Forest loss is a major environmental threat in the Anthropocene. Repercussions are rarely localised and often impacts adjacent ecosystems. For example, forest loss is generally detrimental to freshwater biodiversity. There are however, some uncertainties about its effects on food webs and ecosystem functioning. We tracked changes in the food webs of four tropical stream catchments (two time points separated by a ~20-year interval) affected by varying degrees of forest loss. Our data show that the proportion of assimilated terrestrial organic matter (allochthony) remained largely invariant, but changes in food chain lengths inferred from the trophic positions of apex predators (TP) differed between catchments. Here, we found that higher rates of forest loss resulted in more significant reductions in TP. We speculate that the mechanisms involved are unrelated to diminished terrestrial subsidies as allochthony values were low (~7%) and did not shift in response to forest loss.

Background and Purpose To identify differentially expressed peptides in cerebrospinal fluid (CSF) of neonates with hypoxic-ischemic brain injury (HIBD) or controls, which may give a foundation for finding new promising drugs of neonatal HIBD. Experimental Approach CSF samples were collected from neonates with HIBD (n=4) or controls (n=4). ITRAQ LC-MS/MS was used to identify differentially expressed peptides between two groups. Effects of the peptide from heat shock protein 90-alpha (HSP90α/HSP90AA1) on cell viability and pyroptosis under oxygen and glucose deprivation (OGD) were analyzed using cell counting kit-8 (CCK-8) assay and Annexin V-fluorescein isothiocyanate (FITC) Assay. Expressions of NLRP3, ASC and Caspase-1 were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. Key Results Compared with the control group, one peptide significantly up-regulated and thirty-four peptides significantly down-regulated in the CSF of neonates with HIBD. A fragment of HSP90α/HSP90AA1 is the 2671.5Da peptide (HSQFIGYPITLFVEKER), one of the down-regulated peptides in neonatal HIBD. This peptide, we named it HIBDAP, inhibited pyroptosis of PC12 cells under OGD by suppressing expressions of NLRP3, ASC and Caspase-1. Conclusion and Implications The results of our study identified the characterization and expression profiles of peptides in CSF of neonatal HIBD. Several meaningful peptides such as HIBDAP may play significant roles in neonatal HIBD and may provide new therapeutic targets for neonatal HIBD.

Bio-cementation, or microbially induced calcite precipitation (MICP), has been shown to mitigate sand erosion; however, only few studies have used it on loess. This study used MICP to investigate the effects of this technology on the improvement of the surface erosion resistance of a loess-slope. Polyvinyl acetate (PVAc) was added to the cementation solution to further increase slope stability. The obtained results showed that MICP treatment resulted in an improvement of erosion resistance and treatment with 6 L/m2 of mixed solution achieved the best erosion control and highest surface strength. However, the loss of soil in MICP treated slopes still remained large. After adding PVAc to the cementation solution, the stability of the loess-slope increased significantly and resulted in less soil loss and increased surface strength. With 60 g/L PVAc, the surface strength of the slope decreased compared with 40 g/L PVAc because of the thinner depth of cementation. The high erosion resistance of the slope with added PVAc could be attributed to (1) the stable spatial structure of precipitation, and (2) the stronger resistance to tension or shear force from PVAc. These results demonstrated that MICP-PVAc treatment significantly mitigated surface erosion of loess-slopes, which presents promising potential for application in the field.

Under very high phosphorus (P) supply, Ptilotus hyperaccumulates P without toxicity while Kennedia is intolerant. What physiological mechanisms underlie this difference? P. exaltatus and K. prostrata were grown in sandy soil with low- and high-P treatments. Under high P, both species hyperaccumulated P (>20 mg g–1) in leaves, and shoot dry weight was unchanged for P. exaltatus but decreased by >50% for K. prostrata. Under high P, both species preferentially accumulated leaf P as inorganic P but P. exaltatus preferentially allocated P to mesophyll cells and stored Ca as occasional crystals in specific lower mesophyll cells separate from P, while K. prostrata preferentially allocated P to epidermal and spongy mesophyll cells and co-located P and Ca in palisade mesophyll cells. Mesophyll cellular [P] correlated positively with potassium for both species and negatively with sulfur for P. exaltatus. High P tolerance arose from P and Ca allocation to different leaf cell types, formation of Ca crystals, and enhanced K and decreased S accumulation to balance high cellular [P]. Intolerance to high P arose from the co-location of Ca and P in palisade mesophyll cells. This study advances the understanding of leaf physiological mechanisms for high P tolerance in plants.

Objective: To investigate the learning curve of robot-assisted laparoscopy in early stage cervical cancer and quantify impact on oncological outcomes. Design: Observational cohort study. Setting: Tertiary referral centre with one surgical team. Population: All early stage cervical cancer patients treated consecutively with robot-assisted laparoscopy between 2007 and 2017. Methods: With multivariate risk-adjusted cumulative sum analysis (RA-CUSUM), we assessed the learning curve of robot-assisted laparoscopy of a single surgical team based on cervical cancer recurrence. Subsequently, a survival analysis was conducted comparing oncological outcomes of patients treated during different phases of the learning curve. Main Outcome Measures: Surgical proficiency based on recurrence, survival rates in the different learning phases. Results: 165 cervical cancers patients were operated by robot-assisted laparoscopy, with a median follow-up of 57 months (range 3-132 months). The RA-CUSUM analysis demonstrated two phases of the learning curve: a learning phase of 61 procedures (group 1) and an experienced phase representing the 104 procedures thereafter (group 2). The 5-year disease free survival was 80.2% in group 1 and 91.1% in group 2 (P = 0.040). Both the 5-year disease-specific survival and overall survival significantly increased after the learning phase. Conclusion: The learning phase of robot-assisted laparoscopy in early stage cervical cancer in this institutional cohort is at least 61 procedures, with higher survival rates in the patients treated thereafter. The learning curve of robot-assisted laparoscopy affects oncological outcomes and warrants more attention in the design of future studies. Funding: None. Keywords: Cervical cancer, robot-assisted laparoscopy, learning curve, RA-CUSUM, recurrence, survival.

Objective: To find out the preferred and actual mode of delivery of obstetricians’ own children. Design: Cross-sectional survey. Setting: Three Congresses of Gynecology and Obstetrics and four large maternity hospitals in Rio de Janeiro, Brazil. Population: Physicians who held a specialty degree in gynecology & obstetrics or were trainees in this specialty and worked in the state of Rio de Janeiro. Methods: Prevalence and 95% confidence interval. Main Outcome Measures: Preferred and actual mode of delivery for own children. Results: A total of 465 participants answered the questionnaire in the three Congresses and four maternity hospitals. Seventy six percent (95% CI 71 - 81) of the 262 participants who delivered at least one child had Caesarean for the first child. Seventy two percent (95% CI 68 - 76) claimed they would prefer a vaginal birth for their own children, but only a third of those (34%) delivered vaginally. Conclusions: In a group of well informed, socially privileged and empowered women (especially regarding childbirth decisions), the most common mode of delivery was Caesarean, not the natural vaginal birth. Thus, even for those who want to try and reduce the number of Caesareans, it appears that their success will demand broader strategies, than simply to focus on physicians perversely forcing (or talking into) powerless misinformed women to deliver through C-section; this narrative seems to be wrong, at least in the sample of women in our study. Tweetable Among obstetricians in Rio de Janeiro 76% had a Caesarean for their own children

Lawn is the primary vegetation utilized for urban sporting grounds and garden greenbelts. The N fertilizer addition induced higher N2O emission in various soils including the lawn soil, however, a key gap in knowledge lies in identifying the ecological consequences of the N2O emission and potentially associated microbial mechanisms. N2O is a product of microbial participation in nitrogen transformation processes, which is closely related to the use of nitrogen fertilizer. This study evaluated the effect of N fertilizer on N2O emissions and associated microbial mechanism in lawn soil through incubated experiment under different N application rates [300 kg ha yr-1 (N300), 225 kg ha yr-1 (N225), 150 kg ha yr-1 (N150) and control (N0)]. In addition, the contribution of different microbial communities to N2O emissions was quantified by combining biological inhibitors with high-throughput sequencing. The results indicated that N fertilizer addition induced higher N2O emissions in lawn soil, showed the highest in the N225 treatment. The contribution of fungi to N2O emissions was 45%, significantly higher than that of bacteria (31%). The dominant fungi in the lawn soil included Ascomycota, Basidiomycota, and Mucoromycota. N fertilizer significantly increased the relative abundance of Ascomycota and decreased the relative abundance of Basidiomycota. We found a positive correlation between N2O emission and Ascomycota through RDA analysis. The growth trend of Ascomycota during the four nitrogen fertilizer treatments was consistent with the N2O emission trend in lawn soil. N2O emissions reached their highest levels after the N225 treatment. The relative abundance of Pyrenochaetopsis, Myrothecium, and Humicola was positively correlated with N2O emission. Thus, Pyrenochaetopsis, Myrothecium, and Humicola were found to be the main functional microorganisms leading to N2O production in lawn soil. Our findings can deepen the understanding on N2O emission and associated microbial mechanism in lawn soil with N fertilization.

Decades of research have helped establish the positive relationships between species richness and ecosystem biomass. However, species richness or related taxonomic metrics do not fully capture the functional differences between species, nor are they sufficient to reflect overall stand complexity. Further, the relative importance of structural diversity, functional trait dominance and diversity for stand biomass is still controversial, especially in multispecies stands with differential intra- and interspecific functional and structural patterns. In this study, we used plot level floristic and functional trait data in mixed-species plantations in West Africa, to examine the relationship between multiple diversity metrics and AGB. Multi-model inference and subset regression analyses were performed to identify the most important diversity metrics for AGB. Structural equation models were also used to evaluate both direct and indirect responses of AGB. Overall, 23 species were enumerated in the mixed species stands, plot level values ranging from 1 to 12 species. AGB was in average 15.5 Mg/plot, and varied from 9.3 to 23.1 Mg/plot. The relationship between taxonomic diversity and AGB varied with specific metric. Among taxonomic diversity metrics, only species richness correlated positively with AGB. Neither the single trait-functional diversity nor the functional dominance played a significant role in predicting AGB. In contrast, functional evenness and structural diversity showed positive effects on AGB, and mediated its positive response to species richness. This work reveals that functional evenness showed a significant advantage in predicting and mediating AGB response to species richness, when compared with structural diversity. It also suggests that niche complementarity plays a crucial role in enhancing AGB in mixed plantations, and operates through functional evenness and structural diversity. Maintaining high structural diversity and functional diversity would contribute to preserve biodiversity and enhance stand biomass stock in mixed species plantations.

Standard enthalpies of hydrogenation of 29 unsaturated hydrocarbon compounds were calculated in the gas phase by CCSD(T) theory with complete basis set cc-pVXZ, where X = DZ, TZ, as well as by complete basis set limit extrapolation. Geometries of reactants and products were optimized at the M06-2X/6-31g(d) level. These M06-2X geometries were used in the CCSD(T)/cc-pVXZ//M06-2X/6-31g(d) and cc-PV(DT)Z extrapolation calculations. (MAD) the mean absolute deviations of the enthalpies of hydrogenation between the calculated and experimental results range from 8.8 to 3.4 kJ mol−1 based on the Comparison between the calculation at CCSD(T) and experimental results. The MAD value has improved and decreased to 1.5 kJ mol−1 after using a complete basis set limit extrapolation. The deviations of the experimental values are located inside the “chemical accuracy” (±1 kcal mol−1 ≈ ±4.2 kJ mol−1) as some results showed. Very good linear correlations between experimental and calculated enthalpies of hydrogenation have been obtained at CCSD(T)/cc-pVTZ//M06-2X/6-31g(d) level and CCSD(T)/cc-PV(DT)Z extrapolation levels (SD =2.11 and 2.12 kJ mol−1, respectively).  \cite{Amir_Khairbek_2021}

The aim of this article is to use an Evolutionary Algorithm (EA) to solve the Aircraft Landing Problem (ALP) in an Air Traffic Flow Management (ATFM) environment. The ALP addresses the function of generating optimal or near-optimal landing sequences and time intervals between arrivals to provide runway capacity increase and reduce air delay. Problems of the ALP type in a dynamic environment such as Air Traffic Control (ATC) are considered Non-Polynomial (NP) complete. We simulated three different models. In the first model, the algorithm was applied when there was a schedule conflict between aircraft and separation measures where used to ensure safety. On the second and third models,we scheduled the flights in hourly batches. In the third model, a Maximum Constrained Shift (MCS) restriction was introduced to simulate more realistic conditions. To test the effectiveness of our study, we used actual data from Guarulhos International Airport. Results showed a capacity gain of 12 aircraft and a delay decrease of five percent when compared to the airport current sequencing operations. Introducing this technique represents a shift from the current arrival sequence model to a Trajectory-Based Operations (TBO) model, balancing air traffic demand with airspace capacity to ensure the most efficient use of the airspace system.

The turbulent flow incorporated with forced convection heat transfer is considered as a complex phenomenon and it is hard to predict analytically. Evidently, empirical correlations and numerical simulations regard as the most suitable approaches to estimate the turbulent flow integrated with forced convection heat transfer. The main objective of this study is to derive the DittusBoelter equation (an equation used to find the heat transfer coefficient for turbulent flow through pipes) unexperimentally using the minimum number of numerical trial. This paper uses the numerical simulation data and generate novel random data to reach the dittusBoelter relation; generating minimum data.

Even though multi cloud has been seen as a perfect path to prevent loss of data and avoid the vendor lock in problem, it still lacks in having comprehensive security mechanism due to its inherent nature. This inherent feature enables botnet attack where group of compromised nodes would do abnormal activities which are assigned by the bot master to degrade the quality of service in the environment of cloud. Thus, to recognize and remove the bot master, this work has designed a robust analyzer by proposing agglomerative-divisive based web usage mining, which classifies different types of attributes such as Access time, Destination IP address, port number, types of protocol used. Subsequently, clustered data are fed to the web structural mining based on WAP (Web Access Pattern-tree) which groups the network traffic information based on their topology. The preprocessed network traffic information would be subjected to the robust key identifier which decrypts the network traffic. Finally in order to nab the bot master, the decoded network traffic information would be given to the ensemble learner based on random forest algorithms.

This paper intends to examine existing educational practices, beliefs in Pakistani universities teaching engineering degree programs. It discusses the present situation of engineering education in developing countries like Pakistan, the causes that hinder the smooth process of knowledge creation and dissemination, irrationalities rooted in society and role of university leadership in keeping status-quo. Incumbent education internationalization strategies and academic entrepreneurial policies for the sustainable development are examined in the light of appalling ground realities. Following a qualitative approach, eight heads of departments were interviewed to explore the current situation, problems and the role of leadership. The findings revealed that fundamental causes include pricey education, lack of uniformity in curricula all over the country, lack of focus on practical education, misaligned priorities, rife poverty, rampant fees, business slant and simulation research practices, racial bigotry and political interferences in recruitments. The study indicates that academic leadership plays a decisive role in promoting higher education. Vice-Chancellor, with a significant position, needs to be an extraordinary individual with exceptional capabilities. The study implies that selection of Vice-Chancellor deserves great attention. Besides, it encourages regulating fee, recruiting talented local teachers, enforcing uniform curricula, imparting technical education in collaboration with local industries and raising local education standards. It offers future researchers to test present analysis empirically.

Process analytical technology (PAT) has been defined by the Food and Drug Administration (FDA) as a system for designing, analyzing, and controlling manufacturing through timely measurements to ensure final product quality. Based on quality-by-design (QbD) principles, real-time data monitoring is essential for timely control of critical quality attributes (CQAs) to keep the process in a state of control. To facilitate next-generation continuous bioprocessing, deployment of PAT tools for real-time monitoring is integral for process understanding and control. Real-time monitoring and control of CQAs is essential to keep the process within the design space, which is in alignment with the guiding principles of QbD concepts. The contents of this manuscript are pertinent to the online/at-line monitoring of upstream titer and downstream product quality. We have demonstrated that Waters’ PATROL system can be utilized to measure product titer and CQAs directly from bioreactors and downstream unit operations, respectively. We have established that online titer assay results from fed-batch and perfusion-based alternating tangential flow (ATF) bioreactors are comparable to at-line and conventional offline results. The utility of the PATROL system for online product quality measurements of down-steam unit operations for real-time peak pooling has been demonstrated.

Artificial intelligence (AI) is growing exponentially in various fields, including medicine, and this paper reviews the pertinent aspects of AI in Obstetrics and Gynecology (OBGYN), and how these can be applied to improve patient outcomes, reduce healthcare costs, and workload for clinicians. Although AI has some limitations, this new technology can improve the prognosis and management of patients, reduce healthcare costs, and help OBGYN practitioners to reduce their workload and increase their efficiency and accuracy by incorporating AI systems into their daily practice. AI has the potential to guide practitioners indecision making, reaching a diagnosis, and improve case management.

Objective To quantify the inter-dependency between maternal metabolic risk factors and their association with birthweight and cord blood insulin (CBI) level. Design Prospective cohort study. Setting Guangzhou Women and Children’s Medical Centre (GWCMC). Population Pregnant women with a singleton pregnancy who delivered at GWCMC between Jan 2015 and Jun 2016 and had umbilical cord blood retained (total 1522). Methods Multivariable linear regression and Additive Bayesian Network analysis were used to investigate the association between maternal metabolic risk factors (pre-pregnancy body mass index [BMI], fasting glucose, lipid profiles, and early gestational weight gain [GWG]) and their interdependency in predicting birthweight and CBI concentrations. Main outcome measures Birthweight and cord blood insulin. Results High maternal pre-pregnancy BMI was strongly associated with neonatal birthweight (standardized adjusted regression coefficient [βstd] = 0.27, 95%CI 0.22-0.32) directly; and with CBI indirectly. Maternal fasting glucose was positively associated with increased CBI (βstd=0.12, 95%CI 0.07-0.17). Maternal GWG was positively associated with increased birthweight, but not with CBI. None of the maternal lipids profile was independently associated with birthweight or CBI. Conclusions Maternal pre-pregnancy overweight/obesity is the most influential upstream metabolic risk factor for both maternal and neonatal metabolic health, therefore weight management should be addressed from the preconception period. Maternal dyslipidaemia appears to be secondary to maternal metabolic dysfunction with no clear causality relationship with metabolic adverse outcomes in neonates.

The Janzen-Connell (J-C) hypothesis states that species-specific natural enemies (pathogens, predators) induce local-density dependence which explains high diversity observed in tropical tree communities. However, these natural enemies often attack phylogenetically related species as well. Here, we use a spatially explicit model to study the predictions of a phylogenetic J-C effect for common diversity patterns. The species-area relationship is triphasic, while the species-abundance distribution has a rare species mode (neutral scenario), a two modes (large dispersal distance) or a single interior mode (small dispersal distance). Small dispersal distance forms clusters of species with large phylogenetic distance to the community while large dispersal distance makes species distribute uniformly. Phylogenetic trees show diversification slowdowns and imbalance, consistent with empirical patterns. However, the phylogenetic relatedness effect reduces diversity. We conclude that the spatially explicit phylogenetic J-C effect explains commonly observed diversity patterns, but hyperdiversity only results when the natural enemies are extremely species-specific.

Rapid evolution of traits and of plasticity may enable adaptation to climate change, yet solid experimental evidence under natural conditions is scarce. Here, we imposed rainfall manipulations (+30%, control, -30%) for ten years on entire natural plant communities in two Eastern Mediterranean sites. Additional sites along a natural rainfall gradient and controlled selection analyses assessed whether potential responses were adaptive. In both sites, our annual target species Biscutella didyma consistently evolved earlier phenology and higher reproductive allocation in dry plots. This response was adaptive, as it aligned with theory, corresponding trait shifts along the natural rainfall gradient, and selection analyses under differential watering in the greenhouse. However, another seven candidate traits did not evolve, and there was little support for evolution of plasticity. Our results provide compelling evidence for rapid adaptive evolution under climate change; yet, they also call attention to potential constraints for full adaptation.

The most common form of genetic generalized epilepsy (GGE) is juvenile myoclonic epilepsy (JME), which accounts for 5 to 10% of all epilepsy cases. The gene EFHC1 is associated with JME. However, it remains debatable whether testing for EFHC1 mutations should be included in the diagnostic epilepsy gene panels. To investigate the clinical utility of EFHC1 testing, we studied 125 individuals: 100 with JME and 25 with other GGEs. We amplified and sequenced all EFHC1 coding exons. Then, we applied a revised version of the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology(AMP) guidelines to predict the pathogenicity and benign impact of the variants. Mutation screening revealed 11 missense variants in 44 probands with JME (44%) and in 1 of the 7 individuals with generalized tonic clinic seizures on awakening (14%). Overall, only the variant c.685T>C was strictly classified as ‘pathogenic’ (1/11, 9%), five variants were classified as ‘benign’ (45%), and the remaining five (45%) were considered variants of uncertain significance (VUS). There is currently a limitation to test for genes that predispose an individual to complex, non-monogenic phenotypes. Thus, we consider EFHC1 to be a risk factor for JME but not currently useful for clinical purposes.

Objective. Exposure to airborne pollutants during pregnancy appears to be associated with uterine growth restriction and adverse neonatal outcome. Proprotein convertase subtilisin/kexin type (PCSK9) is a key modulator of low-density lipoprotein (LDL) metabolism, and increases following short term particulate matter (PM10) exposure. Because maternal cholesterol is required for fetal growth, PCSK9 levels could be used to evaluate the potential impact of airborne pollutants on fetal growth. Design. A cohort of 134 healthy women during early pregnancy (11–12 weeks of gestational age) was studied. Results. A significant association was found between circulating PCSK9 levels and three tested air pollutants (PM10, PM2.5, nitric oxide (NO2)). Of importance, gestational age at birth was reduced by approximately 1 week for each 100 ng/mL rise in circulating PCSK9 levels. This effect became more significant at the highest quartile of PM2.5 (with a 1.8 week advance in delivery date for every 100 ng/mL rise in circulating PCSK9). This finding was supported by a significant elevation of the odds ratio for urgent cesarean delivery for each 100 ng/mL rise in PCSK9 (2.99, 95% CI, 1.22–6.57), with similar trends being obtained for PM10 and NO2. Conclusions. The association between exposure to air pollutants during pregnancy and elevation in PCSK9 advances our understanding of the unforeseen influences of environmental exposure in terms of pregnancy associated disorders.

To obtain the best taste of woodland strawberries (Fragaria vesca) at the moment of consumption, it is essential to analyse the dynamics of sugar accumulation during ripening transition stages and explore how to control sucrose reserves after harvest. For this purpose, we analysed the accumulation of major sugars, sucrose-related olygomers and the expression of homologues genes involved in sucrose metabolism in attached strawberries at different ripening stages and after harvest. Measurements were taken during early and late phases of low temperature storage (LT) with and without CO2 pretreatment and further shelf-life at 20 ºC (SL). Our results show an increase in major sugars and sucrose in dark red (DR) strawberries associated with up-regulation of FvSPS1 and down-regulation of FvVINV2. The CO2-treated fruit showed high levels of sucrose, an FvSS1 up-regulation together with a modulation of homologues of FvVINV. Moreover, fruit treated with CO2 during SL (LTC) revealed a reduction in FvVINV homologue expression maintaining the sucrose reserves. High amounts in fructose and myo-inositol at LTC were observed, following a similar trend to that found in DR strawberries. We suggest that CO2 pre-treatment promotes a carbohydrate conserving state which has important implications for reducing weight loss and preserving sweetness.

Chloroplasts, the site of the primary reactions of photosynthesis, are organelles capable of independent protein synthesis, but which depend on the nucleus for most polypeptides. The process of photosynthesis is especially sensitive to environmental conditions and the composition of the photosynthetic apparatus can be modulated in response to environmental change. This acclimation process requires close communication between chloroplast and nucleus. Here we present evidence that the form in which carbon is exported from the chloroplast encodes information about the metabolic status of the photosynthetic apparatus which in turn controls photosynthetic acclimation.

Immuno-related pancytopenia (IRP) is featured by pancytopenia resulting from bone marrow suppression or destruction mediated by autoantibodies (auto-Abs). In a previous study we have established a K562 cDNA library, which was applied in screening 7 possible autoantigens produced by hematopoietic cells in IRP patients, including FTL. In this study FTL was expressed and purified, and then we detected the level of the auto-Abs specific to FTL. Through enzyme-linked immunosorbent assay (ELISA), it is revealed that the titer of anti–FTL antibodies (FTL Abs) was higher in IRP patients without treatment compared with those who recovered from IRP, those with severe aplastic anemia(SAA), those with myelodyplastic syndrome(MDS) and healthy controls. Furthermore, the level of FTL-mRNA was up-regulated in IRP patients without treatment compared with those who recovered from IRP, MDS patients and normal controls. These findings indicate that FTL Abs are highly expressed in IRP patients. Detecting FTL Abs might have some clinical value in differentiating IRP from SAA and MDS. Moreover, in certain type of IRP patients, FTL, as an autoantigen, may induce immune attack on hematopoietic stem cells.

Land degradation has reduced agricultural productivity in Nepal’s Terai. This has raised concern over the viability of conventional agriculture of the Terai farming system. Agroforestry can be a potential solution to the above problem. This paper aims at identifying socio-economic biophysical and institutional factors affecting the adoption of agroforestry with respect to conventional agriculture. Data were collected from a survey of 288 households through a face-to-face interview. A multinomial logistic regression (MNL) was run with conventional agriculture as a base category. It was found male-headed households were more likely to adopt agroforestry. Having an off-farm income source was positively associated with the adoption decision of farmers as it provides a safety net in case of crop failure. Landholding size was found as a major constraint to adoption. Therefore, smallholder farmers were reluctant to adopt Agroforestry as sparing a part of farmland for tree planting means reducing field crop production and thus failing to meet their annual food demand. Some other variables affecting positively include livestock herd size, provision of extension service, home-to-nearest government forest distance, farmers’ group membership and awareness of farmers about environmental benefits of agroforestry. Irrigation was another constraint that has stopped farmers from promoting the tree-based farming systems. The households with means of transport and with larger family (household) size were found to be reluctant towards agroforestry adoption.