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Abdominal pain, including visceral pain, is prevalent in functional gastrointestinal (GI) disorders (FGIDs), affecting the overall quality of a patient's life. Neural circuits in the brain encode, store, and transfer pain information across brain regions. Ascending pain signals actively shape brain dynamics; in turn, the descending system responds to the pain through neuronal inhibition. Pain processing mechanisms in patients are currently mainly studied with neuroimaging techniques; however, these techniques have a relatively poor temporal resolution. A high temporal resolution method is warranted to decode the dynamics of the pain processing mechanisms. Here, we reviewed crucial brain regions that exhibited pain-modulatory effects in an ascending and descending manner. Moreover, we discussed a uniquely well-suited method, namely extracellular electrophysiology, that captures natural language from the brain with high spatiotemporal resolution. This approach allows parallel recording of large populations of neurons in interconnected brain areas and permits the monitoring of neuronal firing patterns and comparative characterization of the brain oscillations. In addition, we discussed the contribution of these oscillations to pain states. In summary, using innovative, state-of-the-art methods, the large-scale recordings of multiple neurons will guide us to better understanding of pain mechanisms in FGIDs. [ABSTRACT FROM AUTHOR]

Pyrazole, an important pharmacophore and a privileged scaffold of immense significance, is a five-membered heterocyclic moiety with an extensive therapeutic profile, viz., anti-inflammatory, anti-microbial, anti-anxiety, anticancer, analgesic, antipyretic, etc. Due to the expansion of pyrazolecent red pharmacological molecules at a quicker pace, there is an urgent need to put emphasis on recent literature with hitherto available information to recognize the status of this scaffold for pharmaceutical research. The reported potential pyrazole-containing compounds are highlighted in the manuscript for the treatment of cancer and inflammation, and the results are mentioned in % inhibition of inflammation, % growth inhibition, IC50, etc. Pyrazole is an important heterocyclic moiety with a strong pharmacological profile, which may act as an important pharmacophore for the drug discovery process. In the struggle to cultivate suitable anti-inflammatory and anticancer agents, chemists have now focused on pyrazole biomolecules. This review conceals the recent expansion of pyrazole biomolecules as anti-inflammatory and anticancer agents with an aim to provide better correlation among different research going around the world. [ABSTRACT FROM AUTHOR]

Graduate employability is a multifaceted concept considering the Sustainable Development Goals. Graduate employability and skills development are also significant determinants for future career success. Graduate employability has seen more sweeping emphasis and concerns in national and global job markets, due to the ever-rising number of unemployed people, which has increased even more due to COVID-19. Due to its importance, this study investigates the current state of skill development initiatives in Bangladesh and the perceptions of university graduates regarding skill development for their future employability. This study uses mixed-method research. Data was collected through surveys and in-depth interviews; various probabilistic and non-probabilistic sample selection methods were used. A total of 437 participants responded to this study. After analysis, the data was shown descriptively. The empirical findings of this study demonstrated that university graduates are well-aware of the skill development requirements for their future employability. However, university graduates face many obstacles in acquiring these necessary skill development opportunities. Therefore, the government and relevant stakeholders must work together to alleviate the obstacles. Furthermore, this study includes recommendations that can assist in developing a model for skill development programs and initiatives in the country for university graduates to ensure their future employability. [ABSTRACT FROM AUTHOR]

Some (E)-3-(3-(4-(benzyloxy)phenyl)-1-phenyl-1H-pyrazol-4-yl)-1-phenylprop-2-en-1-one conjugates 5a–r were designed; synthesized; characterized by 1H, 13C NMR, and ESI-MS; and evaluated for tubulin polymerization inhibitory activity and in vitro cytotoxicity against breast (MCF-7), cervical (SiHa), and prostate (PC-3) cancer cell lines, as well as a normal cell line (HEK-293T). The compounds were also tested to determine their binding modes at the colchicine-binding site of tubulin protein (PDB ID-3E22), for in silico ADME prediction, for bioactivity study, and for PASS prediction studies. Among all the synthesized conjugates, compound 5o exhibited excellent cytotoxicity with an IC50 value of 2.13 ± 0.80 µM (MCF-7), 4.34 ± 0.98 µM (SiHa), and 4.46 ± 0.53 µM (PC-3) against cancer cell lines. The compound did not exhibit significant toxicity to the HEK cells. Results of the in silico prediction revealed that the majority of the conjugates possessed drug-like properties. [ABSTRACT FROM AUTHOR]

The severity and frequency of extremes are changing; thus, it is becoming necessary to evaluate the impacts of land cover changes and urbanisation along with climate change. A framework of the Generalised Extreme Value (GEV) method, Google Earth Engine (GEE), and land cover patterns' classification including Random Forest (RF) and Support Vector Machine (SVM) can be useful for streamflow impact analysis. For this study, we developed a unique framework consisting of a hydrological model in line with the Process-informed Nonstationary Extreme Value Analysis (ProNEVA) GEV model and an ensemble of General Circulation Models (GCMs), mapping land cover patterns using classification methods within the GEE platform. We applied these methods in Southeast Queensland (SEQ) to analyse the maximum instantaneous floods in non-stationary catchment conditions, considering the physical system in terms of cause and effect. Independent variables (DEM, population, slope, roads, and distance from roads) and an integrated RF, SVM methodology were utilised as spatial maps to predict their influences on land cover changes for the near and far future. The results indicated that physical factors significantly influence the layout of landscapes. First, the values of projected evapotranspiration and rainfall were extracted from the multi-model ensemble to investigate the eight GCMs under two climate change scenarios (RCP4.5 and RCP8.5). The AWBM hydrological model was calibrated with daily streamflow and applied to generate historical runoff for 1990–2010. Runoff was projected under two scenarios for eight GCMs and by incorporating the percentage of each land cover into the hydrological model for two horizons (2020–2065 and 2066–2085). Following that, the ProNEVA model was used to calculate the frequency and magnitude of runoff extremes across the parameter space. The maximum peak flood differences under the RCP4.5 and RCP8.5 scenarios were 16.90% and 15.18%, respectively. The outcomes of this study suggested that neglecting the non-stationary assumption in flood frequency can lead to underestimating the amounts that can lead to more risks for the related hydraulic structures. This framework is adaptable to various geographical regions to estimate extreme conditions, offering valuable insights for infrastructure design, planning, risk assessment, and the sustainable management of future water resources in the context of long-term water management plans. [ABSTRACT FROM AUTHOR]

Orange fleshed sweet potatoes (OFSP) are desirable for high productivity and profitability and their distribution to improve the nutrition of river bank inhabitants of Gaibandha and Rangpur districts of Bangladesh. In this context, a field trial was conducted in two riverbank-based farmers' fields such as Saghata, Gaibandha, and Pirganj, Rangpur, particularly in the Active Tista Floodplain Agro-ecological Zone of Bangladesh. Four OFSP varieties were evaluated, i.e., G1: BARI SP-8; G2: BARI SP-12; G3: BARI SP-14; G4: BARI SP-15, along with one local cultivar as a control (Red skin with white flesh). Significant variations among the sweet potato genotypes were noted for a number of tuberous roots plant−1, length of root diameter of roots, tuberous root weight plant−1, root yield (fresh), root yield (dry), beta-carotene yield, as well as energy output. Over the locations, BARI SP-12 produced about 73% higher root yield (32.00 t ha−1) and it was like the BARI SP-8 (31.07 t ha−1), which produced about 68% higher yield in comparison with local cultivar (18.51 t ha−1). Across the location, BARI SP-8 performed better in root yield (31.89 t ha−1) in Gaibandha, 69% superior to local cultivar, whereas BARI SP-12 performed better in Rangpur (33.66 t ha−1), which was 86% greater than the local sweet potato cultivar. Considering the root dry yield production, BARI SP-8 produced the highest in the Gaibandha location after that Rangpur location. Further, BARI SP-14 had wider adaptability and stability over the year and location depended on the AMMI model. The beta carotene yield (Vitamin-A precursor) ranged 336–2957 kg ha−1 among the OFSP varieties, whereas the highest (2957 kg ha−1) carotene was recorded in BARI SP-14, similar to BARI SP-15 (2952 kg ha−1) but was much lower in BARI SP-8 and BARI SP-12. Moreover, BARI SP-8 and BARI SP-12 were also economically profitable in terms of gross margin (3233 and 3364 US$ ha−1, respectively), net return (3039 and 3170 US$ ha−1, respectively) and BCR (3.21 and 3.31, respectively, vs. 1.91) due to higher returns with a similar production cost of the local cultivar. The results suggested that BARI SP-8 is economically profitable in the riverbank areas of Gaibandha, and BARI SP-12 is suitable for the riverbank areas of Rangpur. [ABSTRACT FROM AUTHOR]

Nutrient pollution is one of the major issues in water resources management, which has drawn significant investments into the development of many modelling tools to solve pollution problems worldwide. However, the situation remains unchanged, even likely to be exacerbated due to population growth and climate change. Effective measures to alleviate the issues are essential, dependent upon existing modelling tools' capacities. More complex models have been developed with technological advancement, though applications are mainly limited to academic reach. Hence, there is a need for a paradigm shift in policymaking that looks for a reliable modelling approach. This paper aims to assess the capacity of existing modelling tools in the context of process-based modelling and provide a future direction in research. The article has categorically divided models into plot scale to basin-wide applications for evaluation and discussed the pros and cons of conceptual and process-based modelling. The potential benefits of distributed modelling approach have been elaborated with highlights of a newly developed distributed model and its application in catchments in Japan and Australia. The distributed model is more adequate for predicting the realistic details of pollution problems in a changing environment. Future research needs to focus on more process-based modelling. [ABSTRACT FROM AUTHOR]

Cripto-1 is a glycophosphatidylinositol (GPI) anchored signaling protein of epidermal growth factor (EGF)-Cripto-1-FRL1-Cryptic (CFC) family and plays a significant role in the early developmental stages and in the different types of cancer cells, epithelial to mesenchymal transition and tumor angiogenesis. Previously, we have developed cancer stem cells (miPS-LLCcm) from mouse iPSCs by culturing them in the presence of conditioned medium of Lewis Lung Carcinoma (LLC) cells for four weeks. Nodal and Cripto-1 were confirmed to be expressed in miPS-LLCcm cells by quantitative reverse transcription PCR (rt-qPCR) implying that Cr-1 was required in maintaining stemness. To investigate the biological effect of adding exogenous soluble CR-1 to the cancer stem cells, we have prepared a C-terminally truncated soluble form of recombinant human CR-1 protein (rhsfCR-1), in which the GPI anchored moiety was removed by substitution of a stop codon through site-directed mutagenesis. rhsfCR-1 effectively suppressed the proliferation and sphere forming ability of miPS-LLCcm cells in a dose-dependent manner in the range of 0 to 5 µg/mL, due to the suppression of Nodal-Cripto-1/ALK4/Smad2 signaling pathway. Frequency of sphere-forming cells was dropped from 1/40 to 1/69 by rhsfCR-1 at 1 µg/mL. Moreover, rhsfCR-1 in the range of 0 to 1 µg/mL also limited the differentiation of miPS-LLCcm cells into vascular endothelial cells probably due to the suppression of self-renewal, which should reduce the number of cells with stemness property. As demonstrated by a soluble form of exogenous Cripto-1 in this study, the efficient blockade would be an attractive way to study Cripto-1 dependent cancer stem cell properties for therapeutic application. [ABSTRACT FROM AUTHOR]

Many watersheds are currently experiencing streamflow and water quality related problems that are caused by excess nitrogen. Given that weather is a major driver of nitrogen transport through watersheds, the objective of this study was to predict climate change impacts on streamflow and nitrogen export. A forest and pasture dominated watershed in North Carolina Piedmont region was used as the study area. A physically-based Soil and Water Assessment Tool (SWAT) model parameterized using geospatial data layers and spatially downscaled temperature and precipitation estimates from eight different General Circulation Models (GCMs) were used for this study. While temperature change predictions are fairly consistent across the GCMs for the study watershed, there is significant variability in precipitation change predictions across the GCMs, and this leads to uncertainty in the future conditions within the watershed. However, when the downscaled GCM projections were taken as a model ensemble, the results suggest that both high and low emission scenarios would result in an average increase in streamflow of 14.1% and 12.5%, respectively, and a decrease in the inorganic nitrogen export by 12.1% and 8.5%, respectively, by the end of the century. The results also show clear seasonal patterns with streamflow and nitrogen loading both increasing in fall and winter months by 97.8% and 50.8%, respectively, and decreasing by 20.2% and 35.5%, respectively, in spring and summer months by the end of the century. [ABSTRACT FROM AUTHOR]

The effective management of surface water bodies, such as rivers, lakes, and reservoirs, necessitates a comprehensive understanding of water quality status. Altered precipitation patterns due to climate change may significantly affect the water quality and influence treatment procedures. This study aims to identify the most suitable water quality prediction models for the assessment of the water quality status for three water supply reservoirs in Toowoomba, Australia. It employed four machine learning and two deep learning models for determining the Water Quality Index (WQI) based on five parameters sensitive to rainfall impact. Temporal WQI variations over a period of 22 years (2000–2022) are scrutinised across 4 seasons and 12 months. Through regression analysis, both machine learning and deep learning models anticipate WQI gauged by seven accuracy metrics. Notably, XGBoost and GRU yielded exceptional outcomes, showcasing an R2 value of 0.99. Conversely, Bidirectional LSTM (BiLSTM) demonstrated moderate accuracy with results hovering at 88% to 90% for water quality prediction across all reservoirs. The Coefficient of Efficiency (CE) and Willmott Index (d) showed that the models capture patterns well, while MAE, MAPE and RMSE provided good performance metrics for the RFR, XGBoost and GRU models. These models have provided valuable knowledge that can be utilised to assess the adverse consequences of extreme climate events such as shifts in rainfall patterns. These insights can be used to improve strategies for managing water bodies more effectively. [ABSTRACT FROM AUTHOR]

The frequency and severity of extremes, including extreme precipitation events, extreme evapotranspiration and extreme water storage deficit events, are changing. Thus, the necessity for developing a framework that estimates non-stationary conditions is urgent. The aim of this paper is to develop a framework using the geeSEBAL platform, Generalised Extreme Value (GEV) models and spatiotemporal analysis techniques that incorporate the physical system in terms of cause and effect. Firstly, the geeSEBAL platform has enabled the estimation of actual evapotranspiration (ETa) with an unprecedented level of spatial-temporal resolution. Following this, the Non-stationary Extreme Value Analysis (NEVA) approach employs the Bayesian method using a Differential Evolution Markov Chain technique to calculate the frequency and magnitude of extreme values across the parameter space. Station and global climate datasets have been used to analyse the spatial and temporal variation of rainfall, reference evapotranspiration (ETo), ETa and water storage (WS) variables in the Lockyer Valley located in Southeast Queensland (SEQ), Australia. Frequency analysis of rainfall, ETa, and water storage deficit for 14 stations were performed using a GEV distribution under stationary and non-stationary assumptions. Comparing the ETa, ETo and ERA5 rainfall with station data showed reasonable agreement as follows: Pearson correlation of 0.59–0.75 for ETa, RMSE of 45.23–58.56 mm for ETa, Pearson correlation of 0.96–0.97 for ETo, RMSE of 73.13–87.73 mm for ETo and Pearson correlation of 0.87–0.92 for rainfall and RMSE of 37.53–57.10 mm for rainfall. The lower and upper uncertainty bounds between stationary and non-stationary conditions for rainfall station data of Gatton varied from 550.98 mm (stationary) to 624.97 mm (non-stationary), and for ERA5 rainfall datasets, 441.30 mm (stationary) to 450.77 mm (non-stationary). The results demonstrate that global climate datasets underestimate the difference between stationary and non-stationary conditions by 9.47 mm compared to results of 73.99 mm derived from station data. Similarly, the results demonstrate less variation between stationary and non-stationary conditions in water storage, followed by a sharp variation in rainfall and moderate variation in evapotranspiration. The findings of this study indicate that neglecting the non-stationary condition in some hydrometeorological variables can lead to underestimating their amounts. This framework can be applied to any geographical area for estimating extreme conditions, providing valuable insights for infrastructure planning and design, risk assessment and disaster management. [ABSTRACT FROM AUTHOR]

Understanding the effects of global change and human activities on water supplies depends greatly on surface water dynamics. A comprehensive examination of the hydroclimatic variations at the transboundary level is essential for the development of any adaptation or mitigation plans to deal with the negative effects of climate change. This research paper examines the hydroclimatic factors that contribute to the desiccation of the Doosti Dam's basin in the transboundary area using multisensor satellite data from the Google Earth Engine (GEE) platform. The Mann–Kendall and Sens slope estimator test was applied to the satellite datasets to analyse the spatial and temporal variation of the hydroclimate variables and their trend over the transboundary area for 18 years from 2004 to 2021 (as the dam began operating in 2005). Statistical analysis results showed decreasing trends in temperature and an increase in rainfall with respect to station-observed available data. Evapotranspiration and irrigated area development followed the increasing pattern and a slight decrease in snow cover. The results confirmed a large expansion of the irrigated area, especially during the winter growing season. The increase in irrigated cultivated areas during both winter and summer seasons is possibly the main reason for the diversion of water to meet the irrigation requirements of the developed agriculture areas. The approach followed in this study could be applied to any location around the globe to evaluate the hydrological conditions and spatiotemporal changes in response to climate change, trend analysis and human activities. [ABSTRACT FROM AUTHOR]

In intensive crop production systems, sustainable agricultural development strives to find the balance between productivity and environmental impact. To reduce the N fertilizer-associated environmental risks of intensive cropping, sound agronomic and environmentally acceptable management practices are urgently needed. To attain high yields, improve soil health, and ensure economic return and N usage efficiency in conservation-based intensive agriculture, N management must be optimized, which has not yet been studied systematically in the mustard-boro rice-aman rice cropping pattern. During 2016/17, 2017/18, and 2018/19 cropping seasons in Bangladesh, cropping system experiments were conducted to investigate the interactive effects of tillage practices and nitrogen fertilizer rates on soil characteristics, crop productivity, and profitability under conservation agriculture (CA) systems. The trial featured two tillage systems: (i) conventional tillage (CT) and (ii) strip-tillage (ST). It also used three doses of N fertilizer: N1: 75% of the recommended N fertilizer dose (RND); N2: 100% of the RND; and N3: 125% of the RND. Each crop's experiment was set up in a split-plot design with three replications, with the main plot assigned tillage practices and the sub-plot assigned nitrogen fertilizer rates. For rice, neither the tillage systems nor the interactions between the tillage systems and N levels affected any of the growth parameters, yield, and yield components, but the N levels did. Across the tillage systems, the rice grain and straw yield were similar for the N levels of 100% RND and 125% RND, which were significantly higher than the N level of 75% RND. In mustard, the highest seed yield was recorded from the tillage system ST, with an N level of 125% RND, which was at par with the tillage system ST with 100% RND and CT with 125% RND. The highest system rice equivalent yield (SREY, 14.9 to 15.8 t ha−1) was recorded from the tillage system ST, with an N level of 125% RND, which was at par with the same tillage system with an N level of 100% RND. The soil penetration and bulk density (BD) were higher for the CT than the ST, but soil organic matter (OM), total nitrogen (TN), phosphorus (P), potassium (K), and boron (B) content were higher for the tillage system ST than the CT. Across N levels, the tillage system CT had a 2–4% higher production cost than the ST. Total production cost increased as N levels increased across all tillage systems. The tillage system ST with an N level of 125% RND had the highest system gross return and net profit, which was at par with the same tillage system with 100% RND. This study suggested that farmers should apply slightly higher N for the mustard-boro-aman rice systems for the first couple of years when commencing CA; however, after a few years of consistent CA practice, the N rate may be reduced. [ABSTRACT FROM AUTHOR]

Metastasis develops when cancer cells spread from the primary site of a malignant tumor to the surrounding and distant tissues, and it is the most critical problem in cancer treatment. Our group developed cancer stem cells (CSCs) from induced pluripotent stem cells (iPSCs) in the presence of a conditioned medium (CM) of cancer-derived cells. The CSCs were characterized by the formation of malignant tumors in vivo, followed by metastasis. In this study, CSCs converted from mouse iPSCs in the presence of CM from hepatocellular carcinoma (HCC) cell line Huh7 cells. These converted cells (miPS-Huh7cm cells) were established as the metastatic cells. The generated CSCs were injected into the liver or spleen of nude mice. Almost one month after transplantation, the tumors were excised, and the primary cultured cells derived from the malignant tumors and metastatic nodules were evaluated by stemness and metastatic markers to compare their differences. The miPS-Huh7cm cells exhibited metastatic potential, and efficiently formed malignant tumors with lung and/or liver lesions in vivo, whereas the injected miPS formed teratoma. The primary cultured cells derived from the malignant tumors and metastatic nodules sustained the expression of stemness markers, such as Nanog, Klf4 and c-Myc, and acquired cancer stem markers, such as CD90, CD44 and ALDH1. Simultaneously, the expression of metastatic markers, such as Slug, Twist1 and vimentin, in primary cells derived from the malignant tumors, was higher than in metastatic nodules. The CSCs derived from iPSCs, forming malignant tumors and displaying high metastasis, will provide a good animal model to study the mechanisms of metastasis. [ABSTRACT FROM AUTHOR]

"Combination therapy", which is a treatment modality combining two or more therapeutic agents, is considered a cornerstone of cancer therapy. The combination of anticancer drugs, of which functions are different from the other, enhances the efficiency compared to the monotherapy because it targets cancer cells in a synergistic or an additive manner. In this study, the combination of paclitaxel and sorafenib in low concentration was evaluated to target cancer stem cells, miPS-BT549cmP and miPS-Huh7cmP cells, developed from mouse induced pluripotent stem cells. The synergistic effect of paclitaxel and sorafenib on cancer stem cells was assessed by the inhibition of proliferation, self-renewal, colony formation, and differentiation. While the IC50 values of paclitaxel and sorafenib were approximately ranging between 250 and 300 nM and between 6.5 and 8 µM, respectively, IC50 of paclitaxel reduced to 20 and 25 nM, which was not toxic in a single dose, in the presence of 1 µM sorafenib, which was not toxic to the cells. Then, the synergistic effect was further assessed for the potential of self-renewal of cancer stem cells by sphere formation ability. As a result, 1 µM of sorafenib significantly enhanced the effect of paclitaxel to suppress the number of spheres. Simultaneously, paclitaxel ranging in 1 to 4 nM significantly suppressed not only the colony formation but also the tube formation of the cancer stem cells in the presence of 1 µM sorafenib. These results suggest the combination therapy of paclitaxel and sorafenib in low doses should be an attractive approach to target cancer stem cells with fewer side effects. [ABSTRACT FROM AUTHOR]

Paclitaxel (PTX) is one of the front-line drugs approved for the treatment of ovarian cancer. However, the application of PTX is limited due to the significant hydrophobicity and poor pharmacokinetics. We previously reported target-directed liposomes carrying tumor-selective conjugated antibody and encapsulated glycosylated PTX (gPTX-L) which successfully overcome the PTX limitation. The tubulin stabilizing activity of gPTX was equivalent to that of PTX while the cytotoxic activity of gPTX was reduced. In human ovarian cancer cell lines, SK-OV-3 and OVK18, the concentration at which cell growth was inhibited by 50% (IC50) for gPTX range from 15–20 nM, which was sensitive enough to address gPTX-L with tumor-selective antibody coupling for ovarian cancer therapy. The cell membrane receptor CD44 is associated with cancer progression and has been recognized as a cancer stem cell marker including ovarian cancer, becoming a suitable candidate to be targeted by gPTX-L therapy. In this study, gPTX-loading liposomes conjugated with anti-CD44 antibody (gPTX-IL) were assessed for the efficacy of targeting CD44-positive ovarian cancer cells. We successfully encapsulated gPTX into liposomes with the loading efficiency (LE) more than 80% in both of gPTX-L and gPTX-IL with a diameter of approximately 100 nm with efficacy of enhanced cytotoxicity in vitro and of convenient treatment in vivo. As the result, gPTX-IL efficiently suppressed tumor growth in vivo. Therefore gPTX-IL could be a promising formulation for effective ovarian cancer therapies. [ABSTRACT FROM AUTHOR]