Principal Component Analysis Scores Research Articles

Preparation of a multifunctional and ultrasensitive Au@AgNPs-Van/PDMS film SERS substrate for rapid detection of foodborne pathogens in beef

We present a novel and super-sensitive vancomycin (Van) modified Au@AgNP self-assembly with polydimethylsiloxane (PDMS) (Au@AgNPs/Van-PDMS) film surface-enhanced Raman scattering (SERS) substrate for identification of foodborne pathogens in beef, without the need for in vitro bacterial culture. The results illustrated that the Au@AgNPs/Van-PDMS film exhibited high reproducibility and Raman enhancement effect (1.09 × 105). Clostridium perfringens, Bacillus subtilis and Staphylococcus aureus isolated from beef captured by Au@AgNPs/Van-PDMS film exhibited high reproducibility and significant differences. Principal component analysis score plots distinguished classes of foodborne pathogens, and the qualitative identification of linear discriminant analysis was correct at 100%. The detection limit of S. aureus in beef was as low as 3 CFU/mL. This method could provide an effective means and technical support for realizing the application of SERS technology for quick and highly sensitive detection of foodborne pathogens in complex environments.

A survey of testicular texture in canine ultrasound images.

Computer-based texture analysis provides objective data that can be extracted from medical images, including ultrasound images. One popular methodology involves the generation of a gray-level co-occurrence matrix (GLCM) from the image, and from that matrix, texture fractures can be extracted. We performed texture analysis on 280 ultrasound testicular images obtained from 70 dogs and explored the resulting texture data, by means of principal component analysis (PCA). Various abnormal lesions were identified subjectively in 35 of the 280 cropped images. In 16 images, pinpoint-to-small, well-defined, hyperechoic foci were identified without acoustic shadowing. These latter images were classified as having "microliths." The remaining 19 images with other lesions and areas of non-homogeneous testicular parenchyma were classified as "other." In the PCA scores plot, most of the images with lesions were clustered. These clustered images represented by those scores had higher values for the texture features entropy, dissimilarity, and contrast, and lower values for the angular second moment and energy in the first principal component. Other data relating to the dogs, including age and history of treatment for prostatomegaly or chemical castration, did not show clustering on the PCA. This study illustrates that objective texture analysis in testicular ultrasound correlates to some of the visual features used in subjective interpretation and provides quantitative data for parameters that are highly subjective by human observer analysis. The study demonstrated a potential for texture analysis in prediction models in dogs with testicular abnormalities.

Pulsed electric field enhanced Bacillus sp. DL4 biodegradation of triclosan: focusing on operational performance and metabolomic analysis

ABSTRACT Electrochemical-assisted microbial degradation technology was considered a crucial strategy to reduce micropollutants, but the mechanism of the pulsed electric field (PEF) in affecting biodegradation had not been systematically studied. This study aimed to construct a bio-electrochemical system (BES) using PEF to investigate its effect on the degradation of triclosan (TCS) by the aerobic bacterium Bacillus sp. DL4. The operating optimal parameters for the BES (i.e. 0.01 A of the pulsed current, 1000 Hz of the pulse frequency, Fe (+)–C (−) of the plate materials, 4 cm of the plate spacing) were obtained by batch experiments. The maximum biomass (OD600 = 1.0 ± 0.05) was achieved and the removal efficiency of TCS reached above 95% in 24 h under the obtained operating conditions. Meanwhile, a thorough and methodical investigation of the metabolites in strain DL4 stimulated by PEF using untargeted Liquid Chromatography – Mass Spectrometry (LC-MS). In multivariate analysis, the experimental groups showed a notable separation in Principal Components Analysis (PCA) and Orthogonal Partial Least Squares Analysis discriminant analysis (OPLS-DA) score plots. A total of 3181 differential metabolites were obtained, and the up-regulated metabolites were mainly related to ‘Aminoacyl-tRNA biosynthesis’, ‘Arginine and proline metabolism’, ‘Lysine degradation’, ‘ABC transporters’, and ‘TCA cycle’, implying that PEF enhanced the degradation efficiency of TCS by enriching functional genes with transport ability and ion migration ability in cells. This study illuminated how PEF can affect TCS biodegradation and gives insights into the application prospect of electrochemical-assisted biodegradation technology in water environment treatment.

Multipurpose fluorescent carbon dots from papaya seed waste as sensing materials for Cu2+ detection and diethyl ether vapor sensor via electronic nose system

Herein, carbon dots (CDs) as biocompatible, fluorescent carbon-based nanomaterials were synthesized from papaya seed waste as renewable carbon sources for the first time via a facile acid pyrolysis method. The papaya seed-derived CDs showed blue fluorescence emission under UV light (365 nm) with a quantum yield of 2.74%, and contained oxygen-, and nitrogen- containing functional groups. Due to their surface functionality, the CDs have a great potential for using as fluorescence sensing probe in metal ion sensing application. The CD solution exhibited the most selective detection to Cu2+ as presented the highest fluorescence quenching with the limit of detection (LOD) of 5.16 μM. The CD-paper-based fluorescent sensor was also developed for practical application, and the RGB value was used to compare the sensitivity of CDs toward metal ions. The CD sensing film was also prepared for diethyl ether vapor sensing via optical electronic nose system. The principal component analysis (PCA) score plots revealed the total variance of 99.3%, indicating that the CDs can be used to discriminate different concentrations of diethyl ether/ethanol vapor mixtures. This work demonstrated that the papaya seed-derived CDs have a great attention to be alternative materials for developing sensing materials in both solution and film forms.

PoliBrush – A user-friendly software to aid multivariate image analysis dissemination

PoliBrush is a freely distributed, stand-alone software designed for teaching exploratory multivariate analysis in the frame of color RGB and spectral imaging. PoliBrush implements principal component analysis (PCA) as its core method. It features a single main window that provides users with essential tools for spectral image preprocessing and exploration. The software emphasizes an interactive brushing approach, enabling users to gain a comprehensive understanding of the relationships between PCA score space and image pixel space.In the present paper, PoliBrush usage and its operational procedure is demonstrated through two case studies, which are also available for download. The software has already been successfully used in various educational settings and workshops on multivariate approaches for spectral imaging, proving its effectiveness in teaching key concepts. With this original software publication, our aim is to make these tools also accessible to both experienced and novice image analysts.

Temporal and spatial shifts in the chemical composition of urban coastal rainwaters of Kuwait: The role of air mass trajectory and meteorological variables

The rainwater chemistry encompasses the signatures of geogenic and anthropogenic processes along the regional air mass movement apart from the local sources. The predominance of dust events and anthropogenic emissions in arid regions facilitate new particle formation. Further, rain events of different seasons depict moisture sources from diverse regions reflecting variation in the regional geochemistry with respect to seasons. Hence, to characterize the geochemical composition of rainwater, the study has focused on an integrated approach by considering regional transport, meteorological components and possible local sources. A total of 74 rainwater samples were collected from 27 rain events in 2018, 2019, and 2022, representing urban coastal areas of Kuwait predominantly of Ca-SO4-HCO3 type. The average pH and electrical conductivity of the rainwater were 7.18 and 140 μS/cm, respectively. The sea salt fractions calculated relative to Kuwait seawater ranged from 25.6 to >100 %, with higher values attributed to anthropogenic sources. Sea salt fraction, ion ratios, principal component analysis and factor scores revealed the terrestrial and anthropogenic sources apart from marine contributions. In addition, new particle formation and aerosols contributed to the rainwater chemistry involving SOx, NOx, and photochemical reactions during higher relative humidity and lesser wind speed. The HYSPLIT reflected that the moisture sources were largely from western regions of the study area, and those of December and January events had long-distance travel across the Azores high originating from northeast America. The trajectories of the November events are observed to originate from the Caspian/Black Sea region in the northeastern part of Kuwait with a relatively shorter distance of travel. The rainfall samples had higher ionic concentrations, and saturated with aragonite and calcite minerals in a few locations specifically after the dust events, while the subsequent rain events were less polluted.

Evaluation of Bacillus subtilis Czk1 Metabolites by LC–MS/MS and Their Antifungal Potential against Pyrrhoderma noxium Causing Brow Rot Disease

Brown rot disease caused by Pyrrhoderma noxium is a widespread disease that severely affects the roots of rubber trees (Hevea brasiliensis Muell. Arg.). The economic losses, along with environmental and health problems arising from the use of disease control chemicals, have raised the interest of scholars to explore the use of biological control agents for the effective control of fungal pathogen P. noxium. Here, the inhibition effect of the culture filtrate of B. subtilis Czk1 on P. noxium was demonstrated. The findings indicate that the antifungal activity of this strain is mediated wholly or partly by compounds produced in the culture filtrate. The combined use of liquid chromatography–tandem mass spectrometry and antifungal activity assays rapidly identified compounds produced by B. subtilis Czk1. Metabolic profiles were assessed and used to identify major metabolites based on the scores of variable importance in the projection and the plot scores of principal component analysis. A total of 296 differential metabolites were screened, including 208 in positive ion mode and 88 in negative ion mode. Two key metabolites, diacetyl and trans-2-octenoic acid, were screened from 29 metabolites by antifungal activity assays. The median effective concentration (EC50) of trans-2-octenoic acid and diacetyl were 0.9075 mg/mL and 4.8213 mg/mL, respectively. The antifungal metabolites can disrupt the internal structure of the pathogenic fungal mycelium, thereby impeding its growth. This study is expected to contribute to the existing knowledge of Czk1-produced metabolites and their future antifungal applications. This study is also expected to provide a new biopreservative perspective on unexplored antifungal metabolites produced by Czk1 as a biocontrol agent.

Comparative Study of Camel Milk from Different Areas of Xinjiang Province in China.

Xinjiang province is the main camel feeding area in China with a large square, and camel milk from different areas have different qualities. By now, there are few reports about the quality of camel milk from different areas of Xinjiang province in China. In this study, seven batches of camel milk and one batch of cow milk were collected, and the contents of fat, protein, lactose, total solid, and nonfat milk solid of these milk samples were determined, as well as the contents of lysozyme and vitamin C. All samples were scored and compared by principal component analysis score and comprehensive weighted multi-index score. As the results, camel milk from different areas showed different contents of fat (4.62%-7.02%), protein (3.34%-3.95%), lactose (3.85%-4.79%), total solid (13.59%-17.00%), nonfat milk solid (8.55%-9.73%), vitamin C (12.10-41.25 μg/mL), and lysozyme (8.70-22.80 μg/mL), as well as different qualities. This variation would help people to know more about quanlity of camel milk in Xinjiang province. Camel milk from Jeminay showed the best quality, and then followed by camel milk from Fukang, Changji, and Fuhai, while cow milk showed the lowest score. Therefore, Jeminay is the most suitable place for grazing camels. Our findings show the different qualities of camel milk in different distribution areas of Xinjiang province, and provide an insight for the evaluation of camel milk. In the present study, only seven components in camel milk were determined, many other factors, such as cfu, mineral, and other vitamins, have not been considered.

Improving provider and client communication around family planning in Togo: Results from a cross-sectional survey.

Previous research has shown that clients are better able to achieve their reproductive intentions when family planning (FP) services meet their needs and they have satisfying client provider interactions. There are several areas of quality provider-client communication, including providers taking a complete reproductive history of their clients to best gauge their needs, communication around alternative FP methods and side effects captured in the method information index, and communication around sexually transmitted infections and HIV risk as it relates to FP choices. This study examines data from a clinic-based intervention in Togo that focuses on strengthening health provider counseling related to FP, including improving in these three areas of provider-client communication. A clustered sampling approach was used to select 650 FP clients from 23 intervention facilities and 235 clients from 17 control facilities in the Lomé and Kara districts of Togo. The FP clients' interactions with providers were observed and clients exit interviews were conducted in December 2021. For each communication area measured through client interviews and observations, principal components analysis and Cronbach's alpha scores were used to ensure that the individual components could be indexed. Outcomes variables based on an index of sub-questions were then created for those who had fulfilled each of the components within an index. Multivariate multilevel mixed-effects logit models accounted for clients nested within facilities and included independent variables capturing client demographic and facility variables. Multivariate results show that all three outcome variables representing the three provider-client communication areas were statistically significantly better for FP clients in intervention clinics versus control clinics (p<0.05). The results speak to the emphasis that the Togo Ministry of Health has placed on building the provider capacity to provide quality counseling and administration of FP methods and working to assist in achieving health programming goals through well-designed interventions.

Dietary pattern and brain structure among young adults

AbstractBackgroundEnvironmental factors, such as nutrition, influence brain physiology and health throughout the life course. While research has focused on the extremes of the age spectrum, less is known about early adulthood, yet a critical period for the consolidation of brain maturation and the building of adult behaviors. Nutrition may impact late maturational changes in the post‐adolescent brain and contribute to the degree of brain reserve that minimizes the risk to develop dementia. We took advantage of a large sample of young adults to evaluate the association of dietary behavior with brain structure characteristics.MethodThis cross‐sectional study included 1721 university students (18‐35 years‐old) from the French i‐Share cohort, who underwent brain MRI. A 12‐item online Food Frequency Questionnaire was used to evaluate consumption in major food groups and to determine dietary patterns from Principal Component Analysis (PCA). Multivariable‐adjusted linear regressions were used to estimate the association of PCA scores with brain structure (cortical thickness and surface area, grey matter and white matter volumes, diffusion parameters).ResultThe first PCA component (explained variance, 17%) contrasted a healthy diet (higher fruit and vegetable intakes) to a poor diet (higher fast food, sugary drink and snack consumptions). In models adjusted for total intracranial volume, age, sex, physical activity, body mass index, alcohol and tobacco consumptions, a higher PCA score (reflecting healthier diet) was associated with lower total gray matter volume (β for 1 point score = –0.17 [95%CI, –0.31; –0.03] cm3), in various brain areas (Figure). Healthy diet was also associated with lower global white matter volume (β = –0.18 [–0.32; –0.03] cm3). No association was found with diffusion tensor imaging, and neurite orientation dispersion and density imaging metrics in the white matter.ConclusionIn this large sample of young adults, healthier diet was associated with lower brain volumes, independent of multiple potential confounders. Gray matter volume loss during post‐adolescence is a marker of brain maturation; thus, environmental factors emphasizing this loss may benefit maturation. Our results raise the hypothesis that a healthy diet may favor and a poor diet may hamper brain maturation; an assumption which deserves further investigation in other populations.

Evaluation of Areca Quality Based on Principal Component and Hierarchical Cluster Analyses in Hainan, China

Areca (Areca catechu L.) is one of the most important cash crops in China and is considered the fourth most widely used addictive substance. In addition, areca is widely used in traditional and herbal medicines. The major characteristics of the fruit are affected by its genetic background and growth environment. The growing environment in different regions will impact the quality of agricultural products and the processing quality. The quality of areca is not only the basis of its commercialization development and processing quality, but also is an important basis for the scientific planting of areca. Therefore, determining the quality of areca will provide evidence for scientific planting and more optimal applications. We evaluated the quality of areca by comparing the differences in physicochemical characteristics using principal component analysis (PCA) and hierarchical cluster analysis. A total of 165 arecas, in the same growth period, were collected from 11 main producing regions in Hainan Province. Our results illustrate that the physicochemical characteristics of areca in different regions were significantly different. The PCA was conducted using 10 quality indexes, and three principal components were extracted to reflect 80% of the original variables. The first principal component mainly reflected the fruit shape quality, the second principal component mainly reflected the hardness quality, and the third principal component mainly reflected the functional component quality. The relationship between each producing region and the principal component could be obtained intuitively from the principal component score plots. The arecas in Wanning and Wenchang were larger and their cellulose content was greater than in other areas, indicating that they were more suitable for processing. In contrast, the arecas in Baoting, Wuzhishan, Danzhou, Tunchang, and Dongfang had a greater arecoline content than the other areas, making them more suitable for use as medicinal materials. Hierarchical cluster analysis classified the 11 producing regions into five categories based on the measured parameters, which was consistent with the results of the PCA score plots. These results could provide information to improve the use of areca in China.

18 Fecal microbial metabolite profiles are unaltered by laminitis history

Microbial metabolites of the equine gastrointestinal tract may confer information about health and susceptibility to disease. Laminitis is often associated with metabolic disturbances, but little is known of its impact on functional microbial metabolism. A pilot study compared metabolomic profiles of feces collected from 55 native ponies, comprising n = 15 pairs of previously laminitic (PL) and non-laminitic (NL) ponies matched for location, diet, and management, and n = 25 ponies suspected of having an active episode of laminitis (SL) but without clinical diagnosis. Targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis was used. Univariate analyses (ANOVA with Fisher's least significant difference comparisons of PL, NL and SL groups) was performed with significance set at P < 0.05 following Benjamini-Hochberg correction. Principal component analysis (PCA) wasapplied to visualize clustering of individuals. Analysis was performed using the MetaboAnalyst 5.0 web-based interface. Of a panel of 167 metabolites, 104 were identified in the feces, however, none were significantly different between the laminitis status groups. Assessment of the PCA scores plot revealed no clustering of individuals by metabolic profile based on laminitis status. The similar fecal metabolite profile of previously laminitic and non-laminitic ponies indicates that laminitis may not result in significant long-term, alteration of microbial metabolism. Future work to combine these data with that of microbial abundance and species diversity in the feces may reveal further insights into the functional microbial metabolism in laminitic and healthy animals.

Metabolic Discrimination between Adventitious Roots and Standard Medicinal Part of Atractylodes macrocephala Koidz. Using FT-IR Spectroscopy.

This study aims to examine the metabolic discrimination between in vitro grown adventitious roots and the standard medicinal parts of Atractylodes macrocephala. To achieve this goal, firstly, in vitro culture conditions of adventitious roots such as indole-3-butyric acid (IBA) concentrations, types of media, inorganic salt strength of culture medium, and elicitor types and concentrations were optimized. The optimal culture conditions for proliferation of adventitious roots was found to consist of Murashige and Skoog (MS) medium containing 5 mg L-1 IBA. Whole cell extracts from adventitious roots and the standard medicinal parts of A. macrocephala were subjected to Fourier transform infrared spectroscopy (FT-IR). Principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) from FT-IR spectral data showed that adventitious roots and standard medicinal parts were clearly distinguished in the PCA and PLS-DA score plot. Furthermore, the overall metabolite pattern from adventitious roots was changed depending on the dose-dependent manner of chemicals. These results suggest that FT-IR spectroscopy can be applied as an alternative tool for the screening of higher metabolic root lines and for discriminating metabolic similarity between in vitro grown adventitious roots and the standard medicinal parts. In addition, the adventitious roots proliferation system established in this study can be directly applied as an alternative means for the commercial production of A. macrocephala.

Combination of peak-picking and binning for NMR-based untargeted metabonomics study

In NMR-based untargeted metabolomic studies, 1H NMR spectra are usually divided into equal bins/buckets to diminish the effects of peak shift caused by sample status or instrument instability, and to reduce the number of variables used as input for the multivariate statistical analysis. It was noticed that the peaks near bin boundaries may cause significant changes in integral values of adjacent bins, and the weaker peak may be obscured if it is allocated in the same bin with intense peaks. Several efforts have been taken to improve the performance of binning. Here we propose an alternative method, named P-Bin, based on the combination of the classic peak-picking and binning procedures. The location of each peak defined by peak-picking is used as the center of the individual bin. P-Bin is expected to keep all spectral information associated with the peaks and significantly reduce the data size as the spectral regions without peaks are not considered. In addition, both peak-picking and binning are routine procedures, making P-Bin easy to be implemented. To verify the performance, two sets of experimental data from human plasma and Ganoderma lucidum (G. lucidum) extracts were processed using the conventional binning method and the proposed method, before the principal component analysis (PCA) and the orthogonal projection to latent structures discriminant analysis (OPLS-DA). The results indicate that the proposed method has improved both the clustering performance of PCA score plots and the interpretability of OPLS-DA loading plots, and P-Bin could be an improved version of data preparation for metabonomic study.

Prediction of subglacial lake melt source regions from site characteristics

AbstractSubglacial melt has important implications for ice-sheet dynamics. Locating and identifying subglacial lakes are expensive and time-consuming, requiring radar surveys or satellite methods. We explore three methods to identify source regions for lakes using seven continent-wide environmental characteristics that are sensitive to or influenced by ice-sheet temperature. A simple comparison of environmental properties at lake locations with their continent-wide distributions suggests a statistical relationship (high Kolmogorov-Smirnov statistic) between stable lake locations and ice thickness and surface temperatures, indicating melting under passive conditions. Active lakes, in contrast, show little correlation with direct thermally influenced parameters, instead exhibiting large statistical differences with horizontal velocity and bedrock elevation. More sophisticated techniques, including principal component analysis (PCA) and machine learning (ML) classification, provide better spatial identification of lake types. Positive PCA scores derived from the environmental characteristics correlate with stable lakes, whereas negative values correspond to active lakes. ML methods can also identify regions where subglacial lake melt sources are probable. While ML provides the most accurate classification maps, the combination of approaches adds deeper knowledge of the primary controls on lake formation and the environmental settings in which they are likely to be found.

MP03-03 TRANSCRIPTOME ANALYSIS IN LUMBOSACRAL DORSAL ROOT GANGLIA REVEALS KEY MOLECULAR CHANGES IN ANIMAL MODELS OF UROLOGICAL CHRONIC PELVIC PAIN SYNDROME (UCPPS)

You have accessJournal of UrologyCME1 Apr 2023MP03-03 TRANSCRIPTOME ANALYSIS IN LUMBOSACRAL DORSAL ROOT GANGLIA REVEALS KEY MOLECULAR CHANGES IN ANIMAL MODELS OF UROLOGICAL CHRONIC PELVIC PAIN SYNDROME (UCPPS) Sathish Kumar Yesupatham and Alison Xiaoqiao Xie Sathish Kumar YesupathamSathish Kumar Yesupatham More articles by this author and Alison Xiaoqiao XieAlison Xiaoqiao Xie More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003214.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Patients with UCPPS experience chronic pelvic pain and lower urinary tract symptoms (LUTS), such as urinary frequency, urgency, and nocturia. UCPPS symptoms are often associated with nociceptive sensitization in the peripheral and central nervous system, which underlies symptoms of bladder overactivity, pelvic pain, and centralized pain. Understanding the molecular mechanism underlying the pathogenesis of nociceptive sensitization is necessary for finding better drug targets and neuromodulation protocols to treat UCPPS symptoms. However, despite transcriptomic analysis has been conducted on the L4 & L5 dorsal root ganglia (DRGs) in injury-induced pain models, genomic analysis focusing on bladder sensory pathways have not been performed. The current study aims to characterize transcriptome changes in lumbosacral DRGs receiving bladder and pelvic sensory input in a mouse model of UCPPS. METHODS: Male and female C57BL6/J mice were used in this study. UCPPS symptoms was induced by intravesical instillations of recombinant mouse vascular endothelial growth factor (VEGFA), an animal mode of UCPPS we previously established. As a read-out of visceral hypersensitivity, Von Frey assay was performed and compared between VEGF-instilled experimental group and saline-instilled control group. Mice were sacrificed after VEGF-induced visceral hypersensitivity was observed, and their L1, L2, L6, S1 and S2 DRGs was harvested for bulk-RNA sequencing. RESULTS: Samples were sequenced at a depth of 40 million reads per sample. Data analysis was performed using Basepair Tech platform. Ingenuity pathway analysis (Qiagen) enabled to visualize the biological network changes due to UCPPS. Spliced Transcripts Alignment to a Reference (mm10) revealed changes in the Nociceptor signaling. Principal component analysis score confirms the global gene expression changes in UCPPS-like experimental group. Upstream analysis on VEGF signaling revealed activation/ inhibition of transcriptional factors like ATF3, FOSB, and BCL2. CONCLUSIONS: Our data is the first characterization on key signaling pathway changes in lumbosacral DRGs during the pathogenesis of UCPPS symptoms in animal models. VEGF and its receptors have been recognized as a urine biomarker for UCPPS in patients. Ongoing transcriptome analysis such as Ingenuity pathway analysis and Gene set enrichment analysis will further reveal the etiology of pain centric UCPPS. Source of Funding: NIDDK 25B0965/5R01DK129260-02 (Xie) © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e22 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Sathish Kumar Yesupatham More articles by this author Alison Xiaoqiao Xie More articles by this author Expand All Advertisement PDF downloadLoading ...

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This study assessed the impacts of Farmer Field Schools (FFS) on household food security and environmental conservation in the Western Province of Kenya. The outcome variables were: Maize yield per acre, income per acre, household food insecurity score and environmental conservation score. Principal component analysis and propensity score matching techniques were used for analyses and regression method to test the robustness of matching results. We found that FFS households harvest higher crop yield of up to 9.45 bags which is significantly different (p&lt;0.05) from their counterparts. Consequently, FFS households earn significantly (p&lt;0.05) higher income estimated over KSh 2,800 per acre than Non-FFS households. Although the EC score were not significantly different, FS scores were low in FFS households. The study showed that FFS program significantly (-0.42**) reduce severity of food insecurity this implies that FFS plays a critical role in enhancing household food security. Key words: Farmer field schools, food security, environmental conservation.

Exploring the Use of Raman Spectroscopy and Covariate-Adjusted Multivariate Analysis for the Detection of Irradiated Blood.

Biological dosimetry is a key technique for retrospective radiation dosimetry that provides individual estimates of absorbed dose of ionizing radiation, applicable for use in a large scale radiological/nuclear event. Current techniques for biodosimetry are labor intensive and time consuming and not high through-put. In this proof-of-concept study, we developed a new approach for detecting irradiated blood based on Raman spectroscopy of blood combined with multivariate analysis. Peripheral blood samples from 8 healthy male and female, anonymous donors, were exposed to either 5 Gy X ray radiation or unirradiated (0 Gy). At 3 h postirradiation, the blood was immediately frozen at -80°C. Raman spectra were measured from thawed blood using a portable spectrometer system. Data were preprocessed and analyzed using principal component analysis (PCA) to observe trends in the data, and by using partial least squares-discriminant analysis (PLS-DA) to build a model to discriminate between Raman spectra of control (0 Gy) and irradiated (5 Gy) blood. We found strong evidence of inter-donor variability in the form of donor-wise clustering of PCA scores corresponding to the control Raman spectra, in addition to the poor separation of PLS-DA scores associated with Raman intensities of 0 Gy vs. 5 Gy spectra. However, after adjustment for donor covariates using a linear mixed-effects model, we obtained a better separation between control and irradiated blood using PLS-DA. Evaluation of the coefficients of the PLS-DA loading vectors indicated radiation-induced changes in proteins, lipids and hemoglobin to be major contributors for this discrimination. This pilot study demonstrates the potential of application of Raman spectroscopy to support biodosimetry of blood and blood components.

PCA Analysis of In Situ X-ray Powder Diffraction and Imaging Data Shedding New Light on Solid-State Transformations: The Crystallization of Low Temperature Eutectic Mixtures

Eutectic mixtures are usually studied by differential scanning calorimetry (DSC), able to identify the transition temperatures, possible hysteresis, and investigate the energetic features of transformations. However, DSC is not able to give compositional, structural, or morphological information. A new approach is proposed exploiting powder X-ray diffraction (XRPD) and imaging to overcome the issues posed to diffraction by the presence of an amorphous liquid phase. Principal component analysis (PCA) is applied blindly to in situ XRPD data from both solid and liquid phases in an approach called differential scanning diffraction (DSD), with PCA scores being the reaction coordinate of melting or crystallization steps. PCA was used in a similar way to analyze the imaging data in what was named differential scanning imaging (DSI). Exploiting this approach, the structural and morphological changes during phase transitions can be characterized by XRPD and imaging respectively, complementarily to the energetic effects probed by DSC. Melting and crystallization points can be identified together with the hysteresis between downward and upward temperature ramps, by the structural and morphological viewpoints. A three-component mixture (NaBr, KCl, and water), with wide industrial applications, was studied to describe the behavior around the eutectic composition and examine how small mixture changes can affect the transition temperature and the freezing/melting behaviors. The phase composition at the solid state was elucidated and a new phase of NaBr was identified and its lattice parameters were obtained by XRPD. DSD and DSI resulted complementary to traditional DSC data with many potential applications in solid state chemistry and materials science.

GGE Biplot Analysis for Yield Stability of Lentil Genotypes

The experiment was conducted at three different locations of Bangladesh Agricultural Research Institute viz., at PRC, Ishurdi, Pabna, at PRSS, Joydebpur, Gazipur and RARS, Jashore, during the period November to March in 2014-15 and 2015-16. The experiment was laid out in Randomized Complete Block Design with three replications. Variance analysis showed significant interaction between genotype and environment on yield and its related traits. The highest yield was recorded in genotypes BARI Masur-7 followed by BARI Masur-6, BARI Masur-5, BARI Masur-4 and the lowest was in BLX-66004-12. The PCA (Principal component analysis) scores of a genotype in the GGE analysis indication of the stability or adaptation over environments. GGE biplot analysis related that the PC1 and PC2 for different traits, i.e. 80.8% and 11.7% for days to flowering, 72.4% and 18.7% for days to maturity, 66.3% and 15.4% for plant height, 73.8% and 17.3% for pods/plant, 70.1% and 22.8% for 100 seed weight and 38.37% and 31.04% for yield of the total variation, respectively. Considering regression co-efficient values and also biplot analysis most stable variety was BARI Masur-4 followed by BARI Masur-5 and BARI Masur-6 and lowest stable variety was BLX-05002-6. Among the six environments, Ishurdi 2014-15 and Gazipur 2014-15 were most discriminating (informative) and Jashore 2014-15 and Jashore 2015-16 were less discriminating. Among two years (2014-15 and 2015-16) at different location 2015-16 was found favorable for lentil production.&#x0D; Bangladesh J. Agril. Res. 46(3): 307-320, September 2021