Assessment of Key Factors Impacting Variability in AAV Vector Genome Titration by Digital PCR.

Recombinant adeno-associated virus (rAAV) has emerged as a prominent vector for in vivo gene therapy, owing to its distinct advantages. Accurate determination of the rAAV genome titer is crucial for ensuring the safe and effective administration of clinical doses. The evolution of the rAAV genome titer assay from quantitative PCR (qPCR) to digital PCR (dPCR) has enhanced accuracy and precision, yet practical challenges persist. This study systematically investigated the impact of various operational factors on genome titration in a single-factor manner, aiming to address potential sources of variability in the quantitative determination process. Our findings revealed that a pretreatment procedure without genome extraction exhibits superior precision compared with titration with genome extraction. Additionally, notable variations in titration results across different brands of dPCR instruments were documented, with relative standard deviation (RSD) reaching 23.47% for AAV5 and 11.57% for AAV8. Notably, optimal operations about DNase I digestion were identified; we thought treatment time exceeding 30 min was necessary, and there was no need for thermal inactivation after digestion. And we highlighted that thermal capsid disruption before serial dilution substantially affected AAV genome titers, causing a greater than ten-fold decrease. Conversely, this study found that additive components of dilution buffer are not significant contributors to titration variations. Furthermore, we found that repeated freeze-thaw cycles significantly compromised AAV genome titers. In conclusion, a comprehensive dPCR titration protocol, incorporating insights from these impact factors, was proposed and successfully tested across multiple serotypes of AAV. The results demonstrate acceptable variations, with the RSD consistently below 5.00% for all tested AAV samples. This study provides valuable insights to reduce variability and improve the reproducibility of AAV genome titration using dPCR.

County land use carbon emission and scenario prediction in Mianyang Science and Technology City New District, Sichuan Province, China.

The role of carbon emissions resulting from land use change in the compilation of national greenhouse gas emission inventories is of paramount significance. This study is centered on the Mianyang Science and Technology City New Area located in Sichuan Province, China. We used the CLUE-S model and Sentinel-2A remote sensing data from 2017 to simulate and validate land use changes in 2022. Based on this validation, we established three simulation scenarios: a baseline scenario, an agricultural development scenario, and a construction development scenario. Using remote sensing data from 2022, we projected the land use for 2030. We also used CO2 concentration data collected in 2022 and 2023, processed the data using ArcGIS and Python, and conducted a quantitative analysis of carbon emissions under each scenario. Ultimately, the accuracy of both measured and predicted CO2 values for 2023 was juxtaposed and authenticated, thus concluding the investigative cycle of this study. Key findings include: (1) The accuracy of the CLUE-S model in the study area was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. In 2022, the overall accuracy is 98.19%, the quantity disagreement is 1.7%, and the allocation disagreement is 2.2%. (2) Distinct land resource utilization characteristics in scenarios, highlighting potential impacts on economic development and pollution. (3) Increased carbon emissions across scenarios, with construction development showing the highest rise (4.170%) and agricultural development the lowest (0.766%). (4) The predictive accuracy of the validation group's CO2 concentration values can reach 99.5%. This study proposes precise CO2 prediction at the county level, thus laying the groundwork for future research endeavors. Such findings are indispensable for informing carbon policy formulation and promoting low-carbon development strategies.

Performance assessment of surface-guided radiation therapy and patient setup in head-and-neck and breast cancer patients based on statistical process control.

PURPOSE: To assess the effectiveness of SGRT in clinical applications through statistical process control (SPC). METHODS: Taking the patients' positioning through optical surface imaging (OSI) as a process, the average level of process execution was defined as the process mean. Setup errors detected by cone-beam computed tomography (CBCT) and OSI were extracted for head-and-neck cancer (HNC) and breast cancer patients. These data were used to construct individual and exponentially weighted moving average (EWMA) control charts to analyze outlier fractions and small process shifts from the process mean. Using the control charts and process capability indices derived from this process, the patient positioning-related OSI performance and setup error were analyzed for each patient. RESULTS: Outlier fractions and small shifts from the process mean that are indicative of setup errors were found to be widely prevalent, with the outliers randomly distributed between fractions. A systematic error of up to 1.6 mm between the OSI and CBCT results was observed in all directions, indicating a significantly degraded OSI performance. Adjusting this systematic error for each patient using setup errors of the first five fractions could effectively mitigate these effects. Process capability analysis following adjustment for systematic error indicated that OSI performance was acceptable (process capability index Cpk = 1.0) for HNC patients but unacceptable (Cpk < 0.75) for breast cancer patients. CONCLUSION: SPC is a powerful tool for detecting the outlier fractions and process changes. Our application of SPC to patient-specific evaluations validated the suitability of OSI in clinical applications involving patient positioning.

Understanding fire drivers and relative impacts in different Chinese forest ecosystems.

In this study, spatial patterns and driving factors of fires were identified from 2000 to 2010 using Ripley's K (d) function and logistic regression (LR) model in two different forest ecosystems of China: the boreal forest (Daxing'an Mountains) and sub-tropical forest (Fujian province). Relative effects of each driving factor on fire occurrence were identified based on standardized coefficients in the LR model. Results revealed that fires were spatially clustered and that fire drivers vary amongst differing forest ecosystems in China. Fires in the Daxing'an Mountains respond primarily to human factors, of which infrastructure is recognized as the most influential. In contrast, climate factors played a critical role in fire occurrence in Fujian, of which the temperature of fire season was found to be of greater importance than other climate factors. Selected factors can predict nearly 80% of the total fire occurrence in the Daxing'an Mountains and 66% in Fujian, wherein human and climate factors contributed the greatest impact in the two study areas, respectively. This study suggests that different fire prevention and management strategies are required in the areas of study, as significant variations of the main fire-driving exist. Rapid socio-economic development has produced similar effects in different forest ecosystems within China, implying a strong correlation between socio-economic development and fire regimes. It can be concluded that the influence of human factors will increase in the future as China's economy continues to grow - an issue of concern that should be further addressed in future national fire management.

Evaluating management tradeoffs between economic fiber production and other ecosystem services in a Chinese-fir dominated forest plantation in Fujian Province.

Chinese fir (Cunninghamia lanceolata) is not only a valuable timber species, but also plays an important role in the provision of ecosystem services. Forest management decisions to increase the production of fiber for economic gain may have negative impacts on the long-term flow of ecosystem services from forest resources. Such tradeoffs should be taken into account to fulfill the requirements of sustainable forest management. Here we employed an established, ecosystem-based, stand-level model (FORECAST) in combination with a simplified harvest-scheduling model to evaluate the potential tradeoffs among indicators of provisional, regulating and supporting ecosystem services in a Chinese-fir-dominated landscape located in Fujian Province as a case study. Indicators included: merchantable volume harvested, biomass harvested, ecosystem carbon storage, CO2 fixation, O2 released, biomass nitrogen content, pollutant absorption, and soil fertility. A series of alternative management scenarios, representing different combinations of rotation length and harvest intensity, were simulated to facilitate the analysis. Results from the analysis were summarized in the form of a decision matrix designed to provide a method for forest managers to evaluate management alternatives and tradeoffs in the context of key indicators of ecosystem services. The scenario analysis suggests that there are considerable tradeoffs in terms of ecosystem services associated with stand and landscape-level management decisions. Longer rotations and increased retention tended to favor regulating and supporting services while the opposite was true for provisional services.

[Etiology of off-plate syndrome in cultured larval Apostichopus japonicus at attachment stage and analysis of reservoir of pathogens].

OBJECTIVE: To clarify pathogens and sources of the off-plate syndrome at the attachment stage in the larval culture of Apostichopus japonicus, and further to find out effective medicines for this disease. METHODS: Etiological analysis was performed on larvae with typical off-plate syndrome from three larvae culture factories. Suspicious pathogens were used for artificial infection test, and were identified through morphological, physiological and biochemical tests, and 16S rDNA sequence analysis. Quantitative bacterial analysis was done on the culture systems of the three factories, including water sources, rearing water, ordure (in the pond floor), attachments and feeds. Finally, drug-sensitive tests were done against the pathogens. RESULTS: A common dominant bacterium strain was isolated from all ill larvae included in the study. Artificial infection test showed it was the causative pathogen associated with the disease, and the artificially infected sea cucumbers had same syndromes to the naturally ill ones. The bacterium was identified as Vibrio sp. Bacterial quantity of water sources was in the qualified range (<50 cfu/mL), while out of the standard range in others (> 1 x 10(5) cfu/mL). The sources of the pathogen were complicated, since pathogens were discovered in the water sources, rearing water, ordure, attachments and feeds. However, the density of causative bacteria was the highest in the feeds, middle in the attachments, and lowest in the water sources. Twelve antibiotics could inhibit growth of the pathogens. CONCLUSION: The possible pathogen for off-plate syndrome was Vibrio sp. Feeds may be the main source of the pathogen. Twelve antibiotics besides nalidixic acid could be applied for disease prevention and treatment of Apostichopus japonicus.