Moderation Effects of Streetscape Perceptions on the Associations Between Accessibility, Land Use Mix, and Bike-Sharing Use: Cross-Sectional Study.

Background: Cycling is known to be beneficial for human health. Studies have suggested significant associations of physical activity with macroscale built environments and streetscapes. However, whether good streetscapes can amplify the benefits of a favorable built environment on physical activity remains unknown. Objective: This study examines whether streetscape perceptions can modify the associations between accessibility, land use mix, and bike-sharing use. Methods: This cross-sectional study used data from 18,019,266 bike-sharing orders during weekends in Shanghai, China. A 500 × 500 m grid was selected as the analysis unit to allocate data. Bike-sharing use was defined as the number of bike-sharing origins. Street view images and a human-machine adversarial scoring framework were combined to evaluate lively, safety, and wealthy perceptions. Negative binomial regression was developed to examine the independent effects of the three perceptual factors in both the univariate model and fully adjusted model, controlling for population density, average building height, distance to nearest transit, number of bus stations, number of points of interest, distance to the nearest park, and distance to the central business district. The moderation effect was then investigated through the interaction term between streetscape perception and accessibility and land use mix, based on the fully adjusted model. We also tested whether the findings of streetscape moderation effects are robust when examinations are performed at different geographic scales, using a small-sample statistics approach and different operationalizations of land use mix and accessibility. Results: High levels of lively, safety, and wealthy perceptions were correlated with more bike-sharing activities. There were negative effects for the interactions between the land use Herfindahl-Hirschman index with the lively perception (ß=-0.63; P=.01) and safety perception (ß=-0.52; P=.001). The interaction between the lively perception and road intersection density was positively associated with the number of bike-sharing uses (ß=0.43; P=.08). Among these, the lively perception showed the greatest independent effect (ß=1.29; P<.001), followed by the safety perception (ß=1.22; P=.001) and wealthy perception (ß=0.72; P=.001). The findings were robust in the three sensitivity analyses. Conclusions: A safer and livelier streetscape can enhance the benefits of land use mix in promoting bike-sharing use, with a safer streetscape also intensifying the effect of accessibility. Interventions focused on streetscape perceptions can encourage cycling behavior and enhance the benefits of accessibility and land use mix. This study also contributes to the literature on potential moderators of built environment healthy behavior associations from the perspective of microscale environmental perceptions.

A separate-dural-incision method of extradural dumbbell spinal schwannoma resection: cumulative experience at a single center.

OBJECTIVE: To present our experience in the surgical management of completely extradural dumbbell spinal schwannomas with a new surgical strategy. METHOD: This study is a case series of patients treated at the Neurosurgery Department of the First Affiliated Hospital of USTC, between January 2018 and June 2021. RESULTS: 24 patients met the inclusion criteria, with cervical and lumbar spines being the most frequent locations. All patients underwent surgical treatment. Total gross resection was accomplished in all patients. Two cases had numbness and no case exhibited motor deficit. There was no postoperative CSF leakage or wound infection. CONCLUSION: Based on a limited number of observations, we conclude that our technique was feasible and effective for the treatment of extradural dumbbell spinal schwannomas. CLINICAL TRIAL: http://www.chictr.org.cn/ , No. ChiCTR2400086171.

Dynamics of the epidemiological Predator-Prey system in advective environments.

This paper aims to establish the existence of traveling wave solutions connecting different equilibria for a spatial eco-epidemiological predator-prey system in advective environments. After applying the traveling wave coordinates, these solutions correspond to heteroclinic orbits in phase space. We investigate the existence of the traveling wave solution connecting from a boundary equilibrium to a co-existence equilibrium by using a shooting method. Different from the techniques introduced by Huang, we directly prove the convergence of the solution to a co-existence equilibrium by constructing a special bounded set. Furthermore, the Lyapunov-type function we constructed does not need the condition of bounded below. Our approach provides a different way to study the existence of traveling wave solutions about the co-existence equilibrium. The existence of traveling wave solutions between co-existence equilibria are proved by utilizing the qualitative theory and the geometric singular perturbation theory. Some other open questions of interest are also discussed in the paper.

Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review.

BACKGROUND: The detection and management of intracranial aneurysms (IAs) are vital to prevent life-threatening complications like subarachnoid hemorrhage (SAH). Artificial Intelligence (AI) can analyze medical images, like CTA or MRA, spotting nuances possibly overlooked by humans. Early detection facilitates timely interventions and improved outcomes. Moreover, AI algorithms offer quantitative data on aneurysm attributes, aiding in long-term monitoring and assessing rupture risks. METHODS: We screened four databases (PubMed, Web of Science, IEEE and Scopus) for studies using artificial intelligence algorithms to identify IA. Based on algorithmic methodologies, we categorized them into classification, segmentation, detection and combined, and then their merits and shortcomings are compared. Subsequently, we elucidate potential challenges that contemporary algorithms might encounter within real-world clinical diagnostic contexts. Then we outline prospective research trajectories and underscore key concerns in this evolving field. RESULTS: Forty-seven studies of IA recognition based on AI were included based on search and screening criteria. The retrospective results represent that current studies can identify IA in different modal images and predict their risk of rupture and blockage. In clinical diagnosis, AI can effectively improve the diagnostic accuracy of IA and reduce missed detection and false positives. CONCLUSIONS: The AI algorithm can detect unobtrusive IA more accurately in communicating arteries and cavernous sinus arteries to avoid further expansion. In addition, analyzing aneurysm rupture and blockage before and after surgery can help doctors plan treatment and reduce the uncertainties in the treatment process.

Is Type 2 Diabetes Mellitus Associated with Spinal Degenerative Disorders?: Evidence from Observational and 2-Sample Mendelian Randomization Analyses.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and spinal degenerative disorders (SDD) are common diseases that frequently coexist. However, both traditional observational studies and recent Mendelian randomization (MR) studies have demonstrated conflicting evidence on the association between T2DM and SDD. This comparative study explored and compared the association between T2DM and SDD using observational and MR analyses. METHODS: For observational analyses, cross-sectional studies (44,972 participants with T2DM and 403,095 participants without T2DM), case-control studies (38,234 participants with SDD and 409,833 participants without SDD), and prospective studies (35,550 participants with T2DM and 392,046 participants without T2DM with follow-up information until 2022) were performed to test the relationship between T2DM and SDD using individual-level data from the U.K. Biobank from 2006 to 2022. For MR analyses, the associations between single-nucleotide polymorphisms with SDD susceptibility obtained using participant data from the U.K. Biobank, which had 407,938 participants from 2006 to 2022, and the FinnGen Consortium, which had 227,388 participants from 2017 to 2022, and genetic predisposition to T2DM obtained using summary statistics from a pooled genome-wide association study involving 1,407,282 individuals were examined. The onset and severity of T2DM are not available in the databases being used. RESULTS: Participants with T2DM were more likely to have SDD than their counterparts. Logistic regression analysis identified T2DM as an independent risk factor for SDD, which was confirmed by the Cox proportional hazard model results. However, using single-nucleotide polymorphisms as instruments, the MR analyses demonstrated no causal relationship between T2DM and SDD. The lack of such an association was robust in the sensitivity analysis, and no pleiotropy was seen. CONCLUSIONS: Our results suggest that the association between T2DM and SDD may be method-dependent. Researchers and clinicians should be cautious in interpreting the association, especially the causal association, between T2DM and SDD. Our findings provide fresh insights into the association between T2DM and SDD by various analysis methods and guide future research and clinical efforts in the effective prevention and management of T2DM and SDD. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Semantic effects on the perception of emotional prosody in native and non-native Chinese speakers.

While previous research has found an in-group advantage (IGA) favouring native speakers in emotional prosody perception over non-native speakers, the effects of semantics on emotional prosody perception remain unclear. This study investigated the effects of semantics on emotional prosody perception in Chinese words and sentences for native and non-native Chinese speakers. The critical manipulation was the congruence of prosodic (positive, negative) and semantic (positive, negative, and neutral) valence. Participants listened to a series of audio clips and judged whether the emotional prosody was positive or negative for each utterance. The results revealed an IGA effect: native speakers perceived emotional prosody more accurately and quickly than non-native speakers in Chinese words and sentences. Furthermore, a semantic congruence effect was observed in Chinese words, where both native and non-native speakers recognised emotional prosody more accurately in the semantic-prosody congruent condition than in the incongruent condition. However, in Chinese sentences, this congruence effect was only present for non-native speakers. Additionally, the IGA effect and semantic congruence effect on emotional prosody perception were influenced by prosody valence. These findings illuminate the role of semantics in emotional prosody perception, highlighting perceptual differences between native and non-native Chinese speakers.

FDA approval summary: fam-trastuzumab deruxtecan-nxki for unresectable or metastatic non-small cell lung cancer with activating HER2 mutations.

On August 11, 2022, FDA granted accelerated approval to fam-trastuzumab deruxtecan-nxki (DS-8201a, T-DXd, ENHERTU, Daiichi Sankyo) for adult patients with unresectable or metastatic non-small cell lung cancer (NSCLC) whose tumors have activating human epidermal growth factor receptor 2 (HER2) mutations, as detected by an FDA-approved test, and who have received a prior systemic therapy. The approval was based on a prespecified interim analysis of DESTINY-Lung02 (Study U206), a multi-center, randomized, dose-optimization trial in patients with NSCLC harboring activating HER2-mutations. At the approved dose of 5.4 mg/kg given intravenously every 3 weeks, the overall response rate (ORR) was 58% (95% confidence interval [CI]: 43, 71). The median duration of response was 8.7 months (95% CI: 7.1, not estimable). These results were consistent with response rates observed at the 6.4 mg/kg dose level. The most common (≥ 20%) adverse reactions were nausea, constipation, decreased appetite, vomiting, fatigue, and alopecia. The rate of interstitial lung disease (ILD) or pneumonitis was 6% at the 5.4 mg/kg dose level and 14% at the 6.4 mg/kg dose level. In the setting of similar efficacy and reduced toxicity, approval was granted for the 5.4 mg/kg dose level. The applicant conducted a randomized, dose-optimization study with guidance from the FDA Oncology Center of Excellence's Project Optimus. This is the first approval of a targeted therapy for HER2-mutated NSCLC.

Efficient pyramid channel attention network for pathological myopia recognition with pretraining-and-finetuning.

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, the characteristics of pathology distribution in PM are global-local on the fundus image, which plays a significant role in assisting clinicians in diagnosing PM. However, most existing deep neural networks focused on designing complex architectures but rarely explored the pathology distribution prior of PM. To tackle this issue, we propose an efficient pyramid channel attention (EPCA) module, which fully leverages the potential of the clinical pathology prior of PM with pyramid pooling and multi-scale context fusion. Then, we construct EPCA-Net for automatic PM recognition based on fundus images by stacking a sequence of EPCA modules. Moreover, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM recognition by freezing them and treating the EPCA and other attention modules as adapters. In addition, we construct a PM recognition benchmark termed PM-fundus by collecting fundus images of PM from publicly available datasets. The comprehensive experiments demonstrate the superiority of EPCA-Net over state-of-the-art methods in the PM recognition task. For example, EPCA-Net achieves 97.56% accuracy and outperforms ViT by 2.85% accuracy on the PM-fundus dataset. The results also show that our method based on the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of previous methods based on traditional fine-tuning paradigm with fewer tunable parameters, which has the potential to leverage more natural image foundation models to address the PM recognition task in limited medical data regime.

Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.

BACKGROUND: It was essential to identify individuals at high risk of fragility fracture and prevented them due to the significant morbidity, mortality, and economic burden associated with fragility fracture. The quantitative ultrasound (QUS) showed promise in assessing bone structure characteristics and determining the risk of fragility fracture. AIMS: To evaluate the performance of a multi-channel residual network (MResNet) based on ultrasonic radiofrequency (RF) signal to discriminate fragility fractures retrospectively in postmenopausal women, and compared it with the traditional parameter of QUS, speed of sound (SOS), and bone mineral density (BMD) acquired with dual X-ray absorptiometry (DXA). METHODS: Using QUS, RF signal and SOS were acquired for 246 postmenopausal women. An MResNet was utilized, based on the RF signal, to categorize individuals with an elevated risk of fragility fracture. DXA was employed to obtain BMD at the lumbar, hip, and femoral neck. The fracture history of all adult subjects was gathered. Analyzing the odds ratios (OR) and the area under the receiver operator characteristic curves (AUC) was done to evaluate the effectiveness of various methods in discriminating fragility fracture. RESULTS: Among the 246 postmenopausal women, 170 belonged to the non-fracture group, 50 to the vertebral group, and 26 to the non-vertebral fracture group. MResNet was competent to discriminate any fragility fracture (OR = 2.64; AUC = 0.74), Vertebral fracture (OR = 3.02; AUC = 0.77), and non-vertebral fracture (OR = 2.01; AUC = 0.69). After being modified by clinical covariates, the efficiency of MResNet was further improved to OR = 3.31-4.08, AUC = 0.81-0.83 among all fracture groups, which significantly surpassed QUS-SOS (OR = 1.32-1.36; AUC = 0.60) and DXA-BMD (OR = 1.23-2.94; AUC = 0.63-0.76). CONCLUSIONS: This pilot cross-sectional study demonstrates that the MResNet model based on the ultrasonic RF signal shows promising performance in discriminating fragility fractures in postmenopausal women. When incorporating clinical covariates, the efficiency of the modified MResNet is further enhanced, surpassing the performance of QUS-SOS and DXA-BMD in terms of OR and AUC. These findings highlight the potential of the MResNet as a promising approach for fracture risk assessment. Future research should focus on larger and more diverse populations to validate these results and explore its clinical applications.

Ferrocene-modified covalent organic framework for efficient oxygen evolution reaction and CO2 electroreduction.

A ferrocene-modified COF, namely Ni-Tph-COF-Fc, was synthesized and applied in OER. Compared with Ni-Tph-COF-OH, Ni-Tph-COF-Fc shows improved performance with a current density of 99.6 mA cm-2, an overpotential of 450 mV, and a Tafel slope of 73.1 mV dec-1, which may be attributed to a synergy between introduced ferrocene and metalloporphyrin in the COFs. Moreover, the enhanced OER performance leads to an improved CO2RR performance with an FECO of 93.1%. This work represents an effective strategy to enhance the anodic OER performance and realize efficient CO2RR.

Cross-modal attention network for retinal disease classification based on multi-modal images.

Multi-modal eye disease screening improves diagnostic accuracy by providing lesion information from different sources. However, existing multi-modal automatic diagnosis methods tend to focus on the specificity of modalities and ignore the spatial correlation of images. This paper proposes a novel cross-modal retinal disease diagnosis network (CRD-Net) that digs out the relevant features from modal images aided for multiple retinal disease diagnosis. Specifically, our model introduces a cross-modal attention (CMA) module to query and adaptively pay attention to the relevant features of the lesion in the different modal images. In addition, we also propose multiple loss functions to fuse features with modality correlation and train a multi-modal retinal image classification network to achieve a more accurate diagnosis. Experimental evaluation on three publicly available datasets shows that our CRD-Net outperforms existing single-modal and multi-modal methods, demonstrating its superior performance.

Pyramid Pixel Context Adaption Network for Medical Image Classification With Supervised Contrastive Learning.

Spatial attention (SA) mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency modeling. However, it may perform poorly in medical image analysis. Unfortunately, the existing efforts are often unaware that long-range dependency modeling has limitations in highlighting subtle lesion regions. To overcome this limitation, we propose a practical yet lightweight architectural unit, pyramid pixel context adaption (PPCA) module, which exploits multiscale pixel context information to recalibrate pixel position in a pixel-independent manner dynamically. PPCA first applies a well-designed cross-channel pyramid pooling (CCPP) to aggregate multiscale pixel context information, then eliminates the inconsistency among them by the well-designed pixel normalization (PN), and finally estimates per pixel attention weight via a pixel context integration. By embedding PPCA into a DNN with negligible overhead, the PPCA network (PPCANet) is developed for medical image classification. In addition, we introduce supervised contrastive learning to enhance feature representation by exploiting the potential of label information via supervised contrastive loss (CL). The extensive experiments on six medical image datasets show that the PPCANet outperforms state-of-the-art (SOTA) attention-based networks and recent DNNs. We also provide visual analysis and ablation study to explain the behavior of PPCANet in the decision-making process.

Effect of different inhalant allergens on T-cell subsets in adults with bronchial asthma.

OBJECTIVE: We analyzed the impact of different inhalant allergens on T-lymphocyte subsets in patients diagnosed with bronchial asthma. METHODS: The study included 57 bronchial asthma patients and 22 healthy controls. Asthma patients were categorized into dust mite, animal hair, pollen, and mold groups. Flow cytometry was used to measure the cells in the case group and control group. These T-lymphocyte subset markers were evaluated among patients with bronchial asthma caused by different allergens as well as between the case group and control group. RESULTS: Peripheral blood CD4+ T-cells, CD8+ T-cells, CD4/CD8 ratio, and Th17/Treg ratios were all higher in the case group than in the control group (p < 0.05). Peripheral blood T-lymphocyte subsets were compared among the four groups, and it was found that there were statistical differences in the Th17/Treg ratio among the four groups (p < 0.05). There were no significant differences observed among the four groups in terms of CD3+ cells, CD4+ cells, CD8+ cells, Th1 cells, Th2 cells, Th17 cells, Treg cells, Th9 cells, and Th22 cells. Further pairwise comparison was made, and the results suggested that the peripheral blood Th17/Treg ratio in the pollen mixed group was lower than that in the dust mite mixed group, animal hair mixed group, and mold mixed group (p < 0.05). CONCLUSION: Patients with bronchial asthma show varied T-lymphocyte subset responses to different inhalant allergens. Elevated CD4+ T cells and Th17 cells in peripheral blood could indicate asthma risk. However, small sample size may introduce bias to these findings.

Heterologous synthesis of poly-γ-glutamic acid enhanced drought resistance in maize (Zea mays L.).

Drought stress is the main factor restricting maize yield. Poly-γ-glutamic acid (γ-PGA), as a water-retaining agent and fertilizer synergist, could significantly improve the drought resistance and yield of many crops. However, its high production costs and unclear long-term impact on soil ecology limit its large-scale application. In this study, an environmentally friendly green material γ-PGA was heterologous synthesized in maize for the first time using the synthetic biology method. The genes (PgsA, PgsB, PgsC) participated in γ-PGA synthesis were cloned from Bacillus licheniformis and transformed into maize to produce γ-PGA for the first time. Under drought stress, transgenic maize significantly increased the ear length, ear weight and grain weight by 50 % compared to the control, whereas the yield characteristic of ear weight, grain number per ear, grain weight per ear and 100-grain weight increased by 1.67 %-2.33 %, 3.78 %-13.06 %, 8.41 %-22.06 %, 6.03 %-19.28 %, and 11.85 %-18.36 %, respectively under normal growth conditions. γ-PGA was mainly expressed in the mesophyll cells of maize leaf rosette structure and improved drought resistance and yield by protecting and increasing the expression of genes for the photosynthetic and carbon fixation. This study is an important exploration for maize drought stress molecular breeding and building resource-saving agriculture.

Using Mercury Stable Isotopes to Quantify Directional Soil-Atmosphere Hg(0) Exchanges in Rice Paddy Ecosystems: Implications for Hg(0) Emissions to the Atmosphere from Land Surfaces.

Gaseous elemental mercury [Hg(0)] emissions from soils constitute a large fraction of global total Hg(0) emissions. Existing studies do not distinguish biotic- and abiotic-mediated emissions and focus only on photoreduction mediated emissions, resulting in an underestimation of soil Hg(0) emissions into the atmosphere. In this study, directional mercury (Hg) reduction pathways in paddy soils were identified using Hg isotopes. Results showed significantly different isotopic compositions of Hg(0) between those produced from photoreduction (δ202Hg = -0.80 ± 0.67‰, Δ199Hg = -0.38 ± 0.18‰), microbial reduction (δ202Hg = -2.18 ± 0.25‰, Δ199Hg = 0.29 ± 0.38‰), and abiotic dark reduction (δ202Hg = -2.31 ± 0.25‰, Δ199Hg = 0.50 ± 0.22‰). Hg(0) exchange fluxes between the atmosphere and the paddy soils were dominated by emissions, with the average flux ranging from 2.2 ± 5.7 to 16.8 ± 21.7 ng m-2 h-1 during different sampling periods. Using an isotopic signature-based ternary mixing model, we revealed that photoreduction is the most important contributor to Hg(0) emissions from paddy soils. Albeit lower, microbial and abiotic dark reduction contributed up to 36 ± 22 and 25 ± 15%, respectively, to Hg(0) emissions on the 110th day. These novel findings can help improve future estimation of soil Hg(0) emissions from rice paddy ecosystems, which involve complex biotic-, abiotic-, and photoreduction processes.

Middle school students' psychological health on suicide ideation: based on latent profile analysis.

Introduction: This study identifies potential categories of mental health for adolescents in different school years and further analyzes the relationship between these categories and suicidal ideation. Methods: A total of 1944 middle school students completed SCL-90 and Self-rating Idea of Suicide Scale on November 29, 2022, selecting via a whole-group sampling method. Latent profile analysis was used to analyze the psychological health subtypes of students from a middle school in Southwest China. The R3step method and the DU3step method were conducted to analyze the predictive role of demographic variables and the effects of different profiles on suicidal ideation. Results: Different potential categories of psychological health were observed among middle school students. Junior middle school students can be classified into three types: Psychological Health Type (62.3%), Low-risk Type (27.1%) and High-risk Type (10.7%). Senior middle school students can be classified into four types: Psychological Health Type (43.3%), Low-risk Type (33.9%), Medium -risk Type (16.8%), and High-risk Type (6.0%). Gender and subjective family atmosphere are predictors of psychological health, and they also influence the population distribution of psychological health patterns in different sections of middle school students. Girls and students with poor subjective family atmosphere are more prone to experiencing psychological problems. There were significant differences in suicidal ideation among different potential categories of psychological health of different sections middle school students (χ 2 = 1178.71, 1174.85, p<0.001). Among senior high school students classified as High-risk Type, they exhibited the highest score for suicidal ideation. Conclusion: There is obvious group heterogeneity in psychological health of different sections middle school students. Older students are more likely to have suicidal thoughts.

A Simply Synthesized Shaking-induced Small Molecule System with Repeatableand Instantaneous Discoloration Response.

Force-related discoloration materials are highly valuable because of their characteristics of visualization, easy operation, and environment friendliness. Most force-related discoloration materials focus on polymers and depend on bond scission, which leads to insensitivity and unrecoverable. Small-molecule systems based on well-defined molecular structures and simple composition with high sensitivity would exhibit considerable mechanochromic potential. However, to date, researches about force-related discoloration materials based on small molecule solution remain limited and are rarely reported. In this study, we developed a repeatable and instantaneous discoloration small molecule solution system by simple one-pot synthesis method. It exhibited an instantaneous chromic change from yellowish to dark green under shaking and reverting back to yellow within 1 minute after removal of the shaking. Experimental results confirmed that the discoloration mechanism is attributed to the oscillation accelerating the production of unstable ortho-OH phenoxyl radical. The newly developed shaking-induced discoloration small molecule system (SDSMS) promises in field of mechanical force sensing and optical encryption.

Finite element analysis of endoscopic cross-overtop decompression for single-segment lumbar spinal stenosis based on real clinical cases.

Introduction: For severe degenerative lumbar spinal stenosis (DLSS), the conventional percutaneous endoscopic translaminar decompression (PEID) has some limitations. The modified PEID, Cross-Overtop decompression, ensures sufficient decompression without excessive damage to the facet joints and posterior complex integrity. Objectives: To evaluate the biomechanical properties of Cross-Overtop and provide practical case validation for final decision-making in severe DLSS treatment. Methods: A finite element (FE) model of L4-L5 (M0) was established, and the validity was verified against prior studies. Endo-ULBD (M1), Endo-LOVE (M2), and Cross-Overtop (M3) models were derived from M0 using the experimental protocol. L4-L5 segments in each model were evaluated for the range of motion (ROM) and disc Von Mises stress extremum. The real clinical Cross-Overtop model was constructed based on clinical CT images, disregarding paraspinal muscle influence. Subsequent validation using actual FE analysis results enhances the credibility of the preceding virtual FE analysis. Results: Compared with M0, ROM in surgical models were less than 10°, and the growth rate of ROM ranged from 0.10% to 11.56%, while those of disc stress ranged from 0% to 15.75%. Compared with preoperative, the growth rate of ROM and disc stress were 2.66%-11.38% and 1.38%-9.51%, respectively. The ROM values in both virtual and actual models were less than 10°, verifying the affected segment stability after Cross-Overtop decompression. Conclusion: Cross-Overtop, designed for fully expanding the central canal and contralateral recess, maximizing the integrity of the facet joints and posterior complex, does no significant effect on the affected segmental biomechanics and can be recommended as an effective endoscopic treatment for severe DLSS.

Immune cell signatures and causal association with irritable bowel syndrome: A mendelian randomization study.

BACKGROUND: The mucosal barrier's immune-brain interactions, pivotal for neural development and function, are increasingly recognized for their potential causal and therapeutic relevance to irritable bowel syndrome (IBS). Prior studies linking immune inflammation with IBS have been inconsistent. To further elucidate this relationship, we conducted a Mendelian randomization (MR) analysis of 731 immune cell markers to dissect the influence of various immune phenotypes on IBS. Our goal was to deepen our understanding of the disrupted brain-gut axis in IBS and to identify novel therapeutic targets. AIM: To leverage publicly available data to perform MR analysis on 731 immune cell markers and explore their impact on IBS. We aimed to uncover immunophenotypic associations with IBS that could inform future drug development and therapeutic strategies. METHODS: We performed a comprehensive two-sample MR analysis to evaluate the causal relationship between immune cell markers and IBS. By utilizing genetic data from public databases, we examined the causal associations between 731 immune cell markers, encompassing median fluorescence intensity, relative cell abundance, absolute cell count, and morphological parameters, with IBS susceptibility. Sensitivity analyses were conducted to validate our findings and address potential heterogeneity and pleiotropy. RESULTS: Bidirectional false discovery rate correction indicated no significant influence of IBS on immunophenotypes. However, our analysis revealed a causal impact of IBS on 30 out of 731 immune phenotypes (P < 0.05). Nine immune phenotypes demonstrated a protective effect against IBS [inverse variance weighting (IVW) < 0.05, odd ratio (OR) < 1], while 21 others were associated with an increased risk of IBS onset (IVW ≥ 0.05, OR ≥ 1). CONCLUSION: Our findings underscore a substantial genetic correlation between immune cell phenotypes and IBS, providing valuable insights into the pathophysiology of the condition. These results pave the way for the development of more precise biomarkers and targeted therapies for IBS. Furthermore, this research enriches our comprehension of immune cell roles in IBS pathogenesis, offering a foundation for more effective, personalized treatment approaches. These advancements hold promise for improving IBS patient quality of life and reducing the disease burden on individuals and their families.

Large-Scale Synthesis of High-Purity Isoguanosine and Resolution of its Crystal Structure by Microcrystal Electron Diffraction.

Isoguanosine (isoG) is a natural structural isomer of guanosine (G) with significant potential for applications in ionophores, genetics, gel formation, and cancer therapy. However, the cost of commercially available isoG on a gram scale is relatively high. To date, a detailed method for the large-scale preparation of high-purity isoG has not been reported. This study presented a simple and convenient approach for the large-scale synthesis of isoG through the diazotization of 2,6-diaminopurine riboside with sodium nitrite and acetic acid at room temperature. Further, this method could synthesize isoG derivatives (2'-fluoro-isoguanosine (1) and 2'-deoxy-isoguanosine (2)) from 2,6-diaminopurine nucleoside derivatives using diazotization. The structural information of natural and modified nucleosides is crucial for the modification and substitution of DNA/RNA. This study obtained the single-crystal structure of isoG for the first time and analyzed it in detail using microcrystal electron diffraction. The three-dimensional supramolecular structure of isoG adopted similarly base-pair motifs from π-π stacking interaction of diverse layers, intramolecular hydrogen bonding, and distinct hydrogen bonding interactions from sugar residues. This study has contributed to further isoG modification and its applications in medicinal chemistry and materials.