Factors Associated with Site-specific Distribution of Glioblastoma / 肿瘤防治研究

The treatment of glioblastoma, the most prevalent malignant tumor in the central nervous system, poses considerable challenges. Glioblastoma multiforme, classified as a grade Ⅳ highly malignant brain glioma by the World Health Organization, is typically managed through a combination of surgery, postoperative chemotherapy, and radiotherapy. The treatment of glioblastoma is complicated by its infiltrative nature, genetic heterogeneity, and presence of the blood-brain barrier. Almost all cases of glioblastoma experience recurrence despite aggressive therapy, exploring the development of updated molecular treatment strategies that can improve overall efficacy. A crucial aspect in modern neurosurgery is the precise delineation of brain regions in terms of their anatomy and function. It serves as the fundamental basis for investigating variations in the distribution of brain gliomas. Hence, this review will elucidate the origin of glioblastomas and analyze the potential factors contributing to the spatially specific distribution of gliomas on the basis of a theoretical framework of brain connectomics research. Molecular characteristics, information pathways, tumor microenvironment landscape, and immunology will inform the analysis. We aim to identify novel biomolecular targets and therapeutic pathways to gain scientific insights for effective glioblastoma treatment.

Surveillance of echinococcosis in Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region from 2017 to 2022 / 中国血吸虫病防治杂志

Objective To analyze the echinococcosis surveillance results in Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region from 2017 to 2022, so as to provide insights into formulation of echinococcosis control measures in the prefecture. Methods Villagers were randomly sampled using a multistage sampling method from class I and II echinococcosis endemic counties in Bayingolin Mongolian Autonomous Prefecture from 2017 to 2022 for detection of human echinococcosis, while all patients undergoing ultrasound examinations in medical institutions in class III endemic counties received active echinococcosis screening. In addition, livestock in centralized slaughterhouses or slaughtering sites were screened for echinococcosis using the palpation and necropsy method, and fresh domestic dog feces samples were collected from randomly selected dog owners in each administrative village for detection of Echinococcus copro-antigen in domestic dogs. The trends in detection of human and livestock echinococcosis, detection of newly diagnosed human echinococcosis cases and detection of Echinococcus coproantigen in domestic dogs were analyzed in Bayingolin Mongol Autonomous Prefecture from 2017 to 2022. Results The mean detection rate of human echinococcosis was 0.13% (540/407 803) in Bayingolin Mongol Autonomous Prefecture from 2017 to 2022, which appeared a tendency towards a decline over years (χ2trend = 1 217.21, P < 0.001), and the highest detection of newly diagnosed echinococcosis cases was seen in Hejing County (0.28%, 191/67 865). The detection of livestock echinococcosis appeared a tendency towards a decline over years from 2017 to 2022 (χ2trend = 147.02, P < 0.001), with the highest detection rate seen in Hejing County (3.44%, 86/2 500), and the detection of Echinococcus copro-antigen in domestic dogs appeared a tendency towards a decline over years from 2017 to 2022 (χ2trend = 302.46, P < 0.001), with the highest detection rate in Qiemo County (2.74%, 118/4 313). Conclusions The detection of human and livestock echinococcosis and dog feces antigens Echinococcus copro-antigen in domestic dogs all appeared a tendency towards a decline in Bayingolin Mongol Autonomous Prefecture, Xinjiang Uygur Autonomous Region from 2017 to 2022; however, there is still a high echinococcosis transmission risk in local areas. Sustainable integrated echinococcosis control is required in Bayingolin Mongol Autonomous Prefecture.

Clinical and Genetic Study on 48 Children with Short Stature of Unknown Etiology / 中山大学学报(医学科学版)

ObjectiveTo explore the clinical features and causative genes of short stature children with unknown etiology， providing evidence for precise clinical diagnosis and treatment. MethodsThe study recruited children with suspected but undiagnosed short stature from the pediatric endocrinology department in our hospital between January 2018 and August 2022. A retrospective analysis was performed on the clinical manifestations， laboratory test and whole exome sequencing （WES） results. Causative genes were classified and analyzed according to different pathogenic mechanisms. ResultsA total of 48 children （30 boys and 18 girls） were enrolled， aged 7.73 ± 3.97 years， with a height standard deviation score （ HtSDS） of -3.63 ± 1.67. Of the patients， 33 （68.8%） suffered from facial anomalies， 31 （64.6%） from skeletal abnormalities， 26 ［54.2%， 61.5% of whom born small for gestational age （SGA）］ from perinatal abnormalities， 24 ［50.0%， 87.5% of whom with growth hormone （GH） peak concentration below normal］ from endocrine disorders and 21（43.8%） had a family history of short stature. Laboratory tests showed that GH peak concentration following stimulation test was （9.72 ± 7.25） ng/mL， IGF-1 standard deviation score was -0.82 ± 1.42， the difference between bone age and chronological age was -0.93 ± 1.39 years. Of the 25 cases with mutant genes found by WES， 14 （56.0%） had pathogenic mutation， 6 （24.0%） likely pathogenic mutation， and 5 （20.0%） mutation of uncertain significance. Pathogenic and likely pathogenic variants were identified in 14 genes， including 10 affecting intracellular signaling pathways （PTPN11， RAF1， RIT1， ARID1B， ANKRD11， CSNK2A1， SRCAP， CUL7， SMAD4 and FAM111A） and 4 affecting extracellular matrix （ECM） components or functions （ACAN， FBN1， COL10A1 and COMP）. ConclusionsA rare monogenic disease should be considered as the possible etiology for children with severe short stature accompanied by facial anomalies， disproportionate body types， skeletal abnormalities， SGA， GH peak concentration below normal and a family history of short stature. WES played an important role in identifying the monogenic causes of short stature. This study indicated that affecting growth plate cartilage formation through intracellular signaling pathways and ECM components or functions was the main mechanism of causative genes leading to severe short stature in children. Further research may help discover and study new pathogenic variants and gene functions.

Invasiveness assessment by CT quantitative and qualitative features of lung cancers manifesting ground-glass nodules in 555 patients: A retrospective cohort study / 中国胸心血管外科临床杂志

@#Objective     To explore the correlation between the quantitative and qualitative features of CT images and the invasiveness of pulmonary ground-glass nodules, providing reference value for preoperative planning of patients with ground-glass nodules. Methods    The patients with ground-glass nodules who underwent surgical treatment and were diagnosed with pulmonary adenocarcinoma from September 2020 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were collected. Based on the pathological diagnosis results, they were divided into two groups: a non-invasive adenocarcinoma group with in situ and minimally invasive adenocarcinoma, and an invasive adenocarcinoma group. Imaging features were collected, and a univariate logistic regression analysis was conducted on the clinical and imaging data of the patients. Variables with statistical difference were selected for multivariate logistic regression analysis to establish a predictive model of invasive adenocarcinoma based on independent risk factors. Finally, the sensitivity and specificity were calculated based on the Youden index. Results     A total of 555 patients were collected. The were 310 patients in the non-invasive adenocarcinoma group, including 235 females and 75 males, with a meadian age of 49 (43, 58) years, and 245 patients in the invasive adenocarcinoma group, including 163 females and 82 males, with a meadian age of 53 (46, 61) years. The binary logistic regression analysis showed that the maximum diameter (OR=4.707, 95%CI 2.060 to 10.758), consolidation/tumor ratio (CTR, OR=1.027, 95%CI 1.011 to 1.043), maximum CT value (OR=1.025, 95%CI 1.004 to 1.047), mean CT value (OR=1.035, 95%CI 1.008 to 1.063), spiculation sign (OR=2.055, 95%CI 1.148 to 3.679), and vascular convergence sign (OR=2.508, 95%CI 1.345 to 4.676) were independent risk factors for the occurrence of invasive adenocarcinoma (P<0.05). Based on the independent predictive factors, a predictive model of invasive adenocarcinoma was constructed. The formula for the model prediction was: Logit(P)=–1.293+1.549×maximum diameter of lesion+0.026×CTR+0.025×maximum CT value+0.034×mean CT value+0.72×spiculation sign+0.919×vascular convergence sign. The area under the receiver operating characteristic curve of the model was 0.910 (95%CI 0.885 to 0.934), indicating that the model had good discrimination ability. The calibration curve showed that the predictive model had good calibration, and the decision analysis curve showed that the model had good clinical utility. Conclusion     The predictive model combining quantitative and qualitative features of CT has a good predictive ability for the invasiveness of ground-glass nodules. Its predictive performance is higher than any single indicator.

Evaluation of asymptomatic ocular surface disorders in hospitalized patients with primary pterygium before surgery / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To investigate the preoperative ocular symptoms and the characteristics of asymptomatic ocular surface abnormalities in hospitalized patients with primary pterygium.METHODS: Cross-sectional study. Hospitalized patients diagnosed with primary pterygium and scheduled to receive pterygium excision surgery at the Xiamen Eye Center of Xiamen University from August 2022 to October 2022 were enrolled. Ocular surface disease index questionnaire(OSDI), six examinations including non-invasive tear film break-up time, Schirmer I test, tear meniscus height, lid margin abnormality, meibomian gland dropout and tear film lipid layer thickness, and anterior segment optical coherence tomography(AS-OCT)were performed and statistically analyzed.RESULTS: A total of 178 cases(178 eyes), with a mean age of 54.39±10.75 years old, were recruited, including 75 males(42.1%)and 103 females(57.9%). The average values of ocular surface parameters in these patients included OSDI: 11.47±9.69, tear film break-up time: 7.10±3.86 s; tear meniscus height: 0.16±0.07 mm, Schirmer I test values: 14.39±7.29 mm/5 min, and pterygium thickness: 504.74±175.87 μm. Totally 161 eyes(90.4%)presented with abnormal lid margin, 44 eyes(24.7%)presented with meibomian gland dropout score ≥4, 52 eyes(29.2%)presented with low lipid layer thickness. In the 6 objective examinations, abnormalities in at least 4 of these tests were found in 85.4% of eyes. Pterygium morphology was classified into four grades: 10 eyes(5.6%)of grade Ⅰ, 93 eyes(52.2%)of grade Ⅱ, 60 eyes(33.7%)of grade Ⅲ, and 15 eyes(8.4%)of grade Ⅳ. In patients with a higher grade of pterygium, the tear film break-up time was lower, and the proportion of abnormal lid margin was also significantly higher(P&#x0026;#x003C;0.05). The patients were further divided into two subgroups, including 121 eyes(68.0%)with normal OSDI &#x0026;#x003C;13 in the normal group and 57 eyes(32.0%)with OSDI ≥13 in the abnormal group. No significant difference was found in the proportion of meibomian gland dysfunction between the two groups of patients(71.9% vs. 71.9%, P=0.872). In addition, there were differences in the number of abnormal objective examinations(4.11±0.85 vs. 4.91±0.99, P&#x0026;#x003C;0.001).CONCLUSIONS: Asymptomatic ocular surface abnormalities were present preoperatively in patients hospitalized for primary pterygium. A comparable high incidence of structural or functional meibomian gland dysfunction existed in pterygium patients with or without apparent ocular discomfort. More attention should be paid to the ocular surface abnormalities in those asymptomatic patients before primary pterygium surgery.

Producción y distribución de largometrajes de ficción en maranhão: contradicciones de un mercado invisible en brasil

El estado de Maranhão ocupa un escenario peculiar en el mercado cinematográfico brasileño. Las producciones de ficción en forma de largometrajes tuvieron sus primeras incursiones a mediados de la década de 2000. En un marco desarrollado por la investigadora en su disertación de maestría en curso de História (Silva, 2018), y actualizado hasta 2022, catalogamos veintidós películas, solo seis de los cuales fueron registrados en la Agencia Nacional de Cine. La principal metodología utilizada fue la recolección e interpretación de datos, además de entrevistas no estructuradas o no estructuradas (Lakatos y Marconi, 2003). Como principales resultados podemos señalar: en Maranhão, el mercado es predominantemente informal, con momentos ocasionales de formalidad. La conclusión inicial de nuestra investigación es que el factor económico asociado a la falta de políticas públicas, sumado a la falta de cursos de educación superior en la zona, son los principales impulsores de este incipiente escenario.

The State of Maranhão occupies a peculiar scenario in the Brazilian film market. Fiction productions in the form of feature films had their first forays in the mid-2000s. In a framework developed by the researcher in her masters dissertation in History (Silva, 2018), and updated up to 2022, we cataloged twenty-two films, only six of which were registered in the National Film Agency. The main methodology to be used will be the collection and interpretation of data, in addition to unstructured or unstructured interviews (Lakatos and Marconi, 2003). As main results, we can point out that, in Maranhão, the market is predominantly informal with occasional moments of formality. The initial conclusion of our research is that the economic factor associated with the lack of public policies, added to the lack of higher education courses in the area, are the main drivers of this incipient scenario.

A case of TFE3 translocation renal cell carcinoma with rare morphological features and literature review

Context: TFE3 translocation renal cell carcinoma (RCC) is a rare tumor that represents approximately 1% of RCC. It was classifed as a member of MiT family translocation RCCs by the World Health Organization in 2016. It is characterized by Xp11 translocation gene fusions involving TFE3. The diagnosis of TFE3 translocation RCC is based on immunohistochemical analysis and TFE3 break apart probes in FISH analysis, rather than histological characteristics and imaging examination. Aims: To determine the clinico-pathological, immuno-phenotypic, and cytogenetic characteristics of TFE3 translocation RCC. Methods and Materials: The clinical data of a 52-year-old-female patient with TFE3 translocation RCC exhibiting rare morphological characteristics was analyzed, and the tumor tissues were probed using histopathological staining, immunohistochemistry, and fluorescence in situ hybridization (FISH). In addition, the relevant literature was reviewed. Results: This case is a TFE3 translocation RCC with rare morphological features. It composed of two types of tumor cells. TFE3 and pax-8 were diffusely and strongly expressed in both tumor cells, and they were partially positive for CAIX, RCC, CK, EMA, CD10, Vim, Melan-A, and p504s. Only 2% of the cells were positive for the proliferation marker Ki-67, and the tumor was negative for CK7, CD117, Inhibin-?, HBM45, and p53. FISH showed a positive signal for TFE3 translocation. Conclusions: This case was a TFE3 translocation RCC with rare morphological features. Through this case report, we emphasize the importance of in situ detection of TFE3 gene translocation and protein in TFE3 translocation RCC.

Detection method of early heart valve diseases based on heart sound features / 生物医学工程学杂志

Heart valve disease (HVD) is one of the common cardiovascular diseases. Heart sound is an important physiological signal for diagnosing HVDs. This paper proposed a model based on combination of basic component features and envelope autocorrelation features to detect early HVDs. Initially, heart sound signals lasting 5 minutes were denoised by empirical mode decomposition (EMD) algorithm and segmented. Then the basic component features and envelope autocorrelation features of heart sound segments were extracted to construct heart sound feature set. Then the max-relevance and min-redundancy (MRMR) algorithm was utilized to select the optimal mixed feature subset. Finally, decision tree, support vector machine (SVM) and k-nearest neighbor (KNN) classifiers were trained to detect the early HVDs from the normal heart sounds and obtained the best accuracy of 99.9% in clinical database. Normal valve, abnormal semilunar valve and abnormal atrioventricular valve heart sounds were classified and the best accuracy was 99.8%. Moreover, normal valve, single-valve abnormal and multi-valve abnormal heart sounds were classified and the best accuracy was 98.2%. In public database, this method also obtained the good overall accuracy. The result demonstrated this proposed method had important value for the clinical diagnosis of early HVDs.

Recognition of motor imagery electroencephalogram based on flicker noise spectroscopy and weighted filter bank common spatial pattern / 生物医学工程学杂志

Due to the high complexity and subject variability of motor imagery electroencephalogram, its decoding is limited by the inadequate accuracy of traditional recognition models. To resolve this problem, a recognition model for motor imagery electroencephalogram based on flicker noise spectrum (FNS) and weighted filter bank common spatial pattern ( wFBCSP) was proposed. First, the FNS method was used to analyze the motor imagery electroencephalogram. Using the second derivative moment as structure function, the ensued precursor time series were generated by using a sliding window strategy, so that hidden dynamic information of transition phase could be captured. Then, based on the characteristic of signal frequency band, the feature of the transition phase precursor time series and reaction phase series were extracted by wFBCSP, generating features representing relevant transition and reaction phase. To make the selected features adapt to subject variability and realize better generalization, algorithm of minimum redundancy maximum relevance was further used to select features. Finally, support vector machine as the classifier was used for the classification. In the motor imagery electroencephalogram recognition, the method proposed in this study yielded an average accuracy of 86.34%, which is higher than the comparison methods. Thus, our proposed method provides a new idea for decoding motor imagery electroencephalogram.

A review on intelligent auxiliary diagnosis methods based on electrocardiograms for myocardial infarction / 生物医学工程学杂志

Myocardial infarction (MI) has the characteristics of high mortality rate, strong suddenness and invisibility. There are problems such as the delayed diagnosis, misdiagnosis and missed diagnosis in clinical practice. Electrocardiogram (ECG) examination is the simplest and fastest way to diagnose MI. The research on MI intelligent auxiliary diagnosis based on ECG is of great significance. On the basis of the pathophysiological mechanism of MI and characteristic changes in ECG, feature point extraction and morphology recognition of ECG, along with intelligent auxiliary diagnosis method of MI based on machine learning and deep learning are all summarized. The models, datasets, the number of ECG, the number of leads, input modes, evaluation methods and effects of different methods are compared. Finally, future research directions and development trends are pointed out, including data enhancement of MI, feature points and dynamic features extraction of ECG, the generalization and clinical interpretability of models, which are expected to provide references for researchers in related fields of MI intelligent auxiliary diagnosis.

Deep learning method for magnetic resonance imaging fluid-attenuated inversion recovery image synthesis / 生物医学工程学杂志

Magnetic resonance imaging(MRI) can obtain multi-modal images with different contrast, which provides rich information for clinical diagnosis. However, some contrast images are not scanned or the quality of the acquired images cannot meet the diagnostic requirements due to the difficulty of patient's cooperation or the limitation of scanning conditions. Image synthesis techniques have become a method to compensate for such image deficiencies. In recent years, deep learning has been widely used in the field of MRI synthesis. In this paper, a synthesis network based on multi-modal fusion is proposed, which firstly uses a feature encoder to encode the features of multiple unimodal images separately, and then fuses the features of different modal images through a feature fusion module, and finally generates the target modal image. The similarity measure between the target image and the predicted image in the network is improved by introducing a dynamic weighted combined loss function based on the spatial domain and K-space domain. After experimental validation and quantitative comparison, the multi-modal fusion deep learning network proposed in this paper can effectively synthesize high-quality MRI fluid-attenuated inversion recovery (FLAIR) images. In summary, the method proposed in this paper can reduce MRI scanning time of the patient, as well as solve the clinical problem of missing FLAIR images or image quality that is difficult to meet diagnostic requirements.

Research progress on attention level evaluation based on electroencephalogram signals / 生物医学工程学杂志

Attention level evaluation refers to the evaluation of people's attention level through observation or experimental testing, and its research results have great application value in education and teaching, intelligent driving, medical health and other fields. With its objective reliability and security, electroencephalogram signals have become one of the most important technical means to analyze and express attention level. At present, there is little review literature that comprehensively summarize the application of electroencephalogram signals in the field of attention evaluation. To this end, this paper first summarizes the research progress on attention evaluation; then the important methods for electroencephalogram attention evaluation are analyzed, including data preprocessing, feature extraction and selection, attention evaluation methods, etc.; finally, the shortcomings of the current development in the field of electroencephalogram attention evaluation are discussed, and the future development trend is prospected, to provide research references for researchers in related fields.

Keloid nomogram prediction model based on weighted gene co-expression network analysis and machine learning / 生物医学工程学杂志

Keloids are benign skin tumors resulting from the excessive proliferation of connective tissue in wound skin. Precise prediction of keloid risk in trauma patients and timely early diagnosis are of paramount importance for in-depth keloid management and control of its progression. This study analyzed four keloid datasets in the high-throughput gene expression omnibus (GEO) database, identified diagnostic markers for keloids, and established a nomogram prediction model. Initially, 37 core protein-encoding genes were selected through weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the centrality algorithm of the protein-protein interaction network. Subsequently, two machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) were used to further screen out four diagnostic markers with the highest predictive power for keloids, which included hepatocyte growth factor (HGF), syndecan-4 (SDC4), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), and Rho family guanosine triphophatase 3 (RND3). Potential biological pathways involved were explored through gene set enrichment analysis (GSEA) of single-gene. Finally, univariate and multivariate logistic regression analyses of diagnostic markers were performed, and a nomogram prediction model was constructed. Internal and external validations revealed that the calibration curve of this model closely approximates the ideal curve, the decision curve is superior to other strategies, and the area under the receiver operating characteristic curve is higher than the control model (with optimal cutoff value of 0.588). This indicates that the model possesses high calibration, clinical benefit rate, and predictive power, and is promising to provide effective early means for clinical diagnosis.

Relationship of Microvascular Obstruction with Global and Regional Myocardial Function Determined by Cardiac Magnetic Resonance after ST-Segment Elevation Myocardial Infarction / 中国医学科学杂志(英文版)

Objective To investigate the impact of microvascular obstruction (MVO) on the global and regional myocardial function by cardiac magnetic resonance feature-tracking (CMR-FT) in ST-segment-elevation myocardial infarction (STEMI) patients after percutaneous coronary intervention.Methods Consecutive acute STEMI patients who underwent cardiac magnetic resonance imaging 1 - 7 days after successful reperfusion by percutaneous coronary intervention treatment were included in this retrospective study. Based on the presence or absence of MVO on late gadolinium enhancement images, patients were divided into groups with MVO and without MVO. The infarct zone, adjacent zone, and remote zone were determined based on a myocardial 16-segment model. The radial strain (RS), circumferential strain (CS), and longitudinal strain (LS) of the global left ventricle (LV) and the infarct, adjacent, and remote zones were measured by CMR-FT from cine images and compared between patients with and without MVO using independent-samples t-test. Logistic regression analysis was used to assess the association of MVO with the impaired LV function.Results A total of 157 STEMI patients (mean age 56.66 ± 11.38 years) were enrolled. MVO was detected in 37.58% (59/157) of STEMI patients, and the mean size of MVO was 3.00 ±3.76 mL. Compared with patients without MVO (n =98 ), the MVO group had significantly reduced LV global RS (t= -4.30, P < 0.001), global CS (t= 4.99, P < 0.001), and global LS ( t= 3.51, P = 0.001). The RS and CS of the infarct zone in patients with MVO were significantly reduced (t= -3.38, P = 0.001; t= 2.64, P = 0.01; respectively) and the infarct size was significantly larger (t= 8.37, P < 0.001) than that of patients without MVO. The presence of LV MVO [OR= 4.10, 95%CI: 2.05 - 8.19, P<0.001) and its size [OR=1.38, 95%CI: 1.10-1.72, P=0.01], along with the heart rate and LV infarct size were significantly associated with impaired LV global CS in univariable Logistic regression analysis, while only heart rate (OR=1.08, 95%CI: 1.03 - 1.13, P=0.001) and LV infarct size (OR=1.10, 95%CI: 1.03 - 1.16, P=0.003) were independent influencing factors for the impaired LV global CS in multivariable Logistic regression analysis.Conclusion The infarct size was larger in STEMI patients with MVO, and MVO deteriorates the global and regional LV myocardial function.

Non-rigid registration for medical images based on deformable convolution and multi-scale feature focusing modules / 生物医学工程学杂志

Non-rigid registration plays an important role in medical image analysis. U-Net has been proven to be a hot research topic in medical image analysis and is widely used in medical image registration. However, existing registration models based on U-Net and its variants lack sufficient learning ability when dealing with complex deformations, and do not fully utilize multi-scale contextual information, resulting insufficient registration accuracy. To address this issue, a non-rigid registration algorithm for X-ray images based on deformable convolution and multi-scale feature focusing module was proposed. First, it used residual deformable convolution to replace the standard convolution of the original U-Net to enhance the expression ability of registration network for image geometric deformations. Then, stride convolution was used to replace the pooling operation of the downsampling operation to alleviate feature loss caused by continuous pooling. In addition, a multi-scale feature focusing module was introduced to the bridging layer in the encoding and decoding structure to improve the network model's ability of integrating global contextual information. Theoretical analysis and experimental results both showed that the proposed registration algorithm could focus on multi-scale contextual information, handle medical images with complex deformations, and improve the registration accuracy. It is suitable for non-rigid registration of chest X-ray images.

Research on mild cognitive impairment diagnosis based on Bayesian optimized long-short-term neural network model / 生物医学工程学杂志

The recurrent neural network architecture improves the processing ability of time-series data. However, issues such as exploding gradients and poor feature extraction limit its application in the automatic diagnosis of mild cognitive impairment (MCI). This paper proposed a research approach for building an MCI diagnostic model using a Bayesian-optimized bidirectional long short-term memory network (BO-BiLSTM) to address this problem. The diagnostic model was based on a Bayesian algorithm and combined prior distribution and posterior probability results to optimize the BO-BiLSTM network hyperparameters. It also used multiple feature quantities that fully reflected the cognitive state of the MCI brain, such as power spectral density, fuzzy entropy, and multifractal spectrum, as the input of the diagnostic model to achieve automatic MCI diagnosis. The results showed that the feature-fused Bayesian-optimized BiLSTM network model achieved an MCI diagnostic accuracy of 98.64% and effectively completed the diagnostic assessment of MCI. In conclusion, based on this optimization, the long short-term neural network model has achieved automatic diagnostic assessment of MCI, providing a new diagnostic model for intelligent diagnosis of MCI.

Research on phase modulation to enhance the feature of high-frequency steady-state asymmetric visual evoked potentials / 生物医学工程学杂志

High-frequency steady-state asymmetric visual evoked potential (SSaVEP) provides a new paradigm for designing comfortable and practical brain-computer interface (BCI) systems. However, due to the weak amplitude and strong noise of high-frequency signals, it is of great significance to study how to enhance their signal features. In this study, a 30 Hz high-frequency visual stimulus was used, and the peripheral visual field was equally divided into eight annular sectors. Eight kinds of annular sector pairs were selected based on the mapping relationship of visual space onto the primary visual cortex (V1), and three phases (in-phase[0º, 0º], anti-phase [0º, 180º], and anti-phase [180º, 0º]) were designed for each annular sector pair to explore response intensity and signal-to-noise ratio under phase modulation. A total of 8 healthy subjects were recruited in the experiment. The results showed that three annular sector pairs exhibited significant differences in SSaVEP features under phase modulation at 30 Hz high-frequency stimulation. And the spatial feature analysis showed that the two types of features of the annular sector pair in the lower visual field were significantly higher than those in the upper visual field. This study further used the filter bank and ensemble task-related component analysis to calculate the classification accuracy of annular sector pairs under three-phase modulations, and the average accuracy was up to 91.5%, which proved that the phase-modulated SSaVEP features could be used to encode high- frequency SSaVEP. In summary, the results of this study provide new ideas for enhancing the features of high-frequency SSaVEP signals and expanding the instruction set of the traditional steady state visual evoked potential paradigm.

A non-contact continuous blood pressure measurement method based on video stream / 生物医学工程学杂志

Hypertension is the primary disease that endangers human health. A convenient and accurate blood pressure measurement method can help to prevent the hypertension. This paper proposed a continuous blood pressure measurement method based on facial video signal. Firstly, color distortion filtering and independent component analysis were used to extract the video pulse wave of the region of interest in the facial video signal, and the multi-dimensional feature extraction of the pulse wave was preformed based on the time-frequency domain and physiological principles; Secondly, an integrated feature selection method was designed to extract the universal optimal feature subset; After that, we compared the single person blood pressure measurement models established by Elman neural network based on particle swarm optimization, support vector machine (SVM) and deep belief network; Finally, we used SVM algorithm to build a general blood pressure prediction model, which was compared and evaluated with the real blood pressure value. The experimental results showed that the blood pressure measurement results based on facial video were in good agreement with the standard blood pressure values. Comparing the estimated blood pressure from the video with standard blood pressure value, the mean absolute error (MAE) of systolic blood pressure was 4.9 mm Hg with a standard deviation (STD) of 5.9 mm Hg, and the MAE of diastolic blood pressure was 4.6 mm Hg with a STD of 5.0 mm Hg, which met the AAMI standards. The non-contact blood pressure measurement method based on video stream proposed in this paper can be used for blood pressure measurement.

Esophageal Angiolipoma:Report of One Case and Literature Review / 中国医学科学院学报

Esophageal angiolipoma is a rare disease with unspecific clinical manifestations.This paper reported a case of esophageal angiolipoma confirmed by upper gastrointestinal endoscopy and summarized the clinical manifestations,endoscopic and pathological features,treatment and prognosis of the patients by reviewing the relevant literature,aiming to provide references for clinical diagnosis and treatment of this disease in the future.