Impact of COVID-19 on cancer care in India: a cohort study.

BACKGROUND: The COVID-19 pandemic has disrupted health-care systems, leading to concerns about its subsequent impact on non-COVID disease conditions. The diagnosis and management of cancer is time sensitive and is likely to be substantially affected by these disruptions. We aimed to assess the impact of the COVID-19 pandemic on cancer care in India. METHODS: We did an ambidirectional cohort study at 41 cancer centres across India that were members of the National Cancer Grid of India to compare provision of oncology services between March 1 and May 31, 2020, with the same time period in 2019. We collected data on new patient registrations, number of patients visiting outpatient clinics, hospital admissions, day care admissions for chemotherapy, minor and major surgeries, patients accessing radiotherapy, diagnostic tests done (pathology reports, CT scans, MRI scans), and palliative care referrals. We also obtained estimates from participating centres on cancer screening, research, and educational activities (teaching of postgraduate students and trainees). We calculated proportional reductions in the provision of oncology services in 2020, compared with 2019. FINDINGS: Between March 1 and May 31, 2020, the number of new patients registered decreased from 112 270 to 51 760 (54% reduction), patients who had follow-up visits decreased from 634 745 to 340 984 (46% reduction), hospital admissions decreased from 88 801 to 56 885 (36% reduction), outpatient chemotherapy decreased from 173634 to 109 107 (37% reduction), the number of major surgeries decreased from 17 120 to 8677 (49% reduction), minor surgeries from 18 004 to 8630 (52% reduction), patients accessing radiotherapy from 51 142 to 39 365 (23% reduction), pathological diagnostic tests from 398 373 to 246 616 (38% reduction), number of radiological diagnostic tests from 93 449 to 53 560 (43% reduction), and palliative care referrals from 19 474 to 13 890 (29% reduction). These reductions were even more marked between April and May, 2020. Cancer screening was stopped completely or was functioning at less than 25% of usual capacity at more than 70% of centres during these months. Reductions in the provision of oncology services were higher for centres in tier 1 cities (larger cities) than tier 2 and 3 cities (smaller cities). INTERPRETATION: The COVID-19 pandemic has had considerable impact on the delivery of oncology services in India. The long-term impact of cessation of cancer screening and delayed hospital visits on cancer stage migration and outcomes are likely to be substantial. FUNDING: None. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.

EduNet: A New Video Dataset for Understanding Human Activity in the Classroom Environment.

Human action recognition in videos has become a popular research area in artificial intelligence (AI) technology. In the past few years, this research has accelerated in areas such as sports, daily activities, kitchen activities, etc., due to developments in the benchmarks proposed for human action recognition datasets in these areas. However, there is little research in the benchmarking datasets for human activity recognition in educational environments. Therefore, we developed a dataset of teacher and student activities to expand the research in the education domain. This paper proposes a new dataset, called EduNet, for a novel approach towards developing human action recognition datasets in classroom environments. EduNet has 20 action classes, containing around 7851 manually annotated clips extracted from YouTube videos, and recorded in an actual classroom environment. Each action category has a minimum of 200 clips, and the total duration is approximately 12 h. To the best of our knowledge, EduNet is the first dataset specially prepared for classroom monitoring for both teacher and student activities. It is also a challenging dataset of actions as it has many clips (and due to the unconstrained nature of the clips). We compared the performance of the EduNet dataset with benchmark video datasets UCF101 and HMDB51 on a standard I3D-ResNet-50 model, which resulted in 72.3% accuracy. The development of a new benchmark dataset for the education domain will benefit future research concerning classroom monitoring systems. The EduNet dataset is a collection of classroom activities from 1 to 12 standard schools.

Surface Interaction of Ionic Liquids: Stabilization of Polyethylene Terephthalate-Degrading Enzymes in Solution.

The effect of aqueous solutions of selected ionic liquids solutions on Ideonella sakaiensis PETase with bis(2-hydroxyethyl) terephthalate (BHET) substrate were studied by means of molecular dynamics simulations in order to identify the possible effect of ionic liquids on the structure and dynamics of enzymatic Polyethylene terephthalate (PET) hydrolysis. The use of specific ionic liquids can potentially enhance the enzymatic hydrolyses of PET where these ionic liquids are known to partially dissolve PET. The aqueous solution of cholinium phosphate were found to have the smallest effect of the structure of PETase, and its interaction with (BHET) as substrate was comparable to that with the pure water. Thus, the cholinium phosphate was identified as possible candidate as ionic liquid co-solvent to study the enzymatic hydrolyses of PET.

The CH-π Interaction in Protein-Carbohydrate Binding: Bioinformatics and In Vitro Quantification.

The molecular recognition of carbohydrates by proteins plays a key role in many biological processes including immune response, pathogen entry into a cell, and cell-cell adhesion (e.g., in cancer metastasis). Carbohydrates interact with proteins mainly through hydrogen bonding, metal-ion-mediated interaction, and non-polar dispersion interactions. The role of dispersion-driven CH-π interactions (stacking) in protein-carbohydrate recognition has been underestimated for a long time considering the polar interactions to be the main forces for saccharide interactions. However, over the last few years it turns out that non-polar interactions are equally important. In this study, we analyzed the CH-π interactions employing bioinformatics (data mining, structural analysis), several experimental (isothermal titration calorimetry (ITC), X-ray crystallography), and computational techniques. The Protein Data Bank (PDB) has been used as a source of structural data. The PDB contains over 12 000 protein complexes with carbohydrates. Stacking interactions are very frequently present in such complexes (about 39 % of identified structures). The calculations and the ITC measurement results suggest that the CH-π stacking contribution to the overall binding energy ranges from 4 up to 8 kcal mol-1 . All the results show that the stacking CH-π interactions in protein-carbohydrate complexes can be considered to be a driving force of the binding in such complexes.

Biosensor-based diagnostic approaches for various cellular biomarkers of breast cancer: A comprehensive review.

Breast cancer is the most commonly occurring cancer among women which leads to thousands of deaths worldwide. The chances of survival are more if the breast cancer is diagnosed at early stage. At present, mammography, magnetic resonance imaging, ultrasound and tissue biopsies are the main diagnostic techniques available for the detection of breast cancer. However, despite of offering promising results, requirement of expensive setup, skilled supervision, expert analysis, invasive procedure (biopsy) and low capacity of multiplexing are the main limitations of these diagnostic techniques. Due to high cost, these screening tests are out of reach of people belonging to low socioeconomic groups and this poses serious health burden to the society. Recently, biosensor-based diagnostic technology for early detection of various types of cancers and other non-oncological disorders have gained considerable attention because of their several advantageous features over existing diagnostic technologies such as high throughput, noninvasive nature, cost effectiveness, easy interpretable results and capacity for multiplexing. Further, biosensors can be designed for biomarkers which are confined to particular type of cancer. In this review, we have discussed about various genomic, transcriptomic, proteomic and metabolomic biomarkers associated with breast cancer, various biosensors-based diagnostic approaches designed for detection of specific biomarkers associated with breast cancer are also described. Further, this review throws insight on various biomarkers linked with breast cancer which can be effectively exploited to develop new diagnostic technology. The assessment of these biomarkers associated with BC using biosensors in large population are cost-effective, non-invasive and high throughput. They help in risk assessment of disease at very initial stage even in backward areas and also help to lower the disease burden of society and economic cost of treatment for a common man. This review would provide new avenues for the development of biosensor based diagnostic technology for the detection of biomarkers associated with breast cancer.

Gastric Cancer With Peritoneal Metastasis-A Comprehensive Review of Current Intraperitoneal Treatment Modalities.

The treatment of patients with peritoneal metastasis from gastric cancer continues to evolve. With various forms of intraperitoneal drug delivery available, it is now possible to reach the sites of peritoneal metastases, which were otherwise sub-optimally covered by systemic chemotherapy, owing to the blood peritoneal barrier. We conducted a narrative review based on an extensive literature research, highlighting the current available intraperitoneal treatment options, which resulted in improved survival in well-selected patients of peritoneally metastasized gastric cancer. Intraperitoneal chemotherapy showed promising results in four different treatment modalities: prophylactic, neoadjuvant, adjuvant, and palliative. It is now possible to choose the type of intraperitoneal treatment/s in combination with systemic treatment/s, depending on patients' general condition and peritoneal disease burden, thus providing individualized treatment to these patients. Randomized controlled trials for the different treatment modalities were mainly conducted in Asia and lack further validation in the other parts of the world. Most recent application tools, such as pressurized intraperitoneal aerosol chemotherapy, seem promising and need to pass the ongoing clinical trials.

Closing the Cancer Care Gap in India.

Cancer burden in India is increasing. Cancer treatment today is multi-disciplinary requiring the coordination of many specialists for best outcomes. Bringing such expertise together to the district level is the greatest challenge for cancer care in any country, moreover in India. This article focuses on the step-wise journey to make comprehensive cancer care center in a small city.

Green conversion of hazardous red mud into diagnostic X-ray shielding tiles.

Red mud is a solid hazardous alumina industrial waste, which is rich in iron, titanium, aluminum, silicon, calcium, etc. The red mud contains 30-60% of hematite, which is suitable for shielding high energy X- and gamma rays. So, the iron rich red mud was converted into diagnostic X-ray shielding tiles through ceramic route by adding a certain weight percentage of BaSO4 and binders (kaolin clay or sodium hexametaphosphate) with it. The kaolin clay tile possess sufficient impact strength (failure point is 852 mm for 19 mm steel ball) and flexural strength of ~25 N/mm2, which is suitable for wall applications. The 10.3 mm and 14.7 mm thick red mud:BaSO4:kaolin clay tile possess the attenuation equivalent to 2 mm and 2.3 mm lead at 125 kVp and 140 kVp, respectively. No heavy elements were found to leach out except chromium and arsenic from the sintered tiles. However, the leaching of Cr (0.6 ppm) and As (0.015 ppm) was found to be well below the permissible limit. These tiles can be used in the X-ray diagnosis, CT scanner, bone densitometry, and cath labs instead of toxic lead sheet and thereby to protect the operating personnel, public, and environment from radiation hazards.

Recent advances in copper and copper-derived materials for antimicrobial resistance and infection control.

Antibacterial properties of copper have been known for ages. With the rise of antimicrobial resistance (AMR), hospital-acquired infections, and the current SARS-CoV-2 pandemic, copper and copper-derived materials are being widely researched for healthcare ranging from therapeutics to advanced wound dressing to medical devices. We cover current research that highlights the potential uses of metallic and ionic copper, copper alloys, copper nanostructures, and copper composites as antibacterial, antifungal, and antiviral agents, including those against the SARS-CoV-2 virus. The applications of copper-enabled engineered materials in medical devices, wound dressings, personal protective equipment, and self-cleaning surfaces are discussed. We emphasize the potential of copper and copper-derived materials in combating AMR and efficiently reducing infections in clinical settings.

A Computationally Efficient Method for Hybrid EEG-fNIRS BCI Based on the Pearson Correlation.

A hybrid brain computer interface (BCI) system considered here is a combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). EEG-fNIRS signals are simultaneously recorded to achieve high motor imagery task classification. This integration helps to achieve better system performance, but at the cost of an increase in system complexity and computational time. In hybrid BCI studies, channel selection is recognized as the key element that directly affects the system's performance. In this paper, we propose a novel channel selection approach using the Pearson product-moment correlation coefficient, where only highly correlated channels are selected from each hemisphere. Then, four different statistical features are extracted, and their different combinations are used for the classification through KNN and Tree classifiers. As far as we know, there is no report available that explored the Pearson product-moment correlation coefficient for hybrid EEG-fNIRS BCI channel selection. The results demonstrate that our hybrid system significantly reduces computational burden while achieving a classification accuracy with high reliability comparable to the existing literature.

Blockage of Store-Operated Ca2+ Influx by Synta66 is Mediated by Direct Inhibition of the Ca2+ Selective Orai1 Pore.

The Ca2+ sensor STIM1 and the Ca2+ channel Orai1 that form the store-operated Ca2+ (SOC) channel complex are key targets for drug development. Selective SOC inhibitors are currently undergoing clinical evaluation for the treatment of auto-immune and inflammatory responses and are also deemed promising anti-neoplastic agents since SOC channels are linked with enhanced cancer cell progression. Here, we describe an investigation of the site of binding of the selective inhibitor Synta66 to the SOC channel Orai1 using docking and molecular dynamics simulations, and live cell recordings. Synta66 binding was localized to the extracellular site close to the transmembrane (TM)1 and TM3 helices and the extracellular loop segments, which, importantly, are adjacent to the Orai1-selectivity filter. Synta66-sensitivity of the Orai1 pore was, in fact, diminished by both Orai1 mutations affecting Ca2+ selectivity and permeation of Na+ in the absence of Ca2+. Synta66 also efficiently blocked SOC in three glioblastoma cell lines but failed to interfere with cell viability, division and migration. These experiments provide new structural and functional insights into selective drug inhibition of the Orai1 Ca2+ channel by a high-affinity pore blocker.

Breast cancer risk associated with polymorphisms of IL-1RN and IL-4 gene in Indian women.

Interleukins and cytokines are important regulator of the aetio-pathogenesis of the majority of cancers. Mechanistic role of IL-1RN and IL-4, particularly in breast carcinogenesis, is well documented. However, the role of polymorphisms of IL-1RN and IL-4 combinations associated with risk of breast cancer is not reported. The IL-1RN and IL-4 gene polymorphisms were genotyped with VNTR-PCR in 100 patients (benign tumor n = 32 and breast cancer n = 68) and 200 normal healthy control subjects with normal mammogram. Genotype distribution and allelic frequencies between patients and controls were compared and odds ratios (OR) with 95% confidence intervals (CI) were calculated using SPSS software (version 12.0). There were no significant differences in the genotype distributions of both IL-1RN and IL-4 polymorphisms between cases and controls. Similarly, subgroup analysis showed that there is no significant association for pre- and postmenopausal women. However, BB genotype of IL-1RN significantly differs among benign and malignant stages of breast cancer. IL-1RN and IL-4 polymorphisms alone or in combination are not associated with risk of breast cancer in Indian patients. The association of IL-1RN with malignant stages may indicate its possible role in progression of breast cancer. Further studies in other population are needed to confirm our findings and to elucidate the role of IL-1RN in progression of breast cancer.

Genome-Wide Transcriptomic Analysis Reveals Insights into the Response to Citrus bark cracking viroid (CBCVd) in Hop (Humulus lupulus L.).

Viroids are smallest known pathogen that consist of non-capsidated, single-stranded non-coding RNA replicons and they exploits host factors for their replication and propagation. The severe stunting disease caused by Citrus bark cracking viroid (CBCVd) is a serious threat, which spreads rapidly within hop gardens. In this study, we employed comprehensive transcriptome analyses to dissect host-viroid interactions and identify gene expression changes that are associated with disease development in hop. Our analysis revealed that CBCVd-infection resulted in the massive modulation of activity of over 2000 genes. Expression of genes associated with plant immune responses (protein kinase and mitogen-activated protein kinase), hypersensitive responses, phytohormone signaling pathways, photosynthesis, pigment metabolism, protein metabolism, sugar metabolism, and modification, and others were altered, which could be attributed to systemic symptom development upon CBCVd-infection in hop. In addition, genes encoding RNA-dependent RNA polymerase, pathogenesis-related protein, chitinase, as well as those related to basal defense responses were up-regulated. The expression levels of several genes identified from RNA sequencing analysis were confirmed by qRT-PCR. Our systematic comprehensive CBCVd-responsive transcriptome analysis provides a better understanding and insights into complex viroid-hop plant interaction. This information will assist further in the development of future measures for the prevention of CBCVd spread in hop fields.

Influence of Trp flipping on carbohydrate binding in lectins. An example on Aleuria aurantia lectin AAL.

Protein-carbohydrate interactions are very often mediated by the stacking CH-π interactions involving the side chains of aromatic amino acids such as tryptophan (Trp), tyrosine (Tyr) or phenylalanine (Phe). Especially suitable for stacking is the Trp residue. Analysis of the PDB database shows Trp stacking for 265 carbohydrate or carbohydrate like ligands in 5 208 Trp containing motives. An appropriate model system to study such an interaction is the AAL lectin family where the stacking interactions play a crucial role and are thought to be a driving force for carbohydrate binding. In this study we present data showing a novel finding in the stacking interaction of the AAL Trp side chain with the carbohydrate. High resolution X-ray structure of the AAL lectin from Aleuria aurantia with α-methyl-l-fucoside ligand shows two possible Trp side chain conformations with the same occupation in electron density. The in silico data shows that the conformation of the Trp side chain does not influence the interaction energy despite the fact that each conformation creates interactions with different carbohydrate CH groups. Moreover, the PDB data search shows that the conformations are almost equally distributed across all Trp-carbohydrate complexes, which would suggest no substantial preference for one conformation over another.

Utility of fine-needle aspiration cytology in the identification of parathyroid lesions.

OBJECTIVES: Fine-needle aspiration cytology (FNAC) is a first-line investigation in the evaluation of neck nodules. In an attempt to search for reliable cytomorphological criteria for parathyroid lesions, we systematically evaluated cytomorphology of FNAC of parathyroid lesions. STUDY DESIGN: FNAC of 15 parathyroid and 15 hyperplastic thyroid nodules with histological confirmation were reviewed for following features: Cellularity, follicles, bare nuclei, cohesiveness, vascular profiles, cytoplasmic granularity, intracytoplasmic vacuolation, mitosis, macrophages, and colloid. RESULTS: Vascular proliferation, bare nuclei, intracytoplasmic fat vacuolation, absence of colloid, and high cellularity showed significant association with parathyroid lesions (P ≤ 0.05). Intracytoplasmic fat vacuolation was 53.3% sensitive and 100% specific for parathyroid. Follicular pattern and papillaroid clusters were also important; however, they achieved nearly significant statistical difference (P = 0.05 and P = 0.06, respectively). The combination of vascular proliferation and intracytoplasmic fat vacuolation were significantly associated with parathyroid (P = 0.006) whereas the absence of bare nuclei and the presence of background colloid were associated with thyroid cytomorphology (P = 0.03). CONCLUSION: No single cytological feature is helpful in differentiating parathyroid from thyroid lesion. Vascular proliferation, bare nuclei, intracytoplasmic fat vacuolation, high cellularity, and the absence of colloid were significantly associated with the parathyroid origin. The combination of at least two features - vascular proliferation and intracytoplasmic fat vacuoles - were highly suggestive of parathyroid origin.

Impact of psychological distress due to COVID-19 pandemic on spouse interpersonal relationships

Background: The novel virus, COVID-19, has proven to be a stressor on many levels due to factors like health, economic disruptions, lockdown, and stay-at-home orders. However, one of the significant stressors has been on relationships, primarily the intimate ones, like between spouses. To investigate the correlation between psychological distress and quality of spouse interpersonal relationships. Methodology: The mixed research design (i.e., qualitative and quantitative methods) was employed on 119 participants between 22-62 years of age, followed by a semi-structural interview of 12 participants, all through virtual snowball mode due to the COVID-19 scenario. Socio-demographic profile, psychological distress scale, and the quality of spouse interpersonal relationships scale and a semi-structural interview schedule were used for data collection. Results: The present study shows that psychological distress is negatively correlated with certain aspects like conflict, criticism, resentment, pressure, dominance, relative power, and exclusion of the quality of spouse interpersonal relationships. On the other hand, a positive correlation was observed with affection, emotional support, reliable alliance, satisfaction, companionship, and approval aspects of the quality of spouse interpersonal relationships. Qualitative results shows that argument with each other, disagreement, point out faults, pressurization for intimation, and violence with partner are some of the most prominent negative effects in their present life while developed understanding to each other, sense of trust, feel good, received love and affection, care for each other, emotional support, help in other household errands, and take care of children and parents are some of the positive aspects seen instead of the psychological distress perceived during this pandemic. Conclusions: COVID-19 has had considerable effects on spousal interpersonal relationships and needs further study

Helical folding in heterogeneous foldamers without inter-residual backbone hydrogen-bonding.

This communication describes a set of hybrid foldamers that do not feature inter-residual, but intra-residual backbone hydrogen-bonding, yet adopt a preferentially folded conformation displaying right-handed helical architecture. Conformational ordering is apparently due to the combined conformational restrictions imposed by the conformationally restricted individual amino acid residues with which the oligomers are made of.