π-π conjugated PDI supramolecular regulating the photoluminescence of imine-COFs for sensitive smartphone visual detection of levofloxacin.

As the contamination and enrichment in food chain of levofloxacin (LV) antibiotics have caused a significant threat to life safety, the instant detection of LV has become an urgent need. Here, a PDI-functionalized imine-based covalent organic framework (PDI-COF300) was prepared by the electrostatic self-assembly method as fluorescent probe for smartphone visual detection of LV, which exhibited excellent fluorescence quantum yield (82.68%), greater stability, high sensitivity with detection limit of 0.303 µM. Based on the results of molecular docking and Stern-Volmer equation, the LV detection by PDI-COF300 was mainly a static quenching process through π-π stacked hydrophobic interactions and fluorescence resonance energy transfer. Besides, PDI-COF300 was applied to LV detection in environmental medium and milk samples with recoveries from 85.56% to 108.34% and relative standard deviations <2.70%. This work also provided a new general strategy for using PDI-COF in smartphone devices and fluorescent papers for LV fluorescence detection and microanalysis.

Cereal-Derived Water-Unextractable Arabinoxylans: Structure Feature, Effects on Baking Products and Human Health.

Arabinoxylans (AXs) are non-starch polysaccharides with complex structures naturally occurring in grains (i.e., barley, corn, and others), providing many health benefits, especially as prebiotics. AXs can be classified as water-extractable (WEAX) and water-unextractable (WUAX) based on their solubility, with properties influenced by grain sources and extraction methods. Numerous studies show that AXs exert an important health impact, including glucose and lipid metabolism regulation and immune system enhancement, which is induced by the interactions between AXs and the gut microbiota. Recent research underscores the dependence of AX physiological effects on structure, advocating for a deeper understanding of structure-activity relationships. While systematic studies on WEAX are prevalent, knowledge gaps persist regarding WUAX, despite its higher grain abundance. Thus, this review reports recent data on WUAX structural properties (chemical structure, branching, and MW) in cereals under different treatments. It discusses WUAX applications in baking and the benefits deriving from gut fermentation.

Remnant cholesterol and the risk of diabetic nephropathy progression to end-stage kidney disease in patients with type 2 diabetes mellitus: a longitudinal cohort study.

AIM: Diabetic nephropathy (DN) is the most common cause of end-stage kidney disease (ESKD). Remnant cholesterol has been investigated as a predictor for the progression of DN in type 1 diabetes mellitus patients, as well as the incidence of DN in type 2 diabetes mellitus (T2DM) patients. This study aimed to evaluate the longitudinal relationship between baseline remnant cholesterol and kidney outcomes using a Chinese T2DM with biopsy-confirmed DN cohort. METHODS: We included 334 patients with T2DM and biopsy-confirmed DN during 2010-2019 West China Hospital T2DM-DN cohort. Remnant cholesterol was defined by Martin-Hopkins equation. Patients were divided into four groups based on the median (IQR) remnant cholesterol concentration at the time of renal biopsy. The kidney outcome was defined as ESKD, which was defined as the need for chronic kidney replacement therapy or estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m2. The relationship between remnant cholesterol and kidney outcome was analyzed using the Kaplan‒Meier method and Cox regression analysis. RESULTS: The mean age was 51.1 years, and 235 (70%) were men. During follow-up, a total of 121 (36.2%) patients reached ESKD. The Kaplan‒Meier analysis showed that patients in the highest quartile (quartile 4) group had lower cumulative renal survival (log-rank test, p = 0.033) and shorter median renal survival time [34.0 (26.4-41.6) vs. 55.0 (29.8-80.2) months] than patients in the lowest quartile (quartile 1) group. By univariate analysis, the high remnant cholesterol group was associated with a higher risk of progression to ESKD. Moreover, the risk of progression to ESKD in the highest quartile was still 2.857-fold (95% CI 1.305-6.257, p = 0.009) higher than that in the lowest quartile, and one-SD increase of remnant cholesterol was associated with a higher risk (HR = 1.424; 95% CI 1.075-1.886, p = 0.014) of progression to ESKD, after adjusted for confounding factors. CONCLUSIONS: High remnant cholesterol is independently associated with a higher risk of ESKD in patients with T2DM-DN, and it may be a new noninvasive marker of ESKD. CLINICAL RELEVANCE: Calculated remnant cholesterol has the advantages of being economical and clinically accessible. Moreover, to our knowledge, there are no longitudinal cohort studies for investigating the risk of progression of T2DM-DN to ESKD. In our study, higher remnant cholesterol was associated with a higher risk of ESKD in patients with T2DM-DN, and it may be a new noninvasive predictor of ESKD.

Large-scale flood modeling and forecasting with FloodCast.

Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to accurately forecast flood crests and issue time-critical hazard warnings. In this work, we build a fast, stable, accurate, resolution-invariant, and geometry-adaptive flood modeling and forecasting framework that can perform at large scales, namely FloodCast. The framework comprises two main modules: multi-satellite observation and hydrodynamic modeling. In the multi-satellite observation module, a real-time unsupervised change detection method and a rainfall processing and analysis tool are proposed to harness the full potential of multi-satellite observations in large-scale flood prediction. In the hydrodynamic modeling module, a geometry-adaptive physics-informed neural solver (GeoPINS) is introduced, benefiting from the absence of a requirement for training data in physics-informed neural networks (PINNs) and featuring a fast, accurate, and resolution-invariant architecture with Fourier neural operators. To adapt to complex river geometries, we reformulate PINNs in a geometry-adaptive space. GeoPINS demonstrates impressive performance on popular partial differential equations across regular and irregular domains. Building upon GeoPINS, we propose a sequence-to-sequence GeoPINS model to handle long-term temporal series and extensive spatial domains in large-scale flood modeling. This model employs sequence-to-sequence learning and hard-encoding of boundary conditions. Next, we establish a benchmark dataset in the 2022 Pakistan flood using a widely accepted finite difference numerical solution to assess various flood simulation methods. Finally, we validate the model in three dimensions - flood inundation range, depth, and transferability of spatiotemporal downscaling - utilizing SAR-based flood data, traditional hydrodynamic benchmarks, and concurrent optical remote sensing images. Traditional hydrodynamics and sequence-to-sequence GeoPINS exhibit exceptional agreement during high water levels, while comparative assessments with SAR-based flood depth data show that sequence-to-sequence GeoPINS outperforms traditional hydrodynamics, with smaller simulation errors. The experimental results for the 2022 Pakistan flood demonstrate that the proposed method enables high-precision, large-scale flood modeling with an average MAPE of 14.93 % and an average Mean Absolute Error (MAE) of 0.0610 m for 14-day water depth simulations while facilitating real-time flood hazard forecasting using reliable precipitation data.

Microbial communities reveal niche partitioning across the slope and bottom zones of the challenger deep.

Widespread marine microbiomes exhibit compositional and functional differentiation as a result of adaptation driven by environmental characteristics. We investigated the microbial communities in both seawater and sediments on the slope (7-9 km) and the bottom (9-11 km) of the Challenger Deep of the Mariana Trench to explore community differentiation. Both metagenome-assembled genomes (MAGs) and 16S rRNA amplicon sequence variants (ASVs) showed that the microbial composition in the seawater was similar to that of sediment on the slope, while distinct from that of sediment in the bottom. This scenario suggested a potentially stronger community interaction between seawater and sediment on the slope, which was further confirmed by community assembly and population movement analyses. The metagenomic analysis also indicates a specific stronger potential of nitrate reduction and sulphate assimilation in the bottom seawater, while more versatile nitrogen and sulphur cycling pathways occur on the slope, reflecting functional differentiations among communities in conjunction with environmental features. This work implies that microbial community differentiation occurred in the different hadal niches, and was likely an outcome of microbial adaptation to the extreme hadal trench environment, especially the associated hydrological and geological conditions, which should be considered and measured in situ in future studies.

Computational modeling for the quantitative assessment of cardiac autonomic response to orthostatic stress.

Objective.The autonomic nervous system (ANS) plays a critical role in regulating not only cardiac functions but also various other physiological processes, such as respiratory rate, digestion, and metabolic activities. The ANS is divided into the sympathetic and parasympathetic nervous systems, each of which has distinct but complementary roles in maintaining homeostasis across multiple organ systems in response to internal and external stimuli. Early detection of ANS dysfunctions, such as imbalances between the sympathetic and parasympathetic branches or impairments in the autonomic regulation of bodily functions, is crucial for preventing or slowing the progression of cardiovascular diseases. These dysfunctions can manifest as irregularities in heart rate, blood pressure regulation, and other autonomic responses essential for maintaining cardiovascular health. Traditional methods for analyzing ANS activity, such as heart rate variability (HRV) analysis and muscle sympathetic nerve activity recording, have been in use for several decades. Despite their long history, these techniques face challenges such as poor temporal resolution, invasiveness, and insufficient sensitivity to individual physiological variations, which limit their effectiveness in personalized health assessments.Approach.This study aims to introduce the open-loop Mathematical Model of Autonomic Regulation of the Cardiac System under Supine-to-stand Maneuver (MMARCS) to overcome the limitations of existing ANS analysis methods. The MMARCS model is designed to offer a balance between physiological fidelity and simplicity, focusing on the ANS cardiac control subsystems' input-output curve. The MMARCS model simplifies the complex internal dynamics of ANS cardiac control by emphasizing input-output relationships and utilizing sensitivity analysis and parameter subset selection to increase model specificity and eliminate redundant parameters. This approach aims to enhance the model's capacity for personalized health assessments.Main results.The application of the MMARCS model revealed significant differences in ANS regulation between healthy (14 females and 19 males, age: 42 ± 18) and diabetic subjects (8 females and 6 males, age: 47 ± 14). Parameters indicated heightened sympathetic activity and diminished parasympathetic response in diabetic subjects compared to healthy subjects (p < 0.05). Additionally, the data suggested a more sensitive and potentially more reactive sympathetic response among diabetic subjects (p < 0.05), characterized by increased responsiveness and intensity of the sympathetic nervous system to stimuli, i.e. fluctuations in blood pressure, leading to more pronounced changes in heart rate, these phenomena can be directly reflected by gain parameters and time response parameters of the model.Significance.The MMARCS model represents an innovative computational approach for quantifying ANS functionality. This model guarantees the accuracy of physiological modeling while reducing mathematical complexity, offering an easy-to-implement and widely applicable tool for clinical measurements of cardiovascular health, disease progression monitoring, and home health monitoring through wearable technology.

Lower energy intake associated with higher risk of cardiovascular mortality in chronic kidney disease patients on a low-protein diets.

OBJECTIVE: An increasing number of studies shown that inadequate energy intake causes an increase in adverse incidents in chronic kidney disease (CKD) patients on low-protein diets (LPD). The study aimed to investigate the relationship between energy intake and cardiovascular mortality in CKD patients on a LPD. METHODS: This was a cross-sectional study, a total of 4264 CKD patients were enrolled from the NHANES database between 2009 and 2018. Restricted cubic spline plots and Cox regression analysis were used to analyze the association between energy intake and cardiovascular mortality in CKD patients on a LPD. Additionally, a nomogram was constructed to estimate cardiovascular survival in CKD patients on a LPD. RESULTS: Among CKD patients on a LPD in the United States, 90.05% had an energy intake of less than 25 kcal/kg/day, compared to 36.94% in CKD patients on a non-LPD. Energy intake and cardiovascular mortality showed a linear relationship in CKD patients on a LPD, while a 'U-shaped' relationship was observed in CKD patients on a non-LPD. Multifactorial Cox regression models revealed that for Per-standard deviation (Per-SD) decrement in energy intake, the risk of cardiovascular mortality increased by 41% (HR: 1.41, 95% CI: 1.12, 1.77; P = 0.004) in CKD patients on a LPD. The concordance index of the nomogram was 0.79 (95% CI, 0.75, 0.83). CONCLUSION: CKD patients, especially those on a LPD, have significantly inadequate energy intake. Lower energy intake is associated with higher cardiovascular mortality in CKD patients on a LPD.

Impact of non-alcoholic fatty liver disease and fibrosis on mortality and kidney outcomes in patients with type 2 diabetes and chronic kidney disease: A multi-cohort longitudinal study.

AIM: To evaluate the impact of non-alcoholic fatty liver disease (NAFLD) presence and fibrosis risk on adverse outcomes in patients with type 2 diabetes and chronic kidney disease. METHODS: Data were sourced from two longitudinal cohorts: 1172 patients from the National Health and Nutrition Examination Survey (NHANES) and 326 patients from the kidney biopsy cohort at the West China Hospital of Sichuan University. Cox regression estimated hazard ratios (HRs) for NAFLD and liver fibrosis concerning adverse clinical outcomes. Subsequently, a two-sample Mendelian randomization study using genome-wide association study statistics explored NAFLD's potential causal link to cardio-cerebrovascular events. RESULTS: In the NHANES cohort, NAFLD stood as an independent risk factor for various outcomes: overall mortality [HR 1.53 (95% confidence interval, CI 1.21-1.95)], mortality because of cardio-cerebrovascular diseases [HR 1.63 (95% CI 1.12-2.37)], heart disease [HR 1.58 (95% CI 1.00-2.49)], and cerebrovascular disease [HR 3.95 (95% CI 1.48-10.55)]. Notably, advanced liver fibrosis, identified by a fibrosis-4 (FIB-4) score >2.67, exhibited associations with overall mortality, cardio-cerebrovascular disease mortality and heart disease mortality. Within the kidney biopsy cohort, NAFLD correlated with future end-stage kidney disease [ESKD; HR 2.17 (95% CI 1.41-3.34)], while elevated FIB-4 or NAFLD Fibrosis Scores predicted future ESKD, following full adjustment. Liver fibrosis was positively correlated with renal interstitial fibrosis and tubular atrophy in biopsies. Further Mendelian randomization analysis supported a causal relationship between NAFLD and cardio-cerebrovascular events. CONCLUSIONS: In patients with type 2 diabetes and chronic kidney disease, the NAFLD presence and elevated FIB-4 scores link to heightened mortality risk and ESKD susceptibility. Moreover, NAFLD shows a causal relationship with cardio-cerebrovascular events.

Adaptor protein CEMIP reduces the chemosensitivity of small cell lung cancer via activation of an SRC-YAP oncogenic module.

Small cell lung cancer (SCLC) is a recalcitrant malignancy with dismal prognosis due to rapid relapse after an initial treatment response. More effective treatments for SCLC are desperately needed. Our previous studies showed that cell migration-inducing hyaluronan binding protein (CEMIP) functionally promotes SCLC cell proliferation and metastasis. In this study, we investigated whether and how CEMIP regulates the chemosensitivity of SCLC. Through the GDSC database, we found that CEMIP expression levels were positively correlated with the IC50 values of several commonly used chemotherapeutic drugs in SCLC cells (cisplatin, gemcitabine, 5-fluorouracil and cyclophosphamide). We demonstrated that overexpression or knockdown of CEMIP in SCLC cells resulted in a notable increase or reduction in the IC50 value of cisplatin or etoposide, respectively. We further revealed that CEMIP functions as an adaptor protein in SCLC cells to interact with SRC and YAP through the 1-177 aa domain and 820-1361 aa domain, respectively, allowing the autophosphorylation of Y416 and activation of SRC, thus facilitating the interaction between YAP and activated SRC, and resulting in increased phosphorylation of Y357, protein stability, nuclear accumulation and transcriptional activation of YAP. Overexpressing SRC or YAP counteracted the CEMIP knockdown-mediated increase in the sensitivity of SCLC cells to cisplatin and etoposide. The combination of the SRC inhibitor dasatinib or the YAP inhibitor verteporfin and cisplatin/etoposide (EP regimen) displayed excellent synergistic antitumor effects on SCLC both in vitro and in vivo. This study demonstrated that targeted therapy against the CEMIP/SRC/YAP complex is a potential strategy for SCLC and provides a rationale for the development of future clinical trials with translational prospects.

A Ru-porphyrin metal-organic framework with Mn2+ paddlewheel nodes for the selective oxidation of C(sp3)-H bonds.

The activation and selective functionalization of inert C(sp3)-H bonds is fundamental for industrial applications and occupies a very important place in industry, but it remains a great challenge in current synthetic chemistry. In this paper, we report an approach for activating reactive tert-butyl peroxyl radicals by modifying Ru-porphyrin into metal-organic frameworks (MOFs) for the activation of inert C(sp3)-H bonds. Under mild conditions, the Ru-porphyrinyl MOF can activate the peroxyl radical, extracting a hydrogen atom from the inert C(sp3)-H bond. Mn2+ paddlewheels with unsaturated coordination sites were introduced into the MOF, and direct oxidative conversion using environmentally friendly oxygen provides a new pathway to activate the inert C(sp3)-H bond.

The Combined Use of Fine-Needle Aspiration (FNA) and BRAF V600E Gene Testing: Can it Increase the Definitive Diagnosis Rate of Nodules Categorized as Bethesda III for Papillary Thyroid Carcinoma?

OBJECTIVE: This study aimed to analyze the malignant probability of thyroid nodules diagnosed as indeterminate cytology, including atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS), and investigate the diagnostic value of combining BRAF V600E gene testing within this classification. METHODS: We conducted a retrospective analysis of 126 patients who underwent fine-needle aspiration (FNA) examination of thyroid nodules and subsequent surgical treatment at Beijing Haidian Hospital between October 2021 and November 2022. Among them, there were 22 male and 104 female patients, aged between 18 and 75 years old. Surgical pathology results were considered the gold standard for diagnosing the nature of thyroid nodules, evaluating the malignant incidence of cytological results categorized as AUS/FLUS. Fisher's exact test and diagnostic test evaluation methods were used to analyze the discriminatory diagnostic efficacy of preoperative FNA combined with BRAF V600E gene testing for papillary thyroid carcinoma (PTC). Statistical analysis was performed using SPSS 22.0 software. RESULTS: In PTC patients, the BRAF V600E gene mutation rate was 87.93% (102/116). Within the category of FNA results as AUS/FLUS, the proportion of PTC was 60.00% (15/25). The specificity, sensitivity, positive predictive value, and negative predictive value of the BRAF V600E gene mutation in diagnosing PTC within the AUS/FLUS category were 10/10, 6/15, 6/6, and 10/19, respectively. The BRAF V600E gene mutation significantly increased the detection rate of PTC in patients classified under this cytology (P = 0.028, <0.05). CONCLUSION: Preoperative FNA combined with BRAF V600E gene mutation testing significantly enhances the malignant detection rate of thyroid nodules diagnosed cytologically as AUS/FLUS. This combined approach provides a potent tool to improve diagnostic accuracy in this indeterminate classification.

Connectome-based Brain Marker Moderates the Relationship between Childhood Adversity and Transdiagnostic Psychopathology during Early Adolescence.

Importance: Identifying brain-based markers of resiliency that reliably predict who is and is not at elevated risk for developing psychopathology among children who experience adverse childhood experiences (ACEs) is important for improving our mechanistic understanding of these etiological links between child adversity and psychopathology and guiding precision medicine and prevention efforts for reducing psychiatric impact of ACEs. Objective: To examine associations between ACEs and transdiagnostic psychopathology during the transition from preadolescence to early adolescence and test whether these associations are moderated by a hypothesized resilience factor, a previously identified connectome variate (CV) that is associated with higher cognitive function and lower psychopathology. Design Setting and Participants: This study was conducted in a longitudinal design based on multicenter data from a community cohort of U.S. youth aged of 9-11 at baseline, who participated in the Adolescent Brain Cognitive Development (ABCD) study (N=7,382 at baseline and 6,813 at 2-year follow-up). Linear regression models and moderation analyses were used to characterize concurrent and prospective associations between lifetime ACEs and number of DSM-5 psychiatric disorders (indexing transdiagnostic psychopathology) and to determine if individual variations in these associations were moderated by the CV derived from resting-state fMRI at baseline. Main Outcomes and Measures: Cumulative number of current DSM-5 psychiatric disorders assessed using the computerized self-admin version Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5) and lifetime ACEs assessed from child and parent reports at baseline (9-10 years) and 2-year-follow-up (11-12 years). Results: ACE total scores correlated positively with the cumulative number of current DSM-5 psychiatric disorders at both baseline (r =.258, p < .001) and 2-year follow-up (r =.257, p < .001). The baseline CV score moderated the ACE-disorder associations at baseline (B = -0.021, p < .001) and at 2-year follow-up (B = -0.018, p = .008), as well as the association between the changes in ACE and in the number of disorders from baseline to year 2 (B = -0.012, p = .045). Post-hoc analyses further showed that the moderation effect of CV on ACE-psychopathology associations was specific to the threat-related ACEs and to female youth. Conclusions and Relevance: These findings provide preliminary evidence for a connectome-based resiliency marker and suggest that functional connectivity strength in a broad system including frontal-parietal cortices and subcortical nuclei relevant to cognitive control may protect preadolescents who have experienced lifetime ACEs--especially females and those experiencing threat-related ACEs--from developing transdiagnostic psychopathology.

Characteristics of deformation and damage of surrounding rock along the top roadway in the working face of an isolated island and its evolution law.

This study investigates the deformation and damage characteristics of the surrounding rock along the top return mining roadway of an isolated island working face at different stages and reveals its damage mechanism and evolution law. Utilizing a mine in Yangquan City, Shanxi Province, China, as the engineering background, this research employs FLAC 3D numerical simulation and on-site measurements. The findings suggest that the evolution of the plastic zone along the top roadway of the 15,106 island face is largely similar during both the excavation and mining periods. The plastic zones on either side of the roadway are expanding asymmetrically and gradually merging into the plastic zone of the coal pillar. In the destructive stage, the sub-gangs of the roadway are penetrated, indicating the progression into the plastic zone. The investigation points to extensive damage on the larger side of the roadway, the development of fissures, and the significant depth of damage as primary causes of roadway deformation. Moreover, the extent of the plastic zones on both sides of the roadway correlates positively with their relative distance. Continuous monitoring reveals an ongoing increase in roadway displacement, consistent with general observations in coal mining. The results provide valuable insights for optimizing support structures in similar mining environments.

Effectiveness of exercise training on arterial stiffness and blood pressure among postmenopausal women: a systematic review and meta-analysis.

BACKGROUND: The acute and long-term benefits of exercise training on cardiovascular health have been well established. The systematic review and meta-analysis aimed to systematically assess the effectiveness of exercise training on arterial stiffness and blood pressure among postmenopausal women with elevated blood pressure. METHODS: A comprehensive search was conducted on PubMed, Embase, Web of Science, ProQuest, Cochrane Library, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov website from inception to September 30, 2023, to identify the randomized controlled trials (RCTs), which evaluated the effectiveness of exercise training on arterial stiffness and blood pressure in postmenopausal women. Standardized mean differences (SMD), weighted mean differences (WMD), and 95% confidence intervals (95% CIs) were calculated using random/fixed effects models. Quality assessment was performed using the modified Jadad scale and the Cochrane Risk of Bias Tool. Sensitivity analysis and subgroup analysis were conducted based on drug dosage, treatment duration, and age of administration to further explore potential heterogeneity. Funnel plots were performed to assess publication bias and Begg's regression test was carried out for funnel plot asymmetry. RESULTS: Twenty-two RCTs involving 1978 participants were included in the quantitative analysis. The mean quality of eligible studies was 4.2 out of 7 based on the modified Jadad scale. The results indicated that exercise training had a significant effect on reducing brachial-ankle pulse wave velocity [MD = - 0.69, 95%CI (- 1.11, - 0.27), P = 0.001], decreasing augmentation index (AIx) [MD = - 6.00, 95%CI (- 6.39, - 5.61), P < 0.00001] and AIx normalized to a heart rate of 75 beats per minute (AIx@75%) [MD = - 7.01, 95%CI - 7.91 to - 6.12, P < 0.00001], lowering systolic blood pressure [MD = - 6.19, 95%CI - 9.24 to - 3.15, P < 0.0001], diastolic blood pressure [MD = - 3.57, 95%CI (- 6.10, - 1.03), P = 0.006) and pulse pressure [MD = - 8.52, 95%CI (- 16.27, - 0.76), P = 0.03]. Subgroup analysis revealed that baseline blood pressure levels had a large impact on the effect of exercise training. CONCLUSIONS: The systematic review and meta-analysis suggested that exercise training may ameliorate arterial stiffness and reduce blood pressure in postmenopausal women with elevated blood pressure. However, the optimal mode of exercise training that improves arterial stiffness and blood pressure in this population requires further investigation. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021211268.

Estimated small dense low-density lipoprotein-cholesterol and the risk of kidney and cardiovascular outcomes in diabetic kidney disease.

AIMS: This study aimed to investigate the correlations between estimated small dense low-density lipoprotein-cholesterol (esd-LDL-c) and the development of end-stage kidney disease (ESKD), cardiovascular mortality, and all-cause mortality in individuals with diabetic kidney disease (DKD) or diabetes mellitus (DM) concomitant chronic kidney disease (CKD). METHODS: We analyzed the data from a biopsy-proven DKD cohort conducted at West China Hospital of Sichuan University between 2009 and 2021 (the DKD cohort) and participants with DM and CKD in the National Health and Nutrition Examination Survey (NHANES) 2011-2014 (the NHANES DM-CKD cohort). Cox regression analysis was also used to estimate associations between esd-LDL-c and the incidence of ESKD, cardiovascular mortality, and all-cause mortality. RESULTS: There were 175 ESKD events among 338 participants in the DKD cohort. Patients were divided into three groups based on esd-LDL-c tertiles (T1 < 33.7 mg/dL, T2 ≥ 33.7 mg/dL to <45.9 mg/dL, T3 ≥ 45.9 mg/dL). The highest tertile of esd-LDL-c was associated with ESKD (adjusted HR 2.016, 95% CI 1.144-3.554, p = .015). Furthermore, there were 99 deaths (39 cardiovascular) among 293 participants in the NHANES DM-CKD cohort. Participants were classified into three groups in line with the tertile values of esd-LDL-c in the DKD cohort. The highest tertile of esd-LDL-c was associated with cardiovascular mortality (adjusted HR 3.95, 95% CI 1.3-12, p = .016) and all-cause mortality (adjusted HR 2.37, 95% CI 1.06-5.32, p = .036). CONCLUSIONS: Higher esd-LDL-c was associated with increased risk of ESKD in people with biopsy-proven DKD, and higher cardiovascular and all-cause mortality risk among those with DM-CKD.

Regulation of Glandular Size and Phytoalexin Biosynthesis by a Negative Feedback Loop in Cotton.

Plants have evolved diverse defense mechanisms encompassing physical and chemical barriers. Cotton pigment glands are known for containing various defense metabolites, but the precise regulation of gland size to modulate defense compound levels remains enigmatic. Here, it is discovered that the VQ domain-containing protein JAVL negatively regulates pigment gland size and the biosynthesis of defense compounds, while the MYC2-like transcription factor GoPGF has the opposite effect. Notably, GoPGF directly activates the expression of JAVL, whereas JAVL suppresses GoPGF transcription, establishing a negative feedback loop that maintains the expression homeostasis between GoPGF and JAVL. Furthermore, it is observed that JAVL negatively regulates jasmonate levels by inhibiting the expression of jasmonate biosynthetic genes and interacting with GoPGF to attenuate its activation effects, thereby maintaining homeostatic regulation of jasmonate levels. The increased expression ratio of GoPGF to JAVL leads to enlarged pigment glands and elevated jasmonates and defense compounds, enhancing insect and pathogen resistance in cotton. These findings unveil a new mechanism for regulating gland size and secondary metabolites biosynthesis, providing innovative strategies for strengthening plant defense.

A Recursive Prediction-Based Feature Enhancement for Small Object Detection.

Transformer-based methodologies in object detection have recently piqued considerable interest and have produced impressive results. DETR, an end-to-end object detection framework, ingeniously integrates the Transformer architecture, traditionally used in NLP, into computer vision for sequence-to-sequence prediction. Its enhanced variant, DINO, featuring improved denoising anchor boxes, has showcased remarkable performance on the COCO val2017 dataset. However, it often encounters challenges when applied to scenarios involving small object detection. Thus, we propose an innovative method for feature enhancement tailored to recursive prediction tasks, with a particular emphasis on augmenting small object detection performance. It primarily involves three enhancements: refining the backbone to favor feature maps that are more sensitive to small targets, incrementally augmenting the number of queries for small objects, and advancing the loss function for better performance. Specifically, The study incorporated the Switchable Atrous Convolution (SAC) mechanism, which features adaptable dilated convolutions, to increment the receptive field and thus elevate the innate feature extraction capabilities of the primary network concerning diminutive objects. Subsequently, a Recursive Small Object Prediction (RSP) module was designed to enhance the feature extraction of the prediction head for more precise network operations. Finally, the loss function was augmented with the Normalized Wasserstein Distance (NWD) metric, tailoring the loss function to suit small object detection better. The efficacy of the proposed model is empirically confirmed via testing on the VISDRONE2019 dataset. The comprehensive array of experiments indicates that our proposed model outperforms the extant DINO model in terms of average precision (AP) small object detection.