A review of quantification methods for light absorption enhancement of black carbon aerosol

Black carbon (BC) is a distinct type of carbonaceous aerosol that has a significant impact on the environment, human health, and climate. A non-BC material coating on BC can alter the mixing state of the BC particles, which considerably enhances the mass absorption efficiency of BC by directing more energy toward the BC cores (lensing effect). A lot of methods have been reported for quantifying the enhancement factor (Eabs), with diverse results. However, to the best of our knowledge, a comprehensive review specific to the quantification methods for Eabs has not been systematically performed, which is unfavorable for the evaluation of obtained results and subsequent radiative forcing. In this review, quantification methods are divided into two broad categories, direct and indirect, depending on whether experimental removal of the coating layer from an aged carbonaceous particle is required. The direct methods described include thermal peeling, solvent dissolution, and optical virtual exfoliation, while the indirect methods include intercept-linear regression fitting, minimum R squared, numerical simulation, and empirical value. We summarized the principles, procedures, virtues, and limitations of the major Eabs quantification methods and analyzed the current problems in the determination of Eabs. We pointed out what breakthroughs are needed to improve or innovate Eabs quantification methods, particularly regarding the need to avoid the influence of brown carbon, develop a broadband Eabs quantification scheme, quantify the Eabs values for the emissions of low-efficiency combustions, measure the Eabs of particles in a high-humidity environment, design a real-time monitor of Eabs by a proper combination of mature techniques, and make more use of artificial intelligence for better Eabs quantification. This review deepens the understanding of Eabs quantification methods and benefits the estimation of the contribution of BC to radiative forcing using climate models.

Wastewater-based prediction of COVID-19 cases using a highly sensitive SARS-CoV-2 RNA detection method combined with mathematical modeling

Wastewater-based epidemiology (WBE) has the potential to predict COVID-19 cases; however, reliable methods for tracking SARS-CoV-2 RNA concentrations (C_RNA) in wastewater are lacking. In the present study, we developed a highly sensitive method (EPISENS-M) employing adsorption-extraction, followed by one-step RT-Preamp and qPCR. The EPISENS-M allowed SARS-CoV-2 RNA detection from wastewater at 50 % detection rate when newly reported COVID-19 cases exceed 0.69/100,000 inhabitants in a sewer catchment. Using the EPISENS-M, a longitudinal WBE study was conducted between 28 May 2020 and 16 June 2022 in Sapporo City, Japan, revealing a strong correlation (Pearson's r = 0.94) between C_RNA and the newly COVID-19 cases reported by intensive clinical surveillance. Based on this dataset, a mathematical model was developed based on viral shedding dynamics to estimate the newly reported cases using C_RNA data and recent clinical data prior to sampling day. This developed model succeeded in predicting the cumulative number of newly reported cases after 5 days of sampling day within a factor of √2 and 2 with a precision of 36 % (16/44) and 64 % (28/44), respectively. By applying this model framework, another estimation mode was developed without the recent clinical data, which successfully predicted the number of COVID-19 cases for the succeeding 5 days within a factor of √2 and 2 with a precision of 39 % (17/44) and 66 % (29/44), respectively. These results demonstrated that the EPISENS-M method combined with the mathematical model can be a powerful tool for predicting COVID-19 cases, especially in the absence of intensive clinical surveillance.

Direct quantification of cytosolic delivery of drug nanocarriers using FlAsH-EDT2

The delivery of therapeutics across the cell membrane and into the cytoplasm is a major challenge that limits the development of new therapies. This challenge is compounded by the lack of a general assay for cytosolic delivery. Here we develop this assay based on the pro-fluorophore CrAsH-EDT2, and provide cytosolic penetration results for a variety of drug delivery agents (polyethyleneimine, poly-arginine, Ferritin, poly [maleic anhydride-alt-isobutene] grafted with dodecylamine, and cationic liposomes) into HeLa and T98G cells. Our results show that this method can be widely applicable to different cells and drug delivery agents, and yield statistically robust results. We later use this method to optimize and improve a model drug delivery agent's (Ferritin) cytosolic penetration.

The detectability and removal efficiency of SARS-CoV-2 in a large-scale septic tank of a COVID-19 quarantine facility in Japan

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be present in sewage, and wastewater-based epidemiology has attracted much attention. However, the physical partitioning of SARS-CoV-2 in wastewater and the removal efficiency of treatment systems require further investigation. This study aimed to investigate the detectability and physical partitioning of SARS-CoV-2 in wastewater and assess its removal in a large-scale septic tank employing anaerobic, anoxic, and oxic processes in a sequential batch reactor, which was installed in a coronavirus disease 2019 (COVID-19) quarantine facility. The amount of SARS-CoV-2 RNA in wastewater was determined with polyethylene glycol (PEG) precipitation followed by quantitative polymerase chain reaction (qPCR), and the association of SARS-CoV-2 with wastewater solids was evaluated by the effect of filtration prior to PEG precipitation (pre-filtration). The amount of SARS-CoV-2 RNA detected from pre-filtered samples was substantially lower than that of samples without pre-filtration. These results suggest that most SARS-CoV-2 particles in wastewater are associated with the suspended solids excluded by pre-filtration. The removal efficiency of SARS-CoV-2 in the septic tank was evaluated based on the SARS-CoV-2 RNA concentrations in untreated and treated wastewater, which was determined by the detection method optimized in this study. Escherichia coli and pepper mild mottle virus (PMMoV) were also quantified to validate the wastewater treatment system's performance. The mean log₁₀ reduction values of SARS-CoV-2, E. coli, and PMMoV were 2.47 (range, 2.25-2.68), 2.81 (range, 2.45-3.18), and 0.66 (range, 0.61-0.70), respectively, demonstrating that SARS-CoV-2 removal by the wastewater treatment system was comparable to or better than the removal of fecal indicators. These results suggest that SARS-CoV-2 can be readily removed by the septic tank. This is the first study to determine the removal efficiency of SARS-CoV-2 in a facility-level sequencing batch activated sludge system.

The Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S): A rapid and cost-effective SARS-CoV-2 RNA detection method for routine wastewater surveillance

Wastewater-based epidemiology has attracted attention as a COVID-19 surveillance tool. Here, we developed a practical method for detecting SARS-CoV-2 RNA in wastewater (the EPISENS-S method), which employs direct RNA extraction from wastewater pellets formed via low-speed centrifugation. The subsequent multiplex one-step RT-preamplification reaction with forward and reverse primers for SARS-CoV-2 and a reverse primer only for pepper mild mottle virus (PMMoV) allowed for qPCR quantification of the targets with different abundances in wastewater from the RT-preamplification product. The detection sensitivity of the method was evaluated using wastewater samples seeded with heat-inactivated SARS-CoV-2 in concentrations of 2.11 × 10³ to 2.11 × 10⁶ copies/L. The results demonstrated that the sensitivity of the EPISENS-S method was two orders of magnitude higher than that of the conventional method (PEG precipitation, followed by regular RT-qPCR; PEG-QVR-qPCR). A total of 37 untreated wastewater samples collected from two wastewater treatment plants in Sapporo, Japan when 1.6 to 18 new daily reported cases per 100,000 people were reported in the city (March 4 to July 8, 2021), were examined using the EPISENS-S method to confirm its applicability to municipal wastewater. SARS-CoV-2 RNA was quantified in 92 % (34/37) of the samples via the EPISENS-S method, whereas none of the samples (0/37) was quantifiable via the PEG-QVR-qPCR method. The PMMoV concentrations measured by the EPISENS-S method ranged from 2.60 × 10⁶ to 1.90 × 10⁸ copies/L, and the SARS-CoV-2 RNA concentrations normalized by PMMoV ranged from 5.71 × 10^-6 to 9.51 × 10^-4 . The long-term trend of normalized SARS-CoV-2 RNA concentration in wastewater was consistent with that of confirmed COVID-19 cases in the city. These results demonstrate that the EPISENS-S method is highly sensitive and suitable for routine COVID-19 wastewater surveillance.

The pulse waveform quantification method basing on contour and derivative

OBJECTIVE

Pulse waveform contains abundant physiological and pathological information. The condition of surrounding arteries can be reflected sensitively by the contour and derivative changes of pulse waves. In order to express these changes objectively, the pulse wave needs to be quantified.

METHODS

This study provides a novel quantification method for pulse waveform in the entire cardiac cycle. It involves two new quantification parameters k1 and k2 to display the waveform change caused by the superimposition of wave reflection in the systolic reflex period, which is the most significant changes period. In this method, multi parameters were fused by Kalman filter to obtain an optimal estimation, involving the new parameters and other parameters: k0 for the early systolic period, C1 and C2 for diastole period, and K for pulse pressure.

RESULTS

Use correlation analysis to verify the effectiveness of new parameters that the coefficient is 0.7 between them and the typical augmentation index (AIx). The quantification results of 462 single-cycle pulse waves have consistent change trends with aging in 25-75 different age groups. For respiration analysis, the correlation coefficients are all greater than 0.6, even achieved 0.8 in six multi-cycle data between Kalman optimal estimation and breath wave.

CONCLUSION

This method has quantified the waveform change with physiological status, and these quantification parameters can display the detail of each period.

SIGNIFICANCE

It will be used to verify waveform recognition accuracy and has a vast potential to detect diseases.

Three Gorges Dam alters the footprint of particulate heavy metals in the Yangtze Estuary

Two scenarios were selected to simulate the situation before the closure of the Three Gorges Dam (TGD) in 1996 (Scenario 1) and after the completion of the Three Gorges Project in 2010 (Scenario 2). A modified polar co-ordinated segmented quantification method was proposed to quantify the heavy metal footprint excursion in Scenarios 1 and 2 and further evaluate their influence on the six sensitive targets in the Yangtze Estuary. Scenario 3 was utilised to analyse the negative effects of the footprint range on the spatio-temporal overlap of the Chinese sturgeon juveniles arriving in the estuarine reserve, set in the TGD-altered biological rhythm. Each scenario comprises four simulation sites from March to September, including three major urban sewage outlets, named Bailonggang (BLG), Zhuyuan (ZY), Shidongkou (SDK), and the upstream pollution source, represented by Xuliujing (XLJ). The results showed that the increased discharge in the dry season moved the post-TGD footprint further away from Chongming Island. Additionally, the outward side footprint was formed during the flood season, when the average discharge was lower than that during the pre-TGD period, being 'pushed' to the northwest by the monsoon and Taiwan warm current, resulting in a narrowing of the overall extent. The TGD positively impacted the XLJ and BLG simulation sites, given their shrinking footprint range and the decreasing trajectories of intruding sensitive targets in Scenario 2, in contrast to SDK and ZY.

Development of a homogeneous time-resolved FRET (HTRF) assay for the quantification of Shiga toxin 2 produced by E. coli

Shiga toxin-producing Escherichia coli (STEC) is a major intestinal pathogen and causes serious gastrointestinal illness, which includes diarrhea, hemorrhagic colitis, and life-threatening hemolytic uremic syndrome. The major virulence factors of STEC are Shiga toxins (Stx1 and Stx2), which belong to the AB-type toxin family. Among several subtypes of Stx1 and Stx2, the production of Stx2a is thought to be a risk factor for severe STEC infections, but Stx2a production levels vary markedly between STEC strains, even strains with the same serotype. Therefore, quantitative analyses of Stx2 production by STEC strains are important to understand the virulence potential of specific lineages or sublineages. In this study, we developed a novel Stx2 quantification method by utilizing homogeneous time-resolved fluorescence resonance energy transfer (HTRF) technology. To determine suitable “sandwich” assay conditions, we tested 6 combinations of fluorescence-labeled monoclonal antibodies (mAbs) specific to Stx2 and compared the HTRF signal intensities obtained at various incubation times. Through this analysis, we selected the most suitable mAb pair, one recognizing the A subunit and the other recognizing the B subunit, thus together detecting Stx holotoxins. The optimal incubation time was also determined (18 h). Then, we optimized the concentrations of the two mAbs based on the range for linearity. The established HTRF assay detected 0.5 ng/ml of the highly purified recombinant Stx2a and Stx2e proteins and the working range was 1–64 ng/ml for both Stx2a and Stx2e. Through the quantification analysis of Stx proteins in STEC cell lysates, we confirmed that other Stx2 subtypes (Stx2b, Stx2c, Stx2d and Stx2g) can also be quantified at a certain level of accuracy, while this assay system does not detect Stx2f, which is highly divergent in sequence from other Stx2 subtypes, and Stx1. As the HTRF protocol we established is simple, this assay system should prove useful for the quantitative analysis of Stx2 production levels of a large number of STEC strains.

A novel thermoanalytical method for quantifying microplastics in marine sediments

Microplastic pollution in marine environments is of particular concern on its risk to the ecosystem. To assess and manage microplastic contaminants, their quantitative detection in environmental samples is a high priority. However, uncertainties of current methods still exist when estimating their abundances, particularly with fine-grained (<1 mm) microplastics. This work reports a novel thermoanalytical method for quantifying microplastics by measuring the contents of microplastic-derived carbon (MPC) in samples under the premise of nearly eliminating the limit of their particle appearances. After validating the method via samples with the spiked microplastics, we have conducted a case study on sediment core H43 that spanned 1925-2009 CE from the Yellow Sea for further illustrating the high reliability and practicability of this method for quantifying microplastics in natural samples. Our results have demonstrated that the proposed method may be a promising technique to determine the mass-related concentrations of the total microplastics in marine sediments for evaluating their pollution status and quantitative contribution to marine carbon storage.

Determination of the physical state of a drug in amorphous solid dispersions using artificial neural networks and ATR-FTIR spectroscopy

The objective of the present study was to evaluate the use of artificial neural networks (ANNs) in the development of a new chemometric model that will be able to simultaneously distinguish and quantify the percentage of the crystalline and the neat amorphous drug located within the drug-rich amorphous zones formed in an amorphous solid dispersion (ASD) system. Attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy was used, while Rivaroxaban (RIV, drug) and Soluplus® (SOL, matrix-carrier) were selected for the preparation of a suitable ASD model system. Adequate calibration and test sets were prepared by spiking different percentages of the crystalline and the amorphous drug in the ASDs (prepared by the melting - quench cooling approach), while a 2⁴ full factorial experimental design was employed for the screening of ANN's structure and training parameters as well as spectra region selection and data preprocessing. Results showed increased prediction performance, measured based on the root mean squared error of prediction (RMSEp) for the test sample, for both the crystalline (RMSEp _(crystal) = 0.86) and the amorphous (RMSEp _(amorphous) = 2.14) drug. Comparison with traditional regression techniques, such as partial least square and principle component regressions, revealed the superiority of ANNs, indicating that in cases of high structural similarity between the investigated compounds (i.e., the crystalline and the amorphous forms of the same compound) the implementation of more powerful/sophisticated regression techniques, such as ANNs, is mandatory.

Rapid and highly sensitive quantification of the anti-tuberculosis agents isoniazid, ethambutol, pyrazinamide, rifampicin and rifabutin in human plasma by UPLC-MS/MS

With the increased cases of multidrug- or rifampicin-resistant tuberculosis and co-infection with HIV globally, it is difficult to achieve ideal clinical responses because of poor drug absorption and drug-drug interactions. Herein, a bioanalytical UPLC-MS/MS method was developed and validated to quantify five anti-TB agents in human plasma samples for detecting blood drug concentrations to improve therapeutic effects. To overcome the matrix effects, stable isotope labeled analogue of each analyte was used for internal standardization. A simple single-step protein precipitation by acetonitrile was employed for the sample preparation, then the analytes including rifampicin, rifabutin, pyrazinamid, ethambutol, isoniazid and their isotope labeled internal standards (ILISs) were implemented on an HILIC silica column with a gradient mode. The linear range for each analyte was covering the peak drug concentration (C_max) in the 20 times diluted plasma samples. The coefficient of variation of intra- and inter-day precision was less than 17.0 %, and the accuracy ranged between 91.5 and 110.0 %. The extraction recoveries of all agents were ≥90.2 %, and the matrix effects with internal standard-normalization for all agents were 97.1-110.0 %. The optimal blood sampling time was designed basing on the results of stability validation. This UPLC-MS/MS method with a run time of 3.5 min was successfully applied to routine therapeutic monitoring of the five anti-TB agents in patient plasma.

UPLC-MS/MS method for the simultaneous quantification of bictegravir and 13 others antiretroviral drugs plus cobicistat and ritonavir boosters in human plasma

A sensitive and rapid ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method has been developed and validated for 14 antiretroviral drugs and 2 boosters in human plasma. Plasma (100 μL) was precipitated with a solution of acetonitrile containing labelled internal standards. The compounds were separated with a total chromatic run time of 6 min using an Acclaim TM RSLC 120 C18 column (2.1 × 100 mm, 2.2 μm). The method was fully validated according to the European Medecines Agency guidelines. Linearity of all analytes concentrations was validated up to 5000 ng/mL. Lower limits of quantification were ranged from 2.5 ng/mL to 10 ng/mL according to compounds. Intra-day and inter-day precision ranged from 0.2% to 8.9% and accuracies were below 13%. This UPLC-MS/MS method can be applied to clinical pharmacology research and therapeutic drug monitoring in patients living with HIV.

Quantifying cumulative stress acting on macroinvertebrate assemblages in lowland streams

Macroinvertebrates in lowland streams are exposed to multiple stressors from the surrounding environment. Yet, quantifying how these multiple stressors impact macroinvertebrate assemblages is challenging. The aim of this study was to develop a novel method to quantify the cumulative stress acting on macroinvertebrate assemblages in lowland streams. To this purpose, we considered 22 stressors from different stressor categories such as hydrological, morphological and chemical stressors, acting over multiple spatial scales ranging from instream to the catchment scale. Stressor intensity was categorized into classes based on impact on the macroinvertebrate assemblages. The main stream was divided into segments, after which for each stream segment, the cumulative stressor contribution from headwater catchments, from the riparian zone and from upstream was calculated. To validate the cumulative stress quantification method, the lowland stream Tungelroyse Beek in the Netherlands was used as a case study. For this stream it was shown that independently derived ecological quality scores based on macroinvertebrate samples collected at multiple sites along the stream decreased with increasing calculated cumulative stress scores, supporting the design of the cumulative stress quantification method. Based on the contribution of each specific stressor to the cumulative stress scores, the reasons for the absence and presence of macroinvertebrate species may be elucidated. Hence, the cumulative stress quantification method may help to identify and localize the most stringent stressors limiting macroinvertebrate assemblages, and can thereby provide a better focus for management resources.

Improved measurement of absolute mRNA quantity without reverse transcription

Gene expression studies using microarrays have provided important insights into understanding the mechanisms of transcriptional regulation in a variety of biological and disease phenomena. In a previous study, we developed Photo-DEAN, a universal-microarray-based RNA quantification method that enabled reverse transcription-free multiplex measurement of the absolute amount of RNA. Photo-DEAN promotes high-throughput and bias-less transcriptome analysis without the need for common controls or additional complicated normalization steps. In this study, we empirically identified two conditions (individual specificity and uniform duplex stability) necessary for in silico design of probe sequences, allowing the Photo-DEAN method to accurately measure the absolute amount of target RNA in total RNA. We then demonstrated that using the modified probe design conditions, the Photo-DEAN method successfully measured the absolute amount of pgi mRNA spiked into E. coli total RNA. The measurement was performed at five different sites in the coding region of pgi mRNA, exhibiting no significant site dependence. Theoretical considerations suggested that probe sequences longer than the previously used 30-bases better satisfy the necessary design conditions.

A methodological approach for the on-site quantification of food losses in primary production: Austrian and German case studies using the example of potato harvest

In the last decade, in many European Countries more and more measures have been initiated aiming at the prevention of food losses and wastes along the entire value chain. In order to evaluate or monitor such important measures it is crucial to obtain quantitative information on generated food waste amounts, subsequently enabling the quantitative evaluation of the measure's outcomes and efficiency. Currently there is a paucity of quantitative information, particularly on food losses that are directly generated during harvesting processes. Up to date, no method is available or standardised aiming at the in-situ or on-site quantification of food losses during harvest. Using the example of the potato harvest, this study presents a practical approach for determining potato losses. To test the applicability of the developed method, on-site measurements were conducted directly on the field at five different locations in Austria and Germany. Our method enables the quantification of food losses based on defined areas along the harvested potato rows, where the analyser manually collects potatoes during their harvest. Hereby, two types of potato losses needs to be considered: non-harvested, under-sized potatoes that remain under the earth and the harvested ones, which are rejected on-site because of quality requirements regarding their size, shape, and state of health. Our study shows that between 1 and 9% of field losses (based on yield potential) can be generated during the potato harvest. In future, this method may be the basis for standardised protocols in order to be able to derive cultivar-specific benchmarks and, consequently, to develop measures for preventing food losses. In general, more case studies and evidence-based ground-up measurements on other cultivars and for other regions are needed focusing on the on-site quantification of post-harvest losses.

Comparison of myocardial fibrosis quantification methods by cardiovascular magnetic resonance imaging for risk stratification of patients with suspected myocarditis

BACKGROUND

Although the presence of late gadolinium enhancement (LGE) using cardiovascular magnetic resonance imaging (CMR) is a significant discriminator of events in patients with suspected myocarditis, no data are available on the optimal LGE quantification method.

METHODS

Six hundred seventy consecutive patients (48 ± 16 years, 59% male) with suspected myocarditis were enrolled between 2002 and 2015. We performed LGE quantitation using seven different signal intensity thresholding methods based either on 2, 3, 4, 5, 6, 7 standard deviations (SD) above remote myocardium or full width at half maximum (FWHM). In addition, a LGE visual presence score (LGE-VPS) (LGE present/absent in each segment) was assessed. For each of these methods, the strength of association of LGE results with major adverse cardiac events (MACE) was determined. Inter-and intra-rater variability using intraclass-correlation coefficient (ICC) was performed for all methods.

RESULTS

Ninety-eight (15%) patients experienced a MACE at a medium follow-up of 4.7 years. LGE quantification by FWHM, 2- and 3-SD demonstrated univariable association with MACE (hazard ratio [HR] 1.05, 95% confidence interval [CI]:1.02-1.08, p = 0.001; HR 1.02, 95%CI:1.00-1.04; p = 0.001; HR 1.02, 95%CI: 1.00-1.05, p = 0.035, respectively), whereas 4-SD through 7-SD methods did not reach significant association. LGE-VPS also demonstrated association with MACE (HR 1.09, 95%CI: 1.04-1.15, p < 0.001). In the multivariable model, FWHM, 2-SD methods, and LGE-VPS each demonstrated significant association with MACE adjusted to age, sex, BMI and LVEF (adjusted HR of 1.04, 1.02, and 1.07; p = 0.009, p = 0.035; and p = 0.005, respectively). In these, FWHM and LGE-VPS had the highest degrees of inter and intra-rater reproducibility based on their high ICC values.

CONCLUSIONS

FWHM is the optimal semi-automated quantification method in risk-stratifying patients with suspected myocarditis, demonstrating the strongest association with MACE and the highest technical consistency. Visual LGE scoring is a reliable alternative method and is associated with a comparable association with MACE and reproducibility in these patients.

TRIAL REGISTRATION NUMBER

NCT03470571 . Registered 13th March 2018. Retrospectively registered.

A straightforward assay for measuring glycogen levels and RpoS

Cellular glycogen levels reflect the activity of RpoS, an important stress-inducible bacterial sigma factor known to regulate several stress-resistance related genes, such as katE, encoding hydroperoxidase II (HPII), and the glg genes, encoding glycogen synthesis enzymes, in Escherichia coli. In this study, a straightforward assay for measuring glycogen levels and RpoS activity was developed combining the ease and simplicity of qualitative approaches. The assay reagent was a 2% iodine solution (2% iodine/1M NaOH), and the basic principle of this assay is the iodine-glycogen reaction, which produces a reddish brown color that can be measured using a spectrophotometer. A calibration plot using a known amount of glycogen yielded the best linear fit over a range of 10-300μg/assay (R²=0.994). The applicability of the assay for measuring the glycogen level of various samples was assessed using a wild type (WT) E. coli K-12 strain, glycogen- and RpoS-deficient isogenic mutants, and clinical bacterial isolates with or without RpoS activity; the assay generated reproducible results. Additionally, the assay was successfully applied for measuring glycogen levels in human cells. In conclusion, we developed a straightforward and cost-effective assay for measuring glycogen levels, which can be applied for measuring RpoS activity.

A multiplex RNA quantification method to determine the absolute amounts of mRNA without reverse transcription

We have developed a highly sensitive microarray-based method that determines the absolute amounts of mRNA in a total RNA sample in a multiplex manner without reverse transcription. This direct mRNA measurement promotes high-throughput testing and reduces bias in transcriptome analyses. Furthermore, quantification of the absolute amount of mRNA allows transcriptome analysis without common controls or additional, complicated normalization. The method, called Photo-DEAN, was validated using chemically synthesized RNAs of known quantities and mouse liver total RNA samples. We found that the absolute amounts of mRNA were successfully measured without the cDNA synthesis step, with a sensitivity of 15 zmol achieved in 7 h.

Evaluation of method bias for determining bacterial populations in bacterial community analyses

Various methods are used for analyzing a bacterial community. We recently developed a method for quantifying each bacterium constituting the microbiota by combining a next-generation sequencing (NGS) analysis with a quantitative polymerase chain reaction (NGS-qPCR) assay. Our NGS-qPCR method is useful for analyzing a comprehensive bacterial community because it is enables the easy calculation of the amounts of each bacterium constituting the microbiota. However, it has not been confirmed whether the estimated bacterial community obtained using this NGS-qPCR method corresponds to the results obtained using conventional methods. Accordingly, we prepared model bacterial community samples and analyzed them by several methods (NGS-qPCR, species-specific qPCR, flow cytometry, total direct counting by epifluorescent microscopy [TDC], and plate count). The total bacterial cell densities determined by the PCR-based methods were largely consistent with those determined by the TDC method. There was a difference between the amounts of each bacterium analyzed by NGS-qPCR and species-specific qPCR, although the same trend was shown by both species-specific qPCR and NGS-qPCR. Our findings also demonstrated that there is a strong positive correlation between the cell densities of a specific bacterial group in craft beer samples determined by group-specific qPCR and NGS-qPCR, and there were no significant differences among quantification methods (we tested two bacterial groups: lactic acid bacteria and acetic acid bacteria). Thus, the NGS-qPCR method is a practical method for analyzing a comprehensive bacterial community based on a bacterial cell density.

A simple dilute and shoot methodology for the identification and quantification of illegal insulin

The occurrence of illegal medicines is a well-established global problem and concerns mostly small molecules. However, due to the advances in genomics and recombinant expression technologies there is an increased development of polypeptide therapeutics. Insulin is one of the best known polypeptide drug, and illegal versions of this medicine led to lethal incidents in the past. Therefore, it is crucial for the public health sector to develop reliable, efficient, cheap, unbiased and easily applicable active pharmaceutical ingredient (API) identification and quantification strategies for routine analysis of suspected illegal insulins. Here we demonstrate that our combined label-free full scan approach is not only able to distinguish between all those different versions of insulin and the insulins originating from different species, but also able to chromatographically separate human insulin and insulin lispro in conditions that are compatible with mass spectrometry (MS). Additionally, we were also able to selectively quantify the different insulins, including human insulin and insulin lispro according to the validation criteria, put forward by the United Nations (UN), for the analysis of seized illicit drugs. The proposed identification and quantification method is currently being used in our official medicines control laboratory to analyze insulins retrieved from the illegal market.