Search

Background/Objectives: Radial artery tracking (RAT) in the short-axis view is a pivotal step for ultrasound-guided radial artery catheterization (RAC), which is widely employed in various clinical settings. To eliminate disparities and lay the foundations for automated procedures, a pilot study was conducted to explore the feasibility of U-Net and its variants in automatic RAT. Methods: Approved by the institutional ethics committee, patients as potential RAC candidates were enrolled, and the radial arteries were continuously scanned by B-mode ultrasonography. All acquired videos were processed into standardized images, and randomly divided into training, validation, and test sets in an 8:1:1 ratio. Deep learning models, including U-Net and its variants, such as Attention U-Net, UNet++, Res-UNet, TransUNet, and UNeXt, were utilized for automatic RAT. The performance of the deep learning architectures was assessed using loss functions, dice similarity coefficient (DSC), and Jaccard similarity coefficient (JSC). Performance differences were analyzed using the Kruskal–Wallis test. Results: The independent datasets comprised 7233 images extracted from 178 videos of 135 patients (53.3% women; mean age: 41.6 years). Consistent convergence of loss functions between the training and validation sets was achieved for all models except Attention U-Net. Res-UNet emerged as the optimal architecture in terms of DSC and JSC (93.14% and 87.93%), indicating a significant improvement compared to U-Net (91.79% vs. 86.19%, p < 0.05) and Attention U-Net (91.20% vs. 85.02%, p < 0.05). Conclusions: This pilot study validates the feasibility of U-Net and its variants in automatic RAT, highlighting the predominant performance of Res-UNet among the evaluated architectures.

Bovine viral diarrhea virus (BVDV) is an RNA virus associated with severe economic losses in animal production. Effective vaccination and viral surveillance are urgent for the prevention and control of BVDV infection. However, the application of traditional modified live vaccines and inactivated vaccines is faced with tremendous challenges. In the present study, we describe the preclinical efficacy of two BVDV mRNA vaccines tested in mice and guinea pigs, followed by a field trial in goats, where they were compared to a commercial vaccine (formaldehyde inactivated). The two mRNAs were engineered to express the envelope protein E2 of BVDV-1, the most prevalent subtype across the world, through a 5′ cap-dependent or independent fashion. Better titers of neutralizing antibodies against BVDV-1 were achieved using the capped RNA in the sera of mice and guinea pigs, with maximum values reaching 9.4 and 13.7 (by −log2), respectively, on the 35th day post-vaccination. At the same time point, the antibody levels in goats were 9.1 and 10.2 for the capped and capless RNAs, respectively, and there were no significant differences compared to the commercial vaccine. The animals remained healthy throughout the experiment, as reflected by their normal leukogram profiles. Collectively, our findings demonstrate that mRNA vaccines have good safety and immunogenicity, and we laid a strong foundation for the further exploitation of efficient and safe BVDV vaccines.

Segmenting the left ventricle from the transgastric short-axis views (TSVs) on transesophageal echocardiography (TEE) is the cornerstone for cardiovascular assessment during perioperative management. Even for seasoned professionals, the procedure remains time-consuming and experience-dependent. The current study aims to evaluate the feasibility of deep learning for automatic segmentation by assessing the validity of different U-Net algorithms. A large dataset containing 1388 TSV acquisitions was retrospectively collected from 451 patients (32% women, average age 53.42 years) who underwent perioperative TEE between July 2015 and October 2023. With image preprocessing and data augmentation, 3336 images were included in the training set, 138 images in the validation set, and 138 images in the test set. Four deep neural networks (U-Net, Attention U-Net, UNet++, and UNeXt) were employed for left ventricle segmentation and compared in terms of the Jaccard similarity coefficient (JSC) and Dice similarity coefficient (DSC) on the test set, as well as the number of network parameters, training time, and inference time. The Attention U-Net and U-Net++ models performed better in terms of JSC (the highest average JSC: 86.02%) and DSC (the highest average DSC: 92.00%), the UNeXt model had the smallest network parameters (1.47 million), and the U-Net model had the least training time (6428.65 s) and inference time for a single image (101.75 ms). The Attention U-Net model outperformed the other three models in challenging cases, including the impaired boundary of left ventricle and the artifact of the papillary muscle. This pioneering exploration demonstrated the feasibility of deep learning for the segmentation of the left ventricle from TSV on TEE, which will facilitate an accelerated and objective alternative of cardiovascular assessment for perioperative management.

Sleep deprivation (SD) triggers mitochondrial dysfunction and neural inflammation, leading to cognitive impairment and mental issues. However, the mechanism involving mitochondrial dysfunction and neural inflammation still remains unclear. Here, we report that SD rats exhibited multiple behavioral disorders, brain oxidative stress, and robust brain mitochondrial DNA (mtDNA) oxidation. In particular, SD activated microglia and microglial mtDNA efflux to the cytosol and provoked brain pro-inflammatory cytokines. We observed that the mtDNA efflux and pro-inflammatory cytokines significantly reduced with the suppression of the mtDNA oxidation. With the treatment of a novel mitochondrial nutrient, hydroxytyrosol butyrate (HTHB), the SD-induced behavioral disorders were significantly ameliorated while mtDNA oxidation, mtDNA release, and NF-κB activation were remarkably alleviated in both the rat brain and the N9 microglial cell line. Together, these results indicate that microglial mtDNA oxidation and the resultant release induced by SD mediate neural inflammation and HTHB prevents mtDNA oxidation and efflux, providing a potential treatment for SD-induced mental issues.

The facet joint injection is the most common procedure used to release lower back pain. In this paper, we proposed a deep learning method for detecting and segmenting facet joints in ultrasound images based on convolutional neural networks (CNNs) and enhanced data annotation. In the enhanced data annotation, a facet joint was considered as the first target and the ventral complex as the second target to improve the capability of CNNs in recognizing the facet joint. A total of 300 cases of patients undergoing pain treatment were included. The ultrasound images were captured and labeled by two professional anesthesiologists, and then augmented to train a deep learning model based on the Mask Region-based CNN (Mask R-CNN). The performance of the deep learning model was evaluated using the average precision (AP) on the testing sets. The data augmentation and data annotation methods were found to improve the AP. The AP50 for facet joint detection and segmentation was 90.4% and 85.0%, respectively, demonstrating the satisfying performance of the deep learning model. We presented a deep learning method for facet joint detection and segmentation in ultrasound images based on enhanced data annotation and the Mask R-CNN. The feasibility and potential of deep learning techniques in facet joint ultrasound image analysis have been demonstrated.

Shift work may adversely affect individuals’ health, thus, the current study aimed to investigate the association between shift work and health outcomes in the general population. A total of 41,061 participants were included in this online cross-sectional survey, among which 9612 (23.4%) individuals engaged in shift work and 31,449 (76.6%) individuals engaged in non-shift work. Multiple logistic regression analyses were conducted to explore the association between shift work and health outcomes (psychiatric disorders, mental health symptoms, and physical disorders). In addition, associations between the duration (≤1 year, 1–3 years, 3–5 years, 5–10 years, ≥10 years) and frequency of shift work (p < 0.001), mental health symptoms (OR = 1.76, 95% CI = 1.68–1.85, p < 0.001), and physical disorders (OR = 1.48, 95% CI = 1.39–1.57, p < 0.001). In addition, inverted U-shaped associations were observed between the duration of shift work and health outcomes. These results indicated that shift work was closely related to potential links with poor health outcomes. The findings highlighted the importance of paying attention to the health conditions of shift workers and the necessity of implementing comprehensive protective measures for shift workers to reduce the impact of shift work.

The subtropical region of China possesses abundant broad-leaf tree species resources; however, the anatomical properties and microstructure of the wood are still unclear, which restricts the processing and utilization of wood. In this study, 14 broad-leaf trees and four coniferous trees were selected. Wood anatomical indices and wood microanatomy were used to evaluate the wood properties using a comprehensive index method. The results have shown that Dalbergia assamica exhibited the highest wood basic density among the 14 broad-leaved tree species, accompanied by a significant fiber proportion and vessel lumen diameter but a small vessel proportion and a high number of wood rays. Conversely, Parakmeria lotungensis and Michelia chapensis had relatively low wood basic densities, rendering them less suitable as valuable broad-leaved wood sources. Altingia chinensis, Castanopsis kawakamii, and the remaining 11 tree species exhibited medium-level wood basic densities. The 14 broad-leaved tree species had medium-length fibers. Phoebe bournei, Dalbergia assamica, and Castanopsis kawakamii demonstrated relatively high fiber proportion. Altingia chinensis, Dalbergia assamica, and Castanopsis kawakamii exhibited a large number of wood rays, making their wood more susceptible to cracking, whereas other broad-leaved tree species possessed fewer wood rays. The findings have provided a scientific basis for the exploration of precious broad-leaved tree resources and wood use.

Background: With the development of an aging sociality, aging-related diseases, such as Alzheimer’s disease, cardiovascular disease, and diabetes, are dramatically increasing. To find small molecules from natural products that can prevent the aging of human beings and the occurrence of these diseases, we used the lifespan assay of yeast as a bioassay system to screen an antiaging substance. Isoquercitrin (IQ), an antiaging substance, was isolated from Apocynum venetum L., an herbal tea commonly consumed in Xinjiang, China. Aim of the Study: In the present study, we utilized molecular-biology technology to clarify the mechanism of action of IQ. Methods: The replicative lifespans of K6001 yeasts and the chronological lifespans of YOM36 yeasts were used to screen and confirm the antiaging effect of IQ. Furthermore, the reactive oxygen species (ROS) and malondialdehyde (MDA) assay, the survival assay of yeast under stresses, real-time polymerase chain reaction (RT-PCR) and Western blotting analyses, the replicative-lifespan assay of mutants, such as Δsod1, Δsod2, Δgpx, Δcat, Δskn7, Δuth1, Δatg32, Δatg2, and Δrim15 of K6001, autophagy flux analysis, and a lifespan assay of K6001 yeast after giving a mitophagy inhibitor and activator were performed. Results: IQ extended the replicative lifespans of the K6001 yeasts and the chronological lifespans of the YOM36 yeasts. Furthermore, the reactive nitrogen species (RNS) showed no change during the growth phase but significantly decreased in the stationary phase after treatment with IQ. The survival rates of the yeasts under oxidative- and thermal-stress conditions improved upon IQ treatment, and thermal stress was alleviated by the increasing superoxide dismutase (Sod) activity. Additionally, IQ decreased the ROS and MDA of the yeast while increasing the activity of antioxidant enzymes. However, it could not prolong the replicative lifespans of Δsod1, Δsod2, Δgpx, Δcat, Δskn7, and Δuth1 of K6001. IQ significantly increased autophagy and mitophagy induction, the presence of free green fluorescent protein (GFP) in the cytoplasm, and ubiquitination in the mitochondria of the YOM38 yeasts at the protein level. IQ did not prolong the replicative lifespans of Δatg2 and Δatg32 of K6001. Moreover, IQ treatment led to a decrease in Sch9 at the protein level and an increase in the nuclear translocation of Rim15 and Msn2. Conclusions: These results indicated that the Sch9/Rim15/Msn signaling pathway, as well as antioxidative stress, anti-thermal stress, and autophagy, were involved in the antiaging effects of IQ in the yeasts.

Civic-moral education is a topic that has been widely discussed globally. In China, civic-moral education has a long history and presents different characteristics and methods from other countries due to political, economic, and cultural factors. To summarize the current status of research on civic-moral education in China, we identified 715 papers in 30 years (1992–2022) under related topics and selected a total of 72 papers for further analysis. To show the study trend more clearly, we divided the result section into three parts: the historical and cultural resources of education, the current educational approaches, and the existing challenges in civic-moral education. China is rich in historical resources for civic-moral education, which had an impact across generations. Currently, Chinese educators employ many approaches to improve civic-moral education: building a civic-moral curriculum system, transforming the social climate, and making the most use of the campus. The emphasis on intelligence over morality and the emphasis on knowledge over action, however, may undermine the effectiveness of civic-moral education. To conclude, China attaches great importance to civic-moral education and has come up with many approaches inspired by ancient cultural resources.

Objective: Molecular hydrogen (H2) exhibits antioxidant, anti-inflammatory and anti-apoptotic effects, and has shown benefits in glucose and lipid metabolism in certain animal metabolic disorder models. However, the potential benefits of H2 treatment in individuals with impaired fasting glucose (IFG) has seldom been studied. This randomized controlled study (RCT) aims to investigate the effects of hydrogen-rich water (HRW) on IFG subjects and explore the underlying mechanism involved. Methods: Seventy-three patients with IFG were enrolled in a randomized, double-blind, placebo-controlled clinical study. These patients were assigned to receive either 1000 mL per day of HRW or placebo pure water (no H2 infusion) for a duration of eight weeks. Metabolic parameters and fecal gut microbiota were assessed at baseline (week 0) and at week 8. A combined analysis of metabolomics and intestinal microbiota was conducted to investigate the correlation between the effect of H2 on the metabolisms and the diversity of intestinal flora in the IGF patients. Results: Both pure water and HRW demonstrated a significant reduction in fasting blood glucose in IFG patients, with a significant difference between pure water and HRW after eight weeks. Among IFG patients with abnormal pre-experimental fatty liver, 62.5% (10/16) in the HRW group and 31.6% (6/19) in the pure water group achieved remission. Furthermore, 16S RNA analysis revealed HRW-modified gut microbiota dysbiosis in the fecal samples of IGF patients. Through Pearson correlation analysis, the differential gut microbiota obtained by 16S analysis was found to be highly correlated with nine metabolites. Conclusion: H2 slightly improved metabolic abnormalities and gut microbiota dysbiosis, providing a novel target and theoretical basis for the prevention and treatment of blood glucose regulation in patients with IFG.

In order to mitigate the concentration of NH3 and greenhouse gases (GHGs: CO2, N2O, CH4) in livestock houses, two experiments, one determining the ideal manure removal frequency by cleaning the feces from a livestock house once, twice, three, and four times a day, and one in which microbial deodorant and VenaZn deodorant were sprayed, were conducted in a rabbit breeding house. The NH3, CO2, N2O, and CH4 concentrations were monitored continuously with an Innova 1512 photoacoustic gas monitor during the experiments. The results were as follows: the manure removal frequency had a significant impact on the average concentrations of NH3, CO2, and CH4 in the rabbit house. Cleaning the feces in the rabbit breeding house two to three times a day significantly reduced the NH3 concentration, and, on the contrary, cleaning the feces four times a day increased the NH3 concentration in rabbit house; increasing the manure removal frequency significantly reduced the concentrations of CO2 and CH4 in the rabbit house. Considering the average concentrations of NH3, CO2, N2O, and CH4 in the rabbit house and economic cost, it was better to remove feces twice a day. The average NH3 and CO2 concentration declined significantly within 3 days in the summer and winter; the N2O concentration declined within 3 days in the summer but did not decline in the winter; and there was no effect on the CH4 concentration in the summer and in the winter after spraying the rabbit house with microbial deodorant. Therefore, it was better to spray microbial deodorant twice a week on Monday and Thursday to reduce the NH3, CO2, and N2O concentrations in rabbit houses. The NH3, CO2, N2O, and CH4 concentrations first showed a decreasing trend and then an increasing trend over 5 days in the summer and 7 days in the winter after VenaZn deodorant was sprayed in the rabbit house, and the NH3, CO2, N2O, and CH4 concentrations on day 3 and day 4 were significantly lower than they were on the other days.

The present study assessed the willingness of the general population to receive COVID-19 vaccines and identified factors that influence vaccine hesitancy and resistance. A national online survey was conducted from 29 January 2021 to 26 April 2021 in China. Multinomial logistic regression analyses were conducted to identify factors that influence vaccine hesitancy and resistance. Of the 34,041 participants surveyed, 18,810 (55.3%) were willing to get vaccinated, 13,736 (40.3%) were hesitant, and 1495 (4.4%) were resistant. Rates of vaccine acceptance increased over time, with geographical discrepancies in vaccine hesitancy and resistance between provinces in China. Vaccine safety was the greatest concern expressed by most participants (24,461 [71.9%]), and the major reason for participants’ refusing vaccination (974 [65.2%]). Government agencies (23,131 [68.0%]) and social media (20,967 [61.6%]) were the main sources of COVID-19 vaccine information. Compared with vaccination acceptance, female, young and middle-aged, high income, and perceived low-risk of infection were associated with vaccine hesitancy. Histories of allergic reactions to other vaccines and depression symptoms were related to vaccine resistance. Common factors that influenced vaccine hesitancy and resistance were residing in cities and perceiving less protection with vaccines than with other protective measures. The results indicate that the rate of vaccine resistance is relatively low, but vaccine hesitancy is common. Individuals who are female, young and middle-aged, with a high income, and residing in cities are more likely to be hesitant for vaccination and should be the target populations for vaccination campaigns. Specific vaccine messaging from the government and social media could alleviate public concerns about vaccine safety and efficacy.

Various factors affecting the construction progress are regarded as bottlenecks giving rise to the project duration overrun. The contractor should combine the project schedule with the plan in order to reduce the uncertainty of the project activities. The present research describes the method derived from the theory of constraints (TOC) attempts to enhance the relationship among activities, to revise and further reduce the uncertainty of construction activities to improve the reliability of project progress. The elements of drum, buffer and rope (DBR) in TOC are added to PERT network schedule; through the identification of schedule in the bottleneck process, the implementation plan of the bottleneck is obtained. By measuring buffer time and calculating network schedule buffer time as well as feeding time, the relationship among activities and uncertainty of duration are also improved. To illustrate the impact of DBR applications on improving project schedule reliability, a case of hydropower station as an example is illustrated to show enhanced reliability of scheduling. As compared to program evaluation and review technique network (PERT) simulation, the simulation results showed that the uncertainty of construction progress could be reduced if the DBR are well cooperated mutually.

Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop accurate machine learning models for ACP prediction. In this study, features were extracted from the three-dimensional (3D) structure of peptides to develop the model, compared to most of the previous computational models, which are based on sequence information. In order to develop ACPs with more potency, more selectivity and less toxicity, the model for predicting ACPs, hemolytic peptides and toxic peptides were established by peptides 3D structure separately. Multiple datasets were collected according to whether the peptide sequence was chemically modified. After feature extraction and screening, diverse algorithms were used to build the model. Twelve models with excellent performance (Acc > 90%) in the ACPs mixed datasets were used to form a hybrid model to predict the candidate ACPs, and then the optimal model of hemolytic peptides (Acc = 73.68%) and toxic peptides (Acc = 85.5%) was used for safety prediction. Novel ACPs were found by using those models, and five peptides were randomly selected to determine their anticancer activity and toxic side effects in vitro experiments.

Tight junctions form a barrier to control passive transport of ions and small molecules across epithelia and endothelia. In addition to forming a barrier, some of claudins control transport properties of tight junctions by forming charge- and size-selective ion channels. It has been suggested claudin monomers can form or incorporate into tight junction strands to form channels. Resolving the crystallographic structure of several claudins in recent years has provided an opportunity to examine structural basis of claudins in tight junctions. Computational and theoretical modeling relying on atomic description of the pore have contributed significantly to our understanding of claudin pores and paracellular transport. In this paper, we review recent computational and mathematical modeling of claudin barrier function. We focus on dynamic modeling of global epithelial barrier function as a function of claudin pores and molecular dynamics studies of claudins leading to a functional model of claudin channels.

Cerebral cavernous malformation (CCM) is a disease characterized by mulberry shaped clusters of dilated microvessels, primarily in the central nervous system. Such lesions can cause seizures, headaches, and stroke from brain bleeding. Loss-of-function germline and somatic mutations of a group of genes, called CCM genes, have been attributed to disease pathogenesis. In this review, we discuss the impact of CCM gene encoded proteins on cellular signaling, barrier function of endothelium and epithelium, and their contribution to CCM and potentially other diseases.

K-A-S-H (K2O-Al2O3-SiO2-H2O) gel is a key phase that forms in most alkali-activated binders (eco-friendly binders which utilize a substantial amount of industrial by-product). An in-depth understanding of the microstructure and performance of this nano-sized key phase facilitates better application to alkali-activated binders. However, such studies remain little and undetailed. Therefore, our research aims to provide insights into the microstructure of K-A-S-H particles synthesized with accurate stoichiometric control by the hydrothermal method through thermogravimetric analysis (TG), Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and BET surface area. The results show that for materials prepared at the curing temperature lower than 80 °C, the K-A-S-H products were completely amorphous. With increased curing temperature and time, the K-A-S-H products were transformed from the amorphous phase to the crystalline zeolite phase structure, with a reduction in the specific surface area. The TG results indicate that the crystalline phase contains more non-evaporated water or zeolite water for structural rearrangement. The degree of tetrahedral polymerization slightly decreased with an increase of the K2O/SiO2 ratio as the amount of non-bridged oxygen atoms increased, whereas it gradually increased with an increase of curing temperature and time, as suggested by the FTIR and NMR results. Various K2O/SiO2 ratios resulted in the formation of zeolite K-H and K-G zeolite, both of which exhibited highly polymerized three-dimensional network structures. However, there was no significant effect of the SiO2/Al2O3 ratio on the structure of K-A-S-H products. Overall, these results provide insight into understanding the chemical stability of K-A-S-H.

Plants employ an intricate and dynamic defense system that includes physiological, biochemical, and molecular mechanisms to counteract the effects of herbivorous attacks. In addition to their tolerance to phytotoxins, beet armyworm has quickly developed resistance to deltamethrin; a widely used pyrethroid insecticide in cotton fields. The lethal concentration (LC50) required to kill 50% of the population of deltamethrin to gossypol-fed Spodoptera exigua larvae was 2.34-fold higher than the control group, suggesting a reduced sensitivity as a consequence of the gossypol diet. Piperonyl butoxide (PBO) treatment was found to synergize with deltamethrin in gossypol-fed S. exigua larvae. To counteract these defensive plant secondary metabolites, beet armyworm elevates their production of detoxification enzymes, including cytochrome P450 monooxygenases (P450s). Gossypol-fed beet armyworm larvae showed higher 7-ethoxycoumarin-O-deethylase (ECOD) activities and exhibited enhanced tolerance to deltamethrin after 48 and 72 h when compared to the control. Moreover, gossypol pretreated S. exigua larvae showed faster weight gain than the control group after transferring to a deltamethrin-supplemented diet. Meanwhile, gossypol-induced P450s exhibited high divergence in the expression level of two P450 genes: CYP6AB14 and CYP9A98 in the midgut and fat bodies contributed to beet armyworm tolerance to deltamethrin. Knocking down of CYP6AB14 and CYP9A98, via double-stranded RNAs (dsRNA) in a controlled diet, rendered the larvae more sensitive to the insecticide. These data demonstrate that generalist insects can exploit secondary metabolites from host plants to enhance their defense systems against other toxic chemicals. Impairing this defense pathway by RNA interference (RNAi) holds a potential to eliminate the pest’s tolerance to insecticides and, therefore, reduce the required dosages of agrochemicals in pest control.

The preparation of thioesters through the lipase-catalysed transesterification reaction of thiols with vinyl carboxyl esters is described. The reactions were carried out by Lipase TL IM from Thermomyces lanuginosus as a catalyst and performed under a continuous flow microreactor. We first found that lipase TL IM can be used in the reaction of thioester synthesis with high efficiency. Various reaction parameters were investigated including substrate molar ratio, reaction time, and temperature. Maximum conversion (96%) was obtained under the optimal condition of a substrate molar ratio of 1:2 (4-methylbenzyl mercaptan:vinyl esters) at 50 °C for about 30 min. Compared with other methods, the salient features of this work include mild reaction conditions (50 °C), short reaction times (30 min), high yields, and environment-friendliness.

We herein reported the syntheses, crystal structures, and magnetic properties of a two-dimensional coordination polymer {[CoII(TPT)2/3(H2O)4][CH3COO]2·(H2O)4}n (1) and a chain compound {[CoII(TPT)2(CHOO)2(H2O)2]}n (2) based on the 2,4,6-Tris(4-pyridyl)-1,3,5-triazine (TPT) ligand. Structure analyses showed that complex 1 had a cationic hexagonal framework structure, while 2 was a neutral zig-zag chain structure with different distorted octahedral coordination environments. Magnetic measurements revealed that both complexes exhibit large easy-plane magnetic anisotropy with the zero-field splitting parameter D = 47.7 and 62.1 cm−1 for 1 and 2, respectively. This magnetic anisotropy leads to the field-induced slow magnetic relaxation behaviour. However, their magnetic dynamics are quite different; while complex 1 experienced a dominating thermally activated Orbach relaxation at the whole measured temperature region, 2 exhibited multiple relaxation pathways involving direct, Raman, and quantum tunneling (QTM) processes at low temperatures and Orbach relaxation at high temperatures. The present complexes enlarge the family of framework-based single-ion magnets (SIMs) and highlight the significance of the structural dimensionality to the final magnetic properties.