ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Background During pregnancy, negative emotions such as anxiety and depression may induce cortisol disruption. Cortisol can be transmitted to the fetus through the placental barrier, thereby affecting the neurodevelopment of the offspring. Objective To investigate the relationship between placental cortisol, maternal depression during pregnancy, and neurodevelopment of 3-month-old infants. Methods From September 2022 to September 2023, 171 pregnant women ordered routine prenatal checks at the obstetrics outpatient department of a tertiary hospital in Ningxia were selected using a prospective cohort design. After providing informed consent, these women participated in a questionnaire survey that covered general individual characteristics, prenatal depression, and sleep quality. At birth, placental samples were collected to measure cortisol levels using ELISA kits. Follow-up assessments on the neurodevelopmental of 3-month-old infants were conducted using the Warning Sign for Children Mental and Behavioral Development. LASSO regression analysis was conducted to screen the influencing factors of depression during pregnancy. Huber regression analysis was then applied to assess potential linear relationship between depression during pregnancy and placental cortisol levels. Log-binomial regression was used to analyze the linear relationships between cortisol levels and neurodevelopmental delay in 3-month-old infants. Additionally, a mediation effect model was fitted using R 4.3.3 to assess possible mediating role of cortisol in the association between prenatal depression and neurodevelopmental delay in 3-month-old infants. Results The positive rate of prenatal depression was 33.33%. Nine factors affecting prenatal depression were identified by LASSO regression, including rural residence, high school education or above, extroverted personality characteristics, moderate early pregnancy reactions, baby sex expectation, prenatal anxiety, family dysfunction, exposure to stressful life events during pregnancy, and moderate prenatal sleep quality. The Huber regression model showed a positive linear correlation between prenatal depression and placental cortisol (P<0.05). With or without controlling confounding factors, the results of log-binomial regression modeling showed that cortisol levels were associated with a reduced risk of neurodevelopmental delay in 3-month-old infants (crude model: RR=0.988, 95%CI: 0.9768, 0.9996, P＜0.05; adjusted model: RR=0.988, 95%CI: 0.9764, 0.9993, P＜0.05). A mediating effect of placental cortisol between prenatal depression and the risk of neurodevelopmental delay in 3-month-old offspring was found statistically significant (P=0.045), accounting for 67.0% of the total effect. Conclusion Prenatal depression is associated with elevated placental cortisol levels, and higher cortisol levels are found to be related to a lower risk of neurodevelopmental delay in infants. Placental cortisol mediates the relationship between prenatal depression and infant neurodevelopment.

Ovarian cancer （OC） is a common gynecological malignant tumor in clinical practice. In the early stage，it is often asymptomatic，while in the late stage，it mainly presents with non-specific symptoms such as abdominal distension，poor appetite，and dull abdominal pain. Some patients may also have cachexia such as weight loss and anemia. Early diagnosis is difficult，and the mortality rate ranks first among gynecological malignant tumors，making OC a major challenge in clinical treatment. The classic Chinese medicine formula Guizhi Fulingwan comes from the Jingui Yaolue and has the effects of promoting blood circulation，removing blood stasis，and reducing abdominal lumps. In recent years，it has been widely used to treat OC with good results. This article summarized the clinical application of Guizhi Fulingwan in the treatment of OC from two aspects：The analysis of its basic prescriptions and clinical research. In terms of basic prescriptions，the formula has the ability to promote blood circulation，remove blood stasis，and reduce abdominal lumps. It can exert therapeutic effects considering both water and blood aspects and reduce abdominal lumps， with characteristics of simultaneous Yang warming and heat clearing and parallel supplementation and elimination. Through the methods of "circulation" and "supplementation"， it strengthens the body，dispels evil，and eliminates underlying symptoms. In clinical studies，Guizhi Fulingwan can be applied to various stages of patients with OC，which not only promotes the recovery of the body after OC surgery but also can be combined with chemotherapy and immunotherapy to synergistically treat advanced OC and enhance treatment efficacy. In addition，the formula can also alleviate various adverse reactions caused by chemotherapy，with high safety，improve patients' quality of life，prolong survival，and optimize tumor control effects. Based on the above analysis，this article elaborated on the current clinical research status of Guizhi Fulingwan combined with Western medicine in the treatment of OC and proposed suggestions and improvements to address the shortcomings in current clinical research，so as to provide reference for the clinical application of this formula in the treatment of OC and the construction of a combined traditional Chinese and Western medicine treatment model.

Ovarian cancer （OC） is a common gynecological malignant tumor in clinical practice. In the early stage，it is often asymptomatic，while in the late stage，it mainly presents with non-specific symptoms such as abdominal distension，poor appetite，and dull abdominal pain. Some patients may also have cachexia such as weight loss and anemia. Early diagnosis is difficult，and the mortality rate ranks first among gynecological malignant tumors，making OC a major challenge in clinical treatment. The classic Chinese medicine formula Guizhi Fulingwan comes from the Jingui Yaolue and has the effects of promoting blood circulation，removing blood stasis，and reducing abdominal lumps. In recent years，it has been widely used to treat OC with good results. This article summarized the clinical application of Guizhi Fulingwan in the treatment of OC from two aspects：The analysis of its basic prescriptions and clinical research. In terms of basic prescriptions，the formula has the ability to promote blood circulation，remove blood stasis，and reduce abdominal lumps. It can exert therapeutic effects considering both water and blood aspects and reduce abdominal lumps， with characteristics of simultaneous Yang warming and heat clearing and parallel supplementation and elimination. Through the methods of "circulation" and "supplementation"， it strengthens the body，dispels evil，and eliminates underlying symptoms. In clinical studies，Guizhi Fulingwan can be applied to various stages of patients with OC，which not only promotes the recovery of the body after OC surgery but also can be combined with chemotherapy and immunotherapy to synergistically treat advanced OC and enhance treatment efficacy. In addition，the formula can also alleviate various adverse reactions caused by chemotherapy，with high safety，improve patients' quality of life，prolong survival，and optimize tumor control effects. Based on the above analysis，this article elaborated on the current clinical research status of Guizhi Fulingwan combined with Western medicine in the treatment of OC and proposed suggestions and improvements to address the shortcomings in current clinical research，so as to provide reference for the clinical application of this formula in the treatment of OC and the construction of a combined traditional Chinese and Western medicine treatment model.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

BACKGROUND:The sports medicine community has widely called for the use of machine learning technology to efficiently process the huge and complicated sports data resources,and construct intelligent sports injury prediction models,enabling accurate early warning of sports injuries.It is of great significance to comprehensively summarize and review such research results so as to grasp the direction of early warning model improvement and to guide the construction of sports injury prediction models in China. OBJECTIVE:To systematically review and analyze relevant research on sports injury prediction models based on machine learning technology,thereby providing references for the development of sports injury prediction models in China. METHODS:Literature search was conducted on CNKI,Web of Science and EBSCO databases,which mainly searched for literature related to machine learning techniques and sports injuries.Finally,61 articles related to sports injury prediction models were included for analysis. RESULTS AND CONCLUSION:(1)In terms of external risk feature indicators,there is a lack of competition scenario indicators,and the inclusion of related feature indicators needs to be further improved to further enrich the dimensions of the dataset for model training.In addition,the inclusion feature weighting methods of the sports injury prediction model are mainly based on filtering methods and the use of embedding and wrapping weighting methods needs to be strengthened in order to enhance the analysis of the interaction effects of multiple risk factors.(2)In terms of model body training,supervised learning algorithms become the mainstream choice.Such algorithms have higher requirements for the completeness of sample labeling information,and the application scenarios are easily limited.Therefore,the application of unsupervised and semi-supervised algorithms can be increased in the later stage.(3)In terms of model performance evaluation and optimization,the current studies mainly adopt two verification methods:HoldOut crossover and k-crossover.The range of AUC values is(0.76±0.12),the range of sensitivity is(75.92±11.03)%,the range of specificity is(0.03±4.54)%,the range of F1 score is(80.60±10.63)%,the range of accuracy is(69.96±13.10)%,and the range of precision is(70±14.71)%.Data augmentation and feature optimization are the most common model optimization operations.The accuracy and precision of the current sports injury prediction model are about 70%,and the early warning effect is good.However,the model optimization operation is relatively single,and data augmentation methods are often used to improve model performance.Further adjustments to the model algorithm and hyperparameters are needed to further improve model performance.(4)In terms of model feature extraction,most of the internal risk profile indicators included are mainly based on anthropometrics,training load,years of training,and injury history,but there is a lack of sports recovery and physical function indicators.

Objective: To investigate the occupational health status of medical radiation workers in Hangzhou City, so as to provide the basis for their occupational health risk assessment. Methods: Data on medical radiological workers who underwent occupational health examinations from 2021 to 2022 were collected through the Physical Examination Information Management System of the Hangzhou Occupational Disease Prevention and Control Hospital. The physical examination data including blood routine, eye lens, thyroid ultrasound, thyroid function, liver function, renal function and blood lipid were collected, and the abnormal rates of occupational health examinations among workers with different genders, working years and occupational exposure types were analyzed. Results: A total of 3 968 medical radiation workers were investigated, including 2 310 males (58.22%) and 1 658 females (41.78%). There were 2 039 (51.39%), 821 (20.69%) and 1 108 (27.92%) workers with 1-<6, 6-<10 years and 10 years and above of work, respectively. Diagnostic radiology was the predomenant type of exposure, with 2 240 workers accounting for 56.45%. The abnormal rates of thyroid ultrasound and blood lipid were 47.73% and 45.21%, respectively, which were relatively higher than other items. The abnormal rates of micronucleus rate, thyroid ultrasound, thyroid function and renal function were higher in females than in males, while the abnormal rates of lymphocyte count, liver function and blood lipid in males were higher in males than in females (all P<0.05). With the increase of working years, the abnormal rates of micronucleus rate and blood lipid showed upward trends (both P<0.05). There were statistically significant differences in the abnormal rates of thyroid ultrasound, liver function and blood lipid among different occupational exposure types (all P<0.05). Conclusion Long-term low-dose ionizing radiation environment affects the thyroid, micronucleus rate and blood lipid of medical radiation workers in Hangzhou City, with differences observed among workers with different genders and occupational exposure types.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.