Single-atom nanozymes with peroxidase-like activity: A review.

Single-atom nanozymes (SANs) are nanomaterials-based nanozymes with atomically dispersed enzyme-like active sites. SANs offer improved as well as tunable catalytic activity. The creation of extremely effective SANs and their potential uses have piqued researchers' curiosity due to their advantages of cheap cost, variable catalytic activity, high stability, and large-scale production. Furthermore, SANs with uniformly distributed active centers and definite coordination structures offer a distinctive opportunity to investigate the structure-activity correlation and control the geometric and electrical features of metal centers. SANs have been extensively explored in photo-, thermal-, and electro-catalysis. However, SANs suffer from the following disadvantages, such as efficiency, non-mimicking of the 3-D complexity of natural enzymes, limited and narrow range of artificial SANs, and biosafety aspects. Among a quite limited range of artificial SANs, the peroxidase action of SANs has attracted significant research attention in the last five years with the aim of producing reactive oxygen species for use in cancer therapy, and water treatment among many other applications. In this review, we explore the recent progress of different SANs as peroxidase mimics, the role of the metal center in enzymatic activity, possible prospects, and underlying limitations in real-time applications.

Predicting firm creation in rural Texas: A multi-model machine learning approach to a complex policy problem.

Rural and urban America have becoming increasingly divided, both politically and economically. Entrepreneurship can help rural communities catch back up by jumpstarting economic growth, creating jobs, and building resilience to economic shocks. However, less is known about firm creation in rural areas compared to urban areas. To that end, in this paper we ask: What factors predict firm creation in rural America? Our analysis, based on a comparative framework involving multiple machine learning modeling techniques, helps addresses three gaps in academic literature on rural firm creation. First, entrepreneurship research stretches across disciplines, often using econometric methods to identify the effect of a specific variable, rather than comparing the predictive importance of multiple variables. Second, research on firm creation centers on high-tech, urban firms. Third, modern machine learning techniques have not yet been applied in an integrated way to address rural entrepreneurship, a complex economic and policy problem that defies simple, monocausal claims. In this paper, we apply four machine learning methods (subset selection, lasso, random forest, and extreme gradient boosting) to a novel dataset to examine what social and economic factors are predictive of firm growth in rural Texas counties from 2008-2018. Our results suggest that some factors commonly discussed as promoting entrepreneurship (e.g., access to broadband and patents) may not be as predictive as socioeconomic ones (age distribution, ethnic diversity, social capital, and immigration). We also find that the strength of specific industries (oil, wind, healthcare, and elder/childcare) predicts firm growth, as does the number of local banks. Most factors predictive of firm growth in rural counties are distinct from those in urban counties, supporting the argument that rural entrepreneurship is a distinct phenomenon worthy of distinct focus. More broadly, this multi-model approach can offer initial, focusing guidance to policymakers seeking to address similarly complex policy problems.

Information interventions can increase technology adoption through information network restructuring.

The rapid adoption of residential solar photovoltaic (PV) is recasting the role of individual households as a dynamic and potent construct critical for emissions mitigation and resilience of the electricity system. As residential PV enters more risk-averse customer segments, broader deployment of residential PV depends on overcoming both financial and informational barriers to adoption. Fast-changing residential PV technologies and associated policies means there is both lack of information and often misinformation among customers-gaps that are addressed effectively with local, trusted information networks, especially for big-ticket items such as residential PV. Here, we use an extensively validated agent-based model of residential PV adoption to analyze the effectiveness of different information intervention designs in spurring PV diffusion. We show that intervention designs are effective when they balance long-distance connections and local reinforcement, matching the intervention to both the informational needs of potential adopters and the structure of the underlying network.

Forecasting distributed energy resources adoption for power systems.

Failing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity-the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.

Laser-Assisted Sialolithotripsy: A Correlation of Objective and Subjective Outcomes.

OBJECTIVE: To analyze the long-term symptomatic results of laser-assisted sialolithotripsy (LAS) in cases of obstructive sialolithiasis and correlate with objective criteria using diagnostic sialendoscopy (DS) as a method of examination. METHODS: This is a retrospective study comprising 50 consecutive patients who underwent holmium-YAG LAS and completed follow-up of at least 6 months. Symptom scoring and endoscopic scoring were done at 6 weeks and 6 months intervals for further study purposes. RESULTS: At the end of 6 weeks post-LAS, 70% patients were asymptomatic (A-sym) and only 30% had residual symptoms (Sym). However, obstructed duct (OB-duct) was observed on endoscopic scoring in 88% due to stenosis, residual stones, or both stenosis and residual stones. The obstructed ducts were treated in outpatient clinic and followed up over time, leading to 98% of patients being in A-sym group at the end of study period of 6 months. At the end of study, 82% of patients had clear duct (CL-duct). CONCLUSION: Holmium LAS is a viable option for the management of intermediate-sized stones. LAS if used judiciously, and in properly selected cases, has high rate of stone fragmentation and symptom resolution. A vigilant postoperative protocol taking into account residual mealtime symptoms and altered salivary characteristics combined with early DS can help identify and treat patients with residual stone fragments and ductal stenosis. LEVEL OF EVIDENCE: 3 Laryngoscope, 132:2344-2349, 2022.

Policy and behavioral response to shock events: An agent-based model of the effectiveness and equity of policy design features.

In the aftermath of shock events, policy responses tend to be crafted under significant time constraints and high levels of uncertainty. The extent to which individuals comply with different policy designs can further influence how effective the policy responses are and how equitably their impacts are distributed in the population. Tools which allow policymakers to model different crisis trajectories, policy responses, and behavioral scenarios ex ante can provide crucial timely support in the decision-making process. Set in the context of COVID-19 shelter in place policies, in this paper we present the COVID-19 Policy Evaluation (CoPE) tool, which is an agent-based modeling framework that enables researchers and policymakers to anticipate the relative impacts of policy decisions. Specifically, this framework illuminates the extent to which policy design features and behavioral responsiveness influence the efficacy and equity of policy responses to shock events. We show that while an early policy response can be highly effective, the impact of the timing is moderated by other aspects of policy design such as duration and targeting of the policy, as well as societal aspects such as trust and compliance among the population. More importantly, we show that even policies that are more effective overall can have disproportionate impacts on vulnerable populations. By disaggregating the impact of different policy design elements on different population groups, we provide an additional tool for policymakers to use in the design of targeted strategies for disproportionately affected populations.

Reduced health services at under-electrified primary healthcare facilities: Evidence from India.

Primary healthcare systems worldwide suffer from major gaps in infrastructure and human resources. One key infrastructure gap is access to reliable electricity, absence of which can significantly affect the quantity and quality of healthcare services being delivered at rural primary health facilities. However, absence of granular empirical evidence is a barrier for quantitatively understanding the significance of electricity access as one of the determinants of access to reliable primary healthcare. Using data from India's District Level Household and Facility Survey, we develop zero-inflated negative binomial models with co-variates and state-level fixed effects to estimate the relationship between levels of electricity access and the quantity of basic health services delivered at Primary Health Centers (PHCs). We find that lack of electricity access is associated with a significant and large decrease in the number of deliveries (64 percent), number of in-patients (39 percent), and number of out-patients (38 percent). We further find that lower level of electricity access at primary health centers is disproportionately associated with adverse effects on women's access to safe and quality healthcare.

Largest De Novo Parapharyngeal Pleomorphic Adenoma: A Rare Case Removed Via Minimal Access Approach.

Parapharyngeal tumors are relatively rare tumors of head and neck. In general, pleomorphic adenoma is one of the most common benign tumor of the parapharyngeal region. Various approaches have been described in the literature for removal of parapharyngeal tumor with mandibulotomy generally carried out for large tumors. Here, we describe removal of a large parapharyngeal pleomorphic adenoma transcervically without mandibulotomy which subsequently turned out to be one of the largest ever reported in the literature and describe how large tumors of parapharyngeal can be removed with minimal invasive approach with mandibulotomy kept as a backup thereby avoiding complications associated with mandibulotomy.

Small Is Big: Interactive Trumps Passive Information in Breaking Information Barriers and Impacting Behavioral Antecedents.

The wealth of information available on seemingly every topic creates a considerable challenge both for information providers trying to rise above the noise and discerning individuals trying to find relevant, trustworthy information. We approach this information problem by investigating how passive versus interactive information interventions can impact the antecedents of behavior change using the context of solar energy adoption, where persistent information gaps are known to reduce market potential. We use two experiments to investigate the impact of both passive and interactive approaches to information delivery on the antecedents (attitudes, subjective norms, and perceived behavioral control in the Theory of Planned Behavior) of intentions and behavior, as well as their effect on intentions and behavior directly. The passive information randomized control trial delivered via Amazon Mechanical Turk tests the effectiveness of delivering the same content in a single message versus multiple shorter messages. The interactive information delivery uses an online (mobile and PC) trivia-style gamification platform. Both experiments use the same content and are carried out over a two-week time period. Our findings suggest that interactive, gamified information has greater impact than passive information, and that shorter multiple messages of passive information are more effective than a single passive message.

Filariasis of Stensen's Duct: An Index Case.

Filariasis, a neglected tropical disease, is a global health problem and is endemic to 73 countries including India. It is caused by nematodes of Filariodidea family, namely, W. bancrofti and B. malayi in India, which have a predilection for the lower limbs and testis. We report a never before reported case of filariasis of the main parotid duct in a 25-year-old male that resolved on medical management, exemplifying the importance of maintaining a high index of suspicion and careful examination of cytological smears in endemic countries, allowing for an early diagnosis and treatment, decreasing the morbidity of this debilitating disease.

Electrochemical lateral flow immunosensor for detection and quantification of dengue NS1 protein.

An Electrochemical Lateral Flow Immunosensor (ELFI) is developed combining screen-printed gold electrodes (SPGE) enabling quantification together with the convenience of a lateral flow test strip. A cellulose glassy fiber paper conjugate pad retains the marker immunoelectroactive nanobeads which will bind to the target analyte of interest. The specific immunorecognition event continues to occur along the lateral flow bed until reaching the SPGE-capture antibodies at the end of the cellulosic lateral flow strip. The rationale of the immunoassay consists in the analyte antigen NS1 protein being captured selectively and specifically by the dengue NS1 antibody conjugated onto the immunonanobeads thus forming an immunocomplex. With the aid of a running buffer, the immunocomplexes flow and reach the immuno-conjugated electrode surface and form specific sandwich-type detection due to specific, molecular recognition, while unbound beads move along past the electrodes. The successful sandwich immunocomplex formation is then recorded electrochemically. Specific detection of NS1 is translated into an electrochemical signal contributed by a redox label present on the bead-immobilized detection dengue NS1 antibody while a proportional increase of faradic current is observed with increase in analyte NS1 protein concentration. The first generation ELFI prototype is simply assembled in a cassette and successfully demonstrates wide linear range over a concentration range of 1-25 ng/mL with an ultrasensitive detection limit of 0.5 ng/mL for the qualitative and quantitative detection of analyte dengue NS1 protein.

Navigation in endoscopic sinus surgery: the first Indian experience.

Although the use of image guidance surgery (IGS) is standard practice in developed countries, it has not been in use in Indian Otolaryngology ever since its clinical inception in 1994. Some clinically interesting applications, relevant indications, practical tips and results in the Indian context are presented. Usage technique and data presentation. Indications based on AAO-HNS 2002 guidelines seem valid, and though the accuracy parameters remain still guarded, in line with the best technology available, based on the evidences of scattered reports and expert opinions, the use of navigation can be recommended as state of the art. IGS provides reliable information to a sinus surgeon in difficult circumstances. Its adaptation fortunately does not require a significant learning curve as it does not change the methodology of the surgical procedure. It can be an excellent teaching tool, but its use does not replace proper surgical training.

Electrochemical nanoporous alumina membrane-based label-free DNA biosensor for the detection of Legionella sp.

An electrochemical nanoporous alumina membrane-based label free DNA biosensor is developed using 5'-aminated DNA probes immobilized into the nanochannels of alumina. Alumina nanoporous membrane-like structure is carved over platinum wire electrode of 76 µm diameter dimension by electrochemical anodization. The hybridization of complementary target DNA with probe DNA molecules attached inside the nanochannels influences the pore size and ionic conductivity. Electrochemical biosensing signal is derived from only redox species Fe(CN)(6)(4-) across single wire Pt electrode. The biosensors sensing mechanism relies on the monitoring of electrode's Faradaic current response toward redox species, Fe(CN)(6)(4-), which is sensitive toward the hybridization of complementary target with probe DNA immobilized into the alumina nanochannels. The biosensor demonstrates wide linear range over 7 orders of magnitude with ultrasensitive detection limit 3.1×10(-13) M for the quantification of ss 21 mer DNA sequence and selectively differentiates the complementary sequence from target sequences with single base mismatch (MM1) and triple bases mismatch (MM3) of different strain of Legionella sp. Its applicability is also challenged against real time Legionella pneumophila genomic DNA sample derived from the asymmetric PCR method.

Ultrasensitive cDNA detection of dengue virus RNA using electrochemical nanoporous membrane-based biosensor.

A nanoporous alumina membrane-based ultrasensitive DNA biosensor is constructed using 5'-aminated DNA probes immobilized onto the alumina channel walls. Alumina nanoporous membrane-like structure is carved over platinum wire electrode of 76 µm diameter dimension by electrochemical anodization. The hybridization of complementary target DNA with probe DNA molecules attached inside the pores influences the pore size and ionic conductivity. The biosensor demonstrates linear range over 6 order of magnitude with ultrasensitive detection limit of 9.55×10(-12) M for the quantification of ss-31 mer DNA sequence. Its applicability is challenged against real time cDNA PCR sample of dengue virus serotype1 derived from asymmetric PCR. Excellent specificity down to one nucleotide mismatch in target DNA sample of DENV3 is also demonstrated.

Electrochemically amplified molecular beacon biosensor for ultrasensitive DNA sequence-specific detection of Legionella sp.

An electrochemically amplified molecular beacon (EAMB) biosensor is constructed using thiolated hairpin DNA-ferrocene probes on gold electrode. The switching from "on" to "off" states of individual probes in the presence of complementary DNA target influences the electrode potential, besides the current, owing to changes in surface density of the electroactive hairpin DNA-ferrocene probes. The EAMB biosensor demonstrates linear range over 8 orders of magnitude with ultrasensitive detection limit of 2.3 × 10(-14)M for the quantification of a 21-mer DNA sequence. Its applicability is tested against PCR amplicons derived from genomic DNA of live Legionella pneumophila. Excellent specificity down to one and three nucleotides mismatches in another strain of L. pneumophila and a different bacterium species, respectively, is demonstrated.