Objective: To explore the current status and influencing factors of eating behaviors in adolescents, so as to provide a theoretical foundation for health promotion education among adolescents. Methods: Based on the database from Survey of Chinese Family Health Index (2021), by a random number table method, 1 065 teenagers were selected from the provincial capitals of 22 provinces and 5 autonomous regions in China, as well as 4 municipalities directly under the central government. A general characteristic questionnaire, Patient Health Questionnaire-9 (PHQ-9), Short Form of the Family Health Scale (FHS-SF), 10-item Short Version of the Big Five Personality(BFP-10), Content-based Media Exposure Scale (CM-E) and Sakata Eating Behavior Scale Short Form(EBS-SF) were used to collect information. Multivariate stepwise linear regression analysis was employed to identify and analyze related factors of eating behaviors among adolescents. Receiver operating characteristic was used to validate the predictive ability of the EBS-SF score for overweight and obesity among adolescents. Results: The average scores of BFI-10,C-ME, FHS-SF, PHQ-9 and EBS-SF were (33.08±4.64)(19.20±4.55)(38.48±6.65)(6.09±5.63)(16.75±4.36), respectively. Multivariate linear regression showed that family type (other types), agreeableness, conscientiousness, family health and depression were the main related factors of EBS-SF scores among adolescents( B =2.61,-0.42,0.20,-0.11,0.23, P <0.05).The analysis of receiver operating characteristic curve showed that the EBS-SF scores had a good ability in predicting obesity among male adolescents ( AUC= 0.73, P <0.01). Conclusions Family type, big five personality, family health,depression are the related factors of eating behaviors among adolescents. EBS-SF scores are predictive of obesity in adolescents, which would provide a new perspective for promoting healthy eating habits among adolescents.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

The development of longitudinal cohorts has made the identification and surveillance of multiple biological markers and behavioral factors which influence disease course or health status become possible. However, traditional statistical methods typically use univariate longitudinal data for research, failing to fully exploit the information from multivariate longitudinal data. The group-based multi-trajectory model (GBMTM) emerged as a method to study the developmental trajectory of multivariate data in recent years. GBMTM has distinct advantages in analyzing multivariate longitudinal data by identifying potential subgroups of populations following similar trajectories by multiple indicators that influence the outcome of interest. In this study, we introduced the application of GBMTM by explaining the fundamental principles and using the data from a health management study in the elderly by using smart wearing equipment to investigate the relationship between multiple life-related variables and hypertension to promote the wider use of GBMTM in longitudinal cohort studies.

Objective:To explore the construction and application of an evidence-based practice plan for early postoperative activity in postoperative patients with large area cerebral infarction.Methods:Ninety-six postoperative patients with large area cerebral infarction admitted to Wenzhou Central Hospital from July 2021 to April 2023 were selected as the study subjects for a Clinical trial. They were divided into the control group (48 cases) and the observation group (48 cases) by random number table method. The control group received routine postoperative care for neurosurgery, while the observation group received evidence-based systematic early activity training. Both groups were followed up until 1 month after the patient was discharged from the hospital. The time of postoperative hospitalization, hospitalization expenses, vital signs and pain investigation 48 h after surgery, daily living ability before intervention and 7 d, 1 month after discharge, neurological function before intervention and 7 d and 1 month after surgery, and complications during follow-up between the two groups were compared.Results:In the control group, there were 29 males and 19 females, with an average age of 43-67(56.87 ± 1.76) years. In the observation group, there were 31 males and 17 females, with an average age of 43-68 (57.02 ± 1.82) years. The postoperative hospital stay in the observation group was (6.87 ± 0.65) d, in the control group was (9.06 ± 0.72) d, the difference between them was significant ( t=15.64, P<0.05). 48 hours after surgery, the heart rate, breathing rate and mean arterial pressure in the observation group were (71.65 ± 0, 45) times/min, (14.76 ± 0.36) times/min and (76.98 ± 5.65) mmHg(1 mmHg=0.133 kPa), which were different with those in the control group, (82.76 ± 2.65) times/min, (18.76 ± 2.87) times/min and (93.76 ± 5.93) mmHg ( t=28.64, 9.58 and 14.19, all P<0.05). Seven days after discharge, the score of Activities of Daily Living and the National Institutes of Health Neurological Impairment Scale in the observation group were (84.65 ± 2.45) and (23.65 ± 2.65), which were different than the (79.76 ± 1.97) and (28.54 ± 2.73) in the control group ( t=10.26, 8.91, both P<0.05). A month after discharge, the score of Activities of Daily Living and the National Institutes of Health Neurological Impairment Scale in the observation group were (95.45 ± 1.43) and (18.65 ± 1.98), while in the control group were (87.87 ± 1.39) and (21.54 ± 2.76), the difference between them were significant ( t=26.33, 5.90, both P<0.05). The total incidence of complications such as postoperative bleeding, postoperative infection and hypoxemia in the observation group was 20.83% (10/48), which was significant lower than the 68.75% (33/48) in the control group ( χ2=22.28, P<0.05). Conclusions:Evidence-based systematic early activity training could significantly alleviate postoperative pain in patients with large area cerebral infarction after surgery, improve their daily living ability and neurological function, further effectively shorten their hospitalization time, and reduce the occurrence of complications.

Objective To investigate the application value of single nucleotide polymorphism(SNP)linkage analysis based on next-generation sequencing(NGS)technology in preimplantation genetic testing(PGT)of families with autosomal recessive polycystic kidney disease(ARPKD).Methods A family with ARPKD was selected,where the female member had a pregnancy ultrasound revealing polycystic kidney in the fetus.Genetic testing showed compound heterozygous mutations of the polycystic kidney/polycystic liver disease 1 gene(PKHD1),c.10444C>T(paternal)and c.4303del(maternal),with the c.4303del mutation being reported for the first time.Targeting the coding region of the PKHD1 gene,335 high-density tightly linked SNP sites were selected in the upstream and downstream 2M regions using multiplex polymerase chain reaction(PCR)and NGS.The couple′s SNP risk haplotypes carrying gene mutations were constructed.After in vitro fertilization,blastocyst culture was performed.Trophoblastic cells obtained from the biopsy were subjected to whole-genome amplification,and NGS was used for linkage analysis and low-depth chromosomal aneuploidy screening of the embryos.Sanger sequencing was used to verify the results of embryo linkage analysis.Results Among the 6 biopsied embryos,4 were mutation-free and euploid,1 exhibited heterozygous for the mutation and mosaic while another unstable sequencing data,making it impossible to judge.One of the mutation-free and developmentally healthy euploid embryos was implanted into the maternal uterus,resulting in the full-term delivery of a healthy baby.Conclusion Application of NGS-based SNP linkage analysis in PGT can effectively blocking the vertical transmission of ARPKD within families,while avoiding abortion issues caused by aneuploid embryos.This study is also the first PGT report target-ing the PKHD1 gene c.4303del mutation.

BACKGROUND:In vitro fertilization-embryo transfer is commonly used to solve infertility,but its success rate is not high,the more common reasons are poor endometrial receptivity,poor egg quality,etc.The follicular fluid melatonin can inhibit the aging of the ovary,to a certain extent,can promote the development of embryos,improve the probability of conception,but whether there is a correlation between the two is not known. OBJECTIVE:To explore the correlation between follicular fluid melatonin level and pregnancy rate of single-cycle in vitro fertilization-embryo transfer women. METHODS:A total of 112 female patients who received in vitro fertilization-embryo transfer treatment in the First Affiliated Hospital of Anhui Medical University from December 2020 to April 2021 were selected as the study subjects.They were divided into quartile array(Q1-Q5)according to the follicular fluid melatonin level from low to high.Among them,the melatonin level of group Q1 was<6.99 ng/L(n=18),that of group Q2 was 7.00-9.99 ng/L(n=26),that of group Q3 was 10.00-11.99 ng/L(n=27),and that of group Q4 was 12.00-13.99 ng/L(n=18);and melatonin levels in group Q5 were 14.00-19.99 ng/L(n=23).Clinical data characteristics of the five groups were compared.Multi-factor Logistic regression was used to analyze the correlation between follicular fluid melatonin level and pregnancy rate of women with single-cycle in vitro fertilization-embryo transfer and embryo transfer.A restricted cubic spline Logistic regression model was established to analyze the dose-response relationship,and the model was evaluated by clinical decision curve. RESULTS AND CONCLUSION:(1)Compared with the study population with the lowest melatonin quintile(Q1),with the increase of melatonin level(Q2-Q5),the levels of egg harvest and pregnancy success were gradually increased,and the body mass index was gradually decreased,and the differences were significant(P<0.05).(2)Multivariate Logistic regression analysis showed that after adjusting for confounding factors such as global mass index,number of eggs retrieved,luteinizing hormone,estradiol,progesterone and other confounding factors,follicular fluid melatonin level was still independently correlated with pregnancy rate of single-cycle in vitro fertilization-embryo transfer women(OR=1.538,95%CI:1.032-1.837,P<0.05),and there was significant difference in trend test of follicular fluid melatonin level from low to high quintile array(Ptrend<0.05).(3)The sensitivity test analysis showed that E value was 2.117.Subgroup analysis showed that the study population with higher levels of luteinizing hormone in follicular fluid had a more significant association between follicular fluid melatonin and pregnancy rate in single-cycle in vitro fertilization-embryo transfer women(P interaction=0.008).(4)The results of restricted cubic spline model analysis showed that there was a nonlinear dose-response relationship between follicular fluid melatonin level and pregnancy rate of single-cycle in vitro fertilization-embryo transfer women(P<0.05),and there was an overall positive correlation between follicular fluid melatonin level and pregnancy rate of single-cycle in vitro fertilization-embryo transfer women.(5)The results of clinical decision curve analysis showed that the follicular fluid melatonin level had important clinical value in predicting the pregnancy rate of single-cycle in vitro fertilization-embryo transfer women.(6)Follicular fluid melatonin level is closely related to the pregnancy rate of single-cycle in vitro fertilization-embryo transfer women,and with the decrease of follicular fluid melatonin level,the pregnancy rate of single-cycle in vitro fertilization-embryo transfer women also decreases.

Objective To investigate the factors influencing the pregnancy outcomes during frozen-thawed embryo transfer(FET)cycles in patients with polycystic ovary syndrome(PCOS).Methods A retrospective analysis was conducted on patients'data from 882 FET cycles.According to the pregnancy outcome,the patients were divided into non-implantation group(Group A),abortion group(Group B1)and live birth group(Group B2).Clinical data and laboratory parameters were compared among the three groups,and ordered Logistic regression analysis was used to study the factors influencing pregnancy outcomes after FET.Patients were also divided into four groups(C1-C4)based on the number of high-quality embryos obtained(0-3,4-6,7-10,≥11),and their clinical data and laboratory parameters were compared.Results The clinical pregnancy rate,live birth rate,and miscar-riage rate in the 882 treatment cycles were 71.09%(627/882),61.68%(544/882),and 13.24%(83/627),respectively.Single-factor analysis showed significant differences in body mass index(BMI),infertility type,hu-man chorionic gonadotropin(hCG)day estradiol(E2)level,number of retrieved oocytes,and number of high-quality embryos among Groups A,B1,and B2(P<0.05).Further multiple Logistic regression analysis revealed that BMI(OR=1.046,95%CI:1.001-1.093,P=0.044)and a history of previous pregnancy(OR=1.417,95%CI:1.030-1.950,P=0.032)were independent risk factors for successful FET in PCOS patients,while an in-creased number of high-quality embryos was an independent protective factor for successful pregnancy.Based on the results of Group B2,compared to Group A,OR=0.920,95%CI:0.880-0.962,P=0.000;compared to Group B1,OR=0.923,95%CI:0.862-0.988,P=0.022.Compared with the other three groups(C1-C3),the total amount of gonadotropin(Gn)in the C4 group was the lowest and the number of oocytes obtained was the high-est(P<0.05).Multiple comparisons showed that Group C4 had lower BMI,follicle-stimulating hormone(FSH),very low-density lipoprotein(vLDL)levels,a higher luteinizing hormone and follicle-stimulating hormone(LH/FSH)ratio compared to Group C1(P<0.05).Group C4 had lower fasting insulin(FINS)and homeostasis model assessment of insulin resistance(HOMA-IR)levels compared to Group C3,and higher high-density lipoprotein-cholesterol(HDL-C)and apolipoprotein A1(Apo A1)levels compared to Groups C2 and C3(P<0.05).Con-clusion BMI,the history of previous pregnancy and the number of high-quality embryos were both independent factors for predicting pregnancy outcomes in PCOS patients undergoing FET cycles.Patients with a higher number of high-quality embryos have a higher clinical pregnancy rate during FET cycles.

Objective:To investigate the clinicopathological features and differential diagnosis of eosinophilic vacuolated tumor (EVT).Methods:Seven cases of EVT with characteristic morphology and unequivocal diagnosis from the Affiliated Hospital of Qingdao University (6 cases), Qingdao, China and the 971 Hospital of PLA Navy (1 case), Qingdao, China between January 2010 and December 2021 were subject to morphological and immunohistochemical analyses. Additionally, whole exome sequencing (WES) was performed in two cases. Twenty-two cases of renal oncocytoma (RO) and 17 cases of eosinophilic chromophobe renal cell carcinoma (eChRCC) diagnosed at the same time were used as controls.Results:Four males and three females with a mean age of 42 years (range: 29-61 years) were included in the study. The tumors were nodular and well-circumscribed, with sizes ranging from 1.5 to 4.5 cm. On cross-section, they appeared gray-red or gray-white, solid, and soft. Tumor cells were arranged in nests, solid sheets, and acinar or small vesicular structures. These cells exhibited eosinophilic cytoplasm with large, prominent clear vacuoles and round nuclei with prominent nucleoli. Perinuclear halos were focally present in four cases, while small tumor cells with sparse cytoplasm and hyperchromatic nuclei were seen in one case. No necrosis or mitosis was noted. Edematous stroma was detected in three cases. All tumors were positive for CD117 and Cathepsin K, but negative for vimentin and CK7. CK20 was positive in scattered individual cells, and Ki-67 positivity ranged from 1% to 4%. Point mutations in MTOR were identified in both patients who were subject to the molecular analysis. Statistical differences in the expression of Cathepsin K, CD10, S-100A1, and Cyclin D1 between EVT and RO ( P<0.05) were significant, so were the differences in the expression of Cathepsin K, CD10, CK7 and claudin 7 between EVT and eChRCC ( P<0.001). Seven patients were followed up for 4 to 96 months (mean, 50 months), with no recurrences or metastases. Conclusions:EVT is a rare renal tumor that shares morphological and immunophenotypic features with RO and eChRCC, and it is closely linked to the TSC/MTOR pathway. The presence of large prominent transparent vacuoles in eosinophilic cytoplasm along with conspicuous nucleoli is its key morphological characteristics. The use of combined immunohistochemical stains greatly aids in its diagnosis. Typically, the tumor exhibits indolent biological behaviors with a favorable prognosis.