Purpose To investigate the correlation and prognostic value of tumor-stroma ratio(TSR)combined with fi-brotic focus(FF)and stromal tumor-infiltrating lymphocytes(sTILs)with pathological complete response(pCR)after neoad-juvant therapy in triple-negative breast cancer(TNBC).Meth-ods The clinical data of 170 cases of TNBC were collected.Af-ter double-blind reading of the sections by two senior patholo-gists,the pathological examination results of all cases were re-viewed,and the results of TSR,FF,sTILs and the expression of CD4 and CD8 were evaluated.Then the relationship between the above information and PCR and prognosis was analyzed.Results 170 cases of TNBC after neoadjuvant therapy,57 patients a-chieved pCR,while 113 patients did not achieve pCR.Statistical analysis revealed the following findings:TSR,FF,sTILs,CD4,CD8,Ki67,vascular invasion,and lymph node metastasis exhib-ited significant differences between the pCR and non-pCR groups.There were also significant differences in TSR,FF and sTILs between different Miller-Payne(MP)grades.TSR,sTILs,TSR combined with FF,sTILs and Ki67 were positively correlated with PCR.Meanwhile,TSR,sTILs,TSR combined with FF and sTILs were also positively correlated with MP grade,while FF,intravascular tumor thrombus and lymph node metasta-sis were negatively correlated with PCR.At the same time,TSR and sTILs were also positively correlated with MP grade,and FF was also negatively correlated with MP grade.The prognosis of patients was optimal with TSR＞1,G0 FF and sTILs＞50％.When TSR combined with FF and sTILs,the prognosis of PCR group was better than that of non-PCR group.Conclusion TSR,FF,and sTILs are anticipated to serve as predictive bio-markers for assessing the efficacy and prognosis of neoadjuvant therapy in TNBC patients.These findings offer novel insights into the treatment and research strategies for TNBC.

Purpose To investigate the correlation and prognostic value of tumor-stroma ratio(TSR)combined with fi-brotic focus(FF)and stromal tumor-infiltrating lymphocytes(sTILs)with pathological complete response(pCR)after neoad-juvant therapy in triple-negative breast cancer(TNBC).Meth-ods The clinical data of 170 cases of TNBC were collected.Af-ter double-blind reading of the sections by two senior patholo-gists,the pathological examination results of all cases were re-viewed,and the results of TSR,FF,sTILs and the expression of CD4 and CD8 were evaluated.Then the relationship between the above information and PCR and prognosis was analyzed.Results 170 cases of TNBC after neoadjuvant therapy,57 patients a-chieved pCR,while 113 patients did not achieve pCR.Statistical analysis revealed the following findings:TSR,FF,sTILs,CD4,CD8,Ki67,vascular invasion,and lymph node metastasis exhib-ited significant differences between the pCR and non-pCR groups.There were also significant differences in TSR,FF and sTILs between different Miller-Payne(MP)grades.TSR,sTILs,TSR combined with FF,sTILs and Ki67 were positively correlated with PCR.Meanwhile,TSR,sTILs,TSR combined with FF and sTILs were also positively correlated with MP grade,while FF,intravascular tumor thrombus and lymph node metasta-sis were negatively correlated with PCR.At the same time,TSR and sTILs were also positively correlated with MP grade,and FF was also negatively correlated with MP grade.The prognosis of patients was optimal with TSR＞1,G0 FF and sTILs＞50％.When TSR combined with FF and sTILs,the prognosis of PCR group was better than that of non-PCR group.Conclusion TSR,FF,and sTILs are anticipated to serve as predictive bio-markers for assessing the efficacy and prognosis of neoadjuvant therapy in TNBC patients.These findings offer novel insights into the treatment and research strategies for TNBC.

Objective To develop an intelligent recognition model based on deep learning algorithms of unmanned aerial vehicle (UAV) images, and to preliminarily explore the value of this model for remote identification, monitoring and management of cattle, a source of Schistosoma japonicum infection. Methods Oncomelania hupensis snail-infested marshlands around the Poyang Lake area were selected as the study area. Image datasets of the study area were captured by aerial photography with UAV and subjected to augmentation. Cattle in the sample database were annotated with the annotation software VGG Image Annotator to create the morphological recognition labels for cattle. A model was created for intelligent recognition of livestock based on deep learning-based Mask R-convolutional neural network (CNN) algorithms. The performance of the model for cattle recognition was evaluated with accuracy, precision, recall, F1 score and mean precision. Results A total of 200 original UAV images were obtained, and 410 images were yielded following data augmentation. A total of 2 860 training samples of cattle recognition were labeled. The created deep learning-based Mask R-CNN model converged following 200 iterations, with an accuracy of 88.01%, precision of 92.33%, recall of 94.06%, F1 score of 93.19%, and mean precision of 92.27%, and the model was effective to detect and segment the morphological features of cattle. Conclusion The deep learning-based Mask R-CNN model is highly accurate for recognition of cattle based on UAV images, which is feasible for remote intelligent recognition, monitoring, and management of the source of S. japonicum infection.

Objective:To assess the altered right atrial(RA) function using two-dimensional speckle-tracking imaging(2D-STI) in patients with persistent pulmonary hypertension of the newborn(PPHN), and investigate the diagnostic value of different right heart strain parameters in PPHN.Methods:Ultrasound images of 42 newborns with clinically confirmed diagnosis of PPHN in the neonatal intensive care unit of Shenzhen Children′s Hospital (median gestational age 37 + 1 weeks, median age 6 d) and 30 normal newborns (control group, median gestational age 37 + 3 weeks, median age 6.5 d) from January 2020 to January 2023 were retrospectively analyzed, all with gestational age ≥34 gestational weeks. 2D-STI was applied to evaluate RA function: RA strain(RA LS) and area change fraction(RA FAC), where RA LS included RA reservoir strain (εs), RA conduit strain (εe) and RA active contract strain (εa), while evaluating right ventricle(RV) function: RV global longitudinal strain(RV GLS), RV FAC, etc. And the degree of pulmonary artery pressure(PAP) was assessed by tricuspid regurgitation velocity(TRV). The above parameters were compared between the PPHN group and the control group, and the correlations between RA function parameters, RV function parameters and PAP in PPHN group were analyzed. The area under ROC curve (AUC) was used to compare the accuracy of each parameter in the evaluation of impaired cardiac function in PPHN patients. Results:Compared with the control group, RA function (εs, εe, εa and RA FAC) were impaired in PPHN patients (all P<0.05). εs was positively correlated with RV GLS, RA FAC ( r=0.494, 0.356, both P<0.05) and negatively correlated with minimum right atrial area (RAA min), pulmonary artery diameter (PAD), and tricuspid annular internal diameter ( rs=-0.285, r=-0.495, -0.396; both P<0.05); εe was negatively correlated with PAD ( rs=-0.256, P<0.05); εa was positively correlated with RV GLS ( r=0.499, P<0.05) and negatively correlated with PAD and tricuspid annular internal diameter ( r=-0.390, -0.380; both P<0.05); RA FAC was positively correlated with RV GLS ( r=0.365, P<0.05) and negatively correlated with PAD and tricuspid annular internal diameter ( r=-0.439, -0.328; both P<0.05). RA LS and RA FAC had no correlations with TRV-estimated PAP ( P>0.05). ROC analysis showed that the sensitivity and specificity of εs<40.50% for diagnosing PPHN was 0.905 and 0.800, respectively, with an AUC of 0.929; the sensitivity and specificity of RV GLS<18.55% for diagnosing PPHN were 0.905 and 0.900, respectively, with an AUC of 0.963; εs combined with RV GLS was the best indicator for early detection of right heart functional impairment in PPHN, with sensitivity and specificity of 0.905 and 1.000, respectively, and AUC was 0.985. Conclusions:RA function and RV function are both impaired in PPHN patients. εs combined with RV GLS is the best indicator for early assessment of right heart function impairment and diagnosis of PPHN.

Objective: To determine the spatiotemporal distribution of Schistosoma (S.) japonicum infections in humans, livestock, and Oncomelania (O.) hupensis across the endemic foci of China. Methods: Based on multi-stage continuous downscaling of sentinel monitoring, county-based schistosomiasis surveillance data were captured from the national schistosomiasis surveillance sites of China from 2005 to 2019. The data included S. japonicum infections in humans, livestock, and O. hupensis. The spatiotemporal trends for schistosomiasis were detected using a Joinpoint regression model, with a standard deviational ellipse (SDE) tool, which determined the central tendency and dispersion in the spatial distribution of schistosomiasis. Further, more spatiotemporal clusters of S. japonicum infections in humans, livestock, and O. hupensis were evaluated by the Poisson model. Results: The prevalence of S. japonicum human infections decreased from 2.06% to zero based on data of the national schistosomiasis surveillance sites of China from 2005 to 2019, with a reduction from 9.42% to zero for the prevalence of S. japonicum infections in livestock, and from 0.26% to zero for the prevalence of S. japonicum infections in O. hupensis. Analysis using an SDE tool showed that schistosomiasis-affected regions were reduced yearly from 2005 to 2014 in the endemic provinces of Hunan, Hubei, Jiangxi, and Anhui, as well as in the Poyang and Dongting Lake regions. Poisson model revealed 11 clusters of S. japonicum human infections, six clusters of S. japonicum infections in livestock, and nine clusters of S. japonicum infections in O. hupensis. The clusters of human infection were highly consistent with clusters of S. japonicum infections in livestock and O. hupensis. They were in the 5 provinces of Hunan, Hubei, Jiangxi, Anhui, and Jiangsu, as well as along the middle and lower reaches of the Yangtze River. Humans, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the north of the Hunan Province, south of the Hubei Province, north of the Jiangxi Province, and southwestern portion of Anhui Province. In the 2 mountainous provinces of Sichuan and Yunnan, human, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the northwestern portion of the Yunnan Province, the Daliangshan area in the south of Sichuan Province, and the hilly regions in the middle of Sichuan Province. Conclusions: A remarkable decline in the disease prevalence of S. japonicum infection was observed in endemic schistosomiasis in China between 2005 and 2019. However, there remains a long-term risk of transmission in local areas, with the highest-risk areas primarily in Poyang Lake and Dongting Lake regions, requiring to focus on vigilance against the rebound of the epidemic. Development of high-sensitivity detection methods and integrating the transmission links such as human and livestock infection, wild animal infection, and O. hupensis into the surveillance-response system will ensure the elimination of schistosomiasis in China by 2030.

Objective:To establish the reference for serum metabolomics profiles among healthy Han adults in China, and explore the variation on metabolomics profiles by geographic regions, sex, and age.Methods:Cross-sectional data and serum samples were obtained from the China National Health Survey. A total of 1 039 male and 1 032 female healthy adults(≥30 years) were included in this study. Serum metabolomics analyses were conducted with ultra-performance liquid chromatography-mass spectrometry(UPLC-MS). Orthogonal partial least squares discriminant analysis(OPLS-DA) was performed to compare the differences of metabolomics among different region, sex, and age.Results:Significant differences on metabolomics profiles were identified among region, sex, and age. A total of 114 region-related metabolites were spotted, including 53 metabolites that involved in human metabolic pathways, mainly peptides(20 metabolites) and glycerophospholipid metabolism-related(14 metabolites). Fifty-nine metabolites were pinned down to be sex-related, among which cotinine was significant in all 7 provinces. Age-related metabolites were only found in Shaanxi and Hainan, with 22 metabolites were recognized.Conclusion:Serum metabolomics varies by geographic regions, sex, and age. When metabolomics is applied for diagnosis or biomarker screening in various studies, it shall take into consideration of setting tailored references.

Objective:To preliminarily study the feasibility, safety and efficacy of transcatheter arterial chemoembolization (TACE) combined with selective portal vein embolization (SPVE) before surgical resection in the treatment of large liver cancer.Methods:A retrospective study was conducted on the clinical data of 17 patients with large liver cancer treated with TACE combined with SPVE from January 2016 to December 2019 at the Department of Hepatobiliary Surgery, the Sixth Medical Center of PLA General Hospital. The study included 15 males and 2 females, aged (59.17±10.30) years. The levels of alanine aminotransferase, tumor changes and patient survival were analyzed before operation, after TACE, and after SPVE.Results:Among the 17 patients, the levels of alanine aminotransferase on the 1st and 3rd day after SPVE was significantly higher than those after TACE [191.4 (30.5-1966.4) IU/L vs 125.3 (35.7-846.2) IU/L on the first day, and 298.5 (24.6-1334.2) IU/L vs 208.6 (21.6-775.6) IU/L on the 3rd day], all P<0.05. One month after the two combined embolism, among the 6 patients with a tumor diameter of 5-10 cm, 2 patients (33.3%) had complete remission, 3 patients (50.0%) had partial remission, and 1 patients (16.6%) had stable disease. For the tumor’s longest diameter, among the 11 patients with tumors >10 cm, 1 patient had complete remission (9.1%), 4 patients had partial remission (36.4%), 5 patients had stable diseases (45.5%), and 1 patient had disease progression (9.1%). Eventually, 11 patients underwent surgical exploration. The median residual liver volume before treatment was 329.5 (284.9-365.7) ml, and after the combined procedure 415.6 (354.7-718.8) ml. The median hyperplasia ratio was 28.1% (14.1%-51.3%). Eight patients finally underwent surgical resection. There was no death in the perioperative periods. The median tumor-free survival time was 17 (7-42) months, and the median survival time was 27 (7-42) months. Conclusion:For patients with large liver cancer with insufficient remnant liver volume, preoperative TACE+ SPVE has certain value in controlling tumor progression, promoting remnant liver hyperplasia, increasing surgical resection rate and improving prognosis.

Objective:To analyze the effect of home quarantine on blood glucose and lipids in healthy adults during the COVID-19 epidemic times.Method:From April 7, 2020 to May 1, 2020, 512 adults wereexamined in Beijing physical examination center, of which 87 adults aged olderthan 18, received community closed management or home quarantine from January 23, 2020 to March 30, 2020, and theadultshad physical examination in Beijing physical examination center in the same month of 2018 and 2019 were selected as controls. The change trend of blood glucose and blood lipid acrossthe three years was analyzed by one-way repeated measurement of variance, and the difference of blood lipid and blood glucose between two years of physical examination was further analyzed by Bonferroni method. Datawereanalyzed by gender.Result:Among the 87 subjects, 36 (41.4%) were male and 51(58.6%) were female. The average age was (46.3±13.2) years and ranged from 24 to 74. The difference of high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglyceride (TG), total cholesterol (TC) and fasting blood glucose (FBG) among 2018, 2019 and 2020 was statistically significant (all P<0.05), while differences in LDL-C, TC and FBG were statistically significant for males (all P<0.05) and HDL-C, LDL-C, TC and FBG were statistically significant for females (all P<0.05). HDL-C in 2018and 2020were significantly lower than that in 2019 [(1.27±0.29), (1.30±0.31) vs. (1.36±0.34) mmol/L], LDL-C in 2020was significantly higher than that in 2018and 2019 [(3.11±0.88) vs. (2.81±0.77), (2.84±0.71) mmol/L], TG in 2020 was significantly higher than that in 2019[(1.54±1.17) vs. (1.32±0.80) mmol/L], TC in 2019and 2020were significantly higher than that in 2018 [(4.88±0.94), (5.10±0.99) vs. (4.63±0.90) mmol/L], and the FBG in 2019and 2020were significantly lower than that in 2018 [(5.34±1.17), (5.44±1.58) vs. (5.84±1.70) mmol/L] (all P<0.05). The comparative analysis of men and women showed that the means of LDL-C, TG, TC and FBG of men were higher than those of women while the mean of HDL-C was lower than that of women in each year; compared with 2019, the increase of LDL-C and TC of men was obvious while the decrease of HDL-C of women was obvious (all P<0.05) in 2020. Conclusion:During the epidemic period of COVID-19, the home quarantine has adverse effects on blood glucose and lipid.

Due to the rapid evolution of high-throughput technologies, a tremendous amount of data is being produced in the biological domain, which poses a challenging task for information extraction and natural language understanding. Biological named entity recognition (NER) and named entity normalisation (NEN) are two common tasks aiming at identifying and linking biologically important entities such as genes or gene products mentioned in the literature to biological databases. In this paper, we present an updated version of OryzaGP, a gene and protein dataset for rice species created to help natural language processing (NLP) tools in processing NER and NEN tasks. To create the dataset, we selected more than 15,000 abstracts associated with articles previously curated for rice genes. We developed four dictionaries of gene and protein names associated with database identifiers. We used these dictionaries to annotate the dataset. We also annotated the dataset using pre-trained NLP models. Finally, we analysed the annotation results and discussed how to improve OryzaGP.