OptiMo-LDLr: An Integrated In Silico Model with Enhanced Predictive Power for LDL Receptor Variants, Unraveling Hot Spot Pathogenic Residues

Familial hypercholesterolemia (FH) is an inherited metabolic disease affecting cholesterol metabolism, with 90% of cases caused by mutations in the LDL receptor gene (LDLR), primarily missense mutations. This study aims to integrate six commonly used predictive software to create a new model for predicting LDLR mutation pathogenicity and mapping hot spot residues. Six predictive-software are selected: Polyphen-2, SIFT, MutationTaster, REVEL, VARITY, and MLb-LDLr. Software accuracy is tested with the characterized variants annotated in ClinVar and, by bioinformatic and machine learning techniques all models are integrated into a more accurate one. The resulting optimized model presents a specificity of 96.71% and a sensitivity of 98.36%. Hot spot residues with high potential of pathogenicity appear across all domains except for the signal peptide and the O-linked domain. In addition, translating this information into 3D structure of the LDLr highlights potentially pathogenic clusters within the different domains, which may be related to specific biological function. The results of this work provide a powerful tool to classify LDLR pathogenic variants. Moreover, an open-access guide user interface (OptiMo-LDLr) is provided to the scientific community. This study shows that combination of several predictive software results in a more accurate prediction to help clinicians in FH diagnosis.

Bibliometric analysis of lupus nephritis in children from 1999 to 2022: A review

Lupus nephritis (LN) is a complication of systemic lupus erythematosus and a damaging disease of the kidney. The injury of LN in children is more serious than that in adults. However, the literature in this field is numerous and complex, which brings great challenges for researchers to extract information. The purpose of this study is to carry out bibliometric analysis and visualization of published literatures, and identify current research hotspots and future research trends in this field. Literature was retrieved from the Web Of Science database from 1999 to 2022. The literature was analyzed and visualized using Citespace 6.1.R6, VOSviewer 1.6.18, and Microsoft Excel 2019. A total of 1059 articles were included in this study. In the past 13 years, an increase in the number of publications every year. Brunner HI is the author with the highest number of published and cited papers in this field, followed by Wenderfer SE. The United States and China are the countries with the highest number of published papers. University Toronto is the most productive institution, followed by University Cincinnati. The most prolific journal was Pediatric nephrology (IF 2.67), followed by lupus (IF 2.21). Lupus was cited the most, followed by Pediatric nephrology. The keyword burst showed the earliest and longest burst was antiphospholipid antibody, validation/risk/rituximab/safety is the current research hotspot. The article with the highest number of citations was Hochberg MC 1997 published in Arthritis Rheum. This study provides valuable information summary for the field of LN in children, which is helpful to strengthen the cooperation among countries, institutions and authors, and promote the research in the field of LN in children.

Progress in TLE treatment from 2003 to 2023: scientific measurement and visual analysis based on CiteSpace

Objective

Temporal lobe epilepsy (TLE) is the most common cause of drug-resistant epilepsy and can be treated surgically to control seizures. In this study, we analyzed the relevant research literature in the field of temporal lobe epilepsy (TLE) treatment to understand the background, hotspots, and trends in TLE treatment research.

Methods

We discussed the trend, frontier, and hotspot of scientific output in TLE treatment research in the world in the last 20 years by searching the core collection of the Web of Science database. Excel and CiteSpace software were used to analyze the basic data of the literature.

Result

We identified a total of 2,051 publications on TLE treatment from 75 countries between 2003 and 2023. We found that the publication rate was generally increasing. The United States was the most publishing country; among the research institutions on TLE treatment, the University of California system published the most relevant literature and collaborated the most with other institutions. The co-citation of literature, keyword co-occurrence, and its clustering analysis showed that the early studies focused on open surgical treatment, mainly by lobectomy. In recent years, the attention given to stereotactic, microsurgery, and other surgical techniques has gradually increased, and the burst analysis indicated that new research hotspots may appear in the future in the areas of improved surgical procedures and mechanism research.

Nanosphere Lithography-Enabled Hybrid Ag-Cu Surface-Enhanced Raman Spectroscopy Substrates with Enhanced Absorption of Excitation Light

We demonstrated a low-cost, highly sensitive hybrid Ag-Cu substrate with enhanced absorption for the excitation laser beam via the nanosphere lithography technique. The hybrid Ag-Cu surface-enhanced Raman spectroscopy (SERS) substrate consists of a Cu nanoarray covered with Ag nanoparticles. The geometry of the deposited Cu nanoarray is precisely determined through a self-assembly nanosphere etching process, resulting in optimized absorption for the excitation laser beam. Further Raman enhancement is achieved by incorporating plasmonic hotspots formed by dense Ag nanoparticles, grown by immersing the prepared Cu nanoarray in a silver nitrate solution. The structural design enables analytical enhancement factor of hybrid Ag-Cu SERS substrates of 1.13 × 105. The Ag-Cu SERS substrates exhibit a highly sensitive and reproducible SERS activity, with a low detection limit of 10-13 M for Rhodamine 6G detection and 10-9 M for 4,4'-Bipyridine. Our strategy could pave an effective and promising approach for SERS-based rapid detection in biosensors, environmental monitoring and food safety.

Neighborhood Effect on Elderly Depression in Republic of Korea

This study analyzed the spatial distribution patterns of depression among vulnerable elderly across Republic of Korea. The average level of depression in the basic administrative districts was derived using the individual depression scores from the Health Interview Survey data. Results of the spatial autocorrelation analysis revealed that the Moran's I value was 0.3138, indicating the existence of a neighborhood effect in the depression of the vulnerable older adults at the regional level. Subsequently, cluster analysis and one-way ANOVA were conducted for the hot spots where vulnerable older adult depression was concentrated. Based on the cluster analysis results, hot spots were the areas where the facilities that are necessary for the daily lives of older adults were insufficient and were categorized into three types. The findings indicate that environmental characteristics at the regional level should be considered in addition to the environmental characteristics of the house and neighborhood, which have been primarily addressed in previous studies.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

Identifying Hot Spots of Tuberculosis in Nigeria Using an Early Warning Outbreak Recognition System: Retrospective Analysis of Implications for Active Case Finding Interventions

BACKGROUND

Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. An early warning outbreak recognition system (EWORS) is a system that is primarily used to detect infectious disease outbreaks; this system can be used as a case-based geospatial tool for the real-time identification of hot spot areas with clusters of TB patients. TB screening targeted at such hot spots should yield more TB cases than screening targeted at non-hot spots.

OBJECTIVE

We aimed to demonstrate the effectiveness of an EWORS for TB hot spot mapping as a tool for detecting areas with increased TB case yields in high TB-burden states of Nigeria.

METHODS

KNCV Tuberculosis Foundation Nigeria deployed an EWORS to 14 high-burden states in Nigeria. The system used an advanced surveillance mechanism to identify TB patients' residences in clusters, enabling it to predict areas with elevated disease spread (ie, hot spots) at the ward level. TB screening outreach using the World Health Organization 4-symptom screening method was conducted in 121 hot spot wards and 213 non-hot spot wards selected from the same communities. Presumptive cases identified were evaluated for TB using the GeneXpert instrument or chest X-ray. Confirmed TB cases from both areas were linked to treatment. Data from the hot spot and non-hot spot wards were analyzed retrospectively for this study.

RESULTS

During the 16-month intervention, a total of 1,962,042 persons (n=734,384, 37.4% male, n=1,227,658, 62.6% female) and 2,025,286 persons (n=701,103, 34.6% male, n=1,324,183, 65.4% female) participated in the community TB screening outreaches in the hot spot and non-hot spot areas, respectively. Presumptive cases among all patients screened were 268,264 (N=3,987,328, 6.7%) and confirmed TB cases were 22,618 (N=222,270, 10.1%). The number needed to screen to diagnose a TB case in the hot spot and non-hot spot areas was 146 and 193 per 10,000 people, respectively.

CONCLUSIONS

Active TB case finding in EWORS-mapped hot spot areas yielded higher TB cases than the non-hot spot areas in the 14 high-burden states of Nigeria. With the application of EWORS, the precision of diagnosing TB among presumptive cases increased from 0.077 to 0.103, and the number of presumptive cases needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 people.

Densest subgraph-based methods for protein-protein interaction hot spot prediction

Background

Hot spots play an important role in protein binding analysis. The residue interaction network is a key point in hot spot prediction, and several graph theory-based methods have been proposed to detect hot spots. Although the existing methods can yield some interesting residues by network analysis, low recall has limited their abilities in finding more potential hot spots.

Result

In this study, we develop three graph theory-based methods to predict hot spots from only a single residue interaction network. We detect the important residues by finding subgraphs with high densities, i.e., high average degrees. Generally, a high degree implies a high binding possibility between protein chains, and thus a subgraph with high density usually relates to binding sites that have a high rate of hot spots. By evaluating the results on 67 complexes from the SKEMPI database, our methods clearly outperform existing graph theory-based methods on recall and F-score. In particular, our main method, Min-SDS, has an average recall of over 0.665 and an f2-score of over 0.364, while the recall and f2-score of the existing methods are less than 0.400 and 0.224, respectively.

Conclusion

The Min-SDS method performs best among all tested methods on the hot spot prediction problem, and all three of our methods provide useful approaches for analyzing bionetworks. In addition, the densest subgraph-based methods predict hot spots with only one residue interaction network, which is constructed from spatial atomic coordinate data to mitigate the shortage of data from wet-lab experiments.

Engineered Design of the E-Helix Structure on Ferritin Nanoparticles

Insertion of an immunogenic epitope at the C-terminus of ferritin has shown the potential to produce a stable and efficacious vaccine. There is however limited understanding of how C-terminus insertion affects ferritin protein stability. The E-helix at the C-terminus has attracted interest because there are contradictory reports as to whether it has a role in protein stabilization. Here, we report, for the first time, combining molecular dynamics simulation (MDS) with experiment to engineer the design of the E-helix at the C-terminus of engineered human ferritin heavy chain (F₁) inserted with Epstein-Barr nuclear antigen 1 (EBNA1, E₁) and flexible linker (L₃) residues (to afford F₁L₃E₁). Hot spots on the E-helix of the C-terminus were predicted by MDS at aa 167 (Glu) and aa 171 (Asp). Five (5) variants of F₁L₃E₁ were constructed by considering hot spots and alteration of electrostatic or hydrophobic interfaces, namely, (1) C1, hot spots substituted with noncharged residue Gln; (2) C2, hot spots substituted with positively charged residue Arg; (3) C3, hydrophobic residues substituted with the most hydrophobic residues Val and Ile; (4) C4, hydrophobic residues substituted with the most hydrophilic residues Gln and Asn; and (5) C5, a heptad repeat structure in the E-helix disrupted by substituting "a" and "d" heptad residues with noncharged polar residue Gln. It was found that the E-helix is essential to maintain integrated protein stability and that changing the hydrophobic interface (C3 and C4) had more significant effects on protein folding and stability than changing the electrostatic interface (C1 and C2). It was confirmed by both MDS and experiment that variants C1, C2, and C5 were able to fold to form stable conformational structures with protein surface hydrophobicity similar to that of F₁L₃E₁. However, they are less thermally stable than F₁L₃E₁. Significant changes in hydrophobicity drove significant protein aggregation for variants C3 and C4. It is concluded that the molecular design of the C-terminus in engineered ferritin, especially the E-helix, is important to ensure the epitope-based chimeric vaccine is safe (aggregate free) and efficacious.

Lightweight Hot-Spot Fault Detection Model of Photovoltaic Panels in UAV Remote-Sensing Image

Photovoltaic panels exposed to harsh environments such as mountains and deserts (e.g., the Gobi desert) for a long time are prone to hot-spot failures, which can affect power generation efficiency and even cause fires. The existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both detection accuracy and speed is proposed. In this paper, the feature extraction part of YOLOv5 is replaced by the more lightweight Focus structure and the basic unit of ShuffleNetv2, and then the original feature fusion method is simplified. Considering that there is no publicly available infrared photovoltaic panel image dataset, this paper generates an infrared photovoltaic image dataset through frame extraction processing and manual annotation of a publicly available video. Consequently, the number of parameters of the model was 3.71 M, mAP was 98.1%, and detection speed was 49 f/s. A comprehensive comparison of the accuracy, detection speed, and model parameters of each model showed that the indicators of the new model are superior to other detection models; thus, the new model is more suitable to be deployed on the UAV platform for real-time photovoltaic panel hot-spot fault detection.

Critical assessment of methods for measurement of temperature profiles and heat load history in microwave heating processes-A review

Limitations of microwave processing due to inhomogeneities of power input and energy absorption have been widely described. Over- and underheated product areas influence reproducibility, product quality, and possibly safety. Although a broad range of methods is available for temperature measurement and evaluation of time/temperature effects, none of them is sufficiently able to detect temperature differences and thermally induced effects within the product caused by inhomogeneous heating. The purpose of this review is to critically assess different methods of temperature measurement for their suitability for different microwave applications, namely metallic temperature sensors, thermal imaging, pyrometer measurement, fiber optic sensors, microwave radiometry, magnetic resonance imaging, liquid crystal thermography, thermal paper, and biological and chemical time-temperature indicators. These methods are evaluated according to their advantages and limitations, method characteristics, and potential interference with the electric field. Special attention is given to spatial resolution, accuracy, handling, and purpose of measurement, that is, development work or online production control. Differences of methods and examples of practical application and failure in microwave-assisted food processing are discussed with a special focus on microwave pasteurization and microwave-assisted drying. Based on this assessment, it is suggested that infrared cameras for measuring temperature distribution at the product surface and partially inside the product in combination with a chemical time/temperature indicator (e.g., Maillard reaction, generating heat-induced color variations, depending on local energy absorption) appear to be the most appropriate system for future practical application in microwave food process control, microwave system development, and product design. Reliable detection of inhomogeneous heating is a prerequisite to counteracte inhomogeneity by a targeted adjustment of process and product parameters in microwave applications.

Self-Organized Fractal Structures on Plasma-Exposed Silver Surface

Planar fractal microstructure is observed on the silver film treated by positive corona discharge for the first time. Due to the abundant positive ions driven by the electrical field of positive polarity, surface modification is mainly induced by the plasma oxidation effect, resulting in a large scale of dendritic pattern with self-similarity and hierarchy. In contrast, negative ions dominate the plasma-film interaction under negative corona discharge condition, leading to a different surface morphology without fractal characteristics. A growth model based on the modified diffusion-limited aggregation (DLA) theory is proposed to describe the formation of the dendritic fractal structure, whilst the physics behind is attributed to the electric field directed diffusion of the positive ions around the surface roughness. Numerical simulation verifies the high density of the hot spot in the dendritic pattern, which may enable potential applications in fractal photonic metamaterials.

A feature-based approach to predict hot spots in protein-DNA binding interfaces

DNA-binding hot spot residues of proteins are dominant and fundamental interface residues that contribute most of the binding free energy of protein-DNA interfaces. As experimental methods for identifying hot spots are expensive and time consuming, computational approaches are urgently required in predicting hot spots on a large scale. In this work, we systematically assessed a wide variety of 114 features from a combination of the protein sequence, structure, network and solvent accessible information and their combinations along with various feature selection strategies for hot spot prediction. We then trained and compared four commonly used machine learning models, namely, support vector machine (SVM), random forest, Naïve Bayes and k-nearest neighbor, for the identification of hot spots using 10-fold cross-validation and the independent test set. Our results show that (1) features based on the solvent accessible surface area have significant effect on hot spot prediction; (2) different but complementary features generally enhance the prediction performance; and (3) SVM outperforms other machine learning methods on both training and independent test sets. In an effort to improve predictive performance, we developed a feature-based method, namely, PrPDH (Prediction of Protein-DNA binding Hot spots), for the prediction of hot spots in protein-DNA binding interfaces using SVM based on the selected 10 optimal features. Comparative results on benchmark data sets indicate that our predictor is able to achieve generally better performance in predicting hot spots compared to the state-of-the-art predictors. A user-friendly web server for PrPDH is well established and is freely available at http://bioinfo.ahu.edu.cn:8080/PrPDH.

Predicting the distribution of foraging seabirds during a period of heightened environmental variability

Quantifying the links between the marine environment, prey occurrence, and predator distribution is the first step towards identifying areas of biological importance for marine spatial planning. Events such as marine heatwaves result in an anomalous change in the physical environment, which can lead to shifts in the structure, biomass, and distribution of lower trophic levels. As central-place foragers, seabirds are vulnerable to changes in their foraging grounds during the breeding season. We first quantified spatiotemporal variability in the occurrence and biomass of prey in response to an abrupt change in oceanography as a result of a marine heatwave event. Secondly, using multivariate techniques and machine learning, we investigated if differences in the foraging technique and prey of seabirds resulted in varying responses to changes in prey occurrence and the environment over a 2.5-yr period. We found that the main variables correlated with seabird distribution were also important in structuring the occurrence and biomass of prey; sea-surface temperature (SST), current speed, mixed-layer depth, and bathymetry. Both zooplankton biomass and the occurrence of fish schools exhibited negative relationships with temperature, and temperature was subsequently an important variable in determining seabird distribution. We were able to establish correlations between the distribution of prey and the spatiotemporal distribution of albatross, little penguins and common-diving petrels. We were unable to find a correlation between the distribution of prey and that of short-tailed shearwaters and fairy prions. For high-use coastal areas, the delineation of important foraging regions is essential to balance human use of an area with the needs of marine predators, particularly seabirds.

Druggable hot spots in trypanothione reductase: novel insights and opportunities for drug discovery revealed by DRUGpy

Assessment of target druggability guided by search and characterization of hot spots is a pivotal step in early stages of drug-discovery. The raw output of FTMap provides the data to perform this task, but it relies on manual intervention to properly combine different sets of consensus sites, therefore allowing identification of hot spots and evaluation of strength, shape and distance among them. Thus, the user's previous experience on the target and the software has a direct impact on how data generated by FTMap server can be explored. DRUGpy plugin was developed to overcome this limitation. By automatically assembling and scoring all possible combinations of consensus sites, DRUGpy plugin provides FTMap users a straight-forward method to identify and characterize hot spots in protein targets. DRUGpy is available in all operating systems that support PyMOL software. DRUGpy promptly identifies and characterizes pockets that are predicted by FTMap to bind druglike molecules with high-affinity (druggable sites) or low-affinity (borderline sites) and reveals how protein conformational flexibility impacts on the target's druggability. The use of DRUGpy on the analysis of trypanothione reductases (TR), a validated drug target against trypanosomatids, showcases the usefulness of the plugin, and led to the identification of a druggable pocket in the conserved dimer interface present in this class of proteins, opening new perspectives to the design of selective inhibitors.

Cholera Hot-Spots and Contextual Factors in Burundi, Planning for Elimination

The Republic of Burundi first reported cholera cases in 1978 and outbreaks have been occurring nearly every year since then. From 2008-2020, 6949 cases and 43 deaths were officially reported. To evaluate Burundi's potential to eliminate cholera, we identified hotspots using cholera incidence and disease persistence as suggested by the Global Task Force for Cholera Control. The mean annual incidence for each district that reported cholera ranged from 0.29 to 563.14 cases per 100,000 population per year from 2014-2020. Ten of 12 Health Districts which recorded cholera cases reported a mean annual incidence ≥5 per 100,000 for this time period. Cholera cases occur during the second half of the year in the areas near Lake Tanganyika and along the Ruzizi River, with the highest risk district being Bujumbura Centre. Additional research is needed to understand the role of Lake Tanganyika; risks associated with fishing; migration patterns; and other factors that may explain cholera's seasonality. Due to the consistent epidemiological pattern and the relatively small area affected by cholera, control and elimination are feasible with an integrated program of campaigns using oral cholera vaccine over the short term and community-based interventions including WASH activities for sustained control.

SARS-CoV-2 hot-spot mutations are significantly enriched within inverted repeats and CpG island loci

SARS-CoV-2 is an intensively investigated virus from the order Nidovirales (Coronaviridae family) that causes COVID-19 disease in humans. Through enormous scientific effort, thousands of viral strains have been sequenced to date, thereby creating a strong background for deep bioinformatics studies of the SARS-CoV-2 genome. In this study, we inspected high-frequency mutations of SARS-CoV-2 and carried out systematic analyses of their overlay with inverted repeat (IR) loci and CpG islands. The main conclusion of our study is that SARS-CoV-2 hot-spot mutations are significantly enriched within both IRs and CpG island loci. This points to their role in genomic instability and may predict further mutational drive of the SARS-CoV-2 genome. Moreover, CpG islands are strongly enriched upstream from viral ORFs and thus could play important roles in transcription and the viral life cycle. We hypothesize that hypermethylation of these loci will decrease the transcription of viral ORFs and could therefore limit the progression of the disease.

Relationship Between COVID-19-Infected Number and PM2.5 Level in Ambient Air of Bangkok, Thailand

Several empirical studies of reductions in air pollutants as social distancing and working from home (WFH) policies have sparked recommendations that the COVID-19 pandemic might have been responsible for better air quality particularly in urban area. These findings offer a compelling provocation for the scientific community to detect and investigate variations to air quality as a consequence of government enforced quarantine. In spite of countless research studies focusing on the connection between WFH policy and air pollutant levels, the majority of discussion has unfortunately ignored the central role of other potential sources (e.g. agricultural waste burnings, cooking emissions, and industrial releases) in governing air quality, or has neglected the psychological and social impacts of COVID-19. In this study, a t test was used to compare the average concentrations of PM_2.5 and COVID-19-infected numbers (n) in three different periods which were n < 300 vs. n ≧ 300, n < 500 vs. n ≧ 500, and n < 700 vs. n ≧ 700. Some significant differences were observed in the groups of n < 500 vs. n ≧ 500, and n < 700 vs. n ≧ 700 indicating that the psychological and social impacts play a crucial role in restricting daily activities and thus reducing the atmospheric contents of PM_2.5 in some areas. Further assessments were conducted by separating PM_2.5 contents into three different periods (i.e. Period-I: day-1 ~ day-10; Period-II: day-11 ~ day-20; Period-III: day-21 ~ day-31). Some significant reductions of PM_2.5 during the Period-I were detected in the eastern area of Bangkok. In addition, Pearson correlation analysis showed that hot-spot numbers appear to be a minor of importance in controlling PM_2.5 levels in the ambient air of Bangkok, Thailand.

A GNSS-Based Crowd-Sensing Strategy for Specific Geographical Areas

Infectious diseases, such as COVID-19, SARS, MERS, etc., have seriously endangered human safety, economy, and education. During the spread of epidemics, restricting the range of activities of personnel is one of the options for the prevention and treatment of infectious diseases. A global navigation satellite system (GNSS), it can provide accurate coordinates of latitude and longitude to targets with GNSS receivers. However, it is not common to use GNSS coordinates to represent positions in social life. For epidemic management, it is important to know the locations (and addresses) of targets, especially in social life. When there are many targets, it is not easy to efficiently map these coordinates to locations. Therefore, we propose a GNSS-based crowd-sensing strategy for specific geographical areas that can be used to calculate how many targets are in specific geographical areas or whether a target is in a specific area. This strategy is based on the coordinates of latitude and longitude provided by GNSS to find the locations of these coordinates. As simulated data, the data records containing latitude and longitude in a well-known social networking service platform are used. The strategy is also available for mining hot spots or hot areas.

The Death of Freddie Gray and Its Impact on Homicides in Baltimore and Maryland

This study evaluated the impact that Freddie Gray's death on April, 19, 2015, had on homicides within Baltimore, Prince George's County, and the rest of Maryland. The numbers of these deaths were compared in the 2 years prior and after his death. The average number of homicide per month in Baltimore and Prince George's County, but not the rest of Maryland, showed a statistically significant increase in the 2 years after his death, with a sudden spike in homicides in Baltimore immediately following his death. Spatial density ("heat") maps of homicides showed an increase in clustering of deaths after Freddie Gray's demise in portions of Baltimore, particularly near his arrest site. Hot spot maps showed a massive expansion of statistically significant clusters of homicides in areas of West and East Baltimore after his death. An emerging hot spot analysis revealed consecutive hot spots in large areas of West Baltimore with new hot spots prominent along the southern edge of this area. A review of the history of Baltimore, as well as discussions with Baltimore homicide detectives, revealed that prior socioeconomic and political trends likely primed Baltimore for the protests and violence that occurred after Freddie Gray's death. It is probable that a perceived "overcharging" of officers involved in his death by the State's Attorney resulted in a "pullback" from policing that directly led to increased homicides in Baltimore.

Facile In Situ Photochemical Synthesis of Silver Nanoaggregates for Surface-Enhanced Raman Scattering Applications

Recently, photochemical synthesis has attracted wide interest on in situ preparing the surface-enhanced Raman scattering (SERS) substrate with excellent performance, especially in a compact space and microfluidic channel. Herein, a facile, green and cost-effective approach to in situ photochemically synthesize silver nanoaggregates is demonstrated for SERS applications. By adjusting the photo-irradiation conditions, the morphologies and sizes of the silver nanoaggregates can be deliberately tailored. The synthesized silver nanoaggregates-based substrates exhibit a highly sensitive and reproducible SERS activity with a low detection limit of 10^-8 M for 4-Aminothiophenol detection and relative standard deviation of 12.3%, paving an efficient and promising route for in situ SERS-based rapid detection in the environmental monitoring and food quality control.

Investigating the Effect of Lockdown During COVID-19 on Land Surface Temperature: Study of Dehradun City, India

Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in Dehradun city. The TIRS sensor data of 14 April 2020 (post-lockdown), 28 April 2019, 25 April 2018 and 08 May 2017 were downloaded, and LST was retrieved using radiative transfer equation. The wardwise change in LST, urban hot spots and thermal comfort was studied as a function of built-up density. It was observed that there was an overall decrease in LST values in Dehradun city in post-COVID lockdown period. Wards with high built-up density had minimum decrease in LST; on the contrary, wards with large proportion of open spaces and having low, medium built-up density had the maximum decrease in LST. Hot spot analysis was carried out using Getis Ord GI* statistic, and the level of thermal comfort was found using the urban thermal field variance index. It was observed that there was an increase in number of hot spots accompanied by a decrease in thermal comfort level post-lockdown. The methodology proposed in the present study can be applied to other Indian cities which exhibit similar growth patterns and will provide a tool for rational decision making.

Graphene-Based Spatial Light Modulator Using Metal Hot Spots

Here, we report a graphene-based electric field enhancement structure achieved by several adjacent metal nanoribbons which form the hot spots of the electric field and thus promote the absorption of the single layered graphene below the hot spots. Based on the tunability of the graphene's Fermi level, the absorption rate can be modulated from near 100% to 35% under low electrostatic gating, leading to a 20 dB modulation depth of reflectance. Compared with the existing near infrared spatial light modulators such as optical cavities integrated with graphene and other structures utilizing patterned or highly doped graphene, our design has the advantages of strong optical field enhancement, low power dissipation and high modulation depth. The proposed electro-optic modulator has a promising potential for developing optical communication and exploiting big data interaction systems.

Proteomics for cancer drug design

Introduction: Signal transduction cascades drive cellular proliferation, apoptosis, immune, and survival pathways. Proteins have emerged as actionable drug targets because they are often dysregulated in cancer, due to underlying genetic mutations, or dysregulated signaling pathways. Cancer drug development relies on proteomic technologies to identify potential biomarkers, mechanisms-of-action, and to identify protein binding hot spots. Areas covered: Brief summaries of proteomic technologies for drug discovery include mass spectrometry, reverse phase protein arrays, chemoproteomics, and fragment based screening. Protein-protein interface mapping is presented as a promising method for peptide therapeutic development. The topic of biosimilar therapeutics is presented as an opportunity to apply proteomic technologies to this new class of cancer drug. Expert opinion: Proteomic technologies are indispensable for drug discovery. A suite of technologies including mass spectrometry, reverse phase protein arrays, and protein-protein interaction mapping provide complimentary information for drug development. These assays have matured into well controlled, robust technologies. Recent regulatory approval of biosimilar therapeutics provides another opportunity to decipher the molecular nuances of their unique mechanisms of action. The ability to identify previously hidden protein hot spots is expanding the gamut of potential drug targets. Proteomic profiling permits lead compound evaluation beyond the one drug, one target paradigm.

TAEO-A Thermal Aware & Energy Optimized Routing Protocol for Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are in the spotlight of researchers and engineering industries due to many applications. Remote health monitoring for general as well as military purposes where tiny sensors are attached or implanted inside the skin of the body to sense the required attribute is particularly prominent. To seamlessly accomplish this procedure, there are various challenges, out of which temperature control to reduce thermal effects and optimum power consumption to reduce energy wastage are placed at the highest priority. Regular and consistent operation of a sensor node for a long-time result in a rising of the temperature of respective tissues, where it is attached or implanted. This temperature rise has harmful effects on human tissues, which may lead to the tissue damage. In this paper, a Temperate Aware and Energy Optimized (TAEO) routing protocol is proposed that not only deals with the thermal aspects and hot spot problem, but also extends the stability and lifetime of a network. Analytical simulations are conducted, and the results depict better performance in terms of the network lifetime, throughput, energy preservation, and temperature control with respect to state of the art WBAN protocols.

Molecular subtyping of gastric cancer combining genetic and epigenetic anomalies provides distinct clinicopathological features and prognostic impacts

Both genetic and epigenetic abnormalities play important roles in gastric cancer (GC) development. We investigated whether the molecular subtypes of gastric cancer by combining genetic and epigenetic anomalies define its clinicopathological features and prognosis. The CpG island methylator phenotype (CIMP), MLH1 methylation, TP53, and KRAS mutation statuses were characterized in 214 GCs in relation to their clinicopathological features and prognosis. The molecular subtypes based on CIMP and TP53 hot spot mutation status (R175, G245, R248, R273, and R282) best predicted prognosis of GC. These subtypes contained 120 CIMP-positive (CIMP+) TP53 hot spot mutation-negative (TP53 hot spot-) cases, 81 CIMP-negative (CIMP-) TP53 hot spot- cases, 8 CIMP+TP53 hot spot mutation-positive (TP53 hot spot+) cases, and 5 CIMP- TP53 hot spot+ cases. The CIMP-TP53 hot spot+ group presented the worst overall survival (OS) and progression-free survival (PFS), followed by the CIMP+TP53 hot spot+, CIMP-TP53 hot spot- and CIMP+TP53 hot spot- groups (both P < 0.0001). These subtypes also correlated well with several aggressive clinicopathological features in that order. The molecular subtypes were independent factors for predicting overall survival (hazard ratio = 1.66, 95% CI = 1.07-2.57, P = 0.006). The molecular subtypes combining the CIMP and TP53 hot spot mutation status provide distinct clinicopathological features and prognostic impacts in GC.

Genetic Analysis of KRT9 Gene Revealed Previously Known Mutations and Genotype-Phenotype Correlations in Epidermolytic Palmoplantar Keratoderma

Epidermolytic palmoplantar keratoderma (EPPK, OMIM 144200) is an autosomal dominant inherited disease, clinically characterized by diffuse yellowish thickening of the skin on the palms and soles, usually with erythematous borders developing during the first weeks or months after birth. Pathogenesis of EPPK is determined by mutations in the keratin gene (KRT9). Thirty three mutations in the KRT9 gene from 100 EPPK families have been identified. Among these, 23 mutations are located in the 1A region (a mutation hot spot region), 7 are located in the 2B region, and the remaining 3 are synonymous mutations. In this study, three heterozygous mutations (p.N161S, p.R163W, and p.R163Q), located in regions of the gene encoding the conserved central a-helix rod domain, were detected in the KRT9 gene of the three large Chinese families. This study confirms that codon 163 (48 of 100 cases) is a hot spot mutation site for KRT9. Additional findings identified p.N161S (4%) and p.R163W (4%) as potential hot spot mutations for EPPK associated with knuckle pads, and p.R163Q (15 of 100 cases) as the hot spot mutation of EPPK not occurring in combination with knuckle pads. In conjunction with future studies, this research may help lay the foundation for genetics counseling, prenatal diagnosis and clinical treatment of EPPK.

Multiple Exon Skipping in the Duchenne Muscular Dystrophy Hot Spots: Prospects and Challenges

Duchenne muscular dystrophy (DMD), a fatal X-linked recessive disorder, is caused mostly by frame-disrupting, out-of-frame deletions in the dystrophin (DMD) gene. Antisense oligonucleotide-mediated exon skipping is a promising therapy for DMD. Exon skipping aims to convert out-of-frame mRNA to in-frame mRNA and induce the production of internally-deleted dystrophin as seen in the less severe Becker muscular dystrophy. Currently, multiple exon skipping has gained special interest as a new therapeutic modality for this approach. Previous retrospective database studies represented a potential therapeutic application of multiple exon skipping. Since then, public DMD databases have become more useful with an increase in patient registration and advances in molecular diagnosis. Here, we provide an update on DMD genotype-phenotype associations using a global DMD database and further provide the rationale for multiple exon skipping development, particularly for exons 45–55 skipping and an emerging therapeutic concept, exons 3–9 skipping. Importantly, this review highlights the potential of multiple exon skipping for enabling the production of functionally-corrected dystrophin and for treating symptomatic patients not only with out-of-frame deletions but also those with in-frame deletions. We will also discuss prospects and challenges in multiple exon skipping therapy, referring to recent progress in antisense chemistry and design, as well as disease models.

A Novel Fast Photothermal Therapy Using Hot Spots of Gold Nanorods for Malignant Melanoma Cells

In this paper, the plasmon resonance effects of gold nanorods was used to achieve rapid photothermal therapy for malignant melanoma cells (A375 cells). After incubation with A375 cells for 24 h, gold nanorods were taken up by the cells and gold nanorod clusters were formed naturally in the organelles of A375 cells. After analyzing the angle and space between the nanorods in clusters, a series of numerical simulations were performed and the results show that the plasmon resonance coupling between the gold nanorods can lead to a field enhancement of up to 60 times. Such high energy localization causes the temperature around the nanorods to rise rapidly and induce cell death. In this treatment, a laser as low as 9.3 mW was used to irradiate a single cell for 20 s and the cell died two h later. The cell death time can also be controlled by changing the power of laser which is focused on the cells. The advantage of this therapy is low laser treatment power, short treatment time, and small treatment range. As a result, the damage of the normal tissue by the photothermal effect can be greatly avoided.

Prediction and Targeting of Interaction Interfaces in G-protein Coupled Receptor Oligomers

BACKGROUND

Communication within a protein complex is mediated by physical interactions made among the protomers. Evidence for both the allosteric regulation present among the protomers of the protein oligomer and of the direct effect of membrane composition on this regulation has made it essential to investigate the underlying molecular mechanism that drives oligomerization, the type of interactions present within the complex, and to determine the identity of the interaction interface. This knowledge allows a holistic understanding of dynamics and also modulation of the function of the resulting oligomers/signalling complexes. G-Protein-Coupled Receptors (GPCRs), which are targeted by 40% of currently prescribed drugs in the market, are widely involved in the formation of such physiological oligomers/signalling complexes.

SCOPE

This review highlights the importance of studying Protein-Protein Interactions (PPI) by using a combination of data obtained from cutting-edge experimental and computational methods that were developed for this purpose. In particular, we focused on interaction interfaces found at GPCR oligomers as well as signalling complexes, since any problem associated with these interactions causes the onset of various crucial diseases.

CONCLUSION

In order to have a holistic mechanistic understanding of allosteric PPIs that drive the formation of GPCR oligomers and also to determine the composition of interaction interfaces with respect to different membrane compositions, it is essential to combine both relevant experimental and computational data. In this way, efficient and specific targeting of these interaction interfaces in oligomers/ complexes can be achieved. Thus, effective therapeutic molecules with fewer side effects can be designed to modulate the function of these physiologically important receptor family.

Role of FKS Gene in the Susceptibility of Pathogenic Fungi to Echinocandins

Echinocandins are antifungal agents that specifically inhibit the biosynthesis of 1,3-β-D-glucan, a major structural component of fungal cell walls. Echinocandins are recommended as first-line or alternative/salvage therapy for candidiasis and aspergillosis in antifungal guidelines of various countries. Resistance to echinocandins has been reported in recent years. The mechanism of echinocandin resistance involves amino acid substitutions in hot spot regions of the FKS gene product, the catalytic subunit of 1,3-β-D-glucan synthase. This resistance mechanism contributes to not only acquired resistance in Candida spp., but also inherent resistance in some pathogenic fungi. An understanding of the echinocandin resistance mechanism is important to develop both effective diagnosis and treatment options for echinocandin-resistant fungal diseases.

Anticosti Island: a hot spot for Neospondylis upiformis (Coleoptera: Cerambycidae) in eastern Canada?

Background

During an inventory of insect diversity on Anticosti Island in 1993, we caught unprecedented numbers of Neospondylisupiformis (Mannerheim), a longhorned beetle rarely observed in eastern North America. All specimens were caught using 12-funnel Lindgren traps baited with 95% ethanol and α-pinene. This longhorned beetle was captured again in 2007 on Anticosti with the same traps. Other than that, seven specimens of N.upiformis were caught elsewhere in Quebec between 1993 and 2015. Only 14 specimens were found in the 45 most important insect collections of the province, the most recent specimen dating back to 1964.

New information

At least 90% of the captures came from old-growth balsam fir stands of the south-central part of the island. Seasonal flight activity ranged from early June to late July, but adult captures peaked in early July. Results suggest that Anticosti Island might be a hot spot for N.upiformis in eastern North America, particularly in its south-central part where old-growth balsam fir forests still exist.

Beyond Traditional Hyperthermia: In Vivo Cancer Treatment with Magnetic-Responsive Mesoporous Silica Nanocarriers

In this study, we present an innovation in the tumor treatment in vivo mediated by magnetic mesoporous silica nanoparticles. This device was built with iron oxide magnetic nanoparticles embedded in a mesoporous silica matrix and coated with an engineered thermoresponsive polymer. The magnetic nanoparticles act as internal heating sources under an alternating magnetic field (AMF) that increase the temperature of the surroundings, provoking the polymer transition and consequently the release of a drug trapped inside the silica pores. By a synergic effect between the intracellular hyperthermia and chemotherapy triggered by AMF application, significant tumor growth inhibition was achieved in 48 h after treatment. Furthermore, the small magnetic loading used in the experiments indicates that the treatment is carried out without a global temperature rise of the tissue, which avoids the problem of the necessity to employ large amounts of magnetic cores, as is common in current magnetic hyperthermia.

Glu571 of PheT plays a pivotal role in the thermal stability of Escherichia coli PheRS enzyme

As of date the two temperature sensitive mutations isolated in pheST operon include pheS5 (G₂₉₃ →A₂₉₃ ) and pheT354. Recently, we reported that G₆₇₃ of pheS defines a hot spot for intragenic suppressors of pheS5. In this investigation, in 13 independent experiments, a collection of temperature sensitive mutants were isolated by localized mutagenesis. Complementation using clones bearing pheS⁺ , pheT⁺ , and pheS⁺ T⁺ indicated that 34 mutants could harbor lesion(s) in pheS and four could be in pheT and one mutant might be a double mutant. Surprisingly, all the 34 pheS mutants harbored the very same (G₂₉₃ →A₂₉₃ ) transition mutation as present in the classical pheS5 mutant. Most unexpectedly, the four pheT mutants isolated harbored the same G₁₇₁₁ →A₁₇₁₁ transition, a mutation which is hitherto unreported. Since all the four pheT mutants were defined by the same G₁₇₁₁ →A₁₇₁₁ base change, we believe that getting other mutations could be hard hitting and therefore it is proposed that G₁₇₁₁ itself could be a "hot spot" for emergence of Ts mutations in pheT and similarly G₂₉₃ itself could be a "hot spot" for Ts lesions in pheS. These results clearly imply a vital role for Glutamic acid₅₇₁ (Glu₅₇₁ ) of PheT and reinforce criticality of Glycine₉₈ (Gly₉₈ ) of PheS in the thermal stability of PheRS enzyme.

Supramolecular Control over the Interparticle Distance in Gold Nanoparticle Arrays by Cyclodextrin Polyrotaxanes

Amphiphilic nonionic ligands, synthesized with a fixed hydrophobic moiety formed by a thiolated alkyl chain and an aromatic ring, and with a hydrophilic tail composed of a variable number of oxyethylene units, were used to functionalize spherical gold nanoparticles (AuNPs) in water. Steady-state and time-resolved fluorescence measurements of the AuNPs in the presence of α-cyclodextrin (α-CD) revealed the formation of supramolecular complexes between the ligand and macrocycle at the surface of the nanocrystals. The addition of α-CD induced the formation of inclusion complexes with a high apparent binding constant that decreased with the increasing oxyethylene chain length. The formation of polyrotaxanes at the surface of AuNPs, in which many α-CDs are trapped as hosts on the long and linear ligands, was demonstrated by the formation of large and homogeneous arrays of self-assembled AuNPs with hexagonal close packing, where the interparticle distance increased with the length of the oxyethylene chain. The estimated number of α-CDs per polyrotaxane suggests a high rigidization of the ligand upon complexation, allowing for nearly perfect control of the interparticle distance in the arrays. This degree of supramolecular control was extended to arrays formed by AuNPs stabilized with polyethylene glycol and even to binary arrays. Electromagnetic simulations showed that the enhancement and distribution of the electric field can be finely controlled in these plasmonic arrays.

Mutation Analysis of Families with Autosomal Dominant Congenital Cataract: A Recurrent Mutation in the CRYBA1/A3 Gene Causing Congenital Nuclear Cataract

PURPOSE

To identify the CRYBA1/A3 mutation spectrum and analyze the genotype-phenotype correlations in Chinese families with congenital cataract.

METHODS

Family history and clinical data of 47 unrelated families with autosomal dominant congenital cataract (ADCC) were recorded. CRYBA1/A3 gene sequencing was applied to identify the causative mutation. Haplotypes were constructed using closely linked microsatellite markers and intragenic single-nucleotide polymorphisms (SNPs) to compare the affected haplotype in three families.

RESULTS

Nuclear cataract was the most common type of ADCC in Chinese families, accounting for 42.6% (20/47). A recurrent CRYBA1/A3 deletion mutation (ΔG91) was identified in three families (6.4%) with nonprogressive nuclear congenital cataract. Different haplotypes segregated with the mutation in each family.

CONCLUSIONS

A recurrent ΔG91CRYBA1/A3 mutation occurs independently in 6.4% of the Chinese families with autosomal dominant nuclear cataracts and most likely represents a mutational hot spot, which underscores the relations between nonprogressive nuclear cataract and CRYBA1/A3.

Effects of Temperature on the Meiotic Recombination Landscape of the Yeast Saccharomyces cerevisiae

Although meiosis in warm-blooded organisms takes place in a narrow temperature range, meiosis in many organisms occurs over a wide variety of temperatures. We analyzed the properties of meiosis in the yeast Saccharomyces cerevisiae in cells sporulated at 14°C, 30°C, or 37°C. Using comparative-genomic-hybridization microarrays, we examined the distribution of Spo11-generated meiosis-specific double-stranded DNA breaks throughout the genome. Although there were between 300 and 400 regions of the genome with high levels of recombination (hot spots) observed at each temperature, only about 20% of these hot spots were found to have occurred independently of the temperature. In S. cerevisiae, regions near the telomeres and centromeres tend to have low levels of meiotic recombination. This tendency was observed in cells sporulated at 14°C and 30°C, but not at 37°C. Thus, the temperature of sporulation in yeast affects some global property of chromosome structure relevant to meiotic recombination. Using single-nucleotide polymorphism (SNP)-specific whole-genome microarrays, we also examined crossovers and their associated gene conversion events as well as gene conversion events that were unassociated with crossovers in all four spores of tetrads obtained by sporulation of diploids at 14°C, 30°C, or 37°C. Although tetrads from cells sporulated at 30°C had slightly (20%) more crossovers than those derived from cells sporulated at the other two temperatures, spore viability was good at all three temperatures. Thus, despite temperature-induced variation in the genetic maps, yeast cells produce viable haploid products at a wide variety of sporulation temperatures.

In the yeast Saccharomyces cerevisiae, recombination is usually studied in cells that undergo meiosis at 25°C or 30°C. In a genome-wide analysis, we showed that the locations of genomic regions with high and low levels of meiotic recombination (hot spots and cold spots, respectively) differed dramatically in cells sporulated at 14°C, 30°C, and 37°C. Thus, in yeast, and likely in other non-warm-blooded organisms, genetic maps are strongly affected by the environment.

Marangoni Convection Assisted Single Molecule Detection with Nanojet Surface Enhanced Raman Spectroscopy

Many single-molecule (SM) label-free techniques such as scanning probe microscopies (SPM) and magnetic force spectroscopies (MFS) provide high resolution surface topography information, but lack chemical information. Typical surface enhanced Raman spectroscopy (SERS) systems provide chemical information on the analytes, but lack spatial resolution. In addition, a challenge in SERS sensors is to bring analytes into the so-called "hot spots" (locations where the enhancement of electromagnetic field amplitude is larger than 10³). Previously described methods of fluid transport around hot spots like thermophoresis, thermodiffusion/Soret effect, and electrothermoplasmonic flow are either too weak or detrimental in bringing new molecules to hot spots. Herein, we combined the resonant plasmonic enhancement and photonic nanojet enhancemnet of local electric field on nonplanar SERS structures, to construct a stable, high-resolution, and below diffraction limit platform for single molecule label-free detection. In addition, we utilize Marangoni convection (mass transfer due to surface tension gradient) to bring new analytes into the hotspot. An enhancement factor of ∼3.6 × 10¹⁰ was obtained in the proposed system. Rhodamine-6G (R6G) detection of up to a concentration of 10^-12 M, an improvement of two orders of magnitude, was achieved using the nanojet effect. The proposed system could provide a simple, high throughput SERS system for single molecule analysis at high spatial resolution.

Ecology of Avian Influenza Virus in Wild Birds in Tropical Africa

Several ecologic factors have been proposed to describe the mechanisms whereby host ecology and the environment influence the transmission of avian influenza viruses (AIVs) in wild birds, including bird's foraging behavior, migratory pattern, seasonal congregation, the rate of recruitment of juvenile birds, and abiotic factors. However, these ecologic factors are derived from studies that have been conducted in temperate or boreal regions of the Northern Hemisphere. These factors cannot be directly translated to tropical regions, where differences in host ecology and seasonality may produce different ecologic interactions between wild birds and AIV. An extensive dataset of AIV detection in wildfowl and shorebirds sampled across tropical Africa was used to analyze how the distinctive ecologic features of Afrotropical regions may influence the dynamics of AIV transmission in wild birds. The strong seasonality of rainfall and surface area of wetlands allows testing of how the seasonality of wildfowl ecology (reproduction phenology and congregation) is related to AIV seasonal dynamics. The diversity of the African wildfowl community provides the opportunity to investigate the respective influence of migratory behavior, foraging behavior, and phylogeny on species variation in infection rate. Large aggregation sites of shorebirds in Africa allow testing for the existence of AIV infection hot spots. We found that the processes whereby host ecology influence AIV transmission in wild birds in the Afrotropical context operate through ecologic factors (seasonal drying of wetlands and extended and nonsynchronized breeding periods) that are different than the one described in temperate regions, hence, resulting in different patterns of AIV infection dynamics.

Phenotypic and Molecular Evaluation of Echinocandin Susceptibility of Candida glabrata, Candida bracarensis, and Candida nivariensis Strains Isolated during 30 Years in Argentina

The echinocandin susceptibilities of 122 Candida glabrata complex strains (including 5 Candida nivariensis and 3 Candida bracarensis strains) were evaluated by microdilution and compared with the results from a molecular tool able to detect FKS mutations. No echinocandin resistance was detected. The PCR results coincide with the MIC data in 99.25% of the cases (1 C. glabrata strain was misidentified as resistant) but were 20 h faster. C. nivariensis FKS genes were sequenced and showed differences with C. glabrataFKS genes.

Cost-Effective Plasmonic Platforms: Glass Capillaries Decorated with Ag@SiO2 Nanoparticles on Inner Walls as SERS Substrates

A cost-effective method for the fabrication of a glass capillary based plasmonic platform for the selective detection and identification of analytes of importance in health, environment, and safety is demonstrated. This was achieved by coating Ag@SiO₂ nanoparticles (Ag ∼ 60 nm) having silica shell of varying thickness (∼2 and ∼25 nm) on the inside walls of glass capillaries, over 2 cm in length, with uniform coverage. It was found that the particle density on the surface plays a decisive role on the enhancement of Raman signals. Multiple hot spots, which are essentially junctions of amplified electric field, were generated when ∼30 Ag@SiO₂ particles/μm² were bound onto the walls of glass capillaries. The pores of the silica shell allow the localization of analyte molecules to the vicinity of hot spots resulting in signal enhancements of the order of 10¹⁰ (using pyrene as analyte; excitation wavelength, 632.8 nm). The applicability of Ag@SiO₂ coated capillaries for the detection of a wide range of molecules has been explored, by taking representative examples of polyaromatic hydrocarbons (pyrene), amino acids (tryptophan), proteins (bovine serum albumin), and explosives (trinitrotoluene). By increasing the thickness of the silica shell of Ag@SiO₂ nanoparticles, an effective filtration cum detection method has been developed for the selective identification of small molecules such as amino acids, without the interference of large proteins.

Quantitative tumor heterogeneity assessment on a nuclear population basis

Immunohistochemistry Ki-67 stain is widely used for visualizing cell proliferation. The common method for scoring the proliferation is to manually select and score a hot spot. This method is time-consuming and will often not give reproducible results due to subjective selection of the hotspots and subjective scoring. An automatic hotspot detection and proliferative index scoring would be time-saving, make the determination of the Ki-67 score easier and minimize the uncertainty of the score by introducing a more objective and standardized score. Tissue Micro Array cores stained for Ki-67 and their neighbor slide stained for Pan Cytokeratin were aligned and Ki-67 positive and negative nuclei were identified inside tumor regions. A heatmap was calculated based on these and illustrates the distribution of the heterogenous response of Ki-67 positive nuclei in the tumor tissue. An automatic hot spot detection was developed and the Ki-67 score was calculated. All scores were compared with scores provided by a pathologist using linear regression models. No significant difference was found between the Ki-67 scores guided by the developed heatmap and the scores provided by a pathologist. For comparison, scores were also calculated at a random place outside the hot spot and these scores were found to be significantly different from the pathologist scores. A heatmap visualizing the heterogeneity in tumor tissue expressed by Ki-67 was developed and used for an automatic identification of hot spots in which a Ki-67 score was calculated. The Ki-67 scores did not differ significantly from scores provided by a pathologist. © 2017 International Society for Advancement of Cytometry.

Predicting hot spots in protein interfaces based on protrusion index, pseudo hydrophobicity and electron-ion interaction pseudopotential features

The identification of hot spots, a small subset of protein interfaces that accounts for the majority of binding free energy, is becoming more important for the research of drug design and cancer development. Based on our previous methods (APIS and KFC2), here we proposed a novel hot spot prediction method. For each hot spot residue, we firstly constructed a wide variety of 108 sequence, structural, and neighborhood features to characterize potential hot spot residues, including conventional ones and new one (pseudo hydrophobicity) exploited in this study. We then selected 3 top-ranking features that contribute the most in the classification by a two-step feature selection process consisting of minimal-redundancy-maximal-relevance algorithm and an exhaustive search method. We used support vector machines to build our final prediction model. When testing our model on an independent test set, our method showed the highest F1-score of 0.70 and MCC of 0.46 comparing with the existing state-of-the-art hot spot prediction methods. Our results indicate that these features are more effective than the conventional features considered previously, and that the combination of our and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spots in protein interfaces.

Hexagonal Boron Nitride/Au Substrate for Manipulating Surface Plasmon and Enhancing Capability of Surface-Enhanced Raman Spectroscopy

We report on an insulating two-dimensional material, hexagonal boron nitride (h-BN), which can be used as an effective wrapping layer for surface-enhanced Raman spectroscopy (SERS) substrates. This material exhibits outstanding characteristics such as its crystallinity, impermeability, and thermal conductance. Improved SERS sensitivity is confirmed for Au substrates wrapped with h-BN, the mechanism of which is investigated via h-BN thickness-dependent experiments combined with theoretical simulations. The investigations reveal that a stronger electromagnetic field can be generated at the narrowed gap of the h-BN surface, which results in higher Raman sensitivity. Moreover, the h-BN-wrapped Au substrate shows extraordinary stability against photothermal and oxidative damages. We also describe its capability to detect specific chemicals that are difficult to analyze using conventional SERS substrates. We believe that this concept of using an h-BN insulating layer to protect metallic or plasmonic materials will be widely used not only in the field of SERS but also in the broader study of plasmonic and optoelectronic devices.

"Atomic Force Masking" Induced Formation of Effective Hot Spots along Grain Boundaries of Metal Thin Films

We present an interesting phenomenon, "atomic force masking", which is the deposition of a few-nanometer-thick gold film on ultrathin low-molecular-weight (LMW) polydimethylsiloxane (PDMS) engineered on a polycrystalline gold thin film, and demonstrated the formation of hot spot based on SERS. The essential principle of this atomic force masking phenomenon is that an LMW PDMS layer on a single crystalline grain of gold thin film would repel gold atoms approaching this region during a second cycle of evaporation, whereas new nucleation and growth of gold atoms would occur on LMW PDMS deposited on grain boundary regions. The nanostructure formed by the atomic force masking, denoted here as "hot spots on grain boundaries" (HOGs), which is consistent with finite-difference time-domain (FDTD) simulation, and the mechanism of atomic force masking were investigated by carrying out systematic experiments, and density functional theory (DFT) calculations were made to carefully explain the related fundamental physics. Also, to highlight the manufacturing advantages of the proposed method, we demonstrated the simple synthesis of a flexible HOG SERS, and we used this substrate in a swabbing test to detect a common pesticide placed on the surface of an apple.

Plasmonic Circuit Theory for Multiresonant Light Funneling to a Single Spatial Hot Spot

We present a theoretical framework, based on plasmonic circuit models, for generating a multiresonant field intensity enhancement spectrum at a single "hot spot" in a plasmonic device. We introduce a circuit model, consisting of an array of coupled LC resonators, that directs current asymmetrically in the array, and we show that this circuit can funnel energy efficiently from each resonance to a single element. We implement the circuit model in a plasmonic nanostructure consisting of a series of metal bars of differing length, with nearest neighbor metal bars strongly coupled electromagnetically through air gaps. The resulting nanostructure resonantly traps different wavelengths of incident light in separate gap regions, yet it funnels the energy of different resonances to a common location, which is consistent with our circuit model. Our work is important for a number of applications of plasmonic nanoantennas in spectroscopy, such as in single-molecule fluorescence spectroscopy or Raman spectroscopy.

Parkinsonian monkeys with prior levodopa-induced dyskinesias followed by fetal dopamine precursor grafts do not display graft-induced dyskinesias

Clinical trials testing the hypothesis that fetal dopamine grafts would provide antiparkinsonian benefit in patients who had already developed side effects from their long-term use of L-dopa revealed, in some cases, the presence of dyskinesias even in the absence of L-dopa. The form, intensity, and frequency of these dyskinesias were quite variable, but their manifestation slowed the clinical development of cell replacement therapies. Rodent models of graft-induced dyskinesias (GIDs) have been proposed, but their accuracy in modeling GIDs has been questioned because they usually require amphetamine for their presentation. The present study attempted to model GIDs in parkinsonian monkeys and, for the first time, to test the effect of grafts on previously dyskinetic monkeys. Toward this end, monkeys were rendered parkinsonian with n-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and dyskinetic with levodopa. They then received intraputamenal grafts of fetal dopaminergic cells, control cerebellar cells, or vehicle bilaterally and were studied for 18 months. Dopaminergic cells were grafted in a manner designed to produce either "hot spot" or "widespread" striatal innervation. Although levodopa-induced dyskinesias could be elicited postoperatively, GIDs were never observed in any animal at any time after grafting. Grafted monkeys were also challenged with levodopa but did not show any greater responses to these challenges than before grafting. These studies support the development of future dopamine neuron cell transplantation therapy-based approaches, indicating that in relevant primate models with appropriate cell preparation methodology, with successful graft survival and putamenal dopamine innervation, there is no evidence of graft-induced dyskinesias. J. Comp. Neurol. 525:498-512, 2017. © 2016 Wiley Periodicals, Inc.

Plasmon-Driven Dynamic Response of a Hierarchically Structural Silver-Decorated Nanorod Array for Sub-10 nm Nanogaps

Plasmonic nanogaps serve as a useful configuration for light concentration and local field amplification owing to the extreme localization of surface plasmons. Here, a smart plasmonic nanogap device is fabricated by the dynamic response of an Ag decorated hierarchically structural vertical polymer nanorod array under the light irradiation. Seven nanorods in one unit bend because of plasmonic heating effect and they are centrally collected due to the attraction of the plasmon-induced polaritons, leading to the significantly enhanced local electromagnetic field at the sub-10 nm gaps among the constricted nanorod tops. Compared with tuning capillarity in microscale by wetting and drying, using light as external stimuli is much easier and more tunable in nanoscale. This plasmonic nanogap device is used for a surface-enhanced Raman scattering (SERS) substrate. Its hydrophobic surface with a contact angle of 142 degree can make the probed aqueous solution only access to the Ag tips of nanorods. Thus, the analytes can be driven to the "hot spot" regions where located at the tops of nanorods during the solvent evaporation process, which is beneficial to SERS detection. Discovery of this smart plasmon-driven process broadens the scope for further functionality of both the dynamic nanostructure design and the smart plasmonic devices in the communities of chemistry, biomedicine, and microfluidic engineering.

The spatial distribution of smoking violations on a no-smoking campus: Implications for prevention

OBJECTIVE

The present study extends research on campus smoking bans by examining where smokers are violating the policy at a large university in the southeastern region of the United States.

PARTICIPANTS

The data collection was conducted by one graduate student from the university in August of 2014.

METHODS

A global positioning system device was used to collect the geo-coordinates of littered cigarette butts as a proxy measure for smoking violations.

RESULTS

A hot spot analysis found a number of spatial concentrations on campus, largely around classroom and administrative buildings along with parking lots and garages.

CONCLUSIONS

The implications of such findings can direct enforcement to target these areas in order to reduce offenses and fulfill the initial goals of policy-makers and university administrators who support smoke-free campuses.