Effects of saponins Rb1 and Re in American ginseng combined intervention on immune system of aging model.

Aging is a major risk factor for the development of many pathological processes, such as reduced immunity, cancer, cardiovascular diseases or neurodegenerative diseases, while age-related chronic diseases are the most common causes of death. This paper studies the effects of American ginseng saponin Rb1 and Re alone and combined intervention on the immune system of aging mouse models, by using 30 mg/kg Rb1, 15 mg/kg Re, and Rb1 + Re (30 mg/kg Rb1 and 15 mg/kg Re (co-intervention) was used to intervene in the aging model, and immune indicators such as thymus index, spleen index, interleukin and interferon were detected to evaluate the impact of Rb1 and Re on immune function. The results show that Rb1 and Re intervention alone can increase the spleen index by 7%-12% and the thymus index by 12%-19% in the aging model. After Rb1 or Re alone intervened, the apoptotic cells in the thymus were slightly reduced, and the proportion of apoptotic cells was reduced. The combination of Rb1 + Re can promote the thymus index and spleen index to increase by 23.40% and 25.5% respectively, which is more advantageous than Rb1 or Re alone. In addition, Rb1 and Re intervention can reduce the level of interferon INF to a level comparable to that of young mice. Rb1 + Re can not only reduce the INF content, but also reduce the TNF content. The above results show that American ginseng saponin Rb1 and Re can delay the decline of the immune system in the aging model, and the combined intervention of the two is significantly better than individual intervention in the recovery of the immune system. This paper can provide theoretical basis and data support for the development of American ginseng nutritional supplements and its application in aging groups products to improve immunity.

Short-term association of particulate matter and cardiovascular disease mortality in Shanghai, China between 2003 and 2020.

Objective: Evidence regarding the effects of particulate matter (PM) pollutants on cardiovascular disease (CVD) mortality remains limited in Shanghai, China. Our objective was to thoroughly evaluate associations between PM pollutants and CVD mortality. Methods: Daily data on CVD mortality, PM (PM10 and PM2.5) pollutants, and meteorological variables in Shanghai, China were gathered from 2003 to 2020. We utilized a time-series design with the generalized additive model to assess associations between PM pollutants and CVD mortality. Additionally, we conducted stratified analyses based on sex, age, education, and seasons using the same model. Results: We found that PM pollutants had a significant association with CVD mortality during the study period. Specifically, there was a 0.29% (95%CI: 0.14, 0.44) increase in CVD mortality for every 10 µg/m3 rise in a 2-day average (lag01) concentration of PM10. A 0.28% (95% CI: 0.07, 0.49) increase in CVD mortality was associated with every 10 µg/m3 rise in PM2.5 concentration at lag01. Overall, the estimated effects of PM10 and PM2.5 were larger in the warm period compared with the cold period. Furthermore, males and the older adult exhibited greater susceptibility to PM10 and PM2.5 exposure, and individuals with lower education levels experienced more significant effects from PM10 and PM2.5 than those with higher education levels. Conclusion: Our findings suggested that PM pollutants have a substantial impact on increasing CVD mortality in Shanghai, China. Moreover, the impacts of air pollution on health may be altered by factors such as season, sex, age, and educational levels.

The gut microbiome promotes locomotion of Drosophila larvae via octopamine signaling.

The gut microbiome is a key partner of animals, influencing various aspects of their physiology and behaviors. Among the diverse behaviors regulated by the gut microbiome, locomotion is vital for survival and reproduction, although the underlying mechanisms remain unclear. Here, we reveal that the gut microbiome modulates the locomotor behavior of Drosophila larvae via a specific neuronal type in the brain. The crawling speed of germ-free (GF) larvae was significantly reduced compared to the conventionally reared larvae, while feeding and excretion behaviors were unaffected. Recolonization with Acetobacter and Lactobacillus can fully and partially rescue the locomotor defects in GF larvae, respectively, probably due to the highest abundance of Acetobacter as a symbiotic bacterium in the larval gut, followed by Lactobacillus. Moreover, the gut microbiome promoted larval locomotion, not by nutrition, but rather by enhancing the brain levels of tyrosine decarboxylase 2 (Tdc2), which is an enzyme that synthesizes octopamine (OA). Overexpression of Tdc2 rescued locomotion ability in GF larvae. These findings together demonstrate that the gut microbiome specifically modulates larval locomotor behavior through the OA signaling pathway, revealing a new mechanism underlying larval locomotion regulated by the gut microbiome.

Mitigating Tetracycline antibiotic contamination in chicken manure using ex situ fermentation system.

Excessive use of tetracycline antibiotics in poultry farming results in significant concentrations of these drugs and tetracycline resistance genes (TRGs) in chicken manure, impacting both environmental and human health. Our research represents the first investigation into the removal dynamics of chlortetracycline (CTC) and TRGs in different layers of an ex situ fermentation system (EFS) for chicken waste treatment. By pinpointing and analyzing dominant TRGs-harboring bacteria and their interactions with environmental variables, we've closed an existing knowledge gap. Findings revealed that CTC's degradation half-lives spanned 3.3-5.8 days across different EFS layers, and TRG removal efficiency ranged between 86.82% and 99.52%. Network analysis highlighted Proteobacteria and Actinobacteria's essential roles in TRGs elimination, whereas Chloroflexi broadened the potential TRG hosts in the lower layer. Physical and chemical conditions within the EFS influenced microbial community diversity, subsequently impacting TRGs and integrons. Importantly, our study reports that the middle EFS layer exhibited superior performance in eliminating CTC and key TRGs (tetW, tetG, and tetX) as well as intI2. Our work transcends immediate health and environmental remediation by offering insights that encourage sustainable agriculture practices.

Integrated transcriptomic and proteomic analyses reveal the molecular mechanism underlying the thermotolerant response of Spodoptera frugiperda.

Spodoptera frugiperda (Lepidoptera: Noctuidae) is a highly destructive invasive pest with remarkable adaptability to extreme climatic conditions, posing a substantial global threat. Although the effects of temperature stress on the biological and ecological properties of S. frugiperda have been elucidated, the molecular mechanisms underlying its responses remain unclear. Herein, we combined transcriptomic and proteomic analyses to explore the key genes and proteins involved in thermotolerance regulation in S. frugiperda larvae at 42 °C. Overall, 1528 differentially expressed genes (DEGs) and 154 differentially expressed proteins (DEPs) were identified in S. frugiperda larvae under heat stress, including antioxidant enzymes, heat shock proteins (Hsps), cytochrome P450s, starch and sucrose metabolism genes, and insulin signaling pathway genes, indicating their involvement in heat tolerance regulation. Correlation analysis of DEGs and DEPs revealed that seven and eight had the same and opposite expression profiles, respectively. After nanocarrier-mediated RNA interference knockdown of SfHsp29, SfHsp20.4, SfCAT, and SfGST, the body weight and mortality of S. frugiperda larvae significantly decreased and increased under heat stress, respectively. This indicates that SfHsp29, SfHsp20.4, SfCAT, and SfGST play a crucial role in the thermotolerance of S. frugiperda larvae. These results provide insight into the mechanism of heat tolerance in S. frugiperda.

DNA Damage-Induced Apoptosis Suppressor Triggers Progression and Stemness of Glioma by Enhancing Lymphoid Enhancer-Binding Factor 1 Expression.

Background: DNA damage-induced apoptosis suppressor (DDIAS) has recently been discovered to induce cancer progression, but its functions and mechanisms in glioma have not been well studied. Methods: DDIAS expression in glioma tissues was analyzed by the Gene Expression Profiling Interactive Analysis server (GEPIA) and the Gene Expression database of Normal and Tumor tissue 2 (GENT2) databases. The role of DDIAS in glioma progression was studied by short hairpin RNA (shRNA) targeting DDIAS. The effects of DDIAS on glioma cell viability, cell proliferation, invasion, migration, and tumor sphere formation were determined by cell counting kit-8 (CCK-8), EdU, Transwell, tumor spheroid formation, extreme limiting dilution analysis assays in vitro and xenograft model construction in vivo. In addition, RNA sequencing and further functional experiments were used to analyze the DDIAS regulatory mechanism in glioma. Results: We found that DDIAS was highly expressed in glioma and that upregulated DDIAS indicated poor prognosis. Functionally, DDIAS knockdown inhibited glioma cell viability, cell proliferation, invasion and migration in vitro and tumor growth in vivo. In addition, lymphoid enhancer-binding factor 1 (LEF1) was identified as the downstream effector of DDIAS by RNA sequencing. DDIAS downregulation inhibited LEF1 mRNA and protein expression. The expression of DDIAS and LEF1 was positively correlated, and LEF1 overexpression rescued the inhibitory phenotype induced by DDIAS downregulation. We further showed that DDIAS downregulation inhibited cyclin A1, vimentin and the stemness-related factor CD133 and decreased the sphere formation capability, but these features were rescued by upregulation of LEF1. Conclusion: Taken together, these findings suggest that DDIAS promotes glioma progression and stemness by inducing LEF1 expression, proving that DDIAS may be a potential target for the treatment of glioma.

Regulating valence states of CuFe-PBA for the simultaneous electrochemical detection of Cd2+, Pb2+ and Hg2+ in food application.

Prussian blue analogues, as prospective electrode materials, play a crucial role in detecting heavy metal ions (HMIs), a process closely related to their electron transfer capacities and active surfaces. Here, etched copper-iron Prussian blue analogues (CuFe-PBA) are synthesized through a combination of flash nanoprecipitation (FNP) and an alkali etching process. Furthermore, this study investigates the impact of ammonia on the electronic structure of CuFe-PBA and its electrochemical detection capabilities for HMIs. The etched CuFe-PBA (e-CuFe-PBA) exhibits excellent detection performance for Cd2+, Pb2+ and Hg2+ with 17.6 µA µM-1, 24.2 µA µM-1 and 26.2 µA µM-1, respectively, due to the fact that the ammonia etching not only modulates the electronic properties of the surface of CuFe-PBA but also reduces the degree of agglomeration and enhances the accessible surface area. Additionally, it demonstrates excellent stability and resistance to interference, having been successfully applied to detect HMIs in food samples such as preserved eggs and apple juice. These results provide a new strategy for the use of Prussian blue analogues as electrochemical sensors for food safety applications.

Application of lecture-and-team-based learning in stomatology: in-class and online.

BACKGROUND: This study aimed to evaluate stomatological students' learning efficacy and their attitude towards Lecture-Team-Based Learning (LTBL) on topics regarding the design of removable partial dentures via in-class, online, and both in combination. METHODS: Students from seven distinct grades participated in the course in their fourth academic year (Years 2015, 2016, 2017, 2018, 2019, 2020, and 2021). Students of Years 2015-2019 attended in-class LTBL, students of Year 2020 attended online LTBL, and students of Year 2021 attended the combination mode. The scores of three examinations were compared, namely, individual readiness assessment test, team readiness assurance test, and individual application test. Visual Analog Scales (VAS) were used for students to self-assess their mastery of prosthodontics knowledge before and after the course. Anonymous questionnaires were delivered to evaluate their satisfaction with LTBL via a Likert scale. RESULTS: In each academic year, the three exam scores were significantly improved as the course progressed and VAS-post scores were significantly higher than VAS-pre scores. The three examination and VAS scores of students in Year 2020 were significantly lower than those in Years 2019 and 2021. Students were highly satisfied with the LTBL course based on the three parameters of knowledge acquisition, teamwork, and classroom atmosphere. CONCLUSION: Students were highly satisfied with the LTBL course and their learning performance was improved as the course progressed both in-class and online. Online LTBL could be adopted when students have to study online, while in-class LTBL could perform better when combined with video records of an online LTBL course.

MIHIC: a multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification.

Background: Immunohistochemistry (IHC) is a widely used laboratory technique for cancer diagnosis, which selectively binds specific antibodies to target proteins in tissue samples and then makes the bound proteins visible through chemical staining. Deep learning approaches have the potential to be employed in quantifying tumor immune micro-environment (TIME) in digitized IHC histological slides. However, it lacks of publicly available IHC datasets explicitly collected for the in-depth TIME analysis. Method: In this paper, a notable Multiplex IHC Histopathological Image Classification (MIHIC) dataset is created based on manual annotations by pathologists, which is publicly available for exploring deep learning models to quantify variables associated with the TIME in lung cancer. The MIHIC dataset comprises of totally 309,698 multiplex IHC stained histological image patches, encompassing seven distinct tissue types: Alveoli, Immune cells, Necrosis, Stroma, Tumor, Other and Background. By using the MIHIC dataset, we conduct a series of experiments that utilize both convolutional neural networks (CNNs) and transformer models to benchmark IHC stained histological image classifications. We finally quantify lung cancer immune microenvironment variables by using the top-performing model on tissue microarray (TMA) cores, which are subsequently used to predict patients' survival outcomes. Result: Experiments show that transformer models tend to provide slightly better performances than CNN models in histological image classifications, although both types of models provide the highest accuracy of 0.811 on the testing dataset in MIHIC. The automatically quantified TIME variables, which reflect proportions of immune cells over stroma and tumor over tissue core, show prognostic value for overall survival of lung cancer patients. Conclusion: To the best of our knowledge, MIHIC is the first publicly available lung cancer IHC histopathological dataset that includes images with 12 different IHC stains, meticulously annotated by multiple pathologists across 7 distinct categories. This dataset holds significant potential for researchers to explore novel techniques for quantifying the TIME and advancing our understanding of the interactions between the immune system and tumors.

Iron Complexes as Potential Carriers of Diffuse Interstellar Bands: The Photodissociation Spectrum of Fe+(H2O) at Optical Wavelengths.

The fullerene ion C60+ is the only carrier of diffuse interstellar bands (DIBs) identified so far. Transition-metal compounds feature electronic transitions in the visible and near-infrared regions, making them potential DIB carriers. Since iron is the most abundant transition metal in the cosmos, we here test this idea with Fe+(H2O). Laboratory spectra were obtained by photodissociation spectroscopy at 80 K. Spectra were modeled with the reflection principle. A high-resolution spectrum of the DIB standard star HD 183143 served as an observational reference. Two broad bands were observed from 4120 to 6800 Å. The 4120-4800 Å band has sharp features emerging from the background, which have the width of DIBs but do not match the band positions of the reference spectrum. Calculations show that the spectrum arises from a d-d transition at the iron center. While no match was found for Fe+(H2O) with known DIBs, the observation of structured bands with line widths typical for DIBs shows that small molecules or molecular ions containing iron are promising candidates for DIB carriers.

Prevalence and correlates of depression and anxiety symptoms among older adults in Shenzhen, China: a cross-sectional population-based study.

OBJECTIVES: To investigate the prevalence of depression and anxiety symptoms among older adults in an urban district in China, as well as their associated factors. DESIGN: Cross-sectional study. SETTING: General communities in Shenzhen, Guangdong, China. PARTICIPANTS: A total of 5372 community-dwelling older adults aged 65 years or older were initially recruited. Ultimately, 5331 participants met the inclusion criteria and were included in this study. METHODS: Participants completed a sociodemographic questionnaire, along with assessments including the Patient Health Questionnaire-9, Generalised Anxiety Scale-7, UCLA Loneliness Simplification Scale, Insomnia Severity Index Scale (ISI), Community Dementia Brief Screening Scale and the 8-item Dementia Screening Questionnaire. Statistical analyses included the Shapiro-Wilk test, independent t-test, Wilcoxon rank test, χ2 test and univariate and multivariate linear regression analysis. RESULTS: The prevalence of depression and anxiety symptoms among older adults in Shenzhen communities was 10.4% and 11.3%, respectively. In multivariate analysis, age (B=-0.01, p<0.05), relatively poor health status in the past year (B=1.00, p<0.01), poor health status in the past year (B=2.40, p<0.01), ISI score (B=0.21, p<0.01), -item Ascertain Dementia Questionnaire (AD8) score (B=0.22, p<0.01), UCLA Loneliness Scale (ULS) score (B=0.24, p<0.01) were significantly associated with the severity of depression symptom, Compared with their respective reference categories, relatively poor health status in the past year (B=0.50, p<0.01), poor health status in the past year (B=1.32, p<0.01), ISI score (B=0.23, p<0.01), sleep duration (B=0.05, p<0.01), AD8 score (B=0.21, p<0.01), Community Screening Instrument for Dementia score (B=0.13, p<0.01), ULS score (B=0.22, p<0.01) were significantly associated with the severity of anxiety symptom. CONCLUSIONS: We observed a high prevalence of depression and anxiety symptoms among older adults in this study. The existing welfare system and infrastructure should remain and targeted mental health programmes addressing the identified risk factors should be proposed.

The endoplasmic reticulum stress-related genes and molecular typing predicts prognosis and reveals characterization of tumor immune microenvironment in lung squamous cell carcinoma.

BACKGROUND: Endoplasmic reticulum stress (ERS) acts critical roles on cell growth, proliferation, and metastasis in various cancers. However, the relationship between ERs and lung squamous cell carcinoma (LUSC) prognoses still remains unclear. METHODS: The consensus clustering analysis of ERS-related genes and the differential expression analysis between clusters were investigated in LUSC based on TCGA database. Furthermore, ERS-related prognostic risk models were constructed by LASSO regression and Cox regression analyses. Then, the predictive effect of the risk model was evaluated by Kaplan-Meier, Cox regression, and ROC Curve analyses, as well as validated in the GEO cohort. According to the optimal threshold, patients with LUSC were divided into high- and low- risk groups, and somatic mutations, immune cell infiltration, chemotherapy response and immunotherapy effect were systematically analyzed. RESULTS: Two ERS-related clusters were identified in patients with LUSC that had distinct patterns of immune cell infiltration. A 5-genes ERS-related prognostic risk model and nomogram were constructed and validated. Kaplan-Meier curves and Cox regression analysis showed that ERS risk score was an independent prognostic factor (p < 0.001, HR = 1.317, 95% CI = 1.159-1.496). Patients with low-risk scores presented significantly lower TIDE scores and significantly lower IC50 values for common chemotherapy drugs such as cisplatin and gemcitabine. CONCLUSION: ERS-related risk signature has certain prognostic value and may be a potential therapeutic target and prognostic biomarker for LUSC patients.

Effects of Seipin on Mouse Mesenchymal Stem Cell Osteo-Adipogenic Balance.

Seipin deficiency is an important cause of type 2 Berardinelli-Seip congenital dyslipidemia (BSCL2). BSCL2 is a severe lipodystrophy syndrome with lack of adipose tissue, hepatic steatosis, insulin resistance, and normal or higher bone mineral density. Bone marrow mesenchymal stem cells (BMSCs) are believed to maintain bone and fat homeostasis by differentiating into osteoblasts and adipocytes. We aimed to explore the role of seipin in the osteogenic/adipogenic differentiation balance of BMSCs. Seipin loxP/loxP mice are used to explore metabolic disorders caused by seipin gene mutations. Compared with wild-type mice, subcutaneous fat deficiency and ectopic fat accumulation were higher in seipin knockout mice. Microcomputed tomography of the tibia revealed the increased bone content in seipin knockout mice. We generated seipin-deficient BMSCs in vitro and revealed that lipogenic genes are downregulated and osteogenic genes are upregulated in seipin-deficient BMSCs. In addition, peroxisome proliferator-activated receptor gamma (PPARγ) signaling is reduced in seipin-deficient BMSCs, while using the PPARγ activator increased the lipogenic differentiation and decreased osteogenic differentiation of seipin-deficient BMSCs. Our findings indicated that bone and lipid metabolism can be regulated by seipin through modulating the differentiation of mesenchymal stem cells. Thus, a new insight of seipin mutations in lipid metabolism disorders was revealed, providing a prospective strategy for MSC transplantation-based treatment of BSCL2.

Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study.

OBJECTIVES: To develop and validate a magnetic resonance imaging-based (MRI) deep multiple instance learning (D-MIL) model and combine it with clinical parameters for preoperative prediction of lymph node metastasis (LNM) in operable cervical cancer. METHODS: A total of 392 patients with cervical cancer were retrospectively enrolled. Clinical parameters were analysed by logistical regression to construct a clinical model (M1). A ResNet50 structure is applied to extract features at the instance level without using manual annotations about the tumour region and then construct a D-MIL model (M2). A hybrid model (M3) was constructed by M1 and M2 scores. The diagnostic performance of each model was evaluated by the area under the receiver operating characteristic curve (AUC) and compared using the Delong method. Disease-free survival (DFS) was evaluated by the Kaplan‒Meier method. RESULTS: SCC-Ag, maximum lymph node short diameter (LNmax), and tumour volume were found to be independent predictors of M1 model. For the diagnosis of LNM, the AUC of the training/internal/external cohort of M1 was 0.736/0.690/0.732, the AUC of the training/internal/external cohort of M2 was 0.757/0.714/0.765, and the AUC of the training/internal/external cohort of M3 was 0.838/0.764/0.835. M3 showed better performance than M1 and M2. Through the survival analysis, patients with higher hybrid model scores had a shorter time to reach DFS. CONCLUSION: The proposed hybrid model could be used as a personalised non-invasive tool, which is helpful for predicting LNM in operable cervical cancer. The score of the hybrid model could also reflect the DFS of operable cervical cancer. CRITICAL RELEVANCE STATEMENT: Lymph node metastasis is an important factor affecting the prognosis of cervical cancer. Preoperative prediction of lymph node status is helpful to make treatment decisions, improve prognosis, and prolong survival time. KEY POINTS: • The MRI-based deep-learning model can predict the LNM in operable cervical cancer. • The hybrid model has the highest diagnostic efficiency for the LNM prediction. • The score of the hybrid model can reflect the DFS of operable cervical cancer.

Achieving Bright and Long-Lived Aqueous Room-Temperature Phosphorescence of Carbon Nitrogen Dots Through In Situ Host-Guest Binding.

The development of bright and long-lived aqueous room-temperature phosphorescent (RTP) materials holds paramount importance in broadening the application scope of RTP material system. However, the conventional RTP materials usually exhibit low efficiency and short lifetime in aqueous solution. Herein, an in situ host-guest strategy is proposed to achieve cyanuric acid (CA)-derived phosphorescent carbon nitrogen dots (CNDs) composite (CNDs@CA) that demonstrates a significant enhancement of both quantum yield (QY) and lifetime mediated by water. Detailed investigations reveal that the robust hydrogen bonding networks between CNDs@CA and water effectively stabilize triplet excitons and suppress nonradiative decays, as well as facilitate efficient energy transfer from CA to CNDs, thereby prolonging the lifetime and enhancing the efficiency of RTP. The phosphorescent QY and lifetime of CNDs@CA can be increased to 26.89% (3.9-fold increase) and 951.25 ms (5.5-fold increase), respectively, with the incorporation of 50 wt% water under ambient conditions. Even in fully aqueous environments (with up to 400 wt% water added), CNDs@CA exhibits persistent water-boosted RTP properties, demonstrating exceptional stability. The robust water-boosted RTP property of CNDs@CA in aqueous solutions presents significant potential for high signal-to-noise ratio afterglow bioimaging as well as advanced information encryption.

Effect of neutrophil to lymphocyte ratio on prognosis of elderly patients with severe sepsis combined with diabetes mellitus.

BACKGROUND: To investigate the predictive value of neutrophil-to-lymphocyte ratio (NLR) in the short-term prognosis of elderly patients with severe sepsis combined with diabetes mellitus (DM). METHODS: The clinical data of 162 elderly patients with severe sepsis combined with DM from January 2018 to December 2022 were retrospectively collected. These patients were divided into a survival group (n = 104) and a death group (n = 58) according to 90-day prognosis. The number of neutrophils, lymphocytes, and NLR were compared. The optimal cut-off value for NLR to predict 90-day prognosis in elderly patients with severe sepsis combined with DM was determined using Receiver Operator Characteristic (ROC) curves, and the patients were divided into high and low NLR groups depending on the optimal cut-off value. The Kaplan-Meier method was used to plot the survival curves of the high and low NLR groups. Risk factors for the 90-day death in elderly patients with severe sepsis combined with DM were analyzed by a multivariate cox regression model. RESULTS: There were no significant differences in gender, age, history of hypertension and hyperlipidemia, intensive care unit (ICU) stay, duration of mechanical ventilation, and oxygenation index between the survival group and death group (p > 0.05). However, acute physiological and chronic health evaluation II (APACHE II) scores, and sepsis-related organ failure assessment (SOFA) scores were significantly lower in the survival group compared with the death group (p < 0.05). In the survival group, neutrophils counts and NLR were much lower than those in the death group, while lymphocytes counts were much higher (p < 0.05). ROC curves showed that the optimal cut-off value for NLR to predict 90-day mortality in elderly patients with severe sepsis combined with DM was 3.482. Patients were divided into high NLR and low NLR groups based on whether NLR was ≥ 3.482. In terms of the log-rank test results, patients in the low NLR group had a significantly higher 90-day survival rate than those in the high NLR group (Logrank χ2 = 8.635, p = 0.003). The multivariate cox regression model showed that the length of ICU stay longer than 15 days and NLR ≥ 3.482 were independent risk factors for 90-day prognosis in elderly patients with severe sepsis combined with DM. CONCLUSION: NLR ≥ 3.482 can be used to predict whether poor prognosis occurs in the short term after illness in elderly patients with severe sepsis combined with DM, and has good assessment value.

Study on the correlation between color and taste of beauty tea infusion and the pivotal contributing compounds based on UV-visible spectroscopy, taste equivalent quantification and metabolite analysis.

This study utilized a colorimeter to determine the color values of 23 beauty tea (BT) samples, the color and the taste characteristics were also quantitatively described through ultraviolet-visible (UV-Vis) spectroscopy and taste equivalent quantification. Furthermore, metabolomic analysis was conducted by using ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS). Correlation analysis was employed to preliminarily identify the compounds that contribute to the color and taste of BT infusion. Finally, the contributing compounds were further determined through verification experiment. The results showed that within a certain range, as the color of BT infusion deepened, the taste became stronger, more bitter and astringent, while on the contrary, it became sweeter and mellower. Theaflavins, kaempferol, astragalin, and 5-p-coumaroylquinic acid influenced both the color and taste of the BT infusion. Gallic acid was also determined as a contributor to the color. This study provides new insights into research on tea quality in infusion color and taste aspects.

ALDH3A1 upregulation inhibits neutrophils N2 polarization and halts oral cancer growth.

OBJECTIVES: Tumor-associated neutrophils (TANs) are among the most abundant inflammatory cells in tumor microenvironment (TME). Aldehyde dehydrogenase 3A1 (ALDH3A1) is significantly reduced in oral squamous cell carcinoma (OSCC), ALDH3A1 overexpression suppresses tumorigenesis by inhibiting inflammation. This study investigated the relationship and mechanisms underlying the crosstalk between ALDH3A1 and TANs in OSCC. MATERIALS AND METHODS: Immunohistochemistry and immunofluorescence were performed to investigate the abundance of TANs and the expression of ALDH3A1. dHL-60 were induced with tumor-conditioned media and recombinant IL-6/IL-8. The expression of key proteins in PI3K/AKT/NF-κB pathway were detected by RT-PCR and western blot. A xenograft model was utilized to examine the effect of ALDH3A1 on tumorigenicity and polarization of TANs. RESULTS: In patients with OSCC, TANs significantly increased and were associated with a worse prognosis. Additionally, ALDH3A1 negatively correlated with TANs infiltration and especially the N2 phenotype which was the prominent part in OSCC. Furthermore, our study demonstrated that tumor-derived IL-8 drives ALDH3A1-mediated TANs N2 polarization in the TME through PI3K/AKT/NF-κB pathway in vitro and in vivo. CONCLUSION: Our results indicate that TANs can serve as a prognostic biomarker and ALDH3A1 could be a promising therapeutic target for regulating TANs N2 polarization in antitumor therapy.

Helical-caging enables single-emitted large asymmetric full-color circularly polarized luminescence.

Colorful circularly polarized luminescence materials are desired for 3D displays, information security and asymmetric synthesis, in which single-emitted materials are ideal owing to self-absorption avoidance, evenly entire-visible-spectrum-covered photon emission and facile device fabrication. However, restricted by the synthesis of chiral broad-luminescent emitters, the realization and application of high-performing single-emitted full-color circularly polarized luminescence is in its infancy. Here, we disclose a single-emitted full-color circularly polarized luminescence system (spiral full-color emission generator), composed of whole-vis-spectrum emissive quantum dots and chiral liquid crystals. The system achieves a maximum luminescence dissymmetry factor of 0.8 and remains an order of 10-1 in visible region by tuning its photonic bandgap. We then expand it to a series of desired customized-color circularly polarized luminescence, build chiral devices and further demonstrate the working scenario in the photoinduced enantioselective polymerization. This work contributes to the design and synthesis of efficient chiroptical materials, device fabrication and photoinduced asymmetric synthesis.