TULIPs decorate the three-dimensional genome of PFA ependymoma.

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

The marionette mechanism of domain-domain communication in the antagonist, agonist, and coactivator responses of the estrogen receptor.

The human estrogen receptor α (hERα) is involved in the regulation of growth, development, and tissue homeostasis. Agonists that bind to the receptor's ligand-binding domain (LBD) lead to recruitment of coactivators and the enhancement of gene expression. In contrast, antagonists bind to the LBD and block the binding of coactivators thus decreasing gene expressions. In this work, we carry out simulations using the AWSEM (Associative memory, Water mediated, Structure and Energy Model)-Suite force field along with the 3SPN.2C force field for DNA to predict the structure of hERα and study its dynamics when binding to DNA and coactivators. Using simulations of antagonist-bound hERα and agonist-bound hERα by themselves and also along with bound DNA and coactivators, principal component analyses and free energy landscape analyses capture the pathway of domain-domain communication for agonist-bound hERα. This communication is mediated through the hinge domains that are ordinarily intrinsically disordered. These disordered segments manipulate the hinge domains much like the strings of a marionette as they twist in different ways when antagonists or agonists are bound to the ligand-binding domain.

VirusPredictor: XGBoost-based software to predict virus-related sequences in human data.

MOTIVATION: Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data. RESULTS: We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150-350 (Illumina short reads), 850-950 (Sanger sequencing data), and 2000-5000 bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to >0.98 when query sequences increased from 150-350 to >850 bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. ∼1000 bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients' unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions. AVAILABILITY AND IMPLEMENTATION: www.dllab.org/software/VirusPredictor.html.

Chylomicrons Regulate Lacteal Permeability and Intestinal Lipid Absorption.

BACKGROUND: Lymphatic vessels are responsible for tissue drainage, and their malfunction is associated with chronic diseases. Lymph uptake occurs via specialized open cell-cell junctions between capillary lymphatic endothelial cells (LECs), whereas closed junctions in collecting LECs prevent lymph leakage. LEC junctions are known to dynamically remodel in development and disease, but how lymphatic permeability is regulated remains poorly understood. METHODS: We used various genetically engineered mouse models in combination with cellular, biochemical, and molecular biology approaches to elucidate the signaling pathways regulating junction morphology and function in lymphatic capillaries. RESULTS: By studying the permeability of intestinal lacteal capillaries to lipoprotein particles known as chylomicrons, we show that ROCK (Rho-associated kinase)-dependent cytoskeletal contractility is a fundamental mechanism of LEC permeability regulation. We show that chylomicron-derived lipids trigger neonatal lacteal junction opening via ROCK-dependent contraction of junction-anchored stress fibers. LEC-specific ROCK deletion abolished junction opening and plasma lipid uptake. Chylomicrons additionally inhibited VEGF (vascular endothelial growth factor)-A signaling. We show that VEGF-A antagonizes LEC junction opening via VEGFR (VEGF receptor) 2 and VEGFR3-dependent PI3K (phosphatidylinositol 3-kinase)/AKT (protein kinase B) activation of the small GTPase RAC1 (Rac family small GTPase 1), thereby restricting RhoA (Ras homolog family member A)/ROCK-mediated cytoskeleton contraction. CONCLUSIONS: Our results reveal that antagonistic inputs into ROCK-dependent cytoskeleton contractions regulate the interconversion of lymphatic junctions in the intestine and in other tissues, providing a tunable mechanism to control the lymphatic barrier.

Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA.

Bacteriophage T7 gp4 helicase has served as a model system for understanding mechanisms of hexameric replicative helicase translocation. The mechanistic basis of how nucleoside 5'-triphosphate hydrolysis and translocation of gp4 helicase are coupled is not fully resolved. Here, we used a thermodynamically benchmarked coarse-grained protein force field, Associative memory, Water mediated, Structure and Energy Model (AWSEM), with the single-stranded DNA (ssDNA) force field 3SPN.2C to investigate gp4 translocation. We found that the adenosine 5'-triphosphate (ATP) at the subunit interface stabilizes the subunit-subunit interaction and inhibits subunit translocation. Hydrolysis of ATP to adenosine 5'-diphosphate enables the translocation of one subunit, and new ATP binding at the new subunit interface finalizes the subunit translocation. The LoopD2 and the N-terminal primase domain provide transient protein-protein and protein-DNA interactions that facilitate the large-scale subunit movement. The simulations of gp4 helicase both validate our coarse-grained protein-ssDNA force field and elucidate the molecular basis of replicative helicase translocation.

fMRI-based spatio-temporal parcellations of the human brain.

PURPOSE OF REVIEW: Human brain parcellation based on functional magnetic resonance imaging (fMRI) plays an essential role in neuroscience research. By segmenting vast and intricate fMRI data into functionally similar units, researchers can better decipher the brain's structure in both healthy and diseased states. This article reviews current methodologies and ideas in this field, while also outlining the obstacles and directions for future research. RECENT FINDINGS: Traditional brain parcellation techniques, which often rely on cytoarchitectonic criteria, overlook the functional and temporal information accessible through fMRI. The adoption of machine learning techniques, notably deep learning, offers the potential to harness both spatial and temporal information for more nuanced brain segmentation. However, the search for a one-size-fits-all solution to brain segmentation is impractical, with the choice between group-level or individual-level models and the intended downstream analysis influencing the optimal parcellation strategy. Additionally, evaluating these models is complicated by our incomplete understanding of brain function and the absence of a definitive "ground truth". SUMMARY: While recent methodological advancements have significantly enhanced our grasp of the brain's spatial and temporal dynamics, challenges persist in advancing fMRI-based spatio-temporal representations. Future efforts will likely focus on refining model evaluation and selection as well as developing methods that offer clear interpretability for clinical usage, thereby facilitating further breakthroughs in our comprehension of the brain.

Rapid and Precise Diagnosis of Retroperitoneal Liposarcoma with Deep-Learned Label-Free Molecular Microscopy.

The retroperitoneal liposarcoma (RLPS) is a rare malignancy whose only curative therapy is surgical resection. However, well-differentiated liposarcomas (WDLPSs), one of its most common types, can hardly be distinguished from normal fat during operation without an effective margin assessment method, jeopardizing the prognosis severely with a high recurrence risk. Here, we combined dual label-free nonlinear optical modalities, stimulated Raman scattering (SRS) microscopy and second harmonic generation (SHG) microscopy, to image two predominant tissue biomolecules, lipids and collagen fibers, in 35 RLPSs and 34 normal fat samples collected from 35 patients. The produced dual-modal tissue images were used for RLPS diagnosis based on deep learning. Dramatically decreasing lipids and increasing collagen fibers during tumor progression were reflected. A ResNeXt101-based model achieved 94.7% overall accuracy and 0.987 mean area under the ROC curve (AUC) in differentiating among normal fat, WDLPSs, and dedifferentiated liposarcomas (DDLPSs). In particular, WDLPSs were detected with 94.1% precision and 84.6% sensitivity superior to existing methods. The ablation experiment showed that such performance was attributed to both SRS and SHG microscopies, which increased the sensitivity of recognizing WDLPS by 16.0 and 3.6%, respectively. Furthermore, we utilized this model on RLPS margins to identify the tumor infiltration. Our method holds great potential for accurate intraoperative liposarcoma detection.

Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

Suppression of DNMT2/3 by proinflammatory cytokines inhibits CtBP1/2-dependent genes to promote the occurrence of atrophic nonunion.

Failure of bone healing after fracture often results in nonunion, but the underlying mechanism of nonunion pathogenesis is poorly understood. Herein, we provide evidence to clarify that the inflammatory microenvironment of atrophic nonunion (AN) mice suppresses the expression levels of DNA methyltransferases 2 (DNMT2) and 3A (DNMT3a), preventing the methylation of CpG islands on the promoters of C-terminal binding protein 1/2 (CtBP1/2) and resulting in their overexpression. Increased CtBP1/2 acts as transcriptional corepressors that, along with histone acetyltransferase p300 and Runt-related transcription factor 2 (Runx2), suppress the expression levels of six genes involved in bone healing: BGLAP (bone gamma-carboxyglutamate protein), ALPL (alkaline phosphatase), SPP1 (secreted phosphoprotein 1), COL1A1 (collagen 1a1), IBSP (integrin binding sialoprotein), and MMP13 (matrix metallopeptidase 13). We also observe a similar phenomenon in osteoblast cells treated with proinflammatory cytokines or treated with a DNMT inhibitor (5-azacytidine). Forced expression of DNMT2/3a or blockage of CtBP1/2 with their inhibitors can reverse the expression levels of BGLAP/ALPL/SPP1/COL1A1/IBSP/MMP13 in the presence of proinflammatory cytokines. Administration of CtBP1/2 inhibitors in fractured mice can prevent the incidence of AN. Thus, we demonstrate that the downregulation of bone healing genes dependent on proinflammatory cytokines/DNMT2/3a/CtBP1/2-p300-Runx2 axis signaling plays a critical role in the pathogenesis of AN. Disruption of this signaling may represent a new therapeutic strategy to prevent AN incidence after bone fracture.

Searching for Two-Neutrino and Neutrinoless Double Beta Decay of

^{134}Xe is a candidate isotope for neutrinoless double beta decay (0νßß) search. In addition, the two-neutrino case (2νßß) allowed by the standard model of particle physics has not yet been observed. With the 656-kg natural xenon in the fiducial volume of the PandaX-4T detector, which contains 10.4% of ^{134}Xe, and its initial 94.9-day exposure, we have established the most stringent constraints on 2νßß and 0νßß of ^{134}Xe half-lives, with limits of 2.8×10^{22} yr and 3.0×10^{23} yr at 90% confidence level, respectively. The 2νßß (0νßß) limit surpasses the previously reported best result by a factor of 32 (2.7), highlighting the potential of large monolithic natural xenon detectors for double beta decay searches.

Search for Cosmic-Ray Boosted Sub-MeV Dark-Matter-Electron Scattering in PandaX-4T.

We report the first search for the elastic scatterings between cosmic-ray boosted sub-MeV dark matter (DM) and electrons in the PandaX-4T liquid xenon experiment. Sub-MeV DM particles can be accelerated by scattering with electrons in the cosmic rays and produce detectable electron recoil signals in the detector. Using the commissioning data from PandaX-4T of 0.63 tonne·year exposure, we set new constraints on DM-electron scattering cross sections for DM masses ranging from 10 eV/c^{2} to 3 keV/c^{2}.

19Fluorine-MRI Based Longitudinal Immuno-Microenvironment-Monitoring for Pancreatic Cancer.

BACKGROUND: Pancreatic cancer has a poor prognosis. Targeting Kirsten Rat Sarcoma (KRAS) mutation and its related pathways may enhance immunotherapy efficacy. While in vivo monitoring of therapeutic response and immune cell migration remains challenging, Fluorine-19 MRI (19F MRI) may allow noninvasive longitudinal imaging of immune cells. PURPOSE: Evaluating the potential of 19F MRI for monitoring changes in the tumor immune microenvironment, in response to combined SHP2/MEK inhibition. STUDY TYPE: Pre-clinical animal study. ANIMAL MODEL: Murine genetically engineered pancreatic cancer model (N = 20, both sexes). FIELD STRENGTH/SEQUENCE: 9.4-T, two-dimensional multi-slice Rapid Acquisition with Relaxation Enhancement sequence. Intravenous injection of 19F-perfluorocarbon (PFC) nanoparticles. ASSESSMENT: Upon tumor detection by conventional 1H MRI screening, 19F MRI was performed in mice 24 hours after PFC nanoparticle administration. Animals were randomly assigned to four treatment groups: allosteric Src-homology-2-containing protein tyrosine phosphatase 2 (SHP2) inhibitor SHP099, the mitogen-activated extracellular signal-regulated kinase 1/2 (MEK1/2) inhibitor Trametinib, the combination of both, or a vehicle control (4 to 6 mice each group), administered every other day per oral gavage. 1H and 19F MRI was repeated 7 days and 14 days later. Pancreatic immune cell infiltrates were analyzed by flow cytometry and multiplex immunohistofluorescence (mIHF) upon sacrifice. STATISTICAL TESTS: Independent t-tests and one-way analysis of variance. RESULTS: 19F MRI revealed continuous decrease of PFC-signals in tumors from vehicle controls (100%, 80%, and 74% on days 0, 7, and 14, respectively), contrasting with stable or increasing signals under KRAS-pathway-directed treatment. MEK inhibition showed 100%, 152%, and 84% and dual SHP2/MEK1/2 inhibition demonstrated signals of 100%, 134%, and 100% on days 0, 7, 14, respectively. mIHF analyses indicated CD11b+ macrophages/monocytes as primary contributors to the observed 19F MRI signal differences. DATA CONCLUSION: 19F MRI might provide non-invasive longitudinal estimates for abundance and spatial distribution of CD11b+ macrophages/monocytes in pancreatic cancer. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

TEMPO-Mediated Dehydrogenative Hydroxyfluoroalkylation of Arylamines with Polyfluorinated Alcohols.

An efficient 2,2,6,6-tetramethylpiperidinooxy (TEMPO)-mediated hydroxyfluoroalkylation of arylamines with polyfluorinated alcohols via a radical-triggered C(sp2)-H/C(sp3)-H dehydrogenative cross-coupling process was developed. This transformation features simple operation, high atom economy, broad substrate compatibility, and excellent regioselectivity, leading to a series of hydroxyfluoroalkylated arylamine derivatives. Importantly, these synthetic products were further used to evaluate the antitumor activity in cancer cell lines by Cell Counting Kit-8 assay and the outcomes indicated that some compounds show a potent antiproliferative effect.

Arbuscular Mycorrhizal Fungus Alleviates Charged Nanoplastic Stress in Host Plants via Enhanced Defense-Related Gene Expressions and Hyphal Capture.

Contamination of small-sized plastics is recognized as a factor of global change. Nanoplastics (NPs) can readily enter organisms and pose significant ecological risks. Arbuscular mycorrhizal (AM) fungi are the most ubiquitous and impactful plant symbiotic fungi, regulating essential ecological functions. Here, we first found that an AM fungus, Rhizophagus irregularis, increased lettuce shoot biomass by 25-100% when exposed to positively and negatively charged NPs vs control, although it did not increase that grown without NPs. The stress alleviation was attributed to the upregulation of gene expressions involving phytohormone signaling, cell wall metabolism, and oxidant scavenging. Using a root organ-fungus axenic growth system treated with fluorescence-labeled NPs, we subsequently revealed that the hyphae captured NPs and further delivered them to roots. NPs were observed at the hyphal cell walls, membranes, and spore walls. NPs mediated by the hyphae were localized at the root epidermis, cortex, and stele. Hyphal exudates aggregated positively charged NPs, thereby reducing their uptake due to NP aggregate formation (up to 5000 nm). This work demonstrates the critical roles of AM fungus in regulating NP behaviors and provides a potential strategy for NP risk mitigation in terrestrial ecosystems. Consequent NP-induced ecological impacts due to the affected AM fungi require further attention.

Accumulation of advanced glycation end products promotes atrophic nonunion incidence in mice through a CtBP1/2-dependent mechanism.

Atrophic nonunion (AN) is a complex and poorly understood pathological condition resulting from impaired fracture healing. Advanced glycation end products (AGEs) have been implicated in the pathogenesis of several bone disorders, including osteoporosis and osteoarthritis. However, the role of AGEs in the development of AN remains unclear. This study found that mice fed a high-AGE diet had a higher incidence of atrophic nonunion (AN) compared to mice fed a normal diet following tibial fractures. AGEs induced two C-terminal binding proteins (CtBPs), CtBP1 and CtBP2, which were necessary for the development of AN in response to AGE accumulation. Feeding a high-AGE diet after fracture surgery in CtBP1/2-/- and RAGE-/- (receptor of AGE) mice did not result in a significant occurrence of AN. Molecular investigation revealed that CtBP1 and CtBP2 formed a heterodimer that was recruited by histone deacetylase 1 (HDAC1) and runt-related transcription factor 2 (Runx2) to assemble a complex. The CtBP1/2-HDAC1-Runx2 complex was responsible for the downregulation of two classes of bone development and differentiation genes, including bone morphogenic proteins (BMPs) and matrix metalloproteinases (MMPs). These findings demonstrate that AGE accumulation promotes the incidence of AN in a CtBP1/2-dependent manner, possibly by modulating genes related to bone development and fracture healing. These results provide new insights into the pathogenesis of AN and suggest new therapeutic targets for its prevention and treatment.

Comparison of the Effects of Tenofovir Disoproxil Fumarate (TDF) and Tenofovir Alafenamide (TAF) on Liver Function in Patients with Hepatitis B: A Meta-analysis.

Objective: This is a meta-analysis comparing the efficacy of Tenofovir disoproxil fumarate (TDF) and Tenofovir alafenamide (TAF) in the treatment of chronic hepatitis B (CHB) so as to provide a reference for clinical medication. Methods: Relevant literature about TDF and TAF in the treatment of CHB was searched in the literature databases, and two researchers two researchers conducted independent cross-screening conducted independent cross-screening according to the inclusion and exclusion criteria. The authors, publication time, research subjects. The literature quality was evaluated by, and outcome measures of the selected literature were extracted. The literature quality was evaluated using the Jadad scale and Cochrane risk-of-bias tool. Meta-analysis was conducted using the RevMan 5.3 software. Results: After screening, 5 references were included, with a total of 5324 subjects. Patients who were treated with TDF and TAF were included in the TDF group and TAF group, respectively. The meta-analysis showed no significant difference in viral suppression between groups after 12 months of treatment (P > .05). Still, the alanine transaminase (ALT) normalization rate was higher, and the incidence of adverse reactions was lower in TAF group versus TDF group at 12 months after treatment (P < .05). Conclusions: Both TAF and TDF are effective in the treatment of CHB, but the former is preferred due to its higher safety profile.

Magnetic graphene oxide nanocomposites induce cytotoxicity in ADSCs via GPX4 regulating ferroptosis.

Magnetic graphene oxide nanocomposites (MGO NPs) have been widely studied in biomedical applications. However, their cytotoxicity and underlying mechanisms remain unclear. In this study, the biosafety of MGO NPs was investigated, and the mechanism involved in ferroptosis was further explored. MGO can produce cytotoxicity in ADSCs, which is dependent on their concentration. Ferroptosis was involved in MGO NP-induced ADSC survival inhibition by increasing total ROS and lipid ROS accumulation as well as regulating the expression levels of ferroptosis-related genes and proteins. GPX4 played a critical role in the MGO NP-induced ADSC ferroptosis process, and overexpressing GPX4 suppressed ferroptosis to increase cell survival. This study provides a theoretical basis for the biosafety management of MGO NPs used in the field of biomedical treatment.

Generalizing Treatment Effect to a Target Population Without Individual Patient Data in a Real-World Setting.

The innovative use of real-world data (RWD) can answer questions that cannot be addressed using data from randomized clinical trials (RCTs). While the sponsors of RCTs have a central database containing all individual patient data (IPD) collected from trials, analysts of RWD face a challenge: regulations on patient privacy make access to IPD from all regions logistically prohibitive. In this research, we propose a double inverse probability weighting (DIPW) approach for the analysis sponsor to estimate the population average treatment effect (PATE) for a target population without the need to access IPD. One probability weighting is for achieving comparable distributions in confounders across treatment groups; another probability weighting is for generalizing the result from a subpopulation of patients who have data on the endpoint to the whole target population. The likelihood expressions for propensity scores and the DIPW estimator of the PATE can be written to only rely on regional summary statistics that do not require IPD. Our approach hinges upon the positivity and conditional independency assumptions, prerequisites to most RWD analysis approaches. Simulations are conducted to compare the performances of the proposed method against a modified meta-analysis and a regular meta-analysis.

Transition-Metal-Catalyzed Directed C-H Bond Functionalization with Iodonium Ylides: A Review of the Last 5 Years.

Transition-metal-catalyzed directed C-H functionalization with various carbene precursors has been widely employed for constructing a wide range of complex and diverse active molecules through metal carbene migratory insertion processes. Among various carbene precursors, iodonium ylides serve as a novel and emerging carbene precursor with features including easy accessibility, thermal stability and high activity, which have attracted great attention from organic chemists and have achieved tremendous success in organic transformation. In this review, recent progress on the application of iodonium ylides with multifunctional coupling characteristics in C-H bond activation reactions is summarized, and the potential of iodonium ylides is discussed.

Application of hyperbaric oxygen therapy in diabetic foot ulcers: A meta-analysis.

Hyperbaric oxygen therapy (HBOT) has been used in patients with diabetic foot ulcers (DFU) for many years, but its clinical efficacy is still controversial. Therefore, this study explored the efficacy of HBOT applied to DFU by means of meta-analysis. PubMed, Cochrane Library, Embase, CNKI and Wanfang databases were searched, from database inception to October 2023, and published randomised controlled trials (RCTs) of HBOT in DFU were collected. Two investigators independently screened the collected literature, extracted relevant data and assessed the quality of the literature. Review Manager 5.4 software was applied for data analysis. Twenty-nine RCTs with 1764 patients were included. According to the combined results, when compared with conventional treatment, HBOT significantly increased the complete healing rate of DFUs (46.76% vs. 24.46%, odds ratio [OR]: 2.83, 95% CI: 2.29-3.51, p < 0.00001) and decreased the amputation rate (26.03% vs. 45.00%, OR: 0.41, 95% CI: 0.18-0.95, p = 0.04), but the incidence of adverse events was significantly higher in patients (17.37% vs. 8.27%, OR: 2.49, 95% CI: 1.35-4.57, p = 0.003), whereas there was no significant difference in the mortality (6.96% vs. 12.71%, OR: 0.52, 95% CI: 0.21-1.28, p = 0.16). Our results suggest that HBOT is effective in increasing the complete healing rate and decreasing the amputation rate in patients with DFUs, but increases the incidence of adverse events, while it has no significant effect on mortality.