Effects of antidepressant on FKBP51 mRNA expression and neuroendocrine hormones in patients with panic disorder.

OBJECTIVE: The purpose of this study was to investigate the effects of escitalopram on the peripheral expression of hypothalamic-pituitary-adrenal (HPA) axis-related genes (FKBP51, HSP90, NR3C1 and POMC) and HPA-axis hormones in patients with panic disorder (PD). METHODS: Seventy-seven patients with PD were treated with escitalopram for 12 weeks. All participants were assessed for the severity of panic symptoms using the Panic Disorder Severity Scale (PDSS). The expression of HPA-axis genes was measured using real-time quantitative fluorescent PCR, and ACTH and cortisol levels were measured using chemiluminescence at baseline and after 12 weeks of treatment. RESULTS: At baseline, patients with PD had elevated levels of ACTH and cortisol, and FKBP51 expression in comparison to healthy controls (all p < 0.01). Correlation analysis revealed that FKBP51 expression levels were significantly positively related to cortisol levels and the severity of PD (all p < 0.01). Furthermore, baseline ACTH and cortisol levels, and FKBP51 expression levels were significantly reduced after 12 weeks of treatment, and the change in the PDSS score from baseline to post-treatment was significantly and positively related to the change in cortisol (p < 0.01). CONCLUSIONS: The results suggest that PD may be associated with elevated levels of ACTH and cortisol, and FKBP51 expression, and that all three biomarkers are substantially decreased in patients who have received escitalopram treatment.

An academic achievements visualization research since the 21st century: research on salvage surgery for head and neck cancer.

Background: Head and neck cancer is the 6th most common malignancy worldwide, and its incidence is still on the rise. The salvage surgery has been considered as an important treatment strategy for persistent or recurrent head and neck cancer. Therefore, we conducted a bibliometric analysis of salvage surgery for head and neck cancer since the 21st century. Methods: The literature about salvage surgery of head and neck cancer in Web of Science was searched. CiteSpace and VOSviewer were used to analyze main countries, institutions, authors, journals, subject hotspots, trends, frontiers, etc. Results: A total of 987 papers have been published since the 21st century. These publications were written by 705 authors from 425 institutions in 54 countries. The United States published 311 papers in this field and ranked first. Head & Neck was the most widely published journal. The main keyword clustering included terms such as #0 stereotactic radiotherapy (2012); #1 randomized multicenter (2007); #2 salvage surgery (2004); #3 functional outcomes (2014); #4 transoral robotic surgery (2013); #5 neck high-resolution computed tomography (2010); #6 complications (2008); #7 image guidance (2019). The current research frontiers that have been sustained are "recurrent", "risk factors", and "reirradiation". Conclusion: The current situation of the salvage surgery for head and neck cancer in clinical treatments and basic scientific research were summarized, providing new perspectives for the development of salvage surgery for head and neck cancer in the future.

Amplifying Photon Upconversion in Alloyed Nanoparticles for a Near-Infrared Photodetector.

Photon upconverison has attracted a substantial amount of interest in diverse fields due to its characteristic anti-Stokes emissions. However, obtaining intense emission under low-power laser irradiation has remained a challenge. Here we report a mechanistic design of activator-sensitizer alloyed nanoparticles to achieve bright upconversion under weak infrared irradiation. This design allows a nearest sensitizer-activator separation to facilitate efficient energy transfer that results in remarkably enhanced upconversion (>2 orders of magnitude) under 0.26 W cm-2 irradiation compared to that of the Er sublattice, and the upconversion quantum yield also shows a 20-fold increase. Interestingly, the alloyed nanoparticles exhibit a gradual change in emission color with an increase in Yb3+ content, and moreover, their emission colors can be dynamically controlled by simply modulating the excitation laser power and pulse widths. Such alloyed nanoparticles show great promise for application in a near-infrared photodetector.

Physiological and biochemical characteristics of the carbon ion beam irradiation-generated mutant strain Clostridium butyricum FZM 240 in vitro and in vivo.

Clostridium butyricum (C. butyricum) represents a new generation of probiotics, which is beneficial because of its good tolerance and ability to produce beneficial metabolites, such as short-chain fatty acids and enzymes; however, its low enzyme activity limits its probiotic efficacy. In this study, a mutant strain, C. butyricum FZM 240 was obtained using carbon ion beam irradiation, which exhibited greatly improved enzyme production and tolerance. The highest filter paper, endoglucanase, and amylase activities produced by C. butyricum FZM 240 were 125.69 U/mL, 225.82 U/ mL, and 252.28 U/mL, which were 2.58, 1.95, and 2.21-fold higher, respectively, than those of the original strain. The survival rate of the strain increased by 11.40 % and 5.60 % after incubation at 90 °C for 5 min and with simulated gastric fluid at pH 2.5 for 2 h, respectively, compared with that of the original strain. Whole-genome resequencing and quantitative real-time PCR(qRT-PCR) analysis showed that the expression of genes related to enzyme synthesis (GE000348, GE001963 and GE003123) and tolerance (GE001114) was significantly up-regulated, while that of genes related to acid metabolism (GE003450) was significantly down-regulated. On this basis, homology modeling and functional prediction of the proteins encoded by the mutated genes were performed. According to the results, the properties related to the efficacy of C. butyricum as a probiotic were significantly enhanced by carbon ion beam irradiation, which is a novel strategy for the application of Clostridium spp. as feed additives.

Enhancing extracellular monascus pigment production in submerged fermentation with engineered microbial consortia.

In this study, we investigated the impact of microbial interactions on Monascus pigment (MP) production. We established diverse microbial consortia involving Monascus purpureus and Lactobacillus fermentum. The addition of Lactobacillus fermentum (4% at 48 h) to the submerged fermentation of M. purpureus resulted in a significantly higher MP production compared to that achieved using the single-fermentation system. Co-cultivation with immobilized L. fermentum led to a remarkable increase of 59.18% in extracellular MP production, while mixed fermentation with free L. fermentum caused a significant decrease of 66.93% in intracellular MPs, contrasting with a marginal increase of 4.52% observed during co-cultivation with immobilized L. fermentum and the control group respectively. The findings indicate an evident enhancement in cell membrane permeability of M. purpureus when co-cultivated with immobilized L. fementum. Moreover, integrated transcriptomic and metabolomic analyses were conducted to elucidate the regulatory mechanisms underlying MP biosynthesis and secretion following inoculation with immobilized L. fementum, with specific emphasis on glycolysis, steroid biosynthesis, fatty acid biosynthesis, and energy metabolism.

Reactivation of herpesvirus type 6 and IgA/IgM-mediated responses to activin-A underpin long COVID, including affective symptoms and chronic fatigue syndrome.

BACKGROUND: Persistent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), reactivation of dormant viruses, and immune-oxidative responses are involved in long COVID. OBJECTIVES: To investigate whether long COVID and depressive, anxiety, and chronic fatigue syndrome (CFS) symptoms are associated with IgA/IgM/IgG to SARS-CoV-2, human herpesvirus type 6 (HHV-6), Epstein-Barr Virus (EBV), and immune-oxidative biomarkers. METHODS: We examined 90 long COVID patients and ninety healthy controls. We measured serum IgA/IgM/IgG against HHV-6 and EBV and their deoxyuridine 5'-triphosphate nucleotidohydrolase (duTPase), SARS-CoV-2, and activin-A, C-reactive protein (CRP), advanced oxidation protein products (AOPP), and insulin resistance (HOMA2-IR). RESULTS: Long COVID patients showed significant elevations in IgG/IgM-SARS-CoV-2, IgG/IgM-HHV-6, and HHV-6-duTPase, IgA/IgM-activin-A, CRP, AOPP, and HOMA2-IR. Neural network analysis yielded a highly significant predictive accuracy of 80.6% for the long COVID diagnosis (sensitivity: 78.9%, specificity: 81.8%, area under the ROC curve = 0.876); the topmost predictors were as follows: IGA-activin-A, IgG-HHV-6, IgM-HHV-6-duTPase, IgG-SARS-CoV-2, and IgM-HHV-6 (all positively) and a factor extracted from all IgA levels to all viral antigens (inversely). The top 5 predictors of affective symptoms due to long COVID were IgM-HHV-6-duTPase, IgG-HHV-6, CRP, education, IgA-activin-A (predictive accuracy of r = 0.636). The top 5 predictors of CFS due to long COVID were in descending order: CRP, IgG-HHV-6-duTPase, IgM-activin-A, IgM-SARS-CoV-2, and IgA-activin-A (predictive accuracy: r = 0.709). CONCLUSION: Reactivation of HHV-6, SARS-CoV-2 persistence, and autoimmune reactions to activin-A combined with activated immune-oxidative pathways play a major role in the pathophysiology of long COVID as well as the severity of its affective symptoms and CFS.

Covalent Organic Framework Interlayer Spacings as Perfectly Selective Artificial Proton Channels.

Biological proton channels have perfect selectivity in aqueous environment against almost all ions and molecules, a property that differs itself from other biological channels and a feature that remains challenging to realize for bulk artificial materials. The biological perfect selectivity originates from the fact that the channel has almost no free space for ion or water transport but generates a hydrogen bonded wire in the presence of protons to allow the proton hopping. Inspired by this, we used the interlayer spacings of covalent organic framework materials consisting of hydrophilic functional groups as perfectly selective artificial proton channels. The interlayer spacings are so narrow that no atoms or molecules can diffuse through. However, protons exhibit a diffusivity in the same order of magnitude as that in bulk water. Density functional theory calculations show that water molecules and the COF material form hydrogen bonded wires, allowing the proton hopping. We further demonstrate that the proton transport rate can be tuned by adjusting the acidity of the functional groups.

Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of Ki images by utilizing deep learning techniques to reduce the noise in dynamic PET images. We propose a novel denoising technique, Population-based Deep Image Prior (PDIP), which integrates population-based prior information into the optimization process of Deep Image Prior (DIP). Specifically, the population-based prior image is generated from a supervised denoising model that is trained on a prompts-matched static PET dataset comprising 100 clinical studies. The 3D U-Net architecture is employed for both the supervised model and the following DIP optimization process. We evaluated the efficacy of PDIP for noise reduction in 25%-count and 100%-count dynamic PET images from 23 patients by comparing with two other baseline techniques: the Prompts-matched Supervised model (PS) and a conditional DIP (CDIP) model that employs the mean static PET image as the prior. Both the PS and CDIP models show effective noise reduction but result in smoothing and removal of small lesions. In addition, the utilization of a single static image as the prior in the CDIP model also introduces a similar tracer distribution to the denoised dynamic frames, leading to lower Ki in general as well as incorrect Ki in the descending aorta. By contrast, as the proposed PDIP model utilizes intrinsic image features from the dynamic dataset and a large clinical static dataset, it not only achieves comparable noise reduction as the supervised and CDIP models but also improves lesion Ki predictions.

Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling.

BACKGROUND: There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery. METHODS: We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues. RESULTS: We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues. CONCLUSIONS: Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.

Potential of niacin skin flush response in adolescent depression identification and severity assessment: a case-control study.

BACKGROUND: The diagnosis of adolescent Depressive Disorder (DD) lacks specific biomarkers, posing significant challenges. This study investigates the potential of Niacin Skin Flush Response (NSFR) as a biomarker for identifying and assessing the severity of adolescent Depressive Disorder, as well as distinguishing it from Behavioral and Emotional Disorders typically emerging in childhood and adolescence(BED). METHODS: In a case-control study involving 196 adolescents, including 128 Depressive Disorder, 32 Behavioral and Emotional Disorders, and 36 healthy controls (HCs), NSFR was assessed. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9) and anxious symptoms with the Generalized Anxiety Disorder 7-item scale (GAD-7). Pearson correlation analysis determined the relationships between NSFR and the severity of depression in DD patients. Receiver Operating Characteristic (ROC) was used to identify DD from BED integrating NSFR data with clinical symptom measures. RESULTS: The adolescent Depressive Disorder group exhibited a higher rate of severe blunted NSFR (21.4%) compared to BED (12.5%) and HC ( 8.3%). Adolescent Depressive Disorder with psychotic symptoms showed a significant increase in blunted NSFR (p = 0.016). NSFR had negative correlations with depressive (r = -0.240, p = 0.006) and anxious (r = -0.2, p = 0.023) symptoms in adolescent Depressive Disorder. Integrating NSFR with three clinical scales improved the differentiation between adolescent Depressive Disorder and BED (AUC increased from 0.694 to 0.712). CONCLUSION: The NSFR demonstrates potential as an objective biomarker for adolescent Depressive Disorder, aiding in screening, assessing severity, and enhancing insights into its pathophysiology and diagnostic precision.

A comprehensive and molecular level evaluation of treated wastewater reusing via drip systems: Interactions of dissolved ions and hydraulic shear stresses on calcium carbonate scaling.

To overcome the global water shortage, the treated wastewater is increasingly utilized in agricultural irrigation, and thus reducing freshwater consumption and increasing the water sustainability. Drip irrigation technology is the most appropriate irrigation method to utilize these water sources. However, its operating performance is negatively affected by calcium carbonate (CaCO3) scaling, which is one of the most dominant precipitations and also closely related to dissolved ions and the hydraulic characteristics inside irrigation systems. Thus, the effects of eight common dissolved ions (K+, Mg2+, Mn2+, Zn2+, Fe3+, NO3-, SO42-, and PO43-) in these water sources and four hydraulic shear stresses (0, 0.2, 0.4, and 0.6 Pa) on CaCO3 scaling formation were assessed in this study. Results showed that CaCO3 scaling was primarily formed of calcite and aragonite. Fe3+ would significantly accelerate the CaCO3 scaling accumulation, as it reduced the unit cell volume and chemical bonds of calcite, enhancing calcite adhesion and stability. On the other hand, Mg2+, Mn2+, NO3-, SO42-, and PO43- significantly inhibited CaCO3 scaling. Among them, Mg2+, Mn2+, and PO43- followed the typical water chemical precipitation rule, while NO3- increased water molecule diffusion rate and thus decreased the possibility that Ca2+ and CO32- to precipitate. SO42- grabbed the binding point belonging to CO32- and was adsorbed on the calcite crystal, which inhibited crystal growth. However, those treatments under K+ and Zn2+ did not reach a significant level due to their solubleness. During the precipitation of CaCO3, there were significant (p < 0.01) interactions between dissolved ions and hydraulic shear stresses. When hydraulic shear stresses varied, the effects of Fe3+ and SO42- on the CaCO3 scaling were relatively weakened, while that of Mg2+ was relatively strengthened. In return, dissolved ions affected the effect of hydraulic shear stresses on CaCO3 scaling. Overall, the results obtained could provide theoretical reference for high-efficiency utilization of treated wastewater for agricultural irrigation through the management of CaCO3 scaling.

Autologous liver transplantation for unresectable hepatobiliary malignancies in enhanced recovery after surgery model.

Ex vivo liver resection combined with autologous liver transplantation offers the opportunity to treat otherwise unresectable hepatobiliary malignancies and has been applied in clinic. The implementation of enhanced recovery after surgery (ERAS) program improves the outcome of surgical procedures. This is a retrospective single-center study including 11 cases of patients with liver cancer that underwent autologous liver transplantation and received ERAS: cholangiocarcinoma of the hilar region (n = 5), intrahepatic cholangiocarcinoma (n = 3), gallbladder cancer (n = 1), liver metastasis from colorectal cancer (n = 1), and liver metastasis from gastrointestinal mesenchymal tumor (n = 1). There were no deaths within 30 days and major complications occurred in two patients, and four patients were readmitted upon the first month after the surgery. Median hospital stay was 20 days (range 13-44) and median open diet was Day 4 (range 2-9) after surgery and median early post-operative activity was Day 5 (range 2-9) after surgery. In conclusion, autologous liver transplantation is feasible in the treatment of otherwise unresectable hepatobiliary malignancies, and our study showed favorable results with autologous liver transplantation in ERAS modality. ERAS modality provides a good option for some patients whose tumors cannot be resected in situ and offers a chance for rapid recovery.

DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT.

Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation exposure but leads to increased image noise. Limited-view (LV) SPECT, such as the latest GE MyoSPECT ES system, enables accelerated scanning and reduces hardware expenses but degrades reconstruction accuracy. Additionally, Computed Tomography (CT) is commonly used to derive attenuation maps (µ-maps) for attenuation correction (AC) of cardiac SPECT, but it will introduce additional radiation exposure and SPECT-CT misalignments. Although various methods have been developed to solely focus on LD denoising, LV reconstruction, or CT-free AC in SPECT, the solution for simultaneously addressing these tasks remains challenging and under-explored. Furthermore, it is essential to explore the potential of fusing cross-domain and cross-modality information across these interrelated tasks to further enhance the accuracy of each task. Thus, we propose a Dual-Domain Coarse-to-Fine Progressive Network (DuDoCFNet), a multi-task learning method for simultaneous LD denoising, LV reconstruction, and CT-free µ-map generation of cardiac SPECT. Paired dual-domain networks in DuDoCFNet are cascaded using a multi-layer fusion mechanism for cross-domain and cross-modality feature fusion. Two-stage progressive learning strategies are applied in both projection and image domains to achieve coarse-to-fine estimations of SPECT projections and CT-derived µ-maps. Our experiments demonstrate DuDoCFNet's superior accuracy in estimating projections, generating µ-maps, and AC reconstructions compared to existing single- or multi-task learning methods, under various iterations and LD levels. The source code of this work is available at https://github.com/XiongchaoChen/DuDoCFNet-MultiTask.

Lactic acid induced defense responses in tobacco against Phytophthora nicotianae.

Induced resistance is considered an eco-friendly disease control strategy, which can enhance plant disease resistance by inducing the plant's immune system to activate the defense response. In recent years, studies have shown that lactic acid can play a role in plant defense against biological stress; however, whether lactic acid can improve tobacco resistance to Phytophthora nicotianae, and its molecular mechanism remains unclear. In our study, the mycelial growth and sporangium production of P. nicotianae were inhibited by lactic acid in vitro in a dose-dependent manner. Application of lactic acid could reduce the disease index, and the contents of total phenol, salicylic acid (SA), jasmonic acid (JA), lignin and H2O2, catalase (CAT) and phenylalanine ammonia-lyase (PAL) activities were significantly increased. To explore this lactic acid-induced protective mechanism for tobacco disease resistance, RNA-Seq analysis was used. Lactic acid enhances tobacco disease resistance by activating Ca2+, reactive oxygen species (ROS) signal transduction, regulating antioxidant enzymes, SA, JA, abscisic acid (ABA) and indole-3-acetic acid (IAA) signaling pathways, and up-regulating flavonoid biosynthesis-related genes. This study demonstrated that lactic acid might play a role in inducing resistance to tobacco black shank disease; the mechanism by which lactic acid induces disease resistance includes direct antifungal activity and inducing the host to produce direct and primed defenses. In conclusion, this study provided a theoretical basis for lactic acid-induced resistance and a new perspective for preventing and treating tobacco black shank disease.

Physically based simulation of focusing schlieren imaging for a hypersonic boundary layer flow.

Focusing schlieren systems are more advantageous than conventional schlieren systems in providing a schlieren image with certain spatial discrimination along the light path. The present work employed a hybrid of the optical-transfer matrix and ray-tracing method to faithfully replicate complete physical imaging processes throughout a focusing schlieren optic system. A direct numerical simulation of a hypersonic boundary layer flow was employed to synthesize focusing schlieren images. The influence of various configuration parameters on the properties of focusing schlieren image such as local schlieren structure, brightness, sensitivity, and depth of field were systematically explored. In addition, an approximation method was proposed as a simplified means to facilitate the simulation of a focusing schlieren image.

Spatiotemporal control of photochromic upconversion through interfacial energy transfer.

Dynamic control of multi-photon upconversion with rich and tunable emission colors is stimulating extensive interest in both fundamental research and frontier applications of lanthanide based materials. However, manipulating photochromic upconversion towards color-switchable emissions of a single lanthanide emitter is still challenging. Here, we report a conceptual model to realize the spatiotemporal control of upconversion dynamics and photochromic evolution of Er3+ through interfacial energy transfer (IET) in a core-shell nanostructure. The design of Yb sublattice sensitization interlayer, instead of regular Yb3+ doping, is able to raise the absorption capability of excitation energy and enhance the upconversion. We find that a nanoscale spatial manipulation of interfacial interactions between Er and Yb sublattices can further contribute to upconversion. Moreover, the red/green color-switchable upconversion of Er3+ is achieved through using the temporal modulation ways of non-steady-state excitation and time-gating technique. Our results allow for versatile designs and dynamic management of emission colors from luminescent materials and provide more chances for their frontier photonic applications such as optical anti-counterfeiting and speed monitoring.

A GraphSAGE-based model with fingerprints only to predict drug-drug interactions.

Drugs are an effective way to treat various diseases. Some diseases are so complicated that the effect of a single drug for such diseases is limited, which has led to the emergence of combination drug therapy. The use multiple drugs to treat these diseases can improve the drug efficacy, but it can also bring adverse effects. Thus, it is essential to determine drug-drug interactions (DDIs). Recently, deep learning algorithms have become popular to design DDI prediction models. However, most deep learning-based models need several types of drug properties, inducing the application problems for drugs without these properties. In this study, a new deep learning-based model was designed to predict DDIs. For wide applications, drugs were first represented by commonly used properties, referred to as fingerprint features. Then, these features were perfectly fused with the drug interaction network by a type of graph convolutional network method, GraphSAGE, yielding high-level drug features. The inner product was adopted to score the strength of drug pairs. The model was evaluated by 10-fold cross-validation, resulting in an AUROC of 0.9704 and AUPR of 0.9727. Such performance was better than the previous model which directly used drug fingerprint features and was competitive compared with some other previous models that used more drug properties. Furthermore, the ablation tests indicated the importance of the main parts of the model, and we analyzed the strengths and limitations of a model for drugs with different degrees in the network. This model identified some novel DDIs that may bring expected benefits, such as the combination of PEA and cannabinol that may produce better effects. DDIs that may cause unexpected side effects have also been discovered, such as the combined use of WIN 55,212-2 and cannabinol. These DDIs can provide novel insights for treating complex diseases or avoiding adverse drug events.

Gold Catalysis, Asymmetric Friedel-Crafts Alkylation Cascade for One-Pot Synthesis of Chiral Dihydrocarbazoles and Dihydrodibenzofurans.

A one-pot gold-catalyzed acyl migration followed by ytterbium-catalyzed asymmetric Friedel-Crafts alkylation is disclosed, leading to the rapid synthesis of chiral dihydrocarbazoles and dihydrodibenzofuran in generally moderate to good overall yields with good to excellent enantioselectivities. The gold-catalyzed acyl migration of propargyl acetates generates α-ylidene-ß-diketones with high E/Z ratios, which are then subjected to the ytterbium-catalyzed asymmetric Friedel-Crafts alkylation without any purification. Importantly, this protocol provides a new type of substrate for asymmetric Friedel-Crafts alkylation.

Differentiation route determines the functional outputs of adult megakaryopoiesis.

Emerging evidence has revealed a direct differentiation route from hematopoietic stem cells to megakaryocytes (direct route), in addition to the classical differentiation route through a series of restricted hematopoietic progenitors (stepwise route). This raises the question of the importance of two alternative routes for megakaryopoiesis. Here, we developed fate-mapping systems to distinguish the two routes, comparing their quantitative and functional outputs. We found that megakaryocytes were produced through the two routes with comparable kinetics and quantity under homeostasis. Single-cell RNA sequencing of the fate-mapped megakaryocytes revealed that the direct and stepwise routes contributed to the niche-supporting and immune megakaryocytes, respectively, but contributed to the platelet-producing megakaryocytes together. Megakaryocytes derived from the two routes displayed different activities and were differentially regulated by chemotherapy and inflammation. Our work links differentiation route to the heterogeneity of megakaryocytes. Alternative differentiation routes result in variable combinations of functionally distinct megakaryocyte subpopulations poised for different physiological demands.