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Abstract Ginseng, from the roots of Panax ginseng C. A. Meyer, is a widely used herbal medicine in Asian countries, known for its excellent therapeutic properties. The growth of P. ginseng is depend on specific and strict environments, with a preference for wetness but intolerance for flooding. Under excessive soil moisture, some irregular rust-like substances are deposited on the root epidermis, causing ginseng rusty symptoms (GRS). This condition leads to a significant reduce in yield and quality, resulting in substantial economic loses. However, there is less knowledge on the cause of GRS and there are no effective treatments available for its treatment once it occurs. Unsuitable environments lead to the generation of large amounts of reactive oxygen species (ROS). We investigated the key indicators associated with the stress response during different physiological stages of GRS development. We observed a significant change in ROS level, MDA contents, antioxidant enzymes activities, and non-enzymatic antioxidants contents prior to the GRS. Through the analysis of soil features with an abundance of moisture, we further determined the source of ROS. The levels of nitrate reductase (NR) and nitric oxide synthase (NOS) activities in the inter-root soil of ginseng with GRS were significantly elevated compared to those of healthy ginseng. These enzymes boost nitric oxide (NO) levels, which in turn showed a favorable correlation with the GRS. The activities of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase first rose and then decreased as GRS developed. Excess soil moisture causes a decrease in oxygen levels. This activated NR and NOS in the soil, resulting in a production of excess NO. The NO then diffused into the ginseng root and triggered a burst of ROS through NADPH located on the cell membrane. Additionally, Fe2+ in soil was oxidized to red Fe3+, and finally led to GRS. This conclusion was also verified by the Sodium Nitroprusside (SNP), a precursor compound producing NO. The presence of NO from NR and NOS in water-saturated soil is responsible for the generation of ROS. Among these, NO is the main component that contribute to the occurrence of GRS.

Abstract Human papillomavirus (HPV) 11/16 E6/E7 proteins have been recognized to be pivotal in viral pathogenesis. This study sought to uncover the potential mechanisms of how HPV11/16 E6/E7-transfected keratinocytes inhibit cytokine secretion in peripheral blood mononuclear cells (PBMC). Upon co-culturing HPV11/16 E6/E7-transfected keratinocytes with PBMC in a non-contact manner, we observed a marked decrease in various cytokines secreted by PBMC. To determine if this suppression was mediated by specific common secreted factors, we conducted transcriptomic sequencing on these transfected cells. This analysis identified 53 common differentially secreted genes in all four HPV-transfected cells. Bioinformatics analysis demonstrated these genes were predominantly involved in immune regulation. Results from quantitative PCR (qPCR) and an extensive literature review suggested the downregulation of 12 genes (ACE2, BMP3, BPIFB1, CLU, CST6, CTF1, HMGB2, MMP12, PDGFA, RNASE7, SULF2, TGM2), and upregulation of 7 genes (CCL17, CCL22, FBLN1, PLAU, S100A7, S100A8, S100A9), may be crucial in modulating tumor immunity and combating pathogenic infections, with genes S100A8 and S100A9, and IL-17 signaling pathway being particularly noteworthy. Thus, HPV11/16 E6/E7 proteins may inhibit cytokine secretion of immune cells by altering the expression of host-secreted genes. Further exploration of these genes may yield new insights into the complex dynamics of HPV infection.

Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories. However, when regulatory sequence expression strengths are characterized using only a few reporter genes, they may not be applicable across diverse genes. This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels. To address this, our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels. We combined 41 commonly-used metabolic genes with 15 regulatory sequences, yielding an expression dataset encompassing 520 unique combinations. This dataset highlighted substantial variation in protein expression level under identical regulatory sequences, with relative expression levels ranging from 2.8 to 176-fold. It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins. Utilizing this dataset, we have developed various machine learning models and discovered that the integration of promoter regions, ribosome binding sites, and coding sequences significantly improves the accuracy of predicting protein expression levels, with a Spearman correlation coefficient of 0.72, where the promoter sequence exerts a predominant influence. Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.

Abstract Purpose Our study aimed to develop and validate a homologous recombination deficiency (HRD) scoring algorithm in the Chinese breast cancer population. Methods and materials Ninety-six in-house breast cancer (BC) samples and 6 HRD-positive standard cells were analyzed by whole-genome sequencing (WGS). Besides, 122 BCs from the TCGA database were down-sampled to ~ 1X WGS. We constructed an algorithm named AcornHRD for HRD score calculated based on WGS at low coverage as input data to estimate large-scale copy number alteration (LCNA) events on the genome. A clinical cohort of 50 BCs (15 cases carrying BRCA mutation) was used to assess the association between HRD status and anthracyclines-based neoadjuvant treatment outcomes. Results A 100-kb window was defined as the optimal size using 41 in-house cases and the TCGA dataset. HRD score high threshold was determined as HRD score ≥ 10 using 55 in-house BCs with BRCA mutation to achieve a 95% BRCA-positive agreement rate. Furthermore, the HRD status agreement rate of AcornHRD is 100%, while the ShallowHRD is 60% in standard cells. BRCA mutation was significantly associated with a high HRD score evaluated by AcornHRD and ShallowHRD (p = 0.008 and p = 0.003, respectively) in the TCGA dataset. However, AcornHRD showed a higher positive agreement rate than did the ShallowHRD algorithm (70% vs 60%). In addition, the BRCA-positive agreement rate of AcornHRD was superior to that of ShallowHRD (87% vs 13%) in the clinical cohort. Importantly, the high HRD score assessed by AcornHRD was significantly correlated with a residual cancer burden score of 0 or 1 (RCB0/1). Besides, the HRD-positive group was more likely to respond to anthracycline-based chemotherapy than the HRD-negative group (pCR [OR = 9.5, 95% CI 1.11–81.5, p = 0.040] and RCB0/1 [OR = 10.29, 95% CI 2.02–52.36, p = 0.005]). Conclusion Using the AcornHRD algorithm evaluation, our analysis demonstrated the high performance of the LCNA genomic signature for HRD detection in breast cancers.

Abstract As the most abundant animal in the soil, nematodes are directly or indirectly involved in almost all soil ecological processes. Studying soil nematode population regulation is essential to understanding soil ecological processes. This study found urea combines nematode-trapping fungi to regulate the population of soil nematodes. In soil, compared with no urea, adding 0.2 mg/mL urea after applying Arthrobotrys oligospora and Dactylellina ellipsospora reduced the number of nematodes by 34.7% and 31.7%. Further, the mechanism of urea couple nematode-trapping fungi to regulate the nematode population was explored in the medium environment. The results showed that the addition of 0.2 mg/ml urea accelerated the trap formation of A. oligospora and D. ellipsosporas by 50% and 46.5%, and increased the yield of traps of A. oligospora and D. ellipsosporas by 39.5% and 40.6%, thus, the predatory efficiency of A. oligospora and D. ellipsospora on nematodes was increased by 34.2% and 32.7%. In conclusion, urea regulates the predation ability of A. oligospora and D. ellipsosporas to regulate the soil nematode population. This study deepens the understanding of the regulatory pathways of the soil nematodes but also provides a potential new strategy for harmful nematode bio-control.

Carnosine dipeptidase 1 (CNDP1), an enzyme integral to the hydrolysis of dipeptides containing histidine, plays an indispensable role in myriad physiological processes, including hydrolysis of proteins, maturation of specific biochemical functionalities within proteins, tissue regeneration, and regulation of cell cycle. However, the implications of CNDP1 in oncogenesis and its prognostic value are not yet fully elucidated. Initially, we procured the GSE40367 dataset from the Gene Expression Omnibus and established a protein–protein interaction network. Thereafter, we conducted functional and pathway enrichment analyses utilizing GO, KEGG, and GSEA. Moreover, we undertook an association analysis concerning the expression of CNDP1 with immune infiltration, along with survival analysis across various cancers and specifically in hepatocellular carcinoma (HCC). Our study uncovered a total of 2,248 differentially expressed genes, with a down-regulation of CNDP1 in HCC and other cancers. Our explorations into the relationship between CNDP1 and immune infiltration disclosed a negative correlation between CNDP1 expression and the presence of immune cells in HCC. Survival analyses revealed that diminished expression of CNDP1 correlates with an adverse prognosis in HCC and several other types of cancer. These observations intimate that CNDP1 holds promise as a novel prognostic biomarker for both pan-cancer and HCC.

Objective To explore the adjustment and impact of chronic kidney disease-mineral and bone disorder (CKD-MBD) parameters in maintenance dialysis patients utilizing the Doctor-Patient Care App (Renal Care App). Methods From August 2021 to March 2022, 102 maintenance dialysis (HD) and peritoneal dialysis (PD) patients were randomized into two groups of App management or control (n=51 each). Control group received standard treatment for CKD-MBD while App management group was treated with CKD-MBD management model facilitated by Renal Care App. Follow-up assessments occurred every 3 months over a 12-month period. Changes in serum calcium (Ca), serum phosphorus (P) and serum parathyroid hormone (iPTH) levels were recorded along with patient satisfaction and revisit rates. Results From August 2021 to March 2022, 102 maintenance dialysis (HD) and peritoneal dialysis (PD) patients were randomized into two groups of App management or control (n=51 each). Control group received standard treatment for CKD-MBD while App management group was treated with CKD-MBD management model facilitated by Renal Care App. Follow-up assessments occurred every 3 months over a 12-month period. Changes in serum calcium (Ca), serum phosphorus (P) and serum parathyroid hormone (iPTH) levels were recorded along with patient satisfaction and revisit rates. Conclusions Interventions utilizing the App management model prove advantageous in elevating the rate of CKD-MBD-related parameters attaining the standards among regular dialysis patients. This approach not only improves patient compliance and satisfaction but also demonstrates clinical significance for broader applications.

Congenital solitary functioning kidney (cSFK) is one of the major causes of chronic kidney disease (CKD) in children. Long-term renal hyperfiltration leads to kidney injury with hypertension, proteinuria and lower estimated glomerular filtration rate (eGFR). Early clinical manifestations of cSFK children are generally insignificant. They are more prone to develop kidney injury then progress to end-stage renal disease. Long-term managements and aggressive interventions should be implemented for better outcomes. The pathogenesis, pathophysiological rationales of renal injury, clinical manifestations and proper managements of cSFK were summarized.

Abstract Background Immune cells play a pivotal role in the tumor microenvironment, exerting significant influence on tumor progression and patient outcomes, but the current biomarkers are insufficient to fully capture the complex and diverse tumor immune microenvironment and the impact of immunotherapy. Methods The advent of single‐cell sequencing allows us to explore the tumor microenvironment at an unprecedented resolution, enabling the identification and characterization of distinct subsets of immune cells, thereby paving the way for the development of prognostic models using immune cells. Leveraging single‐cell data, our study deeply investigated the intricacies of immune microenvironment heterogeneity in esophageal carcinoma. Results We elucidated the composition, functionality, evolution, and intercellular communication patterns of immune cells, culminating in the construction of an independent prognostic model at the single‐cell level. Furthermore, we conducted a comprehensive analysis of disparities in immune infiltration and immune checkpoint expression between patients categorized into high‐ and low‐risk groups, which may impact patient prognosis. Conclusion In summary, our study harnessed multiomics data to delineate the immune profile of esophageal carcinoma patients, provide a method for leveraging molecular signatures of immune cells to identify potential biomarkers, while concurrently providing evidence for the potential benefits of immunotherapy.

PurposeThis study aims to explore the effectiveness of enhancing individual spatial cognitive abilities in alleviating the negative symptoms of visually induced motion sickness (VIMS). Additionally, it seeks to develop innovative intervention methods to improve spatial cognition and identify new treatment approaches for VIMS.MethodsThe study investigated the impact of innovative interventions on spatial cognitive abilities and their modulation of VIMS susceptibility. A total of 43 participants were recruited (23 in the experimental group and 20 in the control group). The experimental group underwent six sessions of spatial cognitive ability training, while the control group engaged in activities unrelated to spatial cognition.ResultsThe analysis revealed that the spatial cognitive ability scores of the experimental group significantly improved after the intervention. Furthermore, the experimental group exhibited significant differences in nausea, oculomotor, disorientation, and total SSQ scores before and after the intervention, indicating that the intervention effectively mitigated VIMS symptoms.ConclusionThis study developed a virtual reality training method that effectively enhances individual spatial cognitive abilities and significantly alleviates VIMS symptoms, providing a novel and effective approach for VIMS intervention and treatment.

BackgroundThe nutritional status and coagulation function of peritoneal dialysis (PD) patients are closely associated with their prognosis. This study aims to investigate the prognostic value of the albumin-to-fibrinogen ratio (AFR) on mortality in PD patients and to establish a prognostic prediction model based on AFR.MethodsWe retrospectively collected data from 148 PD patients treated at our hospital between Oct. 2011 and Dec. 2021. Using the “survminer” package in R, we determined the optimal cutoff value for AFR and divided the patients into low-AFR and high-AFR groups. The primary endpoint of this study was overall survival (OS). Univariate and multivariate Cox analyses were used to assess the impact of AFR and other factors on prognosis, and a corresponding prognostic prediction model was constructed using a nomogram, which was evaluated through ROC curves, the c-index, and calibration plots.ResultsThe optimal cutoff value for AFR was 9.06. In the entire cohort, 30 patients (20.2%) were classified into the low-AFR group. Compared to the high-AFR group, patients in the low-AFR group were older, had lower total urine output over 24 h, higher blood urea nitrogen, higher total protein and urinary microalbumin levels, and longer remission times (p

BackgroundPreoperative immune-inflammatory condition influencing the metabolism of malignancies. We sought to investigate the prognostic value of a novel immune-inflammatory metabolic marker, the monocyte-to-high-density lipoprotein ratio (MHR), in patients with locally advanced pancreatic cancer.MethodsA retrospective analysis was conducted on the clinical data of 118 patients with locally advanced pancreatic cancer and obstructive jaundice who underwent allogeneic vascular replacement pancreaticoduodenectomy in our hospital from Apr. 2011 to Dec. 2023. To assess the predictive capacity of immune-inflammatory metabolic marker, we utilized the area under the receiver operating characteristic curve (AUC-ROC) and assessed the predictive potential of MHR in forecasting outcomes through both univariate and multivariate Cox proportional hazard analyses.ResultsThe area under AUC for MHR in predicting 1-year postoperative survival was 0.714, with an optimal cutoff value of 1.184, yielding a sensitivity of 78.9% and specificity of 66.2%. Based on this cutoff value, patients were divided into a low MHR group (MHR ≤1.184, n = 61) and a high MHR group (MHR >1.184, n = 57). The median survival times for the low and high MHR groups were 27.0 months and 12.0 months, respectively (χ2 = 30.575, p < 0.001), and the median DFS were 18.0 months and 8.0 months, respectively (χ2 = 26.330, p < 0.001). Univariate and multivariate analyses indicated that preoperative MHR, preoperative creatinine, operation duration, and TNM stage were independent predictors of postoperative mortality, while preoperative MHR, preoperative creatinine, and TNM stage were independent predictors of postoperative recurrence risk.ConclusionMHR, as an independent immune-inflammatory metabolic predictor of OS and DFS in patients with advanced PC after pancreaticoduodenectomy. Early monitoring and reduction of MHR may be of great significance in improving prognosis.

IntroductionAir pollution is a significant contributor to morbidity and mortality globally and has been linked to an increased risk of dementia. Previous studies within the Betula cohort in Northern Sweden have demonstrated associations between air pollution and dementia, as well as distinctive metabolomic profiles in dementia patients compared to controls. This study aimed to investigate whether air pollution is associated with quantitative changes in metabolite levels within this cohort, and whether future dementia status would modify this association.MethodsBoth short-term and long-term exposure to air pollution were evaluated using high spatial resolution models and measured data. Air pollution from vehicle exhaust and woodsmoke were analyzed separately. Metabolomic profiling was conducted on 321 participants, including 58 serum samples from dementia patients and a control group matched for age, sex, and education level, using nuclear magnetic resonance spectroscopy.ResultsNo statistically significant associations were found between any metabolites and any measures of short-term or long-term exposure to air pollution. However, there were trends potentially suggesting associations between both long-term and short-term exposure to air pollution with lactate and glucose metabolites. Notably, these associations were observed despite the lack of correlation between long-term and short-term air pollution exposure in this cohort. There were also tendencies for associations between air pollution from woodsmoke to be more pronounced in participants that would later develop dementia, suggesting a potential effect depending on urban/rural factors.DiscussionWhile no significant associations were found, the trends observed in the data suggest potential links between air pollution exposure and changes in lactate and glucose metabolites. These findings provide some new insights into the link between air pollution and metabolic markers in a low-exposure setting. However, addressing existing limitations is crucial to improve the robustness and applicability of future research in this area. The pronounced associations in participants who later developed dementia may indicate an influence of urban/rural factors, warranting further investigation.

Objectives: Evidence on the link between long-term ambient particulate matter (PM) exposures and childhood sleep disorders were scarce. We examined the associations between long-term exposures to PM2.5 and PM1 (PM with an aerodynamic equivalent diameter