bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ligand‐Free Copper(0)‐Catalyzed C−S Ullmann‐Type Cross‐Coupling Reaction: S‐Arylation of 5,4‐Disubstituted 2,4‐Dihydro‐3H‐1,2,4‐triazole‐3‐thiones
Authors: Petrosyan Artyom V. , Ayvazyan Armen G. , Ghochikyan Tariel V. , Galstyan Armen S. 
Published: March 2024

AbstractWe investigated the S‐arylation of 5,4‐disubstituted 2,4‐dihydro‐3H‐1,2,4‐triazole‐3‐thiones under ligand‐free Cu(0) catalysis employing Ullmann‐type reaction conditions. We determined optimal reaction conditions and assessed the impact of substituents in the arylating agent on the reaction progress. Notably, the presence of an electron‐withdrawing group (EWG) in the aryl halide facilitated the reaction even without a catalyst. In particular, an EWG in the para position of the aromatic ring exerted a directing effect on the leaving group, regardless of the halogen present.
Simulation of fluid‐structure interaction using the boundary data immersion method with adaptive mesh refinement
Authors: Wang Yuan , Ge Wei 
Published: March 2024

SummaryThe fluid‐structure interaction is simulated using the boundary data immersion method. As the fluid‐structure interface is smeared in the smoothing region, deviations are incurred in fluid simulations. For compressible flow, high order difference schemes with more mesh cells for the stencils are usually employed to achieve high overall accuracy, but near interfaces it requires wider smoothing region of several mesh cells for computational stability and hence lowers its accuracy significantly. To address this issue, the proposed algorithm switches to lower order difference schemes near the interfaces and applies adaptive mesh refining there to compensate the accuracy loss. Implemented with Structured Adaptive Mesh Refinement Application Infrastructure (SAMRAI), the algorithm shows notable improvement in the overall accuracy and efficiency in cases such as channel flow and flow past a cylinder. The algorithm is used to simulate the shock wave past a fixed or free cylinder with Ma and Re , which reveals the relaxation process and the temporal evolution of the drag coefficient, it goes through a valley and maintains at relatively high value for the fixed cylinder, while that of the free cylinder tends to decrease in fluctuation which is found to be caused by the interaction between the forward moving cylinder and vortexes in the unsteady wake.
Influence of a magnetic field on double‐diffusive convection in an inclined porous layer
Authors: Ragoju Ravi 
Published: March 2024

AbstractThe present study investigates the impact of a magnetic field on double‐diffusive convection in an inclined porous layer, employing linear instability theory. The perturbed state is solved using the normal mode technique, and the stability eigenvalue problem is numerically analyzed for longitudinal and traveling rolls using the Runge‐Kutta method coupled with the shooting method. Various dimensionless physical parameters, including solutal and thermal Rayleigh numbers, inclination angle, Hartmann number, and Lewis number, are examined for their influence on system stability. The findings reveal that, for , the Hartmann number, solute Rayleigh number, and inclination angle act as stabilizing factors, with greater stability observed for traveling rolls compared to longitudinal rolls. In the case of , the critical Rayleigh number shows a monotonic relationship with the solute Rayleigh number and inclination angle, while its relationship with the Hartmann number is non‐monotonic for traveling rolls. Moreover, for , the Hartmann number stabilizes the system by raising the onset threshold value, favouring longitudinal modes. The solute Rayleigh number also contributes to system stability. The impact of the inclination angle on system stability is contingent upon its magnitude, with small angles favouring the stability of longitudinal rolls and larger angles leading to an initial transition from traveling to longitudinal rolls, indicating a complex non‐monotonic behavior.
Sodium butyrate activates the KATP channels to regulate the mechanism of Parkinson's disease microglia model inflammation
Authors: Xu Ye , Wen Laofu , Tang Yunyi , Zhao Zhenqiang , Xu Miaojing , Wang Tan , Chen Zhibin 
Published: March 2024

AbstractBackgroundParkinson's disease (PD) is a common neurodegenerative disorder. Microglia‐mediated neuroinflammation has emerged as an involving mechanism at the initiation and development of PD. Activation of adenosine triphosphate (ATP)‐sensitive potassium (KATP) channels can protect dopaminergic neurons from damage. Sodium butyrate (NaB) shows anti‐inflammatory and neuroprotective effects in some animal models of brain injury and regulates the KATP channels in islet β cells. In this study, we aimed to verify the anti‐inflammatory effect of NaB on PD and further explored potential molecular mechanisms.MethodsWe established an in vitro PD model in BV2 cells using 1‐methyl‐4‐phenylpyridinium (MPP+). The effects of MPP+ and NaB on BV2 cell viability were detected by cell counting kit‐8 assays. The morphology of BV2 cells with or without MPP+ treatment was imaged via an optical microscope. The expression of Iba‐1 was examined by the immunofluorescence staining. The intracellular ATP content was estimated through the colorimetric method, and Griess assay was conducted to measure the nitric oxide production. The expression levels of pro‐inflammatory cytokines and KATP channel subunits were evaluated by reverse transcription–quantitative polymerase chain reaction and western blot analysis.ResultsNaB (5 mM) activated the KATP channels through elevating Kir6.1 and Kir6.1 expression in MPP+‐challenged BV2 cells. Both NaB and pinacidil (a KATP opener) suppressed the MPP+‐induced activation of BV2 cells and reduced the production of nitrite and pro‐inflammatory cytokines in MPP+‐challenged BV2 cells.ConclusionNaB treatment alleviates the MPP+‐induced inflammatory responses in microglia via activation of KATP channels.
Obesity correlates with the immunosuppressive ILC2s‐MDSCs axis in advanced breast cancer
Authors: Liu Wei , Li Bingyu , Liu Dan , Zhao Bing , Sun Gang , Ding Jianbing 
Published: March 2024

AbstractAimWe investigated the relationship between the group 2 innate lymphoid cells (ILC2s)‐myeloid‐derived suppressor cells (MDSCs) axis and obesity‐related breast cancer.MethodsFifty‐eight patients with breast cancer who had first relapse and metastasis between January 2019 and August 2021 were enrolled. The proportions of ILC2s and MDSCs in blood and the levels of cytokines in serum were detected with flow cytometry. Correlation analysis among clinical characteristics (such as body mass index [BMI]), cytokines, ILC2s, and MDSCs was conducted.ResultsThere was a significant difference in the proportions of ILC2s and MDSCs between the high BMI group and the normal BMI group (p < .05). In the triple‐negative breast cancer (TNBC) patients, the proportions of ILC2s and MDSCs in the obese group were significantly higher than those in the nonobese group (p < .05). In all breast cancer patients, there was a positive correlation between BMI and the ILC2s‐MDSCs axis (p < .05). However, there was no correlation observed between the number of metastases, progression‐free survival, and the ILC2s‐MDSCs axis (p > .05). Additionally, ILC2s showed positive correlations with MDSCs, interleukin‐5 (IL‐5), IL‐10, IL‐17A, (PD‐L1), programmed cell death 2 ligand 2 (PD‐L2), and molecular typing (p < .05). Similarly, MDSCs exhibited positive correlations with IL‐5, IL‐8, IL‐9, IL‐17A, PD‐L1, and PD‐L2 (p < .05). In patients with TNBC, there was a positive correlation between BMI and IL‐5 (p < .05).ConclusionConclusively, obesity may enhance the immunosuppressive effect of the ILC2‐MDSC axis in advanced breast cancer. IL‐5 may play a vital role in the ILC2‐MDSC axis and obesity in TNBC.
Identification of biological markers in cancer disease using explainable artificial intelligence
Authors: Shahzad Muhammad , Lohana Ruhal , Aurangzeb Khursheed , Ali Isbah Imtiaz , Anwar Muhammad Shahid , Murtaza Mahnoor , Malick Rauf Ahmed Shams , Allayarov Piratdin 
Published: March 2024

AbstractThe research aims to improve the prediction of drug sensitivity on cancer cell lines using gene expression data and molecular fingerprints of drugs. The proposed study uses a deep learning model, BioMarkerX, trained on the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) datasets utilizing Particle Swarm Optimization technique to select specific genes as features. The model achieves high prediction accuracy with a Root Mean Square Error (RMSE) of 0.40 ± 0.02 and R2 of 0.83 ± 0.03 on the CCLE dataset, and an RMSE of 0.36 ± 0.05 and R2 of 0.83 ± 0.03 on the GDSC dataset. The approach also used an explainable artificial intelligence model to discover biological markers linked to cancer development. This can provide insights into targeted therapies for improving cancer treatment outcomes. Overall, the study presents an effective approach for identifying important biological markers relevant to cancer disease, aiding in the development of more efficient anticancer medications.
Evaluation of a discrimination training procedure for establishing praise as a reinforcer
Authors: Sainsbury Erin L. , Sidener Tina M. , Taylor‐Santa Catherine , Reeve Kenneth F. , Sidener David W. 
Published: March 2024

AbstractWe evaluated the effects of a discrimination training procedure for establishing praise as a reinforcer for three children with autism spectrum disorder. After establishing two praise words as discriminative stimuli and two nonsense words as S‐deltas, we evaluated whether the stimuli then functioned as reinforcers by presenting each stimulus as a consequence for a new response. The results demonstrated that previously neutral praise words functioned as reinforcers and nonsense words did not. As in previous studies on establishing reinforcers, the effects were transitory, and praise words did not continue to function as reinforcers after repeated exposure without discrimination training. Recommendations are provided for future research and maintaining reinforcement effects.
Automated segmentation of cell organelles in volume electron microscopy using deep learning
Authors: Nešić Nebojša , Heiligenstein Xavier , Zopf Lydia , Blüml Valentin , Keuenhof Katharina S. , Wagner Michael , Höög Johanna L. , Qi Heng , Li Zhiyang , Tsaramirsis Georgios , Peddie Christopher J. , Stojmenović Miloš , Walter Andreas 
Published: March 2024

AbstractRecent advances in computing power triggered the use of artificial intelligence in image analysis in life sciences. To train these algorithms, a large enough set of certified labeled data is required. The trained neural network is then capable of producing accurate instance segmentation results that will then need to be re‐assembled into the original dataset: the entire process requires substantial expertise and time to achieve quantifiable results. To speed‐up the process, from cell organelle detection to quantification across electron microscopy modalities, we propose a deep‐learning based approach for fast automatic outline segmentation (FAMOUS), that involves organelle detection combined with image morphology, and 3D meshing to automatically segment, visualize and quantify cell organelles within volume electron microscopy datasets. From start to finish, FAMOUS provides full segmentation results within a week on previously unseen datasets. FAMOUS was showcased on a HeLa cell dataset acquired using a focused ion beam scanning electron microscope, and on yeast cells acquired by transmission electron tomography.Research Highlights
Introducing a rapid, multimodal machine‐learning workflow for the automatic segmentation of 3D cell organelles.
Successfully applied to a variety of volume electron microscopy datasets and cell lines.
Outperforming manual segmentation methods in time and accuracy.
Enabling high‐throughput quantitative cell biology.
The continuously evolving phenotype of succinic semialdehyde dehydrogenase deficiency
Authors: Julia‐Palacios Natalia Alexandra , Kuseyri Hübschmann Oya , Olivella Mireia , Pons Roser , Horvath Gabriella , Lücke Thomas , Fung Cheuk‐Wing , Wong Suet‐Na , Cortès‐Saladelafont Elisenda , Rovira‐Remisa M. Mar , Yıldız Yılmaz , Mercimek‐Andrews Saadet , Assmann Birgit , Stevanović Galina , Manti Filippo , Brennenstuhl Heiko , Jung‐Klawitter Sabine , Jeltsch Kathrin , Sivri H. Serap , Garbade Sven F. , García‐Cazorla Àngels , Opladen Thomas 
Published: March 2024

AbstractThe objective of the study is to evaluate the evolving phenotype and genetic spectrum of patients with succinic semialdehyde dehydrogenase deficiency (SSADHD) in long‐term follow‐up. Longitudinal clinical and biochemical data of 22 pediatric and 9 adult individuals with SSADHD from the patient registry of the International Working Group on Neurotransmitter related Disorders (iNTD) were studied with in silico analyses, pathogenicity scores and molecular modeling of ALDH5A1 variants. Leading initial symptoms, with onset in infancy, were developmental delay and hypotonia. Year of birth and specific initial symptoms influenced the diagnostic delay. Clinical phenotype of 26 individuals (median 12 years, range 1.8–33.4 years) showed a diversifying course in follow‐up: 77% behavioral problems, 76% coordination problems, 73% speech disorders, 58% epileptic seizures and 40% movement disorders. After ataxia, dystonia (19%), chorea (11%) and hypokinesia (15%) were the most frequent movement disorders. Involvement of the dentate nucleus in brain imaging was observed together with movement disorders or coordination problems. Short attention span (78.6%) and distractibility (71.4%) were the most frequently behavior traits mentioned by parents while impulsiveness, problems communicating wishes or needs and compulsive behavior were addressed as strongly interfering with family life. Treatment was mainly aimed to control epileptic seizures and psychiatric symptoms. Four new pathogenic variants were identified. In silico scoring system, protein activity and pathogenicity score revealed a high correlation. A genotype/phenotype correlation was not observed, even in siblings. This study presents the diversifying characteristics of disease phenotype during the disease course, highlighting movement disorders, widens the knowledge on the genotypic spectrum of SSADHD and emphasizes a reliable application of in silico approaches.
Difference in radiofrequency ablation profile between during sinus rhythm and atrial fibrillation: Considerations in this era of high‐power short‐duration strategy
Authors: Hara Satoshi , Kusa Shigeki , Sato Yoshikazu , Ohya Hiroaki , Miwa Naoyuki , Hirano Hidenori , Ishizawa Taiki , Nakata Tadanori , Doi Junichi , Hachiya Hitoshi 
Published: March 2024

AbstractBackgroundThe concept of ablation index (AI) was introduced to evaluate radiofrequency (RF) ablation lesions. It is calculated from power, contact force (CF), and RF duration. However, other factors may also affect the quality of ablation lesions. To examine the difference in RF lesions made during sinus rhythm (SR) and atrial fibrillation (AF).MethodsSixty patients underwent index pulmonary vein isolation during SR (n = 30, SR group) or AF (n = 30, AF group). All ablations were performed with a power of 50 W, a targeted CF of 5–15 g, and AI of 400–450 using Thermocool Smarttouch SF. The CF, AI, RF duration, temperature rise (Δtemp), impedance drop (Δimp), and the CF stability of each ablation point quantified as the standard deviation of the CF (CF‐SD) were compared between the two groups.ResultsA total of 3579 ablation points were analyzed, which included 1618 and 1961 points in the SR and the AF groups, respectively. Power, average CF, RF duration per point, and the resultant AI (389 ± 59 vs. 388 ± 57) were similar for the two rhythms. However, differences were seen in the CF‐SD (3.5 ± 2.2 vs. 3.8 ± 2.1 g, p < .01), Δtemp (3.8 ± 1.3 vs. 4.0 ± 1.3°C, p < .005), and Δimp (10.3 ± 5.8 vs. 9.4 ± 5.4 Ω, p < .005).ConclusionsDespite similar AI, various RF parameters differed according to the underlying atrial rhythm. Ablation delivered during SR demonstrated less CF variability and temperature increase and greater impedance drop than during AF.
Efficacy of photodynamic therapy as an adjunct to scaling and root planing on clinical parameters and microbial composition in subgingival plaque of periodontitis patients: A split‐mouth randomized clinical trial
Authors: Nie Min , Huang Peien , Peng Peiyao , Shen Daonan , Zhao Lei , Jiang Duan , Shen Yuqin , Wei Lai , Bible Paul W. , Yang Jingmei , Wang Jun , Wu Yafei 
Published: March 2024

AbstractBackgroundThe aim of this study was to assess the efficacy of photodynamic therapy (PDT) as an adjunct to scaling and root planing (SRP) on clinical parameters and microbial composition in subgingival plaque of periodontitis patients.MethodsSeventeen patients were included in this split‐mouth randomized clinical trial. Sites with probing pocket depth (PPD) ≥5 mm in combination with bleeding on probing in different quadrants were randomized into the control group, the group with a single PDT application right after SRP, and the group with three repeated PDT applications 1 week after SRP. The subgingival plaque was collected for 16S rRNA gene sequencing at baseline, Week 2, and Week 8.ResultsSeventeen patients with 60 sites completed this 8‐week follow‐up, and 157 subgingival plaques were successfully analyzed by sequencing. Significant improvements were observed in two primary outcomes: PPD at Week 8 and subgingival microbial composition. Compared to the control group, the repeated‐PDT group showed a notable improvement in PPD, substantial alterations in the microbial profile, including a reduction in α‐diversity and anaerobic bacteria, and an increase in aerobic bacteria at Week 2. Secondary outcomes, such as clinical attachment level and sulcus bleeding index, also showed improvement at Week 8. Furthermore, both the single‐ and repeated‐PDT groups exhibited a decrease in periodontopathogens and an increase in beneficial bacteria compared with baseline.ConclusionPDT promotes changes in the microbial composition of periodontitis patients’ subgingival plaque in a direction favorable to periodontal health, and repeated PDT is a promising adjunctive therapy for periodontal treatment.
Agri‐mat and grass mulch effect on crop biomass yield in sandy loam and loam soils
Authors: Mgolozeli Sibongiseni , Nciizah Adornis D. , Wakindiki Isaiah I. C. , Onwona‐Agyeman Siaw 
Published: March 2024

AbstractThe role of agri‐mat mulch as a soil and water conservation technology for improved and sustainable plant production has not been explored. The aim of the study was to investigate the effects of agri‐mats and grass mulch on crop biomass yield of maize and spinach under sandy loam and loam soils. The following five mulch treatments were established in two sites (Durban with loam soil and Pretoria with sandy loam soil) during the 2017/18 and 2018/19 planting seasons: (a) full agri‐mat mulch cover (100%AG), (b) half agri‐mat mulch cover, (c) bare (control), (d) six tons of grass mulch per hectare (6t.GM), and (e) three tons of grass mulch per hectare. Crop growth parameters such as number of leaves, leaf length, plant height, and crop biomass yield were measured in both planting seasons. The results indicate that the crop biomass yield (both spinach and maize) was higher under 100%AG treatment compared to other mulching treatments followed by 6t.GM in the Pretoria site. For the Durban site, the highest crop growth parameters and biomass yield for both spinach and maize was recorded under the 100%AG treatment. The 100%AG treatment produced 33% more spinach biomass yield during the 2018 growing season in Durban compared with the 6t.GM treatment, with no percentage differences in the 2019 growing season. In Pretoria, there was a 20% (2018) and 32% (2019) difference in spinach biomass yield between the highest and second‐highest performing treatments. As hypothesized, agri‐mats can effectively improve crop biomass yields in semiarid and humid agro‐ecological zones with different soil types.
Technical advances in motion‐robust MR thermometry
Authors: Kim Kisoo , Narsinh Kazim , Ozhinsky Eugene 
Published: March 2024

AbstractProton resonance frequency shift (PRFS) MR thermometry is the most common method used in clinical thermal treatments because of its fast acquisition and high sensitivity to temperature. However, motion is the biggest obstacle in PRFS MR thermometry for monitoring thermal treatment in moving organs. This challenge arises because of the introduction of phase errors into the PRFS calculation through multiple methods, such as image misregistration, susceptibility changes in the magnetic field, and intraframe motion during MRI acquisition. Various approaches for motion correction have been developed for real‐time, motion‐robust, and volumetric MR thermometry. However, current technologies have inherent trade‐offs among volume coverage, processing time, and temperature accuracy. These tradeoffs should be considered and chosen according to the thermal treatment application. In hyperthermia treatment, precise temperature measurements are of increased importance rather than the requirement for exceedingly high temporal resolution. In contrast, ablation procedures require robust temporal resolution to accurately capture a rapid temperature rise. This paper presents a comprehensive review of current cutting‐edge MRI techniques for motion‐robust MR thermometry, and recommends which techniques are better suited for each thermal treatment. We expect that this study will help discern the selection of motion‐robust MR thermometry strategies and inspire the development of motion‐robust volumetric MR thermometry for practical use in clinics.
Pre‐excitation gradients for eddy current nulled convex optimized diffusion encoding (Pre‐ENCODE)
Authors: Middione Matthew J. , Loecher Michael , Cao Xiaozhi , Setsompop Kawin , Ennis Daniel B. 
Published: March 2024

AbstractPurposeTo evaluate the use of pre‐excitation gradients for eddy current–nulled convex optimized diffusion encoding (Pre‐ENCODE) to mitigate eddy current–induced image distortions in diffusion‐weighted MRI (DWI).MethodsDWI sequences using monopolar (MONO), ENCODE, and Pre‐ENCODE were evaluated in terms of the minimum achievable echo time (TE) and eddy current‐induced image distortions using simulations, phantom experiments, and in vivo DWI in volunteers ().ResultsPre‐ENCODE provided a shorter TE than MONO (71.0 17.7ms vs. 77.6 22.9ms) and ENCODE (71.0 17.7ms vs. 86.2 14.2ms) in 100 of the simulated cases for a commercial 3T MRI system with b‐values ranging from 500 to 3000 s/mm and in‐plane spatial resolutions ranging from 1.0 to 3.0mm. Image distortion was estimated by intravoxel signal variance between diffusion encoding directions near the phantom edges and was significantly lower with Pre‐ENCODE than with MONO (10.1 vs. 22.7, ) and comparable to ENCODE (10.1 vs. 10.4, ). In vivo measurements of apparent diffusion coefficients were similar in global brain pixels (0.37 [0.28,1.45] mm/s vs. 0.38 [0.28,1.45]mm/s, ) and increased in edge brain pixels (0.80 [0.17,1.49] mm/s vs. 0.70 [0.18,1.48]mm/s, ) for MONO compared to Pre‐ENCODE.ConclusionPre‐ENCODE mitigated eddy current–induced image distortions for diffusion imaging with a shorter TE than MONO and ENCODE.