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Abstract While cellular metabolism impacts the DNA damage response, a systematic understanding of the metabolic requirements that are crucial for DNA damage repair has yet to be achieved. Here, we investigate the metabolic enzymes and processes that are essential for the resolution of DNA damage. By integrating functional genomics with chromatin proteomics and metabolomics, we provide a detailed description of the interplay between cellular metabolism and the DNA damage response. Further analysis identified that Peroxiredoxin 1, PRDX1, contributes to the DNA damage repair. During the DNA damage response, PRDX1 translocates to the nucleus where it reduces DNA damage‐induced nuclear reactive oxygen species. Moreover, PRDX1 loss lowers aspartate availability, which is required for the DNA damage‐induced upregulation of de novo nucleotide synthesis. In the absence of PRDX1, cells accumulate replication stress and DNA damage, leading to proliferation defects that are exacerbated in the presence of etoposide, thus revealing a role for PRDX1 as a DNA damage surveillance factor.

We apply the technique of renormalisation group (RG) to investigate periodic solutions of the modified Rayleigh–Liénard oscillator, both in presence of usual integer order damping and fractional order damping. In the latter case, a parametric driven periodic external force is also taken into account. The existence of limit cycle solutions is evident in both scenarios. [ABSTRACT FROM AUTHOR]

We apply Jacobi’s Last Multiplier theory to construct the non-standard Lagrangian and Hamiltonian structures for the Levinson–Smith equations satisfying the Chiellini integrability condition. Then after a brief exposition of the contact geometry, we explore its connection with the non-standard Hamiltonian structures. We present the formulation of the Levinson–Smith equation in terms of General Equation for the Non-Equilibrium Reversible-Irreversible Coupling (GENERIC) method and also study the gradient-type flow. We give a geometric formulation of GENERIC and apply this to general Levinson–Smith equations. [ABSTRACT FROM AUTHOR]

Nuclear metabolism and DNA damage response are intertwined processes, but the precise molecular links remain elusive. Here, we explore this crosstalk using triple-negative breast cancer (TNBC) as a model, a subtype often prone to DNA damage accumulation. We show that the de novo purine synthesis enzyme IMPDH2 is enriched on chromatin in TNBC compared to other subtypes. IMPDH2 chromatin localization is DNA damage dependent, and IMPDH2 repression leads to DNA damage accumulation. On chromatin, IMPDH2 interacts with and modulates PARP1 activity by controlling the nuclear availability of NAD+ to fine-tune the DNA damage response. However, when IMPDH2 is restricted to the nucleus, it depletes nuclear NAD+, leading to PARP1 cleavage and cell death. Our study identifies a non-canonical nuclear role for IMPDH2, acting as a convergence point of nuclear metabolism and DNA damage response. Metabolism plays an important role in response to DNA damage, however the underlying mechanisms are less clear. Here, the authors identify a non-canonical role of IMPDH2 wherein it is recruited to the chromatin following DNA damage and mediates PARP1-dependent DNA damage repair via the regulation of nuclear NAD+ levels. [ABSTRACT FROM AUTHOR]

Subcellular compartmentalization of metabolic enzymes establishes a unique metabolic environment that elicits specific cellular functions. Indeed, the nuclear translocation of certain metabolic enzymes is required for epigenetic regulation and gene expression control. Here, we show that the nuclear localization of the mitochondrial enzyme methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) ensures mitosis progression. Nuclear MTHFD2 interacts with proteins involved in mitosis regulation and centromere stability, including the methyltransferases KMT5A and DNMT3B. Loss of MTHFD2 induces severe methylation defects and impedes correct mitosis completion. MTHFD2 deficient cells display chromosome congression and segregation defects and accumulate chromosomal aberrations. Blocking the catalytic nuclear function of MTHFD2 recapitulates the phenotype observed in MTHFD2 deficient cells, whereas restricting MTHFD2 to the nucleus is sufficient to ensure correct mitotic progression. Our discovery uncovers a nuclear role for MTHFD2, supporting the notion that translocation of metabolic enzymes to the nucleus is required to meet precise chromatin needs. The nuclear localization of metabolic enzymes is fascinating and in most cases remains a mystery. Here, Pardo Lorente and colleagues show that nuclear MTHFD2 is required for successful mitosis by controlling centromeric histone methylation. [ABSTRACT FROM AUTHOR]

Noisy intermediate-scale quantum (NISQ) computers provide a new experimental platform for investigating the behaviour of complex quantum systems. We show that currently available NISQ devices can be used for versatile quantum simulations of chaotic systems. We introduce a classical-quantum hybrid approach for exploring the dynamics of the chaotic quantum kicked top (QKT) on a quantum computer. The programmability of this approach allows us to experimentally explore a broad range of QKT chaoticity parameter regimes inaccessible to previous studies. Furthermore, the number of gates in our simulation does not increase with the number of kicks, thus making it possible to study the QKT evolution for arbitrary number of kicks without fidelity loss. Using a publicly accessible NISQ computer (IBMQ), we observe periodicities in the evolution of the 2-qubit QKT, as well as signatures of chaos in the time-averaged 2-qubit entanglement. We also demonstrate a connection between entanglement and delocalization in the 2-qubit QKT, confirming theoretical predictions. [ABSTRACT FROM AUTHOR]

Improving the forecasting accuracy of agricultural commodity prices is critical for many stakeholders namely, farmers, traders, exporters, governments, and all other partners in the price channel, to evade risks and enable appropriate policy interventions. However, the traditional mono-scale smoothing techniques often fail to capture the non-stationary and non-linear features due to their multifarious structure. This study has proposed a CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise)-TDNN (Time Delay Neural Network) model for forecasting non-linear, non-stationary agricultural price series. This study has evaluated its suitability in comparison with the other three major EMD (Empirical Mode Decomposition) variants (EMD, Ensemble EMD and Complementary Ensemble EMD) and the benchmark (Autoregressive Integrated Moving Average, Non-linear Support Vector Regression, Gradient Boosting Machine, Random Forest and TDNN) models using monthly wholesale prices of major oilseed crops in India. Outcomes from this investigation reflect that the CEEMDAN-TDNN hybrid models have outperformed all other forecasting models on the basis of evaluation metrics under consideration. For the proposed model, an average improvement of RMSE (Root Mean Square Error), Relative RMSE and MAPE (Mean Absolute Percentage Error) values has been observed to be 20.04%, 19.94% and 27.80%, respectively over the other EMD variant-based counterparts and 57.66%, 48.37% and 62.37%, respectively over the other benchmark stochastic and machine learning models. The CEEMD-TDNN and CEEMDAN-TDNN models have demonstrated superior performance in predicting the directional changes of monthly price series compared to other models. Additionally, the accuracy of forecasts generated by all models has been assessed using the Diebold-Mariano test, the Friedman test, and the Taylor diagram. The results confirm that the proposed hybrid model has outperformed the alternative models, providing a distinct advantage. [ABSTRACT FROM AUTHOR]

Bay of Bengal in southern Bangladesh is a major source of water from coastal aquifers, but prone to contamination by seawater intrusion, making climate-vulnerable populations and economies unfit for potable, agricultural water, adopting crops, etc. The study area located in Khulna district lies in the southwestern coast of the country is among the most vulnerable due to its salinity issues. Therefore, this study identified fresh groundwater potential zones in the southwestern coastal zones of the country suited for community usage helping coastal peoples meet their demands. This study focused on twelve thematic layers employing remote sensing and GIS with analytical hierarchy process. Here, groundwater salinity is 84% brackish to saline over 70% of the region [electric conductivity: 295–16,295 micro-Siemens/cm]. However, groundwater chloride in 88% signifies a slightly to medium salty zone. The annual average rainfall reduced surface water infiltration in 75% of the area with little to very slightly soil salinity. The fresh groundwater resource zone has classified based on its potentiality as: very high (0.52%)—for drinking, agricultural irrigation, or industrial work; high (25%)—marginal salinity suitable for agricultural or industrial uses; low (11%)—low salinity, but usable for high salt tolerant crops in irrigation; and very low (64%)—very high groundwater salinity, and not suitable for human consumption and community uses. Finally, this study will help develop sustainable groundwater resources in the coastal region and a fresh groundwater supply plan in saline-prone areas. [ABSTRACT FROM AUTHOR]

Whole-genome sequencing (WGS) and whole-exome sequencing (WES) are crucial within the context of breast cancer (BC) research. They play a role in the detection of predisposed genes, risk stratification, and identification of rare single nucleotide polymorphisms (SNPs). These technologies aid in the discovery of associations between various syndromes and BC, understanding the tumour microenvironment (TME), and even identifying unknown mutations that could be useful in future for personalised treatments. Genetic analysis can find the associated risk of BC and can be used in early screening, diagnosis, specific treatment plans, and prevention in patients who are at high risk of tumour formation. This article focuses on the application of WES and WGS, and how uncovering novel candidate genes associated with BC can aid in treating and preventing BC. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOFs) are highly attractive porous materials with applications spanning the fields of chemistry, physics, biology, and engineering. Their exceptional porosity and structural flexibility have led to widespread use in catalysis, separation, biomedicine, and electrochemistry. Currently, most MOFs are synthesized under equilibrium liquid-phase reaction conditions. Here we show a general and versatile non-equilibrium flame aerosol synthesis of MOFs, in which rapid kinetics of MOF formation yields two distinct classes of MOFs, nano-crystalline MOFs and amorphous MOFs. A key advantage of this far-from-equilibrium synthesis is integration of different metal cations within a single MOF phase, even when this is thermodynamically unfavorable. This can, for example, produce single-atom catalysts and bimetallic MOFs of arbitrary metal pairs. Moreover, we demonstrate that dopant metals (e.g., Pt, Pd) can be exsolved from the MOF framework by reduction, forming nanoclusters anchored on the MOF. A prototypical example of such a material exhibited outstanding performance as a CO oxidation catalyst. This general synthesis route opens new opportunities in MOF design and applications across diverse fields and is inherently scalable for continuous production at industrial scales. Metal-organic frameworks (MOFs) are typically synthesized in equilibrium liquid-phase reactions. Here, the authors have developed and present a general non-equilibrium flame aerosol method to produce nanocrystal, amorphous, and bi-metallic MOFs. [ABSTRACT FROM AUTHOR]

The increasing use of renewable energy sources (RESs) in distribution networks, combined with an ever-increasing load, makes balancing between generation and load difficult. Demand response programs (DRPs) and energy storage come together in a significant way for microgrid operators to avoid purchasing power at a higher cost from the upstream network and to move toward a self-reliant system. This work considers Electric vehicles (EVs), being the most common type of flexible load, can be a demand response (DR) resource for demand-side management (DSM). The work proposes a technique that decides SoC over the number of EV plugged-in chargers in a charging station with time. To cope with the large number of chargers, the work conceptualizes cluster control in dealing with a large population of EV chargers. To achieve the goal, the control concept is implemented by categorizing EV chargers into different bins or groups based on the SoC of plugged-in EVs. The proposed model forecasts EV state transitions using the Markov state transition approach. The probabilistic approach of the state transition matrix is determined to understand the status of the battery SoC of EVs. Hence the significant contribution of the proposed technique does not necessitate sending the SoC values of plugged-in EVs to the control room at sampled intervals. The work then proposed two control techniques based on identifying and prioritizing the chargers of various charging stations to redistribute the EV loads within the short span of the load curve. Two control concepts, on/off control and charging power control, have been developed and applied to the final state transition matrix as a part of the DRP. The results related to the load reduction show the justification of the concept of controlling the power consumption of chargers. [ABSTRACT FROM AUTHOR]

Object detection plays an important role to accelerate the medical diagnosis and automatic polyp detection from colonoscopy images is one of the prominent examples. Visual examination is an error prone and time-consuming process to determine the shape, size, and location of polyps in colonoscopy images. Deep learning models are extensively accepted in the field of object detection. YOLO-v5 is an object detection model which is powered by deep learning technique. In this study we suggest a finetuned YOLO-v5 model for polyp detection from colonoscopy images. Effective data augmentation is also done to improvise the performance of the model. To quantify the efficiency of our solution against other works, two aspects have been fundamentally considered – qualitative performance and practical reliability, which have been achieved successfully. A detailed comparison study has been shared to justify the performance of our proposed method against other deep learning techniques – R-CNN, Faster RCNN and YOLO-v4. Our proposed solution deliberated high value of performance metrics which are comparatively better than other solutions. [ABSTRACT FROM AUTHOR]

The global urbanization surge, with the majority of the global population expected to reside in urbanized places, raises concerns about children’s limited exposure to nature, which could lead to a lack of environmental knowledge, gradually causing a decline in pro-environmental behaviors. Here, a bird-watching activity aims to introduce 10–18 year old students to urban biodiversity, enhance their knowledge of the ecological significance of local bird species, and help them explore their roles in conserving bird diversity. In the lesson, students observe and document bird species in their urban localities, followed by collaboratively designing and constructing bird feeders using waste and reuse of materials. We observed that students displayed excitement during the outdoor bird-walk, and identifying birds by name generated enthusiasm and increased engagement. With little assistance, they generated creative ideas for making bird feeders and could rationalize their choice of materials. This holistic learning experience fosters students’ interpersonal and intrapersonal skills, promotes awareness of and responsibility towards their environmental surroundings, and empowers them to enjoy nature and act as environmental stewards. More broadly, students benefit through improved observational skills, creativity, scientific inquiry, teamwork and interdisciplinary learning. This lesson emphasizes the significance of providing more nature-based experiential learning activities in the curricula by encouraging educators to leverage school campuses and urban green spaces as valuable resources for learning about urban nature. [ABSTRACT FROM AUTHOR]

Research into the anticancer activity of quantum-sized carbon dots (CDs) has emerged as a promising avenue in cancer research. This CDs delves into the opportunities and challenges associated with harnessing the potential of these nanostructures for combating cancer. Quantum-sized carbon dots, owing to their unique physicochemical properties, exhibit distinct advantages as potential therapeutic agents. Opportunities lie in their tunable size, surface functionalization capabilities, and biocompatibility, enabling targeted drug delivery and imaging in cancer cells. However, we include challenges, a comprehensive understanding of the underlying mechanisms, potential toxicity concerns, and the optimization of synthesis methods for enhanced therapeutic efficacy. A succinct summary of the state of the research in this area is given in this review, emphasizing the exciting possibilities and ongoing challenges in utilizing quantum-sized carbon dots as a novel strategy for cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Treatment options for pre-treated patients with metastatic triple-negative breast cancer (mTNBC) remain limited. This is the first study to assess the real-world safety and efficacy of sacituzumab govitecan (SG) in the UK. Methods: Data was retrospectively collected from 16 tertiary UK cancer centres. Pts had a diagnosis of mTNBC, received at least two prior lines of treatment (with at least one being in the metastatic setting) and received at least one dose of SG. Results: 132 pts were included. Median age was 56 years (28–91). All patients were ECOG performance status (PS) 0-3 (PS0; 39, PS1; 76, PS2; 16, PS3;1). 75% (99/132) of pts had visceral metastases including 18% (24/132) of pts with CNS disease. Median PFS (mPFS) was 5.2 months (95% CI 4.5–6.6) with a median OS (mOS) of 8.7 months (95% CI 6.8-NA). The most common adverse events (AEs) were fatigue (all grade; 82%, G3/4; 14%), neutropenia (all grade; 55%, G3/4; 29%), diarrhoea (all grade; 58%, G3/4, 15%), and nausea (all grade; 38%, G3/4; 3%). SG dose reduction was required in 54% of pts. Conclusion: This study supports significant anti-tumour activity in heavily pre-treated pts with mTNBC. Toxicity data aligns with clinical trial experience. [ABSTRACT FROM AUTHOR]

Purpose of Review: Our review delves into the progress across urological malignancies and discusses ongoing challenges and future directions in antibody–drug conjugate (ADC) development, emphasising their transformative potential in cancer care. Recent Findings: ADCs have advanced from hematologic to solid tumours, notably in breast cancer, and are now pivotal in metastatic urological cancers as both monotherapies and in combination regimens, underscored by the FDA's approval of enfortumab vedotin and sacituzumab govitecan for metastatic urothelial cancer. Progress in metastatic prostate cancer, particularly with ADCs targeting PSMA and STEAP1, is noteworthy, although renal cell cancer presents ongoing challenges. There is a continual search for agents in the metastatic, relapsed testicular cancer landscape. Summary: ADCs have emerged as a pivotal innovation in oncology, blending targeted antibody therapy with potent cytotoxic drugs, significantly advancing treatment options for urological malignancies. [ABSTRACT FROM AUTHOR]

In the present study, the researchers have utilized graphite as the reinforced phase of the aluminum metal matrix nanocomposites (AMMNCs) owing to its high strength and lubricating properties. The AMMNCs are processed through combined ultrasonic-stir-squeeze casting process to ensure homogeneity of the reinforced phase in the matrix while minimizing the porosity of the cast ingot. The phase and microstructure of the developed AMMNCs are investigated through characterization techniques such as x-ray diffraction and Field Emission Scanning Electron Microscopy. AMMNCs exhibit lower density in comparison with the as-cast aluminum alloy (AA2014). Hardness of the composites have improved due to addition of the reinforcement, but adversely the porosity also increases with the increase in concentration of graphite. The tribological properties of the AMMNCs are investigated under dry condition and compared with that of the as-cast AA2014. Addition of graphite improves the wear properties of the AMMNCs. However, parameters like concentration of graphite and applied load affect the wear rate considerably. Post-tribological characterization of the wear scars provide detailed information on the influence of hardness and elastic modulus on the tribological properties of the AMMNCs. [ABSTRACT FROM AUTHOR]

Aim: The purpose of this study is to assess the status quo of data sharing in LCA in relation to the FAIR (findability, accessibility, interoperability, and reuse) data principles. Methods: This study investigates how is LCA data from publicly funded research currently shared. Firstly, the focus is on life cycle inventory data shared in journal articles. Given that FAIR data sharing is not only the responsibility of the LCA practitioner, this study further investigates guidelines (e.g., data sharing standards and data management plans) and infrastructure (repositories, data formats, and nomenclature) to identify the tools and services available to LCA community which are essential to enable FAIR data sharing. Results: The study identifies that although there is growing awareness to improve data sharing practices, implementation of FAIR guidelines for data sharing is seldom seen in practice. LCA studies that adhere to FAIR principles are primarily due to use of generic data repositories which provide tools to support data sharing. However, there is no guidance on how LCA specific data should be shared to ensure its findability, accessibility, interoperability, and reusability. This study suggests a workflow to enable FAIRification of LCA data. In addition, the study recommends further efforts within the LCA community on skill and technology development, strategic funding, and recognition of the best practices in relation to data sharing. Conclusion: In conclusion, this study highlights the necessity of data sharing incentives, guidelines, and platforms/repositories specific for the LCA community. [ABSTRACT FROM AUTHOR]

With the advancement of interactive technology, alternative input modalities are often used, instead of conventional ones, to create intuitive, efficient, and user-friendly avenues of controlling and collaborating with robots. Researchers have examined the efficacy of natural interaction modalities such as gesture or voice in single and dual-task scenarios. These investigations have aimed to address the potential of the modalities on diverse applications encompassing activities like online shopping, precision agriculture, and mechanical component assembly, which involve tasks like object pointing and selection. This article aims to address the impact on user performance in a practical human–robot interaction application where a fixed-base robot is controlled through the utilization of natural alternative modalities. We explored this by investigating the impact of single-task and dual-task conditions on user performance for object picking and dropping. We undertook two user studies—one focusing on single-task scenarios, employing a fixed-base robot for object picking and dropping and the other encompassing dual-task conditions, utilizing a mobile robot for a driving scenario. We measured task completion times and estimated cognitive workload through the NASA Task Load Index (TLX), which offers a subjective, multidimensional scale measuring the perceived cognitive workload of a user. The studies revealed that the ranking of completion times for the alternative modalities remained consistent across both single-task and dual-task scenarios. However, the ranking based on perceived cognitive load was different. In the single-task study, the gesture-based modality resulted the highest TLX score, contrasting with the dual-task study, where the highest TLX score was associated with the eye gaze-based modality. Likewise, the speech-based modality achieved a lower TLX score compared to eye gaze and gesture in the single-task study, but its TLX score in the dual-task study was between gesture and eye gaze. These outcomes suggest that the efficacy of alternative modalities is contingent not only on user preferences but also on the specific situational context. [ABSTRACT FROM AUTHOR]

Persistent activation of hepatic stellate cells (HSCs) in the injured liver leads to the progression of liver injury from fibrosis to detrimental cirrhosis. In a previous study, we have shown that survivin protein is upregulated during the early activation of HSCs, which triggers the onset of liver fibrosis. However, the therapeutic potential of targeting survivin in a fully established fibrotic liver needs to be investigated. In this study, we chemically induced hepatic fibrosis in mice using carbon tetrachloride (CCl4) for 6 weeks, which was followed by treatment with a survivin suppressant (YM155). We also evaluated survivin expression in fibrotic human liver tissues, primary HSCs, and HSC cell line by histological analysis. αSMA+ HSCs in human and mice fibrotic liver tissues showed enhanced survivin expression, whereas the hepatocytes and quiescent (qHSCs) displayed minimal expression. Alternatively, activated M2 macrophage subtype induced survivin expression in HSCs through the TGF‐β‐TGF‐β receptor‐I/II signaling. Inhibition of survivin in HSCs promoted cell cycle arrest and senescence, which eventually suppressed their activation. In vivo, YM155 treatment increased the expression of cell senescence makers in HSCs around fibrotic septa such as p53, p21, and β‐galactosidase. YM155 treatment in vivo also reduced the hepatic macrophage population and inflammatory cytokine expression in the liver. In conclusion, downregulation of survivin in the fibrotic liver decreases HSC activation by inducing cellular senescence and modulating macrophage cytokine expression that collectively ameliorates liver fibrosis. [ABSTRACT FROM AUTHOR]

Micellar aqueous solutions of ionic surfactants have been observed to exhibit proton delocalization (the nuclear quantum effect) and to oscillate between a low density (LDL) and a high-density liquid (HDL) state of water at a fixed temperature. It is shown in this paper that such phenomena can be explained with the help of the interpolating Schrӧdinger equation proposed by Ghose. The nuclear quantum effect can be described by the tunneling of a harmonic oscillator in a symmetric double-well potential, and an ensemble of harmonic oscillators can model the LDL-HDL oscillations. The thermodynamics of such harmonic oscillators has been worked out showing continuous transitions between the quantum and classical limits. [ABSTRACT FROM AUTHOR]

Purpose: Demand for Environmental Product Declarations (EPDs) is already high and increasing in the construction and building sectors. The overall purpose of EPDs is comparability of product environmental performance, and they are thus developed in accordance with product category rules (PCRs): requirements and guidelines for how to make EPDs for one or more product groups. Since several organisations publish PCRs, there is a risk of creating conflicting rules leading to inconsistencies and jeopardising the objective of comparability. Methods: This study analyses the causes for inconsistency and the consequences in terms of difference in the results across the life cycle assessment (LCA) models underlying the EPDs. Taking four EPD programmes and their actors as cases, first a document analysis was conducted to identify qualitative and quantitative differences in their guidelines. Further focusing on selected quantitative differences, a series of LCA models were designed for the same triple-glazed window product by adhering to the PCRs of each operator, to highlight the differences in results that occur when performing the same assessment via different but all formally selectable operators and compliant EPDs. Results and discussion: Results show that the EPD of a specific product can return very different impact scores if one or the other guideline is followed. Results can vary more than 10% from the base scenarios, what we consider a significant variation. This is observed across all impact categories. Focusing specifically on the climate change impact, the results show that differences are due to the choice of energy mix, reference service life and other parameters. It is thus the combination of several modelling differences that leads to a overall divergence in results, rather than one single methodological choice. Conclusions: Numerous different but at the same time compliant EPDs can be obtained for the same product, highlighting a serious harmonisation issue within the EPD system. EPDs are thus not necessarily accurate, and it remains doubtful whether EPD comparability can be achieved. This weakness of the EPD system can in the worst case be exploited by producers to obtain lower results and undermines the system. Recommendations: Besides recommending using LCA for learning and process improvement rather than just for external communication and compliance, to increase harmonisation in the EPD system, we recommend limiting the number of product-specific PCRs (e.g. complementary PCRs), align default values, learn from verification, use just one background database, increase transparency and move towards one centralized operator. [ABSTRACT FROM AUTHOR]

Purpose of Review: The treatment of stage III N2 non-small cell lung cancer (NSCLC) remains debated. There is an absence of a universally agreed definition of resectability for this heterogeneous group and a lack of trial data. Recent Findings: We reviewed and compared current international guidelines and evidence surrounding management of stage III N2 NSCLC. The Irish and Australian guidelines advise subcategorising N2 disease into N2a (may be resectable) and N2b (never resectable). On the contrary, American and British guidelines avoid subcategorising N2 disease, emphasising importance of local MDT decisions. It is suggested that evidence for resection of stage III tumours is relatively weak, but that stage IIIA should generally be considered for resection, and stage IIIB is not recommended for resection. For resectable disease, surgery may be combined with neoadjuvant chemoimmunotherapy, or adjuvant chemotherapy followed by immunotherapy and radiotherapy in selected patients. Summary: There is some evidence that technically resectable disease can be treated solely with radiotherapy with similar outcomes to resection. In the event of unresectable disease, chemoradiotherapy has been the traditional management option. However, recent studies with chemoradiotherapy alongside immunotherapy appear promising. There are many factors that influence the treatment pathway offered to patients with stage III N2 NSCLC, including patient factors, team expertise, and local resources. Therefore, the role of MDTs in defining resectability and formulating an individualised treatment plan is crucial. [ABSTRACT FROM AUTHOR]

The Asian small-clawed otter (Aonyx cinereus) is a globally vulnerable mesopredator endemic to South and Southeast Asia. This species is one of the least studied and smallest of all 13 otter species. The species is tolerant of least-aquatic conditions and reported across a wide range of habitats. Its ecology is not fully and methodically deciphered. Recently, new populations were discovered in eastern Bangladesh, the north-western border of the Indo-Burma Biodiversity Hotspot. Based on camera trapping carried out between January and July 2021, we investigated otter occupancy and spatiotemporal coexistence within an anthropized riparian mixed-evergreen forest. We assessed the influence of stream density, the distance between the camera-trap station and the nearest built-up area, and slope on otter habitat use; cumulated precipitation and Julian day on detection probability. Our results revealed a mammalian mesopredator release effect and heavy anthropogenic activities; however, otters and humans exhibited very low spatiotemporal overlap. Detections showed high temporal convergence with the nocturnal-crepuscular carnivore guild. Otter occupancy did not show any pattern when modelled with altitude or human density; detection neither decreased with the progression of the monsoon. Our findings suggest that otters can adapt their habitat use to human pressure in forests dominated by human activities, especially with dense stream networks. We encourage further research to gain a better understanding of the factors that could impact otter habitat preference, such as food abundance, undergrowth vegetation, human-induced forest fires, and fishing or poaching pressure. Understanding otters is a potential tool to step up research investment in anthropized forests. [ABSTRACT FROM AUTHOR]

Li metal batteries using Li metal as negative electrode and LiNi1-x-yMnxCoyO2 as positive electrode represent the next generation high-energy batteries. A major challenge facing these batteries is finding electrolytes capable of forming good interphases. Conventionally, electrolyte is fluorinated to generate anion-derived LiF-rich interphases. However, their low ionic conductivities forbid fast-charging. Here, we use CsNO3 as a dual-functional additive to form stable interphases on both electrodes. Such strategy allows the use of 1,2-dimethoxyethane as the single solvent, promising superior ion transport and fast charging. LiNi1-x-yMnxCoyO2 is protected by the nitrate-derived species. On the Li metal side, large Cs+ has weak interactions with the solvent, leading to presence of anions in the solvation sheath and an anion-derived interphase. The interphase is surprisingly dominated by cesium bis(fluorosulfonyl)imide, a component not reported before. Its presence suggests that Cs+ is doing more than just electrostatic shielding as commonly believed. The interphase is free of LiF but still promises high performance as cells with high LiNi0.8Mn0.1Co0.1O2 loading (21 mg/cm2) and low N/P ratio (~2) can be cycled at 2C (~8 mA/cm2) with above 80% capacity retention after 200 cycles. These results suggest the role of LiF and Cs-containing additives need to be revisited. Fluorinated interphases are often pursued as a design strategy for Li metal batteries. In contrast, here the authors show that an electrolyte with a non-fluorinated solvent and CsNO3 additive results in an LiF-free but inorganic-rich interphase that enables fast-charging of Li metal batteries. [ABSTRACT FROM AUTHOR]

Accurate and in-time prediction of crop yield plays a crucial role in the planning, management, and decision-making processes within the agricultural sector. In this investigation, utilizing area under irrigation (%) as an exogenous variable, we have made an exertion to assess the suitability of different hybrid models such as ARIMAX (Autoregressive Integrated Moving Average with eXogenous Regressor)–TDNN (Time-Delay Neural Network), ARIMAX–NLSVR (Non-Linear Support Vector Regression), ARIMAX–WNN (Wavelet Neural Network), ARIMAX–CNN (Convolutional Neural Network), ARIMAX–RNN (Recurrent Neural Network) and ARIMAX–LSTM (Long Short Term Memory) as compared to their individual counterparts for yield forecasting of major Rabi crops in India. The accuracy of the ARIMA model has also been considered as a benchmark. Empirical outcomes reveal that the ARIMAX–LSTM hybrid modeling combination outperforms all other time series models in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE) values. For these models, an average improvement of RMSE and MAPE values has been observed to be 10.41% and 12.28%, respectively over all other competing models and 15.83% and 18.42%, respectively over the benchmark ARIMA model. The incorporation of the area under irrigation (%) as an exogenous variable in the ARIMAX framework and the inbuilt capability of the LSTM model to process complex non-linear patterns have been observed to significantly enhance the accuracy of forecasting. The performance supremacy of other hybrid models over their individual counterparts has also been evident. The results also suggest avoiding any performance generalization of individual models for their hybrid structures. [ABSTRACT FROM AUTHOR]

Helicobacter pylori (H. pylori) infection is the principal cause of chronic gastritis, gastric ulcers, duodenal ulcers, and gastric cancer. In clinical practice, diagnosis of H. pylori infection by a gastroenterologists' impression of endoscopic images is inaccurate and cannot be used for the management of gastrointestinal diseases. The aim of this study was to develop an artificial intelligence classification system for the diagnosis of H. pylori infection by pre-processing endoscopic images and machine learning methods. Endoscopic images of the gastric body and antrum from 302 patients receiving endoscopy with confirmation of H. pylori status by a rapid urease test at An Nan Hospital were obtained for the derivation and validation of an artificial intelligence classification system. The H. pylori status was interpreted as positive or negative by Convolutional Neural Network (CNN) and Concurrent Spatial and Channel Squeeze and Excitation (scSE) network, combined with different classification models for deep learning of gastric images. The comprehensive assessment for H. pylori status by scSE-CatBoost classification models for both body and antrum images from same patients achieved an accuracy of 0.90, sensitivity of 1.00, specificity of 0.81, positive predictive value of 0.82, negative predicted value of 1.00, and area under the curve of 0.88. The data suggest that an artificial intelligence classification model using scSE-CatBoost deep learning for gastric endoscopic images can distinguish H. pylori status with good performance and is useful for the survey or diagnosis of H. pylori infection in clinical practice. [ABSTRACT FROM AUTHOR]

This study uses geospatial modeling and Multi-Criteria Decision Analysis (MCDA) to assess the Groundwater Potential Zones (GPZs) in Cachar District, India. Twelve influencing factors, namely Geomorphology, geology, soil type, Land Use Land Cover (LULC), rainfall, slope, drainage density, lineament density, elevation, aspect, Topographic Ruggedness Index (TRI), and Topographic Wetness Index (TWI), are considered, and thematic maps are prepared in Geographical Information System (GIS) platform. To measure the weightages of these factors, Analytical Hierarchical Process (AHP) and Best Worst Method (BWM) are the MCDA techniques used. The GPZs are generated using weights and reclassified into low, medium, and high zones. The major portion of the region is classified as the medium potential zone, with 64.25% and 63.96% of the total area using AHP and BWM, respectively. The validation with groundwater data for the two GPZ maps reveals that 10 out of 12 locations have been predicted accurately. BWM, with a lesser comparison matrix, performed as efficiently as AHP and has proven to be a better MCDA technique in spatial modeling GPZ for sustainable groundwater conservation. [ABSTRACT FROM AUTHOR]

The paper contributes the literature in the following ways: (a) It establishes negative sole impact of urban outdoor air-pollution and its interaction-effect with growth, poverty, and urbanisation on female life-expectancy (FLE), hence on female labour force participation rate (FLFPR); proving the positive two-way relation between these two through estimating a simultaneous panel-model comprising equations of FLFPR and FLE, for Indian-states over the period 2017–2022. The significant impact of the interaction-effect shows partial-effect of a change in the concerned variable on FLE and on FLFPR depends on air-pollution. Thus, measures to raise growth, urbanisation or reduce poverty can improve FLE and FLFPR, provided air-pollution is mitigated. (b) Moreover, significant impact of interaction-effect of household-size and growth (Lnnsdp × HHsz) on FLFPR is supported, i.e., the impact of growth on FLFPR depends on household-size and vice-versa. A critical-level of Lnnsdp × HHsz exists; FLFPR increases/falls with Lnnsdp × HHsz according as actual Lnnsdp × HHsz is lesser/higher than critical-level. The higher sample-mean of Lnnsdp × HHsz than critical-value implies FLFPR falls with both growth and household-size, i.e. given household-size, income-effect dominates and women value leisure more. It adds the earlier inverted-U feminisation hypothesis for India investigating only sole-impact of growth on FLFPR. (c) Further, the relationship between interaction-effect of female education and household-size (Hedu × HHsz) on FLFPR is U-type, i.e., a critical level of Hedu × HHsz exists, FLFPR falls/rises with Hedu × HHsz according as actual Hedu × HHsz is lesser/higher than critical-level. The lower sample-mean of Hedu × HHsz than critical-value implies, FLFPR falls with education and household-size, i.e., female education does not necessarily imply higher FLFPR. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of Unmanned Aircraft System Traffic Management (UTM), which refers to an air transportation system wherein unmanned aircraft systems (UAS) are used to deliver small payloads on-demand by safely maneuvering in the low-altitude known urban infrastructure inhabited by dynamic air traffic. A multi-stage framework based on numerical potential fields is proposed for establishing UTM in the non-segregated airspace. Numerical potential fields are adopted for global path planning as they provide optimum stand-off clearance from obstacles in the environment. The proposed global path planning approach is augmented with a prediction-based zone determination algorithm to minimize high-density air traffic encounters by the UAS. In the event of low-density traffic in the vicinity of the UAS, the UAS neighborhood is sectorized into octants. An octant-based local collision avoidance strategy generates force fields that divert the UAS into a vacant octant. Extensive simulations have been carried out to show the efficacy of the proposed method in dense urban settings. [ABSTRACT FROM AUTHOR]

Purpose: The objective of the current research is to formulate a nanoemulsion (NE) of nimodipine (ND) to improve its oral bioavailability and stability by adopting a scientific and systematic quality-by-design (QbD) approach. Methods: Triacetin (oil), Cremophor RH40 (surfactant), and PEG600 (co-surfactant) were selected to formulate NE. Factors affecting critical quality attributes (CQA) were screened by Taguchi design followed by Box-Behnken design (BBD) enabled optimization. The optimized NE was further lyophilized with trehalose (cryoprotectant) to improve the storage stability. Results: Optimized NE (F4), and its lyophilized NE showed globule size less than 200 nm with more than 75% drug diffusion within 30 min. Both NE (F4) and its lyophilized NE exhibited a fivefold increase in area under the curve in comparison to an aqueous dispersion of ND. Lyophilized F4 showed better stability due to the conversion of NE into solid form by lyophilization. Conclusion: Lyophilized NE of ND can be prepared for improved oral bioavailability and stability. The above approach is simple, cost-effective, and scalable to manufacture on a commercial scale. [ABSTRACT FROM AUTHOR]

Purpose: Ultrasound is often the preferred modality for image-guided therapy or treatment in organs such as liver due to real-time imaging capabilities. However, the reduced conspicuity of tumors in ultrasound images adversely impacts the precision and accuracy of treatment delivery. This problem is compounded by deformable motion due to breathing and other physiological activity. This creates the need for a fusion method to align interventional US with pre-interventional modalities that provide superior soft-tissue contrast (e.g., MRI) to accurately target a structure-of-interest and compensate for liver motion. Method: In this work, we developed a hybrid deformable fusion method to align 3D pre-interventional MRI and 3D interventional US volumes to target the structures-of-interest in liver accurately in real-time. The deformable multimodal fusion method involved an offline alignment of a pre-intervention MRI with a pre-intervention US volume using a traditional registration method, followed by real-time prediction of deformation using a trained deep-learning model between interventional US volumes across different respiratory states. This framework enables motion-compensated MRI-US image fusion in real-time for image-guided treatment. Results: The proposed hybrid deformable registration method was evaluated on three healthy volunteers across the pre-intervention MRI and 20 US volume pairs in the free-breathing respiratory cycle. The mean Euclidean landmark distance of three homologous targets in all three volunteers was less than 3 mm for percutaneous liver procedures. Conclusions: Preliminary results show that clinically acceptable registration accuracies for near real-time, deformable MRI-US fusion can be achieved by our proposed hybrid approach. The proposed combination of traditional and deep-learning deformable registration techniques is thus a promising approach for motion-compensated MRI-US fusion to improve targeting in image-guided liver interventions. [ABSTRACT FROM AUTHOR]

Mitochondrial dysfunction and oxidative stress are critical to neurodegeneration in Parkinson's disease (PD). Mitochondrial dysfunction in PD entails inhibition of the mitochondrial complex I (CI) in the dopaminergic neurons of substantia nigra. The events contributing to CI inhibition and downstream pathways are not completely elucidated. We conducted proteomic analysis in a dopaminergic neuronal cell line exposed individually to neurotoxic CI inhibitors: rotenone (Rot), paraquat (Pq) and 1-methyl-4-phenylpyridinium (MPP+). Mass spectrometry (MS) revealed the involvement of biological processes including cell death pathways, structural changes and metabolic processes among others, most of which were common across all models. The proteomic changes induced by Pq were significantly higher than those induced by Rot and MPP+. Altered metabolic processes included downregulated mitochondrial proteins such as CI subunits. MS of CI isolated from the models revealed oxidative post-translational modifications with Tryptophan (Trp) oxidation as the predominant modification. Further, 62 peptides in 22 subunits of CI revealed Trp oxidation with 16 subunits common across toxins. NDUFV1 subunit had the greatest number of oxidized Trp and Rot model displayed the highest number of Trp oxidation events compared to the other models. Molecular dynamics simulation (MDS) of NDUFV1 revealed that oxidized Trp 433 altered the local conformation thereby changing the distance between the Fe-S clusters, Fe-S 301(N1a) to Fe-S 502 (N3) and Fe-S 802 (N4) to Fe-S 801 (N5), potentially affecting the efficiency of electron transfer. The events triggered by the neurotoxins represent CI damage, mitochondrial dysfunction and neurodegeneration in PD. [ABSTRACT FROM AUTHOR]

Mapping the human body at single cell resolution in three dimensions (3D) is important for understanding cellular interactions in context of tissue and organ organization. 2D spatial cell analysis in a single tissue section may be limited by cell numbers and histology. Here we show a workflow for 3D reconstruction of multiplexed sequential tissue sections: MATRICS-A (Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial - Analysis). We demonstrate MATRICS-A in 26 serial sections of fixed skin (stained with 18 biomarkers) from 12 donors aged between 32–72 years. Comparing the 3D reconstructed cellular data with the 2D data, we show significantly shorter distances between immune cells and vascular endothelial cells (56 µm in 3D vs 108 µm in 2D). We also show 10–70% more T cells (total) within 30 µm of a neighboring T helper cell in 3D vs 2D. Distances of p53, DDB2 and Ki67 positive cells to the skin surface were consistent across all ages/sun exposure and largely localized to the lower stratum basale layer of the epidermis. MATRICS-A provides a framework for analysis of 3D spatial cell relationships in healthy and aging organs and could be further extended to diseased organs. Multiplexed imaging and 3D analysis provides insights into cell interactions and effects of sun exposure in human skin. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) has become a prominent pollutant due to rapid economic development, urbanization, industrialization, and transport activities, which has serious adverse effects on human health and the environment. Many studies have employed traditional statistical models and remote-sensing technologies to estimate PM2.5 concentrations. However, statistical models have shown inconsistency in PM2.5 concentration predictions, while machine learning algorithms have excellent predictive capacity, but little research has been done on the complementary advantages of diverse approaches. The present study proposed the best subset regression model and machine learning approaches, including random tree, additive regression, reduced error pruning tree, and random subspace, to estimate the ground-level PM2.5 concentrations over Dhaka. This study used advanced machine learning algorithms to measure the effects of meteorological factors and air pollutants (NOX, SO2, CO, and O3) on the dynamics of PM2.5 in Dhaka from 2012 to 2020. Results showed that the best subset regression model was well-performed for forecasting PM2.5 concentrations for all sites based on the integration of precipitation, relative humidity, temperature, wind speed, SO2, NOX, and O3. Precipitation, relative humidity, and temperature have negative correlations with PM2.5. The concentration levels of pollutants are much higher at the beginning and end of the year. Random subspace is the optimal model for estimating PM2.5 because it has the least statistical error metrics compared to other models. This study suggests ensemble learning models to estimate PM2.5 concentrations. This study will help quantify ground-level PM2.5 concentration exposure and recommend regional government actions to prevent and regulate PM2.5 air pollution. [ABSTRACT FROM AUTHOR]

This review article aims to suggest recycling technological options in India and illustrates plastic recycling clusters and reprocessing infrastructure for plastic waste (PW) recycling in India. The study shows that a majority of states in India are engaged in recycling, road construction, and co-processing in cement kilns while reprocessing capabilities among the reprocessors are highest for polypropylene (PP) and polyethylene (PE) polymer materials. This review suggests that there are key opportunities for mechanical recycling, chemical recycling, waste-to-energy approaches, and bio-based polymers as an alternative to deliver impact to India's PW problem. On the other hand, overall, polyurethane, nylon, and polyethylene terephthalate appear most competitive for chemical recycling. Compared to conventional fossil fuel energy sources, polyethylene (PE), polypropylene (PP), and polystyrene are the three main polymers with higher calorific values suitable for energy production. Also, multi-sensor-based artificial intelligence and blockchain technology and digitization for PW recycling can prove to be the future for India in the waste flow chain and its management. Overall, for a circular plastic economy in India, there is a necessity for a technology-enabled accountable quality-assured collaborative supply chain of virgin and recycled material. [ABSTRACT FROM AUTHOR]

A computational model has been developed to study the effect of the tilt angle (15, 30, 45, and 60°) and pouring temperature (893, 903, 913, and 923 K) on the phase change behavior of the hypoeutectic binary alloy Al–7Si. The analysis has been done with the help of the obtained temperature field, solid fraction evolution, as well as the Si distribution and macrosegregation. The two-dimensional multiphase volume-averaging transient model is used for computational modeling, incorporating phase diagram information, enthalpy-updating scheme, composition–solid fraction coupling, and variation in the thermophysical properties inside a mushy zone. It is observed that the effect of the tilt angle on the cooling rate is much superior to the pouring temperature effect. Moreover, the formation of eutectic plateau and negative macrosegregation are observed near the surface of the tilted plate in the eutectic temperature zone. Negative macrosegregation becomes high near the exit of the tilted surface. [ABSTRACT FROM AUTHOR]

Background: Tumor necrosis factor-α (TNFα) is a pleiotropic cytokine involved in nuclear factor kappa B (NF-κB) mediated cell survival as well as cell death. High serum TNFα levels correlate with liver fibrosis and enhance hepatic stellate cell (HSC) viability. However, the regulatory role of cellular inhibitor of apoptosis-1/2 (cIAP1/2) during TNFα induced NF-κB signaling in activated HSCs is largely unknown. Method and Results: Activated HSCs were treated with cIAP1/2 inhbitiors i.e., SMAC mimetic BV6, and Birinapant in the presence of TNFα and macrophage conditioned media. TNFα cytokine increased cIAP2 expression and enhanced cell viability through the canonical NF-κB signaling in activated HSCs. cIAP2 inhibition via BV6 decreased the TNFα induced canonical NF-κB signaling, and reduced cell viability in activated HSCs. SMAC mimetic, Birinapant alone did not affect the cell viability but treatment of TNFα sensitized HSCs with Birinapant induced cell death. While BV6 mediated cIAP2 ablation was able to decrease the TNFα induced canonical NF-κB signaling, this effect was not observed with Birinapant treatment. Secreted TNFα from M1 polarized macrophages sensitized activated HSCs to BV6 or Birinapant mediated cell death. However, M2 polarized macrophage conditioned medium rescued the activated HSCs from BV6 mediated cytotoxicity. Conclusion: In this study, we describe the regulatory role of cIAP2 in TNFα induced NF-κB signaling in activated HSCs. Targeting cIAP2 may be a promising approach for liver fibrosis treatment via modulating NF-κB signaling in activated HSCs. [ABSTRACT FROM AUTHOR]

Purpose: To describe the risk factors, clinical features and management outcomes of ocular surface squamous neoplasia (OSSN) with 360° of limbal involvement (360-OSSN) and compare with segmental limbal involvement (SL-OSSN). Methods: Retrospective comparative study of 360-OSSN vs SL-OSSN. All 360-OSSN and every 10th patient with SL-OSSN during the study period (2012–2020) were included. Lesions with uncertain diagnosis were excluded. Results: Of 1250 patients diagnosed with OSSN during the study period, 30 (2%) had 360-OSSN. A total of 100 patients of OSSN with SL-OSSN were included for comparison. 360-OSSN patients more often had longer duration of symptoms (mean, 17 vs 8 months; p, 0.003), prior misdiagnosis (17% vs 6%, p, 0.13) and prior intervention (47% vs 13%; p, 0.0002) than patients with SL-OSSN. 360-OSSN had higher incidence of scleral fixity (57% vs 16%; p < 0.0001), corneal/scleral melt (17% vs 0%; p, 0.0005), intraocular tumor extension (17% vs 0%; p, 0.003), orbital tumor extension (33% vs 1%; p < 0.0001), and advanced T stage at presentation (Tis: 37% vs 76%, T1: 0% vs 15%; T2: 7% vs 4%; T3: 27% vs 4%; T4: 30% vs 1%; p < 0.001). Over a mean follow-up of 14 months, lymph node metastasis (8% vs 0%; p, 0.05) and distant metastasis (4% vs 0%; p, 0.23) were more common in 360-OSSN group compared to SL-OSSN group. Conclusion: Risk factors of 360-OSSN include prolonged symptoms, prior misdiagnosis and prior intervention. It represents an advanced form of disease with propensity for corneo-scleral melt and invasive disease which requires aggressive management. [ABSTRACT FROM AUTHOR]

Successful implementation of efficient mobility management techniques is critical to the success of next-generation wireless systems. Handoff management has become more critical in present wireless networks, to support multimedia communications and associated services. This paper intends to study the handoff management aspect of the general mobility management issue which is prevailing in wireless networks. Multilayer mobility management models such as Hierarchical Mobile IPv6 (HMIPv6) and flatter architectures like Proxy Mobile IPv6 have great potential to serve as a mobility management solution for the next-generation networks. Influenced by the advantages of layered mobility management architectures, in this paper, a Three Layered MIPv6 (TLMIPv6) model has been examined for its performance against various parameters like signaling load, packet delivery ratio, end-to-end delay, packet delivery overhead, jitter, bandwidth consumption, throughput, etc. Execution of TLMIPv6 has been contrasted and that of HMIPv6 and PMIPv6 under Random Walk Mobility and Gauss-Markov Mobility models. It is seen from the experimental results that the TLMIPv6 protocol exhibits more than 15% reduction in signaling cost for handoff frequencies greater than 7/sec and more than 20% reduction in end-to-end delay for hop distances above 18, in comparison to HMIPv6 under identical simulation scenarios. The future scopes of the work are outlined. [ABSTRACT FROM AUTHOR]

N-glycosylation is implicated in cancers and aberrant N-glycosylation is recognized as a hallmark of cancer. Here, we mapped and compared the site-specific N-glycoproteomes of colon cancer HCT116 cells and isogenic non-tumorigenic DNMT1/3b double knockout (DKO1) cells using Fbs1-GYR N-glycopeptide enrichment technology and trapped ion mobility spectrometry. Many significant changes in site-specific N-glycosylation were revealed, providing a molecular basis for further elucidation of the role of N-glycosylation in protein function. HCT116 cells display hypersialylation especially in cell surface membrane proteins. Both HCT116 and DKO1 show an abundance of paucimannose and 80% of paucimannose-rich proteins are annotated to reside in exosomes. The most striking N-glycosylation alteration was the degree of mannose-6-phosphate (M6P) modification. N-glycoproteomic analyses revealed that HCT116 displays hyper-M6P modification, which was orthogonally validated by M6P immunodetection. Significant observed differences in N-glycosylation patterns of the major M6P receptor, CI-MPR in HCT116 and DKO1 may contribute to the hyper-M6P phenotype of HCT116 cells. This comparative site-specific N-glycoproteome analysis provides a pool of potential N-glycosylation-related cancer biomarkers, but also gives insights into the M6P pathway in cancer. Comparative site-specific N-glycoproteome analysis of tumorigenic and non-tumorigenic colon cancer cells provides a pool of potential N-glycosylation related cancer biomarkers and insights into the mannose-6-phosphate pathway in cancer. [ABSTRACT FROM AUTHOR]