Transition from scattering to orbiting upon increasing the fuel concentration for an active Janus colloid moving at an obstacle-decorated interface.

Efficient exploration of space is a paramount motive for active colloids in practical applications. Yet, introducing activity may lead to surface-bound states, hindering efficient space exploration. Here, we show that the interplay between self-motility and fuel-dependent affinity for surfaces affects how efficiently catalytically-active Janus microswimmers explore both liquid-solid and liquid-fluid interfaces decorated with arrays of similarly-sized obstacles. In a regime of constant velocity vs. fuel concentration, we find that microswimmer-obstacle interactions strongly depend on fuel concentration, leading to a counter-intuitive decrease in space exploration efficiency with increased available fuel for all interfaces. Using experiments and theoretical predictions, we attribute this phenomenon to a largely overlooked change in the surface properties of the microswimmers' catalytic cap upon H2O2 exposure. Our findings have implications in the interpretation of experimental studies of catalytically active colloids, as well as in providing new handles to control their dynamics in complex environments.

New Linguistic Description Approach for Time Series and its Application to Bed Restlessness Monitoring for Eldercare.

Time series analysis has been an active area of research for years, with important applications in forecasting or discovery of hidden information such as patterns or anomalies in observed data. In recent years, the use of time series analysis techniques for the generation of descriptions and summaries in natural language of any variable, such as temperature, heart rate or CO2 emission has received increasing attention. Natural language has been recognized as more effective than traditional graphical representations of numerical data in many cases, in particular in situations where a large amount of data needs to be inspected or when the user lacks the necessary background and skills to interpret it. In this work, we describe a novel mechanism to generate linguistic descriptions of time series using natural language and fuzzy logic techniques. The proposed method generates quality summaries capturing the time series features that are relevant for a user in a particular application, and can be easily customized for different domains. This approach has been successfully applied to the generation of linguistic descriptions of bed restlessness data from residents at TigerPlace (Columbia, Missouri), which is used as a case study to illustrate the modeling process and show the quality of the descriptions obtained.

Active spheres induce Marangoni flows that drive collective dynamics.

For monolayers of chemically active particles at a fluid interface, collective dynamics is predicted to arise owing to activity-induced Marangoni flow even if the particles are not self-propelled. Here, we test this prediction by employing a monolayer of spherically symmetric active [Formula: see text] particles located at an oil-water interface with or without addition of a nonionic surfactant. Due to the spherical symmetry, an individual particle does not self-propel. However, the gradients produced by the photochemical fuel degradation give rise to long-ranged Marangoni flows. For the case in which surfactant is added to the system, we indeed observe the emergence of collective motion, with dynamics dependent on the particle coverage of the monolayer. The experimental observations are discussed within the framework of a simple theoretical mean-field model.

Conformation-changing enzymes and macromolecular crowding.

We study how crowding affects the activity and catalysis-enhanced diffusion of enzymes and passive tracers by employing a fluctuating-dumbbell model of conformation-changing enzymes. Our Brownian dynamics simulations reveal that the diffusion of enzymes depends qualitatively on the type of crowding. If only enzymes are present in the system, the catalysis-induced enhancement of the enzyme diffusion - somewhat counter-intuitively - increases with crowding, while it decreases if crowding is due to inert particles. For the tracers, the diffusion enhancement increases with increasing the enzyme concentration. We also show how the enzyme activity is reduced by crowding and propose a simple expression to describe this reduction. Our results highlight subtle effects at play concerning enzymatic activity and macromolecular transport in crowded systems, such as, e.g., the interior of living cells.

Home blood pressure data visualization for the management of hypertension: using human factors and design principles.

BACKGROUND: Home blood pressure measurements have equal or even greater predictive value than clinic blood pressure measurements regarding cardiovascular outcomes. With advances in home blood pressure monitors, we face an imminent flood of home measurements, but current electronic health record systems lack the functionality to allow us to use this data to its fullest. We designed a data visualization display for blood pressure measurements to be used for shared decision making around hypertension. METHODS: We used an iterative, rapid-prototyping, user-centred design approach to determine the most appropriate designs for this data display. We relied on visual cognition and human factors principles when designing our display. Feedback was provided by expert members of our multidisciplinary research team and through a series of end-user focus groups, comprised of either hypertensive patients or their healthcare providers required from eight academic, community-based practices in the Midwest of the United States. RESULTS: A total of 40 participants were recruited to participate in patient (N = 16) and provider (N = 24) focus groups. We describe the conceptualization and development of data display for shared decision making around hypertension. We designed and received feedback from both patients and healthcare providers on a number of design elements that were reported to be helpful in understanding blood pressure measurements. CONCLUSIONS: We developed a data display for substantial amounts of blood pressure measurements that is both simple to understand for patients, but powerful enough to inform clinical decision making. The display used a line graph format for ease of understanding, a LOWESS function for smoothing data to reduce the weight users placed on outlier measurements, colored goal range bands to allow users to quickly determine if measurements were in range, a medication timeline to help link recorded blood pressure measurements with the medications a patient was taking. A data display such as this, specifically designed to encourage shared decision making between hypertensive patients and their healthcare providers, could help us overcome the clinical inertia that often results in a lack of treatment intensification, leading to better care for the 35 million Americans with uncontrolled hypertension.

Disparities in Text Messaging Interventions to Improve Diabetes Management in the United States.

Substantial progress has been made in the development of evidence-based interventions to facilitate the management of type 2 diabetes. The increase in ownership of mobile phones has made short messaging services (SMS, or text messaging) a feasible way to enhance information delivery. The goals of this study were to 1) summarize characteristics of diabetes SMS interventions implemented in the United States and 2) identify the extent to which disadvantaged populations are represented in SMS-based diabetes management intervention studies. We conducted a literature search to identify published studies of type 2 diabetes self-management SMS interventions conducted with adults in the United States. Of the 792 articles retrieved, only 9 met inclusion criteria. We systematically extracted data on the theoretical basis, recruitment, incentives, inclusion/exclusion criteria, strategies toward ensuring a racially/ethnically or income-diverse sample, text message delivery, and study duration. Sixty-three percent of the participants across the nine studies were non-white. Only two studies reported participants' education level, and four captured non-English-speaking status. Interventions varied in offering one-way, two-way, or a combination of messaging strategies. Five studies did not describe cultural adaptations or report results separately for different cultural groups. None of the studies provided cell phones, and not having texting capability was an exclusion criterion for six studies. There is a dearth of published research on type 2 diabetes management interventions using text messaging among racially/ethnically or income-diverse populations. Future interventions should be better tailored to these target populations and include the collection of complete sociodemographic data and cell phone/smartphone availability, thereby ensuring cultural appropriateness.

Examining Social Networks in Text Messages About Nursing Home Resident Health Status.

Social network analysis (SNA) uses quantitative methods to analyze relationships between people. In the current study, SNA was applied in two nursing homes (NHs) to describe how health care teams interact via text messages. Two data sources were used: (a) a Qualtrics® survey completed by advanced practice RNs containing resident transfer data, and (b) text messages from a secure platform called Mediprocity™. SNA software was used to generate a visual representation of the social networks and calculate quantitative measures of network structure, including density, clustering coefficient, hierarchy, and centralization. Differences were found in the low and high transfer rate NHs for all SNA measures. Staff in the NH with low transfer rate had greater decision-making interactions, higher information exchange rates, and more individuals communicating with each other compared to the high transfer rate NH. SNA can be applied to examine communication patterns found in text messages occurring around the time of NH resident transfers. [Journal of Gerontological Nursing, 47(7), 16-22.].

Chemically Active Particles: From One to Few on the Way to Many.

Chemically active particles suspended in a liquid solution can achieve self-motility by locally changing the chemical composition of the solution via catalytic reactions at their surfaces. They operate intrinsically out of equilibrium, continuously extracting free energy from the environment to power the dissipative self-motility. The effective interactions involving active particles are, in general, nonreciprocal and anisotropic, even if the particles have simple shapes (e.g., Janus spheres). Accordingly, for chemically active particles a very rich behavior of collective motion and self-assembly may be expected to emerge, including phenomena such as microphase separation in the form of kinetically stable, finite-sized aggregates. Here, I succinctly review a number of recent experimental studies that demonstrate the self-assembly of structures, involving chemically active Janus particles, which exhibit various patterns of motion. These examples illustrate concepts such as "motors made out of motors" (as suggestively named by Fischer [Fischer, P. Nat. Phys. 2018, 14, 1072]). The dynamics of assembly and structure formation observed in these systems can provide benchmark, in-depth testing of the current understanding of motion and effective interactions produced by chemical activity. Finally, one notes that these significant achievements are likely just the beginning of the field. Recently reported particles endowed with time-dependent chemical activity or switchable reaction mechanisms open the way for exciting developments, such as periodic reshaping of self-assembled structures based on man-made internal clocks.

Floor- or Ceiling-Sliding for Chemically Active, Gyrotactic, Sedimenting Janus Particles.

Chemically active particles achieve motility without external forces and torques ("self-propulsion") due to catalytic chemical reactions at their surfaces, which change the chemical composition of the surrounding solution (called "chemical field") and induce hydrodynamic flow of the solution. By coupling the distortions of these fields back to its motion, a chemically active particle experiences an effective interaction with confining surfaces. This coupling can lead to a rich behavior, such as the occurrence of wall-bound steady states of "sliding". Most active particles are density mismatched with the solution and, thus, tend to sediment. Moreover, the often employed Janus spheres, which consist of an inert core material decorated with a cap-like, thin layer of a catalyst, are gyrotactic (i.e., "bottom-heavy"). Whether or not they may exhibit sliding states at horizontal walls depends on the interplay between the active motion and the gravity-driven sedimentation and alignment, such as the gyrotactic tendency to align the axis along the gravity direction being overcome by a competing, activity-driven alignment with a different orientation. It is therefore important to understand and quantify the influence of these gravity-induced effects on the behavior of model chemically active particles moving in the vicinity of walls. For model gyrotactic, self-phoretic Janus particles, here we study theoretically the occurrence of sliding states at horizontal planar walls that are either below ("floor") or above ("ceiling") the particle. We construct "state diagrams" characterizing the occurrence of such states as a function of the sedimentation velocity and of the gyrotactic response of the particle, as well as of the phoretic mobility of the particle. We show that in certain cases sliding states may emerge simultaneously at both the ceiling and the floor, while the larger part of the experimentally relevant parameter space corresponds to particles that would exhibit sliding states only either at the floor or at the ceiling-or there are no sliding states at all. These predictions are critically compared with the results of previous experimental studies, as well as with our dedicated experiments carried out with Pt-coated, polystyrene-core, or silica-core Janus spheres immersed in aqueous hydrogen peroxide solutions.

Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs.

BACKGROUND: Nearly half of US adults with diagnosed hypertension have uncontrolled blood pressure. Clinical inertia may contribute, including patient-physician uncertainty about how variability in blood pressures impacts overall control. Better information display may support clinician-patient hypertension decision making through reduced cognitive load and improved situational awareness. METHODS: A multidisciplinary team employed iterative user-centered design to create a blood pressure visualization EHR prototype that included patient-generated blood pressure data. An attitude and behavior survey and 10 focus groups with patients (N = 16) and physicians (N = 24) guided iterative design and confirmation phases. Thematic analysis of qualitative data yielded insights into patient and physician needs for hypertension management. RESULTS: Most patients indicated measuring home blood pressure, only half share data with physicians. When receiving home blood pressure data, 88% of physicians indicated entering gestalt averages as text into clinical notes. Qualitative findings suggest that including a data visualization that included home blood pressures brought this valued data into physician workflow and decision-making processes. Data visualization helps both patients and physicians to have a fuller understanding of the blood pressure 'story' and ultimately promotes the activated engaged patient and prepared proactive physician central to the Chronic Care Model. Both patients and physicians expressed concerns about workflow for entering and using home blood pressure data for clinical care. CONCLUSIONS: Our user-centered design process with physicians and patients produced a well-received blood pressure visualization prototype that includes home blood pressures and addresses patient-physician information needs. Next steps include evaluating a recent EHR visualization implementation, designing annotation functions aligned with users' needs, and addressing additional stakeholders' needs (nurses, care managers, caregivers). This significant innovation has potential to improve quality of care for hypertension through better patient-physician understanding of control and goals. It also has the potential to enable remote monitoring of patient blood pressure, a newly reimbursed activity, and is a strong addition to telehealth efforts.

Tracking personalized functional health in older adults using geriatric assessments.

BACKGROUND: Higher levels of functional health in older adults leads to higher quality of life and improves the ability to age-in-place. Tracking functional health objectively could help clinicians to make decisions for interventions in case of health deterioration. Even though several geriatric assessments capture several aspects of functional health, there is limited research in longitudinally tracking personalized functional health of older adults using a combination of these assessments. METHODS: We used geriatric assessment data collected from 150 older adults to develop and validate a functional health prediction model based on risks associated with falls, hospitalizations, emergency visits, and death. We used mixed effects logistic regression to construct the model. The geriatric assessments included were Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Short Form 12 (SF12). Construct validators such as fall risks associated with model predictions, and case studies with functional health trajectories were used to validate the model. RESULTS: The model is shown to separate samples with and without adverse health event outcomes with an area under the receiver operating characteristic curve (AUC) of > 0.85. The model could predict emergency visit or hospitalization with an AUC of 0.72 (95% CI 0.65-0.79), fall with an AUC of 0.86 (95% CI 0.83-0.89), fall with hospitalization with an AUC of 0.89 (95% CI 0.85-0.92), and mortality with an AUC of 0.93 (95% CI 0.88-0.97). Multiple comparisons of means using Turkey HSD test show that model prediction means for samples with no adverse health events versus samples with fall, hospitalization, and death were statistically significant (p < 0.001). Case studies for individual residents using predicted functional health trajectories show that changes in model predictions over time correspond to critical health changes in older adults. CONCLUSIONS: The personalized functional health tracking may provide clinicians with a longitudinal view of overall functional health in older adults to help address the early detection of deterioration trends and decide appropriate interventions. It can also help older adults and family members take proactive steps to improve functional health.

Using Sensor Signals in the Early Detection of Heart Failure: A Case Study.

Early detection of heart failure in older adults will be a significant issue for the foreseeable future. The current article presents a case study to describe how monitoring ballistocardiogram (BCG) waveforms captured non-invasively using sensors placed under a bed mattress can detect early heart failure changes. Heart and respiratory rates obtained from the bed sensor of a female older adult who was hospitalized with acute mixed congestive heart failure, clinic notes, and data from computer simulations reflecting increasing diastolic dysfunction were analyzed. Mean heart and respiratory rate trends obtained from her bed sensor in the prior 2 months did not indicate heart failure. BCG waveforms resulting from the simulations demonstrated changes associated with decreasing cardiac output as diastolic function worsened. Developing new methods for clinically interpreting BCG waveforms presents a significant opportunity for improving early heart failure detection. [Journal of Gerontological Nursing, 46(7), 41-46.].

ENVISION: A Tool to Improve Communication in Hospice Interdisciplinary Team Meetings.

Hospice interdisciplinary teams (IDTs) are required to meet regularly to update care plans for terminally ill patients and their family caregivers. Although providers see value in these meetings, they also experience frustration over meeting inefficiencies and communication challenges. The current article presents ENVISION, a tool designed to improve communication in hospice IDT meetings by providing attendees with access to up-to-date patient and family data to inform clinical decision making. In the current qualitative descriptive study, researchers explored the perspectives of hospice providers (n = 21) and family caregivers (n = 10) regarding ENVISION's usefulness and ease of use. Numerous factors influenced participants' perceptions of the tool as useful, including its impact on task efficiency, effectiveness, and difficulty. Perceptions of ENVISION's ease of use focused on ease of learning, operating, and interpreting data the tool provided. Findings suggest ENVISION would benefit hospice nurses in care management and senior leadership positions. [Journal of Gerontological Nursing, 46(7), 9-14.].

Effective Interactions between Chemically Active Colloids and Interfaces.

Chemically active colloids can achieve force- and torque-free motility ("self-propulsion") via the promotion, on their surface, of catalytic chemical reactions involving the surrounding solution. Such systems are valuable both from a theoretical perspective, serving as paradigms for nonequilibrium processes, as well as from an application viewpoint, according to which active colloids are envisioned to play the role of carriers ("engines") in novel lab-on-a-chip devices. The motion of such colloids is intrinsically connected with a "chemical field", i.e., the distribution near the colloid of the number densities of the various chemical species present in the solution, and with the hydrodynamic flow of the solution around the particle. In most of the envisioned applications, and in virtually all reported experimental studies, the active colloids operate under spatial confinement (e.g., within a microfluidic channel, a drop, a free-standing liquid film, etc.). In such cases, the chemical field and the hydrodynamic flow associated with an active colloid are influenced by any nearby confining surfaces, and these disturbances couple back to the particle. Thus, an effective interaction with the spatial confinement arises. Consequently, the particle is endowed with means to perceive and to respond to its environment. Understanding these effective interactions, finding the key parameters which control them, and designing particles with desired, preconfigured responses to given environments, require interdisciplinary approaches which synergistically integrate methods and knowledge from physics, chemistry, engineering, and materials science. Here we review how, via simple models of chemical activity and self-phoretic motion, progress has recently been made in understanding the basic physical principles behind the complex behaviors exhibited by active particles near interfaces. First, we consider the occurrence of "interface-bounded" steady states of chemically active colloids near simple, nonresponsive interfaces. Examples include particles "sliding" along, or "hovering" above, a hard planar wall while inducing hydrodynamic flow of the solution. These states lay the foundations for concepts like the guidance of particles by the topography of the wall. We continue to discuss responsive interfaces: a suitable chemical patterning of a planar wall allows one to bring the particles into states of motion which are spatially localized (e.g., within chemical stripes or along chemical steps). These occur due to the wall responding to the activity-induced chemical gradients by generating osmotic flows, which encode the surface-chemistry of the wall. Finally, we discuss how, via activity-induced Marangoni stresses, long-ranged effective interactions emerge from the strong hydrodynamic response of fluid interfaces. These examples highlight how in this context a desired behavior can be potentially selected by tuning suitable parameters (e.g., the phoretic mobility of the particle, or the strength of the Marangoni stress at an interface). This can be accomplished via a judicious design of the surface chemistry of the particle and of the boundary, or by the choice of the chemical reaction in solution.

Effect of Health Information Technologies on Cardiovascular Risk Factors among Patients with Diabetes.

PURPOSE OF REVIEW: To identify a common effect of health information technologies (HIT) on the management of cardiovascular disease (CVD) risk factors among people with type 2 diabetes (T2D) across randomized control trials (RCT). RECENT FINDINGS: CVD is the most frequent cause of morbidity and mortality among patients with diabetes. HIT are effective in reducing HbA1c; however, their effect on cardiovascular risk factor management for patients with T2D has not been evaluated. We identified 21 eligible studies (23 estimates) with measurement of SBP, 20 (22 estimates) of DBP, 14 (17 estimates) of HDL, 14 (17 estimates) of LDL, 15 (18 estimates) of triglycerides, and 10 (12 estimates) of weight across databases. We found significant reductions in SBP, DBP, LDL, and TG, and a significant improvement in HDL associated with HIT. As adjuvants to standard diabetic treatment, HIT can be effective tools for improving CVD risk factors among patients with T2D, especially in those whose CVD risk factors are not at goal.

Dynamics near planar walls for various model self-phoretic particles.

For chemically active particles suspended in a liquid solution and moving by self-phoresis, the dynamics near chemically inert, planar walls is studied theoretically by employing various choices for the activity function, i.e., the spatial distribution of the sites where various chemical reactions take place. We focus on the case of solutions composed of electrically neutral species. This analysis extends previous studies of the case that the chemical activity can be modeled effectively as the release of a "product" molecular species from parts of the surface of the particle by accounting for annihilation of the product molecules by chemical reactions, either on the rest of the surface of the particle or in the volume of the surrounding solution. We show that, for the models considered here, the emergence of "sliding" and "hovering" wall-bound states is a generic, robust feature. However, the details of these states, such as the range of parameters within which they occur, depend on the specific model for the activity function. Additionally, in certain cases there is a reversal of the direction of the motion compared to the one observed if the particle is far away from the wall. We have also studied the changes of the dynamics induced by a direct interaction between the particle and the wall by including a short-ranged repulsive component to the interaction in addition to the steric one (a procedure often employed in numerical simulations of active colloids). Upon increasing the strength of this additional component, while keeping its range fixed, significant qualitative changes occur in the phase portraits of the dynamics near the wall: for sufficiently strong short-ranged repulsion, the sliding steady states of the dynamics are transformed into hovering states. Furthermore, our studies provide evidence for an additional "oscillatory" wall-bound steady state of motion for chemically active particles due to a strong, short-ranged, and direct repulsion. This kind of particle translates along the wall at a distance from it which oscillates between a minimum and a maximum.

Brownian dynamics assessment of enhanced diffusion exhibited by 'fluctuating-dumbbell enzymes'.

Recent experiments have reported that diffusion of enzymes can be enhanced in the presence of their substrates. Using a fluctuating dumbbell model of enzymes, it has been argued that such an enhancement can be rationalized by the reduction of the enzyme size and by the suppression of the hydrodynamically coupled conformational fluctuations, induced by binding a substrate or an inhibitor to the enzyme [Nano Lett. 2017, 17, 4415]. Herein, we critically examine these expectations via extensive Brownian dynamics simulations of a similar model. The numerical results show that neither of the two mechanisms can cause an enhancement comparable to that reported experimentally, unless very large, physically counter-intuitive, enzyme deformations are invoked.

Linguistic summarization of in-home sensor data.

INTRODUCTION: With the increase in the population of older adults around the world, a significant amount of work has been done on in-home sensor technology to aid the elderly age independently. However, due to the large amounts of data generated by the sensors, it takes a lot of effort and time for the clinicians to makes sense of this data. In this work, we develop a system to help make this data more useful by presenting it in the form of natural language. METHODS: We start by identifying important attributes in the sensor data that are relevant to the health of the elderly. We then develop algorithms to extract these important health related features from the sensor parameters and summarize them in natural language. We focus on making the natural language summaries to be informative, accurate and concise. RESULTS: We designed multiple surveys using real and synthetic data to validate the summaries produced by our algorithms. We show that the algorithms produce meaningful results comparable to human subjects. We also implemented our linguistic summarization system to produce summaries of data leading to health alerts derived from the sensor data. The system is running live in 110 apartments currently. By the means of retrospective case studies, we illustrate that the linguistic summaries are able to make the connection between changes in the sensor data and the health of the elderly. CONCLUSIONS: We present a system that extracts important clinically relevant features from in-home sensor data generated in the apartments of the elderly and summarize those features in natural language. The preliminary testing of our summarization system shows that it has the potential to help the clinicians utilize this data effectively.

Patient Judgments About Hypertension Control: The Role of Variability, Trends, and Outliers in Visualized Blood Pressure Data.

BACKGROUND: Uncontrolled hypertension is a significant health problem in the United States, even though multiple drugs exist to effectively treat this chronic disease. OBJECTIVE: As part of a larger project developing data visualizations to support shared decision making about hypertension treatment, we conducted a series of studies to understand how perceptions of hypertension control were impacted by data variations inherent in the visualization of blood pressure (BP) data. METHODS: In 3 Web studies, participants (internet sample of patients with hypertension) reviewed a series of vignettes depicting patients with hypertension; each vignette included a graph of a patient's BP. We examined how data visualizations that varied by BP mean and SD (Study 1), the pattern of change over time (Study 2), and the presence of extreme values (Study 3) affected patients' judgments about hypertension control and the need for a medication change. RESULTS: Participants' judgments about hypertension control were significantly influenced by BP mean and SD (Study 1), data trends (whether BP was increasing or decreasing over time-Study 2), and extreme values (ie, outliers-Study 3). CONCLUSIONS: Patients' judgment about hypertension control is influenced both by factors that are important predictors of hypertension related-health outcomes (eg, BP mean) and factors that are not (eg, variability and outliers). This study highlights the importance of developing data visualizations that direct attention toward clinically meaningful information.

Chemotaxis of Active Janus Nanoparticles.

While colloids and molecules in solution exhibit passive Brownian motion, particles that are partially covered with a catalyst, which promotes the transformation of a fuel dissolved in the solution, can actively move. These active Janus particles are known as "chemical nanomotors" or self-propelling "swimmers" and have been realized with a range of catalysts, sizes, and particle geometries. Because their active translation depends on the fuel concentration, one expects that active colloidal particles should also be able to swim toward a fuel source. Synthesizing and engineering nanoparticles with distinct chemotactic properties may enable important developments, such as particles that can autonomously swim along a pH gradient toward a tumor. Chemotaxis requires that the particles possess an active coupling of their orientation to a chemical gradient. In this Perspective we provide a simple, intuitive description of the underlying mechanisms for chemotaxis, as well as the means to analyze and classify active particles that can show positive or negative chemotaxis. The classification provides guidance for engineering a specific response and is a useful organizing framework for the quantitative analysis and modeling of chemotactic behaviors. Chemotaxis is emerging as an important focus area in the field of active colloids and promises a number of fascinating applications for nanoparticles and particle-based delivery.