SIRT3: A potential therapeutic target for liver fibrosis.

Sirtuin3 (SIRT3) is a nicotinamide adenine dinucleotide (NAD+)-dependent protein deacetylase located in the mitochondria, which mainly regulates the acetylation of mitochondrial proteins. In addition, SIRT3 is involved in critical biological processes, including oxidative stress, inflammation, DNA damage, and apoptosis, all of which are closely related to the progression of liver disease. Liver fibrosis characterized by the deposition of extracellular matrix is a result of long termed or repeated liver damage, frequently accompanied by damaged hepatocytes, the recruitment of inflammatory cells, and the activation of hepatic stellate cells. Based on the functions and pharmacology of SIRT3, we will review its roles in liver fibrosis from three aspects: First, the main functions and pharmacological effects of SIRT3 were investigated based on its structure. Second, the roles of SIRT3 in major cells in the liver were summarized to reveal its mechanism in developing liver fibrosis. Last, drugs that regulate SIRT3 to prevent and treat liver fibrosis were discussed. In conclusion, exploring the pharmacological effects of SIRT3, especially in the liver, may be a potential strategy for treating liver fibrosis.

Identification of HIST1H2BH as the hub gene associated with multiple myeloma using integrated bioinformatics analysis.

OBJECTIVES: Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy. METHODS: Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines. RESULTS: A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines. CONCLUSIONS: We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.

The causal relationship between genetically predicted blood metabolites and idiopathic pulmonary fibrosis: A bidirectional two-sample Mendelian randomization study.

BACKGROUND: Numerous metabolomic studies have confirmed the pivotal role of metabolic abnormalities in the development of idiopathic pulmonary fibrosis (IPF). Nevertheless, there is a lack of evidence on the causal relationship between circulating metabolites and the risk of IPF. METHODS: The potential causality between 486 blood metabolites and IPF was determined through a bidirectional two-sample Mendelian randomization (TSMR) analysis. A genome-wide association study (GWAS) involving 7,824 participants was performed to analyze metabolite data, and a GWAS meta-analysis involving 6,257 IPF cases and 947,616 control European subjects was conducted to analyze IPF data. The TSMR analysis was performed primarily with the inverse variance weighted model, supplemented by weighted mode, MR-Egger regression, and weighted median estimators. A battery of sensitivity analyses was performed, including horizontal pleiotropy assessment, heterogeneity test, Steiger test, and leave-one-out analysis. Furthermore, replication analysis and meta-analysis were conducted with another GWAS dataset of IPF containing 4,125 IPF cases and 20,464 control subjects. Mediation analyses were used to identify the mediating role of confounders in the effect of metabolites on IPF. RESULTS: There were four metabolites associated with the elevated risk of IPF, namely glucose (odds ratio [OR] = 2.49, 95% confidence interval [95%CI] = 1.13-5.49, P = 0.024), urea (OR = 6.24, 95% CI = 1.77-22.02, P = 0.004), guanosine (OR = 1.57, 95%CI = 1.07-2.30, P = 0.021), and ADpSGEGDFXAEGGGVR (OR = 1.70, 95%CI = 1.00-2.88, P = 0.0496). Of note, the effect of guanosine on IPF was found to be mediated by gastroesophageal reflux disease. Reverse Mendelian randomization analysis displayed that IPF might slightly elevate guanosine levels in the blood. CONCLUSION: Conclusively, hyperglycemia may confer a promoting effect on IPF, highlighting that attention should be paid to the relationship between diabetes and IPF, not solely to the diagnosis of diabetes. Additionally, urea, guanosine, and ADpSGEGDFXAEGGGVR also facilitate the development of IPF. This study may provide a reference for analyzing the potential mechanism of IPF and carry implications for the prevention and treatment of IPF.

Flexible High Lithium-Ion Conducting PEO-Based Solid Polymer Electrolyte with Liquid Plasticizers for High Performance Solid-State Lithium Batteries.

Lithium-ion secondary batteries (LIB) with high energy density have attracted much attention for electric vehicle (EV) applications. However, LIBs have a safety problem because these batteries contain a flammable organic electrolyte. As such, all-solid secondary batteries that are not flammable have been extensively reported recently. In this study, we have focused on polymer electrolytes, which is flexible and is expected to address the safety problem. However, the conventional polymer electrolytes have low electrial conductivity at room temperature. Various attempts have been made to solve this problem, such as the addition of inorganic fillers and ionic liquids; however, these composite polymer electrolytes have not yet reached a practical level of lithium-ion conductivity. In this study, high electrical conductivity and lithium dendrite formation-free PEO based composite electrolytes are developed with both a filler of Li6,4La3Zr1.4Ta0.6O12 and liquid plasticizers of tetraethylene glycol dimethyl ether and 1,2 dimethoxyethane. The proposed flexible polymer electrolyte shows a high electrical conduciviy of 6.01×10-4 S cm-1 at 25 °C.

[Effect of Polyethylene Microplastics on the Microbial Community of Saline Soils].

Mulching to conserve moisture has become an important agronomic practice in saline soil cultivation, and the effects of the dual stress of salinity and microplastics on soil microbes are receiving increasing attention. In order to investigate the effect of polyethylene microplastics on the microbial community of salinized soils, this study investigated the effects of different types (chloride and sulphate) and concentrations (weak, medium, and strong) of polyethylene (PE) microplastics (1% and 4% of the dry weight mass of the soil sample) on the soil microbial community by simulating microplastic contamination in salinized soil environments indoors. The results showed that:PE microplastics reduced the diversity and abundance of microbial communities in salinized soils and were more strongly affected by sulphate saline soil treatments. The relative abundance of each group of bacteria was more strongly changed in the sulphate saline soil treatment than in the chloride saline soil treatment. At the phylum level, the relative abundance of Proteobacteria was positively correlated with the abundance of fugitive PE microplastics, whereas the relative abundances of Bacteroidota, Actinobacteriota, and Acidobacteria were negatively correlated with the abundance of fugitive PE microplastics. At the family level, the relative abundances of Flavobacteriaceae, Alcanivoracaceae, Halomonadaceae, and Sphingomonasceae increased with increasing abundance of PE microplastics. The KEGG metabolic pathway prediction showed that the relative abundance of microbial metabolism and genetic information functions were reduced by the presence of PE microplastics, and the inhibition of metabolic functions was stronger in sulphate saline soils than in chloride saline soils, whereas the inhibition of genetic information functions was weaker than that in chloride saline soils. The secondary metabolic pathways of amino acid metabolism, carbohydrate metabolism, and energy metabolism were inhibited. It was hypothesized that the reduction in metabolic functions may have been caused by the reduced relative abundance of the above-mentioned secondary metabolic pathways. This study may provide a theoretical basis for the study of the effects of microplastics and salinization on the soil environment under the dual pollution conditions.

Dynamics of cavitation bubbles in viscous liquids in a tube during a transient process.

We experimentally, numerically, and theoretically investigate the dynamics of cavitation bubbles in viscous liquids in a tube during a transient process. In experiments, cavitation bubbles are generated by a modified tube-arrest setup, and the bubble evolution is captured with high-speed imaging. Numerical simulations using OpenFOAM are employed to validate our quasi-one-dimensional theoretical model, which effectively characterizes the bubble dynamics. We find that cavitation onset is minimally affected by the liquid viscosity. However, once cavitation occurs, various aspects of bubble dynamics, such as the maximum bubble length, bubble lifetime, collapse time, and collapse speed, are closely related to the liquid viscosity. We further establish that normalized bubble dynamics are solely determined by the combination of the Reynolds number and the Euler number. Moreover, we also propose a new dimensionless number, Ca2, to predict the maximum bubble length, a critical factor in determining the occurrence of liquid column separation.

Flexible Indoor Perovskite Solar Cells by In Situ Bottom-Up Crystallization Modulation and Interfacial Passivation.

A robust perovskite-buried interface is pivotal for achieving high-performance flexible indoor photovoltaics as it significantly influences charge transport and extraction efficiency. Herein, a molecular bridge strategy is introduced utilizing sodium 2-cyanoacetate (SZC) additive at the perovskite-buried interface to simultaneously achieve in situ passivation of interfacial defects and bottom-up crystallization modulation, resulting in high-performance flexible indoor photovoltaic applications. Supported by both theoretical calculations and experimental evidences, it illustrates how SZCs serve as molecular bridges, establishing robust bonds between SnO2 transport layer and perovskite, mitigating oxygen vacancy defects and under-coordinated Pb defects at interface during flexible fabrication. This, in turn, enhances interfacial energy level alignment and facilitates efficient carrier transport. Moreover, this in situ investigation of perovskite crystallization dynamics reveals bottom-up crystallization modulation, extending perovskite growth at the buried interface and influencing subsequent surface recrystallization. This results in larger crystalline grains and improved lattice strain of the perovskite during flexible fabrication. Finally, the optimized flexible solar cells achieve an impressive efficiency exceeding 41% at 1000 lux, with a fill factor as high as 84.32%. The concept of the molecular bridge represents a significant advancement in enhancing the performance of perovskite-based flexible indoor photovoltaics for the upcoming era of Internet of Things (IoT).

Hierarchical Polyimide Microparticles with Controllable Morphology.

Hierarchical polyimides (PIs) not only show outstanding thermal stability and high mechanical strength but also have great advantages in terms of microstructure and surface area, which makes them highly valuable in various fields such as aerospace, microelectronics, adsorption, catalysis, and energy storage. However, great challenges still remain in the synthesis of hierarchical PIs with well-defined microstructure. Herein, polyamide acid salts (PAAS) with tunable ionization degree are synthesized first via the polymerization of dianhydride and diamine monomers in deionized water with 1,2-dimethylimidazole (DMIZ). Then cationic cetyltrimethylammonium chloride (CTAC) is added to the PAAS aqueous solution to induce the formation of polyelectrolyte-surfactant complexes based on electrostatic interaction. After a typical hydrothermal reaction (HTR) procedure, hierarchical PIs with different microstructures such as urchin-like PI microparticles, flower-like PI microparticles, and lamellar PI petals can be fabricated simply by changing the additive amount of DMIZ and CTAC. The nanostructure self-assemblies of PAAS are dominated by the charges on macromolecular chains and the formation of hierarchical structures of polymers is ascribed to a geometrical selection process during crystal growth. This work provides valuable insights into the self-assembly behaviors of polyelectrolyte systems for synthesizing well-defined hierarchical polymers.

Machine learning-based identification of colorectal advanced adenoma using clinical and laboratory data: a phase I exploratory study in accordance with updated World Endoscopy Organization guidelines for noninvasive colorectal cancer screening tests.

Objective: The recent World Endoscopy Organization (WEO) guidelines now recognize precursor lesions of colorectal cancer (CRC) as legitimate screening targets. However, an optimal screening method for detecting advanced adenoma (AA), a significant precursor lesion, remains elusive. Methods: We employed five machine learning methods, using clinical and laboratory data, to develop and validate a diagnostic model for identifying patients with AA (569 AAs vs. 3228 controls with normal colonoscopy). The best-performing model was selected based on sensitivity and specificity assessments. Its performance in recognizing adenoma-carcinoma sequence was evaluated in line with guidelines, and adjustable thresholds were established. For comparison, the Fecal Occult Blood Test (FOBT) was also selected. Results: The XGBoost model demonstrated superior performance in identifying AA, with a sensitivity of 70.8% and a specificity of 83.4%. It successfully detected 42.7% of non-advanced adenoma (NAA) and 80.1% of CRC. The model-transformed risk assessment scale provided diagnostic performance at different positivity thresholds. Compared to FOBT, the XGBoost model better identified AA and NAA, however, was less effective in CRC. Conclusion: The XGBoost model, compared to FOBT, offers improved accuracy in identifying AA patients. While it may not meet the recommendations of some organizations, it provides value for individuals who are unable to use FOBT for various reasons.

Atomic-Resolution In Situ Exploration of the Phase Transition Triggered Failure in a Single-Crystalline Ni-Rich Cathode.

Single-crystalline cathode materials LiNixCoyMn1-y-zO2 (x ≥ 0.6) are important candidates for obtaining better cyclic stability and achieving high energy densities of Li-ion batteries. However, it is liable to initiate phase transitions inside the grains during electrochemical cycling, and the processes and regions of these phase transitions have remained unknown. In this research, we conducted an intrinsic study, investigating the chemicals and microstructural evolution of single-crystalline LiNi0.83Co0.11Mn0.06O2 using in situ biasing transmission electron microscopy at an atomic scale. We observed that the layered structure on the surface of the single-crystalline material was degraded during the charging process, resulting in continuous phase transitions and the formation of surface oxygen vacancies, which can reduce both the structural and thermal stability of the material. Uneven delithiation led to the formation of high-density defects and discontinuous inactive electrochemical phases, such as local antiphase boundaries and the rock salt phase, in the bulk of the material. The non-uniformity of the structure and the coexistence of active and inactive phases introduce significant tensile stress, which can lead to intragranular cracks inside the grains. As the number of cycles increases, the structural degradation caused by the intragranular phase transition will further increase, ultimately affecting the cycling capacity and stability of the battery. This work has broad implications for creating lithium-ion batteries that are effective and long-lasting.

Immune signatures predict response to house dust mite subcutaneous immunotherapy in patients with allergic rhinitis.

BACKGROUND: Identifying predictive biomarkers for allergen immunotherapy response is crucial for enhancing clinical efficacy. This study aims to identify such biomarkers in patients with allergic rhinitis (AR) undergoing subcutaneous immunotherapy (SCIT) for house dust mite allergy. METHODS: The Tongji (discovery) cohort comprised 72 AR patients who completed 1-year SCIT follow-up. Circulating T and B cell subsets were characterized using multiplexed flow cytometry before SCIT. Serum immunoglobulin levels and combined symptom and medication score (CSMS) were assessed before and after 12-month SCIT. Responders, exhibiting ≥30% CSMS improvement, were identified. The random forest algorithm and logistic regression analysis were used to select biomarkers and establish predictive models for SCIT efficacy in the Tongji cohort, which was validated in another Wisco cohort with 43 AR patients. RESULTS: Positive SCIT response correlated with higher baseline CSMS, allergen-specific IgE (sIgE)/total IgE (tIgE) ratio, and frequencies of Type 2 helper T cells, Type 2 follicular helper T (TFH 2) cells, and CD23+ nonswitched memory B (BNSM ) and switched memory B (BSM ) cells, as well as lower follicular regulatory T (TFR ) cell frequency and TFR /TFH 2 cell ratio. The random forest algorithm identified sIgE/tIgE ratio, TFR /TFH 2 cell ratio, and BNSM frequency as the key biomarkers discriminating responders from nonresponders in the Tongji cohort. Logistic regression analysis confirmed the predictive value of a combination model, including sIgE/tIgE ratio, TFR /TFH 2 cell ratio, and CD23+ BSM frequency (AUC = 0.899 in Tongji; validated AUC = 0.893 in Wisco). CONCLUSIONS: A T- and B-cell signature combination efficiently identified SCIT responders before treatment, enabling personalized approaches for AR patients.

Extraction techniques, structural features and biological functions of Hippophae rhamnoides polysaccharides: A review.

Hippophae rhamnoides L. (sea buckthorn) is a type of traditional Chinese medicine with a long history of clinical application. It is used in the improvement and treatment of various diseases as medicine and food to strengthen the stomach and digestion, relieving cough and resolving phlegm, promoting blood circulation, and resolving blood stasis in traditional Chinese medicine. Emerging evidence has shown that H. rhamnoides polysaccharides (HRPs) are vital bioactive macromolecules responsible for its various health benefits. HRPs possess the huge potential to develop a drug improving or treating different diseases. In this review, we comprehensively and systematically summarize the recent information on extraction and purification methods, structural features, biological activities, structure-activity relationships, and potential industry applications of HRPs and further highlight the therapeutic potential and sanitarian functions of HRPs in the fields of therapeutic agents and functional food development. Additionally, this paper also lists a variety of biological activities of HRPs in vitro and in vivo roundly. Finally, this paper also discusses the structure-activity relationships and potential applications of HRPs. Overall, this work will help to have a better in-depth understanding of HRPs and provide a scientific basis and direct reference for more scientific and rational applications.

Status and Prospects of Research on Deep Learning-based De Novo Generation of Drug Molecules.

Traditional molecular de novo generation methods, such as evolutionary algorithms, generate new molecules mainly by linking existing atomic building blocks. The challenging issues in these methods include difficulty in synthesis, failure to achieve desired properties, and structural optimization requirements. Advances in deep learning offer new ideas for rational and robust de novo drug design. Deep learning, a branch of machine learning, is more efficient than traditional methods for processing problems, such as speech, image, and translation. This study provides a comprehensive overview of the current state of research in de novo drug design based on deep learning and identifies key areas for further development. Deep learning-based de novo drug design is pivotal in four key dimensions. Molecular databases form the basis for model training, while effective molecular representations impact model performance. Common DL models (GANs, RNNs, VAEs, CNNs, DMs) generate drug molecules with desired properties. The evaluation metrics guide research directions by determining the quality and applicability of generated molecules. This abstract highlights the foundational aspects of DL-based de novo drug design, offering a concise overview of its multifaceted contributions. Consequently, deep learning in de novo molecule generation has attracted more attention from academics and industry. As a result, many deep learning-based de novo molecule generation types have been actively proposed.

Repeated misdiagnosis of small intestine bronchogenic cyst: a case report.

Bronchogenic cysts are uncommon congenital malformations of the respiratory system. These cysts can be categorized as intrapulmonary, mediastinal, or ectopic. Ectopic bronchogenic cysts, which lack distinctive clinical and imaging features, are particularly challenging to diagnose. This study presents a 48-year-old woman having a small intestinal bronchogenic cyst. She was repeatedly misdiagnosed as having an ovarian chocolate cyst or a cystic mass of bladder origin three years ago. However, no cyst was found during the operation. Half a year prior to presenting at our hospital, the patient developed frequent urination, prompting her to seek further treatment. We eventually discovered a cyst in the small intestine. The histological evaluation of the specimen showed a bronchogenic cyst. Small intestine bronchogenic cysts are extremely rare and easily misdiagnosed. It should be considered as one of the differential diagnoses of pelvic cysts. Particularly, when intraoperative exploration of the pelvic cavity fails to detect any cysts, consideration should be given to the possibility of small intestine bronchogenic cysts.

Research Progress in Tumor Diagnosis Based on Raman Spectroscopy.

BACKGROUND: Cancer is a major disease that threatens human life and health. Raman spectroscopy can provide an effective detection method. OBJECTIVE: The study aimed to introduce the application of Raman spectroscopy to tumor detection. We have introduced the current mainstream Raman spectroscopy technology and related application research. METHODS: This article has first introduced the grim situation of malignant tumors in the world. The advantages of tumor diagnosis based on Raman spectroscopy have also been analyzed. Secondly, various Raman spectroscopy techniques applied in the medical field are introduced. Several studies on the application of Raman spectroscopy to tumors in different parts of the human body are discussed. Then the advantages of combining deep learning with Raman spectroscopy in the diagnosis of tumors are discussed. Finally, the related problems of tumor diagnosis methods based on Raman spectroscopy are pointed out. This may provide useful clues for future work. CONCLUSION: Raman spectroscopy can be an effective method for diagnosing tumors. Moreover, Raman spectroscopy diagnosis combined with deep learning can provide more convenient and accurate detection results.

Sr4Al2O7: A New Sacrificial Layer with High Water Dissolution Rate for the Synthesis of Freestanding Oxide Membranes.

Freestanding perovskite oxide membranes have drawn great attention recently since they offer exceptional structural tunability and stacking ability, providing new opportunities in fundamental research and potential device applications in silicon-based semiconductor technology. Among different types of sacrificial layers, the (Ca, Sr, Ba)3Al2O6 compounds are most widely used since they can be dissolved in water and prepare high-quality perovskite oxide membranes with clean and sharp surfaces and interfaces; However, the typical transfer process takes a long time (up to hours) in obtaining millimeter-size freestanding membranes, let alone realize wafer-scale samples with high yield. Here, a new member of the SrO-Al2O3 family, Sr4Al2O7 is introduced, and its high dissolution rate, ≈10 times higher than that of Sr3Al2O6 is demonstrated. The high-dissolution-rate of Sr4Al2O7 is most likely related to the more discrete Al-O networks and higher concentration of water-soluble Sr-O species in this compound. This work significantly facilitates the preparation of freestanding membranes and sheds light on the integration of multifunctional perovskite oxides in practical electronic devices.

Revision of NMR assignment for Morin-3-O-glucoside and microbial production of Morin-2'-O-glucoside.

Morin is a flavonol having 2',4'-dihydroxy group on B-ring identified especially in Moraceae plants. While morin is widely known, its glycosides are relatively rare. To the best of our knowledge, morin-3-O-glucoside (1) was first reported in 2008. However, the reported chemical shift values of 1 were unsatisfactory with those of the aglycone, morin, which is rather similar to quercetin-3-O-glucoside (2). Therefore, we prepared morin-3-O-glucoside (1) by microbial transformation of morin with Cunninghamella sp., and the NMR assignment was reinvestigated. The microbial culture also produced another compound (3). The NMR and MS analyses of 3 revealed it as a novel compound, morin-2'-O-glucoside (3).In this study, the revision of the NMR assignment of morin-3-O-glucoside (1), and the preparation and structural elucidation of a novel compound, morin-2'-O-glucoside (3), were described.

Preparation of reed fibers reinforced graft-modified starch-based adhesives based on quantum mechanical simulation and molecular dynamics simulation.

Starch is a biomass polymer material with a high yield and comprehensive source. It is used as a raw material for preparing adhesives because of its highly active hydroxyl group. However, poor adhesion and water resistance hinder the application of starch-based adhesives (SBAs). Based on this, the starch was modified through graft copolymerization with itaconic acid as a cross-linking agent, methyl methacrylate and methyl acrylate as copolymers. Additionally, reed fibers were synergistically modified with polydopamine deposition to prepare an environmentally friendly SBA used in plywood production. Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance spectroscopy (1H NMR), X-ray diffraction (XRD), and thermogravimetric analysis (TG) demonstrate that copolymerization of methyl methacrylate and methyl acrylate with starch improves the shear strength, water resistance, and thermal stability of the SBA. Compared to unmodified starch, the modified SBA exhibits a 129 % increase in dry strength and achieves a wet strength of 1.36 MPa. Fukui function, Frontier orbit theory, and molecular dynamics simulation have shown that itaconic acid promotes the copolymerization of starch and acrylate monomers. The modified starch has fewer hydrogen bonds, less order, and a denser macromolecular network structure, which provides a reference for studying the molecular interaction mechanisms of SBAs.

Cisplatin and doxorubicin chemotherapy alters gut microbiota in a murine osteosarcoma model.

The gut microbiota is closely associated with tumor progression and treatment in a variety of cancers. However, the alteration of the gut microbiota during the progression and chemotherapy of osteosarcoma remains poorly understood. This study aimed to explore the relationship between dysbiosis in the gut microbiota during osteosarcoma growth and chemotherapy treatment. We used BALB/c nude mice to establish osteosarcoma xenograft tumor models and administered cisplatin (CDDP) or doxorubicin (DOX) intraperitonially once every 2 days for a total of 5 times to establish effective chemotherapy models. Fecal samples were collected and processed for 16S rRNA sequencing to analyze the composition of the gut microbiota. We observed that the abundances of Colidextribacter, Lachnospiraceae_NK4A136_group, Lachnospiraceae_UCG-010, Lachnospiraceae_UCG-006, and Lachnoclostridium decreased, and the abundances of Alloprevotella and Enterorhabdus increased in the osteosarcoma mouse model group compared to those in the control group. In addition, genera, such as Lachnoclostridium and Faecalibacterium were more abundant in chemotherapy-treated mice than those in saline-treated mice. Additionally, we observed that alterations in some genera, including Lachnoclostridium and Colidextribacter in the osteosarcoma animal model group returned to normal after CDDP or DOX treatment. Furthermore, the function of the gut microbiota was inferred through PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), which indicated that metabolism-related microbiota was highly enriched and significantly different in each group. These results indicate correlations between dysbiosis of the gut microbiota and osteosarcoma growth and chemotherapy treatment with CDDP or DOX and may provide novel avenues for the development of potential adjuvant therapies.