SDMI-Net: Spatially Dependent Mutual Information Network for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation strives to polish deep models with a small amount of labeled data and a large amount of unlabeled data. The efficiency of most semi-supervised medical image segmentation methods based on voxel-level consistency learning is affected by low-confidence voxels. In addition, voxel-level consistency learning fails to consider the spatial correlation between neighboring voxels. To encourage reliable voxel-level consistent learning, we propose a dual-teacher affine consistent uncertainty estimation method to filter out some voxels with high uncertainty. Moreover, we design the spatially dependent mutual information module, which enhances the spatial dependence between neighboring voxels by maximizing the mutual information between the local voxel blocks predicted from the dual-teacher models and the student model, enabling consistent learning at the block level. On two benchmark medical image segmentation datasets, including the Left Atrial Segmentation Challenge dataset and the BraTS-2019 dataset, our method achieves state-of-the-art performance in both quantitative and qualitative aspects.

Association between CBS gene T833C, G919A and 844ins68 polymorphisms in the 8th exon region and coronary artery disease: a meta-analysis.

BACKGROUND: Several studies indicate that the cystathionine ß-synthase (CBS) gene T833C, G919A and 844ins68 polymorphisms in the 8th exon region may be correlated with coronary artery disease (CAD) susceptibility, but the results have been inconsistent and inconclusive. Thus, a meta-analysis was conducted to provide a comprehensive estimate of these associations. METHODS: On the basis of searches in the PubMed, EMBASE, Cochrane Library, Wanfang, VIP, and CNKI databases, we selected 14 case - control studies including 2123 cases and 2368 controls for this meta-analysis. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated accordingly using a fixed-effect or random-effect model. RESULTS: The results indicated an increased risk between the CBS T833C gene polymorphisms and susceptibility to CAD under the dominant model (CC+CT vs. TT: OR = 1.92, 95% CI: 1.11 ~ 3.32), recessive model (CC vs. CT+TT: OR = 1.88, 95% CI: 1.17 ~ 3.03), and homozygous model (CC vs. TT: OR = 2.46, 95% CI: 1.04 ~ 5.83). In these three genetic models, no significant association was identified for CBS G919A (AA+AG vs. GG: OR = 1.48, 95% CI: 0.45 ~ 4.82),(AA vs. AG+GG: OR = 1.58, 95% CI: 0.93 ~ 2.70),(AA vs. GG: OR = 1.66, 95% CI: 0.40 ~ 6.92) or CBS 844ins68 (II+ID vs. DD: OR = 1.04, 95% CI: 0.80 ~ 1.35),(II vs. ID+DD: OR = 1.09, 95% CI: 0.51 ~ 2.36),(II vs. DD: OR = 1.10, 95% CI: 0.51 ~ 2.39). CONCLUSIONS: This meta-analysis suggests that the CBS T833C gene polymorphism is significantly associated with the risk of CAD and it shows a stronger association in Asian populations. Individuals with the C allele of the CBS gene T833C polymorphism might be particularly susceptible to CAD.

Identification and validation of a disulfidptosis-related genes prognostic signature in lung adenocarcinoma.

Disulfidptosis, a newly revealed form of cell death, regulated by numerous genes that has been recently identified. The exact role of disulfidptosis in lung adenocarcinoma (LUAD) still uncertain. Objective of this study was to explore potential prognostic markers among disulfidptosis genes in LUAD. By combining transcriptomic information from Gene Expression Omnibus databases and The Cancer Genome Atlas, we identified differentially expressed and prognostic disulfidptosis genes. By conducting least absolute shrinkage and selection operator with multivariate Cox regression, four disulfidptosis genes were selected to create the prognostic signature. The implementation of the signature separated the training and validation cohorts into groups with high- and low-risk. Subsequently, the model was verified by conducting an independent analysis of receiver operating characteristic (ROC) curves. Further comparisons were made between the two risk-divided groups with regards the tumor microenvironment, immune cell infiltration, immunotherapy response, and drug sensitivity. The signature was constructed using four disulfidptosis-related genes: SLC7A11, SLC3A2, NCKAP1, and GYS1. According to ROC curves, the signature was effective for predicting LUAD prognosis. In addition, the prognostic signature correlated with sensitivity to chemotherapeutic agents and the efficacy of immunotherapy in LUAD. Finally, through external validation, we showed that NCKAP1 are correlated with tumor migration, proliferation, and invasion of LUAD cells. GYS1 affects immune cell, especially M2 macrophage infiltration in the tumor microenvironment. The disulfidptosis four-gene model can reliably predict the prognosis of patients diagnosed with LUAD, thereby providing valuable information for clinical applications and immunotherapy.

Classification of cognitive impairment in older adults based on brain functional state measurement data via hierarchical clustering analysis.

Introduction: Cognitive impairment (CI) is a common degenerative condition in the older population. However, the current methods for assessing CI are not based on brain functional state, which leads to delayed diagnosis, limiting the initiatives towards achieving early interventions. Methods: A total of one hundred and forty-nine community-dwelling older adults were recruited. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Exam (MMSE) were used to screen for CI, while brain functional was assessed by brain functional state measurement (BFSM) based on electroencephalogram. Bain functional state indicators associated with CI were selected by lasso and logistic regression models (LRM). We then classified the CI participants based on the selected variables using hierarchical clustering analysis. Results: Eighty-one participants with CI detected by MoCA were divided into five groups. Cluster 1 had relatively lower brain functional states. Cluster 2 had highest mental task-switching index (MTSi, 13.7 ± 3.4), Cluster 3 had the highest sensory threshold index (STi, 29.9 ± 7.7), Cluster 4 had high mental fatigue index (MFi) and cluster 5 had the highest mental refractory period index (MRPi), and external apprehension index (EAi) (21.6 ± 4.4, 35.4 ± 17.7, respectively). Thirty-three participants with CI detected by MMSE were divided into 3 categories. Cluster 1 had the highest introspective intensity index (IIi, 63.4 ± 20.0), anxiety tendency index (ATi, 67.2 ± 13.6), emotional resistance index (ERi, 50.2 ± 11.9), and hypoxia index (Hi, 41.8 ± 8.3). Cluster 2 had the highest implicit cognitive threshold index (ICTi, 87.2 ± 12.7), and cognitive efficiency index (CEi, 213.8 ± 72.0). Cluster 3 had higher STi. The classifications both showed well intra-group consistency and inter-group variability. Conclusion: In our study, BFSM-based classification can be used to identify clinically and brain-functionally relevant CI subtypes, by which clinicians can perform personalized early rehabilitation.

A Cross-Sectional, Multicenter Study Examining the Validation and Adaptation of the Chinese ROWAN Foot Pain Assessment Questionnaire.

BACKGROUND: The 39-item ROwan Foot Pain Assessment Questionnaire (ROFPAQ) has affective, cognitive, and sensory dimensions to evaluate chronic foot pain. However, to date, the ROFPAQ has only been validated in English and Spanish versions. A simplified Chinese version of ROFPAQ is still not available, even though China has a large population of patients with foot pain. OBJECTIVE: This study's aim was to translate the ROFPAQ into a Chinese version and assess its reliability and validity in Chinese patients with chronic foot pain. STUDY DESIGN: A cross-sectional, multicenter descriptive study. SETTING: This study took place at the Chinese PLA General Hospital, PLA Strategic Support Force Characteristic Medical Center and Wenzhou integrated traditional Chinese and Western Medicine Hospital Affiliated to Zhejiang traditional Chinese Medicine University. METHODS: The ROFPAQ-C (Chinese) was developed by a forward/backward translation protocol and cross-cultural adaptation from the United Kingdom to China, and from English to Chinese Putonghua. A total of 194 patients from 3 centers with chronic foot pain were recruited for test-retest measures from July 2020 though September 2021. RESULTS: Adequate internal consistencies (Cronbach's Alpha) in 3 domains ranged from 0.875 to 0.799 for the cognitive, from 0.795 to 0.629 for the affective, and from 0.801 to 0.811 for the sensory, as well as for the total score from 0.880 to 0.815. Adequate test-retest reliability by intraclass correlation coefficient (ICC) were shown in the cognitive 0.712 (95% CI 0.636 to 0.775), the affective 0.929 (95% CI 0.906 to 0.946), the sensory 0.753 (95% CI 0.685 to 0.808), and the total score 0.932 (95% CI 0.910 to 0.948). Adequate item-total correlations were shown for the cognitive from 0.848 to 0.825, the affective from 0.918 to 0.908, and the sensory from 0.943 to 0.855. LIMITATIONS: The original ROFPAQ with 39 items was developed from a podiatry department of the health care national service of the United Kingdom. CONCLUSIONS: The ROFPAQ-C can be used as a valid and reliable tool for chronic foot pain in the Chinese population.

Intermolecular interactions between ß-cyclodextrin and water.

This study focused on demonstrating the intermolecular interactions between ß-cyclodextrin and water, with the aim to better understand the transfer of small molecules to ß-cyclodextrin. The intermolecular interaction strength between ß-cyclodextrin and water was analyzed using different methods such as the dynamic adsorption of water, the TG-DSC of ß-cyclodextrin and molecular modeling employing MM2 force field calculations. The experiments for the adsorption of water on ß-cyclodextrin was aimed to systematically investigate the adsorption characteristics, such as adsorption capacity, adsorption rate, adsorption heat and activation energy, influenced by the adsorption temperature and vapor pressure of water. The results indicated that the water adsorption on ß-cyclodextrin is an exothermic process. The hysteresis loop type in the adsorption isotherms at multiple temperatures indicated that water adsorption is not purely a traditional physical adsorption due to the existence of structure effects such as the cavity effect and hydrogen bonding. The activation energy during water adsorption was 7.4 kJ mol-1. However, the activation energy during water desorption was in the range of 35-45 kJ mol-1, which decreased with an increase in the amount of water adsorbed. This indicated that water adsorption is much easier than water desorption from ß-cyclodextrin and that water desorption is more difficult with a small amount of adsorbed water compared with a large amount of adsorbed water. Subsequently, the obtained average intermolecular interaction strength between ß-cyclodextrin and water under the experimental conditions was 67.5 kJ mol-1 (water), which was verified by DSC.

Rotation velocity measurement based on a self-mixing grating interferometer.

A novel rotational velocity measurement method based on the self-mixing grating interferometer (SMGI) is explored and presented in this paper. In this method, the target object rotational velocity is measured by the Doppler frequency shift, which can be extracted through the power spectrum without measuring incident angles. The experimental results show that the relative errors are below 0.5%.

Secondary envelope extraction based on multiple Hilbert transforms for laser self-mixing micro-vibration measurement.

This paper presents a method that can be applied to weak feedback and full-range moderate feedback in the field of self-mixing interference measurement, and the target motion displacement can be obtained by multiple Hilbert transforms of the signal after the secondary envelope extraction. Simulations and experiments of multiple micro-vibration measurements were performed with different optical feedback factors, and the results were consistent with theoretical analysis. This method effectively eliminates the impact of the self-mixing interference signal with fringe shift on micro-vibration reconstruction.

Enhanced laser self-mixing Doppler velocity measurement with pre-feedback mirror.

On the basis of conventional measurement, a novel enhanced laser self-mixing Doppler velocimetry is proposed in this paper, with a pre-feedback structure added to enhance the signals. The improved velocimetry is applicable to the measure of the velocity when the feedback light is weak. Through the exploration of the theoretical model and the performance of experiments, the study results show that the proposed method has a significant signal enhancement effect, with experimental measurement relative errors being less than 0.9%.

A highly efficient step-wise biotransformation strategy for direct conversion of phytosterol to boldenone.

Collaborative microbial communities are ubiquitous in nature and exhibit appealing functions for enhanced production of natural products, which provides new possibility for biotechnology development. In this study, we bridged Mycobacterium neoaurum with Pichia pastoris to establish a step-wise biotransformation strategy for efficient biosynthesis of boldenone (BD) from phytosterol (PS). Firstly, the producing strains were rationally designed with overexpression of 3-ketosteroid-Δ1-dehydrogenase (KsdD) and 17ß-hydroxysteroid dehydrogenase (17ßHSD) in M. neoaurum and P. pastoris, respectively. Then, to shorten the total biotransformation process and provide reducing power, semi-batch fermentation strategy and glucose supplementation strategy were introduced at side-chain degradation stage and carbonyl reduction stage, respectively. Under the optimal transformation conditions, the productivity of BD was increased from 10% to 76% and the total biotransformation process was shortened by 41.7%, which is the shortest among the ever reported. Our results demonstrated an excellent biological strategy for production of many other valuable microbial products from bioresources.

Rotation velocity measurement based on self-mixing interference with a dual-external-cavity single-laser diode.

A novel Doppler velocity measurement method based on laser self-mixing interference with two parallel optical external cavities is investigated. In this method, the target object rotation velocity can be measured by the sum of two Doppler frequency shifts, which can be extracted by fast Fourier transform without setting and measuring incident angles. This study highlights the validity of the proposed method through a theoretical model analysis. Experiments realized velocity measurement with a relative error of less than 0.6%.