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Backgroud Breast milk is the optimal food for infant growth and development. The purpose of this study was to evaluate the association between breast milk macronutrient composition with dietary pattern among lactating women. Methods A total of 220 lactating women from 2011 to 2012 in Changsha, a city of south-central China, was recruited using a multi-stage sampling method. Breast milk was collected, and the protein, fat, lactose, total dry matter, and energy contents of breast milk were measured. A 24 h recall method on three consecutive days was used to collect the dietary information of lactating women and an exploratory factor analysis was performed was to identify dietary patterns. The association between the concentration of a breast milk component and dietary pattern was assessed using a multivariable linear regression model. Results Three major dietary patterns were classified. Lactating women with dietary pattern 1 mainly ate fresh vegetables and fresh legumes. Those with dietary pattern 2 mainly ate red meat, cereals and eggs, and those with dietary pattern 3 mainly ate fungi and algae, dries legumes and soy milk. Pattern 2 was positively associated with the concentration of protein (B = 0.07, 95% CI 0.00, 0.15), total dry matter (B = 0.20, 95% CI 0.02, 0.38) and energy (B = 1.66, 95% CI 0.03, 3.30) in breast milk. Morever, lactation period was negatively associated with the protein and total dry matter concentrations and positively associated with lactose. Conclusions The results show the lactation period was an important factor affecting milk composition and a dietary pattern with high intake of red meat, cereals, and eggs was associated with higher protein, total dry matter, and energy contents in breast milk. These findings show that the dietary patterns of lactating women can affect breast milk macronutrient composition and provide a foundation for improving child health.

Although transcranial direct current stimulation (tDCS) has been used in the treatment of epilepsy for many years, further research is needed on the efficacy and safety of tDCS treatment. This systematic review and meta-analysis aimed to explore the effectiveness of tDCS on seizure frequency (SF), epileptiform discharges, depression, anxiety, and cognitive function in epilepsy. We searched the Cochrane Library, PubMed, Embase, Scopus, and Web of Science databases from inception to 9 September 2024. The primary outcomes included SF. The secondary outcomes included epileptiform discharges, depression, anxiety, cognitive function, and adverse events. The meta-analysis was conducted using Review Manager 5.4 software. 12 trials were included, 356 participants (219 in the tDCS group and 137 in the sham group). Among the included studies, three were of high risk, two were of some concern, and seven were of low risk. For the primary outcome metrics, tDCS can reduce the frequency of epileptic seizures (SMD = − 0.63, 95 % CI = [-0.90, − 0.36], P < 0.00001). For secondary outcome measures, there are no statistical differences between the tDCS group and the sham group in epileptiform discharges (SMD = − 0.27, 95 % CI = [-0.71, 0.16], P = 0.22) and adverse events (MD = 1.30, 95 % CI = [0.49, 3.45], P = 0.60). The outcomes of tDCS treatment for depression and anxiety were inconsistent. tDCS did not enhance or impair cognitive function. tDCS can reduce SF but has no effect on epileptiform discharges in patients with epilepsy. The current evidence is limited to support tDCS treatment for depression, anxiety, and cognitive function in epilepsy patients. Future studies should be standardized and personalized, ensure higher methodological rigor, and probe long-term effects to prove the findings further. •tDCS can reduce SF, but has no effect on epileptiform discharges.•The current evidence is limited to support tDCS treatment for depression, anxiety, and cognitive function in epilepsy patients.•Standardizing tDCS techniques and improving study design are significant for future research reliability.

Background Minerals have crucial biological functions in metabolism and are primarily obtained through diet. As a result, various dietary patterns can impact blood mineral levels. The aim of this study was to investigate the correlation between dietary patterns and the concentration of calcium, magnesium, iron, zinc, and copper in the bloodstream. Methods Three hundred eighty healthy children (53.7% male) were recruited in a region of Hunan Province in September 2019. We gathered basic information and measured physical proportions, along with completing a food frequency questionnaire (FFQ). Using principal component analysis (PCA), we determined dietary patterns. To analyze mineral levels in the blood, we used flame atomic absorption spectrometry (FAAS). We utilized linear regression models to investigate if certain dietary patterns are related to mineral concentration. Results Three dietary patterns were identified: ‘Vegetables/Nuts,’ ‘Snacks/Beverages,’ and ‘Cereal/Beans.’ Children from high-income families (annual average income > 50,000 yuan) prefer the ‘Vegetables/Nuts’ dietary pattern ( P  = 0.004). In comparison, those from low-income families (annual average income < 20,000 yuan) prefer the ‘Snacks/Beverages’ dietary pattern ( P  = 0.03). Following adjustment for age, gender, guardian’s identity, education level, and annual household income. We found that an increase in the ‘Vegetables/Nuts’ pattern score (β = 0.153, CI: 0.053 ~ 0.253; P  = 0.003) and ‘Snacks/Beverages’ pattern score (β = 0.103, CI: 0.002 ~ 0.204; P  = 0.033) were significantly associated blood copper concentration. Conclusions Household income was found to be associated with dietary behavior. Furthermore, higher blood copper concentration was significantly correlated with the ‘Vegetables/Nuts’ dietary pattern and ‘Snacks/Beverages’ dietary pattern, but the correlation is extremely low.

Arch structure is a crucial interface between the human body and the ground during landing tasks, but the biomechanical effects of arch support stiffness remain insufficiently explored. This study examines the effects of arch supports with different stiffnesses on lower-limb biomechanics during landing. Twelve male participants (six normal arches, six flat feet) performed a single-leg drop landing from a 45 cm height under four arch support conditions: no arch support pad (NAP), soft-stiffness arch support pad (SAP), medium-stiffness arch support pad (MAP), and high-stiffness arch support pad (HAP). Dominant lower-limb joint angles and moments in the sagittal plane and vertical ground reaction force (vGRF)-related parameters—time to peak vGRF, peak vGRF, and max loading rate—were recorded using a motion capture system and force plate. Data were analyzed using one-way repeated measures analysis of variance (ANOVA). Arch pad stiffness significantly affected ankle and knee kinematics. The NAP condition exhibited significantly higher ankle plantarflexion at initial contact (p ≤ 0.01), as well as larger range of motion (ROM) of the knee (p = 0.03) and hip (p < 0.01), compared to the use of a SAP or MAP. The use of a HAP resulted in a significantly lower peak ankle dorsiflexion moment and larger peak knee flexion angle than the other conditions (p ≤ 0.04). The peak knee extension moment was the highest when using a NAP, and was significantly higher than that shown with the use of a MAP or HAP (p ≤ 0.02). No significant differences were observed in hip joint moments or vGRF-related parameters across conditions (p ≥ 0.52). These results indicate that hard-stiffness arch support pads modulate lower-limb mechanics during landing, potentially enhancing shock absorption and reducing knee loading.

This study investigates the effect of GnRHa pretreatment on pregnancy outcomes in artificial endometrial preparation for frozen–thawed embryo transfer (AC-FET) cycles. A systematic review of English language studies published before 1 September 2022, was conducted, excluding conference papers and preprints. Forty-one studies involving 43,021 participants were analyzed using meta-analysis, with a sensitivity analysis ensuring result robustness. The study found that GnRHa pretreatment generally improved the clinical pregnancy rate (CPR), implantation rate (IR), and live birth rate (LBR). However, discrepancies existed between randomized controlled trials (RCTs) and observational studies; RCTs showed no significant differences in outcomes for GnRHa-treated cycles. Depot GnRHa protocols outperformed daily regimens in LBR. Extended GnRHa pretreatment (two to five cycles) significantly improved CPR and IR compared to shorter treatment. Women with polycystic ovary syndrome (PCOS) saw substantial benefits from GnRHa pretreatment, including improved CPR and LBR and reduced miscarriage rates. In contrast, no significant benefits were observed in women with regular menstruation. More rigorous research is needed to solidify these findings.

Background Evidence-based practice (EBP) education or training are considered fundamental to building and strengthening an EBP culture, as well as to encouraging evidence-based academic and clinical practice in the nursing community. However, few valid and reliable instruments are available for the assessment of EBP teaching and learning in clinical nurses in China. Translation, reliability, and validity testing of the English Evidence-Based Practice Profile Questionnaire (EBP 2 Q), which has strong psychometric properties, may encourage evaluation and promote the implementation of EBP in Mainland China. Methods Based on established guidelines for the development of questionnaires, the English EBP 2 Q was translated and cross-culturally adapted. The Chinese version of the EBP 2 Q (EBP 2 Q-C) was validated using a sample of 543 nurses. Structural validity was evaluated through exploratory factor analysis and confirmatory factor analysis, and the questionnaire was tested for convergent and criterion validity. The internal consistency and test-retest reliability were also evaluated. Results The content validity index demonstrated good content validity (≥0.98). An eight-factor structure was obtained in the exploratory factor analysis, and verified by a three-order factor model from the confirmatory factor analysis ( χ 2 /df  = 2.001; RMSEA = 0.065; SRMR = 0.077; and CFI = 0.884). The Spearman’s rank correlation analysis of the EBP 2 Q-C with the Evidence-Based Practice Questionnaire showed moderate correlations for Practice (0.58) and Confidence (0.68) and a low correlation for Sympathy (0.32). Criterion validity was demonstrated by significant differences in terms of nurses’ highest education, present position, EBP training, involvement in research programs, and level of understanding of English. Both the overall Cronbach’s α and the Cronbach’s α for the domains exceeded 0.70. The intraclass correlation coefficients for the domains ranged between 0.75 and 0.96, indicating satisfactory repeatability. Conclusions Except for the convergent validity of the Sympathy domain, the EBP 2 Q-C provided evidence of validity and reliability. Therefore, it can be applied in EBP education or training assessment in Mainland China.

Objective Fat, as one of the macronutrients in breast milk (BM) plays an important role in infant growth and development. This study aimed to explore the impact of maternal body mass index (BMI) trajectories in different pregnancy periods on the fat composition of BM and clarify the possible metabolic mechanisms. Methods A retrospective longitudinal study was conducted in central south China and a total of 195 lactating women was recruited. Prepregnancy and delivery maternal weights were obtained from the Medical Birth Registry, while postpartum weight and height were measured during the interview. BM macronutrients and fatty acid (FA) profiles were analyzed. Maternal BMI trajectories reflected the combined weight status in different pregnancy periods was identified by Latent Class Growth Model. The associations of BM fat compositions with maternal weight status were used by multiple linear regression analysis. Results Two maternal BMI trajectories characterized by high and low maternal BMI were found from prepregnancy to postpartum. The maternal BMI trajectories was positively associated with BM fat (β = 0.233, 95%CI: 0.092, 0.374), energy (β = 0.208, 95%CI:0.065, 0.351), and saturated fatty acids (SFAs) (0.160, 95%CI: 0.014, 0.306). Moreover, these fat compositions were also positively associated with prepregnancy overweight and obesity. The subgroup analysis by lactaing period found that in both subgroups, BM fat concentration was positively associated with maternal BMI trajectory and prepregnancy overweight and obesity. In addition, the results also revealed that in the lactation period of 90–180 days, maternal prepregnancy overweight and obesity were positively associated with BM concentrations of SFA, n‑6 PUFA, and total FAs. BM fat and energy were positively correlated with BM main FAs C14:0, C16:0, and C18:1n-9, which were associated with diet intake and endogenous synthesis of SFA. Conclusion High maternal BMI trajectory from prepregnancy to postpartum impacted BM fat and energy. The impact mainly depended on the maternal prepregnancy weight status. The potential metabolic mechanisms of maternal weight status on BM fat were associated with SFA endogenous synthesis.

PurposeDiabetic peripheral neuropathy (DPN), a common microvascular complication of diabetes, is linked to glycaemic derangements. Glycaemic variability, as a pattern of glycaemic derangements, is a key risk factor for diabetic complications. We investigated the association of glycaemic variability with DPN in a large-scale sample of type 2 diabetic patients.MethodsIn this cross-sectional study, we enrolled 982 type 2 diabetic patients who were screened for DPN and monitored by a continuous glucose monitoring (CGM) system between February 2011 and January 2017. Multiple glycaemic variability parameters, including the mean amplitude of glycaemic excursions (MAGE), mean of daily differences (MODD), standard deviation of glucose (SD), and 24-h mean glucose (24-h MG), were calculated from glucose profiles obtained from CGM. Other possible risks for DPN were also examined.ResultsOf the recruited type 2 diabetic patients, 20.1% (n = 197) presented with DPN, and these patients also had a higher MAGE, MODD, SD, and 24-h MG than patients without DPN (p < 0.001). Using univariate and multiple logistic regression analyses, MAGE and conventional risks including diabetic duration, HOMA-IR, and hemoglobin A1c (HbA1c) were found to be independent contributors to DPN, and the corresponding odds ratios (95% confidence interval) were 4.57 (3.48–6.01), 1.10 (1.03–1.17), 1.24 (1.09–1.41), and 1.33 (1.15–1.53), respectively. Receiver operating characteristic analysis indicated that the optimal MAGE cutoff value for predicting DPN was 4.60 mmol/L; the corresponding sensitivity was 64.47%, and the specificity was 75.54%.ConclusionsIn addition to conventional risks including diabetic duration, HOMA-IR and HbA1c, increased glycaemic variability assessed by MAGE is a significant independent contributor to DPN in type 2 diabetic patients.

The causes of implantation failure remain a black box in reproductive medicine. The exact mechanism behind the regulation of endometrial receptivity is still unknown. Epigenetic modifications influence gene expression patterns and may alter the receptivity of human endometrium. Cervical secretions contain endometrial genetic material, which can be used as an indicator of the endometrial condition. This study evaluates the association between the cervical secretion gene methylation profile and pregnancy outcome in a frozen-thawed embryonic transfer (FET) cycle. Cervical secretions were collected from women who entered the FET cycle with a blastocyst transfer (36 pregnant and 36 non-pregnant women). The DNA methylation profiles of six candidate genes selected from the literature review were measured by quantitative methylation-specific PCR (qMSP). Bioinformatic analysis of six selected candidate genes showed significant differences in DNA methylation between receptive and pre-receptive endometrium. All candidate genes showed different degrees of correlation with the pregnancy outcomes in the logistic regression model. A machine learning approach showed that the combination of candidate genes’ DNA methylation profiles could differentiate pregnant from non-pregnant samples with an accuracy as high as 86.67% and an AUC of 0.81. This study demonstrated the association between cervical secretion methylation profiles and pregnancy outcomes in an FET cycle and provides a basis for potential clinical application as a non-invasive method for implantation prediction.

The worldwide exclusive breastfeeding rate is suboptimal and this study aims to evaluate effects on infant immune development of formula feeding. A prospective study including 221 infants fed with breast milk or formula was conducted. At 3-month and 9-month, the concentrations of total immunoglobulin (Ig)G, IgM, IgA, IgG1, IgG2, interleukin (IL)-4, interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α) were measured by using enzyme-linked immunosorbent assay (ELISA). Natural killer (NK) cell activity and lymphocyte transformation testing were conducted. Furthermore, the occurrence of infantile diarrhea, respiratory infections and allergic diseases were questioned. The levels of total IgG (Z=-3.21, p=0.001), IgG1 (Z=-2.12, p=0.034), IFN-γ (t=-2.09, p=0.039) and NK cell activity (t=-2.14, p=0.034) were significant higher in formula-fed infants compared to breast-fed after 3 months. At 9-month, the levels of total IgG (Z=-4.34, p<0.001), IgA (Z=-2.05, p=0.041) and TNF-α (t=-2.10, p=0.037) of formula-fed infants were higher, but the lymphocyte stimulation index (t=2.76, p=0.007) was lower than breast-fed infants. While, no significant differences were found in the incidences of diarrhea and respiratory tract infection (p>0.05). This investigation suggested that formula- and breast-feeding have different contributions to infant immune development, but the formula feeding would not cause significantly increase of diarrhea and respiratory infections.