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Dec 2025
Liu LipingCorresponding author
The incidence rate of melasma is notably high among patients with anxiety disorders. Aromatherapy primarily influences the physiological and psychological states of individuals through the inhalation or application of essential oils, thereby facilitating the treatment or alleviation of various conditions. This study aims to explore the action mechanism of complex lemon-angelica sinensis -boswellia essential oil (CEO) in treating anxiety disorders with melasma. We investigated the active ingredients, targets, and pathways of CEO in relation to anxiety and melasma using network pharmacology. We employed cell assays and conducted nebulized essential oil inhalation tests on CUMS mice to validate the intervention effects of CEO on anxiety. A total of 28 active components, including neryl acetate, 3-butenylphthalide and octyl acetate, and 26 cross-targets, such as ESR1, CCND1 and PIK3CA, were identified. GO and KEGG pathway analyses indicated that these cross-targets were primarily involved in endocrine regulation, cell proliferation, and apoptosis, specifically through PI3K/Akt signaling pathway and calcium signaling pathway. The experimental results demonstrated that CEO significantly reduced the secretion of NO, TNF-a and IL-6, as well as the mRNA expressions of ESR1, CCND1 and PIK3CA in cells compared to the inflammatory cell model. Furthermore, CEO notably decreased the forced swimming immobility time of mice and the levels of IL-1β, ESR1 and CCND1 in hippocampus when compared to model mice. These findings suggest that CEO may regulate ESR1, CCND1 and PIK3CA through its citral, 3-butylphthalate and neryl acetate, thereby influencing endocrine function, cell proliferation and apoptosis, inhibiting inflammation and anxiety-like behavior in CUMS-induced mice.
Aug 2025 DOI 10.14302/issn.2379-8572.joa-25-5645
Beridze BerdiaCorresponding author
Purpose The objective of this prospective case-control study was to perform translation, cross-cultural adaptation, and validation of the sino-nasal outcome test 22 (SNOT-22) into the Georgian language. Methods The translation and validation of the SNOT -22 questionnaire was performed using the forward-backward translation technique. After proper translation, the translated questionnaire was completed by chronic rhinosinusitis (CRS) patients before and after functional endoscopic sinus surgery (FESS) and by healthy individuals as controls. Results SNOT22 was translated into the Georgian language; the pilot study involved 34 patients, the test–retest group consisted of 30 patients with CRS and the control group of 71 patients without CRS complaints; 34 patients were evaluated before surgery and 3 months after surgery. The results showed a good internal correlation with Cronbach’s alpha - 0.88 at the initial examination, and 0.93 at the retest examination; both values suggest good internal consistency within SNOT-22. Pearson’s correlation coefficient was 0.72 (p<0.001), revealing a good correlation between initial scores and retest scores. Our sample of healthy individuals had a median score of 10,11 points and the instrument was able to differentiate between the healthy and the patient group, demonstrating its validity (p<0.0001). Conclusions The Georgian version of the SNOT-22 questionnaire is a valid outcome measure for patients with CRS.
May 2026 DOI 10.14302/issn.2578-8590.ipj-26-6121
Bitsch Poulsen MariaCorresponding author
Aims Cardiac autonomic neuropathy is currently an untreatable progressive complication of type 1 diabetes (T1D). Impaired microcirculation is a suspected cause of nerve degeneration in TID. We investigated whether cardiovascular autonomic reflexes often used as indices of nerve functions, are associated with indices of microcirculatory function in young adults with T1D compared with non-diabetic controls. Methods In a cross-sectional study, 15 adults with T1D and 15 age-matched controls (20-40 years) underwent standardized cardiovascular autonomic reflex tests. Continuous recordings of electrocardiogram, cardiac vagal tone, beat-to-beat blood pressure and transcutaneous tissue oxygen (tcpO₂) and carbon dioxide partial pressures (tcpCO2) were done. Results Despite preserved baroreflex, parasympathetic, and sympathetic functions assessed using cardiovascular reflex tests, the individuals with T1D exhibited reduced baseline tcpO2 compared to the controls (37.5±3.75 vs. 49.6 mmHg). During the Valsalva manoeuvre, individuals with T1D exhibited a reduced systolic blood pressure response in phase I (31±10 vs. 43±18 mmHg) and early phase II (-1±15 vs. -18±17 mmHg), and an increased systolic (31±15 vs. 18±14 mmHg) and diastolic (45±11 vs. 33±16 mmHg) response in late phase II compared to controls. The early phase II diastolic response was inversely associated with baseline tcpO2. Conclusion The altered hemodynamic response to the Valsalva manoeuvre is suggestive of possible reduced arterial elasticity, higher vascular resistance, and splanchnic sympatho-vagal imbalance in T1D despite normal autonomic reflex ratios. The concomitant evidence of reduced tissue oxygenation and altered hemodynamics may represent early signs of dysautonomia but require longitudinal validation.
Dec 2025 DOI 10.14302/issn.2381-862X.jwrh-25-5447
J. Factoriza OliviaCorresponding author
Objective This study aimed to explore the respondents’ reproductive health profiles, examining the physiological and psychosocial perimenopausal symptoms affecting productivity, and identifying occupational needs. It also determined the relationship between menopausal symptoms and the productivity and occupational needs of peri-menopausal women. Methodology A descriptive cross-sectional design was used, surveying 50 women over 40 years old with a validated four-point Likert scale instrument. The instrument undergone content validation, reliability test, and ethical approval. Survey was administered personally and online using purposive sampling. Statistical treatments included weighted mean, F-test, T-test, Pearson r correlation, and ranking. Key results The majority of participants had their first menstruation between 11 to 15 years old and experienced regular menstrual cycles. Most had one child, with an equal number of cesarean and normal deliveries, and reported no pregnancy complications. The study found that participants seldom experienced physiological and psychosocial menopausal symptoms. They agreed on the occupational needs during the perimenopausal period. It was found that physiological symptoms were influenced by factors such as early menarche, cesarean delivery, and pregnancy complications. Additionally, psychosocial symptoms varied based on menstrual status, the number of children, and pregnancy complications, with those experiencing earlier menstruation or complications reporting more intense symptoms. The study revealed a significant relationship between both physiological and psychosocial perimenopausal symptoms, which negatively impacted productivity and increased occupational needs. Women with higher menopausal symptoms expressed a greater need for workplace policies that support perimenopausal women, highlighting the need for tailored workplace interventions for this demographic. Future Direction The study recommends including pap smears and mammograms in annual exams for peri-menopausal women, offering awareness seminars on managing perimenopausal symptoms to reduce workplace disruptions, and suggests future research exploring additional variables affecting perimenopausal women’s health and productivity
Mar 2025 DOI 10.14302/issn.2638-4469.japb-25-5395
Divakar ChennamsettiCorresponding author
Plant leaf diseases pose significant threats to crop yield and agricultural sustainability, making early and accurate detection crucial for effective disease management. In current years, deep neural network (DNN) techniques have shown remarkable potential in the field of image classification, including plant disease detection. The study aims to investigate the performance of two popular deep learning architectures, namely, VGG16 and InceptionResNetV2, for the detection of tomato plant leaf disease. The proposed methodology involves acquiring a diverse dataset comprising high-resolution images of healthy and diseased leaves from the target crops. Preprocessing techniques such as image augmentation and normalization are applied to enhance the generalization ability of the models and mitigate overfitting. Transfer learning is employed to initialize the deep learning architectures with weights pre-trained on large-scale image datasets to accelerate convergence and improve the models' performance in limited data scenarios. To evaluate performance of proposed networks various metrics such as validation and test accuracies, precision and recall, F1 score, and the area under the curve (AUC) are considered. From the investigations, the classification accuracy of the finest architectures is as follows: 99.8 percent for VGG16 and 99.4 percent for InceptionResNetV2 on Corn Leaves. The results suggest that the models developed during the investigation phase to identify the leaf disease were superior to any existing Deep Neural Networks (DNNs).
Sep 2023 DOI 10.14302/issn.2692-1537.ijcv-23-4660
Amel Jamehdar SaeidCorresponding author
SARS-CoV-2 real-time reverse-transcription PCR (rRT-PCR) is the most effective testing system available to combat COVID-19, given the absence of any specific treatment or vaccine. Moreover, numerous SARS-CoV-2 rRT-PCR kits have been approved under emergency-use-authorization (EUA) worldwide. In this article, we present a comparison of important performance features among five commercial RT-PCR assays. A total of consecutive nasopharyngeal (NPS) samples and oropharyngeal (OP) swabs were collected from 50 COVID-19 patients to analyze sensitivity and specificity. The results showed variations in sensitivity among all the RT-PCR kits examined. The Pishtaz teb assays demonstrated the highest positive percent agreement (PPA) of 95.2% (40/42), followed by Covitech (90.5% - 38/42), DaAn Gene (83.3% - 35/42), Sansure (66.66% - 28/42), and Power check of SARS- CoV-2 panel (64.3% - 27/42). Conversely, all five molecular assays demonstrated a negative percent agreement (NPA) of 100% (8/8). These findings provide a technical baseline for assessing the performance of five distinct commercial PCR assays for detecting SARS-CoV-2. They could prove practical and useful for laboratories seeking to purchase any of these assays for further clinical validation. Highlights ·Compared five COVID-19 RT-PCR kits approved and available by Iran Ministry of Health. ·Pishtaz teb's kit identified the highest number of positive clinical samples.
Oct 2022 DOI 10.14302/issn.2641-4538.jphi-22-4313
Niyonkuru MathieuCorresponding author
Public Health Department, Mount Kenya University Rwanda
Data quality is defined as a measure of data status that fulfills the following elements: accuracy, completeness, consistency, reliability, and if the data is current. The World Health Organization (WHO) reported that only 40% of all countries have an adequate system to collect information on birth and deaths. Even though the system is there, vital registration systems are inaccurate and incomplete in developing countries. In Rwanda, maternal health related data was over-reported more than other indicators. These are the main reasons for conducting the study to investigate the data quality of four maternal and newborn health indicators reported by Rwandan Western Province health centers. This concurrent-mixed method study included 61 data managers and 12 key informants. Routine data quality assessment tool and structured interview guide were used to collect data. Descriptive statistics were used to get proportion of respondents’ socio-demographic characteristics. The analysis was done for assessing median of data quality index. The results show that 55.7% of data managers were male while 58.3% of responsible of maternity were female. Majority (58.9%) of participants was in age’s category from 33-42, 61.6% have A1 education level and 53.4% have experience less than five years. Data quality index of one out of four (25%) MNH indicators was found below 95% accepted by WHO. The main reasons for insufiscient quality of data are lack of data validation meetings (57.5%) and incompleteness of reporting tools (36.4%). Monthly data validation meetings chaired by HC leaders are important to contribute to high-quality data in healthcare settings. Supportive supervisions done in data quality and management have to be organized in a supportive, and educative way.
Feb 2022
Gobato RicardoCorresponding author
Green Land Landscaping and Gardening, Seedling Growth Laboratory, 86130-000, Parana, Brazil.
Using samples of small cell lung tumors, a research team led by biologist Dr. Raymond discovered two new ways to induce tumor cell death. By activating ferroptosis, one of two subtypes of tumor cells can be targeted: first, iron-dependent cell death due to oxidative stress, and second, oxidative stress. Therefore, cell death can also be induced in a different way. Both types of cell death must be caused by drugs at the same time to eliminate the majority of the tumor mass. It is currently in clinical trials for cancer treatment. Auranofin, which inhibits the production of protective antioxidants in cancer cells, has been used to treat rheumatoid arthritis for decades. Future clinical trials using this combination therapy will determine the extent to which this targeted treatment option improves the prognosis of small cell lung cancer patients. It is currently in clinical trials for cancer treatment. Lung cancer is the leading cause of cancer death in the United States. Despite evidence of molecular abnormalities in biological specimens, progress in this disease is hampered by the lack of diagnostic markers useful for clinical practice. The majority of patients with lung cancer are still diagnosed at an advanced stage, when prognosis is poor. This article reviews new strategies being studied for the early detection of lung cancer. These strategies involve new methods of imaging (including low-dose computed tomography CT scanning), DNA analysis, and proteomic-based techniques. These strategies have not only improved our understanding of lung cancer but show promise in offering better survival to patients with this deadly disease. Of paramount importance in the search for methods of early detection is the need for the identification of the ideal population to screen, a multidisciplinary approach, and validation of promising techniques.
Jan 2022 DOI 10.14302/issn.2578-8590.ipj-21-4026
Karabayev M.Corresponding author
Fergana Medical Institute of Public Health, Uzbekistan.
A theoretical paper proposes applications of golden proportion principles to physiological diagnostics. It outlines proposed metrics and discusses validation needs and limitations.
Nov 2019 DOI 10.14302/issn.2639-3166.jar-19-3089
Masoero GiorgioCorresponding author
Accademia di Agricoltura di Torino, Italy
The agronomic management of symbiotic (S) inoculations, by means of bio-fertilizers (BF), is aimed at inducing modifications of the plant rhizosphere and thereafter of the phenotype and yield of the crop. It is here shown that the yield response of maize to a symbiotic treatment may be correlated to six easy-to-calculate indicator variables on the basis of the raw foliar pH, NIR-Spectroscopy of leaves, and the NIRS of hay litter-bags from soils. It has been confirmed, in a set of thirteen pairwise comparisons of Symbiotic (S) soil inoculated by BF vs. Control (non-inoculated soil; C), that the inoculation on average acidified the leaves by -3.7% pH units (P<0.0001). The responses in yield ranged from +25.2% to -9.2% (av.ge +3.5%; P = 0.03), but with average null responses in two centers and a significant response (+11%) in a third center. NIR-Tomoscopy scans (No. 574) were also performed on the leaves, and in addition, hay-litter-bags that had previously been buried in fields were dug up after two months, and 431 NIR- scans were acquired. The effect-size on the yield was expressed as the logarithm of the response ratio, i.e. the mean of the inoculated Symbiotic treatment divided by the mean of the non-inoculated Control for each pairwise comparison. A multiple regression model was developed to predict the symbiotic response to the treatment using six independent variables, including the squared litter-bag fingerprints, and an R2adj. level of 0.78 (P=0.01) was reached, with a standard error of ±4%. Validation in one external maize field, with a positive response to bio-fertilizers, demonstrates the juxtaposition of the estimated and accomplished yield. In a second experiment, with 40 pairwise comparisons, the two tested maize varieties did not respond to five types of bio-fertilizer, and the negative results were predicted at 84% (P 0.0012). The soil biota is a key factor for the application of appropriate microbial inoculants in the field, but the genotype/genotype interactions between the microbial strain (s) and the crop cultivar (s) require prior screening to obtain the desired results.
Mar 2019 DOI 10.14302/issn.2643-2811.jmbr-19-2652
Zhao BinCorresponding author
School of Science, Hubei University of Technology, Wuhan, Hubei, China.
This methods paper combines molecular docking and biomathematical modeling to construct a virtual neuron framework for studying sleep‑related memory consolidation. It outlines model components and validation approach.
Feb 2019 DOI 10.14302/issn.2471-7061.jcrc-18-2526
E. Ahmed FaridCorresponding author
GEM Tox Labs, Institute for Research in Biotechnology, 2905 South Memorial Drive, Greenville, NC 27834, USA.
There is currently no validated micro(mi)RNA diagnostic stool test to screen for colon cancer (CC) on the market because of the complexity of fecal density, vulnerability of stool to daily changes, and the presence of three sources of miRNAs in stool (cell-free from fecal homogenates, exsosomal miRNAs from fecal exosomes, and fecal colonocytes). To address these complexities, we have first carried out a microarray miRNA experiment, using Affymetrix GeneChip miRNA 2.0 Arrays, on immunocaptured and enriched stool colonocytes of 15 subjects (three healthy controls and twelve colon cancer patients [three TNM stage 0-1 (e.g., polyps◻ ³ 1 cm, villous or tubvillous, or with high grade dysplasia), three stage 2, three stage 3, and three stage 4 in triplicates to select a smaller panel of 14 preferentially expressed mature miRNAs associated with colon cancer (12 Up-Regulated, miR-19a, miR-20a, miR-21, miR-31, miR-34a, miR-96, miR-106a, miR-133a, miR-135b, miR-206, miR-224 and miR-302; and 2 Down-Regulated, miR-143 and miR-145). In a subsequent validation study carried out on total small RNA extracted by immunocapture, followed by RT that employed TaqMan® miRNA Reverse Transcription (RT) Kit and a Custom TaqMan RT Primer Pool, absolute quantification of miRNAs, in copies/µl, was measured using a chip-based Absolute QuantStudio 3D Digital PCR analysis. To ensure that we have chosen human and not bacterial small total RNA, we have carried out coextraction protocols with E. coli K1 strain RS18, compare Agilent electrophoretic patterns, and also sequenced random samples throughout this research using mRNA/miRNA sequencing. Our initial quantitative dPCR miRNA data presented herein showe that the quantitative changes in the expression of a few mature miRNA genes in stool, which are associated with right and left colon cancer, would provide for a more convenient, sensitive and specific diagnostic screening markers thatare more useful than those test markers currently available on the market, such as the low-sensitivity (<15%) fecal occult blood test (FOBT); result in better compliance; and is more economical than the invasive and expensive colonoscopy exam in colon cancer, which can be cured if that cancer is detected at the early TNM stages, and that becomes incurable and deadly if not diagnosed before metastasis. Initial test performance characteristics of the miRNA approach showed that the test has a high numerical predictive value in colon cancer. Moreover, underpinning of the miRNA markers as a function of total RNA showed that the test can numerically differentiate between control subjects and colon cancer patients, particularly at the early stages of that curable cancer. We propose to extend our initial research results to a larger prospective and randomized five-years nested case-control study, to validate the expression of the above 14 miRNAs, in stool of 180 individuals in an epidemiologically designed study, using (30 controls and 150 colon cancer patients (thirty precancerous polyps (stage 0-1), forty five stage 2, and seventy-five colon cancer stages 3 or 4). chosen randomly by an epidemiological method from 900 control and CC subjects to allow for an adequate time to collect the required 900 stool samples, as well as allowing for statistically valid analysis, standardized test conditions, and to provide a mean for determining the true sensitivity and specificity of a miRNA-screening approach in noninvasive human stool. Power-analysis has indicated that a total of 180 individuals, which will take us 5 years to enroll in testing, is an appropriate number of subjects to standardize and validate our proposed miRNA screening test. We may find out at the end of the proposed validation study in stool that fewer miRNAs, or even one miRNA, may suffice to serve as an efficient and a quantitative marker for the non-invasive diagnostic screening of colon cancer in human stool. The above approach when combined with bioinformatics analysis, to correlate miRNA seed data with our previously published messenger (m)RNA target data in stool, allows for a thorough mechanistic understanding of how miRNA genes regulate mRNA expression, and would offer a better comprehensive diagnostic screening test for the non-invasive early detection stage (0-1) of colon cancer. In order to show the clinical sensitivity and specificity of the proposed miRNA test, the absolute miRNA PCR values, in copies/µl, will be correlated with FOBT, colonoscopy, and pathology data. Standardization will establish test’s performance characteristics (sample selection, optimal sample running conditions, preservation and storage) to ensure that the assay will perform the same way in any laboratory, by any trained personnel, anywhere in the World. Ultimately, a smaller number of selected validated miRNAs (<10) showing increased and reduced expression could suffice to give quantitative miRNAs colon cancer expression values, useful for the early diagnostic screening of that curable cancer.
Jan 2019 DOI 10.14302/issn.2641-5526.jmid-18-2529
Luis Fernández-Martínez JuanCorresponding author
Group of Inverse Problems, Optimization and Machine Learning. Department of Mathematics. C/ Federico García Lorca, 18. 33007 Oviedo. University of Oviedo. Spain
Discrimination of case-control status based on gene expression differences has potential to identify novel pathways relevant to neurodegenerative diseases including Parkinson’s disease (PD). In this paper we applied two different novel algorithms to predict dysregulated pathways of gene expression across several different regions of the brain in PD and controls. The Fisher’s ratio sampler uses the Fisher’s ratio of the most discriminatory genes as prior probability distribution to sample the genetic networks and their likelihood (accuracy) was established via Leave-One-Out-Cross Validation (LOOCV). The holdout sampler finds the minimum-scale signatures corresponding to different random holdouts, establishing their likelihood using the validation dataset in each holdout. Phenotype prediction problems have by genesis a very high underdetermined character. We used both approaches to sample different lists of genes that optimally discriminate PD from controls and subsequently used gene ontology to identify pathways affected by disease. Both algorithms identified common pathways of Insulin signaling, FOXA1 Transcription Factor Network, HIF-1 Signaling, p53 Signaling and Chromatin Regulation/Acetylation. This analysis provides new therapeutic targets to treat PD.
Nov 2018 DOI 10.14302/issn.2642-3146.jec-18-2416
K.G. Palmer WilliamCorresponding author
Independent Researcher, TRI-LEA-EM, 76 Sideroad 33-34, RR 5, Paisley, ON N0G 2N0, Canada.
Wind turbines are often perceived as benign. This can be attributed to the population majority dwelling in urban locations distant from most wind turbines. Society may understate the risk to individuals living near turbines due to an overstatement of the perceived benefits of turbines, and an understatement of the risk of injury from falling turbine parts, or shed ice. Flaws in risk calculation may be attributed to a less than fully developed safety culture. Indications of this are the lack of a comprehensive industry failure database, and safety limits enabling the industry growth, but not protective of the public. A comprehensive study of wind turbine failures and risks in the Canadian province of Ontario gives data to enable validation of existing failure models. Failure probabilities are calculated, to show risk on personal property, or in public spaces. Repeated failures, and inadequate safety separation show public safety is not currently assured. A method of calculating setbacks from wind turbines to mitigate public risk is shown. Wind turbines with inadequate setbacks can adversely impact public health both directly from physical risk and indirectly by irritation from loss of safe use of property. Physical public safety setbacks are separate from larger setbacks required to prevent irritation from noise and other stressors, particularly when applied to areas of learning, rest and recuperation. The insights provided by this paper can assist the industry to enhance its image and improve its operation, as well as helping regulators set safety guidelines assuring protection of the public.
Oct 2018 DOI 10.14302/issn.2326-0793.jpgr-18-2418
Tarassishin LeonidCorresponding author
Department of Biological Sciences.
A brief review surveys molecular biomarkers across discovery, validation, and clinical translation, with examples in oncology and chronic disease.
Sep 2018
Alnaji AbbasCorresponding author
Consultant Neurosurgeon, Al-sadir medical city, Najaf, Iraq
This letter presents a clinician's perspective on the biological basis of diabetes mellitus at the cellular level. Drawing on neurosurgical practice, the author argues that persistent dysglycemia hinders recovery and may reflect long-standing intracellular processes, calling for causal, interdisciplinary management beyond symptomatic care. The piece outlines testable hypotheses and invites further laboratory validation.
Aug 2018 DOI 10.14302/issn.2690-4721.ijcm-18-2217
Samaras ShivanthiCorresponding author
Molecular Microbiology, School of Allied Health Sciences, Faculty of Health & Life Sciences, Hawthorn Building, The Gateway, De Montfort University, Leicester, LE1 9BH United Kingdom
Background Overuse of beta-lactam antibiotics has lead to selection for extended-spectrum β-lactamase (ESBL) producing Enterobacteriaceae, a major cause of antibiotic resistant urinary tract infections (UTIs). Standard detection methods are time-consuming, with disputed accuracy. This study describes a novel real-time PCR method to detect CTX-M, SHV, OXA and TEM. Methods 179 Enterobacteriaceae isolates from UTIs were collected from the Leicester Royal Infirmary, UK. A multiplex Plexor®-based real-time PCR assay detected ESBLs using their specific amplicon melting temperature, during each cycle, removing the need for a melt-curve analysis. Validation was achieved by end-point PCR and disk diffusion. Results The method was able to produce rapid and accurate results, achieving a sensitivity and specificity of 94.9% and 72% respectively, and the assay can differentiate between the different ESBL genes, with ease. Conclusions With further investigation, a Plexor®-based assay could form the basis of a high-throughput kit that health services could use to detect ESBLs or other antibiotic resistance genes.
May 2018 DOI 10.14302/issn.2639-3166.jar-18-2084
Masoero GiorgioCorresponding author
Accademia di Agricoltura di Torino, Torino, Italy
The biofertilization of cropsusing microbial biota in the soil (MBS) is a modern practice that is used to sustain fertility. MBS agents can promote the yield and health of crops, by luxuriating in the shoot as well as in the root systems. Farmers devoted to systematic MBS fertilization are creating a “Symbiotic” (S) form of agriculture, which offers a greater advantage of resilience than Conventional (C) or organic farming. Since MBS is involved in organic matter degradation, hay-litter-bag probes can be used to reflect a global functionality of the active soil, in the short-medium term. It is here shown that the NIRS hay-litter-bag technique, intended not as mass decay but as a quality evolution of the hay probes, can be modelled as a valid footprint of S vs. C soils. A patented MBS was used in eight experiments in which litter-bags from an S treated thesis were compared with equivalent litter-bags from a non-inoculated C thesis. The chemical signature of the S vs. C in the litter-bag composition was a percentage decrease of sugars and fibres. A smart NIRS device was used to discriminate the origin of the S vs. C litter-bags and a sensitivity of 71% (P<0.0001) was obtained. External validations on 37 S farms showed that three NIRS models discriminated the true positive S spectra, with a sensitivity of 90% as single and 98% as compound probabilities The NIRS radiation of the hay-litter-bags confirmed the results of the S vs. C agriculture soil footprint. Moreover, the SCIO-NIR devices also made it possible to connect the S farms in a smart network.
Mar 2018
Liu XiaopingCorresponding author
School of Mathematics and Statistics, Shandong University at Weihai, Weihai 264209, China
An important use of proteomics data from Mass Spectrometry (MS) is the classification of tumor types with respect to peptides in specific cancer types. It is highly critical to find an optimal set of markers among specific cancer peptides whose expression can be clinically utilized to build assays for the diagnosis or to track the progression of specific cancer types. A number of feature selection algorithms have been proposed to obtain the classification of MS data. In this article, we proposed an improved feature selection algorithm based on feature weighting. Relief algorithm can calculate the weight of different features according to the correlation between their characteristics and categories. F-score is a simple filter-based feature selection method by evaluating how two sets of real numbers discriminate from each other. The main goal of this paper is to introduce a new feature weighting selection algorithm combining score from f-value and weight from relief, which is more accurate when classifying high-resolution MALDI-TOF (matrix-assisted laser desorption and ionization time-of-flight) MS data. We have developed a four-step strategy for data processing based on: (1) Align the study sets by binning of raw MS data, (2) local maximum search(LMS) peak detection, (3) a new combination feature weighting selection algorithm and (4) support vector machines achieve a satisfactory performance of identifying cancer and the healthy. The best parameter set for LMS were achieved with control variable method, which achieve an average accuracy of 97.4167% (sd = 0.0146) and the best accuracy of 98.6111% in 1000 independent 10 -fold cross validations.
Sep 2017 DOI 10.14302/issn.2474-7785.jarh-17-1727
Akazawa ManabuCorresponding author
Public Health and Epidemiology, Meiji Pharmaceutical University
Background: Healthcare services provided to patients should vary depending on disease severity. However, disease severity bias, a type of selection bias, is a commonly encountered problem in administrative database studies. Herein, we selected chronic obstructive pulmonary disease (COPD), which commonly affects elderly Japanese citizens, for the development and validation of a severity classification system based on a health insurance claims database. Methods: Patients who received COPD-related diagnostic codes in 2011 were selected from a commercially based health insurance claims database. COPD patients were randomly divided into two groups to develop and validate severity scores. A principal component analysis was used to estimate factor loadings used to weight calculations of COPD severity scores. Score validity was evaluated using a linear trend test to predict COPD treatment costs and acute exacerbation events. Results: Using records from 880 patients, ten variables were created: acute exacerbation events, emphysema diagnoses, laboratory test and oxygen therapy procedures, prescribed anticholinergic, inhaled corticosteroid (ICS), short acting beta-agonist, and long acting bronchodilator (LABA) agents, asthma diagnosis and patient birth years. Factor loadings from LABA and ICS prescriptions had the strongest impacts on estimated severity scores (0.50 and 0.49, respectively). Among 300 validation group patients, scores were found to associate with increasing trends of median costs and exacerbation risks (p for trend < 0.05). Conclusions: Estimatedseverity scores would help to predict COPD-related medical costs and exacerbation events. For further clinical implementation, this classification system should be re-evaluated using clinical lung functions information indicative COPD severity and treatment choices.
Jan 2017 DOI 10.14302/issn.2476-1710.jdt-16-1324
Meiser SusanneCorresponding author
University of Potsdam, Department of Psychology
An important step in the validation of disorder-specific etiological models is the examination of the predictive specificity of proposed vulnerability factors. It may advance the understanding of the emergence of comorbidity and the identification of at risk-populations for mental disorders. To enhance the currently limited evidence on the specificity of Beck´s cognitive diathesis-stress model of depression, the present study investigated longitudinal effects of dysfunctional attitudes and stressful life events on the development of depressive, eating disorder and aggressive symptoms in children and adolescents. A large sample of initially asymptomatic children and adolescents completed self-report symptom measures at study entrance and again approx. 20 months later, and reported stressful life events during the study interval. Stressful life events proved to be a risk factor to all investigated symptom domains. Dysfunctional attitudes at T1 were prospectively related to depressive symptoms, aggressive behavior and weight concerns at T2. However, types of associations varied as dysfunctional attitudes showed linear associations with weight concern, but nonlinear effects on depressive and aggressive symptomatology. Findings of the current study thus suggest that dysfunctional attitudes are not uniquely related to the development of depressive symptomatology in children and adolescents, but may contribute to adverse outcomes in various symptom domains. Thus, intervention efforts based on Beck´s vulnerability - stress model of depression may turn out to be useful in reducing vulnerability to a variety of outcomes in children and adolescents.
Oct 2016 DOI 10.14302/issn.2574-450X.jom-16-1003
Daniel CottamCorresponding author
Introduction: The Roux-en-Y Gastric Bypass (RYGB) has been one of the most popular surgeries in the USA for years. While many models have been made to investigate the factors that affect weight loss, these factors are still highly debated. Objective: To create a model that predict performance of RYGB patients. Methods: 110 out of 344 patients who received a RYGB at a single institution between Jan 2010 and April 2014 were included in this study. Data was collected retrospectively. Patients were included if they had greater than 1 year follow up with at least three follow up points and could be modeled with r2>0.95. All patients were one year beyond surgery, while 40 were completely lost to follow up, 104 at 1 month, 138 at 3 months, 188 at 6 months, and 225 at one year. 9 patients were not included because they did not meet the criteria of the study. Patients were divided into quartiles based on percentage excess weight loss (%EWL) at one year. Multivariate analysis was performed to determine the significant factors that influence patients being in the first quartile of weight loss (17-60% %EWL). Results: Only males with a Body Mass Index (BMI) above 44 and females with a BMI above 64 were found to be predictive of patients being in the first quartile. Our model has Positive and Negative predictor values of 66% and 80% respectively with sensitivity and specificity of 29% and 95% respectively. Conclusions: An model to predict %EWL was created, only gender and pre-operative BMI were found to be significant factors. In general females have better outcomes with higher BMI’s than do males. This information should be discussed with patients when deciding a procedure. However, more studies are needed for validation of these results.
May 2014 DOI 10.14302/issn.2374-9431.jbd-13-283
Mei YongCorresponding author
Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011
Continuous-time glucose monitoring (CGM) effectively improves glucose control, as oppose to infrequent glucose measurements (i.e. using Lancet Meters), by providing frequent blood glucose concentration (BGC) to better associate this variation with changes in behavior. Currently, the most widely used CGM devices rely on a sensor that is inserted invasively under the skin. Because of the invasive nature and also the replacement cost of sensors, the primary users of current CGM devices are insulin dependent people (type 1 and some type 2 diabetics). Most non-insulin dependent diabetics use only lancet glucose measurements. The ultimate goal of this research is the development of CGM technology that overcomes these limitations (i.e. invasive sensors and their cost) in an effort to increase CGM applications among non-insulin dependent people. To meet this objective, this preliminary work has developed a methodology to mathematically infer BGC from measurements of non-invasive input variables which can be thought of as a “virtual” or “soft” sensor approach. In this work virtual sensors are developed and evaluated on 20 subjects using four BGC measurements per day and eight input variables representing meals, activity, stress, and clock time. Up to four weeks of data are collected for each subject. One evaluation consists of 3 days of training and up to 25 days of testing data. The second one consists of one week of training, one week of validation, and 2 weeks of testing data. The third one consists two weeks of training, one week of validation and one week of testing data. Model acceptability is determined on an individual basis based on the fitted correlation to CGM testing data. For 3 day, 1 week, and 2 weeks training studies, 35%, 55% and 65% of the subjects, respectively, met the Acceptability Criteria that we established based on the concept of usefulness.
Sep 2013 DOI 10.14302/issn.2326-0793.jpgr-13-257
O’Connell KathleenCorresponding author
Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC,
Lapatinib, a small molecule tyrosine kinase inhibitor is currently used in the treatment of HER2-positive breast cancer. The aim of this study was to further understanding of lapatinib response for the development of novel treatment lapatinib-focussed treatment strategies. HER2-overexpressing SKBR3 breast cancer cells were treated with lapatinib for 12 hours and the resultant proteome analyzed by a comprehensive ion-current-based LC-MS strategy. Among the 1224 unique protein identified from SKBR3 cell lysates, 67 showed a significant change in protein abundance in response to lapatinib. Of these, CENPE a centromeric protein with increased abundance, was chosen for further validation. Knockdown and inhibition of CENPE demonstrated that CENPE enhances SKBR3 cell survival in the presence of lapatinib. Based on this study, CENPE inhibitors may warrant further investigation for use in combination with lapatinib.