Programmed cell death factor 4-mediated hippocampal synaptic plasticity is involved in early life stress and susceptibility to depression.

Early life stress (ELS) increases the risk of depression later in life. Programmed cell death factor 4 (PDCD4), an apoptosis-related molecule, extensively participates in tumorigenesis and inflammatory diseases. However, its involvement in a person's susceptibility to ELS-related depression is unknown. To examine the effects and underlying mechanisms of PDCD4 on ELS vulnerability, we used a "two-hit" stress mouse model: an intraperitoneal injection of lipopolysaccharide (LPS) into neonatal mice was performed on postnatal days 7-9 (P7-P9) and inescapable foot shock (IFS) administration in adolescent was used as a later-life challenge. Our study shows that compared with mice that were only exposed to the LPS or IFS, the "two-hit" stress mice developed more severe depression/anxiety-like behaviors and social disability. We detected the levels of PDCD4 in the hippocampus of adolescent mice and found that they were significantly increased in "two-hit" stress mice. The results of immunohistochemical staining and Sholl analysis showed that the number of microglia in the hippocampus of "two-hit" stress mice significantly increased, with morphological changes, shortened branches, and decreased numbers. However, knocking down PDCD4 can prevent the number and morphological changes of microglia induced by ELS. In addition, we confirmed through the Golgi staining and immunohistochemical staining results that knocking down PDCD4 can ameliorate ELS-induced synaptic plasticity damage. Mechanically, the knockdown of PDCD4 exerts neuroprotective effects, possibly via the mediation of BDNF/AKT/CREB signaling. Combined, these results suggest that PDCD4 may play an important role in the ELS-induced susceptibility to depression and, thus, may become a therapeutic target for depressive disorders.

PD-1 downregulation enhances CAR-T cell antitumor efficiency by preserving a cell memory phenotype and reducing exhaustion.

BACKGROUND: Despite the encouraging outcome of chimeric antigen receptor T cell (CAR-T) targeting B cell maturation antigen (BCMA) in managing relapsed or refractory multiple myeloma (RRMM) patients, the therapeutic side effects and dysfunctions of CAR-T cells have limited the efficacy and clinical application of this promising approach. METHODS: In this study, we incorporated a short hairpin RNA cassette targeting PD-1 into a BCMA-CAR with an OX-40 costimulatory domain. The transduced PD-1KD BCMA CAR-T cells were evaluated for surface CAR expression, T-cell proliferation, cytotoxicity, cytokine production, and subsets when they were exposed to a single or repetitive antigen stimulation. Safety and efficacy were initially observed in a phase I clinical trial for RRMM patients. RESULTS: Compared with parental BCMA CAR-T cells, PD-1KD BCMA CAR-T cell therapy showed reduced T-cell exhaustion and increased percentage of memory T cells in vitro. Better antitumor activity in vivo was also observed in PD-1KD BCMA CAR-T group. In the phase I clinical trial of the CAR-T cell therapy for seven RRMM patients, safety and efficacy were initially observed in all seven patients, including four patients (4/7, 57.1%) with at least one extramedullary site and four patients (4/7, 57.1%) with high-risk cytogenetics. The overall response rate was 85.7% (6/7). Four patients had a stringent complete response (sCR), one patient had a CR, one patient had a partial response, and one patient had stable disease. Safety profile was also observed in these patients, with an incidence of manageable mild to moderate cytokine release syndrome and without the occurrence of neurological toxicity. CONCLUSIONS: Our study demonstrates a design concept of CAR-T cells independent of antigen specificity and provides an alternative approach for improving the efficacy of CAR-T cell therapy.

Canonical pathways for validating steroid-associated osteonecrosis in mice.

The present study aimed to establish and evaluate a preclinical model of steroid-associated osteonecrosis (SAON) in mice. Sixteen 24-week-old male C57BL/6 mice were used to establish SAON by two intraperitoneal injections of lipopolysaccharide (LPS), followed by three subcutaneous injections of methylprednisolone (MPS). Each injection was conducted on working day, with an interval of 24 h. Six cycles of injections were conducted. Additional twelve mice (age- and gender-matched) were used as normal controls. At 2 and 6 weeks after completing induction, bilateral femora and bilateral tibiae were collected for histological examination, micro-CT scanning, and bulk RNA sequencing. All mice were alive until sacrificed at the indicated time points. The typical SAON lesion was identified by histological evaluation at week 2 and week 6 with increased lacunae and TUNEL+ osteocytes. Micro-CT showed significant bone degeneration at week 6 in SAON model. Histology and histomorphometry showed significantly lower Runx2+ area, mineralizing surface (MS/BS), mineral apposition rate (MAR), bone formation rate (BFR/BS), type H vessels, Ki67+ (proliferating) cells, and higher marrow fat fraction, osteoclast number and TNFα+ areas in SAON group. Bulk RNA-seq revealed changed canonical signaling pathways regulating cell cycle, angiogenesis, osteogenesis, and osteoclastogenesis in the SAON group. The present study successfully established SAON in mice with a combination treatment of LPS and MPS, which could be considered a reliable and reproducible animal model to study the pathophysiology and molecular mechanism of early-stage SAON and to develop potential therapeutic approaches for the prevention and treatment of SAON.

Downregulation of UBB potentiates SP1/VEGFA-dependent angiogenesis in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) presents a unique profile characterized by high levels of angiogenesis and robust vascularization. Understanding the underlying mechanisms driving this heterogeneity is essential for developing effective therapeutic strategies. This study revealed that ubiquitin B (UBB) is downregulated in ccRCC, which adversely affects the survival of ccRCC patients. UBB exerts regulatory control over vascular endothelial growth factor A (VEGFA) by directly interacting with specificity protein 1 (SP1), consequently exerting significant influence on angiogenic processes. Subsequently, we validated that DNA methyltransferase 3 alpha (DNMT3A) is located in the promoter of UBB to epigenetically inhibit UBB transcription. Additionally, we found that an unharmonious UBB/VEGFA ratio mediates pazopanib resistance in ccRCC. These findings underscore the critical involvement of UBB in antiangiogenic therapy and unveil a novel therapeutic strategy for ccRCC.

Blood culture quality and turnaround time of clinical microbiology laboratories in Chinese Teaching Hospitals: A multicenter study.

PURPOSE: Blood culture (BC) remains the gold standard for the diagnosis of bloodstream infections. Improving the quality of clinical BC samples, optimizing BC performance, and accelerating antimicrobial susceptibility test (AST) results are essential for the early detection of bloodstream infections and specific treatments. METHODS: We conducted a retrospective multicenter study using 450,845 BC specimens from clinical laboratories obtained from 19 teaching hospitals between 1 January 2021 and 31 December 2021. We evaluated key performance indicators (KPIs), turnaround times (TATs), and frequency distributions of processing in BC specimens. We also evaluated the AST results of clinically significant isolates for four different laboratory workflow styles. RESULTS: Across the 10 common bacterial isolates (n = 16,865) and yeast isolates (n = 1011), the overall median (interquartile range) TATs of AST results were 2.67 (2.05-3.31) and 3.73 (2.98-4.64) days, respectively. The specimen collections mainly occurred between 06:00 and 24:00, and specimen reception and loadings mainly between 08:00 and 24:00. Based on the laboratory workflows of the BCs, 16 of the 19 hospitals were divided into four groups. Time to results (TTRs) from specimen collection to the AST reports were 2.35 (1.95-3.06), 2.61 (1.98-3.32), 2.99 (2.60-3.87), and 3.25 (2.80-3.98) days for groups I, II, III, and IV, respectively. CONCLUSION: This study shows the related BC KPIs and workflows in different Chinese hospitals, suggesting that laboratory workflow optimization can play important roles in shortening time to AST reports and initiation of appropriate timely treatment.

Study on the Behavior of Saturated Cardanol-Based Surfactants at the Crude Oil/Water Interface through Molecular Dynamics Simulations.

Cardanol is a green biosurfactant with broad application prospects, which is expected to be used to enhance oil recovery (EOR). This paper designed two types of surfactants (extended and nonextended), including six kinds of nonionic and anion-nonionic surfactants. The position changes of PO and EO chains and the effects of different hydrophilic groups on the interface properties were studied with molecular dynamics simulations by constructing a model of crude oil (containing four components) and water molecules. The results of interfacial tension and solvent-accessible surface area showed that the interfacial properties of sulfate were better than those of sulfonates and nonionic surfactants. Meanwhile, the interface properties of nonextended surfactants were better than those of extended surfactants. The gyration radius (Rg) and tilt angle data demonstrated that when EO chains were located between hydrophobic groups and PO chains (nonextended surfactants), the adsorption capacity of surfactants at crude oil and water interfaces could be effectively improved. The radial distribution function of the hydrophilic group and hydrophobic group of surfactants with water molecules and four components of the crude oil molecule, respectively, explained that surfactants (8EO8POSO4) had better emulsification performance when the intermolecular interactions between crude oil and water two phases were relatively balanced. This study provides a theoretical reference for the design of oil-displacement surfactants and the mechanism analysis of emulsification properties.

Characterizing Soil Profile Salinization in Cotton Fields Using Landsat 8 Time-Series Data in Southern Xinjiang, China.

Soil salinization is a major obstacle to land productivity, crop yield and crop quality in arid areas and directly affects food security. Soil profile salt data are key for accurately determining irrigation volumes. To explore the potential for using Landsat 8 time-series data to monitor soil salinization, 172 Landsat 8 images from 2013 to 2019 were obtained from the Alar Reclamation Area of Xinjiang, northwest China. The multiyear extreme dataset was synthesized from the annual maximum or minimum values of 16 vegetation indices, which were combined with the soil conductivity of 540 samples from soil profiles at 0~0.375 m, 0~0.75 m and 0~1.00 m depths in 30 cotton fields with varying degrees of salinization as investigated by EM38-MK2. Three remote sensing monitoring models for soil conductivity at different depths were constructed using the Cubist method, and digital mapping was carried out. The results showed that the Cubist model of soil profile electrical conductivity from 0 to 0.375 m, 0 to 0.75 m and 0 to 1.00 m showed high prediction accuracy, and the determination coefficients of the prediction set were 0.80, 0.74 and 0.72, respectively. Therefore, it is feasible to use a multiyear extreme value for the vegetation index combined with a Cubist modeling method to monitor soil profile salinization at a regional scale.

Data-Efficient Learning via Minimizing Hyperspherical Energy.

Deep learning on large-scale data is currently dominant nowadays. The unprecedented scale of data has been arguably one of the most important driving forces behind its success. However, there still exist scenarios where collecting data or labels could be extremely expensive, e.g., medical imaging and robotics. To fill up this gap, this paper considers the problem of data-efficient learning from scratch using a small amount of representative data. First, we characterize this problem by active learning on homeomorphic tubes of spherical manifolds. This naturally generates feasible hypothesis class. With homologous topological properties, we identify an important connection - finding tube manifolds is equivalent to minimizing hyperspherical energy (MHE) in physical geometry. Inspired by this connection, we propose a MHE-based active learning (MHEAL) algorithm, and provide comprehensive theoretical guarantees for MHEAL, covering convergence and generalization analysis. Finally, we demonstrate the empirical performance of MHEAL in a wide range of applications for data-efficient learning, including deep clustering, distribution matching, version space sampling, and deep active learning.

Photoacoustic/ultrasonic dual-mode imaging for monitoring angiogenesis and synovial erosion in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the formation of new vessels, synovial proliferation and destruction of articular cartilage. However, characteristic early diagnostic and therapeutic monitoring methods are still lacking. We report a study using a photoacoustic/ultrasound (PA/US) dual-mode imaging for RA disease. By establishing a collagen-induced (CIA) RA mouse model to classify disease states based on a subjective grading system, PA/US imaging allows real-time assessment of synovial erosion and vascular opacification within the knee joint in different disease states at high spatial resolution. The system also quantitatively monitors subcutaneous vascular physiology and morphology in the hind paw of mice, measuring the area and photoacoustic signal intensity of vascular proliferation and showing a positive correlation with disease grading. Compared to traditional subjective scoring of arthritis severity, the PA/US imaging is more sensitive i.e., vascular signals and synovial erosion can be observed early in the course of arthritis.

Inversion Symmetry and Exotic Interlayer Exciton Behavior in Twisted Trilayer MoS2 Produced by Vapor Deposition.

Two-dimensional materials (2DMs) that are stacked vertically with a certain twist angle provide new degrees of freedom for designing novel physical properties. Twist-related properties of homogeneous bilayer and heterogeneous bilayer 2DMs, such as excitons and phonons, have been described in many pioneering works. However, twist-related properties of homogeneous trilayer 2DMs have been rarely reported. In this work, trilayer MoS2 with the twisted angle of 12° by optimized vapor deposition rather than the conventional mechanical stacking method was successfully fabricated. The inversion symmetry of trilayer MoS2 is changed by twist. Phonons and excitons produced by twist have an enormous influence on the interlayer interaction of trilayer MoS2, making trilayer MoS2 appear to have exotic optical properties. Compared with monolayer MoS2, the phonon vibration and photoluminescence intensity of trilayer MoS2 with one-interlayer-twisted are significantly improved, and the second harmonic generation response in the non-twist region of trilayer MoS2 is ∼3 times that of monolayer MoS2. In addition, interlayer coupling, inversion symmetry, and exciton behavior of the twist region show regional differences. This work provides a new way for designing twist and exploring the influence of twist on the structures of 2DMs with few layers.

SphereFace Revived: Unifying Hyperspherical Face Recognition.

This paper addresses the deep face recognition problem under an open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably chosen metric space. To this end, hyperspherical face recognition, as a promising line of research, has attracted increasing attention and gradually become a major focus in face recognition research. As one of the earliest works in hyperspherical face recognition, SphereFace explicitly proposed to learn face embeddings with large inter-class angular margin. However, SphereFace still suffers from severe training instability which limits its application in practice. In order to address this problem, we introduce a unified framework to understand large angular margin in hyperspherical face recognition. Under this framework, we extend the study of SphereFace and propose an improved variant with substantially better training stability - SphereFace-R. Specifically, we propose two novel ways to implement the multiplicative margin, and study SphereFace-R under three different feature normalization schemes (no feature normalization, hard feature normalization and soft feature normalization). We also propose an implementation strategy - "characteristic gradient detachment" - to stabilize training. Extensive experiments on SphereFace-R show that it is consistently better than or competitive with state-of-the-art methods.

The categorizations of vasculogenic mimicry in clear cell renal cell carcinoma unveil inherent connections with clinical and immune features.

Background: Clear cell renal cell carcinoma (ccRCC) stands as the prevailing variant kidney cancer in humans. Unfortunately, patients with disseminated RCC at diagnosis often have a diminished prognosis. Rapid tumor growth necessitates efficient blood supply for oxygen and nutrients, involving the circulation of blood from vessels to tumor tissues, facilitating tumor cell entry into the extracellular matrix. Vasculogenic mimicry (VM) significantly contributes to tumor growth and metastasis. Within this investigation, we identified vasculogenic mimicry-related genes (VMRGs) by analyzing data from 607 cases of kidney renal clear cell carcinoma (KIRC) in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). These findings offer insights into ccRCC progression and metastasis. Method: We identified VMRGs-related subtypes using consistent clustering methods. The signature of the VMRGs was created using univariate Cox regression and LASSO Cox regression analyses. To evaluate differences in immune cell infiltration, we employed ssGSEA. Afterwards, we created an innovative risk assessment model, known as the VM index, along with a nomogram to forecast the prognosis of ccRCC. Additionally, we verified the expression of an important gene related to VM, peroxiredoxin 2 (PRDX2), in tissue samples. Furthermore, we assessed the sensitivity to drugs in various groups by utilizing the pRRophetic R package. Results: Significant predictors of survival rates in both high- and low-risk groups of KIRC patients were identified as VMRGs. The independent prognostic factors for RCC were confirmed by both univariate and multivariate Cox regression analyses, validating VMRG risk signatures. Differences were observed in drug sensitivity, immune checkpoint expression, and responses to immune therapy between patients classified into high- and low-VMRG-risk groups. Our nomograms consistently demonstrated precise predictive capabilities. Finally, we experimentally verified PRDX2 expression levels and their impact on prognosis. Conclusion: The signature predicts patient prognosis and therapy response, laying the groundwork for future clinical strategies in treating ccRCC patients.

Erratum: Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

[This corrects the article DOI: 10.1038/s42256-021-00421-z.].

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses. However, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalised model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the AI model can be distributedly trained and independently executed at each host institution under a federated learning framework (FL) without data sharing. Here we show that our FL model outperformed all the local models by a large yield (test sensitivity /specificity in China: 0.973/0.951, in the UK: 0.730/0.942), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals leaving out the FL) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans (CTs) from 3,336 patients collected from 23 hospitals located in China and the UK. Collectively, our work advanced the prospects of utilising federated learning for privacy-preserving AI in digital health.

Comparison of Azacitidine and Decitabine in Myelodysplastic Syndromes and Acute Myeloid Leukemia: A Network Meta-analysis.

BACKGROUND: Myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) are hematologic malignancies that mostly affect the elderly and have a poor prognosis. Azacitidine (AZA) and decitabine (DAC) are the most widely used hypomethylating agents. However, few randomized controlled trials (RCTs) have compared AZA and DAC head to head in MDS or AML. This study intended to conduct a network meta-analysis to compare the 2 drugs to provide more guidance using evidence-based medicine. PATIENTS AND METHODS: A comprehensive search for RCTs was performed till July 31, 2020. The network meta-analysis was conducted using the Markov chain Monte Carlo method. The primary endpoints were overall survival (OS) and the incidence of adverse events, and the secondary endpoints were complete remission (CR) rate, overall remission rate (ORR), and AML-free survival. There were 6 RCTs with 1072 MDS patients, and 3 RCTs with 1256 AML patients. RESULTS: In MDS, AZA showed better AML-free survival (hazard ratio = 0.62; 95% CI, 0.43-0.9), whereas DAC had the possibility of achieving better CR and ORR, and AZA had the possibility of obtaining better OS with lower toxicity. As for elderly AML patients, DAC had the possibility of achieving superior CR, ORR, and OS, while the toxicity was relatively higher. Furthermore, subgroup analysis for patients ≥ 75 years old or of high risk in MDS suggested that AZA achieved better OS. CONCLUSION: For MDS, especially patients with intermediate or high risk disease with advanced age and poor general condition, AZA may be a better choice, while DAC may be of more benefit in elderly AML patients.

Simulation of higher-order topological phases and related topological phase transitions in a superconducting qubit.

Higher-order topological phases give rise to new bulk and boundary physics, as well as new classes of topological phase transitions. While the realization of higher-order topological phases has been confirmed in many platforms by detecting the existence of gapless boundary modes, a direct determination of the higher-order topology and related topological phase transitions through the bulk in experiments has still been lacking. To bridge the gap, in this work we carry out the simulation of a two-dimensional second-order topological phase in a superconducting qubit. Owing to the great flexibility and controllability of the quantum simulator, we observe the realization of higher-order topology directly through the measurement of the pseudo-spin texture in momentum space of the bulk for the first time, in sharp contrast to previous experiments based on the detection of gapless boundary modes in real space. Also through the measurement of the evolution of pseudo-spin texture with parameters, we further observe novel topological phase transitions from the second-order topological phase to the trivial phase, as well as to the first-order topological phase with nonzero Chern number. Our work sheds new light on the study of higher-order topological phases and topological phase transitions.

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses; however, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalized model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the artificial intelligence (AI) model can be distributedly trained and independently executed at each host institution under a federated learning framework without data sharing. Here we show that our federated learning framework model considerably outperformed all of the local models (with a test sensitivity/specificity of 0.973/0.951 in China and 0.730/0.942 in the United Kingdom), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals without the federated learning framework) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans from 3,336 patients collected from 23 hospitals located in China and the United Kingdom. Collectively, our work advanced the prospects of utilizing federated learning for privacy-preserving AI in digital health.

Flux Tunable Superconducting Quantum Circuit Based on Weyl Semimetal MoTe2.

Weyl semimetals have drawn considerable attention for their exotic topological properties in many research fields. When in combination with s-wave superconductors, the supercurrent can be carried by their topological surface channels, forming junctions mimicking the behavior of Majorana bound states. Here, we present a transmon-like superconducting quantum intereference device (SQUID) consisting of lateral junctions made of Weyl semimetal Td-MoTe2 and superconducting leads of niobium nitride (NbN). The SQUID is coupled to a readout cavity made of molybdenum rhenium (MoRe), whose response at high power reveals the existence of the constituting Josephson junctions (JJs). The loop geometry of the circuit allows the resonant frequency of the readout cavity to be tuned by the magnetic flux. We demonstrate a JJ made of MoTe2 and a flux-tunable transmon-like circuit based on Weyl semimetals. Our study provides a platform to utilize topological materials in SQUID-based quantum circuits for potential applications in quantum information processing.

The Efficacy and Safety of Vitamin C for Iron Supplementation in Adult Patients With Iron Deficiency Anemia: A Randomized Clinical Trial.

Importance: It remains uncertain whether vitamin C routinely used with oral iron supplements is essential for patients with iron deficiency anemia (IDA). Objective: To compare the equivalence and assess the safety of oral iron supplements plus vitamin C or oral iron supplements alone in patients with IDA. Design, Setting, and Participants: This single-center, open-label, equivalence randomized clinical trial was conducted from January 1, 2016, to December 30, 2017, in Huashan Hospital, Fudan University. Adult patients with newly diagnosed IDA were enrolled. Participants were randomly assigned (1:1) to the oral iron supplements plus vitamin C group or the oral iron supplements-only group. Data analysis was performed from March to December 2018. Interventions: Patients were randomized to receive a 100-mg oral iron tablet plus 200 mg of vitamin C or a 100-mg iron tablet alone every 8 hours daily for 3 months. Main Outcomes and Measures: The primary outcome was the change in hemoglobin level from baseline to 2 weeks of treatment, and an equivalence margin of 1 g/dL in hemoglobin was chosen for the demonstration of comparable efficacy. Secondary outcomes included the change in the reticulocyte percentage after 2 weeks of treatment, the increase in hemoglobin level after 4 weeks of treatment, the increase in serum ferritin level after 8 weeks of treatment, and adverse events. Results: Among the 440 randomized patients (220 each in the oral iron supplements plus vitamin C group and iron-only group; 426 women [96.8%]; mean [SD] age, 38.3 [11.7] years), all were assessed for the primary outcome, and 432 (98.2%) completed the trial. From baseline to the 2-week follow-up, the mean (SD) change in hemoglobin level was 2.00 (1.08) g/dL in the oral iron supplements plus vitamin C group and 1.84 (0.97) g/dL in the oral iron supplements-only group (between-group difference, 0.16 g/dL; 95% CI, -0.03 to 0.35 g/dL), thus meeting the criteria for equivalence. The mean (SD) change in serum ferritin level from baseline to 8-week follow-up was 35.75 (11.52) ng/mL in the vitamin C plus iron group and 34.48 (9.50) ng/mL in the iron-only group (between-group difference, 1.27 ng/mL; 95% CI, -0.70 to 3.24 ng/mL; P = .21). There were no significant differences between the 2 groups regarding the rates of adverse events (46 [20.9%] vs 45 [20.5%]; difference, 0.4%; 95% CI, -6.7% to 8.5%; P = .82). No patient withdrew because of adverse events. Conclusions and Relevance: Among patients with IDA, oral iron supplements alone were equivalent to oral iron supplements plus vitamin C in improving hemoglobin recovery and iron absorption. These findings suggest that on-demand vitamin C supplements are not essential to take along with oral iron supplements for patients with IDA. Trial Registration: ClinicalTrials.gov Identifier: NCT02631668.