Removal of particulate matter and dissolved organic matter from sedimentation sludge water during pre-sedimentation process: Performances and mechanisms.

Sedimentation sludge water (SSW), a prominent constituent of wastewater from drinking water treatment plants, has received limited attention in terms of its treatment and utilization likely due to the perceived difficulties associated with managing SSW sludge. This study comprehensively evaluated the water quality of SSW by comparing it to a well-documented wastewater (filter backwash water (FBW)). Furthermore, it investigated the pollutant variations in the SSW during pre-sedimentation process, probed the underlying reaction mechanism, and explored the feasibility of employing a pilot-scale coagulation-sedimentation process for SSW treatment. The levels of most water quality parameters were generally comparable between SSW and FBW. During the pre-sedimentation of SSW, significant removal of turbidity, bacterial counts, and dissolved organic matter (DOM) was observed. The characterization of DOM components, molecular weight distributions, and optical properties revealed that the macromolecular proteinaceous biopolymers and humic acids were preferentially removed. The characterization of particulates indicated that high surface energy, zeta potential, and bridging/adsorption/sedimentation/coagulation capacities in aluminum residuals of SSW, underscoring its potential as a coagulant and promoting the generation and sedimentation of inorganic-organic complexes. The coagulation-sedimentation process could effectively remove pollutants from low-turbidity SSW ([turbidity]0 < 15 NTU). These findings provide valuable insights into the water quality dynamics of SSW during the pre-sedimentation process, facilitating the development of SSW quality management and enhancing its reuse rate.

Design, synthesis, and in vivo and in vitro biological screening of pseudolaric acid B derivatives as potential anti-tumor agents.

Pseudolaric Acid B (PAB), a natural product with remarkable anti-tumor activity, is a starting point for new anticancer therapeutics. We designed and synthesized 27 PAB derivatives and evaluated their anti-proliferative activities against four cancer cell lines: MCF-7, HCT-116, HepG2, and A549. Compared with unmodified PAB, the PAB derivatives showed stronger anti-proliferative activity. The ability of compound D3 (IC50 = 0.21 µM) to inhibit HCT-116 cells was approximately 5.3 times that of PAB (IC50 = 1.11 µM) and the antiproliferative action was unrelated to cytotoxicity (SI=20.38), indicating its superior safety profile (PAB; SI=0.95). Compound D3 effectively suppressed the EdU-positive rate and reduced colony formation, arrested HCT-116 cells in the S and G2/M phases and induced apoptosis. In vivo experiments further demonstrated low toxicity of compound D3 while suppressing tumor growth in mice. In summary, given its strong anti-proliferative effect and relative safety, further development of compound D3 is warranted.

Visualizing the modulation of neurokinin 1 receptor-positive neurons in the superficial dorsal horn by spinal cord stimulation in vivo.

ABSTRACT: Spinal cord stimulation (SCS) is an effective modality for pain treatment, yet its underlying mechanisms remain elusive. Neurokinin 1 receptor-positive (NK1R+) neurons in spinal lamina I play a pivotal role in pain transmission. To enhance our mechanistic understanding of SCS-induced analgesia, we investigated how different SCS paradigms modulate the activation of NK1R+ neurons, by developing NK1R-Cre;GCaMP6s transgenic mice and using in vivo calcium imaging of superficial NK1R+ neurons under anesthesia (1.5% isoflurane). Neurokinin 1 receptor-positive neurons in the lumbar spinal cord (L4-5) showed a greater activation by electrical test stimulation (TS, 3.0 mA, 1 Hz) at the hindpaw at 2 weeks after tibia-sparing nerve injury (SNI-t) than in naïve mice. Spinal cord stimulation was then delivered through a bipolar plate electrode placed epidurally at L1-2 level. The short-term 50-Hz high-intensity SCS (80% motor threshold [MoT], 10 minutes) induced robust and prolonged inhibition of NK1R+ neuronal responses to TS in both naïve and SNI-t mice. The 30-minute 50-Hz and 900-Hz SCS applied at moderate intensity (50% MoT) also significantly inhibited neuronal responses in SNI-t mice. However, at low intensity (20% MoT), the 30-minute 900-Hz SCS only induced persistent neuronal inhibition in naïve mice, but not in SNI-t mice. In conclusion, both 10-minute high-intensity SCS and 30-minute SCS at moderate intensity inhibit the activation of superficial NK1R+ neurons, potentially attenuating spinal nociceptive transmission. Furthermore, in vivo calcium imaging of NK1R+ neurons provides a new approach for exploring the spinal neuronal mechanisms of pain inhibition by neuromodulation pain therapies.

Risk factors for arrhythmias occurred in cancer patients after chemotherapy: An evidence-based systematic review and meta-analysis.

Objectives: This study aimed to summarize the existing literature on risk factors for arrhythmias after chemotherapy in cancer patients. To provide reliable evidence for treating arrhythmias after chemotherapy in oncology patients by assessing multiple biasing factors in the literature and quantifying the risk factors. Methods: The risk factors for arrhythmia following tumor chemotherapy were systematically collected from various reputable databases, including PubMed, Cochrane Library, MEDLINE, EMBASE, and multiple Chinese databases, covering the period from inception to May 2023. Two independent reviewers performed rigorous article screening, data extraction, and assessment of research quality. Data analysis was conducted using Review Manager 5.4 software, ensuring a standardized and robust approach to evaluate the gathered evidence. Results: The analysis of chemotherapy-induced arrhythmias included 16 articles, encompassing 14,785 cancer patients. Among the patients, 3295 belonged to the arrhythmia group, while 11,490 were in the non-arrhythmia group. These studies identified 12 significant risk factors associated with arrhythmias following chemotherapy in cancer patients. The findings of the analysis are as follows. General patient characteristics: The incidence of post-chemotherapy arrhythmias was 14.33 times higher in oncology patients aged ≥60 years compared to patients <60 years of age [OR = 14.33, 95%CI (8.51, 24.13), P＜0.00001]. Patients with a smoking history exhibited a 1.67-fold higher risk of arrhythmia after chemotherapy [OR = 1.67, 95%CI (1.24, 2.25), P = 0.0007]. However, there was no significant correlation between gender and body mass index (BMI) with arrhythmia after chemotherapy in oncology patients (P = 0.52; P = 0.19). Disease-related factors: Patients with a history of hypertension, diabetes, and cardiovascular disease had a 1.93-fold, 1.30-fold, and 1.76-fold increased risk of arrhythmia after chemotherapy, respectively [OR = 1.93, 95%CI (1.66, 2.24), P＜0.00001; OR = 1.30, 95%CI (1.10, 2.52), P = 0.002; OR = 1.76, 95%CI (1.51, 2.05), P＜0.00001]. Additionally, the incidence of arrhythmia increased 1.97 times in patients with electrolyte and acid-base balance disorders following chemotherapy [OR = 1.97, 95%CI (1.41, 2.76), P＜0.00001]. Chemotherapy-related factors: Seven articles examined the association between chemotherapy drugs and post-chemotherapy arrhythmias. The results indicated that oncology patients were 3.03 times more likely to develop arrhythmias with chemotherapy drugs compared to non-chemotherapy drugs [OR = 3.03, 95%CI (2.59, 3.54), P＜0.00001]. Notably, anthracyclines and fluorouracil chemotherapy demonstrated a 2.98-fold and 3.35-fold increased risk of arrhythmia after chemotherapy, respectively [OR = 2.98, 95%CI (2.51, 3.03), P＜0.00001; OR = 3.35, 95%CI (2.20, 5.10), P＜0.00001]. The risk of arrhythmia after chemotherapy was 1.72 times higher in patients with chemotherapy cycles longer than 4 weeks than those with cycles shorter than 4 weeks [OR = 1.72, 95%CI (1.30, 2.28), P = 0.0001]. Conclusion: The occurrence of arrhythmia after chemotherapy in cancer patients was significantly associated with the patient's age, history of smoking, history of hypertension, history of diabetes, history of cardiovascular disease, chemotherapy drug use, and cycle. However, further high-quality evidence is needed to support these results.

Effects of O2 on accumulation of nitrous and elemental sulfur and microbial community structure in double short-cut sulfur autotrophic denitrification system.

Understanding the effect of O2 on the accumulation characteristics of NO2--N and S0 in the sulfur autotrophic denitrification (DSSADN) system is crucial for enhancing the denitrification efficiency of partial nitrification-anammox using DSSADN. The results revealed that in an environment without O2 entry, the NO2--N accumulation efficiency (NiAE) and S0 accumulation efficiency (S0AE) of the DSSADN system reached 89.40 % and 93.41 %, respectively. Once system entered O2, ORP value kept increasing. When ORP increased to -59.9 mV (DO = 0.1 mg/L), soxB and nirK gene expression rose and as well NiAE and S0AE continuously decreased to 48.13 % and 29.35 %. When ORP was above 30.9 mV (DO >0.2 mg/L) but below 81.0 mV (DO<0.4 mg/L), narG gene expression reduced and the relatively high sqr gene expression allowed NiAE and S0AE remained at 45.08 % and 33.31 %. O2 promoted the synergistic effect of Thiobacillus and Azoarcus without the proliferation of nitrite oxidizing bacteria.

Current trends and hotspots of depressive disorders with colorectal cancer: A bibliometric and visual study.

BACKGROUND: Depression is strongly associated with colorectal cancer (CRC). Few bibliometric analyses have systematically summarized the research focus and recent progress in this field. AIM: To determine the research status and hotspots by bibliometric analysis of relevant publications on the relationship between CRC and depression. METHODS: Articles on depression in CRC patients were collected from the Web of Science Core Collection. CiteSpace and VOSviewer software were used to visualize bibliometric networks. RESULTS: From 2001 to 2022, Supportive Care in Cancer, the United States, Tilburg University, and Mols were the most productive and influential journal, country, institution, and author name. Co-occurrence cluster analysis of keywords placed quality of life, anxiety, and psychological stress in the center of the visual network diagram. Further clustering was performed for the clusters with studies of the relevant mechanism of action, which showed that: (1) Cytokines have a role essential for the occurrence and development of depressive disorders in CRC; (2) MicroRNAs have a role essential for the development of depressive disorders in CRC; (3) Some anticancer drugs have pro-depressant activity; and (4) Selective serotonin reuptake inhibitors have both antitumor and antidepressant activity. CONCLUSION: Life quality and psychological nursing of the cancer population were key topics. The roles of cytokines and microRNAs, the pro-depression activity of anticancer drugs and their antitumor properties deserve in-depth study.

Fabrication and characterization of TPGS-modified chlorogenic acid liposomes and its bioavailability in rats.

Chlorogenic acid (CGA), a polyphenol compound, exhibits excellent anti-oxidative, anti-hypoxic, antibacterial, antiviral, and anti-inflammatory activities, however the bioactivity of it has not been fully utilized in vivo due to its instability and low bioavailability. To address these issues, we prepared and characterized CGA-TPGS-LP, which is a TPGS-modified liposome loaded with CGA. The pharmacokinetics of CGA-TPGS-LP were studied in rats after oral administration. CGA-TPGS-LP was fabricated using a combination of thin film dispersion and ion-driven methods. The liposomes were observed to be uniformly small and spherical in shape. Their membranes were composed of lecithin, cholesterol, and TPGS lipophilic head with a TPGS hydrophilic tail chain coating on its surface. The loading efficiency and encapsulation efficiency were found to be 11.21% and 83.22%, respectively. The physicochemical characterisation demonstrated that the CGA was present in an amorphous form and retained its original structural state within the liposomal formulation. The stability of CGA was significantly improved by fabricating TPGS-LP. CGA-TPGS-LP exhibited good sustained-release properties in both simulated gastric and intestinal fluids. Following oral administration, ten metabolites were identified in rat plasma using UPLC-QTOF-MS. UPLC-QqQ-MS/MS quantitative analysis demonstrated that the oral bioavailability of CGA encapsulated in TPGS-modified liposomes was enhanced by 1.52 times. In addition, the three main metabolites of CGA had higher plasma concentrations and slower degradation rate. These results demonstrate that TPGS-modified liposomes could be a feasible strategy to further enhance the oral bioavailability of CGA, facilitating its clinical use.

Development and validation of a predictive model for prolonged length of stay in elderly type 2 diabetes mellitus patients combined with cerebral infarction.

Background: This study aimed to identify the predictive factors for prolonged length of stay (LOS) in elderly type 2 diabetes mellitus (T2DM) patients suffering from cerebral infarction (CI) and construct a predictive model to effectively utilize hospital resources. Methods: Clinical data were retrospectively collected from T2DM patients suffering from CI aged ≥65 years who were admitted to five tertiary hospitals in Southwest China. The least absolute shrinkage and selection operator (LASSO) regression model and multivariable logistic regression analysis were conducted to identify the independent predictors of prolonged LOS. A nomogram was constructed to visualize the model. The discrimination, calibration, and clinical practicality of the model were evaluated according to the area under the receiver operating characteristic curve (AUROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results: A total of 13,361 patients were included, comprising 6,023, 2,582, and 4,756 patients in the training, internal validation, and external validation sets, respectively. The results revealed that the ACCI score, OP, PI, analgesics use, antibiotics use, psychotropic drug use, insurance type, and ALB were independent predictors for prolonged LOS. The eight-predictor LASSO logistic regression displayed high prediction ability, with an AUROC of 0.725 (95% confidence interval [CI]: 0.710-0.739), a sensitivity of 0.662 (95% CI: 0.639-0.686), and a specificity of 0.675 (95% CI: 0.661-0.689). The calibration curve (bootstraps = 1,000) showed good calibration. In addition, the DCA and CIC also indicated good clinical practicality. An operation interface on a web page (https://xxmyyz.shinyapps.io/prolonged_los1/) was also established to facilitate clinical use. Conclusion: The developed model can predict the risk of prolonged LOS in elderly T2DM patients diagnosed with CI, enabling clinicians to optimize bed management.

A prediction model based on computed tomography characteristics for identifying malignant from benign sub-centimeter solid pulmonary nodules.

Background: Distinguishing benign from malignant sub-centimeter solid pulmonary nodules (SSPNs) continues to be challenging in clinical practice. Earlier diagnosis is crucial for improving patient survival and prognosis. This study aimed to investigate the risk factors of malignant SSPNs and establish and validate a prediction model based on computed tomography (CT) characteristics to assist in their early diagnosis. Methods: A total of 261 consecutive participants with 261 SSPNs were retrospectively recruited between January 2012 and July 2023 from National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (Center 1), including 161 malignant lesions and 100 benign lesions. Patients were randomly assigned to the training set (n=183) and validation set (n=78) according to a 7:3 ratio. Malignant nodules were confirmed by pathology; and benign nodules were confirmed by follow-up or pathology. Clinical data and CT features were collected to estimate the independent predictors of malignancy of SSPN with multivariate logistic analysis. A clinical prediction model was subsequently established by logistic regression. Furthermore, an additional 69 consecutive patients with 69 SSPNs from The Fourth Hospital of Hebei Medical University (Center 2) between January 2022 and December 2022 were retrospectively included as an external cohort to validate the predictive efficacy of the model. The performance of the prediction model was assessed by sensitivity, specificity, and the area under the receiver operating characteristic curve. Results: There were 113 (61.7%), 48 (61.5%) and 28 (40.6%) malignant SSPNs in the training, internal and external validation sets, respectively. Multivariate logistic analysis revealed four independent predictors of malignant SSPNs: tumor-lung interface (P=0.002), spiculation (P=0.04), air bronchogram (P=0.047), and invisible at the mediastinal window (P=0.003). The area under the curve (AUC) for the prediction model in the training set was 0.875 [95% confidence interval (CI): 0.818, 0.933]; and the sensitivity and specificity were 94.7% and 68.6%, respectively. The AUCs in the internal and external validation set were (0.781; 95% CI: 0.664, 0.897) and (0.873; 95% CI: 0.791, 0.955), respectively; the sensitivity and specificity were 66.7% and 83.3% for the internal validation data, and 100.0% and 61.0% for the external validation data, respectively. Conclusions: The prediction model based on CT characteristics could be helpful for distinguishing malignant SSPNs from benign ones.

The genetic architecture of age at menarche and its causal effects on other traits.

Age at menarche (AAM) is a sign of puberty of females. It is a heritable trait associated with various adult diseases. However, the genetic mechanism that determines AAM and links it to disease risk is poorly understood. Aiming to uncover the genetic basis for AAM, we conducted a joint association study in up to 438,089 women from 3 genome-wide association studies of European and East Asian ancestries. A series of bioinformatical analyses and causal inference were then followed to explore in-depth annotations at the associated loci and infer the causal relationship between AAM and other complex traits/diseases. This largest meta-analysis identified a total of 21 novel AAM associated loci at the genome wide significance level (P < 5.0 × 10-8), 4 of which were European ancestry-specific loci. Functional annotations prioritized 33 candidate genes at newly identified loci. Significant genetic correlations were observed between AAM and 67 complex traits. Further causal inference demonstrated the effects of AAM on 13 traits, including forced vital capacity (FVC), high blood pressure, age at first live birth, etc, indicating that earlier AAM causes lower FVC, worse lung function, hypertension and earlier age at first (last) live birth. Enrichment analysis identified 5 enriched tissues, including the hypothalamus middle, hypothalamo hypophyseal system, neurosecretory systems, hypothalamus and retina. Our findings may provide useful insights that elucidate the mechanisms determining AAM and the genetic interplay between AAM and some traits of women.

Base-Promoted Nucleophilic Phosphorylation of Benzyl Fluorides via C(sp3)-F Cleavage.

Herein, a transition-metal-free phosphorylation of benzyl fluorides with P(O)-H compounds is disclosed. In the presence of tBuOK, various benzyl fluorides react with P(O)-H compounds to produce the corresponding benzyl phosphine oxides, phosphinates, and phosphonates in good to high yields. This base-promoted phosphorylation reaction offers a facile and general strategy for the construction of a C(sp3)-P bond.

Common obesity-related anthropometric indices and the risk of gestational diabetes mellitus in a Chinese population: a prospective cohort study.

OBJECTIVE: Anthropometric measurement provides a simple, noninvasive approach to evaluate obesity in pregnant women. We aimed to develop a predictive model utilizing anthropometric index for gestational diabetes mellitus (GDM), the most common obesity-related complications during pregnancy. METHODS: A prospective cohort of 4709 women was enrolled in Qingdao, China. Logistic regression model was constructed to determine the association of body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT) in the first trimester (<14 weeks' gestation) with GDM. The discrimination ability for GDM was assessed using areas under the receiver operating characteristic (ROC) curve (AUC). Delong tests were performed to compare AUC values between different measures. RESULTS: The GDM incidence was 19.50%. GDM risk increased with VAT during early pregnancy, and the risk increased by 117% (OR = 2.17, 95% CI: 1.23-2.83) to 326% (OR = 4.26, 95% CI: 2.29-7.91) in pregnant women with the second quartile or above after adjusting for confounders (all p<.05). Combined index using VAT and BMI demonstrated superior predictive power for GDM compared with BMI alone (p<.05), but didn't differ from VAT (p>.05). Overall, VAT was positively correlated with GDM occurrence, outperforming BMI, WHR, WHtR and SAT in the predicative model. A first-trimester VAT cutoff of 27.05 mm might be promising for GDM risk stratification. CONCLUSIONS: First-trimester routine ultrasound screening may facilitate earlier identification and intervention of GDM. Pregnant women with VAT above the optimal threshold (27.05 mm) might benefit from targeted GDM monitoring.

Metabolic syndrome and cancer risk: A two-sample Mendelian randomization study of European ancestry.

BACKGROUND: The relationship between Metabolic Syndrome and cancer remains controversial. We aimed to assess the association between Metabolic Syndrome and cancer risk at different locations using a Mendelian randomization approach. METHODS: We extracted single nucleotide polymorphisms (SNPs) of MetS and its components from public databases for populations of European ancestry. Causal effects were estimated using inverse variance weighting, MR-Egger, weighted median, and MR-PRESSO. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and funnel plots. In addition, we calculated the Statistical power. Finally, we applied the False Discovery Rate (FDR) to correct our results. RESULTS: IVW methods showed that Genetically predicted Metabolic Syndrome may be a potential risk factor for hepatocellular carcinoma (P=0.031, P-FDR=0.093). Metabolic Syndrome was not causally associated with cancers at other sites (lung, thyroid, breast, prostate, kidney, bladder, colorectal, oesophagus, and stomach). In further analyses, WC may increase the risk of lung (P=0.003, P-FDR=0.018), and oesophageal (P=0.011, P-FDR=0.066) cancers and decrease the risk of prostate cancer (P=0.006, P-FDR=0.001). Furthermore, hypertension may reduce the risk of Hepatic cancer (P=0.014, P-FDR=0.084). CONCLUSION: Our study suggests that genetically predicted Metabolic Syndrome may increase the risk of some cancers. Prevention and treatment of Metabolic Syndrome may help to prevent the development of related cancers.

Gut microbial features and circulating metabolomic signatures of frailty in older adults.

Frailty, a multidimensional indicator of suboptimal aging, reflects cumulative declines across multiple physiological systems. Although age-related changes have been reported in gut microbiota, their role in healthy aging remains unclear. In this study, we calculated frailty index (FI) from 33 health-related items to reflect the overall health status of 1,821 older adults (62-96 years, 55% female) and conducted multi-omics analysis using gut metagenomic sequencing data and plasma metabolomic data. We identified 18 microbial species and 17 metabolites shifted along with frailty severity, with stronger links observed in females. The associations of nine species, including various Clostridium species and Faecalibacterium prausnitzii, with FI were reproducible in two external populations. Plasma glycerol levels, white blood cell count and kidney function partially mediated these associations. A composite microbial score derived from FI significantly predicted 2-year mortality (adjusted hazard ratio across extreme quartiles, 2.86; 95% confidence interval, 1.38-5.93), highlighting the potential of microbiota-based strategies for risk stratification in older adults.

An analytical method to estimate the accuracy representation index of circular and elliptical disc models for rectangular fractures with application to seepage analysis.

Constructing a suitable discrete fracture network (DFN) to represent rock fractures proves vital for tackling engineering projects involving rock masses. Among the commonly used models for constructing DFN, the circular disc model (CDM) and elliptical disc model (EDM) stand out. The selection between these models has been facilitated by the introduction of the Accuracy Representation Index (ARI), which quantitatively assesses their suitability. The existing methods for calculating ARI based on Monte Carlo simulations are time-consuming. In order to quickly estimate the ARI for CDM and EDM concerning any length-width ratio (k r ) of rectangular fracture, the paper derives analytical formulas based on the geometric relationships between circles and ellipses with rectangles. These formulas show that: (a) for the CDM, ARI is only related to k r , and its value decreases as k r increases; (b) for the EDM, ARI is dependent on the relationship between k r and the long-short axis length ratio (k e ) of the ellipse, and it has been theoretically proven that ARI reaches its maximum value of 0.91 when k r is equal to k e . Moreover, we apply ARI to the study of rock mass seepage characteristics, and the results show that ARI could reflect the error rate of permeability of the CDM and EDM for rock masses with rectangular fractures.

FCER1G as a novel immune-associated blood biomarker in cardiogenic stroke.

Background: Cardioembolic stroke (CE) exhibits the highest recurrence rate and mortality rate among all subtypes of cerebral ischemic stroke (CIS), yet its pathogenesis remains uncertain. The immune system plays a pivotal role in the progression of CE. Growing evidence indicates that several immune-associated blood biomarkers may inform the causes of stroke. The study aimed to identify new immune-associated blood biomarkers in patients with CE and create an online predictive tool in distinguishing CE from noncardioembolic stroke (non-CE) in CIS. Methods: Gene expression profiles that were publicly available were obtained from the Gene Expression Omnibus (GEO). The identification of differentially expressed genes (DEGs) was conducted using the Limma package. The hub module and hub genes were identified through the application of weighted gene coexpression network analysis (WGCNA). In order to identify potential diagnostic biomarkers for CE, both the random forest (RF) model and least absolute shrinkage and selection operator (LASSO) regression analysis were employed. Concurrently, the CIBERSORT algorithm was employed to evaluate the infiltration of immune cells in CE samples and examine the correlation between the biomarkers and the infiltrating immune cells. The diagnostic gene expression in blood samples was confirmed using qRT-PCR in a self-constructed dataset. Univariate and multiple logistic regression analyses were used to identify the risk factors for CE. Subsequently, the mathematical model of the nomogram was employed via Java's "Spring Boot" framework to develop the corresponding online tool, which was then deployed on a cloud server utilizing "nginx". Results: Eleven differentially expressed genes (DEGs) that were upregulated and seven DEGs that were downregulated were identified. Through bioinformatics analysis and clinical sample verification, it was discovered that Fc Fragment of IgE Receptor Ig (FCER1G) could serve as a novel potential blood biomarker for CE. FCER1G, along with other risk factors associated with CE, were utilized to develop a nomogram. The training and validation sets, which consisted of 65 CIS patients, yielded areas under the curve (AUCs) of 0.9722 and 0.9689, respectively. These results indicate a high level of precision in risk delineation by the nomogram. Furthermore, the associated online predictive platform has the potential to serve as a more efficacious and appropriate predictive instrument (https://www.origingenetic.com/CardiogenicStroke-FCER1G) for distinguishing between CE and non-CE. Conclusion: Blood biomarker FCER1G has the potential to identify patients who are at a higher risk of cardioembolism and direct the search for occult AF.The utilization of this online tool is anticipated to yield significant implications in terms of distinguishing between CE and non-CE, as well as enhancing the optimization of treatment decision support.

Nonlinear and abnormal relationship between turbidity and suspended solids concentration in mountainous rivers: A case study of the Lai Chi Wo river in Hong Kong, China.

Suspended solids concentration (SSC) in a river is closely relevant to river water turbidity. Investigation of their relationship in this study is accompanied by observed turbidity and SSC values, which were obtained from the testing results of water samples and monitored conditions in streamflow. The water samples were collected from two observation stations with a broad range of sediment concentrations in the Lai Chi Wo catchment in Hong Kong, China. We classified the target rainfall events into single-peak event type and dual-peak event type for a distinguished discussion of the relationship between SSC and turbidity in this study. At a finer classification, each event is separated into defined processes for the analysis, where two main processes refer to the periods that SSC rises from a normal state to a peak state first and the followed periods that SSC recesses to ordinary status gradually. It is advised by the analysis results that the estimation of SSC through turbidity values should be based on the same rainfall types for the upstream station. However, the results show that the classification of rainfall types does not need to take downstream areas into consideration. Furthermore, current research implies that the individual established connections between SSC and turbidity value at different stages (particularly referring to the rising period and recessing period) could be applied to estimate SSC at the same station via continuous turbidity values for both this and other ungauged stations with similar topographical features in the future. Meanwhile, this research approach provides new insight exploring various behaviors of sediments at different stages during an integral rainfall event. A comparison of distinguished performances of sediment during corresponding stages in a rainfall event makes contributions to diverse relationship between SSC and turbidity in the mountainous river.

Fabrication of fluorinated magnetic microporous organic network for selective and efficient extraction of benzoylurea insecticides in tea beverages.

In this work, a novel fluorinated magnetic microporous organic network (Fe3O4@FMON) was exquisitely designed and synthesized for highly efficient and selective magnetic solid phase extraction (MSPE) of fluorinated benzoylurea insecticides (BUs) from complex tea beverage samples. The Fe3O4@FMON exhibited good extraction for BUs via the pre-designed hydrophobic, π-π stacking, hydrogen bonding and specific FF interactions. A sensitive Fe3O4@FMON-based MSPE-HPLC-UV method with wide linear range (0.10-1000 µg L-1, R2 ≥ 0.996), low limits of detection (0.01-0.02 µg L-1), and large enrichment factors (85.6-98.0) for BUs from tea beverage samples was developed. By decorating F elements within MON's networks, the Fe3O4@FMON characterized good hydrophobicity and chemical stability, which could be reused at least 8 times without decrease of recoveries. This work demonstrated the great prospects of Fe3O4@FMON for enriching trace BUs from complex substrates and triggered the potential of FMON for sample pretreatment of fluorinated analytes.

Explainable machine learning for predicting 30-day readmission in acute heart failure patients.

We aimed to develop a machine-learning based predictive model to identify 30-day readmission risk in Acute heart failure (AHF) patients. In this study 2232 patients hospitalized with AHF were included. The variance inflation factor value and 5-fold cross-validation were used to select vital clinical variables. Five machine learning algorithms with good performance were applied to develop models, and the discrimination ability was comprehensively evaluated by sensitivity, specificity, and area under the ROC curve (AUC). Prediction results were illustrated by SHapley Additive exPlanations (SHAP) values. Finally, the XGBoost model performs optimally: the greatest AUC of 0.763 (0.703-0.824), highest sensitivity of 0.660, and high accuracy of 0.709. This study developed an optimal XGBoost model to predict the risk of 30-day unplanned readmission for AHF patients, which showed more significant performance compared with traditional logistic regression (LR) model.