Phenotypic and genotypic analysis of 11 fetal cases with Bardet-Biedl syndrome.

OBJECTIVE: To present the prenatal sonographic features and genomic spectrum of pregnancies with fetal Bardet-Biedl syndrome (BBS). METHODS: This was a retrospective study of 11 cases with BBS diagnosed by prenatal ultrasound and confirmed by genetic testing. Clinical and laboratory data were collected and reviewed for these cases, including maternal demographics, prenatal sonographic findings, molecular testing sequencing results, and pregnancy outcomes. RESULTS: All cases had unremarkable first-trimester ultrasound scans without reporting limb malformations. All had second-trimester abnormal ultrasounds: postaxial polydactyly in nine cases (9/11), renal abnormalities in seven (7/11), reduced amniotic fluid volume in two (2/11), central nervous system anomalies in two (2/11), and ascites in three (3/11). Ten fetuses presented with at least two-system anomalies, and one (Case 11) presented with only postaxial polydactyly. Variants were detected in five genes, including BBS2, ARL6/BBS3, BBS7, CEP290/BBS14 and IFT74/BBS22. Ten pregnancies were terminated in the second trimester, while one continued to term. CONCLUSION: Enlarged hyperechogenic kidneys and postaxial polydactyly are the two most common sonographic features of fetal BBS. Prenatal diagnosis of BBS can be done with ultrasound and genetic testing although the diagnosis may be made in the second trimester.

[Impact of Mild SARS-CoV-2 Infection on Hematological Parameters and Suitability of Apheresis Platelets Donation in Blood Donors].

OBJECTIVE: To investigate the effects of mild SARS-CoV-2 infection on hematological parameters of adult blood donors and the suitability of apheresis platelet donation, the changes of the hematological parameters in blood donors with mild infection of the SARS-CoV-2 Omicron variant strain were evaluated. METHODS: Seventy-two blood donors with mild COVID-19 symptoms who donated consecutive apheresis platelets for 3 times from December 2022 to January 2023, 42 cases among which were included in the infection-positive group, and 30 cases in the suspected infection group. Forty-two donors un-vaccinated against SARS-CoV-2, un-infected, and donated three consecutive apheresis platelets from October to November 2022 were included in the control group. The changes of blood routine testing in the positive group and the suspected infection group were retrospectively compared before (Time1) and after (Time2 and Time3) the onset of symptoms, three consecutive times (Time1, Time2, Time3) in the control group by repeated measures analysis of variance. The Bayesian discriminant method was used to establish a discriminant equation to determine whether the recent infection of SARS-CoV-2 occurred or not. RESULTS: Simple effect of the number times of tests in the positive and suspected infection groups was significant（ Finfection-positive group=6.98, P < 0.001, partial η2=0.79, Fsuspected infection group=4.31, P < 0.001, partial η2=0.70）. The positive group and the suspected infection group had lower RBC, HCT, and HGB, and higher PLT and PCT at Time2 compared to Time1 and Time3(P < 0.05). The positive group and the suspected infection group showes RDW-CV and RDW-SD at Time3 higher than Time1 and Time2 (P < 0.001). The simple effect of the number times of tests in the control group was not significant ( F=0.96, P =0.55, partial η2=0.34). The difference of the whole blood count parameters in the control group for three times was not statistically significant (P >0.05). We established a discriminant equation to determine whether the recent infection of SARS-CoV-2 occurred or not. The equation had an eigenvalue of 0.22, a canonical correlation of 0.43 (χ2=27.81, P < 0.001), and an analysis accuracy of 72.9%. CONCLUSION: The hematological indicators of RBC, HCT, HGB, PLT, PCT, RDW-CV and RDW-SD in blood donors who had infected with mild COVID-19 showed dynamic changes. The discriminant equation for whether they are infected recently with COVID-19 has a high accuracy rate.

Investigating the mechanistic impact of pork soft tissue preparation techniques on the classification precision of laser-induced breakdown spectroscopy.

The investigation of the mechanism underlying the impact of biological soft tissue sample preparation methods on laser-induced breakdown spectroscopy (LIBS) signals can enhance the stability of LIBS signals. Our study focused on four specific preparation methods applied to pork samples: rapid freezing, fresh slicing, drying, and pressing. The influence of various preparation techniques on the signal-to-noise ratio and fluctuation of Ca, Na, Mg, and CN bands within the sample spectra was assessed. The signal-to-noise ratios for samples that were dried and pressed notably improved. And the pressing method effectively mitigated the uneven distribution of pork tissue components, displaying superior spectral line stability. To explain this phenomenon, we used the Saha-Boltzmann diagram to estimate the plasma temperature. Remarkably, there was a significant reduction in plasma temperature fluctuations across four pressed samples, with a standard deviation of 108.53. Furthermore, we undertook a classification analysis employing support vector machine models to corroborate the generalization efficacy of the sample preparation technique. Dried and pressed samples demonstrated notably higher classification accuracy, precision, and recall (all >93%) compared to frozen and fresh samples, where these metrics remained below 86%. The performance of the SVM model was ultimately evaluated using Receiver Operating Characteristic (ROC) curves and the Area Under the Curve (AUC). The AUC for the frozen, fresh, dried, and pressed samples was 0.854, 0.907, 0.989, and 0.996, respectively. The findings revealed that the pressing method exhibited superior performance, followed by drying, fresh slicing, and freezing, in descending order of effectiveness.

Decision-level data fusion based on laser-induced breakdown and Raman spectroscopy: A study of bimodal spectroscopy for diagnosis of lung cancer at different stages.

Lung cancer staging is crucial for personalized treatment and improved prognosis. We propose a novel bimodal diagnostic approach that integrates LIBS and Raman technologies into a single platform, enabling comprehensive tissue elemental and molecular analysis. This strategy identifies critical staging elements and molecular marker signatures of lung tumors. LIBS detects concentration patterns of elemental lines including Mg (I), Mg (II), Ca (I), Ca (II), Fe (I), and Cu (II). Concurrently, Raman spectroscopy identifies changes in molecular content, such as phenylalanine (1033 cm-1), tyrosine (1174 cm-1), tryptophan (1207 cm-1), amide III (1267 cm-1), and proteins (1126 cm-1 and 1447 cm-1), among others. The bimodal information is fused using a decision-level Bayesian fusion model, significantly enhancing the performance of the convolutional neural network architecture in classification algorithms, with an accuracy of 99.17 %, sensitivity of 99.17 %, and specificity of 99.88 %. This study provides a powerful new tool for the accurate staging and diagnosis of lung tumors.

The effects of Tai Chi on standing balance control in older adults may be attributed to the improvement of sensory reweighting and complexity rather than reduced sway velocity or amplitude.

Introduction: Tai Chi has proved to be an effective therapy for balance performance and cognition. However, non-consistency exists in the results of the effect of Tai Chi training on standing balance control in older adults. This study aimed to use traditional and non-traditional methods to investigate the effect of Tai Chi on standing balance in older adults. Methods: Thirty-six Tai Chi practitioners (TC group) and thirty-six older adults with no Tai Chi practice (control group) were recruited in this study. A Nintendo Wii Balance Board was used to record the center of pressure (COP) during standing balance over 20 s in the condition of eyes closed with three repetitions. The wavelet analysis, multiscale entropy, recurrence quantification analysis, and traditional methods were used to evaluate the standing balance control in the anterior-posterior (AP) and mediolateral (ML) directions. Results: (1) Greater sway mean velocity in the AP direction and sway Path length were found in the TC group compared with the control group; (2) lower Very-low frequency band (0.10-0.39 Hz) and higher Moderate frequency band (1.56-6.25 Hz) in the AP and ML directions were found in the TC group compared with the control group; (3) greater complexity index (CI) and lower determinism (DET) in the AP and ML directions were observed in the TC group compared with control group; (4) greater path length linked with smaller Very-low frequency band in the AP and ML directions and higher Moderate frequency band in the AP direction in both groups; (5) greater path length linked with lower DET and higher CI in the AP direction only in the TC group. Conclusion: Long-term Tai Chi practice improved sensory reweighting (more reliance on the proprioception system and less reliance on the vestibular system) and complexity of standing balance control in older adults. In addition, greater sway velocity may be as an exploratory role in standing balance control of TC older adults, which correlated with greater complexity, but no such significant relationship in the control group. Therefore, the effects of Tai Chi practice on standing balance control in older adults may be attributed to the improvement of sensory reweighting and complexity rather than reduced sway velocity or amplitude.

Research on a new multiple-screening method for laser-induced plasma spectroscopy utilizing Lorentz.

In the field of Laser Induced Breakdown Spectroscopy (LIBS) research, the screening and extraction of complex spectra play a crucial role in enhancing the accuracy of quantitative analysis. This paper introduces a novel approach for multiple screenings of LIBS spectra using Lorentz Screening and Sensitivity and Volatility Analysis. Initially, Create symmetrical sampling standards for Lorentz fitting. Then the Lorentz fitting is used to uniformly screen the collected spectral information on both sides in order to eliminate adjacent interference peaks. Subsequently, Sensitivity and Volatility Analysis is employed to further remove overlapping peaks and select spectra with low volatility and high sensitivity. Sensitivity and Volatility Analysis is a spectral discrimination method proposed on the premise of intensity's correlation with concentration. It utilizes a Z-score method that incorporates both deviation and standard deviation for effective analysis. Furthermore, it meticulously selects spectral lines with minimal interference and volatility, thereby augmenting the precision of quantitative analysis. The quantitative accuracy (R2) for Chromium (Cr) and Nickel (Ni) elements can reach 0.9919 and 0.9768, respectively. Their average errors can be reduced to 0.0566 % and 0.1024 %. The study demonstrates that Lorentz Screening and Sensitivity and Volatility Analysis can select high-quality characteristic spectral lines to improve the performance of the model.

Construction and enhancement of government capacity for international communication and promotion of Chinese Wushu.

BACKGROUND: In the process of international communication in Chinese Wushu (ICCW), the government controls the orientation, scale, pace. However, the ICCW currently lacks a standardised government capacity structural system, and a detailed study of framework construction may be required to ensure the smooth development of the ICCW. OBJECTIVES: This study aims to clarify these elements and construct a framework for a governmental capacity system for ICCW. METHODS: For this purpose, an expert interview outline was designed, and in-depth interviews were conducted with 61 experts. Using grounded theory in the qualitative research method, NVivo 12 software was used to conduct a three-level coding analysis of the interview text for data processing and analysis. RESULTS: We extracted 58 opening codes and 11 tree nodes and categorised them into three core categories: supply side government capacity, environment-side government capacity, and demand-side government capacity, accounting for 62.36 %, 24.76 %, and 12.86 % of the total, respectively, which jointly constructed the framework structure system of the governmental capacity system for the ICCW. CONCLUSIONS: This study found that these three-dimensional government capacities have synergistic effects and that multiple measures work together. The government should ensure the supply side's direct promotion effect; the environmental side's indirect influencing effect; and the demand side's internal driving effect to promote ICCW. Meanwhile, a closed-loop systematic study of communication processes should be conducted in combination with communication organisations and individuals.

Fusion of laser-induced breakdown spectroscopy technology and deep learning: a new method to identify malignant and benign lung tumors with high accuracy.

Precisely distinguishing between malignant and benign lung tumors is pivotal for suggesting therapeutic strategies and enhancing prognosis, yet this differentiation remains a daunting task. The growth rates, metastatic potentials, and prognoses of benign and malignant tumors differ significantly. Developing specialized treatment protocols tailored to various tumor types is essential for enhancing patient survival outcomes. Employing laser-induced breakdown spectroscopy (LIBS) in conjunction with a deep learning methodology, we attained a high-precision differential diagnosis of malignant and benign lung tumors. First, LIBS spectra of malignant tumors, benign tumors, and normal tissues were collected. The spectra were preprocessed and Z score normalized. Then, the intensities of the Mg II 279.6, Mg I 285.2, Ca II 393.4, Cu II 518.3, and Na I 589.6 nm lines were analyzed in the spectra of the three tissues. The analytical results show that the elemental lines have different contents in the three tissues and can be used as a basis for distinguishing between the three tissues. Finally, the RF-1D ResNet model was constructed by combining the feature importance assessment method of random forest (RF) and one-dimensional residual network (1D ResNet). The classification accuracy, precision, sensitivity, and specificity of the RF-1D ResNet model were 91.1%, 91.6%, 91.3%, and 91.3%, respectively. And the model demonstrates superior performance with an area under the curve (AUC) value of 0.99. The above results show that combining LIBS with deep learning is an effective way to diagnose malignant and benign tumors.

Clinical and molecular analysis of nine fetal cases with clinically significant variants causing nemaline myopathy.

OBJECTIVE: To present the prenatal features and postnatal outcomes of pregnancies with fetal nemaline myopathy (NM). STUDY DESIGN: This was a retrospective study of nine cases with NM diagnosed by prenatal or postnatal clinical features and confirmed by genetic testing. Clinical and laboratory data were collected and reviewed for these cases, including maternal demographics, prenatal sonographic findings, exome sequencing (ES) results, and pregnancy outcomes. RESULTS: All of the nine cases were detected to have NM-causing variants, involving NEB gene in 2 cases, ACTA1 in 3 cases, KLHL40 in 3 cases, and TPM2 in 1 case. Almost all (8/9) had normal first-trimester ultrasound scans except one who had an increased nuchal translucency. Seven (7/9) cases had second-trimester abnormal ultrasounds with fetal akinesia and/or extremity anomalies. Two (2/9) had only third-trimester abnormal ultrasounds with fetal akinesia and polyhydramnios, with one combined with fetal growth restriction. Four pregnancies with a positive prenatal ES were terminated, while five having not receiving prenatal ES continued to term. Only one infant survived 1 year old, and four passed away within 12 months. CONCLUSION: Prenatal ultrasound can detect clues that lead to the diagnosis of NM, such as reduced or absent fetal movements, polyhydramnios and extremity anomalies.

Isolated polyhydramnios: Is a genetic evaluation of value?

OBJECTIVE: To analyze the risk for genetic aberrations and pregnancy outcomes in pregnancies with isolated polyhydramnios. STUDY DESIGN: This was a retrospective study of singleton pregnancies complicated by isolated polyhydramnios that underwent genetic amniocentesis between 2016 and 2021. Clinical and laboratory data were collected and reviewed for these cases, including maternal demographics, prenatal sonographic findings, chromosomal microarray results, and pregnancy outcomes. RESULTS: A total of 94 singleton pregnancies were included. Three (3.2%) cases with chromosomal abnormalities were detected, including 2 case of trisomy 21 and 1 of 22q21.1 microdeletion. One case was diagnosed as Prader-Willi syndrome caused by maternal uniparental disomy of chromosome 15. Perinatal death occurred in 1 case with severe polyhydramnios, and was retrospectively diagnosed as Bartter syndrome. Of the 90 infants survived, two were identified to have single gene disorders after birth by whole exome sequencing. CONCLUSION: We first attempted to determine the value of exome sequencing in pregnancies with isolated polyhydramnios. Our results warrant more studies to evaluate advanced genetic testing technologies used in such pregnancies.

A rat model established by simulating genetic-environmental interactions recapitulates human Alzheimer's disease pathology.

BACKGROUND: In humans, Alzheimer's disease (AD) is typically sporadic in nature, and its pathology is usually influenced by extensive factors. The study established a rat model based on the genetic-environmental interaction. METHODS: A rat model was established by transduction of an adeno-associated virus combined with acrolein treatment. Rats were assigned to the normal control (NC), acrolein group, AAV (-) group, AAV-APP group, and AAV-APP/acrolein group. The success of model construction was verified in multiple ways, including by assessing cognitive function, examining microstructural changes in the brain in vivo, and performing immunohistochemistry. The contribution of genetic (APP mutation) and environmental (acrolein) factors to AD-like phenotypes in the model was explored by factorial analysis. RESULTS: 1) The AAV-APP/acrolein group showed a decline in cognitive function, as indicated by a reduced gray matter volume in key cognition-related brain areas, lower FA values in the hippocampus and internal olfactory cortex, and Aß deposition in the cortex and hippocampus. 2) The AAV-APP group also showed a decline in cognitive function, although the group exhibited atypical brain atrophy in the gray matter and insignificant Aß deposition. 3) The acrolein group did not show any significant changes in Aß levels, gray matter volume, or cognitive function. 4) The genetic factor (APP mutation) explained 39.74% of the AD-like phenotypes in the model factors, and the environmental factor (acrolein exposure) explained 33.3%. CONCLUSIONS: The genetic-environmental interaction rat model exhibited a phenotype that resembled the features of human AD and will be useful for research on AD.

Prenatal diagnosis of autosomal recessive Noonan syndrome associated with biallelic LZTR1 variants presented with thick nuchal translucency and cardiac abnormalities.

Noonan syndrome (NS) is a common clinical variable disease characterized by a number of features, mainly including congenital heart defects, short stature, and a variable degree of developmental delay. This disorder is transmitted mostly in an autosomal dominant manner and is genetically heterogeneous. We report three prenatal cases of LZTR1-related recessive NS. One case had a recurrent cystic hygroma at 13 weeks gestation and the pregnancy was terminated. Two cases had an increased nuchal translucency at 12 weeks' gestation, but a normal second trimester ultrasound; both presented with hypertrophic cardiomyopathy in the third trimester. The two infants were diagnosed with NS after birth. All of the three cases had invasive genetic investigations during pregnancy, and trio exome sequencing revealed biallelic likely pathogenic or pathogenic LZTR1 variants in the fetuses. All parents were LZTR1 variant carriers. Our report further strengthens the association of LZTR1 with an autosomal recessive form of NS. The affected fetuses are more likely to have cardiac anomalies. Clarification of molecular diagnosis has important implications in these families because they carry a 25% recurrence risk.

A study of the spectral signal effect of self-holes in metal additive manufacturing components using laser-induced breakdown spectroscopy (LIBS).

Understanding the detection mechanism of hole defects in metal additive manufacturing (AM) components is of great significance for the detection of metal AM component defects using laser-induced breakdown spectroscopy (LIBS). In this work, the mapping relationship between the hole defects of metal AM components and the LIBS spectral signal was studied using the controlled variable method. The effect of hole defects mostly showed a suppression effect and peaked at a hole depth of 1.0 mm when the LIBS system was at its optimal excitation parameter. To explore the possible reasons behind the inhibitory effect of self-holes, the variation law of the plasma temperature with and without hole defects was further investigated. Our results showed that the plasma temperature change curve was similar to the spectral line intensity change trend. Finally, the linear relationship between the focal length effect and the hole effect, and the relationship between the constraint effect and the hole effect were studied. The minimum fitting R2 between the constraint effect and the hole effect was 0.979. We believed that the inhibition of the hole effect was mainly caused by the absorption and loss of energy in the plasma during the process of plasma radiation and shock wave reflection from the hole wall. By studying the detection mechanism of hole defects in metal additive manufacturing components excited by LIBS and finding the effective characteristics of hole defects in metal AM components, it is helpful to achieve higher precision and higher sensitivity defect detection.

Application of real-time PCR-based multicolor melting curve with automatic analysis system in pregestational and prenatal thalassemia diagnoses.

BACKGROUND: To evaluate the value of the real-time PCR-based multicolor melting curve analysis (MMCA) with an automatic analysis system used in a mass thalassemia screening and prenatal diagnosis program. METHODS: A total of 18,912 peripheral blood samples from 9456 couples and 1150 prenatal samples were detected by MMCA assay. All prenatal samples were also tested by a conventional method. Samples with unknown melting peaks, unusual peak height ratios between a wild allele and a mutant allele, or a discordant phenotype-genotype match were further studied by using multiplex ligation-dependent probe amplification (MLPA) or Sanger sequencing. All MMCA results were automatically analyzed and manually checked. The consistency between MMCA assay and conventional methods among prenatal samples was investigated. RESULTS: Except for initiation codon (T > G) (HBB:c.2T > G), all genotypes of thalassemia inside the scope of conventional methods were detected by MMCA assay. Additionally, 27 carriers with 10 rare HBB variants, 13 with α fusion gene, 1 with a rare deletion in α globin gene, and 1 with rare HBA variant were detected by using MMCA assay. CONCLUSION: MMCA can be an alternative approach used in routine thalassemia carrier screening and prenatal diagnosis for its high throughput, sufficient stability, low cost, and easy operation.

A deep learning method for foot-type classification using plantar pressure images.

Background: Flat foot deformity is a prevalent and challenging condition often leading to various clinical complications. Accurate identification of abnormal foot types is essential for appropriate interventions. Method: A dataset consisting of 1573 plantar pressure images from 125 individuals was collected. The performance of the You Only Look Once v5 (YOLO-v5) model, improved YOLO-v5 model, and multi-label classification model was evaluated for foot type identification using the collected images. A new dataset was also collected to verify and compare the models. Results: The multi-label classification algorithm based on ResNet-50 outperformed other algorithms. The improved YOLO-v5 model with Squeeze-and-Excitation (SE), the improved YOLO-v5 model with Convolutional Block Attention Module (CBAM), and the multilabel classification model based on ResNet-50 achieved an accuracy of 0.652, 0.717, and 0.826, respectively, which is significantly higher than those obtained using the ordinary plantar-pressure system and the standard YOLO-v5 model. Conclusion: These results indicate that the proposed DL-based multilabel classification model based on ResNet-50 is superior in flat foot type detection and can be used to evaluate the clinical rehabilitation status of patients with abnormal foot types and various foot pathologies when more data on patients with various diseases are available for training.

[Clinical and genetic analysis of a case of Turner syndrome with rapidly progressive puberty and a literature review].

OBJECTIVE: To investigate the clinical features and genetic etiology of a case of Turner syndrome (TS) with rapidly progressive puberty. METHODS: A child who had presented at the Pediatric Endocrinology Clinic of the Shenzhen People's Hospital on January 19, 2022 was selected as the study subject. Clinical data of the child were collected. Peripheral blood sample of the child was subjected to chromosomal microarray analysis (CMA) and multiple ligation-dependent probe amplification (MLPA). Previous studies related to TS with rapidly progressive puberty were retrieved from the CNKI, Wanfang Data Knowledge Service Platform, Boku, CBMdisc and PubMed databases with Turner syndrome and rapidly progressive puberty as the keywords. The duration for literature retrieval was set from November 9, 2021 to May 31, 2022. The clinical characteristics and karyotypes of the children were summarized. RESULTS: The child was a 13-year-and-2-month-old female. She was found to have breast development at 9, short stature at 10, and menarche at 11. At 13, she was found to have a 46,X,i(X)(q10) karyotype. At the time of admission, she had a height of 143.5 cm (< P3), with 6 ~ 8 nevi over her face and right clavicle. She also had bilateral simian creases but no saddle nasal bridge, neck webbing, cubitus valgus, shield chest or widened breast distance. She had menstruated for over 2 years, and her bone age has reached 15.6 years. CMA revealed that she had a 58.06 Mb deletion in the Xp22.33p11.1 region and a 94.49 Mb duplication in the Xp11.1q28 region. MLPA has confirmed monosomy Xp and trisomy Xq. A total of 13 reports were retrieved from the CNKI, Wanfang Data Knowledge Service Platform, Boku, CBMdisc and PubMed databases, which had included 14 similar cases. Analysis of the 15 children suggested that their main clinical manifestations have included short stature and growth retardation, and their chromosomal karyotypes were mainly mosaicisms. CONCLUSION: The main clinical manifestations of TS with rapidly progressive puberty are short stature and growth retardation. Deletion in the Xp22.33p11.1 and duplication in the Xp11.1q28 probably underlay the TS with rapid progression in this child, which has provided a reference for clinical diagnosis and genetic counselling for her.

Artificial Lipid Biomembranes for Full-Length SARS-CoV-2 Receptor.

The angiotensin-converting enzyme 2 (ACE2), as a functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is essential for assessing potential hosts and treatments. However, many studies are based on its truncated version but not full-length structure. Indeed, a single transmembrane (TM) helix presents in the full-length ACE2, influencing its interaction with SARS-CoV-2. Therefore, synthesis of the full-length ACE2 is an urgent requirement. Here, cell-free membrane protein synthesis systems (CFMPSs) are constructed for full-length membrane proteins. MscL is screened as a model among ten membrane proteins based on their expression and solubility. Next, CFMPSs are constructed and optimized based on natural vesicles, vesicles with four membrane proteins removed or two chaperonins added, and 37 types of nanodiscs. They all increase membrane protein solubility to over 50%. Finally, the full-length ACE2 of 21 species are successfully expressed with yields between 0.4 and 0.9 mg mL-1 . The definite functional differences from the truncated version suggest that the TM region affects ACE2's structure and function. CFMPSs can be extended to more membrane proteins, paving the way for further applications.