Monitoring Live Mycobacteria in Real-Time Using a Microfluidic Acoustic-Raman Platform.

Tuberculosis (TB) is the most common cause of death from an infectious disease. Although treatment has been available for more than 70 years, it still takes too long and many patients default risking relapse and the emergence of resistance. It is known that lipid-rich, phenotypically antibiotic-tolerant, bacteria are more resistant to antibiotics and may be responsible for relapse necessitating extended therapy. Using a microfluidic system that acoustically traps live mycobacteria, M. smegmatis, a model organism for M. tuberculosis we can perform optical analysis in the form of wavelength-modulated Raman spectroscopy (WMRS) on the trapped organisms. This system can allow observations of the mycobacteria for up to 8 h. By adding antibiotics, it is possible to study the effect of antibiotics in real-time by comparing the Raman fingerprints in comparison to the unstressed condition. This microfluidic platform may be used to study any microorganism and to dynamically monitor its response to many conditions including antibiotic stress, and changes in the growth media. This opens the possibility of understanding better the stimuli that trigger the lipid-rich downregulated and phenotypically antibiotic-resistant cell state.

Comparison of serological and molecular methods for differentiation between genotype A and genotype B strains of small ruminant lentiviruses.

Introduction: Small ruminant lentiviruses (SRLV) cause multisystemic, degenerative and chronic disease in sheep and goats. There are five genotypes (A, B, C, D and E), of which A and B are the most widespread. The purpose of this study was to evaluate the serotyping efficiency of the Eradikit SRLV Genotyping ELISA and the molecular typing efficiency of a newly developed nested real-time PCR targeting the long terminal repeat-gag (LTR-gag) region using samples from animals infected with subtypes of SRLV known to circulate in Poland. Material and Methods: A total of 97 sera samples taken from 34 sheep and 63 goats were immunoassayed, and 86 DNA samples from 31 sheep and 55 goats were tested with the PCR. All ruminants were infected with known SRLV strains of the A1, A5, A12, A13, A16, A17, A18, A23, A24, A27, B1 and B2 subtypes. Results: A total of 69 (80.2%, 95% confidence interval 71.6%-88.8%) out of 86 tested samples gave positive results in the PCR. In 17 out of the 86 (19.8%) samples, no proviral DNA of SRLV was detected. The differentiation between MVV (genotype A) and CAEV (genotype B) by PCR matched the predating phylogenetic analysis invariably. No cross-reactivity was observed. On the other hand, the proportion of samples genotyped the same by the older phylogenetic analysis and the Eradikit SRLV Genotyping ELISA was 42.3%. The test was unable to classify 40.2% of samples, and 17.5% of sera were incorrectly classified. Conclusion: Our results showed that the Eradikit SRLV genotyping kit is not a reliable method for predicting SRLV genotype, while the nested real-time PCR based on the LTR-gag region did prove to be, at least for genotypes A and B.

A review of pollution-based real-time modelling and control for sewage systems.

Conventional solutions for wastewater collection focus on reducing overflow events in the sewage network, which can be achieved by adapting sewer infrastructure or, a more cost-effective alternative, by implementing a non-engineering management solution. The state-of-the-art solution is centered on Real-Time Control (RTC), which is already resulting in a positive impact on the environment by decreasing the volume of wastewater being discharged into receiving waters. Researchers have been continuing efforts towards upgrading RTC solutions for sewage systems and a new approach, although rudimentary, was introduced in 1997, known as Pollution-based RTC (P-RTC), which added water quality (concentration or load) information explicitly within the RTC algorithm. Formally, P-RTC is encompassed of several control methodologies using a measurement or estimation of the concentration (i.e. COD or ammonia) of the sewage throughout the network. The use of P-RTC can result in a better control performance with a reduction in concentration of overflowing wastewater observed associated with an increase of concentration of sewage arriving at the Wastewater Treatment Plant (WWTP). The literature revealed that P-RTC can be differentiated by: (1) implementation method; (2) how water quality is incorporated, and (3) overall control objectives. Additionally, this paper evaluates the hydrological models used for P-RTC. The objective of this paper is to compile relevant research in pollution-based modelling and real-time control of sewage systems, explaining the general concepts within each P-RTC category and their differences.

An Energy Efficient and Temperature Stable Digital FLL-based Wakeup Timer with Time-Domain Temperature Compensation.

This brief presents an on-chip digital intensive frequency-locked loop (DFLL)-based wakeup timer with a time-domain temperature compensation featuring a embedded temperature sensor. The proposed compensation exploits the deterministic temperature characteristics of two complementary resistors to stabilize the timer's operating frequency across the temperature by modulating the activation time window of the two resistors. As a result, it achieves a fine trimming step (± 1 ppm), allowing a small frequency error after trimming (<± 20 ppm). By reusing the DFLL structure, instead of employing a dedicated sensor, the temperature sensing operates in the background with negligible power (2 %) and hardware overhead (< 1 %). The chip is fabricated in 40 nm CMOS, resulting in 0.9 pJ/cycle energy efficiency while achieving 8 ppm/ºC from -40ºC to 80ºC.

Proof of concept: real-time viability and metabolic profiling of probiotics with isothermal microcalorimetry.

Isothermal microcalorimetry (IMC) is a potent analytical method for the real-time assessment of microbial metabolic activity, which serves as an indicator of microbial viability. This approach is highly relevant to the fields of probiotics and Live Biotherapeutic Products (LBPs), offering insights into microbial viability and growth kinetics. One important characteristic of IMC is its ability to measure microbial metabolic activity separately from cellular enumeration. This is particularly useful in situations where continuous tracking of bacterial activity is challenging. The focus on metabolic activity significantly benefits both probiotic research and industrial microbiology applications. IMC's versatility in handling different media matrices allows for the implementation of viability assessments under conditions that mirror those found in various industrial environments or biological models. In our study, we provide a proof of concept for the application of IMC in determining viability and growth dynamics and their correlation with bacterial count in probiotic organisms. Our findings reinforce the potential of IMC as a key method for process enhancement and accurate strain characterization within the probiotic sector. This supports the broader objective of refining the systematic approach and methods used during the development process, thereby providing detailed insights into probiotics and LBPs.

Microplastics in granular sequencing batch reactors: Effects on pollutant removal dynamics and the microbial community.

This study investigated the relationship between microplastic (MP) presence and pollutant removal in granular sludge sequencing batch reactors (GSBRs). Two types of MPs, polyethylene (PE) and polyethylene terephthalate (PET), were introduced in varying concentrations to assess their effects on microbial community dynamics and rates of nitrogen, phosphorus, and organic compound removal. The study revealed type-dependent variations in the deposition of MPs within the biomass, with PET-MPs exhibiting a stronger affinity for accumulation in biomass. A 50 mg/L dose of PET-MP decreased COD removal efficiency by approximately 4 % while increasing P-PO4 removal efficiency by around 7 % compared to the control reactor. The rate of nitrogen compounds removal decreased with higher PET-MP dosages but increased with higher PE-MP dosages. An analysis of microbial activity and gene abundance highlighted the influence of MPs on the expression of the nosZ and ppk1 genes, which code enzymes responsible for nitrogen and phosphorus transformations. The study also explored shifts in microbial community structure, revealing alterations with changes in MP dose and type. This research contributes valuable insights into the complex interactions between MP, microbial communities, and pollutant removal processes in GSBR systems, with implications for the sustainable management of wastewater treatment in the presence of MP.

The Utility of Real-time PCR, Metagenomic Next-generation Sequencing, and Culture in Bronchoalveolar Lavage Fluid for Diagnosis of Pulmonary Aspergillosis.

Timely detection of Aspergillus infection is crucial given the high mortality rate of pulmonary aspergillosis (PA). Here, the diagnostic performances for PA of mycological culture, Aspergillus real-time Polymerase Chain Reaction (RT-PCR), and metagenomic next-generation sequencing (mNGS) assay from bronchoalveolar lavage fluid (BALF), were evaluated. Totally 139 patients with suspected fungal pneumonia were enrolled between December 2021 and July 2023, collecting 139 BALF samples for RT-PCR and culture, with 87 undergoing mNGS assay. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC) with 95% confidence intervals of these assays for PA were as follows: 35.3% (14.2-61.7%), 100.0% (94.0-100.0%), 100.0% (54.1-100.0%), 84.5% (79.3-88.6%), and 0.676 (0.560-0.779) for culture; 82.4% (56.6-96.2%), 98.3% (91.1-100.0%), 93.3% (66.4-99.0%), 95.2% (87.6-98.2%) and 0.903 (0.815-0.959) for same diagnostic performance of RT-PCR and mNGS; and 94.1% (71.3-99.9%), 96.7% (88.5-99.6%), 88.9% (67.1-96.9%), 98.3% (89.6-99.7%), 0.954 (0.880-0.989) for RT-PCR combining mNGS; RT-PCR, mNGS, and their combination significantly improved in AUC values over culture (p <0.001), but RT-PCR testing and mNGS had no significant difference with each other and their combination. Overall, the performance of culture was limited by low sensitivity, both RT-PCR and mNGS assays as single diagnostic tests are promising compared to culture and combined tests.

Targeting the superior temporal gyrus with real-time fMRI neurofeedback: A pilot study of the indirect effects on self-referential processes in schizophrenia.

BACKGROUND: Individuals with schizophrenia (SZ) and auditory hallucinations (AHs) display a distorted sense of self and self-other boundaries. Alterations of activity in midline cortical structures such as the prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) during self-reference as well as in the superior temporal gyrus (STG) have been proposed as neuromarkers of SZ and AHs. METHODS: In this randomized, participant-blinded, sham-controlled trial, 22 adults (18 males) with SZ spectrum disorders (SZ or schizoaffective disorder) and frequent medication-resistant AHs received one session of real-time fMRI neurofeedback (NFB) either from the STG (n = 11; experimental group) or motor cortex (n = 11; control group). During NFB, participants were instructed to upregulate their STG activity by attending to pre-recorded sentences spoken in their own voice and downregulate it by ignoring unfamiliar voices. Before and after NFB, participants completed a self-reference task where they evaluated if trait adjectives referred to themselves (self condition), Abraham Lincoln (other condition), or whether adjectives had a positive valence (semantic condition). FMRI activation analyses of self-reference task data tested between-group changes after NFB (self>semantic, post>pre-NFB, experimental>control). Analyses were pre-masked within a self-reference network. RESULTS: Activation analyses revealed significantly (p < 0.001) greater activation increase in the experimental, compared to the control group, after NFB within anterior regions of the self-reference network (mPFC, ACC, superior frontal cortex). CONCLUSIONS: STG-NFB was associated with activity increase in the mPFC, ACC, and superior frontal cortex during self-reference. Modulating the STG is associated with activation changes in other, not-directly targeted, regions subserving higher-level cognitive processes associated with self-referential processes and AHs psychopathology in SZ. CLINICALTRIALS: GOV: Rt-fMRI Neurofeedback and AH in Schizophrenia; https://clinicaltrials.gov/study/NCT03504579.

Implementing multiblock techniques in a full-scale plant scenario: On-line prediction of quality parameters in a continuous process for different acrylonitrile butadiene styrene (ABS) products.

BACKGROUND: The study explores the challenges of handling multiblock data of different natures (process and NIR sensors) for on-line quality prediction in a full-scale plant scenario, namely a plant operating in continuous on an industrial scale and producing different grade Acrylonitrile Butadiene Styrene (ABS) products. This environment is an ideal scenario to evaluate the use of multiblock data analysis methods, which can enhance data interpretation, visualization, and predictive performances. In particular, a novel multiblock extension of Locally Weighted PLS has been proposed by the authors, namely Locally Weighted Multiblock Partial Least Squares (LW-MB-PLS). Response-Oriented Sequential Alternation (ROSA) has also been employed to evaluate the diverse block relevance for the prediction of two quality parameters associated with the polymer. Data are split in blocks both according to sensor type and different plant sections, and different models have been built by incremental addition of data blocks to evaluate if early estimation of product quality is feasible. RESULTS: ROSA method showed promising predictive performance for both quality parameters, highlighting the most influential plant sections through the selection of data blocks. The results suggested that both early and late-stage sensors play crucial roles in predicting product quality. A reasonable estimation of quality parameters before production completion has been achieved. On the other hand, the proposed LW-MB-PLS, while comparable in predictive performances, allowed reducing systematic prediction errors for specific products. SIGNIFICANCE: This study contributes valuable insights for continuous production processes, aiding plant operators and paving the way for advancements in online quality prediction and control. Furthermore, it is implemented as a locally weighted extension of MB-PLS.

Microneedle electrochemical sensor based on disposable stainless-steel wire for real-time analysis of indole-3-acetic acid and salicylic acid in tomato leaves infected by Pst DC3000 in situ.

BACKGROUND: Indole-3-acetic acid (IAA) and salicylic acid (SA), pivotal regulators in plant growth, are integral to a variety of plant physiological activities. The ongoing and simultaneous monitoring of these hormones in vivo enhances our comprehension of their interactive and regulatory roles. Traditional detection methods, such as liquid chromatography-mass spectrometry, cannot obtain precise and immediate information on IAA and SA due to the complexity of sample processing. In contrast, the electrochemical detection method offers high sensitivity, rapid response times, and compactness, making it well-suited for in vivo or real-time detection applications. RESULTS: A microneedle electrochemical sensor system crafted from disposable stainless steel (SS) wire was specifically designed for the real-time assessment of IAA and SA in plant in situ. This sensor system included a SS wire (100 µm diameter) coated with carbon cement and multi-walled carbon nanotubes, a plain platinum wire (100 µm diameter), and an Ag/AgCl wire (100 µm diameter). Differential pulse voltammetry and amperometry were adopted for detecting SA and IAA within the range of 0.1-20 µM, respectively. This sensor was applied to track IAA and SA fluctuations in tomato leaves during PstDC3000 infection, offering continuous data. Observations indicated an uptick in SA levels following infection, while IAA production was suppressed. The newly developed disposable SS wire-based microneedle electrochemical sensor system is economical, suitable for mass production, and inflicts minimal damage during the monitoring of SA and IAA in plant tissues. SIGNIFICANCE: This disposable microneedle electrochemical sensor facilitates in vivo detection of IAA and SA in smaller plant tissues and allows for long-time monitoring of their concentrations, which not only propels research into the regulatory and interaction mechanisms of IAA and SA but also furnishes essential tools for advancing precision agriculture.

An improved Trizol method for extracting total RNA from Eleutherococcus senticosus (Rupr. & Maxim.) Maxim leaves.

INTRODUCTION: High-quality nucleic acids are the basis for molecular biology experiments. Traditional RNA extraction methods are not suitable for Eleutherococcus senticosus Maxim. OBJECTIVE: To find a suitable method to improve the quality of RNA extracted, we modified the RNA extraction methods of Trizol. METHODOLOGY: Based on the conventional Trizol method, the modified Trizol method 1 and modified Trizol method 2 were used as the control for extraction of RNA from E. senticosus Maxim leaves. The modified Trizol method 1 added ß-mercaptoethanol on the conventional Trizol method. After RNA was dissolved, a mixed solution of phenol, chloroform, and isoamyl alcohol was added to denature protein and inhibit the degradation of RNA. The modified Trizol method 2 adds PVPP to grind on the basis of modified Trizol method 1, so as to better remove phenols from leaves, and eliminates the step of incubation at -20°C to reduce extraction time and RNA degradation. Chloroform, CTAB, and CH3COONa were used instead of a phenol, chloroform, and isoamyl alcohol mixed solution to ensure complete separation of nucleic acid from plant tissues and to obtain high-purity RNA. RESULTS: The research results showed that the quality of RNA extracted by conventional Trizol method, modified Trizol method 1, was incomplete, accompanied with different degrees of contamination of polysaccharides, polyphenols, and DNA. The modified Trizol method 2 could better extract RNA from E. senticosus Maxim leaves. The ratio of A260/A280 was in the range of 1.8-2.0, and the yield of RNA was the highest, which was 1.68 and 1.15 times compared with that by conventional Trizol method and modified Trizol method 1 extraction, respectively. The reverse transcription cDNA was further tested through PCR with the specific primers. The amplified fragments are displayed in clear and bright bands in accordance with the expected size. CONCLUSION: The modified Trizol method 2 could better extract RNA from E. senticosus Maxim leaves. High-quality RNA has more advantages in molecular biology study of E. senticosus Maxim.

Real-time imaging of intracellular deformation dynamics in vibrated adherent cell cultures.

Mechanical vibration has been shown to regulate cell proliferation and differentiation in vitro and in vivo. However, the mechanism of its cellular mechanotransduction remains unclear. Although the measurement of intracellular deformation dynamics under mechanical vibration could reveal more detailed mechanisms, corroborating experimental evidence is lacking due to technical difficulties. In this study, we aimed to propose a real-time imaging method of intracellular structure deformation dynamics in vibrated adherent cell cultures and investigate whether organelles such as actin filaments connected to a nucleus and the nucleus itself show deformation under horizontal mechanical vibration. The proposed real-time imaging was achieved by conducting vibration isolation and making design improvements to the experimental setup; using a high-speed and high-sensitivity camera with a global shutter; and reducing image blur using a stroboscope technique. Using our system, we successfully produced the first experimental report on the existence of the deformation of organelles connected to a nucleus and the nucleus itself under horizontal mechanical vibration. Furthermore, the intracellular deformation difference between HeLa and MC3T3-E1 cells measured under horizontal mechanical vibration agrees with the prediction of their intracellular structure based on the mechanical vibration theory. These results provide new findings about the cellular mechanotransduction mechanism under mechanical vibration.

Advancing COVID-19 Diagnosis: Enhancement in SERS-PCR with 30-nm Au Nanoparticle-Internalized Nanodimpled Substrates.

Real-time polymerase chain reaction (RT-PCR) with fluorescence detection is the gold standard for diagnosing coronavirus disease 2019 (COVID-19) However, the fluorescence detection in RT-PCR requires multiple amplification steps when the initial deoxyribonucleic acid (DNA) concentration is low. Therefore, this study has developed a highly sensitive surface-enhanced Raman scattering-based PCR (SERS-PCR) assay platform using the gold nanoparticle (AuNP)-internalized gold nanodimpled substrate (AuNDS) plasmonic platform. By comparing different sizes of AuNPs, it is observed that using 30 nm AuNPs improves the detection limit by approximately ten times compared to 70 nm AuNPs. Finite-difference time-domain (FDTD) simulations show that multiple hotspots are formed between AuNPs and the cavity surface and between AuNPs when 30 nm AuNPs are internalized in the cavity, generating a strong electric field. With this 30 nm AuNPs-AuNDS SERS platform, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ribonucleic acid (RNA)-dependent RNA polymerase (RdRp) can be detected in only six amplification cycles, significantly improving over the 25 cycles required for RT-PCR. These findings pave the way for an amplification-free molecular diagnostic system based on SERS.

Innovative use of Australian cancer registry data for early detection of the effects of epidemics and other mass disruptions on cancer incidence.

BACKGROUND: Predictive modelling using pre-epidemic data have long been used to guide public health responses to communicable disease outbreaks and other health disruptions. In this study, cancer registry and related health data available 2-3 months from diagnosis were used to predict changes in cancer detection that otherwise would not have been identified until full registry processing was completed about 18-24 months later. A key question was whether these earlier data could be used to predict cancer incidence ahead of full processing by the cancer registry as a guide to more timely health responses. The setting was the Australian State of New South Wales, covering 31 % of the Australian population. The study year was 2020, the year of emergence of the COVID-19 pandemic. METHODS: Cancer detection in 2020 was modelled using data available 2-3 months after diagnosis. This was compared with data from full registry processing available from 2022. Data from pre-pandemic 2018 were used for exploratory model building. Models were tested using pre-pandemic 2019 data. Candidate predictor variables included pathology, surgery and radiation therapy reports, numbers of breast screens, colonoscopies, PSA tests, and melanoma excisions recorded by the universal Medical Benefits Schedule (MBS). Data were analysed for all cancers collectively and 5 leading types. RESULTS: Compared with full registry processing, modelled data for 2020 had a >95 % accuracy overall, indicating key points of inflexion of cancer detection over the COVID-disrupted 2020 period. These findings highlight the potential of predictive modelling of cancer-related data soon after diagnosis to reveal changes in cancer detection during epidemics and other health disruptions. CONCLUSIONS: Data available 2-3 months from diagnosis in the pandemic year indicated changes in cancer detection that were ultimately confirmed by fully-processed cancer registry data about 24 months later. This indicates the potential utility of using these early data in an early-warning system.

Continuous oxygen monitoring to enhance ex-vivo organ machine perfusion and reconstructive surgery.

Continuous oxygenation monitoring of machine-perfused organs or transposed autologous tissue is not currently implemented in clinical practice. Oxygenation is a critical parameter that could be used to verify tissue viability and guide corrective interventions, such as perfusion machine parameters or surgical revision. This work presents an innovative technology based on oxygen-sensitive, phosphorescent metalloporphyrin allowing continuous and non-invasive oxygen monitoring of ex-vivo perfused vascularized fasciocutaneous flaps. The method comprises a small, low-energy optical transcutaneous oxygen sensor applied on the flap's skin paddle as well as oxygen sensing devices placed into the tubing. An intermittent perfusion setting was designed to study the response time and accuracy of this technology over a total of 54 perfusion cycles. We further evaluated correlation between the continuous oxygen measurements and gold-standard perfusion viability metrics such as vascular resistance, with good agreement suggesting potential to monitor graft viability at high frequency, opening the possibility to employ feedback control algorithms in the future. This proof-of-concept study opens a range of research and clinical applications in reconstructive surgery and transplantation at a time when perfusion machines undergo rapid clinical adoption with potential to improve outcomes across a variety of surgical procedures and dramatically increase access to transplant medicine.

Metabolic profiling of single cells by exploiting NADH and FAD fluorescence via flow cytometry.

The metabolism of different cells within the same microenvironment can differ and dictate physiological or pathological adaptions. Current single-cell analysis methods of metabolism are not label-free. The study introduces a label-free, live-cell analysis method assessing endogenous fluorescence of NAD(P)H and FAD in surface-stained cells by flow cytometry. OxPhos inhibition, mitochondrial uncoupling, glucose exposure, genetic inactivation of glucose uptake and mitochondrial respiration alter the optical redox ratios of FAD and NAD(P)H as measured by flow cytometry. Those alterations correlate strongly with measurements obtained by extracellular flux analysis. Consequently, metabolically distinct live B-cell populations can be resolved, showing that human memory B-cells from peripheral blood exhibit a higher glycolytic flexibility than naïve B cells. Moreover, the comparison of blood-derived B- and T-lymphocytes from healthy donors and rheumatoid arthritis patients unleashes rheumatoid arthritis-associated metabolic traits in human naïve and memory B-lymphocytes. Taken together, these data show that the optical redox ratio can depict metabolic differences in distinct cell populations by flow cytometry.

Molecular and serological prevalence of Leptospira spp. among slaughtered cattle and associated risk factors in the Bahr El Ghazal region of South Sudan.

INTRODUCTION: Leptospirosis is a neglected emerging and zoonotic disease reported worldwide. This study sought to determine the molecular and serological prevalence of Leptospira spp. and the associated risk factors in slaughtered cattle from the Bahr El Ghazal region of South Sudan. MATERIALS AND METHODS: Between January 16th and February 25th, 2023, blood and urine samples were collected from 402 cattle at the Lokoloko Municipal Slaughterhouse in Western Bahr El-Ghazal State. Serum samples were tested using the microscopic agglutination test (MAT), with a panel of 12 serovars (sv) from 12 serogroups (sg) and 4 species (spp) of Leptospira spp. These serovars had been previously identified in Sudan and the East African region. Simultaneously, 400 corresponding urine samples were screened using qualitative real-time polymerase chain reaction (PCR) to detect the shedding of Leptospira spp. in urine. To identify the associated risk factors, the age, sex, breed and body condition score of each sampled cattle was noted at the time of sampling and subsequently analysed using logistic regression models. RESULTS: Among the 402 serum samples screened, a substantial 81.8% (329/402, 95% CI 77.9-85.3) displayed seropositivity for Leptospira spp. with a MAT titre ≥ 100. The prevalence of urine shedding determined by PCR was 6% (23/400, 95% CI 3.8-8.4), while probable recent leptospirosis with a MAT ≥ 1:800 was observed in 33.1% (133/402, 95% CI 28.6-37.8) of the cattle. Multiple reactions were detected in 34.8% (140/402, 95% CI 30.6-39.5) serum samples. The seropositivity was against L. borgpetersenii sg. Tarassovi (78.6%; 316/402, 95% CI 74.4-82.3), followed by L. borgpetersenii sg. Ballum at 20.4% (82/402, 95% CI, 16.7-24.4%), L. kirschneri sg. Autumnalis At 8.7% (35/402, 95% CI 5.7-11.7), L. interrogans sg. of Pomona at 7.0% (28/402, 95% CI 4.5-9.5), and L. interrogans sg. Hebdomadis was 5.0% (20/402, 95% CI 2.8-7.2). Several risk factors are associated with seropositivity. Older animals (≥ 2 years) had 2.0 times greater odds (95% CI 1.14-3.5) of being seropositive than younger animals (< 2 years), P-value = 0.016. Female animals demonstrated 2.1 times greater odds (95% CI 1.2-3.6) of seropositivity than males did (P-value = 0.008). Additionally, Felata/Mbororo cattle exhibited 2.4 times greater odds (95% CI 1.3-4.5) of being seropositive than did local Nilotic cattle (P-value = 0.005). The agreement between the MAT and PCR results was poor, as indicated by a kappa statistic value of 0.001 and a P-value of 0.913. But there was a moderate agreement between MAT high titres ≥ 800 and PCR positivity with a kappa statistic value = 0.501 and a P-value < 0.001. CONCLUSION: In addition to the high seroprevalence, Leptospira spp. were found in the urine of slaughtered cattle, suggesting that leptospirosis is endemic to the study area. This finding underscores the significance of cattle as potential sources of infection for slaughterhouse workers, the general public, and other animal species. To address this issue effectively in the Bahr El Ghazal Region and South Sudan, a comprehensive strategy involving a multidisciplinary approach is essential to minimize disease among animals, hence reducing potential zoonotic risks to humans.

Smartphone image dataset to distinguish healthy and unhealthy leaves in papaya orchards in Bangladesh.

Papaya, renowned for its nutritional benefits, represents a highly profitable crop. However, it is susceptible to various diseases that can significantly impede fruit productivity and quality. Among these, leaf diseases pose a substantial threat, severely impacting the growth of papaya plants. Consequently, papaya farmers frequently encounter numerous challenges and financial setbacks. To facilitate the easy and efficient identification of papaya leaf diseases, a comprehensive dataset has been assembled. This dataset, comprising approximately 1400 images of diseased, infected, and healthy leaves, aims to enhance the understanding of how these ailments affect papaya plants. The images, meticulously collected from diverse regions and under varying weather conditions, offer detailed insights into the disease patterns specific to papaya leaves. Stringent measures have been taken to ensure the dataset's quality and enhance its utility. The images, captured from multiple angles and boasting high resolution are designed to aid in the development of a highly accurate model. Additionally, RGB mode has been employed to meticulously capture each detail, ensuring a flawless representation of the leaves. The dataset meticulously identifies and categorizes five primary types of leaf diseases: Leaf Curl (inclusive of its initial stage), Papaya Mosaic, Ring Spot, Mites (specifically, those affected by Red Spider Mites), and Mealybug. These diseases are recognized for their detrimental effects on both the leaves and the overall fruit production of the papaya plant. By leveraging this curated dataset, it is possible to train a model for the real-time detection of leaf diseases, significantly aiding in the timely identification of such conditions.

Assessment of the utilization of real-time prescription benefits for patient cost savings within an outpatient setting.

Background: This study evaluates the impact of Real-Time Prescription Benefits (RTPB), a tool integrated into electronic health records (EHRs), on patient out-of-pocket costs in an academic institution. RTPB provides prescribers with alternative, less expensive medications based on insurance plans. The primary measure was cost-savings, defined as the difference between the out-of-pocket cost of the prescribed medication and its alternative. Methods: A retrospective analysis of prescriptions from outpatient clinics in a university-based health system was conducted between May 2020 and July 2021. Prescriptions were analyzed at the 2nd level of the Anatomical Therapeutic Chemical (ATC) classification system. Costs were standardized to a 30-day supply. Standardized cost and total cost per prescription, and overall savings for the top 20 medication classes at the 2nd ATC level were calculated. The overall impact of RTPB was estimated based on selecting the least expensive alternative suggested by RTPB. Results: The study found that RTPB information was provided for 22% of prescriptions, with suggested alternatives for 1.26%. Among prescriptions with an alternative selected, the standardized average cost saving was $38.83. The study realized $15,416 in patient total cost savings. If the least expensive RTPB-suggested alternative were chosen for all prescriptions, an estimated $276,386 could have been saved. Psychoanaleptic and psycholeptic medications were the most prescribed with an alternative, with most savings in specialty drugs like anthelmintic and immunostimulant medications. Conclusion: The study highlights the importance of RTPB in reducing patient costs. It reports patient cost-savings with RTPB in prescribing decisions. Future research could explore the impact of RTPB on medication adherence using pharmacy claims data.

Unveiling genomic features linked to traits of plant-growth-promoting bacterial communities from sugarcane.

Microorganisms are ubiquitous, and those inhabiting plants have been the subject of several studies. Plant-associated bacteria exhibit various biological mechanisms that enable them to colonize host plants and, in some cases, enhance their fitness. In this study, we describe the genomic features predicted to be associated with plant growth-promoting traits in six bacterial communities isolated from sugarcane. The use of highly accurate single-molecule real-time sequencing technology for metagenomic samples from these bacterial communities allowed us to recover 17 genomes. The taxonomic assignments for the binned genomes were performed, revealing taxa distributed across three main phyla: Bacillota, Bacteroidota, and Pseudomonadota, with the latter being the most representative. Subsequently, we functionally annotated the metagenome-assembled genomes (MAGs) to characterize their metabolic pathways related to plant growth-promoting traits. Our study successfully identified the enrichment of important functions related to phosphate and potassium acquisition, modulation of phytohormones, and mechanisms for coping with abiotic stress. These findings could be linked to the robust colonization of these sugarcane endophytes.