Impact of microbial-based biopreparations on soil quality, plant health, and fruit chemistry in raspberry cultivation.

Application of microbial-based biopreparations as a pre-harvest strategy offers a method to obtain sustainable agricultural practices and could be an important approach for advancing food science, promoting sustainability, and meeting global food market demands. The impact of a bacterial-fungal biopreparation mixture on soil-plant-microbe interactions, fruit chemical composition and yield of 7 raspberry clones was investigated by examining the structural and functional profiles of microbial communities within leaves, fruits, and soil. Biopreparation addition caused the enhancement of the microbiological utilization of specific compounds, such as d-mannitol, relevant in plant-pathogen interactions and overall plant health. The biopreparation treatment positively affected the nitrogen availability in soil (9-160%). The analysis of plant stress marker enzymes combined with the evaluation of fruit quality and chemical properties highlight changes inducted by the pre-harvest biopreparation application. Chemical analyses highlight biopreparations' role in soil and fruit quality improvement, promoting sustainable agriculture. This effect was dependent on tested clones, showing increase of soluble solid content in fruits, concentration of polyphenols or the sensory quality of the fruits. The results of the next-generation sequencing indicated increase in the effective number of bacterial species after biopreparation treatment. The network analysis showed stimulating effect of biopreparation on microbial communities by enhancing microbial interactions (increasing the number of network edges up to 260%) of and affecting the proportions of mutual relationships between both bacteria and fungi. These findings show the potential of microbial-based biopreparation in enhancing raspberry production whilst promoting sustainable practices and maintaining environmental homeostasis and giving inshght in holistic understanding of microbial-based approaches for advancing food science monitoring.

Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.

One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bacterial genomes contain signatures of natural evolution and adaptive markers that can be exploited to better understand the behavior of pathogen in the food industry. The monitoring of foodborne strains can therefore be facilitated by the use of these genomic markers capable of rapidly providing essential information on isolated strains, such as the source of contamination, risk of illness, potential for biofilm formation, and tolerance or resistance to biocides. The increasing availability of large genome datasets is enhancing the understanding of the genetic basis of complex traits such as host adaptation, virulence, and persistence. Genome-wide association studies have shown very promising results in the discovery of genomic markers that can be integrated into rapid detection tools. In addition, machine learning has successfully predicted phenotypes and classified important traits. Genome-wide association and machine learning tools have therefore the potential to support decision-making circuits intending at reducing the burden of foodborne diseases. The aim of this chapter review is to provide knowledge on the use of these two methods in food microbiology and to recommend their use in the field.

The expression of YAP1 and other transcription factors contributes to lineage plasticity in combined small cell lung carcinoma.

Lineage plasticity in small cell lung carcinoma (SCLC) causes therapeutic difficulties. This study aimed to investigate the pathological findings of plasticity in SCLC, focusing on combined SCLC, and elucidate the involvement of YAP1 and other transcription factors. We analysed 100 surgically resected SCLCs through detailed morphological observations and immunohistochemistry for YAP1 and other transcription factors. Component-by-component next-generation sequencing (n = 15 pairs) and immunohistochemistry (n = 35 pairs) were performed on the combined SCLCs. Compared with pure SCLCs (n = 65), combined SCLCs (n = 35) showed a significantly larger size, higher expression of NEUROD1, and higher frequency of double-positive transcription factors (p = 0.0009, 0.04, and 0.019, respectively). Notably, 34% of the combined SCLCs showed morphological mosaic patterns with unclear boundaries between the SCLC and its partner. Combined SCLCs not only had unique histotypes as partners but also represented different lineage plasticity within the partner. NEUROD1-dominant combined SCLCs had a significantly higher proportion of adenocarcinomas as partners, whereas POU2F3-dominant combined SCLCs had a significantly higher proportion of squamous cell carcinomas as partners (p = 0.006 and p = 0.0006, respectively). YAP1 expression in SCLC components was found in 80% of combined SCLCs and 62% of pure SCLCs, often showing mosaic-like expression. Among the combined SCLCs with component-specific analysis, the identical TP53 mutation was found in 10 pairs, and the identical Rb1 abnormality was found in 2 pairs. On immunohistochemistry, the same abnormal p53 pattern was found in 34 pairs, and Rb1 loss was found in 24 pairs. In conclusion, combined SCLC shows a variety of pathological plasticity. Although combined SCLC is more plastic than pure SCLC, pure SCLC is also a phenotypically plastic tumour. The morphological mosaic pattern and YAP1 mosaic-like expression may represent ongoing lineage plasticity. This study also identified the relationship between transcription factors and partners in combined SCLC. Transcription factors may be involved in differentiating specific cell lineages beyond just 'neuroendocrine'.

A comparative analysis of eDNA metabarcoding and field surveys: Exploring freshwater plant communities in rivers.

While environmental DNA (eDNA) metabarcoding holds promise as a holistic approach to assess vegetation changes and community composition across diverse spatial and temporal scales, systematic investigations of its efficacy compared to conventional field surveys remain scarce in the literature. The present study explores the differences in plant diversity recovered from field surveys and captured with a multi-marker eDNA metabarcoding approach (two nrDNA ITS1 and ITS2, and two cpDNA rbcL and trnL) from river water samples. The eDNA metabarcoding approach retrieved 46 aquatic plants (hydrophytes and helophytes) and 245 terrestrial plants, compared to 24 and 127 species identified from field surveys. On average, eDNA samples collected immediately downstream of the survey sites recovered 43 % and 39 % of the aquatic and terrestrial species observed, respectively. Discrepancies were explained by differences in taxonomic resolution, the stochasticity of the retrieval of rare and elusive species, and the presence of reference sequences. We found a significant positive correlation between spatial and community distances at scales ranging from 2 to 9 km and identified turnover as the driving force of these differences. Metabarcoding demonstrated sensitivity to community changes and both approaches converge on a similar community structure. Interestingly, eDNA samples collected immediately upstream of the survey sites exhibited significant species overlap with the downstream samples (c. 100 m apart). Overall, our results demonstrate that within-site species mismatches between the methods are nonnegligible, and they question the use of eDNA for generating complete species lists at scales comparable to our field surveys (< 100-m transects). However, with adequate sampling and a multi-marker metabarcoding approach, eDNA has the potential to approximate catchment gamma diversity with less sampling effort than conventional surveys.

AtML: An Arabidopsis thaliana root cell identity recognition tool for medicinal ingredient accumulation.

Arabidopsis thaliana synthesizes various medicinal compounds, and serves as a model plant for medicinal plant research. Single-cell transcriptomics technologies are essential for understanding the developmental trajectory of plant roots, facilitating the analysis of synthesis and accumulation patterns of medicinal compounds in different cell subpopulations. Although methods for interpreting single-cell transcriptomics data are rapidly advancing in Arabidopsis, challenges remain in precisely annotating cell identity due to the lack of marker genes for certain cell types. In this work, we trained a machine learning system, AtML, using sequencing datasets from six cell subpopulations, comprising a total of 6000 cells, to predict Arabidopsis root cell stages and identify biomarkers through complete model interpretability. Performance testing using an external dataset revealed that AtML achieved 96.50% accuracy and 96.51% recall. Through the interpretability provided by AtML, our model identified 160 important marker genes, contributing to the understanding of cell type annotations. In conclusion, we trained AtML to efficiently identify Arabidopsis root cell stages, providing a new tool for elucidating the mechanisms of medicinal compound accumulation in Arabidopsis roots.

Genome-wide assessment of population structure and association mapping for agronomic and grain nutritional traits in proso millet (Panicum miliaceum L.).

Proso millet is an important but under-researched and underutilized crop with the potential to become a future smart crop because of its climate-resilient features and high nutrient content. Assessing diversity and marker-trait associations are essential to support the genomics-assisted improvement of proso millet. This study aimed to assess the population structure and diversity of a proso millet diversity panel and identify marker-trait associations for agronomic and grain nutrient traits. In this study, genome-wide single nucleotide polymorphisms (SNPs) were identified by mapping raw genotyping-by-sequencing (GBS) data onto the proso millet genome, resulting in 5621 quality-filtered SNPs in 160 diverse accessions. The modified Roger's Distance assessment indicated an average distance of 0.268 among accessions, with the race miliaceum exhibiting the highest diversity and ovatum the lowest. Proso millet germplasm diversity was structured according to geographic centers of origin and domestication. Genome-wide association mapping identified 40 marker-trait associations (MTAs), including 34 MTAs for agronomic traits and 6 for grain nutrients; 20 of these MTAs were located within genes. Favourable alleles and phenotypic values were estimated for all MTAs. This study provides valuable insights into the population structure and diversity of proso millet, identified marker-trait associations, and reported favourable alleles and their phenotypic values for supporting genomics-assisted improvement efforts in proso millet.

Production of genetically stable and Odontoglossum ringspot virus-free Cymbidium orchid 'New True' plants via meristem-derived protocorm-like body (PLB) subcultures.

BACKGROUND: This study aimed to produce Odontoglossum ringspot virus (ORSV)-free Cymbidium orchid 'New True' plants from ORSV-infected mother plants by culturing their meristems and successively repeating subcultures of protocorm-like bodies (PLBs) derived from the meristems. RESULTS: Initially, ORSV was confirmed as the causative agent of viral symptoms in orchid leaves via reverse transcription-polymerase chain reaction (RT-PCR) analysis. Meristems from infected plants were cultured to generate PLBs, which in sequence were repeatedly subcultured up to four times. RT-PCR and quantitative RT-PCR analyses revealed that while ORSV was undetectable in shoots derived from the first subculture, complete elimination of the virus required at least a second subculture. Genetic analysis using inter-simple sequence repeat markers indicated no somaclonal variation between regenerated plants and the mother plant, suggesting that genetic consistency was maintained. CONCLUSION: Overall, our findings demonstrate that subculturing PLBs for a second time is ideal for producing genetically stable, ORSV-free Cymbidium orchids, thus offering a practical means of generating genetically stable, virus-free plants and enhancing plant health and quality in the orchid industry.

Application of motion prediction based on a long short-term memory network for imaging dose reduction in real-time tumor-tracking radiation therapy.

PURPOSE: To demonstrate the possibility of using a lower imaging rate while maintaining acceptable accuracy by applying motion prediction to minimize the imaging dose in real-time image-guided radiation therapy. METHODS: Time-series of three-dimensional internal marker positions obtained from 98 patients in liver stereotactic body radiation therapy were used to train and test the long-short-term memory (LSTM) network. For real-time imaging, the root mean squared error (RMSE) of the prediction on three-dimensional marker position made by LSTM, the residual motion of the target under respiratory-gated irradiation, and irradiation efficiency were evaluated. In the evaluation of the residual motion, the system-specific latency was assumed to be 100 ms. RESULTS: Except for outliers in the superior-inferior (SI) direction, the median/maximum values of the RMSE for imaging rates of 7.5, 5.0, and 2.5 frames per second (fps) were 0.8/1.3, 0.9/1.6, and 1.2/2.4 mm, respectively. The median/maximum residual motion in the SI direction at an imaging rate of 15.0 fps without prediction of the marker position, which is a typical clinical setting, was 2.3/3.6 mm. For rates of 7.5, 5.0, and 2.5 fps with prediction, the corresponding values were 2.0/2.6, 2.2/3.3, and 2.4/3.9 mm, respectively. There was no significant difference between the irradiation efficiency with and that without prediction of the marker position. The geometrical accuracy at lower frame rates with prediction applied was superior or comparable to that at 15 fps without prediction. In comparison with the current clinical setting for real-time image-guided radiation therapy, which uses an imaging rate of 15.0 fps without prediction, it may be possible to reduce the imaging dose by half or more. CONCLUSIONS: Motion prediction can effectively lower the frame rate and minimize the imaging dose in real-time image-guided radiation therapy.

The inflammatory markers and locoregional pathological results both have an impact on the prognosis of oral squamous cell carcinoma in patients who have undergone neck dissection.

BACKGROUND: Locoregional surgical pathology, with surgical margins at the primary site and lymph node (LN) metastasis, particularly extranodal extension (ENE), plays an important role in the prognosis of oral squamous cell carcinoma (OSCC). In addition, systemic inflammatory response and nutritional status are associated with poor prognosis. PURPOSE: This study aimed to comprehensively assess the effect of inflammatory markers and locoregional factors on the prognosis of patients with OSCC who underwent neck dissection (ND). METHODS: This retrospective cohort study included patients who had undergone ND for OSCC between 2013 and 2021. The primary predictive variables were the weighted lymph node ratio (WLNR) and inflammatory markers. Primary outcome variables were overall survival (OS) and disease-free survival (DFS). RESULTS: Among 153 patients (99 males, 54 females), 55 (35.9 %) had LN metastasis and 11 (7.2 %) exhibited ENE. The inflammatory markers lymphocyte/monocyte ratio (LMR), monocyte/albumin ratio (MAR), C-reactive protein/albumin ratio (CAR), and WLNR demonstrated significant cut-off values for survival, with values of 4.805, 104.72, 0.041, and 0.0235, respectively. The Cox proportional hazards model revealed significant differences in age, WLNR, LMR, MAR, CAR, and vascular, lymphatic, and perineural invasion (Pn). Multivariate analysis indicated that the hazard ratios (95 % confidence intervals) for WLNR (3.416; 1.542-7.566), MAR (2.404; 1.254-4.607), and Pn (2.516; 1.291-4.905) were independent variables for OS. CONCLUSIONS: In patients with OSCC who underwent ND, the inflammatory marker MAR and locoregional factors WLNR and Pn were simultaneously identified as prognostic factors.

Discovery of a major QTL for resistance to the guava root-knot nematode (Meloidogyne enterolobii) in 'Tanzania', an African landrace sweetpotato (Ipomoea batatas).

Sweetpotato, Ipomoea batatas (L.) Lam. (2n = 6x = 90), is among the world's most important food crops and is North Carolina's most important vegetable crop. The recent introduction of Meloidogyne enterolobii poses a significant economic threat to North Carolina's sweetpotato industry and breeding resistance into new varieties has become a high priority for the US sweetpotato industry. Previous studies have shown that 'Tanzania', a released African landrace, is resistant to M. enterolobii. We screened the biparental sweetpotato mapping population, 'Tanzania' x 'Beauregard', for resistance to M. enterolobii by inoculating 246 full-sibs with 10,000 eggs each under greenhouse conditions. 'Tanzania', the female parent, was highly resistant, while 'Beauregard' was highly susceptible. Our bioassays exhibited strong skewing toward resistance for three measures of resistance: reproductive factor, eggs per gram of root tissue, and root gall severity ratings. A 1:1 segregation for resistance suggested a major gene conferred M. enterolobii resistance. Using a random-effect multiple interval mapping model, we identified a single major QTL, herein designated as qIbMe-4.1, on linkage group 4 that explained 70% of variation in resistance to M. enterolobii. This study provides a new understanding of the genetic basis of M. enterolobii resistance in sweetpotato and represents a major step towards the identification of selectable markers for nematode resistance breeding.

The INSIGHT study: a randomized, Phase III study of ripretinib versus sunitinib for advanced gastrointestinal stromal tumor with KIT exon 11 + 17/18 mutations.

Somatic KIT activating mutations drive most gastrointestinal stromal tumors (GISTs). Disease progression eventually develops with first-line imatinib, commonly due to KIT secondary mutations, and different kinase inhibitors have various levels of treatment efficacy dependent on specific acquired resistance mutations. Ripretinib is a broad-spectrum switch-control KIT/PDGFRA tyrosine kinase inhibitor for patients with advanced GIST who received prior treatment with three or more kinase inhibitors, including imatinib. Exploratory baseline circulating tumor DNA analysis from the second-line INTRIGUE trial determined that patients with advanced GIST previously treated with imatinib harboring primary KIT exon 11 mutations and secondary resistance mutations restricted to KIT exons 17/18 had greater clinical benefit with ripretinib versus sunitinib. We describe the rationale and design of INSIGHT (NCT05734105), an ongoing Phase III open-label study of ripretinib versus sunitinib in patients with advanced GIST previously treated with imatinib exclusively harboring KIT exon 11 + 17/18 mutations detected by circulating tumor DNA.Clinical Trial Registration: NCT05734105 (ClinicalTrials.gov).

Gastrointestinal stromal tumor (GIST) is rare, but it is the most common mesenchymal tumor (a type of tumor that develops from cells which give rise to soft tissues) of the gastrointestinal tract. The primary treatment for advanced GIST is medication that targets the abnormal mechanisms in cancer cells in order to block tumor growth and spread. Ripretinib is an inhibitor of a protein known as KIT, which is a member of the tyrosine kinase protein family and is involved in the growth of GIST. In a Phase III clinical trial called INTRIGUE, the effects of ripretinib and another receptor tyrosine kinase inhibitor, sunitinib, were compared in patients with advanced GIST previously treated with the drug imatinib. An exploratory analysis from the INTRIGUE trial that characterized baseline circulating tumor DNA in the blood showed a greater clinical benefit with ripretinib versus sunitinib in patients with gene mutations solely occurring in KIT exon 11 + 17 and/or 18 (exon 11 + 17/18). This article describes the rationale and design for a Phase III clinical trial called INSIGHT that will evaluate the benefit of ripretinib compared with sunitinib in patients with advanced GIST whose tumors have mutations in KIT exon 11 and KIT exon 17 and/or 18. Patients will receive ripretinib or sunitinib in 6-week cycles, and investigators will assess survival without cancer progression as the primary outcome, and overall survival, and response of the tumor to these two drugs as secondary outcomes.

Development of molecular markers based on real-time PCR to detect flax and sesame in commercial amaranth products.

Amaranthus, Sesamum indicum, and Linum usitatissimum are the most popular oilseed grains worldwide. Protein-rich Amaranthus contains bioactive peptides, is nutritious, and exhibits anti-allergic properties. Sesamum indicum is a primary trigger of anaphylaxis. Linum usitatissimum also displays allergenic properties. A DNA marker assessable using quantitative real-time PCR was developed to detect S. indicum and L. usitatissimum as allergenic contaminants of anti-allergenic Amaranthus. The efficiency of each primer set ranged from 90-98%, and high linear correlation (R2 > 0.99) was obtained between crossover values and the log DNA concentration. We established a Ct value of 0.1% of the binary as a cutoff. The practical application of the designed marker was confirmed by analyzing 20 commercial products. The qPCR system developed for detecting flaxseed and sesame can be applied for regulatory monitoring of allergenic substances in commercial amaranth-containing foods, thus contributing to protecting public health and safety. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-024-01584-2.

Trends of bone mineral density and bone quality in a paediatric kidney transplant recipient: A case report.

Kidney transplant (KT) requires long-term glucocorticoid (GC) treatment against acute and/or chronic rejection. Glucocorticoid-induced osteoporosis (GIOP) is one of the major concerns in kidney transplant recipients (KTRs). Therefore, it is essential to accumulate GIOP data from paediatric KTRs to aid in their healthy growth. A serial observational study of bone strength was carried out in an 8-year-old girl with bilateral hypoplastic kidney who underwent ABO-compatible living-donor KT and GC treatment over 2 years. Bone strength was evaluated by bone mineral density (BMD) and serum bone turnover markers (BTMs), including serum alkaline phosphatase (S-ALP), serum tartrate-resistant acid phosphatase 5b (S-TRACP-5b), and serum undercarboxylated osteocalcin (S-ucOC). All the levels of BTMs and BMD from 1 M to 4 M remained lower than the levels at 0 months (0 M: baseline). After gradual reduction of GC dose (4 M-24 M), S-ALP levels increased from baseline and S-TRACP-5b levels remained lower than the baseline level, but BMD recovered to baseline and increased. The S-ucOC levels did not increase from baseline. The patient's height growth velocity SDS was +3.99 for 23 months, and no fracture occurred during this observation period. A consistent, predominantly formative state of bone, which maintained higher S-ALP levels and lower S-TRACP-5b levels compared to baseline, could contribute to increased BMD. In addition, no increase in S-ucOC levels from baseline could be associated with no deterioration of bone strength. This case suggests that measurement of BMD and, S-ALP, TRACP-5b and ucOC could be useful for evaluating the trend on bone strength in a paediatric KTR.

The role of C-reactive protein as a risk marker of postoperative delirium in older hip fracture patients: a prospective cohort study.

PURPOSE: Postoperative delirium (POD) is a common and serious neuropsychiatric syndrome that leads to higher morbidity and mortality. We investigated the association between serum C-reactive protein (CRP) and the occurrence of POD in older hip fracture patients, and whether CRP predicted POD better than a clinical model. METHODS: Patients aged ≥ 75 years admitted for surgical repair of an acute hip fracture were recruited. We compared serum CRP levels between patients with and without POD. RESULTS: Sixty patients were included, of whom 21 (35%) developed POD. Serum CRP levels were significantly higher in patients who developed delirium (p = 0.011). In a multiple regression model including clinical variables and CRP, cognitive impairment (p = 0.003) and infection (p = 0.001) were the best predictors of POD. CONCLUSIONS: Although higher levels of serum CRP were significantly associated with POD in older hip fracture patients, pre-existing cognitive impairment and infections were the most important risk factors for POD.

High-resolution spiral microfluidic channel integrated electrochemical device for isolation and detection of extracellular vesicles without lipoprotein contamination.

Recent studies have indicated significant correlation between the concentration of immune checkpoint markers borne by extracellular vesicles (EVs) and the efficacy of immunotherapy. This study introduces a high-resolution spiral microfluidic channel-integrated electrochemical device (HiMEc), which is designed to isolate and detect EVs carrying the immune checkpoint markers programmed death ligand 1 (PD-L1) and programmed death protein 1 (PD-1), devoid of plasma-abundant lipoprotein contamination. Antigen-antibody reactions were applied to immobilize the lipoproteins on bead surfaces within the plasma, establishing a size differential with EVs. A plasma sample was then introduced into the spiral microfluidic channel, which facilitated the acquisition of nanometer-sized EVs and the elimination of micrometer-sized lipoprotein-bead complexes, along with the isolation and quantification of EVs using HiMEc. PD-L1 and PD-1 expression on EVs was evaluated in 30 plasma samples (10 from healthy donors, 20 from lung cancer patients) using HiMEc and compared to the results obtained from standard tissue-based PD-L1 testing, noting that HiMEc could be utilized to select further potential candidates. The obtained results are expected to contribute positively to the clinical assessment of potential immunotherapy beneficiaries.

Walking in a controlled ankle motion (CAM) boot: In-boot measurement of joint kinematics and kinetics.

Research investigating ankle function during walking in a controlled ankle motion (CAM) boot has either placed markers on the outside of the boot or made major alterations to the structure of the CAM boot to uncover key landmarks. The aim of this study was to quantify joint kinematics and kinetics using "in-boot" skin markers whilst making only minimal structural alterations. Seventeen healthy participants walked at their preferred walking speed in two conditions: (1) in standard athletic trainers (ASICS patriot 8, ASICS Oceania Pty Ltd, USA), and (2) using a hard-cased CAM boot (Rebound® Air Walker, Össur, Iceland) fitted on the right foot. Kinematic measurements revealed that CAM boots restrict sagittal plane ankle range of motion to less than 5°, and to ∼3° in the frontal plane, which is a reduction of 85% and 73% compared to standard footwear, respectively (p < 0.001). This ankle restriction resulted in a reduction of ankle joint total limb work contribution from 38 ± 5% in normal footwear to 13 ± 4% in the CAM boot (p < 0.001). This study suggests that CAM boots do restrict the ankle joint's ability to effectively perform work during walking, which leads to compensatory mechanisms at the ipsilateral and contralateral hip and knee joints. Our findings align with previous research that employed "on-boot" kinematic measurements, so we conclude that in-boot approaches do not offer any benefit to the researcher and instead, on-boot measurements are suitable.

Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities.

In an environment, microbes often work in communities to achieve most of their essential functions, including the production of essential nutrients. Microbial biofilms are communities of microbes that attach to a nonliving or living surface by embedding themselves into a self-secreted matrix of extracellular polymeric substances. These communities work together to enhance their colonization of surfaces, produce essential nutrients, and achieve their essential functions for growth and survival. They often consist of diverse microbes including bacteria, viruses, and fungi. Biofilms play a critical role in influencing plant phenotypes and human microbial infections. Understanding how these biofilms impact plant health, human health, and the environment is important for analyzing genotype-phenotype-driven rule-of-life functions. Such fundamental knowledge can be used to precisely control the growth of biofilms on a given surface. Metagenomics is a powerful tool for analyzing biofilm genomes through function-based gene and protein sequence identification (functional metagenomics) and sequence-based function identification (sequence metagenomics). Metagenomic sequencing enables a comprehensive sampling of all genes in all organisms present within a biofilm sample. However, the complexity of biofilm metagenomic study warrants the increasing need to follow the Findability, Accessibility, Interoperability, and Reusable (FAIR) Guiding Principles for scientific data management. This will ensure that scientific findings can be more easily validated by the research community. This study proposes a dockerized, self-learning bioinformatics workflow to increase the community adoption of metagenomics toolkits in a metagenomics and meta-transcriptomics investigation. Our biofilm metagenomics workflow self-learning module includes integrated learning resources with an interactive dockerized workflow. This module will allow learners to analyze resources that are beneficial for aggregating knowledge about biofilm marker genes, proteins, and metabolic pathways as they define the composition of specific microbial communities. Cloud and dockerized technology can allow novice learners-even those with minimal knowledge in computer science-to use complicated bioinformatics tools. Our cloud-based, dockerized workflow splits biofilm microbiome metagenomics analyses into four easy-to-follow submodules. A variety of tools are built into each submodule. As students navigate these submodules, they learn about each tool used to accomplish the task. The downstream analysis is conducted using processed data obtained from online resources or raw data processed via Nextflow pipelines. This analysis takes place within Vertex AI's Jupyter notebook instance with R and Python kernels. Subsequently, results are stored and visualized in Google Cloud storage buckets, alleviating the computational burden on local resources. The result is a comprehensive tutorial that guides bioinformaticians of any skill level through the entire workflow. It enables them to comprehend and implement the necessary processes involved in this integrated workflow from start to finish. This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

An Overview of the Deubiquitinase USP53: A Promising Diagnostic Marker and Therapeutic Target.

Ubiquitination and deubiquitination are important mechanisms to maintain normal physiological activities, and their disorders or imbalances can lead to various diseases. As a subgroup of deubiquitinases (DUBs), the ubiquitin-specific peptidase (USP) family is closely related to many biological processes. USP53, one of the family members, is widely expressed in human tissues and participates in a variety of life activities, such as cell apoptosis, nerve transmission, and bone remodeling. Mutations in the USP53 gene can cause cholestasis and deafness and may also be a potential cause of schizophrenia. Knockout of USP53 can alleviate neuropathic pain induced by chronic constriction injury. Loss of USP53 up-regulates RANKL expression, promotes the cytogenesis and functional activity of osteoclasts, and triggers osteodestructive diseases. USP53 plays a tumor-suppressive role in lung cancer, renal clear cell carcinoma, colorectal cancer, liver cancer, and esophageal cancer but reduces the radiosensitivity of cervical cancer and esophageal cancer to induce radioresistance. Through the in-depth combination of literature and bioinformatics, this review suggested that USP53 may be a good potential biomarker or therapeutic target for diseases.

Predictive biomarkers of preeclampsia severity in a low resource setting: Role of red blood cell indices, NLR, and albumin-to-creatinine ratio.

Preeclampsia (PE), a serious medical condition with substantial maternal and perinatal implications, poses a significant challenge, particularly in high-incidence countries like Indonesia. Red blood cell (RBC) indices, neutrophil-to-lymphocyte ratio (NLR), and microalbuminuria (albumin-to-creatinine ratio (ACR)) may signal systemic inflammation and endothelial dysfunction, recently recognized as potential indicators for diagnosing and predicting disease severity. The aim of this study was to analyze RBC indices, NLR, and ACR changes in women with PE and their potential for predicting disease severity. A cross-sectional study was conducted at multi-center hospitals across Medan, Indonesia, from June 2022 to June 2023. The patients were grouped into PE cases with and without severe features. Demographic characteristics and complications were recorded while blood and urine were tested. The Chi-squared test, Fisher's exact test and Mann-Whitney test were used to determine biomarkers associated with severe PE. A total of 208 PE patients were included in the study (104 patients for each PE with and without severe features). Our data indicated that PE patients with severe features had higher red cell distribution width (18.5% vs 13.7%; p<0.001), NLR (5.66% vs 4.1%; p<0.001), and ACR (755.97 mg/dL vs 468.63 mg/dL; p<0.001) compared to those without severe features. In contrast, the platelet count was lower in severe features than those without (21.9 × 106/µL vs 27.0 × 106/µL; p=0.002). This study highlighted that PE patients with severe features predominantly had higher levels of RDW, NLR, and ACR and lower platelet counts compared to those without severe features. Therefore, basic tests such as complete blood count and urinalysis, which are inexpensive and feasible in primary care settings with limited resources, offer hope as valuable diagnostic biomarkers for pregnant women diagnosed with PE in a low resource setting.

TSPO Radioligands for Neuroinflammation: An Overview.

The translocator protein (TSPO) is predominately localized on the outer mitochondrial membrane in steroidogenic cells. In the brain, TSPO expression, low under normal conditions, results upregulated in response to glial cell activation, that occurs in neuroinflammation. As a consequence, TSPO has been extensively studied as a biomarker of such conditions by means of TSPO-targeted radiotracers. Although [11C]-PK11195, the prototypical TSPO radioligand, is still widely used for in vivo studies, it is endowed with severe limitations, mainly low sensitivity and poor amenability to quantification. Consequently, several efforts have been focused on the design of new radiotracers for the in vivo imaging of TSPO. The present review will provide an outlook on the latest advances in TSPO radioligands for neuroinflammation imaging. The final goal is to pave the way for (radio)chemists in the future design and development of novel effective and sensitive radiopharmaceuticals targeting TSPO.