Neurodegenerative diseases (NDDs) refer to a complex heterogeneous group of diseases which are associated with the accumulation of amyloid fibrils or plaques in the brain leading to progressive loss of neuronal functions. Alzheimer's disease is one of the major NDD responsible for 60-80% of all dementia cases. Currently, there are no curative or disease-reversing/modifying molecules for NDDs except a few such as donepezil, rivastigmine, galantamine, carbidopa and levodopa which treat the disease-associated-symptoms. Similarly, there are few FDA-approved tracers such as flortaucipir for tau fibril-imaging and florbetaben, flutemetamol, and florbetapir for amyloid-imaging available for diagnosis. Recent advances in the cryo-EM reported distinctly different microstructures for tau fibrils associated with different tauopathies highlighting the possibility to develop tauopathy-specific imaging agents and therapeutics. In addition, it is important to identify the proteins that are associated with disease development and progression to know about their 3D structure to develop various diagnostics, therapeutics and theranostic agents. The current article discusses in detail the disease-associated amyloid and non-amyloid proteins along with their structural insights. We discuss various proteins associated with NDDs and their implications in NDD. In addition, we document chemical compounds developed for diagnosis and therapy of different NDDs with special emphasis on theranostic agents.
OBJECTIVES: To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa). MATERIALS AND METHODS: Eighty-eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM-DKI data were acquired using 13 b values (0-2000 s/mm2) and analyzed using the IVIM-DKI model with the total variation (TV) method. PCa patients were categorized into two groups: clinically insignificant prostate cancer (CISPCa) (Gleason grade ≤ 6) and clinically significant prostate cancer (CSPCa) (Gleason grade ≥ 7). One-way analysis-of-variance, t test, and receiver operating characteristic analysis was performed to measure the discriminative ability to detect PCa using IVIM-DKI parameters. A chi-square test was used to select important texture features of apparent diffusion coefficient (ADC) and IVIM-DKI parameters. These selected texture features were used in an artificial neural network for PCa detection. RESULTS: ADC and diffusion coefficient (D) were significantly lower (p < 0.001), and kurtosis (k) was significantly higher (p < 0.001), in PCa as compared with benign prostatic hyperplasia (BPH) and normal peripheral zone (PZ). ADC, D, and k showed high areas under the curves (AUCs) of 0.92, 0.89, and 0.88, respectively, in PCa detection. ADC and D were significantly lower (p < 0.05) as compared with CISPCa versus CSPCa. D for detecting CSPCa was high, with an AUC of 0.63. A negative correlation of ADC and D with GS (ADC, ρ = -0.33; D, ρ = -0.35, p < 0.05) and a positive correlation of k with GS (ρ = 0.22, p < 0.05) were observed. Combined IVIM-DKI texture showed high AUC of 0.83 for classification of PCa, BPH, and normal PZ. CONCLUSION: D, f, and k computed using the IVIM-DKI model with the TV method were able to differentiate PCa from BPH and normal PZ. Texture features of combined IVIM-DKI parameters showed high accuracy and AUC in PCa detection.
BACKGROUND: For assessment of COVID-19 vaccine efficacy, neutralization activity of anti-SARS-CoV-2 antibody is measured. This study was undertaken to determine optimum levels of binding antibody units (BAU/ml) in new quantitative chemiluminescent assay (CLIA) that corresponded to neutralizing potential (30% inhibition) of sVNT assay. METHODS: Ninety-one blood samples were analyzed by CLIA and sVNT assays. Test samples (n = 75) were collected from blood donors post-2nd vaccination dose, while control samples (n = 16) were archived pre-COVID donor samples. Correlation between CLIA and sVNT was calculated and receiver operating characteristic (ROC) curve was drawn and analyzed. RESULTS: Results indicated excellent correlation between 57.5 BAU/ml on CLIA and 30%inhibition on sVNT assay. ROC curve analysis revealed that the area under the curve (AUC) was 0.971. DISCUSSION: The present study determined that 57.5 BAU/ml on CLIA corresponded to 30% inhibition on sVNT assay. Periodic quantitative analysis.
Our study aimed to explore the genetic variation in the Toll-like receptor 4 (TLR4) gene and establish its association with somatic cell score (SCS) and milk production traits in four Indian camel breeds namely Bikaneri, Kachchhi, Jaisalmeri and Mewari. TLR4 gene fragment of 573 bp spanning 5' UTR, exon-1 and partial intron-1 region was amplified and genotyped using the PCR-sequence based typing method. Only one SNP located at position C472T was identified. Genotyping revealed two alleles (C and T) and three genotypes: CC, CT and TT. The genotype frequencies for CC, CT and TT were 0.116, 0.326 and 0.558 and allele frequencies for C and T alleles were 0.279 and 0.721, respectively. Association study inferred that the effect of genotype on SCS, lactation yield (LY) and peak yield (PY) was non-significant however heterozygote (CT) genotypes recorded lower SCS and higher LY and PY. It can be concluded that the TLR4 gene possesses limited genetic variation, depicting polymorphism at a single locus in Indian camel breeds with a predominance of the TT genotype. The association study indicated that heterozygote animals possess better udder health and production performance, the statistical significance of which needs to be established using a large data set.
Camelus , Toll-Like Receptor 4 , Female , Animals , Camelus/genetics , Toll-Like Receptor 4/genetics , Milk , Polymorphism, Genetic , Gene Frequency , Genotype , Lactation/genetics , Polymorphism, Single Nucleotide/genetics
BACKGROUND AND OBJECTIVE: Non-small cell lung cancer (NSCLC) exhibits intrinsic molecular heterogeneity, primarily driven by the mutation of specific biomarkers. Identification of these biomarkers would assist not only in distinguishing NSCLC into its major subtypes - Adenocarcinoma and Squamous Cell Carcinoma, but also in developing targeted therapy. Medical practitioners use one or more types of omic data to identify these biomarkers, copy number variation (CNV) being one such type. CNV provides a measure of genomic instability, which is considered a hallmark of carcinoma. However, the CNV data has not received much attention for biomarker identification. This paper aims to identify biomarkers for NSCLC using CNV data. METHODS: An eXplainable AI (XAI)-driven L1-regularized deep learning architecture, XL1R-Net, is proposed that introduces a novel modification of the standard L1-regularized gradient descent algorithm to arrive at an improved deep neural classifier for NSCLC subtyping. Further, XAI-based feature identification has been used to leverage the trained classifier to uncover a set of twenty NCSLC-relevant biomarkers. RESULTS: The identified biomarkers are evaluated based on their classification performance and clinical relevance. Using Multilayer Perceptron (MLP)-based model, a classification accuracy of 84.95% using 10-fold cross-validation is achieved. Moreover, the statistical significance test on the classification performance also revealed the superiority of the MLP model over the competitive machine learning models. Further, the publicly available Drug-Gene Interaction Database reveals twelve of the identified biomarkers as potentially druggable. The K-M Plotter tool was used to verify eighteen of the identified biomarkers with a high probability of predicting NSCLC patients' likelihood of survival. While nine of the identified biomarkers confirm the recent literature, five find mention in the OncoKB Gene List. CONCLUSION: A set of seven novel biomarkers that have not been reported in the literature could be investigated for their potential contribution towards NSCLC therapy. Given NSCLC's genetic diversity, using only one omics data type may not adequately capture the tumor's complexity. Multiomics data and its integration with other sources will be examined in the future to better understand NSCLC heterogeneity.
Adenocarcinoma , Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Carcinoma, Non-Small-Cell Lung/diagnosis , Carcinoma, Non-Small-Cell Lung/genetics , Lung Neoplasms/diagnosis , Lung Neoplasms/genetics , DNA Copy Number Variations , Biomarkers
Severe acute malnutrition (SAM) is a major contributor to under-five mortality in developing countries such as India, where SAM children are susceptible to infections. However, there is inconsistent literature on the derangement of immune mechanisms and subsequent infection-related mounting of inflammatory responses in SAM cases compared to nutritionally-normal controls with infections. To address this, authors conducted a case-control study comparing serum inflammatory markers in 60 SAM children with systemic infections to nutritionally-normal children with infection. Cases had a lower mean serum C-reactive protein (CRP) on admission compared to controls (p-value <0.001), which continued during the follow-up (p-value <0.001). Cases also had a lower mean serum interleukin-6 (IL-6) on admission (p-value = 0.04). Baseline CRP, procalcitonin, and follow-up procalcitonin were positively correlated with antibiotic therapy duration (p-value = 0.018, 0.025, and 0.007, respectively). This study suggests that SAM children had some ability to mount an inflammatory response during a systemic infection, but it was weaker compared to nutritionally normal children with a systemic infection.
To mitigate the adverse effects of fossil fuel-based energy, mankind is in constant search of clean and cost-effective sources of energy, such as solar energy. The economic viability of a power plant to harness solar energy mostly depends on the efficiency of solar panels. Investigations over the years show that the solar panel efficiency significantly depends on the different meteorological parameters. Therefore, there is an imminent need for a correlation explaining the relations between the efficiency and different meteorological parameters. In this study, an effort has been made to analyze the effects of various meteorological parameters on the efficiency and subsequently propose a correlation between them. Initial investigations reveal that the optimal tilt angle for the maximum power output is 26°. The study demonstrates that efficiency is directly proportional to solar intensity and wind speed while being inversely proportional to temperature, humidity, and dew point temperature. Regression analysis of a data set comprising 100 data sets establishes a strong correlation between efficiency and five meteorological parameters: temperature, humidity, wind speed, solar intensity, and dew factor. The calculated efficiencies using the developed correlation deviate from the experimental values, with absolute errors ranging from 0.08 to 1.20%. The findings provided valuable insights for optimizing solar power plant performance by understanding the relationship between efficiency and meteorological parameters.
INTRODUCTION: Infections are a common cause of paediatric morbidity. Antibiotics are vital in treating them. Erratic prescribing practices are an important cause for the development of antibiotic resistance. Our objective was to estimate the effectiveness of educational interventions to improve empirical antibiotic prescribing practices among paediatric trainees. We aimed to improve the compliance to antibiotic protocols and to sustain it over 6 months. METHODS: It is a time interrupted non-randomised trial conducted in a tertiary hospital in India. Initially, 200 admitted children were selected randomly. Their antibiotic prescriptions, adherence of prescriptions to the then existing antibiotics guidelines, course during hospital stay and the final outcome were noted. The existing antibiotic policy and its use were reviewed. It was then considered essential to prepare a fresh antibiotic policy based on national guidelines, local sensitivity patterns and with inputs from microbiologists. This was distributed to the residents through seminars, posters and cellphone friendly documents. Compliance to the policy was also tracked twice a week. The adherence to guideline was recorded in the subsequent 6 months. RESULTS: The adherence of empirical antibiotic prescriptions was 59% before intervention which improved to 72% in the first month, 90% in the second month, 86% and 78% in the third and sixth months, respectively. There was no significant difference in duration of stay and the outcome at discharge in the patients in adherent and non-adherent groups. CONCLUSION: Educational interventions and frequent monitoring improved antibiotic prescribing practices among residents with no negative impact on patient outcomes. Quality improvements need persistent reinforcement and frequent monitoring to be sustainable.
Anti-Bacterial Agents , Quality Improvement , Child , Humans , Anti-Bacterial Agents/therapeutic use , India , Tertiary Care Centers , Tertiary Healthcare
The survival rate of oral squamous cell carcinoma (OSCC) patients is very poor, but it can be improved using highly sensitive, specific, and accurate techniques. Autofluorescence and fluorescence techniques are very sensitive and helpful in cancer screening; being directly linked with the molecular levels of human tissue, they can be used as a quantitative tool for cancer detection. Here, we report the development of multi-modal autofluorescence and fluorescence imaging and spectroscopic (MAF-IS) smartphone-based systems for fast and real-time oral cancer screening. MAF-IS system is indigenously developed and offers the advantages of being a low-cost, handy, non-contact, non-invasive, and easily operable device that can be employed in hospitals, including low-resource settings. In this study, we report the results of 43 individuals with 28 OSCC and 15 oral potentially malignant disorders (OPMDs), i.e., epithelial dysplasia and oral submucous fibrosis, using the developed devices. We observed a red shift in fluorescence emission spectrain vivo. We found red-shift of 7.72 ± 6 nm, 3 ± 4.36 nm, and 1.33 ± 0.47 nm in the case of OSCC, epithelial dysplasia, and oral submucous fibrosis, respectively, compared to normal. The results were compared with histopathology and found to be consistent. Further, the MAF-IS system provides results in real-time with higher accuracy and sensitivity compared to devices using a single modality. Our system can achieve an accuracy of 97% with sensitivity and specificity of 100% and 94.7%, respectively, even with a smaller number of patients (28 patients of OSCC). The proposed MAF-IS device has great potential for fast screening and diagnosis of oral cancer in the future.
Carcinoma, Squamous Cell , Mouth Neoplasms , Oral Submucous Fibrosis , Humans , Early Detection of Cancer , Mouth Neoplasms/diagnostic imaging , Carcinoma, Squamous Cell/diagnostic imaging , Spectrometry, Fluorescence , Optical Imaging
The conditions of health-care professionals including dental fraternity have been extremely affected during the COVID-19 pandemic. Dental care workers have suspended all routine dental activities with the fear of transmission of the virus from aerosol-generating dental procedures. They have also stood with medical care professionals as frontline warriors because of the exponentially overburdened of the COVID-19-positive patients worldwide. With the available literature, the aim of this article is to address the trajectories of the life of oral health workers during the outbreak of COVID-19 as well as to analyze what measures shall be taken to improve their overall physical, mental, social, and economic health and precautions while working in dental environment.
Additive manufacturing technology and its benefits have a significant impact on different industrial applications. The 3D printing technologies help manufacture lightweight intricate geometrical designs with enhanced strengths. The present study investigates the blended effects of previously recommended parameters of different infill patterns (line, triangle, and concentric) and infill densities (75, 80, and 85%) with varying thicknesses of layers (100, 200, and 300 µm). The test samples were created through Fused Filament Fabrication (FFF) technology using Acrylonitrile Butadiene Styrene (ABS) 3D printing. Mechanical properties were evaluated through tensile and impact strength tests conducted in accordance with ASTM standards. The experimental investigation reveals that the infill pattern greatly affected both tensile and impact strength. The best results were obtained with a concentric infill pattern, along with 80% infill density and 100 µm layer thickness. These conditions resulted in 123% and 115% higher tensile strength and 168% and 80% higher impact strength compared to line and triangle patterns, respectively.
A novel green fabrication approach is being proposed based on radiation assisted modification of Whatman filter paper 1 (WFP) for development of Acid Free-Paper based Analytical Devices (Af-PADs). Af-PADs exude immense potential as handy tools for on-site detection of toxic pollutants such as, Cr(VI), boron, etc., which have established detection protocols involving acid mediated colorimetric reactions that necessitate external acid addition. The proposed Af-PAD fabrication protocol asserts its novelty through elimination of external acid addition step, making the detection process safer and simpler. To achieve this, poly(acrylic acid) (PAA) was grafted onto WFP via a single step, room temperature process of gamma radiation induced simultaneous irradiation grafting, introducing acidic -COOH groups in the paper thereon. Grafting parameters namely, absorbed dose and concentrations of monomer, homopolymer inhibitor and acid were optimized. The -COOH groups incorporated in PAA-grafted-WFP (PAA-g-WFP) provide localized acidic conditions for colorimetric reactions between pollutants and their sensing agents, anchored on the PAA-g-WFP. Af-PADs loaded with 1,5-diphenylcarbazide (DPC) have been ably demonstrated for visual detection and quantitative estimation of Cr(VI) in water samples using RGB image analysis, with LOD value of 1.2 mg.L-1 and a measurement range comparable to that of commercially available PADs based Cr(VI) visual detection kits.
In the present investigation cyanostilbene based molecular probes, PCS and PCO, bearing N,N-dimethylthiocarbamate and N,N-dimethylcarbamoyal groups, respectively, have been synthesised. These probes exhibit AIEE activity in their aggregated state in the mixed solvent system of THF: H2O by way of turning on their emission, which has also been observed in powder, neat thin films and hybrid polymer films. While the probe PCO is silent to ClO-, PCS exhibits a significant response towards ClO- rationalised on the basis of HOCl specific oxidation of thiocarbamate, which is also extended to detect ClO- in water samples. Additionally, applicability of the test strips of PCS for rapid on-site detection of ClO- has been demonstrated. The experimental results are supplemented by the theoretical calculations wherever possible.
The novel coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is causing significant morbidity and mortality worldwide. The common presentations in children include involvement of respiratory system leading to pneumonia and acute respiratory distress syndrome, as well as multiorgan dysfunction syndrome and multisystem inflammatory syndrome in children (MIS-C). Pediatric COVID-19 is a milder disease as compared with the adults. Also, there is rise in MIS-C cases which is a hyperinflammatory condition temporally associated with SARS-CoV-2. Since respiratory system is predominantly involved, few of these critically ill children often require respiratory support which can range from simple oxygen delivery devices, high-flow nasal cannula (HFNC), noninvasive ventilation (NIV), invasive mechanical ventilation, and extracorporeal membrane oxygenation (ECMO). Most of the oxygen delivery devices and respiratory interventions generate aerosols and pose risk of transmission of virus to health care providers (HCPs). The use of HFNC and NIV should be limited to children with mild respiratory distress preferably in negative pressure rooms and with adequate personal protective equipment (PPE). However, there should be low thresholds for intubation and invasive mechanical ventilation in the event of clinical deterioration while on any respiratory support. The principle of providing respiratory support requires special droplet and air-borne precautions to limit exposure or transmission of virus to HCPs and at the same time ensuring safety of the patient.
The availability of several bioorthogonal reactions that can proceed selectively and efficiently under physiologically relevant conditions has garnered the interest of biochemists and organic chemists alike. Bioorthogonal cleavage reactions represent the latest innovation in click chemistry. Here, we employed the Staudinger ligation reaction to release radioactivity from immunoconjugates, improving target-to-background ratios. In this proof-of-concept study, model systems, including the anti-HER2 antibody trastuzumab, radioisotope I-131, and a newly synthesized bifunctional phosphine, were used. Staudinger ligation occurred when biocompatible N-glycosyl azides reacted with this radiolabeled immunoconjugate, leading to cleavage of the radioactive label from the molecule. We demonstrated this click cleavage in vitro and in vivo. Biodistribution studies in tumor models showed that radioactivity was eliminated from the bloodstream, thereby improving tumor-to-blood ratios. SPECT imaging revealed that tumors could be visualized with enhanced clarity. Our simple approach represents a novel application of bioorthogonal click chemistry in the development of antibody-based theranostics.
OBJECTIVE: Fluorescence-based methods are highly specific and sensitive and have potential in breast cancer detection. Simultaneous fluorescence imaging and spectroscopy during intraoperative procedures of breast cancer have great advantages in detection of tumor margin as well as in classification of tumor to healthy tissues. Intra-operative real-time confirmation of breast cancer tumor margin is the aim of surgeons, and therefore, there is an urgent need for such techniques and devices which fulfill the surgeon's priorities. METHODS: In this article, we propose the development of fluorescence-based smartphone imaging and spectroscopic point-of-care multi-modal devices for detection of invasive ductal carcinoma in tumor margin during removal of tumor. These multimodal devices are portable, cost-effective, noninvasive, and user-friendly. Molecular level sensitivity of fluorescence process shows different behavior in normal, cancerous and marginal tissues. We observed significant spectral changes, such as, red-shift, full-width half maximum (FWHM), and increased intensity as we go towards tumor center from normal tissue. High contrast in fluorescence images and spectra are also recorded for cancer tissues compared to healthy tissues. Preliminary results for the initial trial of the devices are reported in this article. RESULTS: A total 44 spectra from 11 patients of invasive ductal carcinoma (11 spectra for invasive ductal carcinoma and rest are normal and negative margins) are used. Principle component analysis is used for the classification of invasive ductal carcinoma with an accuracy of 93%, specificity of 75% and sensitivity of 92.8%. We obtained an average 6.17 ± 1.66 nm red shift for IDC with respect to normal tissue. The red shift and maximum fluorescence intensity indicates p < 0.01. These results described here are supported by histopathological examination of the same sample. CONCLUSION: In the present manuscript, simultaneous fluorescence-based imaging and spectroscopy is accomplished for the classification of IDC tissues and breast cancer margin detection.
Breast Neoplasms , Carcinoma, Ductal , Humans , Female , Breast Neoplasms/surgery , Point-of-Care Systems , Spectrum Analysis , Optical Imaging
Non-Small Cell Lung Cancer (NSCLC) exhibits intrinsic heterogeneity at the molecular level that aids in distinguishing between its two prominent subtypes - Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC). This paper proposes a novel explainable AI (XAI)-based deep learning framework to discover a small set of NSCLC biomarkers. The proposed framework comprises three modules - an autoencoder to shrink the input feature space, a feed-forward neural network to classify NSCLC instances into LUAD and LUSC, and a biomarker discovery module that leverages the combined network comprising the autoencoder and the feed-forward neural network. In the biomarker discovery module, XAI methods uncovered a set of 52 relevant biomarkers for NSCLC subtype classification. To evaluate the classification performance of the discovered biomarkers, multiple machine-learning models are constructed using these biomarkers. Using 10-Fold cross-validation, Multilayer Perceptron achieved an accuracy of 95.74% (±1.27) at 95% confidence interval. Further, using Drug-Gene Interaction Database, we observe that 14 of the discovered biomarkers are druggable. In addition, 28 biomarkers aid the prediction of the survivability of the patients. Out of 52 discovered biomarkers, we find that 45 biomarkers have been reported in previous studies on distinguishing between the two NSCLC subtypes. To the best of our knowledge, the remaining seven biomarkers have not yet been reported for NSCLC subtyping and could be further explored for their contribution to targeted therapy of lung cancer.
Adenocarcinoma of Lung , Carcinoma, Non-Small-Cell Lung , Carcinoma, Squamous Cell , Lung Neoplasms , Humans , Carcinoma, Non-Small-Cell Lung/genetics , Lung Neoplasms/genetics , Carcinoma, Squamous Cell/genetics , Machine Learning
Herein, we report temperature- and field-induced magnetic states in CsPbBr3 perovskite quantum dots (PQDs) attributed to Br defects. We find that temperature-dependent structural distortion is the main source of various temperature-induced magnetic states in Br-defect host CsPbBr3 PQDs. Comprehensively examined magnetization data through Arrott plots, Langevin and Brillouin function fitting, and structural analysis reveal the presence of various oxidation states (i.e., Pb0, Pb+, Pb2+, and Pb3+) yielding different magnetic states, such as diamagnetic states above 90 K, paramagnetic states below ≈90 K, and perhaps locally ordered states between 58 and 90 K. It is realized from theoretical fits that paramagnetic ions exist (i.e., superparamagnetic behavior) due to Br defects causing Pb+ (and/or Pb3+ ions) in the diamagnetic region. We anticipate that our findings will spur future research of the development of spin-optoelectronics, such as spin light-emitting diodes, and spintronics devices based on CsPbBr3 PQDs.
In the present investigation, we have designed and synthesised Zn2+ sensitive Julolidine-hydrazone (JSB) based chemosensor, which crystallised in a monoclinic crystal system with P21/c space group. The bare JSB was nonemissive, but in the presence of Zn2+ ions in solution it showed emission, ascribed to the chelation enhanced emission process, which is also utilised to detect Zn2+ in water samples. Comparing the chromaticity coordinates deduced from the emission colors of the JSB-Zn2+ in solution, powder and hybrid polymer thin film, using CIE (Commission Internationale de I'Eclairage 1931) chromaticity diagram, it was found that compared to the emission of the solution, the emission of the powder was red shifted, while that of the thin film was blue shifted. Further, the sensing of Zn2+ showed reversibility in the presence of pyrophosphate (PPi), which allowed quantification of PPi. Interestingly, in addition to the detection of PPi using the in-situ formed JSB-Zn2+ complex, the process was selective and discriminated PPi from ADP and ATP. The detection of PPi was rationalized via a decomplexation reaction, and translated in the construction of INHIBIT logic gate. Additionally, the possible use of the JSB coated sensor paper for the on-site detection of Zn2+ and subsequent JSB-Zn2+ complex for PPi ions has been demonstrated. The experimental results showed good correlation with the theoretical calculations wherever possible.
Hydrazones , Zinc , Zinc/chemistry , Powders , Fluorescent Dyes/chemistry , Adenosine Triphosphate , Ions
A new julolidine-fluorene based excited state intramolecular proton transfer (ESIPT)/aggregate induced emission (AIE) active Schiff-base (JDF) has been synthesized and evaluated for its photophysical properties in solution and aggregated/solid states. The correlation between the emission behavior and the solid state crystal packing structure revealed the interplay of ESIPT coupled excimer reaction occurring in the solid state, which is one of the rare examples reported so far. For a comprehensive comparison, we synthesized a non-ESIPT methyl derivative (JDF-Me) of JDF capable of showing excimer emission only in the solid state. Further, JDF exhibits normal as well as keto emission in solution, upon addition of water, its poor solvent, that promotes aggregation, the fluorescence emission shows the preponderance of the excimer band in the low energy region. It was also interesting to note that in the solid state (thin films), JDF shows emission beyond the excimer emission, which is wavelength dependent. This is attributed to the formation of diverse clusters leading to the extended delocalization beyond excimers, and represents a clustering-triggered emission ascribing bright red color to the solid JDF. Such mélange of emission characteristics of JDF are responsible for the multicolor emission covering a broad range of electromagnetic spectrum, which is demonstrated by the confocal microscopy images of the JDF recorded in different states. Further, in its aggregated state, JDF recognized Cu2+ ions, selectively, manifested in the form of emission quenching via the interaction of Cu2+ ions with the oxygen and nitrogen atoms of JDF inhibiting the excimer formation.
