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  1. Article ; Online: Automated Synthesis of [11C]PiB via [11CH3OTf]-as Methylating Agent for PET Imaging of β-Amyloid.

    Singh, Akhilesh K / Gambhir, Sanjay / Dixit, Manish

    Current radiopharmaceuticals

    2024  

    Abstract: Aim: Efficient synthesis of precursor from commercially available starting materials and automated radiosynthesis of [11C]PiB using commercially available dedicated [11C]- Chemistry module from the synthesized precursor.: Background: [11C]PiB is a ... ...

    Abstract Aim: Efficient synthesis of precursor from commercially available starting materials and automated radiosynthesis of [11C]PiB using commercially available dedicated [11C]- Chemistry module from the synthesized precursor.
    Background: [11C]PiB is a promising radiotracer for PET imaging of β-Amyloid, advancing Alzheimer's disease research. The availability of precursors and protocols for efficient radiolabelling foster the applications of any radiotracer. Efficient synthesis of PiB precursor was performed using anisidine and 4-nitrobenzoyl chloride as starting materials in 5 steps, having addition, substitutions, and cyclization chemical methodologies. This precursor was used for fully automated radiosynthesis of [11C]PiB in a commercially available synthesizer, MPS-100 (SHI, Japan). The synthesized [11C]PiB was purified via solid-phase methodology, and its quality control was by the quality and safety criteria required for clinical use.
    Methods: The synthesis of desired precursors and standard authentic compounds started with commercially available materials with 70-80% yields. The standard analytical methods characterized all synthesized compounds. The fully automated [11C]-chemistry synthesizer (MPS-100) used for radiosynthesis of [11C]PiB with [11C]CH3OTf acts as a methylating agent. For radiolabelling, varied amounts of precursor and time of reaction were explored. The resulting crude product underwent purification through solid-phase cartridges. The synthesized radiotracer was analyzed using analytical tools such as radio TLC, HPLC, pH endo-toxicity, and half-life.
    Results: The precursor for radiosynthesis of [11C]PiB was achieved in excellent yield using simple and feasible chemistry. A protocol for radiolabelling of precursor to synthesized [11C]PiB was developed using an automated synthesizer. The crude radiotracer was purified by solid-phase cartridge, with a decay-corrected radiochemical yield of 40±5% and radiochemical purity of more than 97% in approx 20 minutes (EOB). The specific activity was calculated and found in a 110-121 mCi/μmol range.
    Conclusion: A reliable methodology was developed for preparing precursor followed by fully automated radiolabeling using [11C]MeOTf as a methylating agent to synthesize [11C]PiB. The final HPLC-free purification yielded more than 97% radiochemical purity tracer within one radionuclide half-life. The method was reproducible and efficient for any clinical center.
    Language English
    Publishing date 2024-03-06
    Publishing country United Arab Emirates
    Document type Journal Article
    ISSN 1874-4729
    ISSN (online) 1874-4729
    DOI 10.2174/0118744710295705240229114137
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Light management using CsPbBr

    Singh, Akhilesh K

    Methods and applications in fluorescence

    2020  

    Abstract: CsPbBr3 colloidal quantum dots have been synthesized by hot-injection method showing spherical shape with an average diameter of ~ 10.5 nm. UV-vis absorption of CsPbBr3 colloidal quantum dots shows a broad spectrum with an optical bandgap of ~ 2.3682 eV. ...

    Abstract CsPbBr3 colloidal quantum dots have been synthesized by hot-injection method showing spherical shape with an average diameter of ~ 10.5 nm. UV-vis absorption of CsPbBr3 colloidal quantum dots shows a broad spectrum with an optical bandgap of ~ 2.3682 eV. The steady-state photoluminescence measurement reveals a narrow emission peak at 2.352 eV with full-width at half maximum of 0.113 eV. Absolute photoluminescence quantum yield of colloidal quantum dots dispersed in poly(methyl methacrylate) was found to be 60±1%. The time-resolved photoluminescence data recorded at 266 nm excitation were well fitted using a mono-exponential curve with a decay time of 25.36 (5) ns. A luminescent solar concentrator was fabricated using colloidal quantum dots in transparent poly(methyl methacrylate) polymer uniformly coated over glass substrate that shows an external optical conversion efficiency of ~ 5.4 % under one sun illumination. The experimental results presented in this manuscript reveals that luminescent solar concentrator prepared using colloidal CsPbBr3 quantum dots shows absorption in wide spectral range, high absorption coefficient, high photoluminescence quantum yield, high external optical conversion efficiency, and good photostability, thermal stability and long-term stability under ambient conditions and therefore are in many ways superior to the other luminescent materials explored for LSC devices.
    Language English
    Publishing date 2020-09-17
    Publishing country England
    Document type Journal Article
    ISSN 2050-6120
    ISSN (online) 2050-6120
    DOI 10.1088/2050-6120/abb99c
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: The immediate impact of mandatory helmet law on maxillo-facial trauma: A comparative study in a major trauma center, Uttar Pradesh.

    Pandey, Arun / Chaturvedi, Thakur P / Sharma, Naresh K / Singh, Akhilesh K / Kumar, Janani A / Mishra, Nitesh

    National journal of maxillofacial surgery

    2024  Volume 15, Issue 1, Page(s) 116–120

    Abstract: Aim: To analyze the effect of the mandatory helmet rule in helmet usage among motorcycle riders and on facial trauma and to determine the significance of difference in the possibility of facial trauma between the helmeted and non-helmeted motorcycle ... ...

    Abstract Aim: To analyze the effect of the mandatory helmet rule in helmet usage among motorcycle riders and on facial trauma and to determine the significance of difference in the possibility of facial trauma between the helmeted and non-helmeted motorcycle riders.
    Setting and design: A retrospective comparative study conducted in a major trauma center at Uttar Pradesh.
    Material and method: Data for the present study was obtained from records of the Emergency Department of Trauma Center, for a period of two months before and after the implementation of The Motor Vehicles Act in UP. The study included patients with a history of non-fatal motorcycle accidents who sustained facial injuries regardless of the presence of injuries to other areas of the body during the study period. Information regarding helmet usage during the accident was also recorded. The results were compared between the pre-law period and post-law period.
    Statistical analysis used: Sample t-test was applied to find the level of significance.
    Results: Out of 219 injured patients, 152 (69.40%) subjects were not wearing helmets, whereas only 67 (30.59%) subjects were wearing helmets. It was observed that around 68.18% of people stated wearing helmets after law implementation with a statistical significance (P value < 0.05).
    Conclusion: Our study shows that the mandatory helmet rule with elevated penalty rates has significantly increased the usage of helmet among the motorcycle riders, and it also proves that the possibility of facial trauma is significantly higher in non-helmeted riders when compared to helmeted riders.
    Language English
    Publishing date 2024-03-19
    Publishing country India
    Document type Journal Article
    ZDB-ID 2653583-X
    ISSN 2229-3418 ; 0975-5950
    ISSN (online) 2229-3418
    ISSN 0975-5950
    DOI 10.4103/njms.njms_313_21
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Oral rhabdomyosarcoma of mandibular region: A case report.

    Batra, Sakshi / Srivastava, Adit / Singh, Akhilesh K / Krishnan, Aswathi

    National journal of maxillofacial surgery

    2023  Volume 14, Issue 2, Page(s) 330–333

    Abstract: Rhabdomyosarcoma is a malignant neoplasm of mesenchymal cells, showing varying degrees of striated muscle cell differentiation. The most common sites of occurrence are the head and neck (40%), genitourinary tract (25%), and extremities (20%). ... ...

    Abstract Rhabdomyosarcoma is a malignant neoplasm of mesenchymal cells, showing varying degrees of striated muscle cell differentiation. The most common sites of occurrence are the head and neck (40%), genitourinary tract (25%), and extremities (20%). Rhabdomyosarcoma is anatomically divided into two categories including parameningeal and nonparameningeal. It predominantly occurs in children while rarely found in adults, and involvement of the oral cavity accounts for only 10%-20% of all head and neck cases. The present case is of oral rhabdomyosarcoma of a 27-year-old woman, involving the mandibular region and demonstrates its clinical, radiological, histological, and immunohistochemical findings.
    Language English
    Publishing date 2023-07-13
    Publishing country India
    Document type Case Reports
    ZDB-ID 2653583-X
    ISSN 2229-3418 ; 0975-5950
    ISSN (online) 2229-3418
    ISSN 0975-5950
    DOI 10.4103/njms.njms_55_22
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Activated PI3Kδ specifically perturbs mouse Treg homeostasis and function leading to immune dysregulation.

    Singh, Akhilesh K / Qureshah, Fahd Al / Drow, Travis / Hou, Baidong / Rawlings, David J

    bioRxiv : the preprint server for biology

    2023  

    Abstract: ... ...

    Abstract Foxp3
    Language English
    Publishing date 2023-12-23
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.12.21.569665
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Management and outcome of locally advanced oral squamous cell carcinoma.

    Bera, Rathindra N / Tandon, Sapna / Singh, Akhilesh K / Boojar, Fargol M A / Jaiswal, Gaurav / Borse, Shraddha / Pal, Uma S / Sharma, Naresh K

    National journal of maxillofacial surgery

    2023  Volume 14, Issue 2, Page(s) 185–189

    Abstract: Management of locally advanced OSCC is multimodal. No single therapy has been proved to be efficacious. However there is a trend towards surgical intervention in operable disease. In this review we appraise the various therapies used for the management ... ...

    Abstract Management of locally advanced OSCC is multimodal. No single therapy has been proved to be efficacious. However there is a trend towards surgical intervention in operable disease. In this review we appraise the various therapies used for the management of locally advanced OSCC. We review the literature with regards to the various treatment options for locally advanced OSCC. We categorically divided the manuscript into resectable, unresectable and technically unresectable disease. Surgery is the ideal treatment modality for resectable disease. For unresectable disease concurrent chemoradiation appears to improve survival compared to radiotherapy alone. Induction therapy might downstage tumors in the unresectable category. Targeted and Immunotherapy is reserved for recurrent, metastatic or platinum refractory OSCC. Management of locally advanced OSCC is multimodal with surgery playing the primary role. In the event where the tumor is in operable concurrent chemoradiotherapy is regarded as the best treatment modality. Induction chemotherapy currently cannot be recommended for resectable or even unresectable oral squamous cell carcinomas. However for technically unresectable disease it might play a role in improving respectability but it depends on the response of the tumor. Targeted therapy and immunotherapy is currently used for recurrent, metastatic and/or platinum refractory Head and Neck cancers. Currently it is not recommended for initial management of locally advanced disease.
    Language English
    Publishing date 2023-07-13
    Publishing country India
    Document type Journal Article ; Review
    ZDB-ID 2653583-X
    ISSN 2229-3418 ; 0975-5950
    ISSN (online) 2229-3418
    ISSN 0975-5950
    DOI 10.4103/njms.njms_125_22
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Advancements and Challenges in Developing Malaria Vaccines: Targeting Multiple Stages of the Parasite Life Cycle.

    Rajneesh / Tiwari, Rahul / Singh, Vishal K / Kumar, Awnish / Gupta, Rohit P / Singh, Akhilesh K / Gautam, Vibhav / Kumar, Rajiv

    ACS infectious diseases

    2023  Volume 9, Issue 10, Page(s) 1795–1814

    Abstract: Malaria, caused ... ...

    Abstract Malaria, caused by
    Language English
    Publishing date 2023-09-14
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2373-8227
    ISSN (online) 2373-8227
    DOI 10.1021/acsinfecdis.3c00332
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: An automated weed identification framework for sugarcane crop: A deep learning approach

    Modi, Rajesh U. / Kancheti, Mrunalini / Subeesh, A. / Raj, Chandramani / Singh, Akhilesh K. / Chandel, Narendra S. / Dhimate, Ashish S. / Singh, Mrityunjai K. / Singh, Shweta

    Crop Protection. 2023 Nov., v. 173 p.106360-

    2023  

    Abstract: Automatic weed identification using deep learning (DL) models will mark a revolution in developing site– specific artificial intelligence (AI) based herbicide sprayers which intend to maximize herbicide efficiency with reduced herbicide application in ... ...

    Abstract Automatic weed identification using deep learning (DL) models will mark a revolution in developing site– specific artificial intelligence (AI) based herbicide sprayers which intend to maximize herbicide efficiency with reduced herbicide application in agriculture production systems and hence contribute to higher yields. Conventional weed control strategies pose challenges for integrating smart herbicide delivery and machinery systems. This deep learning approach significantly impacts developing a system for weed identification required in establishing successful real time precision weed management systems like smart spraying systems and AI based smart machinery. Minimal research has been done on automatic weed identification in sugarcane (Saccharum officinarum L.) cropping systems. This study analyzed the feasibility of a computer vision based DL approach for weed identification to achieve autonomous weed control. The image dataset containing 5660 augmented images was deployed to train and evaluate DL models with a spilt of 90% for training and the rest for validation. We trained the six DL models for identifying weeds in sugarcane crop using field imagery (5094 images), validated (566 images) and further evaluated their accuracy and F1 score performance. Model training was undertaken by varying the hyperparameters, such as mini batch size (16 and 32) and epoch (10, 20 and 30) at a learning rate of 0.001. DarkNet53 accomplished a high F1 score value (>99%) and outperformed other models (AlexNet, GoogLeNet, InceptionV3, ResNet50, and Xception) for the identification of weeds in actively growing sugarcane crop. Weeds can be identified with a higher level of confidence (>98%) with a minimum error rate (<1%) at the mini batch size of 16 and epochs 20. Post-training and validation, DarkNet53 was tested (stage I) with an independent 200-image dataset followed by stage II testing (30 images) and obtained 96.6% net accuracy compared with naked eye weed identification. Based on the high – level performance of DarkNet53, we conclude that DL based weed identification laid a potential future avenue with an effective decision system in the machine vision aspects of a precision herbicide applicator for weed control in sugarcane fields through a low cost camera integrated with a single board computer.
    Keywords Saccharum officinarum ; agricultural productivity ; applicators ; artificial intelligence ; automation ; cameras ; chemical weed control ; computer vision ; computers ; data collection ; herbicide application ; herbicides ; plant protection ; sugarcane ; weeds ; Autonomous weed detection ; Classification ; Convolutional neural network ; Deep learning
    Language English
    Dates of publication 2023-11
    Publishing place Elsevier Ltd
    Document type Article ; Online
    ZDB-ID 786839-x
    ISSN 1873-6904 ; 0261-2194
    ISSN (online) 1873-6904
    ISSN 0261-2194
    DOI 10.1016/j.cropro.2023.106360
    Database NAL-Catalogue (AGRICOLA)

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  9. Article ; Online: State-of-the-art computer vision techniques for automated sugarcane lodging classification

    Modi, Rajesh U. / Chandel, Abhilash K. / Chandel, Narendra S. / Dubey, Kumkum / Subeesh, A. / Singh, Akhilesh K. / Jat, Dilip / Kancheti, Mrunalini

    Field Crops Research. 2023 Feb., v. 291 p.108797-

    2023  

    Abstract: Sugarcane crop lodging is an agronomic condition that critically affects the cane yield and sugar quality. Lodging also impedes intercultural management and harvest operations. Currently, no approaches known exist to non-invasively assess sugarcane ... ...

    Abstract Sugarcane crop lodging is an agronomic condition that critically affects the cane yield and sugar quality. Lodging also impedes intercultural management and harvest operations. Currently, no approaches known exist to non-invasively assess sugarcane lodging. This study is therefore focused on expedited and autonomous sugarcane lodging detection using state-of-the-art computer vision techniques. Total 1600 digital red-green-blue (RGB) images of lodged and non-lodged sugarcane were acquired for two cultivars and two years (2020, and 2021) of growing seasons. These images were augmented to obtain a total of 6400 images. Based on tested proportions for minimum model overfittings, 80 % of the 6400 images were used for training, 10 % for validation, and remaining 10 % for testing of seven state-of-the-art deep learning (DL) models; ResNet50, GoogLeNet, DarkNet53, Inception V3, Xception, AlexNet, and MobileNetV2. When validated, amongst all, ResNet50 demonstrated the highest lodging prediction accuracy of 98.5 %, followed by GoogLeNet (98.0 %), DarkNet53 (97.6 %), InceptionV3 (97.6 %), Xception (97.1 %), AlexNet (96.5 %), and MobileNetV2 (93.6 %) and respective model precisions of 98.6 %, 98.6 %, 97.5 %, 97.2 %, 96.9 %, 96.1 %, and 93.1 %. Maximum accuracies and minimum model overfitting were observed for batch size of 16 and 30 epochs for all the models. The overall error rate for MobileNetV2, AlexNet, Xception, DarkNet53, InceptionV3, GoogLeNet, and ResNet50 models were 6.4 %, 3.5 %, 2.9 %, 2.4 %, 2.4 %, 2.0 % and 1.5 %, respectively. Best performing ResNet50 model was again tested on 50 independent images from real field conditions from both years and a net accuracy of 94 % was obtained. The residual blocks and skip connection features of ResNet50 help optimizing training parameters and therefore achieved better performance compared to other DL models. Autonomous lodging assessments with AI models could help guide supervised harvest operations without compromising the lodged crop, yield potentials, and site-specific management of other intercultural operations.
    Keywords automation ; computer vision ; cultivars ; models ; prediction ; research ; sugarcane ; sugars ; Lodging identification ; Deep learning ; Classification accuracy
    Language English
    Dates of publication 2023-02
    Publishing place Elsevier B.V.
    Document type Article ; Online
    ZDB-ID 435684-6
    ISSN 1872-6852 ; 0378-4290
    ISSN (online) 1872-6852
    ISSN 0378-4290
    DOI 10.1016/j.fcr.2022.108797
    Database NAL-Catalogue (AGRICOLA)

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  10. Article: Mycosynthesis of highly fluorescent selenium nanoparticles from

    Islam, Sk Najrul / Naqvi, Syed Mohd Adnan / Raza, Azam / Jaiswal, Amit / Singh, Akhilesh K / Dixit, Manish / Barnwal, Atul / Gambhir, Sanjay / Ahmad, Absar

    3 Biotech

    2022  Volume 12, Issue 11, Page(s) 309

    Abstract: In the past few years, photo-luminescent inorganic materials have been studied extensively as fluorescent sensors, and diagnostic and bioimaging tools. The assessment of photoluminescence (PL) properties of selenium nanoparticles (Se NPs), especially ... ...

    Abstract In the past few years, photo-luminescent inorganic materials have been studied extensively as fluorescent sensors, and diagnostic and bioimaging tools. The assessment of photoluminescence (PL) properties of selenium nanoparticles (Se NPs), especially mycosynthesized Se NPs, is still in its infancy. Herein, we have biosynthesized highly dispersed fluorescent Se NPs (42 nm) using endophytic fungus
    Language English
    Publishing date 2022-10-05
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2600522-0
    ISSN 2190-5738 ; 2190-572X
    ISSN (online) 2190-5738
    ISSN 2190-572X
    DOI 10.1007/s13205-022-03383-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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