Development and internal validation of a predictive model for prolonged intensive care unit stays in patients with psychotropic drug poisoning.

BACKGROUND: Some patients with psychotropic drug poisoning need intensive care unit (ICU) admission, but risk prediction models for prolonged ICU stays are lacking. OBJECTIVES: Develop and evaluate a prediction model for prolonged ICU stays in patients with psychotropic drug poisoning. METHODS: The clinical data of patients with psychotropic drug poisoning were collected from the Medical Information Mart for Intensive Care (MIMIC)-Ⅳ 2.2 database. Patients were grouped by their ICU length of stay: non-prolonged (<2 days) and prolonged (≥2 days). Variable selection methods included LASSO and logistic regression. The selected variables were used to construct the model, which was subsequently evaluated for discrimination, calibration, and clinical utility. RESULTS: The cohort included 413 patients with psychotropic drug poisoning, 49.4 % male, with a median age of 41 years. The variables stepwise selected for model construction through LASSO and logistic regression include sepsis, SAPS Ⅱ, heart rate, respiratory rate, and mechanical ventilation. The model showed good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.785 (95 % CI: 0.736-0.833) and was validated well with bootstrap internal validation (AUC: 0.792, 95 % CI: 0.745-0.839). Calibration curves indicated good fit (χ2 = 4.148, P = 0.844), aligning observed and predicted rates of prolonged ICU stays. Decision curve analysis (DCA) showed positive net benefits across a threshold probability range of 0.07-0.85. CONCLUSIONS: The model developed in this study may help predict the risk of prolonged ICU stays for patients with psychotropic drug poisoning.

Electronically actuated artificial hinged cilia for efficient bidirectional pumping.

Cilial pumping is a potent mechanism used to control and manipulate fluids on microscales. Recently, we introduced an electronically driven µ-cilial platform that can create arbitrary flow patterns in liquids near a surface with the potential for various engineering applications. This µ-cilial platform, however, utilized the coupling between elasticity and viscous drag to obtain pumping and had several limitations. For example, each cilium could only pump in one direction. Thus, to create bidirectional flows, it was necessary to fabricate and separately actuate two oppositely facing cilia. As another example, the generation of non-reciprocal cilial motions, a necessary condition for pumping at these scales, could only be achieved by matching the elastic stresses inherent in actuating the cilia with the viscous drag forces generated by the flows. This criterion severely restricted the frequency range over which the cilia could be operated and resulted in a small swept area, both of which restricted the volume of fluid being pumped in each cycle. These limitations contrast with the capabilities of natural cilia, which can achieve omnidirectional transport and operation over a broad range of frequencies. In natural cilia, these capabilities arise from their complex internal structure. Inspired by this strategy we designed hinged cilia and show they can achieve bidirectional pumping of larger fluid volumes over a broad range of frequencies. Finally, we demonstrate that even regular arrays of individually controlled hinged cilia can generate a variety of flow patterns using fewer cilia than in previous cilia metasurface designs.

Parametrization of lower limit temperature in crop water stress index model: A case study of Quercus variabilis plantation.

The lower limit temperature in the crop water stress index (CWSI) model refers to the canopy temperature (Tc) or the canopy-air temperature differences (dT) under well-watered conditions, which has significant impacts on the accuracy of the model in quantifying plant water status. At present, the direct estimation of lower limit temperature based on data-driven method has been successfully used in crops, but its applicability has not been tes-ted in forest ecosystems. We collected continuously and synchronously Tc and meteorological data in a Quercus variabilis plantation at the southern foot of Taihang Mountain to evaluate the feasibility of multiple linear regression model and BP neural network model for estimating the lower limit temperature and the accuracy of the CWSI indicating water status of the plantation. The results showed that, in the forest ecosystem without irrigation conditions, the lower limit temperature could be obtained by setting soil moisture as saturation in the multiple linear regression mo-del and the BP neural network model with soil water content, wind speed, net radiation, vapor pressure deficit and air temperature as input parameters. Combining the lower limit temperature and the upper limit temperature determined by the theoretical equation to normalize the measured Tc and dT could realize the non-destructive, rapid, and automatic diagnosis of the water status of Q. variabilis plantation. Among them, the CWSI obtained by combining the lower limit temperature determined by the dT under well-watered condition calculated by the BP neural network model and the upper limit temperature was the most suitable for accurate monitoring water status of the plantation. The coefficient of determination, root mean square error, and index of agreement between the calculated CWSI and measured CWSI were 0.81, 0.08, and 0.90, respectively. This study could provide a reference method for efficient and accurate monitoring of forest ecosystem water status.

A stable thymidine kinase 1 tetramer for improved quality control of serum level quantification.

DNA synthesis is a critical process for cell growth and division. In cancer patients, an enzyme called thymidine kinase 1 (TK1) is often elevated in the blood, making it a valuable biomarker for cancer diagnosis and treatment. However, previous studies have shown that recombinant TK1 can exist in unstable mixtures of tetramers and dimers, leading to inconsistent results and potentially affecting accuracy. To address this issue, we hypothesized that incorporating tetrameric coiled-coil peptides could enhance TK1 self-assembly into stable tetramers without requiring additional adenosine triphosphate. In this study, we successfully expressed a recombinant TK1 tetramer protein in the Escherichia coli system. We optimized the induction conditions, significantly increasing protein expression levels, functionality, and solubility. Size exclusion chromatography confirmed the formation of a tetrameric structure in the expressed TK1 protein, with a molecular weight of 127.2 KDa, consistent with our expectations. We also found that the TK1 tetramer exhibited higher affinity with anti-TK1 IgY than wild-type TK1, as shown by enzyme-linked immunosorbent assay experiments. Moreover, the TK1 tetramer demonstrated good stability against heating, freeze-thawing and lyophilization with almost no immunoactivity lost. These findings suggest that recombinant TK1 tetramers have the potential to serve as calibrators in diagnostic assay kits, becoming promising candidates for quality control of clinical laboratory and in vitro diagnostic reagents.

Enhanced nitrogen removal for low C/N wastewater via preventing futile carbon oxidation and augmenting anammox.

Efficient carbon use is crucial for biological nitrogen removal. Traditional aerobic processes can waste carbon sources, exacerbating carbon deficiency. This study explores an anaerobic/oxic/anoxic system with sludge double recirculation to improve nitrogen removal in low C/N wastewater. This system integrated aerobic nitrification after the carbon intracellular storage, separating carbon and nitrogen by denitrifying glycogen-accumulating organisms (DGAOs) with endogenous partial denitrification and Anammox within the anoxic units. A significant efficiency of 91.02±7.01% chemical oxygen demand (COD) was converted into intracellular carbon in anaerobic units, significantly reducing carbon futile oxidation in the aerobic units by effectively separating COD from ammonia. Intracellular storage of carbon sources and microbial adaptation to carbon scarcity prevent futile oxidation of COD in the aerobic units even with short-term high dissolved oxygen (DO), thereby enhancing nitrogen removal under anoxic conditions with sufficient intracellular carbon source. The microbial analysis identified Candidatus Brocadia as the dominant anammox bacteria, in combination with the activity of DGAOs and other related microbial communities, accounting for 37.0% of the TN removal. Consequently, the system demonstrated remarkable nitrogen removal efficiencies, achieving 81.3±3.3% for total nitrogen (TN) and 98.5±0.9% for ammonia nitrogen while maintaining an effluent COD concentration of 17.2±9.1 mg/L, treating the low C/N of 4.18 in the influent wastewater. The findings in this study provide a sustainable and energy-saving technique for conventional WWTPs to meet strict discharge standards by avoiding futile oxidation of COD and encouraging anammox contributions.

Deep-learning-assisted sidewall profiling white light interferometry system for accurately measuring 3D profiles and surface roughness on the groove sidewalls of precision components.

The accurate measurement of surface three-dimensional (3D) profile and roughness on the groove sidewalls of components is of great significance to diverse fields such as precision manufacturing, machining processes, energy transportation, medical equipment, and semiconductor industry. However, conventional optical measurement methods struggle to measure surface profiles on the sidewall of a small groove. Here, we present a deep-learning-assisted sidewall profiling white light interferometry system, which consists of a microprism-based interferometer, an optical path compensation device, and a convolutional neural network (CNN), for the accurate measurement of surface 3D profile and roughness on the sidewall of a small groove. We have demonstrated that the sidewall profiling white light interferometry system can achieve a measurement accuracy of 2.64 nm for the 3D profile on a groove sidewall. Moreover, we have demonstrated that the CNN-based single-image super-resolution (SISR) technique could improve the measurement accuracy of surface roughness by over 30%. Our system can be utilized in cases where the width of the groove is only 1 mm and beyond, limited only by the size of the microprism and the working distance of the objective used in our system.

Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics.

OBJECTIVES: This study aims to evaluate image quality and regional lymph node metastasis (LNM) in patients with rectal cancer (RC) on multi-b-value diffusion-weighted imaging (DWI). METHODS: This retrospective study included 199 patients with RC who had undergone multi-b-value DWI. Subjective (five-point Likert scale) and objective assessments of quality images were performed on DWIb1000, DWIb2000, and DWIb3000. Patients were randomly divided into a training (n = 140) or validation cohort (n = 59). Radiomics features were extracted within the whole volume tumor on ADC maps (b = 0, 1000 s/mm2), DWIb1000, DWIb2000, and DWIb3000, respectively. Five prediction models based on selected features were developed using logistic regression analysis. The performance of radiomics models was evaluated with a receiver operating characteristic curve, calibration, and decision curve analysis (DCA). RESULTS: The mean signal intensity of the tumor (SItumor), signal-to-noise ratio (SNR), and artifact and anatomic differentiability score gradually were decreased as the b-value increased. However, the contrast-to-noise (CNR) on DWIb2000 was superior to those of DWIb1000 and DWIb3000 (4.58 ± 0.86, 3.82 ± 0.77, 4.18 ± 0.84, p < 0.001, respectively). The overall image quality score of DWIb2000 was higher than that of DWIb3000 (p < 0.001) and showed no significant difference between DWIb1000 and DWIb2000 (p = 0.059). The area under curve (AUC) value of the radiomics model based on DWIb2000 (0.728) was higher than conventional ADC maps (0.690), DWIb1000 (0.699), and DWIb3000 (0.707), but inferior to multi-b-value DWI (0.739) in predicting LNM. CONCLUSION: DWIb2000 provides better lesion conspicuity and LNM prediction than DWIb1000 and DWIb3000 in RC. CLINICAL RELEVANCE STATEMENT: DWIb2000 offers satisfactory visualization of lesions. Radiomics features based on DWIb2000 can be applied for preoperatively predicting regional lymph node metastasis in rectal cancer, thereby benefiting the stratified treatment strategy. KEY POINTS: Lymph node staging is required to determine the best treatment plan for rectal cancer. DWIb2000 provides superior contrast-to-noise ratio and lesion conspicuity and its derived radiomics best predict lymph node metastasis. DWIb2000 may be recommended as the optimal b-value in rectal MRI protocol.

Recurrent Oral Ulcers: Are They Horses or Zebras?

Oral ulcers are one of the most common complaints seen by general practitioners in their offices. Recurrent aphthous stomatitis affects roughly 20% of the general population. When ulcers persist despite conventional treatment, it is crucial to consider systemic diseases such as Behçet's disease to prevent delays in care. Early recognition and appropriate management of underlying conditions are essential for improving patient outcomes and quality of life. We present a case of a 41-year-old Scottish male who came in with complaints of recurrent oral ulcers and oral thrush. Initial treatment by an infectious disease specialist resolved the oral thrush but not the ulcers. Despite further treatment attempts for three years, including biopsy and antiviral therapy, ulcers persisted. Finally, referral to rheumatology led to comprehensive autoimmune testing, revealing positive HLA B51 and a diagnosis of Behçet's disease. Treatment with topical steroids and colchicine yielded significant improvement.

Membrane protein MHZ3 regulates the on-off switch of ethylene signaling in rice.

Ethylene regulates plant growth, development, and stress adaptation. However, the early signaling events following ethylene perception, particularly in the regulation of ethylene receptor/CTRs (CONSTITUTIVE TRIPLE RESPONSE) complex, remains less understood. Here, utilizing the rapid phospho-shift of rice OsCTR2 in response to ethylene as a sensitive readout for signal activation, we revealed that MHZ3, previously identified as a stabilizer of ETHYLENE INSENSITIVE 2 (OsEIN2), is crucial for maintaining OsCTR2 phosphorylation. Genetically, both functional MHZ3 and ethylene receptors prove essential for OsCTR2 phosphorylation. MHZ3 physically interacts with both subfamily I and II ethylene receptors, e.g., OsERS2 and OsETR2 respectively, stabilizing their association with OsCTR2 and thereby maintaining OsCTR2 activity. Ethylene treatment disrupts the interactions within the protein complex MHZ3/receptors/OsCTR2, reducing OsCTR2 phosphorylation and initiating downstream signaling. Our study unveils the dual role of MHZ3 in fine-tuning ethylene signaling activation, providing insights into the initial stages of the ethylene signaling cascade.

Serum dithiothreitol-oxidizing capacity (DOC) is a promising biomarker for excluding significant liver fibrosis: a proof-of-concept study.

BACKGROUND: APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs). METHODS: Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations. RESULTS: Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P < 0.05, P < 0.01 and P < 0.001 in 3, 1 and 3 cohort comparisons, respectively). Conversely, the DOC test was equivalent to APRI and FIB-4 when all tests showed moderate/adequate diagnostic performances (P > 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%). CONCLUSIONS: This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

Exploring the relationship between heavy metals and diabetic retinopathy: a machine learning modeling approach.

Diabetic retinopathy (DR) is one of the leading causes of adult blindness in the United States. Although studies applying traditional statistical methods have revealed that heavy metals may be essential environmental risk factors for diabetic retinopathy, there is a lack of analyses based on machine learning (ML) methods to adequately explain the complex relationship between heavy metals and DR and the interactions between variables. Based on characteristic variables of participants with and without DR and heavy metal exposure data obtained from the NHANES database (2003-2010), a ML model was developed for effective prediction of DR. The best predictive model for DR was selected from 11 models by receiver operating characteristic curve (ROC) analysis. Further permutation feature importance (PFI) analysis, partial dependence plots (PDP) analysis, and SHapley Additive exPlanations (SHAP) analysis were used to assess the model capability and key influencing factors. A total of 1042 eligible individuals were randomly assigned to two groups for training and testing set of the prediction model. ROC analysis showed that the k-nearest neighbour (KNN) model had the highest prediction performance, achieving close to 100% accuracy in the testing set. Urinary Sb level was identified as the critical heavy metal affecting the predicted risk of DR, with a contribution weight of 1.730632 ± 1.791722, which was much higher than that of other heavy metals and baseline variables. The results of the PDP analysis and the SHAP analysis also indicated that antimony (Sb) had a more significant effect on DR. The interaction between age and Sb was more significant compared to other variables and metal pairs. We found that Sb could serve as a potential predictor of DR and that Sb may influence the development of DR by mediating cellular and systemic senescence. The study revealed that monitoring urinary Sb levels can be useful for early non-invasive screening and intervention in DR development, and also highlighted the important role of constructed ML models in explaining the effects of heavy metal exposure on DR.

Comment on Ambra et al. Could Selenium Supplementation Prevent COVID-19? A Comprehensive Review of Available Studies. Molecules 2023, 28, 4130.

The authors of this Comment are longstanding selenium investigators with a total of 200 or more published articles on selenium; the corresponding author (Margaret P [...].

Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding.

Computational methods are desired for single-cell-resolution spatial transcriptomics (ST) data analysis to uncover spatial organization principles for how individual cells exert tissue-specific functions. Here, we present ST data analysis via interaction-aware cell embedding (SPACE), a deep-learning method for cell-type identification and tissue module discovery from single-cell-resolution ST data by learning a cell representation that captures its gene expression profile and interactions with its spatial neighbors. SPACE identified spatially informed cell subtypes defined by their special spatial distribution patterns and distinct proximal-interacting cell types. SPACE also automatically discovered "cell communities"-tissue modules with discernible boundaries and a uniform spatial distribution of constituent cell types. For each cell community, SPACE outputs a characteristic proximal cell-cell interaction network associated with physiological processes, which can be used to refine ligand-receptor-based intercellular signaling analyses. We envision that SPACE can be used in large-scale ST projects to understand how proximal cell-cell interactions contribute to emergent biological functions within cell communities. A record of this paper's transparent peer review process is included in the supplemental information.

Interfacial Stabilization by Prelithiated Trithiocyanuric Acid as an Organic Additive in Sulfide-Based All-Solid-State Lithium Metal Batteries.

Sulfide-based all-solid-state battery (ASSB) with a lithium metal anode (LMA) is a promising candidate to surpass conventional Li-ion batteries owing to their inherent safety against fire hazards and potential to achieve a higher energy density. However, the narrow electrochemical stability window and chemical reactivity of the sulfide solid electrolyte towards the LMA results in interfacial degradation and poor electrochemical performance. In this direction, we introduce an organic additive approach, that is the mixing of prelithiated trithiocyanuric acid, Li3TCA, with Li6PS5Cl, to establish a stable interface while preserving high ionic conductivity. Including 2.5 wt % Li3TCA alleviates the decomposition of the electrolyte on the lithium metal interface, decreasing the Li2S content in the solid-electrolyte interface (SEI) thus forming a more stable interface. In Li|Li symmetric cells, this strategy enables a rise in the critical current density from 1.0 to 1.9 mA cm-2 and stable cycling for over 750 hours at a high current density of 1.0 mA cm-2. This approach also enables Li|NbO-NCM811 full cell to operate more than 500 cycles at 0.3 C.

Influence of EGCG oxidation on inhibitory activity against the SARS-CoV-2 main protease.

SARS-CoV-2 main protease (Mpro) is a well-recognized target for COVID-19 therapy. Green tea (-)-epigallocatechin-3-gallate (EGCG) possesses Mpro-inhibitory activity; however, the influence of EGCG oxidation on its inhibition activity remains obscure, given its high oxidation propensity. This study reveals that prolonged EGCG oxidation in the presence of Mpro dramatically increases its inhibitory activity with an IC50 of 0.26 µM. The inhibitory mechanism is that EGCG-quinone preferentially binds the active site Mpro-Cys145-SH, which forms a quinoprotein. Though Mpro is present in the cell lysate, EGCG preferentially depletes its thiols. Non-cytotoxic EGCG effectively generates a quinoprotein in living cells, thus EGCG might selectively inhibit Mpro in SARS-CoV-2 infected cells. Chlorogenic acid facilitates EGCG oxidation. Together, they synergistically deplete multiple Mpro thiols though this is not more beneficial than EGCG alone. By contrast, excessive EGCG oxidation prior to incubation with Mpro largely compromises its inhibitory activity. Overall, the low IC50 and the high selectivity imply that EGCG is a promising dietary Mpro inhibitor. While EGCG oxidation in the presence of Mpro has a pivotal role in inhibition, enhancing EGCG oxidation by chlorogenic acid no longer increases its inhibitory potential. EGCG oxidation in the absence of Mpro should be avoided to maximize its Mpro-inhibitory activity.

High expression of 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) associated with Diquat-induced damage.

Diquat (DQ) is a commonly used bipyridine herbicide known for its toxic properties and adverse effects on individuals. However, the mechanism underlying DQ-induced damage remain elusive. Our research aimed to uncover the regulatory network involved in DQ-induced damage. We analyzed publicly accessible gene expression patterns and performed research using a DQ-induced damage animal model. The GSE153959 dataset from the Gene Expression Omnibus collection and the animal model of DQ-induced kidney injury were used to identify differentially expressed genes (DEGs). Pathways including the regulation of DNA-templated transcription in response to stress, RNA polymerase II transcription regulator complex and transcription coregulatory activity were shown to be enriched in 21 DEGs. We used least absolute shrinkage and selection operator (LASSO) regression analysis to find possible diagnostic biomarkers for DQ-induced damage. Then, we used an HK-2 cell model to confirm these results. Additionally, we confirmed that 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) was the major gene associated with DQ-induced damage using multi-omics screening. The sample validation strongly suggested that HMGCS2 has promise as a diagnostic marker and may provide new targets for therapy in the context of DQ-induced damage.

Carbon fluxes and water-use efficiency in a Pinus tabuliformis plantation in Northeast China and their relationship to drought.

The impact of extreme weather events on carbon fluxes and water-use efficiency (WUE) in revegetated areas under water-limited conditions is poorly understood. We analyzed changes in carbon fluxes and WUE over three years of eddy-covariance measurements in a Pinus tabuliformis plantation in Northeast China to investigate carbon fluxes and WUE responses to drought events at different time scales. Mean annual net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (Re) were -368.48, 1042.42, and 673.94 g C m-2, respectively. Drought events increased NEE, as GPP was more sensitive to water stress than Re at different growing stages. Mean annual WUE was 2.46 g C kg-1 H2O, and plant phenology played a key role in WUE responses to drought. Water stress had negative and positive effects on daily WUE at the early and late growing stages, respectively, and daily WUE was generally insensitive to drought at the mid growing stage. A lagged effect existed in the carbon fluxes and WUE dynamics after drought events at various time scales. Water stress at the early growing stage was more important than that at other growing stages on annual carbon sequestration and WUE, as it dominated canopy growth in the current year. The annual mean normalized difference vegetation index controlled interannual variations in carbon fluxes and WUE in the plantation. Our findings contribute to the prediction of possible changes in carbon and water fluxes under climate warming in the afforested areas of Northeast China.

CELLULOSE SYNTHASE-LIKE C proteins modulate cell wall establishment during ethylene-mediated root growth inhibition in rice.

The cell wall shapes plant cell morphogenesis and affects the plasticity of organ growth. However, the way in which cell wall establishment is regulated by ethylene remains largely elusive. Here, by analyzing cell wall patterns, cell wall composition and gene expression in rice (Oryza sativa, L.) roots, we found that ethylene induces cell wall thickening and the expression of cell wall synthesis-related genes, including CELLULOSE SYNTHASE-LIKE C1, 2, 7, 9, 10 (OsCSLC1, 2, 7, 9, 10) and CELLULOSE SYNTHASE A3, 4, 7, 9 (OsCESA3, 4, 7, 9). Overexpression and mutant analyses revealed that OsCSLC2 and its homologs function in ethylene-mediated induction of xyloglucan biosynthesis mainly in the cell wall of root epidermal cells. Moreover, OsCESA-catalyzed cellulose deposition in the cell wall was enhanced by ethylene. OsCSLC-mediated xyloglucan biosynthesis likely plays an important role in restricting cell wall extension and cell elongation during the ethylene response in rice roots. Genetically, OsCSLC2 acts downstream of ETHYLENE-INSENSITIVE3-LIKE1 (OsEIL1)-mediated ethylene signaling, and OsCSLC1, 2, 7, 9 are directly activated by OsEIL1. Furthermore, the auxin signaling pathway is synergistically involved in these regulatory processes. These findings link plant hormone signaling with cell wall establishment, broadening our understanding of root growth plasticity in rice and other crops.

miR-21-Mediated Endothelial Senescence and Dysfunction Are Involved in Cigarette Smoke-Induced Pulmonary Hypertension through Activation of PI3K/AKT/mTOR Signaling.

Smoking is a pathogenic factor for pulmonary hypertension (PH). Our previous study showed that serum miR-21 levels are elevated in smokers. miR-21 is considered as engaged in the PH process; however, its mechanisms remain unclear. In this investigation, we found that in the lung tissue of smoking-induced PH patients, the levels of miR-21 and aging markers (p21 and p16) were upregulated, and the function of pulmonary vascular endothelial cells was also impaired. Exposure of mice to cigarette smoke (CS) for four months caused similar changes in lung tissues and increased pulmonary arterial pressure, which were attenuated by knockout of miR-21. Further, human umbilical vein endothelial cells (HUVECs) exposed to cigarette smoke extract (CSE) revealed upregulation of miR-21 levels, depression of PTEN, activation of PI3K/AKT/mTOR signaling, an increase in senescence indexes, and enhanced dysfunction. Inhibiting miR-21 overexpression reversed the PTEN-mTOR signaling pathway and prevented senescence and dysfunction of HUVECs. In sum, our data indicate that miR-21-mediated endothelial senescence and dysfunction are involved in CS-induced PH through the activation of PI3K/AKT/mTOR signaling, which suggests that selective miR-21 inhibition offers the potential to attenuate PH.

Preparation of Medical 228Th-224Ra Radionuclide Generator Based on SiO2@TiO2 Microspheres.

224Ra (T1/2 = 3.63 d), an α-emitting radionuclide, holds significant promise in cancer endoradiotherapy. Current 224Ra-related therapy is still scarce because of the lack of reliable radionuclide supply. The 228Th-224Ra radionuclide generator can undoubtedly introduce continuous and sustainable availability of 224Ra for advanced nuclear medicine. However, conventional metal oxides for such radionuclide generators manifest suboptimal adsorption capacities for the parent nuclide, primarily attributable to their limited surface area. In this work, core-shell SiO2@TiO2 microspheres were proposed to develop as column materials for the construction of a 228Th-224Ra generator. SiO2@TiO2 microspheres were well prepared and systematically characterized, which has also been demonstrated to have good adsorption capacity to 228Th and very weak binding affinity toward 224Ra via simulated chemical separation. Upon introducing 228Th-containing solution onto the SiO2@TiO2 functional column, a 228Th-224Ra generator with excellent retention of the parent radionuclide and ideal elution efficiency of daughter radionuclide was obtained. The prepared 228Th-224Ra generator can produce 224Ra with high purity and medical usability in good elution efficiency (98.72%) even over five cycles. To the best of our knowledge, this is the first time that the core-shell mesoporous materials have been applied in a radionuclide generator, which can offer valuable insights for materials chemistry, radiochemical separation, and biological medicine.