Exonuclease-assisted enrichment and base resolution analysis of pseudouridine in single-stranded RNA.

Pseudouridine (Ψ) is one of the most abundant RNA modifications, playing crucial roles in various biological processes. Identifying Ψ sites is vital for understanding their functions. In this study, we proposed a novel method for identifying Ψ sites with an improved signal-to-noise ratio. This method, called RNA exonuclease-assisted identification of pseudouridine sites (RIPS), combines specific CMC-labeling of Ψ sites with an exonuclease-assisted digestion strategy for the detection of Ψ sites. Utilizing exonuclease XRN1 to digest RNA strands not labeled by CMC, RIPS significantly reduces the background signal from unlabeled strands and enhances the positive signal of Ψ sites labeled by CMC, which terminates exonuclease digestion. As a result, we can enrich Ψ sites and identify them at single-base resolution. Considering the unique functions of single-stranded RNA (ssRNA), we employed RIPS to distinguish Ψ sites in single-stranded and double-stranded regions of RNA. Our results indicated that CMC could specifically label Ψ sites in ssRNA under natural conditions, enabling RIPS to selectively identify Ψ sites in ssRNA, which may facilitate the study on the functions of Ψ sites.

Female patients with hepatitis B may exhibit a reduced risk of breast cancer: A review of NHANES data.

Hepatic viral infections and breast cancer (BC) constitute major global health challenges, yet the interconnection between these hepatic infections and BC continues to be ambiguous. Conducting a comprehensive evaluation of the link between hepatitis virus infection and the incidence of BC and leveraging data from the National Health and Nutrition Examination Survey covering the period from 1999 to March 2022, we utilized logistic regression and subgroup analysis, among other methodologies, to execute a cross-sectional investigation. The univariate logistic regression analysis elucidates that individuals classified as non-Hispanic White exhibit a markedly higher incidence of BC at 2.620 (95% confidence interval [CI], 1.117-7.676; P = .045); moreover, advanced age at 1.063 (95% CI, 1.036-1.093; P < .001), elevated educational attainment at 1.962 (95% CI, 1.17-3.366; P = .012), and higher income levels at 2.835 (95% CI, 1.303-7.439; P = .017) emerge as significant predisposing factors for BC. In contrast, a greater number of live births significantly diminishes the risk of BC, reducing the incidence to 81.1% with each additional birth. Pertaining to hepatitis and vaccination status, our analysis distinctly demonstrates that only hepatitis B at 0.110 (95% CI, 0.018-0.353; P = .002) bears a significant inverse relationship with BC risk, suggesting a protective effect. The multivariate logistic regression analysis further reveals a negative association between hepatitis B infection and BC incidence, whereas hepatitis B vaccination shows a positive correlation with the disease incidence. After adjusting for all covariates, model 3 delineates odds ratios (95% CI) as follows: 0.14 (0.02-0.50; P = .009) and 1.92 (0.99-3.62; P = .046). Our investigation uncovers that within the general populace, there exists an inverse correlation between hepatitis B infection and BC incidence; in addition, the administration of the hepatitis B virus vaccine is potentially positively associated with the prevalence of BC.

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

Background and objective: Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy metal exposures and the incidence of DKD. Methods: We analyzed data from the NHANES (2005-2020), using machine learning, and cross-sectional survey. Our study also involved a bidirectional two-sample Mendelian randomization (MR) analysis. Results: Machine learning reveals correlation coefficients of -0.5059 and - 0.6510 for urinary Ba and urinary Tl with DKD, respectively. Multifactorial logistic regression implicates urinary Ba, urinary Pb, blood Cd, and blood Pb as potential associates of DKD. When adjusted for all covariates, the odds ratios and 95% confidence intervals are 0.87 (0.78, 0.98) (p = 0.023), 0.70 (0.53, 0.92) (p = 0.012), 0.53 (0.34, 0.82) (p = 0.005), and 0.76 (0.64, 0.90) (p = 0.002) in order. Furthermore, multiplicative interactions between urinary Ba and urinary Sb, urinary Cd and urinary Co, urinary Cd and urinary Pb, and blood Cd and blood Hg might be present. Among the diabetic population, the OR of urinary Tl with DKD is a mere 0.10, with a 95%CI of (0.01, 0.74), urinary Co 0.73 (0.54, 0.98) in Model 3, and urinary Pb 0.72 (0.55, 0.95) in Model 2. Restricted Cubic Splines (RCS) indicate a linear linkage between blood Cd in the general population and urinary Co, urinary Pb, and urinary Tl with DKD among diabetics. An observable trend effect is present between urinary Pb and urinary Tl with DKD. MR analysis reveals odds ratios and 95% confidence intervals of 1.16 (1.03, 1.32) (p = 0.018) and 1.17 (1.00, 1.36) (p = 0.044) for blood Cd and blood Mn, respectively. Conclusion: In the general population, urinary Ba demonstrates a nonlinear inverse association with DKD, whereas in the diabetic population, urinary Tl displays a linear inverse relationship with DKD.

Learning Causes of Functional Dynamic Targets: Screening and Local Methods.

This paper addresses the challenge of identifying causes for functional dynamic targets, which are functions of various variables over time. We develop screening and local learning methods to learn the direct causes of the target, as well as all indirect causes up to a given distance. We first discuss the modeling of the functional dynamic target. Then, we propose a screening method to select the variables that are significantly correlated with the target. On this basis, we introduce an algorithm that combines screening and structural learning techniques to uncover the causal structure among the target and its causes. To tackle the distance effect, where long causal paths weaken correlation, we propose a local method to discover the direct causes of the target in these significant variables and further sequentially find all indirect causes up to a given distance. We show theoretically that our proposed methods can learn the causes correctly under some regular assumptions. Experiments based on synthetic data also show that the proposed methods perform well in learning the causes of the target.

Adverse drug events associated with fluorouracil use in patients with metastatic colorectal cancer: a real-world pharmacovigilance study based on the FDA adverse event reporting system.

BACKGROUND: Fluorouracil (5-FU) is widely used to treat metastatic colorectal cancer (mCRC), but real-world safety data is limited. Our study aimed to evaluate 5-FU's safety profile in a large mCRC population using the FAERS database. RESEARCH DESIGN AND METHODS: We conducted disproportionality analyses to identify adverse drug events associated with 5-FU use in mCRC patients from 2004 to 2023. Subgroup analyses, gender difference analyses, and logistic regression were also performed. RESULTS: We identified 1,458 reports with 5-FU as the primary suspected drug, with males accounting for 48.8% of reports. Gastrointestinal disorders were the most common adverse event (864 cases), while pregnancy-related conditions showed the strongest signal intensity (ROR = 2.97). We found 19 preferred terms with positive signals, including ischemic hepatitis (ROR = 59.32), blood iron increased (ROR = 59.32), and stress cardiomyopathy (ROR = 51.94). Males were more susceptible to weight loss and skin toxicity. Most adverse events occurred within the first month of 5-FU administration. CONCLUSION: Our study provides a comprehensive analysis of 5-FU's safety profile in mCRC patients, helping healthcare professionals mitigate risks in clinical practice.

Untargeted Metabolome Analyses Revealed Potential Metabolic Mechanisms of Leymus chinensis in Response to Simulated Animal Feeding.

Leymus chinensis (Trin.) Tzvel., also known as the "Alkali Grass", is a major forage grass in the eastern and northeastern steppe vegetation in the Songnen Prairie. It is of great practical significance for grassland management to understand the influence of animal saliva on L. chinensis during animal feeding. In this study, we used clipping and daubing animal saliva to simulate responses to grazing by L. chinensis, and analyzed the physiological and metabolomic changes in response to simulated animal feeding. Results showed that the effects of animal saliva on physiological and metabolic processes of the treated plants produced a recovery phenomenon. Moreover, the effects of animal saliva produced a large number of differential metabolites related to several known metabolic pathways, among which the flavonoid biosynthesis pathway has undergone significant and persistent changes. We posit that the potential metabolic mechanisms of L. chinensis in response to simulated animal feeding are closely related to flavonoid biosynthesis.

Disparate External Electric Field Effect on the Adsorption and Shear Behavior of Monovalent and Trivalent Ions in Electrolyte Solution.

Reducing friction is of great interest, and an external potential applied to the friction pair can regulate lubricity. Electrochemical atomic force microscopy (EC-AFM) is used to study the tribological and adsorption behavior of monovalent and trivalent ionic solutions between charged surfaces. An opposite trend of coefficient of friction (COF) and normal force that varies with the applied electric potential is witnessed. Direct force measurements and theoretical models have disclosed that, for the NaCl solution, the negative electric field reduces the COF by increasing cation adsorption. As for LaCl3 solution, the positive electric field promotes the primary adsorption of anions on HOPG, resulting in the disappearance of the attractive ion-ion correlation between the trivalent ions, thereby reducing the COF. The shear behavior of adsorbed ions in electrolyte solution is sensitive to their valence, because of their different surface force contribution. The study further provides a framework to optimize the design of hydration lubrication.

A bisulfite-assisted and ligation-based qPCR amplification technology for locus-specific pseudouridine detection at base resolution.

Over 150 types of chemical modifications have been identified in RNA to date, with pseudouridine (Ψ) being one of the most prevalent modifications in RNA. Ψ plays vital roles in various biological processes, and precise, base-resolution detection methods are fundamental for deep analysis of its distribution and function. In this study, we introduced a novel base-resolution Ψ detection method named pseU-TRACE. pseU-TRACE relied on the fact that RNA containing Ψ underwent a base deletion after treatment of bisulfite (BS) during reverse transcription, which enabled efficient ligation of two probes complementary to the cDNA sequence on either side of the Ψ site and successful amplification in subsequent real-time quantitative PCR (qPCR), thereby achieving selective and accurate Ψ detection. Our method accurately and sensitively detected several known Ψ sites in 28S, 18S, 5.8S, and even mRNA. Moreover, pseU-TRACE could be employed to measure the Ψ fraction in RNA and explore the Ψ metabolism of different pseudouridine synthases (PUSs), providing valuable insights into the function of Ψ. Overall, pseU-TRACE represents a reliable, time-efficient and sensitive Ψ detection method.

Immune cell senescence and exhaustion promote the occurrence of liver metastasis in colorectal cancer by regulating epithelial-mesenchymal transition.

BACKGROUND: Liver metastasis (LM) stands as a primary cause of mortality in metastatic colorectal cancer (mCRC), posing a significant impediment to long-term survival benefits from targeted therapy and immunotherapy. However, there is currently a lack of comprehensive investigation into how senescent and exhausted immune cells contribute to LM. METHODS: We gathered single-cell sequencing data from primary colorectal cancer (pCRC) and their corresponding matched LM tissues from 16 mCRC patients. In this study, we identified senescent and exhausted immune cells, performed enrichment analysis, cell communication, cell trajectory, and cell-based in vitro experiments to validate the results of single-cell multi-omics. This process allowed us to construct a regulatory network explaining the occurrence of LM. Finally, we utilized weighted gene co-expression network analysis (WGCNA) and 12 machine learning algorithms to create prognostic risk model. RESULTS: We identified senescent-like myeloid cells (SMCs) and exhausted T cells (TEXs) as the primary senescent and exhausted immune cells. Our findings indicate that SMCs and TEXs can potentially activate transcription factors downstream via ANGPTL4-SDC1/SDC4, this activation plays a role in regulating the epithelial-mesenchymal transition (EMT) program and facilitates the development of LM, the results of cell-based in vitro experiments have provided confirmation of this conclusion. We also developed and validated a prognostic risk model composed of 12 machine learning algorithms. CONCLUSION: This study elucidates the potential molecular mechanisms underlying the occurrence of LM from various angles through single-cell multi-omics analysis in CRC. It also constructs a network illustrating the role of senescent or exhausted immune cells in regulating EMT.

Characterization of two novel hydrolases from Sphingopyxis sp. DBS4 for enantioselective degradation of chiral herbicide diclofop-methyl.

Diclofop-methyl, an aryloxyphenoxypropionate (AOPP) herbicide, is a chiral compound with two enantiomers. Microbial detoxification and degradation of various enantiomers is garnering immense research attention. However, enantioselective catabolism of diclofop-methyl has been rarely explored, especially at the molecular level. This study cloned two novel hydrolase genes (dcmA and dcmH) in Sphingopyxis sp. DBS4, and characterized them for diclofop-methyl degradation. DcmA, a member of the amidase superfamily, exhibits 26.1-45.9% identity with functional amidases. Conversely, DcmH corresponded to the DUF3089 domain-containing protein family (a family with unknown function), sharing no significant similarity with other biochemically characterized proteins. DcmA exhibited a broad spectrum of substrates, with preferential hydrolyzation of (R)-(+)-diclofop-methyl, (R)-(+)-quizalofop-ethyl, and (R)-(+)-haloxyfop-methyl. DcmH also preferred (R)-(+)-quizalofop-ethyl and (R)-(+)-haloxyfop-methyl degradation while displaying no apparent enantioselective activity towards diclofop-methyl. Using site-directed mutagenesis and molecular docking, it was determined that Ser175 was the fundamental residue influencing DcmA's activity against the two enantiomers of diclofop-methyl. For the degradation of AOPP herbicides, DcmA is an enantioselective amidase that has never been reported in research. This study provided novel hydrolyzing enzyme resources for the remediation of diclofop-methyl in the environment and deepened the understanding of enantioselective degradation of chiral AOPP herbicides mediated by microbes.

Long-cycling and High-voltage Solid State Lithium Metal Batteries Enabled by Fluorinated and Crosslinked Polyether Electrolytes.

Solid-state lithium metal batteries (LMBs), constructed through the in situ fabrication of polymer electrolytes, are considered a critical strategy for the next-generation battery systems with high energy density and enhanced safety. However, the constrained oxidation stability of polymers, such as the extensively utilized polyethers, limits their applications in high-voltage batteries and further energy density improvements. Herein, an in situ fabricated fluorinated and crosslinked polyether-based gel polymer electrolyte, FGPE, is presented, exhibiting a high oxidation potential (5.1 V). The fluorinated polyether significantly improves compatibility with both lithium metal and high-voltage cathode, attributed to the electron-withdrawing -CF3 group and the generated LiF-rich electrolyte/electrode interphase. Consequently, the solid-state Li||LiNi0.6Co0.2Mn0.2O2 batteries employing FGPE demonstrate exceptional cycling performances of 1000 cycles with 78 % retention, representing one of the best results ever reported for polymer electrolytes. Moreover, FGPE enables batteries to operate at 4.7 V, realizing the highest operating voltage of polyether-based batteries to date. Notably, our designed in situ FGPE provides the solid-state batteries with exceptional cycling stability even at practical conditions, including high cathode loading (21 mg cm-2) and industry-level 18650-type cylindrical cells (1.3 Ah, 500 cycles). This work provides critical insights into the development of oxidation-stable polymer electrolytes and the advancement of practical high-voltage LMBs.

Nano-PROTACs: state of the art and perspectives.

PROteolysis TArgeting Chimeras (PROTACs), as a recently identified technique in the field of new drug development, provide new concepts for disease treatment and are expected to revolutionize drug discovery. With high specificity and flexibility, PROTACs serve as an innovative research tool to target and degrade disease-relevant proteins that are not currently pharmaceutically vulnerable to eliminating their functions by hijacking the ubiquitin-proteasome system. To date, PROTACs still face the challenges of low solubility, poor permeability, off-target effects, and metabolic instability. The combination of nanotechnology and PROTACs has been explored to enhance the in vivo performance of PROTACs regarding overcoming these challenging hurdles. In this review, we summarize the latest advancements in the building-block design of PROTAC prodrug nanoparticles and provide an overview of existing/potential delivery systems and loading approaches for PROTAC drugs. Furthermore, we discuss the current status and prospects of the split-and-mix approach for PROTAC drug optimization. Additionally, the advantages and translational potentials of carrier-free nano-PROTACs and their combinational therapeutic effects are highlighted. This review aims to foster a deeper understanding of this rapidly evolving field and facilitate the progress of nano-PROTACs that will continue to push the boundaries of achieving selectivity and controlled release of PROTAC drugs.

Revealing the solid solution tendency of tungsten ions in phases of Ordinary Portland cement clinker: A study based on experiments and DFT calculations.

The collaborative utilization of solid waste through cement kiln represents a highly effective approach in the current era for harnessing solid waste resources. In this paper, density functional theory simulations is used to predict the substitution tendency of tungsten (W) in Ordinary Portland cement (OPC) clinker. By employing experimental design, X-ray diffraction testing, and element distribution spectrum analysis, the doping preference of W ions in OPC clinker was comprehensively investigated. The findings demonstrate that a minor fraction of WO3 firstly infiltrates C4AF through the substitution of Fe atoms, whereas the majority of WO3 infiltrates C3S and C2S secondly by substituting Si atoms, with negligible infiltration observed in C3A finally. The substitution of Fe with W exhibits a lower formation energy compared to other ions, thereby indicating its preference for the formation of solid solutions in C4AF. This preference is primarily determined by the overlapping distribution of WO and FeO bond order-bond length and their similar electron contributions in spatial distribution. However, it should be noted that the newly formed WO bond has weaker strength than the FeO bond, which may explain the limited solubility of W in C4AF. The in-depth investigation of these fundamental issues is expected to offer an effective approach for enhancing solubility of W in OPC clinker through increasing content of C4AF and silicate minerals, thereby providing valuable guidance for synthesizing OPC clinker using W-bearing solid wastes.

The dopamine receptor D1 inhibitor, SKF83566, suppresses GBM stemness and invasion through the DRD1-c-Myc-UHRF1 interactions.

BACKGROUND: Extensive local invasion of glioblastoma (GBM) cells within the central nervous system (CNS) is one factor that severely limits current treatments. The aim of this study was to uncover genes involved in the invasion process, which could also serve as therapeutic targets. For the isolation of invasive GBM cells from non-invasive cells, we used a three-dimensional organotypic co-culture system where glioma stem cell (GSC) spheres were confronted with brain organoids (BOs). Using ultra-low input RNA sequencing (ui-RNA Seq), an invasive gene signature was obtained that was exploited in a therapeutic context. METHODS: GFP-labeled tumor cells were sorted from invasive and non-invasive regions within co-cultures. Ui-RNA sequencing analysis was performed to find a gene cluster up-regulated in the invasive compartment. This gene cluster was further analyzed using the Connectivity MAP (CMap) database. This led to the identification of SKF83566, an antagonist of the D1 dopamine receptor (DRD1), as a candidate therapeutic molecule. Knockdown and overexpression experiments were performed to find molecular pathways responsible for the therapeutic effects of SKF83566. Finally, the effects of SKF83566 were validated in orthotopic xenograft models in vivo. RESULTS: Ui-RNA seq analysis of three GSC cell models (P3, BG5 and BG7) yielded a set of 27 differentially expressed genes between invasive and non-invasive cells. Using CMap analysis, SKF83566 was identified as a selective inhibitor targeting both DRD1 and DRD5. In vitro studies demonstrated that SKF83566 inhibited tumor cell proliferation, GSC sphere formation, and invasion. RNA sequencing analysis of SKF83566-treated P3, BG5, BG7, and control cell populations yielded a total of 32 differentially expressed genes, that were predicted to be regulated by c-Myc. Of these, the UHRF1 gene emerged as the most downregulated gene following treatment, and ChIP experiments revealed that c-Myc binds to its promoter region. Finally, SKF83566, or stable DRD1 knockdown, inhibited the growth of orthotopic GSC (BG5) derived xenografts in nude mice. CONCLUSIONS: DRD1 contributes to GBM invasion and progression by regulating c-Myc entry into the nucleus that affects the transcription of the UHRF1 gene. SKF83566 inhibits the transmembrane protein DRD1, and as such represents a candidate small therapeutic molecule for GBMs.

Single-cell RNA-Seq Elucidates the Crosstalk Between Cancer Stem Cells and the Tumor Microenvironment in Hepatocellular Carcinoma.

Background: The challenge of systemic treatment for hepatocellular carcinoma (HCC) stems from the development of drug resistance, primarily driven by the interplay between cancer stem cells (CSCs) and the tumor microenvironment (TME). However, there is a notable dearth of comprehensive research investigating the crosstalk between CSCs and stromal cells or immune cells within the TME of HCC. Methods: We procured single-cell RNA sequencing (scRNA-Seq) data from 16 patients diagnosed with HCC. Employing meticulous data quality control and cell annotation procedures, we delineated distinct CSCs subtypes and performed multi-omics analyses encompassing metabolic activity, cell communication, and cell trajectory. These analyses shed light on the potential molecular mechanisms governing the interaction between CSCs and the TME, while also identifying CSCs' developmental genes. By combining these developmental genes, we employed machine learning algorithms and RT-qPCR to construct and validate a prognostic risk model for HCC. Results: We successfully identified CSCs subtypes residing within malignant cells. Through meticulous enrichment analysis and assessment of metabolic activity, we discovered anomalous metabolic patterns within the CSCs microenvironment, including hypoxia and glucose deprivation. Moreover, CSCs exhibited aberrant activity in signaling pathways associated with lipid metabolism. Furthermore, our investigations into cell communication unveiled that CSCs possess the capacity to modulate stromal cells and immune cells through the secretion of MIF or MDK, consequently exerting regulatory control over the TME. Finally, through cell trajectory analysis, we found developmental genes of CSCs. Leveraging these genes, we successfully developed and validated a prognostic risk model (APCS, ADH4, FTH1, and HSPB1) with machine learning and RT-qPCR. Conclusions: By means of single-cell multi-omics analysis, this study offers valuable insights into the potential molecular mechanisms governing the interaction between CSCs and the TME, elucidating the pivotal role CSCs play within the TME. Additionally, we have successfully established a comprehensive clinical prognostic model through bulk RNA-Seq data.

Robot-assisted augmented reality surgical navigation based on optical tracking for mandibular reconstruction surgery.

PURPOSE: This work proposes a robot-assisted augmented reality (AR) surgical navigation system for mandibular reconstruction. The system accurately superimposes the preoperative osteotomy plan of the mandible and fibula into a real scene. It assists the doctor in osteotomy quickly and safely under the guidance of the robotic arm. METHODS: The proposed system mainly consists of two modules: the AR guidance module of the mandible and fibula and the robot navigation module. In the AR guidance module, we propose an AR calibration method based on the spatial registration of the image tracking marker to superimpose the virtual models of the mandible and fibula into the real scene. In the robot navigation module, the posture of the robotic arm is first calibrated under the tracking of the optical tracking system. The robotic arm can then be positioned at the planned osteotomy after the registration of the computed tomography image and the patient position. The combined guidance of AR and robotic arm can enhance the safety and precision of the surgery. RESULTS: The effectiveness of the proposed system was quantitatively assessed on cadavers. In the AR guidance module, osteotomies of the mandible and fibula achieved mean errors of 1.61 ± 0.62 and 1.08 ± 0.28 mm, respectively. The mean reconstruction error of the mandible was 1.36 ± 0.22 mm. In the AR-robot guidance module, the mean osteotomy errors of the mandible and fibula were 1.47 ± 0.46 and 0.98 ± 0.24 mm, respectively. The mean reconstruction error of the mandible was 1.20 ± 0.36 mm. CONCLUSIONS: The cadaveric experiments of 12 fibulas and six mandibles demonstrate the proposed system's effectiveness and potential clinical value in reconstructing the mandibular defect with a free fibular flap.

Application of a modified osteotomy and positioning integrative template system (MOPITS) based on a truncatable reconstruction model in the precise mandibular reconstruction with fibula free flap: a pilot clinical study.

BACKGROUND: Mandibular defects can greatly affect patients' appearance and functionality. The preferred method to address this issue is reconstructive surgery using a fibular flap. The current personalized guide plate can improve the accuracy of osteotomy and reconstruction, but there are still some problems such as complex design process and time-consuming. Therefore, we modified the conventional template to serve the dual purpose of guiding the mandible and fibula osteotomy and facilitating the placement of the pre-bent titanium. METHODS: The surgery was simulated preoperatively using Computer-Aided Design (CAD) technology. The template and truncatable reconstruction model were produced in the laboratory using 3D printing. After pre-bending the titanium plate according to the contour, the reconstruction model was truncated and the screw trajectory was transferred to form a modified osteotomy and positioning integrative template system (MOPITS). Next, the patient underwent a composite template-guided vascularized fibula flap reconstruction of the mandible. All cases were reviewed for the total operative time and accuracy of surgery. RESULTS: The procedures involved 2-4 fibular segments in 15 patients, averaging 3 fibular segments per procedure. The osteotomy error is 1.01 ± 1.02 mm, while the reconstruction angular error is 1.85 ± 1.69°. The preoperative and postoperative data were compared, and both p > 0.05. During the same operation, implant placement was performed on four patients, with an average operative time of 487.25 ± 60.84 min. The remaining malignant tumor patients had an average operative time of 397.18 ± 73.09 min. The average postoperative hospital stay was 12.95 ± 3.29 days. CONCLUSIONS: This study demonstrates the effectiveness of MOPITS in facilitating precise preoperative planning and intraoperative execution of fibula flap reconstruction. MOPITS represents a promising and reliable tool for reconstructive surgery, particularly for inexperienced surgeons navigating the challenges of mandible defect reconstruction.

Does proton pump inhibitors use increase risk of digestive tumors?: A 2-sample Mendelian randomization study.

The objective of this study was to explore the causal relationship between the use of proton pump inhibitors (PPIs) and 16 types of digestive system tumors. We utilized a 2-sample Mendelian randomization (MR) approach to investigate this relationship. We obtained exposure and outcome data from the UK Biobank and the Finland Biobank, respectively. The genetic data used in the analysis were derived from genome-wide association studies (GWAS) studies conducted on European populations. We screened single nucleotide polymorphisms significantly associated with the use of omeprazole, a commonly used PPIs, as instrumental variables. We then performed MR analyses using the inverse variance weighting (IVW) method, MR-Egger regression, and the weighted median method to evaluate the causal effect of omeprazole use on the 16 types of digestive system tumors. Our MR analysis revealed a significant causal relationship between the use of omeprazole and pancreatic malignancies, but not with any other types of digestive system tumors. The IVW analysis showed an odds ratio of 4.33E-05 (95%CI: [4.87E-09, 0.38], P = .03) and the MR-Egger analysis showed an odds ratio of 5.81E-11 (95%CI: [2.82E-20, 0.12], P = .04). We found no significant heterogeneity or pleiotropy, and sensitivity analysis confirmed the robustness of our results. Furthermore, statistical power calculations suggested that our findings were reliable. Conclusion The use of PPIs is a protective factor for pancreatic malignancies, but no causal relationship has been found with other digestive system tumors.

Oxeiptosis core genes and their multi-omics analysis in hepatocellular carcinoma.

Oxeiptosis is a recently discovered caspase-independent, non-inflammatory programmed cell death modality. Current studies suggest that oxeiptosis has crucial effects on biological processes in a variety of diseases. However, the mechanism of oxeiptosis in hepatocellular carcinoma (HCC) remains unclear and no relevant studies have been published. Therefore, this study is intended to investigate the mechanism and prognostic role of oxeiptosis-related genes in HCC. We explored the mechanisms and molecular phenotypes underlying the role of oxeiptosis in HCC through multi-omics analysis. Firstly, we obtained RNA-sequencing and clinical data from public database and divided the samples into trial and validation cohorts in subsequent analyses. We then screened oxeiptosis core genes (OCGs) and screened prognosis-related genes. Based on different molecular markers, we identified the molecular phenotypes of HCC, and the potential OCGs molecular mechanisms were explored. Subsequently, we construct a prognostic prediction system for HCC. Finally, we analyzed the tumor microenvironment and the immune escape phenomenon. We screened a total of 69 OCGs, most of which were prognostic risk factors for HCC. A majority of OCGs were enriched in cell cycle regulation and mitotic processes, which were related to both tumor cell proliferation and death. We identified 2 different molecular typing options with significant differences in prognosis, function, and signaling pathway enrichment between different molecular subtypes. The prognostic prediction model combined with molecular phenotypes and had a good predictive effect. Finally, we found CD4 + T-cell exhaustion in samples with specific molecular phenotypes. Through multi-omics analysis of OCGs, we not only revealed the possible molecular mechanisms of OCGs in HCC but also provided a prognostic prediction system for clinical application through molecular typing and risk scoring model. Meanwhile, we found immune escape mechanisms in HCC.

Rapid multi-task diagnosis of oral cancer leveraging fiber-optic Raman spectroscopy and deep learning algorithms.

Introduction: Oral cancer, a predominant malignancy in developing nations, represents a global health challenge with a five-year survival rate below 50%. Nonetheless, substantial reductions in both its incidence and mortality rates can be achieved through early detection and appropriate treatment. Crucial to these treatment plans and prognosis predictions is the identification of the pathological type of oral cancer. Methods: Toward this end, fiber-optic Raman spectroscopy emerges as an effective tool. This study combines Raman spectroscopy technology with deep learning algorithms to develop a portable intelligent prototype for oral case analysis. We propose, for the first time, a multi-task network (MTN) Raman spectroscopy classification model that utilizes a shared backbone network to simultaneously achieve different clinical staging and histological grading diagnoses. Results: The developed model demonstrated accuracy rates of 94.88%, 94.57%, and 94.34% for tumor staging, lymph node staging, and histological grading, respectively. Its sensitivity, specificity, and accuracy compare closely with the gold standard: routine histopathological examination. Discussion: Thus, this prototype proposed in this study has great potential for rapid, non-invasive, and label-free pathological diagnosis of oral cancer.