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NaV1.4 is a voltage-gated sodium channel subtype that is predominantly expressed in skeletal muscle cells. It is essential for producing action potentials and stimulating muscle contraction, and mutations in NaV1.4 can cause various muscle disorders. The discovery of the cryo-EM structure of NaV1.4 in complex with β1 has opened new possibilities for designing drugs and toxins that target NaV1.4. In this review, we summarize the current understanding of channelopathies, the binding sites and functions of chemicals including medicine and toxins that interact with NaV1.4. These substances could be considered novel candidate compounds or tools to develop more potent and selective drugs targeting NaV1.4. Therefore, studying NaV1.4 pharmacology is both theoretically and practically meaningful.

BackgroundFreezing of gait (FOG) is a common and disabling phenomenon in patients with Parkinson’s disease (PD), but effective treatment approach remains inconclusive. Dysfunctional emotional factors play a key role in FOG. Since primary motor cortex (M1) connects with prefrontal areas via the frontal longitudinal system, where are responsible for emotional regulation, we hypothesized M1 may be a potential neuromodulation target for FOG therapy. The purpose of this study is to explore whether high-frequency rTMS over bilateral M1 could relieve FOG and emotional dysregulation in patients with PD.MethodsThis study is a single-center, randomized double-blind clinical trial. Forty-eight patients with PD and FOG from the Affiliated Hospital of Xuzhou Medical University were randomly assigned to receive 10 sessions of either active (N = 24) or sham (N = 24) 10 Hz rTMS over the bilateral M1. Patients were evaluated at baseline (T0), after the last session of treatment (T1) and 30 days after the last session (T2). The primary outcomes were Freezing of Gait Questionnaire (FOGQ) scores, with Timed Up and Go Test (TUG) time, Standing-Start 180° Turn (SS-180) time, SS-180 steps, United Parkinson Disease Rating Scales (UPDRS) III, Hamilton Depression scale (HAMD)-24 and Hamilton Anxiety scale (HAMA)-14 as secondary outcomes.ResultsTwo patients in each group dropped out at T2 and no serious adverse events were reported by any subject. Two-way repeated ANOVAs revealed significant group × time interactions in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14. Post-hoc analyses showed that compared to T0, the active group exhibited remarkable improvements in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14 at T1 and T2. No significant improvement was found in the sham group. The Spearman correlation analysis revealed a significantly positive association between the changes in HAMD-24 and HAMA-14 scores and FOGQ scores at T1.ConclusionHigh-frequency rTMS over bilateral M1 can improve FOG and reduce depression and anxiety in patients with PD.

With the deepening of the concept of green, low-carbon, and sustainable development, the continuous growth of the ownership of new energy vehicles has led to increasing public concerns about the traffic safety issues of these vehicles. In order to conduct research on the traffic safety of new energy vehicles, three sampling methods, namely, Synthetic Minority Over-sampling Technique (SMOTE), Edited Nearest Neighbours (ENN), and SMOTE-ENN hybrid sampling, were employed, along with cost-sensitive learning, to address the problem of imbalanced data in the UK road traffic accident dataset. Three algorithms, eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost), were selected for modeling work. Lastly, the evaluation criteria used for model selection were primarily based on G-mean, with AUC and accuracy as secondary measures. The TreeSHAP method was applied to explain the interaction mechanism between accident severity and its influencing factors in the constructed models. The results showed that LightGBM had a more stable overall performance and higher computational efficiency. XGBoost demonstrated a balanced combination of computational efficiency and model performance. CatBoost, however, was more time-consuming and showed less stability with different datasets. Studies have found that people using fewer protective means of transportation (bicycles, motorcycles) and vulnerable groups such as pedestrians are susceptible to serious injury and death.

Agricultural products may deteriorate due to various reasons during storage and transportation, resulting in serious losses. However, the mechanism of deterioration is complex, and many mechanisms are currently unclear. In recent years, the rapid development of omics technologies, such as genomics, proteomics, transcriptomics, and metabolomics, has led to breakthroughs in exploring the mechanism of product quality changes during the storage and transportation of agricultural products, and also help to understand molecular mechanisms. By using omics technology to gain a deeper understanding of the changes in agricultural products during storage and transportation, more efficient, environmentally friendly, and resource saving storage and transportation methods can be developed, providing a research foundation for the sustainability of China’s agricultural food system. In addition, research on omics technology has provided theoretical support for screening more suitable storage methods and transportation conditions. This review presents the potential application omics technologies in agricultural product storage and transportation. The application examples of omics technology in the storage and transportation process of agricultural products were discussed. Finally, the prospects indicate that omics technology has unlimited potential.

Legal prediction presents one of the most significant challenges when applying artificial intelligence (AI) to the legal field. The legal system is a complex adaptive system characterized by the ambiguity of legal language and the diversity of value functions. The imprecision and procedural knowledge inherent in law makes judicial issues difficult to be expressed in a computer symbol system. Current semantic processing and machine learning technologies cannot fully capture the complex nature of legal relations, thereby raising doubts about the accuracy of legal predictions and reliability of judicial models. Cognitive computing, designed to emulate human brain functions and aid in enhancing decision-making processes, offers a better understanding of legal data and the processes of legal reasoning. This paper discusses the advancements made in cognitive methods applied to legal concept learning, semantic extraction, judicial data processing, legal reasoning, understanding of judicial bias, and the interpretability of judicial models. The integration of cognitive neuroscience with law has facilitated several constructive attempts, indicating that the evolution of cognitive law could be the next frontier in the intersection of AI and legal practice.

Myocardial fibrosis, which is a common pathological manifestation of many cardiovascular diseases, is characterized by excessive proliferation, collagen deposition and abnormal distribution of extracellular matrix fibroblasts. In clinical practice, modern medicines, such as diuretic and β receptor blockers, and traditional Chinese medicines, such as salvia miltiorrhiza and safflower extract, have certain therapeutic effects on myocardial fibrosis. We reviewed some representative modern medicines and traditional Chinese medicines (TCMs) and their related molecular mechanisms for the treatment of myocardial fibrosis. These drugs alleviate myocardial fibrosis by affecting related signaling pathways and inhibiting myocardial fibrosis-related protein synthesis. This review will provide more references and help for the research and treatment of myocardial fibrosis.

BackgroundLow-dose computed tomography (LDCT) has been promoted as a promising screening strategy for early detection of lung cancer. China released the latest lung cancer screening guideline in 2021. The compliance of the individuals who received LDCT for lung cancer screening with the guideline is unknown yet. It is necessary to summarize the distribution of guideline-defined lung cancer–related risk factors in the Chinese population so as to inform the selection of target population for the future lung cancer screening.MethodsA single-center, cross-sectional study design was adopted. All participants were individuals who underwent LDCT at a tertiary teaching hospital in Hunan, China, between 1 January and 31 December 2021. LDCT results were derived along with guideline-based characteristics for descriptive analysis.ResultsA total of 5,486 participants were included. Over one-quarter (1,426, 26.0%) of the participants who received screening did not meet the guideline-defined high-risk population, even among non-smokers (36.4%). Most of the participants (4,622, 84.3%) were found to have lung nodules, while no clinical intervention was required basically. The detection rate of positive nodules varied from 46.8% to 71.2% when using different cut-off values for positive nodules. Among non-smoking women, ground glass opacity appeared to be more significantly common compared with non-smoking men (26.7% vs. 21.8%).ConclusionOver one-quarter of individuals who received LDCT screening did not meet the guideline-defined high-risk populations. Appropriate cut-off values for positive nodules need to be continuously explored. More precise and localized criteria for high-risk individuals are needed, especially for non-smoking women.

ObjectiveArterial spasm is proved to be an inducer of cerebral ischemia and cerebral infarction, while when a venous spasm occurs, cerebral edema is seen to be caused by a disturbance in cerebral blood flow. However, it is unclear and unproven whether venous spasm occurs after subarachnoid hemorrhage (SAH). To provide the theoretical basis for treating cerebral vasospasm after SAH, magnetic resonance imaging (MRI) was employed to observe the changes in the diameter of deep cerebral veins in rabbits after SAH.MethodsFourteen New Zealand rabbits were randomly divided into the SAH group (n = 10) and the normal saline group (NS group, n = 4). Specifically, the SAH models were established by the ultrasound-guided double injections of blood into cisterna magna. Moreover, the MRI was performed to observe the changes in the diameter of deep cerebral veins (internal cerebral vein, basilar vein, and great cerebral vein) and basilar artery before modeling (0 d) and 1, 3, 5, 7, 9, and 11 d after modeling.ResultsIn the SAH group, the diameter of the basilar artery showed no evident change on the 1st d. However, it became narrower obviously on the 3rd d and 5th d, and the stenosis degree was more than 30%. The diameter gradually relieved from 7th to 9th d, and finally returned to normal on the 11th d. Moreover, the diameter of the internal cerebral vein significantly narrowed on the 1st d, the stenosis degree of which was 19%; the stenosis then relieved slightly on the 3rd d (13%), reached the peak (34%) on the 5th d, and gradually relieved from 7th d to 11th d. Moreover, the stenosis degree of the basilar vein was 18% on the 1st d, 24% on the 3rd d, and reached the peak (34%) on the 5th d.ConclusionAfter SAH in rabbits, the cerebral vasospasm was seen to occur in the basilar artery, and likewise, spasmodic changes took place in the deep cerebral vein. Furthermore, the time regularity of spasmodic changes between the cerebral vein and basilar artery was of significant difference, indicating that the venous vasospasm resulted in active contraction.

α-Keto acids are important raw materials for pharmaceuticals and functional foods, which could be produced from cheap feed stock by whole cell biocatalysts containing L-amino acid deaminases (L-AADs). However, the production capacity is limited by the low activity of L-AADs. The L-AAD mediated redox reaction employs the electron transport chain to transfer electrons from the reduced FADH2 to O2, implying that the interaction between L-AAD and the cell membrane affects its catalytic activity. To improve the catalytic activity of L-AAD from Proteus vulgaris, we redesigned the membrane-bound hydrophobic insertion sequences (INS, residues 325–375) by saturation mutagenesis and high-throughput screening. Mutants D340N and L363N exhibited higher affinity and catalytic efficiency for L-leucine, with half-life 1.62-fold and 1.28-fold longer than that of wild-type L-AAD. D340N catalyzed L-leucine to produce 81.21 g⋅L–1 α-ketoisocaproate, with a bioconversion rate of 89.06%, which was 17.57% higher than that of the wild-type. It is predicted that the mutations enhanced the interaction between the protein and the cell membrane.

BackgroundDepression accompanying chronic pain (CP) is one of the most common comorbid psychiatric disorders. This study aimed to investigate the effectiveness of transcutaneous auricular vagus nerve stimulation (taVNS) combined with electroacupuncture at Baihui (GV20) and Yintang (GV29) acupoints compared with citalopram.MethodsSixty patients with depression and pain comorbidity were enrolled in a prospective 8-week, single-blind, randomized controlled trial. Participants were randomly assigned to receive either taVNS combined with electroacupuncture treatment (taVNS: 8 weeks, 3 sessions per week; electroacupuncture: 8 weeks, twice per day, no drugs) or citalopram treatment (8 weeks, 40 mg/day). The primary outcome was Montgomery–Åsberg Depression Rating Scale (MADRS). The secondary endpoints were evaluated using the McGill Pain Questionnaire (SF-MPQ), self-reported 36-Item Short Form Survey (SF-36), Pittsburgh Sleep Quality Index (PSQI), Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Scale (HAMA).ResultsBoth the taVNS combined with electroacupuncture and citalopram groups had significant reductions in depressive and pain symptoms, as indicated by the decrease in MARDS and SF-MPQ scores. Regarding the analgesic effect, the pain intensity score of the SF-MPQ showed a larger reduction with citalopram than with taVNS combined with electroacupuncture at 6 weeks (P = 0.036). The reduction in the BP score of the SF-36 was higher at week 4 (P = 0.000), with no significant difference observed at week 8 (P = 0.1110). This result indicated that the pain intensity can be improved rapidly with citalopram compared with taVNS combined with electroacupuncture. Similarly, the comparison of PSQI scores at 4, 6, and 8 weeks indicates that there was no significant difference between groups, except in the use of sleeping medications. At week 6, higher medication use was found in the citalopram group than in the taVNS combined with electroacupuncture group (P = 0.049).ConclusionIn summary, compared with citalopram, taVNS combined with electroacupuncture produces similar positive effects on depressive and pain symptoms in patients with depression and chronic pain, which last for at least 8 weeks.

Antimicrobial peptides (AMPs), as an important part of the innate immune system of an organism, is a kind of promising drug candidate for novel antibiotics due to their unique antibacterial mechanism. However, the discovery of novel AMPs is facing a great challenge due to the complexity of systematic experiments and the poor predictability of antimicrobial activity. Here, a novel and comprehensive screening system, the Multiple Descriptor Multiple Strategy (MultiDS), was proposed based on 59 physicochemical and structural parameters, three strategies, and four algorithms for the mining of α-helical AMPs. This approach was applied to mine the encrypted peptide antibiotics from the global human genome, including introns and exons. A library of approximately 70 billion peptides with 15–25 amino acid residues was screened by the MultiDS system and generated a list of peptides with the Multiple Descriptor Index (MD index) scores, which was the core part of the MultiDS system. Sixty peptides with top MD scores were chemically synthesized and experimentally tested their antimicrobial activity against 10 kinds of Gram-positive bacteria, Gram-negative bacteria (including drug-resistant pathogens). A total of fifty-nine out of 60 (98.3%) peptides exhibited antimicrobial activity (MIC ≤ 64 μg/mL), and 24 out of 60 (40%) peptides showed high activity (MIC ≤ 2 μg/mL), validating the MultiDS system was an effective and predictive screening tool with high hit rate and superior antimicrobial activity. For further investigation, AMPs S1, S2, and S3 with the highest MD scores were used to treat the skin infection mouse models in vivo caused by Escherichia coli, drug-resistance Escherichia coli, and Staphylococcus aureus, respectively. All of S1, S2, and S3 showed comparable therapeutic effects on promoting infection healing to or even better than the positive drug levofloxacin. A mechanism study discovered that rapid bactericidal action was caused by cell membrane disruption and content leakage. The MultiDS system not only provides a high-throughput approach that allows for the mining of candidate AMPs from the global genome sequence but also opens up a new route to accelerate the discovery of peptide antibiotics.

Radiations towards the continuum not only brings non-Hermicity to photonic systems but also provides observable channels for understanding their intrinsic physics underneath. In this article, we review the fundamental physics and applications of topological polarization singularities, which are defined upon the far-field radiation of photonic systems and characterized by topological charges as the winding numbers of polarization orientation around a given center. A brief summarizing of topological charge theory is presented. A series of applications related to topological polarization singularities are then discussed.

In this work, nanosized P-doped SnO2 (SnO2-P) was prepared by a sol–gel method as a catalyst for the V3+/V2+ redox reaction in vanadium redox flow battery. Compared with SnO2, the electrochemical performance of SnO2-P is significantly improved. This is because P doping provides more active sites and shows greatly improved electrical conductivity, thereby increasing the electron transfer rate. As a result, SnO2-P shows better catalytic performance than SnO2. The SnO2-P modified cell is designed, and it exhibits an increase of 47.2 mA h in discharge capacity and 8.7% in energy efficiency compared with the pristine cell at 150 mA cm−2. These increases indicate that the modified cell has a higher electrolyte utilization rate. This study shows that SnO2-P is a new and efficient catalyst for vanadium redox flow battery.

In this study, a SnO2-carbon nanotube (SnO2-CNT) composite as a catalyst for vanadium redox flow battery (VRFB) was prepared using a sol-gel method. The effects of this composite on the electrochemical performance of VO2+/VO2+, and on the V2+/V3+ redox reactions and VRFB performance were investigated. The SnO2-CNT composite has better catalytic activity than pure SnO2 and CNT due to the synergistic catalysis of SnO2 and the CNT. SnO2 mainly provides the catalytic active sites and the CNTs mainly provide the three-dimensional structure and high electrical conductivity. Therefore, the SnO2-CNT composite has a larger specific surface area and an excellent synergistic catalytic performance. For cell performance, it was found that the SnO2-CNT cell shows a greater discharge capacity and energy efficiency. In particular, at 150 mA cm−2, the discharge capacity of the SnO2-CNT cell is 28.6 mAh higher than that of the pristine cell. The energy efficiency of the modified cell (7%) is 7.2% higher than that of the pristine cell (62.8%). This study shows that the SnO2-CNT is an efficient and promising catalyst for VRFB.

Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network (CaSCN), winner-take-all and cortex–subcortex covariance network (WTA-CSSCN), and modulation analysis of structural covariance network (MOD-SCN) have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface (GUI) toolkit of brain structural covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily.

Transcutaneous auricular vagus nerve stimulation (taVNS) has gained growing interest as a non-invasive and non-pharmacologic treatment option in various neurological and psychiatric disorders. Animal experiments and clinical trials confirm that taVNS at the auricular concha region has beneficial effects on depression. However, stimulation frequencies are selected empirically, and there is no evidence showing that any frequency is superior to the others. This study explores antidepressant-like effects of three frequencies of taVNS on rats subjected to chronic unpredictable mild stress (CUMS). Sprague-Dawley rats were randomly divided into five groups, i.e., the control, CUMS, 5 Hz-taVNS, 20 Hz-taVNS, and 100 Hz-taVNS groups. The three different frequencies were administered during the 30-min taVNS procedure once a day for 28 consecutive days. Rats exposed to CUMS showed signs of depression-like behaviors, including reduction in sucrose preference and increased immobility time in forced swimming and open field tests as well as significant dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis as detected by plasma corticosterone and adrenocorticotropic hormone concentration. The 28 days’ taVNS sessions with three frequencies elicited quite different consequences. Although 20 Hz taVNS significantly reversed the depression-like behaviors and downregulated the hyperactivity of the HPA axis, neither 5 nor 100 Hz showed any antidepressant-like effect on CUMS-induced rat behavior. Based on these results, we propose that, out of the three frequencies for taVNS intervention on depression, 20 Hz may be the optimized frequency to have a better modulation effect on HPA axis function by activating the auricular vagus nerve.