Emerging contaminants in water environments: progress, evolution, and prospects.

This article employs bibliometric tools like VOSviewer, Bibliometrix, and CiteSpace for a comprehensive visual analysis of 1,612 documents on Emerging Contaminants in Waters from the Web of Science database. The objective is to elucidate the historical development, research hotspots, and trends in international studies of this field, offering valuable insights and guidance for future research directions. The analysis reveals a consistent increase in publications from 2003 to 2023, with the United States, China, and Spain being the most prolific contributors. A detailed examination of keyword co-occurrence and cluster analysis shows a predominant focus on themes such as pollutant detection, risk assessment, and biogeochemical cycling. Furthermore, the study underscores the significance of forming interdisciplinary networks among authors and institutions, highlighting its critical role in enhancing the quality and innovation of scientific research. The findings of this study not only chart the progression and focal points of research in this domain but also underscore the pivotal role of international collaboration, serving as an indispensable reference for shaping future research trajectories and fostering global cooperation.

Association of soluble TREM2 with Alzheimer's disease and mild cognitive impairment: a systematic review and meta-analysis.

Objective: Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) is a potential neuroinflammatory biomarker linked to the pathogenesis of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Previous studies have produced inconsistent results regarding sTREM2 levels in various clinical stages of AD. This study aims to establish the correlation between sTREM2 levels and AD progression through a meta-analysis of sTREM2 levels in cerebrospinal fluid (CSF) and blood. Methods: Comprehensive searches were conducted in PubMed, Embase, Web of Science, and the Cochrane Library to identify observational studies reporting CSF and blood sTREM2 levels in AD patients, MCI patients, and healthy controls. A random effects meta-analysis was used to calculate the standardized mean difference (SMD) and 95% confidence intervals (CIs). Results: Thirty-six observational studies involving 3,016 AD patients, 3,533 MCI patients, and 4,510 healthy controls were included. CSF sTREM2 levels were significantly higher in both the AD [SMD = 0.28, 95% CI (0.15, 0.41)] and MCI groups [SMD = 0.30, 95% CI (0.13, 0.47)] compared to the healthy control group. However, no significant differences in expression were detected between the AD and MCI groups [SMD = 0.09, 95% CI (-0.09, 0.26)]. Furthermore, increased plasma sTREM2 levels were associated with a higher risk of AD [SMD = 0.42, 95% CI (0.01, 0.83)]. Conclusion: CSF sTREM2 levels are positively associated with an increased risk of AD and MCI. Plasma sTREM2 levels were notably higher in the AD group than in the control group and may serve as a promising biomarker for diagnosing AD. However, sTREM2 levels are not effective for distinguishing between different disease stages of AD. Further investigations are needed to explore the longitudinal changes in sTREM2 levels, particularly plasma sTREM2 levels, during AD progression. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024514593.

Risk factors for secondary thyroid cancer in patients with breast cancer: a propensity­matched SEER analysis.

With the rapid development of imaging technology and comprehensive treatment in modern medicine, the early diagnosis rate of breast cancer is constantly improving, and the prognosis is also improving; As breast cancer patients survive longer, the risk of developing second primary cancers increases. Since both breast and thyroid are Hormone receptor sensitive organs, which are regulated by hypothalamus pituitary target gland endocrine axis, changes in body endocrine status may lead to the occurrence of these two diseases in succession or simultaneously. This study extracted clinical data and survival outcomes of breast cancer patients registered in the Surveillance, Epidemiology and End Results (SEER) database between 2010 and 2019. After matching the case and controls with propensity scores, the selected patients were randomly split into training and test datasets at a ratio of 7:3. Univariate and multivariate COX proportional regression analysis is used to determine independent risk factors for secondary thyroid cancer and construct a column chart prediction model. Age, ethnicity, whether radiotherapy, tumor primary location, N stage, M stage were identified by Cox regression as independent factors affecting secondary thyroid cancer in patients with breast cancer patients, and a risk factor nomogram was established to predict patients' 3 and 5 year survival probabilities. The AUC values for 3 and 5 years in the training set were 0.713, 0.707, and the c-index was 0.693 (95% CI 0.67144, 0.71456), and the AUC values for 3 and 5 years in the validation set were 0.681, 0.681, and the c-index was 0.673 (95% CI 0.64164, 0.70436), respectively.

Application of machine learning algorithms to identify people with low bone density.

Background: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis. Objective: This study aimed to develop a machine learning algorithm to effectively identify people with low bone density, using readily available demographic and blood biochemical data. Methods: Using NHANES 2017-2020 data, participants over 50 years old with complete femoral neck BMD data were selected. This cohort was randomly divided into training (70%) and test (30%) sets. Lasso regression selected variables for inclusion in six machine learning models built on the training data: logistic regression (LR), support vector machine (SVM), gradient boosting machine (GBM), naive Bayes (NB), artificial neural network (ANN) and random forest (RF). NHANES data from the 2013-2014 cycle was used as an external validation set input into the models to verify their generalizability. Model discrimination was assessed via AUC, accuracy, sensitivity, specificity, precision and F1 score. Calibration curves evaluated goodness-of-fit. Decision curves determined clinical utility. The SHAP framework analyzed variable importance. Results: A total of 3,545 participants were included in the internal validation set of this study, of whom 1870 had normal bone density and 1,675 had low bone density Lasso regression selected 19 variables. In the test set, AUC was 0.785 (LR), 0.780 (SVM), 0.775 (GBM), 0.729 (NB), 0.771 (ANN), and 0.768 (RF). The LR model has the best discrimination and a better calibration curve fit, the best clinical net benefit for the decision curve, and it also reflects good predictive power in the external validation dataset The top variables in the LR model were: age, BMI, gender, creatine phosphokinase, total cholesterol and alkaline phosphatase. Conclusion: The machine learning model demonstrated effective classification of low BMD using blood biomarkers. This could aid clinical decision making for osteoporosis prevention and management.

BeEAM vs. BEAM: evaluating conditioning regimens for autologous stem cell transplantation in patients with relapsed or refractory DLBCL.

PURPOSE: To evaluate whether BeEAM is an alternative to BEAM for autologous stem cell transplantation (ASCT) in patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL). METHODS: Data of 60 patients with relapsed or refractory DLBCL who underwent ASCT from January 2018 to June 2023 in our center, including 30 patients in the BeEAM group and 30 patients in the BEAM group, were retrospectively analyzed. The time to hematopoietic reconstitution, treatment-related adverse events, number of hospitalization days, hospitalization cost, and survival benefit were compared between the two groups. RESULTS: The clinical characteristics of the patients did not significantly differ between the two groups. The median number of reinfused CD34 + cells was 5.06 × 106/kg and 5.17 × 106/kg in the BeEAM and BEAM groups, respectively, which did not significantly different (p = 0.8829). In the BeEAM and BEAM groups, the median time to neutrophil implantation was 10.2 and 10.27 days, respectively (p = 0.8253), and the median time to platelet implantation was 13.23 and 12.87 days, respectively (p = 0.7671). In the BeEAM and BEAM groups, the median hospitalization duration was 30.37 and 30.57 days, respectively (p = 0.9060), and the median hospitalization cost was RMB 83,425 and RMB 96,235, respectively (p = 0.0560). The hospitalization cost was lower in the BeEAM group. The most common hematologic adverse events were grade ≥ 3 neutropenia and thrombocytopenia, whose incidences were similar in the two groups. The most common non-hematologic adverse events were ≤ grade 2 and the incidences of these events did not significantly differ between the two groups. Median overall survival was not reached in either group, with predicted 5-year overall survival of 72.5% and 60% in the BeEAM and BEAM groups, respectively (p = 0.5872). Five-year progression-free survival was 25% and 20% in the BeEAM and BEAM groups, respectively (p = 0.6804). CONCLUSION: As a conditioning regimen for relapsed or refractory DLBCL, BeEAM has a desirable safety profile and is well tolerated, and its hematopoietic reconstitution time, number of hospitalization days, and survival benefit are not inferior to those of BEAM. BeEAM has a lower hospitalization cost and is an alternative to BEAM.

Genetic Complexities of Cerebral Small Vessel Disease, Blood Pressure, and Dementia.

Importance: Vascular disease is a treatable contributor to dementia risk, but the role of specific markers remains unclear, making prevention strategies uncertain. Objective: To investigate the causal association between white matter hyperintensity (WMH) burden, clinical stroke, blood pressure (BP), and dementia risk, while accounting for potential epidemiologic biases. Design, Setting, and Participants: This study first examined the association of genetically determined WMH burden, stroke, and BP levels with Alzheimer disease (AD) in a 2-sample mendelian randomization (2SMR) framework. Second, using population-based studies (1979-2018) with prospective dementia surveillance, the genetic association of WMH, stroke, and BP with incident all-cause dementia was examined. Data analysis was performed from July 26, 2020, through July 24, 2022. Exposures: Genetically determined WMH burden and BP levels, as well as genetic liability to stroke derived from genome-wide association studies (GWASs) in European ancestry populations. Main Outcomes and Measures: The association of genetic instruments for WMH, stroke, and BP with dementia was studied using GWASs of AD (defined clinically and additionally meta-analyzed including both clinically diagnosed AD and AD defined based on parental history [AD-meta]) for 2SMR and incident all-cause dementia for longitudinal analyses. Results: In 2SMR (summary statistics-based) analyses using AD GWASs with up to 75 024 AD cases (mean [SD] age at AD onset, 75.5 [4.4] years; 56.9% women), larger WMH burden showed evidence for a causal association with increased risk of AD (odds ratio [OR], 1.43; 95% CI, 1.10-1.86; P = .007, per unit increase in WMH risk alleles) and AD-meta (OR, 1.19; 95% CI, 1.06-1.34; P = .008), after accounting for pulse pressure for the former. Blood pressure traits showed evidence for a protective association with AD, with evidence for confounding by shared genetic instruments. In the longitudinal (individual-level data) analyses involving 10 699 incident all-cause dementia cases (mean [SD] age at dementia diagnosis, 74.4 [9.1] years; 55.4% women), no significant association was observed between larger WMH burden and incident all-cause dementia (hazard ratio [HR], 1.02; 95% CI, 1.00-1.04; P = .07). Although all exposures were associated with mortality, with the strongest association observed for systolic BP (HR, 1.04; 95% CI, 1.03-1.06; P = 1.9 × 10-14), there was no evidence for selective survival bias during follow-up using illness-death models. In secondary analyses using polygenic scores, the association of genetic liability to stroke, but not genetically determined WMH, with dementia outcomes was attenuated after adjusting for interim stroke. Conclusions: These findings suggest that WMH is a primary vascular factor associated with dementia risk, emphasizing its significance in preventive strategies for dementia. Future studies are warranted to examine whether this finding can be generalized to non-European populations.

Exciton Localization Modulated by Ultradeep Moiré Potential in Twisted Bilayer γ-Graphdiyne.

Twisted moiré superlattice is featured with its moiré potential energy, the depth of which renders an effective approach to strengthening the exciton-exciton interaction and exciton localization toward high-performance quantum photonic devices. However, it remains as a long-standing challenge to further push the limit of moiré potential depth. Herein, owing to the pz orbital induced band edge states enabled by the unique sp-C in bilayer γ-graphdiyne (GDY), an ultradeep moiré potential of ∼289 meV is yielded. After being twisted into the hole-to-hole layer stacking configuration, the interlayer coupling is substantially intensified to augment the lattice potential of bilayer GDY up to 475%. The presence of lateral constrained moiré potential shifts the spatial distribution of electrons and holes in excitons from the regular alternating mode to their respective separated and localized mode. According to the well-established wave function distribution of electrons contained in excitons, the AA-stacked site is identified to serve for exciton localization. This work extends the materials systems available for moiré superlattice design further to serial carbon allotropes featured with benzene ring-alkyne chain coupling, unlocking tremendous potential for twistronic-based quantum device applications.

Primate-Specific DAZ Regulates Translation of Cell Proliferation-Related mRNAs and is Essential for Maintenance of Spermatogonia.

Primate-specific DAZ (deleted in azoospermia) has evolved in the azoospermia factor c (AZFc) locus on the Y chromosome. Loss of DAZ is associated with azoospermia in patients with deletion of the AZFc region (AZFc_del). However, the molecular mechanisms of DAZ in spermatogenesis remain uncertain. In this study, the molecular mechanism of DAZ is identified, which is unknown since it is identified 40 years ago because of the lack of a suitable model. Using clinical samples and cell models, it is shown that DAZ plays an important role in spermatogenesis and that loss of DAZ is associated with defective proliferation of c-KIT-positive spermatogonia in patients with AZFc_del. Mechanistically, it is shown that knockdown of DAZ significantly downregulated global translation and subsequently decreased cell proliferation. Furthermore, DAZ interacted with PABPC1 via the DAZ repeat domain to regulate global translation. DAZ targeted mRNAs that are involved in cell proliferation and cell cycle phase transition. These findings indicate that DAZ is a master translational regulator and essential for the maintenance of spermatogonia. Loss of DAZ may result in defective proliferation of c-KIT-positive spermatogonia and spermatogenic failure.

An Integrated Gather-and-Distribute Mechanism and Attention-Enhanced Deformable Convolution Model for Pig Behavior Recognition.

The behavior of pigs is intricately tied to their health status, highlighting the critical importance of accurately recognizing pig behavior, particularly abnormal behavior, for effective health monitoring and management. This study addresses the challenge of accommodating frequent non-rigid deformations in pig behavior using deformable convolutional networks (DCN) to extract more comprehensive features by incorporating offsets during training. To overcome the inherent limitations of traditional DCN offset weight calculations, the study introduces the multi-path coordinate attention (MPCA) mechanism to enhance the optimization of the DCN offset weight calculation within the designed DCN-MPCA module, further integrated into the cross-scale cross-feature (C2f) module of the backbone network. This optimized C2f-DM module significantly enhances feature extraction capabilities. Additionally, a gather-and-distribute (GD) mechanism is employed in the neck to improve non-adjacent layer feature fusion in the YOLOv8 network. Consequently, the novel DM-GD-YOLO model proposed in this study is evaluated on a self-built dataset comprising 11,999 images obtained from an online monitoring platform focusing on pigs aged between 70 and 150 days. The results show that DM-GD-YOLO can simultaneously recognize four common behaviors and three abnormal behaviors, achieving a precision of 88.2%, recall of 92.2%, and mean average precision (mAP) of 95.3% with 6.0MB Parameters and 10.0G FLOPs. Overall, the model outperforms popular models such as Faster R-CNN, EfficientDet, YOLOv7, and YOLOv8 in monitoring pens with about 30 pigs, providing technical support for the intelligent management and welfare-focused breeding of pigs while advancing the transformation and modernization of the pig industry.

Constitutive Model and Microstructure Evolution of Ti65 Titanium Alloy.

The hot deformation behavior and mechanism of Ti65 alloy with a bimodal microstructure were investigated by isothermal compression experiments conducted on the Thermecmastor-Z simulator equipment at temperatures ranging from 950 to 1110 °C and strain rates ranging from 0.01 to 10.0 s-1. The Arrhenius constitutive model, based on strain compensation, and Grey Wolf optimization-neural network with back propagation model (GWO-BP), were both established. The differences between the experimental and predicted value of flow stress were compared and analyzed using the two models. The results show that the prediction accuracy of GWO-BP in the two-phase region is higher than that of Arrhenius model. In the single-phase region, both methods demonstrated high prediction accuracy. Compared to the single-phase region, the flow stress of Ti65 alloy shows a higher degree of softening in the two-phase region. During deformation in the two-phase region, the initial lamellar α phase transformed from a kinked and elongated morphology to a globularized topography as the strain rate decreased. Boundary-splitting was the primary mechanism leading to the spheroidization process. The degree of recrystallization increased with the increase in strain rate during the deformation in the single-phase region, while dynamic recovery and strain-induced grain boundary migration were the main deformation mechanisms at a lower strain rate. Discontinuous dynamic recrystallization may be the dominant recrystallization mechanism under a high strain rate of 10 s-1.

Enhancing the understanding of SARS-CoV-2 protein with structure and detection methods: An integrative review.

As the rapid and accurate screening of infectious diseases can provide meaningful information for outbreak prevention and control, as well as owing to the existing limitations of the polymerase chain reaction (PCR), it is imperative to have new and validated detection techniques for SARS-CoV-2. Therefore, the rationale for outlining the techniques used to detect SARS-CoV-2 proteins and performing a comprehensive comparison to serve as a practical benchmark for future identification of similar viral proteins is clear. This review highlights the urgent need to strengthen pandemic preparedness by emphasizing the importance of integrated measures. These include improved tools for pathogen characterization, optimized societal precautions, the establishment of early warning systems, and the deployment of highly sensitive diagnostics for effective surveillance, triage, and resource management. Additionally, with an improved understanding of the virus' protein structure, considerable advances in targeted detection, treatment, and prevention strategies are expected to greatly improve our ability to respond to future outbreaks.

Oxidized sodium alginate hydrogel-mouse nerve growth factor sustained release system promotes repair of peripheral nerve injury.

In recent years, mouse nerve growth factor (mNGF) has emerged as an important biological regulator to repair peripheral nerve injury, but its systemic application is restricted by low efficiency and large dosage requirement. These limitations prompted us to search for biomaterials that can be locally loaded. Oxidized sodium alginate hydrogel (OSA) exhibits good biocompatibility and physicochemical properties, and can be loaded with drugs to construct a sustained-release system that can act locally on nerve injury. Here, we constructed a sustained-release system of OSA-mouse nerve growth factor (mNGF), and investigated the loading and release of the drug through Fourier transform infrared spectroscopy and drug release curves. In vitro and in vivo experiments showed that OSA-mNGF significantly promoted the biological activities of RSC-96 cells and facilitated the recovery from sciatic nerve crush injury in rats. This observation may be attributed to the additive effect of OSA on promoting Schwann cell biological activities or its synergistic effect of cross-activating phosphoinositide 3-kinase (PI3K) through extracellular signal regulated kinase (ERK) signaling. Although the specific mechanism of OSA action needs to be explored in the future, the current results provide a valuable preliminary research basis for the clinical application of the OSA-mNGF sustained-release system for nerve repair.

Real-time soft body dissection simulation with parallelized graph-based shape matching on GPU.

BACKGROUND AND OBJECTIVE: Interactive soft tissue dissection has been a fundamental procedure in virtual surgery systems. Existing cutting algorithms involve complex topology changes of simulation meshes, which can increase simulation overhead and produce visual artifacts. In this paper, we proposed a novel graph-based shape-matching method that allows for real-time, flexible, progressive, and discontinuous cuts on soft tissue. METHODS: We employed shape-matching constraints within the position-based dynamics (PBD) framework, a widely adopted approach for real-time simulation applications. The soft tissue was effectively modeled using overlapping clusters, each governed by shape-matching constraints. The dissection process was bifurcated into two distinct stages. In the first stage, the surgical scalpel presses the surface of the soft tissue. The soft tissue is cut apart when the surface pressure exceeds a threshold, entering the second stage. To address the discrepancy between the visual mesh and the simulation model during cluster separation, we developed an Aggregate Finding Connected Components (AFCC) algorithm, optimized for GPU computation and integrated with a background grid. This approach also avoids ghost forces and fragmentation artifacts. To control the increase in the number of clusters, we also propose a merging strategy that can run in parallel. RESULTS: Our simulation outcomes demonstrated that the AFCC dissection algorithm effectively manages cluster separation and expansion with robustness. There were no ghost forces between the cutting surface and unrealistic fragments. Our simulation capability extended to supporting intricate and discontinuous cutting routes. Our dissection simulation maintained real-time performance even with over 100,000 particles constituting the soft tissue. CONCLUSIONS: Our real-time and robust surgical dissection simulation technique enables the performance of complex cuts in various surgical scenarios, demonstrating its potential in virtual surgery applications.

Preparation and Performance of Ceramic Tiles with Steel Slag and Waste Clay Bricks.

Steel slag and waste clay bricks are two prevalent solid waste materials generated during industrial production. The complex chemical compositions of these materials present challenges to their utilization in conventional alumina silicate ceramics manufacturing. A new type of ceramic tile, which utilizes steel slag and waste clay brick as raw materials, has been successfully developed in order to effectively utilize these solid wastes. The optimal composition of the ceramic material was determined through orthogonal experimentation, during which the effects of the sample molding pressure, the soaking time, and the sintering temperature on the ceramic properties were studied. The results show that the optimal ceramic tile formula was 45% steel slag, 35% waste clay bricks, and 25% talc. The optimal process parameters for this composition included a molding pressure of 25 MPa, a sintering temperature of 1190 °C, and a soaking time of 60 min. The prepared ceramic tile samples had compositions in which solid waste accounted for more than 76% of the total material. Additionally, they possessed a modulus of rupture of more than 73.2 MPa and a corresponding water absorption rate of less than 0.05%.

Network Pharmacology Analysis of Liquid-Cultured Armillaria ostoyae Mycelial Metabolites and Their Molecular Mechanism of Action against Gastric Cancer.

Armillaria sp. are traditional edible medicinal mushrooms with various health functions; however, the relationship between their composition and efficacy has not yet been determined. Here, the ethanol extract of liquid-cultured Armillaria ostoyae mycelia (AOME), a pure wild Armillaria sp. strain, was analyzed using UHPLC-QTOF/MS, network pharmacology, and molecular docking techniques. The obtained extract affects various metabolic pathways, such as JAK/STAT and PI3K/AKT. The extract also contains important compounds such as 4-(dimethylamino)-N-[7-(hydroxyamino)-7-oxoheptyl] benzamide, isoliquiritigenin, and 7-hydroxycoumarin. Moreover, the extract targets key proteins, including EGFR, SCR, and IL6, to suppress the progression of gastric cancer, thereby synergistically inhibiting cancer development. The molecular docking analyses indicated that the main compounds stably bind to the target proteins. The final cell culture experimental data showed that the ethanol extract inhibited MGC-803 gastric cancer cells. In summary, our research revealed the beneficial components of AOME for treating gastric cancer and its associated molecular pathways. However, further research is needed to confirm its effectiveness and safety in gastric cancer patients.

Catalytic hairpin self-assembly amplification fluorescence detection of chloramphenicol based on cross-shaped DNA and UiO-66.

A catalytic hairpin self-assembly (CHA) amplification method was developed for CAP detection based on cross-shaped DNA and UiO-66. MOF was used to quench the fluorescent signal of FAM labeled DNA. Cross-shaped DNA with four fluorophore group (FAM) was utilized to enhance the fluorescent intensity. CAP could open hairpin structure of H-apt and induce CHA reaction. The product of CHA hybridized with cross-shaped DNA, resulting its leaving from the surface of UiO-66 and recovery of fluorescent signal. The limit of detection (LOD) was low to 0.87 pM. This method had been successfully applied for the detection of CAP in actual samples. Importantly, the high sensitivity was attributed to the great amplification efficiency of CHA, strong fluorescent intensity of cross-shaped DNA structure and great fluorescent quenched efficiency of UiO-66.

Identification, Characterization, Cloning, and Cross-Reactivity of Zan b 2, a Novel Pepper Allergen of 11S Legumin.

Protein from Sichuan peppers can elicit mild to severe allergic reactions. However, little is known about their allergenic proteins. We aimed to isolate, identify, clone, and characterize Sichuan pepper allergens and to determine its allergenicity and cross-reactivities. Sichuan pepper seed proteins were extracted and then analyzed by SDS-PAGE. Western blotting was performed with sera from Sichuan pepper-allergic individuals. Proteins of interest were purified using hydrophobic interaction chromatography and gel filtration and further analyzed by analytical ultracentrifugation, circular dichroism spectroscopy, and mass spectrometry (MS). Their coding region was amplified in the genome. IgE reactivity and cross-reactivity of allergens were evaluated by dot blot, enzyme-linked immunosorbent assay (ELISA), and competitive ELISA. Western blot showed IgE binding to a 55 kDa protein. This protein was homologous to the citrus proteins and has high stability and a sheet structure. Four DNA sequences were cloned. Six patients' sera (60%) showed specific IgE reactivity to this purified 11S protein, which was proved to have cross-reactivation with extracts of cashew nuts, pistachios, and citrus seeds. A novel allergen in Sichuan pepper seeds, Zan b 2, which belongs to the 11S globulin family, was isolated and identified. Its cross-reactivity with cashew nuts, pistachios, and citrus seeds was demonstrated.

Comparison of the therapeutic effects of medication therapy, specific immunotherapy and anti-IgE (Omalizumab) in patients with hay fever.

Background: Hay fever, characterized by seasonal allergic reactions, poses a significant health challenge. Existing therapies encompass standard drug regimens, biological agents, and specific immunotherapy. This study aims to assess and compare the effectiveness of anti-IgE (omalizumab), medication therapy, and subcutaneous immunotherapy (SCIT) for hay fever. Methods: Conducted as a retrospective cohort study, this research involved 98 outpatient hay fever patients who underwent routine medication, omalizumab treatment, or SCIT before the onset of the spring pollen season. A follow-up was performed one month after the start of the pollen season. The comprehensive symptoms and drug scores were used to evaluate patients with different intervention methods, facilitating a comparative analysis of therapeutic outcomes. Results: Compared with before treatment, the symptoms of patients treated with the three methods were all significantly relieved, and the medication score were significantly reduced. Patients treated with omalizumab demonstrated higher symptoms and medication scores than SCIT group before treatment, but similar scores after treatment, which were both lower than medicine treatment group. After treatment with omalizumab or SCIT, patients in both groups had significantly lower medication scores than the medication group and were close to no longer using medication for symptom relief. The mountain juniper-sIgE was significantly higher after treatment than before treatment in both medicine treatment group and omalizumab treatment group. Conclusion: Omalizumab and SCIT offer superior effects than medication therapy in hay fever patients.

Overexpression of the PtrNF-YA6 gene inhibits secondary cell wall thickening in poplar.

The NF-Y gene family in plants plays a crucial role in numerous biological processes, encompassing hormone response, stress response, as well as growth and development. In this study, we first used bioinformatics techniques to identify members of the NF-YA family that may function in wood formation. We then used molecular biology techniques to investigate the role and molecular mechanism of PtrNF-YA6 in secondary cell wall (SCW) formation in Populus trichocarpa. We found that PtrNF-YA6 protein was localized in the nucleus and had no transcriptional activating activity. Overexpression of PtrNF-YA6 had an inhibitory effect on plant growth and development and significantly suppressed hemicellulose synthesis and SCW thickening in transgenic plants. Yeast one-hybrid and ChIP-PCR assays revealed that PtrNF-YA6 directly regulated the expression of hemicellulose synthesis genes (PtrGT47A-1, PtrGT8C, PtrGT8F, PtrGT43B, PtrGT47C, PtrGT8A and PtrGT8B). In conclusion, PtrNF-YA6 can inhibit plant hemicellulose synthesis and SCW thickening by regulating the expression of downstream SCW formation-related target genes.

Ultralow Thermal Conductivity of a Chalcogenide System Pt3Bi4Q9 (Q = S, Se) Driven by the Hierarchy of Rigid [Pt6Q12]12- Clusters Embedded in Soft Bi-Q Sublattice.

Knowledge of structure-property relationships in solids with intrinsic low thermal conductivity is crucial for fields such as thermoelectrics, thermal barrier coatings, and refractories. Herein, we propose a new "rigidness in softness" structural scheme for intrinsic low lattice thermal conductivity (κL), which embeds rigid clusters into the soft matrix to induce large lattice anharmonicity, and accordingly discover a new series of chalcogenides Pt3Bi4Q9 (Q = S, Se). Pt3Bi4S9-xSex (x = 3, 6) achieved an intrinsic ultralow κL down to 0.39 W/(m K) at 773 K, which is considerably low among the Bi chalcogenide thermoelectric materials. Pt3Bi4Q9 contains the rigid cubic [Pt6Q12]12- clusters embedded in the soft Bi-Q sublattice, involving multiple bonding interactions and vibration hierarchy. The hierarchical structure yields a large lattice anharmonicity with high Grüneisen parameters (γ) 1.97 of Pt3Bi4Q9, as verified by the effective scatter of low-lying optical phonons toward heat-carrying acoustic phonons. Consequently, the rigid-soft coupling significantly inhibits heat propagation, exhibiting low acoustic phonon frequencies (∼25 cm-1) and Debye temperatures (ΘD = 170.4 K) in Pt3Bi4Se9. Owing to the suppressed κL and considerable power factor (PF), the ZT value of Pt3Bi4S6Se3 can reach 0.56 at 773 K without heavy carrier doping, which is competitive among the pristine Bi chalcogenides. Theoretical calculations predicted a large potential for performance improvement via proper doping, indicating the great potential of this structure type for promising thermoelectric materials.