BACKGROUND/OBJECTIVES: Unhealthy diets are associated with chronic stress. An allostatic load (AL) is a comprehensive physiological index that measures the chronic stress response of the body. As a healthy dietary pattern, the role of Dietary Approaches to Stop Hypertension (DASH) in the development of an AL during pregnancy remains unclear. This study examined the relationship between the DASH dietary pattern and AL during pregnancy. SUBJECTS/METHODS: This study was a prospective study. From January 2024 to November 2024, 134 pregnant women in the second trimester (23–27 weeks) and third trimester (32–36 weeks) of pregnancy who met the inclusion and exclusion criteria in the obstetrics clinic of a tertiary general hospital in Anhui Province were selected for a questionnaire survey, physical examination, and laboratory examination. The DASH dietary pattern was assessed using the DASH scoring tool, and the total AL score was calculated using nine biomarkers that represent the cardiovascular, metabolic, and immune systems. Logistic regression was used to analyze the relationship between the DASH score and AL. RESULTS: One hundred and thirty-four pregnant women were included in this study. At the second and third trimesters, 41.8% and 37% of pregnant women, respectively, were in the high AL group. The binary logistic regression results showed that the DASH score was negatively correlated with the AL in the unadjusted model (odds ratio [OR], 0.878; 95% confidence interval [CI], 0.807–0.957; P = 0.003) and adjusted model (OR, 0.878; 95% CI, 0.792–0.973; P = 0.013) in the second trimester, the DASH score was negatively correlated with the AL in the unadjusted model (OR, 0.832; 95% CI, 0.758–0.913; P < 0.001) and adjusted model (OR, 0.806; 95% CI, 0.716–0.908; P < 0.001) in the third trimester. CONCLUSION The DASH score was negatively correlated with the AL in pregnant women.A low DASH score may increase the risk of a high AL, which may have adverse effects on physical and mental health.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Objective:To summarize the clinical characteristics of elderly patients with stage Ⅰ diffuse large B-cell lymphoma (DLBCL) and analyze the factors associated with prognosis.Methods:A case series study was conducted by retrospectively collecting clinical data from patients aged over 60 years with newly diagnosed stage Ⅰ DLBCL across 20 medical centers in Jiangsu Province, China, between June 2010 and April 2023. The involved site, classification and treatment plan were summarized. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Statistical analyses were performed using the Kaplan-Meier method, and Cox regression model.Results:The study included 255 patients with a median age of 69 years, of whom 130 (51.0%) were male, 66 (25.9%) were aged ≥75 years and 26 (10.1%) had a high Charlson Comorbidity Index (CCI) score of ≥2. Extranodal involvement was observed in 163 (63.9%) patients, with the stomach (37.4%, 61/163), intestine (19.0%, 31/163), testes (11.0%, 18/163), and breast (7.4%, 12/163) being the most frequently affected sites. The non-germinal center B-cell (non-GCB) subtype was prevalent in 63.7% of patients (142/223), with no significant difference between the nodal and extranodal groups ( P=0.681). Furthermore, 73.9% (184/249) and 11.7% (29/249) of patients received the R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) and R-miniCHOP regimen, respectively. The overall 3-year PFS rate was 81.5%, and the 3-year OS rate was 85.6%. Patients aged ≥75 years ( HR=2.910, 95% CI 1.565-5.408, P=0.001) and/or with a CCI score ≥2 ( HR=2.324, 95% CI 1.141-4.732, P=0.020) had a significantly poorer PFS. Incorporating age ≥75 years and CCI score ≥2 into the stage-modified international prognostic index (sm-IPI) can better stratify the prognosis of elderly patients with stage Ⅰ DLBCL. The 3-year PFS rate was 48.7% in the high-risk group versus 85.7% in the low-risk group ( P<0.001). Conclusions:Our findings show that the elderly patients with stage Ⅰ DLBCL were predominantly characterized by extranodal involvement (particularly in the stomach and intestinal tract) and non-GCB subtype. Age ≥75 years and CCI ≥2 were identified as independent prognostic factors. The newly established sm-IPI-75-CCI incorporating these factors demonstrated superior prognostic discrimination compared to conventional risk assessment systems.

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: Coronavirus disease 2019 (COVID-19) can result in fatigue and post-exertional malaise; however, whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exacerbates lower urinary tract symptoms (LUTS) is unclear. This study investigated the association between prenatal SARS-CoV-2 infection and postpartum LUTS. METHODS: A multicenter, retrospective cohort study was conducted at two tertiary hospitals in China from November 1, 2022, to November 1, 2023. Participants were classified into infected and uninfected groups based on SARS-CoV-2 antigen results. LUTS prevalence and severity were assessed using self-reported symptoms and the Incontinence Impact Questionnaire-Short Form (IIQ-7). Pelvic floor muscle activity was measured using electromyography following the Glazer protocol. Group comparisons were performed to evaluate the association of SARS-CoV-2 infection with LUTS and electromyography parameters, with stratified analyses conducted using SPSS version 26.0. RESULTS: Among 3,652 participants (681 infected, 2,971 uninfected), no significant differences in LUTS prevalence or IIQ-7 scores were observed. However, SARS-CoV-2 infection was an independent factor influencing the electromyographic activity of the pelvic floor muscles (mean tonic contraction amplitudes), regardless of delivery mode ( P = 0.001). CONCLUSION Prenatal SARS-CoV-2 infection was not significantly associated with an increased risk of postpartum LUTS but independently altered pelvic floor muscle electromyographic activity, suggesting potential neuromuscular effects.
Humans ; Female ; COVID-19/epidemiology* ; Retrospective Studies ; Adult ; Pregnancy ; Lower Urinary Tract Symptoms/virology* ; Postpartum Period ; Pregnancy Complications, Infectious/virology* ; China/epidemiology* ; Electromyography ; SARS-CoV-2/physiology* ; Pelvic Floor/physiopathology* ; Prevalence

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To explore the effect of simvastatin monotherapy or in combination with doxorubicin on diffuse large B-cell lymphoma(DLBCL)cells and its possible molecular mechanisms.Methods:The differences in the expression levels of genes and proteins related to the mevalonate(MVA)pathway between DLBCL tissues and reactive lymph node hyperplasia tissues were compared via database analysis,as well as their effects on the prognosis.CCK-8 assay was used to detect the effect of simvastatin and doxorubicin on the viability of different subtypes of DLBCL cells,EdU was used to detect cell proliferation,flow cytometry was used to detect apoptosis,and Western blot was used to detect related protein and signaling pathway proteins.Results:The expression levels of MVA pathway-related genes were increased in tumor tissues of DLBCL patients through the TCGA database,and the median overall survival time of DLBCL patients in HMGCR high expression group was shorter(all P＜0.05).Meanwhile,according to The Human Protein Atlas database,HMGCR protein was significantly high expressed in DLBCL tumor tissue compared with normal tissue.The viability of DLBCL cell lines treated with simvastatin or doxorubicin monotherapy was decreased in time-and concentration-dependent manner,and could be further inhibited by simvastatin combined with doxorubicin especially in GCB subtype cell lines.Both simvastatin and doxorubicin could inhibit the proliferation of DLBCL cell lines,and their combination further suppressed dramatically.Both the two drugs promoted apoptosis in DLBCL cell lines,and the apoptosis was further increased after their combination.Compared with monotherapy,the expression of HMGCR protein and apoptosis-related protein Bcl-2 was further decreased but cleaved-caspase3 and Bax increased after combination therapy.Meanwhile,the expression level of phosphorylated proteins in PI3K-Akt pro-survival signaling pathway were decreased especially in GCB subtype cell lines.Conclusion:HMGCR,the protein associated with cholesterol synthesis pathway,is highly expressed in DLBCL tumor tissues and indicates poor prognosis.Simvastatin,a lipid-lowering drug,combined with doxorubicin can further affect the survival of DLBCL tumor cells at the cellular level.

Objective:To summarize the clinical characteristics of elderly patients with stage Ⅰ diffuse large B-cell lymphoma (DLBCL) and analyze the factors associated with prognosis.Methods:A case series study was conducted by retrospectively collecting clinical data from patients aged over 60 years with newly diagnosed stage Ⅰ DLBCL across 20 medical centers in Jiangsu Province, China, between June 2010 and April 2023. The involved site, classification and treatment plan were summarized. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Statistical analyses were performed using the Kaplan-Meier method, and Cox regression model.Results:The study included 255 patients with a median age of 69 years, of whom 130 (51.0%) were male, 66 (25.9%) were aged ≥75 years and 26 (10.1%) had a high Charlson Comorbidity Index (CCI) score of ≥2. Extranodal involvement was observed in 163 (63.9%) patients, with the stomach (37.4%, 61/163), intestine (19.0%, 31/163), testes (11.0%, 18/163), and breast (7.4%, 12/163) being the most frequently affected sites. The non-germinal center B-cell (non-GCB) subtype was prevalent in 63.7% of patients (142/223), with no significant difference between the nodal and extranodal groups ( P=0.681). Furthermore, 73.9% (184/249) and 11.7% (29/249) of patients received the R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) and R-miniCHOP regimen, respectively. The overall 3-year PFS rate was 81.5%, and the 3-year OS rate was 85.6%. Patients aged ≥75 years ( HR=2.910, 95% CI 1.565-5.408, P=0.001) and/or with a CCI score ≥2 ( HR=2.324, 95% CI 1.141-4.732, P=0.020) had a significantly poorer PFS. Incorporating age ≥75 years and CCI score ≥2 into the stage-modified international prognostic index (sm-IPI) can better stratify the prognosis of elderly patients with stage Ⅰ DLBCL. The 3-year PFS rate was 48.7% in the high-risk group versus 85.7% in the low-risk group ( P<0.001). Conclusions:Our findings show that the elderly patients with stage Ⅰ DLBCL were predominantly characterized by extranodal involvement (particularly in the stomach and intestinal tract) and non-GCB subtype. Age ≥75 years and CCI ≥2 were identified as independent prognostic factors. The newly established sm-IPI-75-CCI incorporating these factors demonstrated superior prognostic discrimination compared to conventional risk assessment systems.

Aim To explore the mechanism of Bushen Tongfu prescription(BSTF)regulating gut microbiota and improving learning and memory ability of Alzhei-mer's disease(AD)model mice.Methods APP/PS1 mice were administered by BSTF for eight weeks.The spatial learning and memory ability of mice were detected by Morris water maze.The changes in the gut microbiota abundance and diversity of mice were detec-ted by 16S rDNA technology.The morphological chan-ges of hippocampus were observed by HE staining.The expression of the activation of microglia in hippocampus was detected by immunofluorescence.The expressions of pro-inflammatory factors of TLR4,NF-κB and IL-6 in brain tissue were detected by Western blot.Results Compared with the model group,the escape latency and swimming path were shortened,the times of target crossings after removing the platform increased in BSTF groups(P＜0.05),the α-diversity increased and the abundance of gut microbiota was regulated,the mor-phological structure and pathological damage of hipp-ocampal cells were improved,the co-expression of iN-OS/Iba1 decreased and the co-expression of Arg1/Iba1 increased significantly(P＜0.01),the transformation of M1 to M2 of microglial cells was promoted,and the expression of TLR4,NF-κB and IL-6 protein decreased significantly.Conclusions BSTF can improve the learning and memory ability of APP/PS1 mice,and its mechanism may be related to regulating the gut micro-biota and the LPS/TLR4/NF-κB pathway,inhibiting the activation of pro-inflammatory microglia,reducing inflammation in hippocampus and improving the patho-logical damage of hippocampal cells.

The patient was a boy aged 1 year and 9 months who presented with 46,XY disorder of sex development (DSD), with severe undermasculinization of the external genitalia. Laboratory tests and ultrasound examinations showed normal functions of Leydig cells and Sertoli cells in the testes. Genetic testing revealed a novel pathogenic heterozygous variant, c.1186dupA (p.T396Nfs*17), in the PPP1R12A gene. Thirteen cases of PPP1R12A gene variants have been reported previously. These variants may cause isolated involvement of the genitourinary or neurological systems, or affect other systems/organs including the digestive tract, eyes, heart, etc. Patients with DSD typically present with a 46,XY karyotype and variable degrees of undermasculinization involving the external genitalia, gonads, and reproductive tract. This article reports a child with 46,XY DSD accompanied by growth retardation caused by a heterozygous variant in the PPP1R12A gene, which expands the clinical disease spectrum associated with PPP1R12A gene variants.
Humans ; Male ; Infant ; Disorder of Sex Development, 46,XY/etiology* ; Protein Phosphatase 1/genetics*