Author Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Analysis of the Human Protein Atlas Image Classification competition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Analysis of the Human Protein Atlas Image Classification competition.

Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition to identify deep learning solutions to solve this task. Challenges included training on highly imbalanced classes and predicting multiple labels per image. Over 3 months, 2,172 teams participated. Despite convergence on popular networks and training techniques, there was considerable variety among the solutions. Participants applied strategies for modifying neural networks and loss functions, augmenting data and using pretrained networks. The winning models far outperformed our previous effort at multi-label classification of protein localization patterns by ~20%. These models can be used as classifiers to annotate new images, feature extractors to measure pattern similarity or pretrained networks for a wide range of biological applications.

Social Determinants of Health and Patient-Reported Outcomes Following Total Hip and Knee Arthroplasty in Veterans.

BACKGROUND: Social determinants of health (SDOH) are the conditions in which people are born, grow, live, work, and age. They are associated with disparities in outcomes following total joint arthroplasty (TJA). These disparities occur even in equal-access healthcare systems such as the Veterans Health Administration (VHA). Our goal was to determine whether SDOH affect patient-reported outcome measures (PROMs) following TJA in VHA patients. METHODS: Patients scheduled to undergo total hip or knee arthroplasty at VHA Hospitals in Minneapolis, MN, Palo Alto, CA, and San Francisco, CA, prospectively completed PROMs before and 1 year after surgery. PROMs included the Hip disability and Osteoarthritis Outcome Score, the Knee injury and Osteoarthritis Outcome Score, and their Joint Replacement subscores. SDOH included race, ethnicity, marital status, education, and employment status. The level of poverty in each patient's neighborhood was determined. Medical comorbidities were recorded. Univariate and multivariate analyses were performed to determine whether SDOH were significantly associated with PROM improvement after surgery. RESULTS: On multivariate analysis, black race was significantly negatively correlated with knee PROM improvement and Hispanic ethnicity was significantly negatively correlated with hip PROM improvement compared to whites. Higher baseline PROM scores and lower age were significantly associated with lower PROM improvement. Significant associations were also found based on education, gender, comorbidities, and neighborhood poverty. CONCLUSION: Minority VHA patients have lower improvement in PROM scores after TJA than white patients. Further research is required to identify the reasons for these disparities and to design interventions to reduce them.

Metal-Dependent DNAzymes for the Quantitative Detection of Metal Ions in Living Cells: Recent Progress, Current Challenges, and Latest Results on FRET Ratiometric Sensors.

Many different metal ions are involved in various biological functions including metallomics and trafficking, and yet there are currently effective sensors for only a few metal ions, despite the first report of metal sensors for calcium more than 40 years ago. To expand upon the number of metal ions that can be probed in biological systems, we and other laboratories employ the in vitro selection method to obtain metal-specific DNAzymes with high specificity for a metal ion and then convert these DNAzymes into fluorescent sensors for these metal ions using a catalytic beacon approach. In this Forum Article, we summarize recent progress made in developing these DNAzyme sensors to probe metal ions in living cells and in vivo, including several challenges that we were able to overcome for this application, such as DNAzyme delivery, spatiotemporal control, and signal amplification. Furthermore, we have identified a key remaining challenge for the quantitative detection of metal ions in living cells and present a new design and the results of a Förster resonance energy transfer (FRET)-based DNAzyme sensor for the ratiometric quantification of Zn2+ in HeLa cells. By converting existing DNAzyme sensors into a ratiometric readout without compromising the fundamental catalytic function of the DNAzymes, this FRET-based ratiometric DNAzyme design can readily be applied to other DNAzyme sensors as a major advance in the field to develop much more quantitative metal-ion probes for biological systems.

Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial.

BACKGROUND: Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PGHD in TJA to predict patient-reported outcome measures (PROMs). METHODS: Twenty-two TJA patients were recruited for this pilot study. Three activity trackers collected 35 features from 4 weeks before to 6 weeks following surgery. PROMs were collected at both endpoints (Hip and Knee Disability and Osteoarthritis Outcome Score, Knee Osteoarthritis Outcome Score, and Veterans RAND 12-Item Health Survey Physical Component Score). We used ML to identify features with the highest correlation with PROMs. The algorithm trained on a subset of patients and used 3 feature sets (A, B, and C) to group the rest into one of the 3 PROM clusters. RESULTS: Fifteen patients completed the study and collected 3 million data points. Three sets of features with the highest R2 values relative to PROMs were selected (A, B and C). Data collected through the 11th day had the highest predictive value. The ML algorithm grouped patients into 3 clusters predictive of 6-week PROM results, yielding total sum of squares values ranging from 3.86 (A) to 1.86 (C). CONCLUSION: This small but critical proof-of-concept study demonstrates that ML can be used in combination with PGHD to predict 6-week PROM data as early as 11 days following TJA surgery. Further study is needed to confirm these findings and their clinical value.

Optimal Sampling Frequency for Wearable Sensor Data in Arthroplasty Outcomes Research. A Prospective Observational Cohort Trial.

BACKGROUND: Wearable sensors can track patient activity after surgery. The optimal data sampling frequency to identify an association between patient-reported outcome measures (PROMs) and sensor data is unknown. Most commercial grade sensors report 24-hour average data. We hypothesize that increasing the frequency of data collection may improve the correlation with PROM data. METHODS: Twenty-two total joint arthroplasty (TJA) patients were prospectively recruited and provided wearable sensors. Second-by-second (Raw) and 24-hour average data (24Hr) were collected on 7 gait metrics on the 1st, 7th, 14th, 21st, and 42nd days postoperatively. The average for each metric as well as the slope of a linear regression for 24Hr data (24HrLR) was calculated. The R2 associations were calculated using machine learning algorithms against individual PROM results at 6 weeks. The resulting R2 values were defined having a mild, moderate, or strong fit (R2 ≥ 0.2, ≥0.3, and ≥0.6, respectively) with PROM results. The difference in frequency of fit was analyzed with the McNemar's test. RESULTS: The frequency of at least a mild fit (R2 ≥ 0.2) for any data point at any time frame relative to either of the PROMs measured was higher for Raw data (42%) than 24Hr data (32%; P = .041). There was no difference in frequency of fit for 24hrLR data (32%) and 24Hr data values (32%; P > .05). Longer data collection improved frequency of fit. CONCLUSION: In this prospective trial, increasing sampling frequency above the standard 24Hr average provided by consumer grade activity sensors improves the ability of machine learning algorithms to predict 6-week PROMs in our total joint arthroplasty cohort.

Optical Control of Metal Ion Probes in Cells and Zebrafish Using Highly Selective DNAzymes Conjugated to Upconversion Nanoparticles.

Spatial and temporal distributions of metal ions in vitro and in vivo are crucial in our understanding of the roles of metal ions in biological systems, and yet there is a very limited number of methods to probe metal ions with high space and time resolution, especially in vivo. To overcome this limitation, we report a Zn2+-specific near-infrared (NIR) DNAzyme nanoprobe for real-time metal ion tracking with spatiotemporal control in early embryos and larvae of zebrafish. By conjugating photocaged DNAzymes onto lanthanide-doped upconversion nanoparticles (UCNPs), we have achieved upconversion of a deep tissue penetrating NIR 980 nm light into 365 nm emission. The UV photon then efficiently photodecages a substrate strand containing a nitrobenzyl group at the 2'-OH of adenosine ribonucleotide, allowing enzymatic cleavage by a complementary DNA strand containing a Zn2+-selective DNAzyme. The product containing a visible FAM fluorophore that is initially quenched by BHQ1 and Dabcyl quenchers is released after cleavage, resulting in higher fluorescent signals. The DNAzyme-UCNP probe enables Zn2+ sensing by exciting in the NIR biological imaging window in both living cells and zebrafish embryos and detecting in the visible region. In this study, we introduce a platform that can be used to understand the Zn2+ distribution with spatiotemporal control, thereby giving insights into the dynamical Zn2+ ion distribution in intracellular and in vivo models.

In vitro selection of a sodium-specific DNAzyme and its application in intracellular sensing.

Over the past two decades, enormous progress has been made in designing fluorescent sensors or probes for divalent metal ions. In contrast, the development of fluorescent sensors for monovalent metal ions, such as sodium (Na(+)), has remained underdeveloped, even though Na(+) is one the most abundant metal ions in biological systems and plays a critical role in many biological processes. Here, we report the in vitro selection of the first (to our knowledge) Na(+)-specific, RNA-cleaving deoxyribozyme (DNAzyme) with a fast catalytic rate [observed rate constant (ko(bs)) ∼ 0.1 min(-1)], and the transformation of this DNAzyme into a fluorescent sensor for Na(+) by labeling the enzyme strand with a quencher at the 3' end, and the DNA substrate strand with a fluorophore and a quencher at the 5' and 3' ends, respectively. The presence of Na(+) catalyzed cleavage of the substrate strand at an internal ribonucleotide adenosine (rA) site, resulting in release of the fluorophore from its quenchers and thus a significant increase in fluorescence signal. The sensor displays a remarkable selectivity (>10,000-fold) for Na(+) over competing metal ions and has a detection limit of 135 µM (3.1 ppm). Furthermore, we demonstrate that this DNAzyme-based sensor can readily enter cells with the aid of α-helical cationic polypeptides. Finally, by protecting the cleavage site of the Na(+)-specific DNAzyme with a photolabile o-nitrobenzyl group, we achieved controlled activation of the sensor after DNAzyme delivery into cells. Together, these results demonstrate that such a DNAzyme-based sensor provides a promising platform for detection and quantification of Na(+) in living cells.

Current Management Strategy for Active Surveillance in Prostate Cancer.

PURPOSE OF REVIEW: Active surveillance has been increasingly utilized as a strategy for the management of favorable-risk, localized prostate cancer. In this review, we describe contemporary management strategies of active surveillance, with a focus on traditional stratification schemes, new prognostic tools, and patient outcomes. RECENT FINDINGS: Patient selection, follow-up strategy, and indication for delayed intervention for active surveillance remain centered around PSA, digital rectal exam, and biopsy findings. Novel tools which include imaging, biomarkers, and genetic assays have been investigated as potential prognostic adjuncts; however, their role in active surveillance remains institutionally dependent. Although 30-50% of patients on active surveillance ultimately undergo delayed treatment, the vast majority will remain free of metastasis with a low risk of dying from prostate cancer. The optimal method for patient selection into active surveillance is unknown; however, cancer-specific mortality rates remain excellent. New prognostication tools are promising, and long-term prospective, randomized data regarding their use in active surveillance will be beneficial.

Multimodal Detection of a Small Molecule Target Using Stimuli-Responsive Liposome Triggered by Aptamer-Enzyme Conjugate.

Nanomaterials which can respond to external stimuli have attracted considerable attention due to their potential applications in sensing and biomedicine. One of the most promising classes of such materials is the stimuli-responsive liposome that can release its contents in response to a specific target. Despite recent progress, development of liposomes responsive to small molecular targets remains a challenge, due to the difficulty in designing the transduction process to link between target binding and triggered release, even though small molecular metabolites play important roles in many biological processes. Herein, we demonstrate a combination of an aptamer (apt) for target recognition and enzyme phosphatidylcholine 2-acetylhydrolase (PLA2) for rupture of liposome. As a proof-of-concept, cocaine molecules were used to trigger the release of the enzyme. The exposure to DNA-PLA2 conjugates induced the rupture of liposome containing uranin and gadopentetic acid (Gd-DTPA), allowing multimodal fluorescent and MRI detection of cocaine. The strategy demonstrated in this work can be generally applied to other imaging modalities by loading different imaging agents, as well as other targets by using different functional DNAs.

The Effects of Spacer Length and Composition on Aptamer-Mediated Cell-Specific Targeting with Nanoscale PEGylated Liposomal Doxorubicin.

Aptamer-based targeted drug delivery systems have shown significant promise for clinical applications. Although much progress has been made in this area, it remains unclear how PEG coating would affect the selective binding of DNA aptamers and thus influence the overall targeting efficiency. To answer this question, we herein report a systematic investigation of the interactions between PEG and DNA aptamers on the surface of liposomes by using a series of nanoscale liposomal doxorubicin formulations with different DNA aptamer and PEG modifications. We investigated how the spatial size and composition of the spacer molecules affected the targeting ability of the liposome delivery system. We showed that a spacer of appropriate length was critical to overcome the shielding from surrounding PEG molecules in order to achieve the best targeting effect, regardless of the spacer composition. Our findings provide important guidelines for the design of aptamer-based targeted drug delivery systems.

Biochemical and Biophysical Understanding of Metal Ion Selectivity of DNAzymes.

This review summarizes research into the metal-binding properties of catalytic DNAzymes, towards the goal of understanding the structural properties leading to metal ion specificity. Progress made and insight gained from a range of biochemical and biophysical techniques are covered, and promising directions for future investigations are discussed.

DNA sequence-dependent morphological evolution of silver nanoparticles and their optical and hybridization properties.

A systematic investigation of the effects of different DNA sequences on the morphologies of silver nanoparticles (AgNPs) grown from Ag nanocube seeds is reported. The presence of 10-mer oligo-A, -T, and -C directed AgNPs growth from cubic seeds into edge-truncated octahedra of different truncation extents and truncated tetrahedral AgNPs, while AgNPs in the presence of oligo-G remained cubic. The shape and morphological evolution of the nanoparticle growth for each system is investigated using SEM and TEM and correlated with UV-vis absorption kinetic studies. In addition, the roles of oligo-C and oligo-G secondary structures in modulating the morphologies of AgNPs are elucidated, and the morphological evolution for each condition of AgNPs growth is proposed. The shapes were found to be highly dependent on the binding affinity of each of the bases and the DNA secondary structures, favoring the stabilization of the Ag{111} facet. The AgNPs synthesized through this method have morphologies and optical properties that can be varied by using different DNA sequences, while the DNA molecules on these AgNPs are also stable against glutathione. The AgNP functionalization can be realized in a one-step synthesis while retaining the biorecognition ability of the DNA, which allows for programmable assembly.

Structural social support predicts functional social support in an online weight loss programme.

BACKGROUND: Online weight loss programmes allow members to use social media tools to give and receive social support for weight loss. However, little is known about the relationship between the use of social media tools and the perception of specific types of support. OBJECTIVE: To test the hypothesis that the frequency of using social media tools (structural support) is directly related to perceptions of Encouragement, Information and Shared Experiences support (functional support). DESIGN: Online survey. PARTICIPANTS: Members of an online weight loss programme. METHODS: The outcome was the perception of Encouragement (motivation, congratulations), Information (advice, tips) and Shared Experiences (belonging to a group) social support. The predictor was a social media scale based on the frequency of using forums and blogs within the online weight loss programme (alpha = 0.91). The relationship between predictor and outcomes was evaluated with structural equation modelling (SEM) and logistic regression, adjusted for sociodemographic characteristics, BMI and duration of website membership. RESULTS: The 187 participants were mostly female (95%) and white (91%), with mean (SD) age 37 (12) years and mean (SD) BMI 31 (8). SEM produced a model in which social media use predicted Encouragement support, but not Information or Shared Experiences support. Participants who used the social media tools at least weekly were almost five times as likely to experience Encouragement support compared to those who used the features less frequently [adjusted OR 4.8 (95% CI 1.8-12.8)]. CONCLUSIONS: Using the social media tools of an online weight loss programme at least once per week is strongly associated with receiving Encouragement for weight loss behaviours.

Neurologic deterioration in a child undergoing treatment for tuberculosis meningitis.

Clinical deterioration while receiving antituberculosis (anti-TB) therapy can be due to a number of etiologies, including drug resistance, disease progression despite effective therapy, or alternative diagnoses. We present the case of a 22-month-old girl diagnosed with TB meningitis 4 months prior to presentation. At time of her initial diagnosis, computed tomography showed hydrocephalus and basilar meningitis with some evidence of ischemic damage. She required placement of a ventriculoperitoneal shunt and was discharged on multidrug anti-TB therapy and corticosteroids. At the time of her second emergency department presentation, she had developed new-onset seizures and hemiparesis. Her steroids had been tapered and discontinued. Differential diagnosis included shunt malfunction and/or shunt infection. Magnetic resonance imaging of the brain showed interval development of tuberculomas. Symptomatic and radiographic improvement was seen after initiation of corticosteroids for immune reconstitution inflammatory syndrome, which can be seen in immunocompetent children, with onset weeks to months after starting antituberculous therapy.

Photocaged DNAzymes as a general method for sensing metal ions in living cells.

DNAzymes, which are sequences of DNA with catalytic activity, have been demonstrated as a potential platform for sensing a wide range of metal ions. Despite their significant promise, cellular sensing using DNAzymes has however been difficult, mainly because of the "always-on" mode of first-generation DNAzyme sensors. To overcome this limitation, a photoactivatable (or photocaged) DNAzyme was designed and synthesized, and its application in sensing Zn(II) in living cells was demonstrated. In this design, the adenosine ribonucleotide at the scissile position of the 8-17 DNAzyme was replaced by 2'-O-nitrobenzyl adenosine, rendering the DNAzyme inactive and thus allowing its delivery into cells intact, protected from nonspecific degradation within cells. Irradiation at 365 nm restored DNAzyme activity, thus allowing the temporal control over the sensing activity of the DNAzyme for metal ions. The same strategy was also applied to the GR-5 DNAzyme for the detection of Pb(II), thus demonstrating the possible scope of the method.

An exceptionally simple strategy for DNA-functionalized up-conversion nanoparticles as biocompatible agents for nanoassembly, DNA delivery, and imaging.

Lanthanide-doped up-conversion nanoparticles (UCNPs) have shown promise in biomedical applications. However, as the UCNPs are normally capped with hydrophobic ligands, it remains challenging to prepare biocompatible UCNPs with specific molecular recognition capabilities. We herein report an exceptionally simple strategy to prepare uniform DNA-modified UCNPs as versatile bioprobes. The approach can directly convert as-prepared hydrophobic UCNPs into water-soluble DNA-UCNPs without any chemical modification of UCNPs or oligonucleotides. Furthermore, DNA molecules on the DNA-UCNPs retain their biorecognition ability, allowing programmable assembly of hybrid nanostructures. More importantly, we show that these DNA-UCNPs are capable of crossing cell membranes without the need of transfection agents, and their use as agents for bioimaging and DNA delivery are also demonstrated. Finally, DNA aptamer-conjugated UCNPs can be readily used for targeted imaging of cancer cells.

A DNAzyme-gold nanoparticle probe for uranyl ion in living cells.

DNAzymes have shown great promise as a general platform for detecting metal ions, as many metal-specific DNAzymes can be obtained using in vitro selection. While DNAzyme-based metal sensors have found many applications in the extracellular environment, no intracellular application of DNAzyme sensors has yet been reported. Here, we demonstrate a novel type of metal ion sensor for intracellular metal ion detection. The probe consists of a 13 nm gold nanoparticle (AuNP) core functionalized with a shell consisting of a uranyl-specific 39E DNAzyme whose enzyme strand contains a thiol at the 3' end for conjugation to the AuNP, and whose substrate strand is modified with a Cy3 fluorophore at the 5' end and a molecular quencher at the 3' end. In the absence of uranyl, the fluorescence of the Cy3 is quenched by both AuNP and the molecular quencher. In the presence of uranyl, the DNAzyme cleaves the fluorophore-labeled substrate strand, resulting in release of the shorter product strand containing the Cy3 and increased fluorescence. We demonstrate that this DNAzyme-AuNP probe can readily enter cells and can serve as a metal ion sensor within a cellular environment, making it the first demonstration of DNAzymes as intracellular metal ion sensors. Such a method can be generally applied to the detection of other metal ions using other DNAzymes selected through in vitro selection.