A mix & act liposomes of phospholipase A2-phosphatidylserine for acute brain detoxification by blood‒brain barrier selective-opening.

In the treatment of central nervous system disease, the blood-brain barrier (BBB) is a major obstruction to drug delivery that must be overcome. In this study, we propose a brain-targeted delivery strategy based on selective opening of the BBB. This strategy allows some simple bare nanoparticles to enter the brain when mixed with special opening material; however, the BBB still maintains the ability to completely block molecules from passing through. Based on the screening of BBB opening and matrix delivery materials, we determined that phospholipase A2-catalyzed 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine liposomes can efficiently carry drugs into the brain immediately. At an effective dose, this delivery system is safe, especially with its effect on the BBB being reversible. This mix & act delivery system has a simple structure and rapid preparation, making it a strong potential candidate for drug delivery across the BBB.

Hypocapnia is associated with increased in-hospital mortality and 1 year mortality in acute heart failure patients.

AIMS: Both hypercapnia and hypocapnia are common in patients with acute heart failure (AHF), but the association between partial pressure of arterial carbon dioxide (PaCO2) and AHF prognosis remains unclear. The objective of this study was to investigate the connection between PaCO2 within 24 h after admission to the intensive care unit (ICU) and mortality during hospitalization and at 1 year in AHF patients. METHODS AND RESULTS: AHF patients were enrolled from the Medical Information Mart for Intensive Care IV database. The patients were divided into three groups by PaCO2 values of <35, 35-45, and >45 mmHg. The primary outcome was to investigate the connection between PaCO2 and in-hospital mortality and 1 year mortality in AHF patients. The secondary outcome was to assess the prediction value of PaCO2 in predicting in-hospital mortality and 1 year mortality in AHF patients. A total of 2374 patients were included in this study, including 457 patients in the PaCO2 < 35 mmHg group, 1072 patients in the PaCO2 = 35-45 mmHg group, and 845 patients in the PaCO2 > 45 mmHg group. The in-hospital mortality was 19.5%, and the 1 year mortality was 23.9% in the PaCO2 < 35 mmHg group. Multivariate logistic regression analysis showed that the PaCO2 < 35 mmHg group was associated with an increased risk of in-hospital mortality [hazard ratio (HR) 1.398, 95% confidence interval (CI) 1.039-1.882, P = 0.027] and 1 year mortality (HR 1.327, 95% CI 1.020-1.728, P = 0.035) than the PaCO2 = 35-45 mmHg group. The PaCO2 > 45 mmHg group was associated with an increased risk of in-hospital mortality (HR 1.387, 95% CI 1.050-1.832, P = 0.021); the 1 year mortality showed no significant difference (HR 1.286, 95% CI 0.995-1.662, P = 0.055) compared with the PaCO2 = 35-45 mmHg group. The Kaplan-Meier survival curves showed that the PaCO2 < 35 mmHg group had a significantly lower 1 year survival rate. The area under the receiver operating characteristic curve for predicting in-hospital mortality was 0.591 (95% CI 0.526-0.656), and the 1 year mortality was 0.566 (95% CI 0.505-0.627) in the PaCO2 < 35 mmHg group. CONCLUSIONS: In AHF patients, hypocapnia within 24 h after admission to the ICU was associated with increased in-hospital mortality and 1 year mortality. However, the increase in 1 year mortality may be influenced by hospitalization mortality. Hypercapnia was associated with increased in-hospital mortality.

Clinicopathological factors predict residual lymph node metastasis in locally advanced rectal cancer with ypT0-2 after neoadjuvant chemoradiotherapy.

PURPOSE: Residual lymph node metastases (RLNM) remained a great concern in the implementation of organ-preserving strategies and led to poor prognosis in locally advanced rectal cancer (LARC). In this study, we aimed to identify the clinicopathological factors correlated with RLNM in LARC patients with ypT0-2 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 417 patients histologically diagnosed middle-low LARC after NCRT and total mesorectal excision (TME), whose pathological staging was ypT0-2. All patients received pelvic magnetic resonance imaging (MRI) before NCRT. The radiation doses were 50-50.6 Gy for the planning gross tumor volume and 41.8-45 Gy for the planning target volume, respectively. A nomogram for predicting RLNM was constructed using a binary logistic regression. Nomogram performance was assessed by receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC). RESULTS: After surgery, 191 patients (45.8%) were ypT0, 43 patients (10.3%) were ypT1 and 183 patients (43.9%) were ypT2, and a total of 49 patients (11.8%) were found the presence of RLNM. Multivariable analyses identified MRI-defined mesorectal fascia (MRF)-positive, high-grade histopathology at biopsy, advanced ypT-category, and the presence of perineural invasion (PNI) as the predictive factors. The nomogram, incorporating all these predictors, showed good discrimination and calibration efficacy, with the areas under the ROC curve of 0.690 (95% CI: 0.610-0.771). Both DCA and CIC demonstrated that this nomogram has good clinical usefulness. CONCLUSION: The nomogram model can predict RLNM in patients with ypT0-2 tumors. It can help select suitable patients for performing organ-preserving strategies after NCRT.

Novel targets and their functions in the prognosis of uterine corpus endometrial cancer patients.

Aberrant mRNA expression is implicated in uterine corpus endometrial carcinoma (UCEC) oncogenesis and progression. However, effective prognostic biomarkers for UCEC remain limited. We aimed to construct a reliable multi-gene risk model using gene expression profiles. Utilizing TCGA data (543 UCEC samples, 35 controls), we identified 1517 differentially acting genes. Weighted gene co-expression complex analysis (WGCCA), hub gene screening, and risk regression analysis (RRA) were employed to determine prognosis-related genes and construct the risk model. Nomograms visualized risk scores and receiver operator characteristic (ROC) curves assessed model performance. Seven novel prognosis-related hub genes (ANGPT1, ASB2, GAL, GDF7, ONECUT2, SV2B, TRPC6) were identified. The model's concordance index (C index) by multivariate Cox regression analysis was 0.79. ROC curves yielded AUCs of 0.811 (3-year) and 0.79 (5-year), demonstrating the model's efficacy in predicting UCEC survival. Our study proposes a promising seven-biomarker risk model for predicting UCEC prognosis, offering potential clinical utility.

Role of transient receptor potential ankyrin 1 in idiopathic pulmonary fibrosis: modulation of M2 macrophage polarization.

Idiopathic pulmonary fibrosis (IPF) poses significant challenges due to limited treatment options despite its complex pathogenesis involving cellular and molecular mechanisms. This study investigated the role of transient receptor potential ankyrin 1 (TRPA1) channels in regulating M2 macrophage polarization in IPF progression, potentially offering novel therapeutic targets. Using a bleomycin-induced pulmonary fibrosis model in C57BL/6J mice, we assessed the therapeutic potential of the TRPA1 inhibitor HC-030031. TRPA1 upregulation was observed in fibrotic lungs, correlating with worsened lung function and reduced survival. TRPA1 inhibition mitigated fibrosis severity, evidenced by decreased collagen deposition and restored lung tissue stiffness. Furthermore, TRPA1 blockade reversed aberrant M2 macrophage polarization induced by bleomycin, associated with reduced Smad2 phosphorylation in the TGF-ß1-Smad2 pathway. In vitro studies with THP-1 cells treated with bleomycin and HC-030031 corroborated these findings, highlighting TRPA1's involvement in fibrotic modulation and macrophage polarization control. Overall, targeting TRPA1 channels presents promising therapeutic potential in managing pulmonary fibrosis by reducing pro-fibrotic marker expression, inhibiting M2 macrophage polarization, and diminishing collagen deposition. This study sheds light on a novel avenue for therapeutic intervention in IPF, addressing a critical need in the management of this challenging disease.

Diagnostic Performance of Radiomics and Deep Learning to Identify Benign and Malignant Soft Tissue Tumors: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: To systematically evaluate the application value of radiomics and deep learning (DL) in the differential diagnosis of benign and malignant soft tissue tumors (STTs). MATERIALS AND METHODS: A systematic review was conducted on studies published up to December 11, 2023, that utilized radiomics and DL methods for the diagnosis of STTs. The methodological quality and risk of bias were evaluated using the Radiomics Quality Score (RQS) 2.0 system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. A bivariate random-effects model was used to calculate the summarized sensitivity and specificity. To identify factors contributing to heterogeneity, meta-regression and subgroup analyses were performed to assess the following covariates: diagnostic modality, region/volume of interest, imaging examination, study design, and pathology type. The asymmetry of Deeks' funnel plot was used to assess publication bias. RESULTS: A total of 21 studies involving 3866 patients were included, with 13 studies using independent test/validation sets included in the quantitative statistical analysis. The average RQS was 21.31, with substantial or near-perfect inter-rater agreement. The combined sensitivity and specificity were 0.84 (95% CI: 0.76-0.89) and 0.88 (95% CI: 0.69-0.96), respectively. Meta-regression and subgroup analyses showed that study design and the region/volume of interest were significant factors affecting study heterogeneity (P < 0.05). No publication bias was observed. CONCLUSION: Radiomics and DL can accurately distinguish between benign and malignant STTs. Future research should concentrate on enhancing the rigor of study designs, conducting multicenter prospective validations, amplifying the interpretability of DL models, and integrating multimodal data to elevate the diagnostic accuracy and clinical utility of soft tissue tumor assessments.

Potential Common Mechanisms of Cytotoxicity Induced by Organophosphorus Pesticides via NLRP3 Inflammasome Activation.

The Multi-Threat Medical Countermeasure (MTMC) technique is crucial for developing common biochemical signaling pathways, molecular mediators, and cellular processes. This study revealed that the Nod-like receptor 3 (NLRP3) inflammasome pathway may be a significant contributor to the cytotoxicity induced by various organophosphorus pesticides (OPPs). The study demonstrated that exposure to six different types of OPPs (paraoxon, dichlorvos, fenthion, dipterex, dibrom, and dimethoate) led to significant cytotoxicity in BV2 cells, which was accompanied by increased expression of NLRP3 inflammasome complexes (NLRP3, ASC, Caspase-1) and downstream inflammatory cytokines (IL-1ß, IL-18), in which the order of cytotoxicity was dichlorvos > dipterex > dibrom > paraoxon > fenthion > dimethoate, based on the IC50 values of 274, 410, 551, 585, 2,158, and 1,527,566 µM, respectively. The findings suggest that targeting the NLRP3 inflammasome pathway could be a potential approach for developing broad-spectrum antitoxic drugs to combat multi-OPPs-induced toxicity. Moreover, inhibition of NLRP3 efficiently protected the cells against cytotoxicity induced by these six OPPs, and the expression of NLRP3, ASC, Caspase-1, IL-1ß, and IL-18 decreased accordingly. The order of NLRP3 affinity for OPPs was dimethoate > paraoxon > dichlorvos > dibrom > (fenthion and dipterex) based on K D values of 89.8, 325, 1,460, and 2,690 µM, respectively. Furthermore, the common molecular mechanism of NLRP3-OPPs was clarified by the presence of toxicity effector groups (benzene ring, nitrogen/oxygen-containing functional group); =O, -O-, or =S (active) groups; and combination residues (Gly271, Asp272). This finding provided valuable insights into exploring the common mechanisms of multiple threats and developing effective therapeutic strategies to prevent OPPs poisoning.

Elongin B promotes breast cancer progression by ubiquitinating tumor suppressor p14/ARF.

Elongin B (ELOB), a pivotal element in the ELOB/c-Cullin2/5-SOCS-box E3 ubiquitin-protein ligase complex, plays a significant role in catalyzing the ubiquitination and subsequent degradation of a broad spectrum of target proteins. Notably, it is documented to facilitate these processes. However, the regulatory role of ELOB in breast cancer remains ambiguous. In this study, through bio-informatic analysis of The Cancer Genome Atlas and Fudan University Shanghai Cancer Center database, we demonstrated that ELOB was over-expressed in breast cancer tissues and was related to unfavorable prognosis. Additionally, pathway enrichment analysis illustrated that high expression of ELOB was associated with multiple cancer promoting pathways, like cell cycle, DNA replication, proteasome and PI3K - Akt signaling pathway, indicating ELOB as a potential anticancer target. Then, we confirmed that both in vivo and in vitro, the proliferation of breast cancer cells could be significantly suppressed by the down-regulation of ELOB. Mechanically, immunoprecipitation and in vivo ubiquitination assays prompted that, as the core element of Cullin2-RBX1-ELOB E3 ligase (CRL2) complex, ELOB regulated the ubiquitination and the subsequent degradation of oncoprotein p14/ARF. Moreover, the anticancer efficacy of erasing ELOB could be rescued by simultaneous knockdown of p14/ARF. Finally, through analyzing breast cancer tissue microarrays and western blot of patient samples, we demonstrated that the expression of ELOB in tumor tissues was elevated in compared to adjacent normal tissues. In conclusion, ELOB is identified to be a promising innovative target for the drug development of breast cancer by promoting the ubiquitination and degradation of oncoprotein p14/ARF.

Diagnosis of a Familial Psittacosis Outbreak with Clinical Analysis and Metagenomic Next-Generation Sequencing Under COVID-19: A Case Series.

Purpose: To explore the clinical characteristics, diagnosis, and treatment of family outbreak of psittacosis and to improve the success rate of treatment. Patients and Methods: The clinical characteristics, diagnosis, treatment, and outcome of family outbreak of psittacosis, which consists three patients, diagnosed by clinical analysis and metagenomic next-generation sequencing (mNGS) in our hospital were analyzed retrospectively. Results: We report on three instances of clustered atypical pneumonia, which were caused by Chlamydia psittaci during the COVID-19 pandemic. All patients exhibited symptoms of fever and cough, while one patient also experienced gastrointestinal symptoms such as nausea, vomiting, and diarrhea. Laboratory tests indicated no significant increase in leukocytes and neutrophils, but a mild increase in C-reactive protein was observed in all three patients. Chest computed tomography (CT) scans revealed a consolidation shadow in a unilateral lung lobe in all three patients. Both patients were treated with empirical moxifloxacin, yielding unsatisfactory outcomes. mNGS was conducted on sputum samples from one adult patient, revealing the presence of Chlamydia psittaci. Additional doxycycline was prescribed immediately, and then the patients' temperatures were stabilized, and the lesion in chest CT was absorbed. The pediatric patient exhibited less severe symptoms compared to the adult patients and exhibited a favorable response to azithromycin administration. Conclusion: This study reports a cluster of a family outbreak of atypical pneumonia caused by C. psittaci in China. The occurrence of a family outbreak during the COVID-19 pandemic may be attributed to familial aggregation resulting from the epidemic. The three cases reported in this study did not experience severe complications, which can be attributed to the prompt medical intervention and swift diagnosis. This finding implies the need to enhance patients' awareness and vigilance towards their health. Additionally, mNGS emerges as a valuable technique for accurately identifying pathogens causing pulmonary infections.

Effect of Low-Intensity Bloodflow Restriction Training on Nontraumatic Knee Joint Conditions: A Systematic Review and Meta-analysis.

CONTEXT: Nontraumatic knee conditions are common in clinical practice. Existing pharmaceutical and immobilization approaches provide limited pain relief and functional enhancement. Low-intensity bloodflow restriction training (LI-BFRT) is being investigated as a nonpharmacological alternative; however, its efficacy is uncertain. OBJECTIVE: To assess the effectiveness of LI-BFRT for nontraumatic knee conditions and compare it with high-intensity resistance training (HI-RT) and low-intensity resistance training (LI-RT). DATA SOURCES: PubMed, EBSCO, Science Direct, Cochrane Library, China Knowledge Infrastructure, Wanfang Data, and VIP databases were searched until May 30, 2023. STUDY SELECTION: Original randomized controlled trials involving nontraumatic knee joint conditions with interventions consisting mainly of LI-BFRT, HI-RT, or LI-RT. The results assessed mainly pain and muscle performance. STUDY DESIGN: Systematic review and meta-analysis. LEVEL OF EVIDENCE: Level 1. DATA EXTRACTION: Sample characteristics, study design, country, disease, groups, evaluation time, duration, and outcomes were extracted. RESULTS: A total of 13 randomized controlled trials were included in the systematic review. Compared with pretreatment, LI-BFRT significantly alleviated pain (weighted standardized mean difference [SMD], -1.33; 95% CI, -1.62 to -1.05), with better additional effects on hip muscle training (SMD, -3.14; 95% CI, -4.07 to -2.75). Compared with LI-RT, LI-BFRT significantly relieved pain in male patients (SMD, -1.47; 95% CI, -1.92 to -1.01). LI-BFRT significantly increased quadriceps cross-sectional area (SMD, 0.53; 95% CI, 0.27-0.78), knee extension strength (SMD, 0.84; 95% CI, 0.48-1.2), and leg press strength (SMD, 0.64; 95% CI, 0.34-0.94) compared with pretreatment. Its effects were superior to those of LI-RT and similar to those of HI-RT. However, sex differences in muscle strength improvement were observed. CONCLUSION: In patients with nontraumatic knee joint conditions, LI-BFRT effectively alleviated pain, increased muscle cross-sectional area, and enhanced muscle strength. LI-BFRT showed pain relief comparable with that of LI-RT while surpassing LI-RT in muscle growth and strength improvement.

Time-dependent CT score-based model for identifying severe/critical COVID-19 at a fever clinic after the emergence of Omicron variant.

Rationale and objectives: The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors. Materials and methods: This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination. Results: A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed. Conclusion: The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.

Universal growth of perovskite thin monocrystals from high solute flux for sensitive self-driven X-ray detection.

Metal-halide perovskite thin monocrystals featuring efficient carrier collection and transport capabilities are well suited for radiation detectors, yet their growth in a generic, well-controlled manner remains challenging. Here, we reveal that mass transfer is one major limiting factor during solution growth of perovskite thin monocrystals. A general approach is developed to overcome synthetic limitation by using a high solute flux system, in which mass diffusion coefficient is improved from 1.7×10-10 to 5.4×10-10 m2 s-1 by suppressing monomer aggregation. The generality of this approach is validated by the synthesis of 29 types of perovskite thin monocrystals at 40-90 °C with the growth velocity up to 27.2 µm min-1. The as-grown perovskite monocrystals deliver a high X-ray sensitivity of 1.74×105 µC Gy-1 cm-2 without applied bias. The findings regarding limited mass transfer and high-flux crystallization are crucial towards advancing the preparation and application of perovskite thin monocrystals.

Soil bacterial community in a photovoltaic system adopted different survival strategies to cope with small-scale light stress under different vegetation restoration modes.

Solar photovoltaic (PV) power generation is a major carbon reduction technology that is rapidly developing worldwide. However, the impact of PV plant construction on subsurface microecosystems is currently understudied. We conducted a systematic investigation into the effects of small-scale light stress caused by shading of PV panels and sampling depth on the composition, diversity, survival strategy, and key driving factors of soil bacterial communities (SBCs) under two vegetation restoration modes, i.e., Euryops pectinatus (EP) and Loropetalum chinense var. rubrum (LC). The study revealed that light stress had a greater impact on rare species with relative abundances below 0.01% than on high-abundance species, regardless of the vegetation restoration pattern. Additionally, PV shadowing increased SBCs' biomass by 20-30% but had varying negative effects on the numbers of Operational Taxonomic Unit (OTU), Shannon diversity, abundance-based coverage estimator (ACE), and Chao1 richness index. Co-occurrence and correlation network analysis revealed that symbiotic relationships dominated the key SBCs in the LC sample plots, with Chloroflexi and Actinobacteriota being the most ecologically important. In contrast, competitive relationships were significantly increased in the EP sample plots, with Actinobacteriota having the most ecological importance. In the EP sample plot, SBCs were found to be more tightly linked and had more stable ecological networks. This suggests that EP is more conducive to the stability and health of underground ecosystems in vulnerable areas when compared with LC. These findings offer new insights into the effects of small-scale light stress on subsurface microorganisms under different vegetation restoration patterns. Moreover, they may provide a reference for optimizing ecological restoration patterns in fragile areas.

The mechanism of lncRNA MALAT1 targeting the miR-124-3p/IGF2BP1 axis to regulate osteogenic differentiation of periodontal ligament stem cells.

OBJECTIVES: This study aimed to investigate the regulatory roles of lncRNA MALAT1, miR-124-3p, and IGF2BP1 in osteogenic differentiation of periodontal ligament stem cells (PDLSCs). MATERIALS AND METHODS: We characterized PDLSCs by employing quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analyses to evaluate the expression of key osteogenic markers including ALPL, SPP1, and RUNX2. Manipulation of lncRNA MALAT1 and miR-124-3p expression levels was achieved through transfection techniques. In addition, early osteogenic differentiation was assessed via Alkaline phosphatase (ALP) staining, and mineral deposition was quantified using Alizarin Red S (ARS) staining. Cellular localization of lncRNA MALAT1 was determined through Fluorescence In Situ Hybridization (FISH). To elucidate the intricate regulatory network, we conducted dual-luciferase reporter assays to decipher the binding interactions between lncRNA MALAT1 and miR-124-3P as well as between miR-124-3P and IGF2BP1. RESULTS: Overexpression of lncRNA MALAT1 robustly promoted osteogenesis in PDLSCs, while its knockdown significantly inhibited the process. We confirmed the direct interaction between miR-124-3p and lncRNA MALAT1, underscoring its role in impeding osteogenic differentiation. Notably, IGF2BP1 was identified as a direct binding partner of lncRNA MALAT1, highlighting its pivotal role within this intricate network. Moreover, we determined the optimal IGF2BP1 concentration (50 ng/ml) as a potent enhancer of osteogenesis, effectively countering the inhibition induced by si-MALAT1. Furthermore, in vivo experiments utilizing rat calvarial defects provided compelling evidence, solidifying lncRNA MALAT1's crucial role in bone formation. CONCLUSIONS: Our study reveals the regulatory network involving lncRNA MALAT1, miR-124-3p, and IGF2BP1 in PDLSCs' osteogenic differentiation. CLINICAL RELEVANCE: These findings enhance our understanding of lncRNA-mediated osteogenesis, offering potential therapeutic implications for periodontal tissue regeneration and the treatment of bone defects.

LiDAR Dynamic Target Detection Based on Multidimensional Features.

To address the limitations of LiDAR dynamic target detection methods, which often require heuristic thresholding, indirect computational assistance, supplementary sensor data, or postdetection, we propose an innovative method based on multidimensional features. Using the differences between the positions and geometric structures of point cloud clusters scanned by the same target in adjacent frame point clouds, the motion states of the point cloud clusters are comprehensively evaluated. To enable the automatic precision pairing of point cloud clusters from adjacent frames of the same target, a double registration algorithm is proposed for point cloud cluster centroids. The iterative closest point (ICP) algorithm is employed for approximate interframe pose estimation during coarse registration. The random sample consensus (RANSAC) and four-parameter transformation algorithms are employed to obtain precise interframe pose relations during fine registration. These processes standardize the coordinate systems of adjacent point clouds and facilitate the association of point cloud clusters from the same target. Based on the paired point cloud cluster, a classification feature system is used to construct the XGBoost decision tree. To enhance the XGBoost training efficiency, a Spearman's rank correlation coefficient-bidirectional search for a dimensionality reduction algorithm is proposed to expedite the optimal classification feature subset construction. After preliminary outcomes are generated by XGBoost, a double Boyer-Moore voting-sliding window algorithm is proposed to refine the final LiDAR dynamic target detection accuracy. To validate the efficacy and efficiency of our method in LiDAR dynamic target detection, an experimental platform is established. Real-world data are collected and pertinent experiments are designed. The experimental results illustrate the soundness of our method. The LiDAR dynamic target correct detection rate is 92.41%, the static target error detection rate is 1.43%, and the detection efficiency is 0.0299 s. Our method exhibits notable advantages over open-source comparative methods, achieving highly efficient and precise LiDAR dynamic target detection.

Preparation, structural characterization, biological activity, and nutritional applications of oligosaccharides.

Oligosaccharides are low-molecular-weight carbohydrates between monosaccharides and polysaccharides. They can be extracted directly from natural products by physicochemical methods or obtained by chemical synthesis or enzymatic reaction. Oligosaccharides have important physicochemical and physiological properties. Their research and production involve many disciplines such as medicine, chemical industry, and biology. Functional oligosaccharides, as an excellent functional food base, can be used as dietary fibrer and prebiotics to enrich the diet; improve the microecology of the gut; exert antitumour, anti-inflammatory, antioxidant, and lipid-lowering properties. Therefore, the industrial applications of oligosaccharides have increased rapidly in the past few years. It has great prospects in the field of food and medicinal chemistry. This review summarized the preparation, structural features and biological activities of oligosaccharides, with particular emphasis on the application of functional oligosaccharides in the food industry and human nutritional health. It aims to inform further research and development of oligosaccharides and food chemistry.

Polar Aromatic Two-dimensional Dion-Jacobson Halide Perovskites for Efficient Photocatalytic H2 Evolution.

Polar materials with spontaneous polarization (Ps) have emerged as highly promising photocatalysts for efficient photocatalytic H2 evolution owing to the Ps-enhanced photogenerated carrier separation. However, traditional inorganic polar materials often suffer from limitations such as wide band gaps and poor carrier transport, which hinders their photocatalytic H2 evolution efficiency. Here, we rationally synthesized a series of isostructural two-dimensional (2D) aromatic Dion-Jacobson (DJ) perovskites, namely (2-(2-Aminoethyl)pyridinium)PbI4 (2-APDPI), (3-(2-Aminoethyl)pyridinium)PbI4 (3-APDPI), and (4-(2-Aminoethyl)pyridinium)PbI4 (4-APDPI), where 2-APDPI and 4-APDPI crystalize in polar space groups with piezoelectric constants (d33) of approximately 40 pm V-1 and 3-APDPI adopts a centrosymmetric structure. Strikingly, owing to the Ps-facilitated separation of photogenerated carriers, polar 2-APDPI and 4-APDPI exhibit a 3.9- and 2.8-fold increase, respectively, in photocatalytic H2 evolution compared to the centrosymmetric 3-APDPI. As a pioneering study, this work provides an efficient approach for exploring new polar photocatalysts and highlights their potential in promoting photocatalytic H2 evolution.

Effects of Land Use Type Transformation on the Structure and Diversity of Soil Bacterial Communities.

Soil microbiota are significantly influenced by their microenvironments. Therefore, to understand the impacts of various land use patterns on the diversity and composition of soil bacterial communities, this study focused on three typical land use types-NF (natural forest), AF (artificial forests), and FL (farmland)-in the Heilongjiang Central Station Black-billed Capercaillie National Nature Reserve, located in the southwestern part of Heihe City, Heilongjiang Province, China. Using high-throughput sequencing of the 16S rRNA gene, we examined the soil bacterial community structures in these different land use types and explored their correlation with soil environmental factors. The following were our main observations: (1) Significant variations in soil chemical properties among different land use patterns were observed. In artificial forests, total nitrogen (TN), alkali hydrolyzed nitrogen (AN), total phosphorus (TP), and available phosphorus (AP) were higher compared to farmland and significantly higher than those in natural forests. Furthermore, the organic carbon content (SOC) in natural forests was higher than in artificial forests and significantly higher than in farmland. (2) Comparative analysis using the Shannon and Simpson indices revealed that bacterial community diversity was higher in artificial forests than in natural forests, which was significantly higher than in farmland. (3) The effect of different land use types on soil bacterial community structure was not significant. The three land types were dominated by Proteobacteria, Acidobacteria, and Actinobacteria. Proteobacteria exhibited a higher relative abundance in farmland and artificial forests compared to natural forests, whereas Actinobacteria exhibited the lowest relative abundance in natural forests. (4) Redundancy analysis (RDA) revealed that SOC, TN, AN, and AP were key environmental factors influencing the microbial communities of soil. Collectively, our findings demonstrated that land use practices can significantly alter soil nutrient levels, thereby influencing the structure of bacterial communities.

Insights into lenvatinib resistance: mechanisms, potential biomarkers, and strategies to enhance sensitivity.

Lenvatinib is a multitargeted tyrosine kinase inhibitor capable of promoting apoptosis, suppressing angiogenesis, inhibiting tumor cell proliferation, and modulating the immune response. In multiple cancer types, lenvatinib has presented manageable safety and is currently approved as an effective first-line therapy. However, with the gradual increase in lenvatinib application, the inevitable progression of resistance to lenvatinib is becoming more prevalent. A series of recent researches have reported the mechanisms underlying the development of lenvatinib resistance in tumor therapy, which are related to the regulation of cell death or proliferation, histological transformation, metabolism, transport processes, and epigenetics. In this review, we aim to outline recent discoveries achieved in terms of the mechanisms and potential predictive biomarkers of lenvatinib resistance as well as to summarize untapped approaches available for improving the therapeutic efficacy of lenvatinib in patients with various types of cancers.

Optimising first-line subtyping-based therapy in triple-negative breast cancer (FUTURE-SUPER): a multi-cohort, randomised, phase 2 trial.

BACKGROUND: Triple-negative breast cancers display heterogeneity in molecular drivers and immune traits. We previously classified triple-negative breast cancers into four subtypes: luminal androgen receptor (LAR), immunomodulatory, basal-like immune-suppressed (BLIS), and mesenchymal-like (MES). Here, we aimed to evaluate the efficacy and safety of subtyping-based therapy in the first-line treatment of triple-negative breast cancer. METHODS: FUTURE-SUPER is an ongoing, open-label, randomised, controlled phase 2 trial being conducted at Fudan University Shanghai Cancer Center (FUSCC), Shanghai, China. Eligible participants were females aged 18-70 years, with an Eastern Cooperative Oncology Group performance status of 0-1, and histologically confirmed, untreated metastatic or recurrent triple-negative breast cancer. After categorising participants into five cohorts according to molecular subtype and genomic biomarkers, participants were randomly assigned (1:1) with a block size of 4, stratified by subtype, to receive, in 28-day cycles, nab-paclitaxel (100 mg/m2, intravenously on days 1, 8, and 15) alone (control group) or with a subtyping-based regimen (subtyping-based group): pyrotinib (400 mg orally daily) for the LAR-HER2mut subtype, everolimus (10 mg orally daily) for the LAR-PI3K/AKTmut and MES-PI3K/AKTmut subtypes, camrelizumab (200 mg intravenously on days 1 and 15) and famitinib (20 mg orally daily) for the immunomodulatory subtype, and bevacizumab (10 mg/kg intravenously on days 1 and 15) for the BLIS/MES-PI3K/AKTWT subtype. The primary endpoint was investigator-assessed progression-free survival for the pooled subtyping-based group versus the control group in the intention-to-treat population (all randomly assigned participants). Safety was analysed in all patients with safety records who received at least one dose of study drug. This study is registered with ClinicalTrials.gov (NCT04395989). FINDINGS: Between July 28, 2020, and Oct 16, 2022, 139 female participants were enrolled and randomly assigned to the subtyping-based group (n=69) or control group (n=70). At the data cutoff (May 31, 2023), the median follow-up was 22·5 months (IQR 15·2-29·0). Median progression-free survival was significantly longer in the pooled subtyping-based group (11·3 months [95% CI 8·6-15·2]) than in the control group (5·8 months [4·0-6·7]; hazard ratio 0·44 [95% CI 0·30-0·65]; p<0·0001). The most common grade 3-4 treatment-related adverse events were neutropenia (21 [30%] of 69 in the pooled subtyping-based group vs 16 [23%] of 70 in the control group), anaemia (five [7%] vs none), and increased alanine aminotransferase (four [6%] vs one [1%]). Treatment-related serious adverse events were reported for seven (10%) of 69 patients in the subtyping-based group and none in the control group. No treatment-related deaths were reported in either group. INTERPRETATION: These findings highlight the potential clinical benefits of using molecular subtype-based treatment optimisation in patients with triple-negative breast cancer, suggesting a path for further clinical investigation. Phase 3 randomised clinical trials assessing the efficacy of subtyping-based regimens are now underway. FUNDING: National Natural Science Foundation of China, Natural Science Foundation of Shanghai, Shanghai Hospital Development Center, and Jiangsu Hengrui Pharmaceuticals. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.