Regulating the valence and size of the active center of Co/Al2O3 catalyst improved the performance and selectivity of NH3-SCO.

To improve the activity of Co/Al2O3 catalysts in selective catalytic oxidation of ammonia (NH3-SCO), valence state and size of active centers of Al2O3-supported Co catalysts were adjusted by conducting H2 reduction pretreatment. The NH3-SCO activity of the adjusted 2Co/Al2O3 catalyst was substantially improved, outperforming other catalysts with higher Co-loading. Fresh Co/Al2O3 catalysts exhibited multitemperature reduction processes, enabling the control of the valence state of the Co-active centers by adjusting the reduction temperature. Changes in the state of the Co-active centers also led to differences in redox capacity of the catalysts, resulting in different reaction mechanisms for NH3-SCO. However, in situ diffuse reflectance infrared Fourier transform spectra revealed that an excessive O2 activation capacity caused overoxidation of NH3 to NO and NO2. The NH3-SCO activity of the 2Co/Al2O3 catalyst with low redox capacity was successfully increased while controlling and optimizing the N2 selectivity by modulating the active centers via H2 pretreatment, which is a universal method used for enhancing the redox properties of catalysts. Thus, this method has great potential for application in the design of inexpensive and highly active catalysts.

Nitrate removal by a novel aerobic denitrifying Pelomonas puraquae WJ1 in oligotrophic condition: Performance and carbon source metabolism.

Reducing nitrate contamination in drinking water has become a critical issue in urban water resource management. Here a novel oligotrophic aerobic denitrifying bacterium, Pelomonas puraquae WJ1, was isolated and purified from artificial lake sediments. For the first time, excellent aerobic denitrification capabilities were demonstrated. At a carbon-to­nitrogen ratio of 5.0, strain WJ1 achieved 100.0 % nitrate removal and 84.92 % total nitrogen removal within 24 h, with no nitrite accumulation. PCR amplification and sequencing confirmed the presence of the denitrification genes napA, nirS, and nosZ in the strain. The nitrogen balance demonstrated that approximately 74.95 % of the initial nitrogen was eliminated as gaseous products under aerobic conditions. Furthermore, carbon balance analysis showed that most electron donors from strain WJ1 were directed towards oxygen, with limited availability for nitrate reduction. A combination of bio-ECO analysis and network modeling indicated that strain WJ1 has robust metabolic capabilities for diverse carbon sources and exhibits high adaptability to complex carbon environments. Overall, Pelomonas puraquae WJ1 removed approximately 45.89 % of the nitrates in raw water, demonstrating significant potential for practical applications in oligotrophic denitrification.

Comparative bibliometric analysis of artificial intelligence-assisted polyp diagnosis and AI-assisted digestive endoscopy: trends and growth in AI gastroenterology (2003-2023).

Introduction: Artificial intelligence is already widely utilized in gastroenterology. This study aims to comprehensively evaluate the research hotspots and development trends within the field of AI in gastroenterology by employing bibliometric techniques to scrutinize geographical distribution, authorship, affiliated institutions, keyword usage, references, and other pertinent data contained within relevant publications. Methods: This investigation compiled all pertinent publications related to artificial intelligence in the context of gastrointestinal polyps and digestive endoscopy from 2003 to 2023 within the Web of Science Core Collection database. Furthermore, the study harnessed the tools CiteSpace, VOSviewer, GraphPad Prism and Scimago Graphica for visual data analysis. The study retrieved a total of 2,394 documents in the field of AI in digestive endoscopy and 628 documents specifically related to AI in digestive tract polyps. Results: The United States and China are the primary contributors to research in both fields. Since 2019, studies on AI for digestive tract polyps have constituted approximately 25% of the total AI digestive endoscopy studies annually. Six of the top 10 most-cited studies in AI digestive endoscopy also rank among the top 10 most-cited studies in AI for gastrointestinal polyps. Additionally, the number of studies on AI-assisted polyp segmentation is growing the fastest, with significant increases in AI-assisted polyp diagnosis and real-time systems beginning after 2020. Discussion: The application of AI in gastroenterology has garnered increasing attention. As theoretical advancements in AI for gastroenterology have progressed, real-time diagnosis and detection of gastrointestinal diseases have become feasible in recent years, highlighting the promising potential of AI in this field.

Association between serum branched chain amino acids, mammalian target of rapamycin levels and the risk of gestational diabetes mellitus: a 1:1 matched case control study.

BACKGROUND: To investigate the association between serum branched chain amino acids (BCAAs), mammalian target of rapamycin (mTOR) levels and the risk of gestational diabetes mellitus (GDM) in pregnant women. METHODS: 1:1 matched case-control study was conducted including 66 GDM patients and 66 matched healthy pregnant women (± 3 years) in 2019, in China. Fasting bloods of pregnant women were collected in pregnancy at 24 ~ 28 weeks gestation. And the serum levels of valine (Val), leucine (Leu), isoleucine (Ile) and mTOR were determined. Conditional logistic regressions models were used to estimate the associations of BCAAs and mTOR concentrations with the risk of GDM. RESULTS: Concentrations of serum Val and mTOR in cases were significantly higher than that in controls (P < 0.05). After adjusted for the confounded factors, both the second tertile and the third tertile of mTOR increased the risk of GDM (OR = 11.771, 95%CI: 3.949-35.083; OR = 4.869 95%CI: 1.742-13.611, respectively) compared to the first tertile of mTOR. However, the second tertile of serum Val (OR = 0.377, 95%CI:0.149-0.954) and the second tertile of serum Leu (OR = 0.322, 95%CI: 0.129-0.811) decreased the risk of GDM compared to the first tertile of serum Val and Leu, respectively. The restricted cubic spline indicated a significant nonlinear association between the serum levels of mTOR and the risk of GDM (P values for non-linearity = 0.0058). CONCLUSION: We confirmed the association of higher mTOR with the increased risk of GDM in pregnant women. Pregnant women who were in the certain range level of Val and Leu were at lower risk of GDM. Our findings provided epidemiological evidence for the relation of serum BCAAs and mTOR with risk of GDM.

Causal effects of lipid-lowering drugs on inflammatory skin diseases: Evidence from drug target Mendelian randomisation.

Clinical research has revealed that inflammatory skin diseases are associated with dyslipidaemia. Modulating lipids is also a rising potential treatment option. However, there is heterogeneity in the existing evidence and a lack of large-scale clinical trials. Observational research is prone to bias, making it difficult to determine causality. This study aimed to evaluate the causal association between lipid-lowering drugs and inflammatory skin diseases. A drug target Mendelian randomisation (MR) analysis was conducted. Genetic targets of lipid-lowering drugs, including proprotein convertase subtilis kexin 9 (PCSK9) and 3-hydroxy-3-methylglutaryl-assisted enzyme A reductase (HMGCR) inhibitor, were screened. Common inflammatory skin diseases, including psoriasis, allergic urticaria, rosacea, atopic dermatitis, systemic sclerosis and seborrhoeic dermatitis, were considered as outcomes. Gene-predicted inhibition of PCSK9 was causally associated with a decreased risk of psoriasis (ORIVW [95%CI] = 0.600 [0.474-0.761], p = 2.48 × 10-5) and atopic dermatitis (ORIVW [95%CI] = 0.781 [0.633-0.964], p = 2.17 × 10-2). Gene-predicted inhibition of HMGCR decreased the risk of seborrhoeic dermatitis (ORIVW [95%CI] = 0.407 [0.168-0.984], p = 4.61 × 10-2) but increased the risk of allergic urticaria (ORIVW [95%CI] = 3.421 [1.374-8.520], p = 8.24 × 10-3) and rosacea (ORIVW [95%CI] = 3.132 [1.260-7.786], p = 1.40 × 10-2). Among all causal associations, only PCSK9 inhibition demonstrated a robust causal effect on psoriasis after a more rigorous Bonferroni test (p < 4.17 × 10-3, which is 0.05/12). Modulating lipids via PCSK9 inhibition may offer potential therapeutic targets for psoriasis and atopic dermatitis. Given the potential cutaneous side effects associated with HMGCR inhibitors, PCSK9 inhibitors could be considered viable alternatives in lipid-lowering medication.

RCDdb: A manually curated database and analysis platform for regulated cell death.

Regulated cell death is a pivotal regulatory mechanism governing the development and homeostasis of multicellular organisms. A comprehensive understanding of RCD's regulatory mechanisms is crucial for developing novel therapeutic strategies against diseases associated with cell death, such as cancer and neurodegenerative diseases. However, existing data repositories support limited types of cell death data and lack comprehensive annotation and analytical functionalities. Thus, establishing an extensive cell death database is an urgent imperative. To address this gap, we developed the Regulated Cell Death Database (RCDdb, chenyclab.com/RCDdb), the first comprehensively manually annotated database designed to support annotations and analytical capabilities across all RCD types. We compiled 3090 marker gene annotations associated with 15 RCD types from 2180 relevant articles. The RCDdb includes annotation data on these marker genes concerning diseases, drugs, pathways, proteins, and gene expressions. Furthermore, it provides 49 diverse visualization methods to present this information. More importantly, the RCDdb features three online analysis tools for identifying and analyzing RCD-related features within user-submitted data. Furthermore, the RCDdb offers a user-friendly interface for querying, browsing, analysis, and visualization of detailed information associated with each RCD category. This resource promises to significantly aid researchers in better understanding the mechanisms of cell death, thereby accelerating progress in research and therapeutic strategies aimed at combating RCD-related diseases.

Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy.

The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R2), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R2 was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R2 is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R2 was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R2 is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients.

pH and H2O2 dual-sensitive nanoparticles enable enhanced and safe glucose-responsive oral insulin delivery for diabetes mellitus treatment.

Background: Oral insulin delivery is considered a revolutionary alternative to daily subcutaneous injection. However, the oral bioavailability of insulin is very low due to the poor oral absorption into blood circulation. Methods: To promote penetration across the intestinal epithelium and achieve enhanced and safe glucose-responsive oral insulin delivery, pH and H2O2 dual-sensitive nanoparticles (NPs) were constructed. The NPs were loaded of glucose oxidase (GOx) and insulin by pH and H2O2 dual-sensitive amphiphilic polymer incorporated with phenylboronic ester-conjugated poly(2-hydroxyethyl methacrylate) and poly(carboxybetaine) (PCB). The dual-sensitive NPs were utilized for the treatment of type 1 diabetes mellitus (T1DM) after oral administration. Results: The dual-sensitive NPs could enhance the transport of insulin across the intestinal epithelium into blood facilitated by zwitterionic PCB. By virtue of the generated low pH and high H2O2 with GOx in hyperglycemic environment, the pH and H2O2 dual-sensitive NPs were disassembled to achieve rapid and sustained release of insulin. After oral administration of the dual-sensitive NPs in enteric capsules into T1DM mouse model, the oral bioavailability of insulin reached 20.24%, and the NPs achieved hypoglycemic effect for a few hours longer than subcutaneously injected insulin. Importantly, the pH and H2O2 dual-sensitive NPs could ameliorate the local decline of pH and rise of H2O2 to avoid the toxic side effect. Conclusion: Therefore, this work would provide a promising platform for the enhanced and safe treatment of diabetes mellitus.

A Versatile Point Cloud Compressor Using Universal Multiscale Conditional Coding - Part II: Attribute.

A universal multiscale conditional coding framework, Unicorn, is proposed to code the geometry and attribute of any given point cloud. Attribute compression is discussed in Part II of this paper, while geometry compression is given in Part I of this paper. We first construct the multiscale sparse tensors of each voxelized point cloud attribute frame. Since attribute components exhibit very different intrinsic characteristics from the geometry element, e.g., 8-bit RGB color versus 1-bit occupancy, we process the attribute residual between lower-scale reconstruction and current-scale data. Similarly, we leverage spatially lower-scale priors in the current frame and (previously processed) temporal reference frame to improve the probability estimation of attribute intensity through conditional residual prediction in lossless mode or enhance the attribute reconstruction through progressive residual refinement in lossy mode for better performance. The proposed Unicorn is a versatile, learning-based solution capable of compressing a great variety of static and dynamic point clouds in both lossy and lossless modes. Following the same evaluation criteria, Unicorn significantly outperforms standard-compliant approaches like MPEG G-PCC, V-PCC, and other learning-based solutions, yielding state-of-the-art compression efficiency with affordable encoding/decoding runtime.

Copper-Catalyzed Enantioselective [4π + 2σ] Cycloaddition of Bicyclobutanes with Nitrones.

The selective construction of bridged bicyclic scaffolds has garnered increasing attention because of their extensive use as saturated bioisosteres of arene in pharmaceutical industry. However, in sharp contrast to their racemic counterparts, assembling chiral bridged bicyclic structures in an enantioselective and regioselective manner remains challenging. Herein, we describe our protocol for constructing chiral 2-oxa-3-azabicyclo[3.1.1]heptanes (BCHeps) by enantioselective [4π + 2σ] cycloadditions of bicyclo[1.1.0]butanes (BCBs) and nitrones taking advantage of a chiral copper(II) complex as a Lewis acid catalyst. This method features mild conditions, good functional group tolerance, high yield (up to 99%), and excellent enantioselectivity (up to 99% ee). Density functional theory (DFT) calculation elucidates the origin of the reaction's enantioselectivity and the mechanism of BCB activation by Cu(II) complex.

Proteome and Phosphoproteome Profiling Reveal the Toxic Mechanism of Clostridium perfringens Epsilon Toxin in MDCK Cells.

Epsilon toxin (ETX), a potential agent of biological and toxic warfare, causes the death of many ruminants and threatens human health. It is crucial to understand the toxic mechanism of such a highly lethal and rapid course toxin. In this study, we detected the effects of ETX on the proteome and phosphoproteome of MDCK cells after 10 min and 30 min. A total of 44 differentially expressed proteins (DEPs) and 588 differentially phosphorylated proteins (DPPs) were screened in the 10 min group, while 73 DEPs and 489 DPPs were screened in the 30 min group. ETX-induced proteins and phosphorylated proteins were mainly located in the nucleus, cytoplasm, and mitochondria, and their enrichment pathways were related to transcription and translation, virus infection, and intercellular junction. Meanwhile, the protein-protein interaction network screened out several hub proteins, including SRSF1/2/6/7/11, SF3B1/2, NOP14/56, ANLN, GTPBP4, THOC2, and RRP1B. Almost all of these proteins were present in the spliceosome pathway, indicating that the spliceosome pathway is involved in ETX-induced cell death. Next, we used RNAi lentiviruses and inhibitors of several key proteins to verify whether these proteins play a critical role. The results confirmed that SRSF1, SF3B2, and THOC2 were the key proteins involved in the cytotoxic effect of ETX. In addition, we found that the common upstream kinase of these key proteins was SRPK1, and a reduction in the level of SRPK1 could also reduce ETX-induced cell death. This result was consistent with the phosphorylated proteomics analysis. In summary, our study demonstrated that ETX induces phosphorylation of SRSF1, SF3B2, THOC2, and SRPK1 proteins on the spliceosome pathway, which inhibits normal splicing of mRNA and leads to cell death.

SimpleTrackV2: Rethinking the Timing Characteristics for Multi-Object Tracking.

Multi-object tracking tasks aim to assign unique trajectory codes to targets in video frames. Most detection-based tracking methods use Kalman filtering algorithms for trajectory prediction, directly utilizing associated target features for trajectory updates. However, this approach often fails, with camera jitter and transient target loss in real-world scenarios. This paper rethinks state prediction and fusion based on target temporal features to address these issues and proposes the SimpleTrackV2 algorithm, building on the previously designed SimpleTrack. Firstly, to address the poor prediction performance of linear motion models in complex scenes, we designed a target state prediction algorithm called LSTM-MP, based on long short-term memory (LSTM). This algorithm encodes the target's historical motion information using LSTM and decodes it with a multilayer perceptron (MLP) to achieve target state prediction. Secondly, to mitigate the effect of occlusion on target state saliency, we designed a spatiotemporal attention-based target appearance feature fusion (TSA-FF) target state fusion algorithm based on the attention mechanism. TSA-FF calculates adaptive fusion coefficients to enhance target state fusion, thereby improving the accuracy of subsequent data association. To demonstrate the effectiveness of the proposed method, we compared SimpleTrackV2 with the baseline model SimpleTrack on the MOT17 dataset. We also conducted ablation experiments on TSA-FF and LSTM-MP for SimpleTrackV2, exploring the optimal number of fusion frames and the impact of different loss functions on model performance. The experimental results show that SimpleTrackV2 handles camera jitter and target occlusion better, achieving improvements of 1.6%, 3.2%, and 6.1% in MOTA, IDF1, and HOTA, respectively, compared to the SimpleTrack algorithm.

Identification of hsa-miR-193a-5p-SURF4 axis related to the gut microbiota-metabolites- cytokines in lung cancer based on Mendelian randomization study and bioinformatics analysis.

BACKGROUND: Lung cancer is a significant disease that affects people's physical and mental health. Currently, the treatment outcomes still do not meet clinical needs, and the causes of the disease are still unclear, therefore further exploration is needed. METHODS: We analyzed the exposure factors of lung cancer, including gut microbiota, serum metabolites, and cytokines, through Mendelian randomization studies and bioinformatics analysis. We identified common SNPs and performed gene annotation, leading to the discovery of the key gene SURF4, which may affect the onset of lung cancer. We validated the oncogenic function and mechanism of SURF4 through public data analysis using GO and KEGG, and constructed a ceRNA network, revealing the lung cancer oncogenic pathway involving lncRNA/pseudogene-microRNA-SURF4. RESULTS: We first conducted a Mendelian randomization analysis on 418 gut microbiota, 1400 serum metabolites, and 41 cytokines in relation to lung cancer. We found that 16 gut microbiota, 29 serum metabolites, and 2 cytokines were closely associated with lung cancer. Further comparison of all differential SNPs revealed that rs550057 on chromosome 9 was a common SNP among these three exposure factors, indicating its crucial role in lung cancer formation. Through gene functional annotation using R language, we found that the expression of 15 genes, including SURF4, was influenced by rs550057. By querying these 15 genes from public databases for their differential expression and prognosis in lung cancer, we found significant differences in SURF4, MED22, and RPL7A. Furthermore, by querying the expression and correlation coefficients of upstream microRNAs of these three genes through the starBase website, we found that hsa-miR-193a-5p-SURF4 had the most significant effect on lung cancer. Through GO and KEGG analysis of SURF4-related genes, we identified the molecular pathways associated metabolic synthesis and microbial infection related to the promotion of lung cancer by SURF4. This validated the results of the previous Mendelian randomization study. Furthermore, we constructed a ceRNA network for SURF4 and identified two upstream differentially expressed pseudogenes and nine lncRNAs, confirming the functionality of the pseudogene/lncRNA-microRNA-SUFR4 pathway. CONCLUSIONS: In summary, we have elucidated the regulatory role of the pseudogene/lncRNA-microRNA-SUFR4 pathway in the progression of lung cancer, combining the research hotspots of gut microbiota-serum metabolites-cytokines. We have also confirmed the pathway and mechanism through SURF4 and its related genes promoting lung cancer formation. This may provide effective therapeutic methods for lung cancer and serve as a potential prognostic marker.

ACE2 alleviates sepsis-induced cardiomyopathy through inhibiting M1 macrophage via NF-κB/STAT1 signals.

Angiotensin-converting enzyme 2 (ACE2), a crucial element of the renin-angiotensin system (RAS), metabolizes angiotensin II into Ang (1-7), which then combines with the Mas receptor (MasR) to fulfill its protective role in various diseases. Nevertheless, the involvement of ACE2 in sepsis-induced cardiomyopathy (SIC) is still unexplored. In this study, our results revealed that CLP surgery dramatically impaired cardiac function accompanied with disruption of the balance between ACE2-Ang (1-7) and ACE-Ang II axis in septic heart tissues. Moreover, ACE2 knockin markedly alleviated sepsis induced RAS disorder, cardiac dysfunction and improved survival rate in mice, while ACE2 knockout significantly exacerbates these outcomes. Adoptive transfer of bone marrow cells and in vitro experiments showed the positive role of myeloid ACE2 by mitigating oxidative stress, inflammatory response, macrophage polarization and cardiomyocyte apoptosis by blocking NF-κB and STAT1 signals. However, the beneficial impacts were nullified by MasR antagonist A779. Collectively, these findings showed that ACE2 alleviated SIC by inhibiting M1 macrophage via activating the Ang (1-7)-MasR axis, highlight that ACE2 might be a promising target for the management of sepsis and SIC patients.

Aß25-35-induced autophagy and apoptosis are prevented by the CRMP2-derived peptide ST2-104 (R9-CBD3) via a CaMKKß/AMPK/mTOR signaling hub.

We previously reported that the peptide ST2-104 (CBD3, for Ca2+ channel-binding domain 3), derived from the collapsin response mediator protein 2 (CRMP2)-a cytosolic phosphoprotein, protects neuroblastoma cells against ß-amyloid (Aß) peptide-mediated toxicity through engagement of a phosphorylated CRMP2/NMDAR pathway. Abnormal aggregation of Aß peptides (e.g., Aß25-35) leads to programmed cell death (apoptosis) as well autophagy-both of which contribute to Alzheimer's disease (AD) progression. Here, we asked if ST2-104 affects apoptosis and autophagy in SH-SY5Y neuroblastoma challenged with the toxic Aß25-35 peptide and subsequently mapped the downstream signaling pathways involved. ST2-104 protected SH-SY5Y cells from death following Aß25-35 peptide challenge by reducing apoptosis and autophagy as well as limiting excessive calcium entry. Cytotoxicity of SHY-SY5Y cells challenged with Aß25-35 peptide was blunted by ST2-104. The autophagy activator Rapamycin blunted the anti-apoptotic activity of ST2-104. ST2-104 reversed Aß25-35-induced apoptosis via inhibiting Ca2+/CaM-dependent protein kinase kinase ß (CaMKKß)-mediated autophagy, which was partly enhanced by STO-609 (an inhibitor of CaMKKß). ST2-104 attenuated neuronal apoptosis by inhibiting autophagy through a CaMKKß/AMPK/mTOR signaling hub. These findings identify a mechanism whereby, in the face of Aß25-35, the concerted actions of ST2-104 leads to a reduction in intracellular calcium overload and inhibition of the CaMKKß/AMPK/mTOR pathway resulting in attenuation of autophagy and cellular apoptosis. These findings define a mechanistic framework for how ST2-104 transduces "outside" (calcium channels) to "inside" signaling (CaMKKß/AMPK/mTOR) to confer neuroprotection in AD.

Efficacy and comfort following the implantation of extended depth of focus, multifocal, and monofocal intraocular lenses in cataract patients.

BACKGROUND: Extended depth of focus (EDOF) and multifocal (Multi) intraocular lenses (IOL) can provide a fixed distance of near vision, which may result in some discomfort for patients who prefer different near distances. The aim of this study was to compare the vision, comfortable near distance (CND) and visual comfort in patients who underwent implantation of EDOF, Multi, and monofocal (Mono) IOLs. METHODS: A total of 100 eyes were implanted with Tecnis ZXR00, ZMB00 or ZCB00 IOLs. Uncorrected distance, intermediate, and near visual acuity (UDVA, UIVA, and UNVA, respectively), corrected distance visual acuity (CDVA), the fluctuations of CND, the ability to see at comfortable or standard near distance and visual comfort were evaluated at 3-month postoperative. RESULTS: At 3 months postoperative, the EDOF and Multi groups showed non-inferiority compared to the Mono group in the UDVA (P > 0.05) and CDVA (P > 0.05) but superiority in the UNVA (P < 0.001). The UIVA was better in the EDOF group, with comparable results for the Multi and Mono groups. There was no difference in preoperative and postoperative CND in the three groups. The CND visual acuity (CNDVA) was lower than the UNVA in the three groups, especially in the EDOF and Multi groups (P < 0.05). The CND effectively improved patients' near visual comfort and visual clarity, except for one patient in the Multi group who complained of severe fatigue and was unable to tolerate the experience at month 3. CONCLUSION: The EDOF and Multi IOLs achieved excellent visual quality and superior UNVA compared to the Mono IOL, but the CNDVA was significantly inferior to the UNVA. Patients' near visual experience can be effectively improved at their CND.

Differences in cognitive impairment and its correlation with circulating cell-free mitochondrial DNA in medication-free depression and bipolar depression patients.

OBJECTIVE: This study aimed to investigate whether there are differences in cognitive impairment between medication-free patients with bipolar depression (BD) and major depressive disorder (MDD) and whether these differences are related to circulating cell-free mtDNA (ccf-mtDNA). METHODS: For this cross-sectional study, 76 outpatients with BD, 86 outpatients with MDD and 70 healthy controls (HCs) were enrolled. Sociodemographic and clinical data were collected. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Stroop Color-Word Test were used to assess cognitive function. Plasma ccf-mtDNA levels were measured via qPCR. RESULTS: BD and MDD patients had similar scores for immediate memory, language, attention, delayed memory, the RBANS total score, Stroop color, Stroop word, and Stroop total score, which were significantly lower than the HCs. The visuospatial/constructive scores of the BD patients were significantly lower than those of the HCs (p < 0.001) and MDD patients (p = 0.008), but there was no difference between the HCs and MDD patients. The ccf-mtDNA levels in the BD and MDD patient groups were significantly higher than those in the HC group, and those in the MDD group were higher than those in the BD group (p = 0.016). Multiple stepwise regression analysis showed that ccf-mtDNA was negatively correlated with language in patients with depression (t = -2.11, p = 0.039). CONCLUSION: There were differences in specific cognitive dimensions between patients with BD and MDD. Increased ccf-mtDNA levels were found in BD and MDD patients, suggesting ccf-mtDNA may be involved in the pathophysiology of MDD and BD.

Soil and stone terraces offset the negative impacts of sloping cultivation on soil microbial diversity and functioning by protecting soil carbon.

Cultivation of sloping land is a main cause for soil erosion. Conservation practices, such as soil and stone terraces, may reduce the impacts of erosion but their impacts on soil microbial diversity and functioning related to carbon (C) and nutrient metabolisms remain unclear. This study was conducted to evaluate the effects of slope gradients (5°, 8°, 15°, 25°) and conservation practices (cultivated, uncultivated, soil terrace, and stone terrace) on bacterial and fungal diversities, metagenomic and metabolomic functioning associated with basic soil properties. Our results showed that steep slopes at 25° significantly decreased soil pH, silt percentage, and bacterial and fungal abundances, but that soil and stone terraces increased soil organic C (SOC), silt and clay contents, and fungal abundance compared to sloping cultivated lands. In addition, soil and stone terraces increased both bacterial and fungal alpha diversities, and relative abundances of Crenarchaeota, Nitrospirota, and Latescibacterota, but reduced the proportions of Actinobacteriota and Patescibacteria, thus shifting microbial beta diversities, which were significantly associated with increased SOC and silt content. For metagenomics, soil and stone terraces greatly increased the relative abundance of functional genes related to Respiration, Virulence, disease and defense, Stress response, and nitrogen and potassium metabolisms, such as Denitrification and Potassium homeostasis. For soil metabolomics, a total of 22 soil metabolites was enriched by soil and stone terraces, such as Lipids and lipid-like molecules (Arachidonic acid, Gamma-Linolenic acid, and Pentadecanoic acid), and Organoheterocyclic compounds (Adenine, Laudanosine, Methylpyrazine, and Nicotinic acid). To sum up, soil and stone terraces could reduce some of the negative impacts of steep slope cultivation on soil microbial diversity as well as their metagenomic and metabolomic functioning related to C and nutrient metabolism useful for soil health improvement, potentially bolstering the impact of sustainable practices in erosion hotspots around the world.

Zinc and methyl jasmonate improve sugar beet tolerance to high boron stress by enhanced leaf photochemical performance.

Nutrient imbalances, such as high boron (B) stress, occur within, as well as across, agricultural systems worldwide and have become an important abiotic factor that reduces soil fertility and inhibits plant growth. Sugar beet is a B-loving crop and is better suited to be grown in high B environments, but the methods and mechanisms regarding the enhancement of high-B stress tolerance traits are not clear. The main objective of this research was to elucidate the effects of the alone and/or combined foliar spraying of zinc sulfate (ZnSO4) and methyl jasmonate (MeJA) on the growth parameters, tolerance, and photochemical performance of sugar beet under high-B stress. Results demonstrated that the photosynthetic performance was inhibited under high-B stress, with a reduction of 11.33% in the net photosynthetic rate (Pn) and an increase of 25.30% in the tolerance index. The application of ZnSO4, MeJA, and their combination enhanced sugar beet's adaptability to high-B stress, with an increase in Pn of 9.22%, 4.49%, and 2.85%, respectively, whereas the tolerance index was elevated by 15.33%, 8.21%, and 5.19%, respectively. All three ameliorative treatments resulted in increased photochemical efficiency (Fv/Fm) and the photosynthetic performance index (PIABS) of PSII. Additionally, they enhanced the light energy absorption (ABS/RC) and trapping capacity (DIO/RC), reduced the thermal energy dissipation (TRO/RC), and facilitated the QA to QB transfer in the electron transport chain (ETC) of PSII, which collectively improved the photochemical performance. Therefore, spraying both ZnSO4 and MeJA can better alleviate high-B stress and promote the growth of sugar beet, but the combined spraying effect of ZnSO4 and MeJA is lower than that of individual spraying. This study provides a reference basis for enhancing the ability of sugar beet and other plants to tolerate high-B stress and for sugar beet cultivation in high B areas.

Hierarchical bound states in heat transport.

Higher-order topological phases in non-Hermitian photonics revolutionize the understanding of wave propagation and modulation, which lead to hierarchical states in open systems. However, intrinsic insulating properties endorsed by the lattice symmetry of photonic crystals fundamentally confine the robust transport only at explicit system boundaries, letting alone the flexible reconfiguration in hierarchical states at arbitrary positions. Here, we report a dynamic topological platform for creating the reconfigurable hierarchical bound states in heat transport systems and observe the robust and nonlocalized higher-order states in both the real- and imaginary-valued bands. Our experiments showcase that the hierarchical features of zero-dimension corner and nontrivial edge modes occur at tailored positions within the system bulk states instead of the explicit system boundaries. Our findings uncover the mechanism of non-localized hierarchical non-trivial topological states and offer distinct paradigms for diffusive transport field management.