Characterizing Mental Health Status and Service Utilization in Chinese Americans With Type 2 Diabetes in New York City: Cross-Sectional Study.

BACKGROUND: Emerging evidence indicates that individuals with type 2 diabetes (T2D) are more prone to mental health issues than the general population; however, there is a significant lack of data concerning the mental health burden in Chinese Americans with T2D. OBJECTIVE: The aim of this study was to explore the comorbid mental health status, health-seeking behaviors, and mental service utilization among Chinese Americans with T2D. METHODS: A cross-sectional telephone survey was performed among 74 Chinese Americans with T2D in New York City. We used standardized questionnaires to assess mental health status and to gather data on mental health-seeking behaviors and service utilization. Descriptive statistics were applied for data analysis. RESULTS: A total of 74 Chinese Americans with T2D completed the survey. Most participants (mean age 56, SD 10 years) identified as female (42/74, 57%), were born outside the United States (73/74, 99%), and had limited English proficiency (71/74, 96%). Despite nearly half of the participants (34/74, 46%) reporting at least one mental health concern (elevated stress, depressive symptoms, and/or anxiety), only 3% (2/74) were currently using mental health services. Common reasons for not seeking care included no perceived need, lack of information about Chinese-speaking providers, cost, and time constraints. The cultural and language competence of the provider was ranked as the top factor related to seeking mental health care. CONCLUSIONS: Chinese Americans with T2D experience relatively high comorbid mental health concerns yet have low service utilization. Clinicians may consider team-based care to incorporate mental health screening and identify strategies to provide culturally and linguistically concordant mental health services to engage Chinese Americans with T2D.

Screening of Methyl-ß-cyclodextrins as an Antifading Agent for Cyanine Dye-Labeled Streptavidin to Improve the Performance of Genotyping Chips.

As a photostabilizing agent for cyanine dye, methyl-ß-cyclodextrin (MßCD) was investigated as a possible antifading agent for cyanine dye-labeled proteins. Cyanine-3 (Cy3)-labeled streptavidin (SA-Cy3) solutions containing MßCD exhibited improved resistance against photobleaching. Further research revealed that MßCD can be used as a coating material on the surface of gene chips. Chips loaded with cyanine dye (Cy3 and Cyanine-5 (Cy5))-conjugated model microbeads exhibited resistance against photobleaching with MßCD coatings. MßCD coatings improved the imaging quality of model chips and resulted in higher discrimination ratios (DR) of single base recognition by a set of control beads (NP68). In a whole genome genotyping assay for human samples, the MßCD-coated samples were found to have a better clustering performance than the noncoated ones for a group of randomly picked single nucleotide polymorphisms (SNPs).

Giant manipulation of thermal conductivity anisotropy in black phosphorene under external electric fields.

The thermal anisotropy of materials holds significant theoretical and practical implications in the domains of thermal transport and thermoelectricity. Black phosphorene, a novel two-dimensional (2D) semiconductor, is notable for its exceptional chemical and physical properties, attracting substantial attention for its thermal transport characteristics. Similar to other 2D materials, black phosphorene exhibits pronounced in-plane thermal anisotropy. Given its expanding applications in nanoelectronics, optoelectronics, and thermoelectrics, there is a growing need to manipulate its anisotropic thermal transport. Current methods for adjusting anisotropy or isotropy typically involve structural engineering or materials processing, which are often costly, time-consuming, and irreversible. In contrast, little progress has been made with methods that are intact, robust, and reversible. Driven by the intrinsic relationship between interatomic interaction-mediated phonon transport and electronic charges, we conduct a comprehensive investigation into the impact of an external electric field on the thermal transport properties of 2D black phosphorene using first-principles calculations and the phonon Boltzmann transport equation. Our findings reveal that applying an electric field in the Zigzag direction reduces the lattice thermal conductivity of black phosphorene, with the Zigzag direction being more responsive to the electric field than the Armchair direction. By adjusting the electric field to a maximum of E(f_xx) = 0.2 V Å-1, the anisotropic thermal conductivity of black phosphorene decreases by more than 28%, demonstrating effective manipulation of anisotropy. This significant transition in anisotropic thermal transport arises from the substantial reduction in thermal conductivity along the Zigzag direction at moderate electric field strengths. The underlying cause of this variation in anisotropy can be attributed to changes in group velocity, with the phonon lifetime serving as a scaling factor for reducing anisotropy. Analysis of the electronic structures shows that stronger electric fields induce more charges, enhancing the screening effect. The electric field significantly alters thermal conductivity by affecting bond ionicity and anharmonicity. Our study introduces a robust approach for tuning the anisotropy of phonon transport in materials using an external electric field, without altering the atomic structure, thus offering considerable advantages for applications in nanoelectronics and thermoelectric energy conversion.

Study on the Antibacterial Activity and Bone Inductivity of Nanosilver/PLGA-Coated TI-CU Implants.

Background: Implants are widely used in the field of orthopedics and dental sciences. Titanium (TI) and its alloys have become the most widely used implant materials, but implant-associated infection remains a common and serious complication after implant surgery. In addition, titanium exhibits biological inertness, which prevents implants and bone tissue from binding strongly and may cause implants to loosen and fall out. Therefore, preventing implant infection and improving their bone induction ability are important goals. Purpose: To study the antibacterial activity and bone induction ability of titanium-copper alloy implants coated with nanosilver/poly (lactic-co-glycolic acid) (NSPTICU) and provide a new approach for inhibiting implant-associated infection and promoting bone integration. Methods: We first examined the in vitro osteogenic ability of NSPTICU implants by studying the proliferation and differentiation of MC3T3-E1 cells. Furthermore, the ability of NSPTICU implants to induce osteogenic activity in SD rats was studied by micro-computed tomography (micro-CT), hematoxylin-eosin (HE) staining, masson staining, immunohistochemistry and van gieson (VG) staining. The antibacterial activity of NSPTICU in vitro was studied with gram-positive Staphylococcus aureus (Sa) and gram-negative Escherichia coli (E. coli) bacteria. Sa was used as the test bacterium, and the antibacterial ability of NSPTICU implanted in rats was studied by gross view specimen collection, bacterial colony counting, HE staining and Giemsa staining. Results: Alizarin red staining, alkaline phosphatase (ALP) staining, quantitative real-time polymerase chain reaction (qRT-PCR) and western blot analysis showed that NSPTICU promoted the osteogenic differentiation of MC3T3-E1 cells. The in vitro antimicrobial results showed that the NSPTICU implants exhibited better antibacterial properties. Animal experiments showed that NSPTICU can inhibit inflammation and promote the repair of bone defects. Conclusion: NSPTICU has excellent antibacterial and bone induction ability, and has broad application prospects in the treatment of bone defects related to orthopedics and dental sciences.

Development of the fetal brain cortico-cortical structural network during the second-to-third trimester based on diffusion MRI.

During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the inter-wired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and post-mortem fetal brains, the in-utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in-utero dMRI data from human fetuses of both sexes between 26 to 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intra-hemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for the Wernicke's area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.Significance Statement We studied the normal development of intra-hemispheric cortico-cortical structural connectivity networks (SCNs) of the fetal brain from 26 to 38 gestational weeks using in-utero diffusion MRI data. Graph-theory-based analysis revealed significant enhancement in network efficiency and clustering, as well as persisted small-worldness with age, revealing balanced integration and segregation in the fetal brain SCN during the studied period, supported by regional developmental patterns. Leftward lateralization in network efficiency, clustering coefficient and small-worldness was observed. Regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge. We also summarized the challenges of investigating the fetal brain SCN development, and provided suggestions for future studies.

Brain Short-Chain Fatty Acids Induce ACSS2 to Ameliorate Depressive-Like Behavior via PPARγ-TPH2 Axis.

Short-chain fatty acids (SCFAs) have been increasingly evidenced to be important bioactive metabolites of the gut microbiota and transducers in controlling diverse psychiatric or neurological disorders via the microbiota-gut-brain axis. However, the precise mechanism by which brain SCFAs extert multiple beneficial effects is not completely understood. Our previous research has demonstrated that the acetyl-coenzyme A synthetase short-chain family member 2 (ACSS2) is a novel target of the rapid and long-lasting antidepressant responses. Here, we show that micromolar SCFAs significantly augment both total cellular and nuclear ACSS2 to trigger tryptophan hydroxylase 2 (TPH2) promoter histone acetylation and its transcription in SH-SY5Y cells. In chronic-restraint-stress-induced depression mice, neuronal ACSS2 knockdown by stereotaxic injection of adeno-associated virus in the hippocampus abolished SCFA-mediated improvements in depressive-like behaviors of mice, supporting that ACSS2 is required for SCFA-mediated antidepressant responses. Mechanistically, the peroxisome-proliferator-activated receptor gamma (PPARγ) is identified as a novel partner of ACSS2 to activate TPH2 transcription. Importantly, PPARγ is also responsible for SCFA-mediated antidepressant-like effects via ACSS2-TPH2 axis. To further support brain SCFAs as a therapeutic target for antidepressant effects, d-mannose, which is a naturally present hexose, can significantly reverse the dysbiosis of gut microbiota in the chronic-restraint-stress-exposure mice and augment brain SCFAs to protect against the depressive-like behaviors via ACSS2-PPARγ-TPH2 axis. In summary, brain SCFAs can activate ACSS2-PPARγ-TPH2 axis to play the antidepressive-like effects, and d-mannose is suggested to be an inducer of brain SCFAs in resisting depression.

Fast simulation for interacting four-level Rydberg atoms: electromagnetically induced transparency and Autler-Townes splitting.

Quantum sensing using Rydberg atoms is an emerging technology for precise measurement of electric fields. However, most existing computational methods are all based on a single-particle model and neglect Rydberg-Rydberg interaction between atoms. In this study, we introduce the interaction term into the conventional four-level optical Bloch equations. By incorporating fast iterations and solving for the steady-state solution efficiently, we avoid the computation of a massive 4N × 4N dimensional matrix. Additionally, we apply the Doppler frequency shift to each atom used in the calculation, eliminating the requirement for an additional Doppler iteration. These schemes allow for the calculation of the interaction between 7000 atoms around one minute. Based on the many-body model, we investigate the Rydberg-Rydberg interaction of Rydberg atoms under different atomic densities. Furthermore, we compare our results with the literature data of a three-level system and the experimental results of our own four-level system. The results demonstrate the validity of our model, with an effective error of 4.59% compared to the experimental data. Finally, we discover that the many-body model better predicts the linear range for measuring electric fields than the single-particle model, making it highly applicable in precise electric field measurements.

Interface-driven structural evolution on diltiazem as novel uPAR inhibitors: from in silico design to in vitro evaluation.

The urokinase-type plasminogen activator receptor (uPAR) emerges as a key target for anti-metastasis owing to its pivotal role in facilitating the invasive and migratory processes of cancer cells. Recently, we identified the uPAR-targeting anti-metastatic ability of diltiazem (22), a commonly used antihypertensive agent. Fine-tuning the chemical structures of known hits represents a vital branch of drug development. To develop novel anti-metastatic drugs, we performed an interface-driven structural evolution strategy on 22. The uPAR-targeting and anti-cancer abilities of this antihypertensive drug wereidentified by us recently. Based on in silico strategy, including extensive molecular dynamics (MD) simulations, hierarchical binding free energy predictions, and ADMET profilings, we designed, synthesized, and identified three new diltiazem derivatives (221-8, 221-57, and 221-68) as uPAR inhibitors. Indeed, all of these three derivatives exhibited uPAR-depending inhibitory activity against PC-3 cell line invasion at micromolar level. Particularly, derivatives 221-68 and 221-8 showed enhanced uPAR-dependent inhibitory activity against the tumor cell invasion compared to the original compound. Microsecond timesclae MD simulations demonstrated the optimized moiety of 221-68 and 221-8 forming more comprehensive interactions with the uPAR, highlighting the reasonability of our strategy. This work introduces three novel uPAR inhibitors, which not only pave the way for the development of effective anti-metastatic therapeutics, but also emphasize the efficacy and robustness of an in silico-based lead compound optimization strategy in drug design.

Automated diagnosis of schizophrenia based on spatial-temporal residual graph convolutional network.

BACKGROUND: Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is required. NEW METHOD: In this study, we provide a classification approach for SZ patients based on a spatial-temporal residual graph convolutional neural network (STRGCN). The model primarily collects spatial frequency features and temporal frequency features by spatial graph convolution and single-channel temporal convolution, respectively, and blends them both for the classification learning, in contrast to traditional approaches that only evaluate temporal frequency information in EEG and disregard spatial frequency features across brain regions. RESULTS: We conducted extensive experiments on the publicly available dataset Zenodo and our own collected dataset. The classification accuracy of the two datasets on our proposed method reached 96.32% and 85.44%, respectively. In the experiment, the dataset using delta has the best classification performance in the sub-bands. COMPARISON WITH EXISTING METHODS: Other methods mainly rely on deep learning models dominated by convolutional neural networks and long and short time memory networks, lacking exploration of the functional connections between channels. In contrast, the present method can treat the EEG signal as a graph and integrate and analyze the temporal frequency and spatial frequency features in the EEG signal. CONCLUSION: We provide an approach to not only performs better than other classic machine learning and deep learning algorithms on the dataset we used in diagnosing schizophrenia, but also understand the effects of schizophrenia on brain network features.

Remodeling of tumor microenvironment by extracellular matrix protein 1a differentially regulates ovarian cancer metastasis.

We previously reported that extracellular matrix protein 1 isoform a (ECM1a) promotes epithelial ovarian cancer (EOC) through autocrine signaling by binding to cell surface receptors αXß2. However, the role of ECM1a as a secretory molecule in the tumor microenvironment is rarely reported. In this study, we constructed murine Ecm1-knockout mice and human ECM1a-knockin mice and further generated orthotopic or peritoneal xenograft tumor models to mimic the different metastatic stages of EOC. We show that ECM1a induces oncogenic metastasis of orthotopic xenograft tumors, but inhibits early-metastasis of peritoneal xenograft tumors. ECM1a remodels extracellular matrices (ECM) and promotes remote metastases by recruiting and transforming bone marrow mesenchymal stem cells (BMSCs) into platelet-derived growth factor receptor beta (PDGFRß+) cancer-associated fibroblasts (CAFs) and facilitating the secretion of angiopoietin-like protein 2 (ANGPTL2). Competing with ECM1a, ANGPTL2 also binds to integrin αX through the P1/P2 peptides, resulting in negative effects on BMSC differentiation. Collectively, this study reveals the dual functions of ECM1a in remodeling of TME during tumor progression, emphasizing the complexity of EOC phenotypic heterogeneity and metastasis.

Self-Illuminating Nanoagonist Simultaneously Induces Dual Cell Death Pathways via Death Receptor Clustering for Cancer Therapy.

Inducing death receptor 5 (DR5) clustering holds particular promise in tumor-specific therapeutics because it could trigger an apoptotic cascade in cancerous cells. Herein, we present a tumor microenvironment H2O2-responsive self-illuminating nanoagonist, which could induce dual tumor cell death pathways through enhancing DR5 clustering. By conjugating DR5 ligand peptides onto the surfaces of self-illuminating nanoparticles with cross-linking capacity, this strategy not only provides scaffolds for ligands to bind receptors but also cross-links them through photo-cross-linking. This strategy allows for efficient activation of DR5 downstream signaling, initiating the extrinsic apoptosis pathway and immunogenic cell death of tumor cells, and contributes to improved tumor-specific immune responses, resulting in enhanced antitumor efficacy and minimized systemic adverse effects.

An ERP study on the late stage of Chinese metaphor processing.

Psycholinguistic models of metaphor processing remain a subject of debate. A prime-probe design using Chinese materials with a specific time span (300 ms) was applied to test the mechanisms of metaphor processing. Conventional and familiarized metaphors were designed as primes, followed by a probe word semantically related to the prime metaphor (MT), a probe word related to the literal meaning of the final word of the prime metaphor (LT), control/unrelated probe word (UT), or non-word. Event-related potentials (ERPs) elicited by the probes were recorded to examine metaphor processing. In N400, results revealed that UT and LT elicited significantly more negative waveforms than MT in both primes. MTs and LTs showed no difference between conventional and familiarized metaphors, suggesting that metaphorical meaning may be accessed directly, regardless of whether conventional or familiarized metaphors. The results were generally compatible with the direct processing model.

Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study.

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

Trends in the mobility of primary healthcare human resources in underdeveloped regions of western China from 2000 to 2021: Evidence from Nanning.

OBJECTIVE: This research aimed to identify the fundamental and geographic characteristics of the primary healthcare personnel mobility in Nanning from 2000 to 2021 and clarify the determinants that affect their transition to non-primary healthcare institutions. METHODS: Through utilizing the Primary Healthcare Personnel Database (PHPD) for 2000-2021, the study conducts descriptive statistical analysis on demographic, economic, and professional aspects of healthcare personnel mobility across healthcare reform phases. Geographic Information Systems (QGIS) were used to map mobility patterns, and R software was employed to calculate spatial autocorrelation (Moran's I). Logistic regression identified factors that influenced the transition to non-primary institutions. RESULTS: Primary healthcare personnel mobility is divided into four phases: initial (2000-2008), turning point (2009-2011), rapid development (2012-2020), and decline (2021). The rapid development stage saw increased mobility with no spatial clustering in inflow and outflow. From 2016 to 2020, primary healthcare worker mobility reached its peak, in which the most significant movement occurred between township health centers and other institutions. Aside from their transition to primary medical institutions, the primary movement of grassroots health personnel predominantly directs towards secondary general hospitals, tertiary general hospitals, and secondary specialized hospitals. Since 2012, the number and mobility distance of primary healthcare workers have become noticeably larger and remained at a higher level from 2016 to 2020. The main migration of primary healthcare personnel occurred in their districts (counties). Key transition factors include gender, education, ethnicity, professional category, general practice registration, and administrative division. CONCLUSIONS: This study provides evidence of the features of primary healthcare personnel mobility in the less developed western regions of China, in which Nanning was taken as a case study. It uncovers the factors that impact the flow of primary healthcare personnel to non-primary healthcare institutions. These findings are helpful to policy refinement and support the retention of primary healthcare workers.

Knowledge mapping of graph neural networks for drug discovery: a bibliometric and visualized analysis.

Introduction: In recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research. Methods: Publications from 2017 to 2023 about the application of graph neural network in drug discovery were collected from the Web of Science Core Collection. Bibliometrix, VOSviewer, and Citespace were mainly used for bibliometric studies. Results and Discussion: In this paper, a total of 652 papers from 48 countries/regions were included. Research interest in this field is continuously increasing. China and the United States have a significant advantage in terms of funding, the number of publications, and collaborations with other institutions and countries. Although some cooperation networks have been formed in this field, extensive worldwide cooperation still needs to be strengthened. The results of the keyword analysis clarified that graph neural network has primarily been applied to drug-target interaction, drug repurposing, and drug-drug interaction, while graph convolutional neural network and its related optimization methods are currently the core algorithms in this field. Data availability and ethical supervision, balancing computing resources, and developing novel graph neural network models with better interpretability are the key technical issues currently faced. This paper analyzes the current state, hot spots, and trends of graph neural network applications in drug discovery through bibliometric approaches, as well as the current issues and challenges in this field. These findings provide researchers with valuable insights on the current status and future directions of this field.

Upconversion Emission and Dual-Mode Sensing Characteristics of NaYF4:Yb3+/Er3+ Microcrystals at High and Ultralow Temperatures.

In this study, we investigate micrometer-sized NaYF4 crystals double-doped with Yb3+/Er3+ lanthanide ions, designed for temperature-sensing applications. In contrast to previous studies, which focused predominantly on the high-temperature regime, our investigation spans a comprehensive range of both high and ultralow temperatures. We explore the relationship between temperature and the upconversion luminescence (UCL) spectra in both frequency and time domains. Our findings highlight the strong dependence of these spectral characteristics of lanthanide-doped NaYF4 crystals on temperature. Furthermore, we introduce a dual-mode luminescence temperature measurement technique, leveraging the upconversion emission intensity ratio for both green and red emissions. This study also examines the correlation between temperature sensing, energy level disparities, and thermal coupling in Er3+ ions across various temperature scales. Our research contributes to advancing the understanding and application of lanthanide-doped materials, setting a foundation for future innovations in temperature sensing across diverse fields.

Mechanism of electro-acupuncture in alleviating intestinal injury in septic mice via polyamine-related M2-macrophage polarization.

Objective: The objective of this study was to investigate the impact of electro-acupuncture (EA) on sepsis-related intestinal injury and its relationship with macrophage polarization. Methods: A sepsis model was established using cecal ligation and puncture (CLP) to assess the effectiveness of EA. The extent of pathological injury was evaluated using Chiu's score, the expression of ZO-1 and Ocludin, and the impact on macrophage polarization was examined through flow cytometry and immunofluorescence staining. The expression of spermidine, one type of polyamine, and ornithine decarboxylase (ODC) was measured using ELISA and PCR. Once the efficacy was determined, a polyamine depletion model was created, and the role of polyamines was reassessed by evaluating efficacy and observing macrophage polarization. Results: EA treatment reduced the Chiu's score and increased the expression of ZO-1 and Ocludin in the intestinal tissue of septic mice. It inhibited the secretion of IL-1ß and TNF-α, promoted the polarization of M2-type macrophages, increased the secretion of IL-10, and upregulated the expression of Arg-1, spermidine, and ODC. However, after depleting polyamines, the beneficial effects of EA on alleviating intestinal tissue damage and modulating macrophage polarization disappeared. Conclusion: The mechanism underlying the alleviation of intestinal injury associated with CLP-induced sepsis by EA involves with the promotion of M2-type macrophage polarization mediated by spermidine expression.

Overactivated MX1 Positive Natural Killer Cells Promote the Progression of Sepsis-Induced Acute Respiratory Distress Syndrome.

Background: Natural killer (NK) cells are key regulators of immune defense in sepsis-induced acute respiratory distress syndrome (ARDS), yet the characteristics of NK cell clusters in ARDS remain poorly understood. Methods: A prospective and observational study enrolled septic patients with ARDS or not was conducted to determine the percentage of NK cells via flow cytometry. The transcriptomes of peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with sepsis only, and patients with sepsis-induced ARDS were profiled. Vitro experiments were performed to confirm the mechanism mediating MX1+NK cell infiltration. Results: A total of 115 septic patients were analyzed, among whom 63 patients developed ARDS and 52 patients did not. Decreased NK percentages were found in sepsis with ARDS patients (%, 7.46±4.40 vs 11.65±6.88, P=0.0001) compared with sepsis-only patients. A lower percentage of NK cells showed a significant increase in 28-day mortality. Single-cell sequencing analysis revealed distinct characteristics of NK cells in sepsis-induced ARDS, notably the identification of a unique cluster defined as MX1+NK cells. Flow cytometry analysis showed an elevated percentage of MX1+NK cells specifically in individuals with sepsis-induced ARDS, compared with patients with sepsis only. Pseudo-time analysis showed that MX1+NK cells were characterized by upregulation of type I interferon-induced genes and other pro-inflammatory genes. MX1+NK cells can respond to type I interferons and secrete type I interferons themselves. Ligand-receptor interaction analysis also revealed extensive interaction between MX1+NK cells and T/B cells, leading to an uncontrolled inflammatory response in ARDS. Conclusion: MX1+NK cells can respond to type I interferons and secrete type I interferons themselves, promoting the development of sepsis-induced ARDS. Interfering with the infiltration of MX1+NK cells could be a therapeutic approach for this disease. Due to the limited sample size, a larger sample size was needed for further exploration.

Antitumor Activity and Mechanistic Insights of a Mitochondria-Targeting Cu(I) Complex.

Using copper-ionophores to translocate extracellular copper into mitochondria is a clinically validated anticancer strategy that has been identified as a new type of regulated cell death termed "cuproptosis." This study reports a mitochondria-targeting Cu(I) complex, Cu(I)Br(PPh3)3 (CBP), consisting of a cuprous ion coordinated by three triphenylphosphine moieties and a Br atom. CBP exhibited antitumor and antimetastatic efficacy in vitro and in vivo by specifically targeting mitochondria instigating mitochondrial dysfunction. The cytotoxicity of CBP could only be reversed by a copper chelator rather than inhibitors of the known cell death, indicating copper-dependent cytotoxicity. Furthermore, CBP induced the oligomerization of lipoylated proteins and the loss of Fe-S cluster proteins, consistent with characteristic features of cuproptosis. Additionally, CBP induced remarkable intracellular generation of reactive oxygen species (ROS) through a Fenton-like reaction, indicating a complex antitumor mechanism. This is a proof-of-concept study exploiting the antitumor activity and mechanism of the Cu(I)-based mitochondria-targeting therapy.

Municipal pipeline networks as preferential vapor intrusion pathways: A review.

Recent reports show a rise in instances where municipal networks, such as sewer lines, serve as pathways for vapor intrusion (VI), enabling volatile organic compounds (VOCs) vapors to travel along these networks. These VOCs pose potential health risks to occupants of buildings connected to these networks. Currently, there's a lack of specific technical or regulatory guidance on identifying and assessing the VI risk associated with sewer as preferential VI pathways. This critical review summarizes key findings from studies and site investigations related to sewer VI pathways. These findings cover background VOCs concentration levels in sewers, updates to site conceptual models, advances in sewer sampling techniques, innovative tools for identifying and characterizing sewer VI, and practices for assessing and mitigating sewer VI risk. While significant improvements have been made towards understanding how municipal pipeline networks act as VI pathways, more research is still needed to develop strategies for investigating sites and assessing risks associated with "pipeline VI pathways". Future research could focus on the development of "pipeline VI pathways" data set, the improvement and validation of investigation tools, and improving the understanding of VOCs transportation mechanisms within these "pipeline VI pathways".