Self-assembly of discrete multi-chromophoric systems.

Self-assembly of chromophoric systems is a prerequisite to create well-ordered, processable nanomaterials with multiple functionalities. In the past two decades, the field of functional organic materials has primarily focused on systems featuring only one type of dye/π-conjugated unit. Consequently, many reports with mechanistic insights on the self-assembly of the dyes featuring different molecular packing have been reported. Subsequently, we have witnessed several attempts to organize the multi-chromophoric systems in solution and solid-state via different approaches using self-assembly as a tool. Incorporation of more than one dye is important in creating materials with tuneable optoelectronic properties. Consequently, self-assembly of more than one chromophoric systems have been investigated to some extent. This review aims to discuss the self-assembled materials derived from discrete π-conjugated systems comprising more than one dye units connected through covalent bonding (multi-chromophoric systems). Molecular design of various multi-chromophoric systems leading to the formation of crystals, liquid crystals and supramolecular polymers have been correlated with corresponding properties. We envisage that classification of self-assembled multi-chromophoric systems, with a note on tuneable optoelectronic properties, can provide a deeper understanding on the molecular design strategies, which is important in the fabrication of functional organic materials with optimum performances.

Machine Learning-Assisted Determination of C6H14 Mole Fraction From Molecular Emissions of Laser-Induced Hexane-Air Plasmas.

Laser-induced plasmas of materials containing hydrocarbons present strong carbon molecular emission features. Using these emissions to build models relating changes in spectral features to a physical parameter of the system, such as hydrocarbon content, can be difficult because of the dynamic complexity of the spectral features and temperature disequilibrium between molecular species. This study presents machine learning models trained to quantify the mole fraction of hexane in hexane-air plasmas from CN Violet and C2 Swan spectral features. Ensemble regression methods provide the most accurate predictions with root mean squared error on the order 10-2. Artificial neural network regressions produce predictions with superlative sensitivity, exhibiting detection limits as low as 0.008. These foundational models can be further refined with more advanced data to quantify the presence of carbon species in complex plasma environments, such as high-speed reacting flows.

Bladder-Induced Compression of the External Iliac Veins: Recognition and Implications for Treatment.

The effect of changes in bladder volume on the caliber of adjacent veins is underappreciated but essential to recognize to avoid complications such as unnecessary stenting or clot migration causing pulmonary embolism. Here the authors illustrate the importance of this finding in 3 cases using venographic and endovascular sonographic imaging: the first in which BPH-induced chronic bladder outlet obstruction resulted in DVT formation, the second in which the cause was unrecognized and unnecessary stenting performed, and the third in which inappropriate treatment was avoided by decompressing the bladder.

Reliability of the electric pulp tester as an indicator of pulpal anesthesia in primary maxillary posterior teeth to assess the need for supplemental injections: An observational clinical study.

Background: The primary maxillary molars occasionally remain sensitive during operative procedures even post the buccal supraperiosteal injection. This could be due to the widely flared palatal roots receiving accessory innervation from the palatal nerves. Identifying inadequate anesthesia upfront using the electric pulp test (EPT) would give vital information to the clinician on the need of a supplemental palatal injection. Aim: The aim of this study was to assess and evaluate the reliability of the EPT as an indicator of pulpal anesthesia in primary maxillary molars. Methodology: Fifty one primary maxillary molars were subjected to the EPT following a buccal supraperiosteal injection. During the operative procedure, the " Face Legs Activity Cry Consolability" (FLACC) scores were recorded. The outcome of the EPT was correlated with the results of the FLACC score using Pearson's Chi-square test.Results: The EPT results were correlated to the FLACC scores. Five out of the 10 primary maxillary second molars which responded to the EPT scored 0 on the FLACC scale. The remaining 5 teeth scored 1 on the FLACC scale. The P value was 0.056 which was not statistically significant. This infers that the EPT is not a reliable tool to assess the adequacy of pulpal anesthesia in primary maxillary second molars. Conclusion: From the results of the present study, it can be concluded that the EPT is not a reliable tool to be used as an indicator of pulpal anesthesia in primary maxillary molars.

"Selection of statistical tests influences the interpretation of a study outcome" a comment on "Giriraja KV, Bhatnagar SK, Tomlinson L, Sancilio F. An open-label, multicenter, phase 2 study of a food enriched with docosahexaenoic acid in adults with sickle cell disease. Prostaglandins Leukot Essent Fatty Acids. 2023 Jun; 193:102574. Doi: 10.1016/j.plefa.2023.102574. Epub 2023 Apr 7. PMID: 37121179".

Parametric tests such as t-tests require a normal distribution of data. However, the determination of normal distribution may not be conclusive while dealing with a small sample size. Non-parametric tests such as Wilcoxon tests may be used in this situation, as these tests do not require normal distribution.

Suction thrombectomy of catheter-associated right atrial thrombus in two patients.

Catheter associated right atrial thrombus (CRAT) is an uncommon but potentially life-threatening condition. There are no established guidelines for management, and treatment ranges from systemic anticoagulation and thrombolysis to open surgery. While there have been reports on use of suction thrombectomy for right atrial thrombi, the feasibility and outcomes of suction thrombectomy in CRAT have not been described. These two cases describe a successful off-label use of two devices (Triever 20, Inari Medical, Irvine, CA, and AlphaVac, AngioDynamics, Latham, NY) for thrombectomy in CRAT. Both patients had near complete extraction of chronic appearing thrombus, with follow up imaging demonstrating complete resolution. Suction thrombectomy may have a unique role in management in CRAT, especially in cases of infected thrombi. A formal exemption from the institutional review board was obtained for publication.

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited].

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Screening for Microbial Contamination of Multi-dose Lignocaine Vials in a Dental Hospital: A Prospective Study.

Aim: Multidose vials (MDVs) for local anesthetic injections are routinely used in dental practice. MDVs contain multiple doses of a parenteral drug intended for administration to the same or multiple patients. Potentially harmful microbes have been shown to be able to live and occasionally multiply in MDVs if not handled aseptically. The goal of this study thus was to evaluate the bacterial and fungal contamination (FC) of lignocaine MDVs after use in a dental hospital. Materials and methods: A total of 27 MDVs of lignocaine free of any microbial contamination were distributed to different departments of the dental hospital and they were asked to use them on patients routinely. The samples were recollected from the departments either at the end of the 28th day or as and when the contents in the MDVs reached a predetermined level marked on the bottle during its usage, whichever was earlier. These leftover samples were subjected to a microbiological investigation by inoculation into thioglycolate broth and subsequent subculturing onto agar plates. Results: None of the inoculated broths showed turbidity. Subcultured agar plates, even on the 7th day of incubation, did not show any bacterial or fungal growth. The lignocaine MDVs tested after use were thus found to be sterile. Conclusion: There was no bacterial or FC detected in MDVs of lignocaine subjected to testing after use in the dental hospital. Clinical significance: Multidose vials (MDVs) continue to be used in clinics for economic reasons. But the clinician opting for MDVs should be conscious of their potential for microbial contamination and should meticulously follow the protocol for their aseptic use. How to cite this article: Renu SM, Rao AP, Biranthabail D, et al. Screening for Microbial Contamination of Multi-dose Lignocaine Vials in a Dental Hospital: A Prospective Study. Int J Clin Pediatr Dent 2023;16(5):678-680.

Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra.

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of 0.33% and an LoD of 0.015% for quantification of Ga in a Ce matrix. This study concludes that these machine learning methods could yield robust prediction models for rapid quality control analysis of plutonium alloys.

A polygenic score for acute vaso-occlusive pain in pediatric sickle cell disease.

Individuals with monogenic disorders can experience variable phenotypes that are influenced by genetic variation. To investigate this in sickle cell disease (SCD), we performed whole-genome sequencing (WGS) of 722 individuals with hemoglobin HbSS or HbSß0-thalassemia from Baylor College of Medicine and from the St. Jude Children's Research Hospital Sickle Cell Clinical Research and Intervention Program (SCCRIP) longitudinal cohort study. We developed pipelines to identify genetic variants that modulate sickle hemoglobin polymerization in red blood cells and combined these with pain-associated variants to build a polygenic score (PGS) for acute vaso-occlusive pain (VOP). Overall, we interrogated the α-thalassemia deletion -α3.7 and 133 candidate single-nucleotide polymorphisms (SNPs) across 66 genes for associations with VOP in 327 SCCRIP participants followed longitudinally over 6 years. Twenty-one SNPs in 9 loci were associated with VOP, including 3 (BCL11A, MYB, and the ß-like globin gene cluster) that regulate erythrocyte fetal hemoglobin (HbF) levels and 6 (COMT, TBC1D1, KCNJ6, FAAH, NR3C1, and IL1A) that were associated previously with various pain syndromes. An unweighted PGS integrating all 21 SNPs was associated with the VOP event rate (estimate, 0.35; standard error, 0.04; P = 5.9 × 10-14) and VOP event occurrence (estimate, 0.42; standard error, 0.06; P = 4.1 × 10-13). These associations were stronger than those of any single locus. Our findings provide insights into the genetic modulation of VOP in children with SCD. More generally, we demonstrate the utility of WGS for investigating genetic contributions to the variable expression of SCD-associated morbidities.

Rapid quantitative analysis of trace elements in plutonium alloys using a handheld laser-induced breakdown spectroscopy (LIBS) device coupled with chemometrics and machine learning.

We present the first reported quantification of trace elements in plutonium via a portable laser-induced breakdown spectroscopy (LIBS) device and demonstrate the use of chemometric analysis to enhance the handheld device's sensitivity and precision. Quantification of trace elements such as iron and nickel in plutonium metal via LIBS is a challenging problem due to the complex nature of the plutonium optical emission spectra. While rapid analysis of plutonium alloys has been demonstrated using portable LIBS devices, such as the SciAps Z300, their detection limits for trace elements are severely constrained by their achievable pulse power and length, light collection optics, and detectors. In this paper, analytical methods are evaluated as a means to circumvent the detection constraints. Three chemometric methods often used in analytical spectroscopy are evaluated; principal component regression, partial least-squares regression, and artificial neural networks. These models are evaluated based on goodness-of-fit metrics, root mean-squared error, and their achievable limits of detection (LoDs). Partial least squares proved superior for determining content of iron and nickel in plutonium metal, yielding LoDs of 15 and 20 ppm, respectively. These results of identifying the undesirable trace elements in plutonium components are critical for applications such as fabricating radioisotope thermoelectric generators or nuclear fuel.

Comparative evaluation of efficacy and patient-reported outcome measures of oral hygiene instruction methods for calibrated interdental brush.

OBJECTIVES: To compare the efficacy and patient-reported outcome measures of oral hygiene instruction methods for calibrated interdental brush. MATERIALS AND METHODS: A total of 60 participants, with 30 each in control and test group, participated in the study. Clinical examination included gingival index, full mouth bleeding scores and approximal plaque index. Supragingival scaling was performed. Interdental access probe was used to assess the size of interdental brush and corresponding interdental brush were given to the participants. For the control group, oral hygiene instructions were given through demonstration with model and video. For the test group, oral hygiene instructions were given through 'Touch-to-Teach' method. At 4-week follow-up, oral hygiene instructions were repeated to respective groups. After 3 months, clinical examination was done and exit survey on patient-reported outcome measures was administered. Statistical analysis was done. RESULTS: Intergroup comparison of gingival index, full mouth bleeding index and approximal plaque index showed statistically significant difference between test and control group. 'Touch-to-Teach' method of oral hygiene instruction was found to be 'Good'. Acceptance of interdental brush was regarded to be 'Good'. CONCLUSION: Within limitations of the study, Touch-to-Teach method of oral hygiene instruction method was found to be effective and more acceptable and participants used the interdental brush regularly.

Validation of the breathmobile case identification survey for asthma screening in children with sickle cell disease.

Background: Asthma is a chronic airway disorder with variable/recurring symptoms, airflow obstruction, bronchial hyperresponsiveness, and an inflammation. The expert panel report of the National Heart Lung and Blood Institute recommends asthma screening in sickle cell disease (SCD); however, specific approach is not mentioned. We hypothesize that the breathmobile case identification survey (BCIS) is a valid asthma screening tool in children with SCD.Methods: This prospective, single-center study enrolled 129 SCD patients aged 5 to 18 years from March 2016 to March 2018. All patients completed BCIS, spirometry, and fractional exhaled nitric oxide (FeNO). A single pulmonologist blinded to the BCIS results evaluated patients for asthma.Results: Asthma prevalence was 41%. Male gender (60.4%; p = 0.041), allergic rhinitis (86.8%; p < 0.01), hydroxyurea usage (73.6%; p < 0.01), and family history of asthma (34%; p < 0.01) were higher but not self-reported parental asthma history, eczema, and tobacco smoke exposure in the asthma group compared to the nonasthma group. FEV1 (p = 0.003), FVC (p = 0.02), FEV1/FVC (p = 0.053), and FEF25-75% (p = 0.02) were lower in asthma. FeNO levels were comparable in both groups. The sensitivity, specificity, positive predictive value, and negative predictive value of the abbreviated BCIS were 67.3%, 90.8%, 83.3%, and 80.2% for asthma; and 82.1%, 90.8%, 76.7%, and 93.2% for persistent asthma, respectively. Persistent asthma patients had a trend of higher hydroxyurea use (82.8% vs. 58.3%; p = 0.049) and tobacco smoke exposure (55.2% vs. 29.2%; p = 0.057) compared to intermittent asthma.Conclusion: We have validated the BCIS to screen for asthma in SCD. Spirometry but not FeNO may support an asthma diagnosis.

Evaluation of Changes in the Occlusion and Occlusal Vertical Dimension in Children Following the Placement of Preformed Metal Crowns Using the Hall Technique.

Objectives: To evaluate the time taken and the mechanism through which the occlusion settles following the placement of a preformed metal crown (PMC) using the Hall technique. The secondary objective was to assess any temporo mandibular joint dysfunction (TMD) resulting from the Hall technique through a questionnaire. Study Design: 44 children fulfilling the inclusion criteria were evaluated for changes in overbite and occlusal vertical dimension (OVD) following the placement of preformed metal crowns (PMCs) using the Hall technique. The overbite and OVD measurements were taken before treatment, immediately post treatment, then at one, two, three and four weeks post treatment. After four weeks, a questionnaire recorded the occurrence of any signs or symptoms of TMD. Results: At the fourth week, the overbite measurement did not show a statistically significant difference (p value= 0.58) compared to baseline values indicating that the occlusion settled by the fourth week. By the third week the OVD values obtained did not show a significant difference compared to the baseline (p value= 0.42) indicating that the OVD had been restored. The questionnaire provided at the end of four weeks showed negative response for signs and symptoms of TMD in all the children. Conclusion: Any changes in occlusion following the placement of a Hall crown settles in four weeks. The OVD settles three weeks post placement implying that extrusion of teeth do not play a role in settling of the occlusion. The children do not develop any signs or symptoms of TMD post a Hall crown.

Assessing the behavior management problems during the first dental visit of preschool children using a doll placement test.

CONTEXT: Assessing dental anxiety as a predictor of the likely behavior of the child in the dental operatory is of paramount importance for a clinician to render quality care. AIM: This study aims to correlate the dental anxiety of preschool children as shown during the doll placement test with that of their behavioral patterns during the first dental visit. SETTINGS AND DESIGN: This cross-sectional study was conducted between the ages of 3-7 years. MATERIALS AND METHODS: During their first dental visit, the background variables were elicited from parent/guardian at the reception desk. Later at the play area, the child was given a set of dolls representing dentist, child, and mother to place them in a model dental office having a dental chair. The child was then taken for the initial oral examination, during which the behavior of the child was rated using Frankl's Behavior Rating Scale. The data collected were analyzed using Chi-square test and binary regression analysis. RESULTS: The observed association between the doll placement pattern and the behavior of the patient during dental treatment was statistically significant (P < 0.001). The binary regression analysis showed that the child's unpleasant previous medical and parent's unpleasant dental experiences had higher odds favoring uncooperative behavior (46.63 and 41.93, respectively). CONCLUSIONS: The child's behavior on the dental chair is associated with the doll placement pattern, which is also influenced by experiences of the child during his/her encounter with the medical doctor and previous dental experiences of their parents.

Shape Estimation for Elongated Deformable Object using B-spline Chained Multiple Random Matrices Model.

In this paper, a B-spline chained multiple random matrix models (RMMs) representation is proposed to model geometric characteristics of an elongated deformable object. The hyper degrees of freedom structure of the elongated deformable object make its shape estimation challenging. Based on the likelihood function of the proposed B-spline chained multiple RMMs, an expectation-maximization (EM) method is derived to estimate the shape of the elongated deformable object. A split and merge method based on the Euclidean minimum spanning tree (EMST) is proposed to provide initialization for the EM algorithm. The proposed algorithm is evaluated for the shape estimation of the elongated deformable objects in scenarios, such as the static rope with various configurations (including configurations with intersection), the continuous manipulation of a rope and a plastic tube, and the assembly of two plastic tubes. The execution time is computed and the accuracy of the shape estimation results is evaluated based on the comparisons between the estimated width values and its ground-truth, and the intersection over union (IoU) metric.