国外动物智能军事应用情报研究

目的：阐述动物智能在军事学的应用及意义。方法：以学术论文、新闻、报纸、智库报告等作为信息源，综合研究国外动物智能军事应用实例及内在关联，描述动物智能在未来战场应用场景。结果：动物智能军事应用主要是动物特殊能力的军事应用和动物智能的仿生武器应用。结论：动物部队、仿生作战部队和动物战术是未来战争不可忽视的重要组成部分，动物智能的隐匿、灵活、多变等特点正逐渐被广泛应用于战场。     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

Enlarged high frequency oscillations of the median nerve somatosensory evoked potential and survival in amyotrophic lateral sclerosis

ObjectiveA large N20 and P25 of the median nerve somatosensory evoked potential (SEP) predicts short survival in amyotrophic lateral sclerosis (ALS). We investigated whether high frequency oscillations (HFOs) over N20 are enlarged and associated with survival in ALS.MethodsA total of 145 patients with ALS and 57 healthy subjects were studied. We recorded the median nerve SEP and measured the onset-to-peak amplitude of N20 (N20o-p), and peak-to-peak amplitude between N20 and P25 (N20p-P25p). We obtained early and late HFO potentials by filtering SEP between 500 and 1 kHz, and measured the peak-to-peak amplitude. We followed up patients until endpoints (death or tracheostomy) and analyzed the relationship between SEP or HFO amplitudes and survival using a Cox analysis.ResultsPatients showed larger N20o-p, N20p-P25p, and early and late HFO amplitudes than the control values. N20p-P25p was associated with survival periods (p = 0.0004), while early and late HFO amplitudes showed no significant association with survival (p = 0.4307, and p = 0.6858, respectively).ConclusionsThe HFO amplitude in ALS is increased, but does not predict survival.SignificanceThe enlarged HFOs in ALS might be a compensatory phenomenon to the hyperexcitability of the sensory cortex pyramidal neurons.     

EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

Classification of needle-EMG resting potentials by machine learning

Introduction: The diagnostic importance of audio signal characteristics in needle electromyography (EMG) is well established. Given the recent advent of audio-sound identification by artificial intelligence, we hypothesized that the extraction of characteristic resting EMG signals and application of machine learning algorithms could help classify various EMG discharges. Methods: Data files of 6 classes of resting EMG signals were divided into 2-s segments. Extraction of characteristic features (384 and 4,367 features each) was used to classify the 6 types of discharges using machine learning algorithms. Results: Across 841 audio files, the best overall accuracy of 90.4% was observed for the smaller feature set. Among the feature classes, mel-frequency cepstral coefficients (MFCC)-related features were useful in correct classification. Conclusions: We showed that needle EMG resting signals were satisfactorily classifiable by the combination of feature extraction and machine learning, and this can be applied to clinical settings. Muscle Nerve 59 :224–228, 2019     

An extensive pattern of atypical neural speech-sound discrimination in newborns at risk of dyslexia

ObjectiveIdentifying early signs of developmental dyslexia, associated with deficient speech-sound processing, is paramount to establish early interventions. We aimed to find early speech-sound processing deficiencies in dyslexia, expecting diminished and atypically lateralized event-related potentials (ERP) and mismatch responses (MMR) in newborns at dyslexia risk.MethodsERPs were recorded to a pseudoword and its variants (vowel-duration, vowel-identity, and syllable-frequency changes) from 88 newborns at high or no familial risk. The response significance was tested, and group, laterality, and frontality effects were assessed with repeated-measures ANOVA.ResultsAn early positive and right-lateralized ERP component was elicited by standard pseudowords in both groups, the response amplitude not differing between groups. Early negative MMRs were absent in the at-risk group, and MMRs to duration changes diminished compared to controls. MMRs to vowel changes had significant laterality × group interactions resulting from right-lateralized MMRs in controls.ConclusionsThe MMRs of high-risk infants were absent or diminished, and morphologically atypical, suggesting atypical neural speech-sound discrimination.SignificanceThis atypical neural basis for speech discrimination may contribute to impaired language development, potentially leading to future reading problems.     

Factors determining phage stability/activity: challenges in practical phage application

Introduction: Phages consist of nucleic acids and proteins that may lose their activity under different physico-chemical conditions. The production process of phage formulations may decrease phage infectivity. Ingredients present in the preparation may influence phage particles, although preparation and storage conditions may also cause variations in phage titer. Significant factors are the manner of phage application, the patient’s immune system status, the type of medication being taken, and diet.

Areas covered: We discuss factors determining phage activity and stability, which is relevant for the preparation and application of phage formulations with the highest therapeutic efficacy. Our article should be helpful for more insightful implementation of clinical trials, which could pave the way for successful phage therapy.

Expert opinion: The number of naturally occurring phages is practically unlimited and phages vary in their susceptibility to external factors. Modern methods offer engineering techniques which should lead to enhanced precision in phage delivery and anti-bacterial activity. Recent data suggesting that phages may also be used in treating nonbacterial infections as well as anti-inflammatory and immunomodulatory agents add further weight to such studies. It may be anticipated that different phage activities could have varying susceptibility to factors determining their actions.