Enteritis: a window to the diagnosis of systemic lupus erythematosus in an adolescent girl: case report

BACKGROUND

Enteritis is one of the rare systemic manifestations in childhood-onset systemic lupus erythematosus and its diagnosis is very challenging. This is a rare case of an adolescent girl with recurrent non-specific gastro-intestinal symptoms which were later diagnosed to be owing to lupus enteritis, the only presenting manifestation of an active flare.

CASE REPORT

A 15-year-old girl was admitted with recurrent episodes of abdominal pain, vomiting and loose stools. She had diffuse abdominal tenderness. Abdominal ultrasonography demonstrated moderate ascites. A contrast-enhanced abdominal computerised tomography scan revealed thickening of the small bowel wall. On colonoscopy, there were rectal erosions, and microscopic examination of the biopsy specimens demonstrated mild inflammation. Non-specific enteritis was diagnosed and she was given antibiotics and supportive care. She was re-admitted 6months later with abdominal pain. An abdominal contrast-enhanced computerised tomography scan revealed thickening of the bowel wall and the target sign and comb sign in the small intestine. The anti-nuclear antibody was positive. Renal biopsy demonstrated grade 2 lupus nephritis. Lupus enteritis was diagnosed and the case satisfied the 2019 EULAR-ACR criteria and SLICC criteria. She was treated with methylprednisolone, cyclophosphamide and hydroxychloroquine. She improved with treatment and has remained asymptomatic during follow-up.

CONCLUSION

This case emphasises the need for healthcare providers to be alert to the possibility of lupus enteritis. It also highlights the importance of close follow-up of cases who have non-specific gastro-intestinal symptoms. Lupus enteritis should be considered in the differential diagnosis of recurrent non-specific gastro-intestinal symptoms in children, especially adolescents, to ensure timely diagnosis and treatment.Abbreviations: ACR American College of Rheumatology; ANA anti-nuclear antibody; CRP: C-reactive protein; CT: computerised tomography; CECT: contrast-enhanced computerised tomography; EULAR: European League Against Rheumatism; GI: gastro-intestinal; LE: lupus enteritis; SLE systemic lupus erythematosis; SLICC: Systemic Lupus International Collaborating Clinics; SLEDAI: SLE disease activity index.

Skull Base Metastasis and Krukenberg Tumor in a Pregnant Woman: An Unusual Presentation of Metastatic Gastric Cancer

Gastric cancer is an infrequent cause of vomiting during pregnancy. It is often diagnosed at an advanced stage due to late presentation by patients, mistaking it for gestational symptoms. We report a 24-year-old pregnant woman with gastric cancer with skull base metastasis and Krukenberg tumor on initial diagnosis. She underwent medical termination of pregnancy and best supportive care before dying of her illness.

Radiological Parameters Predicting the Round Window Niche Visibility through Facial Recess Approach in Cochlear Implantation

Aim

The aim was to study the radiological parameters using High Resolution Computed Tomography (HRCT) temporal bone to predict the Round Window Niche (RWN) visibility through the facial recess approach and to study radiological types of the round window niche.

Materials and Methods

Prospective study was done in the patients underwent CI surgery from 2019 to 2021. HRCT radiological parameters of the patients and their intraoperative visualisation from video recordings were compared to predict the most feasible parameters to predict good visualisation of RWN.

Results

Among 51 patients (34 males, 17 females) in 48 children round window membrane insertion was done and in three children cochleostomy was done and in two children partial canal wall drilling was done due to poor visualisation of RWN area. Multiple parameters to assess the visibility of the RWN were used. Facial recess width (4.2 mm), location of the mastoid segment of facial nerve (2 mm), external auditory canal to basal turn of cochlea angle (< 13.50) and the radiological types (tunnel shape and semi-circular shape) of the RWN by HRCT were found to be significant parameters in predicting a good visualisation of the RWN.

Conclusion

HRCT parameters prepare the surgeon to face the possibility of a difficult surgery and plan to deal with difficult situations. This would eventually lead to better preparedness of surgeons for management of complications.

Diagnostic challenges in cerebral tuberculoma presenting with seizures in pregnancy

Tuberculoma is an uncommon presentation of tuberculosis and is found in regions with a high prevalence of tuberculosis. This is rarely diagnosed during pregnancy. The presentation can mimic other etiologies such as eclampsia or cerebral venous sinus thrombosis so the diagnosis can be challenging, particularly when presenting with seizures in pregnancy. Described here is a woman in her first pregnancy who presented with seizures mimicking eclampsia and was suspected to have a brain tumour on neuroimaging. She was diagnosed to have a intracerebral tuberculoma on histopathological examination following surgical decompression after delivery.

Advance on the biology, behaviour ecology and management of the coffee white stem borer, Xylotrechus quadripes Chevrolat, 1863 (Coleoptera: Cerambycidae)

The coffee white stem borer, Xylotrechus quadripes Chevrolat, 1863 (Coleoptera: Cerambycidae) - here removed from the synonymy with X. javanicus (Laporte & Gory, 1841) - is the most notorious pest in Arabica coffee plantations in many southeast Asian countries. It can cause damage up to 80% in various gardens. The borer is reported on 16 different host plants other than coffee. The severity of the pest was more commonly recorded on the Arabica coffee than on other species. More pest intensity on the coffee may be due to its innate evolutionary relation compared to other host plants. Studies revealed that the borer is more specific and attracted to the volatile of coffee plants but it is still needs a strong supporting data. Some of the behavioural and ecological-adaptations of borers leads to avoid predation and chemical-pesticides reaching them. Hence, no single method gives perfect control of this pest; therefore, harmonic use of different tools such as cultural, mechanical, physical, bio-control and chemical methods are the best way to combat this pest. Though the pest is economically important, the information on chemical and ecological behaviour, host plant resistance and recent advancements in the pest management are scanty. The present article is an endeavour to shed a light on biology, behaviour, host selection and management of X. quadripes with multiple instances, that will give a new avenue for the researchers to work on the least concerned fields to develop strong management practice and alert against future pest outbreak.

Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic review

Deep learning has become a thriving force in the computer aided diagnosis of liver cancer, as it solves extremely complicated challenges with high accuracy over time and facilitates medical experts in their diagnostic and treatment procedures. This paper presents a comprehensive systematic review on deep learning techniques applied for various applications pertaining to liver images, challenges faced by the clinicians in liver tumour diagnosis and how deep learning bridges the gap between clinical practice and technological solutions with an in-depth summary of 113 articles. Since, deep learning is an emerging revolutionary technology, recent state-of-the-art research implemented on liver images are reviewed with more focus on classification, segmentation and clinical applications in the management of liver diseases. Additionally, similar review articles in literature are reviewed and compared. The review is concluded by presenting the contemporary trends and unaddressed research issues in the field of liver tumour diagnosis, offering directions for future research in this field.

Evidence-based insecticide resistance in South American tomato leaf miner, Phthorimaea absoluta (Meyrick) under laboratory selection

The South American tomato moth, Phthorimaea absoluta (Meyrick), is one of the key pests of tomato in India. Since its report in 2014, chemical control has been the main means of tackling this pest, both in the open field and protected cultivation. Despite regular insecticidal sprays, many outbreaks were reported from major tomato-growing regions of South India during 2019-2020. A study was conducted to investigate the effect of insecticide resistance on biology, biochemical enzymes, and gene expression in various P. absoluta field populations viz., Bangalore, Kolar, Madurai, Salem, and Anantapur to commonly used insecticides such as flubendiamide, cyantraniliprole, and indoxacarb. Increased levels of insecticide resistance ratios (RR) were recorded in P. absoluta populations of different locations. A significant increase in cytochrome P450 monooxygenase (CYP/MFO) and esterase levels was noticed in the resistant population compared to susceptible one. Through molecular studies, we identified four new CYP genes viz., CYP248f (flubendiamide), CYP272c, CYP724c (cyantraniliprole), and CYP648i (indoxacarb). The expression levels of these genes significantly increased as the folds of resistance increased from G1 to G20 (generation), indicating involvement of the identified genes in insecticide resistance development in P. absoluta. In addition, the resistant populations showed decreased fecundity, increased larval development period, and adult longevity, resulting in more crop damage. The information generated in the present study thus helps in understanding the development of insecticide resistance by P. absoluta and suggests the farmers and researchers to use insecticides wisely by adopting insecticide resistance management as a strategy under integrated pest management.

Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease

PURPOSE

Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases.

METHODS

The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature.

RESULTS

The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.

A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal

Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These arrhythmias can lead to potentially deadly consequences, putting your life in jeopardy. As a result, arrhythmia identification and classification are an important aspect of cardiac diagnostics. An electrocardiogram (ECG), a recording collecting the heart's pumping activity, is regarded the guideline for catching these abnormal episodes. Nevertheless, because the ECG contains so much data, extracting the crucial data from imagery evaluation becomes extremely difficult. As a result, it is vital to create an effective system for analyzing ECG's massive amount of data. The ECG image from ECG signal is processed by some image processing techniques. To optimize the identification and categorization process, this research presents a hybrid deep learning-based technique. This paper contributes in two ways. Automating noise reduction and extraction of features, 1D ECG data are first converted into 2D pictures. Then, based on experimental evidence, a hybrid model called CNNLSTM is presented, which combines CNN and LSTM models. We conducted a comprehensive research using the broadly used MIT_BIH arrhythmia dataset to assess the efficacy of the proposed CNN-LSTM technique. The results reveal that the proposed method has a 99.10 percent accuracy rate. Furthermore, the proposed model has an average sensitivity of 98.35 percent and a specificity of 98.38 percent. These outcomes are superior to those produced using other procedures, and they will significantly reduce the amount of involvement necessary by physicians.

An Automated Deep Learning Model for the Cerebellum Segmentation from Fetal Brain Images

Cerebellum measures taken from routinely obtained ultrasound (US) images have been frequently employed to determine gestational age and identify developing central nervous system's anatomical abnormalities. Standardized cerebellar assessments from large-scale clinical datasets are required to investigate correlations between the growing cerebellum and postnatal neurodevelopmental results. These studies could uncover structural abnormalities that could be employed as indicators to forecast neurodevelopmental and growth consequences. To achieve this, higher-throughput, precise, and impartial measures must be used to replace the existing human, semiautomatic, and advanced algorithms, which seem to be time-consuming and inaccurate. In this article, we presented an innovative deep learning (DL) technique for automatic fetal cerebellum segmentation from 2-dimensional (2D) US brain images. We present ReU-Net, a semantic segmentation network tailored to the anatomy of the fetal cerebellum. Moreover, we use U-Net as a foundation models with the incorporation of residual blocks and Wiener filter over the last 2 layers to segregate the cerebellum (c) from the noisy US data. 590 images for training and 150 images for testing were taken; also, we employed a 5-fold cross-assessment method. Our ReU-Net scored 91%, 92%, 25.42, 98%, 92%, and 94% for Dice Score Coefficient (DSC), F1-score, Hausdorff Distance (HD), accuracy, recall, and precision, correspondingly. The suggested method outperforms the other U-Net predicated techniques by a quantitatively significant margin (p 0.001). Our presented approach can be used to allow high bandwidth imaging techniques in medical study fetal US images as well as biometric evaluation on a broader scale in fetal US images.

Study of ureteral and renal morphometry on the outcome of ureterorenoscopic lithotripsy: The critical role of maximum ureteral wall thickness at the site of ureteral stone impaction

Purpose:

The purpose is to study the association of stone, ureteral, and renal morphometric parameters with the relevant outcome variables, i.e., complication rate, stone-free rate (SFR), and operating time of ureterorenoscopic lithotripsy. Although a safe procedure, it still occasionally has major complications. Computed tomography (CT) scan is often performed to diagnose ureteral calculi, providing opportunities for ureteral morphometry that may have a bearing on the outcome of the procedure.

Materials and Methods:

Ureteric, renal, and stone morphometric parameters were measured from CT of the abdomen and pelvis of the 110 patients with ureteral calculi who underwent ureteroscopic lithotripsy (URSL). Data were collected retrospectively in 25 patients and prospectively in 85 patients. Association of these parameters with the outcome variables of the procedure mentioned above was studied.

Results:

On univariate analysis, body mass index, stone size, and maximum ureteral wall thickness (MUWT) were found to have a significant association with URSL complications, SFR, and duration of surgery. On multivariable analysis, only MUWT was found to be an independent risk factor for URSL complications. In 90% of total patients with residual stones, MUWT was found to be >4.8 mm.

Conclusion:

Ureteral wall thickness of >4.8 mm is associated with prolonged duration of surgery and lower SFR. Patients with ureteral wall thickness of >4.8 mm at the site of ureteral stone who are planned for URSL must be counseled about the higher chances of residual stones and the need for additional procedure.

Clinical relevance of cagA and vacA and association with mucosal findings in Helicobacter pylori-infected individuals from Chennai, South India

Helicobacter pylori is associated with a spectrum of severe gastrointestinal conditions. In this study, an attempt was made to correlate endoscopic mucosal patterns with H. pylori infection and examine the pathogenic potential of the strains. Among the 147 dyspeptic individuals studied, 42.2% were H. pylori infected. Association of H. pylori with type 3 and 4 mucosal patterns (P = 0.001) and intestinal metaplasia (P = 0.012) was seen. vacA was associated with histological (P = 0.014) and endoscopy findings (P = 0.009). Association of mucosal patterns with H. pylori infection could be useful for clinicians to decide on the need for eradication therapy.

Identification and fine mapping of a new gene, BPH31 conferring resistance to brown planthopper biotype 4 of India to improve rice, Oryza sativa L

BACKGROUND

Rice (Oryza sativa L.) is the staple food for more than 3.5 billion people, mainly in Asia. Brown planthopper (BPH) is one of the most destructive insect pests of rice that limits rice production. Host-plant resistance is one of the most efficient ways to overcome BPH damage to the rice crop.

RESULTS

BPH bioassay studies from 2009 to 2015 conducted in India and at the International Rice Research Institute (IRRI), Philippines, revealed that the cultivar CR2711-76 developed at the National Rice Research Institute (NRRI), Cuttack, India, showed stable and broad-spectrum resistance to several BPH populations of the Philippines and BPH biotype 4 of India. Genetic analysis and fine mapping confirmed the presence of a single dominant gene, BPH31, in CR2711-76 conferring BPH resistance. The BPH31 gene was located on the long arm of chromosome 3 within an interval of 475 kb between the markers PA26 and RM2334. Bioassay analysis of the BPH31 gene in CR2711-76 was carried out against BPH populations of the Philippines. The results from bioassay revealed that CR2711-76 possesses three different mechanisms of resistance: antibiosis, antixenosis, and tolerance. The effectiveness of flanking markers was tested in a segregating population and the InDel type markers PA26 and RM2334 showed high co-segregation with the resistance phenotype. Foreground and background analysis by tightly linked markers as well as using the Infinium 6 K SNP chip respectively were applied for transferring the BPH31 gene into an indica variety, Jaya. The improved BPH31-derived Jaya lines showed strong resistance to BPH biotypes of India and the Philippines.

CONCLUSION

The new BPH31 gene can be used in BPH resistance breeding programs on the Indian subcontinent. The tightly linked DNA markers identified in the study have proved their effectiveness and can be utilized in BPH resistance breeding in rice.

Green synthesis of selenium nanoparticles conjugated Clausena dentata plant leaf extract and their insecticidal potential against mosquito vectors

Mosquitoes are major vectors for the transmission of many diseases like chikungunya, malaria, dengue, zika, etc. worldwide. In the present study, selenium nanoparticles (SeNPs) were synthesized from Clausena dentata and were tested for their larvicidal efficacy against the fourth-instar larvae of Anopheles stephensi, Aedes Aegypti, and Culex quinquefasciatus. The synthesized nanoparticles were characterized using UV-Vis spectroscopy, Fourier Transform Infrared Radiation (FTIR) spectroscopy, EDaX, and SEM. The results recorded from UV-Vis spectroscopy show the peak absorption spectrum at 420 nm. In FTIR, the maximum peak value is 2922.25 cm^-1 assigned to N-H group (amide group). In EDaX analysis shows peak around 72.64 which confirm the binding intensity of selenium. In SEM analysis, the synthesized SeNPs sizes were ranging from 46.32 nm to 78.88 nm. The synthesized SeNPs produced high mortality with very low concentration (LC₅₀) were 240.714 mg/L; 104.13 mg/L, and 99.602 mg/L for A. stephensi, A. Aegypti, and C. quinquefasciatus, respectively. These results suggest that the C. dentata leaf extract-mediated biosynthesis of SeNPs has the potential to be used as an ideal ecofriendly approach toward the control of mosquito vectors at early stages.

Nucleotide variation and identification of novel blast resistance alleles of Pib by allele mining strategy

Pib is one of significant rice blast resistant genes, which provides resistance to wide range of isolates of rice blast pathogen, Magnaporthe oryzae. Identification and isolation of novel and beneficial alleles help in crop enhancement. Allele mining is one of the best strategies for dissecting the allelic variations at candidate gene and identification of novel alleles. Hence, in the present study, Pib was analyzed by allele mining strategy, and coding and non-coding (upstream and intron) regions were examined to identify novel Pib alleles. Allelic sequences comparison revealed that nucleotide polymorphisms at coding regions affected the amino acid sequences, while the polymorphism at upstream (non-coding) region affected the motifs arrangements. Pib alleles from resistant landraces, Sercher and Krengosa showed better resistance than Pib donor variety, might be due to acquired mutations, especially at LRR region. The evolutionary distance, Ka/Ks and phylogenetic analyzes also supported these results. Transcription factor binding motif analysis revealed that Pib (Sr) had a unique motif (DPBFCOREDCDC3), while five different motifs differentiated the resistance and susceptible Pib alleles. As the Pib is an inducible gene, the identified differential motifs helps to understand the Pib expression mechanism. The identified novel Pib resistant alleles, which showed high resistance to the rice blast, can be used directly in blast resistance breeding program as alternative Pib resistant sources.

Nucleotide diversity of Pita, a major blast resistance gene and identification of its minimal promoter

Improvement of host plant resistance is one of the best methods to protect the yield from biotic stresses. Incorporation of major resistance genes or their variants into elite rice varieties will enhance the host plant resistance and its durability. Allele mining is a preferred choice to discover the novel allelic variants of major genes from wide range of germplasm. 'True' allele mining includes coding and noncoding regions, which are known to affect the plant phenotype, eventually. In this study, major blast resistance gene, Pita was analyzed by allele and promoter mining strategy and its different allelic variants were discovered from landraces and wild Oryza species. Polymorphisms at allelic sequences as well as transcription factor binding motif (TFBM) level were examined. At motif level, MYB1AT is present in Pita(Tadukan) and other resistance alleles, but was absent in the susceptible allele. Core promoter was demarked with 449 bp, employing serial promoter deletion strategy. Promoter with 1592 bp upstream region could express the gfp two fold higher than the core promoter. The identified Pita resistance allele (Pita(Konibora)) can be directly used in rice blast resistance breeding programs. Moreover, characterization of Pita core promoter led to deeper understanding of resistance gene's regulation and the identified core promoter can be utilized to express similar genes in rice.

The molecular diversity and evolution of Rice tungro bacilliform virus from Indian perspective

Rice tungro disease is caused by a combination of two viruses: Rice tungro spherical virus and Rice tungro bacilliform virus (RTBV). This study was performed with the objective to decipher the molecular variability and evolution of RTBV isolates present in the tungro-affected states of Indian subcontinent. Phylogenetic analysis based on ORF-I, ORF-II, and ORF-IV sequences showed distinct divergence of Indian RTBV isolates into two groups; one consisted isolates from Hyderabad (Andhra Pradesh), Cuttack (Orissa), and Puducherry and another from West Bengal, Chinsura West Bengal, and Kanyakumari (Tamil Nadu). The results obtained from phylogenetic analysis were further supported with the single nucleotide polymorphisms (SNPs), insertion and deletion (INDELs) and evolutionary distance analysis. In addition, sequence difference count matrix revealed a maximum of 56 (ORF-I), 13 (ORF-II) and 73 (ORF-IV) nucleotides differences among all the Indian RTBV isolates taken in this study. However, at the protein level these differences were not significant as revealed by K (a)/K (s) ratio calculation. Sequence identity at nucleotide and amino acid level was 92-100 % (ORF-I), 96-100 % (ORF-II), 94-100 % (ORF-IV) and 86-100 % (ORF-I), 98-100 % (ORF-II) and 95-100 % (ORF-IV), respectively, among Indian isolates of RTBV. The divergence of RTBV isolates into two independent clusters of Indian and non-Indian was shown with the help of the data obtained from phylogeny, SNPs, and INDELs, evolutionary distance analysis, and conserved motifs analysis. The important role of ORF-I and ORF-IV in RTBV diversification and adaptation to different rice growing regions is also discussed.

Genetic variation of coat protein gene among the isolates of Rice tungro spherical virus from tungro-endemic states of the India

Rice tungro disease, one of the major constraints to rice production in South and Southeast Asia, is caused by a combination of two viruses: Rice tungro spherical virus (RTSV) and Rice tungro bacilliform virus (RTBV). The present study was undertaken to determine the genetic variation of RTSV population present in tungro endemic states of Indian subcontinent. Phylogenetic analysis based on coat protein sequences showed distinct divergence of Indian RTSV isolates into two groups; one consisted isolates from Hyderabad (Andhra Pradesh), Cuttack (Orissa), and Puducherry and another from West Bengal, Coimbatore (Tamil Nadu), and Kanyakumari (Tamil Nadu). The results obtained from phylogenetic study were further supported with the SNPs (single nucleotide polymorphism), INDELs (insertion and deletion) and evolutionary distance analysis. In addition, sequence difference count matrix revealed 2-68 nucleotides differences among all the Indian RTSV isolates taken in this study. However, at the protein level these differences were not significant as revealed by Ka/Ks ratio calculation. Sequence identity at nucleotide and amino acid level was 92-100% and 97-100%, respectively, among Indian isolates of RTSV. Understanding of the population structure of RTSV from tungro endemic regions of India would potentially provide insights into the molecular diversification of this virus.

Synthesis and antibacterial activity of a novel series of acylides active against community acquired respiratory pathogens

A novel series of acylides 4 were designed to overcome antibacterial resistance and evaluated for in vitro and in vivo activity. This series of acylides was designed from clarithromycin by changing the substitution on the desosamine nitrogen, followed by conversion to 3-O-acyl and 11,12-carbamate. These compounds showed significantly potent antibacterial activity against not only Gram-positive pathogens, including macrolide-lincosamide-streptogramin B (MLS(B))-resistant and efflux-resistant strains, but also Gram-negative pathogens such as Haemophilus influenzae. These acylides also showed better activity against telithromycin resistant Streptococcus pneumoniae strains.

Bt rice evaluation and deployment strategies

Bacillus thuringiensis (Bt), a gram positive soil bacteria was first identified and named by Japanese microbiologist Shigetane Ishiwata in 1901. During sporulation Bt produces proteinaceous parasporal crystal proteins called δ-endotoxins, or Cry proteins, which are insecticidal. Numerous Cry proteins have been isolated and characterized from different Bt strains with activity against insects, mites and nematodes. Sprayable formulations containing these Cry proteins as active ingredients have contributed significantly in the field of insect pest management. Since the first cloning of cry genes from Bt,1 scientists have successively demonstrated that plants could be genetically engineered to express these cry genes for the control of dreadful insect pests. Eventually, the first transgenic crop expressing Btcry1Ac gene in cotton was approved in 1996 for commercial cultivation in the USA to manage bollworms.