AScirRNA: A novel computational approach to discover abiotic stress-responsive circular RNAs in plant genome.

In the realm of plant biology, understanding the intricate regulatory mechanisms governing stress responses stands as a pivotal pursuit. Circular RNAs (circRNAs), emerging as critical players in gene regulation, have garnered attention in recent days for their potential roles in abiotic stress adaptation. A comprehensive grasp of circRNAs' functions in stress response offers avenues for breeders to manipulating plants to develop abiotic stress resistant crop cultivars to thrive in challenging climates. This study pioneers a machine learning-based model for predicting abiotic stress-responsive circRNAs. The K-tuple nucleotide composition (KNC) and Pseudo KNC (PKNC) features were utilized to numerically represent circRNAs. Three different feature selection strategies were employed to select relevant and non-redundant features. Eight shallow and four deep learning algorithms were evaluated to build the final predictive model. Following five-fold cross-validation process, XGBoost learning algorithm demonstrated superior performance with LightGBM-chosen 260 KNC features (Accuracy: 74.55 %, auROC: 81.23 %, auPRC: 76.52 %) and 160 PKNC features (Accuracy: 74.32 %, auROC: 81.04 %, auPRC: 76.43 %), over other combinations of learning algorithms and feature selection techniques. Further, the robustness of the developed models were evaluated using an independent test dataset, where the overall accuracy, auROC and auPRC were found to be 73.13 %, 72.34 % and 72.68 % for KNC feature set and 73.52 %, 79.53 % and 73.09 % for PKNC feature set, respectively. This computational approach was also integrated into an online prediction tool, AScirRNA (https://iasri-sg.icar.gov.in/ascirna/) for easy prediction by the users. Both the proposed model and the developed tool are poised to augment ongoing efforts in identifying stress-responsive circRNAs in plants.

Ambipolar macrocycle derived from spiro-xanthene and carbazole: synthesis, structure-property relationships, electronic properties and host-guest investigation.

For the first time, we present the detailed synthesis, photophysical, electrochemical, host-guest and charge transport properties of spiro[fluorene-9,9'-xanthene] (SFX) and carbazole macrocycle SPS-NR-02. The electron and hole transport values measured using the space charge limited current (SCLC) method resulted in ambipolar charge transport with an electron to hole mobility ratio of 0.39.

Molybdenum trioxide as a newer diversified economic catalyst for the transformation of nitroarenes to arylamine and 5-substituted-1H-tetrazole.

The present work has developed a straightforward, gentle, and effective approach for synthesizing arylamines and 5-substituted-1H-tetrazole derivatives, and among the two tested catalysts, molybdenum trioxide (MoO3) proved to be highly effective. The selective hydrogenation of nitroarenes to arylamines presents a significant challenge due to the complex reaction mechanism and the competitive hydrogenation of other reducible functional groups. It facilitated the transfer hydrogenation of nitrobenzene using hydrazine hydrate-produced amino compounds and enabled the [3 + 2] cycloaddition of sodium azide with aromatic nitriles to yield 5-substituted-1H-tetrazoles. The structure of compound 5-(4-bromophenyl)-1H-tetrazole (5k) was verified through single-crystal X-ray analysis, and the calculation of Green Chemistry Metrics showed the optimal range. Notably, the MoO3 catalyst can be reutilized for up to seven cycles with minimal loss of effectiveness. These attributes make molybdenum trioxide particularly attractive for industrial applications. This methodology offers several advantages over traditional synthetic methods.

PredPSP: a novel computational tool to discover pathway-specific photosynthetic proteins in plants.

Photosynthetic proteins play a crucial role in agricultural productivity by harnessing light energy for plant growth. Understanding these proteins, especially within C3 and C4 pathways, holds promise for improving crops in challenging environments. Despite existing models, a comprehensive computational framework specifically targeting plant photosynthetic proteins is lacking. The underutilization of plant datasets in computational algorithms accentuates the gap this study aims to fill by introducing a novel sequence-based computational method for identifying these proteins. The scope of this study encompassed diverse plant species, ensuring comprehensive representation across C3 and C4 pathways. Utilizing six deep learning models and seven shallow learning algorithms, paired with six sequence-derived feature sets followed by feature selection strategy, this study developed a comprehensive model for prediction of plant-specific photosynthetic proteins. Following 5-fold cross-validation analysis, LightGBM with 65 and 90 LGBM-VIM selected features respectively emerged as the best models for C3 (auROC: 91.78%, auPRC: 92.55%) and C4 (auROC: 99.05%, auPRC: 99.18%) plants. Validation using an independent dataset confirmed the robustness of the proposed model for both C3 (auROC: 87.23%, auPRC: 88.40%) and C4 (auROC: 92.83%, auPRC: 92.29%) categories. Comparison with existing methods demonstrated the superiority of the proposed model in predicting plant-specific photosynthetic proteins. This study further established a free online prediction server PredPSP ( https://iasri-sg.icar.gov.in/predpsp/ ) to facilitate ongoing efforts for identifying photosynthetic proteins in C3 and C4 plants. Being first of its kind, this study offers valuable insights into predicting plant-specific photosynthetic proteins which holds significant implications for plant biology.

MCP-1 exerts the inflammatory response via ILK activation during endometriosis pathogenesis.

AIMS: MCP-1 has been shown to be elevated in endometriosis. ILK functions in several cellular events and interacts with MCP-1-signaling. In the current study, we evaluated the role of MCP-1-ILK signaling in human endometriotic cell's (Hs832(C).TCs) potential for colonization, invasion, adhesion, etc. and differentiation of macrophage along with inflammation in an endometriosis mouse model. MATERIALS AND METHODS: A mouse model of endometriosis with elevated levels of MCP-1 was developed by injecting MCP-1. We examined the migration, adhesion, colonization and invasion of Hs832(C).TCs in response to MCP-1-ILK signaling. We also examined the differentiation of THP-1 cells to macrophage in response to MCP-1-ILK signaling. KEY FINDINGS: We observed that MCP-1 increased Ser246 phosphorylation of ILK in Hs832(C).TCs and enhanced the migration, adhesion, colonization, and invasion of Hs832(C).TCs. In the mouse model of endometriosis, we found elevated chemokines (CCL-11, CCL-22 and CXCL13) levels. An increased level of MCP-1 mediated ILK activation, leading to increased inflammatory reaction and infiltration of residential and circulatory macrophages, and monocyte differentiation, but suppressed the anti-inflammatory reaction. The inhibitor (CPD22) of ILK reversed the MCP-1-mediated action by restoring Hs832(C).TCs and THP-1 phenotype. ILK inhibition in a mouse model of endometriosis reduced the effects of MCP-1 mediated pro-inflammatory cytokines, but increased anti-inflammatory response along with T-regulatory and T-helper cell restoration. SIGNIFICANCE: Targeting ILK restores MCP-1 milieu in the peritoneal cavity and endometrial tissues, reduces the inflammatory response, improves the T-regulatory and T-helper cells in the endometriosis mouse model and decreases the migration, adhesion, colonization and invasion of endometriotic cells.

Optical, vibrational, and photoluminescence properties of holmium-doped boro-bismuth-germanate glasses.

Holmium (Ho3+)-doped boro-bismuth-germanate glasses having the chemical composition (30-x)B2O3 + 20GeO2 + 20Bi2O3 + 20Na2O + 10Y2O3 + xHo2O3, where x = 0.1, 0.5, 1.0, and 2.0 mol% were prepared by melt-quenching technique. The prepared glasses were examined for thermal, optical, vibrational, and photoluminescent properties. The prepared glasses were found to be thermally very stable. The optical bandgap and Urbach energies of 0.1 mol% Ho2O3-doped boro-bismuth-germanate glass were calculated to be 3.3 eV and 377 MeV, respectively, using the absorption spectrum. The Judd-Ofelt analysis was performed on the 0.1 mol% Ho2O3-doped glass and compared the obtained parameters with literature. The branching ratio (ß) and emission cross-section (σem) of the green band were determined to be 0.7 and 0.24 × 10-20 cm2, respectively. Under 450 nm excitation, a strong green emission around 550 nm was observed and assigned to the (5S2 + 5F4) → 5I8 (Ho3+) transition. Upon an increase of Ho2O3 content from 0.1 to 2.0 mol%, the intensities of all observed emission bands as well as decay time of the (5S2 + 5F4) → 5I8 transition have been decreased gradually. The reasons behind the decrease in emission intensity and decay time were discussed. The strong green emission suggests that these glasses may be a better option for display devices and green emission applications.

Synthesis of ciprofloxacin-linked 1,2,3-triazole conjugates as potent antibacterial agents using click chemistry: exploring their function as DNA gyrase inhibitors via in silico- and in vitro-based studies.

The antibacterial efficacy of some newly developed C-3 carboxylic group-containing ciprofloxacin-linked 1,2,3-triazole conjugates was studied. Twenty-one compounds from three different series of triazoles were synthesized using click chemistry and evaluated for their antibacterial activity against nine different pathogenic strains, including three Gram-positive strains, i.e. Enterococcus faecalis (ATCC29212), Staphylococcus aureus (ATCC25923), Staphylococcus epidermidis (clinical isolate), and six Gram-negative bacterial strains, i.e. Escherichia coli (ATCC25922), Pseudomonas aeruginosa (ATCC27853), Salmonella typhi (clinical isolate), Proteus mirabilis (clinical isolate), Acinetobacter baumannii (clinical isolate) and Klebsiella pneumonia (clinical isolate). Among the compounds, 10, 10a, 10b, 10c, 10d, 11a, 11f, 12c, 12e and 12f showed excellent activity with MIC values upto 12.5 µg mL-1, whereas the control ciprofloxacin showed MIC values of 0.781-25 µg mL-1 towards various strains. In addition, the low toxicity profile of the synthesized molecules revealed that they are potent antibiotics. Molecular docking and MD analysis were performed using the protein structure of E. coli DNA gyrase B, which was further corroborated with an in vitro assay to evaluate the inhibition of DNA gyrase. The analysis revealed that compound 10b was the most potent inhibitor of DNA gyrase compared to ciprofloxacin, which was employed as the positive control. Furthermore, the structure of two title compounds (11a and 12d) was characterized using single-crystal analysis.

ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins.

Prokaryotic DNA binding proteins (DBPs) play pivotal roles in governing gene regulation, DNA replication, and various cellular functions. Accurate computational models for predicting prokaryotic DBPs hold immense promise in accelerating the discovery of novel proteins, fostering a deeper understanding of prokaryotic biology, and facilitating the development of therapeutics targeting for potential disease interventions. However, existing generic prediction models often exhibit lower accuracy in predicting prokaryotic DBPs. To address this gap, we introduce ProkDBP, a novel machine learning-driven computational model for prediction of prokaryotic DBPs. For prediction, a total of nine shallow learning algorithms and five deep learning models were utilized, with the shallow learning models demonstrating higher performance metrics compared to their deep learning counterparts. The light gradient boosting machine (LGBM), coupled with evolutionarily significant features selected via random forest variable importance measure (RF-VIM) yielded the highest five-fold cross-validation accuracy. The model achieved the highest auROC (0.9534) and auPRC (0.9575) among the 14 machine learning models evaluated. Additionally, ProkDBP demonstrated substantial performance with an independent dataset, exhibiting higher values of auROC (0.9332) and auPRC (0.9371). Notably, when benchmarked against several cutting-edge existing models, ProkDBP showcased superior predictive accuracy. Furthermore, to promote accessibility and usability, ProkDBP (https://iasri-sg.icar.gov.in/prokdbp/) is available as an online prediction tool, enabling free access to interested users. This tool stands as a significant contribution, enhancing the repertoire of resources for accurate and efficient prediction of prokaryotic DBPs.

RBProkCNN: Deep learning on appropriate contextual evolutionary information for RNA binding protein discovery in prokaryotes.

RNA-binding proteins (RBPs) are central to key functions such as post-transcriptional regulation, mRNA stability, and adaptation to varied environmental conditions in prokaryotes. While the majority of research has concentrated on eukaryotic RBPs, recent developments underscore the crucial involvement of prokaryotic RBPs. Although computational methods have emerged in recent years to identify RBPs, they have fallen short in accurately identifying prokaryotic RBPs due to their generic nature. To bridge this gap, we introduce RBProkCNN, a novel machine learning-driven computational model meticulously designed for the accurate prediction of prokaryotic RBPs. The prediction process involves the utilization of eight shallow learning algorithms and four deep learning models, incorporating PSSM-based evolutionary features. By leveraging a convolutional neural network (CNN) and evolutionarily significant features selected through extreme gradient boosting variable importance measure, RBProkCNN achieved the highest accuracy in five-fold cross-validation, yielding 98.04% auROC and 98.19% auPRC. Furthermore, RBProkCNN demonstrated robust performance with an independent dataset, showcasing a commendable 95.77% auROC and 95.78% auPRC. Noteworthy is its superior predictive accuracy when compared to several state-of-the-art existing models. RBProkCNN is available as an online prediction tool (https://iasri-sg.icar.gov.in/rbprokcnn/), offering free access to interested users. This tool represents a substantial contribution, enriching the array of resources available for the accurate and efficient prediction of prokaryotic RBPs.

ASPTF: A computational tool to predict abiotic stress-responsive transcription factors in plants by employing machine learning algorithms.

BACKGROUND: Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic stresses. Therefore, it is crucial to identify TFs associated with abiotic stress response for breeding of abiotic stress tolerant crop cultivars. METHODS: Based on a machine learning framework, a computational model was envisaged to predict TFs associated with abiotic stress response in plants. To numerically encode TF sequences, four distinct sequence derived features were generated. The prediction was performed using ten shallow learning and four deep learning algorithms. For prediction using more pertinent and informative features, feature selection techniques were also employed. RESULTS: Using the features chosen by the light-gradient boosting machine-variable importance measure (LGBM-VIM), the LGBM achieved the highest cross-validation performance metrics (accuracy: 86.81%, auROC: 92.98%, and auPRC: 94.03%). Further evaluation of the proposed model (LGBM prediction method + LGBM-VIM selected features) was also done using an independent test dataset, where the accuracy, auROC and auPRC were observed 81.98%, 90.65% and 91.30%, respectively. CONCLUSIONS: To facilitate the adoption of the proposed strategy by users, the approach was implemented as a prediction server called ASPTF, accessible at https://iasri-sg.icar.gov.in/asptf/. The developed approach and the corresponding web application are anticipated to supplement experimental methods in the identification of transcription factors (TFs) responsive to abiotic stress in plants.

Syntheses and Properties of Hole-Transporting Biindenofluorenes.

Described herein is a straightforward approach to synthesizing three biindenofluorene (BIF) derivatives, composed of antiaromatic indenofluorene units, which are the first non-alternant congeners of known bipentacene. Dimerization of indeno[1,2-b]fluorene and indeno[2,1-c]fluorene units by connecting carbons 3 and 3' and carbons 2 and 2', respectively, is shown to influence the highest occupied and lowest unoccupied molecular orbital energy levels of the resulting BIFs, affording band gaps (1.5-1.6 eV) that are smaller than that of a known indenofluorene polymer (2.3 eV). The hole mobilities of BIFs were determined to be ∼10-2 cm2 V-1 s-1.

Pure red upconverted and near-infrared luminescence properties of Er3+ -doped SnO2 nanocrystals for lighting applications.

Tin oxide (SnO2 ) nanocrystalline powders doped with erbium ion (Er3+ ) in different molar ratios (0, 3, 5, and 7 mol%) were prepared using a solid-state reaction technique. These samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), ultraviolet-visible absorption, visible upconversion, and near-infrared luminescence techniques. XRD analysis revealed the tetragonal rutile structure of SnO2 and the average crystallite size was about 32 nm. From Tauc's plots, it was confirmed that the substitution of Er3+ ions into the SnO2 host lattice resulted in the narrowing its band gap. Optical absorption bands at 520 and 654 nm correspond to the 4f electron transitions of Er3+ further confirming visible light absorption. Infrared luminescence spectra showed a broad band centred at 1536 nm which is assigned to the 4 I13/2 → 4 I15/2 transition of Er3+ . Visible upconverted emission spectra under 980 nm excitation exhibit a strong red luminescence with a main peak at 672 nm which is attributed to the 4 F9/2 → 4 I15/2 transition of Er3+ . Power-dependent upconversion spectra confirmed that two photons participated in the upconversion mechanism. Enhancement in the intensities of both visible and infrared luminescence was observed when raising the concentration. The results pave the way for the potential applications of these nanocrystalline powders in energy harvesting applications such as infrared light upconverting layer in solar cells, light emitting diodes, infrared broadband sources and amplifiers, and biological labelling.

Highly Soluble Ambipolar anti-Perylene-3,4 : 9,10-bis(benzimidazole)s Stabilize a Room-Temperature Columnar Hexagonal Phase.

A new series of highly soluble perylene anti-bis(4,5-dialkoxybenzimidazole)s bearing branched flexible chains stabilizing room temperature columnar hexagonal phase and with balanced ambipolar charge carrier mobility is reported for the first time. Only the anti isomer was successfully separated and characterized. These compounds have a high extinction coefficient, small optical band gap and wide absorption range, thus making them a promising class of ambipolar organic semiconductors capable of self-organizing.

Orange-red luminescence of samarium-doped bismuth-germanium-borate glass for light-emitting devices.

Samarium (Sm3+ )-doped glass has sparked a rising interest in demonstrating a noticeable emission in the range of 400-700, which is advantageous in solid-state lasers in the visible region, colour displays, undersea communication, and optical memory devices. This study reports the fabrication of Sm3+ -doped bismuth-germanium-borate glasses were established using a standard melt-quenching technique and inspection by absorption, steady-state luminescence, and transient studies. The typical peaks of Sm3+ ions were detected in the visible range under 403 nm excitation. A strong emission band was detected at 599 nm that resembles the 4 G5/2 →6 H7/2 transition of Sm3+ ions for BGBiNYSm0.5 glass. Furthermore, a reddish-orange (coral) luminescence at 646 nm that resembles the 4 G5/2 →6 H9/2 transition was also perceived. The stimulated emission cross-section of 4 G5/2 level for BGBiNYSm0.5 glass was 0.39 × 10-22  cm2 . Lifetime of the 4 G5/2 level was enhanced for the BGBiNYSm0.5 glass and decreased with an increase in active ion concentrations. The lifetime quenching of ions at the metastable state was because of energy transfer among Sm3+ ions by cross-relaxation channels. Commission Internationale de l'Éclairage (CIE) coordinates were evaluated from the emission spectra. Moreover, all the findings recommend these glass as light-emitting materials in the coral region at 599 nm for solid-state lighting applications.

Directed searching optimized texture based adaptive gamma correction (DSOTAGC) technique for medical image enhancement.

Because of complexity and low contrast in medical images, few enhancement techniques result unwanted artifacts and information loss by affecting the structure similarity and peak signal to noise ratio. To meet these challenges, a Directed searching optimized texture-based adaptive gamma correction technique is proposed in this article. This proposed technique utilizes the textured regions of the image and suppresses the effect of non-textured regions for eliminating the artifacts. An adaptive clipping threshold is used in the textured image to control the enhancement rate. For improving the contrast, the transfer function of the enhanced image is evaluated using the modified weighted probability density function and adaptive gamma parameter. To make the algorithm more adaptive, parameters like clipped threshold, gamma parameter, and textural threshold are to be optimized using directed searching optimization algorithm. For improving the information contents and noise suppression capability, the proposed technique incorporated a fitness function which is a combination of entropy and peak signal to noise ratio. Equal weightage has been given to each parameter in the fitness function for obtaining a balanced optimal result. Then, the performance of the proposed technique is evaluated in terms of visual quality, information contents, average mean brightness error, noise suppression, and structural similarity. Experimental results show the proposed technique results in better visual effects without information loss. It effectively suppresses the effect of artifacts and significantly improves the contrast by making edges clearer and textures richer over other algorithms.

Morphometry around Cochleostomy Site to Aid Safe Cochlear Implantation.

Introduction: In morphologically normal-appearing inner ears, measurements of the distance between the round window and carotid canal (RCD), the maximum diameter of the basal turn of the cochlea next to the round window (BD), and the thickness of the promontory (PT) just lateral to the basal turn may be used as guide for safe cochleostomy and implant placement. Materials and Methods: From January to March 2022, a cross-sectional observational study was carried out in a tertiary care hospital. The round window to carotid canal distance (RCD), the largest diameter of the cochlea's basal turn next to the round window (BD), and the thickness of the promontory immediately lateral to the basal turn (PT) were measured using CT temporal bone images of 150 persons without cochlear abnormalities. The values obtained were compared using Paired T-test for significance of difference between both genders and sides. Results: A total of 150 participants-75 men and 75 women-with a mean age of 37.5 years were enrolled in the study. With a range of 7.18 mm to 10.52 mm, the mean RCD was 8.84 mm (SD 0.8 mm). The mean BD was 2.27 mm (SD 0.4 mm), while the mean PT was 1.15 mm (SD 0. mm). The values obtained did not differ significantly in both the genders and the right and left sides (p = 0.37 and 0.24, respectively). Conclusion: The present study has defined and calculated pertinent measures at cochleostomy site that will aid safe electrode insertion and prevent misplacement.

Estimation of Normal Semi-circular Canal Dimensions on Computed Tomography.

Aims: To measure and compare length, width and luminal diameters of semi-circular canals (SCC) on Multiplanar reformatted CT images in individuals without any features of vestibular dysfunction. Materials And Methods: A prospective, cross sectional, observational study was conducted in a tertiary care hospital in October - November 2021. Multiplanar reformatted CT temporal bone images of 50 participants without features of vestibular dysfunction were used to measure the curved lengths, widths and luminal diameters of the three semi-circular canals. Unpaired t-test was used to ascertain and compare the values obtained. Results: Fifty participants, 27 women and 23 men (mean age 38.5 years) were included in the study. Mean curved lengths of Superior, posterior and Lateral SCCs were 1.37 cm, 1.33 cm and 1.19 cm respectively. Semi-circular width of Superior SCC (4.8 mm) was significantly larger than Posterior SCC (4.17 mm, p = 0.03) which was significantly larger than Lateral SCC (3.65 mm, p = 0.04). No significant difference was found between mean mid luminal diameters of the three SCCs. Mid luminal diameters were significantly smaller than the diameters at either ends of all SCCs. Conclusion: The results can potentially serve as reference values for Indians and for further studies on pathophysiology of disequilibrium.

First example of ambipolar naphthalene diimide exhibiting a room temperature columnar phase.

A self-assembled ambipolar organic semiconductor based on naphthalene diimide with low clearing temperature, solution processability, and high molar extinction coefficient, exhibiting a room temperature columnar hexagonal liquid crystalline phase is reported.

MRF: a tool to overcome the barrier of inconsistent genome annotations and perform comparative genomics studies for the largest animal DNA virus.

BACKGROUND: The genome of the largest known animal virus, the white spot syndrome virus (WSSV) responsible for huge economic losses and loss of employment in aquaculture, suffers from inconsistent annotation nomenclature. Novel genome sequence, circular genome and variable genome length led to nomenclature inconsistencies. Since vast knowledge has already accumulated in the past two decades with inconsistent nomenclature, the insights gained on a genome could not be easily extendable to other genomes. Therefore, the present study aims to perform comparative genomics studies in WSSV on uniform nomenclature. METHODS: We have combined the standard mummer tool with custom scripts to develop missing regions finder (MRF) that documents the missing genome regions and coding sequences in virus genomes in comparison to a reference genome and in its annotation nomenclature. The procedure was implemented as web tool and in command-line interface. Using MRF, we have documented the missing coding sequences in WSSV and explored their role in virulence through application of phylogenomics, machine learning models and homologous genes. RESULTS: We have tabulated and depicted the missing genome regions, missing coding sequences and deletion hotspots in WSSV on a common annotation nomenclature and attempted to link them to virus virulence. It was observed that the ubiquitination, transcription regulation and nucleotide metabolism might be essentially required for WSSV pathogenesis; and the structural proteins, VP19, VP26 and VP28 are essential for virus assembly. Few minor structural proteins in WSSV would act as envelope glycoproteins. We have also demonstrated the advantage of MRF in providing detailed graphic/tabular output in less time and also in handling of low-complexity, repeat-rich and highly similar regions of the genomes using other virus cases. CONCLUSIONS: Pathogenic virus research benefits from tools that could directly indicate the missing genomic regions and coding sequences between isolates/strains. In virus research, the analyses performed in this study provides an advancement to find the differences between genomes and to quickly identify the important coding sequences/genomes that require early attention from researchers. To conclude, the approach implemented in MRF complements similarity-based tools in comparative genomics involving large, highly-similar, length-varying and/or inconsistently annotated viral genomes.

Ambipolar Columnar Self-assembled Organic Semiconductors based on Heteroatom bay-Annulated Perylene Bisimides.

Highly electron-deficient heteroatom (N, S, Se) bay-annulated PBIs exhibiting ordered columnar phase over a wide mesomorphic range including ambient temperature are reported in this manuscript. These compounds with six peripheral n-decyloxy chains exhibited absorption spectra with high molar extinction coefficients, electron-deficient nature and self-assembling behaviour. A detailed comparison with the PBIs bearing six peripheral n-decyl chains was also carried out to get the valuable insights on the structure-property relations in this important class of organic semiconductors. Both of the PBI series were tested for their charge carrier mobility by space charge limited current method and found that they exhibit ambipolar conductivity. This is in contrary to the vast body of literature, where most of the PBI based semiconductors exhibit electron transport behaviour. In general, PBIs derived from tri-n-alkyl anilines exhibit higher mobility values than the PBIs derived from tri-n-alkoxy anilines. Especially, the ambipolar S-annulated PBI derived from tri-n-alkyl aniline exhibited highest hole (8.39×10-3  cm2 /V.s) and electron (1.5×10-2  cm2 /V.s) mobility values and promising for the application in organic electronics.