Objectives: This study aimed to investigate the usefulness of a new non-contrast CT scan (NCCT) sign called the dHU, which represented the difference in mean Hounsfield unit values between follow-up and the initial NCCT for predicting 90-day poor functional outcomes in acute supratentorial spontaneous intracerebral hemorrhage(sICH) using deep convolutional neural networks.Methods: A total of 377 consecutive patients with sICH from center 1 and 91 patients from center 2 (external validation set) were included. A receiver operating characteristic (ROC) analysis was performed to determine the critical value of dHU for predicting poor outcome at 90 days. Modified Rankin score (mRS) > 3 or >2 was defined as the primary and secondary poor outcome, respectively. Two multivariate models were developed to test whether dHU was an independent predictor of the two unfavorable functional outcomes.Results: The ROC analysis showed that a dHU > 2.5 was a critical value to predict the poor outcomes (mRS > 3) in sICH. The sensitivity, specificity, and accuracy of dHU > 2.5 for poor outcome prediction were 37.5%, 86.0%, and 70.6%, respectively. In multivariate models developed after adjusting for all elements of the ICH score and hematoma expansion, dHU > 2.5 was an independent predictor of both primary and secondary poor outcomes (OR = 2.61, 95% CI [1.32,5.13], P = 0.006; OR = 2.63, 95% CI [1.36,5.10], P = 0.004, respectively). After adjustment for all possible significant predictors (p < 0.05) by univariate analysis, dHU > 2.5 had a positive association with primary and secondary poor outcomes (OR = 3.25, 95% CI [1.52,6.98], P = 0.002; OR = 3.42, 95% CI [1.64,7.15], P = 0.001).Conclusions: The dHU of hematoma based on serial CT scans is independently associated with poor outcomes after acute sICH, which may help predict clinical evolution and guide therapy for sICH patients.
<b><i>Objective:</i></b> To determine whether orbitofrontal cortex (OFC) function improves with blepharospasm (BSP) symptom remission using a verbal fluency task and near-infrared spectroscopy (NIRS). <b><i>Methods:</i></b> Nineteen BSP patients and 9 healthy controls (HCs) matched by gender and education were examined using NIRS. The BSP patients were divided into 2 groups based on the onset or remission of BSP symptoms. A covariance analysis was conducted to analyze the differences among the 3 groups to avoid the influence of different ages. The least significant difference was used to process the post hoc test. <b><i>Results:</i></b> The hemoglobin concentration and cerebral blood flow of the bilateral orbitofrontal area (channels 27, 31, 34, 37, and 39) were not significantly different between the BSP remission and HC groups (<i>p</i> > 0.05); however, both groups were significantly increased compared with the BSP onset group (BSP remission group vs. BSP onset group: <i>p</i> = 0.003, <i>p</i> = 0.018, <i>p</i> = 0.013, <i>p</i> = 0.001, and <i>p</i> = 0.011, respectively; BSP remission group vs. BSP onset group: <i>p</i> = 0.037, <i>p</i> = 0.044, <i>p</i> = 0.023, <i>p</i> = 0.016, and <i>p</i> = 0.025, respectively). <b><i>Conclusion:</i></b> This is the first investigation to control for symptom stages in BSP patients examined via NIRS. Cognitive ability and OFC function improve with BSP symptom remission. Thus, the OFC may be inter-connected with motor and cognitive symptoms in BSP.
The diversity of cognitive task paradigms using functional near-infrared spectroscopy (fNIRS) and the lack of theoretical explanations for these functional imaging atlases have greatly hindered the application of fNIRS in psychiatry. The fNIRS brain imaging based on multiple cognitive tasks could generally reflect the working patterns and neurovascular coupling changes in the prefrontal working memory network. By alternating the stimulation patterns of resting and task states, six typical symptom-related functional brain imaging waveforms related to psychiatric disorders are identified and three joint networks of the prefrontal working memory, namely, the attentional working memory primary coordination network, the perceptual content working memory secondary network, and the emotional-behavioral working memory executive network, are initially represented. This is the first attempt to characterize the cognitive, emotional, and behavioral regulation of the prefrontal working memory network using fNIRS, which may promote the application of fNIRS in clinical settings.
Objective: To observe the clinical effect of Pingle Zhanjin tincture on Carpal tunnel syndrome. Methods: The28 cases of patients of Carpal tunnel syndrome were treated by external application of Pingle Zhanjin tincture. The remission of the symptom was observed, as well as the median nerve electrophysiological examination in 3 weeks, to evaluate the efficacy. Results: There were 4 cases with recovery, 18 cases markedly effective, 5 cases effective and 1 case ineffective, the to-tal efficiency of 96.4%. Physical examination findings electrical nerve showed that the median nerve motor conduction distal latency decreased, amplitude increased, and that the sensory nerve conduction velocity increased; there was statistical signifi-cance(P0.05). Conclusion: Pingle Zhanjin Tincture can provide good clinical efficacy on Carpal tunnel syndrome.
Lower limb rehabilitation is essential for recovery post-injury, stroke, or surgery, improving functional mobility and quality of life. Traditional therapy, dependent on therapists' expertise, faces challenges that are addressed by rehabilitation robotics. In the domain of lower limb rehabilitation, machine learning is progressively manifesting its capabilities in high personalization and data-driven approaches, gradually transforming methods of optimizing treatment protocols and predicting rehabilitation outcomes. However, this evolution faces obstacles, including model interpretability, economic hurdles, and regulatory constraints. This review explores the synergy between machine learning and robotic-assisted lower limb rehabilitation, summarizing scientific literature and highlighting various models, data, and domains. Challenges are critically addressed, and future directions proposed for more effective clinical integration. Emphasis is placed on upcoming applications such as Virtual Reality and the potential of deep learning in refining rehabilitation training. This examination aims to provide insights into the evolving landscape, spotlighting the potential of machine learning in rehabilitation robotics and encouraging balanced exploration of current challenges and future opportunities.
Abstract Despite an increase in approved cancer-targeting antibody drugs over the last decade, the process of identifying novel therapeutic antibodies is routinely hampered by limitations in the discovery process. Such barriers include immune tolerance of highly homologous genes, antibody sequence humanization, clone selection and models for drug efficacy/safety evaluation. To overcome these challenges and increase the diversity of antibody paratopes and sequences that recognize functional epitopes, we developed the RenMice™ HiTS (Hyperimmune Target Specific) Platform, which consists of chromosome engineered mice with fully human immunoglobulin variable domains replacing the mouse loci, each with a specific target gene knocked out. Immunization of target-specific RenMice™ generates a sizeable diversity of antibodies, including those that recognize conserved regions between the antigen and the endogenous proteins of the immunized species. The platform is ideal for challenging targets, such as proteins with high homology across species, or multi-pass transmembrane proteins, such as GPCRs/ion channels, and can be used to generate antibodies that cross-react with human, monkey, dog, and mouse targets using a hybrid immunization strategy with both human and mouse/dog antigen. Generation of these species cross-reactive antibodies can be used for high-throughput in vivo efficacy screening in wild-type mice, and the preliminary response and toxicity can be assessed in dogs. Altogether, the RenMice™ HiTS platform facilitates the generation of antibodies that recognize novel epitopes and challenging targets while simultaneously allowing for a streamlined and successful preclinical phase based on in vivo efficacy and safety.
Sous Vide (SV) is a potential meat thermal processing technology. In our research, three scales, including molecular, meso, and macroscopic, were carried out to analyze the two-level meat colloidal system. Moreover, electromyography analysis was used to collaborate the texture results between human sensory evaluation and machine detection. Although the denaturation and dehydration of subcontinuous phase cytoskeletal protein are unavoidable even under 55 °C at 1 h or 65 °C at 0.5 h heating, the main-continuous phase collagen can achieve slow denaturation and sufficient conversion to gelatin if SV was applied. Different from collagen under high temperature processing, gelatin does not exert shrinkage stress to subcontinuous phase upon SV, and insignificant lateral contraction was revealed by differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). Thus, limited water migration and minimized cooking loss was achieved because of the integrity of the colloid system upon SV. Physical properties (low mechanical hardness and high sensory evaluation of tenderness) proved the tenderization effect of SV. Results showed that multiscale colloidal combined with electromyography study was useful in revealing the textual detail of pure meat or imitation meat.
Dendrobium huoshanense C. Z. Tang et S. J. Cheng (DH) is a traditional medicinal herb with a long history of medicinal use. DH has been recorded as protecting the gastrointestinal function. Modern pharmacology research shows that DH regulates intestinal flora, intestinal mucosal immunity, gastrointestinal peristalsis and secretion of digestive juices. At the same time, some studies have shown that DH has a good therapeutic effect on ulcerative colitis, but its mechanism of action has not been fully elucidated.
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