Non-invasive prenatal testing (NIPT) based on fetal free DNA is a non-invasive technique to screen for common fetal aneuploidies by analyzing cell-free fetal DNA (cffDNA) in the peripheral blood of pregnant women. This technique has opened a new era of prenatal screening for its high safety and reliability. In recent years, it has been shown that NIPT can not only screen for fetal aneuploidies, but may also reveal maternal genomic abnormalities. The incidental detection of maternal tumors has aroused widespread concern in the clinical settings. The aim of this review is to systematically summarize the research progress of NIPT technique in incidental detection of maternal tumors, and to discuss its clinical significance, technical challenges, and future development direction. It has been found that multiple chromosome aneuploidies (MCAs) in NIPT detection is one of the important biomarkers suggesting occult maternal malignant tumors. In this paper, the relevant progress of NIPT technique in the incidental discovery of maternal tumors were reviewed in order to provide a reference for individualized and standardized application of NIPT technique in maternal health monitoring.
Humans ; Female ; Pregnancy ; Cell-Free Nucleic Acids/blood* ; Prenatal Diagnosis/methods* ; Incidental Findings ; Neoplasms/genetics* ; Noninvasive Prenatal Testing/methods* ; Aneuploidy ; Fetus/metabolism*

ObjectiveMitochondria are not only the central organelles responsible for cellular energy metabolism but also play essential roles in regulating cell cycle progression and cytoskeletal dynamics. In recent years, accumulating evidence has demonstrated that mitochondrial homeostasis is closely associated with mitotic progression and cytokinesis. Schizosaccharomyces pombe serves as a classical and well-established model organism. Because its cell cycle regulatory mechanisms are highly conserved throughout evolution, its genetic background is clearly defined, and experimental manipulation is efficient and convenient, it has been extensively applied in studies of cell growth, division, and reproductive mechanisms. The SPBC1604.04 gene encodes a previously uncharacterized mitochondrial carrier protein in Schizosaccharomyces pombe. This gene is located on chromosome II and spans 1 018 base pairs in length. It encodes a protein consisting of 238 amino acids with a predicted molecular mass of approximately 31.03 ku. Bioinformatic analysis predicts that this protein is responsible for the transport of thiamine pyrophosphate (TPP) into mitochondria. However, the effects of SPBC1604.04 gene deletion on mitotic cell dynamics under different temperature conditions have not been fully elucidated. MethodsThe SPBC1604.04 deletion strain of Schizosaccharomyces pombe was used as the experimental model. Fluorescent protein markers were constructed in the deletion background to label mitochondria, microtubules, actin, myosin, the nuclear envelope, and chromosomes. Live-cell imaging was performed using a TCS-SP8 laser scanning confocal microscope under normal temperature conditions (25℃) and heat stress conditions (37℃). Time-lapse microscopy was applied to dynamically monitor mitochondrial morphology and distribution, spindle assembly and elongation, chromosome segregation, as well as the formation and constriction of the actomyosin ring during cytokinesis. ImageJ software was used for quantitative measurements, including microtubule length during mitosis, spindle length at different mitotic stages, mitochondrial fluorescence intensity as an indicator of mitochondrial content, actomyosin ring length, nuclear envelope area, and chromosome segregation timing. Statistical analyses were conducted to compare phenotypic differences between the wild-type and SPBC1604.04 deletion strains at both temperature conditions. Through these analyses, we systematically investigated the impact of SPBC1604.04 deletion on mitotic cell dynamics in fission yeast under both normal physiological conditions and temperature stress. ResultsAt 25℃, compared with wild-type cells, the SPBC1604.04Δ strain exhibited a pronounced tendency toward mitochondrial fragmentation, accompanied by abnormal mitochondrial content and a significant reduction in mitochondrial fluorescence intensity. These observations suggest impaired mitochondrial homeostasis under normal growth conditions. In addition, the constriction time of actomyosin ring during cytokinesis was markedly prolonged, indicating that deletion of SPBC1604.04 affects the dynamics of the contractile machinery. However, no obvious defects were observed in spindle assembly, spindle elongation, or chromosome segregation. Under heat stress at 37℃, mitochondrial morphology in the SPBC1604.04Δ strain showed a tendency to recover toward a continuous tubular network structure. Mitochondrial content was restored, fluorescence intensity increased, and the constriction time of the actomyosin ring returned to levels comparable to those of wild-type cells. These results indicate that the mitotic defects observed at normal temperature are partially or fully alleviated under heat stress conditions. ConclusionThis study demonstrates that deletion of the SPBC1604.04 gene leads to abnormal mitochondrial content in Schizosaccharomyces pombe. The mitochondrial carrier protein SPBC1604.04 participates in regulating actomyosin ring constriction during mitosis but does not appear to be directly involved in the regulation of spindle dynamics or chromosome segregation. Our findings provide key experimental evidence for understanding the functional link between the SPBC1604.04 gene, mitochondrial homeostasis, and mitotic regulation.

ObjectiveMitochondria are not only the central organelles responsible for cellular energy metabolism but also play essential roles in regulating cell cycle progression and cytoskeletal dynamics. In recent years, accumulating evidence has demonstrated that mitochondrial homeostasis is closely associated with mitotic progression and cytokinesis. Schizosaccharomyces pombe serves as a classical and well-established model organism. Because its cell cycle regulatory mechanisms are highly conserved throughout evolution, its genetic background is clearly defined, and experimental manipulation is efficient and convenient, it has been extensively applied in studies of cell growth, division, and reproductive mechanisms. The SPBC1604.04 gene encodes a previously uncharacterized mitochondrial carrier protein in Schizosaccharomyces pombe. This gene is located on chromosome II and spans 1 018 base pairs in length. It encodes a protein consisting of 238 amino acids with a predicted molecular mass of approximately 31.03 ku. Bioinformatic analysis predicts that this protein is responsible for the transport of thiamine pyrophosphate (TPP) into mitochondria. However, the effects of SPBC1604.04 gene deletion on mitotic cell dynamics under different temperature conditions have not been fully elucidated. MethodsThe SPBC1604.04 deletion strain of Schizosaccharomyces pombe was used as the experimental model. Fluorescent protein markers were constructed in the deletion background to label mitochondria, microtubules, actin, myosin, the nuclear envelope, and chromosomes. Live-cell imaging was performed using a TCS-SP8 laser scanning confocal microscope under normal temperature conditions (25℃) and heat stress conditions (37℃). Time-lapse microscopy was applied to dynamically monitor mitochondrial morphology and distribution, spindle assembly and elongation, chromosome segregation, as well as the formation and constriction of the actomyosin ring during cytokinesis. ImageJ software was used for quantitative measurements, including microtubule length during mitosis, spindle length at different mitotic stages, mitochondrial fluorescence intensity as an indicator of mitochondrial content, actomyosin ring length, nuclear envelope area, and chromosome segregation timing. Statistical analyses were conducted to compare phenotypic differences between the wild-type and SPBC1604.04 deletion strains at both temperature conditions. Through these analyses, we systematically investigated the impact of SPBC1604.04 deletion on mitotic cell dynamics in fission yeast under both normal physiological conditions and temperature stress. ResultsAt 25℃, compared with wild-type cells, the SPBC1604.04Δ strain exhibited a pronounced tendency toward mitochondrial fragmentation, accompanied by abnormal mitochondrial content and a significant reduction in mitochondrial fluorescence intensity. These observations suggest impaired mitochondrial homeostasis under normal growth conditions. In addition, the constriction time of actomyosin ring during cytokinesis was markedly prolonged, indicating that deletion of SPBC1604.04 affects the dynamics of the contractile machinery. However, no obvious defects were observed in spindle assembly, spindle elongation, or chromosome segregation. Under heat stress at 37℃, mitochondrial morphology in the SPBC1604.04Δ strain showed a tendency to recover toward a continuous tubular network structure. Mitochondrial content was restored, fluorescence intensity increased, and the constriction time of the actomyosin ring returned to levels comparable to those of wild-type cells. These results indicate that the mitotic defects observed at normal temperature are partially or fully alleviated under heat stress conditions. ConclusionThis study demonstrates that deletion of the SPBC1604.04 gene leads to abnormal mitochondrial content in Schizosaccharomyces pombe. The mitochondrial carrier protein SPBC1604.04 participates in regulating actomyosin ring constriction during mitosis but does not appear to be directly involved in the regulation of spindle dynamics or chromosome segregation. Our findings provide key experimental evidence for understanding the functional link between the SPBC1604.04 gene, mitochondrial homeostasis, and mitotic regulation.

ObjectiveTo evaluate the feasibility of various strength levels of deep learning image reconstruction （DLIR） algorithms for improving non-contrast abdominal CT image quality at ultra-low radiation doses， by comparing ultra-low-dose DLIR images with low-dose filtered back projection （FBP） images. MethodsA prospective collection of 85 patients undergoing non-contrast abdominal CT scans was performed， and a self-controlled study method was employed to conduct low-dose （LD） group and ultra-low-dose （ULD） group scans. The LD group used a noise index of 10 and employed FBP for image reconstruction （LD-FBP group）. The ULD group used a noise index of 30 and employed DLIR at different levels （low， medium， high）， resulting in three subgroups of reconstructed images： ULD-DLIR-L， ULD-DLIR-M， and ULD-DLIR-H. For each group， CT values， standard devia-tion （SD）， signal-to-noise ratio （SNR）， and contrast-to-noise ratio （CNR） were measured and calculated for the liver， spleen， kidneys， aorta， psoas major， and subcutaneous fat. Effective dose （ED） was also recorded. Two radiologists independently performed subjective evaluations of image quality using a 5-point scale. ResultsCompared with the LD-FBP group， the ULD-DLIR-L group showed significantly lower SNR and CNR values in the liver， spleen， kidneys， aorta， and psoas major （P<0.001）， while the ULD-DLIR-H group exhibited significantly higher values （P<0.001）. The difference of SNR and CNR values for the ULD-DLIR-M group showed no statistically significant difference. For subjective evaluation， the scores of the ULD-DLIR-L and ULD-DLIR-M groups were lower than those of the LD-FBP group， while there was no statistically significant difference in scores between the ULD-DLIR-H group and the LD-FBP group. The ED value of the ULD group was approximately 88% lower than that of the LD group. ConclusionCompared with the LD-FBP group， the ULD-DLIR-H group significantly reduces SD values while increasing SNR and CNR values， effectively improving the image quality of non-contrast abdominal CT scans.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Objective： To investigate the relationship between the lipid metabolism-related gene sterol carrier protein 2(SCP2) and prostate cancer (PCa) from a multi-omics perspective using single-cell transcriptomes combined with Mendelian randomization. Methods： Single-cell transcriptome data of benign and malignant prostate tissues were obtained from GSE120716, GSE157703 and GSE141445 datasets, respectively. Integration, quality control and annotation were performed on the data to categorize the epithelial cells into high and low SCP2 expression groups, followed by further differential and trajectory analyses. Single nucleotide polymorphism (SNP) data for SCP2 expression quantitative trait loci (eQTL) were subsequently downloaded from Genotype-Tissue Expression (GTEx) and investigated from the PCa Society Cancer-Related Genomic Alteration Panel for the Investigation of Cancer-Related Alterations (PRACTICAL) to obtain PCa outcome data for Mendelian randomization analysis to validate the causal relationship between SCP2 and PCa. Results： High SCP2-expressing epithelial cells had higher energy metabolism and proliferation capacity with low immunotherapy response and metastatic tendency. Trajectory analysis showed that epithelial cells with high SCP2 expression may have a higher degree of malignancy, and SCP2 may be a key marker gene for differentiation of malignant epithelial cells in the prostate. Further Mendelian randomization results showed a significant causal relationship between SCP2 and PCa development (OR=1.045, 95% CI: 1.010 －1.083, P=0.011). Conclusion： By combining single-cell transcriptome and Mendelian randomization, the role of the lipid metabolism-related gene SCP2 in PCa development has been confirmed, and new targets and therapeutic directions for PCa treatment have been provided.
Humans ; Prostatic Neoplasms/genetics* ; Male ; Mendelian Randomization Analysis ; Polymorphism, Single Nucleotide ; Quantitative Trait Loci ; Single-Cell Analysis ; Sequence Analysis, RNA ; Carrier Proteins/genetics* ; Transcriptome ; Lipid Metabolism

Intravitreal injection of anti-vascular endothelial growth factor(VEGF)agents has become the primary treatment for macular edema associated with retinal vascular disease such as diabetic retinopathy and retinal vein occlusion, but there are limitations such as variable treatment efficacy and insufficient durability of therapeutic effects. As the first bispecific antibody applied in ophthalmic treatment, Faricimab achieves favorable outcomes by simultaneously targeting both VEGF-A and angiopoietin-2(Ang-2)pathways. Based on evidence from recent clinical trials and real-world studies, this article reviews the research progress on Faricimab for the treatment of diabetic macular edema(DME), retinal vein occlusion-associated macular edema(RVO-ME)and refractory macular edema compared to the therapeutic effects of other agents. Additionally, based on Faricimab's safety characteristics and future potential, its therapeutic prospects for macular edema associated with retinal vascular diseases are discussed. This review aims to provide evidence-based references for optimizing clinical treatment strategies, thereby contributing to mitigating the risk of vision loss due to macular edema.