Causal relationship between the gut microbiota, immune cells, and coronary heart disease: a mediated Mendelian randomization analysis.

Background: Recent studies have shown that the gut microbiota (GM), immune cells, and coronary heart disease (CHD) are closely related, but the causal nature of these relationships is largely unknown. This study aimed to investigate this causal relationship and reveal the effect of GM and immune cells on the risk of developing CHD using mediated Mendelian randomization (MR) analysis. Methods: First, we searched for data related to GM, immune cells, and CHD through published genome-wide association studies (GWAS). We filtered the single nucleotide polymorphisms (SNPs) associated with GM and immune cells and then performed the first MR analysis to identify disease-associated intestinal bacteria and disease-associated immune cells. Subsequently, three MR analyses were conducted: from disease-associated GM to disease-associated immune cells, from disease-associated immune cells to CHD, and from disease-associated GM to CHD. Each MR analysis was conducted using inverse variance weighting (IVW), MR-Egger regression, weighted median, weighted models, and simple models. Results: A total of six GM and 25 immune cells were found to be associated with CHD. In the MR analysis using the inverse variance weighting (IVW) method, g__Desulfovibrio.s__Desulfovibrio_piger was associated with EM DN (CD4-CD8-) %T cells (P < 0.05 and OR > 1), EM DN (CD4-CD8-) %T cells was associated with CHD (P < 0.05 and OR < 1), and g__Desulfovibrio.s__Desulfovibrio_piger was associated with CHD (P < 0.05 and OR < 1). Conclusion: An increase in the abundance of g__Desulfovibrio.s__Desulfovibrio_piger leads to an increase in the amount of EM DN (CD4-CD8-) %T cells, and an increase in the amount of EM DN (CD4-CD8-) %T cells reduces the risk of developing CHD. Our study provides some references for reducing the incidence of CHD by regulating GM and immune cells.

Transcriptome analyses reveal key features of mouse seminal vesicle during aging.

Despite the significant morphological changes that occur in the seminal vesicles with aging, the transcriptomic characteristics remain largely unexplored. To address this, we performed bulk RNA sequencing on seminal vesicle samples from mice aged 3, 13, and 21 months to uncover transcriptomic alterations. Our findings reveal that aged seminal vesicles display cystic dilatation, epithelial hypoplasia, disordered muscle layers, fibrosis, and reduced proliferation capability. A comparison between 3-month-old and 21-month-old mice indicated that leukocyte-mediated immunity and leukocyte migration were the most significantly upregulated biological processes among differentially expressed genes (DEGs). Notably, several DEGs associated with "leukocyte migration," such as Vcam1, Cxcl13, and Ccl8, exhibited an increasing trend in transcriptomic and protein expression at three different time points in the seminal vesicles of mice. Additionally, we identified multiple aging-associated DEGs, including P21 and Tnfrsf1b. Two genes (Cd209f and Ccl8) were consistently upregulated across all six regions of the male reproductive glands (testis, epididymis, and seminal vesicle) in the comparison of bulk RNA datasets from 3-month-old and 21-month-old mice. These analyses highlight an enhanced state of immune and inflammatory response in aged seminal vesicles. This study represents the first exploration of the overall transcriptome landscape of seminal vesicles in a murine model of natural aging, offering new insights into the mechanisms underlying aging-related seminal vesicle dysfunction.

Antiferromagnetic Ordering in A One-Dimensional Organic Copper Chloride Hybrid Insulator.

Low dimensional (LD) organic metal halide hybrids (OMHHs) have recently emerged as new generation functional materials with exceptional structural and property tunability. Despite the remarkable advances in the development of LD OMHHs, optical properties have been the major functionality extensively investigated for most of LD OMHHs developed to date, while other properties, such as magnetic and electronic properties, remain significantly under-explored. Here we report for the first time the characterization of the magnetic and electronic properties of a 1D OMHH, organic-copper (II) chloride hybrid (C8H22N2)Cu2Cl6. Owing to the antiferromagnetic coupling between Cu atoms through chloride bridges in 1D [Cu2Cl62-]∞ chains, (C8H22N2)Cu2Cl6 is found to exhibit antiferromagnetic ordering with a Néel temperature of 24K. The two-terminal (2T) electrical measurement on a (C8H22N2)Cu2Cl6 single crystal reveals its insulating nature. This work shows the potential of LD OMHHs as a highly tunable quantum material platform for spintronics.

Research on the Corrosion Detection of Rebar in Reinforced Concrete Based on SMFL Technology.

The corrosion damage of rebars is a leading cause of structural failure in reinforced concrete structures. Timely detection and evaluation of corrosion damage are crucial for ensuring structural safety. The self-magnetic flux leakage (SMFL) technology is often used due to its unique advantages in detecting corrosion damage of rebars. However, challenges persist in theoretically characterizing corrosion damage and exploring influencing factors. Therefore, the magnetic dipole theory model coupled with multiple-shaped defects is proposed and the influence of corrosion expansion force on the detection of corrosion damage is analyzed. The results show that the standard deviation of the magnetic field intensity induced by corrosion varied by up to 833%, while that induced by corrosion expansion force did not exceed 10%. So the changes in the SMFL field induced by corrosion damage play the dominant role and the influence of corrosion expansion force can be ignored. In addition, corrosion damage experiments on reinforced concrete based on the SMFL technology were conducted. The results indicate that the SFML curves of rebars change monotonically with the increasing corrosion degree. Significant variations in the curves correspond well with the locations of severe corrosion on the rebars. There is a positive relationship between the proposed magnetic parameters and the corrosion degree of the rebars. Furthermore, a corrosion damage evaluation model considering multiple parameters is developed to predict the corrosion degree of rebars. The prediction results demonstrate high accuracy, with an average absolute error of only 8.33%, which is within 10%.

A dataset for deep learning based detection of printed circuit board surface defect.

Printed circuit board (PCB) may display diverse surface defects in manufacturing. These defects not only influence aesthetics but can also affect the performance of the PCB and potentially damage the entire board. Thus, achieving efficient and highly accurate detection of PCB surface defects is fundamental for quality control in fabrication. The rapidly advancing deep learning (DL) technology holds promising prospects for providing accurate and efficient detection methods for surface defects on PCB. To facilitate DL model training, it is imperative to compile a comprehensive dataset encompassing diverse surface defect types found on PCB at a significant scale. This work categorized PCB surface defects into 9 distinct categories based on factors such as their causes, locations, and morphologies and developed a dataset of PCB surface defect (DsPCBSD+). In DsPCBSD+, a total of 20,276 defects were annotated manually by bounding boxes on the 10,259 images. This openly accessible dataset is aimed accelerating and promoting further researches and advancements in the field of DL-based detection of PCB surface defect.

[Corrigendum] miR­146b­5p inhibits tumorigenesis and metastasis of gallbladder cancer by targeting Toll­like receptor 4 via the nuclear factor­κB pathway.

Following the publication of the article, the authors drew to the Editor's attention that, in Fig. 4D on p. 7, the data correctly shown to represent the E­cadherin bands for the "NOZ" experiment had inadvertently been used to show the Vimentin bands. However, the authors retained their original data, and the corrected version of Fig. 4, now showing the correct data for the Vimentin bands in Fig. 4D for the "NOZ" experiment, is shown on the next page. Note that this error did not grossly affect either the results or the conclusions reported in this work. All the authors agree with the publication of this Corrigendum, and are grateful to the Editor of Oncology Reports for granting them the opportunity to correct the error that was made during the assembly of this figure. Lastly, the authors apologize to the readership for any inconvenience this error may have caused. [Oncology Reports  45: 15, 2021; DOI: 10.3892/or.2021.7966].

Effects of an Early Intensive Blood Pressure-lowering Strategy Using Remifentanil and Dexmedetomidine in Patients with Spontaneous Intracerebral Hemorrhage: A Multicenter, Prospective, Superiority, Randomized Controlled Trial.

BACKGROUND: Although it has been established that elevated blood pressure and its variability worsen outcomes in spontaneous intracerebral hemorrhage, antihypertensives use during the acute phase still lacks robust evidence. A blood pressure-lowering regimen using remifentanil and dexmedetomidine might be a reasonable therapeutic option given their analgesic and antisympathetic effects. The objective of this superiority trial was to validate the efficacy and safety of this blood pressure-lowering strategy that uses remifentanil and dexmedetomidine in patients with acute intracerebral hemorrhage. METHODS: In this multicenter, prospective, single-blinded, superiority randomized controlled trial, patients with intracerebral hemorrhage and systolic blood pressure (SBP) 150 mmHg or greater were randomly allocated to the intervention group (a preset protocol with a standard guideline management using remifentanil and dexmedetomidine) or the control group (standard guideline-based management) to receive blood pressure-lowering treatment. The primary outcome was the SBP control rate (less than 140 mmHg) at 1 h posttreatment initiation. Secondary outcomes included blood pressure variability, neurologic function, and clinical outcomes. RESULTS: A total of 338 patients were allocated to the intervention (n = 167) or control group (n = 171). The SBP control rate at 1 h posttreatment initiation in the intervention group was higher than that in controls (101 of 161, 62.7% vs. 66 of 166, 39.8%; difference, 23.2%; 95% CI, 12.4 to 34.1%; P < 0.001). Analysis of secondary outcomes indicated that patients in the intervention group could effectively reduce agitation while achieving lighter sedation, but no improvement in clinical outcomes was observed. Regarding safety, the incidence of bradycardia and respiratory depression was higher in the intervention group. CONCLUSIONS: Among intracerebral hemorrhage patients with a SBP 150 mmHg or greater, a preset protocol using a remifentanil and dexmedetomidine-based standard guideline management significantly increased the SBP control rate at 1 h posttreatment compared with the standard guideline-based management.

Unlocking Li superionic conductivity in face-centred cubic oxides via face-sharing configurations.

Oxides with a face-centred cubic (fcc) anion sublattice are generally not considered as solid-state electrolytes as the structural framework is thought to be unfavourable for lithium (Li) superionic conduction. Here we demonstrate Li superionic conductivity in fcc-type oxides in which face-sharing Li configurations have been created through cation over-stoichiometry in rocksalt-type lattices via excess Li. We find that the face-sharing Li configurations create a novel spinel with unconventional stoichiometry and raise the energy of Li, thereby promoting fast Li-ion conduction. The over-stoichiometric Li-In-Sn-O compound exhibits a total Li superionic conductivity of 3.38 × 10-4 S cm-1 at room temperature with a low migration barrier of 255 meV. Our work unlocks the potential of designing Li superionic conductors in a prototypical structural framework with vast chemical flexibility, providing fertile ground for discovering new solid-state electrolytes.

Biological signatures of the International Prognostic Index in diffuse large B-cell lymphoma.

ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) is a highly aggressive subtype of lymphoma with clinical and biological heterogeneity. The International Prognostic Index (IPI) shows great prognostic capability in the era of rituximab, but the biological signatures of IPI remain to be discovered. In this study, we analyzed the clinical data in a large cohort of 2592 patients with newly diagnosed DLBCL. Among them, 1233 underwent DNA sequencing for oncogenic mutations, and 487 patients underwent RNA sequencing for lymphoma microenvironment (LME) alterations. Based on IPI scores, patients were categorized into 4 distinct groups, with 5-year overall survival of 41.6%, 55.3%, 71.7%, and 89.7%, respectively. MCD-like subtype was associated with age of >60 years, multiple extranodal involvement, elevated serum lactate dehydrogenase (LDH), and IPI scores ranging from 2 to 5, whereas ST2-like subtype showed an opposite trend. Patients with EZB-like MYC+ and TP53Mut subtypes exhibited poor clinical outcome independent of the IPI; integrating TP53Mut into IPI could better distinguish patients with dismal survival. The EZB-like MYC-, BN2-like, N1-like, and MCD-like subtypes had inferior prognosis in patients with IPI scores of ≥2, indicating necessity for enhanced treatment. Regarding LME categories, the germinal center-like LME was more prevalent in patients with normal LDH and IPI scores of 0 to 1. The mesenchymal LME served as an independent protective factor, whereas the germinal center-like, inflammatory, and depleted LME categories correlated with inferior prognosis for IPI scores of 2 to 5. In summary, our work explored the biological signatures of IPI, thus providing useful rationale for future optimization of the IPI-based treatment strategies with multi-omics information in DLBCL.

Clinical and dosimetric predictors of radiation-induced rhinosinusitis following VMAT for nasopharyngeal carcinoma: A retrospective study.

Background: We aimed to investigate the clinical and dosimetric factors associated with radiation-induced rhinosinusitis, and further elucidate the optimal dose-volume constraints for nasopharyngeal cancer patients who underwent volumetric-modulated arc therapy (VMAT). Methods: A retrospective review of 196 nasopharyngeal carcinoma (NPC) patients who underwent definitive VMAT between August 2018 and May 2021 was conducted. Both clinical and dose-volume histogram (DVH) data of NPC patients without rhinosinusitis at baseline were selected for analysis. Results: The cumulative incidence of post-RT rhinosinusitis at the 3-, 6-, 9-, and 12-months, and >1 year were 29.6 %, 41.3 %, 42.9 %, and 45.4 %, and 47.4 %, respectively. Nasal irrigation was negatively associated with post-RT rhinosinusitis (p < 0.001). Higher cumulative incidences of maxillary and ethmoid sinusitis were associated with V70 > 1.16 % and >1.00 %, respectively (p = 0.027 and p = 0.002). Sphenoid sinusitis was more frequent when Dmax(maxillary sinus) exceeded 69.2Gy (p = 0.005). Conclusions: Regular nasal irrigation may reduce the development of rhinosinusitis. Dose-volume constraints of V70 and Dmax to the maxillary sinus are suggested for VMAT planning. Patients exceeding these thresholds should be closely monitored and potentially offered preventative interventions within 3-6 months post-RT.

Selective formation of metastable polymorphs in solid-state synthesis.

Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions. This framework presents reaction energy as a rarely used handle for polymorph selection, which influences the role of surface energy in promoting the nucleation of metastable phases. Through in situ characterization and density functional theory calculations on two distinct synthesis pathways targeting LiTiOPO4, we demonstrate how precursor selection and its effect on reaction energy can effectively be used to control which polymorph is obtained from solid-state synthesis. A general approach is outlined to quantify the conditions under which metastable polymorphs are experimentally accessible. With comparison to historical data, this approach suggests that using appropriate precursors could enable targeted materials synthesis across diverse chemistries through selective polymorph nucleation.

Patterns Lead the Way to Far-from-Equilibrium Materials.

The universe is a complex fabric of repeating patterns that unfold their beauty in system-specific diversity. The periodic table, crystallography, and the genetic code are classic examples that illustrate how even a small number of rules generate a vast range of shapes and structures. Today, we are on the brink of an AI-driven revolution that will reveal an unprecedented number of novel patterns, many of which will escape human intuition and expertise. We suggest that in the second half of the 21st century, the challenge for Physical Chemistry will be to guide and interpret these advances in the broader context of physical sciences and materials-related engineering. If we succeed in this role, Physical Chemistry will be able to extend to new horizons. In this article, we will discuss examples that strike us as particularly promising, specifically the discovery of high-entropy and far-from-equilibrium materials as well as applications to origins-of-life research and the search for life on other planets.

Phase Selection Rules of Multi-Principal Element Alloys.

Computational prediction of phase stability of multi-principal element alloys (MPEAs) holds a lot of promise for rapid exploration of the enormous design space and autonomous discovery of superior structural and functional properties. Regardless of many plausible works that rely on phenomenological theory and machine learning, precise prediction is still limited by insufficient data and the lack of interpretability of some machine learning algorithms, e.g., convolutional neural network. In this work, a comprehensive approach is presented, encompassing the development of a complete dataset that contains 72 387 density functional theory calculations, as well as a predictive global phenomenological descriptor. The phase selection descriptor, based on atomic electronegativity and valence electron concentration, significantly outperforms the widely used valence electron concentration, excelling in both accuracy (with an f1 score of 63% compared to 47%) and its ability to predict the HCP phase (0.48 recall compared to 0). The comprehensive data mining on the global design space of 61 425 quaternary MPEAs made from 28 possible metals, together with the phenomenological theory and physical interpretation, will set up a solid computational science foundation for data-driven exploration of MPEAs.

ALKBH5 promotes the development of lung adenocarcinoma by regulating the polarization of M2 macrophages through CDCA4.

OBJECTIVE: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, with high morbidity and mortality. N6-methyladenosine (m6A) is an important regulator of LUAD progression. Here, we investigated the potential biological functions of ALKBH5 (a m6A demethylated enzyme) and cell division cycle associated protein 4 (CDCA4) in the progression of LUAD. METHODS: The expressions of CDCA4, METTL3, ALKBH5, FTO, YTHDC2 and YTHDC1 mRNA and proteins in LUAD and adjacent tissues, as well as NCI-H1299 and NCI-H157 cells were detected by RT-qPCR and western blot. Meanwhile, the role of ALKBH5 and CDCA4 in macrophage polarization was explored through tumor formation in Lewis lung carcinoma (LLC) mice and the co-culture system of NCI-H1299 and NCI-H157/THP-1 cells. Cell characterization was further analyzed. The expression of Ki-67 in tumor tissue was tested by immunohistochemistry. The scale of M1 and M2 macrophages was determined by flow cytometry. RESULTS: CDCA4 was significantly overexpressed in NCI-H1299 and NCI-H157 cell lines compared with BEAS-2B cells. The fold enrichment of CDCA4 m6A level in the overexpression (oe)-METTL3 or short hairpin (sh)-ALKBH5 cells was enhanced. Overexpression of CDCA4 promoted the cell viability, proliferation and migration, and inhibited apoptosis, which was reversed by sh-ALKBH5 intervention. Overexpression of YTHDC2 (not YTHDC1) inhibited the effect of CDCA4 on sh-ALKBH5 cells. sh-CDCA4 inhibited tumor growth and weight of LLC cells in mice, and promoted M1/M2 ratio in LLC mice and NCI-H1299/THP-1 and NCI-H157/THP-1 co-culture systems. Oe-CDCA4 promoted the volume and weight of tumor and inhibited the M1/M2 ratio of tumor tissue in LLC mice, but was reversed by sh-ALKBH5 intervention. CONCLUSION: m6A demethylase ALKBH5 promotes the development of LUAD through CDCA4 regulation of malignant characterization and M1/M2 macrophage polarization.

Atomic-scale probing of short-range order and its impact on electrochemical properties in cation-disordered oxide cathodes.

Chemical short-range-order has been widely noticed to dictate the electrochemical properties of Li-excess cation-disordered rocksalt oxides, a class of cathode based on earth abundant elements for next-generation high-energy-density batteries. Existence of short-range-order is normally evidenced by a diffused intensity pattern in reciprocal space, however, derivation of local atomic arrangements of short-range-order in real space is hardly possible. Here, by a combination of aberration-corrected scanning transmission electron microscopy, electron diffraction, and cluster-expansion Monte Carlo simulations, we reveal the short-range-order is a convolution of three basic types: tetrahedron, octahedron, and cube. We discover that short-range-order directly correlates with Li percolation channels, which correspondingly affects Li transport behavior. We further demonstrate that short-range-order can be effectively manipulated by anion doping or post-synthesis thermal treatment, creating new avenues for tailoring the electrochemical properties. Our results provide fundamental insights for decoding the complex relationship between local chemical ordering and properties of crystalline compounds.

Performance of the Cement Grouting Material and Optimization of the Mix Proportion for the Free Section of the Prestressed Anchor Bar.

Increasing the water-cement ratio and water-reducer dosage of cement slurry enhances its fluidity. However, a high water-cement ratio diminishes the beneficial effects of water reducers on fluidity. The stone content of the slurry decreases as the water-reducer dosage increases. Additionally, the water-cement ratio significantly affects stone content. However, when the water-cement ratio exceeds a threshold value, stone content decreases. Furthermore, the threshold value of the water-cement ratio decreases with increasing water-reducer dosage. Without the addition of the water reducer, as the water-cement ratio increases the overall integrity of the grout stone decreases. The addition of the water reducer alters the surface pore distribution, wherein "uniform small pores" change to "localized large pores." Based on the multi-objective optimization of Matlab, the recommended optimal mix composition for a slow-setting cement slurry is a water-cement ratio of 0.25 and water-reducer dosage of 1.5%. With the use of this optimized mix composition, the stone content and compressive strength increase by 7.8% and 145.6%, respectively, compared to those obtained using the recommended mix ratio in the specifications. Additionally, all relevant performance parameters meet the requirements specified by previous standards.

Design principles for NASICON super-ionic conductors.

Na Super Ionic Conductor (NASICON) materials are an important class of solid-state electrolytes owing to their high ionic conductivity and superior chemical and electrochemical stability. In this paper, we combine first-principles calculations, experimental synthesis and testing, and natural language-driven text-mined historical data on NASICON ionic conductivity to achieve clear insights into how chemical composition influences the Na-ion conductivity. These insights, together with a high-throughput first-principles analysis of the compositional space over which NASICONs are expected to be stable, lead to the successful synthesis and electrochemical investigation of several new NASICONs solid-state conductors. Among these, a high ionic conductivity of 1.2 mS cm-1 could be achieved at 25 °C. We find that the ionic conductivity increases with average metal size up to a certain value and that the substitution of PO4 polyanions by SiO4 also enhances the ionic conductivity. While optimal ionic conductivity is found near a Na content of 3 per formula unit, the exact optimum depends on other compositional variables. Surprisingly, the Na content enhances the ionic conductivity mostly through its effect on the activation barrier, rather than through the carrier concentration. These deconvoluted design criteria may provide guidelines for the design of optimized NASICON conductors.