Preparation and Characterization of Silica Material from Rice Husk Ash – An Economically Viable Method

Rice husk is a form of agricultural biomass that provides an abundant silicon source. Rice husks are widely burnt in agricultural fields in India because it is difficult to find other uses for them. Farmers burn rice hulls usually under incomplete combustion conditions to avoid accidental fires. The objective of this study was to develop a new method of amorphous silica was prepared from rice husk ash by sol - gel method. Initially received from Rice husk ash was calcined at 4000C, 5000C, 6000C and 7000C for 5 hrs to remove the volatiles in the sample and determine the amorphous structure of SiO2. Next, the thermally treated RHA was mixed with alkali solution to produce sodium silicate solution and precipitated silica was produced by the neutralization of sodium silicate solution. Rice Husks soaked in nitric acid produced the maximum amount of the sodium silicate solution and precipitated silica. Sodium oxide (Na2O) content and silica (SiO2) content in the sodium silicate solution were also determined. Extracted precipitated silica particles were characterized by Fourier transform infrared (FTIR), X-Ray diffraction and Optical microscopy techniques. The chemical composition of silica was confirmed by FTIR and SEM with EDX.. Highly pure amorphous silica was derived from rice husk ash was confirmed by XRD pattern. The morphology of the obtained materials was analyzed by SEM. At optimized conditions, a nano sized highly pure silica was produced with a high reactivity and 99.9% amorphous in form. This economic technology as applied to waste material also provides many benefits to the local agro industry. Thus this paper may be providing a low cost and simple method to prepare functional materials. Keywords: Rice husk ash, Silica gel, Minerals, Amorphous material, Agricultural bio-wast

Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features

Plant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products.  Automatic detection of plant diseases is an essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect the symptoms of diseases as soon as they appear on plant leaves.  The proposed system is a software solution for automatic detection and classification of plant leaf diseases.  The developed processing scheme consists of four main steps, first a color transformation structure for the input RGB image is created, then the green pixels are masked and removed using specific threshold value followed by segmentation process, the texture statistics are computed for the useful segments, finally the extracted features are passed through the classifier.  The proposed algorithm’s efficiency can successfully detect and classify the examined diseases with an accuracy of 94%.  Experimental results on a database of about 500 plant leaves confirm the robustness of the proposed approach.   Keywords: HSI, color co-occurrence matrix, texture, SVM, plant leaf disease

To assess the Effectiveness of Ice Pack Massage on Labour Pain Perception during First Stage of Labour among Primi Gravid Mothers admitted at Labour Ward, Government Rajaji Hospital, Madurai

BACKGROUND: Childbirth is a crucial experience in women's life as it has a substantial psychological, emotional and physical impact. A childbirth positive experience is important to the woman, infant's health and well-being, and mother-infant relationship. During labour, women experience a high level of intense, stressful and steady pain that may negatively affect both mothers and neonates. Painkillers have previously been used for childbearing women, but nowadays, owing to some well-known limitations and serious side effects, non pharmacological methods such as Ice pack massage are being broadly recommended. STATEMENT OF THE PROBLEM: The present study was conducted “to assess the effectiveness of ice pack massage on labour pain perception during first stage of labour among primi gravid mothers admitted at labour ward, Government Rajaji hospital, Madurai – 20.” METHOD: Primigravid mothers from the labour room were randomly assigned to experimental group (30) and control group (30) by Lottery method. Standardized Modified Numerical Pain Intensity Scale and Labour Progress Measurement Tool were used to assess the pain perception and labour progress during pre test and post test of ice pack massage among experimental group primigravid mothers. RESULTS: Data analysis was done using independent and paired‘t’- tests. The results showed a significant difference in the pain perception between the experimental group and control group (t=6.17 P=0.001) after the administration of ice pack massage. There was also a significant difference in the pre test and post test assessment of pain perception among the experimental group primigravid mothers after the administration of ice pack massage (t=7.82 P=0.001). Similarly there was a significant difference between the experimental and control group primigravid mothers in the labour progress (t=2.56 P=0.01). There was also a significant difference in the pre test and post test assessment of labour progress among the experimental group primigravid mothers after the administration of ice pack massage (t=8.22 P=0.001). INTERPRETATION AND CONCLUSION: The results show that ice pack massage during labour proved to be effective non pharmacological methods of treatment to reduce labour pain perception of mothers in labour. The study concluded that ice pack massage was effective in reducing the level of labour pain perception

HPTLC fingerprinting of stem bark extract of Nyctanthes arbor-tristis (L.)

Fingerprint profile of   bark extract of Nyctanthes arbor-tristis using High Performance Thin Layer chromatography (HPTLC) has been established. HPTLC is a valuable tool for the investigation of medicinal plants with reference to the qualitative analysis of the phytoconstituents. Separation of the active constituents from the extracts has been developed using solvent system of Toluene: Ethyl acetate: Formic acid (5:4:1). The HPTLC analysis showed the presence of the flavonoid quercetin in the standard as well  as in the sample  and the  Rf value was  0.73. These images of fingerprinting help in the proper identification and quantification of the   marker compounds. On the basis of the marker compounds, new drugs could be formulated to treat various diseases Keywords: Nyctanthes arbor- tristis, HPTLC analysis, quercetin, bark extrac

Remote Monitoring of the Heart Condition of Athletes by Measuring the Cardiac Action Potential Propagation Time Using a Wireless Sensor Network

Highly performing athletes are susceptible to cardiac damage of several kinds which may be irreversible. The monitoring of heart rate and ECG waveforms from such subjects by wireless sensor networks has been reported in health and sports care documents. However, a more decisive parameter for instant to instant changes would be the time of Cardiac Action Potential Propagation. This time, which can be between 15-20 ms would shoot suddenly in acute stress in highly performing athletes for short durations. Repeated incidents of such rising values will tend to cause irreversible damage to the heart. We developed the technique of measuring this time and reporting it through a wireless sensor network to monitoring station

Cystatin C and lactoferrin concentrations in biological fluids as possible prognostic factors in eye tumor development

Objectives. To investigate the possible role of cystatin C in eye biological fluids locally and in serum and lactoferrin revealing anti-tumor activity in eye tumor development. Background. The increased number of eye tumors was registered recently not only in the countries with high insolation, but also in the northern countries including Russia (11 cases per million of population). Search for new biological markers is important for diagnosis and prognosis in eye tumors. Cystatin C, an endogenous inhibitor of cysteine proteases, plays an important protective role in several tumors. Lactoferrin was shown to express anti-tumor and antiviral activities. It was hypothesized that cystatin C and lactoferrin could serve as possible biomarkers in the diagnosis of malignant and benign eye tumors. Study design. A total of 54 patients with choroidal melanoma and benign eye tumors were examined (part of them undergoing surgical treatment). Serum, tear fluid and intraocular fluid samples obtained from the anterior chamber of eyes in patients with choroidal melanoma were studied. Methods. Cystatin C concentration in serum and eye biological fluids was measured by commercial ELISA kits for human (BioVendor, Czechia); lactoferrin concentration – by Lactoferrin-strip D 4106 ELISA test systems (Vector-BEST, Novosibirsk Region, Russia). Results. Cystatin C concentration in serum of healthy persons was significantly higher as compared to tear and intraocular fluids. In patients with choroidal melanoma, increased cystatin C concentration was similar in tear fluid of both the eyes. Lactoferrin level in tear fluid of healthy persons was significantly higher than its serum level. Significantly increased lactoferrin concentration in tear fluid was noted in patients with benign and malignant eye tumors. Conclusion. Increased level of cystatin C in tear fluid seems to be a possible diagnostic factor in the eye tumors studied. However, it does not allow us to differentiate between malignant and benign eye tumors. Similar changes were noted for lactoferrin in tear fluid

Noise sensitivity of 89Zr-Immuno-PET radiomics based on count-reduced clinical images

PURPOSE: Low photon count in (89)Zr-Immuno-PET results in images with a low signal-to-noise ratio (SNR). Since PET radiomics are sensitive to noise, this study focuses on the impact of noise on radiomic features from (89)Zr-Immuno-PET clinical images. We hypothesise that (89)Zr-Immuno-PET derived radiomic features have: (1) noise-induced variability affecting their precision and (2) noise-induced bias affecting their accuracy. This study aims to identify those features that are not or only minimally affected by noise in terms of precision and accuracy. METHODS: Count-split (89)Zr-Immuno-PET patient scans from previous studies with three different (89)Zr-labelled monoclonal antibodies were used to extract radiomic features at 50% (S50p) and 25% (S25p) of their original counts. Tumour lesions were manually delineated on the original full-count (89)Zr-Immuno-PET scans. Noise-induced variability and bias were assessed using intraclass correlation coefficient (ICC) and similarity distance metric (SDM), respectively. Based on the ICC and SDM values, the radiomic features were categorised as having poor [0, 0.5), moderate [0.5, 0.75), good [0.75, 0.9), or excellent [0.9, 1] precision and accuracy. The number of features classified into these categories was compared between the S50p and S25p images using Fisher’s exact test. All p values < 0.01 were considered statistically significant. RESULTS: For S50p, a total of 92% and 90% features were classified as having good or excellent ICC and SDM respectively, while for S25p, these decreased to 81% and 31%. In total, 148 features (31%) showed robustness to noise with good or moderate ICC and SDM in both S50p and S25p. The number of features classified into the four ICC and SDM categories between S50p and S25p was significantly different statistically. CONCLUSION: Several radiomic features derived from low SNR (89)Zr-Immuno-PET images exhibit noise-induced variability and/or bias. However, 196 features (43%) that show minimal noise-induced variability and bias in S50p images have been identified. These features are less affected by noise and are, therefore, suitable candidates to be further studied as prognostic and predictive quantitative biomarkers in (89)Zr-Immuno-PET studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-022-00444-4

Deregulation of apoptotic proteins by induction of Dendropthae falcata (L.f.) Ettingsh plant extract in breast cancer cells: A proteome-wide analysis

Objective(s): The present study evaluated the protein-based analysis to unravel the role and mechanism behind the Dendropthae falcata plant extract treatment in breast cancer cells. Materials and Methods: The protein sample was extracted from the cancer cells after treatment with the plant extract and subjected to two-dimensional electrophoresis for protein separation. Further, the proteins that were differentially regulated among the samples which were treated and non-treated were selected and processed further for protein identification using a tandem mass spectrometry approach.Results: Using these strategies, we identified 16 potential candidates which were showing remarkable changes in treated samples. All the candidates were analyzed further for gene ontology analysis, and it was observed that all proteins were involved in multiple pathways pertaining to the carcinogenesis process. Specifically, apoptotic pathway proteins including BAD, BIK, BID, CASP8, MCL1, BCL2, and BAK1 were highly impacted by treatment with D. falcata plant extract. All these protein hits were further taken for validation experiments using RT PCR analysis. Conclusion: Initiation of these apoptotic proteins by D. falcata plant extract treatment in breast cancer cells shows a positive direction toward nature-based alternative medicine