BACKGROUND: Ovarian cancer is insidious and usually detected in advanced stages of the disease. As the ovaries are pelvic organs, changes in their pelvic fluid metabolites may be associated with ovarian cancer.
METHODS: Metabolomic changes in the pelvic fluid were detected using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patients with ovarian cancer, ovarian cysts and uterine fibroids. Area under the curve (AUC) analysis was used to assess the diagnostic performance of lipid metabolites and blood tumor indices. The Pearson correlation algorithm was used to analyze the correlation between clinical characteristics and lipid metabolites in ovarian cancer patients.
RESULTS: There were 24 lipid metabolites significantly changed in the pelvic fluid of ovarian cancer patients (p < 0.05). Palmitoylcarnitine, lipoamide, lipid metabolites, and blood tumor indices (CA15-3 and CA125) showed AUC > 0.8, with palmitoylcarnitine reaching a high of 0.942. In addition, we found that some lipid metabolites were significantly associated with the clinical stage, abdominal water volume, lymphatic metastasis, and recurrence (p < 0.05, r > 0.5).
CONCLUSIONS: Levels of specific lipid metabolites are potential biomarkers of ovarian cancer and may play a key role in the early diagnosis and prognostic assessment of ovarian cancer.
CONCLUSIONS: Our results showed that pelvic metabolites, especially some lipid metabolites, play an important role in the diagnosis of ovarian cancer. Meanwhile, partial lipid metabolites were closely associated with the clinical presentation and prognosis of patients with ovarian cancer. We believe that our study makes a significant contribution to the literature because it provides a potential approach that is more effective for ovarian cancer detection.

Total antioxidants play a crucial role in human health, and detection of the total antioxidant capacity (TAC) has broad application prospects in fields such as food safety, environmental assessment, and disease diagnosis. However, a long detection time, cumbersome steps, high cost, reliance on professional equipment, and nonportability still remain significant challenges. In this work, an efficient strategy of point-of-care testing (POCT) of the TAC in body fluids by nanozyme-catalyzed colorimetric paper-based microfluidic sensors is proposed. The paper-based microfluidic sensors coupled with a smartphone can reduce testing costs and provide portability. The nanozyme prepared by the solvothermal method presents Michaelis constants of 0.11 and 0.129 mM for H2O2 and TMB, respectively. A method for immobilizing nanozymes and chromogenic agents on a paper-based microfluidic chip is established. Based on smartphone photography and image grayscale extraction, the TAC can be qualitatively detected with a detection limit and linear range of 33.4 and 50-700 μM, respectively. Furthermore, the proposed sensor can realize the one-step quantitative analysis of the TAC in body fluids (blood, saliva, and sweat) within 15 min. The proposed nanozyme-catalyzed colorimetric paper-based microfluidic sensors presented in this study exhibit promising application prospects in the fields of biochemical analysis and POCT.

Magnesium-based biodegradable metal bone implants exhibit superior mechanical properties compared to biodegradable polymers for orthopedic and cardiovascular stents. In this study, MgZZC-x (x = 1, 1.2) alloys were screened by in vitro biocompatibility tests in three simulated body fluids under nontoxic conditions. The MgZZC-1 alloys with better biocompatibility were selected to predict the days required for complete degradation. The evolution of degradation products was analyzed, and the mechanism of formation of the product film was inferred. A degradation kinetic model was established to investigate the effect of MEM components on the degradation of the alloys. The results demonstrate that the proteins in MEM can greatly retard the degradation progress by attaching to the surface of MgZZC-1 alloys, which are predicted to degrade completely within 341 days. The carbonate and phosphate buffers were adjusted to pH in MEM solution, delaying the degradation of magnesium alloys. This process in MEM more accurately reflects the actual degradation in the body and is superior to that in Hanks and SBF solutions. This study will promote the application of biodegradable materials in clinical medicine.

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

In forensic practice, mixture stains containing various body fluids are common, presenting challenges for interpretation, particularly in multi-contributor mixtures. Traditional STR profiles face difficulties in such scenarios. Over recent years, RNA has emerged as a promising biomarker for body fluid identification, and mRNA polymorphism has shown excellent performance in identifying body fluid donors in previous studies. In this study, a massively parallel sequencing assay was developed, encompassing 202 coding region SNPs (cSNPs) from 45 body fluid/tissue-specific genes to identify both body fluid/tissue origin and the respective donors, including blood, saliva, semen, vaginal secretion, menstrual blood, and skin. The specificity was evaluated by examining the single-source body fluids/tissue and revealed that the same body fluid exhibited similar expression profiles and the tissue origin could be identified. For laboratory-generated mixtures containing 2-6 different components and mock case mixtures, the donor of each component could be successfully identified, except for the skin donor. The discriminatory power for all body fluids ranged from 0.997176329 (menstrual blood) to 0.99999999827 (blood). The concordance of DNA typing and mRNA typing for the cSNPs in this system was also validated. This cSNP typing system exhibits excellent performance in mixture deconvolution.

Fluid biopsy technology, characterized by its minimally invasive nature, speed, and continuity, has become a rapidly advancing and widely applied real-time diagnostic technique. Among various biomarkers, proteins represent the most abundant class of disease indicators. The sensitive and accurate detection of protein markers in bodily fluids is significantly influenced by the control exerted by recognition ligands. Aptamers, which are structurally dynamic functional oligonucleotides, exhibit high affinity, specific recognition of targets, and notable characteristics of high editability and modularity. These features make aptamer universal \"recognition-capture\" components, contribute to a significant leap in their applications within the biosensor domain. In this context, we provide a comprehensive review of the extensive application of aptamer-based biosensors in fluid biopsy. We systematically compile the characteristics and construction strategies of aptamer-based biosensors tailored for fluid biopsy, including aptamer sequences, affinity (KD), fluid background, sensing technologies, sensor construction strategies, incubation time, detection performance, and influencing factors. Furthermore, a comparative analysis of their advantages and disadvantages was conducted. In conclusion, we delineate and deliberate on prospective research trajectories and challenges that lie ahead in the realm of aptamer-based biosensors for fluid biopsy.

In conventional clinical disease diagnosis and screening based on biomarker detection, most analysis samples are collected from serum, blood. However, these invasive collection methods require specific instruments, professionals, and may lead to infection risks. Additionally, the diagnosis process suffers from untimely results. The identification of skin-related biomarkers plays an unprecedented role in early disease diagnosis. More importantly, these skin-mediated approaches for collecting biomarker-containing biofluid samples are noninvasive or minimally invasive, which is more preferable for point-of-care testing (POCT). Therefore, skin-based biomarker detection patches have been promoted, owing to their unique advantages, such as simple fabrication, desirable transdermal properties and no requirements for professional medical staff. Currently, the skin biomarkers extracted from sweat, interstitial fluid (ISF) and wound exudate, are achieved with wearable sweat patches, transdermal MN patches, and wound patches, respectively. In this review, we detail these three types of skin patches in biofluids collection and diseases-related biomarkers identification. Patch classification and the corresponding manufacturing as well as detection strategies are also summarized. The remaining challenges in clinical applications and current issues in accurate detection are discussed for further advancement of this technology (Scheme 1).

Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords (\"metabolomics\" OR \"metabolite\") AND \"cancer\" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.

UNASSIGNED: Extracellular vesicles (EVs) are membrane-bound vesicles containing various proteins, lipids, and nucleic acids. EVs are found in many body fluids, such as blood and urine. The release of EVs can facilitate intercellular communication through fusion with the plasma membrane or endocytosis into the recipient cell or through internalization of the contents. Recent studies have reported that EVs isolated from human endometrial epithelial cells (EECs) promote sperm fertilization ability. EVs from uterine flushing fluid more closely resemble the physiological condition of the uterus. However, it is unclear whether EVs derived directly from uterine flushing fluid have the same effect on sperm. This study aimed to research the effect of EVs from uterine flushing fluid on sperm.
UNASSIGNED: EVs were isolated from the uterine flushing fluid. The presence of EVs was confirmed by nanoparticle tracking analysis (NTA), Western blot, and transmission electron microscopy (TEM). EVs were incubated with human sperm for 2 h and 4 h. The effects of EVs on sperm were evaluated by analyzing acrosome reaction, sperm motility, and reactive oxygen species (ROS).
UNASSIGNED: The EVs fractions isolated from the uterine fluid were observed in cup-shaped vesicles of different sizes by TEM. All isolated vesicles contained similar numbers of vesicles in the expected size range (30-200 nm) by NTA. CD9 and CD63 were detected in EVs by western blot. Comparing the motility of the two groups incubated sperm motility significantly differed at 4 h. The acrosome reactions were promoted by incubating with EVs significantly. ROS were increased in sperm incubated with EVs.
UNASSIGNED: Our results showed EVs present in the uterine fluid. Acrosome reactions and ROS levels increased in human sperm incubated with EVs. EVs from uterine fluid can promote the capacitation of human sperm. The increased capacitation after sperm interaction with EVs suggests a possible physiological effect during the transit of the uterus.

OBJECTIVE: To observe the effect of penetrating-moxibustion therapy on postpartum uterine involution.
METHODS: Eighty puerpera were randomized into an observation group and a control group, 40 cases in each one. In the control group, oxytocin injection was administered by intravenous drip, 20 U each time, once daily. In the observation group, on the base of the treatment as the control group, the penetrating-moxibustion therapy was used at Shenque (GV 8), Qihai (CV 6) and Guanyuan (CV 4), 30 min to 40 min each time, twice a day. The intervention of each group started from the first day after childbirth and lasted 3 days. The uterine volume before and after treatment, and in 42 days of postpartum, the height decrease of the fundus of the uterus, the score of visual analogue scale (VAS) for uterine contraction, the volume of lochia rubra in 1 to 3 days of treatment, and lochia duration were compared between the two groups; and the clinical effect was evaluated.
RESULTS: The uterine volume in the observation group was smaller than that of the control group after treatment (P<0.01). In 1 to 3 days of treatment, the height decrease of the fundus of the uterus in the observation group was larger (P<0.01), VAS scores of uterine contraction were lower (P<0.05, P<0.01), the lochia rubra volume was less (P<0.01) than those in the control group. The duration of lochia rubra and lochia was shorter (P<0.01) in the observation group when compared with that of the control group. The favorable rate of uterine involution in the observation group was 95.0% (38/40), higher than that of the control group (75.0%, 30/40, P<0.05).
CONCLUSIONS: Penetrating-moxibustion therapy accelerates the recovery of the uterine volume, relieves uterine contraction, shortens the duration of lochia, reduces the lochia volume and promotes the postpartum uterine involution.
目的: 观察透灸法对产后子宫复旧的影响。方法: 将80例产妇随机分为观察组和对照组，每组40例。对照组予缩宫素注射液静脉滴注，每次20 U，每日1次；在对照组治疗基础上，观察组采用透灸法治疗，穴取神阙、气海、关元，每次30~40 min，每日2次。均从产后第1天开始，共治疗3 d。比较两组产妇治疗前后及产后42 d子宫体积、治疗1~3 d子宫底下降高度、治疗1~3 d宫缩痛视觉模拟量表（VAS）评分、治疗1~3 d阴道血性恶露量和恶露持续时间，并评定两组临床疗效。结果: 观察组治疗后子宫体积小于对照组（P<0.01），治疗1~3 d子宫底下降高度均大于对照组（P<0.01），治疗1~3 d宫缩痛 VAS评分均低于对照组（P<0.05，P<0.01），治疗1~3 d阴道血性恶露量均少于对照组（P<0.01），血性恶露及恶露持续时间短于对照组（P<0.01）。观察组子宫复旧良好率为95.0%（38/40），高于对照组的75.0%（30/40，P<0.05）。结论: 透灸法能加速产后子宫体积恢复，缓解宫缩痛，缩短恶露持续时间，减少恶露排出量，促进子宫复旧。.