Association of food folate with asthma in US children and adolescents: a cross-sectional study.

BACKGROUND: Asthma is a chronic inflammatory disease. Currently, contradictory findings exist regarding the association between food folate and asthma. Therefore, we hypothesize a positive correlation between food folate and asthma. PURPOSE: To investigate the possible relationship between food folate intake and the development of asthma in children and adolescents in the United States. METHODS: Data from the U.S. National Health and Nutrition Examination Survey (NHANES) from 2009 to 2018 were analyzed cross-sectionally by covariate adjustment using multivariate logistic regression, restricted triple spline curves, threshold effects, and stratified analyses. RESULTS: There were 8,821 participants, of whom 1,697 (19.2%) self-reported having received a diagnosis of asthma from a physician or other health professional. After accounting for potential confounders, the adjusted odds ratios (ORs) for asthma in the second (T2, 111-178 µg/day) and third (T3, >178 µg/day) groups were 1.15 (1-1.33) and 1.23 (1.04-1.46), respectively, compared with the group with the lowest food folate intake (T1, <111 µg/day). In addition, the association between food folate intake and asthma showed an inverse L-shaped curve (non-linear relationship, p = 0.003), and stratified analysis further validated the robustness of the results. The OR of asthma in subjects with food folate intake less than 263.9 µg/day was 1.002 (1.001-1.004). CONCLUSION: In children and adolescents in the United States, there is a non-linear association (inverted "L" shape) between food folate intake and asthma, with an inflection point at 263.9 micrograms per day.

The Hidden Agony of the Pancreas: A Comprehensive Case Study of Paraduodenal Pancreatitis.

Paraduodenal pancreatitis (PP), also known as groove pancreatitis (GP), is a rare and distinct variant of chronic pancreatitis and presents significant diagnostic and therapeutic challenges. This comprehensive case study explores a 54-year-old male patient's journey, highlighting the intricate relationship between clinical presentation, diagnostic modalities, and management strategies. Despite a history of smoking and alcohol consumption, the diagnosis of PP was primarily reliant on advanced imaging techniques, including computed tomography and magnetic resonance imaging, which revealed characteristic findings of GP. The case underscores the importance of a high index of suspicion and a step-up approach to management, starting with conservative treatment and progressing to surgical intervention as necessary. This study contributes to the growing body of knowledge on PP, emphasizing the need for awareness and understanding of this rare condition to improve patient outcomes.

Tea, coffee, and caffeine intake and risk of dementia and Alzheimer's disease: a systematic review and meta-analysis of cohort studies.

Background: Limited and conflicting evidence exists for the associations between tea, coffee, and caffeine intake and risk of dementia and Alzheimer's disease (AD). This meta-analysis aimed to elucidate these associations and quantify potential dose-response relationships. Methods: PubMed, EMBASE, and Web of Science were searched up to 11 June 2024 for cohort studies. Random effects models were used to calculate pooled relative risks (RRs) and 95% confidence intervals (CIs), with the dose-response relationship assessed using restricted cubic splines. The Grading of Recommendations Assessment Development and Evaluation (GRADE) tool was used to assess the risk of bias. Results: Our analysis encompassed 38 cohorts, totalling 751 824 participants and 13 017 dementia and 17 341 AD cases. For dementia, compared with the lowest category, the pooled RRs (95% CI) in the highest category of tea, coffee, and caffeine were 0.84 (0.74-0.96, n = 6), 0.95 (0.87-1.02, n = 9), and 0.94 (0.70-1.25, n = 5), with all rated as low certainty in GRADE. For AD, the pooled RRs (95% CI) in the highest category of tea, coffee, and caffeine compared to the lowest category were 0.93 (0.87-1.00, n = 6), 1.01 (0.90-1.12, n = 10), and 1.34 (1.04-1.74, n = 2), with certainty ratings of low, low, and very low, respectively. Dose-response analysis indicated a non-linear relationship between coffee intake (Poverall = 0.04 and Pnonlinear = 0.01) and dementia risk, showing the protective association of risk of dementia with 1 to 3 cups per day of coffee intake. There is a linear association between tea intake and risk of dementia, with a significantly decreased risk of dementia for each 1 cup per day increase in tea consumption (0.96, 95% CI 0.94-0.99, Poverall = 0.01 and Pnonlinear = 0.68). Conclusion: Increased tea consumption was associated with a decreased risk of dementia and AD, and a non-linear relationship was found between coffee and dementia, supporting public health recommendations for dementia prevention.

PRECEDE-PROCEED Model Nursing Intervention in Health Education for Parents of Obese Children.

Objective: To study the intervention effects of the health education and health promotion (PRECEDE-PROCEED) model on the health behaviors and quality of life of obese children and their parents. Methods: 524 patients who attended our pediatric obesity clinic from January to December 2021 were selected and divided into two groups: the control group (n = 262) and the test group (n = 262). The control group was guided by conventional weight reduction instruction, while the test group implemented the PRECEDE-PROCEED model. Based on this model, interventions were developed following the 9 links of the model, with tendency factors, contributing factors, and reinforcing factors as the core and 6 aspects of health behaviors were focused upon, and were followed up for 12 months. A home-made questionnaire scale was used to assess the subjects at their initial visit and one year after the intervention. Results: After the intervention, the awareness rate of obesity-related knowledge, support rate of attitude toward improving childhood obesity, awareness rate of disease harm caused by obesity, and formation rate of controlling childhood obesity behavior had significantly improved among the parents of the test group compared to the control group, with significant differences between the two groups (P < .05). Conclusion: The PRECEDE-PROCEED model can transform the way parents of obese children apply health education at home, improving health behaviors and quality of life.

Lycopene inhibits pyroptosis of endothelial progenitor cells induced by ox-LDL through the AMPK/mTOR/NLRP3 pathway.

The malfunction of endothelial progenitor cells (EPCs) due to ox-LDL is a risk contributor for arteriosclerotic disease. Meanwhile, lycopene possesses anti-inflammatory and antioxidative qualities. This investigation aimed to determine if lycopene can protect EPCs from ox-LDL-induced damage and to elucidate the underlying mechanism. The effects of lycopene on the survival, migration, and tube-forming capacity of EPCs were determined via in vitro assays. Expression of proteins related to pyroptosis and cellular proteins related to AMPK/mTOR/NLRP3 signaling was determined by western blot/flow cytometry. Our results demonstrated that lycopene treatment significantly enhanced proliferation, tube formation, and migration of EPCs stimulated by ox-LDL. Additionally, lycopene was found to suppress pyroptosis in ox-LDL-induced EPCs through the activation of AMPK, which led to the inhibition of mTOR phosphorylation and subsequent downregulation of the downstream NLRP3 inflammasome. In summary, our study suggests that lycopene mitigates ox-LDL-induced dysfunction in EPCs and inhibits pyroptosis via AMPK/mTOR/NLRP3 signaling. Our study suggests that lycopene may act as promising therapies for preventing atherosclerosis.

Lewis acid-rich SrFexTi1-xO3/TiO2 to enhance the photocatalytic reduction of nitrate to N2.

The photocatalytic reduction of nitrate has received considerable attention due to its high efficiency and environmentally friendly nature. The excessive addition of hole scavengers is the most commonly used method to increase the nitrate reduction efficiency. However, achieving high selectivity in the photocatalytic reduction of nitrate to N2 with low concentration of hole scavengers remains challenging. In this study, the SrFexTi1-xO3/TiO2 S-scheme heterojunction photocatalysts with many Lewis acidic adsorption sites have been developed. The experimental results demonstrated that the incorporation of 6% Fe into SrFe0.06Ti0.94O3/TiO2 (SFTO6) resulted in the nitrate conversion rate of 97.68% and the N2 selectivity reached 96.35% with 25 mmol/L formic acid. Moreover, it also exhibited excellent stability and recycle ability. After 5 cycles, SFTO6 still exhibited a stable photocatalytic denitration efficiency of 92.94%, highlighting its potential for practical application. Through comprehensive mechanistic investigations, enhancing direct reduction process is considered the key to its high reduction efficiency with low formic acid. And the Lewis acidic adsorption sites enhance N2 selectivity by enriching NOx- on the surface of the material. Overall, this study provides a novel approach for achieving efficient photocatalytic reduction of nitrate to N2 under conditions with low concentration of hole scavengers.

Electroacupuncture and carbamazepine for patients with trigeminal neuralgia: a randomized, controlled, 2 × 2 factorial trial.

BACKGROUND: Trigeminal neuralgia (TN) is difficult to treat due to its severe pain intensity and recurring episodes, which significantly impact quality of life. OBJECTIVES: We aimed to assess the effectiveness of electroacupuncture (EA) in alleviating the pain intensity in TN, and to determine whether EA combined with low-dosage carbamazepine (CBZ) has a synergistic effect. METHODS: A multi-centre, randomized, 2 × 2 factorial trial was conducted. Participants who met the inclusion criteria received active EA or sham EA for 60 min, three times a week for four weeks; CBZ (300 mg per day) or placebo for four weeks. The primary outcome was the change in visual analog scale (VAS) score from baseline to weeks 2, 4, 16, and 28. Secondary outcomes included quality of life and adverse events. RESULTS: A total of 120 participants (75 females and 45 males; mean (SD) age, 58.5 (15.3) years) were included. The main effects of EA and CBZ were significant (P < 0.001), and there was a significant interaction was identified between the interventions (P = 0.041). Participants who received EA (mean difference [MD], -0.3 [95% CI, -0.40 to -0.20] at week 2; -1.6 [-1.70 to -1.50] at week 4; -1.1 [-1.31 to -0.89] at week 16; -0.8 [-1.01 to -0.59] at week 28), CBZ (MD, -0.6 [95% CI, -0.70 to -0.50] at week 2; -0.9 [-1.03 to -0.77] at week 4, -0.2 [-0.41 to 0.01] at week 16, 0.2 [-0.01 to 0.41] at week 28), and the combination of both (MD, -1.8 [95% CI, -1.90 to -1.70] at week 2; -3.7 [-3.83 to -3.57] at week 4, -3.4 [-3.61 to -3.19] at week 16, -2.9 [-3.11 to -2.69] at week 28) had a greater reduction in VAS score over the treatment phase than their respective control groups (sham EA, placebo, and sham EA plus placebo). EA-related adverse events (6/59, 10.17%) were lower than that of CBZ (15/59, 25.42%) during the whole phases. CONCLUSIONS: EA or CBZ alone are effective treatments for TN, while the combination of EA and low-dosage CBZ exerts a greater benefit. These findings in this trial demonstrate that the combination of EA and low-dosage CBZ may be clinically effective under certain circumstances. TRIAL REGISTRATION: NCT03580317.

Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis.

BACKGROUND: Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP. METHOD: The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test. RESULTS: Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678-0.784. CONCLUSIONS: This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.

The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities.

BACKGROUND: Chromosomal microarray analysis (CMA) has emerged as a critical instrument in prenatal diagnostic procedures, notably in assessing congenital heart diseases (CHD). Nonetheless, current research focuses solely on CHD, overlooking the necessity for thorough comparative investigations encompassing fetuses with varied structural abnormalities or those without apparent structural anomalies. OBJECTIVE: This study sought to assess the relation of single nucleotide polymorphism-based chromosomal microarray analysis (SNP-based CMA) in identifying the underlying causes of fetal cardiac ultrasound abnormalities. METHODS: A total of 2092 pregnant women who underwent prenatal diagnosis from 2017 to 2022 were included in the study and divided into four groups based on the presence of ultrasound structural abnormalities and the specific type of abnormality. The results of the SNP-Array test conducted on amniotic fluid samples from these groups were analyzed. RESULTS: Findings from the study revealed that the non-isolated CHD group exhibited the highest incidence of aneuploidy, overall chromosomal abnormalities, and trisomy 18, demonstrating statistically significant differences from the other groups (p < 0.001). Regarding the distribution frequency of copy number variation (CNV) segment size, no statistically significant distinctions were observed between the isolated CHD group and the non-isolated CHD group (p > 0.05). The occurrence rates of 22q11.2 and 15q11.2 were also not statistically different between the isolated CHD group and the non-isolated congenital heart defect group (p > 0.05). CONCLUSION: SNP-based CMA enhances the capacity to detect abnormal CNVs in CHD fetuses, offering valuable insights for diagnosing chromosomal etiology and facilitating genetic counseling. This research contributes to the broader understanding of the utility of SNP-based CMA in the context of fetal cardiac ultrasound abnormalities.

Machine learning improves early prediction of organ failure in hyperlipidemia acute pancreatitis using clinical and abdominal CT features.

BACKGROUND: This study aimed to investigate and validate machine-learning predictive models combining computed tomography and clinical data to early predict organ failure (OF) in Hyperlipidemic acute pancreatitis (HLAP). METHODS: Demographics, laboratory parameters and computed tomography imaging data of 314 patients with HLAP from the First Affiliated Hospital of Wenzhou Medical University between 2017 and 2021, were retrospectively analyzed. Sixty-five percent of patients (n = 204) were assigned to the training group and categorized as patients with and without OF. Parameters were compared by univariate analysis. Machine-learning methods including random forest (RF) were used to establish model to predict OF of HLAP. Areas under the curves (AUCs) of receiver operating characteristic were calculated. The remaining 35% patients (n = 110) were assigned to the validation group to evaluate the performance of models to predict OF. RESULTS: Ninety-three (45.59%) and fifty (45.45%) patients from the training and the validation cohort, respectively, developed OF. The RF model showed the best performance to predict OF, with the highest AUC value of 0.915. The sensitivity (0.828) and accuracy (0.814) of RF model were both the highest among the five models in the study cohort. In the validation cohort, RF model continued to show the highest AUC (0.820), accuracy (0.773) and sensitivity (0.800) to predict OF in HLAP, while the positive and negative likelihood ratios and post-test probability were 3.22, 0.267 and 72.85%, respectively. CONCLUSIONS: Machine-learning models can be used to predict OF occurrence in HLAP in our pilot study. RF model showed the best predictive performance, which may be a promising candidate for further clinical validation.

Unusual outbreaks of curly top disease in processing tomato fields in northern California in 2021 and 2022 were caused by a rare strain of beet curly top virus and facilitated by extreme weather events.

In the western United States, curly top disease (CTD) is caused by beet curly top virus (BCTV). In California, CTD causes economic loss to processing tomato production in central and southern areas but, historically, not in the north. Here, we document unusual CTD outbreaks in processing tomato fields in the northern production area in 2021 and 2022, and show that these were caused by the rare spinach curly top strain (BCTV-SpCT). These outbreaks were associated with proximity of fields to foothills and unusually hot, dry, and windy spring weather conditions, possibly by altering migrations of the beet leafhopper (BLH) vector from locations with BCTV-SpCT reservoirs. Support for this hypothesis came from the failure to observe CTD outbreaks and BLH migrations in 2023, when spring weather conditions were cool and wet. Our results show the climate-induced emergence of a rare plant virus strain to cause an economically important disease in a new crop and location.

Macrophages-derived exo-miR-4449 induced by Cryptococcus affects HUVEC permeability and promotes pyroptosis in BEAS-2B via the HIC1 pathway.

Macrophages have recently been discovered to assume a significant role in the progression of cryptococcosis. However, the potential involvement of macrophage-derived exosomes in the pathogenesis of cryptococcosis remains uncertain. In this study, we investigated the changes of microRNAs in macrophage exosomes (exo-miRNAs) in cryptococcal infections and the role of markedly altered exo-miRNAs in the modulation of Human Umbilical Vein Endothelial Cells (HUVEC) permeability and ROS accumulation and pyroptosis in Human Bronchial Epithelioid Cells (BEAS-2B). Techniques such as microarray analysis and real-time quantitative PCR were used to detect different exo-miRNAs and to screen for the most highly expressed exo-miRNAs. Then its mimics were transfected into HUVEC to study its effect on the monolayer permeability of HUVEC. Finally, the relationship between this exo-miRNAs and the ROS accumulation and pyroptosis was verified by bioinformatics analysis. The results showed that five exo-miRNAs were overexpressed and two exo-miRNAs were reduced, among which, exo-miR-4449 was expressed at the highest level. Exo-miR-4449 could be internalized by HUVEC and enhanced its monolayer permeability. Moreover, exo-miR-4449 was found to promote ROS accumulation and pyroptosis in BEAS-2B through HIC1 pathway. Thus, exo-miR-4449 plays an important role in the pathogenesis of cryptococcosis and holds promise as a significant biomarker for treatment.

ETU-Net: edge enhancement-guided U-Net with transformer for skin lesion segmentation.

Objective.Convolutional neural network (CNN)-based deep learning algorithms have been widely used in recent years for automatic skin lesion segmentation. However, the limited receptive fields of convolutional architectures hinder their ability to effectively model dependencies between different image ranges. The transformer is often employed in conjunction with CNN to extract both global and local information from images, as it excels at capturing long-range dependencies. However, this method cannot accurately segment skin lesions with blurred boundaries. To overcome this difficulty, we proposed ETU-Net.Approach.ETU-Net, a novel multi-scale architecture, combines edge enhancement, CNN, and transformer. We introduce the concept of edge detection operators into difference convolution, resulting in the design of the edge enhanced convolution block (EC block) and the local transformer block (LT block), which emphasize edge features. To capture the semantic information contained in local features, we propose the multi-scale local attention block (MLA block), which utilizes convolutions with different kernel sizes. Furthermore, to address the boundary uncertainty caused by patch division in the transformer, we introduce a novel global transformer block (GT block), which allows each patch to gather full-size feature information.Main results.Extensive experimental results on three publicly available skin datasets (PH2, ISIC-2017, and ISIC-2018) demonstrate that ETU-Net outperforms state-of-the-art hybrid methods based on CNN and Transformer in terms of segmentation performance. Moreover, ETU-Net exhibits excellent generalization ability in practical segmentation applications on dermatoscopy images contributed by the Wuxi No.2 People's Hospital.Significance.We propose ETU-Net, a novel multi-scale U-Net model guided by edge enhancement, which can address the challenges posed by complex lesion shapes and ambiguous boundaries in skin lesion segmentation tasks.

TBUnet: A Pure Convolutional U-Net Capable of Multifaceted Feature Extraction for Medical Image Segmentation.

Many current medical image segmentation methods utilize convolutional neural networks (CNNs), with some extended U-Net-based networks relying on deep feature representations to achieve satisfactory results. However, due to the limited receptive fields of convolutional architectures, they are unable to explicitly model the varying range dependencies present in medical images. Recently, advancements in large kernel convolution have allowed for the extraction of a wider range of low frequency information, making this task more achievable. In this paper, we propose TBUnet for solving the problem of difficult to accurately segment lesions with heterogeneous structures and fuzzy borders, such as melanoma, colon polyps and breast cancer. The TBUnet is a pure convolutional network with three branches for extracting high frequency information, low frequency information, and boundary information, respectively. It is capable of extracting features in various areas. To fuse the feature maps from the three branches, TBUnet presents the FL (fusion layer) module, which is based on threshold and logical operation. We design the FE (feature enhancement) module on the skip-connection to emphasize the fine-grained features. In addition, our method varies the number of input channels in different branches at each stage of the network, so that the relationship between low and high frequency features can be learned. TBUnet yields 91.08 DSC on ISIC-2018 for melanoma segmentation, and achieves better performance than state-of-the-art medical image segmentation methods. Furthermore, experimental results with 82.48 DSC and 89.04 DSC obtained on the BUSI dataset and the Kvasir-SEG dataset show that TBUnet outperforms the advanced segmentation methods. Experiments demonstrate that TBUnet has excellent segmentation performance and generalisation capability.

Research Progress on Microbial Community Succession in the Postmortem Interval Estimation.

The postmortem interval (PMI) estimation is a key and difficult point in the practice of forensic medicine, and forensic scientists at home and abroad have been searching for objective, quantifiable and accurate methods of PMI estimation. With the development and combination of high-throughput sequencing technology and artificial intelligence technology, the establishment of PMI model based on the succession of the microbial community on corpses has become a research focus in the field of forensic medicine. This paper reviews the technical methods, research applications and influencing factors of microbial community in PMI estimation explored by using high-throughput sequencing technology, to provide a reference for the related research on the use of microbial community to estimate PMI.

The association between n-3 polyunsaturated fatty acid intakes and asthma in US children and adolescents: A cross-sectional study from NHANES.

BACKGROUND: Asthma is an inflammatory disease. The potential of n-3 polyunsaturated fatty acids (PUFAs) to alleviate asthma symptoms through their anti-inflammatory effects and immune modulation has been explored. However, the precise role of dietary n-3 PUFAs in childhood and adolescent asthma remains unclear. OBJECTIVE: This study aimed to evaluate the association between dietary n-3 PUFAs intake and asthma in children and adolescents in the United States. METHODS: We conducted a cross-sectional analysis of 8543 children and adolescents from the National Health and Nutrition Examination Survey (NHANES) between 2013 and 2020 by adjusting for covariates and using multivariate logistic regression, restricted cubic spline, threshold effects, and subgroup analyses. RESULTS: Among 8354 participants, 1456 (16.5%) self-reported diagnosis of asthma by a healthcare provider. After adjusting for potential confounding factors, compared with individuals in the lowest n-3 PUFA consumption group (T1, <26.07 mg/kg/day), the adjusted odds ratio (OR) for asthma was 0.71 (95% CI: 0.6-0.84, p < .001) in the second group (T2, 26.07-48.93 mg/kg/day) and 0.58 (95% CI: 0.47-0.73, p < .001) in the third group (T3, >48.93 mg/kg/day). Furthermore, a nonlinear (L-shaped) relationship was observed between n-3 PUFA intake and asthma (p = .009), with subgroup and sensitivity analyses confirming the stability of the results. In the threshold analysis, a critical turning point was observed at approximately 59.0 mg/kg/day (OR = 0.984, 95% CI: 0.977-0.991, p < .001). CONCLUSION: Dietary intake of n-3 PUFAs exhibited an L-shaped relationship with asthma in children and adolescents in the United States, with a critical turning point observed at approximately 59.0 mg/kg/day.

Is HER2 ultra-low breast cancer different from HER2 null or HER2 low breast cancer? A study of 1363 patients.

OBJECTIVE: This study aims to analyze whether there are any differences in clinicopathological features and prognosis between HER2 ultra-low, HER2-null, and HER2-low expression in Chinese breast cancer (BC) patients. METHODS: The clinicopathological data of 1363 HER2-negative BC patients were retrospectively collected (from January 2018 to December 2019). HER2 status was further classified into HER2-null, HER2 ultra-low, and HER2-low. HER2-null expression is defined as infiltrating cancer cells completely free of staining. HER2 ultra-low expression is defined as ≤10% of infiltrating cancer cells showing incomplete and faint/weak membrane staining. HER2-low expression is defined as HER2 immunohistochemistry (IHC) 1+ or 2+ with negative in situ hybridization (ISH) assay. RESULTS: Of 1363 patients, there were 86 (6.3%) HER2-null patients, 395 (29.0%) HER2 ultra-low patients, and 882 (64.7%) HER2-low patients. HER2 ultra-low patients were different from HER2-low patients in terms of N stage, hormone receptor (HR) status, Ki-67 expression, and type of surgery. There were also significant differences in histologic type and postoperative endocrine therapy between HER2 ultra-low and HER2-null patients. HR+ (81.0%) tumors was more common than HR- (19.0%) in HER2 ultra-low patients. In addition, there was a significant difference in HR status between HER2 ultra-low and HER2-low patients (P = 0.001). The survival analysis showed that HER2 status had no effect on disease-free survival (DFS) in HER2-negative patients (all P > 0.05). However, regardless of HER2 status, HR+ patients had better DFS than HR- patients (P = 0.003). Cox multivariate analysis revealed that age (HR [95% CI] = 0.950 [0.928, 0.972], P < 0.001), HR status (HR [95% CI] = 3.342 [1.658, 6.736], P = 0.001), and postoperative endocrine therapy (HR [95% CI] = 0.048 [0.048, 0.023], P < 0.001) were important influencing factors of DFS in HER2-negative BC patients. CONCLUSION: HER2 ultra-low BC patients demonstrated distinct clinicopathological features from HER2-null and HER2-low tumors; while, HER2 status (null, ultra-low, or low) had no prognostic value in these HER2-negative BC population. Consistent with the published literature, HR status was an independent prognostic factor for DFS in HER2-negative BC patients.

Mitochondrial DNA Copy Number and Risk of Diabetes Mellitus and Metabolic Syndrome.

CONTEXT: Mitochondrial DNA (mtDNA) plays a key role in diabetes mellitus and metabolic syndrome (MetS). An increasing number of studies have reported the association between mtDNA copy number (mtDNA-CN) and the risk of diabetes mellitus and MetS; however, the associations remain conflicted and a systematic review and meta-analysis on the association between mtDNA-CN and diabetes mellitus and MetS is lacking. OBJECTIVE: We aimed to investigate the association of mtDNA-CN and diabetes mellitus and MetS using a systematic review and meta-analysis of observational studies. METHODS: PubMed, EMBASE, and Web of Science were searched up to December 15, 2022. Random-effect models were used to summarize the relative risks (RRs) and 95% CIs. RESULTS: A total of 19 articles were included in the systematic review and 6 articles (12 studies) in the meta-analysis involving 21 714 patients with diabetes (318 870 participants) and 5031 MetS (15 040 participants). Compared to the highest mtDNA-CN, the summary RR (95% CIs) for the lowest mtDNA-CN were 1.06 (95% CI, 1.01-1.12; I2 = 79.4%; n = 8) for diabetes (prospective study: 1.11 (1.02-1.21); I2 = 22.6%; n = 4; case-control: 1.27 (0.66-2.43); I2 = 81.8%; n = 2; cross-sectional: 1.01 (0.99-1.03); I2 = 74.7%; n = 2), and 1.03 (0.99-1.07; I2 = 70.6%; n = 4) for MetS (prospective: 2.87 (1.51-5.48); I2 = 0; n = 2; cross-sectional: 1.02 (1.01-1.04); I2 = 0; n = 2). CONCLUSION: Decreased mtDNA-CN was associated with increased risk of diabetes mellitus and MetS when limited to prospective studies. More longitudinal studies are warranted.

The Fe-S cluster assembly protein IscU2 increases α-ketoglutarate catabolism and DNA 5mC to promote tumor growth.

IscU2 is a scaffold protein that is critical for the assembly of iron-sulfur (Fe-S) clusters and the functions of Fe-S-containing mitochondrial proteins. However, the role of IscU2 in tumor development remains unclear. Here, we demonstrated that IscU2 expression is much higher in human pancreatic ductal adenocarcinoma (PDAC) tissues than in adjacent normal pancreatic tissues. In PDAC cells, activated KRAS enhances the c-Myc-mediated IscU2 transcription. The upregulated IscU2 stabilizes Fe-S cluster and regulates the activity of tricarboxylic acid (TCA) cycle enzymes α-ketoglutarate (α-KG) dehydrogenase and aconitase 2, which promote α-KG catabolism through oxidative and reductive TCA cycling, respectively. In addition to promoting mitochondrial functions, activated KRAS-induced and IscU2-dependent acceleration of α-KG catabolism results in reduced α-KG levels in the cytosol and nucleus, leading to an increase in DNA 5mC due to Tet methylcytosine dioxygenase 3 (TET3) inhibition and subsequent expression of genes including DNA polymerase alpha 1 catalytic subunit for PDAC cell proliferation and tumor growth in mice. These findings underscore a critical role of IscU2 in KRAS-promoted α-KG catabolism, 5mC-dependent gene expression, and PDAC growth and highlight the instrumental and integrated regulation of mitochondrial functions and gene expression by IscU2 in PDAC cells.

Integrated metabolome and transcriptome analyses provide insight into the effect of red and blue LEDs on the quality of sweet potato leaves.

Red and blue light-emitting diodes (LEDs) affect the quality of sweet potato leaves and their nutritional profile. Vines cultivated under blue LEDs had higher soluble protein contents, total phenolic compounds, flavonoids, and total antioxidant activity. Conversely, chlorophyll, soluble sugar, protein, and vitamin C contents were higher in leaves grown under red LEDs. Red and blue light increased the accumulation of 77 and 18 metabolites, respectively. Alpha-linoleic and linolenic acid metabolism were the most significantly enriched pathways based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A total of 615 genes were differentially expressed between sweet potato leaves exposed to red and blue LEDs. Among these, 510 differentially expressed genes were upregulated in leaves grown under blue light compared with those grown under red light, while the remaining 105 genes were expressed at higher levels in the latter than in the former. Among the KEGG enrichment pathways, blue light significantly induced anthocyanin and carotenoid biosynthesis structural genes. This study provides a scientific reference basis for using light to alter metabolites to improve the quality of edible sweet potato leaves.