Ex Vivo Calcium Imaging for Drosophila Model of Epilepsy.

Epilepsy is a neurological disorder characterized by recurrent seizures, partially correlated with genetic origin, affecting over 70 million individuals worldwide. Despite the clinical importance of epilepsy, the functional analysis of neural activity in the central nervous system is still to be developed. Recent advancements in imaging technology, in combination with stable expression of genetically encoded calcium indicators, such as GCaMP6, have revolutionized the study of epilepsy at both brain-wide and single-cell resolution levels. Drosophila melanogaster has emerged as a tool for investigating the molecular and cellular mechanisms underlying epilepsy due to its sophisticated molecular genetics and behavioral assays. In this study, we present a novel and efficient protocol for ex vivo calcium imaging in GCaMP6-expressing adult Drosophila to monitor epileptiform activities. The whole brain is prepared from cac, a well-known epilepsy gene, knockdown flies for calcium imaging with a confocal microscope to identify the neural activity as a follow-up to the bang-sensitive seizure-like behavior assay. The cac knockdown flies showed a higher rate of seizure-like behavior and abnormal calcium activities, including more large spikes and fewer small spikes than wild-type flies. The calcium activities were correlated to seizure-like behavior. This methodology serves as an efficient methodology in screening the pathogenic genes for epilepsy and exploring the potential mechanism of epilepsy at the cellular level.

UBR4 deficiency causes male sterility and testis abnormal in Drosophila.

Introduction: It has been established that UBR4 encodes E3 ubiquitin ligase, which determines the specificity of substrate binding during protein ubiquitination and has been associated with various functions of the nervous system but not the reproductive system. Herein, we explored the role of UBR4 on fertility with a Drosophila model. Methods: Different Ubr4 knockdown flies were established using the UAS/GAL4 activating sequence system. Fertility, hatchability, and testis morphology were studied, and bioinformatics analyses were conducted. Our results indicated that UBR4 deficiency could induce male sterility and influent egg hatchability in Drosophila. Results: We found that Ubr4 deficiency affected the testis during morphological analysis. Proteomics analysis indicated 188 upregulated proteins and 175 downregulated proteins in the testis of Ubr4 knockdown flies. Gene Ontology analysis revealed significant upregulation of CG11598 and Sfp65A, and downregulation of Pelota in Ubr4 knockdown flies. These proteins were involved in the biometabolic or reproductive process in Drosophila. These regulated proteins are important in testis generation and sperm storage promotion. Bioinformatics analysis verified that UBR4 was low expressed in cryptorchidism patients, which further supported the important role of UBR4 in male fertility. Discussion: Overall, our findings suggest that UBR4 deficiency could promote male infertility and may be involved in the protein modification of UBR4 by upregulating Sfp65A and CG11598, whereas downregulating Pelota protein expression.

Efficient strategies based on behavioral and electrophysiological methods for epilepsy-related gene screening in the Drosophila model.

Introduction: With the advent of trio-based whole-exome sequencing, the identification of epilepsy candidate genes has become easier, resulting in a large number of potential genes that need to be validated in a whole-organism context. However, conducting animal experiments systematically and efficiently remains a challenge due to their laborious and time-consuming nature. This study aims to develop optimized strategies for validating epilepsy candidate genes using the Drosophila model. Methods: This study incorporate behavior, morphology, and electrophysiology for genetic manipulation and phenotypic examination. We utilized the Gal4/UAS system in combination with RNAi techniques to generate loss-of-function models. We performed a range of behavioral tests, including two previously unreported seizure phenotypes, to evaluate the seizure behavior of mutant and wild-type flies. We used Gal4/UAS-mGFP flies to observe the morphological alterations in the brain under a confocal microscope. We also implemented patch-clamp recordings, including a novel electrophysiological method for studying synapse function and improved methods for recording action potential currents and spontaneous EPSCs on targeted neurons. Results: We applied different techniques or methods mentioned above to investigate four epilepsy-associated genes, namely Tango14, Klp3A, Cac, and Sbf, based on their genotype-phenotype correlation. Our findings showcase the feasibility and efficiency of our screening system for confirming epilepsy candidate genes in the Drosophila model. Discussion: This efficient screening system holds the potential to significantly accelerate and optimize the process of identifying epilepsy candidate genes, particularly in conjunction with trio-based whole-exome sequencing.

Atmospheric moisture variability and transmission of hemorrhagic fever with renal syndrome in Changsha City, Mainland China, 1991-2010.

BACKGROUND: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by environmental determinants. This study aimed to explore the association between atmospheric moisture variability and the transmission of hemorrhagic fever with renal syndrome (HFRS) for the period of 1991-2010 in Changsha, China. METHODS AND FINDINGS: Wavelet analyses were performed by using monthly reported time series data of HFRS cases to detect and quantify the periodicity of HFRS. A generalized linear model with a Poisson distribution and a log link model were used to quantify the relationship between climate and HFRS cases, highlighting the importance of moisture conditions. There was a continuous annual oscillation mode and multi-annual cycle around 3-4 years from 1994 to 1999. There was a significant association of HFRS incidence with moisture conditions and the Multivariate El Niño-Southern Oscillation Index (MEI). Particularly, atmospheric moisture has a significant effect on the propagation of HFRS; annual incidence of HFRS was positively correlated with annual precipitation and annual mean absolute humidity. CONCLUSIONS: The final model had good accuracy in forecasting the occurrence of HFRS and moisture condition can be used in disease surveillance and risk management to provide early warning of potential epidemics of this disease.

[Study on sensitivity of climatic factors on influenza A (H1N1) based on classification and regression tree and wavelet analysis].

OBJECTIVE: To analyze the periodicity of pandemic influenza A (H1N1) in Changsha in year 2009 and its correlation with sensitive climatic factors. METHODS: The information of 5439 cases of influenza A (H1N1) and synchronous meteorological data during the period between May 22th and December 31st in year 2009 (223 days in total) in Changsha city were collected. The classification and regression tree (CART) was employed to screen the sensitive climatic factors on influenza A (H1N1); meanwhile, cross wavelet transform and wavelet coherence analysis were applied to assess and compare the periodicity of the pandemic disease and its association with the time-lag phase features of the sensitive climatic factors. RESULTS: The results of CART indicated that the daily minimum temperature and daily absolute humidity were the sensitive climatic factors for the popularity of influenza A (H1N1) in Changsha. The peak of the incidence of influenza A (H1N1) was in the period between October and December (Median (M) = 44.00 cases per day), simultaneously the daily minimum temperature (M = 13°C) and daily absolute humidity (M = 6.69 g/m(3)) were relatively low. The results of wavelet analysis demonstrated that a period of 16 days was found in the epidemic threshold in Changsha, while the daily minimum temperature and daily absolute humidity were the relatively sensitive climatic factors. The number of daily reported patients was statistically relevant to the daily minimum temperature and daily absolute humidity. The frequency domain was mostly in the period of (16 ± 2) days. In the initial stage of the disease (from August 9th and September 8th), a 6-day lag was found between the incidence and the daily minimum temperature. In the peak period of the disease, the daily minimum temperature and daily absolute humidity were negatively relevant to the incidence of the disease. CONCLUSION: In the pandemic period, the incidence of influenza A (H1N1) showed periodic features; and the sensitive climatic factors did have a "driving effect" on the incidence of influenza A (H1N1).

[Study on the influence of landscape elements regarding on the transmission of hemorrhagic fever with renal syndrome in Changsha].

OBJECTIVE: To explore the influence of landscape elements on the transmission of hemorrhagic fever with renal syndrome (HFRS) in Changsha. METHODS: A total of 327 cases of HFRS diagnosed between year 2005 - 2009 were recruited in the study. Based on the demographic data, meteorological data and the data of second national land survey during the same period, a GIS landscape elements database of HFRS at the township scale of Changsha was established. Spatial-temporal cluster analysis methods were adopted to explore the influence of landscape elements on the spatial-temporal distribution of HFRS in Changsha during the year of 2005 - 2009. RESULTS: The annual incidences of HFRS in Changsha between year 2005 - 2009 were 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000(87 cases), 0.75/100 000(47 cases) and 1.02/100 000(65 cases) respectively. The results of poisson regression model analysis of principal component showed that the incidence of HFRS was positively correlated with farmland area (M = 29.00 km2) and urban and rural area (M = 6.12 km2; incidence rate ratios (IRR) = 1.34, 95% CI: 1.27 - 1.41); but negatively correlated with forestland area (M = 39.00 km2; IRR = 0.67, 95% CI: 0.55 - 0.81) and garden plot area (M = 0.99 km2; IRR = 0.74, 95% CI: 0.63 - 0.86). A significant cluster of the spatial-temporal distribution of HFRS cases was found in the study. The primary cluster (28.9 N, 113.37 E, radius at 22.22 km, RR = 5.23, log likelihood ratio (LLR) = 51.61, P <0.01, 67 cases of HFRS and incidence at 4.4/100 000) was found between year 2006 and 2007; and the secondary cluster (28.2 N, 113.6 E, RR = 10.77, LLR = 16.01, P < 0.01, 11 cases of HFRS and the incidence at 10.6/100 000) was found between year 2008 and 2009. CONCLUSION: The landscape elements were found to be closely related to the prevalence and transmission of HFRS.

[Spatio-temporal process and the influencing factors on influenza A (H1N1) pandemic in Changsha].

OBJECTIVE: To analyze the spatio-temporal process on 2009 influenza A (H1N1) pandemic in Changsha and the influencing factors during the diffusion process. METHODS: Data were from the following 5 sources, influenza A (H1N1) pandemic gathered in 2009, Geographic Information System (GIS) of Changsha, the broad range of theorems and techniques of hot spot analysis, spatio-temporal process analysis and Spearman correlation analysis. RESULTS: Hot spot areas appeared to be more in the economically developed areas, such as cities and townships. The cluster of spatial-temporal distribution of influenza A (H1N1) pandemic was most likely appearing in Liuyang city (RR = 22.70, P < 0.01). The secondary cluster would include districts as Yuelu (RR = 6.49, P < 0.01), Yuhua (RR = 81.63, P < 0.01). Xingsha township appeared as the center in the Changsha county (RR = 2.90, P < 0.01) while townships as Yutangping (RR = 19.31, P < 0.01), Chengjiao (RR = 73.14, P < 0.01) and Longtian appeared as the center in the west of Ningxiang county (RR = 14.43, P < 0.01) and Wushan as the center in the Wangcheng county (RR = 13.84, P < 0.01). As time went on, the epidemic moved towards the eastern and more developed regions. Regarding factor analysis, population, the amount of students, geographic relationship and business activities etc. appeared to be the key elements influencing the transmission of influenza A (H1N1) pandemic. At the beginning of the epidemic, population density served as the main factor (r = 0.477, P < 0.05) but during the initial and fast growing stages, it was replaced by the size of students to serve as the important indicator (r = 0.831, P < 0.01; r = 0.518, P < 0.01). However, during the peak of the epidemics, the business activities played an important role (r = -0.676, P < 0.01). CONCLUSION: Groups under high risk and districts with high incidence rates were shifting, along with the temporal process of influenza A (H1N1) pandemic, suggesting that the protection measures need to be adjusted, according to the significance of influencing factors at different stages.

[The warning model and influence of climatic changes on hemorrhagic fever with renal syndrome in Changsha city].

OBJECTIVE: To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. METHODS: A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. RESULTS: The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). CONCLUSION: Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.