Intracerebral hemorrhage (ICH) is associated with high mortality and disability, and current treatments offer limited benefits for functional recovery. Human umbilical cord-derived mesenchymal stromal cell (hUCMSC) have strong proliferative, neuroprotective, and immunomodulatory properties, making them attractive for clinical translation. We evaluated the therapeutic effects of intravenously administered hUCMSCs in a collagenase-induced ICH model using male mice. Mice received low or high doses of hUCMSC once or twice within 72 h after ICH. Repeated high-dose administration significantly improved motor, cognitive, and affective behaviors. Although repeated administration of high-dose hUCMSCs produced the most pronounced behavioral recovery, most subsequent analyses were performed using the single-dose groups. Histological analysis showed reduced neuronal apoptosis and microglial activation, consistent with neuroprotection. In vitro assays demonstrated suppression of inflammatory gene expression and promotion of an anti-inflammatory phenotype in immune cells. Flow cytometry revealed selective reduction of pro-inflammatory macrophages and microglia, increased reparative subsets, and systemic modulation of myeloid dynamics. Our results suggest that intravenous hUCMSC administration at a higher dose confers robust neuroprotection through coordinated local and systemic immunomodulation, providing translational insights for clinical MSC therapy in ICH.

Piezo1 plays a key role in the immune response during sepsis. To date, our understanding of the role of Piezo1 in inflammatory diseases has mostly been limited to influencing vasomotor function and regulating inflammatory infiltration. Whether and how Piezo1 in macrophages is involved in developing septic cardiac dysfunction has never been explored. Here, we have successfully established a mouse model with myeloid cell-specific knockdown of Piezo1. The intraperitoneal injection of lipopolysaccharide (LPS) resulted in a significant increase in cardiac macrophage infiltration, as well as an increase in the expression of inflammatory factors and the inflammatory response. However, myeloid cell-specific knockdown of Piezo1 impaired this response, leading to an increase in macrophage polarization towards the M2 type and the decreased inflammatory response. As a result, myocardial injury caused by sepsis was attenuated. We have also demonstrated that the PI3K/AKT pathway is significantly activated after Piezo1 knockdown, resulting in reduced myocardial dysfunction. Our data indicate that myeloid cell-specific knockdown of Piezo1 can influence macrophage polarization and thus exert cardioprotective effects in a murine model of sepsis, providing potential ideas and targets for the treatment of infectious cardiac dysfunction.

Lateral flow immunoassay (LFIA) is a vital point-of-care testing (POCT) technique that is widely used for on-site detection and in vitro diagnosis. Many diseases, particularly cardiovascular diseases (CVDs), require the quantitative detection of multiple biomarkers across a broad dynamic range. Recurrent viral infections like COVID-19 elevate CVDs risk, necessitating early warning and prognostic monitoring, especially based on POCT of multiple blood biomarkers of D-dimer, NT-proBNP, and cTnI across a broad range from pg/mL to μg/mL. Traditional LFIAs lack ultrasensitivity and broad-range quantification. We design the surface chemistry-mediated template-free assembly of metal-aggregation-induced emission luminogens (AIEgen) framework@gold nanoparticles (MAF@AuNPs) for developing ultrasensitive and dynamic dual-quantitative LFIA (ddLFIA). The template-free self-assembled MAF@AuNPs have strong fluorescent and plasmonic properties, avoiding complicated synthesis, chemical modifications, and covalent conjugations, thus leading to highly convenient and versatile visual POCT. MAF@AuNPs ddLFIA achieves a normal detection at ng/mL using chromogenic AuNPs and ultrasensitive detection at pg/mL using fluorogenic MAFs, for which the fluorescence signal is 10²-10³ times more sensitive than the color signal. MAFs and AuNPs are functionally complementary to form a dynamic, broad-range quantification system covering over 5 orders of magnitude, at the same time having a naked eye sensitivity near 1 pg/mL. The visual POCT using MAF@AuNPs ddLFIA aligns well with clinical chemiluminescent assays. MAF@AuNPs ddLFIA perfectly matches ultrasensitive and broad-range multiple biomarker detections for clinical CVDs diagnosis.

Homozygous familial hypercholesterolemia (HoFH) is a leading cause of premature atherosclerotic cardiovascular disease (ASCVD) and early mortality if left untreated or inadequately treated.

This study presents 2 pediatric cases of early death from Pakistan due to familial hypercholesterolemia (FH) and provides a systematic review of similar cases reported globally.

Genetic analysis was conducted using next-generation sequencing to confirm pathogenic variants. For the systematic review, published reports of individuals with FH who died before the age of 18 years were identified. Data were extracted on demographic features, personal and family history, genetic variants, treatment given, and cause of death.

Both patients, born to consanguineous families, presented with markedly elevated low-density lipoprotein cholesterol (LDL-C) levels (792 mg/dL [20.48 mmol/L] and 896 mg/dL [23 mmol/L], respectively), multiple xanthomas, and early-onset myocardial infarction, and died at the ages of 5 and 7 years, respectively. Their genetic analysis revealed a pathogenic frameshift variant in the LDLR gene: NM_000527.5: c.2416dupG (p.Val806GlyfsTer11). The systematic review included 12 studies reporting pediatric FH-related mortality. Common clinical features included tendon xanthomas, elevated LDL-C levels, family history, and early-onset ASCVD. Genetic testing was performed in a few cases, which revealed pathogenic variations in the LDLR gene. Most of the patients received inadequate lipid-lowering therapy. The most common causes of death were severe coronary artery disease, myocardial infarction, and sudden cardiac arrest.

Our 2 cases and the accompanying systematic review identified additional cases of premature mortality. Collectively, these findings highlight diagnostic delays and inadequate treatment as common factors among patients who died prematurely.

The platelet to white blood cell ratio (PWR) has shown prognostic value in many diseases. Yet its predictive utility for patients with atherosclerotic cardiovascular disease (ASCVD) who receive care in the intensive care unit (ICU) remains uncertain. We examined whether PWR at ICU admission is associated with short term all cause mortality among ICU patients with ASCVD.

We used the MIMIC IV and eICU databases to study the association between PWR and 30 day all cause mortality in critically ill patients with ASCVD. Patients were grouped by PWR quartiles. Collinearity was checked with the variance inflation factor (VIF). Nonlinearity was assessed with restricted cubic splines(RCS). Survival was compared with Kaplan Meier(KM) curves and the log rank test. Hazard ratios were estimated with stratified and adjusted Cox models. We also built machine learning models that included PWR and clinical features selected with the Boruta algorithm to predict 30 day mortality. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC). External validation in the eICU database was used to assess generalizability.

A total of 10 943 ICU patients with ASCVD were included, 62 % were men, and the median age was 71 years. The highest PWR quartile had a lower 30 day all cause mortality than the lowest quartile, 11 % versus 15 % (p < 0.001). In multivariable Cox models the highest quartile had a lower risk (HR 0.80, 95 % CI 0.67 to 0.95, p = 0.012). RCS suggested a nonlinear association. Age modified the association, with a stronger protective effect in patients younger than 70 years (HR 0.64, 95 % CI 0.47 to 0.87, interaction p < 0.001). The best machine learning model achieved an AUC of 0.812 in internal validation and 0.80 in external validation. SHAP analysis showed that higher PWR was linked to a lower predicted risk of death.

PWR independently predicts 30 day all cause mortality in ICU patients with ASCVD. These findings support the use of PWR for risk stratification and to inform management in critical care for ASCVD.

Optical Coherence Tomography Angiography (OCTA) is a revolutionary technology widely used in the diagnosis and management of fundus, skin and cardiovascular diseases. However, unavoidable movements, such as breathing, often introduce motion artifacts into OCTA images, which can significantly degrade image quality, obscure critical vascular details, and reduce the diagnostic reliability of the modality. Although recent advances in learning-based image inpainting methods for OCTA enface images have made notable progress in artifact removal, these methods typically require large amounts of accurately labeled data and the generation of pseudo stripes to construct paired training datasets. Additionally, the abundant structural information and flow intensity signals available in OCTA B-scans are often under-utilized. Here we proposed a novel method:B-scans to Enface Conditional Diffusion Guidance (B2E-CDG), which translates signal-void B-scans into normal B-scans. Moreover, the normal B-scans were introduced in a connection manner and the specified reference B-scans in a gradient-based manner as style feature guidance within a diffusion model. Importantly, conditional guidance facilitates a more controlled and precise generation process for flow signal recovery in B-scans. Notably, our method eliminates the need for labeled datasets and pseudo stripes, due to the repetitive scanning nature of OCTA inherently provides paired signal-void and normal B- scans. Our results demonstrated that B2E-CDG effectively removes motion artifacts and restores vascular and structural details. The proposed method shows superior performance in vascular recovery and artifact removal metrics, thereby improving the clinical utility and diagnostic reliability of OCTA.

Wearable devices with embedded photoplethysmography (PPG) enable continuous non-invasive monitoring of cardiac activity, offering a promising strategy to reduce the global burden of cardiovascular diseases. However, monitoring during daily life introduces motion artifacts that can compromise the signals. Traditional signal decomposition techniques often fail with severe artifacts. Deep learning denoisers are more effective but have poorer interpretability, which is critical for clinical acceptance. This study proposes a framework that combines the advantages of both signal decomposition and deep learning approaches.

We leverage algorithm unfolding to integrate prior knowledge about the PPG structure into a deep neural network, improving its interpretability. A learned convolutional sparse coding model encodes the signal into a sparse representation using a learned dictionary of kernels that capture recurrent morphological patterns. The network is trained for denoising using the PulseDB dataset and a synthetic motion artifact model from the literature. Performance is benchmarked with PPG during daily activities using the PPG-DaLiA dataset and compared with two reference deep learning methods.

On the synthetic dataset, the proposed method, on average, improved the signal-to-noise ratio (SNR) from -7.06 dB to 11.23 dB and reduced the heart rate mean absolute error (MAE) by 55%. On the PPG-DaLiA dataset, the MAE decreased by 23%. The proposed method obtained higher SNR and comparable MAE to the reference methods.

Our method effectively enhances the quality of PPG signals from wearable devices and enables the extraction of meaningful waveform features, which may inspire innovative tools for monitoring cardiovascular diseases.

The growing prevalence of Parkinson's disease (PD) drives the need for better therapies. Chinese patent medicines (CPMs) can complement conventional western medicine (CWM) in treating PD, but their variety complicates clinical choices. This study systematically ranks CPMs combined with CWM to guide treatment decisions.

We systematically searched for randomized controlled trials (RCTs) of CPM for the treatment of PD in China National Knowledge Infrastructure (CNKI), Wanfang Database, China Weipu Science and Technology Journal Database (VIP), Chinese Biomedical Literature Database (CBM), PubMed, Embase, Web of Science, and Cochrane Library from the establishment of the database to January 2nd, 2025. R 4.4.2 and Stata 14.0 software were used for data analysis.

We analyzed 35 RCTs comprising 3281 patients and 11 CPMs. Among the CPMs evaluated, Bushen Huoxue capsules (BSHX) showed higher total effective rates, while Tianma Gouteng granules (TMGT) led in reducing Unified Parkinson's Disease Rating Scale (UPDRS) total scores and improving Mini-Mental State Examination (MMSE) performance. Zishen Pingchan granules (ZSPC) were most effective in improving the Parkinson's Disease Sleep Scale (PDSS) score. Qishen Huanwu capsules (QSHW) excelled in reducing cystatin C (Cys-C) and homocysteine (Hcy). Xifeng Dingchan pills (XFDC) maximized superoxide dismutase (SOD) activity, and Tiandan Tongluo capsules (TDTL) lowered malondialdehyde (MDA) levels.

This study demonstrated the efficacy of combining CPMs with CWM for PD, identifying QSHW and TMGT as the optimal CPMs. QSHW markedly reduced Hcy and Cys-C levels, and TMGT improved MMSE and UPDRS scores. However, their personalized application necessitates validation in large-scale RCTs.

This study aimed to evaluate the pharmacological effects of Shengmai Injection(SMI) on cerebral ischemia/reperfusion(I/R) injury and explore its underlying mechanisms in regulating inflammatory responses following cerebral ischemia. Male SD rats were randomly divided into a sham group, a model group, a low-dose SMI group(2 mL·kg~(-1)), a medium-dose SMI group(4 mL·kg~(-1)), a high-dose SMI group(6 mL·kg~(-1)), and a positive control group(Ginaton Injection at 4 mL·kg~(-1)), with 16 rats in each group. A rat model of middle cerebral artery occlusion/reperfusion(MCAO/R) was established using the intraluminal suture method. Drug administration began on the day of modeling and continued for three consecutive days. The therapeutic effects of SMI on brain injury in MCAO/R rats were evaluated using neurological function scoring, cerebral blood flow monitoring, cerebral infarction area determination, hematoxylin-eosin(HE) staining, and Nissl staining. The predominant therapeutic mechanisms and key signaling pathways involved in SMI treatment of cerebral ischemia in the rat model were explored using proteomic analysis. The expression of major indicators and related proteins was subsequently validated using enzyme-linked immunosorbent assay(ELISA) and Western blot. In addition, targeted metabolomics was employed to investigate downstream arachidonic acid metabolism of the related signaling pathways. RESULTS:: show that compared with the sham group, the model group showed significantly increased neurological function scores and cerebral infarction area, accompanied by significantly decreased cerebral blood flow and Nissl body density. Compared with the model group, the SMI-treated groups showed significantly decreased neurological function scores and cerebral infarction area, accompanied by significantly increased cerebral blood flow and Nissl body density. The proteomic analysis results showed that the inflammatory response was the main process involved in SMI's therapeutic effect on cerebral ischemia, with the mitogen-activated protein kinase(MAPK) signaling pathway identified as the key signaling pathway. ELISA and Western blot results showed that SMI significantly reduced the expression levels of inflammatory factors in brain tissue of MCAO/R rats, including tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), and interleukin-6(IL-6), with significantly regulated expression levels of phosphorylated JNK(p-JNK)/JNK and p-p38 MAPK/p38 MAPK. Targeted metabolomics further reveals that SMI significantly reduced the levels of arachidonic acid(AA) and its metabolites, such as prostaglandin D_2(PGD_2), prostaglandin E_2(PGE_2), 12(S)-hydroxyeicosatetraenoic acid [12(S)-HETE], and 15(S)-hydroxyeicosatetraenoic acid [15(S)-HETE], and other pro-inflammatory mediators, accompanied by a reduced ratio of thromboxane B_2(TXB_2) to 6-keto-prostaglandin F_(1α)(6-keto-PGF_(1α)). In conclusion, SMI can effectively alleviate cerebral ischemia injury, primarily through modulation of the inflammatory response. The potential mechanism is closely related to the regulation of the MAPK signaling pathway and the downstream arachidonic acid metabolism.

The number of adolescents with depression has increased in mental health services over the past decade. New intervention options are needed for these patients.

Patients aged 13 to 17 years with depression are recruited from adolescent mental health services. Participants will be randomized into two groups. The treatment group will attend dance movement therapy for 12 weeks in addition to treatment as usual, while the control group will receive treatment as usual. The outcome measures include questionnaires and interviews assessing depression symptoms and body image. The primary outcome measures are the Beck Depression Inventory (BDI-21) and the Young Person's Clinical Outcome in Routine Evaluation (YP-CORE). Additional measures include the Adolescent Depression Rating Scale (ADRS) and a body image scale.

This study will provide information about the effectiveness of dance-movement therapy for adolescents with depression in a naturalistic environment. Variety in the choice of therapies may aid in quicker improvement and prevent prolonged depression.

This protocol was registrated 29.8.2022 at ClinicalTrials.gov. with identifier. Clinical trial number 07293806.