Association between Body Iron Status and Cognitive Task Performance in a Nationally Representative Sample of Older Adults.

Iron is an essential micronutrient that is necessary for proper cognitive function. However, the dose-response relationship between body iron status and cognitive function remains unclear. The objective of this study was to investigate the association between serum ferritin concentrations, an indicator of body iron status, and cognitive function in older adults. Based on the National Health and Nutrition Examination Survey (NHANES) 1999 -2002 in the United States, nationally representative data was collected from 2,567 adults aged 60 years and older who had objectively measured serum ferritin levels and cognitive performance. High ferritin levels were defined as a serum ferritin level >200 ng/mL in women and >300 ng/mL in men. Low ferritin levels were defined as a serum ferritin level <30 ng/mL. The digit symbol substitution test (DSST) was employed to assess cognitive function. Multivariable logistic regression analyses with survey weights were performed after the DSST was dichotomized at the median score. The weighted prevalence of adults with normal, low, and high serum ferritin levels were 73.98%, 9.12%, and 16.91%, respectively. A U-shaped association between serum ferritin concentrations and cognitive task performance was observed. After adjusting for demographic, socioeconomic, lifestyle, and C-reactive protein factors, the odds ratio (95% confidence intervals) for lower cognitive performance was 1.39 (1.11, 1.74) in adults with high ferritin levels and 1.38 (0.86, 2.22) in adults with low ferritin levels, compared with those with normal ferritin levels. The association between serum ferritin levels and lower cognitive performance was stronger in adults aged 60 to 69 years old than those aged 70 years and older. In conclusion, in a nationally representative sample of older adults in the United States, a high serum ferritin level was significantly associated with worse cognitive task performance. Thus, the relationship between low serum ferritin concentrations and cognitive task performance warrants further investigation.

Assessing Patterns of CGM use and Metrics of Glycemic Control in T1D and T2D Patients in the Veterans Healthcare System: Integrating CGM Device Data with EHR Data.

OBJECTIVE: To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for type 1 and type 2 diabetes patients in the Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. RESEARCH DESIGN AND METHODS: This observational study used Dexcom CGM device data linked with EHR (from 2015-2020) for a large national cohort of diabetes patients. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. RESULTS: The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged three weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 hours over nearly three years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. CONCLUSIONS: The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both type 1 and type 2 patients within the Veterans Affairs Healthcare System and is similar across major race/ethnicity and age groups.

Construction of cellulose-based hybrid hydrogel beads containing carbon dots and their high performance in the adsorption and detection of mercury ions in water.

Cellulose-based adsorbents have been extensively developed in heavy metal capture and wastewater treatment. However, most of the reported powder adsorbents suffer from the difficulties in recycling due to their small sizes and limitations in detecting the targets for the lack of sensitive sensor moieties in the structure. Accordingly, carbon dots (CDs) were proposed to be encapsulated in cellulosic hydrogel beads to realize the simultaneous detection and adsorption of Hg (II) in water due to their excellent fluorescence sensing performance. Besides, the molding of cellulose was beneficial to its recycling and further reduced the potential environmental risk generated by secondary pollution caused by adsorbent decomposition. In addition, the detection limit of the hydrogel beads towards Hg (II) reached as low as 8.8 × 10-8 M, which was below the mercury effluent standard declared by WHO, exhibiting excellent practicability in Hg (II) detection and water treatment. The maximum adsorption capacity of CB-50 % for Hg (II) was 290.70 mg/g. Moreover, the adsorbent materials also had preeminent stability that the hydrogel beads could maintain sensitive and selective sensing performance towards Hg (II) after 2 months of storage. Additionally, only 3.3% of the CDs leaked out after 2 weeks of immersion in water, ensuring the accuracy of Hg (II) evaluation. Notably, the adsorbent retained over 80% of its original adsorption capacity after five consecutive regeneration cycles, underscoring its robustness and potential for sustainable environmental applications.

Theoretical Insights into the Effect of Different Numbers of Thiophene Groups on Hydrogen Bond Interaction and Excited-State Intramolecular Proton-Transfer Process for Flavonoid Derivatives.

In this study, we systematically explored the impact of varying the number of thiophene groups on the hydrogen bond interaction and excited-state intramolecular proton-transfer (ESIPT) processes in flavonoid derivatives (STF, DTF, and TTF) using the density functional theory and time-dependent density functional theory methods. Initially, a thorough analysis of the optimized geometric structures revealed that the intramolecular hydrogen bond in the S1 state is enhanced and gradually weakened as the number of thiophene groups increases. To gain a deeper understanding of the hydrogen bond interaction, topological analysis, interaction region indicator scatter plots, and isosurface plots were employed. These images provide further insights that align with the structural analysis. Additionally, we observed a red-shift in the electronic spectra (absorption and fluorescence spectra), which is primarily attributed to the narrowing of the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, as elucidated by the frontier molecular orbitals. Furthermore, a combined analysis between the hole-electron distribution and the transition density matrix heat map shows that electron excitation involves the unidirectional charge-transfer mechanism. In the end, by conducting relaxed potential energy curve scans, we found that an increase in the number of thiophene groups elevates the energy barrier for ESIPT, making it more challenging for the reaction. In summary, our study underscores the vital effect of thiophene-substituted numbers in modulating the ESIPT process, which is able to provide valuable insights for the design and synthesis of desired organic fluorescent probes in the future.

Revealing mechanism of phenol-amine reaction to form humus in compost based on high-resolution liquid chromatography mass spectrometry and spectroscopy.

Humus is the stable form of carbon storage in straw compost. The phenol-amine reaction is a pathway for humus formation in straw compost. In this study, two reaction systems, GP group (pyrogallol and glycine) and GCP group (catechol, pyrogallol, and glycine), were constructed in a simulated composting environment and revealed the molecular binding mechanism of the phenol-amine reaction through spectroscopy and mass spectrometry. The results showed that phenolic self-polymerization was faster than phenol-amine reaction. Therefore, the aromatization degree of GP was 27.14 % higher than that of GCP. The phenol-amine reaction first produced fulvic acid, and then formed humus units rich in active functional group structures (i.e., phenolic hydroxyl and carboxyl groups). These units further captured small molecule compounds to form humic acid eventually. This study would provide theoretical support for exploring the humus formation process and the promotion of straw humification by adding phenol or amino acids to compost.

The effect of liver metastases on clinical efficacy of first-line programmed death-1 inhibitor plus chemotherapy in esophageal squamous cell carcinoma: A post hoc analysis of ASTRUM-007 and meta-analysis.

OBJECTIVE: To explore the efficacy of serplulimab plus chemotherapy in esophageal squamous cell carcinoma (ESCC) patients with liver metastases. METHODS: A post hoc exploratory analysis of ASTRUM-007 study was performed, focusing on the association between the liver metastases status and the clinical outcomes. A systematic literature search of electronic databases was conducted to identify eligible randomized controlled trials for the meta-analysis. Study-level pooled analyses of hazard ratios (HRs) for PFS according to liver metastases were performed. RESULTS: The post hoc analysis of ASTRUM-007 showed that although patients with liver metastases had a worse prognosis comparing with the non-liver metastases patients in both treatment arms (serplulimab plus chemotherapy arm: median PFS, 5.7 vs. 6.6 months, HR 1.57 [95% CI, 1.15-2.13]; median OS, 13.7 vs. 15.3 months, HR 1.48 [95% CI, 1.09-1.98]; placebo plus chemotherapy arm: median PFS, 4.3 vs. 5.5 months, HR 1.58 [95% CI, 1.01-2.39]; median OS, 10.3 vs. 11.2 months, HR 1.32 [95% CI, 0.84-2.00]), OS and PFS benefits derived from serplulimab plus chemotherapy versus placebo plus chemotherapy in this study were observed in both patients with liver metastases (HR of PFS: 0.60; 95% CI, 0.37-0.97; HR of OS: 0.68; 95% CI, 0.43-1.11) and the non-liver metastases patients (HR of PFS: 0.62; 95% CI, 0.49-0.80; HR of OS: 0.69; 95% CI, 0.55-0.87) with similar magnitude. Three randomized controlled trials were included in the meta-analysis. Pooled HRs demonstrated that the addition of anti-PD-1 antibodies significantly improved PFS compared to chemotherapy alone regardless of liver metastases status. CONCLUSIONS: This study reveals that the presence of liver metastases is a poor prognostic factor but does not affect the improvements in both PFS and OS brought by adding PD-1 blockade to chemotherapy in ESCC patients. Predictive biomarkers for survival in these patients warrant further investigation.

Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method.

Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using 'off-the-shelf' products, such as allogeneic CAR natural killer T (AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced AlloCAR-NKT cells with high yield and purity. We generated AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of AlloCAR-NKT cells support their potential for clinical translation.

Construction and validation of "WCH-nomogram" for predicting the prognosis after resection of colorectal liver metastases.

BACKGROUND: The prognostic predictive tool for patients with colorectal liver metastasis (CRLM) is limited and the criteria for administering preoperative neoadjuvant chemotherapy in CRLM patients remain controversial. METHODS: This study enrolled 532 CRLM patients at West China Hospital (WCH) from January 2009 to December 2019. Prognostic factors were identified from the training cohort to construct a WCH-nomogram and evaluating accuracy in the validation cohort. Receiver operating characteristic (ROC) curve analysis was used to compare the prediction accuracy with other existing prediction tools. RESULTS: From the analysis of the training cohort, four independent prognostic risk factors, namely tumor marker score, KRAS mutation, primary lymph node metastasis, and tumor burden score were identified on which a WCH-nomogram was constructed. The C-index of the two cohorts were 0.674 (95% CI: 0.634-0.713) and 0.655 (95% CI: 0.586-0.723), respectively, which was better than the previously reported predication scores (CRS, m-CS and GAME score). ROC curves showed AUCs for predicting 1-, 3-, and 5-year overall survival (OS) of 0.758, 0.709, and 0.717 in the training cohort, and 0.860, 0.669, and 0.692 in the validation cohort, respectively. A cutoff value of 114.5 points was obtained for the WCH-nomogram total score based on the maximum Youden index of the ROC curve of 5-year OS. Risk stratification showed significantly better prognosis in the low-risk group, however, the high-risk group was more likely to benefit from neoadjuvant chemotherapy. CONCLUSIONS: The WCH-nomogram demonstrates superior prognostic stratification compared to prior scoring systems, effectively identifying CRLM patients who may benefit the most from neoadjuvant chemotherapy.

Efficacy of acupuncture for a cough-related symptom cluster in patients with lung cancer: A randomized controlled trial.

PURPOSE: This study was designed to evaluate the effect of acupuncture on cough, expectoration, and shortness of breath in lung cancer patients. METHODS: Between December 2021 and June 2022, a total of 130 lung cancer patients were recruited, and they were split into control and intervention groups at random. Routine nursing was provided to the control group, whereas routine nursing with acupuncture using LU7 (Lie Que), LU9 (Tai Yuan), BL13 (Fei Shu), and BL20 (Pi Shu) was administered to the intervention group for 7 days. The severity of cough, expectoration, and shortness of breath was assessed 1 day before and after the interventions using the lung cancer-specific module of the MDASI. A two-way ANOVA was performed for group comparisons. RESULTS: Compared with the control group, the symptoms of cough in the intervention group were significantly improved (F = 5.095, MD = -0.32, 95% CI, -0.59 to 0.04, P = 0.025), while expectoration (F = 0.626, MD = -0.11, 95% CI, -0.38 to 0.16, P = 0.430) and shortness of breath (F = 0.165, MD = -0.05, 95% CI, -0.27 to 0.18, P = 0.685) had no significant change. Cough also identified an obvious interaction effect (P = 0.014), and the post-intervention simple main effect test demonstrated a tangible difference between the two groups (MD = -0.66, 95% CI, -0.99 to 0.33, P < 0.001) post-intervention. CONCLUSIONS: Acupuncture using LU7, LU9, BL13, and BL20 can relieve the cough of lung cancer patients, but not relieve expectoration and shortness of breath.

USFM: A universal ultrasound foundation model generalized to tasks and organs towards label efficient image analysis.

Inadequate generality across different organs and tasks constrains the application of ultrasound (US) image analysis methods in smart healthcare. Building a universal US foundation model holds the potential to address these issues. Nevertheless, the development of such foundation models encounters intrinsic challenges in US analysis, i.e., insufficient databases, low quality, and ineffective features. In this paper, we present a universal US foundation model, named USFM, generalized to diverse tasks and organs towards label efficient US image analysis. First, a large-scale Multi-organ, Multi-center, and Multi-device US database was built, comprehensively containing over two million US images. Organ-balanced sampling was employed for unbiased learning. Then, USFM is self-supervised pre-trained on the sufficient US database. To extract the effective features from low-quality US images, we proposed a spatial-frequency dual masked image modeling method. A productive spatial noise addition-recovery approach was designed to learn meaningful US information robustly, while a novel frequency band-stop masking learning approach was also employed to extract complex, implicit grayscale distribution and textural variations. Extensive experiments were conducted on the various tasks of segmentation, classification, and image enhancement from diverse organs and diseases. Comparisons with representative US image analysis models illustrate the universality and effectiveness of USFM. The label efficiency experiments suggest the USFM obtains robust performance with only 20% annotation, laying the groundwork for the rapid development of US models in clinical practices.

AI-2 quorum sensing signal disrupts coral symbiotic homeostasis and induces host bleaching.

Symbiotic microorganisms play critical ecophysiological roles that facilitate the maintenance of coral health. Currently, information on the gene and protein pathways contributing to bleaching responses is lacking, including the role of autoinducers. Although the autoinducer AI-1 is well understood, information on AI-2 is insufficient. Here, we observed a 3.7-4.0 times higher abundance of the AI-2 synthesis gene luxS in bleached individuals relative to their healthy counterparts among reef-building coral samples from the natural environment. Laboratory tests further revealed that AI-2 contributed significantly to an increase in coral bleaching, altered the ratio of potential probiotic and pathogenic bacteria, and suppressed the antiviral activity of specific pathogenic bacteria while enhancing their functional potential, such as energy metabolism, chemotaxis, biofilm formation and virulence release. Structural equation modeling indicated that AI-2 influences the microbial composition, network structure, and pathogenic features, which collectively contribute to the coral bleaching status. Collectively, our results offer novel potential strategies for coral conservation based on a signal manipulation approach.

Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold.

Out-of-distribution (OOD) detection is crucial for enhancing the reliability of machine learning models when confronted with data that differ from their training distribution. In the image domain, we hypothesize that images inhabit manifolds defined by latent properties such as color, position, and shape. Leveraging this intuition, we propose a novel approach to OOD detection using a diffusion model to discern images that deviate from the in-domain distribution. Our method involves training a diffusion model using in-domain images. At inference time, we lift an image from its original manifold using a masking process, and then apply a diffusion model to map it towards the in-domain manifold. We measure the distance between the original and mapped images, and identify those with a large distance as OOD. Our experiments encompass comprehensive evaluation across various datasets characterized by differences in color, semantics, and resolution. Our method demonstrates strong and consistent performance in detecting OOD images across the tested datasets, highlighting its effectiveness in handling images with diverse characteristics. Additionally, ablation studies confirm the significant contribution of each component in our framework to the overall performance.

Cellulose-based adsorbent using in mercury detection and removal from water via an efficient grafting strategy of fluorometric sensors by click reaction.

Mercury pollution in waters attracts lots of attention due to its serious toxicity and high bioenrichment and many efforts have been devoted in the development of adsorbents for mercury detection and removal. Herein, a cellulose-based adsorbent Cell-TriA-HQ is functionalized with quinoline fluorophore by covalent immobilization through "Click reaction" with high yield. In addition to the admirable adsorptive performance, the prepared adsorbent exhibits excellent selectivity and sensitivity towards Hg (II) in water that the detection limit for Hg (II) is determined to be as low as 1.92 × 10-7 M. The sensitive fluorescence enhancement response is considered to be resulted from the inhibition of photo-induced electron transfer between triazole and quinoline groups and the reinforcement of structural rigidity. The easy manipulation along with excellent performance of adsorption capacity, detective ability and reusability for the multifunctional adsorbent makes it potential in mercury monitoring and removal from aqueous solutions in the field of water treatment.

Exosomes derived from HUVECs alleviate ischemia-reperfusion induced inflammation in neural cells by upregulating KLF14 expression.

Neuroinflammation plays a key role in the progression of secondary brain injury after ischemic stroke, and exosomes have been increasingly recognized to eliminate inflammatory responses through various mechanisms. This study aimed to explore the effect and possible mechanism of human umbilical vein endothelial cells derived exosomes (H-EXOs) on neuroinflammation. We established a transient middle cerebral artery occlusion/reperfusion (tMCAO/R) in male rats and oxygen-glucose-deprivation/reoxygenation (OGD/R) model in cultured neurons to mimic secondary brain injury after ischemic stroke in vivo. H-EXOs were administered at the same time of reperfusion. Results showed that the production of pro-inflammatory cytokines TNF-α, IL-1ß, and IL-6, and the transcription factor Krüppel-like factor 14 (KLF14) were significantly increased both in rat brain tissue and cultured neural cells after ischemic-reperfusion (I/R) injury. H-EXOs treatment significantly improved the cultured cell viability, reduced infarct sizes, mitigated neurobehavioral defects, and alleviated the expression of pro-inflammatory cytokines compared with the control group, indicating that H-EXOs exerted anti-inflammatory effect against I/R injury. Further studies revealed that the anti-inflammatory effect of H-EXOs could be weakened by small-interfering RNA (siKLF4) transfection. KLF14 was a protective factor produced during cerebral ischemia-reperfusion injury. In conclusion, H-EXOs protect neurons from inflammation after I/R injury by enhancing KLF14 expression.

PSAEEGNet: pyramid squeeze attention mechanism-based CNN for single-trial EEG classification in RSVP task.

Introduction: Accurate classification of single-trial electroencephalogram (EEG) is crucial for EEG-based target image recognition in rapid serial visual presentation (RSVP) tasks. P300 is an important component of a single-trial EEG for RSVP tasks. However, single-trial EEG are usually characterized by low signal-to-noise ratio and limited sample sizes. Methods: Given these challenges, it is necessary to optimize existing convolutional neural networks (CNNs) to improve the performance of P300 classification. The proposed CNN model called PSAEEGNet, integrates standard convolutional layers, pyramid squeeze attention (PSA) modules, and deep convolutional layers. This approach arises the extraction of temporal and spatial features of the P300 to a finer granularity level. Results: Compared with several existing single-trial EEG classification methods for RSVP tasks, the proposed model shows significantly improved performance. The mean true positive rate for PSAEEGNet is 0.7949, and the mean area under the receiver operating characteristic curve (AUC) is 0.9341 (p < 0.05). Discussion: These results suggest that the proposed model effectively extracts features from both temporal and spatial dimensions of P300, leading to a more accurate classification of single-trial EEG during RSVP tasks. Therefore, this model has the potential to significantly enhance the performance of target recognition systems based on EEG, contributing to the advancement and practical implementation of target recognition in this field.

Abietane diterpenoids from Caryopteris incana (Thunb.) Miq. And their HIF-2α inhibitory activities in vitro.

Eleven previously undescribed abietane-type diterpenoids, named caryopincanoids A-K (1-11), together with five known compounds, were isolated from the EtOH extract of the aerial parts of Caryopteris incana (Thunb.) Miq. Their structures were elucidated on the basis of comprehensive spectroscopic data, NMR calculations, and ECD calculations. The inhibitory activities of all compounds against HIF-2α gene expression in 786-O cells were tested by luciferase assay. Compounds 7, 9, 15, and 16 showed significant inhibitory effects with IC50 values ranging from 12.73 to 23.80 µM. The preliminary structure-activity relationship of these compounds was also discussed.

Ag-Catalyzed Switchable Synthesis of Site-Specifically Functionalized Pyrroles via Azafulvenium Intermediates.

Here, we present a versatile, silver-catalyzed multi-auto-tandem reaction involving enamines, alkynals, and nucleophiles, utilizing the highly reactive intermediate azafulvenium. This method allows for flexible and switchable regiodivergent reactions through either intermolecular or intramolecular nucleophilic attacks, which can be controlled by adjusting the catalytic conditions. A range of site-specific functionalized or polycyclic fused pyrrole products were efficiently produced with a high level of chemocontrol.

Engineering of a compact, high-fidelity EbCas12a variant that can be packaged with its crRNA into an all-in-one AAV vector delivery system.

The CRISPR-associated endonuclease Cas12a has become a powerful genome-editing tool in biomedical research due to its ease of use and low off-targeting. However, the size of Cas12a severely limits clinical applications such as adeno-associated virus (AAV)-based gene therapy. Here, we characterized a novel compact Cas12a ortholog, termed EbCas12a, from the metagenome-assembled genome of a currently unclassified Erysipelotrichia. It has the PAM sequence of 5'-TTTV-3' (V = A, G, C) and the smallest size of approximately 3.47 kb among the Cas12a orthologs reported so far. In addition, enhanced EbCas12a (enEbCas12a) was also designed to have comparable editing efficiency with higher specificity to AsCas12a and LbCas12a in mammalian cells at multiple target sites. Based on the compact enEbCas12a, an all-in-one AAV delivery system with crRNA for Cas12a was developed for both in vitro and in vivo applications. Overall, the novel smallest high-fidelity enEbCas12a, this first case of the all-in-one AAV delivery for Cas12a could greatly boost future gene therapy and scientific research.

Influence of atomic electronegativity on ESIPT behaviour for the BTDI and its derivatives: Theoretical exploration.

In this work, we theoretically explored the influence of atomic electronegativity on excited-state intramolecular proton transfer (ESIPT) behavior among novel fluorescent probes BTDI and its derivatives (BODI and BSeDI). A thorough examination of the optimized structural parameters and infrared vibrational spectra reveals an enhancement in intramolecular hydrogen bonding within BTDI and its derivatives upon light excitation. This finding is further reinforced by topological analysis and interaction region indicator scatter plots, which underscores the sensitivity of atomic electronegativity to variations in hydrogen bonding strength. With regards to absorption and fluorescence spectra, the decrease in atomic electronegativity leads to a pronounced redshift, primarily attributed to the narrowing of the energy gap. Additionally, an analysis of potential energy curves and the exploration of intrinsic reaction coordinate paths based on transition state structures afford a deeper understanding of the mechanism underlying ESIPT and being modulated through the manipulation of atomic electronegativity. We anticipate that this work on atomic electronegativity regulating ESIPT behavior will serve as a catalyst for novel fluorescent probes in the future, offering fresh perspectives and insights.