Cytoplasmic Ca2+ influx mediates iron- and reactive oxygen species-dependent ferroptotic cell death in rice immunity.

Iron- and reactive oxygen species (ROS)-dependent ferroptosis occurs in plant cells. Ca2+ acts as a conserved key mediator to control plant immune responses. Here, we report a novel role of cytoplasmic Ca2+ influx regulating ferroptotic cell death in rice immunity using pharmacological approaches. High Ca2+ influx triggered iron-dependent ROS accumulation, lipid peroxidation, and subsequent hypersensitive response (HR) cell death in rice (Oryza sativa). During Magnaporthe oryzae infection, 14 different Ca2+ influx regulators altered Ca2+, ROS and Fe2+ accumulation, glutathione reductase (GR) expression, glutathione (GSH) depletion and lipid peroxidation, leading to ferroptotic cell death in rice. High Ca2+ levels inhibited the reduction of glutathione isulphide (GSSG) to GSH in vitro. Ca2+ chelation by ethylene glycol-bis (2-aminoethylether)-N, N, N', N'-tetra-acetic acid (EGTA) suppressed apoplastic Ca2+ influx in rice leaf sheaths during infection. Blocking apoplastic Ca2+ influx into the cytoplasm by Ca2+ chelation effectively suppressed Ca2+-mediated iron-dependent ROS accumulation and ferroptotic cell death. By contrast, acibenzolar-S-methyl (ASM), a plant defense activator, significantly enhanced Ca2+ influx, as well as ROS and iron accumulation to trigger ferroptotic cell death in rice. The cytoplasmic Ca2+ influx through calcium-permeable cation channels, including the putative resistosomes, could mediate iron- and ROS-dependent ferroptotic cell death under reduced GR expression levels in rice immune responses.

A Fusion Learning Model Based on Deep Learning for Single-Cell RNA Sequencing Data Clustering.

Single-cell RNA sequencing (scRNA-seq) technology provides a means for studying biology from a cellular perspective. The fundamental goal of scRNA-seq data analysis is to discriminate single-cell types using unsupervised clustering. Few single-cell clustering algorithms have taken into account both deep and surface information, despite the recent slew of suggestions. Consequently, this article constructs a fusion learning framework based on deep learning, namely scGASI. For learning a clustering similarity matrix, scGASI integrates data affinity recovery and deep feature embedding in a unified scheme based on various top feature sets. Next, scGASI learns the low-dimensional latent representation underlying the data using a graph autoencoder to mine the hidden information residing in the data. To efficiently merge the surface information from raw area and the deeper potential information from underlying area, we then construct a fusion learning model based on self-expression. scGASI uses this fusion learning model to learn the similarity matrix of an individual feature set as well as the clustering similarity matrix of all feature sets. Lastly, gene marker identification, visualization, and clustering are accomplished using the clustering similarity matrix. Extensive verification on actual data sets demonstrates that scGASI outperforms many widely used clustering techniques in terms of clustering accuracy.

Preparation of Chitosan Nanoparticles through a Readily Solvent-Exchange Process for Efficient and Enhanced Gene Delivery.

In view of the excellent prospects of gene therapy and the potential safety and immunogenicity issues challenged by viral vectors, it is of great significance to develop a nonviral vector with low toxicity and low cost. In this work, we report a chitosan nanoparticle (CSNP) to be used as a gene vector prepared through a facile solvent-exchange strategy. Chitosan is first dissolved in ionic liquid 1-ethyl-3-methylimidazolium acetate (EMIM Ac), and then, the solvent is exchanged with water/phosphate-buffered saline (PBS) to remove ionic liquid, forming a final CSNP dispersion after ultrasonication. The prepared CSNP shows a positive surface charge and can condense green fluorescent protein-encoding plasmid (pGFP) at weight ratios (CSNP/pGFP) of 5/1 or higher. Dynamic light scattering size and ζ-potential characterization and gel retardation results confirm the formation of CSNP/pGFP complexes. Compared with plain pGFP, efficient cellular internalization and significantly enhanced green fluorescent protein (GFP) expression are observed by using CSNP as a plasmid vector. Benefitting from the intrinsic biocompatibility, low cost, low immunogenicity, and abundant sources of chitosan, as well as the facile preparation and the efficient gene transfection capacity of CSNP, it is believed that this CSNP could be used as a nonviral gene vector with great clinical translational potentials.

Exploring functional metabolites and proteomics biomarkers in late-preterm and natural-born pigs.

Introduction: Pigs are often used to study the intestinal development of newborns, particularly as preterm pig models that mimic the intestinal growth of human preterm infants. Neonatology's study of delivery mode's impact on neonatal development is crucial. Methods: We established 14 newborn pigs delivered via cesarean sections (C-section, at 113 days of gestational age, CS group) and 8 naturally born pigs were used as controls (at 114 days of gestational age, NF group). The impact of two alternative delivery procedures (C-section and natural birth) on the levels of short-chain fatty acids (SCFAs) and organic acids in the hepatic and intestines of newborn pigs were compared using metabolomics. The underlying molecular pathways are examined at the "protein-metabolite" level by integrating proteomic data. Results: The findings demonstrated that the mode of delivery changed the metabolism of SCFAs in newborn pigs, perhaps by affecting the physiology levels of cyclic intermediates such as lactate and malate in the pyruvate metabolic pathway. Additionally, by participating in the fatty acid metabolism pathway, two distinct proteins (FASN and HSD17B4) may impact the physiological concentration of these tiny metabolites. Discussion: In conclusion, this study provided reliable animal model data for understanding the physiological SCFA metabolic information and its affecting mechanism of large-gestational age preterm infants.

Unraveling the dynamic transcriptomic changes during the dimorphic transition of Talaromyces marneffei through time-course analysis.

Introduction: Systemic dimorphic fungi pose a significant public health challenge, causing over one million new infections annually. The dimorphic transition between saprophytic mycelia and pathogenic yeasts is strongly associated with the pathogenesis of dimorphic fungi. However, despite the dynamic nature of dimorphic transition, the current omics studies focused on dimorphic transition primarily employ static strategies, partly due to the lack of suitable dynamic analytical methods. Methods: We conducted time-course transcriptional profiling during the dimorphic transition of Talaromyces marneffei, a model organism for thermally dimorphic fungi. To capture non-uniform and nonlinear transcriptional changes, we developed DyGAM-NS (dynamic optimized generalized additive model with natural cubic smoothing). The performance of DyGAM-NS was evaluated by comparison with seven other commonly used time-course analysis methods. Based on dimorphic transition induced genes (DTIGs) identified by DyGAM-NS, cluster analysis was utilized to discern distinct gene expression patterns throughout dimorphic transitions of T. marneffei. Simultaneously, a gene expression regulatory network was constructed to probe pivotal regulatory elements governing the dimorphic transitions. Results: By using DyGAM-NS, model, we identified 5,223 DTIGs of T. marneffei. Notably, the DyGAM-NS model showcases performance on par with or superior to other commonly used models, achieving the highest F1 score in our assessment. Moreover, the DyGAM-NS model also demonstrates potential in predicting gene expression levels throughout temporal processes. The cluster analysis of DTIGs suggests divergent gene expression patterns between mycelium-to-yeast and yeast-to-mycelium transitions, indicating the asymmetrical nature of two transition directions. Additionally, leveraging the identified DTIGs, we constructed a regulatory network for the dimorphic transition and identified two zinc finger-containing transcription factors that potentially regulate dimorphic transition in T. marneffei. Discussion: Our study elucidates the dynamic transcriptional profile changes during the dimorphic transition of T. marneffei. Furthermore, it offers a novel perspective for unraveling the underlying mechanisms of fungal dimorphism, emphasizing the importance of dynamic analytical methods in understanding complex biological processes.

Conditional survival of male breast cancer.

BACKGROUND: The incidence of male breast cancer has been increasing in recent years; however, the long-term survival outcomes of diagnosed patients remain uncertain. This study was designed to evaluate the conditional survival of male breast cancer patients and to predict the future survival of patients through the conditional nomogram, to provide important suggestions for clinical decision-making. METHODS: Retrospective data from the SEER database included 3600 male breast cancer patients, divided into training and validation groups (7 : 3 ratio). Overall survival rates were calculated using Kaplan-Meier analysis. Conditional survival analysis described survival at specific years. Time-dependent multivariate Cox analysis identified prognostic factors' impact. The conditional survival nomogram model predicted real-time survival rates. RESULTS: Over time, the 5-year real-time survival rate of patients gradually improved, increasing from 70.5 to 74.8, 79.4, 85.8, and 92.9% (respectively, representing 5-year survival rates of 1-4 years after diagnosis). In addition, the improvement in conditional survival rate CS5 showed a nonlinear trend. After 5 years of diagnosis, age, tumor size, and tumor stage had a sustained impact on patient prognosis. Finally, a conditional survival nomogram was constructed to predict the 10-year survival rate in real time. CONCLUSION: Five years after diagnosis, the conditional survival rate of male patients with breast cancer has improved, but it is not nonlinear. In the first 5 years after diagnosis, patients with older age, larger tumor size, poorer tumor stage, and distant metastasis should be actively followed up and treated to improve their long-term survival.

The abnormalities of lipid metabolism in children and adolescents with major depressive disorder and relationship with suicidal ideation and attempted suicide.

Background: Major depressive disorder (MDD) is a widespread health issue in many countries, which has an extremely negative impact on the health of children and adolescents in particular. In the context of depression and metabolic disorders, dyslipidemia and metabolism-related problems become more prominent comorbidities. However, they continue to be the main barrier to the successful recovery of the clinical progress. In this study we investigated the rate of dyslipidemia, additional risk factors among Chinese children and adolescents with MDD, and association of the suicidal behavior with lipid levels. Methods: The study took 756 people from the Third People's Hospital of Fuyang between January 2020 and December 2021, aged between 8 and 18, with major depressive disorders diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). We determined the FBG (fasting blood glucose) and lipid parameters in all subjects and also investigated the history of suicidal ideation, the cases of attempted suicide, and the scores of depressive symptoms. Sociodemographic and clinical data were gathered and analyzed using the SPSS-23.0 version. Results: The prevalence of hypercholesterolemia, hypertriglyceridemia, high LDL-C, and low HDL-C were 5.42 % (41/756), 10.58 % (80/756), 3.84 % (29/756) and 5.42 % (41/756) respectively. For hypercholesterolemia and hypertriglyceridemia, they were positive associated with suicidal ideation and suicide attempts, and the positive correlation is shown between low HDL-C levels and suicide attempts. Nevertheless, non-ideation and inversely suicidal attempts were not discovered among high-LDL-C subjects. Logistic analysis showed that high levels of FBG (OR = 2.86, 95 % CI: 1.31-6.25, P = 0.008) and worse LDL-C (OR = 357.82, 95 % CI: 66.16-1935.10, P < 0.001) are the independent associated factors for hypercholesterolemia. More hospitalizations (OR = 1.89, 95 % CI: 1.07-3.35, P = 0.028), obesity (OR = 2.55, 95 % CI: 1.25-5.18, P = 0.010), high levels of TC (OR = 2.15, 95 % CI: 1.03-4.48, P = 0.042), and higher doses of antidepressants (OR = 1.02, 95 % CI: 1.00-1.04, P = 0.029) were independently associated factors for hypertriglyceridemia, while high levels of HDL-C (OR = 0.11, 95 % CI: 0.04-0.31, P < 0.001) were protective factors. In addition, high levels of TC (OR = 113.94, 95 % CI: 20.01-648.85) were statistically different (P < 0.001) and suggested that the factor was significantly related to high LDL-C. Meanwhile, older age (OR = 1.25, 95 % CI: 1.02-1.52, P = 0.030) and high levels of TG (OR = 3.00, 95 % CI: 1.98-4.55, P < 0.001) were independent factors contributing to low HDL-C. Conclusion: The high prevalence of dyslipidemia in childhood and adolescence among children and adolescents with depressive disorder has become a public health issue. Hypercholesterolemia and hypertriglyceridemia showed a positive correlation with suicidal thoughts and suicidal attempts. Monitoring the incidence of suicidal thoughts and attempts among them would carry some predictor meaning in therapy and for jumping back to health.

Genomic analysis of Clostridium perfringens type D isolates from goat farms.

C. perfringens type D strains are the leading cause of enterotoxaemia in ruminants such as goats, sheep, and cattle. However, there has been no prior research on the genomic characteristics of C. perfringens type D strains from various regions in China. Here, we investigated the antibiotic resistance, genomic characteristics, and phylogenetic relationship of C. perfringens type D isolates recovered from goat farms in Shaanxi, Gansu, and Ningxia provinces. The antibiotic resistance test indicated that the isolates displayed high minimum inhibitory concentration (MIC) values to sulfafurazole, whereas the other antibiotics tested, such as penicillin, enrofloxacin, and florfenicol, worked well on them. Additionally, only tetracycline resistance genes [tetA(P) and tetB(P)] were identified from the isolates. A collective of 13 toxin genes, including etx and cpe were detected among the isolates. Sequence comparison revealed that the etx and cpe genes shared high sequence identities, and they could coexist on a pCW3-like plasmid, representing a potential risk to both animal breeding and public health. Phylogenetic analysis using core genome multi-locus sequence typing (cgMLST) and core genome single nucleotide polymorphisms (SNPs) revealed the close genetic relationship and potential regional/transregional transmission of the C. perfringens type D isolates in Shaanxi and Gansu provinces. Furthermore, pan-genomic analysis suggested the functional differences at the protein-coding gene level, although isolates from the same source shared a close genetic relationship. In conclusion, this study indicated the antibiotic resistance, virulence markers, potential transregional transmission, and genomic diversity of C. perfringens type D strains from various regions in China, which could provide references for the prevention of C. perfringens foodborne diseases and further research.

In Situ Quantitative Imaging of Plasma Membrane Stiffness in Live Cells Using a Genetically Encoded FRET Sensor.

Cell membrane stiffness is critical for cellular function, with cholesterol and sphingomyelin as pivot contributors. Current methods for measuring membrane stiffness are often invasive, ex situ, and slow in process, prompting the need for innovative techniques. Here, we present a fluorescence resonance energy transfer (FRET)-based protein sensor designed to address these challenges. The sensor consists of two fluorescent units targeting sphingomyelin and cholesterol, connected by a linker that responds to the proximity of these lipids. In rigid membranes, cholesterol and sphingomyelin are in close proximity, leading to an increased FRET signal. We utilized this sensor in combination with confocal microscopy to explore changes in plasma membrane stiffness under various conditions, including differences in osmotic pressure, the presence of reactive oxygen species (ROS) and variations in substrate stiffness. Furthermore, we explored the impact of SARS-CoV-2 on membrane stiffness and the distribution of ACE2 after attachment to the cell membrane. This tool offers substantial potential for future investigations in the field of mechanobiology.

Activating Macrophage Continual Efferocytosis via Microenvironment Biomimetic Short Fibers for Reversing Inflammation in Bone Repair.

Efferocytosis-mediated inflammatory reversal plays a crucial role in bone repairing process. However, in refractory bone defects, the macrophage continual efferocytosis may be suppressed due to the disrupted microenvironment homeostasis, particularly the loss of apoptotic signals and overactivation of intracellular oxidative stress. In this study, a polydopamine-coated short fiber matrix containing biomimetic "apoptotic signals" to reconstruct the microenvironment and reactivate macrophage continual efferocytosis for inflammatory reversal and bone defect repair is presented. The "apoptotic signals" (AM/CeO2) are prepared using CeO2 nanoenzymes with apoptotic neutrophil membrane coating for macrophage recognition and oxidative stress regulation. Additionally, a short fiber "biomimetic matrix" is utilized for loading AM/CeO2 signals via abundant adhesion sites involving π-π stacking and hydrogen bonding interactions. Ultimately, the implantable apoptosis-mimetic nanoenzyme/short-fiber matrixes (PFS@AM/CeO2), integrating apoptotic signals and biomimetic matrixes, are constructed to facilitate inflammatory reversal and reestablish the pro-efferocytosis microenvironment. In vitro and in vivo data indicate that the microenvironment biomimetic short fibers can activate macrophage continual efferocytosis, leading to the suppression of overactivated inflammation. The enhanced repair of rat femoral defect further demonstrates the osteogenic potential of the pro-efferocytosis strategy. It is believed that the regulation of macrophage efferocytosis through microenvironment biomimetic materials can provide a new perspective for tissue repair.

Zhibai dihuang pill (ZBDH) exhibits therapeutic effects on idiopathic central sexual precocity in rats by modulating the gut microflora.

To reveal the role of gut microbiota (GM) in the occurrence and development of idiopathic central precocious puberty (ICPP) using 16S rDNA sequencing and bioinformatics analysis. The Danazol-induced ICPP model was successfully constructed in this study. ZBDH and GnRHa treatments could effectively inhibit ICPP in rats, as manifested by the delayed vaginal opening time, reduced weight, decreased uterine organ coefficient, and decreased uterine wall thickness and corpus luteum number, as well as remarkably reduced serum hormone (LH, FSH, and E2) levels. According to 16S rDNA sequencing analysis results, there was no significant difference in the GM community diversity across different groups; however, the composition of the microbial community and the abundance of the dominant microbial community were dramatically different among groups. ZBDH and GnRHa treatments could effectively reduce the abundance of Muribaculateae and Lactobacillus and promote Prevotella abundance. ZBDH and GnRHa were effective in treating Danazol-induced ICPP model rats. The therapeutic effects of ZBDH and GnRHa could be related to the changes in GM in rats.

Comprehensive genomic characterization and expression analysis of calreticulin gene family in tomato.

Calreticulin (CRT) is a calcium-binding endoplasmic reticulum (ER) protein that has been identified for multiple cellular processes, including protein folding, regulation of gene expression, calcium (Ca2+) storage and signaling, regeneration, and stress responses. However, the lack of information about this protein family in tomato species highlights the importance of functional characterization. In the current study, 21 CRTs were identified in four tomato species using the most recent genomic data and performed comprehensive bioinformatics and SlCRT expression in various tissues and treatments. In the bioinformatics analysis, we described the physiochemical properties, phylogeny, subcellular positions, chromosomal location, promoter analysis, gene structure, motif distribution, protein structure and protein interaction. The phylogenetic analysis classified the CRTs into three groups, consensus with the gene architecture and conserved motif analyses. Protein structure analysis revealed that the calreticulin domain is highly conserved among different tomato species and phylogenetic groups. The cis-acting elements and protein interaction analysis indicate that CRTs are involved in various developmental and stress response mechanisms. The cultivated and wild tomato species exhibited similar gene mapping on chromosomes, and synteny analysis proposed that segmental duplication plays an important role in the evolution of the CRTs family with negative selection pressure. RNA-seq data analysis showed that SlCRTs were differentially expressed in different tissues, signifying the role of calreticulin genes in tomato growth and development. qRT-PCR expression profiling showed that all SlCRTs except SlCRT5 were upregulated under PEG (polyethylene glycol) induced drought stress and abscisic acid (ABA) treatment and SlCRT2 and SlCRT3 were upregulated under salt stress. Overall, the results of the study provide information for further investigation of the functional characterization of the CRT genes in tomato.

Advanced gallbladder cancer with high tumor mutation burden: a case report and literature review.

Background: Gallbladder cancer (GBC) is a common malignant tumor of the biliary system. It is characterised by insidious onset, rapid progression and poor prognosis. Symptoms often indicate advanced or late-stage disease, with a 5-year survival rate of only 5-15%. Case Description: We present a case study of a patient with GBC who had a tumor mutation burden (TMB) of 32.5/MB (≥10 muts/MB). The patient received mFOLFIRINOX as first-line chemotherapy, which demonstrated significant efficacy. After stabilizing the disease, a sequential chemotherapy regimen was chosen. This regimen combined the immune checkpoint inhibitor (ICI) toripalimab (JS001), a humanised IgG4 monoclonal antibody targeting programmed cell death protein 1 (PD-1), with S-1 therapy, an oral fluoropyrimidine derivative. However, this treatment did not provide any significant clinical benefit for the patient. Therefore, we hypothesise that combining immunotherapy with chemotherapy may be more effective as a first line treatment for high-TMB advanced GBC. This hypothesis needs to be validated in large-scale clinical studies. Conclusions: In summary, mFOLFIRINOX is a safe and effective first-line chemotherapy regimen for advanced GBC. The timing of combining immunotherapy with chemotherapy requires careful consideration. Further clinical trials involving immunotherapy in advanced GBC are necessary to identify biomarkers that can guide clinical decisions.

PSA: an effective method for predicting horizontal gene transfers through parsimonious phylogenetic networks.

Horizontal gene transfer (HGT) from one organism to another, according to some researchers, can be abundant in the evolution of species. A phylogenetic network is a network structure that describes the HGTs among species. Several studies have proposed methods to construct phylogenetic networks to predict HGTs based on parsimony values. Existing definitions of parsimony values for a phylogenetic network are based on the assumption that each gene site or segment evolves independently along different trees in the network. However, in the current study, we define a novel parsimony value, denoted the p definition, for phylogenetic networks, considering that a gene as a whole typically evolves along a tree. Using Simulated Annealing, a new method called the Phylogeny with Simulated Annealing (PSA) algorithm is proposed to search for an optimal network based on the p definition. The PSA method is tested on the simulated data. The results reveal that the parsimonious networks constructed using PSA can better represent the evolutionary relationships of species involving HGTs. Additionally, the HGTs predicted using PSA are more accurate than those predicted using other methods. The PSA algorithm is publicly accessible at http://github.com/imustu/sap.

Comparative effectiveness of multiple androgen receptor signaling inhibitor medicines with androgen deprivation therapy for metastatic hormone-sensitive prostate cancer: a study in the real world.

Background: The current treatment strategy for metastatic Hormone-Sensitive Prostate Cancer (mHSPC) is the combination of Androgen Receptor Signaling Inhibitors (ARSIs) medicines with androgen deprivation therapy (ADT). However, there is a lack of real-world data comparing the efficacy of different ARSI pharmaceuticals. Therefore, the objective of this study was to compare the effectiveness and safety of bicalutamide, abiraterone, enzalutamide, and apalutamide in combination with ADT for patients with mHSPC. Methods: We retrospectively analyzed 82 patients diagnosed with mHSPC, including 18 patients treated with abiraterone acetate with prednisone, 21 patients with enzalutamide, 20 patients with apalutamide, and 23 patients with bicalutamide. We evaluated PSA progression-free survival (PSA-PFS), imaging progression-free survival (r PFS), castration resistance progression-free survival (CRPC-PFS), and overall survival (OS) using Kaplan-Meier survival analyses. Additionally, we explored relevant factors affecting prognosis through univariate and multivariate Cox risk-proportionality models. PSA response rates at 3, 6, and 12 months, nadir PSA levels (nPSA), and time to nadir (TTN) in different medication subgroups after treatment were documented, and we used one-way ANOVA to determine the effect of these measures on patient prognosis. Results: In comparison with bicalutamide, both enzalutamide and apalutamide have shown significant advantages in delaying disease progression among mHSPC patients. Specifically, enzalutamide has been found to significantly prolong PSA-PFS (HR 2.244; 95% CI 1.366-3.685, p=0.001), rPFS (HR 2.539; 95% CI 1.181-5.461; p= 0.007), CRPC-PFS (HR 2.131; 95% CI 1.295-3.506; p= 0.003), and OS (HR 2.06; 95% CI 1.183-3.585; P=0.005). Similarly, apalutamide has significantly extended PSA-PFS (HR 5.071; 95% CI 1.711-15.032; P= 0.003) and CRPC-PFS (HR 6.724; 95% CI 1.976-22.878; P=0.002) among patients. On the other hand, the use of abiraterone in combination with ADT did not demonstrate a significant advantage in delaying diseases progression when compared with the other three agents in mHSPC patients. There were no significant differences in overall adverse event rates among the four pharmaceuticals in terms of safety. Additionally, the observation of PSA kinetics revealed that enzalutamide, apalutamide, and abiraterone acetate had a significant advantage in achieving deep PSA response (PSA ≤ 0.2 ng/ml) compared with bicalutamide (p=0.007 at 12 months). Enzalutamide and apalutamide exhibited preeminence efficacy, with no substantial difference observed between the two medications. Conclusions: Abiraterone, enzalutamide, and apalutamide were found to significantly reduce and stabilize PSA levels in mHSPC patients more quickly and thoroughly than bicalutamide. Furthermore, enzalutamide and apalutamide were found to significantly prolong survival and delay disease progression in mHSPC patients compared with bicalutamide. It should be noted that abiraterone did not demonstrate a significant advantage in delaying disease compared with enzalutamide and apalutamide. After conducting drug toxicity analyses, it was determined that there were no significant differences among the four drugs.

Blocking lncRNA HCG18 re-sensitizes Taxol resistant lung cancer cells to Taxol through modulating the miR-34a-5p/HDAC1 axis.

Lung cancer is one of the most frequently diagnosed cancers worldwide, associated with a poor survival rate. Taxol (Paclitaxel) is commonly used as a chemotherapeutic treatment for advanced lung cancers. While Taxol has improved clinical outcomes for lung cancer patients, a significant number of them develop resistance to Taxol, resulting in treatment failure. The role of the long noncoding RNA HCG18 in lung cancer and Taxol resistance has not yet been fully understood. To investigate this, we examined the expression of HCG18 and miR-34a-5p in lung tumors and normal lung tissues using qRT-PCR. We also assessed Taxol resistance through cell viability and apoptosis assays. Through the starBase online service, we analyzed the interactions between lncRNA and mRNA as well as miRNA and mRNA. We further validated the association between lncRNA and miRNA through luciferase and RNA pull-down assays. Our findings demonstrated that HCG18 was significantly upregulated in lung cancer tissues compared to normal lung tissues. Silencing HCG18 increased the sensitivity of lung cancer cells to Taxol. Additionally, our study established a Taxol-resistant cell line and observed a substantial upregulation of HCG18 in Taxol-resistant lung cancer cells. Bioinformatic analysis predicted that HCG18 could bind to miR-34a-5p, forming a competing endogenous RNA network, which was confirmed through luciferase assay. We found that miR-34a-5p was downregulated in lung cancer tissues and negatively correlated with Taxol resistance, as it directly bound to the 3'UTR region of HDAC1. Further results showed that inhibition of HCG18 significantly increased miR-34a-5p expression and sensitized lung cancer cells to Taxol. This sensitization could be reversed by inhibiting miR-34a-5p. Finally, we demonstrated in a xenograft mouse model that inhibition of HCG18 sensitized Taxol-resistant lung cancer cells to Taxol treatment by modulating the miR-34a-5p-HDAC1 axis. In conclusion, our in vitro and in vivo results uncover a novel molecular mechanism by which HCG18 promotes Taxol resistance through modulation of the miR-34a-5p/HDAC1 axis. These findings contribute to the diagnosis and treatment of chemo-resistant lung cancer.

The effect of the 13C abundance of soil microbial DNA on identifying labelled fractions after ultracentrifugation.

DNA-based stable isotope probing (DNA-SIP) technology has been widely employed to trace microbes assimilating target substrates. However, the fractions with labelled universal genes are sometimes difficult to distinguish when detected by quantitative real-time PCR. In this experiment, three paddy soils (AQ, CZ, and NB) were amended with 0.1% glucose containing 13C at six levels, and DNA was then extracted after a 7-day incubation and subjected to isopycnic gradient centrifugation. The results showed that the amount of labelled DNA was notably related to the 13C-glucose percentage, while the separation spans of 18S rRNA and 16S rRNA genes between labelled and unlabelled treatments became notably clearer when the δ13C values of the total DNA were 90.9, 61.6, and 38.9‰ and 256.2, 104.5 and 126.1‰ in the AQ, CZ, and NB soils, respectively. Moreover, fractionated DNA was also labelled by determining the δ13C values while adding only 5 atom% 13C-glucose to the soil. The results suggest that the optimal labelling fractions were not always those fractions with the maximal gene abundance, and detecting the δ13C values of the total and fractionated DNA was beneficial in estimating the results of DNA-SIP. KEY POINTS: • Appropriate 13C-DNA amount was needed for DNA-SIP. • Detecting the 13C ratio of fractionated DNA directly was an assistant method for identifying the labelled fractions. • Fractions with the maximal 18S or 16S rRNA gene abundance always were not labelled.

Mycotoxin contamination in organic and conventional cereal grain and products: A systematic literature review and meta-analysis.

There is still considerable controversy about the relative risk of mycotoxin exposure associated with the consumption of organic and conventional cereals. Using validated protocols, we carried out a systematic literature review and meta-analyses of data on the incidence and concentrations of mycotoxins produced by Fusarium, Claviceps, Penicillium, and Aspergillus species in organic and conventional cereal grains/products. The standard weighted meta-analysis of concentration data detected a significant effect of production system (organic vs. conventional) only for the Fusarium mycotoxins deoxynivalenol, with concentrations ∼50% higher in conventional than organic cereal grains/products (p < 0.0001). Weighted meta-analyses of incidence data and unweighted meta-analyses of concentration data also detected small, but significant effects of production system on the incidence and/or concentrations of T-2/HT-2 toxins, zearalenone, enniatin, beauvericin, ochratoxin A (OTA), and aflatoxins. Multilevel meta-analyses identified climatic conditions, cereal species, study type, and analytical methods used as important confounding factors for the effects of production system. Overall, results from this study suggest that (i) Fusarium mycotoxin contamination decreased between the 1990s and 2020, (ii) contamination levels are similar in organic and conventional cereals used for human consumption, and (iii) maintaining OTA concentrations below the maximum contamination levels (3.0 µg/kg) set by the EU remains a major challenge.

A Competing Risk Nomogram for Prediction of Prognosis in Patients With Primary Squamous Cell Thyroid Carcinoma.

Objective: Primary squamous cell thyroid carcinoma (PSCTC) is an extremely rare carcinoma, accounting for less than 1% of all thyroid carcinomas. However, the factors contributing to PSCTC outcomes remain unclear. This study aimed to identify the prognostic factors and develop a prognostic predictive model for patients with PSCTC. Methods: The analysis included patients diagnosed with thyroid carcinoma between 1975 and 2016 from the Surveillance, Epidemiology, and End Results database. Prognostic differences among the 5 pathological types of thyroid carcinomas were analyzed. To determine prognostic factors in PSCTC patients, the Cox regression model and Fine-Gray competing risk model were utilized. Based on the Fine-Gray competing risk model, a nomogram was established for predicting the prognosis of patients with PSCTC. Results: A total of 198,757 thyroid carcinoma patients, including 218 PSCTC patients, were identified. We found that PSCTC and anaplastic thyroid cancer had the worst prognosis among the 5 pathological types of thyroid carcinoma (P < .001). According to univariate and multivariate Cox regression analyses, age (71-95 years) was an independent risk factor for poorer overall survival and disease-specific survival in PSCTC patients. Using Fine-Gray regression analysis, the total number of in situ/malignant tumors for patient (Number 1) (≥2) was identified as an independent protective factor for prognosis of PSCTC. The area under the curve, the concordance index (C-index), calibration curves and decision curve analysis revealed that the nomogram was capable of predicting the prognosis of PSCTC patients accurately. Conclusion: The competing risk nomogram is highly accurate in predicting prognosis for patients with PSCTC, which may help clinicians to optimize individualized treatment decisions.