Water-soluble AIE photosensitizer in short-wave infrared region for albumin-enhanced and self-reporting phototheranostics.

Organic photosensitizers (PSs) play important roles in phototheranostics, and contribute to the fast development of precision medicine. However, water-soluble and highly emissive organic PSs, especially those emitting in the short-wave infrared region (SWIR), are still challenging. Also, it's difficult to prepare self-reporting PSs for visualizing the treatment via stimulated emission depletion (STED) nanoscopy. Thus, in this work, a water-soluble molecule of DTPAP-TBZ-I with aggregation-induced emission features is designed for the self-reporting photodynamic therapy (PDT) in an ultra-high resolution. In contrast to single molecule, its complex (DTPAP-TBZ-I@BSA) shows much enhanced fluorescence properties and reactive oxygen species (ROS) generation in SWIR window. Their photoluminescence quantum yield is determined to be ∼20.6 % and the enhancement of ROS generation is ∼18-fold. During the PDT, immigration of the complex from cytoplasm to nucleus is also observed via STED nanoscopy with a resolution of 66.11 nm, which allows self-report in the PDT treatment. DTPAP-TBZ-I@BSA is finally utilized for the imaging-guided PDT in vivo with a tumor inhibition rate of 84 %. This is the first work in albumin-enhanced water-soluble organic PSs in SWIR window for self-reporting phototheranostics at ultra-high resolutions, providing an ideal solution for the next generation of photosensitizers for precise medicine.

Mesenchymal stem cell-loaded hydrogel to inhibit inflammatory reaction in surgical brain injury via mitochondria transfer.

Neurosurgical procedures are the key therapeutic interventions for the cerebral hemorrhage and brain tumors. However, neurosurgical procedures inevitably cause surgical brain injury (SBI), which will induce hemorrhage and inflammation. Gelatin Sponges are still the primary hemostatic materials used in clinical, but their anti-inflammatory efficacy is poor. Herein, we developed a cross-linked gelatin hydrogel (GelMA) to load mesenchymal stem cells (MSC) and directly implant them to the SBI site. Upon contacting the SBI site, the GelMA showed better clotting performance than Gelatin Sponges. Moreover, the MSC can reduce oxidative stress and enhance mitochondrial fusion via mitochondria transfer, resulting in ameliorating mitochondrial damage and reducing inflammation. Thus, the GelMA containing MSC can effectively reduce brain edema and inflammation and improve neurological function in SBI mouse models. In addition, GelMA exhibits excellent hemocompatibility and low cytotoxicity. It also enhances the proliferation of MSCs and decelerates the rapid depletion of MSCs. Therefore, MSC-loaded GelMA exhibits excellent hemostatic and anti-inflammatory effects, making it a potential new-generation biomaterial for SBI.

Size-dependent translocation and lymphatic transportation of polymeric nanocarriers post intraperitoneal administration.

Intraperitoneal (i.p.) administered nanomedicine has been widely applied in the clinical treatment of intra-abdominal diseases and preclinical pharmacological investigations. However, current understandings about the in vivo fate of i.p.-administered drug remains controversial owing to lack of reliable investigation tools. This work presents a nanoparticle-labeling strategy based on aggregation-caused quenching (ACQ) probes in the second near-infrared (NIR-II) window, which can eliminate the interference of unbound probes and allow for non-invasive tracking of nanoparticles in deep tissues. Our results strongly evidence a size-dependent absorption and biodistribution of the i.p.-administered polymeric nanocarriers (PNs) with particle sizes ranging from 30 to 1000 nm both in vivo and ex vivo, and moreover provide a clear visualization of lymphatic transportation and lymph node retention of integral PNs. Importantly, our findings suggest that small particles (≤30 nm) are favorable in systemic therapies due to their rapid absorption and high concentration (>19 %ID mL-1) in circulation, while large particles (over 1000 nm) are meant for localized treatment of abdominal diseases. Besides, the high retention of 200 nm nanoparticles within lymph nodes indicates their promising role in cancer vaccines and lymphatic diseases including lymph node metastasis.

Activation of Piezo1 by intracranial hypertension induced neuronal apoptosis via activating hippo pathway.

AIM: Most of the subarachnoid hemorrhage (SAH) patients experienced the symptom of severe headache caused by intracranial hypertension. Piezo1 is a mechanosensitive ion channel protein. This study aimed to investigate the effect of Piezo1 on neurons in response to intracranial hypertension. METHODS: The SAH rat model was performed by the modified endovascular perforation method. Piezo1 inhibitor GsMTx4 was administered intraperitoneally after SAH induction. To investigate the underlying mechanism, the selective Piezo1 agonist Yoda1, Piezo1 shRNA, and MY-875 were administered via intracerebroventricular injection before SAH induction. In vitro, we designed a pressurizing device to exclusively explore the effect of Piezo1 activation on primary neurons. Neurons were pretreated with Piezo1 inhibition followed by intracranial hypertension treatment, and then apoptosis-related proteins were detected. RESULTS: Piezo1 inhibition significantly attenuated neuronal apoptosis and improved the outcome of neurological deficits in rats after SAH. The Hippo pathway agonist MY-875 reversed the anti-apoptotic effects of Piezo1 knockdown. In vitro, intracranial hypertension mimicked by the pressurizing device induced Piezo1 expression, resulting in Hippo pathway activation and neuronal apoptosis. The Hippo pathway inhibitor Xmu-mp-1 attenuated Yoda1-induced neuronal apoptosis. In addition, the combination of hypertension and oxyhemoglobin treatment exacerbated neuronal apoptosis. CONCLUSIONS: Intracranial hypertension induced Piezo1 expression, neuronal apoptosis, and the Hippo pathway activation; the Hippo signaling pathway is involved in Piezo1 activation-induced neuronal apoptosis in respond to intracranial hypertension. Primary neurons treated with intracranial hypertension and oxyhemoglobin together can better characterize the circumstance of SAH in vivo, which is contributed to construct an ideal in vitro SAH model.

An atlas of genetic effects on the monocyte methylome across European and African populations.

Elucidating the genetic architecture of DNA methylation (DNAm) is crucial for decoding the etiology of complex diseases. However, current epigenomic studies often suffer from incomplete coverage of methylation sites and the use of tissues containing heterogeneous cell populations. To address these challenges, we present a comprehensive human methylome atlas based on deep whole-genome bisulfite sequencing (WGBS) and whole-genome sequencing (WGS) of purified monocytes from 298 European Americans (EA) and 160 African Americans (AA) in the Louisiana Osteoporosis Study. Our atlas enables the analysis of over 25 million DNAm sites. We identified 1,383,250 and 1,721,167 methylation quantitative trait loci (meQTLs) in cis -regions for EA and AA populations, respectively, with 880,108 sites shared between ancestries. While cis -meQTLs exhibited population-specific patterns, primarily due to differences in minor allele frequencies, shared cis -meQTLs showed high concordance across ancestries. Notably, cis -heritability estimates revealed significantly higher mean values in the AA population (0.09) compared to the EA population (0.04). Furthermore, we developed population-specific DNAm imputation models using Elastic Net, enabling methylome-wide association studies (MWAS) for 1,976,046 and 2,657,581 methylation sites in EA and AA, respectively. The performance of our MWAS models was validated through a systematic multi-ancestry analysis of 41 complex traits from the Million Veteran Program. Our findings bridge the gap between genomics and the monocyte methylome, uncovering novel methylation-phenotype associations and their transferability across diverse ancestries. The identified meQTLs, MWAS models, and data resources are freely available at www.gcbhub.org and https://osf.io/gct57/ .

In vivo fluorescence imaging of nanocarriers in near-infrared window II based on aggregation-caused quenching.

Accurate fluorescence imaging of nanocarriers in vivo remains a challenge owing to interference derived mainly from biological tissues and free probes. To address both issues, the current study explored fluorophores in the near-infrared (NIR)-II window with aggregation-caused quenching (ACQ) properties to improve imaging accuracy. Candidate fluorophores with NIR-II emission, ACQ984 (λem = 984 nm) and IR-1060 (λem = 1060 nm), from the aza-BODIPY and cyanine families, respectively, were compared with the commercial fluorophore ICG with NIR-II tail emission and the NIR-I fluorophore P2 from the aza-BODIPY family. ACQ984 demonstrates high water sensitivity with complete fluorescence quenching at a water fraction greater than 50%. Physically embedding the fluorophores illuminates various nanocarriers, while free fluorophores cause negligible interference owing to the ACQ effect. Imaging based on ACQ984 revealed fine structures in the vascular system at high resolution. Moreover, good in vivo and ex vivo correlations in the monitoring of blood nanocarriers can be established, enabling real-time noninvasive in situ investigation of blood pharmacokinetics and dynamic distribution in various tissues. IR-1060 also has a good ACQ effect, but the lack of sufficient photostability and steady post-labeling fluorescence undermines its potential for nanocarrier bioimaging. P2 has an excellent ACQ effect, but its NIR-I emission only provides nondiscriminative ambiguous images. The failure of the non-ACQ probe ICG to display the biodistribution details serves as counterevidence for the improved imaging accuracy by NIR-II ACQ probes. Taken together, it is concluded that fluorescence imaging of nanocarriers based on NIR-II ACQ probes enables accurate in vivo bioimaging and real-time in situ pharmacokinetic analysis.

How health seeking behavior develops in patients with type 2 diabetes: a qualitative study based on health belief model in China.

Background: Type 2 diabetes(T2DM) is a global health problem which is accompanied with multi-systemic complications, and associated with long-term health burden and economic burden. Effective health seeking behavior (HSB) refers to reasonably utilize health resources, effectively prevent and treat diseases, and maintain health. Effective health seeking behavior (HSB) is vital to mitigate the risk of T2DM complications. However, health seeking behavior for T2DM patients remains sub-optimal worldwide. Objective: The study aimed to explore the internal logic of how health seeking behavior of T2DM patients develops and the influencing factors of health seeking behavior. With a view to provide a reference basis for improving the health seeking behavior situation of T2DM patients. Methods: This study was conducted at an integrated tertiary hospital in China. People who were diagnosed with T2DM, capable of expressing clearly and had no mental illness, were approached based on a purposive sampling. The experience of T2DM and health seeking behavior were collected via in-depth interviews. A theory-driven thematic analysis based on Health Belief Model (HBM) was applied for data analysis. Inductive reasoning was used to identify emerging themes which were not included in HBM. Results: 26 patients with T2DM were included in the current study. Seven themes were identified, including: (1) T2DM diagnosis and severity; (2) T2DM treatment and management; (3) Perceived susceptibility of diabetes progression; (4) Perceived severity of diabetes progression; (5) Perceived benefits of health seeking behavior; (6) Perceived barriers of health seeking behavior; (7) Perception of behavioral cues. Generally, patients with T2DM lacked reliable sources of information, considered T2DM to be slow-progressing and without posing an immediate threat to life. Consequently, they did not fully grasp the long-term risks associated with T2DM or the protective effects of health seeking behavior. Conclusion: This study highlighted the challenges in health seeking behavior for patients with T2DM. It suggested that future interventions and strategies should involve multi-faceted approaches, targeting healthcare providers (HCPs), patients with T2DM, and their support networks. This comprehensive strategy can help patients better understand their condition and the importance of effective health seeking behavior. Ultimately, enhancing their capacity for adopting appropriate health-seeking practices.

Antimony Redox Catalysis: Hydroboration of Disulfides through Unique Sb(I)/Sb(III) Redox Cycling.

The stibinidene ArSbI (Ar = [2,6-(tBuN═CH)2-C6H3], 1) reacts with S2Tol2 (Tol = p-tolyl) to form ArSbIII(STol)2 (2), which upon treatment with pinacolborane, regenerates 1. These processes unveil an unprecedented antimony redox catalysis involving Sb(I)/Sb(III) cycling for the hydroboration of organic disulfides. Elementary reaction studies and density functional theory calculations support that the catalysis mimics transition metal processes, proceeding through oxidative addition, ligand metathesis, and reductive elimination. The thiophenols and sulfidoborates generated from the hydroboration of disulfides react in situ with α,ß-unsaturated carbonyl compounds with the assistance of 1 as a base catalyst. These tandem reactions establish a one-pot synthetic method for ß-sulfido carbonyl compounds, in which a stibinidene functions as a redox catalyst and a base catalyst successively, illustrating the versatility and efficiency of antimony catalysis in organic synthesis.

Julolidinyl aza-BODIPYs as NIR-II fluorophores for the bioimaging of nanocarriers.

The aggregation-caused quenching (ACQ) rationale has been employed to improve the fluorescence imaging accuracy of nanocarriers by precluding free probe-derived interferences. However, its usefulness is undermined by limited penetration and low spatiotemporal resolution of NIR-I (700-900 nm) bioimaging owing to absorption and diffraction by biological tissues and tissue-derived autofluorescence. This study aimed to develop ACQ-based NIR-II (1000-1700 nm) probes to further improve the imaging resolution and accuracy. The strategy employed is to install highly planar and electron-rich julolidine into the 3,5-position of aza-BODIPY based on the larger substituent effects. The newly developed probes displayed remarkable photophysical properties, with intense absorption centered at approximately 850 nm and bright emission in the 950-1300 nm region. Compared with the NIR-I counterpart P2, the NIR-II probes demonstrated superior water sensitivity and quenching stability. ACQ1 and ACQ6 exhibited more promising ACQ effects with absolute fluorescence quenching at water fractions above 40% and higher quenching stability with less than 2.0% fluorescence reillumination in plasma after 24 h of incubation. Theoretical calculations verified that molecular planarity is more important than hydrophobicity for ACQ properties. Additionally, in vivo and ex vivo reillumination studies revealed less than 2.5% signal interference from prequenched ACQ1, in contrast to 15% for P2.

MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Effects of socioeconomic status and regional inequality on the association between PM2.5 and its components and cardiometabolic multimorbidity: A multicenter population-based survey in eastern China.

BACKGROUND: Despite evidence linking fine particulate matter (PM2.5) to cardiometabolic multimorbidity (CMM), the impact of its components remains unclear. Socioeconomic status (SES) and regional disparities may confound their association. We aim to evaluate the associations between PM2.5 components and CMM and explore how socioeconomic status and regional disparities affect these relationships. METHODS: We recruited 108,941 participants aged 35-76 years from ten cities in eastern China. Individual exposure was assessed using Tracking Air Pollution in China (TAP) data, including PM2.5 and five components: ammonium (NH4+), black carbon (BC), nitrates (NO3-), organic matter (OM), and sulfates (SO42-). Generalized linear models and quantile g-computation models were employed to quantify the effects of PM2.5 components on CMM and to identify key components. Stratified analyses were performed to investigate the modifying effect of SES and regional disparities. RESULTS: For each increase in interquartile range (IQR), BC (odds ratio [OR] 1.37, 95 % CI 1.29-1.47), OM (1.38, 1.29-1.48), NH4+ (1.31, 1.21-1.40), NO3- (1.34, 1.25-1.44), and SO42- (1.28, 1.20-1.38) were positively associated with CMM. Joint exposure to five components was significantly positively associated with CMM (OR: 1.27, 95 % CI: 1.21-1.33), with SO42- having the highest estimated weight, followed by NO3- and BC. These associations were stronger for participants from low socio-economic status and poor regions. CONCLUSION: In summary, we found a stronger hazard effect of PM2.5 and its components on CMM, compared to those suffering from CMDs, particularly among participants with low socioeconomic status and in poor regions. SO42- may be a primary contributor to the association between PM2.5 components and CMM. These findings underscore the importance of prioritizing CMM and targeting SO42-related pollution sources in health policies, particularly amid China's aging population, reducing environmental health inequalities is critical.

Enhanced Corrosion Resistance in Aluminum-Based Electrolyzer Components via Stoichiometry Tuned Atomic Layer-Deposited TiOx Films.

Titanium (Ti) is widely used as anode current collectors in proton exchange membrane (PEM)-based water electrolyzers due to its self-passivated oxide layer, which protects it from corrosion in acidic solutions. However, the cost of the material and machining process for Ti is high. A wider utilization of water electrolyzers to produce hydrogen could be favored by the use of less expensive coated aluminum (Al) substrates, which could potentially replace high-cost Ti-based components. It is shown here by depositing a pinhole-free oxygen vacancy-rich titanium oxide (TiOx) protection layer by atomic layer deposition (ALD), the corrosion resistance of Al substrates in acidic environments at oxygen evolution potentials can be enhanced. The optimization of the oxygen vacancy concentration is accomplished by tuning the ALD parameters to achieve ideal stoichiometry and conformal coating on rough substrates. The robustness of the coatings was evaluated at high potentials (2.4 V vs NHE = normal hydrogen electrode) in low pH conditions. A low TiOx dissolution rate of the order of ∼6 nm year-1 was observed. By testing under industrially relevant conditions, i.e., high applied voltages (2.4 V) and low pH, an Al loss at around the zero ppb level was achieved using optimized ALD parameters. It is proposed that a 40 nm TiOx coating on Al may be adequate to provide 60,000 h of durability in a PEM water electrolyzer anode current collector.

A review of big data technology and its application in cancer care.

The development of modern medical devices and information technology has led to a rapid growth in the amount of data available for health protection information, with the concept of medical big data emerging globally, along with significant advances in cancer care relying on data-driven approaches. However, outstanding issues such as fragmented data governance, low-quality data specification, and data lock-in still make sharing challenging. Big data technology provides solutions for managing massive heterogeneous data while combining artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) to better mine the intrinsic connections between data. This paper surveys and organizes recent articles on big data technology and its applications in cancer, dividing them into three different types to outline their primary content and summarize their critical role in assisting cancer care. It then examines the latest research directions in big data technology in cancer and evaluates the current state of development of each type of application. Finally, current challenges and opportunities are discussed, and recommendations are made for the further integration of big data technology into the medical industry in the future.

A qualitative study on inner experience of self-management behavior among elderly patients with type 2 diabetes in rural areas.

BACKGROUND: As a chronic metabolic disease, diabetes poses a serious threat to human health and has become a major public health problem in China and worldwide. In 2020, 30% of Chinese people (aged ≥ 60 years) reported having diabetes mellitus. Moreover, individuals with diabetes living in rural areas face a significantly higher mortality risk compared to those in urban areas. In this study, we explored the inner experience of self-management behaviors in elderly patients with type 2 diabetes in rural areas to inform targeted interventions. METHODS: A phenomenological research design was used to explore the inner experience of self-management in rural elderly diabetes. Ten elderly diabetic patients were sampled from December 2022 to March 2023 in rural areas of Yangcheng County, Jincheng City, ShanXi Province, China. The seven-step Colaizzi phenomenological was used to analyze the interview data and generate themes. RESULTS: Four themes emerged: "Insufficient self-management cognition", "Negative self-management attitude", "Slack self-management behavior", and "No time for self-management". CONCLUSION: The level of self-management among elderly patients with type 2 diabetes in rural areas is low. Healthcare professionals should develop targeted interventions aimed at enhancing their cognitive levels, modifying their coping styles, and improving their self-management abilities to improve their quality of life.

Modulation of Electrokinetic Potentials Using Graphene-Based Surfaces and Variable Substrate Charge Density.

Enhanced electrokinetic phenomena, manifested through the observation of a large streaming potential (Vs), were obtained in microchannels with single-layer graphene (SLG)-coated and few-layer graphene (FLG)-coated surfaces. In comparison to silicon microchannels, the Vs obtained for a given pressure difference along the channel (ΔP) was higher by 75% for the graphene-based channels, with larger values in the SLG case. Computational modeling was used to correlate the surface charge density, tuned through plasma processing, and related zeta potential to measured Vs. The implications related to deploying lower dimensional material surfaces for modulating electrokinetic flows were investigated.

Optical Second Harmonic Generation of Low-Dimensional Semiconductor Materials.

In recent years, the phenomenon of optical second harmonic generation (SHG) has attracted significant attention as a pivotal nonlinear optical effect in research. Notably, in low-dimensional materials (LDMs), SHG detection has become an instrumental tool for elucidating nonlinear optical properties due to their pronounced second-order susceptibility and distinct electronic structure. This review offers an exhaustive overview of the generation process and experimental configurations for SHG in such materials. It underscores the latest advancements in harnessing SHG as a sensitive probe for investigating the nonlinear optical attributes of these materials, with a particular focus on its pivotal role in unveiling electronic structures, bandgap characteristics, and crystal symmetry. By analyzing SHG signals, researchers can glean invaluable insights into the microscopic properties of these materials. Furthermore, this paper delves into the applications of optical SHG in imaging and time-resolved experiments. Finally, future directions and challenges toward the improvement in the NLO in LDMs are discussed to provide an outlook in this rapidly developing field, offering crucial perspectives for the design and optimization of pertinent devices.

Non-contact, highly sensitive sugar concentration detection based on Co3Sn2S2 Weyl semimetal thin film sensor by terahertz wave.

Blood sugar is an important biomedical parameter of diabetic patients. The current blood sugar testing is based on an invasive method, which is not very friendly for patients who require long-term monitoring, while the non-invasive method is still in the developing stage. In this paper, we design a non-invasive and highly sensitive terahertz wave detector with Co3Sn2S2 semimetal thin film to test sugar concentration. As different concentrations have inconsistent responses to terahertz wave, we can deduce the concentration of the sugar solution to realize real-time highly sensitive detection of blood sugar concentration. This novel method can be further expanded to 6 G edge intelligence for non-invasive and real-time monitoring of blood sugar, and promote the development of 6 G technology.

Associations between genetically predicted plasma protein levels and Alzheimer's disease risk: a study using genetic prediction models.

BACKGROUND: Specific peripheral proteins have been implicated to play an important role in the development of Alzheimer's disease (AD). However, the roles of additional novel protein biomarkers in AD etiology remains elusive. The availability of large-scale AD GWAS and plasma proteomic data provide the resources needed for the identification of causally relevant circulating proteins that may serve as risk factors for AD and potential therapeutic targets. METHODS: We established and validated genetic prediction models for protein levels in plasma as instruments to investigate the associations between genetically predicted protein levels and AD risk. We studied 71,880 (proxy) cases and 383,378 (proxy) controls of European descent. RESULTS: We identified 69 proteins with genetically predicted concentrations showing associations with AD risk. The drugs almitrine and ciclopirox targeting ATP1A1 were suggested to have a potential for being repositioned for AD treatment. CONCLUSIONS: Our study provides additional insights into the underlying mechanisms of AD and potential therapeutic strategies.

PO-YOLOv5: A defect detection model for solenoid connector based on YOLOv5.

Solenoid connectors play important role in electronic stability system design, with the features of small size, low cost, fast response time and high reliability. The main production process challenge for solenoid connectors is the accurate detection of defects, which is closely related to safe driving. Both faultless and defective products have similar color and shape at the defect location, making proper inspection challenging. To address these issues, we proposed a defect detection model called PO-YOLOv5 to achieve accurate defect detection for solenoid connectors. First, an additional prediction head was added to enable the model to acquire more semantic information to detect larger-scale defective features. Second, we introduced dynamic convolution to learn complementary connections between the four dimensions of the convolution kernel by utilizing its multidimensional attention mechanism. Replacing conventional convolution with dynamic convolution enhances the detection accuracy of the model and reduces the inference time. Finally, we validated PO-YOLOv5 versus the state-of-the-art object detection methods on the same solenoid connectors dataset. Experiments revealed that our proposed approach exhibited higher accuracy. The mAP (mean Average Precision) result of PO-YOLOv5 was found to be about 90.1%. Compared with the original YOLOv5, PO-YOLOv5 exhibited improved precision by about 3%.