Structures and Single-Molecule Magnet Behavior of Dy3 and Dy4 Clusters Constructed by Different Dysprosium(III) Salts.

Using the Schiff base ligand H2L-pyra (N'-(2-hydroxybenzoyl)pyrazine-2-carbohydrazonamide) with multiple dentate sites, the trinuclear DyIII-based complex [Dy3(HL-pyra)2(L-pyra)2(CH3COO)3]·2H2O (1) was synthesized. By analyzing the fragmented assembly process and fine-tuning the bridging anions, complex [Dy4(HL-pyra)2(L-pyra)4(NO3)2(H2O)2]·8H2O (2) with different nuclear numbers was successfully synthesized. Magnetic studies demonstrated that 1 did not exhibit magnetic relaxation behavior under the external field; however, 2 exhibited zero-field single-molecule magnetic relaxation behavior with an effective energy barrier (Ueff) of 197.44 K. This is attributed to the improved anisotropy of the single ion after the normalization of the crystal structure, thus realizing the molecular magnetic switching. Moreover, magnetic dilution analysis of 2 demonstrated that the weak magnetic interaction between metal ions inhibited the occurrence of quantum tunneling of magnetization (QTM), resulting in high-performance single-molecule magnet (SMM) behavior. The reasons for the magnetic difference between these two complexes were analyzed using ab initio calculation and magneto-structural correlations. This study provides a reasonable prediction of the ideal configuration of the approximately parallelogram DyIII-based SMMs, thus offering an effective approach for synthesizing Dy4 complexes with excellent properties.

Derived Neutrophils to Lymphocyte Ratio Predicts Survival Benefit from TPF Induction Chemotherapy in Local Advanced Oral Squamous Cellular Carcinoma.

BACKGROUND: This study aimed to evaluate the derived neutrophil to lymphocyte ratio (dNLR) in predicting the prognosis of patients with locally advanced oral squamous cell carcinoma (LAOSCC) and to assess the survival benefits from docetaxel, cisplatin, and 5-fluorouracil (5-FU) (TPF) induction chemotherapy (IC). METHODS: Patients from a phase III trial involving TPF IC in stage III/IVA OSCC patients (NCT01542931) were enrolled. Receiver operating characteristic curves were constructed, and the area under the curve was computed to determine dNLR cutoff points. Kaplan-Meier survival estimates and Cox proportional hazards models were used for longitudinal analysis. RESULTS: A total of 224 patients were identified (median age: 55.4 years; range: 26 to 75 years; median follow-up: 90 months; range: 3.2 to 93 months). The cutoff point for the dNLR was 1.555. Multivariate analysis showed that the dNLR was an independent negative predictive factor for survival (overall survival (OS): hazard ratio (HR) = 1.154, 95% confidence interval (CI): 1.018-1.309, p = 0.025; disease-free survival (DFS): HR = 1.123, 95% CI: 1.000-1.260, p = 0.050; local recurrence-free survival (LRFS): HR = 1.134, 95% CI: 1.002-1.283, p = 0.047; distant metastasis-free survival (DMFS): HR = 1.146, 95% CI: 1.010-1.300, p = 0.035). A low dNLR combined with cTNM stage III disease predicted benefit from TPF IC for the patients [OS (χ2 = 4.674, p = 0.031), DFS (χ2 = 7.134, p = 0.008), LRFS (χ2 = 5.937, p = 0.015), and DMFS (χ2 = 4.832, p = 0.028)]. CONCLUSIONS: The dNLR is an independent negative predictive factor in LAOSCC patients. Patients with cTNM stage III disease and a low dNLR can benefit from TPF IC.

Contamination Status and Serotypes Distribution of Salmonella in Food in Yantai City, China: A 14-Year Continuous Monitoring Study.

Salmonella is a foodborne zoonotic pathogen that threatens food safety and public health. However, few people have conducted long-term and systematic studies on Salmonella contamination in food in Yantai City. In order to investigate the situation of Salmonella contamination in food and improve the ability of early warning and control of foodborne diseases, a total of 3420 samples from 20 categories were collected from 13 monitoring points in Yantai City, from 2010 to 2023. The difference in detection rate and bacterial strain of different monitoring points, different types, and different sources of samples was compared. Of the 3420 samples, 80 were positive with a detection rate of 2.34%. Salmonella detection rates were significantly different for samples collected at different monitoring sites. Salmonella was detected only in meat and meat products and catering food, and none of the other types were detected. The detection rate of Salmonella was higher in raw animal meat and raw poultry. Samples collected at the market stage had the highest detection rate (5.81%), and there was a significant difference in detection rate between samples from different sources (χ2 = 36.93, p < 0.05). Eighty-one strains of Salmonella were detected out of 3420 samples (2 different strains were detected in 1 positive sample). The serological test identified 8 groups and 27 serotypes. The dominant serum groups were group B 30.86% (25/81), group E1 23.46% (19/81), and group D 16.05% (13/81). The main dominant serotypes were Salmonella give 17.28% (14/81), Salmonella enteritidis 16.05% (13/81), and Salmonella derby 13.58% (11/81). Meat and meat products and catering food were the main food products contaminated with Salmonella. The resulting secondary contamination is the hidden threat of foodborne diseases and should be given sufficient attention.

A separation-free paper-based hydrogel device for one-step reactive oxygen species determination by a smartphone.

Paper-based analytical devices (PADs) are very convenient for determining biomarkers in point-of-care (POC) diagnosis while requiring sample pre-treatment or impurity separation. This study reports a novel hydrogel-coupled, paper-based analytical device (PAD) for separation-free H2O2 colorimetric detection in both aqueous solution and cell lysis with sample-to-answer analysis by directly loading into the sample test zone. By encapsulating an inorganic mimic enzyme and chromogenic substrate into the sodium alginate (SA) hydrogel, amplification of the color signal after catalyzing the substrate could be achieved. Taking advantage of the nanoscale porous structure of the hydrogel and the lateral flow channel of the PAD, large interference fragments or bio-macromolecules are prevented from diffusing into the chromogenic reaction, whereas the small target molecules enter the sensing region to trigger the catalytic reaction. This method demonstrated a rapid and accurate analysis with a limit of detection as low as 0.06 mM and detection selectivity. Our proposed device requires no enzyme and is separation-free, portable, easy-to-fabricate, and low-cost, and may offer a platform for quantitative or qualitative analysis of other analytes in body fluids for POC applications.

A Membrane-Confined Signal Amplification Strategy for Sensitive Monitoring of Extracellular Enzymatic Activity Upon Drug Stimulus.

Extracellular enzymes are not only strongly correlated with disease development but also play critical roles in modulating immune responses. Therefore, real-time monitoring of extracellular enzymatic activity can afford straightforward insights into their spatiotemporal dynamics upon drug stimulus, and provide promising tools to unravel their key roles in modulating the cell signaling. Although DNA-based sensing probes have been frequently developed for the detection of a variety of biomolecules, there still lacks a modular design strategy for amplified imaging of extracellular enzymatic activity associated with live cells. Herein, we developed an enzymatically triggerable signal amplification strategy for real-time dynamic imaging of extracellular enzyme activity through a cell membrane-confined hybrid chain reaction (HCR). We demonstrated that, by modifying the initiator DNA with enzyme-specific incision sites and cholesterol tail, extracellular enzyme-trigged HCR could be fulfilled on the surface of the cellular membrane, facilitating amplified detection of extracellular enzymatic activity. Dynamic monitoring of enzyme secretion of cancer cells upon stimulus or macrophage cells upon inflammation challenge has also been achieved. We envision that the design strategy could provide valuable information for dissecting the role of extracellular enzymes in modulating cell responses to drug treatment.

Projected Impact of Nonpharmacologic Management of Stage 1 Hypertension Among Lower-Risk US Adults.

BACKGROUND: The 2017 American College of Cardiology/American Heart Association blood pressure guideline classified 31 million US adults as having stage 1 hypertension and recommended clinicians provide counseling on behavioral change to the low-risk portion of this group. However, nationwide reductions in cardiovascular disease (CVD) and associated health care expenditures achievable by nonpharmacologic therapy remain unquantified. METHODS: We simulated interventions on a target population of US adults aged 35 to 64 years, identified from the 2015-2018 National Health and Nutrition Examination Survey, with low-risk stage 1 systolic hypertension: that is, untreated systolic blood pressure 130 to 139 mm Hg with diastolic BP <90 mm Hg; no history of CVD, diabetes, or chronic kidney disease; and a low 10-year risk of CVD. We used meta-analyses and trials to estimate the effects of population-level behavior modification on systolic blood pressure. We assessed the extent to which restricting intervention to those in regular contact with clinicians might prevent the delivery of nonpharmacologic therapy. RESULTS: Controlling systolic blood pressure to <130 mm Hg among the 8.8 million low-risk US adults with stage 1 hypertension could prevent 26 100 CVD events, avoid 2900 deaths, and save $1.7 billion in total direct health care costs over 10 years. Adoption of the Dietary Approaches to Stop Hypertension diet could prevent 28 000 CVD events. Other nonpharmacologic interventions could avert between 3800 and 19 500 CVD events. However, only 51% of men and 75% of women regularly interacted with clinicians for counseling opportunities. CONCLUSIONS: Among low-risk adults with stage 1 hypertension, substantial benefits to cardiovascular health could be achieved through public policy that promotes the adoption of nonpharmacologic therapy.

A two-center randomized controlled trial of a repairing mask as an adjunctive treatment for mild to moderate rosacea.

OBJECTIVE: To investigate the efficacy and safety of a repairing mask as an adjunctive treatment for skin barrier maintenance of mild to moderate rosacea. METHODS: Patients with rosacea were recruited in this dual center randomized controlled trial from November 2019 to December 2021. A total of 64 patients were included and randomized into two groups at a ratio of 3:1 into a mask group (n = 47) and a control group (n = 17). Patients in the mask group received treatment with Dr. Yu Centella asiatica repairing facial mask three times weekly for a duration of 6 weeks. All participants were instructed to continue their regimen of 50 mg oral minocycline twice daily and to apply Dr. Yu Intensive Hydrating Soft Cream twice daily. The primary endpoint of this study was the Investigator Global Assessment (IGA) score. RESULTS: A total of 54 patients completed this trial, with 41 in the mask group and 13 in the control group. After using this facial mask for 3 and 6 weeks, the IGA, facial skin dryness, facial flushing, and severity of skin lesion in the mask group showed significantly improvement (p < 0.05). Moreover, the change in the delta degree of skin flushing was significantly higher than that in the control group (p = 0.037). Throughout the study, no adverse events were reported in either group of participants. CONCLUSION: The Dr. Yu Centella asiatica repairing facial mask, as an adjunctive treatment of rosacea, appears to effectively repair and protect the skin barrier, alleviate cutaneous symptoms of rosacea, and is both efficacious and safe for patient use.

Geriatric nutritional risk index and mortality from all-cause, cancer, and non-cancer in US cancer survivors: NHANES 2001-2018.

Background: Malnutrition is strongly correlated with worsened treatment outcomes, reduced standard of living, and heightened mortality rates among individuals with cancer. Our research explores how the Geriatric Nutritional Risk Index (GNRI), a measure of nutritional status, relates to all-cause mortality, cancer-specific, and non-cancer mortality among middle-aged and older adult cancer patients. Methods: We enrolled 3,253 participants aged 40 and above who were diagnosed with cancer. The data was obtained from the National Health and Nutrition Examination Survey (NHANES) dataset covering the period from 2001 to 2018, with a median follow-up duration of 83 months. According to the GNRI levels, patients in the study were classified into two distinct groups: the group with a low GNRI (<98) and the group with a high GNRI (≥ 98). We conducted a Kaplan-Meier survival analysis to assess how survival rates vary with different nutritional conditions. Multivariable Cox regression analyses were performed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality, as well as cancer-specific and non-cancer-related mortality. Restricted cubic spline (RCS) analyses and subgroup evaluations were performed to augment the robustness and validity of our findings. Results: A total of 1,171 deaths were documented, with 383 attributed to cancer, and 788 from other causes. After adjusting for potential confounders, the analysis demonstrated that, within a specified range, an elevation in the GNRI is inversely associated with mortality from all causes, cancer-specific, and non-cancer causes. Moreover, Kaplan-Meier survival curves for all-cause, cancer-specific, and non-cancer mortality distinctly showed a more pronounced decrease in survival rates among individuals in the low GNRI group (<98). Notably, the restricted cubic spline regression model (RCS) revealed statistically significant non-linear associations between GNRI scores and mortality rates. The P-values were ≤0.001 for both all-cause and non-cancer mortality, and 0.024 for cancer-specific mortality. Conclusion: Our study conclusively demonstrated a robust correlation between GNRI scores and mortality rates among cancer patients, encompassing all-cause mortality as well as specific mortality related to both cancerous and non-cancerous causes. The GNRI may be a valuable prognostic tool for predicting cancer mortality outcomes, offering insights that may inform nutritional management and influence the clinical treatment strategies for cancer survivors.

FGF13 enhances the function of TRPV1 by stabilizing microtubules and regulates acute and chronic itch.

Itching is an aversive somatosensation that triggers the desire to scratch. Transient receptor potential (TRP) channel proteins are key players in acute and chronic itch. However, whether the modulatory effect of fibroblast growth factor 13 (FGF13) on acute and chronic itch is associated with TRP channel proteins is unclear. Here, we demonstrated that conditional knockout of Fgf13 in dorsal root ganglion neurons induced significant impairment in scratching behaviors in response to acute histamine-dependent and chronic dry skin itch models. Furthermore, FGF13 selectively regulated the function of the TRPV1, but not the TRPA1 channel on Ca2+ imaging and electrophysiological recordings, as demonstrated by a significant reduction in neuronal excitability and current density induced by TRPV1 channel activation, whereas TRPA1 channel activation had no effect. Changes in channel currents were also verified in HEK cell lines. Subsequently, we observed that selective modulation of TRPV1 by FGF13 required its microtubule-stabilizing effect. Furthermore, in FGF13 knockout mice, only the overexpression of FGF13 with a tubulin-binding domain could rescue TRP channel function and the impaired itch behavior. Our findings reveal a novel mechanism by which FGF13 is involved in TRPV1-dependent itch transduction and provide valuable clues for alleviating pathological itch syndrome.

Conditional survival nomogram for patients with colon mucinous adenocarcinoma to predict prognosis: a dynamic survival analysis.

The aim was to assess conditional survival for colon mucinous adenocarcinoma (MAC) patients, and to construct nomograms to predict conditional survival probability. Survival analysis was done using conditional survival, which was defined as the probability of surviving additional y years for patients who have survived for x years. The mathematical definition was express as: CS (y|x) = S (x + y)/S (x). Cox regression analyses were used to identify prognostic factors. A nomogram is constructed to predict conditional disease-free survival (DFS) and overall survival (OS) probability according to years that already survive. A total of 179 colon MAC patients were included. The 5-year DFS was 67% after surgery, and the 5-year survival probability of patients, who already survived 1, 2, 3, and 4 years were 75%, 87%, 95%, and 98%, respectively. The 5-year OS was 73% after surgery and increased to 76%, 82%, 88%, and 92% at 1, 2, 3, and 4 years, respectively. Subgroup analyses demonstrated the superiority of conditional survival was more pronounced in advanced stages than in stage I. And pT stage, pN stage, and lymphovascular invasion were significantly associated with DFS and OS. Conditional survival nomograms were constructed to predict the 5-year conditional DFS and OS probability given survival for 1, 2, 3, 4 years after surgery. Conditional survival can provide dynamic survival probability according to years that already survive, especially for patients with advanced stages. Taking into account the years already survived accounted for, novel nomograms contributed to effectively predicting conditional survival.

Machine Learning-Based Predictive Modeling of Diabetic Nephropathy in Type 2 Diabetes Using Integrated Biomarkers: A Single-Center Retrospective Study.

Purpose: Diabetic nephropathy (DN), a major complication of diabetes mellitus, significantly impacts global health. Identifying individuals at risk of developing DN is crucial for early intervention and improving patient outcomes. This study aims to develop and validate a machine learning-based predictive model using integrated biomarkers. Methods: A cross-sectional analysis was conducted on a baseline dataset involving 2184 participants without DN, categorized based on their development of DN over a follow-up period of 36 months: DN (n=1270) and Non-DN (n=914). Various demographic and clinical parameters were analyzed. The findings were validated using an independent dataset comprising 468 participants, with 273 developing DN and 195 remaining as Non-DN over the follow-up period. Machine learning algorithms, alongside traditional descriptive statistics and logistic regression were used for statistical analyses. Results: Elevated levels of serum creatinine, urea, and reduced eGFR, alongside an increased prevalence of retinopathy and peripheral neuropathy, were prominently observed in those who developed DN. Validation on the independent dataset further confirmed the model's robustness and consistency. The SVM model demonstrated superior performance in the training set (AUC=0.79, F1-score=0.74) and testing set (AUC=0.83, F1-score=0.82), outperforming other models. Significant predictors of DN included serum creatinine, eGFR, presence of diabetic retinopathy, and peripheral neuropathy. Conclusion: Integrating machine learning algorithms with clinical and biomarker data at baseline offers a promising avenue for identifying individuals at risk of developing diabetic nephropathy in type 2 diabetes patients over a 36-month period.

Association between life's essential 8 and frailty status among cancer survivors in the United States: a cross-sectional analysis.

BACKGROUND: Frailty not only affects disease survival but also impacts the long-term function and quality life of all adults diagnosed with and/or treated for cancer.The American Heart Association has introduced Life's Essential 8 (LE8) as a novel metric for assessing cardiovascular health. Currently, LE8's application in evaluating the frailty of cancer survivors remains unreported. This research seeks to explore the connection between LE8 scores and frailty levels in cancer survivors across the United States, thereby addressing a significant void in existing studies. METHODS: This study analyzed data from cancer survivors enrolled in the National Health and Nutrition Examination Surveys (NHANES) spanning the years 2005 to 2018, providing a comprehensive dataset. Multivariable logistic regression models were used to examine the linkage between LE8 rankings and frailty condition in cancer survivors. Furthermore, the study delved deeper into this correlation using restricted cubic spline (RCS) curves and subgroup analyses. RESULTS: In the fully adjusted model, an increased LE8 level was closely associated with a reduced odds ratio of frailty among cancer survivors, with an OR of 0.95 (95% CI: 0.94-0.96, p < 0.0001).This pattern persisted across different categorizations of LE8 into low, moderate, and high groups, demonstrating a consistent trend. The analysis revealed a non-linear relationship between LE8 scores and frailty status, further supporting a straightforward association (p-value for non-linearity = 0.0729). CONCLUSION: Studies have found that the higher the LE8 score, the less likely a cancer patient is to develop debilitating symptoms.This indicates that the LE8 scores may provide an opportunity for interventions aimed at improving the prognosis of cancer patients.

Co-assembly of cisplatin and dasatinib in hyaluronan nanogel to combat triple negative breast cancer with reduced side effects.

Treatment for triple negative breast cancer (TNBC) remains a huge challenge due to the lack of targeted therapeutics and tumor heterogenicity. Cisplatin (Cis) have demonstrated favorable therapeutic response in TNBC and thus is used together with various kinase inhibitors to fight the heterogenicity of TNBC. The combination of Cis with SRC inhibitor dasatinib (DAS) has shown encouraging anti-TNBC efficacy although the additive toxicity was commonly observed. To overcome the severe side effects of this Cis involved therapy, here we co-encapsulated Cis and DAS into a self-assembled hyaluronan (HA) nanogel (designated as HA/Cis/DAS (HCD) nanogel) to afford the TNBC targeted delivery by using the 4T1 mouse model. The acquired HCD nanogel was around 181 nm in aqueous solution, demonstrating the pharmacological activities of both Cis and DAS. Taking advantages of HA's targeting capability towards CD44 that is overexpressed on many TNBC cells, the HCD could well maintain the anticancer efficacy of the Cis and DAS combination, significantly increase the maximum tolerated dose and relieve the renal toxicity in vivo. The current HCD nanogel provides a potent strategy to improve the therapeutic outcome of Cis and DAS combination and thus representing a new targeted treatment option for TNBC.

High-resolution vasomotion analysis reveals novel arteriole physiological features and progressive modulation of cerebral vascular networks by stroke.

Spontaneous cerebral vasomotion, characterized by ∼0.1 Hz rhythmic contractility, is crucial for brain homeostasis. However, our understanding of vasomotion is limited due to a lack of high-precision analytical methods to determine single vasomotion events at basal levels. Here, we developed a novel strategy that integrates a baseline smoothing algorithm, allowing precise measurements of vasodynamics and concomitant Ca2+ dynamics in mouse cerebral vasculature imaged by two-photon microscopy. We identified several previously unrecognized vasomotion properties under different physiological and pathological conditions, especially in ischemic stroke, which is a highly harmful brain disease that results from vessel occlusion. First, the dynamic characteristics between SMCs Ca2+ and corresponding arteriolar vasomotion are correlated. Second, compared to previous diameter-based estimations, our radius-based measurements reveal anisotropic vascular movements, enabling a more precise determination of the latency between smooth muscle cell (SMC) Ca2+ activity and vasoconstriction. Third, we characterized single vasomotion event kinetics at scales of less than 4 seconds. Finally, following pathological vasoconstrictions induced by ischemic stroke, vasoactive arterioles entered an inert state and persisted despite recanalization. In summary, we developed a highly accurate technique for analyzing spontaneous vasomotion, and our data suggested a potential strategy to reduce stroke damage by promoting vasomotion recovery.

Quantum-level investigation of air decomposed pollutants gas sensor (Pd-modified g-C3N4) influenced by micro-water content.

In the electrical industry, there are many hazardous gases that pollute the environment and even jeopardize human health, so timely detection and effective control of these hazardous gases is of great significance. In this work, the gas-sensitive properties of Pd-modified g-C3N4 interface for each hazardous gas molecule were investigated from a microscopic viewpoint, taking the hazardous gases (CO, NOx) that may be generated in the power industry as the detection target. Then, the performance of Pd-modifiedg-C3N4 was evaluated for practical applications as a gas sensor material. Novelly, an unconventional means was designed to briefly predict the effect of humidity on the adsorption properties of this sensor material. The final results found that Pd-modified g-C3N4 is most suitable as a potential gas-sensitizing material for NO2 gas sensors, followed by CO. Interestingly, Pd-modified g-C3N4 is less suitable as a potential gas-sensitizing material for NO gas sensors, but has the potential to be used as a NO cleaner (adsorbent). Unconventional simulation explorations of humidity effects show that in practical applications Pd-modified g-C3N4 remains a promising material for gas sensing in specific humidity environments. This work reveals the origin of the excellent properties of Pd-modified g-C3N4 as a gas sensor material and provides new ideas for the detection and treatment of these three hazardous gases.

Surface engineered multifunctional nano-systems for localised drug delivery against thyroid cancer: A review of current practices.

Thyroid cancer, the most prevalent cancer of the endocrine system and cervical region, has experienced a significant increase in incidence over recent decades. Nanomedicine has fundamentally revolutionized cancer treatment, particularly through the development of multifunctional nano-therapeutics. The progress in this field has been facilitated by the distinctive properties of nanomaterials, such as their capacity to perform several functions, be modified, and offer various detection methods. These features allow for non-invasive and practical diagnostic techniques through versatile imaging. Surface engineering plays a pivotal role in the design of multifunctional nano-systems for localized drug delivery against thyroid cancer. Nano-systems can be customized via surface modification techniques, such as functionalization with targeting ligands and inclusion of therapeutic drugs. This customization allows the nano-systems to specifically target cancer cells while reducing the impact on non-target cells. As a result, bovine serum albumin-coated nanostructures have emerged as powerful diagnostic and targeting nanosystems for thyroid cancer. This targeted strategy enhances the effectiveness of cancer treatment while reducing overall body toxicity. This comprehensive review aims to provide an extensive overview of the latest advancements in surface-engineered nanoparticle-based approaches for both diagnosing and treating thyroid cancer. It highlights the promising research endeavors aimed at creating novel and effective multifunctional nanomedicine for localized delivery to thyroid cancer sites. The review examines different nanomedicines that have been developed for cancer treatment and diagnosis. It also analyzes the current trends, future possibilities, and obstacles in this rapidly advancing sector. By synthesizing the current state of knowledge on surface-engineered multifunctional nano-systems, this review contributes to a better understanding of their potential applications in thyroid cancer treatment and paves the way for future research directions in this promising field of nanomedicine.

Inducible Fgf13 ablation alleviates cardiac fibrosis via regulation of microtubule stability.

Fibroblast growth factor (FGF) isoform 13, a distinct type of FGF, boasts significant potential for therapeutic intervention in cardiovascular dysfunctions. However, its impact on regulating fibrosis remains unexplored. This study aims to elucidate the role and mechanism of FGF13 on cardiac fibrosis. Here, we show that following transverse aortic constriction (TAC) surgery, interstitial fibrosis and collagen content increase in mice, along with reduced ejection fraction and fractional shortening, augmented heart mass. However, following Fgf13 deletion, interstitial fibrosis is decreased, ejection fraction and fractional shortening are increased, and heart mass is decreased, compared with those in the TAC group. Mechanistically, incubation of cardiac fibroblasts with transforming growth factor ß (TGFß) increases the expressions of types I and III collagen proteins, as well as α-smooth muscle actin (α-SMA) proteins, and enhances fibroblast proliferation and migration. In the absence of Fgf13, the expressions of these proteins are decreased, and fibroblast proliferation and migration are suppressed, compared with those in the TGFß-stimulated group. Overexpression of FGF13, but not FGF13 mutants defective in microtubule binding and stabilization, rescues the decrease in collagen and α-SMA protein and weakens the proliferation and migration function of the Fgf13 knockdown group. Furthermore, Fgf13 knockdown decreases ROCK protein expression via microtubule disruption. Collectively, cardiac Fgf13 knockdown protects the heart from fibrosis in response to haemodynamic stress by modulating microtubule stabilization and ROCK signaling pathway.

A double-branch convolutional neural network model for species identification based on multi-modal data.

For species identification analysis, methods based on deep learning are becoming prevalent due to their data-driven and task-oriented nature. The most commonly used convolutional neural network (CNN) model has been well applied in Raman spectra recognition. However, when faced with similar molecules or functional groups, the features of overlapping peaks and weak peaks may not be fully extracted using the CNN model, which can potentially hinder accurate species identification. Based on these practical challenges, the fusion of multi-modal data can effectively meet the comprehensive and accurate analysis of actual samples when compared with single-modal data. In this study, we propose a double-branch CNN model by integrating Raman and image multi-modal data, named SI-DBNet. In addition, we have developed a one-dimensional convolutional neural network combining dilated convolutions and efficient channel attention mechanisms for spectral branching. The effectiveness of the model has been demonstrated using the Grad-CAM method to visualize the key regions concerned by the model. When compared to single-modal and multi-modal classification methods, our SI-DBNet model achieved superior performance with a classification accuracy of 98.8%. The proposed method provided a new reference for species identification based on multi-modal data fusion.

Association Between Young Adult Characteristics and Blood Pressure Trajectories.

BACKGROUND: Blood pressure (BP) trajectories from young adulthood through middle age are associated with cardiovascular risk. We examined the associations of hypertension risk factors with BP trajectories among a large diverse sample. METHODS AND RESULTS: We analyzed data from young adults, aged 18 to 39 years, with untreated BP <140/90 mm Hg at baseline from Kaiser Permanente Southern California (N=355 324). We used latent growth curve models to identify 10-year BP trajectories and to assess the associations between characteristics in young adulthood and BP trajectories. We identified the following 5 distinct systolic BP trajectories, which appeared to be determined mainly by the baseline BP with progressively higher BP at each year: group 1 (lowest BP trajectory, 7.9%), group 2 (26.5%), group 3 (33.0%), group 4 (25.4%), and group 5 (highest BP trajectory, 7.3%). Older age (adjusted odds ratio for 30-39 versus 18-29 years, 1.23 [95% CI, 1.18-1.28]), male sex (13.38 [95% CI, 12.80-13.99]), obesity (body mass index ≥30 versus 18.5-24.9 kg/m2, 14.81 [95% CI, 14.03-15.64]), overweight (body mass index 25-29.9 versus 18.5-24.9 kg/m2, 3.16 [95% CI, 3.00-3.33]), current smoking (1.58 [95% CI, 1.48-1.67]), prediabetes (1.21 [95% CI, 1.13-1.29]), diabetes (1.60 [95% CI, 1.41-1.81]) and high low-density lipoprotein cholesterol (≥160 versus <100 mg/dL, 1.52 [95% CI, 1.37-1.68]) were associated with the highest BP trajectory (group 5) compared with the reference group (group 2). CONCLUSIONS: Traditional hypertension risk factors including smoking, diabetes, and elevated lipids were associated with BP trajectories in young adults, with obesity having the strongest association with the highest BP trajectory group.

Cardiovascular Risk Associated With Social Determinants of Health at Individual and Area Levels.

Importance: The benefit of adding social determinants of health (SDOH) when estimating atherosclerotic cardiovascular disease (ASCVD) risk is unclear. Objective: To examine the association of SDOH at both individual and area levels with ASCVD risks, and to assess if adding individual- and area-level SDOH to the pooled cohort equations (PCEs) or the Predicting Risk of CVD Events (PREVENT) equations improves the accuracy of risk estimates. Design, Setting, and Participants: This cohort study included participants data from 4 large US cohort studies. Eligible participants were aged 40 to 79 years without a history of ASCVD. Baseline data were collected from 1995 to 2007; median (IQR) follow-up was 13.0 (9.3-15.0) years. Data were analyzed from September 2023 to February 2024. Exposures: Individual- and area-level education, income, and employment status. Main outcomes and measures: ASCVD was defined as the composite outcome of nonfatal myocardial infarction, death from coronary heart disease, and fatal or nonfatal stroke. Results: A total of 26 316 participants were included (mean [SD] age, 61.0 [9.1] years; 15 494 women [58.9%]; 11 365 Black [43.2%], 703 Chinese American [2.7%], 1278 Hispanic [4.9%], and 12 970 White [49.3%]); 11 764 individuals (44.7%) had at least 1 adverse individual-level SDOH and 10 908 (41.5%) had at least 1 adverse area-level SDOH. A total of 2673 ASCVD events occurred during follow-up. SDOH were associated with increased risk of ASCVD at both the individual and area levels, including for low education (individual: hazard ratio [HR], 1.39 [95% CI, 1.25-1.55]; area: HR, 1.31 [95% CI, 1.20-1.42]), low income (individual: 1.35 [95% CI, 1.25-1.47]; area: HR, 1.28 [95% CI, 1.17-1.40]), and unemployment (individual: HR, 1.61 [95% CI, 1.24-2.10]; area: HR, 1.25 [95% CI, 1.14-1.37]). Adding area-level SDOH alone to the PCEs did not change model discrimination but modestly improved calibration. Furthermore, adding both individual- and area-level SDOH to the PCEs led to a modest improvement in both discrimination and calibration in non-Hispanic Black individuals (change in C index, 0.0051 [95% CI, 0.0011 to 0.0126]; change in scaled integrated Brier score [IBS], 0.396% [95% CI, 0.221% to 0.802%]), and improvement in calibration in White individuals (change in scaled IBS, 0.274% [95% CI, 0.095% to 0.665%]). Adding individual-level SDOH to the PREVENT plus area-level social deprivation index (SDI) equations did not improve discrimination but modestly improved calibration in White participants (change in scaled IBS, 0.182% [95% CI, 0.040% to 0.496%]), Black participants (0.187% [95% CI, 0.039% to 0.501%]), and women (0.289% [95% CI, 0.115% to 0.574%]). Conclusions and Relevance: In this cohort study, both individual- and area-level SDOH were associated with ASCVD risk; adding both individual- and area-level SDOH to the PCEs modestly improved discrimination and calibration for estimating ASCVD risk for Black individuals, and adding individual-level SDOH to PREVENT plus SDI also modestly improved calibration. These findings suggest that both individual- and area-level SDOH may be considered in future development of ASCVD risk assessment tools, particularly among Black individuals.