Medicinal plants and their extracts have been used as important sources for drug discovery. In particular, plant-derived natural compounds, including phytochemicals, antioxidants, vitamins, and minerals, are gaining attention as they promote health and prevent disease. Although several in vitro methods have been developed to confirm the biological activities of natural compounds, there is still considerable room to reduce time and cost. To overcome these limitations, several in silico methods have been proposed for conducting large-scale analysis, but they are still limited in terms of dealing with incomplete and heterogeneous natural compound data. Here, we propose a deep learning-based approach to identify the medicinal uses of natural compounds by exploiting massive and heterogeneous drug and natural compound data. The rationale behind this approach is that deep learning can effectively utilize heterogeneous features to alleviate incomplete information. Based on latent knowledge, molecular interactions, and chemical property features, we generated 686 dimensional features for 4,507 natural compounds and 2,882 approved and investigational drugs. The deep learning model was trained using the generated features and verified drug indication information. When the features of natural compounds were applied as input to the trained model, potential efficacies were successfully predicted with high accuracy, sensitivity, and specificity.

This study investigated the long-term functional changes in patients with moderate-to-severe ischemic stroke. In addition, we investigated whether there was a difference between the modified Barthel Index (MBI) and Functional Independence Measure (FIM) according to severity. To evaluate the changes in the long-term functional independence of the subjects, six evaluations were conducted over 2 years, and the evaluation was performed using MBI and FIM. A total of 798 participants participated in this study, of which 673 were classified as moderate and 125 as severe. During the first 3 months, the moderate group showed greater recovery than the severe group. The period of significant change in the National Institutes of Health Stroke Scale (NIHSS) score was up to 6 months after onset in the moderate group, and up to 3 months after onset in the severe group. In the severe group, MBI evaluation showed significant changes up to 6 months after onset, whereas FIM showed significant changes up to 18–24 months. Our results showed that functional recovery of patients with ischemic stroke in the 3 months after onset was greater in the moderate group than in the severe group. FIM is more appropriate than MBI for evaluating the functional status of patients with severe stroke.

Kim DY, et al. Brain Neurorehabil. 2023 Jul;16(2):e18. https://doi.org/10.12786/bn.2023.16.e18

Background and Purpose: Nutritional status can influence the outcomes and mortality of various diseases. The association between initial nutritional status and ischemic stroke outcomes, however, remains poorly understood. This study investigated whether the Controlling Nutritional Status (CONUT) score at admission could predict functional recovery, complications, and survival following an ischemic stroke. Methods: We enrolled a total of 938 patients experiencing their first acute ischemic stroke and categorized them into three groups based on their CONUT score at admission: CONUT 0–1, CONUT 2–4, and CONUT 5–12. The CONUT score was assessed using the serum albumin, total cholesterol, and lymphocyte count. We evaluated the incidence of complications during their hospital stay. Outcomes, including the Modified Rankin Scale (mRS), Functional Independence Measurement (FIM), Functional Ambulatory Classification (FAC), and mortality, were assessed at baseline, as well as at three and six months post-stroke. Results: CONUT scores were significantly associated with functional outcomes (mRS, FIM, and FAC) and mortality during the six-month follow-up period post-stroke (all p < 0.05). The CONUT 5–12 group exhibited significantly poorer improvements in mRS, FIM, and FAC scores (all p < 0.05) and a lower survival rate (p < 0.01) during the six-month follow-up compared to the CONUT 0–1 and CONUT 2–4 groups. Additionally, the incidence of pneumonia, urinary tract infections, pressure sores, falling injuries, and fractures was significantly higher in the CONUT 5–12 group than in the other groups (all p < 0.01). Conclusions: CONUT scores at admission are associated with functional recovery, mortality, and the incidence of complications following a first-ever ischemic stroke. Consequently, the early identification of patients at risk of malnutrition via CONUT scores can be crucial in enhancing patient assessment after an acute stroke.

Transcranial alternating current stimulation (tACS) is a neuromodulation procedure that is currently studied for the purpose of improving cognitive function in various diseases. A few studies have shown positive effects of tACS in Alzheimer’s disease (AD). However, the mechanism underlying tACS has not been established. The purpose of this study was to investigate the mechanism of tACS in five familial AD mutation (5xFAD) mouse models. We prepared twenty 4-month-old mice and divided them into four groups: wild-type mice without stimulation (WT-NT group), wild-type mice with tACS (WT-T group), 5xFAD mice without stimulation (AD-NT group), and 5xFAD mice with tACS (AD-T group). The protocol implemented was as follows: gamma frequency 200 μA over the bilateral frontal lobe for 20 min over 2 weeks. The following tests were conducted: excitatory postsynaptic potential (EPSP) recording, Western blot analysis (cyclic AMP response element-binding (CREB) proteins, phosphorylated CREB proteins, brain-derived neurotrophic factor, and parvalbumin) to examine the synaptic plasticity. The EPSP was remarkably increased in the AD-T group compared with in the AD-NT group. In the Western blot analysis, the differences among the groups were not significant. Hence, tACS can affect the long-lasting enhancement of synaptic transmission in mice models of AD.

This study investigated the synergistic effects of scalp acupuncture (SA) and repetitive transcranial magnetic stimulation (rTMS), known to be effective for cerebral infarction. This outcome-assessor-blinded, randomized controlled clinical trial included a per-protocol analysis to compare the efficacy of SA and electromagnetic convergence stimulation (SAEM-CS) and single or no stimulation. The trial was conducted with 42 cerebral infarction patients (control group, 12; SA group, 11; rTMS group, 8; SAEM-CS group, 11). All patient groups underwent two sessions of CSRT per day. SA, rTMS, and SAEM-CS were conducted once per day, 5 days per week, for 3 weeks. The primary outcome was evaluated using the Fugl–Mayer assessment (FMA). FMA Upper Extremity, FMA total, MBI, and FIM scores significantly increased in the rTMS group compared with the control group. Additionally, FMA Upper Extremity, FMA total, MBI and FIM scores significantly increased in the rTMS group compared with the SAEM-CS group. However, there were no significant changes in the SA or SAEM-CS groups. In conclusion, low-frequency rTMS in the contralesional hemisphere may have long-term therapeutic effects on upper extremity motor function recovery and improvements in activities of daily living. SAEM-CS did not show positive synergistic effects of SA and rTMS.