Spinal astroblastoma, MN1 altered in 3-year-old child: An uncommon tumor at an unusual site.

Astroblastoma is an uncommon circumscribed glial tumor mostly involving the cerebral hemisphere. The characteristic molecular alteration is meningioma (disrupted in balanced translocation) 1 (MN1) rearrangement. No definite World Health Organization grade has been assigned as both low- and high-grade tumors are known to occur. Tumors in the spine are extremely rare; to date only three cases have been reported in the literature. A vigilant microscopy and ancillary testing aid in diagnosis when the tumors present in unusual locations, as in our case. The prompt differentiation of this tumor from its mimickers is a mandate as modalities of management are different and not clearly established.

Accelerated inertial regime in the spinodal decomposition of magnetic fluids.

Furukawa predicted that at late times, the domain growth in binary fluids scales as (t) ∼ t2/3, and the growth is driven by fluid inertia. The inertial growth regime has been highly elusive in molecular dynamics (MD) simulations. We perform coarsening studies of the (d = 3) Stockmayer (SM) model comprising of magnetic dipoles that interact via long-range dipolar interactions as well as the usual Lennard-Jones (LJ) potential. This fascinating polar fluid exhibits a gas-liquid phase coexistence, and magnetic order even in the absence of an external field. From comprehensive MD simulations, we observe the inertial scaling [(t) ∼ t2/3] in the SM fluid for an extended time window. Intriguingly, the fluid inertia is overwhelming from the outset - our simulations do not show the early diffusive regime [(t) ∼ t1/3] and the intermediate viscous regime [(t) ∼ t] prevalent in LJ fluids.

Evaluation of Medical Certification of Cause of Death in Tertiary Cancer Hospitals in Northern India.

BACKGROUND: Medical certification of cause of death (MCCD) provides valuable data regarding disease burden in a community and for formulating health policy. Inaccurate MCCDs can significantly impair the precision of national health information. OBJECTIVE: To evaluate the accuracy of cause of death certificates prepared at two tertiary cancer care hospitals in Northern India during the study period (May 2018 to December 2020). METHOD: A retrospective observational study at two tertiary cancer care hospitals in Varanasi, India, over a period of two and a half years. Medical records and cause of death certificates of all decedents were examined. Demographic characteristics, administrative details and cause of death data were collected using the WHO recommended death certificates. Accuracy of death certification was validated by electronic medical records and errors were graded. RESULTS: A total of 778 deaths occurred in the two centres during the study period. Of these, only 30 (3.9%) certificates were error-free; 591 (75.9%) certificates had an inappropriate immediate cause of death; 231 (29.7%) certificates had incorrectly labelled modes of death as the immediate cause of death; and 585 (75.2%) certificates had an incorrect underlying cause of death. The majority of certificates were prepared by junior doctors and were significantly associated with higher certification errors. CONCLUSION: A high rate of errors was identified in death certification at the cancer care hospitals during the study period. Inaccurate MCCDs related to cancers can potentially influence cancer statistics and thereby affect policy making for cancer control. IMPLICATIONS: This study has identified the pressing need for appropriate interventions to improve quality of certification through training of doctors.

Machine learning-based approach for prediction of ion channels and their subclasses.

Ion channels are ion-permeable protein pores that are found in all cell lipid membranes. Distinct ion channels play multiple roles in biological processes. Proteomic data is fast accumulating as a result of the fast growth of mass spectrometry and giving us the chance to comprehensively explore ion channel classes along with their subclasses. This paper proposes an eXtreme Gradient Boosting (XGBoost)-based method to estimate the ion channel classes and their subclasses. Here, 12 feature vectors are applied to better characterize protein sequences like amino acid composition, pseudo-amino acid composition, normalized moreau-broto autocorrelation, amphiphilic pseudo-amino acid composition, dipeptide composition, Geary autocorrelation, tripeptide composition, sequence-order-coupling number, composition/transition/distribution, conjoint triad, moran autocorrelation, quasi-sequence-order descriptors. Here, a total of 9920 features are extracted from the protein sequence. The principal component analysis is applied to determine the optimal number of features to optimize the performance. In 10-fold cross-validation the proposed XGBoost based approach with optimal 50 features achieved accuracy of 100%, 98.70%, 98.77%, 97.26%, 87.40%, 97.39%, 98.03%, 96.42%, and F1-Score of 100%, 99%, 99%, 97%, 87%, 97%, 98%, 97%, for prediction of ion channel and nonion channel, voltage-gated and ligand-gated ion channels, subclasses of voltage-gated ion channels (VGICs), subclasses of ligand-gated ion channels (LGICs), subclasses of voltage-gated calcium channels (VGCCs), subclasses of voltage-gated potassium channels (VGKCs), subclasses of voltage-gated sodium channels (VGSCs), and subclasses of voltage-gated chloride channels, respectively. Here the proposed approach also compares with the other approaches such as support vector machine, k-nearest neighbor, Gaussian Naïve Bayes, and random forest and also compares with existing methods such as support vector machine (SVM) with maximum relevance maximum distance with an accuracy of 86.6%, 83.7%, and 85.1%, for ion channels, non-ion channels and overall respectively and SVM with radial basis function kernel-based method with an accuracy of 100%, 97% and 99.9% for ion channels, nonion channels, and overall accuracy, respectively.

Phase separation of a magnetic fluid: Asymptotic states and nonequilibrium kinetics.

We study self-assembly in a colloidal suspension of magnetic particles by performing comprehensive molecular dynamics simulations of the Stockmayer (SM) model, which comprises spherical particles decorated by a magnetic moment. The SM potential incorporates dipole-dipole interactions along with the usual Lennard-Jones interaction and exhibits a gas-liquid phase coexistence observed experimentally in magnetic fluids. When this system is quenched from the high-temperature homogeneous phase to the coexistence region, the nonequilibrium evolution to the condensed phase proceeds with the development of spatial as well as magnetic order. We observe density-dependent coarsening mechanisms-a diffusive growth law ℓ(t)∼t^{1/3} in the nucleation regime and hydrodynamics-driven inertial growth law ℓ(t)∼t^{2/3} in the spinodal regimes. [ℓ(t) is the average size of the condensate at time t after the quench.] While the spatial growth is governed by the expected conserved order parameter dynamics, the growth of magnetic order in the spinodal regime exhibits unexpected nonconserved dynamics. The asymptotic morphologies have density-dependent shapes which typically include the isotropic sphere and spherical bubble morphologies in the nucleation region, and the anisotropic cylinder, planar slab, cylindrical bubble morphologies in the spinodal region. The structures are robust and nonvolatile, and exhibit characteristic magnetic properties. For example, the oppositely magnetized hemispheres in the spherical morphology impart the characteristics of a Janus particle to it. The observed structures have versatile applications in catalysis, drug delivery systems, memory devices, and magnetic photonic crystals, to name a few.

Cancer care continuum at a tertiary care centre in India during the Covid-19 pandemic and nationwide lockdown: Healthcare delivery through telemedicine.

Background The Covid-19 pandemic and subsequent lockdown in India caused disruptions in cancer treatment due to the restriction on movement of patients. We aimed to maintain continuity in cancer treatment during the lockdown through teleconsultations. We tried to reach out to our patients using telephonic consultations by establishing a Teleconsult Centre facility run by a team of doctors and patient navigators. Methods We telephonically contacted all patients who had outpatient appointments from 23 March to 30 April 2020 at our centre through the Teleconsult Centre to understand their current circumstances, feasibility of follow-up, local resources and offered best possible alternatives to continue cancer treatment, if required. Results Of the 2686 patients scheduled for follow-up during this period, we could contact 1783 patients in 9 working days. Through teleconsultations, we could defer follow-ups of 1034 patients (57.99%, 95% confidence interval [CI] 55.6%-60.3%), thus reducing the need for patients to travel to the hospital. Change in systemic therapy was made in 75 patients (4.2%, 95% CI 3.3%-5.2%) as per the requirements and available resources. Symptoms suggestive of disease progression were picked up in 12 patients (0.67%, 95% CI 0.35%-1.17%), who were advised to meet local physicians. Conclusion Our study suggests that the majority of patients on follow-up can be managed with teleconsultation in times of crisis. Teleconsultation has the potential of being one of the standard methods of patient follow-up even during periods of normalcy.

A Cross Sectional Assessment of the Profile of Risk Factors of Non-Communicable Diseases Among Health Care Staff of a Tertiary Cancer Hospital.

Background: Non-communicable disease (NCD) is the leading cause of death, accounting for 70% of total death globally, and posing a major public health challenge. In India, nearly 5.8 million people (WHO report, 2015) die from NCDs every year. The basic element of NCD prevention is the identification of the associated risk factors and risk modification. The objective of the current study was conducted to assess the prevalence of risk factors for NCDs among healthcare staff of the two units of a Tertiary Cancer Hospital in Varanasi, India, using WHO STEPS approach. Methods: This cross sectional study was conducted among 528 participants who were willing to participate in the study, from among 967 healthcare staffs of the two units of the Tertiary Cancer Hospital. The participants were interviewed and the anthropometric and biochemical parameters were measured. Results: The prevalence of risk factors, associated with NCD, tobacco use, alcohol use, extra salt in diet, less than 5 servings of fruits/vegetables, physical inactivity and self-perceived high stress score was found in 34 (6.43%), 90 (17.04%), 461 (87.3%), 412 (78.03%), 409 (77.4%) and 159 (30.11%) respondents, respectively. Multiple logistic regression revealed that Diabetes was significantly associated with male sex, high BMI and physical inactivity. Hypertension was found significantly associated with male sex, increasing age, tobacco and or alcohol consumption, high BMI and high stress. Dyslipidemia was also found significantly associated with high BMI, male sex, physical inactivity and high stress levels. Conclusion: A high prevalence of risk factors for NCDs was found among the healthcare staff and it is the need of the hour to take preventive measures to reduce the prevailing burden of NCD.

Federated Learning With Taskonomy for Non-IID Data.

Classical federated learning approaches incur significant performance degradation in the presence of non-independent and identically distributed (non-IID) client data. A possible direction to address this issue is forming clusters of clients with roughly IID data. Most solutions following this direction are iterative and relatively slow, also prone to convergence issues in discovering underlying cluster formations. We introduce federated learning with taskonomy (FLT) that generalizes this direction by learning the task relatedness between clients for more efficient federated aggregation of heterogeneous data. In a one-off process, the server provides the clients with a pretrained (and fine-tunable) encoder to compress their data into a latent representation and transmit the signature of their data back to the server. The server then learns the task relatedness among clients via manifold learning and performs a generalization of federated averaging. FLT can flexibly handle a generic client relatedness graph, when there are no explicit clusters of clients, as well as efficiently decompose it into (disjoint) clusters for clustered federated learning. We demonstrate that FLT not only outperforms the existing state-of-the-art baselines in non-IID scenarios but also offers improved fairness across clients. Our codebase can be found at: https://github.com/hjraad/FLT/.

Predicting the impact of the third wave of COVID-19 in India using hybrid statistical machine learning models: A time series forecasting and sentiment analysis approach.

BACKGROUND: Since January 2020, India has faced two waves of COVID-19; preparation for the upcoming waves is the primary challenge for public health sectors and governments. Therefore, it is important to forecast future cumulative confirmed cases to plan and implement control measures effectively. METHODS: This study proposed a hybrid autoregressive integrated moving average (ARIMA) and Prophet model to predict daily confirmed and cumulative confirmed cases. The built-in auto.arima function was first used to select the optimal hyperparameter values of the ARIMA model. Then, the modified ARIMA model was used to find the best fit between the test and forecast data to find the best model parameter combinations. Articles, blog posts, and news stories from virologists, scientists, and health experts related to the third wave of COVID-19 were gathered using the Python web scraping package Beautiful Soup. Their opinions (sentiments) toward the potential third wave were analyzed using natural language processing (NLP) libraries. RESULTS: A spike in daily confirmed and cumulative confirmed cases was predicted in India in the next 180 days based on past time series data. The results were validated using various analytical tools and evaluation metrics, producing a root mean square error (RMSE) of 0.14 and a mean absolute percentage error (MAPE) of 0.06. The NLP processing results revealed negative sentiments in most articles and blogs, with few exceptions. CONCLUSION: The findings of this study suggest that there will be more active cases in the upcoming days. The proposed models can forecast future daily confirmed and cumulative confirmed cases. This study will help the country and states plan appropriate public health measures for the upcoming waves of COVID-19.

Clinical characteristics, laboratory parameters and outcomes of COVID-19 in cancer and non-cancer patients from a tertiary Cancer Centre in India.

BACKGROUND: There is paucity of data regarding clinical characteristics, laboratory parameters and outcomes of coronavirus disease (COVID-19) in cancer versus non-cancer patients, particularly from India. MATERIALS AND METHODS: This was an observational, single-centre, retrospective analysis of patients with laboratory-confirmed COVID-19 hospitalised in our institution between 22 May 2020 and 1 December 2020. We compared baseline clinical characteristics, laboratory parameters and outcomes of COVID-19 (overall mortality, time to discharge) between cancer and non-cancer patients. RESULTS: A total of 200 COVID-19 infection episodes were analysed of which 109 (54.5%) were patients with cancer and 91 (45.5%) were patients without cancer. The median age was 43 (interquartile range [IQR]:32-57), 51 (IQR: 33-62) and 38 (IQR: 31.5-49.3) years; of whole cohort, cancer and non-cancer patients, respectively. Comparison of outcomes showed that oxygen requirement (31.2% [95% CI: 22.6-40.7] vs. 17.6% [95% CI: 10.4-26.9]; p = 0.03), median time to discharge (11 days [IQR: 6.75-16] vs. 6 days [IQR: 3-9.75]; p < 0.001) and mortality (10.0% [95% CI: 5.2-17.3] vs. 1.1% [95% CI: 0.03-5.9]; p = 0.017) were significantly higher in patients with cancer. In univariable analysis, factors associated with higher mortality in the whole cohort included diagnosis of cancer (10.1% vs. 1.1%; p = 0.027; odds ratio [OR]: 7.04), age ≥60 (17.4% vs. 2.6%; p = 0.001; OR: 7.38), oxygen requirement (22% vs. 0.6%; p < 0.001; OR: 29.01), chest infiltrates (19.2% vs. 1.4%; p < 0.001; OR: 22.65), baseline absolute lymphocyte count <1 × 109 /L (10.8% vs. 1.9%; p = 0.023; OR:5.1), C-reactive protein >1 mg% (12.8% vs. 0%; p = 0.027; OR: 24.69), serum procalcitonin >0.05 ng/ml (22.65% vs. 0%; p = 0.004; OR: 4.49) and interleukin-6 >6 pg/ml (10.8% vs. 1.3%; p = 0.036; OR: 3.08). In multivariable logistic regression, factors significantly associated with mortality were oxygen requirement (p = 0.005; OR: 13.11) and high baseline procalcitonin level (p = 0.014; OR: 37.6). CONCLUSION: Cancer patients with COVID-19 have higher mortality and require longer hospital stay. High procalcitonin levels and oxygen requirement during admission are other factors that affect outcomes adversely.

Tumor necrosis factor-α induced protein 8 (TNFAIP8/TIPE) family is differentially expressed in oral cancer and regulates tumorigenesis through Akt/mTOR/STAT3 signaling cascade.

BACKGROUND: Highest incidence of oral cancer is reported in India with reduced survival rate in the advanced stages due to lack of effective biomarkers. Therefore, it is essential to develop novel biomarkers for the better management of this disease. In the current study, TNFAIP8/TIPE protein family comprising of four proteins is explored for its role in oral cancer. METHODS: IHC analysis of oral cancer TMA and Western blot analysis of tobacco treated oral cancer cells were performed to determine the differential expression of TIPE proteins in oral cancer. Further, CRISPR/Cas9-mediated gene editing was done to generate TIPE proteins' knockouts and MTT, colony formation, wound healing, cell cycle and Western blot analysis were performed to determine the effect of gene knockouts on various cancer hallmarks and the associated molecular targets of TIPE proteins. RESULTS AND DISCUSSION: IHC results revealed that expression of TIPE, TIPE2 and TIPE3 were upregulated and TIPE1 was downregulated in oral cancer tissues compared to normal tissues. Similar results were observed upon treating oral cancer cells with tobacco carcinogens. Furthermore, knockout of TIPE or TIPE2 or TIPE3 significantly reduced the survival, proliferation, colony formation and migration of oral cancer cells whereas knockout of TIPE1 had an opposite effect. Further, TIPE, TIPE2 and TIPE3 knockout-mediated inhibition of proliferation was associated with inhibition of cell cycle progression at S or G2/M phases, and downregulation of proteins involved in cancer progression. We found that TIPE, TIPE1 and TIPE2 proteins regulate oral cancer progression through modulation of Akt/mTOR signaling cascade, whereas TIPE3 acts through an Akt-independent mTOR/STAT3 pathway. CONCLUSION: Collectively, the TIPE proteins were proved to play significant roles in the progression of oral cancer thus warranting research and clinic attention for their therapeutic and prognostic values and raising the importance of specific targeting of TIPE proteins in cancer treatment.

Clinical course of severe COVID19 treated with tocilizumab and antivirals post-allogeneic stem cell transplant with extensive chronic GVHD.

Recipients of allogeneic hematopoietic stem cell transplantation (allo-HSCT) are an immunocompromised group who are likely to develop severe complications and mortality because of coronavirus disease 2019 (COVID-19). We report here a 61-year-old male patient of primary myelofibrosis who underwent an allo-HSCT 6 years earlier, had chronic graft-versus-host disease (cGVHD) involving the liver, lung, eyes, and skin, (with recurrent episodes of pulmonary infections) who developed severe COVID-19. The patient was treated with tocilizumab, and a combination of lopinavir/ritonavir, ribavirin, interferon-ß1b. He was discharged after 31 days with full recovery. Tocilizumab, a humanized monoclonal antibody against IL6, has been shown to benefit respiratory manifestations in severe COVID19. However, this is first report, to our knowledge, of its use and benefit in a post HSCT recipient.

Orai-1 and Orai-2 regulate oral cancer cell migration and colonisation by suppressing Akt/mTOR/NF-κB signalling.

Despite remarkable progress in understanding and treating oral cancer (OC), it still remains one of the life-threatening diseases and predominant cancers in the world. Therefore, deciphering the molecular mechanisms of this disease would help us to develop highly efficacious therapies. Multiple lines of evidence suggest that calcium and its dysregulation play significant role in the development of various cancers. As an adaptation of survival mechanism, upon depletion of ER calcium stores, store-operated calcium entry (SOCE) has been induced via SOCE channels (SOCC) in various mammalian cells. SOCC are regulated by Orai-1, Orai-2 and Orai-3 located on plasma membrane and two calcium-sensing ER membrane proteins known as stromal interaction molecules (STIM-1 and STIM-2). Hence, the present study was aimed at analysing the role of Orai-1 and Orai-2 in oral cancer and the underlying mechanism. Our results suggest that both Orai-1 and Orai-2 proteins were overexpressed in oral cancer tissues and cell lines (SAS) compared to normal epithelial tissues and cell lines respectively. In addition, silencing of Orai-1 and Orai-2 via chemical SOCE inhibitors and siRNAs inhibited calcium uptake and suppressed oral cancer cell proliferation, colony formation and migration. Furthermore, silencing of Orai-1 and Orai-2 inhibited Akt/mTOR/NF-κB pathway in oral cancer cells. Interestingly, tobacco carcinogen NNN and synthetic carcinogen 4-NQO, enhanced the expression of Orai-1 and Orai-2 in SAS cells. Therefore, we conclude that Orai-1 and Orai-2 have significant role in oral cancer and can be further explored to develop novel therapies for the treatment of this disease.

Mesenchymal stem cell-conditioned media: A novel alternative of stem cell therapy for quality wound healing.

Mesenchymal stem cells-conditioned media (MSCs-CM) contains several growth factors and cytokines, thus may be used as a better alternative to stem cell therapy, which needs to be elucidated. The present study was conducted to evaluate the therapeutic potential of caprine, canine, and guinea pig bone marrow-derived MSCs-CM in excision wound healing in a guinea pig model. MSCs were obtained from bone marrow, expanded ex vivo and characterized as per ISCT criteria. CM was collected assayed by western blot to ascertain the presence of important secretory biomolecules. Quantitative estimation by enzyme-linked immunosorbent assay was done for a vascular epidermal growth factor (VEGF) and interleukin-6 (IL-6) in caprine MSCs-CM and optimum time for collection of CM was decided as 72 hr. CM from all the species was lyophilized by freeze-drying method. Full-thickness (2 × 2 cm2 ) excision skin wounds were created in guinea pigs (six animals in each group) and respective lyophilized CM mixed with laminin gel was applied topically at weekly interval. On Day 28, histopathological examinations of healed skin were done by hemotoxylin and eosin staining. MSCs were found to secrete important growth factors and cytokines (i.e., VEGF, transforming growth factor-ß1, fibroblast growth factor-2, insulin-like growth factor-1, stem cell factor, and IL-6) as demonstrated by immunohistochemistry and western blot assay. It was found that allogenic and xenogenic application of CM significantly improved quality wound healing with minimal scar formation. Thus, MSCs-CM can be used allogenically as well as xenogenically for quality wound healing.

Elucidation of genotype-environment interactions and genetic stability parameters for yield, quality and agromorphological traits in ashwagandha (Withania somnifera (L.) Dunal).

The present study was undertaken to delineate genotype-environment interactions and stability status of 16 genotypes of ashwagandha (Withania somnifera (L.) Dunal) in context to the 12 characters, namely plant height, number of primary branches, number of secondary branches, days to flowering, days to maturity, number of berries, number of seeds/berry, root length, root diameter, root branches, dry root yield and total alkaloid content (%). Experiment was carried out in a randomized complete block design with three replicationsover three different locations (S. K. Nagar, Jagudan and Bhiloda) in north Gujarat for three years (2016-17, 2017-18 and 2018-19). Pooled analysis of variance revealed that the mean squares due to genotypes and genotype 9 environment interaction along with linear and nonlinear components were highly significant (P<0.01) for most of the traits under study. Stability parameters for component traits through Eberhart and Russell model showed that genotypes that can be used directly in breeding programme are SKA-4 for early flowering, SKA-21 for early maturity and SKA-1, SKA-4, SKA-6 and SKA-17 for shorter plant height. Further, SKA-21 could be used for improving number of primary branches per plant, SKA-11 and SKA-17 for number of secondary branches per plant, SKA-19 for number of berries per plant, SKA-6, SKA-21, SKA-27 and AWS-1 for root branches and SKA-17 for root length as these genotypes were found to be moststable across the environments for mentioned traits. The result revealed that some reliable predictions about genotype 9 environment interaction and its unpredictable components were involved significantly in determining the stability of genotypes. Hence, the present investigation can be exploited for the identification of more productive genotypes in specific environments, leading to significant increase in root productivity of ashwagandha.

TIPE2 Induced the Proliferation, Survival, and Migration of Lung Cancer Cells Through Modulation of Akt/mTOR/NF-κB Signaling Cascade.

Lung cancer represents the most common cause of cancer deaths in the world, constituting around 11.6% of all new cancer cases and 18.4% of cancer-related deaths. The propensity for early spread, lack of suitable biomarkers for early diagnosis, as well as prognosis and ineffective existing therapies, contribute to the poor survival rate of lung cancer. Therefore, there is an urgent need to develop novel biomarkers for early diagnosis and prognosis which in turn can facilitate newer therapeutic avenues for the management of this aggressive neoplasm. TIPE2 (tumor necrosis factor-α-induced protein 8-like 2), a recently identified cytoplasmic protein, possesses enormous potential in this regard. Immunohistochemical analysis showed that TIPE2 was significantly upregulated in different stages and grades of lung cancer tissues compared to normal lung tissues, implying its involvement in the positive regulation of lung cancer. Further, knockout of TIPE2 resulted in significantly reduced proliferation, survival, and migration of human lung cancer cells through modulation of the Akt/mTOR/NF-κB signaling axis. In addition, knockout of TIPE2 also caused arrest in the S phase of the cell cycle of lung cancer cells. As tobacco is the most predominant risk factor for lung cancer, we therefore evaluated the effect of TIPE2 in tobacco-mediated lung carcinogenesis as well. Our results showed that TIPE2 was involved in nicotine-, nicotine-derived nitrosamine ketone (NNK)-, N-nitrosonornicotine (NNN)-, and benzo[a]pyrene (BaP)-mediated lung cancer through inhibited proliferation, survival, and migration via modulation of nuclear factor kappa B (NF-κB)- and NF-κB-regulated gene products, which are involved in the regulation of diverse processes in lung cancer cells. Taken together, TIPE2 possesses an important role in the development and progression of lung cancer, particularly in tobacco-promoted lung cancer, and hence, specific targeting of it holds an enormous prospect in newer therapeutic interventions in lung cancer. However, these findings need to be validated in the in vivo and clinical settings to fully establish the diagnostic and prognostic importance of TIPE2 against lung cancer.

Isoform-Specific Role of Akt in Oral Squamous Cell Carcinoma.

Protein kinase B (Akt) plays a very significant role in various cancers including oral cancer. However, it has three isoforms (Akt1, Akt2, and Akt3) and they perform distinct functions and even play contrasting roles in different cancers. Therefore, it becomes essential to evaluate the isoform-specific role of Akt in oral cancer. In the present study, an attempt has been made to elucidate the isoform-specific role of Akt in oral cancer. The immunohistochemical analysis of oral cancer tissues showed an overexpression of Akt1 and 2 isoforms but not Akt3. Moreover, the dataset of "The Cancer Genome Atlas" for head and neck cancer has suggested the genetic alterations of Akt1 and 2 tend to be associated with the utmost poor clinical outcome in oral cancer. Further, treatment of oral cancer cells with tobacco and its components such as benzo(a)pyrene and nicotine caused increased mRNA levels of Akt1 and 2 isoforms and also enhanced the aggressiveness of oral cancer cells in terms of proliferation, and clonogenic and migration potential. Finally, silencing of Akt1 and 2 isoforms caused decreased cell survival and induced cell cycle arrest at the G2/M phase. Akt1/2 silencing also reduced tobacco-induced aggressiveness by decreasing the clonogenic and migration potential of oral cancer cells. Moreover, silencing of Akt1 and 2 isoforms was found to decrease the expression of proteins regulating cancer cell survival and proliferation such as cyclooxygenase-2, B-cell lymphoma 2 (Bcl-2), cyclin D1, and survivin. Thus, the important role of Akt1 and 2 isoforms have been elucidated in oral cancer with in-depth mechanistic analysis.

Assessment of topsoil contamination in an urbanized interfluve region of Indo-Gangetic Plains (IGP) using magnetic measurements and spectroscopic techniques.

The magnetic susceptibility (MS) measurements are used for rapid and cost-effective soil surveys and for accessing heavy metal contamination worldwide. In the sub-Himalayan plains of India, nearly 6.05 × 104 km2 area of most the fertile land occurs as interfluve of Late Quaternary age between the two major glacier-fed rivers (Ganga and Yamuna). The vast areal expanse of interfluve terminates at the rivers' confluence in Sangam (25°25'13″N-81°53'22″E), Allahabad. This is the first study of MS soil survey of the interfluve region at the confluence comprising 490 samples from 49 locations. The MS values are between 8.84 and 261.25 × 10-8 m3 kg-1 and the change is more pronounced (8.84-312.65 × 10-8 m3 kg-1) with increasing depth. A sudden increase in the MS between 12- (11.28-303.32 × 10-8 m3 kg-1) and 14-cm (11.21-238.45 × 10-8 m3 kg-1) depth is observed similar to observations worldwide. The high MS hotspots are aligned parallel to major traffic networks of the city suggesting a major contribution emanating from the anthropogenic load. A significant difference has been noted in the MS values of present-day mid-channel bar sediments of Ganga (25.24 × 10-8 m3 kg-1) and Yamuna (116.47 × 10-8 m3 kg-1) Rivers. The laser-induced breakdown spectroscopy (LIBS) data showed the presence of heavy (Fe, Ti, Cr, Cu, Cd, Zn, and Pb) and light (H, C, N, and O) elements supporting MS data. The concentration of toxic elements predicted by partial least squares regression (PLSR) approach concurs with magnetic measurements. The topsoil MS values increase up to a depth of ~ 6.25 cm suggesting the dominant role of anthropogenic source for the increased heavy metal concentration compared with basement contributions.