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Inverse kinematics, crucial in robotics, involves computing joint configurations to achieve specific end-effector positions and orientations. This task is particularly complex for six-degree-of-freedom (six-DoF) anthropomorphic robots due to complicated mathematical equations, nonlinear behaviours, multiple valid solutions, physical constraints, non-generalizability and computational demands. The primary contribution of this work is to address the complex inverse kinematics problem for six-DoF anthropomorphic robots through the systematic exploration of AI models. This study involves rigorous evaluation and Bayesian optimization for hyperparameter tuning to identify the optimal regressor, balancing both accuracy and computational efficiency. Utilizing five-fold cross-validation on a publicly available dataset, the selected model demonstrates exceptional performance in predicting six joint angles for end effector configuration, yielding an average mean square error of 1.934 × 10 -3 to 3.522 × 10 -3 . Its computational efficiency, with a prediction time of approximately 1.25 ms per sample, makes it a practical choice. Additionally, the study employs Explainable AI, using SHAP (SHapley Additive exPlanations) analysis to gain an understanding of feature importance. This analysis not only enhances model interpretability but also reaffirms the efficacy in this challenging multi-input multi-output predictive task. This research advances state-of-the-art models and neural networks by prioritizing computational efficiency alongside accuracy-a critical yet often overlooked factor. Pioneering a significant advancement in anthropomorphic robot kinematics, it balances accuracy and efficiency, offering practical robotic automation solutions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 ISA. Published by Elsevier Ltd. All rights reserved.)

Identification of the geographic origin of invasive species can be critical to effective management and amelioration of negative impacts in the introduced range. Liriomyza huidobrensis is a polyphagous leafmining fly that is a devastating pest of many vegetable and floriculture crops around the world. Considered native to South and possibly Central America, L. huidobrensis became invasive in the 1980s and has since spread to at least 30 countries on five continents. We used phylogeographic analysis of over 2 kb of mitochondrial cytochrome oxidase I and II sequence data from 403 field-collected specimens from both native and introduced populations to investigate the geographic origins of invasive L. huidobrensis worldwide. Within South America, there was substantial genetic variation, as well as the strong phylogeographic structure typical of a native range. In contrast, leafminers from the introduced range and Central America all contained little genetic variation and shared the same small set of haplotypes. These haplotypes trace to Peru as the ultimate geographic origin of invasive populations. Central America is rejected as part of the original geographic range of L. huidobrensis. Within Peru, the primary export region of Lima shared an extremely similar pattern of reduced haplotype variation to the invasive populations. An additional 18 specimens collected at US ports of entry did not share the same haplotype profile as contemporary invasive populations, raising perplexing questions on global pathways and establishment success in this species., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Author(s). Evolutionary Applications published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Background: Breast cancer remains a leading cause of female mortality worldwide, exacerbated by limited awareness, inadequate screening resources, and treatment options. Accurate and early diagnosis is crucial for improving survival rates and effective treatment., Objectives: This study aims to develop an innovative artificial intelligence (AI) based model for predicting breast cancer and its various histopathological grades by integrating multiple biomarkers and subject age, thereby enhancing diagnostic accuracy and prognostication., Methods: A novel ensemble-based machine learning (ML) framework has been introduced that integrates three distinct biomarkers-beta-human chorionic gonadotropin (β-hCG), Programmed Cell Death Ligand 1 (PD-L1), and alpha-fetoprotein (AFP)-alongside subject age. Hyperparameter optimization was performed using the Particle Swarm Optimization (PSO) algorithm, and minority oversampling techniques were employed to mitigate overfitting. The model's performance was validated through rigorous five-fold cross-validation., Results: The proposed model demonstrated superior performance, achieving a 97.93% accuracy and a 98.06% F1-score on meticulously labeled test data across diverse age groups. Comparative analysis showed that the model outperforms state-of-the-art approaches, highlighting its robustness and generalizability., Conclusion: By providing a comprehensive analysis of multiple biomarkers and effectively predicting tumor grades, this study offers a significant advancement in breast cancer screening, particularly in regions with limited medical resources. The proposed framework has the potential to reduce breast cancer mortality rates and improve early intervention and personalized treatment strategies., Competing Interests: Declaration of competing interest The authors state that the study provided in the paper was not impacted by any known competing financial or interpersonal interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Air pollution is a significant issue for a developing country like India and the air quality index (AQI) forecasting helps to predict air quality levels in advance and allows individuals to take precautionary measures to protect their health., Objectives: The study aimed to forecast the AQI for an industrial area (SIDCUL, Haridwar City) using a time series regression model., Materials and Methods: Three years of existing AQI data points (post-COVID-19) were collected from the Uttarakhand Pollution Control Board for the SIDCUL area of Haridwar City and tried to know the status of AQI values for the following 12 months. Trend and seasonality components were seen through the decomposition process. Further, the augmented Dickey-Fuller test was applied to check the stationarity of the series before finalizing the best-suited time series model for forecasting the AQI values., Results: With the help of autocorrelation function (ACF)/partial ACF plots, a seasonal autoregressive integrated moving average (ARIMA) (0,1,0) (1,0,0)[12] model was selected with the minimum akaike information criterion (253.143) and mean absolute percentage error (17.42%). The AQI values have also been forecasted for this industrial area (SIDCUL) for the following year., Conclusion: The seasonal ARIMA (0,1,0) (1,0,0)[12] model may be helpful to forecast the AQI values for a nonstationary time series dataset. Research indicates that the air of the SIDCUL area will become moderately polluted and may cause breathing discomfort to asthma patients' health. The scientists might apply this model to other polluted regions of the country so that the public and the government can take preventive measures in advance., (Copyright © 2024 Copyright: © 2024 Indian Journal of Public Health.)

The lethal novel coronavirus disease 2019 (COVID-19) pandemic is affecting the health of the global population severely, and a huge number of people may have to be screened in the future. There is a need for effective and reliable systems that perform automatic detection and mass screening of COVID-19 as a quick alternative diagnostic option to control its spread. A robust deep learning-based system is proposed to detect the COVID-19 using chest X-ray images. Infected patient's chest X-ray images reveal numerous opacities (denser, confluent, and more profuse) in comparison to healthy lungs images which are used by a deep learning algorithm to generate a model to facilitate an accurate diagnostics for multi-class classification (COVID vs. normal vs. bacterial pneumonia vs. viral pneumonia) and binary classification (COVID-19 vs. non-COVID). COVID-19 positive images have been used for training and model performance assessment from several hospitals of India and also from countries like Australia, Belgium, Canada, China, Egypt, Germany, Iran, Israel, Italy, Korea, Spain, Taiwan, USA, and Vietnam. The data were divided into training, validation and test sets. The average test accuracy of 97.11 ± 2.71% was achieved for multi-class (COVID vs. normal vs. pneumonia) and 99.81% for binary classification (COVID-19 vs. non-COVID). The proposed model performs rapid disease detection in 0.137 s per image in a system equipped with a GPU and can reduce the workload of radiologists by classifying thousands of images on a single click to generate a probabilistic report in real-time., (© 2021 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.)

Visually impaired people face numerous difficulties in their daily life, and technological interventions may assist them to meet these challenges. This paper proposes an artificial intelligence-based fully automatic assistive technology to recognize different objects, and auditory inputs are provided to the user in real time, which gives better understanding to the visually impaired person about their surroundings. A deep-learning model is trained with multiple images of objects that are highly relevant to the visually impaired person. Training images are augmented and manually annotated to bring more robustness to the trained model. In addition to computer vision-based techniques for object recognition, a distance-measuring sensor is integrated to make the device more comprehensive by recognizing obstacles while navigating from one place to another. The auditory information that is conveyed to the user after scene segmentation and obstacle identification is optimized to obtain more information in less time for faster processing of video frames. The average accuracy of this proposed method is 95.19% and 99.69% for object detection and recognition, respectively. The time complexity is low, allowing a user to perceive the surrounding scene in real time.

Liriomyza huidobrensis (Blanchard) is native to South America but has expanded its range and invaded many regions of the world, primarily on flowers and to a lesser extent on horticultural product shipments. As a result of initial invasion into an area, damage caused is usually significant but not necessarily sustained. Currently, it is an economic pest in selected native and invaded regions of the world. Adults cause damage by puncturing abaxial and adaxial leaf surfaces for feeding and egg laying sites. Larvae mine the leaf parenchyma tissues which can lead to leaves drying and wilting. We have recorded 365 host plant species from 49 families and more than 106 parasitoid species. In a subset of the Argentinian data, we found that parasitoid community composition attacking L. huidobrensis differs significantly in cultivated and uncultivated plants. No such effect was found at the world level, probably due to differences in collection methods in the different references. We review the existing knowledge as a means of setting the context for new and unpublished data. The main objective is to provide an update of widely dispersed and until now unpublished data, evaluate dispersion of the leafminer and management strategies in different regions of the world, and highlight the need to consider the possible effects of climate change on further regional invasions or expansions., (© The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America.)

Predicting functions of proteins and alternatively spliced isoforms encoded in a genome is one of the important applications of bioinformatics in the post-genome era. Due to the practical limitation of experimental characterization of all proteins encoded in a genome using biochemical studies, bioinformatics methods provide powerful tools for function annotation and prediction. These methods also help minimize the growing sequence-to-function gap. Phylogenetic profiling is a bioinformatics approach to identify the influence of a trait across species and can be employed to infer the evolutionary history of proteins encoded in genomes. Here we propose an improved phylogenetic profile-based method which considers the co-evolution of the reference genome to derive the basic similarity measure, the background phylogeny of target genomes for profile generation and assigning weights to target genomes. The ordering of genomes and the runs of consecutive matches between the proteins were used to define phylogenetic relationships in the approach. We used Escherichia coli K12 genome as the reference genome and its 4195 proteins were used in the current analysis. We compared our approach with two existing methods and our initial results show that the predictions have outperformed two of the existing approaches. In addition, we have validated our method using a targeted protein-protein interaction network derived from protein-protein interaction database STRING. Our preliminary results indicates that improvement in function prediction can be attained by using coevolution-based similarity measures and the runs on to the same scale instead of computing them in different scales. Our method can be applied at the whole-genome level for annotating hypothetical proteins from prokaryotic genomes.

The prediction of burn patient survivability is a difficult problem to investigate till present times. In present study a prediction Model for patients with burns was built, and its capability to accurately predict the survivability was assessed. We have compared different data mining techniques to asses the performance of various algorithms based on the different measures used in the analysis of information pertaining to medical domain. Obtained results were evaluated for correctness with the help of registered medical practitioners. The dataset was collected from SRT (Swami Ramanand Tirth) Hospital in India, which is one of the Asia's largest rural hospitals. Dataset contains records of 180 patients mainly suffering from burn injuries collected during period from the year 2002 to 2006. Features contain patients' age, sex and percentage of burn received for eight different parts of the body. Prediction models have been developed through rigorous comparative study of important and relevant data mining classification techniques namely, navie bayes, decision tree, support vector machine and back propagation. Performance comparison was also carried out for measuring unbiased estimate of the prediction models using 10-fold cross-validation method. Using the analysis of obtained results, we show that Navie bayes is the best predictor with an accuracy of 97.78% on the holdout samples, further, both the decision tree and support vector machine (SVM) techniques demonstrated an accuracy of 96.12%, and back propagation technique resulted in achieving accuracy of 95%.

The purpose of this study was to present the variation of clinical target volume (CTV) with different computed tomography (CT) slice thicknesses and the impact of CT slice thickness on 3-dimensional (3D) conformal radiotherapy treatment planning. Fifty patients with brain tumors were selected and CT scans with 2.5-, 5-, and 10-mm slice thicknesses were performed with non-ionic contrast enhancement. The patients were selected with tumor volume ranging from 2.54 cc to 222 cc. Three-dimensional treatment planning was performed for all three CT datasets. The target coverage and the isocenter shift between the treatment plans for different slice thickness were correlated with the tumor volume. An important observation from our study revealed that for volume <25 cc, most of the cases were underdosed by 18% with 5-mm slice thickness and 27% with 10-mm slickness. For volume >25 cc, the target underdosage was less than 6.7% for 5-mm slice thickness and 8% for 10-mm slice thickness. For 3D conformal radiotherapy treatment planning (3DCRT), a CT slice thickness of 2.5 mm is optimum for tumor volume <25 cc, and 5 mm is optimum for tumor volume >25 cc.

In this study, the dosimetric characteristics of multileaf collimators (MLCs) with 120 leaves and 80 leaves were evaluated. The dose rate, percentage depth dose, surface dose, dose in the build-up region, beam profile, flatness, symmetry, and penumbra width were measured by three field-defining methods: (1) "Jaw only", (2) "MLC only", and (3) "MLC + Jaw", for a 6-MV photon beam with the two MLC systems. Analysis of the dose rate showed that the dose rate for the "MLC only" field was higher than that for the other two fields. The surface dose was more pronounced for the "MLC only" fields. The dose in the build-up region was higher for the "MLC only" fields, and no significant difference was found in the percentage depth dose (PDD) beyond the dose maximum point (d(max)) for both MLC systems. Beam profiles showed that the differences in flatness and symmetry for both systems were less than 3%. The penumbra width between 80 and 20% isodose levels for the "MLC only" field was more than that for the other two field defining methods. The widths of the 50% dose levels of the beam profiles were analyzed. The dosimetric characteristics of the two MLC systems were the same in all aspects except the surface dose, penumbra, the dose in the build-up region, and the width of the 50% dose levels.

Setup error plays a significant role in the final treatment outcome in radiotherapy. The effect of setup error on the planning target volume (PTV) and surrounding critical structures has been studied and the maximum allowed tolerance in setup error with minimal complications to the surrounding critical structure and acceptable tumor control probability is determined. Twelve patients were selected for this study after breast conservation surgery, wherein 8 patients were right-sided and 4 were left-sided breast. Tangential fields were placed on the 3-dimensional-computed tomography (3D-CT) dataset by isocentric technique and the dose to the PTV, ipsilateral lung (IL), contralateral lung (CLL), contralateral breast (CLB), heart, and liver were then computed from dose-volume histograms (DVHs). The planning isocenter was shifted for 3 and 10 mm in all 3 directions (X, Y, Z) to simulate the setup error encountered during treatment. Dosimetric studies were performed for each patient for PTV according to ICRU 50 guidelines: mean doses to PTV, IL, CLL, heart, CLB, liver, and percentage of lung volume that received a dose of 20 Gy or more (V20); percentage of heart volume that received a dose of 30 Gy or more (V30); and volume of liver that received a dose of 50 Gy or more (V50) were calculated for all of the above-mentioned isocenter shifts and compared to the results with zero isocenter shift. Simulation of different isocenter shifts in all 3 directions showed that the isocentric shifts along the posterior direction had a very significant effect on the dose to the heart, IL, CLL, and CLB, which was followed by the lateral direction. The setup error in isocenter should be strictly kept below 3 mm. The study shows that isocenter verification in the case of tangential fields should be performed to reduce future complications to adjacent normal tissues.

Objective: The aim of this study was to establish whether radiation treatment planning using MRI alone could replace CT-based planning for brain tumors while retaining the dosimetric accuracy. This would help to provide a single imaging modality for both target delineation as well as treatment planning, thus saving time and resources., Methods: Twenty-five patients with brain tumors were scanned on a spiral CT scanner and 1.5 T MRI scanner. Three treatment plans were generated for all patients. The first plan was generated using the CT scan images with inhomogeneity correction (CT + IC); the second plan used the CT scan without inhomogeneity correction (CT-IC) and the third plan was generated using the MRI scan (MRI alone)., Results: The maximum distortion in the MRI phantom study was less than 1 mm. There were no statistically significant differences in any of the target coverage parameters analysed in this study. Similarly, the maximum antero-posterior and lateral dimensions for the CT-based and MRI-based planning did not show any statistical difference., Conclusion: MRI-based treatment planning for brain lesions is feasible and gives equivalent dosimetric results compared to CT-based treatment planning.

Contralateral breast (CLB) cancer is a rare but serious concern in radiotherapy. In this study, the CLB dose was measured using MOSFET dosimeter in 49 patients who underwent breast conservation surgery treated by different radiotherapy tangential field techniques, which included enhanced dynamic wedge (EDW), physical wedge, and intensity modulated radiation therapy (IMRT). The mean percent of the prescribed dose received by the contralateral areola in treatment technique using physical wedge (Cobalt), physical wedge (Linac), EDW, and IMRT were 4.27% (SD: 0.65), 3.61% (SD: 0.60), 3.38% (SD: 0.58), and 1.65% (SD: 0.24), respectively. There was a 29% CLB dose reduction at 3 cm from the medial tangential field border with IMRT compared to other wedged tangential field techniques. The study shows that the CLB dose could be reduced with IMRT or reducing or avoiding the medial wedge in conventional tangential field planning for breast cancer.

Cardiac toxicity is an important concern in tangential field breast radiotherapy. In this study, the impact of three different breathing conditions on the dose to surrounding normal structures such as heart, ipsilateral lung, liver and contralateral breast has been assessed. Thirteen patients with early breast cancer who underwent conservative surgery (nine left-sided and four right-sided breast cancer patients) were selected in this study. Spiral CT scans were performed for all the three breathing conditions, viz., deep inspiration breath-hold (DIBH), normal breathing phase (NB) and deep expiration breath-hold (DEBH). Conventional tangential fields were placed on the 3D-CT dataset, and the parameters such as V30 (volume covered by dose >30 Gy) for heart, V20 (volume covered by dose >20 Gy) for ipsilateral lung and V(50) (volume receiving >50% of the prescription dose) for heart and liver were studied. The average reduction in cardiac dose due to DIBH was 64% (range: 26.5-100%) and 74% (range: 37-100%) as compared to NB and DEBH respectively. For right breast cancer, DIBH resulted in excellent liver sparing. Our results indicate that in patients with breast cancer, delivering radiation in deep inspiration breath-hold condition can considerably reduce the dose to the surrounding normal structures, particularly heart and liver.

In vitro dose-response calibration curves for (60)Co gamma rays have been established for unstable chromosome aberrations in human peripheral blood lymphocytes. The observed dose-response data were fitted to a linear quadratic model. The calibration curve parameters were used to estimate the equivalent whole-body dose and dose to the irradiated region in partial body irradiation of cancer patients. The derived partial body doses and fractions of lymphocytes irradiated were in agreement with those estimated from the radiotherapy regimes.

This paper presents a model using fuzzy synthetic evaluation to estimate the methane generation rate constant, k, for landfills. Four major parameters, precipitation, temperature, waste composition and landfill depth were used as inputs to the model. Whereas, these parameters are known to impact the methane generation, mathematical relationships between them and the methane generation rate constant required to estimate methane generation in landfills, are not known. In addition, the spatial variations of k within a landfill combined with the necessity of site-specific information to estimate its value, makes k one of the most elusive parameters in the accurate prediction of methane generation within a landfill. In this paper, a fuzzy technique was used to develop a model to predict the methane generation rate constant. The model was calibrated and verified using k values from 42 locations. Data from 10 sites were used to calibrate the model and the rest were used to verify it. The model predictions are reasonably accurate. A sensitivity analysis was also conducted to investigate the effect of uncertainty in the input parameters on the generation rate constant.

The presence of high levels of salts because of produced brine water disposal at flare pits and the presence of metals at sufficient concentrations to impact microbial activity are of concern to bioremediation of flare pit waste in the upstream oil and gas industry. Two slurry-phase biotreatment experiments based on three-level factorial statistical experimental design were conducted with a flare pit waste. The experiments separately studied the primary effect of cadmium [Cd(II)] and interaction effect between Cd(II) and salinity and the primary effect of zinc [Zn(II)] and interaction effect between Zn(II) and salinity on hydrocarbon biodegradation. The results showed 42-52.5% hydrocarbon removal in slurries spiked with Cd and 47-62.5% in the slurries spiked with Zn. The analysis of variance showed that the primary effects of Cd and Cd-salinity interaction were statistically significant on hydrocarbon degradation. The primary effects of Zn and the Zn-salinity interaction were statistically insignificant, whereas the quadratic effect of Zn was highly significant on hydrocarbon degradation. The study on effects of metallic chloro-complexes showed that the total aqueous concentration of Cd or Zn does not give a reliable indication of overall toxicity to the microbial activity in the presence of high salinity levels.

Introduction: Total skin electron irradiation (TSEI) therapy is the treatment of choice for mycosis fungoides. However, conventional TSEI therapy is time consuming as well as patient unfriendly. Therefore we used high-dose rate (HDR) mode TSEI in these patients. High-dose rate mode of TSEI is a technological innovation attached to a Linear Accelerator (Philips, SL-20, Netherlands), which can deliver an electron beam of 30 Gy/min at the iso-center. The iso-center faces the patient, 100 cm away from the target of the linear accelerator. The patient is treated at a distance of 10 feet from the iso-center of the linear accelerator. The dose delivered to the skin was 1.13 Gy/min, making the treatment execution much easier and patient compliance much better., Methods: Seven male patients between 40 and 64 years in age having mycosis fungoides for 9-18 months were treated by TSEI using high-dose rate mode between 1998 and 2000. The TSEI was performed according to the Stanford technique, delivering a total dose of 36 Gy. Each patient received a dose of 1.2 Gy/field/day. There were six fields, i.e. anterior, posterior, left and right anterior obliques, and left and right posterior obliques in both the upper and lower parts of the body. The eyes and nails were shielded at each session of radiotherapy. The times taken at each session of the therapy and radiation-associated side-effects were determined in each patient. The patients were followed up to 26 months (median 9 months) to look for any relapse., Results: Three patients had early stage disease (IB) whereas four patients had advanced disease (IIB). Six patients out of these had complete remission following TSEI while one patient died as a result of progression of the disease during treatment. The treatment time taken at each treatment session in each individual patient was approximately 15 min. Radiation-associated morbidity was seen in all patients. Cutaneous lesions relapsed in two patients after 4 and 10 months, respectively, while four patients were alive without the disease at the end of 2 years., Conclusions: Total skin electron irradiation using high-dose rate mode delivery of electrons is an easy, better, compliant and effective therapeutic modality for treatment of mycosis fungoides with an acceptable range of toxicities.

NAD(P)H:nitrate reductase (NaR, EC 1.7.1.1-3) is a useful enzyme in biotechnological applications, but it is very complex in structure and contains three cofactors-flavin adenine dinucleotide, heme-Fe, and molybdenum-molybdopterin (Mo-MPT). A simplified nitrate reductase (S-NaR1) consisting of Mo-MPT-binding site and nitrate-reducing active site was engineered from yeast Pichia angusta NaR cDNA (YNaR1). S-NaR1 was cytosolically expressed in high-density fermenter culture of methylotrophic yeast Pichia pastoris. Total amount of S-NaR1 protein produced was approximately 0.5 g per 10 L fermenter run, and methanol phase productivity was 5 microg protein/g wet cell weight/h. Gene copy number in genomic DNA of different clones showed direct correlation with the expression level. S-NaR1 was purified to homogeneity in one step by immobilized metal affinity chromatography (IMAC) and total amount of purified protein per run of fermentation was approximately 180 mg. Polypeptide size was approximately 55 kDa from electrophoretic analysis, and S-NaR1 was mainly homo-tetrameric in its active form, as shown by gel filtration. S-NaR1 accepted electrons efficiently from reduced bromphenol blue (kcat = 2081 s(-1)) and less so from reduced methyl viologen (kcat = 159 s(-1)). The nitrate KM for S-NaR1 was 30 +/- 3 microM, which is very similar to YNaR1. S-NaR1 is capable of specific nitrate reduction, and direct electric current, as shown by catalytic nitrate reduction using protein film cyclic voltammetry, can drive this reaction. Thus, S-NaR1 is an ideal form of this enzyme for commercial applications, such as an enzymatic nitrate biosensor formulated with S-NaR1 interfaced to an electrode system.

Background: Cutaneous T-cell lymphoma (CTCL) is a rare occurrence in India. Total skin electron irradiation (TSEI) is a well-accepted therapeutic modality for the treatment of CTCL throughout the world. The aim of this study was to retrospectively analyze the treatment outcome of TSEI in Indian patients with CTCL and to determine the different parameters affecting the disease-free survival in these patients., Methods: Fourteen male patients between 27 and 82 years of age with CTCL (duration of disease, 4 months to 2 years) were treated with TSEI between 1985 and 1998. Seven patients had early stage disease, while the other seven had advanced disease. Two patients had lymph node involvement at the time of presentation. The TSEI was performed according to the Stanford technique delivering a total dose in the range 8-36 Gy., Results: Of the 14 patients, 10 showed complete remission following TSEI. The total follow-up period was 4-110 months (median, 52 months). Five patients were disease free at the end of 5 years. Two patients died due to rapid progression of the disease, while the cutaneous lesions relapsed in three patients after 2-27 months and one patient developed visceral metastasis., Conclusions: TSEI was an effective therapeutic modality for the treatment of CTCL in this group of patients, both as a curative and palliative measure, although the long-term prognosis is poor.

Compacted soils restrict root penetration hindering productivity. In this paper, genetic variability of cotton (Gossipium spp.) root capacity to penetrate hard soil layers and the patterns of gene expression during penetration event were investigated. To mimic hard soil layers, wax-petrolatum mixtures were used. Genetic variability among 27 cotton genotypes for the root capacity to penetrate wax-petrolatum disks of 500-700 g wax/kg of mixture was high indicating that breeding efforts targeted to improve this trait can be successful. In the root tips of a cotton strain with high root penetrating ability (G. hirsutum HS 200) which penetrated through wax-petrolatum disks (P), quantity of four polypeptides with molecular weights 35-66 kDa increased compared to those root tips which grew in the absence of mechanical impedance (NP). Differential display showed significant differences in the sets of mRNA expressed in P and NP roots. Out of a total of 917 cDNAs scored in the differential display experiment, 118 cDNAs, or 13%, were specific to P roots and hence could be associated with the root penetration event. Further detailed study of gene expression in penetrated roots will pinpoint molecular factors involved in root penetration ability in cotton.

Stereotactic irradiation, either in the form of stereotactic radiosurgery (SRS) or stereotactic radiotherapy (SRT) of brain lesions requires high precision and submillimetre accuracy in the isocentre, the main determinants being gantry and couch rotations. It is thus necessary to evaluate the isocentre variation due to gantry and couch rotations in the particular setup for SRS/SRT. This paper describes variation in the isocentre of a Philips (now Elekta) SL-20 linear accelerator modified for adapting a couch-mounted radiosurgery system. By considering the isocentre as defined by a mechanical index as the standard, the variations in the isocentre of the linear accelerator were independently measured for the gantry and for couch rotations. The variation in the isocentre for gantry rotation was found to be between 0.1 mm and 0.9 mm, conforming to the submillimetre accuracy required for SRS/SRT. However, the isocentre variation due to couch rotation varied considerably, possibly because the couch is of the RAM type. The isocentre variation due to couch rotation is rectified by microadjusting the couch mount at the time of treatment using a laser target localizing frame. It is our conclusion that a modified linear accelerator can be used for performing SRS/SRT after careful and separate evaluation of the isocentre stability due to gantry and couch rotations.

Radical radiotherapy is considered as the treatment of choice in locally advanced cancer cervix. In late stages radiotherapy produce optimum palliation and to some extent cure. Three hundred cases of cancer cervix (stage I-IV) comprising stage-I (7), stage-II (144), stage-III (145) and stage IV (4) were evaluated and treated with radiotherapy between April 1990 to July 1994. FIGO stage IB, IIA and IIB (early), were treated with predominant intracavitary radiotherapy (34 Gy X 2 fractions; within one week) followed by external pelvic radiotherapy to a dose of 36 Gy in 18 fractions; treating 200 cGy per fraction, 5 days a week. The late stage (stage-IIB, IIIA and IIIB, IVA) of disease were managed with initial external radiotherapy to a dose of 50 Gy, followed by a single intracavitary dose of 30 Gy to point-A. The median follow up was 33 months (range 12-72 months). The tumor volume less than 100 cc were associated with better survival than volume more than 100 cc (p < 0.05). The five year actuarial survival was 83%, 68% and 58% respectively in FIGO stage I-III disease. There were 0.33% and 2.6% late grade-III bladder and rectal complications. Our experience shows effectiveness of radiotherapy in the management of locally advanced cancer of the cervix.

A detailed analysis of host-tumor factors and interstitial physical factors influencing the disease-free control in carcinoma of the tongue was carried out. Twenty-eight cases of carcinoma of the tongue T1-3, NO-1, MO were treated radically with combined external irradiation and 192Iridium interstitial brachytherapy (one patient received brachytherapy only). The teletherapy dose ranged from 44 Gy to 56 Gy (average 48 Gy), the brachytherapy dose ranged from 16 Gy to 55 Gy (average 22 Gy). The interstitial practice involved loop technique in all the cases. Dose distribution analysis to assess factors influencing local control included indices of dose rate, source activity, inter-planar distance, and discontinuity in the prescribed isodose in other planes when compared to mid-plane. Two-year actuarial disease-free survival (DFS) was 46% with primary treatment and 63% when salvage treatment was also included. DFS was significantly poorer when the interplanar distance at mid-plane exceeded 10 mm (p < 0.05). Similarly, tumor control was poorer (p < 0.008) when there was discontinuity in the prescribed isodose in 1 or 2 planes (1 cm superior and inferior to mid-plane). Interplanar distance of around 10 mm, prescribed isodose continuity in all three planes and limiting the dose maximum within a factor of 2 will optimize the results of interstitial implants.

Humoral antibody responses in cattle or rabbits infected with virulent rinderpest virus or lapinised rinderpest virus respectively were assessed. Rinderpest specific antibodies could be first detected 6 days post-infection. No correlation could be established between antibody response and the course of the disease in infected animals during the early stages of infection. The animals with fatal infection either did not respond or had a transient antibody response. A gradual increase in antibody titre from 7 days post-infection was observed in animals which ultimately recovered.