Antimalarial Drug Resistance Profiling of Plasmodium falciparum Infections in India Using Next-Generation Sequencing.

Background: Tracking the emergence and spread of antimalarial drug resistance has become critical to sustaining progress towards the control and eventual elimination of malaria in South Asia, especially India. Methods: An amplicon sequencing protocol was used for high-throughput molecular surveillance of antimalarial drug resistance in a total of 158 isolates at three sites in India: Chennai, Nadiad and Rourkela. Five genes of the Plasmodium falciparum implicated in antimalarial resistance were investigated here; Pfcrt for chloroquine resistance, Pfdhfr for pyrimethamine resistance, Pfdhps for sulfadoxine resistance, Pfk13 for artemisinin resistance and Pfmdr1 for resistance to multiple antimalarials. Results: Mutations in the propeller domain of PfK13 were observed in two samples only, however these mutations are not validated for artemisinin resistance. A high proportion of parasites from the P. falciparum dominant site Rourkela showed wild-type Pfcrt and Pfdhfr haplotypes, while mutant Pfcrt and Pfdhfr haplotypes were fixed at the P. vivax dominant sites Chennai and Nadiad. The wild-type PfDHPS haplotype was predominant across all study sites. Finally, we observed the largest proportion of suspected multi-clonal infections at Rourkela, which has the highest transmission of P. falciparum among our study sites. Conclusion: This is the first simultaneous high-throughput next generation sequencing of five complete P. falciparum genes from infected patients in India.

QTL mapping and identification of candidate genes linked to red rot resistance in sugarcane.

Sugarcane (Saccharum species hybrid) is one of the most important commercial crops cultivated worldwide for products like white sugar, bagasse, ethanol, etc. Red rot is a major sugarcane disease caused by a hemi-biotrophic fungus, Colletotrichum falcatum Went., which can potentially cause a reduction in yield up to 100%. Breeding for red rot-resistant sugarcane varieties has become cumbersome due to its complex genome and frequent generation of new pathotypes of red rot fungus. In the present study, a genetic linkage map was developed using a selfed population of a popular sugarcane variety CoS 96268. A QTL linked to red rot resistance (qREDROT) was identified, which explained 26% of the total phenotypic variation for the trait. A genotype-phenotype network analysis performed to account for epistatic interactions, identified the key markers involved in red rot resistance. The differential expression of the genes located in the genomic region between the two flanking markers of the qREDROT as well as in the vicinity of the markers identified through the genotype-phenotype network analysis in a set of contrasting genotypes for red rot infection further confirmed the mapping results. Further, the expression analysis revealed that the plant defense-related gene coding 26S protease regulatory subunit is strongly associated with the red rot resistance. The findings can help in the screening of disease resistant genotypes for developing red rot-resistant varieties of sugarcane. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03481-7.

Indian Sugar Industry: Towards Self-reliance for Sustainability.

The South-Asian region including India is a major hub of sugar producing countries with ample presence in the global sugar scenario. India has a rich history of sugarcane and sugar production since time immemorial, and the industry has gradually evolved to find a place among the top sugar producing countries of the world. The innovative technological interventions for sugarcane improvement, production and management have helped the industry to progress towards a diversified and bio-based productive, sustainable and profitable one, thereby gradually becoming self-reliant. This self-reliant industry with the right mix of linkages and collaborations, has been successful in tackling the various unforeseen challenges including those that cropped up during COVID-19 pandemic. The industry also fulfils its Corporate Social Responsibilities leading to the overall betterment of its stakeholders. This has enabled the Indian sugar industry to align itself with the 2030 Agenda for Sustainable Development Goals.

Bioacoustic signal analysis through complex network features.

The paper proposes a graph-theoretical approach to auscultation, bringing out the potential of graph features in classifying the bioacoustics signals. The complex network analysis of the bioacoustics signals - vesicular (VE) and bronchial (BR) breath sound - of 48 healthy persons are carried out for understanding the airflow dynamics during respiration. The VE and BR are classified by the machine learning techniques extracting the graph features - the number of edges (E), graph density (D), transitivity (T), degree centrality (Dcg) and eigenvector centrality (Ecg). The higher value of E, D, and T in BR indicates the temporally correlated airflow through the wider tracheobronchial tract resulting in sustained high-intense low-frequencies. The frequency spread and high-frequencies in VE, arising due to the less correlated airflow through the narrow segmental bronchi and lobar, appears as a lower value for E, D, and T. The lower values of Dcg and Ecg justify the inferences from the spectral and other graph parameters. The study proposes a methodology in remote auscultation that can be employed in the current scenario of COVID-19.

Acclimatization through thermal diffusivity tuning of coconut oil - A mode mismatched dual-beam thermal lens study.

BACKGROUND: Ayurvedic medicinal oils traditionally prepared by blending herbal extracts in different compositions are commonly used for treatment and improving health. The estimation of the thermal properties of medicinal oils is essential for practical applications. OBJECTIVE: The present work aims to expound the ability of medicinal oils for the acclimatization of body temperature by determining its thermal diffusivity and thereby providing a validation to the traditional knowledge. MATERIALS AND METHODS: The medicinal oils are prepared by incorporating black pepper (Piper nigrum), aloe vera (Aloe barbadensis), hibiscus bud (Hibiscus rosa-sinensis) and Ocimum sanctum in coconut oil base. The samples are subjected to thermal diffusivity study using the mode-mismatched dual-beam thermal lens technique. RESULTS: The study reveals that the incorporation of black pepper (Piper nigrum), having hot potency (Ushna veerya), to the base fluid lowers the thermal diffusivity value, suggesting its potential in heat-trapping. The addition of aloe vera (Aloe barbadensis), hibiscus bud (Hibiscus rosa-sinensis), and O. sanctum dissipates heat energy quickly, thus increases the thermal diffusivity of coconut oil revealing a cold potency (Sheeta veerya). The study provides a validation for traditional knowledge and delineates the possiblity of thermal diffusivity tuning of the base fluids. CONCLUSION: The thermal diffusivity tuning through incorporation of herbal extracts can effectively be used to acclimatize the human body temperature with the surroundings. A higher thermal diffusivity value induces a cooling effect and the lower value causes heating effect. This, opens up the possibility of using thermally tuned oils depending on climate and geographical location.

Graph-based feature extraction and classification of wet and dry cough signals: a machine learning approach.

This article proposes a unique approach to bring out the potential of graph-based features to reveal the hidden signatures of wet (WE) and dry (DE) cough signals, which are the suggestive symptoms of various respiratory ailments like COVID 19. The spectral and complex network analyses of 115 cough signals are employed for perceiving the airflow dynamics through the infected respiratory tract while coughing. The different phases of WE and DE are observed from their time-domain signals, indicating the operation of the glottis. The wavelet analysis of WE shows a frequency spread due to the turbulence in the respiratory tract. The complex network features namely degree centrality, eigenvector centrality, transitivity, graph density and graph entropy not only distinguish WE and DE but also reveal the associated airflow dynamics. A better distinguishability between WE and DE is obtained through the supervised machine learning techniques (MLTs)-quadratic support vector machine and neural net pattern recognition (NN), when compared to the unsupervised MLT, principal component analysis. The 93.90% classification accuracy with a precision of 97.00% suggests NN as a better classifier using complex network features. The study opens up the possibility of complex network analysis in remote auscultation.

Phase portrait for high fidelity feature extraction and classification: A surrogate approach.

This paper proposes a novel surrogate method of classification of breath sound signals for auscultation through the principal component analysis (PCA), extracting the features of a phase portrait. The nonlinear parameters of the phase portrait like the Lyapunov exponent, the sample entropy, the fractal dimension, and the Hurst exponent help in understanding the degree of complexity arising due to the turbulence of air molecules in the airways of the lungs. Thirty-nine breath sound signals of bronchial breath (BB) and pleural rub (PR) are studied through spectral, fractal, and phase portrait analyses. The fast Fourier transform and wavelet analyses show a lesser number of high-intense, low-frequency components in PR, unlike BB. The fractal dimension and sample entropy values for PR are, respectively, 1.772 and 1.041, while those for BB are 1.801 and 1.331, respectively. This study reveals that the BB signal is more complex and random, as evidenced by the fractal dimension and sample entropy values. The signals are classified by PCA based on the features extracted from the power spectral density (PSD) data and the features of the phase portrait. The PCA based on the features of the phase portrait considers the temporal correlation of the signal amplitudes and that based on the PSD data considers only the signal amplitudes, suggesting that the former method is better than the latter as it reflects the multidimensional aspects of the signal. This appears in the PCA-based classification as 89.6% for BB, a higher variance than the 80.5% for the PR signal, suggesting the higher fidelity of the phase portrait-based classification.

Time series and fractal analyses of wheezing: a novel approach.

Since the outbreak of the pandemic Coronavirus Disease 2019, the world is in search of novel non-invasive methods for safer and early detection of lung diseases. The pulmonary pathological symptoms reflected through the lung sound opens a possibility of detection through auscultation and of employing spectral, fractal, nonlinear time series and principal component analyses. Thirty-five signals of vesicular and expiratory wheezing breath sound, subjected to spectral analyses shows a clear distinction in terms of time duration, intensity, and the number of frequency components. An investigation of the dynamics of air molecules during respiration using phase portrait, Lyapunov exponent, sample entropy, fractal dimension, and Hurst exponent helps in understanding the degree of complexity arising due to the presence of mucus secretions and constrictions in the respiratory airways. The feature extraction of the power spectral density data and the application of principal component analysis helps in distinguishing vesicular and expiratory wheezing and thereby, giving a ray of hope in accomplishing an early detection of pulmonary diseases through sound signal analysis.

Nonlinear time series and principal component analyses: Potential diagnostic tools for COVID-19 auscultation.

The development of novel digital auscultation techniques has become highly significant in the context of the outburst of the pandemic COVID 19. The present work reports the spectral, nonlinear time series, fractal, and complexity analysis of vesicular (VB) and bronchial (BB) breath signals. The analysis is carried out with 37 breath sound signals. The spectral analysis brings out the signatures of VB and BB through the power spectral density plot and wavelet scalogram. The dynamics of airflow through the respiratory tract during VB and BB are investigated using the nonlinear time series and complexity analyses in terms of the phase portrait, fractal dimension, Hurst exponent, and sample entropy. The higher degree of chaoticity in BB relative to VB is unwrapped through the maximal Lyapunov exponent. The principal component analysis helps in classifying VB and BB sound signals through the feature extraction from the power spectral density data. The method proposed in the present work is simple, cost-effective, and sensitive, with a far-reaching potential of addressing and diagnosing the current issue of COVID 19 through lung auscultation.

Downscaling of sample entropy of nanofluids by carbon allotropes: A thermal lens study.

The work reported in this paper is the first attempt to delineate the molecular or particle dynamics from the thermal lens signal of carbon allotropic nanofluids (CANs), employing time series and fractal analyses. The nanofluids of multi-walled carbon nanotubes and graphene are prepared in base fluid, coconut oil, at low volume fraction and are subjected to thermal lens study. We have studied the thermal diffusivity and refractive index variations of the medium by analyzing the thermal lens (TL) signal. By segmenting the TL signal, the complex dynamics involved during its evolution is investigated through the phase portrait, fractal dimension, Hurst exponent, and sample entropy using time series and fractal analyses. The study also explains how the increase of the photothermal energy turns a system into stochastic and anti-persistent. The sample entropy (S) and refractive index analyses of the TL signal by segmenting into five regions reveal the evolution of S with the increase of enthalpy. The lowering of S in CAN along with its thermal diffusivity (50%-57% below) as a result of heat-trapping suggests the technique of downscaling sample entropy of the base fluid using carbon allotropes and thereby opening a novel method of improving the efficiency of thermal systems.

Impact of COVID-19 on Indian Sugar Industry.

The Indian sugar industry, a significant player in the national economy, has faced many challenges in the course of its journey. The threat posed by the growing pandemic novel corona virus (COVID-19), has been the most recent one and it is impacting sugar industry stakeholders and its integrated industries, not only in India, but all over the world. The entire value chain of the Indian sugar industry, viz., sugarcane, sugar, molasses, ethanol and their subsequent marketing and export, has been adversely affected from the spillover impacts. The major impacts of COVID-19 on Indian sugar industry are discussed.

Temporal evolution of sample entropy in thermal lens system.

The photothermal phenomenon resulting in thermal lens formation in liquid media involves complex molecular dynamics responsible for temperature and refractive index variation. As a thermodynamic system, the entropy of the medium also changes. In this paper, the time series and phase portrait analysis of the thermal lens signal is carried out to understand the molecular dynamics. The study reveals the increase in complexity, disorder, and antipersistance nature through fractal dimension, sample entropy, and Hurst exponent, respectively. The analysis of the signal on segmentation reveals the evolution of sample entropy and the stochastic nature of the system with time. The phase portrait analysis also is in support of these observations. Thus, the study suggests that the temporal evolution of sample entropy is similar to the temperature-dependent refractive index.

Hard plant tissues do not contribute meaningfully to dental microwear: evolutionary implications.

Reconstructing diet is critical to understanding hominin adaptations. Isotopic and functional morphological analyses of early hominins are compatible with consumption of hard foods, such as mechanically-protected seeds, but dental microwear analyses are not. The protective shells surrounding seeds are thought to induce complex enamel surface textures characterized by heavy pitting, but these are absent on the teeth of most early hominins. Here we report nanowear experiments showing that the hardest woody shells - the hardest tissues made by dicotyledonous plants - cause very minor damage to enamel but are themselves heavily abraded (worn) in the process. Thus, hard plant tissues do not regularly create pits on enamel surfaces despite high forces clearly being associated with their oral processing. We conclude that hard plant tissues barely influence microwear textures and the exploitation of seeds from graminoid plants such as grasses and sedges could have formed a critical element in the dietary ecology of hominins.

Optical emission diagnosis of carbon nanoparticle-incorporated chlorophyll for sensing applications.

Chlorophyll fluorescence (Chl F) is widely used in sensing applications to understand terrestrial vegetation and environmental and climatic variations. The increasing rates of industrialization and carbon emission from internal combustion engines (ICEs) pose a threat to sustainable development. This study analyses the impact of carbon nanoparticles (CNPs) from ICEs on the optical absorption and fluorescence emission of leaf pigments. Leaf pigments without and with CNPs were subjected to UV-visible and photoluminescence (PL) spectroscopy analyses. The field emission scanning electron microscopy and high-resolution transmission electron microscopy images of CNPs showed their morphology. The Jablonski diagram of the CNP-incorporated chlorophyll system helped in understanding the fluorescence emission, internal conversion, and the exchange of energy between them. The variations in (i) total chlorophyll, (ii) optical absorbance by total chlorophyll, (iii) PL emission peak (at 675 nm and 718 nm) intensities for different excitation wavelengths, and (iv) normalized absorbance at the PL emission peaks with different CNP concentrations were analysed by dividing into three regions. In Region I (0-0.625 mg ml-1), the radiative component dominated the nonradiative component as a result of energy transfer from CNPs to chlorophyll. In Region II (0.625-1.2 mg ml-1), the increase in CNP concentration initiated diffusion into chloroplasts, resulting in the increase in the nonradiative part of total energy and decrease in PL peak intensity. In Region III (1.2-2.5 mg ml-1), the energy absorbed by the CNPs dissipated more nonradiatively, leading to a slow rate of increase in the radiative part. The visual response of PL emission, color purity, and the distribution of the emitted energy over the spectrum studied with the help of CIE plots, power spectrum, and confocal fluorescence microscopy revealed the fluorescence emission in the red region. This study suggests the possibility of employing Chl F in agricultural, environmental, and biological fields for sensing applications.

Raman spectroscopic and fractal analysis of blood samples of dengue fever patients.

BACKGROUND: The limitations of the existing techniques for the early detection of dengue fever necessitate the development of a powerful optical technique. OBJECTIVE: The present work is a study of Raman spectral modifications of blood on dengue infection and thereby to develop a spectroscopic method for its early detection. The images of the samples are subjected to fractal analysis to find the variation of fractal dimensions on dengue infection. METHODS: Correlation of platelet counts of dengue infected blood with Raman spectrum modification and fractal dimension. The effect of lowering of blood platelet count due to dengue infection is found to show some interesting changes in the spectrum. RESULTS: The full width at half maximum (FWHM) of the two bands in the region 950-1200 cm-1 increase with the decrease of blood platelet count. The increase in fractal dimension gives an indication of the decrease of platelet count and hence the dengue infection. CONCLUSIONS: Raman spectrum and fractal analysis can effectively be used as potential techniques for the early detection of dengue infection.

From Futile to Fruitful: Diesel Soot as White Light Emitter.

The present work describes a solution for the effective use of the hazardous particulate matter (diesel soot) from the internal combustion engines (ICEs) as a potential material emitting white light for white light emitting diodes (WLEDs). The washed soot samples are subjected to Field Emission Scanning Electron Microscopy (FESEM), High- Resolution Transmission Electron Microscopy (HR-TEM), Energy Dispersive Spectroscopy (EDS), UV-Visible, Photoluminescent (PL) Spectroscopy and quantum yield measurements. The CIE plot and Correlated Color Temperature (CCT) reveals the white fluorescence on photoexcitation. The sample on ultraviolet (UV) laser excitation, provides a visual confirmation of white light emission from the sample. The diesel soot collected from public transport buses of different years of manufacture invariably exhibit white fluorescence at an excitation of 350 nm. The sample show a quantum yield of 47.09%. The study is significant in the context of pollution and search for low-cost, rare-earth phosphor free material for white light emission and thereby turning the hazardous, futile material into a fruitful material that can be used for potential applications in photonics and electronics.

MicroRNAs and Their Regulatory Role in Sugarcane.

Sugarcane, one of the most photosynthetically efficient crops, is an important source of sugar and feedstock for green energy and co-generation. The high level of polyploidy and genomic peculiarities in this crop point towards a complex mechanism of regulation for the economically important traits like sugar content, cane yield related traits, resistance to biotic and abiotic stresses etc. The regulatory pathways for these traits comprise of a number of genes, transcription factors and different categories of RNAs like small interference RNAs (siRNAs), and Micro RNAs (miRNAs). MicroRNAs (miRNAs) are found to play an important regulatory role in many crops. As in other crops, several miRNAs have been identified in sugarcane too and these are speculated to have a role in regulating the various metabolic processes. Role of miRNAs in relation to drought tolerance has been studied to a great extent in this crop. miRNAs have been predicted to be linked to expression of other traits like disease resistance, salinity tolerance, waterlogging and axillary bud growth in sugarcane. miRNAs can have a significant role in biomass production in sugarcane, as reported in several biofuel crops. Till now, miRNAs linked to sugar accumulation have not been identified in sugarcane, but studies suggest an important role for miRNAs in sugar metabolic pathway in crops like Sorghum and switch grass. It is presumed that in sugarcane too, sugar accumulation as well as the other important metabolic pathways might be regulated to some extent by the miRNAs. The review examines the progress made in understanding the miRNA regulation in sugarcane and the extent to which miRNA mediated regulation can be utilized in sugarcane improvement.

Dental abrasion as a cutting process.

A mammalian tooth is abraded when a sliding contact between a particle and the tooth surface leads to an immediate loss of tooth tissue. Over time, these contacts can lead to wear serious enough to impair the oral processing of food. Both anatomical and physiological mechanisms have evolved in mammals to try to prevent wear, indicating its evolutionary importance, but it is still an established survival threat. Here we consider that many wear marks result from a cutting action whereby the contacting tip(s) of such wear particles acts akin to a tool tip. Recent theoretical developments show that it is possible to estimate the toughness of abraded materials via cutting tests. Here, we report experiments intended to establish the wear resistance of enamel in terms of its toughness and how friction varies. Imaging via atomic force microscopy (AFM) was used to assess the damage involved. Damage ranged from pure plastic deformation to fracture with and without lateral microcracks. Grooves cut with a Berkovich diamond were the most consistent, suggesting that the toughness of enamel in cutting is 244 J m(-2), which is very high. Friction was higher in the presence of a polyphenolic compound, indicating that this could increase wear potential.

Structure and scale of the mechanics of mammalian dental enamel viewed from an evolutionary perspective.

Mammalian enamel, the contact dental tissue, is something of an enigma. It is almost entirely made of hydroxyapatite, yet exhibits very different mechanical behavior to a homogeneous block of the same mineral. Recent approaches suggest that its hierarchical composite form, similar to other biological hard tissues, leads to a mechanical performance that depends very much on the scale of measurement. The stiffness of the material is predicted to be highest at the nanoscale, being sacrificed to produce a high toughness at the largest scale, that is, at the level of the tooth crown itself. Yet because virtually all this research has been conducted only on human (or sometimes "bovine") enamel, there has been little regard for structural variation of the tissue considered as evolutionary adaptation to diet. What is mammalian enamel optimized for? We suggest that there are competing selective pressures. We suggest that the structural characteristics that optimize enamel to resist large-scale fractures, such as crown failures, are very different to those that resist wear (small-scale fracture). While enamel is always designed for damage tolerance, this may be suboptimal in the enamel of some species, including modern humans (which have been the target of most investigations), in order to counteract wear. The experimental part of this study introduces novel techniques that help to assess resistance at the nanoscale.

Development, cross-species/genera transferability of novel EST-SSR markers and their utility in revealing population structure and genetic diversity in sugarcane.

Sugarcane (Saccharum spp. hybrid) with complex polyploid genome requires a large number of informative DNA markers for various applications in genetics and breeding. Despite the great advances in genomic technology, it is observed in several crop species, especially in sugarcane, the availability of molecular tools such as microsatellite markers are limited. Now-a-days EST-SSR markers are preferred to genomic SSR (gSSR) as they represent only the functional part of the genome, which can be easily associated with desired trait. The present study was taken up with a new set of 351 EST-SSRs developed from the 4085 non redundant EST sequences of two Indian sugarcane cultivars. Among these EST-SSRs, TNR containing motifs were predominant with a frequency of 51.6%. Thirty percent EST-SSRs showed homology with annotated protein. A high frequency of SSRs was found in the 5'UTR and in the ORF (about 27%) and a low frequency was observed in the 3'UTR (about 8%). Two hundred twenty-seven EST-SSRs were evaluated, in sugarcane, allied genera of sugarcane and cereals, and 134 of these have revealed polymorphism with a range of PIC value 0.12 to 0.99. The cross transferability rate ranged from 87.0% to 93.4% in Saccharum complex, 80.0% to 87.0% in allied genera, and 76.0% to 80.0% in cereals. Cloning and sequencing of EST-SSR size variant amplicons revealed that the variation in the number of repeat-units was the main source of EST-SSR fragment polymorphism. When 124 sugarcane accessions were analyzed for population structure using model-based approach, seven genetically distinct groups or admixtures thereof were observed in sugarcane. Results of principal coordinate analysis or UPGMA to evaluate genetic relationships delineated also the 124 accessions into seven groups. Thus, a high level of polymorphism adequate genetic diversity and population structure assayed with the EST-SSR markers not only suggested their utility in various applications in genetics and genomics in sugarcane but also enriched the microsatellite marker resources in sugarcane.