Rapid testing of antibiotic residues to increase food safety awareness of animal origin.

Background and Aim: Antibiotics are used to improve growth, reduce disease, and decrease mortality in animals grown for food. The government regulates and prohibits the use of antibiotics, in particular, the use of antibiotic growth promoter (AGP) in livestock; however, it is not yet known whether the use of antibiotics is in accordance with regulations so that there are no antibiotic residues in food of animal origin. To ensure food safety of animal origin and to raise awareness of food safety, it is necessary to detect antibiotic residues in fish, eggs, and chicken meat from Yogyakarta Special Province through monitoring and monitoring. To ensure food safety and regulatory compliance in food samples, antibiotic residue screening techniques are essential. A number of methods, such as time-consuming and costly chromatographic and spectroscopic methods, have been developed for the detection of antibiotic residues in food samples; however, not all laboratories have these facilities. Therefore, a rapid diagnosis of food of animal origin is required. The purpose of this study was to rapidly test antibiotic residues by using Premi®test kits (R-Biopharm AG, Germany) to increase awareness of food safety of animal origin. Materials and Methods: We tested 345 animal-based food samples from traditional markets, supermarkets, and central markets in five districts of Yogyakarta Special Province for antibiotic residues using rapid test kits and observation questionnaires to identify risk factors. Results: The presence of antibiotic residues in food-animal origin samples from the Yogyakarta region had an antibiotic residue level of 9.28% (32/345), consisting of fish samples 11.3% (18/97), eggs 15.65% (1/114), and chicken meat samples 0.87% (13/102). The highest percentage of samples positive for residual antibiotics was 21.9% (7/32) from supermarket meat samples. The highest amounts of antibiotic residues were found in fish samples collected from Sleman Regency, up to 25% (8/32), whereas in supermarket fish samples, there were as high as 18.8% (6/32). Conclusion: Antibiotic residues in animal-based food can be attributed to various factors, including product source, transportation conditions, and environmental conditions. The widespread distribution of antibiotic residues in fish comes from environmental conditions during maintenance, distribution, and retailing. Monitoring antibiotic residue prevalence in food-animal origins, particularly chicken meat, eggs, and fish, is crucial for improving animal food quality and safety.

A rapid and multi-endpoint ecotoxicological test using Mychonastes afer for efficient screening of metals and herbicides.

Microalgal growth-based tests are international standards for ecotoxicity assessment; however, their long exposure times, large sample volumes, and reliance on a single growth-endpoint make them inadequate for rapid toxicity screening. Here, we aimed to develop a rapid and simple ecotoxicological test using the fast-growing green alga Mychonastes afer, with multiple endpoints-growth, lipid content, and photosynthesis. We exposed M. afer to two metals-silver and copper-and two herbicides-atrazine and diuron-for 24 h and identified the most sensitive and reliable endpoints for each toxicant: the maximum electron transport rate (ETRmax) for Ag, Cu and atrazine, and the lipid content for diuron. Lipid content was found to be both a sensitive and reliable biomarker, meeting the effluent limit guidelines in both the Republic of Korea and the USA. The sensitivity of M. afer to Ag and atrazine also closely matched the HC5 values derived from the species sensitivity distribution approach, confirming its reliability for setting regulatory concentrations of these contaminants. Our calculated predicted no-effect concentration (PNEC) values were similar to established European Union PNECs for Ag, Cu, atrazine, and diuron, underlining the utility of these biological endpoints for ecological risk assessment and regulatory decision making. This method required lower sample volume (2 mL vs 100 mL) and exposure time (24 h vs 72-120 h) than conventional green algal tests, and eliminated the need for labour-intensive cell counting, expensive equipment, and chlorophyll fluorescence measurement expertise. Overall, this M. afer test can be a valuable tool for the rapid screening of wastewater for metals and herbicides, contributing to environmental protection and management practices.

3D spheroid HepaRG and fluorescent biphasic tracer for CYP3A4-mediated antibiotic interaction monitoring in sepsis.

Cytochrome P450 3A4 (CYP3A4) is a crucial enzyme in the metabolism of xenobiotics, particularly in drug metabolism interactions (DDIs), making it a significant factor in clinical drug use. However, current assay techniques are both laborious and costly, making it difficult to construct a high-throughput monitoring method that can be used in conjunction with the clinic. This poses certain safety hazards for drug combination. Therefore, it is crucial to develop a synchronized monitoring method for the inhibition and induction of CYP3A4. In this study, we utilized 3D culture technology to develop a HepaRG cells spheroid model. The CYP450 and transporter expression, the albumin secretion, and urea synthesis capacity characteristics were analyzed. The NEN probe was utilized as a tracer molecule for CYP3A4. The fluorescence intensity of metabolites was characterized by laser confocal technique to determine the inhibition and expression of CYP3A4 in the HepaRG cell spheroid model by the antibiotics for sepsis. The results indicate that the HepaRG sphere model successfully possessed the physiological phenotype of the liver, which could be used for drug interaction monitoring. Through positive drug testing, NEN probe was able to achieve bidirectional characterization of CYP3A4 induction and inhibition. The monitoring method described in this paper was successfully applied to drug interaction monitoring of commonly used antibiotics in sepsis patients, which is a convenient and rapid monitoring method. The proposed method offers a new strategy for monitoring CYP3A4-mediated drug-drug interactions with a high-throughput assay, which will help to improve the safety of clinical drug combination.

The feasible screening of genuine fresh palmyrah toddy and sugar or rice toddy using near-infrared spectroscopy.

The use of combination of Near-Infrared (NIR) absorption spectroscopic and k-mean multivariant statical cluster analysis as a screening tools for genuine fresh palmyrah toddy(G.F) and sugar (ATS) or rice toddy(ATS) is discussed. The quick and simple screening methods to ensure the authenticity of G.F is prime important to keep up its commercial value. Here we performed NIR spectroscopic analysis, k-mean multivariant analysis, and hierarchical cluster analysis to screen the G.F from ATR and ATS. For comparison, we performed chemical analysis and distinguished G.F from ATR and ATS. However, based on the NIR spectroscopic analysis together with the multivariant analysis G.F quickly screened from ATR and ATS. The plot of k-means cluster analysis and hierarchical cluster analysis shows three distinct clusters and it could be a useful tool to quickly screen the genuine toddy from artificial toddy.

Differentiating Microplastics from Natural Particles in Aqueous Suspensions Using Flow Cytometry with Machine Learning.

Microplastics (MPs) in natural waters are heterogeneously mixed with other natural particles including algal cells and suspended sediments. An easy-to-use and rapid method for directly measuring and distinguishing MPs from other naturally present colloids in the environment would expedite analytical workflows. Here, we established a database of MP scattering and fluorescence properties, either alone or in mixtures with natural particles, by stain-free flow cytometry. The resulting high-dimensional data were analyzed using machine learning approaches, either unsupervised (e.g., viSNE) or supervised (e.g., random forest algorithms). We assessed our approach in identifying and quantifying model MPs of diverse sizes, morphologies, and polymer compositions in various suspensions including phototrophic microorganisms, suspended biofilms, mineral particles, and sediment. We could precisely quantify MPs in microbial phototrophs and natural sediments with high organic carbon by both machine learning models (identification accuracies over 93%), although it was not possible to distinguish between different MP sizes or polymer compositions. By testing the resulting method in environmental samples through spiking MPs into freshwater samples, we further highlight the applicability of the method to be used as a rapid screening tool for MPs. Collectively, this workflow can be easily applied to a diverse set of samples to assess the presence of MPs in a time-efficient manner.

High-Throughput Screening of PAM-Flexible Cas9 Variants for Expanded Genome Editing in the Silkworm (Bombyx mori).

Genome editing provides novel opportunities for the precise genome engineering of diverse organisms. Significant progress has been made in the development of genome-editing tools for Bombyx mori (B. mori) in recent years. Among these, CRISPR/Cas9, which is currently the most commonly used system in lepidopteran insects, recognizes NGG protospacer adjacent motif (PAM) sequences within the target locus. However, Cas9 lacks the ability to target all gene loci in B. mori, indicating the need for Cas9 variants with a larger editing range. In this study, we developed a high-throughput screening platform to validate Cas9 variants at all possible recognizable and editable PAM sites for target sequences in B. mori. This platform enabled us to identify PAM sites that can be recognized by both xCas9 3.7 and SpCas9-NG variants in B. mori and to assess their editing efficiency. Cas9 shows PAM sites every 13 base pairs in the genome, whereas xCas9 3.7 and SpCas9-NG have an average distance of 3.4 and 3.6 base pairs, respectively, between two specific targeting sites. Combining the two Cas9 variants could significantly expand the targeting range of the genome, accelerate research on the B. mori genome, and extend the high-throughput rapid screening platform to other insects, particularly those lacking suitable NGG PAM sequences.

Rapid screening of infertility-associated gynecological conditions via ambient glow discharge mass spectrometry utilizing urine metabolic fingerprints.

Infertility presents a widespread challenge for many families worldwide, often arising from various gynecological diseases (GDs) that hinder successful pregnancies. Current diagnostic methods for GDs have disadvantages such as low efficiency, high cost, misdiagnose, invasive injury and etc. This paper introduces a rapid, non-invasive, efficient, and straightforward analytical method that utilizes desorption, separation, and ionization mass spectrometry (DSI-MS) platform in conjunction with machine learning (ML) to detect urine metabolite fingerprints in patients with different GDs. We analyzed 257 samples from patients diagnosed with polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), endometriosis (EMS), recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), and 87 samples from healthy control (HC) individuals. We identified metabolite differences and dysregulated pathways through dimensionality reduction methods, with the result of the discovery of 7 potential biomarkers for GDs diagnosis. The ML method effectively distinguished subtle differences in urine metabolite fingerprints. We anticipate that this innovative approach will offer a patient-friendly, rapid screening, and differentiation method for infertility-related GDs patients.

Discriminating extra virgin olive oils from common edible oils: Comparable performance of PLS-DA models trained on low-field and high-field 1H NMR data.

INTRODUCTION: Olive oil, derived from the olive tree (Olea europaea L.), is used in cooking, cosmetics, and soap production. Due to its high value, some producers adulterate olive oil with cheaper edible oils or fraudulently mislabel oils as olive to increase profitability. Adulterated products can cause allergic reactions in sensitive individuals and can lack compounds which contribute to the perceived health benefits of olive oil, and its corresponding premium price. OBJECTIVE: There is a need for robust methods to rapidly authenticate olive oils. By utilising machine learning models trained on the nuclear magnetic resonance (NMR) spectra of known olive oil and edible oils, samples can be classified as olive and authenticated. While high-field NMRs are commonly used for their superior resolution and sensitivity, they are generally prohibitively expensive to purchase and operate for routine screening purposes. Low-field benchtop NMR presents an affordable alternative. METHODS: We compared the predictive performance of partial least squares discrimination analysis (PLS-DA) models trained on low-field 60 MHz benchtop proton (1H) NMR and high-field 400 MHz 1H NMR spectra. The data were acquired from a sample set consisting of 49 extra virgin olive oils (EVOOs) and 45 other edible oils. RESULTS: We demonstrate that PLS-DA models trained on low-field NMR spectra are highly predictive when classifying EVOOs from other oils and perform comparably to those trained on high-field spectra. We demonstrated that variance was primarily driven by regions of the spectra arising from olefinic protons and ester protons from unsaturated fatty acids in models derived from data at both field strengths.

Rapid screening of the novel bioactive peptides with notable α-glucosidase inhibitory activity by UF-LC-MS/MS combined with three-AI-tool from black beans.

This work aimed to propose a rapid method to screen the bioactive peptides with anti-α-glucosidase activity instead of traditional multiple laborious purification and identification procedures. 242 peptides binding to α-glycosidase were quickly screened and identified by bio-affinity ultrafiltration combined with LC-MS/MS from the double enzymatic hydrolysate of black beans. Top three peptides with notable anti-α-glucosidase activity, NNNPFKF, RADLPGVK and FLKEAFGV were further rapidly screened and ranked by the three artificial intelligence tools (three-AI-tool) BIOPEP database, PeptideRanker and molecular docking from the 242 peptides. Their IC50 values were in order as 4.20 ± 0.11 mg/mL, 2.83 ± 0.03 mg/mL, 1.32 ± 0.09 mg/mL, which was opposite to AI ranking, for the hydrophobicity index of the peptides was not included in the screening criteria. According to the kinetics, FT-IR, CD and ITC analyses, the binding of the three peptides to α-glucosidase is a spontaneous and irreversible endothermic reaction that results from hydrogen bonds and hydrophobic interactions, which mainly changes the α-helix structure of α-glucosidase. The peptide-activity can be evaluated vividly by AFM in vitro. In vivo, the screened FLKEAFGV and RADLPGVK can lower blood sugar levels as effectively as acarbose, they are expected to be an alternative to synthetic drugs for the treatment of Type 2 diabetes.

A Prospective Study of an Early Prediction Model of Attention Deficit Hyperactivity Disorder Based on Artificial Intelligence.

OBJECTIVE: To explore the relationship between the Parent Symptom Questionnaire (PSQ) and attention deficit hyperactivity disorder (ADHD) in China, and the application value of PSQ questionnaire. METHOD: Two hundred two children aged 3 to 14 years were enrolled in this study. Statistical methods were used to screen characteristic factors and explore the relationship between PSQ items and ADHD. Machine learning algorithms were used to evaluate the clinical application value of PSQ in screening ADHD. RESULTS: By Mean-Whitney U test, LASSO regression and decision tree, 44, 24 and 12 items were screened out from PSQ with high correlation with ADHD. Then the above items were classified, and the accuracy reached more than 90%. Moreover, the items of ADHD hyperactivity index of PSQ under artificial intelligence algorithm are different from those of PSQ. CONCLUSION: There are some differences in the items of hyperactivity index between the PSQ and ADHD in China. The artificial intelligence algorithm model of ADHD children based on PSQ scale has a high accuracy.

Evaluation of universal preenrichment broth and comparison of rapid molecular methods for the detection of Salmonella from spent sprout irrigation water (SSIW).

Sprouts and spent sprout irrigation water (SSIW) present unique challenges for the development of a Salmonella detection method in food matrices. This study aimed to compare universal preenrichment broth (UPB) and lactose broth (LB) as preenrichment media for cultural and rapid screening methods and to compare their abilities to recover Salmonella in SSIW samples from different sprout varieties (i.e., alfalfa, broccoli, and mung bean sprouts). The associated co-enriched microbiota with different sprout varieties using different preenrichment media were also examined using a quasi-metagenomic approach. The performance of media and detection methods was compared using the relative level of detection (RLOD) value, as recommended by ISO 16140-2:2016. The level of detection (LOD) for Salmonella culture method with UPB was similar to that with LB in low aerobic plate count (APC) background samples (the relative LOD, i.e., RLOD, was nearly 1 after adjusting for the effects of SSIW variety and serovar), but significantly lower than that with LB in high APC background samples (RLOD = 0.32). The LOD for Salmonella with selected rapid methods was comparable to each other (RLOD from 0.97 to 1.50) and to the culture method (RLOD from 0.69 to 1.03), and no significant difference was detected between preenrichment broths in low APC background samples with RLOD values between 0.76 and 1.04. In samples with a high APC background, however, a drastic difference in LOD was observed between methods and between preenrichment broths for each method. The RLOD ranged from 0.03 to 0.32 when UPB was compared to LB as preenrichment broth. The composition and relative abundance (RA) of co-enriched microbiota was affected by multiple factors including food matrices, preenrichment media and Salmonella contamination. Altogether, this study validated UPB as a better preenrichment broth than LB for the detection of Salmonella enterica from SSIW. This study also suggested UPB may also be an optimal preenrichment medium for rapid screening methods when APC level is high. The observation of potential exclusion of Salmonella in preenrichment through the overgrowth of competitive microflora from the quasi-metagenomic study provided novel information that may be used to further optimize preenrichment formulations.

The cost of adding rapid screening for diabetes, hypertension, and COVID-19 to COVID-19 vaccination queues in Johannesburg, South Africa.

Background: Non-communicable diseases (NCDs) are responsible for 51% of total mortality in South Africa, with a rising burden of hypertension (HTN) and diabetes mellitus (DM). Incorporating NCD and COVID-19 screening into mass activities such as COVID-19 vaccination programs could offer significant long-term benefits for early detection interventions. However, there is limited knowledge of the associated costs and resources required. We evaluated the cost of integrating NCD screening and COVID-19 antigen rapid diagnostic testing (Ag-RDT) into a COVID-19 vaccination program. Methods: We conducted a prospective cost analysis at three public sector primary healthcare clinics and one academic hospital in Johannesburg, South Africa, conducting vaccinations. Participants were assessed for eligibility and recruited during May-Dec 2022. Costs were estimated from the provider perspective using a bottom-up micro-costing approach and reported in 2022 USD. Results: Of the 1,376 enrolled participants, 240 opted in to undergo a COVID-19 Ag-RDT, and none tested positive for COVID-19. 138 (10.1%) had elevated blood pressure, with 96 (70%) having no prior HTN diagnosis. 22 (1.6%) were screen-positive for DM, with 12 (55%) having no prior diagnosis. The mean and median costs per person screened for NCDs were $2.53 (SD: 3.62) and $1.70 (IQR: $1.38-$2.49), respectively. The average provider cost per person found to have elevated blood glucose levels and blood pressure was $157.99 and $25.19, respectively. Finding a new case of DM and HTN was $289.65 and $36.21, respectively. For DM and DM + HTN screen-positive participants, diagnostic tests were the main cost driver, while staff costs were the main cost driver for - and HTN screen-positive and screen-negative participants. The mean and median cost per Ag-RDT was $6.13 (SD: 0.87) and $5.95 (IQR: $5.55-$6.25), with costs driven mainly by test kit costs. Conclusions: We show the cost of finding new cases of DM and HTN in a vaccine queue, which is an essential first step in understanding the feasibility and resource requirements for such initiatives. However, there is a need for comparative economic analyses that include linkage to care and retention data to fully understand this cost and determine whether opportunistic screening should be added to general mass health activities.

Plastic probe electrospray ionization mass spectrometry developed for rapid fingerprint profile of biological samples without pretreatment.

A triangular-shaped flat plastic substrate probe was prepared for direct electrospray ionization mass spectrometry (ESI-MS) for analysis of untreated chemical and biological samples including liquids (Met-Arg-Phe-Ala peptide, reserpine, and dodecyl aldehyde), solids (biological samples, traditional Chinese medicine), and powders (roasted coffee, rhizoma coptidis, lotus plumule, and Schisandra sphenanthera). Quantitative analysis of reserpine in water yielded a detection limit of 1 ng mL-1, dynamic response range within 1-500 ng mL-1, and linearity of signal response ˃0.9925. Compared to the conventional capillary ESI, this plastic probe ESI offers lower cost of analysis (US $0.0056 per probe), higher sensitivity, lower sample consumption, longer signal duration (>6 min), better reproducibility, signal stability, and higher speed of analysis (<10 s per sample, including sample loading). Overall, the results indicate the potential of ESI-MS based on flat plastic probes as a versatile method for simple, sensitive, and stable analysis of untreated biological sample analysis.

Triplet-primed PCR and Melting Curve Analysis for Rapid Molecular Screening of Spinocerebellar Ataxia Types 1, 2, and 3.

There are more than 40 types of spinocerebellar ataxia (SCA), most of which are caused by abnormal expansion of short tandem repeats at various gene loci. These phenotypically similar disorders require molecular testing at multiple loci by fluorescent PCR and capillary electrophoresis to identify the causative repeat expansion. We describe a simple strategy to screen for the more common SCA1, SCA2, and SCA3 by rapidly detecting the abnormal CAG repeat expansion at the ATXN1, ATXN2, and ATXN3 loci using melting curve analysis of triplet-primed PCR products. Each of the three separate assays employs a plasmid DNA carrying a known repeat size to generate a threshold melt peak temperature, which effectively distinguishes expansion-positive samples from those without a repeat expansion. Samples that are screened positive based on their melt peak profiles are subjected to capillary electrophoresis for repeat sizing and genotype confirmation. These screening assays are robust and provide accurate detection of the repeat expansion while eliminating the need for fluorescent PCR and capillary electrophoresis for every sample.

Investigation of Chemical Constituents and Antioxidant Activity of Biologically Active Plant-Derived Natural Products.

The aim of this publication is to present rapid screening methods (visual/colorimetric) that will enable quick identification of the presence of biologically active compounds in aqueous solutions. For this reason, 26 plant extracts obtained by ultrasound-assisted extraction were analysed for the content of these compounds. Higher plants, used as a raw material for extraction, are common in Europe and are easily available. The article proposes a comparison of various protocols for the identification of various compounds, e.g., phenolic compounds (phenols, tannins, anthocyanins, coumarins, flavones, flavonoids), vitamin C, quinones, quinines, resins, glycosides, sugars. Initial characterisation of the composition of plant extracts using fast and inexpensive methods allows you to avoid the use of time-consuming analyses with the use of advanced research equipment. In addition, the antioxidant activity of plant extracts using spectrophotometric methods (DPPH, ABTS, FRAP assay) and quantitative analysis of plant hormones such as abscisic acid, benzoic acid, gibberellic acid, indole acetic acid, jasmonic acid, salicylic acid, zeatin, zeatin riboside, and isipentenyl adenine was performed. The obtained results prove that the applied visual methods show different sensitivity in detecting the sought chemical compounds. Therefore, it is necessary to confirm the presence or absence of bioactive substances and their concentration using modern analytical methods.

Screening Method and Antibacterial Activity of 1,3,4-Oxadiazole Sulfone Compounds against Citrus Huanglongbing.

Citrus Huanglongbing (HLB) is one of the most destructive diseases in the citrus industry. At present, Candidatus Liberibacter asiaticus (CLas) cannot be cultured in vitro, and there is a lack of rapid methods to test antibacterial activity, which greatly hinders the discovery of new antibacterial agents against HLB. To establish a rapid screening method for antibacterial agents against HLB with simple operation, a short cycle, and a large number of tests, the CLas contents in leaves from different citrus branches, different leaves from the same citrus branch, and two halves of the same citrus leaf were detected. Compared with the leaves on different branches and different leaves on the same branch, the difference in CLas content of the left and right halves of the same leaf was small; the difference was basically between 0.7 and 1.3. A rapid and efficient method for primary screening agents against HLB termed the "half-leaf method" was established through our long-term optimization and improvement. To verify the stability and reliability of the activity data measured using this method, 6-chloropurine riboside, which is highly soluble in water, was used as the test agent, and its antibacterial activity against HLB was tested 45 times. The results of the antibacterial activity test showed little difference in the mean values of each data group, indicating that this method could be used as a rapid method for screening agents against HLB. We used this method to test the antibacterial activity of compounds synthesized by our research group against HLB and found that some of the compounds showed good activity.

Real-time on-site detection of the three 'Candidatus Liberibacter' species associated with HLB disease: a rapid and validated method.

Huanglongbing (HLB) is a devastating disease that affects all commercial citrus species worldwide. The disease is associated with bacteria of three species of the genus 'Candidatus Liberibacter' transmitted by psyllid vectors. To date, HLB has no cure, so preventing its introduction into HLB-free areas is the best strategy to control its spread. For that, the use of accurate, sensitive, specific, and reliable detection methods is critical for good integrated management of this serious disease. This study presents a new real-time recombinase polymerase amplification (RPA) protocol able to detect the three 'Ca. Liberibacter' species associated with HLB in both plant and insect samples, validated according to European and Mediterranean Plant Protection Organization (EPPO) guidelines and tested on 365 samples from nine different geographic origins. This new protocol does not require nucleic acid purification or specialized equipment, making it ideal to be used under field conditions. It is based on specific primers and probe targeting a region of fusA gene, which shows a specificity of 94%-100%, both in silico and in vitro, for the 'Ca. Liberibacter' species associated with HLB. The analytical sensitivity of the new protocol is excellent, with a reliable detection limit in the order of 101 copies per microliter in HLB-infected plant and insect material. The repeatability and reproducibility of the new methods showed consistent results. Diagnostic parameters of the new RPA protocol were calculated and compared with the gold standard technique, a quantitative real-time PCR, in both crude extracts of citrus plants and insect vectors. The agreement between the two techniques was almost perfect according to the estimated Cohen's kappa index, with a diagnostic sensitivity and specificity of 83.89% and 100%, respectively, and a relative accuracy of 91.59%. Moreover, the results are obtained in less than 35 min. All these results indicate the potential of this new RPA protocol to be implemented as a reliable on-site detection kit for HLB due to its simplicity, speed, and portability.

Validation of quantitative real-time polymerase chain reaction for detection of Legionella pneumophila in hospital water networks.

BACKGROUND: Rapid monitoring of Legionella pneumophila (Lp) is essential to reduce the risk of Legionnaires' disease in healthcare facilities. However, culture results take at least eight days, delaying the implementation of corrective measures. Here, we assessed the performance of a qPCR method and determined qPCR action thresholds for the detection of Lp in hospital hot water networks (HWNs). METHODS: Hot water samples (N = 459) were collected from a hospital HWN. Lp were quantified using iQ-Check® Quanti real-time PCR Quantification kits (Bio-Rad) and the results were compared with those of culture. qPCR thresholds corresponding to the culture action thresholds of 10 and 1000 cfu/L were determined on a training dataset and validated on an independent dataset. RESULTS: Lp concentrations measured by culture and qPCR were correlated for both the training dataset (Spearman's correlation coefficient ρ = 0.687, P<0.0001) and the validation dataset (ρ = 0.661, P<0.0001). Lp qPCR positivity thresholds corresponding to culture action thresholds of 10 cfu/L was 91 genome units (gu) per litre (sensitivity, 86.4%; negative predictive value - NPV, 93.3%) and that corresponding to culture action thresholds of 1000 cfu/L was 1048 gu/L (sensitivity, 100%; NPV, 100%). CONCLUSION: Detection of Lp by qPCR could be implemented with confidence in hospitals as a complement to culture in the monitoring strategy to speed up the implementation of corrective measures.

Rapid screening of benzyl dodecyl dimethyl ammonium bromide co-metabolic degrading bacteria based on NIR hyperspectral imaging technology.

As a typical disinfectant, the use of benzyl dodecyl dimethyl ammonium bromide (BDAB) has dramatically increased since the emergence of SARS-CoV-2, posing a threat to environmental balance and human health. Screening BDAB co-metabolic degrading bacteria is required for efficient microbial degradation. Conventional methods for screening co-metabolic degrading bacteria are laborious and time-consuming, especially when the number of strains is large. This study aimed to develop a novel method for the rapid screening of BDAB co-metabolic degrading bacteria from the cultured solid medium using near-infrared hyperspectral imaging (NIR-HSI) technology. Based on NIR spectra, the concentration of BDAB in the solid medium can be well predicted by partial least squares regression (PLSR) models, non-destructively and rapidly, with Rc2 > 0.872 and Rcv2 > 0.870. The results show that the predicted BDAB concentrations decrease after degrading bacteria utilization, comparing with the regions where no degrading bacteria grew. The proposed method was applied to directly identify the BDAB co-metabolic degrading bacteria cultured on the solid medium, and two kinds of co-metabolic degrading bacteria RQR-1 and BDAB-1 were correctly identified. This method provides a high-efficiency method for screening BDAB co-metabolic degrading bacteria from a large number of bacteria.

A RaPID Macrocyclic Peptide That Inhibits the Formation of α-Synuclein Amyloid Fibrils.

There is considerable interest in drug discovery targeting the aggregation of α-synuclein (αSyn) since this molecular process is closely associated with Parkinson's disease. However, inhibiting αSyn aggregation remains a major challenge because of its highly dynamic nature which makes it difficult to form a stable binding complex with a drug molecule. Here, by exploiting Random non-standard Peptides Integrated Discovery (RaPID) system, we identified a macrocyclic peptide, BD1, that could interact with immobilized αSyn and inhibit the formation of fibrils. Furthermore, improving the solubility of BD1 suppresses the co-aggregation with αSyn fibrils while it kinetically inhibits more effectively without change in their morphology. We also revealed the molecular mechanism of kinetic inhibition, where peptides bind to fibril ends of αSyn, thereby preventing further growth of fibrils. These results suggest that our approach for generating non-standard macrocyclic peptides is a promising approach for developing potential therapeutics against neurodegeneration.