Hierarchical superstructure aerogels for in situ biofluid metabolomics.

High-throughput biofluid metabolomics analysis for screening life-threatening diseases is urgently needed. However, the high salt content of biofluid samples, which introduces severe interference, can greatly limit the analysis throughput. Here, a new 3-D interconnected hierarchical superstructure, namely a "plasmonic gold-on-silica (Au/SiO2) double-layered aerogel", integrating distinctive features of an upper plasmonic gold aerogel with a lower inert silica aerogel was successfully developed to achieve in situ separation and storage of inorganic salts in the silica aerogel, parallel enrichment of metabolites on the surface of the functionalized gold aerogel, and direct desorption/ionization of enriched metabolites by the photo-excited gold aerogel for rapid, sensitive, and comprehensive metabolomics analysis of human serum/urine samples. By integrating all these unique advantages into the hierarchical aerogel, multifunctional properties were introduced in the SALDI substrate to enable its effective utilization in clinical metabolomics for the discovery of reliable metabolic biomarkers to achieve unambiguous differentiation of early and advanced-stage lung cancer patients from healthy individuals. This study provides insight into the design and application of superstructured nanomaterials for in situ separation, storage, and photoexcitation of multi-components in complex biofluid samples for sensitive analysis.

Exogenous Streptomyces spp. enhance the drought resistance of naked oat (Avena nuda) seedlings by augmenting both the osmoregulation mechanisms and antioxidant capacities.

Drought is a major obstacle to the development of naked oat industry. This work investigated mechanisms by which exogenous Streptomyces albidoflavus T4 and Streptomyces rochei D74 improved drought tolerance in naked oat (Avena nuda ) seedlings. Results showed that in the seed germination experiment, germination rate, radicle and hypocotyl length of naked oat seeds treated with the fermentation filtrate of T4 or D74 under PEG induced drought stress increased significantly. In the hydroponic experiment, the shoot and root dry weights of oat seedlings increased significantly when treated with the T4 or D74 fermentation filtrate under the 15% PEG induced drought stress (S15). Simultaneously, the T4 treatment also significantly increased the surface area, volume, the number of tips and the root activity of oat seedlings. Both T4 and D74 treatments elicited significant increases in proline and soluble sugar contents, as well as the catalase and peroxidase activities in oat seedlings. The results of comprehensive drought resistance capacity (CDRC) calculation of oat plants showed that the drought resistance of oat seedlings under the T4 treatment was better than that under the D74 treatment, and the effect was better under higher drought stress (S15). Findings of this study may provide a novel and effective approach for enhancing plant defenses against drought stress.

Higher Seed Rates Enlarge Effects of Wide-Belt Sowing on Canopy Radiation Capture, Distribution, and Use Efficiency in Winter Wheat.

The optimized winter wheat sowing method comprising wide-belt sowing (WBS) can improve the ears number and biomass to increase the grain yield, compared with conventional narrow-drill sowing (NDS). The seed rate and the interaction between the sowing method and seed rate also affect yield formation. However, the effects of the sowing method and seed rate, as well as their interaction on biomass production, particularly the interception of solar radiation (ISR) and radiation use efficiency (RUE), are unclear. A field experiment was conducted for two seasons in southern Shanxi province, China, using a split-plot design with sowing method as the main plot (WBS and NDS) and seed rate as the sub-plot (100-700 m-2). Our results showed that while WBS had a significant and positive effect, increasing the yield by 4.7-15.4%, the mechanism differed between seed rates. Yield increase by WBS was mainly attributed to the increase in total biomass resulting from both the promoted pre- and post-anthesis biomass production, except that only the increase in post-anthesis biomass mattered at the lowest seed rate (100 m-2). The higher biomass was attributed to the increased ISR before anthesis. After anthesis, the increased ISR contributed mainly to the increased biomass at low seed rates (100 and 200 m-2). In contrast, the increased RUE, resulting from the enhanced radiation distribution within canopy and LAI, contributed to the higher post-anthesis biomass at medium and high seed rates (400 to 700 m-2). The greatest increases in total biomass, pre-anthesis ISR, and post-anthesis RUE by WBS were all achieved at 500 seed m-2, thereby obtaining the highest yield. In summary, WBS enhanced grain yield by increasing ISR before anthesis and improving RUE after anthesis, and adopting relatively higher seed rates (400-500 m-2) was necessary for maximizing the positive effect of WBS, and thus the higher wheat yield.

A machine learning approach for predicting radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma undergoing tomotherapy.

The purpose of this study was to establish an integrated predictive model that combines clinical features, DVH, radiomics, and dosiomics features to predict RIHT in patients receiving tomotherapy for nasopharyngeal carcinoma. Data from 219 patients with nasopharyngeal carcinoma were randomly divided into a training cohort (n = 175) and a test cohort (n = 44) in an 8:2 ratio. RIHT is defined as serum thyroid-stimulating hormone (TSH) greater than 5.6 µU/mL, with or without a decrease in free thyroxine (FT4). Clinical features, 27 DVH features, 107 radiomics features and 107 dosiomics features were extracted for each case and included in the model construction. The least absolute shrinkage and selection operator (LASSO) regression method was used to select the most relevant features. The eXtreme Gradient Boosting (XGBoost) was then employed to train separate models using the selected features from clinical, DVH, radiomics and dosiomics data. Finally, a combined model incorporating all features was developed. The models were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. In the test cohort, the area under the receiver operating characteristic curve (AUC) for the clinical, DVH, radiomics, dosiomics and combined models were 0.798 (95% confidence interval [CI], 0.656-0.941), 0.673 (0.512-0.834), 0.714 (0.555-0.873), 0.698 (0.530-0.848) and 0.842 (0.724-0.960), respectively. The combined model exhibited higher AUC values compared to other models. The decision curve analysis demonstrated that the combined model had superior clinical utility within the threshold probability range of 1% to 79% when compared to the other models. This study has successfully developed a predictive model that combines multiple features. The performance of the combined model is superior to that of single-feature models, allowing for early prediction of RIHT in patients with nasopharyngeal carcinoma after tomotherapy.

Tetris-inspired detector with neural network for radiation mapping.

Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

[Research progress of non-coding RNA involved in glycolysis regulation of hepatocellular carcinoma].

Liver cancer is a common tumor of digestive system. Hepatocellular carcinoma (HCC) is a common type of liver cancer, which has a high degree of malignancy and ranks among the top causes of cancer-related death in the world. Metabolic reprogramming is considered to be an important marker of carcinogenesis. Glucose metabolism is one of the main ways for cells to produce energy. Glycolysis, as the basic reaction of glucose metabolism, plays an important role in cell metabolism. Therefore, the regulation of glycolysis is of great significance to the proliferation and evolution of tumors. More and more non-coding RNAs (ncRNA) have been proved to play an important role in the regulation of tumor glycolysis. This article reviews the role of ncRNA in the regulation of HCC glycolysis and its related mechanisms. At the same time, the prospect of targeted therapy for HCC based on the related mechanisms of glycolysis regulation is put forward.

Research status and prospect of ratoon rice in China under mechanically harvested condition.

The proportion and area of ratoon rice planting in China have been substantially increased, due to continuous improvement of rice breeding methods and consecutive innovation of cultivation technology, which has developed into one of rice planting modes with significant production efficiency. Combining the experience in research and practice, from the perspective of crop physiology and ecology, we reviewed the current situation and prospects of high-yielding formation and physiological mechanisms of ratoon rice. We focused on four key aspects: screening and breeding of ratoon rice cultivars and the classification; suitable stubble height for mechanically harvested ratoon rice, as well as water and fertilizer management; dry matter production and allocation in ratoon rice and the relationship with yield formation; regenerative activity and vigor of ratoon rice roots and their relationship with rhizosphere micro-ecological characteristics. As for the extending of mechanized low-cut stubbles ratoon rice technique, we should properly regulate the rhizosphere system, coordinate rhizosphere nutrient supply, germination of axillary buds, and tillering regeneration, to achieve the target of "four-high-one-low", that is high regeneration coefficient, high number of regeneration panicle, high harvest index, high yield, high quality, low-carbon and safe, aiming to improve the sustainability of ratoon rice industry.

Using machine learning to identify key subject categories predicting the pre-clerkship and clerkship performance: 8-year cohort study.

BACKGROUND: Medical students need to build a solid foundation of knowledge to become physicians. Clerkship is often considered the first transition point, and clerkship performance is essential for their development. We hope to identify subjects that could predict the clerkship performance, thus helping medical students learn more efficiently to achieve high clerkship performance. METHODS: This cohort study collected background and academic data from medical students who graduated between 2011 and 2019. Prediction models were developed by machine learning techniques to identify the affecting features in predicting the pre-clerkship performance and clerkship performance. Following serial processes of data collection, data pre-processing before machine learning, and techniques and performance of machine learning, different machine learning models were trained and validated using the 10-fold cross-validation method. RESULTS: Thirteen subjects from the pre-med stage and ten subjects from the basic medical science stage with an area under the ROC curve (AUC) greater than 0.7 for either pre-clerkship performance or clerkship performance were found. In each subject category, medical humanities and sociology in social science, chemistry and physician scientist-related training in basic science, and pharmacology, immunology-microbiology, and histology in basic medical science have predictive abilities for clerkship performance above the top tertile. Using a machine learning technique based on random forest, the prediction model predicted clerkship performance with 95% accuracy and 88% AUC. CONCLUSION: Clerkship performance was predicted by selected subjects or combination of different subject categories in the pre-med and basic medical science stages. The demonstrated predictive ability of subjects or categories in the medical program may facilitate students' understanding of how these subjects or categories of the medical program relate to their performance in the clerkship to enhance their preparedness for the clerkship.

The relationship between graduation school background and geographical distribution of dentists in Taiwan.

Background/purpose: Taiwan's eight dental schools are all located in the western region. This study attempted to analyze the relationship between the geographical distribution of dentists in Taiwan and their graduation school background and to develop several statistical indicators to analyze the geographical distribution of dentists. Materials and methods: The method of the secondary data analysis was adopted to collect the open information related to the number of the practicing dentists based on their graduation schools and practice locations by cities and counties in Taiwan in January 2023. The data were used to develop several statistical indicators to analyze the geographical distribution of dentists. Results: There were 16,533 practicing dentists in Taiwan in January 2023. Of the 16,533 dentists, 15,687 (94.88 %) graduated from domestic dental schools and 846 (5.12 %) graduated from foreign dental schools. For the school location, the coefficient of variation, Gini coefficient, population proportion index, and population density index were the largest (168.57 %, 0.47, 10.76 %, and 3927.01 people/square kilometer) in the dentists graduating from the northern dental schools. In overall, the dentists were concentrated in municipalities, cities, and the northern region of Taiwan, especially those graduating from the northern dental schools. Conclusion: In Taiwan, the geographical distribution of dentists is highly related to their graduation school background. Promoting a balanced distribution of dental enrollment quotas and dental student sources from different geographical locations and inducing the movement of dentists to the dentist-shortage areas may be the more feasible ways to solve the uneven geographical distribution of dentists in Taiwan.

Ultrasound-based radiomics-clinical nomogram for noninvasive prediction of residual cancer burden grading in breast cancer.

PURPOSE: To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients. METHODS: This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images. Subsequently, multivariate LR (logistic regression) analysis incorporating both radiomic scores and clinical factors was performed to construct a nomogram. Finally, Receiver operating characteristics (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate and validate the diagnostic accuracy and effectiveness of the nomogram. RESULTS: A total of 1122 patients were included in this study. Among them, 427 patients exhibited a favorable response to NAC chemotherapy, while 695 patients demonstrated a poor response to NAC therapy. The radiomics model achieved an AUC value of 0.84 in the training cohort and 0.83 in the validation cohort. The ultrasound-based radiomics-clinical nomogram achieved an AUC value of 0.90 in the training cohort and 0.91 in the validation cohort. CONCLUSIONS: Ultrasound-based radiomics-clinical nomogram can accurately predict the effectiveness of NAC therapy by predicting RCB grading in breast cancer patients.

Studying the impact of marital status on diagnosis and survival prediction in pancreatic ductal carcinoma using machine learning methods.

Pancreatic cancer is a commonly occurring malignant tumor, with pancreatic ductal carcinoma (PDAC) accounting for approximately 95% of cases. According of its poor prognosis, identifying prognostic factors of pancreatic ductal carcinoma can provide physicians with a reliable theoretical foundation when predicting patient survival. This study aimed to analyze the impact of marital status on survival outcomes of PDAC patients using propensity score matching and machine learning. The goal was to develop a prognosis prediction model specific to married patients with PDAC. We extracted a total of 206,968 patient records of pancreatic cancer from the SEER database. To ensure the baseline characteristics of married and unmarried individuals were balanced, we used a 1:1 propensity matching score. We then conducted Kaplan-Meier analysis and Cox proportional-hazards regression to examine the impact of marital status on PDAC survival before and after matching. Additionally, we developed machine learning models to predict 5-year CSS and OS for married patients with PDAC specifically. In total, 24,044 PDAC patients were included in this study. After 1:1 propensity matching, 8043 married patients and 8,043 unmarried patients were successfully enrolled. Multivariate analysis and the Kaplan-Meier curves demonstrated that unmarried individuals had a poorer survival rate than their married counterparts. Among the algorithms tested, the random forest performed the best, with 0.734 5-year CSS and 0.795 5-year OS AUC. This study found a significant association between marital status and survival in PDAC patients. Married patients had the best prognosis, while widowed patients had the worst. The random forest is a reliable model for predicting survival in married patients with PDAC.

The Effects of Secondary Task Demands on Cybersickness in Active Exploration Virtual Reality Experiences.

Active exploration in virtual reality (VR) involves users navigating immersive virtual environments, going from one place to another. While navigating, users often engage in secondary tasks that require attentional resources, as in the case of distracted driving. Inspired by research generally studying the effects of task demands on cybersickness (CS), we investigated how the attentional demands specifically associated with secondary tasks performed during exploration affect CS. Downstream of this, we studied how increased attentional demands from secondary tasks affect spatial memory and navigational performance. We discuss the results of a multi-factorial between-subjects study, manipulating a secondary task's demand across two levels and studying its effects on CS in two different sickness-inducing levels of an exploration experience. The secondary task's demand was manipulated by parametrically varying $n$ in an aural $n$-back working memory task and the provocativeness of the experience was manipulated by varying how frequently users experienced a yaw-rotational reorientation effect during the exploration. Results revealed that increases in the secondary task's demand increased sickness levels, also resulting in a higher temporal onset rate, especially when the experience was not already highly sickening. Increased attentional demand from the secondary task also vitiated navigational performance and spatial memory. Overall, increased demands from secondary tasks performed during navigation produce deleterious effects on the VR experience.

Impact of miscarriage and termination of pregnancy on subsequent pregnancies: A longitudinal study of maternal and paternal depression, anxiety and eudaimonia.

BACKGROUND: Although miscarriage and termination of pregnancy affect maternal mental illnesses on subsequent pregnancies, their effects on the positive mental health (e.g., eudaimonia) of both first-time and multi-time parents have received minimal attention, especially for fathers. This longitudinal study examines the effects of experiences of miscarriage and termination on parental well-being in subsequent pregnancies from prenatal to postpartum years, while simultaneously considering parity. METHODS: Pregnant women and their partners were recruited during early prenatal visits in Taiwan from 2011 to 2022 and were followed up from mid-pregnancy to 1 year postpartum. Six waves of self-reported assessments were employed. RESULTS: Of 1813 women, 11.3 % and 14.7 % had experiences of miscarriage and termination, respectively. Compared with the group without experiences of miscarriage or termination, experiences of miscarriage were associated with increased risks of paternal depression (adjusted odds ratio = 1.6, 95 % confidence interval [CI] = 1.13-2.27), higher levels of anxiety (adjusted ß = 1.83, 95 % CI = 0.21-3.46), and lower eudaimonia scores (adjusted ß = -1.09, 95 % CI = -1.99 to -0.19) from the prenatal to postpartum years, particularly among multiparous individuals. Additionally, experiences of termination were associated with increased risks of depression in their partner. LIMITATIONS: The experiences of miscarriage and TOP were self-reported and limited in acquiring more detailed information through questioning. CONCLUSIONS: These findings highlight the decreased well-being of men whose partners have undergone termination of pregnancy or experienced miscarriage, and stress the importance of interventions aimed at preventing adverse consequences among these individuals.

Constructing Robust 3D Ionomer Networks in the Catalyst Layer to Achieve Stable Water Electrolysis for Green Hydrogen Production.

The widespread application of proton exchange membrane water electrolyzers (PEMWEs) is hampered by insufficient lifetime caused by degradation of the anode catalyst layer (ACL). Here, an important degradation mechanism has been identified, attributed to poor mechanical stability causing the mass transfer channels to be blocked by ionomers under operating conditions. By using liquid-phase atomic force microscopy, we directly observed that the ionomers were randomly distributed (RD) in the ACL, which occupied the mass transfer channels due to swelling, creeping, and migration properties. Interestingly, we found that alternating treatments of the ACL in different water/temperature environments resulted in forming three-dimensional ionomer networks (3D INs) in the ACL, which increased the mechanical strength of microstructures by 3 times. Benefitting from the efficient and stable mass transfer channels, the lifetime was improved by 19 times. A low degradation rate of approximately 3.0 µV/h at 80 °C and a high current density of 2.0 A/cm2 was achieved on a 50 cm2 electrolyzer. These data demonstrated a forecasted lifetime of 80 000 h, approaching the 2026 DOE lifetime target. This work emphasizes the importance of the mechanical stability of the ACL and offers a general strategy for designing and developing a durable PEMWE.

Discontinuity third harmonic generation microscopy for label-free imaging and quantification of intraepidermal nerve fibers.

Label-free imaging methodologies for nerve fibers rely on spatial signal continuity to identify fibers and fail to image free intraepidermal nerve endings (FINEs). Here, we present an imaging methodology-called discontinuity third harmonic generation (THG) microscopy (dTHGM)-that detects three-dimensional discontinuities in THG signals as the contrast. We describe the mechanism and design of dTHGM and apply it to reveal the bead-string characteristics of unmyelinated FINEs. We confirmed the label-free capability of dTHGM through a comparison study with the PGP9.5 immunohistochemical staining slides and a longitudinal spared nerve injury study. An intraepidermal nerve fiber (IENF) index based on a discontinuous-dot-connecting algorithm was developed to facilitate clinical applications of dTHGM. A preliminary clinical study confirmed that the IENF index was highly correlated with skin-biopsy-based IENF density (Pearson's correlation coefficient R = 0.98) and could achieve differential identification of small-fiber neuropathy (p = 0.0102) in patients with diabetic peripheral neuropathy.

Integration of Prior Expectations and Suppression of Prediction Errors During Expectancy-Induced Pain Modulation: The Influence of Anxiety and Pleasantness.

Pain perception arises from the integration of prior expectations with sensory information. Although recent work has demonstrated that treatment expectancy effects (e.g., placebo hypoalgesia) can be explained by a Bayesian integration framework incorporating the precision level of expectations and sensory inputs, the key factor modulating this integration in stimulus expectancy-induced pain modulation remains unclear. In a stimulus expectancy paradigm combining emotion regulation in healthy male and female adults, we found that participants' voluntary reduction in anticipatory anxiety and pleasantness monotonically reduced the magnitude of pain modulation by negative and positive expectations, respectively, indicating a role of emotion. For both types of expectations, Bayesian model comparisons confirmed that an integration model using the respective emotion of expectations and sensory inputs explained stimulus expectancy effects on pain better than using their respective precision. For negative expectations, the role of anxiety is further supported by our fMRI findings that (1) functional coupling within anxiety-processing brain regions (amygdala and anterior cingulate) reflected the integration of expectations with sensory inputs and (2) anxiety appeared to impair the updating of expectations via suppressed prediction error signals in the anterior cingulate, thus perpetuating negative expectancy effects. Regarding positive expectations, their integration with sensory inputs relied on the functional coupling within brain structures processing positive emotion and inhibiting threat responding (medial orbitofrontal cortex and hippocampus). In summary, different from treatment expectancy, pain modulation by stimulus expectancy emanates from emotion-modulated integration of beliefs with sensory evidence and inadequate belief updating.

Quantifying isotope parameters associated with carbonyl-water oxygen exchange during sucrose translocation in tree phloem.

Stable oxygen isotope ratio of tree-ring α-cellulose (δ18Ocel) yields valuable information on many aspects of tree-climate interactions. However, our current understanding of the mechanistic controls on δ18Ocel is incomplete, with a knowledge gap existent regarding the fractionation effect characterizing carbonyl-water oxygen exchange during sucrose translocation from leaf to phloem. To address this insufficiency, we set up an experimental system integrating a vapor 18O-labeling feature to manipulate leaf-level isotopic signatures in tree saplings enclosed within whole-canopy gas-exchange cuvettes. We applied this experimental system to three different tree species to determine their respective relationships between 18O enrichment of sucrose in leaf lamina (Δ18Ol_suc) and petiole phloem (Δ18Ophl_suc) under environmentally/physiologically stable conditions. Based on the determined Δ18Ophl_suc-Δ18Ol_suc relationships, we estimated that on average, at least 25% of the oxygen atoms in sucrose undergo isotopic exchange with water along the leaf-to-phloem translocation path and that the biochemical fractionation factor accounting for such exchange is c. 34‰, markedly higher than the conventionally assumed value of 27‰. Our study represents a significant step toward quantitative elucidation of the oxygen isotope dynamics during sucrose translocation in trees. This has important implications with respect to improving the δ18Ocel model and its related applications in paleoclimatic and ecophysiological contexts.

Streptococcus taonis sp. nov., a novel bacterial species isolated from a blood culture of a patient.

One Gram stain-positive, catalase-negative, α-hemolytic, chain-forming or paired cocci, designated ST22-14T, was isolated from a blood culture of a child with suspected infection. The results of 16S rRNA gene sequences analyses showed that the most closely related species to strain ST22-14T were "Streptococcus vulneris" DM3B3T (99.2%), Streptococcus mitis NCTC 12261T (99.0%), "Streptococcus gwangjuense" ChDC B345T, (99.0%), Streptococcus oralis subsp. dentisani 7747T (99.0%), Streptococcus downii CECT 9732T (99.0%), and Streptococcus infantis ATCC 700779T (98.9%). The genome of strain ST22-14T consists of 2,053,261 bp with a G + C content of 39.4%. Average nucleotide identity values between strain ST22-14T and Streptococcus mitis NCTC 12261T or other five species were from 82.2 to 88.0%. In silico DNA-DNA hybridization of ST22-14T showed an estimated DNA reassociation value of 34.6% with the closest species. The main cellular fatty acids of strain ST22-14T were 16:0, 18:0, 14:0, 18:1ω7c and 18:1ω6c. Based on these results, strain ST22-14T should be classified as a novel species of genus Streptococcus, for which the name Streptococcus taonis sp. nov. is proposed (type strain ST22-14T = NBRC 116002T = BCRC 81402T).

Investigating the Effects of Avatarization and Interaction Techniques on Near-field Mixed Reality Interactions with Physical Components.

Mixed reality (MR) interactions feature users interacting with a combination of virtual and physical components. Inspired by research investigating aspects associated with near-field interactions in augmented and virtual reality (AR & VR), we investigated how avatarization, the physicality of the interacting components, and the interaction technique used to manipulate a virtual object affected performance and perceptions of user experience in a mixed reality fundamentals of laparoscopic peg-transfer task wherein users had to transfer a virtual ring from one peg to another for a number of trials. We employed a 3 (Physicality of pegs) X 3 (Augmented Avatar Representation) X 2 (Interaction Technique) multi-factorial design, manipulating the physicality of the pegs as a between-subjects factor, the type of augmented self-avatar representation, and the type of interaction technique used for object-manipulation as within-subjects factors. Results indicated that users were significantly more accurate when the pegs were virtual rather than physical because of the increased salience of the task-relevant visual information. From an avatar perspective, providing users with a reach envelope-extending representation, though useful, was found to worsen performance, while co-located avatarization significantly improved performance. Choosing an interaction technique to manipulate objects depends on whether accuracy or efficiency is a priority. Finally, the relationship between the avatar representation and interaction technique dictates just how usable mixed reality interactions are deemed to be.