Own price elasticities of the demand for sugar-sweetened beverages in Bangladesh.

BACKGROUND: Consumption of sugar-sweetened beverages (SSB) is a major global public health problem. Increasing the price of SSBs through taxation is an effective tool to reduce SSB consumption. Price-elasticity estimates are useful in measuring the effect of taxation on consumption. We estimated the own price elasticities of demand for SSBs in Bangladesh, which will inform how SSB taxes could affect behaviour. METHODS: We used Household Income and Expenditure Survey (HIES) 2016 data, which is a nationally representative dataset at the household level across the country and is conducted using stratified random sampling method. Deaton's method was used to estimate the price elasticities for SSBs in Bangladesh. RESULTS: We found that the own price elasticity for SSBs varied between - 0.53% to -1.17% by types of SSBs in Bangladesh. The price elasticity for soft drinks was - 1.17, indicating that if the price of soft drinks increases by 10% via taxes, the quantity consumed of these beverages would reduce by 11.7%. CONCLUSION: This is the first study that estimates the own price elasticities of demand for SSBs in Bangladesh. Our results suggest to raise SSB prices through increased taxation in order to reduce SSB consumption and ensure public health gains in Bangladesh.

Electronic aggregated data collection on cervical cancer screening in Bangladesh since 2014: what the data tells us?

INTRODUCTION: To reduce the high prevalence of cervical cancers among the Bangladeshi women, the Government of Bangladesh established a national cervical cancer screening programme in 2005 for women aged 30 to 60 years. The District Health Information System Version 2 (DHIS2) based electronic aggregated data collection system is used since the year 2013. This study summarises data from the year 2014 to 2022 to assess the effectiveness of the electronic data collection system in understanding the outcome of the screening programme. METHODS: This is a descriptive study based on secondary data extracted in MS Excel from the DHIS2-based electronic repository of the national cervical cancer screening programme of Bangladesh. The respondents were women aged 30-60 years, screened for cervical cancer using VIA (Visual Inspection of cervix with Acetic acid) method in 465 government health facilities. The data were collected on the participants' residential location, month and year of screening, name and type of health facilities performing VIA, and VIA screening results. RESULTS: The national screening programme reported a total 3.36 million VIA tests from 465 government hospitals in 8 years (2014 to 2022). The national average VIA-positivity rate was 3.6%, which varied from 1.4 to 9.5% among the districts. This national screening programme witnessed an exponential growth, year after year, with 83.3% increase in VIA test from 2014 to 2022. The primary and the secondary care hospitals were the highest collective contributors of VIA tests (86.2%) and positive cases (77.8%). The VIA-positivity rates in different hospital types varied widely, 7.0% in the medical university hospital, 5.7% in the medical college hospitals, 3.9% in the district/general hospitals, and 3.0% in the upazila health complexes. CONCLUSIONS: A national cervical cancer screening programme using VIA method and a DHIS2-based electronic data collection backbone, is effective, sustainable, and useful to understand the screening coverage, VIA positivity rate and geographic distribution of the participants and case load to initiate policy recommendations and actions. Decentralization of the screening programme and more efforts at the primary and secondary care level is required to increase screening performances.

Assessment of the botanical origin of Saudi Arabian honey samples to identify pollen with chromatographic tools and packing and storage.

The increasing demand for honey purification and authentication necessitates the global utilization of advanced processing tools. Common honey processing techniques, such as chromatography, are commonly used to assess the quality and quantity of valuable honey. In this study, 15 honey samples were authenticated using HPLC and GC-MS chromatographic methods to analyze their pollen spectrum. Various monofloral honey samples were collected, including Acacia, Hypoestes, Lavandula, Tamarix, Trifolium, and Ziziphus species, based on accurate identification by apiarists in 2023 from the Kingdom of Saudi Arabia. Honey analysis revealed the extraction of pollen from 20 different honeybee floral species. Pollen identified from honey samples using advanced chromatographic tools revealed dominant vegetation resources: Ziziphus species (23%), Acacia species (25%), Tamarix species (34%), Lavandula species (26%), Hypoestes species (34%), and Trifolium species (31%). This study uses HPLC to extract phenolic compounds, revealing dominant protocatechuic acid (4.71 mg g-1), and GC-MS to analyze organic compounds in honey pollen. Specifically, 2-dodecanone was detected with a retention time of 7.34 min. The utilization of chromatographic tools in assessing honey samples for pollen identification provides a reliable and efficient method for determining their botanical origins, thereby contributing to the quality control and authentication of honey products.

Characterization of an endo-beta-1,4 glucanase gene from paper-degrading and denim bio-stoning cellulase producing Aspergillus isolates.

Cellulases are used in textile, pulp and paper, brewery and wine, sugars, and ethanol industries. Four fungal isolates obtained from organic municipal solid wastes (OMSW) were selected based on their cellulolytic activity on carboxymethyl cellulose (CMC) agar medium. Based on the internal transcribed spacer (ITS) sequence of the ribosomal DNA, the four cellulolytic isolates were identified as Aspergillus fumigatus AKAL1, Aspergillus oryzae AKAL4, Aspergillus flavus AKAL8, and Aspergillus flavus AKAL9. After 9 days of fermentation at 30°C and pH 6.5 under 110 rpm agitation, these isolates produced the maximum amount of cellulase. The cellulase showed optimum activity at temperature 35-40°C and pH 6.0-7.0 and was stable for 1 h at 25-45°C and pH 5.0-7.0. The Mg2+ and Zn2+ significantly increased but Hg2+ , K+ , and Ca2+ severely repressed the cellulase activity. Degradation of filter papers and bio-stoning of denim was successfully done with the crude cellulase. An endo-ß-1,4-glucanase was isolated and characterized from Aspergillus isolates. Genome-wide analysis revealed that the genomes of A. oryzae, A. fumigatus, and A. flavus, the pertinent species of the fungal isolates, had 23, 25, and 22 cellulase genes, respectively. Phylogenetic analysis revealed that the cellulases in these fungal species were divided into three major groups, and the isolated endo-ß-1,4-glucanase clustered to Group II. Ten different motifs are present in cellulases of the three species. Results herein provide a valuable resource for understanding cellulase genes in Aspergillus species and potential application of cellulase in textile and fermentable sugars production industries.

The crowding-out effect of sugar-sweetened beverages (SSBs) on household expenditure patterns in Bangladesh.

BACKGROUND: Consumption of sugar-sweetened beverages (SSBs) or sugary drinks may reduce or even eliminate the household income allocation for other essential commodities. Reducing expenditure for consumption of other household commodities is known as the crowding-out effect of SSB. We aimed to determine the crowding-out effect of SSB expenditure on other household commodities. In addition, we also identified the factors influencing the household's decision to purchase of SSBs. METHODS: We used the logistic regression (logit and multinomial logit models) and the Seemingly Unrelated Regression (SUR) models. In order to find the probability of a given change in the socio-demographic variables, we also estimated the average marginal effects from the logistic regression. In addition, we regressed the SUR model by gender differences. We used Household Income and Expenditure Survey (HIES) 2016 data to estimate our chosen econometric models. HIES is nationally representative data on the household level across the country and is conducted using a multistage random sampling method by covering 46,075 households. RESULTS: The findings from the logit model describe that the greater proportion of male members, larger household size, household heads with higher education, profession, having a refrigerator, members living outside of the house, and households with higher income positively affect the decision of purchasing SSB. However, the determinants vary with the various types of SSB. The unadjusted crowding out effect shows that expenditure on SSB or sugar-added drinks crowds out the household expenditure on food, clothing, housing, and energy items. On the other hand, the adjusted crowding out effect crowds out the spending on housing, education, transportation, and social and state responsibilities. CONCLUSION: Although the household expenditure on beverages and sugar-added drinks is still moderate (around 2% of monthly household expenditure), the increased spending on beverages and sugar-added drinks is a concern due to the displacement of household expenditure for basic commodities such as food, clothing, housing, education, and energy. Therefore, evidence-based policies to regulate the sale and consumption of SSB are required for a healthy nation.

SNR enhancement for Brillouin distributed optical fiber sensors based on asynchronous control.

We propose the asynchronous control of anisotropic diffusion (AD) algorithm, and such asynchronous anisotropic diffusion (AAD) algorithm is demonstrated experimentally to reduce noise from the sensing signals obtained from Brillouin distributed optical fiber sensors. The performance of the proposed AAD algorithm is analyzed in detail for different experimental conditions and compared with that of block-matching and 3D filtering, two-dimensional wavelet denoising, AD, and non-local means algorithms. Some key factors of the proposed algorithm, such as the impact of convolution kernel size on the performance of AD algorithms, the influence of low sampling point number (SPN) on the quality of Brillouin frequency shift and the selection of diffusion thresholds are analyzed and discussed with experimental results. The experimental results validate that the AAD algorithm can provide better root-mean-square error (RMSE) and spatial resolution (SR) than the other four algorithms, especially for higher signal-to-noise ratio (SNR) improvement and higher SPNs. For lower SPNs, the performance of AAD is also not inferior to the RMSE performance of NLM and AD. The runtime of the AAD algorithm is also quite low. Moreover, the proposed algorithm offers the best SR performance as compared to other noise reduction algorithms investigated in this study. Thus, the proposed AAD algorithm can be an effective candidate to improve the measurement accuracy of Brillouin distributed optical fiber sensors.

Genistein: A Potential Natural Lead Molecule for New Drug Design and Development for Treating Memory Impairment.

Genistein is a naturally occurring polyphenolic molecule in the isoflavones group which is well known for its neuroprotection. In this review, we summarize the efficacy of genistein in attenuating the effects of memory impairment (MI) in animals. Scopus, PubMed, and Web of Science databases were used to find the relevant articles and discuss the effects of genistein in the brain, including its pharmacokinetics, bioavailability, behavioral effects, and some of the potential mechanisms of action on memory in several animal models. The results of the preclinical studies highly suggested that genistein is highly effective in enhancing the cognitive performance of the MI animal models, specifically in the memory domain, including spatial, recognition, retention, and reference memories, through its ability to reduce oxidative stress and attenuate neuroinflammation. This review also highlighted challenges and opportunities to improve the drug delivery of genistein for treating MI. Along with that, the possible structural modifications and derivatives of genistein to improve its physicochemical and drug-likeness properties are also discussed. The outcomes of the review proved that genistein can enhance the cognitive performance and ameliorate MI in different preclinical studies, thus indicating its potential as a natural lead for the design and development of a novel neuroprotective drug.

Tilianin: A Potential Natural Lead Molecule for New Drug Design and Development for the Treatment of Cardiovascular Disorders.

Cardiovascular disorders (CVDs) are the leading risk factor for death worldwide, and research into the processes and treatment regimens has received a lot of attention. Tilianin is a flavonoid glycoside that can be found in a wide range of medicinal plants and is most commonly obtained from Dracocephalum moldavica. Due to its extensive range of biological actions, it has become a well-known molecule in recent years. In particular, numerous studies have shown that tilianin has cardioprotective properties against CVDs. Hence, this review summarises tilianin's preclinical research in CVDs, as well as its mechanism of action and opportunities in future drug development. The physicochemical and drug-likeness properties, as well as the toxicity profile, were also highlighted. Tilianin can be a natural lead molecule in the therapy of CVDs such as coronary heart disease, angina pectoris, hypertension, and myocardial ischemia, according to scientific evidence. Free radical scavenging, inflammation control, mitochondrial function regulation, and related signalling pathways are all thought to play a role in tilianin's cardioprotective actions. Finally, we discuss tilianin-derived compounds, as well as the limitations and opportunities of using tilianin as a lead molecule in drug development for CVDs. Overall, the scientific evidence presented in this review supports that tilianin and its derivatives could be used as a lead molecule in CVD drug development initiatives.

Kirenol: A Potential Natural Lead Molecule for a New Drug Design, Development, and Therapy for Inflammation.

Kirenol, a potential natural diterpenoid molecule, is mainly found in Sigesbeckia species. Kirenol has received a lot of interest in recent years due to its wide range of pharmacological actions. In particular, it has a significant ability to interact with a wide range of molecular targets associated with inflammation. In this review, we summarise the efficacy and safety of kirenol in reducing inflammation, as well as its potential mechanisms of action and opportunities in future drug development. Based on the preclinical studies reported earlier, kirenol has a good therapeutic potential against inflammation involved in multiple sclerosis, inflammatory bowel disorders, diabetic wounds, arthritis, cardiovascular disease, bone damage, and joint disorders. We also address the physicochemical and drug-like features of kirenol, as well as the structurally modified kirenol-derived molecules. The inhibition of pro-inflammatory cytokines, reduction in the nuclear factor kappa-B (NF-κB), attenuation of antioxidant enzymes, stimulation of heme-oxygenase-1 (HO-1) expression, and nuclear factor erythroid 2-related factor 2 (Nrf2) phosphorylation are among the molecular mechanisms contributing to kirenol's anti-inflammatory actions. Furthermore, this review also highlights the challenges and opportunities to improve the drug delivery of kirenol for treating inflammation. According to the findings of this review, kirenol is an active molecule against inflammation in numerous preclinical models, indicating a path to using it for new drug discovery and development in the treatment of a wide range of inflammations.

Blood biochemical parameters for assessment of COVID-19 in diabetic and non-diabetic subjects: a cross-sectional study.

This study aims to identify blood biomarkers for rapidly predicting progression and severity assessment of COVID-19 in type 2 diabetic (DM) and non-DM (NDM) patients. Among 211 hospitalized patients suspected of COVID-19, 98 were confirmed COVID-19 by rRT-PCR. The COVID-19 positive group contained 58 DM and 40 NDM patients with total death 9 of which 7 were males and 6 were DM, indicating males and DM individuals as more susceptible to COVID-19. Blood biomarkers notably serum ferritin, CRP, D-dimer, ALT, troponin I, and Hb1Ac were significantly (p < 0.05) higher in COVID-19 patients. Ferritin and HbA1c levels were significantly (p < 0.05) higher in DM than NDM COVID-19 patients. The present study suggests that ferritin and HbA1c levels for DM patients, and ferritin, D-dimer, ALT for NDM patients could be routinely used as biomarkers for progression and severity assessment of COVID-19. CRP and Troponin-I could be the predictor only for poor prognosis of COVID-19.

The Therapeutic Application of Tamarix aphylla Extract Loaded Nanoemulsion Cream for Acid-Burn Wound Healing and Skin Regeneration.

Background and Objectives: Nanomedicine is a constantly growing field for the diagnosis and treatment of various diseases as well as for regenerative therapy. Nanotechnology-based drug-delivery systems improve pharmacological and pharmacokinetic profiles of plants based biologically active molecules. Based on traditional claims, leaves of the Tamarix aphylla (TA) were investigated for their potential healing activity on burn wounds. Materials and Methods: In this study, TA-based nanoemulsion was prepared. The nanoemulsion was characterized for size, zeta potential, pH, viscosity, and stability. The nanoemulsion containing plant extract was converted into cream and evaluated for its efficacy against acid-burn wounds inflicted in the dorsum of rabbits. The animals were classified into four main groups: Group A as a normal control group, Group B as a positive control (treated with cream base + silver sulfadiazine), Group C as a standard drug (silver sulfadiazine), and Group D as a tested (treated with nanoemulsion cream containing TA extract). The prepared system could deliver TA to the target site and was able to produce pharmacological effects. On days 0, 7, 14, 21, 28, and 35, wound contraction rate was used to determine healing efficacy. The wound samples were collected from the skin for histological examination. Results: Based on statistical analysis using wound-healing time, Group D showed a shorter period (21.60 ± 0.5098) (p < 0.01) than the average healing time of Group C (27.40 ± 0.6002) (p < 0.05) and Group B (33.40 ± 0.8126) (p < 0.05). The histopathological assessment showed that burn healing was better in Group D compared with Group C and Group B. The nanoemulsion cream had a non-sticky texture, low viscosity, excellent skin sensations, and a porous structure. By forming a protective layer on the skin and improving moisture, it enhanced the condition of burnt skin. Conclusions: According to the findings of this study, nanoemulsion cream containing TA extract has great potential in healing acid-burn wounds

Routine mortality surveillance to identify the cause of death pattern for out-of-hospital adult (aged 12+ years) deaths in Bangladesh: introduction of automated verbal autopsy.

BACKGROUND: In Bangladesh, a poorly functioning national system of registering deaths and determining their causes leaves the country without important information on which to inform health programming, particularly for the 85% of deaths that occur in the community. In 2017, an improved death registration system and automated verbal autopsy (VA) were introduced to 13 upazilas to assess the utility of VA as a routine source of policy-relevant information and to identify leading causes of deaths (COD) in rural Bangladesh. METHODS: Data from 22,535 VAs, collected in 12 upazilas between October 2017 and August 2019, were assigned a COD using the SmartVA Analyze 2.0 computer algorithm. The plausibility of the VA results was assessed using a series of demographic and epidemiological checks in the Verbal Autopsy Interpretation, Performance and Evaluation Resource (VIPER) software tool. RESULTS: Completeness of community death reporting was 65%. The vast majority (85%) of adult deaths were due to non-communicable diseases, with ischemic heart disease, stroke and chronic respiratory disease comprising about 60% alone. Leading COD were broadly consistent with Global Burden of Disease study estimates. CONCLUSIONS: Routine VA collection using automated methods is feasible, can produce plausible results and provides critical information on community COD in Bangladesh. Routine VA and VIPER have potential application to countries with weak death registration systems.

Ex-situ catalytic pyrolysis of chicken litter for bio-oil production: Experiment and characterization.

The depletion of fossil fuels has been a greater concern to the world due to the demand for energy that tremendously increasing with urbanization and population growth. For sustainable development, power industries are trying to find suitable substitute of petroleum fuel which is environment friendly and economically feasible. The biomass such as the production of bio-oil from chicken litter could be a possible alternative source of energy. The conversion of the feedstock was conducted through a catalytic pyrolysis process in an ex-situ fixed bed reactor heated at 500 °C with a heating rate of 50 °C/min. Proximate, ultimate, and calorific analysis of the feedstock was studied using TGA/DTG analysis, CHNS, and bomb calorimeter, respectively. GCMS and py-GCMS experiments on the bio-oil showed that the HHV of the feedstock was 16.01 MJ/kg. The addition of catalyst improved the quality of the bio-oil yield. The presence of dolomite and ZMS-5 catalyst enhances the phenols and aromatic content, respectively. Biomass to catalyst (B/C) ratio increased the oil production from 43.6g to 51.9g for dolomite and 43.6g-47.1g for ZMS-5 with the B/C ration of 20g:3g. Elevating the B/C ratio increases the pyrolytic liquid yield with greater influence on the furanic compound.

Kinetics, detergent compatibility and feather-degrading capability of alkaline protease from Bacillus subtilis AKAL7 and Exiguobacterium indicum AKAL11 produced with fermentation of organic municipal solid wastes.

Alkaline proteases having activity and stability at alkaline pH possess a large variety of applications in many industries. Growing renewed interest urges the need to find a single alkaline protease with promising properties to be used in different industrial processes. Herein, alkaline proteases produced through fermentation of cheap and easily available organic municipal solid wastes by Bacillus subtilis AKAL7 and Exiguobacterium indicum AKAL11 were purified to investigate their kinetic and thermodynamic parameters, detergent compatibility, dehairing and feather-degrading capability. Sodium dodecyl sulfate polyacrylamide gel electrophoresis revealed that the purified protease from B. subtilis and E. indicum had molecular mass of ∼45 and 75 kDa, respectively. The protease from B. subtilis and E. indicum showed highest activity at 55 and 50 °C having low K m 1.17 and 0.567 mg/mL and high V max 416.67 and 333.33 µmole/min, respectively. The activation energy and temperature quotient of protease from B. subtilis and E. indicum were 26.52 and 65.75 kJ/mole, and 1.0004 and 1.0003 at 20-55 and 20-50 °C, respectively. Thermodynamics analysis revealed the formation of more ordered enzyme-substrate complexes along with spontenity of enzyme reaction. The protease from E. indicum exhibited better compatibility at higher concentration of detergents compared to that from B. subtilis. However, both proteases could retain more than 80% of the activity in the presence of 0.1% commercial laundry detergents. The purified protease from the both sources could degrade almost 90% of barbs and 40% of dry weight of the native feather and that from E. indicum could dehair cow skin. Results reported herein suggest that the alkaline protease from B. subtilis AKAL7 and E. indicum AKAL11 has biotechnological implications in detergent, leather and poultry feather processing industries.

Improving coverage of civil registration and vital statistics, Bangladesh.

PROBLEM: Bangladesh has no national system for registering deaths and determining their causes. As a result, policy-makers lack reliable and complete data to inform public health decisions. APPROACH: In 2016, the government of Bangladesh introduced a pilot project to strengthen the civil registration and vital statistics system and generate cause of death data in Kaliganj Upazila. Community-based health workers were trained to notify births and deaths to the civil registrar, and to conduct verbal autopsy interviews with family members of a deceased person. International experts in cause-of-death certification and coding trained master trainers on how to complete the international medical certificate of cause of death. These trainers then trained physicians and coders. LOCAL SETTING: Kaliganj Upazila has an estimated population of 304 600, and 5600 births and 1550 deaths annually. Health assistants and family welfare assistants make regular visits to households to track certain health outcomes. RELEVANT CHANGES: Following the start of the project in 2016, the number of births registered within 45 days rose from 873 to 4630 in 2018. The number of deaths registered within 45 days increased from 458 to 1404. During this period, health assistants conducted 7837 verbal autopsy interviews. Between January 2017 and December 2018, 105 master trainers and more than 7000 physicians were trained to complete the international medical certificate of cause of death and they completed more than 12 000 certificates. LESSONS LEARNT: Training community-based health workers, physicians and coders were successful approaches to improve death registration completeness and availability of cause-of-death data.

Enzalutamide and CXCR7 inhibitor combination treatment suppresses cell growth and angiogenic signaling in castration-resistant prostate cancer models.

Previous studies have shown that increased levels of chemokine receptor CXCR7 are associated with the increased invasiveness of prostate cancer cells. We now show that CXCR7 expression is upregulated in VCaP and C4-2B cells after enzalutamide (ENZ) treatment. ENZ treatment induced apoptosis (sub-G1) in VCaP and C4-2B cells, and this effect was further increased after combination treatment with ENZ and CCX771, a specific CXCR7 inhibitor. The levels of p-EGFR (Y1068), p-AKT (T308) and VEGFR2 were reduced after ENZ and CCX771 combination treatment compared to single agent treatment. In addition, significantly greater reductions in migration were shown after combination treatment compared to those of single agents or vehicle controls, and importantly, similar reductions in the levels of secreted VEGF were also demonstrated. Orthotopic VCaP xenograft growth and subcutaneous MDA133-4 patient-derived xenograft (PDX) tumor growth was reduced by single agent treatment, but significantly greater suppression was observed in the combination treatment group. Although overall microvessel densities in the tumor tissues were not different among the different treatment groups, a significant reduction in large blood vessels (>100 µm2 ) was observed in tumors following combination treatment. Apoptotic indices in tumor tissues were significantly increased following combination treatment compared with vehicle control-treated tumor tissues. Our results demonstrate that significant tumor suppression mediated by ENZ and CXCR7 combination treatment may be due, in part, to reductions in proangiogenic signaling and in the formation of large blood vessels in prostate cancer tumors.

Temperature extraction in Brillouin optical time-domain analysis sensors using principal component analysis based pattern recognition.

We propose and experimentally demonstrate the use of principal component analysis (PCA) based pattern recognition to extract temperature distribution from the measured Brillouin gain spectra (BGSs) along the fiber under test (FUT) obtained by Brillouin optical time domain analysis (BOTDA) system. The proposed scheme employs a reference database consisting of relevant ideal BGSs with known temperature attributes. PCA is then applied to the BGSs in the reference database as well as to the measured BGSs so as to reduce their size by extracting their most significant features. Now, for each feature vector of the measured BGS, we determine its best match in the reference database comprised of numerous reduced-size feature vectors of the ideal BGSs. The known temperature attribute corresponding to the best-matched BGS in the reference database is then taken as the extracted temperature of the measured BGS. We analyzed the performance of PCA-based pattern recognition algorithm in detail and compared it with that of curve fitting method. The experimental results validate that the proposed technique can provide better accuracy, faster processing speed and larger noise tolerance for the measured BGSs. Therefore, the proposed PCA-based pattern recognition algorithm can be considered as an attractive method for extracting temperature distributions along the fiber in BOTDA sensors.

Signal processing using artificial neural network for BOTDA sensor system.

We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

Can simple rules control development of a pioneer vertebrate neuronal network generating behavior?

How do the pioneer networks in the axial core of the vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge of the constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules to generate model networks that retain individual neuron and synapse resolution and are capable of reproducing correct, whole animal responses. We apply our developmental strategy to young Xenopus tadpoles, whose brainstem and spinal cord share a core vertebrate plan, but at a tractable complexity. Following detailed anatomical and physiological measurements to complete a descriptive library of each type of spinal neuron, we build models of their axon growth controlled by simple chemical gradients and physical barriers. By adding dendrites and allowing probabilistic formation of synaptic connections, we reconstruct network connectivity among up to 2000 neurons. When the resulting "network" is populated by model neurons and synapses, with properties based on physiology, it can respond to sensory stimulation by mimicking tadpole swimming behavior. This functioning model represents the most complete reconstruction of a vertebrate neuronal network that can reproduce the complex, rhythmic behavior of a whole animal. The findings validate our novel developmental strategy for generating realistic networks with individual neuron- and synapse-level resolution. We use it to demonstrate how early functional neuronal connectivity and behavior may in life result from simple developmental "rules," which lay out a scaffold for the vertebrate CNS without specific neuron-to-neuron recognition.

Discovery and validation of vascular endothelial growth factor (VEGF) pathway polymorphisms in esophageal adenocarcinoma outcome.

Polymorphisms in the vascular endothelial growth factor (VEGF)/angiogenesis pathway have been implicated previously in cancer risk, prognosis and response to therapy including in esophageal adenocarcinoma. Prior esophageal adenocarcinoma studies focused on using candidate polymorphisms, limiting the discovery of novel polymorphisms. Here, we applied the tagSNP (single nucleotide polymorphism) approach to identify new VEGF pathway polymorphisms associated with esophageal adenocarcinoma prognosis and validated them in an independent cohort of esophageal adenocarcinoma patients. In 231 esophageal adenocarcinoma patients of all stages/treatment plans, 58 genetic polymorphisms (18 KDR, 7 VEGFA and 33 FLT1) selected through tagging and assessment of predicted function were genotyped. Cox-proportional hazard models adjusted for important socio-demographic and clinico-pathological factors were applied to assess the association of genetic polymorphisms with overall survival (OS) and progression-free survival (PFS). Significantly associated polymorphisms were then validated in an independent cohort of 137 esophageal adenocarcinoma patients. Among the 231 discovery cohort patients, 86% were male, median diagnosis age was 64 years, 34% were metastatic at diagnosis and median OS and PFS were 20 and 12 months, respectively. KDR rs17709898 was found significantly associated with PFS (adjusted hazard ratio, aHR = 0.69, 95% confidence interval (CI): 0.53-0.90; P = 5.9E-3). FLT1 rs3794405 and rs678714 were significantly associated with OS (aHR = 1.44, 95% CI: 1.04-1.99; P = 0.03 and aHR = 1.50, 95% CI: 1.01-2.24; P = 0.045, respectively). No VEGFA polymorphisms were found significantly associated with either outcome. Upon validation, FLT1 rs3794405 remained strongly associated with OS (aHR = 1.59, 95% CI: 1.04-2.44; P = 0.03). FLT1 rs3794405 is significantly associated with OS in esophageal adenocarcinoma, whereby each variant allele confers a 45-60% increased risk of mortality. Validation and evaluation of this association in other cancer sites are warranted.