Blood-activating, depression-relieving formula alleviates post-stroke depression: mechanistic insights from network pharmacology and microglial validation

 You're so fucking incompetent you need to treat depression rather than having EXACT RECOVERY PROTOCOLS so that depression treatment isn't needed! I'd suggest taking up basket weaving; more in line with your IQ.

Blood-activating, depression-relieving formula alleviates post-stroke depression: mechanistic insights from network pharmacology and microglial validation

• N

  Na Zhao

• L

  Lumi Zhang

• W

  Wei Li

• Y

  Yiru Wang

• Z

  Zhengyu Zhu

• 

  Zhimin Wu *

• Department of Neurology, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Zhejiang, China

Abstract

Introduction: 

Post-stroke depression (PSD) is common and disabling, yet mechanism-based, multi-target therapies that jointly curb neuroinflammation and support cell survival are scarce. We evaluated a Blood-Activating, Depression-Relieving (BADR) herbal formula for effects on PSD-relevant molecular hubs and microglial phenotypes.

Methods: 

BADR constituents from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform were standardised and mapped to human protein targets. Target-disease interaction networks were assembled in Search Tool for the Retrieval of Interacting Genes/Proteins, clustered with Molecular Complex Detection, and functionally annotated via Kyoto Encyclopedia of Genes and Genomes Orthology-Based Annotation System (KEGG/GO). For experimental validation, BV2 microglia were activated with lipopolysaccharide (LPS; 24 h) and co-treated with BADR within a pre-established non-cytotoxic range; dexamethasone (1 μM) served as comparator. Outcomes included cytokines (IL-1β, TNF-α, IL-6; enzyme-linked immunosorbent assay), expression of selected nodes (EGFR, STAT3, JUN, PIK3CA, BCL2; quantitative real-time polymerase chain reaction/western blot), viability (Cell Counting Kit-8), and apoptosis (flow cytometry).

Results: 

Network analysis highlighted two dense modules enriched for PI3K-AKT, JAK–STAT, and neuroactive-ligand signaling. Hubs included EGFR, AKT1, STAT3, JUN, PIK3CA, and BCL2, with EGFR, STAT3, PIK3CA, JUN, and BCL2 prioritised for cellular validation based on topology, pathway relevance, and compound-target connectivity. In BV2 cells, BADR attenuated LPS-induced IL-1β, TNF-α, and IL-6 surges, improved viability, and reduced total apoptosis, with directionally comparable effects to dexamethasone. Mechanistically, BADR down-regulated EGFR/JUN/STAT3/PIK3CA and restored BCL2 at transcript and protein levels.

Conclusion: 

By converging network-level predictions with microglial phenotyping, the formula exerts coordinated anti-inflammatory and pro-survival effects centred on the EGFR-STAT3-PI3K nodes in a PSD-relevant context. These data provide a mechanistic rationale for further phosphorylation-level and in vivo validation toward multi-target PSD therapeutics.

More at link.

Towards routine biomechanical data collection in stroke rehabilitation: a usability comparison of IMU and markerless motion capture systems for functional upper-limb assessments

  'Assessments' DO NOTHING FOR RECOVERY! With no protocols based on the assessment; THIS WAS COMPLETELY FUCKING USELEESS! You're all fired! You, your mentors and senior researchers are obviously clueless on how to get survivors recovered! I'd suggest basket weaving for your mental capacity.

Towards routine biomechanical data collection in stroke rehabilitation: a usability comparison of IMU and markerless motion capture systems for functional upper-limb assessments

• Tim Unger,
• Xin Yao,
• Anna Schmitt,
• Lea Cebulla &
• Chris Easthope Awai 

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Objective measurement of upper-limb movement quality based on biomechanical data collected in clinical routine has the potential to enable precision neurorehabilitation at scale. However, integrating biomechanical data collection into daily clinical workflows remains challenging. In this exploratory study, we evaluated the usability of two technologies for routine kinematic data collection: an IMU-based version of the instrumented Action Research Arm Test (iARAT-IMU) and a MMC markerless motion capture (MMC) system. First, five physiotherapists independently operated the iARAT-IMU across seven clinical routine assessment sessions at a rehabilitation clinic in Switzerland to quantify learning curves, setup times, and usability. Second, we conducted a preference study in which the same therapists used both, the IMU- and MMC-system, during a standardized drinking task and completed quantitative and qualitative usability assessments focusing on system preference and underlying reasons. Results show that therapists rapidly learned to operate the tablet application for scoring the iARAT; however, the IMU system added approximately 11 min of setup time and sometimes required assistance. In contrast, the MMC workflow required approximately 2 min of additional time - well within the 5-minute maximum indicated a priori by therapists as acceptable for clinical routine and received consistently higher usability ratings. Most therapists preferred this approach due to greater efficiency and reduced patient burden. These findings highlight important design considerations for future digital assessment tools and indicate that MMC systems may offer a more feasible pathway toward routine biomechanical data collection for upper-limb assessments in clinical neurorehabilitation.

Towards routine biomechanical data collection in stroke rehabilitation: a usability comparison of IMU and markerless motion capture systems for functional upper-limb assessments

 'Assessments' DO NOTHING FOR RECOVERY! With no protocols based on the assessment; THIS WAS COMPLETELY FUCKING USELEESS! You're all fired! You, your mentors and senior researchers are obviously clueless on how to get survivors recovered! I'd suggest basket weaving for your mental capacity.

Towards routine biomechanical data collection in stroke rehabilitation: a usability comparison of IMU and markerless motion capture systems for functional upper-limb assessments

• Tim Unger,
• Xin Yao,
• Anna Schmitt,
• Lea Cebulla &
• Chris Easthope Awai 

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Objective measurement of upper-limb movement quality based on biomechanical data collected in clinical routine has the potential to enable precision neurorehabilitation at scale. However, integrating biomechanical data collection into daily clinical workflows remains challenging. In this exploratory study, we evaluated the usability of two technologies for routine kinematic data collection: an IMU-based version of the instrumented Action Research Arm Test (iARAT-IMU) and a MMC markerless motion capture (MMC) system. First, five physiotherapists independently operated the iARAT-IMU across seven clinical routine assessment sessions at a rehabilitation clinic in Switzerland to quantify learning curves, setup times, and usability. Second, we conducted a preference study in which the same therapists used both, the IMU- and MMC-system, during a standardized drinking task and completed quantitative and qualitative usability assessments focusing on system preference and underlying reasons. Results show that therapists rapidly learned to operate the tablet application for scoring the iARAT; however, the IMU system added approximately 11 min of setup time and sometimes required assistance. In contrast, the MMC workflow required approximately 2 min of additional time - well within the 5-minute maximum indicated a priori by therapists as acceptable for clinical routine and received consistently higher usability ratings. Most therapists preferred this approach due to greater efficiency and reduced patient burden. These findings highlight important design considerations for future digital assessment tools and indicate that MMC systems may offer a more feasible pathway toward routine biomechanical data collection for upper-limb assessments in clinical neurorehabilitation.

The rate-pressure product combined model within 24 h on admission predicts the 30-day mortality rate in conservatively treated patients with intracerebral hemorrhage

 If you're not going to do useful research like delivering recovery or preventing mortality instead of this crapola of predicting failure to recover, I'd suggest getting the hell out of stroke and doing something easier like basket weaving.

The rate-pressure product combined model within 24 h on admission predicts the 30-day mortality rate in conservatively treated patients with intracerebral hemorrhage

Hui ZhengYuguang TangHai ZhouXiang Ji^*

• Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China

Background and objectives: Recently, some literature has proposed new indicators such as rate-pressure product, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, etc. However, there has been no literature that has utilized these new indicators to establish a predictive model for assessing the risk of mortality in patients within 24 h on admission. Therefore, this study aims to build a predictive model that can rapidly assess the likelihood of mortality in patients within 24 h of admission.

Methods: The datasets used in this study are available from the corresponding author upon reasonable request. Patients were randomly assigned to the training or validation cohort based on a ratio of 7:3, which was implemented as internal validations for the final predictive models. In the training set, least absolute shrinkage and selection operator (LASSO) regression was employed to select predictive factors, followed by both univariate and subsequent multivariate analysis. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve.

Results: A total of 428 patients were included in our research. The final model included 4 independent predictors (Glasgow Coma Scale, hematoma volume, rate-pressure product, c-reactive protein) and was developed as a simple-to-use nomogram. The training set and internal validation set model’s C-index are 0.933 and 0.954, demonstrating moderate predictive ability with regard to risks of mortality. Compared to ICH score (AUC: 0.910 and 0.925), the net reclassification index (NRI) is 0.298 (CI = −0.105 to 0.701, p: 0.147) and integrated discrimination improvement (IDI) is 0.089 (CI = −0.049 to 0.228, p: 0.209). Our model is equally excellent as the classic ICH score model.

Conclusion: We developed a model with four independent risk factors to predict the mortality of ICH patients. Our predictive model is effective in assessing the risk of mortality in patients within 24 h on admission, which might be worth considering in clinical settings after further external validation.