BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

Objective To evaluate the effect of donor gender on short-term survival rate of lung transplant recipients. Methods A retrospective analysis was conducted on the data of 1 066 lung transplant recipients. The log-rank test was used to evaluate the differences in short-term fatality among different donor gender groups and donor-recipient gender combination groups. Multivariate Cox regression, propensity score (PS) regression, and propensity score matching (PSM) were employed to control for confounding factors and further assess the differences in fatality. Subgroup analyses were also performed based on donor gender. Results Multivariate Cox regression analysis showed no statistically significant differences in fatality at 30 days, 1 year, 2 years and 3 years postoperatively between male and female donor groups (all P>0.05). After PS regression and PSM, univariate Cox regression analysis indicated that recipients from female donors had a higher fatality at 2 years postoperatively compared to those from male donors, with hazard ratios (95% confidence intervals) of 1.29 (1.01-1.65) and 1.36 (1.03-1.80) respectively. Multivariate Cox regression analysis also revealed no statistically significant differences in fatality at various follow-up time points among different donor-recipient gender combination groups (all P>0.05). Subgroup analyses based on donor sex showed no statistically significant differences in fatality among recipients of different gender within either male or female donor groups (all P>0.05). Conclusions Female donors may reduce the short-term postoperative survival rate of lung transplant recipients, but this negative impact is not sustainable in the long term. At present, there is no evidence to support the inclusion of sex as a factor in lung allocation rules.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

ObjectiveTo reveal the correlation of Rehmannia glutinosa-soil feedback process with the formation of its continuous cropping obstacles through the identification of the root exudates of R. glutinosa and analysis of the specific rhizomicrobes recruited by the root exudate. MethodThe root exudates of R. glutinosa seedlings germinated under sterilized condition and those enriched in the rhizosphere of R. glutinosa cultivated in the field were collected and analyzed using the ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry（UPLC-Q-TOF-MS）. The highly abundant compounds identified in the root exudates were added into blank soil， and the soil microbial community was profiled using Illumina Miseq sequencing. The bacterial and fungal functions were predicted by PICRUSt and FUNGuild， respectively. ResultThe identification results showed that seven phenylethanoid glycosides were found in R. glutinosa root exudates， and acteoside possessed the highest abundance. In the soil enriched with acteoside， the bacterial genera such as Agromyces， Pseudomonas， Lysobacter， Sphingobium， Pseudoxanthomonas and Sphingomonas were enriched. For the fungi， the genera Neocosmospora， Plectosphaerella and Dactylonectria， and the species such as Neocosmospora rubicola， Plectosphaerella cucumerina， Dactylonectria alcacerensis and Fusarium solani showed higher abundance. The functional analysis indicated the above-mentioned bacterial genera may realize rapid proliferation by utilizing， biodegrading and transforming phenylethanoid glycosides， and some potential fungal pathogens were colonized. ConclusionThe R. glutinsoa-soil feedbacks were likely generated by the phenylethanoid glycosides in the root exudates together with the specific rhizomicrobes. The investigations of R. glutinsoa-soil feedbacks under continuous cropping system are critical to the further understanding of the underlying mechanisms related to its continuous cropping obstacles.

Humans ; Vascular Stiffness ; Coal Mining ; Occupational Diseases/epidemiology* ; Risk Factors ; Coal ; Miners

Objective To observe the clinical efficacy of the modified Huangan Lipi Decoction(mainly composed of Sclerotium Poriae Pararadicis,Paeoniae Radix Alba,Atractylodis Macrocephalae Rhizoma,Polygalae Radix,Acori Tatarinowii Rhizoma,and Curcumae Radix)combined with acupuncture at Sifeng(EX-UE10)points in the treatment of children with tic disorders(TD).Methods Seventy cases of TD children with spleen deficiency and liver hyperactivity syndrome were randomly divided into the treatment group and the control group,with 35 cases in each group.The control group was treated with conventional western medicine of Tiapride Hydrochloride Tablets,while the treatment group was treated with the combination of the modified Huangan Lipi Decoction and acupuncture at Sifeng points.Both groups were treated for 8 weeks.The changes of the Yale Global Tic Severity Scale(YGTSS)item scores of tic muscle group,tic frequency,tic intensity,complexity and interference degree as well as their total scores in the two groups were observed before and after treatment.Moreover,the clinical efficacy and safety in the two groups were evaluated.Results(1)After 8 weeks of treatment,the total effective rate of the treatment group was 88.57%(31/35),and that of the control group was 68.57%(24/35).The intergroup comparison showed that the total effective rate(tested by chi-square test)and the overall therapeutic efficacy(tested by rank-sum test)of the treatment group were significantly superior to those of the control group,and the differences were statistically significant(P＜0.05).(2)After treatment,the YGTSS item scores of tic muscle group,tic frequency,tic intensity,complexity and interference degree as well as their total scores in the two groups were significantly lower than those before treatment(P＜0.01),and the effect on lowering the above scores of the treatment group was significantly superior to that of the control group,the differences being all statistically significant(P＜0.01).(3)During the treatment,the incidence of adverse reactions in the treatment group was 2.86%(1/35)and that in the control group was 8.57%(3/35).The intergroup comparison showed that the incidence of adverse reactions in the treatment group tended to be lower than that of the control group,but the difference was not statistically significant(P＞0.05).Conclusion Modified Huangan Lipi Decoction combined with acupuncture at Sifeng points exert certain effect in the treatment of TD children with spleen deficiency and liver hyperactivity syndrome,and its efficacy is superior to that of the western medicine Tiapride Hydrochloride Tablets.