human-robot coupling respiratory system to track the target profile. CONCLUSION: The biomimetic robot can achieve extracorporeal closed-loop respiratory regulation for a diverse population. SIGNIFICANCE: The soft robot has important potential to assist respiration for people with respiratory difficulty, whether in a hospital or a home setting.

An Imidazo[1, 2-a]Pyridine Based Fluorescent Probe for the Continuous "on-off-on" Detection of Fe3+ and F.

An "on-off-on" fluorescent probe LK was synthesized from 2-benzoylpyridine and o-vanillin, which could sequentially detect Fe3+ and F- in DMSO/H2O solutions (v/v = 1/1, HEPES buffer, 1.0 mM, pH 7.0) with large Stokes shift (178 nm). LK exhibited not only high selectivity and sensitivity towards Fe3+ and F-, but also strong anti-interference ability to other ions. LK was coordinated with Fe3+ at a ratio of 2:1, with a binding constant (Ka) of 1.3 × 104 M- 1. The detection limits for Fe3+ and F- were 6.9 × 10- 8 M and 3.0 × 10- 7 M, respectively. Due to its excellent sensing performance, LK was successfully applied in actual water samples and test papers for the detection of Fe3+ and F-.

Long-term prognosis of patients with gallbladder carcinoma after curative-intent resection based on changes in the ratio of carbohydrate antigen 19-9 to total bilirubin (CA19-9/TB): a multicenter retrospective cohort study.

BACKGROUND: The prognostic value of carbohydrate antigen 19-9 (CA19-9) is known to be affected by elevated bilirubin levels in patients with gallbladder carcinoma (GBC). The clinical significance of changes in the ratio of CA19-9 levels to total bilirubin (TB) levels in patients with GBC after curative-intent resection remains unknown. The aim of this study was to determine the prognostic value of changes in preoperative and postoperative CA19-9/TB ratio in these patients. METHODS: Prospectively collected data on consecutive patients who underwent curative-intent resection for GBC between January 2015 and December 2020 stored in a multicenter database from 10 hospitals were analyzed in this retrospective cohort study. Based on the adjusted CA19-9 defined as the ratio of CA19-9 to TB, and using 2×10 3  U/µmol as the upper normal value, patients were divided into a normal group (with normal preoperative and postoperative adjusted CA19-9), a normalization group (with abnormal preoperative but normal postoperative adjusted CA19-9), and a non-normalization group (with abnormal postoperative adjusted CA19-9). The primary outcomes were overall survival (OS) and recurrence-free survival (RFS). The log-rank test was used to compare OS and RFS among the groups. The Cox regression model was used to determine factors independently associated with OS and RFS. RESULTS: The normal group ( n =179 patients) and the normalization group ( n =73 patients) had better OS and RFS than the non-normalization group ( n =65 patients) (the 3-year OS rates 72.0%, 58.4% and 24.2%, respectively; the RFS rates 54.5%, 25.5% and 11.8%, respectively; both P <0.001). There were no significant differences between the normal and the normalization groups in OS and RFS (OS, P =0.255; RFS, P =0.130). Cox regression analysis confirmed that the non-normalization group was independently associated with worse OS and RFS. Subgroup analysis revealed that the non-normalization group of patients who received adjuvant therapy had significantly improved OS and RFS as compared to those who did not receive adjuvant therapy (OS, P =0.025; RFS, P =0.003). CONCLUSIONS: Patients with GBC who underwent curative-intent surgical resection with postoperative abnormal levels of adjusted CA19-9 (the CA19-9/TB ratio) were associated with poorer long-term survival outcomes. Adjuvant therapy after surgery improved the long-term outcomes of these patients.

Mitochondrial complex I subunit MT-ND1 mutations affect disease progression.

Mitochondrial respiratory chain complex I is an important component of the oxidative respiratory chain, with the mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit 1 (MT-ND1) being one of the core subunits. MT-ND1 plays a role in the assembly of complex I and its enzymatic function. MT-ND1 gene mutation affects pathophysiological processes, such as interfering with the early assembly of complex I, affecting the ubiquinone binding domain and proton channel of complex I, and affecting oxidative phosphorylation, thus leading to the occurrence of diseases. The relationship between MT-ND1 gene mutation and disease has been has received increasing research attention. Therefore, this article reviews the impact of MT-ND1 mutations on disease progression, focusing on the impact of such mutations on diseases and their possible mechanisms, as well as the application of targeting MT-ND1 gene mutations in disease diagnosis and treatment. We aim to provide a new perspective leading to a more comprehensive understanding of the relationship between MT-ND1 gene mutations and diseases.

Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends.

Background: Anesthesiology plays a crucial role in perioperative care, critical care, and pain management, impacting patient experiences and clinical outcomes. However, our understanding of the anesthesiology research landscape is limited. Accordingly, we initiated a data-driven analysis through topic modeling to uncover research trends, enabling informed decision-making and fostering progress within the field. Methods: The easyPubMed R package was used to collect 32,300 PubMed abstracts spanning from 2000 to 2022. These abstracts were authored by 737 Anesthesiology Principal Investigators (PIs) who were recipients of National Institute of Health (NIH) funding from 2010 to 2022. Abstracts were preprocessed, vectorized, and analyzed with the state-of-the-art BERTopic algorithm to identify pillar topics and trending subtopics within anesthesiology research. Temporal trends were assessed using the Mann-Kendall test. Results: The publishing journals with most abstracts in this dataset were Anesthesia & Analgesia 1133, Anesthesiology 992, and Pain 671. Eight pillar topics were identified and categorized as basic or clinical sciences based on a hierarchical clustering analysis. Amongst the pillar topics, "Cells & Proteomics" had both the highest annual and total number of abstracts. Interestingly, there was an overall upward trend for all topics spanning the years 2000-2022. However, when focusing on the period from 2015 to 2022, topics "Cells & Proteomics" and "Pulmonology" exhibit a downward trajectory. Additionally, various subtopics were identified, with notable increasing trends in "Aneurysms", "Covid 19 Pandemic", and "Artificial intelligence & Machine Learning". Conclusion: Our work offers a comprehensive analysis of the anesthesiology research landscape by providing insights into pillar topics, and trending subtopics. These findings contribute to a better understanding of anesthesiology research and can guide future directions.

Selective degradation of PL2L60 by metabolic stresses­induced autophagy suppresses multi­cancer growth.

It has been reported that PL2L60 proteins, a product of PIWIL2 gene which might be activated by an intragenic promoter, could mediate a common pathway specifically for tumorigenesis. In the present study, it was further identified by using western blot assay that the PL2L60 proteins could be degraded in cancer cells through a mechanism of selective autophagy in response to oxidative stress. The PL2L60 was downregulated in various types of cancer cells under the hypoxic condition independently of HIF­1α, resulting in apoptosis of cancer cells. Inhibition of autophagy by small interfering RNA targeting of either Beclin­1 (BECN1) or Atg5 resulted in restoration of PL2L60 expression in hypoxic cancer cell. The hypoxic degradation of PL2L60 was also blocked by the attenuation of the autophagosome membrane protein Atg8/microtubule­associated protein 1 light chain 3 (LC3) or autophagy cargo protein p62 expression. Surprisingly, Immunofluorescence analysis demonstrated that LC3 could be directly bound to PL2L60 and was required for the transport of PL2L60 from the nucleus to the cytoplasm for lysosomal flux under basal or activated autophagy in cancer cells. Moreover, flow cytometric analysis displayed that knocking down of PL2L60 mRNA but not PIWIL2 mRNA effectively inhibited cancer cell proliferation and promoted apoptosis of cancer cells. The similar results were obtained from in vivo tumorigenic experiment, in which PL2L60 downregulation in necroptosis areas was confirmed by immunohistochemistry. These results suggested that various cancer could be suppressed by promoting autophagy. The present study revealed a key role of autophagic degradation of PL2L60 in hypoxia­induced cancer cell death, which could be used as a novel therapeutic target of cancer.

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Intra- and post-pandemic impact of the COVID-19 outbreak on Stanford Health Care.

Stanford Health Care, which provides about 7% of overall healthcare to approximately 9 million people in the San Francisco Bay Area, has undergone significant changes due to the opening of a second hospital in late 2019 and, more importantly, the COVID-19 pandemic. We examine the impact of these events on anatomic pathology (AP) cases, aiming to enhance operational efficiency in response to evolving healthcare demands. We extracted historical census, admission, lab tests, operation, and AP data since 2015. An approximately 45% increase in the volume of laboratory tests (P < 0.0001) and a 17% increase in AP cases (P < 0.0001) occurred post-pandemic. These increases were associated with progressively increasing (P < 0.0001) hospital census. Census increase stemmed from higher admission through the emergency department (ED), and longer lengths of stay mostly for transfer patients, likely due to the greater capability of the new ED and changes in regional and local practice patterns post-pandemic. Higher census led to overcapacity, which has an inverted U relationship that peaked at 103% capacity for AP cases and 114% capacity for laboratory tests. Overcapacity led to a lower capability to perform clinical activities, particularly those related to surgical procedures. We conclude by suggesting parameters for optimal operations in the post-pandemic era.

The application of the propensity score matching method in stock prediction among stocks within the same industry.

Stock price prediction is crucial in stock market research, yet existing models often overlook interdependencies among stocks in the same industry, treating them as independent entities. Recognizing and accounting for these interdependencies is essential for precise predictions. Propensity score matching (PSM), a statistical method for balancing individuals between groups and improving causal inferences, has not been extensively applied in stock interdependence investigations. Our study addresses this gap by introducing PSM to examine interdependence among pharmaceutical industry stocks for stock price prediction. Additionally, our research integrates Improved particle swarm optimization (IPSO) with long short-term memory (LSTM) networks to enhance parameter selection, improving overall predictive accuracy. The dataset includes price data for all pharmaceutical industry stocks in 2022, categorized into chemical pharmaceuticals, biopharmaceuticals, and traditional Chinese medicine. Using Stata, we identify significantly correlated stocks within each sub-industry through average treatment effect on the treated (ATT) values. Incorporating PSM, we match five target stocks per sub-industry with all stocks in their respective categories, merging target stock data with weighted data from non-target stocks for validation in the IPSO-LSTM model. Our findings demonstrate that including non-target stock data from the same sub-industry through PSM significantly improves predictive accuracy, highlighting its positive impact on stock price prediction. This study pioneers PSM's use in studying stock interdependence, conducts an in-depth exploration of effects within the pharmaceutical industry, and applies the IPSO optimization algorithm to enhance LSTM network performance, providing a fresh perspective on stock price prediction research.

L-Type Calcium Channel Modulates Low-Intensity Pulsed Ultrasound-Induced Excitation in Cultured Hippocampal Neurons.

As a noninvasive technique, ultrasound stimulation is known to modulate neuronal activity both in vitro and in vivo. The latest explanation of this phenomenon is that the acoustic wave can activate the ion channels and further impact the electrophysiological properties of targeted neurons. However, the underlying mechanism of low-intensity pulsed ultrasound (LIPUS)-induced neuro-modulation effects is still unclear. Here, we characterize the excitatory effects of LIPUS on spontaneous activity and the intracellular Ca2+ homeostasis in cultured hippocampal neurons. By whole-cell patch clamp recording, we found that 15 min of 1-MHz LIPUS boosts the frequency of both spontaneous action potentials and spontaneous excitatory synaptic currents (sEPSCs) and also increases the amplitude of sEPSCs in hippocampal neurons. This phenomenon lasts for > 10 min after LIPUS exposure. Together with Ca2+ imaging, we clarified that LIPUS increases the [Ca2+]cyto level by facilitating L-type Ca2+ channels (LTCCs). In addition, due to the [Ca2+]cyto elevation by LIPUS exposure, the Ca2+-dependent CaMKII-CREB pathway can be activated within 30 min to further regulate the gene transcription and protein expression. Our work suggests that LIPUS regulates neuronal activity in a Ca2+-dependent manner via LTCCs. This may also explain the multi-activation effects of LIPUS beyond neurons. LIPUS stimulation potentiates spontaneous neuronal activity by increasing Ca2+ influx.

Research Progress on the Geomechanical Properties of Block-in-Matrix Rocks.

The differences in geomechanical properties and the uncertainty in the spatial distribution of Bimrock pose significant challenges to the construction and disaster prediction of geotechnical engineering. To clarify the geomechanical characteristics of Bimrock, this paper summarizes the basic concepts and classification methods of Bimrock at home and abroad. It discusses the methods and characteristics of determining the geometric features of Bimrock blocks and explores the influencing factors and laws of failure modes and strength under different stress states of Bimrock. The study finds that the failure mode of Bimrock is mainly influenced by factors such as block proportion, degree of welding between blocks and matrix, strength ratio between blocks and matrix, and geometric properties of blocks. Among these factors, block proportion is the most significant, and the degree of welding is a controlling factor. However, due to the complexity of Bimrock structures, there is a lack of applicable methods and mechanical models for the evaluation of geomechanical characteristics of Bimrock in engineering practice. This article also explores the influence and research methods of the geological characteristics of Bimrock in slope and tunnel engineering and, finally, provides prospects for the future research trends relating to Bimrock.

Identification of transcription factor genes responsive to MeJA and characterization of a LaMYC2 transcription factor positively regulates lycorine biosynthesis in Lycoris aurea.

Jasmonates (JAs) are among the main phytohormones, regulating plant growth and development, stress responses, and secondary metabolism. As the major regulator of the JA signaling pathway, MYC2 also plays an important role in plant secondary metabolite synthesis and accumulation. In this study, we performed a comparative transcriptome analysis of Lycoris aurea seedlings subjected to methyl jasmonate (MeJA) at different treatment times. A total of 31,193 differentially expressed genes (DEGs) were identified by RNA sequencing. Among them, 732 differentially expressed transcription factors (TFs) comprising 51 TF families were characterized. The most abundant TF family was WRKY proteins (80), followed by AP2/ERF-EFR (67), MYB (59), bHLH (52), and NAC protein (49) families. Subsequently, by calculating the Pearson's correlation coefficient (PCC) between the expression level of TF DEGs and the lycorine contents, 41 potential TF genes (|PCC| >0.8) involved in lycorine accumulation were identified, including 36 positive regulators and 5 negative regulators. Moreover, a MeJA-inducible MYC2 gene (namely LaMYC2) was cloned on the basis of transcriptome sequencing. Bioinformatic analyses revealed that LaMYC2 proteins contain the bHLH-MYC_N domain and bHLH-AtAIB_like motif. LaMYC2 protein is localized in the cell nucleus, and can partly rescue the MYC2 mutant in Arabidopsis thaliana. LaMYC2 protein could interact with most LaJAZs (especially LaJAZ3 and LaJAZ4) identified previously. Transient overexpression of LaMYC2 increased lycorine contents in L. aurea petals, which might be associated with the activation of the transcript levels of tyrosine decarboxylase (TYDC) and phenylalanine ammonia lyase (PAL) genes. By isolating the 887-bp-length promoter fragment upstream of the start codon (ATG) of LaTYDC, we found several different types of E-box motifs (CANNTG) in the promoter of LaTYDC. Further study demonstrated that LaMYC2 was indeed able to bind the E-box (CACATG) present in the LaTYDC promoter, verifying that the pathway genes involved in lycorine biosynthesis could be regulated by LaMYC2, and that LaMYC2 has positive roles in the regulation of lycorine biosynthesis. These findings demonstrate that LaMYC2 is a positive regulator of lycorine biosynthesis and may facilitate further functional research of the LaMYC2 gene, especially its potential regulatory roles in Amaryllidaceae alkaloid accumulation in L. aurea.

A multi-objective optimization evaluation model for seismic performance of slopes reinforced by pile-anchor system.

The significance means of the seismic reinforcement effect of a pile-anchor system for slope reinforcement has been widely recognized. However, cases of deformation failure and instability sliding of the pile-anchor system itself and the reinforced slope under seismic action continue to be recorded. Therefore, it is crucial to evaluate the seismic performance of slopes reinforced by a pile-anchor system to prevent the system's failure. Current evaluation models of a slope reinforced by a pile-anchor system mainly focus on slope stability; however, the safety of the pile-anchor system itself is not sufficiently considered in these models. Consequently, in this study, we propose a multi-objective optimization evaluation (MOE) model for evaluating the seismic performance of slopes reinforced by a pile-anchor system that considers slope stability, safety of the pile-anchor system, and dynamic response of the slope. This model considers slope displacement, acceleration amplification factor of a slope, pile displacement, and anchor displacement as negative indexes, and anti-slide pile bending moment, shear force, and anchor axial force as intermediate indexes. The comprehensive weight of relevant indexes is obtained by combining subjective and objective weights, and the seismic reinforcement effect of the pile-anchor system is evaluated subsequently. In conclusion, the MOE model proposed in this study provides a novel solution for the optimization evaluation of a slope reinforced by a pile-anchor system in forthcoming projects.

Mechanistic regulation of FOXO transcription factors in the nucleus.

FOXO proteins represent evolutionarily conserved transcription factors (TFs) that play critical roles in responding to various physiological signals or pathological stimuli, either through transcription-dependent or -independent mechanisms. Dysfunction of these proteins have been implicated in numerous diseases, including cancer. Although the regulation of FOXO TFs shuttling between the cytoplasm and the nucleus has been extensively studied and reviewed, there's still a lack of a comprehensive review focusing on the intricate interactions between FOXO, DNA, and cofactors in the regulation of gene expression. In this review, we aim to summarize recent advances and provide a detailed understanding of the mechanism underlying FOXO proteins binding to target DNA. Additionally, we will discuss the challenges associated with pharmacological approaches in modulating FOXO function, and explore the dynamic association between TF, DNA, and RNA on chromatin. This review will contribute to a better understanding of mechanistic regulations of eukaryotic TFs within the nucleus.