Intelligent cholinergic white matter pathways algorithm based on U-net reflects cognitive impairment in patients with silent cerebrovascular disease.

BACKGROUND AND OBJECTIVE: The injury of the cholinergic white matter pathway underlies cognition decline in patients with silent cerebrovascular disease (SCD) with white matter hyperintensities (WMH) of vascular origin. However, the evaluation of the cholinergic white matter pathway is complex with poor consistency. We established an intelligent algorithm to evaluate WMH in the cholinergic pathway. METHODS: Patients with SCD with WMH of vascular origin were enrolled. The Cholinergic Pathways Hyperintensities Scale (CHIPS) was used to measure cholinergic white matter pathway impairment. The intelligent algorithm used a deep learning model based on convolutional neural networks to achieve WMH segmentation and CHIPS scoring. The diagnostic value of the intelligent algorithm for moderate-to-severe cholinergic pathway injury was calculated. The correlation between the WMH in the cholinergic pathway and cognitive function was analysed. RESULTS: A number of 464 patients with SCD were enrolled in internal training and test set. The algorithm was validated using data from an external cohort comprising 100 patients with SCD. The sensitivity, specificity and area under the curve of the intelligent algorithm to assess moderate and severe cholinergic white matter pathway injury were 91.7%, 87.3%, 0.903 (95% CI 0.861 to 0.952) and 86.5%, 81.3%, 0.868 (95% CI 0.819 to 0.921) for the internal test set and external validation set. for the. The general cognitive function, execution function and attention showed significant differences among the three groups of different CHIPS score (all p<0.05). DISCUSSION: We have established the first intelligent algorithm to evaluate the cholinergic white matter pathway with good accuracy compared with the gold standard. It helps more easily assess the cognitive function in patients with SCD.

Thermal transport of graphene-C3B superlattices and van der Waals heterostructures: a molecular dynamics study.

Two-dimensional (2D) materials have attracted more and more attention due to their excellent properties. In this work, we systematically explore the heat transport properties of Graphene-C3B (GRA-C3B) superlattices and van der Waals (vdW) heterostructures using molecular dynamics method. The effects of interface types and heat flow directions on the in-plane interfacial thermal resistance (ITRip) are analyzed. Obvious thermal rectification is detected in the more energy stable interface, GRA zigzag-C3B zigzag (ZZ) interface, which also has the minimum value of ITRip. The dependence of the superlattices thermal conductivity (k) of the ZZ interface on the period length (lp) is investigated. The results show that when thelpis 3.5 nm, thekreaches a minimum value of 35.52 W m-1K-1, indicating a transition stage from coherent phonon transport to incoherent phonon transport. Afterwards, the effects of system size, temperature, coupling strength and vacancy defect on the out-of-plane interfacial thermal resistance (ITRop) are evaluated. With the increase of temperature, coupling strength and vacancy defect, ITRopare found to reduce effectively due to the enhanced Umklapp phonon scattering and increased probability of energy transfer. Phonon density of states and phonon participation ratio is evaluated to reveal phonon behavior during heat transport. This work is expected to provide essential guidance for the thermal management of nanoelectronics based on 2D monolayer GRA and C3B.

Automatic Identification of Brain Injury Mechanism Based on Deep Learning.

OBJECTIVES: To apply the convolutional neural network (CNN) Inception_v3 model in automatic identification of acceleration and deceleration injury based on CT images of brain, and to explore the application prospect of deep learning technology in forensic brain injury mechanism inference. METHODS: CT images from 190 cases with acceleration and deceleration brain injury were selected as the experimental group, and CT images from 130 normal brain cases were used as the control group. The above-mentioned 320 imaging data were divided into training validation dataset and testing dataset according to random sampling method. The model classification performance was evaluated by the accuracy rate, precision rate, recall rate, F1-value and AUC value. RESULTS: In the training process and validation process, the accuracy rate of the model to classify acceleration injury, deceleration injury and normal brain was 99.00% and 87.21%, which met the requirements. The optimized model was used to test the data of the testing dataset, the result showed that the accuracy rate of the model in the test set was 87.18%, and the precision rate, recall rate, F1-score and AUC of the model to recognize acceleration injury were 84.38%, 90.00%, 87.10% and 0.98, respectively, to recognize deceleration injury were 86.67%, 72.22%, 78.79% and 0.92, respectively, to recognize normal brain were 88.57%, 89.86%, 89.21% and 0.93, respectively. CONCLUSIONS: Inception_v3 model has potential application value in distinguishing acceleration and deceleration injury based on brain CT images, and is expected to become an auxiliary tool to infer the mechanism of head injury.

Increased expression of TIGIT and KLRG1 correlates with impaired CD56bright NK cell immunity in HPV16-related cervical intraepithelial neoplasia.

BACKGROUND: The onset and progression of cervical intraepithelial neoplasia (CIN) are closely associated with the persistent infection of high-risk HPV (especially type16), which is mainly caused by immune escape. Natural killer (NK) cells play an important role against virally infected cells and tumor cells through a fine balance of signals from multiple surface receptors. Overexpression of non-MHC-I specific inhibitory receptors TIGIT, KLRG1, Siglec-7, LAIR-1, and CD300a on NK cells correlates with cellular exhaustion and immune evasion, but these receptors have not been investigated in CIN. The aim of the present study was to examine the potential role of NK cell non-MHC-I specific inhibitory receptors expression in immune escape from HPV16(+)CIN patients. METHODS: The subset distribution, IFN-γ and TNF-α expression levels and immunophenotype of TIGIT, KLRG1, Siglec-7, LAIR-1, and CD300a of NK cells were investigated in peripheral blood mononuclear cell samples by flow cytometry from 82 women who were HPV16(+) with CIN grades 0, I, II-III or HPV(-) CIN 0. Immunohistochemistry was applied to detect the expression of ligands for NK receptors in the cervical tissues. HPV types were identified by PCR assays. RESULTS: The HPV16(+) subjects with high-grade lesions had an increased number of circulating peripheral blood CD56bright NK cells with reduced functionality and IFN-γ secretion. The expression levels of the inhibitory molecules TIGIT and KLRG1 on CD56bright NK cells increased in parallel with increasing CIN grade. In addition, TIGIT and KLRG1 related ligands, Poliovirus receptor (PVR), N-Cadherin and E-Cadherin expression level was also elevated with increasing CIN grade. CONCLUSIONS: Our results suggest that up-regulation of the inhibitory TIGIT, KLRG1 and their ligands may negatively regulate cervical CD56bright NK-mediated immunity to HPV16 and contribute to the progression of CIN. These results may facilitate the development of early-warning immune predictors and therapeutic strategies for HPV16(+) CIN based on the TIGIT and KLRG1 inhibitory pathways of NK cells.

Correction to "Application of Nanocellulose in Oilfield Chemistry".

[This corrects the article DOI: 10.1021/acsomega.1c02095.].

Application of Nanocellulose in Oilfield Chemistry.

The preparation and classification of nanocellulose are briefly introduced, and the modification of nanocellulose and the application of modified nanocellulose in oilfield chemistry are reviewed. The principles and methods of surface modification, including surface adsorption, oxidation, acetylation, silanization, etherification, and polymer grafting, are summarized. Meanwhile, this paper focuses on the application of nanocellulose research progress in drilling fluid, enhanced oil recovery, and oilfield sewage treatment. In addition, the application issues and natural advantages of nanocellulose are analyzed, and suggestions and ideas on how to expand its application are put forward. Finally, the development and potential application of nanocellulose in oilfield chemistry are proposed.

The Acute Effect of Diesel Exhaust Particles and Different Fractions Exposure on Blood Coagulation Function in Mice.

The toxicity and widespread exposure opportunity of diesel exhaust particles (DEP) has aroused public health concerns. This study aimed to investigate the acute effect of DEP and different fractions exposure on blood coagulation function in mice. In this study, nine- week-old C57BL/6J male mice were divided into four exposure groups (with 15 mice in each group). The water-soluble (WS) and water-insoluble (WIS) fractions of DEP were isolated, and intratracheal instillation was used for DEP, WS and WIS exposure. The phosphate buffer saline (PBS) exposure group was set as the control group. After 24 h exposure, the mice were sacrificed for blood routine, coagulation function and bleeding time examinations to estimate the acute effect of DEP, WS and WIS exposure on the blood coagulation function. In our results, no statistically significant difference in weight of body, brain and lung was observed in different exposure groups. While several core indexes in blood coagulation like bleeding time (BT), fibrinogen (FIB), activated partial thromboplastin time (APTT) and prothrombin time (PT) altered or showed a lower tendency after DEP, WS and WIS exposure. For example, BT was lower In WIS exposure group (211.00 s) compared with PBS exposure group (238.50 s) (p < 0.01), and FIB was lower in WS exposure group (233.00 g/L) compared with PBS exposure group (249.50 g/L) (p < 0.05). Additionally, systemic inflammation-related indexes like white blood cell count (WBC), neutrophil count (NEUT), lymphocyte count (LYMPH) altered after DEP, WS and WIS exposure. In conclusion, DEP, WS and WIS fractions exposure could result in the hypercoagulable state of blood in mice. The noteworthy effects of WS and WIS fractions exposure on blood coagulation function deserve further investigation of the potential mechanism.

UPLC-Q-TOF/MS-based plasma metabolome to identify biomarkers and time of injury in traumatic brain injured rats.

BACKGROUND: To identify the potent metabolic biomarkers and time of injury of traumatic brain injured (TBI). METHODS: A total of 70 Sprague-Dawley rats were used to establish the TBI model in this study. The serum was collected at 3 h, 6 h, 12 h, 24 h, 3 days and 7 days after surgery. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was performed to analyze metabolic changes in the serum of the TBI rats from different groups. The differences between the metabolic profiles of the rats in seven groups were analyzed using partial least squares discriminant analysis. RESULTS: Metabolic profiling revealed significant differences between the sham-operated and other groups. A total of 49 potential TBI metabolite biomarkers were identified between the sham-operated group and the model groups at different time points. Among them, six metabolites (methionine sulfone, kynurenine, 3-hydroxyanthranilic acid, 3-Indolepropionic acid, citric acid and glycocholic acid) were identified as biomarkers of TBI to estimate the injury time. CONCLUSION: Using metabolomic analysis, we identified new TBI serum biomarkers for accurate detection and determination of the timing of TBI injury.

Evolutionary transitions in body plan and reproductive mode alter maintenance metabolism in squamates.

BACKGROUND: Energy (resources) acquired by animals should be allocated towards competing demands, maintenance, growth, reproduction and fat storage. Reproduction has the second lowest priority in energy allocation and only is allowed after meeting the energetic demands for maintenance and growth. This hierarchical allocation of energy suggests the hypothesis that species or taxa with high maintenance costs would be less likely to invest more energy in reproduction or to evolve an energetically more expensive mode of reproduction. Here, we used data on standard metabolic rate so far reported for 196 species of squamates to test this hypothesis. RESULTS: We found that maintenance costs were lower in snakes than in lizards, and that the costs were lower in viviparous species than in oviparous species. As snakes generally invest more energy per reproductive episode than lizards, and viviparity is an energetically more expensive mode of reproduction than oviparity, our results are consistent with the hypothesis tested. CONCLUSION: The transition from lizard-like to snake-like body form and the transition from oviparity to viviparity are major evolutionary transitions in vertebrates, which likely alter many aspects of biology of the organisms involved. Our study is the first to demonstrate that evolutionary transitions in body plan and reproductive mode alter maintenance metabolism in squamates.

The complete mitochondrial genome of the toad-headed lizard, Phrynocephalus albolineatus (Reptilia, Squamata, Agamidae).

In this study, we report the complete mitochondrial genome of Phrynocephalus albolineatus (Reptilia, Squamata, Agamidae), which is a circular molecule of 16 808 bp in size and consists of 13 protein-coding genes, 22 transfer RNAs, 2 ribosomal RNAs, and 2 non-coding sequence (D-loop). The mitogenome of P. albolineatus was similar to the typical mtDNA of vertebrates in gene arrangement and composition. The control region was comprised by two parts, one (992 bp) between tRNA-Phe and 12S rRNA, and the other (650 bp) between tRNA-Thr and tRNA-Pro. The A + T content of overall base of H-strand is 63.1% (T: 26.7%, C: 24.6%, A: 36.4%, G: 12.3%). The whole mitogenomic sequence of P. albolineatus provides powerful data to study the molecular systematic, population genetics and phylogeography of Squamata.

[Analysis of 21 autopsy cases of aortic dissection with disputes].

OBJECTIVE: To explore procedures and methods of forensic investigation for the death cases of aortic dissection with disputes. METHODS: Twenty-one death cases of aortic dissection with disputes from 2006 to 2011 were collected. All the data were analyzed to investigate the reasons and features of the disputes. RESULTS: The main causes of the disputes were clinical misdiagnosis or slight force. The pathologic type of De Bakey (I and II) or Stanford A were common in each case. For the cases dying of aortic dissection, it was significantly important to detect the rupture of entry and exit and observe the dissection of arterial wall. CONCLUSION: The main causes of clinical misdiagnosis are insufficient experiences, careless observation and curtness in medical treatment. The difficult points in these cases are confirmation of the relationships between injury and disease, the primary affection and complication.

Prediction of binding motifs in hepatitis C virus NS5A and human proteins.

From the extensive analysis, we identified three highly conserved sequence segments in HCV NS5A proteins and one binding motif in human proteins. The binding motif of human proteins often forms a full helix or an extended strand-loop structure, and is in good agreement with the experimental findings of previous studies.

Hepatitis C virus contact map prediction based on binary encoding strategy.

Inter-residue contact map is an important two-dimensional representation of protein spatial structure, and has much potential application in the area of understanding protein fold mechanism. In the present note, a 19-bit binary input encoding strategy, integrating with residue pair conformational features (possible residue pairwise, residue classification, secondary structure, sequence length, and sequence separation information), is proposed for the purpose of capturing mapping relationship of protein sequence. Simulation results on a set of 61 hepatitis C virus (HCV) retrieved from the protein data bank (PDB) demonstrate that the proposed encoding scheme could precisely capture conformational patterns within HCV protein sequence. This promising result could provide some useful insights into the nature of HCV protein fold mechanism.

[Following up investigation of forensic psychiatry judicial expert mental testimony].

OBJECTIVE: To study different viewpoints to the conclusion and treatment, And the following up factors concerning social effect after the judgment of forensic psychiatry. METHODS: By letters, calls, visits and by investigation forms made by myself, 208 testimonied cases were followed up separately from judicial organ or other organizations and institutes, individuals testimonied or their family members, victims and their family members. RESULTS: Most testimonied individuals were married man of 30 years old or so whose average education were 4.84 years and testimonied by the public security organs. In criminal cases, violental criminals (129 cases, 83.77%) were much more than non-violental criminals (25 cases, 16.23%) and homicide criminals (44 cases, 28.57%) were most common in the former but civil cases were few. The rate of retstinvony was 2.93%. The testimonied individuals and their family members thought the condemn were appropriate (76.47%) for the people without criminal capacity and thought the condemn were appropriate (41.94%) or not appropriate (41.94%) for the people with criminal capacity. The opinions of the condemn for partial criminal capacity were between the former two cases. And they thought the condemn for 28 cases of non-guilty were appropriate (71.43%) and not appropriate (10.7%). 7 victims were dead. 10 victims were crippled. 10 victims restored to health. In 41 persons testimonied and set free with a verdict of "not guilty", 4 homicided again (4.87%), 2 set on fire (4.87%), 2 stealed (4.87%) and 3 had wrecked behavior (7.31%). CONCLUSION: So it is suggested that the department concerned should keep criminals with mental disorder under control and treatment.

Prediction of protein secondary structure using improved two-level neural network architecture.

In this paper we propose constructing an improved two-level neural network to predict protein secondary structure. Firstly, we code the whole protein composition information as the inputs to the first-level network besides the evolutionary information. Secondly, we calculate the reliability score for each residue position based on the output of the first-level network, and the role of the second-level network is to take full advantage of the residues with a higher reliability score to impact the neighboring residues with a lower one for improving the whole prediction accuracy. Thirdly, considering it is indeed a problem that the target protein can be lost in the multiple sequence alignment we propose to code single sequence into the second-level network. The experimental results show that our proposed method can efficiently improve the prediction accuracy.

Inter-residue spatial distance map prediction by using integrating GA with RBFNN.

The spatial ordering information of amino acid residue in protein primary sequence is an important determinant of protein three-dimensional structure. In this paper, we describe a radial basis function neural network (RBFNN), whose hidden centers and basis function widths are optimized by a genetic algorithm (GA), for the purpose of predicting three dimensional spatial distance location from primary sequence information. Experimental evidence on soybean protein sequences indicates the utility of this approach.

Prediction of inter-residue contacts map based on genetic algorithm optimized radial basis function neural network and binary input encoding scheme.

Inter-residue contacts map prediction is one of the most important intermediate steps to the protein folding problem. In this paper, we focus on the problem of protein inter-residue contacts map prediction based on neural network technique. Firstly, we use a genetic algorithm (GA) to optimize the radial basis function widths and hidden centers of a radial basis function neural network (RBFNN), then a novel binary encoding scheme is employed to train the network for the purpose of learning and predicting the inter-residue contacts patterns of protein sequences got from the protein data bank (PDB). The experimental evidence indicates the utility of our proposed encoding strategy and GA optimized RBFNN. Moreover, the simulation results demonstrate that the network got a better performance for these proteins, whose residue length falls into the area of (100, 300), and the predicted accuracy with a contact threshold of 7 Angstroms scores higher than the other 3 values with 5, 6, and 8 Angstroms.