mTORC1 pathway activity biases cell fate choice.

Pluripotent stem cells can differentiate into distinct cell types but the intracellular pathways controlling cell fate choice are not well understood. The social amoeba Dictyostelium discoideum is a simplified system to study choice preference as proliferating amoebae enter a developmental cycle upon starvation and differentiate into two major cell types, stalk and spores, organised in a multicellular fruiting body. Factors such as acidic vesicle pH predispose amoebae to one fate. Here we show that the mechanistic target of rapamycin complex 1 (mTORC1) pathway has a role in cell fate bias in Dictyostelium. Inhibiting the mTORC1 pathway activity by disruption of Rheb (activator Ras homolog enriched in brain), or treatment with the mTORC1 inhibitor rapamycin prior to development, biases cells to a spore cell fate. Conversely activation of the pathway favours stalk cell differentiation. The Set1 histone methyltransferase, responsible for histone H3 lysine4 methylation, in Dictyostelium cells regulates transcription at the onset of development. Disruption of Set1 leads to high mTORC1 pathway activity and stalk cell predisposition. The ability of the mTORC1 pathway to regulate cell fate bias of cells undergoing differentiation offers a potential target to increase the efficiency of stem cell differentiation into a particular cell type.

Assembly of a stem cell-derived human postimplantation embryo model.

The embryonic and extraembryonic tissue interactions underlying human embryogenesis at implantation stages are not currently understood. We have generated a pluripotent stem cell-derived model that mimics aspects of peri-implantation development, allowing tractable experimentation otherwise impossible in the human embryo. Activation of the extraembryonic lineage-specific transcription factors GATA6 and SOX17 (hypoblast factors) or GATA3 and TFAP2C (encoding AP2γ; trophoblast factors) in human embryonic stem (ES) cells drive conversion to extraembryonic-like cells. When combined with wild-type ES cells, self-organized embryo-like structures form in the absence of exogenous factors, termed human inducible embryoids (hiEmbryoids). The epiblast-like domain of hiEmbryoids polarizes and differentiates in response to extraembryonic-secreted extracellular matrix and morphogen cues. Extraembryonic mesenchyme, amnion and primordial germ cells are specified in hiEmbryoids in a stepwise fashion. After establishing stable inducible ES lines and converting ES cells to RSeT culture media, the protocol takes 7-10 d to generate hiEmbryoids. Generation of hiEmbryoids can be performed by researchers with basic expertise in stem cell culture.

Mapping of oil spills in China Seas using optical satellite data and deep learning.

Oils spilled into the ocean can form various weathered oils (non-emulsified oil slicks (NEOS), oil emulsions (OE)) which threaten the oceanic and coastal environments and ecosystems. Optical remote sensing has the unique ability to discriminate oil types and quantify oil volumes as their spectral contrasts with oil-free seawater. Here, a deep learning-based model is developed for identification, classification, and quantification of various oil types. Based on the oil-contained datasets collected from 7 satellite sensors from April 2019 to August 2023, the origin, quantity, and spatial distribution of oils spilled from ships and rigs in the China Seas are mapped in detail. We found that oil spill incidents are primarily from ship discharges (85.8 %), while platform leaks lead to more oil emulsions (58.6 % compared to 13.1 % from ships), which illuminates that the drilling oils are the main source of oil spill pollution in China Seas. The spilled oils correlate with major port locations, including offshore Qingdao and Rongcheng, Bohai Bay, the adjacent areas of Beihai, and Hue and Danang in Vietnam. This study provides new insights into the assessment and management of offshore and marine oil spills.

CCL4/CCR5 regulates chondrocyte biology and OA progression.

BACKGROUND: Osteoarthritis (OA) is a common musculoskeletal disorder characterized by chondrocyte apoptosis and extracellular matrix degradation. This study aimed to investigate the role of CCL4/CCR5 in regulating chondrocyte apoptosis and reactive oxygen species (ROS) levels in OA progression. METHODS: Bioinformatics analysis was employed to identify CCL4 as the target gene, following which primary chondrocytes were treated with varying concentrations of CCL4. Apoptosis rate of chondrocytes and ROS levels were assessed using flow cytometry. The mechanism by which CCL4 regulated the extracellular matrix was investigated through Western blot and Immunofluorescence analyses. Additionally, maraviroc, a CCR5 inhibitor, was administered to chondrocytes in order to explore the potential signaling pathway of CCL4/CCR5. RESULTS: Our study found that CCL4 was predominantly up-regulated among the top 10 hub genes identified in RNA-sequencing analysis. Validation through quantitative polymerase chain reaction (qPCR) confirmed elevated CCL4 expression in patients with Hip joint osteoarthritis, knee joint osteoarthritis, and facet joint osteoarthritis. The upregulation of CCL4 was associated with an increase in chondrocyte apoptosis and ROS levels. Mechanistically, CCL4, upon binding to its receptor CCR5, triggered the downstream phosphorylation of P65 in the nuclear factor-κB (NF-κB) signaling pathway. In vitro experiments demonstrated that treatment with maraviroc mitigated chondrocyte apoptosis, reduced intracellular ROS levels, and attenuated extracellular matrix degradation. CONCLUSION: The study highlights the critical role of CCL4/CCR5 in modulating chondrocyte apoptosis and ROS levels in OA progression. Targeting this pathway may offer promising therapeutic interventions for mitigating the pathogenic mechanisms associated with OA.

Effect of chickpea protein modified with combined heating and high-pressure homogenization on enhancing the gelation of reduced phosphate myofibrillar protein.

The effects of chickpea protein (CP) modified by heating and/or high-pressure homogenization (HPH) on the gelling properties of myofibrillar protein under reduced phosphate conditions (5 mM sodium triphosphate, STPP) were investigated. The results showed that heating and HPH dual-modified CP could decrease the cooking loss by 29.57 %, elevate the water holding capacity by 17.08 %, and increase the gel strength by 126.88 %, which conferred myofibrillar protein with gelation performance comparable with, or even surpassing, that of the high-phosphate (10 mM STPP) control. This gelation behavior improvement could be attributed to enhanced myosin tail-tail interactions, decreased myosin thermal stability, elevated trans-gauche-trans disulfide conformation, strengthened hydrophobic interactions and hydrogen bonding, the uncoiling of α-helical structures, the formation of well-networked myofibrillar protein gel, and the disulfide linkages between the myosin heavy chain, actin, and CP subunits. Therefore, the dual-modified CP could be a promising phosphate alternative to develop healthier meat products.

Inhibition of OLR1 reduces SASP of nucleus pulposus cells by targeting autophagy-GATA4 axis.

Targeting cellular senescence and Senescence Associated Secretory Phenotype (SASP) through autophagy has emerged as a promising intervertebral disc (IVD) degeneration (IDD) treatment strategy in recent years. This study aimed to clarify the role and mechanism of autophagy in preventing IVD SASP. Methods involved in vitro experiments with nucleus pulposus (NP) tissues from normal and IDD patients, as well as an in vivo IDD animal model. GATA4's regulatory role in SASP was validated both in vitro and in vivo, while autophagy modulators were employed to assess their impact on GATA4 and SASP. Transcriptomic sequencing identified Oxidized low-density lipoprotein receptor 1 (OLR1) as a key regulator of autophagy and GATA4. A series of experiments manipulated OLR1 expression to investigate associated effects. Results demonstrated significantly increased senescent NP cells (NPCs) and compromised autophagy in IDD patients and animal models, with SASP closely linked to IDD progression. The aged disc milieu impeded autophagic GATA4 degradation, leading to elevated SASP expression in senescent NPCs. Restoring autophagy reversed senescence by degrading GATA4, hence disrupting the SASP cascade. Moreover, OLR1 was identified for its regulation of autophagy and GATA4 in senescent NPCs. Silencing OLR1 enhanced autophagic activity, suppressing GATA4-induced senescence and SASP expression in senescent NPCs. In conclusion, OLR1 was found to control autophagy-GATA4 and SASP, with targeted OLR1 inhibition holding promise in alleviating GATA4-induced senescence and SASP expression while delaying extracellular matrix degradation, offering a novel therapeutic approach for IDD management.

From smoke to stroke: quantifying the impact of smoking on stroke prevalence.

PURPOSE: The objective of this study is to assess the impact of smoking on stroke prevalence and to delineate the relationship between smoking-related factors and the risk of stroke, incorporating an analysis of demographic variations influencing this association. METHODS: Our analysis encompassed 9,176 participants, evaluating clinical attributes alongside smoking-related characteristics such as duration of cigarette consumption, and levels of nicotine, tar, and carbon monoxide. We employed weighted univariate logistic regression and restricted cubic splines to examine the association between smoking indicators and stroke risk, complemented by subgroup analyses for demographic differentiation. RESULTS: The overall prevalence of stroke in our cohort was 3.4%. Statistically significant associations were found between stroke incidence and factors such as age, gender, education, and marital status (p < 0.05). Adjusted logistic regression models showed increased odds ratios (ORs) for stroke with higher nicotine and carbon monoxide levels across progressively adjusted models: Model 1 (unadjusted), Model 2 (adjusted for age, gender), Model 3 (further adjusted for education, marital status, BMI, PIR), and Model 4 (fully adjusted for additional factors including hypertension, hyperlipidemia, diabetes, and drinking). Specifically, ORs for nicotine increased from 2.39 in Model 1 to 2.64 in Model 4; for carbon monoxide, from 1.10 to 1.11 over the same models.​The threshold analysis using restricted cubic splines revealed critical points for stroke risk increase at smoke exposure levels of 410 units, tar 12 mg, nicotine 1.1 mg, and carbon monoxide 12 ppm. Above these thresholds, stroke risk escalates significantly. Additionally, the presence of family smoking history was associated with higher stroke risks compared to those without such history. CONCLUSION: This study confirms that smoking significantly contributes to increased stroke risk, particularly through exposure to nicotine and carbon monoxide. The findings emphasize the necessity for tailored stroke prevention strategies that specifically address smoking behaviors and consider demographic susceptibilities. Incorporating smoking-related indicators into risk assessment models could enhance the precision of stroke prevention efforts.

Associations of oxidative balance score with lumbar spine osteopenia in 20-40 years adults: NHANES 2011-2018.

PURPOSE: Current research suggests that oxidative stress may decrease bone mineral density (BMD) by disrupting bone metabolism balance. However, no study investigated the relationship between systemic oxidative stress status and adult BMD. This study aims to investigate whether oxidative balance score (OBS) is associated with BMD in adults under 40. METHODS: 3963 participants were selected from the National Health and Nutrition Survey (NHANES) from 2011 to 2018. OBS is scored based on 20 dietary and lifestyle factors. Weighted multiple logistic regression and restricted cubic splines were used to assess the correlation between OBS and osteopenia. RESULTS: After adjusting for confounding factors, the weighted logistic regression results showed that compared with the first tertile of OBS, the highest tertile had a 38% (OR: 0.62, 95% CI: 0.47-0.82) lower risk of osteopenia. The restrictive cubic spline curve indicates a significant nonlinear correlation between OBS and the risk of osteopenia. CONCLUSION: The research findings emphasize the relationship between OBS and the risk of osteopenia in young adults. Adopting an antioxidant diet and lifestyle may help young adults to maintain bone mass.

Phosphorus fertilization enhanced overwintering, root system and forage yield of late-seeded alfalfa in sodic soils.

Sowing date and soil fertility are very important factors in the overwintering and production performance of alfalfa (Medicago sativa L.), yet there's a knowledge gap in knowledge on how late-seeded alfalfa responds to phosphorus (P) fertilization. A field study was conducted in Inner Mongolia from 2020 to 2022 using a split-plot design. The main plots consisted of five sowing dates (31 July, 8, 16, and 24 August, and 1 September), while the subplots involved five P application rates (0, 40, 70, 100, and 130 kg P2O5 ha-1). Throughout the growing seasons, the overwintering rate, root traits, forage yield, and yield components were measured. The results revealed a consistent decrease in overwintering ability and productivity with the delayed sowing. This reduction in overwintering rate was mainly due to diminished root traits, while the decrease in forage yield was largely associated with a reduction in plants per square meter. However, P fertilizer application to late-seeded alfalfa demonstrated potential in enhancing the diameter of both the crown and taproot, thus strengthening the root system and improving the overwintering rate, the rate of increase ranges from 11.6 to 49%. This adjustment could also improve the shoots per square meter and mass per shoot, increasing by 9.4-31.3% and 15.0-27.1% respectively in 2 years, which can offset the decline in forage yield caused by late sowing and might even increase the forage yield. Regression and path analysis indicated that alfalfa forage yield is primarily affected by mass per shoot rather than shoots per square meter. This study recommended that the sowing of alfalfa in similar regions of Inner Mongolia should not be later than mid-August. Moreover, applying P fertilizer (P2O5) at 70.6-85.9 kg ha-1 can enhance the forage yield and persistence of late-seeded alfalfa. Therefore, appropriate late sowing combined with the application of P fertilizer can be used as an efficient cultivation strategy for alfalfa cultivation after a short-season crop harvest in arid and cold regions.

Unraveling the impact of Spartina alterniflora invasion on greenhouse gas production and emissions in coastal saltmarshes: New insights from dissolved organic matter characteristics and surface-porewater interactions.

Saltmarshes along the Chinese coast are threatened by the invasion of Spartina alterniflora (S. alterniflora). This study was carried out in the Andong Shoal, Hangzhou Bay, China, with the aim of comprehending the intricate impacts of S. alterniflora invasion on greenhouse gases (GHG) production and emissions. To address this issue, we thoroughly examined the chemistry of dissolved organic matter (DOM) and the rate of surface water-porewater interaction. Porewater and surface water samples were collected from farm land, S. alterniflora invaded areas, and Scirpus mariqueter (S. mariqueter) dominated areas. The findings indicated that the invasion of S. alterniflora impeded the interaction between surface water and porewater, resulting in reduced porewater exchange rates within its affected region (0.015-0.440 cm d-1), in contrast to areas dominated by S. mariqueter (9.635-18.232 cm d-1). The invasion also increased dissolved organic carbon concentration in porewater and created a stable and closed soil environment that resulted in DOM with smaller molecule sizes and higher humification levels. The presence of high tryptophan-like fluorescent DOM caused an increase in the production of methane and carbon dioxide in S. alterniflora invaded area. However, both limited surface-porewater exchange and significant differences in GHG concentrations between porewater and surface water suggested that the aerenchyma tissues of S. alterniflora may play an important role in transporting GHG from soil to the atmosphere.

Natural Language Processing-Driven Artificial Intelligence Models for the Diagnosis of Lumbar Disc Herniation with L5 and S1 Radiculopathy: A Preliminary Evaluation.

OBJECTIVE: To develop and validate natural language processing-driven artificial intelligence (AI) models for the diagnosis of lumbar disc herniation (LDH) with L5 and S1 radiculopathy using electronic health records (EHRs). METHODS: EHRs of patients undergoing single-level percutaneous endoscopic lumbar discectomy for the treatment of LDH at the L4/5 or L5/S1 level between June 1, 2013, and December 31, 2021, were collected. The primary outcome was LDH with L5 and S1 radiculopathy, which was defined as nerve root compression recorded in the operative notes. Datasets were created using the history of present illness text and positive symptom text with radiculopathy (L5 or S1), respectively. The datasets were randomly split into a training set and a testing set in a 7:3 ratio. Two machine learning models, the long short-term memory network and Extreme Gradient Boosting, were developed using the training set. Performance evaluation of the models on the testing set was done using measures such as the receiver operating characteristic curve, area under the curve, accuracy, recall, F1-score, and precision. RESULTS: The study included a total of 1681 patients, with 590 patients having L5 radiculopathy and 1091 patients having S1 radiculopathy. Among the 4 models developed, the long short-term memory model based on positive symptom text showed the best discrimination in the testing set, with precision (0.9054), recall (0.9405), accuracy (0.8950), F1-score (0.9226), and area under the curve (0.9485). CONCLUSIONS: This study provides preliminary validation of the concept that natural language processing-driven AI models can be used for the diagnosis of lumbar disease using EHRs. This study could pave the way for future research that may develop more comprehensive and clinically impactful AI-driven diagnostic systems.

Machine learning-based antibiotic resistance prediction models: An updated systematic review and meta-analysis.

BACKGROUND: The widespread use of antibiotics has led to a gradual adaptation of bacteria to these drugs, diminishing the effectiveness of treatments. OBJECTIVE: To comprehensively assess the research progress of antibiotic resistance prediction models based on machine learning (ML) algorithms, providing the latest quantitative analysis and methodological evaluation. METHODS: Relevant literature was systematically retrieved from databases, including PubMed, Embase and the Cochrane Library, from inception up to December 2023. Studies meeting predefined criteria were selected for inclusion. The prediction model risk of bias assessment tool was employed for methodological quality assessment, and a random-effects model was utilised for meta-analysis. RESULTS: The systematic review included a total of 22 studies with a combined sample size of 43,628; 10 studies were ultimately included in the meta-analysis. Commonly used ML algorithms included random forest, decision trees and neural networks. Frequently utilised predictive variables encompassed demographics, drug use history and underlying diseases. The overall sensitivity was 0.57 (95% CI: 0.42-0.70; p< 0.001; I2= 99.7%), the specificity was 0.95 (95% CI: 0.79-0.99; p< 0.001; I2 = 99.9%), the positive likelihood ratio was 10.7 (95% CI: 2.9-39.5), the negative likelihood ratio was 0.46 (95% CI: 0.34-0.61), the diagnostic odds ratio was 23 (95% CI: 7-81) and the area under the receiver operating characteristic curve was 0.78 (95% CI: 0.74-0.81; p< 0.001), indicating a good discriminative ability of ML models for antibiotic resistance. However, methodological assessment and funnel plots suggested a high risk of bias and publication bias in the included studies. CONCLUSION: This meta-analysis provides a current and comprehensive evaluation of ML models for predicting antibiotic resistance, emphasising their potential application in clinical practice. Nevertheless, stringent research design and reporting are warranted to enhance the quality and credibility of future studies. Future research should focus on methodological innovation and incorporate more high-quality studies to further advance this field.

Polyphenols as Potential Antioxidants for the Treatment of Intervertebral Disc Degeneration.

Intervertebral disc degeneration (IDD) is a common musculoskeletal system disease, which is one of the most important causes of low back pain. Despite the high prevalence of IDD, current treatments are limited to relieving symptoms, and there are no effective therapeutic agents that can block or reverse the progression of IDD. Oxidative stress, the result of an imbalance between the production of reactive oxygen species (ROS) and clearance by the antioxidant defense system, plays an important role in the progression of IDD. Polyphenols are antioxidant compounds that can inhibit ROS production, which can scavenge free radicals, reduce hydrogen peroxide production, and inhibit lipid oxidation in nucleus pulposus (NP) cells and IDD animal models. In this review, we discussed the antioxidant effects of polyphenols and their regulatory role in different molecular pathways associated with the pathogenesis of IDD, as well as the limitations and future prospects of polyphenols as a potential treatment of IDD.

The Effects of Assisted Freezing with Different Ultrasound Power Rates on the Quality and Flavor of Braised Beef.

This study investigated the effects of ultrasound-assisted immersion freezing (UIF) at different power rates (0, 200, 400, and 600 W) on the changes in beef quality and flavor after braising. The results demonstrated that UIF treatment at 400 W significantly reduced the juice loss (cooking loss decreased from 49.04% to 39.74%) and fat oxidation (TBARS value decreased from 0.32 mg/kg to 0.20 mg/kg) of braised beef. In addition, the tenderness (hardness value decreased from 5601.50 g to 2849.46 g) and color stability of braised beef were improved after UIF treatment. The flavor characteristics of braised beef were characterized using an electronic nose and an electronic tongue. The PCA analysis data showed that the cumulative contribution rates of the first and second principal components were 85% and 93.2%, respectively, with the first principal component accounting for a higher proportion. The UIF-400 W group had the highest concentration for the first principal component, and the differentiation was not significant compared to the control group. The total amino acid values of different power UIF treatment groups were improved compared to the AF treatment group, indicating that UIF can effectively reduce the losses caused by freezing. The results demonstrate that ultrasound-assisted freezing treatment is beneficial in enhancing the tenderness and flavor attributes of beef after braising, providing new insights into the processing of meat products with desirable quality characteristics.

A Mendelian randomization investigation of the causal association between the gut microbiota and sleep disorders.

Background: Increasing numbers of people are suffering from sleep disorders. The gut microbiota of these individuals differs significantly. However, no reports are available on the causal associations between specific gut microbiota and sleep disorders. Methods: Data on gut genera were obtained from the MiBioGen consortium. Twenty-four cohorts with 18,340 individuals of European origin were included. Sleep disorder data, which included 216,454 European individuals, were retrieved from the FinnGen Biobank. Subsequently, two-sample Mendelian randomization was performed to analyze associations between sleep disorders and specific components of the gut microbiota. Results: Inverse variance weighting (IVW) revealed a negative correlation between Coprobacter and sleep disorders (OR = 0.797, 95% CI = 0.66-0.96, and p = 0.016), a positive correlation between Lachnospiraceae and sleep disorders (OR = 1.429, 95% CI = 1.03-1.98, and p = 0.032), a negative association between Oscillospira and sleep disorders (OR = 0.745, 95% CI = 0.56-0.98, and p = 0.038), and a negative association between Peptococcus and sleep disorders (OR = 0.858, 95% CI = 0.74-0.99, p = 0.039). Conclusion: A significant causal relationship was found between four specific gut microbiota and sleep disorders. One family, Lachnospiraceae, was observed to increase the risk of sleep disorders, while three genera, namely, Coprobacter, Oscillospira, and Peptococcus, could reduce the risk of sleep disorders. However, further investigations are needed to confirm the specific mechanisms by which the gut microbiota affects sleep.

Development and validation of a nomogram for predicting the prognosis in children with spinal cord injuries.

AIMS: This research aims to construct and verify an accurate nomogram for forecasting the 3-, 5-, and 7-year outcomes in pediatric patients afflicted with spinal cord injury (SCI). METHODS: Pediatric patients with SCI from multiple hospitals in China, diagnosed between Jan 2005 and Jan 2020, were incorporated into this research. Half of these patients were arbitrarily chosen for training sets, and the other half were designated for external validation sets. The Cox hazard model was employed to pinpoint potential prognosis determinants related to the American Spinal Injury Association (ASIA) and Functional Independence Assessment (FIM) index. These determinants were then employed to formulate the prognostic nomogram. Subsequently, the bootstrap technique was applied to validate the derived model internally. RESULTS: In total, 224 children with SCI were considered for the final evaluation, having a median monitoring duration of 68.0 months. The predictive nomogram showcased superior differentiation capabilities, yielding a refined C-index of 0.924 (95% CI: 0.883-0.965) for the training cohort and a C-index of 0.863 (95% CI: 0.735-0.933) for the external verification group. Additionally, when applying the aforementioned model to prognostic predictions as classified by the FIM, it demonstrated a high predictive value with a C-index of 0.908 (95% CI: 0.863-0.953). Moreover, the calibration diagrams indicated a consistent match between the projected and genuine ASIA outcomes across both sets. CONCLUSION: The crafted and verified prognostic nomogram emerges as a dependable instrument to foresee the 3-, 5-, and 7-year ASIA and FIM outcomes for children suffering from SCI.

Characterization of radial artery perforation patterns using optical coherence tomography.

BACKGROUND: The characterization of radial artery perforation (RAP) patterns using optical coherence tomography (OCT) has not been well established. This study aimed to identify the characteristic RAP patterns in patients diagnosed through post-procedural OCT examination. METHODS: This retrospective study included 1936 consecutive patients who underwent radial artery (RA) OCT following OCT-guided transradial coronary intervention (TRI) from January 2016 to July 2022. Data regarding RAP characteristics were collected through OCT, including the perforation site as well as dimensions such as the length, width, and arc. Furthermore, RAP types were classified as small or large perforations, with a cut-off arc value of ≤90°. RESULTS: RAP, as identified by RA angiography (RAA) during TRI and on post-procedural OCT, was found in 16 out of 1936 patients (0.83 %). RA OCT imaging showed that the median distance between the RA ostium and the perforation site, the perforation length, width, and arc were 30.6 (14.4-42.2) mm, 1.55 (1.03-1.92) mm, 0.74 (0.60-1.14) mm, and 42.5 (25.0-58.1) °, respectively. Small perforations (arc ≤90°) were observed in 14 out of the 16 (87.5 %) patients with RAP. Post-procedural RAA revealed that 15 out of the 16 (93.7 %) patients with RAP had sealed perforations, with the remaining patient requiring external compression. CONCLUSIONS: Our findings demonstrated that RAP is uncommon during TRI, with clearly defined characteristic patterns on OCT. Most RAPs are small and tend to spontaneous seal through catheter tamponade.

Identification and quantification of nanoplastics in different crops using pyrolysis gas chromatography-mass spectrometry.

Quantitative studies of nanoplastics (NPs) abundance on agricultural crops are crucial for understanding the environmental impact and potential health risks of NPs. However, the actual extent of NP contamination in different crops remains unclear, and therefore insufficient quantitative data are available for adequate exposure assessments. Herein, a method with nitric acid digestion, multiple organic extraction combined with pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) quantification was used to determine the chemical composition and mass concentration of NPs in different crops (cowpea, flowering cabbage, rutabagas, and chieh-qua). Recoveries of 74.2-109.3% were obtained for different NPs in standard products (N = 6, RSD <9.6%). The limit of detection (LOD) and the limit of quantitation (LOQ) were 0.02-0.5 µg and 0.06-1.5 µg, respectively. The detection method for NPs exhibited good external calibration curves and linearity with 0.99. The results showed that poly (vinylchloride) (PVC), poly (ethylene terephthalate) (PET), polyethylene (PE), and polyadiohexylenediamine (PA66) NPs could be detected in crop samples, although the accumulation levels associated with the various crops varied significantly. PVC (N.D.-954.3 mg kg-1, dry weight (DW)) and PE (101.3-462.9 mg kg-1, DW) NPs were the dominant components in the samples of all four crop species, while high levels of PET (414.3-1430.1 mg kg-1, DW) NPs were detected in cowpea samples. Furthermore, there were notable differences in the accumulation levels of various edible crop parts, such as stems (60.2%) > leaves (39.8%) in flowering cabbage samples and peas (58.8%) > pods (41.2%) in cowpea samples. This study revealed the actual extent of NP contamination in different types of crops and provided crucial reference data for future research.

Automated machine learning-based model for the prediction of pedicle screw loosening after degenerative lumbar fusion surgery.

The adequacy of screw anchorage is a critical factor in achieving successful spinal fusion. This study aimed to use machine learning algorithms to identify critical variables and predict pedicle screw loosening after degenerative lumbar fusion surgery. A total of 552 patients who underwent primary transpedicular lumbar fixation for lumbar degenerative disease were included. The LASSO method identified key features associated with pedicle screw loosening. Patient clinical characteristics, intraoperative variables, and radiographic parameters were collected and used to construct eight machine learning models, including a training set (80% of participants) and a test set (20% of participants). The XGBoost model exhibited the best performance, with an AUC of 0.884 (95% CI: 0.825-0.944) in the test set, along with the lowest Brier score. Ten crucial variables, including age, disease diagnosis: degenerative scoliosis, number of fused levels, fixation to S1, HU value, preoperative PT, preoperative PI-LL, postoperative LL, postoperative PT, and postoperative PI-LL were selected. In the prospective cohort, the XGBoost model demonstrated substantial performance with an accuracy of 83.32%. This study identified crucial variables associated with pedicle screw loosening after degenerative lumbar fusion surgery and successfully developed a machine learning model to predict pedicle screw loosening. The findings of this study may provide valuable information for clinical decision-making.

Novel solid self-emulsifying drug delivery system to enhance oral bioavailability of cabazitaxel.

In this study, a novel cabazitaxel solid self-emulsifying drug delivery system (CTX S-SEDDS) was developed by solvent evaporation and liquid-solid compression technology, which overcame the limitations of the traditional SEDDS and improved the oral bioavailability. From the results of solubility, pseudo-ternary phase diagram, and single-factor analysis, Tween 80 (surfactant), Tricaprylin (oil), and Glyceryl monooleate (oil) with the ratio of 30:55:15 showed optimized particle size (140.87 nm), short emulsification and high cabazitaxel (CTX) loading capacity (50 mg·g-1). Based on the liquid-solid compression mathematical model, Syloid XDP3050 was determined as carrier material and Syloid 244FP as coating material. The prepared CTX S-SEDDS showed excellent flowability, tabletability, and reconstitution property. In vivo pharmacokinetics in rats demonstrated the absolute bioavailability of CTX S-SEDDS (17.27 %) was significantly enhanced compared with CTX solution (1.69 %), which was close to that of CTX-SEDSS (20.48 %). Lymphatic absorption was verified by in vitro imaging to be an important absorption route for self-emulsifying preparations. These results suggested that CTX S-SEDDS could enhance oral bioavailability of poorly water-soluble drug cabazitaxel while avoiding SEDDS limitations and harnessing the dual advantages of solid and liquid preparations.