Retrospective analysis of predictive factors for AVF dysfunction in patients undergoing MHD.

To construct an early clinical prediction model for AVF dysfunction in patients undergoing Maintenance Hemodialysis (MHD) and perform internal and external verifications. We retrospectively examined clinical data from 150 patients diagnosed with MHD at Hefei Third People's Hospital from January 2014 to June 2023. Depending on arteriovenous fistula (AVF) functionality, patients were categorized into dysfunctional (n = 62) and functional (n = 88) cohorts. Using the least absolute shrinkage and selection operator(LASSO) regression model, variables potentially influencing AVF functionality were filtered using selected variables that underwent multifactorial logistic regression analysis. The Nomogram model was constructed using the R software, and the Area Under Curve(AUC) value was calculated. The model's accuracy was appraised through the calibration curve and Hosmer-Lemeshow test, with the model undergoing internal validation using the bootstrap method. There were 11 factors exhibiting differences between the group of patients with AVF dysfunction and the group with normal AVF function, including age, sex, course of renal failure, diabetes, hyperlipidemia, Platelet count (PLT), Calcium (Ca), Phosphorus, D-dimer (D-D), Fibrinogen (Fib), and Anastomotic width. These identified factors are included as candidate predictive variables in the LASSO regression analysis. LASSO regression identified age, sex, diabetes, hyperlipidemia, anastomotic diameter, blood phosphorus, and serum D-D levels as 7 predictive factors. Unconditional binary logistic regression analysis revealed that advanced age (OR = 4.358, 95% CI: 1.454-13.062), diabetes (OR = 4.158, 95% CI: 1.243-13.907), hyperlipidemia (OR = 3.651, 95% CI: 1.066-12.499), D-D (OR = 1.311, 95% CI: 1.063-1.616), and hyperphosphatemia (OR = 4.986, 95% CI: 2.513-9.892) emerged as independent risk factors for AVF dysfunction in MHD patients. The AUC of the predictive model was 0.934 (95% CI: 0.897-0.971). The Hosmer-Lemeshow test showed high consistency between the model's predictive results and actual clinical observations (χ2 = 1.553, P = .092). Internal validation revealed an AUC of 0.911 (95% CI: 0.866-0.956), with the Calibration calibration curve nearing the ideal curve. Advanced age, coexisting diabetes, hyperlipidemia, blood D-D levels, and hyperphosphatemia are independent risk factors for AVF dysfunction in patients undergoing MHD.

Developmental pleiotropy of SDP1 from seedling to mature stages in B. napus.

Rapeseed, an important oil crop, relies on robust seedling emergence for optimal yields. Seedling emergence in the field is vulnerable to various factors, among which inadequate self-supply of energy is crucial to limiting seedling growth in early stage. SUGAR-DEPENDENT1 (SDP1) initiates triacylglycerol (TAG) degradation, yet its detailed function has not been determined in B. napus. Here, we focused on the effects of plant growth during whole growth stages and energy mobilization during seedling establishment by mutation in BnSDP1. Protein sequence alignment and haplotypic analysis revealed the conservation of SDP1 among species, with a favorable haplotype enhancing oil content. Investigation of agronomic traits indicated bnsdp1 had a minor impact on vegetative growth and no obvious developmental defects when compared with wild type (WT) across growth stages. The seed oil content was improved by 2.0-2.37% in bnsdp1 lines, with slight reductions in silique length and seed number per silique. Furthermore, bnsdp1 resulted in lower seedling emergence, characterized by a shrunken hypocotyl and poor photosynthetic capacity in the early stages. Additionally, impaired seedling growth, especially in yellow seedlings, was not fully rescued in medium supplemented with exogenous sucrose. The limited lipid turnover in bnsdp1 was accompanied by induced amino acid degradation and PPDK-dependent gluconeogenesis pathway. Analysis of the metabolites in cotyledons revealed active amino acid metabolism and suppressed lipid degradation, consistent with the RNA-seq results. Finally, we proposed strategies for applying BnSDP1 in molecular breeding. Our study provides theoretical guidance for understanding trade-off between oil accumulation and seedling energy mobilization in B. napus.

Identification and bioinformatics analysis of lncRNAs in serum of patients with ankylosing spondylitis.

OBJECTIVES: The aim of this study was to explore the long non-coding RNA (lncRNA) expression profiles in serum of patients with ankylosing spondylitis (AS). The role of these lncRNAs in this complex autoimmune situation needs to be evaluated. METHODS: We used high-throughput whole-transcriptome sequencing to generate sequencing data from three patients with AS and three normal controls (NC). Then, we performed bioinformatics analyses to identify the functional and biological processes associated with differentially expressed lncRNAs (DElncRNAs). We confirmed the validity of our RNA-seq data by assessing the expression of eight lncRNAs via quantitative reverse transcription polymerase chain reaction (qRT-PCR) in 20 AS and 20 NC samples. We measured the correlation between the expression levels of lncRNAs and patient clinical index values using the Spearman correlation test. RESULTS: We identified 72 significantly upregulated and 73 significantly downregulated lncRNAs in AS patients compared to NC. qRT-PCR was performed to validate the expression of selected DElncRNAs; the results demonstrated that the expression levels of MALAT1:24, NBR2:9, lnc-DLK1-35:13, lnc-LARP1-1:1, lnc-AIPL1-1:7, and lnc-SLC12A7-1:16 were consistent with the sequencing analysis results. Enrichment analysis showed that DElncRNAs mainly participated in the immune and inflammatory responses pathways, such as regulation of protein ubiquitination, major histocompatibility complex class I-mediated antigen processing and presentation, MAPkinase activation, and interleukin-17 signaling pathways. In addition, a competing endogenous RNA network was constructed to determine the interaction among the lncRNAs, microRNAs, and mRNAs based on the confirmed lncRNAs (MALAT1:24 and NBR2:9). We further found the expression of MALAT1:24 and NBR2:9 to be positively correlated with disease severity. CONCLUSION: Taken together, our study presents a comprehensive overview of lncRNAs in the serum of AS patients, thereby contributing novel perspectives on the underlying pathogenic mechanisms of this condition. In addition, our study predicted MALAT1 has the potential to be deeply involved in the pathogenesis of AS.

Looking Beyond Mortality Prediction: Primary Care Physician Views of Patients' Palliative Care Needs Predicted by a Machine Learning Tool.

OBJECTIVE: To assess primary care physicians' (PCPs) perception of the need for serious illness conversations (SIC) or other palliative care interventions in patients flagged by a machine learning tool for high one-year mortality risk. MATERIALS AND METHODS: We surveyed PCPs from four Brigham and Women's Hospital primary care practice sites. Multiple mortality prediction algorithms were ensembled to assess adult patients of these PCPs who were either enrolled in the hospital's integrated care management program or had one of several chronic conditions. The patients were classified as high or low-risk of one-year mortality. A blinded survey had PCPs evaluate these patients for palliative care needs. We measured PCP and machine learning tool agreement regarding patients' need for an SIC/elevated risk of mortality. RESULTS: Of 66 PCPs, 20 (30.3%) participated in the survey. Out of 312 patients evaluated, 60.6% were female, with a mean (SD) age of 69.3 (17.5) years, and a mean (SD) Charlson comorbidity index of 2.80 (2.89). The machine learning tool identified 162 (51.9%) patients as high-risk. Excluding deceased or unfamiliar patients, PCPs felt that an SIC was appropriate for 179 patients; the machine learning tool flagged 123 of these patients as high-risk (68.7% concordance). For 105 patients whom PCPs deemed SIC-unnecessary, the tool classified 83 as low-risk (79.1% concordance). There was substantial agreement between PCPs and the tool (Gwet's agreement coefficient of 0.640). CONCLUSIONS AND RELEVANCE: A machine learning mortality prediction tool offers promise as a clinical decision aid, helping clinicians pinpoint patients needing palliative care interventions.

QDPR deficiency drives immune suppression in pancreatic cancer.

The relevance of biopterin metabolism in resistance to immune checkpoint blockade (ICB) therapy remains unknown. We demonstrate that the deficiency of quinoid dihydropteridine reductase (QDPR), a critical enzyme regulating biopterin metabolism, causes metabolite dihydrobiopterin (BH2) accumulation and decreases the ratio of tetrahydrobiopterin (BH4) to BH2 in pancreatic ductal adenocarcinomas (PDACs). The reduced BH4/BH2 ratio leads to an increase in reactive oxygen species (ROS) generation and a decrease in the distribution of H3K27me3 at CXCL1 promoter. Consequently, myeloid-derived suppressor cells are recruited to tumor microenvironment via CXCR2 causing resistance to ICB therapy. We discovered that BH4 supplementation is capable to restore the BH4/BH2 ratio, enhance anti-tumor immunity, and overcome ICB resistance in QDPR-deficient PDACs. Tumors with lower QDPR expression show decreased responsiveness to ICB therapy. These findings offer a novel strategy for selecting patient and combining therapies to improve the effectiveness of ICB therapy in PDAC.

Enhancing Early Detection of Cognitive Decline in the Elderly through Ensemble of NLP Techniques: A Comparative Study Utilizing Large Language Models in Clinical Notes.

Background: Early detection of cognitive decline in elderly individuals facilitates clinical trial enrollment and timely medical interventions. This study aims to apply, evaluate, and compare advanced natural language processing techniques for identifying signs of cognitive decline in clinical notes. Methods: This study, conducted at Mass General Brigham (MGB), Boston, MA, included clinical notes from the 4 years prior to initial mild cognitive impairment (MCI) diagnosis in 2019 for patients ≥ 50 years. Note sections regarding cognitive decline were labeled manually. A random sample of 4,949 note sections filtered with cognitive functions-related keywords were used for traditional AI model development, and 200 random subset were used for LLM and prompt development; another random sample of 1996 note sections without keyword filtering were used for testing. Prompt templates for large language models (LLM), Llama 2 on Amazon Web Service and GPT-4 on Microsoft Azure, were developed with multiple prompting approaches to select the optimal LLM-based method. Baseline comparisons were made with XGBoost and a hierarchical attention-based deep neural network model. An ensemble of the three models was then constructed using majority vote. Results: GPT-4 demonstrated superior accuracy and efficiency to Llama 2. The ensemble model outperformed individual models, achieving a precision of 90.3%, recall of 94.2%, and F1-score of 92.2%. Notably, the ensemble model demonstrated a marked improvement in precision (from a 70%-79% range to above 90%) compared to the best performing single model. Error analysis revealed 63 samples were wrongly predicted by at least one model; however, only 2 cases (3.2%) were mutual errors across all models, indicating diverse error profiles among them. Conclusion: Our findings indicate that LLMs and traditional models exhibit diverse error profiles. The ensemble of LLMs and locally trained machine learning models on EHR data was found to be complementary, enhancing performance and improving diagnostic accuracy.

Targeting of vulnerabilities of drug-tolerant persisters identified through functional genetics delays tumor relapse.

Drug-tolerant persisters (DTPs) are a rare subpopulation of cells within a tumor that can survive therapy through nongenetic adaptive mechanisms to develop relapse and repopulate the tumor following drug withdrawal. Using a cancer cell line with an engineered suicide switch to kill proliferating cells, we perform both genetic screens and compound screens to identify the inhibition of bromodomain and extraterminal domain (BET) proteins as a selective vulnerability of DTPs. BET inhibitors are especially detrimental to DTPs that have reentered the cell cycle (DTEPs) in a broad spectrum of cancer types. Mechanistically, BET inhibition induces lethal levels of ROS through the suppression of redox-regulating genes highly expressed in DTPs, including GPX2, ALDH3A1, and MGST1. In vivo BET inhibitor treatment delays tumor relapse in both melanoma and lung cancer. Our study suggests that combining standard of care therapy with BET inhibitors to eliminate residual persister cells is a promising therapeutic strategy.

Unmasking bias in artificial intelligence: a systematic review of bias detection and mitigation strategies in electronic health record-based models.

OBJECTIVES: Leveraging artificial intelligence (AI) in conjunction with electronic health records (EHRs) holds transformative potential to improve healthcare. However, addressing bias in AI, which risks worsening healthcare disparities, cannot be overlooked. This study reviews methods to handle various biases in AI models developed using EHR data. MATERIALS AND METHODS: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, analyzing articles from PubMed, Web of Science, and IEEE published between January 01, 2010 and December 17, 2023. The review identified key biases, outlined strategies for detecting and mitigating bias throughout the AI model development, and analyzed metrics for bias assessment. RESULTS: Of the 450 articles retrieved, 20 met our criteria, revealing 6 major bias types: algorithmic, confounding, implicit, measurement, selection, and temporal. The AI models were primarily developed for predictive tasks, yet none have been deployed in real-world healthcare settings. Five studies concentrated on the detection of implicit and algorithmic biases employing fairness metrics like statistical parity, equal opportunity, and predictive equity. Fifteen studies proposed strategies for mitigating biases, especially targeting implicit and selection biases. These strategies, evaluated through both performance and fairness metrics, predominantly involved data collection and preprocessing techniques like resampling and reweighting. DISCUSSION: This review highlights evolving strategies to mitigate bias in EHR-based AI models, emphasizing the urgent need for both standardized and detailed reporting of the methodologies and systematic real-world testing and evaluation. Such measures are essential for gauging models' practical impact and fostering ethical AI that ensures fairness and equity in healthcare.

Adsorption of humic acid from different organic solid waste compost to phenanthrene, is fluorescence excitation or quenching?

Humic acid (HA) from different organic solid waste (OSW) compost has been shown good adsorption properties for phenanthrene. However, the raw material of HA can affect its structure, resulting in differences in adsorption capacity. Therefore, this study focused on the adsorption characteristics of phenanthrene by HA from different OSW compost. In this work, chicken manure (CM), rice straw (RS) and lawn waste (LW) were selected as sources of composted HA. The adsorption mechanism of HA from different OSW compost were revealed through analytical techniques including three-dimensional fluorescence spectroscopy (EEM), two-dimensional correlation spectroscopy (2DCOS), and Fourier-transform infrared spectroscopy (FTIR). The results suggested that HA from LW compost had a better adsorption affinity for phenanthrene because of its more complex fluorescent component, where C1 as a simple component determined the adsorption process specifically. Furthermore, after HA from LW compost adsorbed phenanthrene, the increase in aromatic -COOH and -NH was the main reason for fluorescence quenching. These results indicated that HA from LW compost had better adsorption effect for phenanthrene. The results of this study were expected to provide a selection scheme for the control of phenanthrene pollution and environmental remediation.

Exploration of the Healthy Donor Effect Among 0.6 Million Blood Donors in China: Longitudinal Study.

BACKGROUND: The World Health Organization emphasizes the importance of completely voluntary blood donation to maintain safe and sustainable blood supplies. However, the benefits of blood donation for donors, such as reducing the risk of disease, remain a topic of debate due to the existence of the healthy donor effect (HDE). This effect arises because of inherent health differences between blood donors and the general population, and it is also considered a methodological issue. OBJECTIVE: This study aims to generate a more detailed health profile of blood donors from a donor cohort study to mitigate and quantify the HDE and properly interpret the association between blood donation and disease outcomes among blood donors. METHODS: A retrospective cohort study was conducted between January 2012 and December 2018 among donors before their first donation. One-to-one propensity score matching was conducted through a random selection of individuals without any history of blood donation, as reported from their electronic health records. We conducted a Poisson regression between blood donors and non-blood donors before the first donation to estimate the adjusted incidence rate ratio (AIRR) of selected blood donation-related diseases, as defined by 13 categories of International Classification of Diseases, Tenth Revision (ICD-10) codes. RESULTS: Of the 0.6 million blood donors, 15,115 had an inpatient record before their first donation, whereas 17,356 non-blood donors had an inpatient record. For the comparison between blood donors and the matched non-blood donors, the HDE (the disease incidence rate ratio between non-blood donors and blood donors) was an AIRR of 1.152 (95% CI 1.127-1.178; P<.001). Among disease categories not recommended for blood donation in China, the strongest HDE was observed in the ICD-10 D50-D89 codes, which pertain to diseases of the blood and blood-forming organs as well as certain disorders involving the immune mechanism (AIRR 3.225, 95% CI 2.402-4.330; P<.001). After age stratification, we found that people who had their first blood donation between 46-55 years old had the strongest HDE (AIRR 1.816, 95% CI 1.707-1.932; P<.001). Both male and female donors had significant HDE (AIRR 1.082, 95% CI 1.05-1.116; P=.003; and AIRR 1.236, 95% CI 1.196-1.277; P<.001, respectively) compared with matched non-blood donors. CONCLUSIONS: : Our research findings suggest that the HDE is present among blood donors, particularly among female donors and those who first donated blood between the ages of 46 and 55 years. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200055983; https://www.chictr.org.cn/showproj.html?proj=51760.

Study on the electrodeposition of uranium in chloride molten salt.

This study focuses on the recovery of UO2 from oxide spent fuel using electrodeposition. U3O8 was used as the initial material and dissolved in NaCl-2CsCl using NH4Cl at high temperatures by means of chlorination reaction. The electrolysis process was conducted using a three-electrode system to investigate the effects of cathode material and diameter, electrolysis temperature, electrolysis time, electrolysis voltage, and uranium concentration in the molten salt on the electrolysis reaction. By optimizing the electrolysis conditions, pure UO2 with a recovery efficiency of 97% was obtained, and the products were characterized using XRD, SEM-EDS, ICP-AES and XPS. It was found that within the scope of this experiment, increasing the cathode diameter, extending the electrolysis time, and increasing the reduction voltage appropriately all led to an improvement in the recovery efficiency of the electrolysis reaction, while other conditions had minimal effect on the reaction. Furthermore, doping of the electrolyte system was performed by adding La, Ce and Nd elements, while the removal of La showed good purification effects, with a maximum decontamination factor of 119. Furthermore, the system showed good purification effects for Nd, with a decontamination factor of 57.

Characteristics of MDR E. coli strains isolated from Pet Dogs with clinic diarrhea: A pool of antibiotic resistance genes and virulence-associated genes.

The increasing number of multi-drug resistant (MDR) bacteria in companion animals poses a threat to both pet treatment and public health. To investigate the characteristics of MDR Escherichia coli (E. coli) from dogs, we detected the antimicrobial resistance (AMR) of 135 E. coli isolates from diarrheal pet dogs by disc diffusion method (K-B method), and screened antibiotic resistance genes (ARGs), virulence-associated genes (VAGs), and population structure (phylogenetic groups and MLST) by polymerase chain reaction (PCR) for 74 MDR strains, then further analyzed the association between AMRs and ARGs or VAGs. Our results showed that 135 isolates exhibited high resistance to AMP (71.11%, 96/135), TET (62.22%, 84/135), and SXT (59.26%, 80/135). Additionally, 54.81% (74/135) of the isolates were identified as MDR E. coli. In 74 MDR strains, a total of 12 ARGs in 6 categories and 14 VAGs in 4 categories were observed, of which tetA (95.95%, 71/74) and fimC (100%, 74/74) were the most prevalent. Further analysis of associations between ARGs and AMRs or VAGs in MDR strains revealed 23 significant positive associated pairs were observed between ARGs and AMRs, while only 5 associated pairs were observed between ARGs and VAGs (3 positive associated pairs and 2 negative associated pairs). Results of population structure analysis showed that B2 and D groups were the prevalent phylogroups (90.54%, 67/74), and 74 MDR strains belonged to 42 STs (6 clonal complexes and 23 singletons), of which ST10 was the dominant lineage. Our findings indicated that MDR E. coli from pet dogs carry a high diversity of ARGs and VAGs, and were mostly belong to B2/D groups and ST10. Measures should be taken to prevent the transmission of MDR E. coli between companion animals and humans, as the fecal shedding of MDR E. coli from pet dogs may pose a threat to humans.

Sustainable all-weather CO2 utilization by mimicking natural photosynthesis in a single material.

Solar-driven CO2 conversion into hydrocarbon fuels is a sustainable approach to synchronously alleviating the energy crisis and achieving net CO2 emissions. However, the dependence of the conversion process on solar illumination hinders its practical application due to the intermittent availability of sunlight at night and on cloudy or rainy days. Here, we report a model material of Pt-loaded hexagonal tungsten trioxide (Pt/h-WO3) for decoupling light and dark reaction processes, demonstrating the sustainable CO2 conversion under dark conditions for the first time. In such a material system, hydrogen atoms can be produced by photocatalytic water splitting under solar illumination, stored together with electrons in the h-WO3 through the transition of W6+ to W5+ and spontaneously released to trigger catalytic CO2 reduction under dark conditions. Furthermore, we demonstrate using natural light that CH4 production can persist at night and on rainy days, proving the accomplishment of all-weather CO2 conversion via a sustainable way.

MiR-134-3p targets HMOX1 to inhibit ferroptosis in granulosa cells of sheep follicles.

BACKGROUND: The intricate interplay of gene expression within ovarian granulosa cells (GCs) is not fully understood. This study aimed to investigate the miRNA regulatory mechanisms of ferroptosis during the process of follicle development in lamb GCs. METHODS: Employing transcriptome sequencing, we compared differentially expressed mRNAs (DE-mRNAs) and miRNAs (DE-miRNAs) in GCs from lambs treated with follicle-stimulating hormone (FL) to untreated controls (CL). We further screened differentially expressed ferroptosis-related genes and identified potential miRNA regulatory factors. The expression patterns of HMOX1 and miRNAs in GCs were validated using qRT‒PCR and Western blotting. Additionally, we investigated the regulatory effect of oar-miR-134-3p on HMOX1 and its function in ferroptosis through cell transfection and erastin treatment. RESULTS: We identified a total of 4,184 DE-mRNAs and 304 DE-miRNAs. The DE-mRNAs were mainly enriched in ferroptosis, insulin resistance, and the cell cycle. Specifically, we focused on the differential expression of ferroptosis-related genes. Notably, the ferroptosis-related genes HMOX1 and SLC3A2, modulated by DE-miRNAs, were markedly suppressed in FLs. Experimental validation revealed that HMOX1 was significantly downregulated in FL and large follicles, while oar-miR-134-3p was significantly upregulated compared to that in the CLs. HMOX1 expression was regulated by the targeting effect of oar-miR-134-3p. Functional assays further revealed that modulation of oar-miR-134-3p influenced HMOX1 expression and altered cellular responses to ferroptosis induction by erastin. CONCLUSION: This study suggested that oar-miR-134-3p and HMOX1 may be one of the pathways regulating ferroptosis in GCs. This finding provides new clues to understanding the development and regulatory process of follicles.

Angiotensin-(1-9) attenuates adriamycin-induced cardiomyopathy in rats via the angiotensin type 2 receptor.

Adriamycin (ADR) causes irreversible damage to the heart, leading to ADR-induced cardiomyopathy (ACM). Angiotensin-(1-9) [Ang-(1-9)] is a peptide from the counter-regulatory renin-angiotensin system, but the effects on ACM is unclear. Our study was aimed to explore the effects and underlying molecular mechanisms of Ang-(1-9) against ACM in Wistar rats. Rats were injected intraperitoneally with ADR via six equal doses (each containing 2.5 mg/kg) within a period of 2 weeks to induce ACM. After 2 weeks of ADR treatment, the rats were treated with Ang-(1-9) (200 ng/kg/min) or angiotensin type 2 receptor (AT2R) antagonist PD123319 (100 ng/kg/min) for 4 weeks. Although Ang-(1-9) treatment did not influence blood pressure, it significantly improved left ventricular function and remodeling in ADR-treated rats, by inhibiting collagen deposition, the expression of TGF-ß1, inflammatory response, cardiomyocyte apoptosis and oxidative stress. Moreover, Ang-(1-9) reduced ERK1/2 and P38 MAPK phosphorylation. The therapeutic effects of Ang-(1-9) were blocked by the AT2R antagonist PD123319, which also offset the down-regulation protein expression of pERK1/2 and pP38 MAPK induced by Ang-(1-9). These data suggest that Ang-(1-9) improved left ventricular function and remodeling in ADR-treated rats by an AT2R/ ERK1/2 and P38 MAPK-dependent mechanism. Thus, the Ang-(1-9)/AT2R axis may provide a novel and promising target to the prevention and treatment of ACM.

Caesalpinflavans D-F and caesalpinnone B, hybrid flavan-chalcones and normonoterpene-chalcone heterodimer from Caesalpinia digyna.

Three undescribed hybrid flavan-chalcones, caesalpinflavans D-F, and an unreported normonoterpene-chalcone heterodimer, caesalpinnone B, along with three known biflavonoids were isolated from the twigs and leaves of Caesalpinia digyna. Their structures were elucidated based on extensive spectroscopic analysis and quantum chemical calculations. Caesalpinflavan F was identified as a bis-(hybrid flavan-chalcone), its natural occurrence was supported by HPLC-IT-TOF-MS analysis. The condensation of caesalpinflavan B with acetone was possibly a key step in the biosynthesis of caesalpinflavan F. Caesalpinnone B represents an unprecedented meroterpenoid featuring a cyclobutane central framework, which was derived from chalcone and normonoterpenoid via a key [2 + 2] cyclization reaction. Biological evaluation revealed that compounds caesalpinflavan D, oxytrodiflavanone A, and caesalpinnone B exhibited moderate cytotoxicity against HL-60, SMMC-7721, SW480, A-549 and/or MDA-MB-231 cell lines with IC50 values ranging from 8.051 ± 0.673 to 24.26 ± 0.61 µM. This study provided evidence for further research and possible utilization of C. digyna in the future.

Magnetic resonance imaging on brain structure and function changes in diabetic peripheral neuropathy.

With the significant increase in the global prevalence of diabetes mellitus (DM), the occurrence of diabetic peripheral neuropathy (DPN) has become increasingly common complication associated with DM. It is particularly in the peripheral nerves of the hands, legs, and feet. DPN can lead to various adverse consequences that greatly affect the quality of life for individuals with DM. Despite the profound impact of DPN, the specific mechanisms underlying its development and progression are still not well understood. Advancements in magnetic resonance imaging (MRI) technology have provided valuable tools for investigating the central mechanisms involved in DPN. Structural and functional MRI techniques have emerged as important methods for studying the brain structures and functions associated with DPN. Voxel-based morphometry allows researchers to assess changes in the volume and density of different brain regions, providing insights into potential structural alterations related to DPN. Functional MRI investigates brain activity patterns, helping elucidate the neural networks engaged during sensory processing and pain perception in DPN patients. Lastly, magnetic resonance spectroscopy provides information about the neurochemical composition of specific brain regions, shedding light on potential metabolic changes associated with DPN. By synthesizing available literature employing these MRI techniques, this study aims to enhance our understanding of the neural mechanisms underlying DPN and contribute to the improvement of clinical diagnosis.

Retrospective cohort study of neonatal blood transfusion in China.

BACKGROUND: Blood transfusion therapy is extremely important for certain neonatal diseases, but the threshold for neonatal blood transfusion is not the same in different countries. Until now, clinical studies to determine the suitable threshold for newborns in China are lacking. Therefore, it is of high importance to establish a multi-center cohort study to explore appropriate transfusion thresholds for newborns in China. METHODS: This retrospective cohort study investigated neonatal blood transfusion therapy administered from January 1, 2017 to June 30, 2018, with the aim of evaluating the effect of restricted and nonrestricted blood transfusion on neonatal health. The subjects were enrolled in 46 hospitals in China. A total of 5669 neonatal cases were included in the study. Clinical diagnosis and transfusion treatment of these neonates were collected and the data were retrospectively analyzed. The neonates were followed up 1 week and 1 month after leaving the hospital. The newborns' and their mothers' data were collected containing 280 variables in the database. The primary outcome of the study was mortality, and the secondary outcomes were complications, hospital stays, NICU hospital stays and hospital costs. RESULTS: Results from the < 1500 g group showed that there was a higher mortality rate in the restricted transfusion group (11.41%) when compared with the non-restricted transfusion group (5.12%) (P = 0.000). Among the secondary outcomes, the restricted transfusion group had fewer costs. Results from the 1500-2500 g group showed that the mortality rates of the restricted and non-restricted transfusion groups were 3.53% and 4.71%, respectively, however there was no statistical significance between the two groups (P = 0.345). Among the secondary outcomes, the restricted transfusion group had fewer hospital stays, NICU hospital stays and hospital costs. The incidence of necrotizing enterocolitis was lower in the restricted transfusion group (OR, 2.626; 95% confidence interval [CI], 1.445 to 4.773; P = 0.003). The results from the ≥ 2500 g restricted transfusion group suggested that the mortality rate of (3.02%) was significantly lower than that of non-restricted transfusion group (9.55%) (P = 0.000). Among the secondary outcomes, the restricted transfusion group had fewer hospital stays and hospital costs. The incidence of retinopathy of prematurity was lower in the restricted transfusion group (OR, 4.624; 95% confidence interval [CI], 2.32 to 9.216; P = 0.000). CONCLUSIONS: Current transfusion protocols for newborns weighing less than 1500 g may be inappropriate and lead to higher mortality. The current transfusion threshold performed better for the other two weight groups.