Authentication of Tinospora cordifolia derived herbal supplements using high resolution mass spectrometry-based metabolomics approach – A pilot study

Tinospora cordifolia herbal supplements have recently gained prominence due to their promising immunomodulatory and anti-viral effects against SARS-CoV-2. Mislabelling or diluting Tinospora supplements for profit may harm public health. Thus, validating the label claim of these supplements in markets is critical. This study investigated how high resolution mass spectrometry-based metabolomics and chemometrics can be used to distinguish Tinospora cordifolia from two other closely related species (T. crispa and T. sinensis). The Orthogonal Partial Least Square Discriminant Analysis (OPLS-DA) and PLS-DA based chemometric models predicted the species identity of Tinospora with 94.44% accuracy. These classification models were trained using 54 T. cordifolia, 21 T. crispa, and 21 T. sinensis samples. We identified 7 biomarkers, including corydine, malabarolide, ecdysterone, and reticuline, which discriminated Tinospora cordifolia from the two other species. The label claim of 25 commercial Tinospora samples collected from different parts of India was verified based on the relative abundance of the biomarker compounds, of which 20 were found authentic. The relative abundance of biomarkers significantly varied in the 5 suspicious market samples. This pilot study demonstrates a robust metabolomic approach for authenticating Tinospora species, which can further be used in other herbal matrices for product authentication and securing quality. © 2023 Elsevier B.V.

Preface

International Conference on Geospatial Science for Digital Earth Observation (GSDEO 2021)The international conference on "Geospatial Science for Digital Earth Observation” (GSDEO) 2021 was successfully held on a virtual platform of Zoom on March 26th and 27th, 2021. The conference was jointly organized by the Indian Society of Remote Sensing (ISRS), Kolkata chapter, and the Department of Geography, School of Basic and Applied Sciences, Adamas University. Due to the non-predictable behaviour of the COVID-19 second wave, which imposed restrictions on organizing offline events, the GSDEO (2021) organizing committee decided to organize the conference online, instead of postponing the event.Remotely sensed data and geographic information systems have been increasingly used together for a vast range of applications, which include land use/land cover mapping, water resource management, weather forecasting, environmental monitoring, agriculture, disaster management, etc. Currently, intensive research is being carried out using remotely sensed data on the geoinformatics platform. New developments have led to dynamic advances in recent years. The objective of the international conference on Geospatial Science for Digital Earth Observation (GSDEO 2021) was to bring the scientists, academicians, and researchers, in the field of geo-environmental sciences on a common platform to exchange ideas and their recent findings related to the latest advances and applications of geospatial science. The call for papers received an enthusiastic response from the academic community, and over 100+ participants from 50+ colleges, universities, and institutions participated in the conference. In total 50+ research papers had been presented through the virtual Zoom conference platform in GSDEO 2021.The conference witnessed the presentation of research papers from diverse applied fields of geospatial sciences, which include the application of geoinformatics in geomorphology, hydrology, urban science, land use planning, climate, and environmental studies. There were four sessions namely, TS 1: Geomorphology and Hydrology, TS 2: Urban Science, TS 3: Social Sustainability and Land Use Planning, and TS 4: Climate and Environment. Each session was further subdivided, into two parts, namely Technical Session 1-A and 1-B. Each sub-session had been designed with one keynote speech and 5 oral presentations. Oral sessions were organized in two parts and offered through live and pre-recorded components based on the preference of the presenters. The presentation session was followed by a live Q&A session. The session chairs moderated the discussions. Similarly, poster sessions were organized in three parts and offered e-poster, live, and pre-recorded components. The best presenter of each sub-session received the best paper award.Dr. Prithvish Nag, Ex-Director of NATMO & Ex Surveyor General of India delivered the inaugural speech, and Dr. P. Chakrabarti, Former Chief Scientist of the DST&B, Govt. of West Bengal delivered a special lecture after the inaugural session. Eight eminent keynote speakers, Prof. S.P. Agarwal from the Indian Institute of Remote Sensing, Prof. Ashis Kumar Paul from Vidyasagar University, Prof. Soumya Kanti Ghosh from the Indian Institute of Technology, Kharagpur, Prof. L. N. Satpati from the University of Calcutta, Prof. R.B. Singh from the University of Delhi, Dr. A.K. Raha, IFS (Retd), Prof. Gerald Mills from the University College Dublin and Prof. Sugata Hazra from Jadavpur University enriched the knowledge of participants in the field of geoinformatics by their informative lectures. The presentations and discussions widely covered the various spectrums of geoinformatics and its application in monitoring natural resources like vegetation mapping, agricultural resource monitoring, forest health assessment, water, and ocean resource management, disaster management, land resource management, water and climate studies, drought vulnerability assessment, groundwater quality monitoring, accretion mapping and the use of geospatial sci nce in studying morphological, hydrological, and other biophysical characteristics of a region etc. Application of geoinformatics in predicting urban expansion, urban climate, disaster management, healthcare accessibility, anthropogenic resource monitoring, spatial-interaction mapping, and, sustainable regional planning were well-discussed topics of the conference.List of Committees, photos are available in the pdf.

Late acceptance hill climbing aided chaotic harmony search for feature selection: An empirical analysis on medical data

In today's era of data-driven digital society, there is a huge demand for optimized solutions that essentially reduce the cost of operation, thereby aiming to increase productivity. Processing a huge amount of data, like the Microarray based gene expression data, using machine learning and data mining algorithms has certain limitations in terms of memory and time requirements. This would be more concerning, when a dataset comes with redundant and non-important information. For example, many report-based medical datasets have several non-informative attributes which mislead the classification algorithms. To this end, researchers have been developing several feature selection algorithms that try to discard the redundant information from the raw datasets before feeding them to machine learning algorithms. Metaheuristic based optimization algorithms provide an excellent option to solve feature selection problems. In this paper, we propose a music-inspired harmony search (HS) algorithm based wrapper feature selection method. At the beginning, we use a chaotic mapping to initialize the population of the HS algorithm in order to better coverage of the search space. Further to complement the inferior exploitation of the HS algorithm, we integrate it with the Late Acceptance Hill Climbing (LAHC) method. Thus the combination of these two algorithms provides a good balance between the exploration and exploitation of the HS algorithm. We evaluate the proposed feature selection method on 15 UCI datasets and the obtained results are found to be better than many state-of-the-art methods both in terms of the classification accuracy and the number of features selected. To evaluate the effectiveness of our algorithm, we utilize a combination of precision, recall, F1 score, fitness value, and execution time as performance indicators. These metrics enable us to obtain a comprehensive assessment of the algorithm's abilities and limitations. We also apply our method on 3 microarray based gene expression datasets used for prediction of cancer to ensure the scalability and robustness as a feature selection method in real-life scenarios. In addition to this, we test our approach using the COVID-19 dataset, and it performs better than several metaheuristic based optimization techniques. © 2023

Organ preservation and total neoadjuvant therapy for rectal cancer: Investigating longcourse chemoradiation versus short-course radiation therapy

Background: Interest in organ preservation (OP) strategies for rectal cancer (RC) patients persists. The efficacy of long course chemoradiation (LCRT) vs. short course radiation therapy (SCRT) relative to OP is unknown. We compared OP rates between SCRT and LCRT total neoadjuvant therapy (TNT) strategies. Method(s): During the COVID-19 pandemic we established an institutional SCRT mandate with no exceptions. For comparison, we identified RC patients treated with LCRT immediately before and after the mandate period. After completion of TNT, patients were restaged by clinical exam, endoscopy, and MRI. A watch and wait (WW) approach was recommended for patients with a clinical complete response (cCR), defined by the MSK regression schema. Total mesorectal excision (TME) was recommended for non-cCR patients. OP was defined as alive, TME-free, and with no evidence of disease in the pelvis. We performed survival analysis for: local regrowth rate, OP, disease-free survival (DFS), and overall survival (OS). Result(s): We identified 563 consecutive patients with RC treated with TNT, of whom 231 were excluded due to either metastatic disease, synchronous/metachronous malignancies, or non-adenocarcinoma histology (Jan. 2018-Jan. 2021). Patient and tumor characteristics were similar in the LCRT (n = 256) and SCRT (n = 76) cohorts. No significant differences in high-risk features were noted. Most patients had clinical stage III disease (82% in LCRT vs. 83% in SCRT). Induction chemotherapy followed by consolidative radiation was the most common treatment order (78% (LCRT) vs. 70% (SCRT)). The median interval from end of TNT to clinical restaging was 8 weeks (LCRT) and 9 weeks (SCRT). The cCR rate was 46% in both cohorts. The cCR rate was numerically higher in patients treated with radiation first, as compared to chemotherapy first (53% vs. 44% (LCRT) and 52% vs. 43% (SCRT)). Among patients with a cCR, the likelihood of WW management was similar (98% (LCRT) vs. 94% (SCRT)). From start of TNT, the median follow-up was 32 and 28 months respectively for LCRT and SCRT. The 2-year OS (95% vs. 92%), DFS (78% vs 70%), and distant recurrence (20% vs. 21%) rates were similar. Among all patients, the 2-year OP rate was 40% (95% CI 35-47%) for LCRT and 29% (95% CI 20-42%) with SCRT. In those patients managed by WW, the 2-year local regrowth rate was 20% (95% CI 12-27%) with LCRT vs. 36% (95% CI 16-52%) with SCRT. Conclusion(s): In this nonrandomized comparison, while cCR rates were similar, we observed a numerically higher OP rate with LCRT-TNT than with SCRT-TNT. The ongoing ACO/ARO/AIO-18.1 trial, hypothesizing that LCRT-TNT will increase OP rates relative to SCRT-TNT, should definitively answer this question.

Deep learning methods for scientific and industrial research

Deep learning (DL) is a very powerful computational tool for various applications in scientific and industrial research which can be real-time implemented for societal benefits. Several factors impact the development of optimized DL models for better prediction including the amount of quality sample data, domain-specific knowledge, and the architecture of the model for extraction of the useful features/patterns from the data. The present chapter demonstrates the state-of-the-art DL methodologies used by the researchers from different laboratories under the Council of Scientific and Industrial Research (CSIR), India to solve important research activities across several sectors like Medical, Healthcare, Agriculture, Energy, etc. The Convolutional Neural Network (CNN) techniques are utilized for Tumor diagnosis, classifying molecular subtypes of glioma tissues, and predicting driver gene mutations in glioma. Similarly, the Long short-term memory (LSTM) model is applied for the assessment of crop production, and transfer learning is used for the classification of tea leaves. Further, the ensemble LSTM methodology is implemented for short-term prediction of wind speed to enhance the renewable energy sectors. Finally, the multivariate LSTM models were developed by integrating the weather parameters for the prediction of covid-19 spread over different states in India which is an input for policy planning and supply chain management during the pandemic time. All the use cases are being validated and the results are quite satisfying and provide confidence for the real-time application of DL for scientific and industrial research and societal benefit to the common people. © 2023 Elsevier B.V.

GREEN OR BROWN: Global environment in the post-COVIDian era, and challenges for India

The Covid-19 pandemic was a wakeup call for policy makers around the world to revisit their obsession with economic growth and prioritise social welfare. Climate change will soon throw up similar challenges. Policy makers need to be prepared to start addressing the twin challenges of public and ecological health in an integrated matter. After drawing parallels between the current Covid-19 crisis and the ongoing climate change crisis, we discuss their interrelationship. We then assess the impact of Covid-19 on the environment, with a focus on India. The series of lockdowns that ensued as a response to the Covid-19 crisis affected business adversely, and we discuss how firms could react to the “new normal” that has emerged, in the context of the ecological environment. The impact of economic stimulus packages on the ecological health of the planet, and more specifically on the progress towards meeting commitments made by nations towards climate change is examined next. We conclude with a few pointers on policy directions that could promote green economic growth for a sustainable future with lower risks of pandemics. © 2022 selection and editorial matter, Rajib Bhattacharyya, Ananya Ghosh Dastidar and Soumyen Sikdar;individual chapters, the contributors.

Laboratory diagnostics in COVID-19

Multiple laboratory parameters have been Mproposed for use in the diagnosis and prognosis in COVID-19. They are useful as prognostic factors, in choosing certain therapeutic agents and in determining trophism of the disease in particular organ systems or particular inflammatory syndrome like secondary hemophagocytic lymphohistiocytosis (S-HLH). ?ISARIC 4C? score, using 8 variables, including 2 laboratory markers (CRP and urea) is used in predicting disease outcome. However, to capture nuances in disease behaviour, wider biomarker assessment is required. Ddimer, Lactate dehydrogenase, Ferritin all represented disease severity. Procalcitonin can differentiate bacterial infection from inflammation. Troponin has been associated with mortality in patients with and without underlying coronary artery disease. This is also associated with myocarditis. IL-6 and CRP (cutoff>75mg/dL in RECOVERY trial) has been used in selecting patients for Tocilizumab. Ferritin has been shown to predict Methyl Prednisolone response and in identifying S-HLH. Neutrophil:Lymphocytic ratio and Red Cell Distribution Width (RDW) trajectory have been shown to be useful predictor of disease outcome. Circulatory histone has been shown to play important role in COVID-associated coagulopathy and mortality. In ISARIC study, multiple markers (GM-CSF, CCL-4, CXCL 10 )have been shown to have role in prognostication. Genomic study showed strong genetic predisposition towards mortality in critically ill patients, suggesting accurate prognostication is impossible without genetic data. Given that multiple laboratory parameters have role in COVID-19 in variable degree, there is a need for a holistic view of the patients, keeping in mind their demographic and physiological factors and also the subtle interplay between different laboratory features.

Functional Outcome of Conservative Management of Displaced Midshaft Clavicle Fracture: It’s Significance During Covid-19 Pandemic

Background: With increasing popularity of surgical interventions in the past few decades in the field of Orthopaedics, conservative treatment methods were challenged by surgical techniques of fracture fixation with various implants. However, due to the COVID-19 pandemic, the need for pragmatic management that balances optimum treatment of patients against clinically safe practice has brought conservative treatment methods back into focus. Methods: The functional outcome of displaced mid-shaft clavicle fracture in 20 patients (6 females, 14 males) managed conservatively with figure of eight bandage was studied prospectively over a period of 9 months from March-November 2020. The demographic and the clinical data including the Constant Murley Score, length of shortening of the fractured clavicle, non-union and cosmetic outcome of the patients were recorded over 3 follow up visits at 2 weeks, 6 weeks and 3 months. The correlation between the study variables and the functional and clinical outcome was then calculated. Results: The mean shortening of fractured clavicle was 15.65±2.94 mm and the mean Constant Murley Score was 76.90±3.27. On an average, the union was achieved at 3 months and there were no non-union cases. Out of the 20 patients, 18 patients were satisfied with the treatment and 2 were dissatisfied with the outcome. Dissatisfaction was more among the males as compared to the females. 2 out of14 males were not satisfied. There was no significant association between the satisfaction of treatment and shortening of the bone (P value >0.05). There was a linear correlation between the Constant Murley Score and bone shortening with the functional outcome being better with lesser bone shortening. Conclusion: During the treatment of displaced mid shaft clavicle fractures in adults, the conservative management with figure of eight bandage yielded a good functional outcome with fewer follow-up visits to the hospital. The conservative treatment still had a significant place in the armamentarium of fracture management during the COVID 19 pandemic.

Empathy and Hope: Resource Transfer to Model Inter-country Social Media Dynamics

The ongoing COVID-19 pandemic resulted in significant ramifications for international relations ranging from travel restrictions, global ceasefires, and international vaccine production and sharing agreements. Amidst a wave of infections in India that resulted in a systemic breakdown of healthcare infrastructure, a social welfare organization based in Pakistan offered to procure medical-grade oxygen to assist India - a nation which was involved in four wars with Pakistan in the past few decades. In this paper, we focus on Pakistani Twitter users' response to the ongoing healthcare crisis in India. While #IndiaNeedsOxygen and #PakistanStandsWithIndia featured among the toptrending hashtags in Pakistan, divisive hashtags such as #EndiaSaySorryToKashmir simultaneously started trending. Against the back-drop of a contentious history including four wars, divisive content of this nature, especially when a country is facing an unprecedented healthcare crisis, fuels further deterioration of relations. In this paper, we define a new task of detecting supportive content and demonstrate that existing NLP for social impact tools can be effectively harnessed for such tasks within a quick turnaround time. We also release the first publicly available data set(1) at the intersection of geopolitical relations and a raging pandemic in the context of India and Pakistan.

Feasibility of Organ Preservation With Short Course Radiation Therapy as Part of Total Neoadjuvant Therapy in Locally Advanced Rectal Cancer During the COVID-19 Pandemic

Purpose/Objective(s): While long course chemoradiation therapy has been studied as part of a watch-and-wait (WW) strategy for patients with locally advanced rectal cancer, it is unclear whether short-course radiation therapy (SCRT) will be associated with similar rates of organ preservation. We hypothesized that a WW strategy to facilitate organ preservation with SCRT, as part of a total neoadjuvant therapy (TNT) approach during the COVID-19 pandemic, would be both safe and feasible. Materials/Methods: From March to June of 2020, due to the COVID-19 pandemic, per institutional policy, all patients undergoing radiation therapy for locally advanced rectal cancer were treated with SCRT. After completion of SCRT-TNT, patients were clinically restaged by exam, endoscopy and MRI and the decision was made to manage the patient surgically or with a WW approach. The decision for WW or surgery was made by the surgeon in conjunction with patient consent. After IRB waiver was obtained, we reviewed consecutive patients treated during our SCRT mandate. The main outcome of interest was total mesorectal excision (TME)-free survival among patients eligible for WW after SCRT-TNT. Results: Our cohort included 42 patients with a median age of 57 years (Interquartile Range [IQR] 48-67), 24 (57%) of whom were male. Median follow-up from end of SCRT-TNT was 7 months (IQR 6-8). The median tumor cranio-caudal size was 4.1 cm (IQR 3.3-5.2) with a median distance from the anal verge of 7 cm (IQR 5-9). The majority had cT3 (71%) or cN+ (74%) disease. Patients underwent a median of 14 weeks (IQR 13-15) of FOLFOX or CAPEOX chemotherapy, with 32 (76%) patients receiving chemotherapy prior to SCRT and 10 (24%) patients receiving chemotherapy after SCRT. The median time from completion of TNT to endoscopic restaging was 9 weeks (IQR 7-10). Nineteen (45%) patients were recommended to undergo surgical resection, of whom 17 went on to TME and 2 refused TME. Of the 15 patients with pathology available, 2 had a pCR (13%). Notably, one of these patients had a cCR at post-TNT endoscopy, but due to the presence of a stricture, WW was deemed unfeasible. Of the 23 patients managed by a WW strategy after SCRT-TNT completion, 19 had a clinical complete response (cCR), 3 had a near-CR, and 1 had an incomplete response. The 6-month TME-free survival was 85% for patients on WW. Four (17%) patients had a local regrowth at a median of 20 weeks (IQR 17-24), 3 of whom were salvaged with TME and 1 who declined surgery and opted for further surveillance. One of these patients had regrowth confirmed by biopsy, but had a pCR confirmed in the TME specimen. The 6-month TME- free survival of the entire cohort was 52%, and the combined pCR/6-month cCR was 52%. Conclusion: Our data suggest WW after SCRT-TNT is feasible. Longer term follow-up is required to confirm the durability and oncologic safety of these results.

Immunoboosting Potential of Spices with Special Reference to North East India against the Novel Coronavirus Pandemic- A Review

Spices, which is key ingredient in every household products not only used for adding aroma to food but however, has health promoting and protective activity against foreign pathogens. Different spices used in day to day life boosts the immune system that leads to healthy and prosperous life. The commonly used spices not only have antimicrobial or antiviral activity, but also serve as a rich source of various vitamins, minerals, antioxidants etc. The medicinal importance of spices dates from ancient Ayurveda and many studies indicating the potential of spices as immunoboosting agent had been carried out in the recent years. Therefore, this review highlights the medicinal importance of commonly used spices in North-East India as immunobooster against the current coronavirus pandemic.