Effect of propofol and ciprofol on the euphoric reaction in patients with painless gastroscopy: A prospective randomized controlled trial.

Objective: To explore the effects of propofol and ciprofol on patient euphoric reactions during sedation in patients undergoing gastroscopy and to investigate potential factors that may influence euphoric reactions in patients. Methods: A total of 217 patients were randomly divided into two groups: the propofol group (P group, n = 109) and the ciprofol group (C group, n = 108). The patients in the P group were given 2 mg/kg propofol, and those in the C group were given 0.5 mg/kg ciprofol. The patients were assessed using the Addiction Research Center Inventory-Chinese Version (ARCI-CV) to measure euphoric reactions at three time points: preexamination, 30 min after awakening, and 1 week after examination. Anxiety, depression, and sleep status were evaluated using appropriate scales at admission and 1 week after the examination. The dream rate, sedative effects, vital sign dynamics, and adverse reactions were documented during the sedation process. Results: After 30 min of awakening, the P group and C group showed no statistically significant differences in the mean morphine-benzedrine group (MBG) score (8.84 vs. 9.09, P > 0.05), dream rate (42.2 % vs. 40.7 %, P > 0.05), or MBG score one week after the examination (7.04 vs. 7.05, P > 0.05). The regression analysis revealed that sex, dream status, Alcohol Use Disorders Identification Test (AUDIT) score, and examination time had notable impacts on the MBG-30 min score. No statistically significant differences were observed in sedative effects, anxiety, depression, or sleep status between the two groups (P > 0.05). The incidence of injection pain and severe hypotension was significantly lower in the C group (P < 0.05), and hemodynamics and SpO2 were more stable during sedation (P < 0.05). Conclusion: There was no significant difference between propofol and ciprofol in terms of euphoria experienced by patients after sedation in patients undergoing gastroscopy. Ciprofol has demonstrated addictive potential similar to that of propofol, warranting careful attention to its addictive potential during clinical application.

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of risk factor status is provider knowledge-dependent and requires extensive manual chart review by experts. Natural Language Processing (NLP) has shown promise in automated data extraction from the electronic health record (EHR). We aimed to use NLP for automated extraction of PDAC risk factors from unstructured clinical notes in the EHR. METHODS: We first developed rule-based NLP algorithms to extract PDAC risk factors at the document-level, using an annotated corpus of 2091 clinical notes. Next, we further improved the NLP algorithms using a cohort of 1138 patients through patient-level training, validation, and testing, with comparison against a pre-specified reference standard. To minimize false-negative results we prioritized algorithm recall. RESULTS: In the test set (n = 807), the NLP algorithms achieved a recall of 0.933, precision of 0.790, and F1-score of 0.856 for family history of PDAC. For germline genetic mutations, the algorithm had a high recall of 0.851, while precision and F1-score were lower at 0.350 and 0.496 respectively. Most false positives for germline mutations resulted from erroneous recognition of tissue mutations. CONCLUSIONS: Rule-based NLP algorithms applied to unstructured clinical notes are highly sensitive for automated identification of PDAC risk factors. Further validation in a large primary-care patient population is warranted to assess real-world utility in identifying HRIs for pancreatic cancer screening.

Identification of the coexisting virus-derived siRNA in maize and rice infected by rice black-streaked dwarf virus.

Rice black-streaked dwarf virus is transmitted by small brown planthoppers, which causes maize rough dwarf disease and rice black-streaked dwarf disease. This virus leads to slow growth or death of the host plants. During the co-evolutionary arms race between viruses and plants, virus-derived small interfering RNAs challenge the plant's defense response and inhibit host immunity through the RNA silencing system. However, it is currently unknown if rice black-streaked dwarf virus can produce the same small interfering RNAs to mediate the RNA silencing in different infected species. In this study, four small RNA libraries and four degradome libraries were constructed by extracting total RNAs from the leaves of the maize (Zea mays) inbred line B73 and japonica rice (Oryza sativa) variety Nipponbare exposed to feeding by viruliferous and non-viruliferous small brown planthoppers. We analyzed the characteristics of small RNAs and explored virus-derived small interfering RNAs in small RNA libraries through high-throughput sequencing. On analyzing the characteristics of small RNA, we noted that the size distributions of small RNAs were mainly 24-nt (19.74%-62.00%), whereas those of virus-derived small interfering RNAs were mostly 21-nt (41.06%-41.87%) and 22-nt (39.72%-42.26%). The 5'-terminal nucleotides of virus-derived small interfering RNAs tended to be adenine or uracil. Exploring the distribution of virus-derived small interfering RNAs hot spots on the viral genome segments revealed that the frequency of hot spots in B73 was higher than those in Nipponbare. Meanwhile, hotspots in the S9 and S10 virus genome segments were distributed similarly in both hosts. In addition, the target genes of small RNA were explored by degradome sequencing. Analyses of the regulatory pathway of these target genes unveiled that viral infection affected the ribosome-related target genes in maize and target genes in metabolism and biosynthesis pathways in rice. Here, 562 and 703 virus-derived small interfering RNAs were separately obtained in maize and rice, and 73 virus-derived small interfering RNAs named as co-vsiRNAs were detected in both hosts. Stem-loop PCR and RT-qPCR confirmed that co-vsiRNA 3.1 and co-vsiRNA 3.5 derived from genome segment S3 simultaneously play a role in maize and rice and inhibited host gene expression. The study revealed that rice black-streaked dwarf virus can produce the same small interfering RNAs in different species and provides a new direction for developing the new antiviral strategies.

A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

BACKGROUND: Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic factors contributing to their occurrence, and the identification of underlying causes to refine the NLP model and improve its performance. Conducting error analysis can be complex, requiring a combination of NLP expertise and domain-specific knowledge. Due to the high heterogeneity of electronic health record (EHR) settings across different institutions, challenges may arise when attempting to standardize and reproduce the error analysis process. OBJECTIVES: This study aims to facilitate a collaborative effort to establish common definitions and taxonomies for capturing diverse error types, fostering community consensus on error analysis for clinical concept extraction tasks. MATERIALS AND METHODS: We iteratively developed and evaluated an error taxonomy based on existing literature, standards, real-world data, multisite case evaluations, and community feedback. The finalized taxonomy was released in both .dtd and .owl formats at the Open Health Natural Language Processing Consortium. The taxonomy is compatible with several different open-source annotation tools, including MAE, Brat, and MedTator. RESULTS: The resulting error taxonomy comprises 43 distinct error classes, organized into 6 error dimensions and 4 properties, including model type (symbolic and statistical machine learning), evaluation subject (model and human), evaluation level (patient, document, sentence, and concept), and annotation examples. Internal and external evaluations revealed strong variations in error types across methodological approaches, tasks, and EHR settings. Key points emerged from community feedback, including the need to enhancing clarity, generalizability, and usability of the taxonomy, along with dissemination strategies. CONCLUSION: The proposed taxonomy can facilitate the acceleration and standardization of the error analysis process in multi-site settings, thus improving the provenance, interpretability, and portability of NLP models. Future researchers could explore the potential direction of developing automated or semi-automated methods to assist in the classification and standardization of error analysis.

A new strategy based on a cascade amplification strategy biosensor for on-site eDNA detection and outbreak warning of crown-of-thorns starfish.

Population outbreaks of the crown-of-thorns starfish (COTS) seriously threaten the sustainability of coral reef ecosystems. However, traditional ecological monitoring techniques cannot provide early warning before the outbreaks, thus preventing timely intervention. Therefore, there is an urgent need for a more accurate and faster technology to predict the outbreaks of COTS. In this work, we developed an electrochemical biosensor based on a programmed catalytic hairpin assembly (CHA) and hybridization chain reaction (HCR) cyclic amplification strategy for sensitive and selective detection of COTS environmental DNA (eDNA) in water bodies. This biosensor exhibited excellent electrochemical characteristics, including a low limit of detection (LOD = 18.4 fM), low limit of quantification (LOQ = 41.1 fM), and wide linear range (50 fM - 10 nM). The biosensing technology successfully allowed the detection of COTS eDNA in the aquarium environment, and the results also demonstrated a significant correlation between eDNA concentration and COTS number (r = 0.990; P < 0.001). The reliability and accuracy of the biosensor results have been further validated through comparison with digital droplet PCR (ddPCR). Moreover, the applicability and accuracy of the biosensor were reconfirmed in field tests at the COTS outbreak site in the South China Sea, which has shown potential application in dynamically monitoring the larvae before the COTS outbreak. Therefore, this efficient electrochemical biosensing technology offers a new solution for on-site monitoring and early warning of the COTS outbreak.

Tumor cell-intrinsic epigenetic dysregulation shapes cancer-associated fibroblasts heterogeneity to metabolically support pancreatic cancer.

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) involves a significant accumulation of cancer-associated fibroblasts (CAFs) as part of the host response to tumor cells. The origins and functions of transcriptionally diverse CAF populations in PDAC remain poorly understood. Tumor cell-intrinsic genetic mutations and epigenetic dysregulation may reshape the TME; however, their impacts on CAF heterogeneity remain elusive. SETD2, a histone H3K36 trimethyl-transferase, functions as a tumor suppressor. Through single-cell RNA sequencing, we identify a lipid-laden CAF subpopulation marked by ABCA8a in Setd2-deficient pancreatic tumors. Our findings reveal that tumor-intrinsic SETD2 loss unleashes BMP2 signaling via ectopic gain of H3K27Ac, leading to CAFs differentiation toward lipid-rich phenotype. Lipid-laden CAFs then enhance tumor progression by providing lipids for mitochondrial oxidative phosphorylation via ABCA8a transporter. Together, our study links CAF heterogeneity to epigenetic dysregulation in tumor cells, highlighting a previously unappreciated metabolic interaction between CAFs and pancreatic tumor cells.

Differential impact of intermittent versus continuous treatment with clozapine on fatty acid metabolism in the brain of an MK-801-induced mouse model of schizophrenia.

Continuous antipsychotic treatment is often recommended to prevent relapse in schizophrenia. However, the efficacy of antipsychotic treatment appears to diminish in patients with relapsed schizophrenia and the underlying mechanisms are still unknown. Moreover, though the findings are inconclusive, several recent studies suggest that intermittent versus continuous treatment may not significantly differ in recurrence risk and therapeutic efficacy but potentially reduce the drug dose and side effects. Notably, disturbances in fatty acid (FA) metabolism are linked to the onset/relapse of schizophrenia, and patients with multi-episode schizophrenia have been reported to have reduced FA biosynthesis. We thus utilized an MK-801-induced animal model of schizophrenia to evaluate whether two treatment strategies of clozapine would affect drug response and FA metabolism differently in the brain. Schizophrenia-related behaviors were assessed through open field test (OFT) and prepulse inhibition (PPI) test, and FA profiles of prefrontal cortex (PFC) and hippocampus were analyzed by gas chromatography-mass spectrometry. Additionally, we measured gene expression levels of enzymes involved in FA synthesis. Both intermittent and continuous clozapine treatment reversed hypermotion and deficits in PPI in mice. Continuous treatment decreased total polyunsaturated fatty acids (PUFAs), saturated fatty acids (SFAs) and FAs in the PFC, whereas the intermittent administration increased n-6 PUFAs, SFAs and FAs compared to continuous administration. Meanwhile, continuous treatment reduced the expression of Fads1 and Elovl2, while intermittent treatment significantly upregulated them. This study discloses the novel findings that there was no significant difference in clozapine efficacy between continuous and intermittent administration, but intermittent treatment showed certain protective effects on phospholipid metabolism in the PFC.

Changing clinical characteristics of pediatric inpatients with pneumonia during COVID-19 pandamic: a retrospective study.

BACKGROUND: The COVID-19 pandemic have impacts on the prevalence of other pathogens and people's social lifestyle. This study aimed to compare the pathogen, allergen and micronutrient characteristics of pediatric inpatients with pneumonia prior to and during the COVID-19 pandemic in a large tertiary hospital in Shanghai, China. METHODS: Patients with pneumonia admitted to the Department of Pediatric Pulmonology of Xinhua Hospital between March-August 2019 and March-August 2020 were recruited. And clinical characteristics of the patients in 2019 were compared with those in 2020. RESULTS: Hospitalizations for pneumonia decreased by 74% after the COVID-19 pandemic. For pathogens, virus, mycoplasma pneumoniae (MP) and mixed infection rates were all much lower in 2020 than those in 2019 (P < 0.01). Regarding allergens, compared with 2019, the positive rates of house dust mite, shrimp and crab were significantly higher in 2020 (P < 0.01). And for micronutrients, the levels of vitamin B2, B6, C and 25-hydroxyvitamin D (25(OH)D) in 2020 were observed to be significantly lower than those in 2019 (P < 0.05). For all the study participants, longer hospital stay (OR = 1.521, P = 0.000), milk allergy (OR = 6.552, P = 0.033) and calcium (Ca) insufficiency (OR = 12.048, P = 0.019) were identified as high-risk factors for severe pneumonia by multivariate analysis. CONCLUSIONS: The number of children hospitalized with pneumonia and incidence of common pathogen infections were both reduced, and that allergy and micronutrient status in children were also changed after the outbreak of the COVID-19 pandemic.

A web-based dynamic predictive model for postoperative nausea and vomiting in patient receiving gynecological laparoscopic surgery.

OBJECTIVE: The aim of this study was to develop a web-based dynamic prediction model for postoperative nausea and vomiting (PONV) in patients undergoing gynecologic laparoscopic surgery. METHODS: The patients (N = 647) undergoing gynecologic laparoscopic surgery were included in this observational study. The candidate risk-factors related to PONV were included through literature search. Lasso regression was utilized to screen candidate risk-factors, and the variables with statistical significance were selected in multivariable logistic model building. The web-based dynamic Nomogram was used for model exhibition. Accuracy and validity of the experimental model (EM) were evaluated by generating receiver operating characteristic (ROC) curves and calibration curves. Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model. Decision curve analysis (DCA) was used to evaluate the clinical practicability of the risk prediction model. RESULTS: Ultimately, a total of five predictors including patient-controlled analgesia (odds ratio [OR], 4.78; 95% confidence interval [CI], 1.98-12.44), motion sickness (OR, 4.80; 95% CI, 2.71-8.65), variation of blood pressure (OR, 4.30; 95% CI, 2.41-7.91), pregnancy vomiting history (OR, 2.21; 95% CI, 1.44-3.43), and pain response (OR, 1.64; 95% CI, 1.48-1.83) were selected in model building. Assessment of the model indicates the discriminating power of EM was adequate (ROC-areas under the curve, 93.0%; 95% CI, 90.7%-95.3%). EM showed better accuracy and goodness of fit based on the results of the calibration curve. The DCA curve of EM showed favorable clinical benefits. CONCLUSIONS: This dynamic prediction model can determine the PONV risk in patients undergoing gynecologic laparoscopic surgery.

Genome-wide CRISPR screens identify PKMYT1 as a therapeutic target in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with an overall 5-year survival rate of <12% due to the lack of effective treatments. Novel treatment strategies are urgently needed. Here, PKMYT1 is identified through genome-wide CRISPR screens as a non-mutant, genetic vulnerability of PDAC. Higher PKMYT1 expression levels indicate poor prognosis in PDAC patients. PKMYT1 ablation inhibits tumor growth and proliferation in vitro and in vivo by regulating cell cycle progression and inducing apoptosis. Moreover, pharmacological inhibition of PKMYT1 shows efficacy in multiple PDAC cell models and effectively induces tumor regression without overt toxicity in PDAC cell line-derived xenograft and in more clinically relevant patient-derived xenograft models. Mechanistically, in addition to its canonical function of phosphorylating CDK1, PKMYT1 functions as an oncogene to promote PDAC tumorigenesis by regulating PLK1 expression and phosphorylation. Finally, TP53 function and PRKDC activation are shown to modulate the sensitivity to PKMYT1 inhibition. These results define PKMYT1 dependency in PDAC and identify potential therapeutic strategies for clinical translation.

GmTCP40 Promotes Soybean Flowering under Long-Day Conditions by Binding to the GmAP1a Promoter and Upregulating Its Expression.

Soybean [Glycine max (L.) Merr.] is a short-day (SD) plant that is sensitive to photoperiod, which influences flowering, maturity, and even adaptation. TEOSINTE-BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factors have been shown to regulate photoperiodic flowering. However, the roles of TCPs in SD plants such as soybean, rice, and maize remain largely unknown. In this study, we cloned the GmTCP40 gene from soybean and investigated its expression pattern and function. Compared with wild-type (WT) plants, GmTCP40-overexpression plants flowered earlier under long-day (LD) conditions but not under SD conditions. Consistent with this, the overexpression lines showed upregulation of the flowering-related genes GmFT2a, GmFT2b, GmFT5a, GmFT6, GmAP1a, GmAP1b, GmAP1c, GmSOC1a, GmSOC1b, GmFULa, and GmAG under LD conditions. Further investigation revealed that GmTCP40 binds to the GmAP1a promoter and promotes its expression. Analysis of the GmTCP40 haplotypes and phenotypes of soybean accessions demonstrated that one GmTCP40 haplotype (Hap6) may contribute to delayed flowering at low latitudes. Taken together, our findings provide preliminary insights into the regulation of flowering time by GmTCP40 while laying a foundation for future research on other members of the GmTCP family and for efforts to enhance soybean adaptability.

African swine fever virus A137R protein inhibits NF-κB activation via suppression of MyD88 signaling in PK15 and 3D4/21 cells in vitro.

African swine fever (ASF) is an infectious disease with high mortality caused by African swine fever virus (ASFV), which poses a great threat to the global swine industry. ASFV has evolved multiple strategies to evade host antiviral innate immunity by perturbing inflammatory responses and interferon production. However, the molecular mechanisms underlying manipulation of inflammatory responses by ASFV proteins are not fully understood. Here, we report that A137R protein of ASFV is a key suppressor of host inflammatory responses. Ectopic expression of ASFV A137R in HEK293T cells significantly inhibited the activation of IL-8 and NF-κB promoters triggered by Sendai virus (SeV), influenza A virus (IAV), or vesicular stomatitis virus (VSV). Accordingly, forced A137R expression caused a significant decrease in the production of several inflammatory cytokines such as IL-8, IL-6 and TNF-α in the cells infected with SeV or IAV. Similar results were obtained from experiments using A137R overexpressing PK15 and 3D4/21 cells infected with SeV or VSV. Furthermore, we observed that A137R impaired the activation of MAPK and NF-κB signaling pathways, as enhanced expression of A137R significantly decreased the phosphorylation of JNK, p38 and p65 respectively upon viral infection (SeV or IAV) and IL-1ß treatment. Mechanistically, we found that A137R interacted with MyD88, and dampened MyD88-mediated activation of MAPK and NF-κB signaling. Together, these findings uncover a critical role of A137R in restraining host inflammatory responses, and improve our understanding of complicated mechanisms whereby ASFV evades innate immunity.

Ultrastiff metamaterials generated through a multilayer strategy and topology optimization.

Metamaterials composed of different geometrical primitives have different properties. Corresponding to the fundamental geometrical forms of line, plane, and surface, beam-, plate-, and shell-based lattice metamaterials enjoy many advantages in many aspects, respectively. To fully exploit the advantages of each structural archetype, we propose a multilayer strategy and topology optimization technique to design lattice metamaterial in this study. Under the frame of the multilayer strategy, the design space is enlarged and diversified, and the design freedom is increased. Topology optimization is applied to explore better designs in the larger and diverse design space. Beam-plate-shell-combined metamaterials automatically emerge from the optimization to achieve ultrahigh stiffness. Benefiting from high stiffness, energy absorption performances of optimized results also demonstrate substantial improvements under large geometrical deformation. The multilayer strategy and topology optimization can also bring a series of tunable dimensions for lattice design, which helps achieve desired mechanical properties, such as isotropic elasticity and functionally grading material property, and superior performances in acoustic tuning, electrostatic shielding, and fluid field tuning. We envision that a broad array of synthetic and composite metamaterials with unprecedented performance can be designed with the multilayer strategy and topology optimization.

Effect of S-Ketamine on Postoperative Nausea and Vomiting in Patients Undergoing Video-Assisted Thoracic Surgery: A Randomized Controlled Trial.

Purpose: Postoperative nausea and vomiting (PONV) frequently occur in patients after surgery. In this study, the authors investigated whether perioperative S-ketamine infusion could decrease the incidence of PONV in patients undergoing video-assisted thoracoscopic surgery (VATS) lobectomy. Patients and Methods: This prospective, randomized, double-blinded, controlled study was conducted a total of 420 patients from September 2021 to May 2023 at Xuzhou Central Hospital in China, who underwent elective VATS lobectomy under general anesthesia with tracheal intubation. The patients were randomly assigned to either the S-ketamine group or the control group. The S-ketamine group received a bolus injection of 0.5 mg/kg S-ketamine and an intraoperative continuous infusion of S-ketamine at a rate of 0.25 mg/kg/h. The control group received an equivalent volume of saline. All patients were equipped with patient-controlled intravenous analgesia (PCIA), with a continuous infusion rate of 0.03 mg/kg/h S-ketamine in the S-ketamine group or 0.03 µg/kg/h sufentanil in the control group. The primary outcome was the incidence of PONV. Secondary outcomes included perioperative opioid consumption, hemodynamics, postoperative pain, and adverse events. Results: The incidence of PONV in the S-ketamine group (9.7%) was significantly lower than in the control group (30.5%). Analysis of perioperative opioid usage revealed that remifentanil usage was 40.0% lower in the S-ketamine group compared to the control group (1414.8 µg vs 2358.2 µg), while sufentanil consumption was 75.2% lower (33.1 µg vs 133.6 µg). The S-ketamine group demonstrated better maintenance of hemodynamic stability. Additionally, the visual analogue scale (VAS) scores on postoperative day 1 (POD-1) and postoperative day 3 (POD-3) were significantly lower in the S-ketamine group. Finally, no statistically significant difference in other postoperative adverse reactions was observed between the two groups. Conclusion: The results of this trial indicate that perioperative S-ketamine infusion can effectively reduce the incidence of PONV in patients undergoing VATS lobectomy.

Exploring the molecular mechanisms and shared gene signatures between celiac disease and ulcerative colitis based on bulk RNA and single-cell sequencing: Experimental verification.

Many immune-mediated diseases have the common genetic basis, as an autoimmune disorder, celiac disease (CeD) primarily affects the small intestine, and is caused by the ingestion of gluten in genetically susceptible individuals. As for ulcerative colitis (UC), which most likely involves a complex interplay between some components of the commensal microbiota and other environmental factors in its origin. These two autoimmune diseases share a specific target organ, the bowel. The etiology and immunopathogenesis of both conditions characterized by chronic intestinal inflammation, ulcerative colitis and celiac disease, are not completely understood. Both are complex diseases with genetics and the environmental factors contributing to dysregulation of innate and adaptive immune responses, leading to chronic inflammation and disease. This study is designed to further clarify the relationship between UC and CeD. The GEO database was used to download gene expression profiles for CeD (GSE112102) and UC (GSE75214). The GSEA KEGG pathway analysis revealed that immune-related pathways were significantly associated with both diseases. Further, we screened 187 shared differentially expressed genes (DEGs) of the two diseases. Gene Ontology (GO) and WikiPathways were carried out to perform the biological process and pathway enrichment analysis. Subsequently, based on the DEGs, the least absolute shrinkage and selection operator (LASSO) analysis was performed to screen for the diagnostic biomarkers of the diseases. Moreover, single-cell RNA-sequencing (RNA-seq) data from five colonic propria with UC showed that REG4 expression was present in Goblet cell, Enteroendocrine cell, and Epithelial. Finally, our work identified REG4 is the shared gene of UC and CeD via external data validation, cellular experiments, and immunohistochemistry. In conclusion, our study elucidated that abnormal immune response could be the common pathogenesis of UC and CeD, and REG4 might be a key potential biomarker and therapeutic target for the comorbidity of these two diseases.

Identification and bioactivity evaluation of ring-opening and lactone forms of enterolactone from sheep fed flaxseed cake.

The previously undescribed lactone ring-opening enterolactone and its sulphate were purified along with the lactone counterparts from the urine of dairy sheep fed flaxseed cake. The structures were determined by NMR and MS analyses. The ring-opening and lactone forms underwent mutual transformation with changes in pH and milk could protect the lactone form. Enterolactone exhibited more effective anti-proliferation activity on MDA-MB-231 breast cancer cells than its ring-opening counterpart, while the ring-opening enterolactone demonstrated more effective anti-osteoporosis activity than the lactone form. The results indicated the potential for targeting biological functions through pH and medium manipulation.

FedFSA: Hybrid and federated framework for functional status ascertainment across institutions.

INTRODUCTION: Patients' functional status assesses their independence in performing activities of daily living, including basic ADLs (bADL), and more complex instrumental activities (iADL). Existing studies have discovered that patients' functional status is a strong predictor of health outcomes, particularly in older adults. Depite their usefulness, much of the functional status information is stored in electronic health records (EHRs) in either semi-structured or free text formats. This indicates the pressing need to leverage computational approaches such as natural language processing (NLP) to accelerate the curation of functional status information. In this study, we introduced FedFSA, a hybrid and federated NLP framework designed to extract functional status information from EHRs across multiple healthcare institutions. METHODS: FedFSA consists of four major components: 1) individual sites (clients) with their private local data, 2) a rule-based information extraction (IE) framework for ADL extraction, 3) a BERT model for functional status impairment classification, and 4) a concept normalizer. The framework was implemented using the OHNLP Backbone for rule-based IE and open-source Flower and PyTorch library for federated BERT components. For gold standard data generation, we carried out corpus annotation to identify functional status-related expressions based on ICF definitions. Four healthcare institutions were included in the study. To assess FedFSA, we evaluated the performance of category- and institution-specific ADL extraction across different experimental designs. RESULTS: ADL extraction performance ranges from an F1-score of 0.907 to 0.986 for bADL and 0.825 to 0.951 for iADL across the four healthcare sites. The performance for ADL extraction with impairment ranges from an F1-score of 0.722 to 0.954 for bADL and 0.674 to 0.813 for iADL across four healthcare sites. For category-specific ADL extraction, laundry and transferring yielded relatively high performance, while dressing, medication, bathing, and continence achieved moderate-high performance. Conversely, food preparation and toileting showed low performance. CONCLUSION: NLP performance varied across ADL categories and healthcare sites. Federated learning using a FedFSA framework performed higher than non-federated learning for impaired ADL extraction at all healthcare sites. Our study demonstrated the potential of the federated learning framework in functional status extraction and impairment classification in EHRs, exemplifying the importance of a large-scale, multi-institutional collaborative development effort.

A novel biosensing strategy on the dynamic and on-site detection of Vibrio coralliilyticus eDNA for coral health warnings.

Heat stress and coral diseases are the predominant factors causing the degradation of coral reef ecosystems. Over recent years, Vibrio coralliilyticus was identified as a temperature-dependent pathogen causing tissue lysis in Pocillopora damicornis and one of the primary pathogens causing bleaching and mortality in other corals. Yet current detection techniques for V. coralliilyticus rely primarily on qPCR and ddPCR, which cannot meet the requirements for non-invasive and real-time detection. Herein, we developed an effective electrochemical biosensor modified by an Au-MoS2/rGO (AMG) nanocomposites and a specific capture probe to dynamically detect V. coralliilyticus environment DNA (eDNA) in aquarium experiments, with a lower limit of detection (0.28 fM) for synthetic DNA and a lower limit of quantification (9.8 fg/µL, ∼0.86 copies/µL) for genomic DNA. Its reliability and accuracy were verified by comparison with the ddPCR method (P > 0.05). Notably, coral tissue started to lyse at only 29 °C when the concentration of V. coralliilyticus increased abruptly to 880 copies/µL, indicating the biosensor could reflect the types of pathogen and health risks of corals under heat stress. Overall, the novel and reliable electrochemical biosensing technology provides an efficient strategy for the on-site monitoring and early warning of coral health in the context of global warming.

Effects of atmospheric particulate pollution on lung function of athletes.

There is a knowledge gap on how ground-level particulate pollution affects labor productivity in emerging nations due to a lack of study, especially when it comes to outdoor work settings like couriers in the express delivery industry. Combining findings from two research projects, this paper examines the socioeconomic consequences of particulate matter and ground-level particulate pollution. Special panel dataset from China's express delivery companies are used, we study how particulate pollution affects courier productivity. The instrumental variable of our analysis was built by particulate pollution data from upwind towns. Moreover, a comparable rise in particulate levels during the 30 days caused a significant 23.7% decline in worker productivity. This draws attention to a neglected area of the economic effects of particulate pollution, especially in underdeveloped countries. Our results also highlight the wider health hazards connected to outdoor activities in high-pollution locations, drawing comparisons on outdoor exercisers and particulate matter concentrations. The critical need for coordinated policy attention addressing both ground-level Particulate and particle matters in developing nations is highlighted by the increased risk of lung function impairment among outdoor exercisers owing to excessive particulate matter concentrations. The interrelated risks that air pollution poses to public health and economic productivity are clarified by this Comprehensive viewpoint.

The radiomics nomogram predicts the prognosis of pancreatic cancer patients with hepatic metastasis after chemoimmunotherapy.

OBJECTIVE: To construct a prognostic model based on MR features and clinical data to evaluate the progression free survival (PFS), overall survival (OS) and objective response rate (ORR) of pancreatic cancer patients with hepatic metastases who received chemoimmunotherapy. METHODS: 105 pancreatic cancer patients with hepatic metastases who received chemoimmunotherapy were assigned to the training set (n = 52), validation set (n = 22), and testing set (n = 31). Multi-lesion volume of interest were delineated, multi-sequence radiomics features were extracted, and the radiomics models for predicting PFS, OS and ORR were constructed, respectively. Clinical variables were extracted, and the clinical models for predicting PFS, OS and ORR were constructed, respectively. The nomogram was jointly constructed by radiomics model and clinical model. RESULT: The ORR exhibits no significant correlation with either PFS or OS. The area under the curve (AUC) of nomogram for predicting 6-month PFS reached 0.847 (0.737-0.957), 0.786 (0.566-1.000) and 0.864 (0.735-0.994) in the training set, validation set and testing set, respectively. The AUC of nomogram for predicting 1-year OS reached 0.770 (0.635-0.906), 0.743 (0.479-1.000) and 0.818 (0.630-1.000), respectively. The AUC of nomogram for predicting ORR reached 0.914 (0.828-1.00), 0.938 (0.840-1.00) and 0.846 (0.689-1.00), respectively. CONCLUSION: The prognostic models based on MR imaging features and clinical data are effective in predicting the PFS, OS and ORR of chemoimmunotherapy in pancreatic cancer patients with hepatic metastasis, and can be used to evaluate the prognosis of patients.