Fluorescence Spectroscopy Based Identification of Pseudomonas Aeruginosa and Escherichia Coli Suspensions.

In this article, Fluorescence spectroscopy has been employed for the identification of Pseudomonas aeruginosa (PA) and Escherichia coli (E. coli) in water suspension. Emission spectra of PA and E. coli suspensions have been acquired by using excitation wavelengths from 270 to 420 nm with steps of 10 nm to explore their spectral features. It has been found that the emission spectra of tryptophan, tyrosine, NADH and FAD, being the intracellular biomolecules present in both bacteria, can be used as fingerprints for their identification, differentiation and quantification. Both bacterial strains can clearly be differentiated from water and from each other by using λex 270-290 nm through spectral analysis and from λex: 300-500 nm by applying statistical analysis. Furthermore, calibration curves for different bacterial loads of PA and E. coli suspensions have been produced between colonies forming units per ml (CFUs/ml) the integrated intensities of their emission spectra. CFUs/ml of both bacterial suspensions have been determined through plate count method which was used as cross-reference for the analysis of emission spectra of both bacterial suspensions. These curves may be used to estimate CFU/ml of both PA and E. coli in unknown water suspensions by determining the integrating intensity of their emission spectra.

Overdose Risk and Brain Injury (Traumatic Brain Injury/Acquired Brain Injury), A Commentary.

OBJECTIVE: This commentary seeks to evaluate existing knowledge about the relationship between brain injury (BI) and overdose (OD), to unify distant bodies of literature, and to enhance prevention and treatment for opioid OD among individuals with BI. BACKGROUND: There is a hidden epidemic of undiagnosed BI in the United States. Due to lack of screening, the vast majority of BI sufferers do not know they have a BI. Not only are those with BI at elevated risk for opioid use, misuse, and opioid use disorder, but also they are at elevated risk for OD. Conversely, those with OUD and those who experienced an OD, are more likely to sustain BI. Key Findings/Conclusions: The existing literature suggests that primary strategies to reduce ABI (Acquired Brain Injury)/TBI (Traumatic Brain Injury) harms involve addressing: screening, stigma, racial disparities, and popular misconceptions about OD. The association between TBI and OD is an underexamined public health issue, exacerbated by the bidirectional nature of the relationship. Not only is TBI a risk factor for opioid OD; opioid OD was also found to be a major cause of ABI, which can have lifelong effects similar to Alzheimer's disease. Screening tools for BI were underutilized and inconsistently implemented across reviewed studies. Enhanced screening population wide is a promising intervention, complemented with expanded treatment and research. Black individuals face worse outcomes in BI and treatment outcomes. Anti-racist strategies must fight inequity while addressing social and structural drivers of overdose and BI within the opioid and opioid overdose crises.

Creating and evaluating the score to assess overdose: the OD score.

BACKGROUND: During disasters (including epidemics such as coronavirus disease 2019), the capacity of emergency departments is exceeded, thereby hindering the administration of appropriate lifesaving measures. Furthermore, the number of overdose patients increases because of the stress overload during emergency situation. The fact that overdose patients are forced to be transported to medical facilities that do not typically treat them is becoming worrisome. Moreover, there is no definitive score for overdose. This study aimed to create a patient-specific scoring system to assess overdose. METHODS: This was a retrospective single-center study. The evidence-based OD score was evaluated on a scale of 0-15. Further, logistic analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate the score. RESULTS: Overall, 262 patients (including 118 overdose patients) receiving care at the intensive care unit of Japan's Teikyo University Hospital in 2021 were targeted. Regarding the total OD score, ROC analysis revealed a cutoff of 8 (area under the curve [AUC]: 0.99, 95% confidence interval [CI]: 0.980-0.997, sensitivity: 0.95, specificity: 0.95, p < 0.05), which was considered to indicate an overdose. Of the items evaluated in the OD score, the scenario at the location of the patient's discovery (adjusted odds ratio [AOR]: 16.8, 95% CI: 5.0-255.9, p = 0.002) and recent experience of mental anxiety (AOR: 55.7, 95% CI: 2.8-5399.5, p = 0.03) significantly predicted an overdose in multivariable logistic regression analysis. External validation revealed that the OD score could also identify overdose in patients treated in a cohort from 2022 (average cutoff: 8.6, average AUC: 1.0, p < 0.0001). CONCLUSIONS: The OD score could accurately assess overdose patients. Medical facilities that do not frequently address overdose patients will benefit from the use of this score.

Synthesis of Enantiopure (S)-Atenolol by Utilization of Lipase-Catalyzed Kinetic Resolution of a Key Intermediate.

(S)-Atenolol ((S)-2-(4-(2-Hydroxy-3-(isopropylamino)propoxy)phenyl)acetamide) has been synthesized in >99% enantiomeric excess (ee) with the use of Candida antarctica lipase B from Syncozymes (Shanghai, China), in a kinetic resolution of the corresponding racemic chlorohydrin. A catalytic amount of base was used in deprotonation of the phenol building block. The enantiopurity of the chlorohydrin building block remained unchanged upon subsequent amination to yield the final drug. All four steps in the synthesis protocol have been optimized compared to previously reported methods, which makes this new protocol more sustainable and in accordance with green chemistry principles. The overall yield of (S)-atenolol was 9.9%, which will be further optimized.

The ß3-subunit modulates the effect of venom peptides ProTx-II and OD1 on NaV 1.7 gating.

The voltage-gated sodium channel NaV 1.7 is involved in various pain phenotypes and is physiologically regulated by the NaV -ß3-subunit. Venom toxins ProTx-II and OD1 modulate NaV 1.7 channel function and may be useful as therapeutic agents and/or research tools. Here, we use patch-clamp recordings to investigate how the ß3-subunit can influence and modulate the toxin-mediated effects on NaV 1.7 function, and we propose a putative binding mode of OD1 on NaV 1.7 to rationalise its activating effects. The inhibitor ProTx-II slowed the rate of NaV 1.7 activation, whilst the activator OD1 reduced the rate of fast inactivation and accelerated recovery from inactivation. The ß3-subunit partially abrogated these effects. OD1 induced a hyperpolarising shift in the V1/2 of steady-state activation, which was not observed in the presence of ß3. Consequently, OD1-treated NaV 1.7 exhibited an enhanced window current compared with OD1-treated NaV 1.7-ß3 complex. We identify candidate OD1 residues that are likely to prevent the upward movement of the DIV S4 helix and thus impede fast inactivation. The binding sites for each of the toxins and the predicted location of the ß3-subunit on the NaV 1.7 channel are distinct. Therefore, we infer that the ß3-subunit influences the interaction of toxins with NaV 1.7 via indirect allosteric mechanisms. The enhanced window current shown by OD1-treated NaV 1.7 compared with OD1-treated NaV 1.7-ß3 is discussed in the context of differing cellular expressions of NaV 1.7 and the ß3-subunit in dorsal root ganglion (DRG) neurons. We propose that ß3, as the native binding partner for NaV 1.7 in DRG neurons, should be included during screening of molecules against NaV 1.7 in relevant analgesic discovery campaigns.

The acceptability of overdose alert and response technologies: introducing the TPOM-ODART framework.

BACKGROUND: Opioids were implicated in approximately 88,000 fatal overdoses (OD) globally. However, in principle all opioid OD are reversible with the timely administration of naloxone hydrochloride. Despite the widespread availability of naloxone among people who use opioids (PWUO), many who suffer fatal OD use alone, without others present to administer the reversal agent. Recognising this key aspect of the challenge calls for innovations, a number of technological approaches have emerged which aim to connect OD victims with naloxone. However, the acceptability of OD response technologies to PWUO is of key concern. METHODS: Drawing on the Technology People Organisations Macroenvironment (TPOM) framework, this study sought to integrate acceptability-related findings in this space with primary research data from PWUO, affected family members and service providers to understand the factors involved in harm reduction technology acceptability. A qualitative study using a focus group methodology was conducted. The participant groups were people with lived experience of problem opioid use, affected family members and service providers. Data analysis followed a multi-stage approach to thematic analysis and utilised both inductive and deductive methods. RESULTS: Thirty individuals participated in one of six focus groups between November 2021 and September 2022. The analysis generated six major themes, three of which are reported in this article-selected for their close relevance to PWUO and their importance to developers of digital technologies for this group. 'Trust-in technologies, systems and people' was a major theme and was closely linked to data security, privacy and confidentiality. 'Balancing harm reduction, safety and ambivalence' reflects the delicate balance technological solutions must achieve to be acceptable to PWUO. Lastly, 'readiness-a double bind' encapsulates the perception shared across participant groups, that those at the highest risk, may be the least able to engage with interventions. CONCLUSION: Effective digital strategies to prevent fatal OD must be sensitive to the complex relationships between technological, social/human, organisational and wider macroenvironmental factors which can enable or impede intervention delivery. Trust, readiness and performance are central to technology acceptability for PWUO. An augmented TPOM was developed (the TPOM-ODART).

Sex Biased Variance in the Structural and Functional Diversity of the Midgut Bacterial Community of Last Instar Larvae of Pectinophora gossypiella (Lepidoptera: Gelechiidae).

Elucidating the midgut bacterial diversity in an important cotton bollworm Pectinophora gossypiella can be a stepping stone in understanding the possible role of midgut bacteria in field evolved resistance against Bt cotton as well as to commonly used insecticides. Present study targeted metagenomics of 16S rRNA V3-V4 region to understand the influence of sex, if exists, in community diversity of gut microbes vis a vis their function in pink bollworm larvae. The results of the present study revealed that Proteobacteria, Firmicutes, and Actinobacteria were the predominant phyla in the midgut of pink bollworm. Distinctive differences were found in the Shannon and Simpson diversity indices, ChaoI and ACE richness estimates in male and female larvae. The alpha diversity analysis showed that the gut bacteria of male were diverse and rich as compared to that of female. Further, beta diversity analysis indicated that the gut bacterial communities of both larval groups were unique from each other. These findings are the maiden report on sex-based variation in gut bacteria in P. gossypiella larvae. Role of candidate phyla OD1 (Parcubacteria) and TM7 (Saccharibacteria) in the living organisms needs to be studied, and their fairly significant composition in male and negligible composition in female larva raises question on their obvious role. Taxonomic to phenotypic mapping revealed that these gut bacteria play vital role in many metabolic and physiological activities of pink bollworm. Difference in potential functions of gut bacteria also varied with the sex.

Deep feed forward neural network-based screening system for diabetic retinopathy severity classification using the lion optimization algorithm.

Diabetic Retinopathy (DR) has become a major cause of blindness in recent years. Diabetic patients should be screened on a regular basis for early detection, which can help them avoid blindness. Furthermore, the number of diabetic patients undergoing these screening procedures is rapidly increasing, resulting in increased workload for ophthalmologists. An efficient screening system that assists ophthalmologists in DR diagnosis saves ophthalmologists a lot of time and effort. To address this issue, an automatic DR detection screening system is required to improve diagnosis speed and detection accuracy. Appropriate treatment can be provided to patients to prevent vision loss if the severity levels of DR are accurately diagnosed in the early stages. A growing number of screening systems for DR diagnosis have been developed in recent years using various deep learning models, and the majority of the published work did not include any optimization algorithm in the neural network for severity classification. The use of an optimization algorithm with the necessary hyper parameter tuning will improve the model's performance. Considering this as motivation, we proposed a five-phase DFNN-LOA model. The DFNN-LOA algorithm presented here has five phases: (i) pre-processing, (ii) optic disc detection, (iii) segmentation, (iv) feature extraction, and (v) severity classification. The proposed model's experimental analysis is carried out on the MESSIDOR dataset. The experimental results show that the proposed DFNN-LOA model has superior characteristics, with maximum accuracy, sensitivity, specificity, F1-score, PPV, and NPV of 97.6%, 98.4%, 90.7%, 96.5%, 94.6%, and 97.1%, respectively.

Contextual and psychological factors influencing open defecation free status: an exploratory qualitative study in rural South Western Uganda.

INTRODUCTION: Achieving the Open defecation free (ODF) status remains a major challenge in Uganda, yet it contributes significantly to child health improvement. Literature on social, cultural and behavioral aspects that influence the ODF status in rural Uganda is limited. The study therefore, explored perceived factors influencing the ODF status in rural South Western Uganda. METHODS: An exploratory study employing qualitative techniques and based on deductive analysis between month December 2020 and January 2021 was conducted. Seven Focus Group Discussions (FGDs and three Key Informant Interviews (KIs) were conducted in Kabale District, southwestern Uganda. Focus Group Discussion participants were mothers and fathers having children of 2 years and below while KIIs included local community leaders and health extension workers. Data was analyzed using a categorization matrix derived from the Risks, Attitudes, Norms, Abilities, and Self-regulation (RANAS) model which is comprised of contextual and psychological factors. Text was further categorized into high and low statements for attainment of ODF status. RESULTS: The contextual factors influencing the Open Defecation Free status behavior included; farming activities far from home, financial constraints, rainy seasons, collapsible soft soils, and alcohol use. Psychological factors influencing ODF status included; perceived health risk for typhoid disease, low perceived severity for lack of ODF components, negative attitude of less value attached to ODF components, and a feeling of time wastage practicing ODF status behavior. The perception that the community has the ability to attain the ODF status was high. Although, the capability to maintain ODF was low when it comes to replacement of ODF component if stolen or destroyed. CONCLUSION: Open Defecation Free status is influenced by contextual and psychological factors. Therefore, it's crucial for sanitation promotors to always identify such context specific factors in order to design sanitation and hygiene promotion interventions to address the ODF free status related challenges.

Real-Time System for Daily Modal Split Estimation and OD Matrices Generation Using IoT Data: A Case Study of Tartu City.

In recent years, we have witnessed the emergence of the implementation and integration of significant working solutions in transportation, especially within the smart city concept. A lot of cities in Europe and around the world support this initiative of making their cities smarter for enhanced mobility and a sustainable environment. In this paper, we present a case study of Tartu city, where we developed and designed a daily real-time system for extracting and performing a modal split analysis. Our web-based platform relied on an optimization approach for calibrating our simulation in order to perform the analysis with the use of real data streams from IoT devices installed around the city. The results obtained from our system demonstrated acceptable performance versus the quality of the available data source. In addition, our platform provides downloadable OD matrices for each mode of mobility for the community.

Chiral separation and molecular simulation study of six antihistamine agents on a coated cellulose tri-(3,5-dimethylphenycarbamate) column (Chiralcel OD-RH) and its recognition mechanisms.

Enantiomeric separation of six antihistamine agents was first systematically investigated on a cellulose-based chiral stationary phase (CSP), that is, cellulose tris-(3,5-dimethyl phenyl carbamate) (Chiralcel OD-RH), under the reversed-phase mode. Orphenadrine, meclizine, terfenadine, dioxopromethazine, and carbinoxamine enantiomers were completely separated under the optimized mobile phase conditions with resolutions of 5.02, 1.93, 1.68, 1.67, and 1.54, respectively. Mequitazine was partially separated with a resolution of 0.77. The influences of type and concentration of buffer salt, the pH of buffer solution, and the type and ratio of organic modifier on the chiral separation were evaluated and optimized. For a better insight into the enantiorecognition mechanisms, molecular docking was carried out via the Autodock software. The lowest binding energy and the optimal conformations of the analytes/CSP complexes were supplied, and the mechanisms of chiral recognition were determined. According to the results, the key interactions for the chiral recognition of these six analytes on CDMPC were π-π interactions, hydrophobic interactions, hydrogen bond interactions, and some special interactions.

Astaxanthin attenuates joint inflammation induced by monosodium urate crystals.

Gouty arthritis is the one of the most painful arthritis and is caused by an inflammatory reaction. This study investigated whether astaxanthin (AXT), which has documented anti-inflammatory and antioxidant properties, exhibits protective effects against monosodium urate (MSU) crystal-induced inflammation. Cell viability of J774A.1 murine macrophages was assessed by AXT dose-dependent incubation by MTT assays, and expression levels of iNOS and COX-2 proteins as well as secretion of IL-1ß were also analyzed under MSU crystals stimulation with or without AXT treatment. The production of inflammatory mediators was found to significantly decrease with AXT treatment, and the formation of the inflammasome complex was also attenuated when cells were co-stimulated with MSU crystals and AXT. Furthermore, we found that expression of the MAPK pathway was downregulated in J774A.1 cells. AXT also inhibited the induction of COX-2 and IL-6 in human chondrocytes and synovial fibroblasts by western blots. Finally, an MSU crystal intra-articular injection rat model for gouty arthritis was utilized in which treatment groups received 5-daily intraperitoneal injections of AXT prior to MSU crystal stimulation, or once intra-articular injections of AXT following MSU crystal stimulation for 6 hours. Results of synovitis score analysis revealed that inflammation was significantly attenuated in the group which received intraperitoneal AXT injection prior to MSU crystal stimulation compared to the group which received MSU only. These results indicate that AXT attenuates the effects of MSU crystal-induced inflammation by suppressing the production of pro-inflammatory cytokines and inflammatory mediators. Our findings that the anti-inflammatory activities of AXT may be beneficial in the treatment of MSU crystal-induced arthritis.

The odontoid-CSVL distance in a global population of asymptomatic volunteers: normative values and implications for spinal coronal alignment.

PURPOSE: In a population of asymptomatic volunteers across 5 countries, we sought to: (a) establish normative values of the Odontoid-Central Sacral Vertical Line (OD-CSVL) across patient factors, and (b) assess correlations of OD-CSVL with other radiographic parameters. METHODS: A prospective, cross-sectional study of asymptomatic adult volunteers, ages 18-80 years, were enrolled across 5 countries (France, Japan, Singapore, Tunisia, United States) forming the Multi-Ethnic Alignment Normative Study (MEANS) cohort. Included volunteers had no known spinal disorder(s), no significant neck/back pain (VAS ≤ 2; ODI ≤ 20), and no significant scoliosis (Cobb ≤ 20°). Radiographic measurements included commonly used coronal alignment parameters (mm) and angles (°). OD-CSVL was defined as the difference between the odontoid plumb line (line from the tip of the odontoid vertically down) and the CSVL (vertical line from the center of the sacrum). Chi-square, student's t tests, Kruskal-Wallis, Wilcoxon rank-sum, linear regression, and Pearson's correlation were used with significance at p < 0.05. RESULTS: 467 volunteers were included with normative OD-CSVL values by age decade, gender, BMI, and country. Mean ± SD OD-CSVL was 8.3 mm ± 6.5 mm and 31 (6.6%) volunteers were almost perfectly aligned (OD-CSVL < 1 mm). A linear relationship was seen between OD-CSVL with both age (p < 0.001) and BMI (p = 0.015). Significant variation was seen between OD-CSVL and 5 different ethnicities (p = 0.004). OD-CSVL correlated best with other coronal radiographic parameters, C7-CSVL (r = 0.743, p < 0.001), OD-knee (r = 0.230, p < 0.001), CAM-knee (r = 0.612, p < 0.001), and regional TL cobb angle (r = 0.4214, p = 0.005). CONCLUSION: Among asymptomatic volunteers, increased OD-CSVL was significantly associated with increased age, increased BMI, and ethnicity, but not gender. OD-CSVL correlated strongest with C7-CSVL, TL cobb angle, OD-knee, and CAM-knee. OD-CSVL. These results support further study of OD-CSVL in symptomatic adult spine deformity patients.

Hourly Origin-Destination Matrix Estimation Using Intelligent Transportation Systems Data and Deep Learning.

Predicting the travel demand plays an indispensable role in urban transportation planning. Data collection methods for estimating the origin-destination (OD) demand matrix are being extensively shifted from traditional survey techniques to the pre-collected data from intelligent transportation systems (ITSs). This shift is partly due to the high cost of conducting traditional surveys and partly due to the diversity of scattered data produced by ITSs and the opportunity to derive extra benefits out of this big data. This study attempts to predict the OD matrix of Tehran metropolis using a set of ITS data, including the data extracted from automatic number plate recognition (ANPR) cameras, smart fare cards, loop detectors at intersections, global positioning systems (GPS) of navigation software, socio-economic and demographic characteristics as well as land-use features of zones. For this purpose, five models based on machine learning (ML) techniques are developed for training and test. In evaluating the performance of the models, the statistical methods show that the convolutional neural network (CNN) leads to the best performance in terms of accuracy in predicting the OD matrix and has the lowest error in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE). Moreover, the predicted OD matrix was structurally compared with the ground truth matrix, and the CNN model also shows the highest structural similarity with the ground truth OD matrix in the presented case.

A Bayesian Method for Dynamic Origin-Destination Demand Estimation Synthesizing Multiple Sources of Data.

In this paper a Bayesian method is proposed to estimate dynamic origin-destination (O-D) demand. The proposed method can synthesize multiple sources of data collected by various sensors, including link counts, turning movements at intersections, flows, and travel times on partial paths. Time-dependent demand for each O-D pair at each departure time is assumed to satisfy the normal distribution. The connections among multiple sources of field data and O-D demands for all departure times are established by their variance-covariance matrices. Given the prior distribution of dynamic O-D demands, the posterior distribution is developed by updating the traffic count information. Then, based on the posterior distribution, both point estimation and the corresponding confidence intervals of O-D demand variables are estimated. Further, a stepwise algorithm that can avoid matrix inversion, in which traffic counts are updated one by one, is proposed. Finally, a numerical example is conducted on Nguyen-Dupuis network to demonstrate the effectiveness of the proposed Bayesian method and solution algorithm. Results show that the total O-D variance is decreasing with each added traffic count, implying that updating traffic counts reduces O-D demand uncertainty. Using the proposed method, both total error and source-specific errors between estimated and observed traffic counts decrease by iteration. Specifically, using 52 multiple sources of traffic counts, the relative errors of almost 50% traffic counts are less than 5%, the relative errors of 85% traffic counts are less than 10%, the total error between the estimated and "true" O-D demands is relatively small, and the O-D demand estimation accuracy can be improved by using more traffic counts. It concludes that the proposed Bayesian method can effectively synthesize multiple sources of data and estimate dynamic O-D demands with fine accuracy.

Nanoparticles of cisplatin augment drug accumulations and inhibit multidrug resistance transporters in human glioblastoma cells.

BACKGROUND: Cisplatin (CSP) is a potent anticancer drug widely used in treating glioblastoma multiforme (GBM). However, CSP's clinical efficacy in GBM contrasted with low therapeutic ratio, toxicity, and multidrug resistance (MDR). Therefore, we have developed a system for the active targeting of cisplatin in GBM via cisplatin loaded polymeric nanoplatforms (CSP-NPs). METHODS: CSP-NPs were prepared by modified double emulsion and nanoprecipitation techniques. The physiochemical characterizations of CSP-NPs were performed using zeta sizer, scanning electron microscopy (SEM), drug release kinetics, and drug content analysis. Cytotoxicity, induction of apoptosis, and cell cycle-specific activity of CSP-NPs in human GBM cell lines were evaluated by MTT assay, fluorescent microscopy, and flow cytometry. Intracellular drug uptake was gauged by fluorescent imaging and flow cytometry. The potential of CSP-NPs to inhibit MDR transporters were assessed by flow cytometry-based drug efflux assays. RESULTS: CSP-NPs have smooth surface properties with discrete particle size with required zeta potential, polydispersity index, drug entrapment efficiency, and drug content. CSP-NPs has demonstrated an 'initial burst effect' followed by sustained drug release properties. CSP-NPs imparted dose and time-dependent cytotoxicity and triggered apoptosis in human GBM cells. Interestingly, CSP-NPs significantly increased uptake, internalization, and accumulations of anticancer drugs. Moreover, CSP-NPs significantly reversed the MDR transporters (ABCB1 and ABCG2) in human GBM cells. CONCLUSION: The nanoparticulate system of cisplatin seems to has a promising potential for active targeting of cisplatin as an effective and specific therapeutic for human GBM, thus eliminating current chemotherapy's limitations.

An agonist for membrane progestin receptor (mPR) induces oocyte maturation and ovulation in zebrafish in vivo.

The maturation and ovulation of fish oocytes are well-characterized biological processes induced by progestins via coordination of nongenomic actions and genomic actions. Previously, we established a procedure that enables the induction of oocyte maturation and ovulation in live zebrafish by simple administration of the natural teleost maturation-inducing hormone 17 alpha, 20 beta-dihydroxy-4-pregnen-3-one (17,20ß-DHP) into the surrounding water. By this in vivo assay, the potencies of chemicals in inducing or preventing oocyte maturation and ovulation can be evaluated. The potencies of compounds in inducing ovulation of zebrafish oocytes also can be evaluated in vivo with improved in vitro assays. Here, we attempted to evaluate the effect of Org OD 02-0 (Org OD 02), a selective agonist for membrane progestin receptor (mPR), on fish oocyte maturation and ovulation with in vitro and in vivo assays. As reported previously, Org OD 02 triggered oocyte maturation in vitro. The same Org OD 02 triggered oocyte maturation within several hours in vivo. Surprisingly, Org OD 02 even induced ovulation both in in vivo and in vitro. Eggs from Org OD 02-induced ovulation could be fertilized by artificial insemination. The juveniles developed normally. These results indicated that Org OD 02 triggered physiological ovulation in live zebrafish. In summary, we have demonstrated the effect of Org OD 02 on fish oocyte maturation and ovulation in vitro and in vivo. The results suggested that Org OD 02 acted as an agonist not only of mPR but also of nuclear progesterone receptor (nPR).

microRNA-199a counteracts glucocorticoid inhibition of bone marrow mesenchymal stem cell osteogenic differentiation through regulation of Klotho expression in vitro.

Osteogenic differentiation (OD) of bone marrow mesenchymal stem cells (BMSCs) is critically important for mitigation of osteoporosis. Glucocorticoids (GCs) are extensively used for treating chronic inflammation, although long-term exposure to GCs is capable of triggering osteoporosis. microRNAs (miRNAs) have been reported to play a critical role in bone diseases. In the present study, we treated BMSCs with dexamethasone (DEX) during OD to stimulate GC-mediated osteoporosis. Microarray and quantitative polymerase chain reaction (Q-PCR) assays demonstrated that miR-199a was upregulated during OD of BMSCs, while DEX treatment caused a significant reduction in miR-199a. Alkaline phosphatase (ALP) activity, Alizarin red (AR) staining, and Q-PCR were applied to assess the role of miRNA-199a overexpression in DEX-triggered OD inhibition. miR-199a was able to rescue OD and ALP activity, which were inhibited by DEX. Additionally, we observed that ALP, BMP2, COL1A1, and Runx2 were increased after transfection of miRNA-199a mimics. Furthermore, we confirmed that miRNA-199a facilitates OD of BMSCs through direct inhibition of Klotho protein and messenger RNA expression affecting the downstream fibroblast growth factor receptor 1/extracellular-signal-regulated kinase and Janus kinase 1/signal transducer and activator of transcription 1 pathways. This study indicates that miR-199a plays a critical role in preventing GC-mediated osteoblast differentiation and may function as a promising miRNA biomarker for osteoporosis.

Origin-Destination Flow Estimation from Link Count Data Only.

All established models in transportation engineering that estimate the numbers of trips between origins and destinations from vehicle counts use some form of a priori knowledge of the traffic. This paper, in contrast, presents a new origin-destination flow estimation model that uses only vehicle counts observed by traffic count sensors; it requires neither historical origin-destination trip data for the estimation nor any assumed distribution of flow. This approach utilises a method of statistical origin-destination flow estimation in computer networks, and transfers the principles to the domain of road traffic by applying transport-geographic constraints in order to keep traffic embedded in physical space. Being purely stochastic, our model overcomes the conceptual weaknesses of the existing models, and additionally estimates travel times of individual vehicles. The model has been implemented in a real-world road network in the city of Melbourne, Australia. The model was validated with simulated data and real-world observations from two different data sources. The validation results show that all the origin-destination flows were estimated with a good accuracy score using link count data only. Additionally, the estimated travel times by the model were close approximations to the observed travel times in the real world.

The Specific Effects of OD-1, a Peptide Activator, on Voltage-Gated Sodium Current and Seizure Susceptibility.

OD-1, a scorpion toxin, has been previously recognized as an activator of voltage-gated Na+ currents. To what extent this agent can alter hippocampal neuronal Na+ currents and network excitability and how it can be applied to neuronal hyperexcitability research remains unclear. With the aid of patch-clamp technology, it was revealed that, in mHippoE-14 hippocampal neurons, OD-1 produced a concentration-, time-, and state-dependent rise in the peak amplitude of INa. It shifted the INa inactivation curve to a less negative potential and increased the frequency of spontaneous action currents. Further characterization of neuronal excitability revealed higher excitability in the hippocampal slices treated with OD-1 as compared with the control slices. A stereotaxic intrahippocampal injection of OD-1 generated a significantly higher frequency of spontaneous seizures and epileptiform discharges compared with intraperitoneal injection of lithium-pilocarpine- or kainic acid-induced epilepsy, with comparable pathological changes. Carbamazepine significantly attenuated OD-1 induced seizures and epileptiform discharges. The OD-1-mediated modifications of INa altered the electrical activity of neurons in vivo and OD-1 could potentially serve as a novel seizure and excitotoxicity model.