Association between the sarcopenia index and abnormal liver function in the adult population in the United States: a cross-sectional study.

Background: The objective of this study was to explore the association between the sarcopenia index and abnormal liver function in adult individuals in the United States. Methodology: This study employed a rigorous cross-sectional analysis of data derived from the National Health and Nutrition Examination Survey (NHANES) conducted between 2017 and 2018. The primary objective was to investigate the correlation between the sarcopenia index and abnormal liver function. To achieve this, an advanced multivariate regression model was utilized, allowing for comprehensive analysis and meticulous adjustment of relevant variables. To ensure the robustness of the findings, a visually appealing smooth curve was constructed, and a two-stage regression model was applied for validation. Additionally, a detailed gender-stratified analysis was conducted to further explore the association between the sarcopenia index and abnormal liver function within distinct subgroups. Results: Through our rigorous participant selection process, a total of 1756 individuals were included in the study. The meticulously adjusted multivariate regression model revealed a significant negative association between the sarcopenia index and abnormal liver function, with an adjusted odds ratio (OR) of 0.73 and a 95% confidence interval (CI) ranging from 0.63 to 0.86. The robustness of this association was further supported by the visually appealing smooth curve plot. Moreover, in the gender-stratified subgroup analysis, after meticulous adjustment for confounding factors, notable differences in this association emerged (males: OR = 0.8, 95% CI: 0.66-0.98; females: OR = 0.61, 95% CI: 0.47-0.79). Conclusion: This cross-sectional study yields robust evidence indicating a negative correlation between the sarcopenia index and abnormal liver function, predominantly observed among females.

A Nomogram-Based Model for Predicting the Risk of Severe Acute Cholangitis Occurrence.

Background: Acute cholangitis is a severe inflammatory disease associated with an infection of the biliary system, which can lead to complications and adverse outcomes. The existing nomogram-based risk assessment methods largely rely on a limited set of clinical features and laboratory indicators, and are mostly constructed using univariable models, which have limitations in predicting the severity. This study aims to develop a nomogram-based model that integrates multiple variables to improve risk prediction for acute cholangitis. Methods: Data were retrospectively collected from 152 patients with acute cholangitis who attended the People's Hospital of Jiangsu University between January 2019 and March 2022, and were graded as having mild to moderate versus severe cholangitis according to the 2018 Tokyo guidelines. Univariate and multivariate analyses were employed to discern independent risk factors associated with severe acute cholangitis, which were subsequently integrated into a nomogram model. The efficacy of the model was appraised by leveraging Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA). Results: Aspartate to alanine transaminase ratio (Transaminase ratio or TR), Neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), and D-dimer (DD) levels were independent risk factors for severe acute cholangitis. A nomogram model was constructed based on these 4 risk factors. ROC and calibration curves were well differentiated and calibrated. DCA had a high net gain in the range of 7% to 83%. The above model was tested internally. According to the nomogram model when patients using characteristic curve critical values were divided into a low-risk group and a high-risk group, the incidence in the high-risk group was significantly higher than in the low-risk group. Conclusion: This nomogram model may provide clinicians with an effective tool to predict the potential risk of severe acute cholangitis in patients and guide informed intervention measures and treatment decisions.

Quantum decoherence of dark pulses in optical microresonators.

Quantum fluctuations disrupt the cyclic motions of dissipative Kerr solitons (DKSs) in nonlinear optical microresonators and consequently cause timing jitter of the emitted pulse trains. This problem is translated to the performance of several applications that employ DKSs as compact frequency comb sources. Recently, device manufacturing and noise reduction technologies have advanced to unveil the quantum properties of DKSs. Here we investigate the quantum decoherence of DKSs existing in normal-dispersion microresonators known as dark pulses. By virtue of the very large material nonlinearity, we directly observe the quantum decoherence of dark pulses in an AlGaAs-on-insulator microresonator, and the underlying dynamical processes are resolved by injecting stochastic photons into the microresonators. Moreover, phase correlation measurements show that the uniformity of comb spacing of quantum-limited dark pulses is better than 1.2 × 10-16 and 2.5 × 10-13 when normalized to the optical carrier frequencies and repetition frequencies, respectively. Comparing DKSs generated in different material platforms explicitly confirms the advantages of dark pulses over bright solitons in terms of quantum-limited coherence. Our work establishes a critical performance assessment of DKSs, providing guidelines for coherence engineering of chip-scale optical frequency combs.

Detection of multiple biomarkers associated with satellite cell fate in the contused skeletal muscle of rats for wound age estimation.

From the perspective of forensic wound age estimation, experiments related to skeletal muscle regeneration after injury have rarely been reported. Here, we examined the time-dependent expression patterns of multiple biomarkers associated with satellite cell fate, including the transcription factor paired box 7 (Pax7), myoblast determination protein (MyoD), myogenin, and insulin-like growth factor (IGF-1), using immunohistochemistry, western blotting, and quantitative real-time PCR in contused skeletal muscle. An animal model of skeletal muscle contusion was established in 30 Sprague-Dawley male rats, and another five rats were employed as non-contused controls. Morphometrically, the data obtained from the numbers of Pax7 + , MyoD + , and myogenin + cells were highly correlated with the wound age. Pax7, MyoD, myogenin, and IGF-1 expression patterns were upregulated after injury at both the mRNA and protein levels. Pax7, MyoD, and myogenin protein expression levels confirmed the results of the morphometrical analysis. Additionally, the relative quantity of IGF-1 protein > 0.92 suggested a wound age of 3 to 7 days. The relative quantity of Pax7 mRNA > 2.44 also suggested a wound age of 3 to 7 days. Relative quantities of Myod1, Myog, and Igf1 mRNA expression > 2.78, > 7.80, or > 3.13, respectively, indicated a wound age of approximately 3 days. In conclusion, the expression levels of Pax7, MyoD, myogenin, and IGF-1 were upregulated in a time-dependent manner during skeletal muscle wound healing, suggesting the potential for using them as candidate biomarkers for wound age estimation in skeletal muscle.

Logistic Regression Analysis of the Mechanism of Blunt Brain Injury Inference Based on CT Images.

OBJECTIVES: To study the correlation between CT imaging features of acceleration and deceleration brain injury and injury degree. METHODS: A total of 299 cases with acceleration and deceleration brain injury were collected and divided into acceleration brain injury group and deceleration brain injury group according to the injury mechanism. Subarachnoid hemorrhage (SAH) and Glasgow coma scale (GCS), combined with skull fracture, epidural hematoma (EDH), subdural hematoma (SDH) and brain contusion on the same and opposite sides of the stress point were selected as the screening indexes. χ2 test was used for primary screening, and binary logistic regression analysis was used for secondary screening. The indexes with the strongest correlation in acceleration and deceleration injury mechanism were selected. RESULTS: χ2 test showed that skull fracture and EDH on the same side of the stress point; EDH, SDH and brain contusion on the opposite of the stress point; SAH, GCS were correlated with acceleration and deceleration injury (P<0.05). According to binary logistic regression analysis, the odds ratio (OR) of EDH on the same side of the stress point was 2.697, the OR of brain contusion on the opposite of the stress point was 0.043 and the OR of GCS was 0.238, suggesting there was statistically significant (P<0.05). CONCLUSIONS: EDH on the same side of the stress point, brain contusion on the opposite of the stress point and GCS can be used as key indicators to distinguish acceleration and deceleration injury mechanism. In addition, skull fracture on the same side of the stress point, EDH and SDH on the opposite of the stress point and SAH were relatively weak indicators in distinguishing acceleration and deceleration injury mechanism.

Automatic Identification of Brain Injury Mechanism Based on Deep Learning.

OBJECTIVES: To apply the convolutional neural network (CNN) Inception_v3 model in automatic identification of acceleration and deceleration injury based on CT images of brain, and to explore the application prospect of deep learning technology in forensic brain injury mechanism inference. METHODS: CT images from 190 cases with acceleration and deceleration brain injury were selected as the experimental group, and CT images from 130 normal brain cases were used as the control group. The above-mentioned 320 imaging data were divided into training validation dataset and testing dataset according to random sampling method. The model classification performance was evaluated by the accuracy rate, precision rate, recall rate, F1-value and AUC value. RESULTS: In the training process and validation process, the accuracy rate of the model to classify acceleration injury, deceleration injury and normal brain was 99.00% and 87.21%, which met the requirements. The optimized model was used to test the data of the testing dataset, the result showed that the accuracy rate of the model in the test set was 87.18%, and the precision rate, recall rate, F1-score and AUC of the model to recognize acceleration injury were 84.38%, 90.00%, 87.10% and 0.98, respectively, to recognize deceleration injury were 86.67%, 72.22%, 78.79% and 0.92, respectively, to recognize normal brain were 88.57%, 89.86%, 89.21% and 0.93, respectively. CONCLUSIONS: Inception_v3 model has potential application value in distinguishing acceleration and deceleration injury based on brain CT images, and is expected to become an auxiliary tool to infer the mechanism of head injury.

Probing material absorption and optical nonlinearity of integrated photonic materials.

Optical microresonators with high quality (Q) factors are essential to a wide range of integrated photonic devices. Steady efforts have been directed towards increasing microresonator Q factors across a variety of platforms. With success in reducing microfabrication process-related optical loss as a limitation of Q, the ultimate attainable Q, as determined solely by the constituent microresonator material absorption, has come into focus. Here, we report measurements of the material-limited Q factors in several photonic material platforms. High-Q microresonators are fabricated from thin films of SiO2, Si3N4, Al0.2Ga0.8As, and Ta2O5. By using cavity-enhanced photothermal spectroscopy, the material-limited Q is determined. The method simultaneously measures the Kerr nonlinearity in each material and reveals how material nonlinearity and ultimate Q vary in a complementary fashion across photonic materials. Besides guiding microresonator design and material development in four material platforms, the results help establish performance limits in future photonic integrated systems.

Neural stem cell transplantation alleviates functional cognitive deficits in a mouse model of tauopathy.

The mechanisms of the transplantation of neural stem cells (NSCs) in the treatment of Alzheimer's disease remain poorly understood. In this study, NSCs were transplanted into the hippocampal CA1 region of the rTg (tau P301L) 4510 mouse model, a tauopathy model that is thought to reflect the tau pathology associated with Alzheimer's disease. The results revealed that NSC transplantation reduced the abnormal aggregation of tau, resulting in significant improvements in the short-term memory of the tauopathy model mice. Compared with wild-type and phosphate-buffered saline (PBS)-treated mice, mice that received NSC transplantations were characterized by changes in the expression of multiple proteins in brain tissue, particularly those related to the regulation of tau aggregation or misfolding. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) function analysis revealed that these proteins were primarily enriched in pathways associated with long-term potentiation, neurogenesis, and other neurobiological processes. Changes in the expression levels of key proteins were verified by western blot assays. These data provided clues to improve the understanding of the functional capacity associated with NSC transplantation in Alzheimer's disease treatment. This study was approved by the Beijing Animal Ethics Association and Ethics Committee of Beijing Institute of Technology (approval No. SYXK-BIT-school of life science-2017-M03) in 2017.

High-performance lasers for fully integrated silicon nitride photonics.

Silicon nitride (SiN) waveguides with ultra-low optical loss enable integrated photonic applications including low noise, narrow linewidth lasers, chip-scale nonlinear photonics, and microwave photonics. Lasers are key components to SiN photonic integrated circuits (PICs), but are difficult to fully integrate with low-index SiN waveguides due to their large mismatch with the high-index III-V gain materials. The recent demonstration of multilayer heterogeneous integration provides a practical solution and enabled the first-generation of lasers fully integrated with SiN waveguides. However, a laser with high device yield and high output power at telecommunication wavelengths, where photonics applications are clustered, is still missing, hindered by large mode transition loss, non-optimized cavity design, and a complicated fabrication process. Here, we report high-performance lasers on SiN with tens of milliwatts output power through the SiN waveguide and sub-kHz fundamental linewidth, addressing all the aforementioned issues. We also show Hertz-level fundamental linewidth lasers are achievable with the developed integration techniques. These lasers, together with high-Q SiN resonators, mark a milestone towards a fully integrated low-noise silicon nitride photonics platform. This laser should find potential applications in LIDAR, microwave photonics and coherent optical communications.

Development and validation of an individualized immune prognostic model in stage I-III lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) possesses a poor prognosis even for stages I-III resected patients. Reliable prognostic biomarkers that can stratify and predict clinical outcomes for stage I-III resected LUSC patients are urgently needed. Based on gene expression of LUSC tissue samples from five public datasets, consisting of 687 cases, we developed an immune-related prognostic model (IPM) according to immune genes from ImmPort database. Then, we comprehensively analyzed the immune microenvironment and mutation burden that are significantly associated with this model. According to the IPM, patients were stratified into high- and low-risk groups with markedly distinct survival benefits. We found that patients with high immune risk possessed a higher proportion of immunosuppressive cells such as macrophages M0, and presented higher expression of CD47, CD73, SIRPA, and TIM-3. Moreover, When further stratified based on the tumor mutation burden (TMB) and risk score, patients with high TMB and low immune risk had a remarkable prolonged overall survival compared to patients with low TMB and high immune risk. Finally, a nomogram combing the IPM with clinical factors was established to provide a more precise evaluation of prognosis. The proposed immune relevant model is a promising biomarker for predicting overall survival in stage I-III LUSC. Thus, it may shed light on identifying patient subset at high risk of adverse prognosis from an immunological perspective.

Dispersive-wave induced noise limits in miniature soliton microwave sources.

Compact, low-noise microwave sources are required throughout a wide range of application areas including frequency metrology, wireless-communications and airborne radar systems. And the photonic generation of microwaves using soliton microcombs offers a path towards integrated, low noise microwave signal sources. In these devices, a so called quiet-point of operation has been shown to reduce microwave frequency noise. Such operation decouples pump frequency noise from the soliton's motion by balancing the Raman self-frequency shift with dispersive-wave recoil. Here, we explore the limit of this noise suppression approach and reveal a fundamental noise mechanism associated with fluctuations of the dispersive wave frequency. At the same time, pump noise reduction by as much as 36 dB is demonstrated. This fundamental noise mechanism is expected to impact microwave noise (and pulse timing jitter) whenever solitons radiate into dispersive waves belonging to different spatial mode families.

Shotgun metagenomics reveals both taxonomic and tryptophan pathway differences of gut microbiota in major depressive disorder patients.

BACKGROUND: The microbiota-gut-brain axis, especially the microbial tryptophan (Trp) biosynthesis and metabolism pathway (MiTBamp), may play a critical role in the pathogenesis of major depressive disorder (MDD). However, studies on the MiTBamp in MDD are lacking. The aim of the present study was to analyze the gut microbiota composition and the MiTBamp in MDD patients. METHODS: We performed shotgun metagenomic sequencing of stool samples from 26 MDD patients and 29 healthy controls (HCs). In addition to the microbiota community and the MiTBamp analyses, we also built a classification based on the Random Forests (RF) and Boruta algorithm to identify the gut microbiota as biomarkers for MDD. RESULTS: The Bacteroidetes abundance was strongly reduced whereas that of Actinobacteria was significantly increased in the MDD patients compared with the abundance in the HCs. Most noteworthy, the MDD patients had increased levels of Bifidobacterium, which is commonly used as a probiotic. Four Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K01817, K11358, K01626, K01667) abundances in the MiTBamp were significantly lower in the MDD group. Furthermore, we found a negative correlation between the K01626 abundance and the HAMD scores in the MDD group. Finally, RF classification at the genus level can achieve an area under the receiver operating characteristic curve of 0.890. CONCLUSIONS: The present findings enabled a better understanding of the changes in gut microbiota and the related Trp pathway in MDD. Alterations of the gut microbiota may have the potential as biomarkers for distinguishing MDD patients form HCs.

Shotgun metagenomics reveals both taxonomic and tryptophan pathway differences of gut microbiota in bipolar disorder with current major depressive episode patients.

BACKGROUND: The microbiome-gut-brain axis, especially the microbial tryptophan biosynthesis and metabolism pathway (MiTBamp), is closely connected to bipolar disorder with current major depressive episode (BPD). METHODS: We performed shotgun metagenomics sequencing (SMS) of faecal samples from 25 BPD patients and 28 healthy controls (HCs). Except for the microbiota taxa and MiTBamp analyses, we also built a classification model using the Random Forests (RF) and Boruta algorithm to find the microbial biomarkers for BPD. RESULTS: Compared to HCs, the phylum Bacteroidetes abundance was significantly reduced, whereas that of the Actinobacteria and Firmicutes were significantly increased in BPD patients. We also identified 38 species increased and 6 species decreased significantly in the BPD group. In the MiTBamp, we identified that two Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K00658 and K00837) were significantly lower in the BPD, and five KOs (K01696, K00382, K00626, K01667, and K03781) were significantly higher in the BPD group. We also identified significant genera and species which were closely related to these KOs. Finally, RF classification based on gut microbiota at the genus level can achieve an area under the receiver operating characteristic curve of 0.997. LIMITATIONS: The features of cross-sectional design, limited sample size, the heterogeneity of bipolar disorders, and a lack of serum/plasma tryptophan concentration measurements. CONCLUSIONS: The present findings enable a better understanding of changes in gastrointestinal microbiome and MiTBamp in BPD. Alterations of microbes may have potential as biomarkers for distinguishing the BPD patients form HCs.

The Superior Ability of Human BDCA3+ (CD141+) Dendritic Cells (DCs) to Cross-Present Antigens Derived From Necrotic Lung Cancer Cells.

Dendritic cells (DCs) play a key role in initiating and regulating the immune responses to pathogens, self-antigens, and cancers. Human blood DCs comprise a family of different subsets: plasmacytoid DCs (pDCs) and CD16+, CD1c/BDCA1+, and BDCA3+ (CD141+) myeloid DCs and possess different phenotypes and functional characteristics. Lung cancer is the most common cancer, with the highest morbidity and mortality in the world. However, which DC subset plays a leading role in the lung cancer immune responses is unclear. We reanalyzed C-type lectin domain family 9 member A (CLEC9A) and CD141 (THBD) gene expression profiles from the Cancer Genome Atlas (TCGA) database and performed the Kaplan-Meier survival analysis of overall survival for several cancers according to their expression levels. Next, we investigated the capacities of five human blood DC subsets to stimulate T cell proliferation and capture, process and (cross-) present tumor antigen. Human BDCA3+ (CD141+) DCs have a superior capacity to stimulate allogeneic CD4+T cells proliferation and induce superior Th1 response compared with other DC subsets. Interestingly, toll-like receptor (TLR) agonists have little effect on DCs to induce the proliferation of naïve CD4+ T cells, but contribute to their differentiation. Importantly, BDCA3+ (CD141+) DCs possess the most potent ability to cross-present human tumor antigen after their uptake of necrotic lung cancer cells despite their lower antigen uptake. These findings suggest that human BDCA3+ (CD141+) DCs are critical mediators of cytotoxic T lymphocyte responses against EGFR-positive lung cancer. Therefore, our findings may provide theoretical basis for the development of DC-based antitumor vaccines.

Integrated turnkey soliton microcombs.

Optical frequency combs have a wide range of applications in science and technology1. An important development for miniature and integrated comb systems is the formation of dissipative Kerr solitons in coherently pumped high-quality-factor optical microresonators2-9. Such soliton microcombs10 have been applied to spectroscopy11-13, the search for exoplanets14,15, optical frequency synthesis16, time keeping17 and other areas10. In addition, the recent integration of microresonators with lasers has revealed the viability of fully chip-based soliton microcombs18,19. However, the operation of microcombs requires complex startup and feedback protocols that necessitate difficult-to-integrate optical and electrical components, and microcombs operating at rates that are compatible with electronic circuits-as is required in nearly all comb systems-have not yet been integrated with pump lasers because of their high power requirements. Here we experimentally demonstrate and theoretically describe a turnkey operation regime for soliton microcombs co-integrated with a pump laser. We show the appearance of an operating point at which solitons are immediately generated by turning the pump laser on, thereby eliminating the need for photonic and electronic control circuitry. These features are combined with high-quality-factor Si3N4 resonators to provide microcombs with repetition frequencies as low as 15 gigahertz that are fully integrated into an industry standard (butterfly) package, thereby offering compelling advantages for high-volume production.

Chaos-assisted two-octave-spanning microcombs.

Since its invention, optical frequency comb has revolutionized a broad range of subjects from metrology to spectroscopy. The recent development of microresonator-based frequency combs (microcombs) provides a unique pathway to create frequency comb systems on a chip. Indeed, microcomb-based spectroscopy, ranging, optical synthesizer, telecommunications and astronomical calibrations have been reported recently. Critical to many of the integrated comb systems is the broad coverage of comb spectra. Here, microcombs of more than two-octave span (450 nm to 2,008 nm) is demonstrated through χ(2) and χ(3) nonlinearities in a deformed silica microcavity. The deformation lifts the circular symmetry and creates chaotic tunneling channels that enable broadband collection of intracavity emission with a single waveguide. Our demonstration introduces a new degree of freedom, cavity deformation, to the microcomb studies, and our microcomb spectral range is useful for applications in optical clock, astronomical calibration and biological imaging.

Ultra-efficient frequency comb generation in AlGaAs-on-insulator microresonators.

Recent advances in nonlinear optics have revolutionized integrated photonics, providing on-chip solutions to a wide range of new applications. Currently, state of the art integrated nonlinear photonic devices are mainly based on dielectric material platforms, such as Si3N4 and SiO2. While semiconductor materials feature much higher nonlinear coefficients and convenience in active integration, they have suffered from high waveguide losses that prevent the realization of efficient nonlinear processes on-chip. Here, we challenge this status quo and demonstrate a low loss AlGaAs-on-insulator platform with anomalous dispersion and quality (Q) factors beyond 1.5 × 106. Such a high quality factor, combined with high nonlinear coefficient and small mode volume, enabled us to demonstrate a Kerr frequency comb threshold of only ∼36 µW in a resonator with a 1 THz free spectral range, ∼100 times lower compared to that in previous semiconductor platforms. Moreover, combs with broad spans (>250 nm) have been generated with a pump power of ∼300 µW, which is lower than the threshold power of state-of the-art dielectric micro combs. A soliton-step transition has also been observed for the first time in an AlGaAs resonator.

Clinical value of MLH1-negative circulating tumor cells in lung cancer patients.

Circulating tumor cells (CTCs) serve as valuable biomarkers. However, MutL homolog 1 (MLH1)-negative CTCs and their clinical significance in lung cancer are nearly unknown.Here, bioinformatic analysis of MLH1 expression and its clinical significance was conducted using the Oncomine, Ualcan, and Kaplan-Meier plotter websites. Size-based isolation and RNA in situ hybridization assays were used to identify CTCs and evaluate MLH1 and mesenchymal marker expression in CTCs. MLH1 was downregulated in lung cancer patients. Patients with lower MLH1 expression levels had worse prognoses. In a cohort of 32 randomly selected patients with lung cancer, the patients with poorer treatment responses had more MLH1-negative CTCs. The total CTCs, MLH1-negative CTCs and mesenchymal markers-expressing CTCs levels were negatively correlated with prognosis in the lung cancer patients.Our data showed the clinical significance of MLH1 expression in lung cancer tissues. The characterization and numeration of CTCs based on the expression of MLH1 and mesenchymal markers may be a convenient approach for predicting treatment response and prognosis in lung cancer.

Similarly in depression, nuances of gut microbiota: Evidences from a shotgun metagenomics sequencing study on major depressive disorder versus bipolar disorder with current major depressive episode patients.

BACKGROUND: To probe the differences of gut microbiota among major depressive disorder (MDD), bipolar disorder with current major depressive episode (BPD) and health participants. METHODS: Thirty one MDD patients, thirty BPD patients, and thirty healthy controls (HCs) were recruited. All the faecal samples were analyzed by shotgun metagenomics sequencing. Except for routine analyses of alpha diversity, we specially designed a new indicator, the Gm coefficient, to evaluate the inequality of relative abundances of microbiota for each participant. RESULTS: The Gm coefficients are significant decreased in both MDD and BPD groups. The relative abundances of increased phyla Firmicutes and Actinobacteria and decreased Bacteroidetes were significantly in the MDD and BPD groups. At genus level, four of top five enriched genera (Bacteroides, Clostridium, Bifidobacterium, Oscillibacter and Streptococcus) were found increased significantly in the MDD and BPD groups compared with HCs. The genera Escherichia and Klebsiella showed significant changes in abundances only between the BPD and HC groups. At the species level, compared with BPD patients, MDD patients had a higher abundance of Prevotellaceae including Prevotella denticola F0289, Prevotella intermedia 17, Prevotella ruminicola, and Prevotella intermedia. Furthermore, the abundance of Fusobacteriaceae, Escherichia blattae DSM 4481 and Klebsiella oxytoca were significantly increased, whereas the Bifidobacterium longum subsp. infantis ATCC 15697 = JCM 1222 was significantly reduced in BPD group compared with MDD group. CONCLUSIONS: Our study suggested that gut microbiota may be involved in the pathogenesis of both MDD and BPD patients, and the nuances of bacteria may have the potentiality of being the biomarkers of MDD and BPD.