Maternal inheritance of glucose intolerance via oocyte TET3 insufficiency.

Diabetes mellitus is prevalent among women of reproductive age, and many women are left undiagnosed or untreated1. Gestational diabetes has profound and enduring effects on the long-term health of the offspring2,3. However, the link between pregestational diabetes and disease risk into adulthood in the next generation has not been sufficiently investigated. Here we show that pregestational hyperglycaemia renders the offspring more vulnerable to glucose intolerance. The expression of TET3 dioxygenase, responsible for 5-methylcytosine oxidation and DNA demethylation in the zygote4, is reduced in oocytes from a mouse model of hyperglycaemia (HG mice) and humans with diabetes. Insufficient demethylation by oocyte TET3 contributes to hypermethylation at the paternal alleles of several insulin secretion genes, including the glucokinase gene (Gck), that persists from zygote to adult, promoting impaired glucose homeostasis largely owing to the defect in glucose-stimulated insulin secretion. Consistent with these findings, mouse progenies derived from the oocytes of maternal heterozygous and homozygous Tet3 deletion display glucose intolerance and epigenetic abnormalities similar to those from the oocytes of HG mice. Moreover, the expression of exogenous Tet3 mRNA in oocytes from HG mice ameliorates the maternal effect in offspring. Thus, our observations suggest an environment-sensitive window in oocyte development that confers predisposition to glucose intolerance in the next generation through TET3 insufficiency rather than through a direct perturbation of the oocyte epigenome. This finding suggests a potential benefit of pre-conception interventions in mothers to protect the health of offspring.

Polycystic Ovary Syndrome Fuels Cardiovascular Inflammation and Aggravates Ischemic Cardiac Injury.

BACKGROUND: Reducing cardiovascular disease burden among women remains challenging. Epidemiologic studies have indicated that polycystic ovary syndrome (PCOS), the most common endocrine disease in women of reproductive age, is associated with an increased prevalence and extent of coronary artery disease. However, the mechanism through which PCOS affects cardiac health in women remains unclear. METHODS: Prenatal anti-Müllerian hormone treatment or peripubertal letrozole infusion was used to establish mouse models of PCOS. RNA sequencing was performed to determine global transcriptomic changes in the hearts of PCOS mice. Flow cytometry and immunofluorescence staining were performed to detect myocardial macrophage accumulation in multiple PCOS models. Parabiosis models, cell-tracking experiments, and in vivo gene silencing approaches were used to explore the mechanisms underlying increased macrophage infiltration in PCOS mouse hearts. Permanent coronary ligation was performed to establish myocardial infarction (MI). Histologic analysis and small-animal imaging modalities (eg, magnetic resonance imaging and echocardiography) were performed to evaluate the effects of PCOS on injury after MI. Women with PCOS and control participants (n=200) were recruited to confirm findings observed in animal models. RESULTS: Transcriptomic profiling and immunostaining revealed that hearts from PCOS mice were characterized by increased macrophage accumulation. Parabiosis studies revealed that monocyte-derived macrophages were significantly increased in the hearts of PCOS mice because of enhanced circulating Ly6C+ monocyte supply. Compared with control mice, PCOS mice showed a significant increase in splenic Ly6C+ monocyte output, associated with elevated hematopoietic progenitors in the spleen and sympathetic tone. Plasma norepinephrine (a sympathetic neurotransmitter) levels and spleen size were consistently increased in women with PCOS when compared with those in control participants, and norepinephrine levels were significantly correlated with circulating CD14++CD16- monocyte counts. Compared with animals without PCOS, PCOS animals showed significantly exacerbated atherosclerotic plaque development and post-MI cardiac remodeling. Conditional Vcam1 silencing in PCOS mice significantly suppressed cardiac inflammation and improved cardiac injury after MI. CONCLUSIONS: Our data documented previously unrecognized mechanisms through which PCOS could affect cardiovascular health in women. PCOS may promote myocardial macrophage accumulation and post-MI cardiac remodeling because of augmented splenic myelopoiesis.

From stem cells to pancreatic ß-cells: strategies, applications, and potential treatments for diabetes.

Loss and functional failure of pancreatic ß-cells results in disruption of glucose homeostasis and progression of diabetes. Although whole pancreas or pancreatic islet transplantation serves as a promising approach for ß-cell replenishment and diabetes therapy, the severe scarcity of donor islets makes it unattainable for most diabetic patients. Stem cells, particularly induced pluripotent stem cells (iPSCs), are promising for the treatment of diabetes owing to their self-renewal capacity and ability to differentiate into functional ß-cells. In this review, we first introduce the development of functional ß-cells and their heterogeneity and then turn to highlight recent advances in the generation of ß-cells from stem cells and their potential applications in disease modeling, drug discovery and clinical therapy. Finally, we have discussed the current challenges in developing stem cell-based therapeutic strategies for improving the treatment of diabetes. Although some significant technical hurdles remain, stem cells offer great hope for patients with diabetes and will certainly transform future clinical practice.

Long-term health risk of offspring born from assisted reproductive technologies.

Since the world's first in vitro fertilization baby was born in 1978, there have been more than 8 million children conceived through assisted reproductive technologies (ART) worldwide, and a significant proportion of them have reached puberty or young adulthood. Many studies have found that ART increases the risk of adverse perinatal outcomes, including preterm birth, low birth weight, small size for gestational age, perinatal mortality, and congenital anomalies. However, data regarding the long-term outcomes of ART offspring are limited. According to the developmental origins of health and disease theory, adverse environments during early life stages may induce adaptive changes and subsequently result in an increased risk of diseases in later life. Increasing evidence also suggests that ART offspring are predisposed to an increased risk of non-communicable diseases, such as malignancies, asthma, obesity, metabolic syndrome, diabetes, cardiovascular diseases, and neurodevelopmental and psychiatric disorders. In this review, we summarize the risks for long-term health in ART offspring, discuss the underlying mechanisms, including underlying parental infertility, epigenetic alterations, non-physiological hormone levels, and placental dysfunction, and propose potential strategies to optimize the management of ART and health care of parents and children to eliminate the associated risks. Further ongoing follow-up and research are warranted to determine the effects of ART on the long-term health of ART offspring in later life.

Assessment of cognitive dysfunction and its influencing factors after acute ischemic stroke.

OBJECTIVE: In order to provide a more accurate and effective basis for clinical diagnosis and treatment, patients with cognitive dysfunction after acute ischemic stroke (AIS) were evaluated and their influencing factors were analyzed. METHODS: A rigorous and systematic logistic regression analysis was conducted to comprehensively investigate the various influencing factors that contribute to cognitive dysfunction. RESULTS: Among them, the sex granulocyte/lymphocyte ratio (NLR), low-density lipoprotein cholesterol (LDL-C) level, and C-reactive protein (CRP) were also higher than those in the control group (p < 0.05). The scores of memory, orientation, visual and spatial function, abstract thinking and language in the control group were higher than those in the experimental group (p < 0.05). The results of multivariate logistic regression analysis showed that history of diabetes mellitus, high NLR, high LDL-C, high CRP, smoking and temporal lobe infarction were risk factors for cognitive dysfunction after AIS, while elevated BMI and love of exercise were protective factors for cognitive dysfunction after AIS. CONCLUSION: Patients with cognitive dysfunction had the highest incidence of temporal lobe infarction, and they scored lower than the control group on memory, orientation, visual and spatial function, abstract thinking, and language function. Multivariate logistic regression analysis showed that a history of diabetes mellitus, high NLR, high LDL-C, high CRP, smoking, and temporal lobe infarction were independent risk factors for cognitive dysfunction after acute ischemic stroke, while elevated BMI and a love of exercise were protective factors for cognitive dysfunction after acute ischemic stroke.

Effectiveness of ChatGPT in clinical pharmacy and the role of artificial intelligence in medication therapy management.

BACKGROUND: The use of artificial intelligence (AI) to optimize medication therapy management (MTM) in identifying drug interactions may potentially improve MTM efficiency. ChatGPT, an AI language model, may be applied to identify medication interventions by integrating patient and drug databases. ChatGPT has been shown to be effective in other areas of clinical medicine, from diagnosis to patient management. However, ChatGPT's ability to manage MTM related activities is little known. OBJECTIVES: To evaluate the effectiveness of ChatGPT in MTM services in simple, complex, and very complex cases to understand AI contributions in MTM. METHODS: Two clinical pharmacists rated and validated the difficulty of patient cases from simple, complex, and very complex. ChatGPT's response to the cases was assessed based on 3 criteria: the ability to identify drug interactions, precision in recommending alternatives, and appropriateness in devising management plans. Two clinical pharmacists validated the accuracy of ChatGPT's responses and compared them to actual answers for each complexity level. RESULTS: ChatGPT 4.0 accurately solved 39 out of 39 (100 %) patient cases. ChatGPT successfully identified drug interactions, provided therapy recommendations and formulated general management plans, but it did not recommend specific dosages. Results suggest it can assist pharmacists in formulating MTM plans to improve overall efficiency. CONCLUSION: The application of ChatGPT in MTM has the potential to enhance patient safety and involvement, lower healthcare costs, and assist healthcare providers in medication management and identifying drug interactions. Future pharmacists can utilize AI models such as ChatGPT to improve patient care. The future of the pharmacy profession will depend on how the field responds to the changing need for patient care optimized by AI and automation.

Study of the Structure and Bioactivity of Polysaccharides from Different Parts of Stemona tuberosa Lour.

The polysaccharides from Stemona tuberosa Lour, a kind of plant used in Chinese herbal medicine, have various pharmacological activities, such as anti-inflammatory and antioxidant properties. However, the effects of the extraction methods and the activity of polysaccharides from different parts are still unknown. Therefore, this study aimed to evaluate the effects of different extraction methods on the yields, chemical compositions, and bioactivity of polysaccharides extracted from different parts of Stemona tuberosa Lour. Six polysaccharides were extracted from the leaves, roots, and stems of Stemona tuberosa Lour through the use of hot water (i.e., SPS-L1, SPS-R1, and SPS-S1) and an ultrasound-assisted method (i.e., SPS-L2, SPS-R2, and SPS-S2). The results showed that the physicochemical properties, structural properties, and biological activity of the polysaccharides varied with the extraction methods and parts. SPS-R1 and SPS-R2 had higher extraction yields and total sugar contents than those of the other SPSs (SPS-L1, SPS-L2, SPS-S1, and SPS-S2). SPS-L1 had favorable antioxidant activity and the ability to downregulate MUC5AC expression. An investigation of the anti-inflammatory properties showed that SPS-R1 and SPS-R2 had greater anti-inflammatory activities, while SPS-R2 demonstrated the strongest anti-inflammatory potential. The results of this study indicated that SPS-L1 and SPS-L2, which were extracted from non-medicinal parts, may serve as potent natural antioxidants, but further study is necessary to explore their potential applications in the treatment of diseases. The positive anti-inflammatory effects of SPS-R1 and SPS-R2 in the roots may be further exploited in drugs for the treatment of inflammation.

Effects of exposure to multiple metallic elements in the first trimester of pregnancy on the risk of preterm birth.

Exposure to certain heavy metals has been demonstrated to be associated with a higher risk of preterm birth (PTB). However, studies focused on the effects of other metal mixtures were limited. A nested case‒control study enrolling 94 PTB cases and 282 controls was conducted. Metallic elements were detected in maternal plasma collected in the first trimester using inductively coupled plasma‒mass spectrometry. The effect of maternal exposure on the risk of PTB was investigated using logistic regression, least absolute shrinkage and selection operator, restricted cubic spline (RCS), quantile g computation (QGC) and Bayesian kernel machine regression (BKMR). Vanadium (V) and arsenic (As) were positively associated with PTB risk in the logistic model, and V remains positively associated in the multi-exposure logistic model. QGC analysis determined V (69.42%) and nickel (Ni) (70.30%) as the maximum positive and negative contributors to the PTB risk, respectively. BKMR models further demonstrated a positive relationship between the exposure levels of the mixtures and PTB risk, and V was identified as the most important independent variable among the elements. RCS analysis showed an inverted U-shape effect of V and gestational age, and plasma V more than 2.18 µg/L was considered a risk factor for shortened gestation length. Exposure to metallic elements mixtures consisting of V, As, cobalt, Ni, chromium and manganese in the first trimester was associated with an increased risk of PTB, and V was considered the most important factor in the mixtures in promoting the incidence of PTB.

Bent π-Conjugation within a Macrocycle: Asymmetric Total Syntheses of Spirohexenolides A and B.

Macrocycles with bent π-conjugation motif are extremely rare in nature and synthetically daunting and anticancer haouamines and spirohexenolides were representative of such rare natural products with synthetically challenging bent π-conjugation within a macrocycle. While the total synthesis of haouamines has been elegantly achieved, spirohexenolides remains an unmet synthetic challenge due to the highly strained bent 1,3,5-triene conjugation within C15 macrocycle. Inspired by the chemical synthesis of cycloparaphenylenes (CPPs) and haouamines, herein we devise a synthetic strategy to overcome the highly strained bent 1,3,5-triene conjugation within the macrocycle and achieve the first, asymmetric total synthesis of spirohexenolides A (>20 mg) and B (>50 mg). Our synthesis features strategic design of ring-closing metathesis (RCM) macrocyclization followed by double dehydration to achieve the C15 macrocycle with the deformed nonplanar 1,3,5-triene conjugation. In addition, we have developed a new enantioselective construction of highly functionalized spirotetronate fragment (northeast moiety) through RCM and Ireland-Claisen rearrangement. Our in vitro bioassay studies reveal that both spirohexenolides are cytotoxic against a panel of human cancer cells with IC50 1.2-13.3 µM and spirohexenolide A is consistently more potent (up to 3 times) than spirohexenolide B, suggesting the importance of alcohol for their bioactivity and for medicinal chemistry development.

Effects of Particulate Matter on the Risk of Gestational Hypertensive Disorders and Their Progression.

Associations between particulate matter (PM) and gestational hypertensive disorders (GHDs) are well documented, but there is no evidence on the associations between PM and GHD progression, especially among those with assisted reproductive technology (ART) conceptions. To explore the effects of PM on the risk of GHDs and their progression among pregnant women with natural or ART conception, we enrolled 185,140 pregnant women during 2014-2020 in Shanghai and estimated the associations during different periods using multivariate logistic regression. During the 3 months of preconception, 10 µg/m3 increases in PM concentrations were associated with increased risks of gestational hypertension (GH) (PM2.5: aOR = 1.076, 95% CI: 1.034-1.120; PM10: aOR = 1.042, 95% CI: 1.006-1.079) and preeclampsia (PM2.5: aOR = 1.064, 95% CI: 1.008-1.122; PM10: aOR = 1.048, 95% CI: 1.006-1.092 ) among women with natural conception. Furthermore, for women with ART conceptions who suffered current GHD, 10 µg/m3 increases in PM concentrations in the third trimester elevated the risk of progression (PM2.5: aOR = 1.156, 95% CI: 1.022-1.306 ; PM10: aOR = 1.134, 95% CI: 1.013-1.270). In summary, women with natural conception should avoid preconceptional PM exposure to protect themselves from GH and preeclampsia. For women with ART conceptions suffering from GHD, it is necessary to avoid PM exposure in late pregnancy to prevent the disease from progressing.

Fetal weight estimation based on deep neural network: a retrospective observational study.

BACKGROUND: Improving the accuracy of estimated fetal weight (EFW) calculation can contribute to decision-making for obstetricians and decrease perinatal complications. This study aimed to develop a deep neural network (DNN) model for EFW based on obstetric electronic health records. METHODS: This study retrospectively analyzed the electronic health records of pregnant women with live births delivery at the obstetrics department of International Peace Maternity & Child Health Hospital between January 2016 and December 2018. The DNN model was evaluated using Hadlock's formula and multiple linear regression. RESULTS: A total of 34824 live births (23922 primiparas) from 49896 pregnant women were analyzed. The root-mean-square error of DNN model was 189.64 g (95% CI 187.95 g-191.16 g), and the mean absolute percentage error was 5.79% (95%CI: 5.70%-5.81%), significantly lower compared to Hadlock's formula (240.36 g and 6.46%, respectively). By combining with previously unreported factors, such as birth weight of prior pregnancies, a concise and effective DNN model was built based on only 10 parameters. Accuracy rate of a new model increased from 76.08% to 83.87%, with root-mean-square error of only 243.80 g. CONCLUSIONS: Proposed DNN model for EFW calculation is more accurate than previous approaches in this area and be adopted for better decision making related to fetal monitoring.

Tracking of menstrual cycles and prediction of the fertile window via measurements of basal body temperature and heart rate as well as machine-learning algorithms.

BACKGROUND: Fertility awareness and menses prediction are important for improving fecundability and health management. Previous studies have used physiological parameters, such as basal body temperature (BBT) and heart rate (HR), to predict the fertile window and menses. However, their accuracy is far from satisfactory. Additionally, few researchers have examined irregular menstruators. Thus, we aimed to develop fertile window and menstruation prediction algorithms for both regular and irregular menstruators. METHODS: This was a prospective observational cohort study conducted at the International Peace Maternity and Child Health Hospital in Shanghai, China. Participants were recruited from August 2020 to November 2020 and followed up for at least four menstrual cycles. Participants used an ear thermometer to assess BBT and wore the Huawei Band 5 to record HR. Ovarian ultrasound and serum hormone levels were used to determine the ovulation day. Menstruation was self-reported by women. We used linear mixed models to assess changes in physiological parameters and developed probability function estimation models to predict the fertile window and menses with machine learning. RESULTS: We included data from 305 and 77 qualified cycles with confirmed ovulations from 89 regular menstruators and 25 irregular menstruators, respectively. For regular menstruators, BBT and HR were significantly higher during fertile phase than follicular phase and peaked in the luteal phase (all P < 0.001). The physiological parameters of irregular menstruators followed a similar trend. Based on BBT and HR, we developed algorithms that predicted the fertile window with an accuracy of 87.46%, sensitivity of 69.30%, specificity of 92.00%, and AUC of 0.8993 and menses with an accuracy of 89.60%, sensitivity of 70.70%, and specificity of 94.30%, and AUC of 0.7849 among regular menstruators. For irregular menstruators, the accuracy, sensitivity, specificity and AUC were 72.51%, 21.00%, 82.90%, and 0.5808 respectively, for fertile window prediction and 75.90%, 36.30%, 84.40%, and 0.6759 for menses prediction. CONCLUSIONS: By combining BBT and HR recorded by the Huawei Band 5, our algorithms achieved relatively ideal performance for predicting the fertile window and menses among regular menstruators. For irregular menstruators, the algorithms showed potential feasibility but still need further investigation. TRIAL REGISTRATION: ChiCTR2000036556. Registered 24 August 2020.

Association between paternal age and subtypes of preterm birth: a retrospective study.

RESEARCH QUESTION: Is advanced paternal age (APA) associated with preterm birth overall and with the subtypes of preterm birth? DESIGN: A total of 66,167 pregnancies were included. Linear regression and logistic regression models were used to analyse the association between paternal age and subtypes of preterm birth. RESULTS: APA was associated with a higher risk of preterm birth (35-44 years: odds ratio [OR] 1.16 [1.04-1.28], P = 0.006; >44 years: OR 1.40 [1.10-1.78], P = 0.007) and very early preterm birth (VPTB; <34 weeks) (35-44 years: OR 1.46 [1.17-1.81], P = 0.002; >44 years: OR 1.65 [1.01-2.69], P = 0.045). The increased risk of preterm birth was mostly associated with preterm birth with premature rupture of membranes (PROM-PTB) (35-44 years: OR 1.23 [1.03-1.48], P = 0.021) and medically induced preterm birth (MI-PTB) (>44 years: OR 1.55 [1.12-2.15], P = 0.008). For women who carried a male fetus, having the father in the 35- to 44-year-old group carried a 1.29-fold risk of PROM-PTB (OR 1.29 [1.02-1.63], P = 0.031) and a 1.26-fold risk of MI-PTB (OR 1.26 [1.04-1.52], P = 0.017). There was no evidence of a higher risk of PROM-PTB among women carrying a female fetus, but there was a 1.67-fold higher risk of MI-PTB for the 45-or-older paternal age group (OR 1.67 [1.04-2.67], P = 0.035). CONCLUSIONS: These results suggest that APA is associated with a higher risk of preterm birth and VPTB, mainly related to PROM-PTB and MI-PTB. The study also indicates a fetal sex-specific association between APA and a higher risk of PROM-PTB for male fetuses.

Interactive effects of ambient air pollution and sunshine duration on the risk of intrahepatic cholestasis of pregnancy.

INTRODUCTION: While the associations among ambient pollutants and various pregnancy complications are well documented, the effect of ambient pollutants on intrahepatic cholestasis of pregnancy (ICP) has not been examined. This study aimed to explore the effects of ambient pollutants and sunshine duration on ICP. METHODS: The study enrolled 169,971 pregnant women who delivered between 2015 and 2020 in two hospitals. The associations between ICP and exposure to ambient pollutants and sunshine duration, averaged throughout different periods (including the 3 months before conception, 1st trimester and 2nd trimester), were estimated using a generalized linear model. The interaction effects of ambient pollutants and sunshine duration on ICP were estimated. RESULTS: The fitted curves for ICP incidence were similar to the temporal trends of PM2.5, PM10, SO2, CO and NO2 but not that of O3. The risk of ICP was significantly elevated following a 10-µg/m3 increase in PM2.5 (aOR [adjusted odds ratio] = 1.057, 95% CI [confidence interval]: 1.017-1.099) and PM10 (aOR = 1.043, 95% CI: 1.013-1.074) and a 1-h decrease in sunshine duration (aOR = 1.039, 95% CI: 1.011-1.068) during the 3 months before conception. In the second trimester, a 1-µg/m3 increase in the concentration of SO2 was associated with an increased risk of ICP (aOR = 1.011, 95% CI: 1.001-1.021). Increased concentrations of PM2.5 and PM10 had interactive effects with reduced sunshine duration during the 3 months before conception on increasing the risk of ICP. CONCLUSIONS: Exposure to PM2.5 and PM10 during the 3 months before conception and exposure to SO2 in the second trimester were associated with an increased ICP risk. Reduced sunshine duration had an interactive effect with increased concentrations of PM2.5 and PM10 during the 3 months before conception on the occurrence of ICP.

Association between prenatal exposure to ambient air pollutants and postpartum depressive symptoms: A multi-city cohort study.

BACKGROUND: Women are vulnerable to depression during postpartum period. While several studies have shown associations between ambient air pollution exposure and depression in general population, there was few studies focused on the effect of various air pollutants on postpartum depression (PPD). OBJECTIVE: This study is designed to explore the association between prenatal exposure to air pollutants and PPD, and to reveal the potential vulnerable exposure time point. METHODS: The study enrolled 10,209 pregnant women who delivered between October 2019 and February 2021 in 5 participating hospitals from 3 cities in China. Edinburgh Postnatal Depression Scale (EPDS) was administered at 6 weeks postpartum to identify PPD symptoms. Associations between PPD symptoms and exposure levels in PM2.5, PM10, SO2, CO, NO2, and O3 averaged over the whole pregnancy and each trimester were estimated using logistic regression models after adjusting for potential confounding factors. Distributed lag models (DLMs) were used to determine the relevant associations in each gestational week. RESULTS: The risk for developing PPD symptoms was significant following a 10 µg/m3 increase in PM10 (aOR = 1.47, 95%CI:1.36-1.59), NO2 (aOR = 1.63, 95%CI:1.44-1.85), and 0.1 mg/m3 increase in CO (aOR = 2.31, 95%CI: 1.99-2.69) during the whole pregnancy. Similar results were also found in exposure during each trimester of pregnancy. Besides, SO2 exposure during the second trimester was a major risk factor for developing PPD symptoms (aOR = 1.10, 95%CI:1.03-1.18). Consistent effects were also observed in DLMs, except for PM2.5 and O3, which showed no significant sensitive windows throughout pregnancy period. CONCLUSION: Exposure to PM10, CO, NO2, and SO2 in pregnancy is associated with increased risks of developing depression at 6 weeks postpartum. Our findings reveal the importance of air pollution control for preventing maternal mental health disorders among the public.

Antepartum sleep quality, mental status, and postpartum depressive symptoms: a mediation analysis.

BACKGROUND: Poor sleep quality and maternal mood disturbances are common during pregnancy and may play pivotal roles in the development of postpartum depression. We aim to examine the trajectories of sleep quality and mental health in women from early pregnancy to delivery and explore the mediating effects of sleep quality and mental status on the link between antepartum depressive symptoms and postpartum depressive symptoms. METHODS: In an ongoing prospective birth cohort, 1301 women completed questionnaires in the first, second and third trimesters and at 6 weeks postpartum. In each trimester, sleep quality was measured utilizing the Pittsburgh Sleep Quality Index (PSQI), and mental health was assessed with the Center for Epidemiologic Studies Depression Scale (CES-D), the Self-Rating Anxiety Scale (SAS) and the Perceived Stress Scale (PSS). Postpartum depressive symptoms were evaluated by the Edinburgh Postnatal Depression Scale (EPDS). The bootstrap method was used to test the mediation effect. RESULTS: The PSQI, CES-D, and SAS scores presented U-shaped curves across the antenatal period while the PSS score followed a descending trend. Antenatal sleep quality, depressive symptoms, anxiety symptoms and perceived stress all predicted depressive symptoms at 6 weeks postpartum. The influence of antepartum depressive symptoms on postpartum depressive symptoms was mediated by antepartum sleep quality and anxiety symptoms, which accounted for 32.14%, 39.25% and 31.25% in the first, second and third trimesters (P = 0.002, P = 0.001, P = 0.001, respectively). CONCLUSIONS: Poor sleep quality and anxiety symptoms in pregnancy mediated the relationship between antepartum depressive symptoms and postpartum depressive symptoms. Interventions aimed at detecting and managing sleep quality and elevated anxiety among depressed women in pregnancy warrant further investigation as preventative strategies for postpartum depression.

Effects of vaginal microecology and immunity on the pregnancy outcome of cervical cerclage.

OBJECTIVE: To investigate the effects of vaginal microecology and immune status on the pregnancy outcome of cervical cerclage. METHODS: The clinical data of 125 patients with cervical incompetence who underwent transvaginal cervical cerclage in our hospital from January 2018 to January 2021 were collected, based on which the associations of vaginal microecology and related immune cytokines (IL-1ß, IL-6, IL-8 and TNF-α) with the cervical cerclage outcome were explored. RESULTS: All of the 125 patients had singleton pregnancies, who were aged 20-43 years, with a mean of (32.34 ± 5.17) years. The surgery was successful in 104 patients (full-term delivery or survival of premature infants), while unsuccessful in 21 patients (late miscarriage or death of premature infants), revealing a success rate of 83.20%. There were 70 full-term deliveries, 34 premature deliveries (28 survived while 6 died), and 15 late miscarriages. Univariate analysis revealed statistically significant differences in the timing of surgery, gestational age of cerclage, preoperative cervical canal length, genital tract infections and preoperative invasive procedures between the successful and unsuccessful groups (P < 0.05). Insignificant differences were found in the pre-pregnancy body mass index (BMI) (P > 0.05). According to the multivariate analysis results, cerclage timing and genital tract infections were independent risk factors for postoperative pregnancy failure (P < 0.05). The pathogen detection rates in the two groups of pregnant women were analyzed, finding significantly higher incidence of bacterial vaginosis (BV) in the unsuccessful group than in the successful group (P < 0.05). Inter-group comparison revealed that the positive rates for vaginal microenvironmental factors (LE, NAG, SNA, H2O2 and pH) were all significantly higher in the unsuccessful group than in the successful group (P < 0.05). Besides, the immune cytokine levels in the cervicovaginal secretions were also all significantly higher in the unsuccessful group than in the successful group (P < 0.05). CONCLUSION: The pregnancy outcome of patients undergoing cervical cerclage is associated with the imbalance of vaginal microecology and the levels of IL-1ß, IL-6, IL-8 and TNF-α in cervicovaginal secretions.

Value of 3D ultrasound flow imaging combined with serum AFP, ß-hCG, sFlt-1 and CK in the diagnosis of placenta accreta.

PURPOSE: To analyze the diagnostic value of placenta three-dimensional (3D) energy blood flow parameters combined with maternal serum AFP, ß-hCG, sFlt-1 and CK levels for PA. METHODS: 30 pregnant women with PA and 30 pregnant women with normal placenta were randomly selected in the Affiliated Maternal and Child Health Hospital of Nantong University from January 2021 to December 2021. Thereafter, the 3D energy ultrasound was applied to detect the placenta VI, FI and VFI. Moreover, the diagnostic value of different parameters combined with serum AFP, ß-hCG, sFlt-1 and CK levels for PA was analyzed. RESULTS: Multivariate analysis results indicated that, gravidity > 2 and with/without placenta previa were the independent risk factors for PA (P < 0.05). In PA group, the AFP, ß-hCG, CK, placenta VI, FI and VFI values were higher than those in non-PA group, while sFlt-1 was apparently lower than that in non-PA group. With the increase in PA degree, the serum AFP, ß-hCG and CK levels increased. Meanwhile, serum sFlt-1 level was negatively correlated with PA degree. Serum AFP, ß-hCG, sFlt-1, CK and placenta VFI showed prediction potency for PA, and their combined detection attained the optimal diagnostic value for predicting PA. ROC curve analysis suggested that, serum AFP, ß-hCG, sFlt-1, CK and 3D ultrasound VFI value had the greatest AUC values in predicting PA, which might provide reference for the clinical diagnosis and disease evaluation of PA. Conclusion Serum AFP, ß-hCG, sFlt-1, CK and placental VFI can increase the consistency in the diagnosis of PA. Serum markers combined with 3D ultrasound blood flow imaging can improve the sensitivity and specificity of prenatal diagnosis of PA, which provides an important reference for clinical diagnosis and treatment.

Framework to enable pharmacist access to health care data using Blockchain technology and artificial intelligence.

BACKGROUND: Decentralization and authentication are embedded in blockchain technology, which utilizes artificial intelligence (AI) to ensure seamless sharing of data among different health care providers while safeguarding data privacy. Although community pharmacists are highly accessible to patients and possess robust clinical knowledge, they are limited in the clinical services they can provide owing to their lack of access to patient health records. We proposed a blockchain- and AI-based conceptual framework by performing a scoping review of successful blockchain integration in health systems. OBJECTIVE: To formulate a conceptual framework based on a scoping review to improve access to health care data in the community pharmacy setting through the adoption of blockchain technology and AI. METHODS: We performed a scoping review of literature based on Preferred Reporting Items for Systematic reviews and Meta-Analyses review criteria to identify the specific areas where blockchain can be implemented in health systems. We utilized the Pharmacists' Patient Care Process (PPCP) to identify 2 critical areas for blockchain integration that can support community pharmacists to access patient electronic health records and implement patient-specific information in clinical decision-making. RESULTS: We included 7 articles out of 70 articles in our final review. The 2 areas in the PPCP identified for the use of blockchain on the basis of the literature review were "Assess" and "Implement." Our proposed model involves pharmacists using AI and blockchain technology to comprehensively assess any concerns with the prescribed medication through access to laboratory results for patients and then implement a plan based on a comprehensive assessment of the patient's health record. CONCLUSIONS: Utilizing blockchain to securely share health data with community pharmacies has the potential to improve patient outcomes, optimize medication safety, and amplify pharmacists' roles in patient care. Future research should focus on implementing the model in the real-world settings.

ß-Caryophyllene Acts as a Ferroptosis Inhibitor to Ameliorate Experimental Colitis.

Macrophage infiltration is one of the main pathological features of ulcerative colitis (UC) and ferroptosis is a type of nonapoptotic cell death, connecting oxidative stress and inflammation. However, whether ferroptosis occurs in the colon macrophages of UC mice and whether targeting macrophage ferroptosis is an effective approach for UC treatment remain unclear. The present study revealed that macrophage lipid peroxidation was observed in the colon of UC mice. Subsequently, we screened several main components of essential oil from Artemisia argyi and found that ß-caryophyllene (BCP) had a good inhibitory effect on macrophage lipid peroxidation. Additionally, ferroptotic macrophages were found to increase the mRNA expression of tumor necrosis factor alpha (Tnf-α) and prostaglandin-endoperoxide synthase 2 (Ptgs2), while BCP can reverse the effects of inflammation activated by ferroptosis. Further molecular mechanism studies revealed that BCP activated the type 2 cannabinoid receptor (CB2R) to inhibit macrophage ferroptosis and its induced inflammatory response both in vivo and in vitro. Taken together, BCP potentially ameliorated experimental colitis inflammation by inhibiting macrophage ferroptosis. These results revealed that macrophage ferroptosis is a potential therapeutic target for UC and identified a novel mechanism of BCP in ameliorating experimental colitis.