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Previous studies have demonstrated that cancer cells harbor unique metabolic characteristics relative to healthy counterparts. The current study is a prospective ex-vivo HR-MAS NMR analysis of malignant colorectal cancer (CRC) tissue specimens and its corresponding benign tissues.To assess the HR-MAS Spectroscope qualitatively & to analyze significant difference between the normal, benign and malignant intestinal mucosa.Between November 2013and January 2016, 36 consecutive patients with confirmed CRC were recruited to a prospective observational study. Fresh tissue samples were obtained from center of tumor and 5 cm from tumor margin from surgical resection specimens. Samples were run in duplicate where tissue volume permitted to compensate for anticipated sample heterogeneity. Typically, the sample was packed into a 4 mm ZrO2 rotor of 50 μl capacity; a volume of 20μl of D2O having 0.03% TSP was used as a chemical shift reference. The sample-rotor-setup was then transferred into the HR-MAS NMR probe for analysis.A total of 36 spectra were acquired (center of tumor, n = 18; 5 cm from tumor margin, n = 18). The malignant clustering occurs due to increased Val (0.90ppm), Lac (1.34ppm), Ala(1.48ppm) levels of acetate (1.90ppm), glutamate (2.35ppm), taurine (3.23 ppm), choline containing compounds (3.20-3.22ppm), glycine (3.56ppm), lactate (4.12ppm) and α-H of Leu, Ileu, Val, Lys, Ala (3.76-3.79ppm . In addition unique metabolic profiles were observed for tumors of differing T-stage. The information gathered from clustering in PCA had highly suggested that malignancy induces metabolic perturbations at cellular levels.HR-MAS NMR profiling demonstrates cancer-specific metabolic signatures in CRC and reveals metabolic differences between benign and malignant tumors. In addition, this approach reveals that tumor metabolism undergoes modification during local tumor advancement, offering potential in future staging and therapeutic approaches.

This paper examines the impact of the extent of the regionalization of MNEs’ R&D activities on their inventive performance. By joining the regionalization theory with the recombinant view of invention, we challenge the implicit assumption that all foreign knowledge-seeking activities will necessarily offer new knowledge to the firm. We introduce the (dis)economies of interdependence, defined as the (dis)advantages that the firm derives due to the interdependence among countries within a region, as a new theoretical mechanism explaining the benefits and costs of regionalization. Our analysis of global pharmaceutical firms shows that an inverted U-shaped relationship exists between the number of regions in which a firm has R&D activities and its inventive performance. Our results also indicate that a firm’s recombinant capability moderates the inverted U-shaped relationship in such a way that, when a firm’s recombinant capability is high, it reaches its turning point in a larger number of regions and the inverted U-shaped relationship is flatter. These results underscore that recombinant capability significantly influences the firm’s ability to derive benefits and reduce costs from the regionalization of its R&D activities. Our findings suggest that it is through the consideration of the (dis)economies of interdependence that offers the essential reasoning needed to unwind the inferred assumption that all foreign knowledge-seeking activities will offer access to new knowledge.

Purpose The purpose of this paper is to explore how the entrepreneurs' social connections and types of employment differentially affect the survival of startup firms in the USA and India. Further, the authors analyze the differences during both the early stage and the later stages of new ventures. Design/methodology/approach The authors use data from the Global Entrepreneurship Monitor (GEM) database between 2012 and 2014 and examine the hypothesized effects with logistic regression analyses. Findings The analysis reveals that an entrepreneur's social connections with other entrepreneurs favor the survival of the focal entrepreneur's early-stage business in the USA. However, social connections are more critical for later-stage ventures in India. During the early stage, new ventures of full-time entrepreneurs are more likely to survive in India, whereas those by hybrid entrepreneurs are more likely to survive in the USA. The differences between the importance of full-time and hybrid entrepreneurs across geographies are less discernible during the later stages of new ventures. Originality/value The novelty of this paper is that it demonstrates the significant differences in the way social connections and types of employment (hybrid versus full-time) affect the survival of entrepreneurial firms in the early and later stages. The study also expands the international business literature by shedding new light on country-level differences that affect the survival of new ventures.

Genomics, proteomics, and metabolomics are the major areas in clinical, preclinical, and translational research. The last two decades have witnessed profound growth and advancements in all three areas, although we are still struggling for accurate diagnosis and effective treatment of the most common dreaded diseases. Standard disease diagnoses and treatment management are still based on clinical phenotypes, which are suboptimal and imprecise due to our inability to bridge between the clinical traits or symptoms and the observed manifestation in the genome, proteome, or metabolome. Metabolites are the end product of cellular processes; therefore, it is more likely to have a correlation with a clinical phenotype. The advancement in the metabolic platform has offered to quantify hundreds to thousands of metabolites from a sample in a robust manner. However, due to the high dimensionality of the data, an efficient interpretation of this multivariate data is challenging. Nevertheless, the ever-increasing computational power and advanced statistical tools facilitated a better understanding and dynamics of metabolites. Advance statistical tools also provide plausible correlations with the clinical score and offer accurate disease-diagnosis and management. Big-data analysis and applications, such as machine learning and deep-learning were able to cater to more accurate patient stratification and precision medicine. However, more recently, the integration of pan-omics data offered a new field—phenomics. Phenomics is the systematic analysis of qualitative and quantitative phenotypes, for better understanding and interpretation of a disease phenotype. Although, rigorous and timely validation of phenotypic data is challenging, however, phenomics would allow a translation of bench to bedside for advanced diagnosis and prognosis. Although among many challenges, such as phenotypic degeneracy, which imposes restrictions for precise disease diagnosis and treatment management. The current emergence of novel and innovative technologies, such as “big data” analyses will offer new and meaningful information from the pan-omics data. This will hopefully reduce phenotypic degeneracy and offer clinicians and specialists, to use this knowledge in effective decision-making for the treatment and management of diseases.

Oral cancer is a sixth commonly occurring cancer globally. The use of tobacco and alcohol consumption are being considered as the major risk factors for oral cancer. The metabolic profiling of tissue specimens for developing carcinogenic perturbations will allow better prognosis. To profile and generate precise 1H HRMAS NMR spectral and quantitative statistical models of oral squamous cell carcinoma (OSCC) in tissue specimens including tumor, bed, margin and facial muscles. To apply the model in blinded prediction of malignancy among oral and neck tissues in an unknown set of patients suffering from OSCC along with neck invasion. Statistical models of 1H HRMAS NMR spectral data on 180 tissues comprising tumor, margin and bed from 43 OSCC patients were performed. The combined metabolites, lipids spectral intensity and concentration-based malignancy prediction models were proposed. Further, 64 tissue specimens from twelve patients, including neck invasions, were tested for malignancy in a blinded manner. Forty-eight metabolites including lipids have been quantified in tumor and adjacent tissues. All metabolites other than lipids were found to be upregulated in malignant tissues except for ambiguous glucose. All of three prediction models have successfully identified malignancy status among blinded set of 64 tissues from 12 OSCC patients with an accuracy of above 90%. The efficiency of the models in malignancy prediction based on tumor induced metabolic perturbations supported by histopathological validation may revolutionize the OSCC assessment. Further, the results may enable machine learning to trace tumor induced altered metabolic pathways for better pattern recognition. Thus, it complements the newly developed REIMS-MS iKnife real time precession during surgery.

We combine insights received from prior research on the role of lead user and prior investigations of disruptive innovation. Our research illustrates the role of a particular lead user, which we refer to as the relevant lead user, in paving the way for the potentially disruptive technology to be a definitely disruptive one. Through focused consideration, we reveal characteristics that may be significant in identifying users as relevant in relation to potentially disruptive innovation. Our research also reveals that contrary to Christensen's assumption, incumbents do not embrace the inevitable and jump from the old technology to the new. Rather, the transformation occurs over a period of time.

Research Summary: Prior research suggests that large incumbents will become victims of disruptive technological change. We investigate the image sensor industry in which the emergence of CMOS sensors challenged the manufacturers of CCD sensors. Although this disruptive technological change led to the demise of CCD technology, it also led to avianization—or strategic renewal—for some incumbents, similar to how some dinosaurs survived the mass Cretaceous-Tertiary extinction by evolving into birds. We find that CCD manufacturers that did avianize were preadapted to the disruptive CMOS technology in that they possessed relevant complementary technologies and access to in-house users that allowed them to strategically renew themselves. Managerial Summary: We investigate the transition from CCD to CMOS image sensors in the digital image sensor industry. Although the emergence of CMOS sensors was disruptive to CCD sensors, we find that CCD sensor manufacturers such as Sony and Sharp successfully transitioned to manufacturing CMOS sensors. Contrary to popular press and prior academic research characterizing disruptive change as being a source of failure for large firms, our research reveals that firms that possess relevant complementary technologies and have access to in-house users are able to strategically renew themselves in the face of a disruptive threat.

We report the synthesis and characterization of manganese(II) complexes having pentadentate ligands L1 (2,6-bis(1-(2-phenyl-2-(pyridin-2-yl)hydrazono)ethyl)pyridine), L2 (methyl 2,6-bis((E)-1-(2-phenyl-2-(pyridin-2yl)hydrazono)ethyl)isonicotinate), L3 (N-(2-(1H-indol-3-yl)ethyl)-2,6-bis((E)-1-(2-phenyl-2-(pyridin2yl)hydrazono)ethyl)isonicotiamide) and their application as dual contrast agents for simultaneous T1 and T2 weighted magnetic resonance imaging. Single crystal analysis of all the complexes [MnIIL1, MnIIL2 and MnIIL3] confirm the formation of novel seven-coordinate manganese complexes with an inner sphere water and perchlorate ion. The Magnetic Resonance Imaging (MRI) contrast agent [MnL2] was further modified by incorporating tryptamine as a binding moiety specific to Amyloid Beta-fibrils (Aβ-fibrils) in Alzhiemer's disease (AD) and it's in vitro evaluation for specific binding with Aβ-fibrils indicated as a bio-marker of AD.

Background Cerebrospinal fluid (CSF) is an essential bio-fluid of the central nervous system (CNS), playing a vital role in the protection of CNS and performing neuronal function regulation. The chemical composition of CSF varies during onset of meningitis, neurodegenerative disorders (positive controls) and in traumatic cases (negative controls). Methods The study design was broadly categorized into meningitis cases, negative controls and positive controls. Further differentiation among the three groups was carried out using Principal Component Analysis (PCA) followed by supervised Partial Least Square Discriminant Analysis (PLS-DA). Results The statistical analysis of meningitis vs. negative controls using PLS-DA model resulted in R2 of 0.97 and Q2 of 0.85. There was elevation in the levels of ketone bodies, total free amino acids, glutamine, creatine, citrate and choline containing compounds (choline and GPC) in meningitis cases. Similarly, meningitis vs. positive controls resulted in R2 of 0.80 and Q2 of 0.60 and showed elevation in the levels of total free amino acids, glutamine, creatine/creatinine and citrate in the meningitis group. Four cases of HIV were identified by PLS-DA model as well as by clinical investigations. Conclusion On the basis of metabolic profile it was found that negative control CSF samples are more appropriate for differentiation of meningitis than positive control CSF samples.

Miniaturization has been the main driver of product innovation in image sensors and other semiconductor devices for several decades. Strategy and technology researchers, however, have somewhat overlooked the enablers of miniaturization. Using charge-coupled device image sensors as the context, we find that innovations in complementary technologies played a vital role in mitigating the technological trade-offs associated with such product innovations. In the process, we contribute to our understanding of technological evolution by relating the enabling role of complementary technologies to product innovation.

We examine the puzzling geographic pattern that shows firms entering countries with weak intellectual property rights (IPR) protection with their research and development (R&D) activities. Geographic entry into weak IPR protection countries is at odds with conventional wisdom as such an environment erodes a firm's ability to appropriate from its innovations. We offer that while the well-established practice of spreading out a firm's value chain activities across a region has important implications for value creation, what remains unaddressed is the value appropriation aspect of such activities. We introduce a multilevel theory and maintain that operating regionally through commercialization activities (downstream activities) provides complementary assets to the upstream activities – specifically R&D activities in a country within that region – with which focal firms can appropriate more from their innovations. We find that regional downstream commercialization activities can substitute for weak IPR regimes, thereby providing firms with an alternative mechanism for protecting their intellectual property in weak IPR countries.

Oral microflora is a well-orchestrated and acts as a sequential defense mechanism for any infection related to oral disease. Chronic periodontitis is a disease of a microbial challenge to symbiosis and homeostasis. Periodontal surgery is the most promising cure with repair process during periodontal regeneration. It has an encouraging outcome in terms of early recovery biomarkers. Saliva of periodontal surgery subjects with the chronic periodontitis have been evaluated by 1H NMR spectroscopy in search of possible early metabolic differences that could be obtained in order to see the eradication of disease which favours the symbiotic condition. The study employed 1H NMR spectroscopy on 176 human saliva samples in search of distinctive differences and their spectral data were further subjected to multivariate and quantitative analysis. The 1H NMR study of periodontal surgery samples shows clear demarcation and profound metabolic differences when compared with the diseased condition. Several metabolites such as lactate, ethanol, succinate, and glutamate were found to be of higher significance in periodontal surgery in contrast to chronic periodontitis subjects. The PLS-DA model of the studied group resulted in R2 of 0.83 and Q2 of 0.70. Significant metabolites could be considered as early repair markers for chronic periodontitis disease as they are being restored to achieve symbiosis. The study, therefore, concluded the early recovery process of the diseased subjects with the restoration of possible metabolomic profile similar to the healthy controls.

Oral cancer is a sixth commonly occurring cancer globally. The use of tobacco and alcohol consumption are being considered as the major risk factors for oral cancer. The metabolic profiling of tissue specimens for developing carcinogenic perturbations will allow better prognosis.To profile and generate preciseStatistical models ofForty-eight metabolites including lipids have been quantified in tumor and adjacent tissues. All metabolites other than lipids were found to be upregulated in malignant tissues except for ambiguous glucose. All of three prediction models have successfully identified malignancy status among blinded set of 64 tissues from 12 OSCC patients with an accuracy of above 90%.The efficiency of the models in malignancy prediction based on tumor induced metabolic perturbations supported by histopathological validation may revolutionize the OSCC assessment. Further, the results may enable machine learning to trace tumor induced altered metabolic pathways for better pattern recognition. Thus, it complements the newly developed REIMS-MS iKnife real time precession during surgery.

Research summary: We investigate the effect of incumbents' stock of downstream complementary assets on their product innovation during a disruptive technological change. We theorize that a firm's stock of downstream complementary assets, by providing critical information about shifting demand conditions, will play a catalytic role in firm adaptation during such a change. Using the advent of disruptive computer numerical control machine tools in the U.S. machine tool industry during the 1970s and 1980s as the context, we find that firms with greater stocks of downstream complementary assets are likely to be product innovation leaders during such a change. Managerial summary: Disruptive changes are challenging firms across industries. We concentrate on the U.S. machine tool industry during the 1970s and 1980s when Japanese manufacturers with disruptive computer numerical control systems challenged the U.S. manufacturers. We find that, under the threat of disruption, the greater the stock of downstream complementary assets a U.S. machine tool manufacturer has, the more likely it is to be the product innovation leader with the disruptive technology. Our findings provide novel insights for managers in companies that face disruptive changes and can help them avoid the consequences of such changes as predicted by prior research. Copyright © 2016 John Wiley & Sons, Ltd.

A rapid and reliable method was developed and validated for determining betulin and betulinic acid in bark in Betula utilis by high-resolution magic angle spinning 1H nuclear magnetic resonance (HR-MAS NMR) spectroscopy. HR-MAS NMR spectroscopy clearly distinguished the resonances of betulin and betulinic acid in the bark of all accessions of B. utilis. The concentrations of betulin and betulinic acid were calculated and added to the spectra. The determination of the targeted metabolites in chloroform extract of bark of each accession of B. utilis was performed by high-performance liquid chromatography (HPLC). Quantitatively, betulin was present at higher concentrations than betulinic acid in all accessions. The HR-MAS NMR and HPLC results showed that betulin and betulinic acid varied significantly among accessions of B. utilis. Principal component analysis of the NMR and HPLC results provided classification into three metabolic groups in which the betulin concentration was high, moderate, or low....

This paper investigates the determinants of opportunity selection, in which an opportunity is defined in the literature as an idea for an innovation that may have value with additional investment o...