Extra-corporeal detoxification in insects.

Upon uptake of toxins, insects launch a detoxification program. This program is deployed in multiple organs and cells to raise their tolerance against the toxin. The molecular mechanisms of this program inside the insect body have been studied and understood in detail. Here, we report on a yet unexplored extra-corporeal detoxification of insecticides in Drosophila melanogaster. Wild-type D. melanogaster incubated with DDT, a contact insecticide, in a closed environment died as expected. However, incubation of a second cohort in the same environment after removal of the dead flies was not lethal. The effect was significantly lower if the flies of the two cohorts were unrelated. Incubation assays with Chlorpyrifos, another contact insecticide, yielded identical results, while incubation assays with Chlorantraniliprole, again a contact insecticide, was toxic for the second cohort of flies. A cohort of flies incubated in a DDT environment after an initial incubation of a honeybee survived treatment. Together, our data suggest that insects including Apis mellifera and D. melanogaster have the capacity to modify their proximate environment. Consequently, in their ecological niche, following individuals might be saved from intoxication thereby facilitating colonisation of an attractive site.

Benchmarking feature selection and feature extraction methods to improve the performances of machine-learning algorithms for patient classification using metabolomics biomedical data.

Objective: Classification tasks are an open challenge in the field of biomedicine. While several machine-learning techniques exist to accomplish this objective, several peculiarities associated with biomedical data, especially when it comes to omics measurements, prevent their use or good performance achievements. Omics approaches aim to understand a complex biological system through systematic analysis of its content at the molecular level. On the other hand, omics data are heterogeneous, sparse and affected by the classical "curse of dimensionality" problem, i.e. having much fewer observation, samples (n) than omics features (p). Furthermore, a major problem with multi-omics data is the imbalance either at the class or feature level. The objective of this work is to study whether feature extraction and/or feature selection techniques can improve the performances of classification machine-learning algorithms on omics measurements. Methods: Among all omics, metabolomics has emerged as a powerful tool in cancer research, facilitating a deeper understanding of the complex metabolic landscape associated with tumorigenesis and tumor progression. Thus, we selected three publicly available metabolomics datasets, and we applied several feature extraction techniques both linear and non-linear, coupled or not with feature selection methods, and evaluated the performances regarding patient classification in the different configurations for the three datasets. Results: We provide general workflow and guidelines on when to use those techniques depending on the characteristics of the data available. To further test the extension of our approach to other omics data, we have included a transcriptomics and a proteomics data. Overall, for all datasets, we showed that applying supervised feature selection improves the performances of feature extraction methods for classification purposes. Scripts used to perform all analyses are available at: https://github.com/Plant-Net/Metabolomic_project/.

Home range size and habitat selection of owned outdoor domestic cats (Felis catus) in urban southwestern Ontario.

Domestic cats (Felis catus) play a dual role in society as both companion animals and predators. When provided with unsupervised outdoor access, cats can negatively impact native wildlife and create public health and animal welfare challenges. The effective implementation of management strategies, such as buffer zones or curfews, requires an understanding of home range size, the factors that influence their movement, and the types of habitats they use. Here, we used a community/citizen scientist approach to collect movement and habitat use data using GPS collars on owned outdoor cats in the Kitchener-Waterloo-Cambridge-Guelph region, southwestern Ontario, Canada. Mean (± SD) 100% minimum convex polygon home range size was 8 ± 8 ha (range: 0.34-38 ha) and was positively associated with road density but not with intrinsic factors such as boldness, sex, or age. With regards to habitat selection, cats used greenspaces, roads, and agricultural land less often than predicted but strongly selected for impervious surfaces (urban areas other than greenspaces or roads). Our results suggest that wildlife near buildings and residential areas are likely at the greatest risk of cat predation and that a buffer size of 840 m would be needed to restrict cats from entering areas of conservation concern.

Clonal hematopoiesis in people with advanced HIV and associated inflammatory syndromes.

People with HIV (PWH) have a higher age-adjusted mortality due to chronic immune activation and age-related comorbidities. PWH also have higher rates of clonal hematopoiesis (CH) than age-matched non-HIV cohorts, however, risk factors influencing the development and expansion of CH in PWH remain incompletely explored. We investigated the relationship between CH, immune biomarkers, and HIV-associated risk factors (CD4, CD8 T-cells, nadir CD4 count, opportunistic infections [OIs], and immune reconstitution inflammatory syndrome [IRIS]) in a diverse cohort of 197-PWH with median age of 42-years, using a 56-gene panel. Seventy-nine percent had a CD4 nadir < 200, 58.9% had prior OIs, and 34.5% had a history of IRIS. The prevalence of CH was high (27.4%), even in younger individuals, and CD8 T-cells and nadir CD4 counts strongly associated with CH after controlling for age. A history of IRIS was associated with CH in a subgroup analysis of ≥ 35-years-old patients. Inflammatory biomarkers were higher in CH carriers compared to non-carriers supporting a dysregulated immune state. These findings suggest PWH with low nadir CD4 and/or inflammatory complications may be at high risk of CH regardless of age and represent a high-risk group that could benefit from risk reduction and potentially targeted immunomodulation.

Children's evaluations of culturally diverse lunchbox foods.

Previous research indicates that children make ingroup-outgroup judgments based on notions of food conventionality and that ethnic minority children have been teased or bullied for bringing non-conventional foods to school. This series of three studies experimentally investigated U.S. school-age children's evaluations of culturally diverse lunchbox foods. Study 1 examined an online sample of children aged 5 to 12 years and their evaluations of foods from four cultures (mainstream American, Chinese, Indian, and Mexican) on the taste, smell, and messiness of the food, the appropriateness of bringing the food to school, and whether "cool kids" eat the food. Compared with the mainstream American lunchbox, children rated the Chinese, Indian, and Mexican lunchboxes as less tasty, more messy, and less likely that cool kids would bring those foods to school. In Studies 2 and 3, we examined children's behavioral choices in a hypothetical cafeteria. In both studies, we found that the match between children's own lunch preferences and what was displayed in the mainstream American lunchbox was the only predictor of children's choice to sit at the table with the American lunchbox. Individual variables (e.g., child age, food pickiness) and contextual variables (e.g., neighborhood diversity) did not predict children's table choices. This research highlights children's understanding of familiarity and conventionality of foods and the social consequences of their behavioral choices.

A Hypermutable Region in the DISP2 Gene Links to Natural Selection and Late-Onset Neurocognitive Disorders in Humans.

(CCG) short tandem repeats (STRs) are predominantly enriched in genic regions, mutation hotspots for C to T truncating substitutions, and involved in various neurological and neurodevelopmental disorders. However, intact blocks of this class of STRs are widely overlooked with respect to their link with natural selection. The human neuron-specific gene, DISP2 (dispatched RND transporter family member 2), contains a (CCG) repeat in its 5' untranslated region. Here, we sequenced this STR in a sample of 448 Iranian individuals, consisting of late-onset neurocognitive disorder (NCD) (N = 203) and controls (N = 245). We found that the region spanning the (CCG) repeat was highly mutated, resulting in several flanking (CCG) residues. However, an 8-repeat of the (CCG) repeat was predominantly abundant (frequency = 0.92) across the two groups. While the overall distribution of genotypes was not different between the two groups (p > 0.05), we detected four genotypes in the NCD group only (2% of the NCD genotypes, Mid-p = 0.02), consisting of extreme short alleles, 5- and 6-repeats, that were not detected in the control group. The patients harboring those genotypes received the diagnoses of probable Alzheimer's disease and vascular dementia. We also found six genotypes in the control group only (2.5% of the control genotypes, Mid-p = 0.01) that consisted of the 8-repeat and extreme long alleles, 9- and 10-repeats, of which the 10-repeat was not detected in the NCD group. The (CCG) repeat specifically expanded in primates. In conclusion, we report an indication of natural selection at a novel hypermutable region in the human genome and divergent alleles and genotypes in late-onset NhCDs and controls. These findings reinforce the hypothesis that a collection of rare alleles and genotypes in a number of genes may unambiguously contribute to the cognition impairment component of late-onset NCDs.

Promotion of apoplastic oxidative burst by artificially selected GhCBSX3A enhances Verticillium dahliae resistance in upland cotton.

Verticillium wilt (VW) is a devasting disease affecting various plants, including upland cotton, a crucial fiber crop. Despite its impact, the genetic basis underlying cotton's susceptibility or defense against VW remains unclear. Here, we conducted a genome-wide association study on VW phenotyping in upland cotton and identified a locus on A13 that is significantly associated with VW resistance. We then identified a cystathionine ß-synthase domain gene at A13 locus, GhCBSX3A, which was induced by Verticillium dahliae. Functional analysis, including expression silencing in cotton and overexpression in Arabidopsis thaliana, confirmed that GhCBSX3A is a causal gene at the A13 locus, enhancing SAR-RBOHs-mediated apoplastic oxidative burst. We found allelic variation on the TATA-box of GhCBSX3A promoter attenuated its expression in upland cotton, thereby weakening VW resistance. Interestingly, we discovered that altered artificial selection of GhCBSX3A_R (an elite allele for VW) under different VW pressures during domestication and other improved processes allows specific human needs to be met. Our findings underscore the importance of GhCBSX3A in response to VW, and we propose a model for defense-associated genes being selected depending on the pathogen's pressure. The identified locus and gene serve as promising targets for VW resistance enhancement in cotton through genetic engineering.

The nature and distribution of putative non-functional alleles suggest only two independent events at the origins of Astyanax mexicanus cavefish populations.

BACKGROUND: Several studies suggested that cavefish populations of Astyanax mexicanus settled during the Late Pleistocene. This implies that the cavefish's most conspicuous phenotypic changes, blindness and depigmentation, and more cryptic characters important for cave life, evolved rapidly. RESULTS: Using the published genomes of 47 Astyanax cavefish from la Cueva de El Pachón, El Sótano de la Tinaja, La Cueva Chica and El Sótano de Molino, we searched for putative loss-of-function mutations in previously defined sets of genes, i.e., vision, circadian clock and pigmentation genes. Putative non-functional alleles for four vision genes were identified. Then, we searched genome-wide for putative non-functional alleles in these four cave populations. Among 512 genes with segregating putative non-functional alleles in cavefish that are absent in surface fish, we found an enrichment in visual perception genes. Among cavefish populations, different levels of shared putative non-functional alleles were found. Using a subset of 12 genes for which putative loss-of-function mutations were found, we extend the analysis of shared pseudogenes to 11 cave populations. Using a subset of six genes for which putative loss-of-function mutations were found in the El Sótano del Toro population, where extensive hybridization with surface fish occurs, we found a correlation between the level of eye regression and the amount of putative non-functional alleles. CONCLUSIONS: We confirm that very few putative non-functional alleles are present in a large set of vision genes, in accordance with the recent origin of Astyanax mexicanus cavefish. Furthermore, the genome-wide analysis indicates an enrichment of putative loss-of-function alleles in genes with vision-related GO-terms, suggesting that visual perception may be the function chiefly impacted by gene losses related to the shift from a surface to a cave environment. The geographic distribution of putative loss-of-function alleles newly suggests that cave populations from Sierra de Guatemala and Sierra de El Abra share a common origin, albeit followed by independent evolution for a long period. It also supports that populations from the Micos area have an independent origin. In El Sótano del Toro, the troglomorphic phenotype is maintained despite massive introgression of the surface genome.

Integrative analysis with microbial modelling and machine learning uncovers potential alleviators for ulcerative colitis.

Ulcerative colitis (UC) is a challenging form of inflammatory bowel disease, and its etiology is intricately linked to disturbances in the gut microbiome. To identify the potential alleviators of UC, we employed an integrative analysis combining microbial community modeling with advanced machine learning techniques. Using metagenomics data sourced from the Integrated Human Microbiome Project, we constructed individualized microbiome community models for each participant. Our analysis highlighted a significant decline in both α and ß-diversity of strain-level microbial populations in UC subjects compared to controls. Distinct differences were also observed in the predicted fecal metabolite profiles and strain-to-metabolite contributions between the two groups. Using tree-based machine learning models, we successfully identified specific microbial strains and their associated metabolites as potential alleviators of UC. Notably, our experimental validation using a dextran sulfate sodium-induced UC mouse model demonstrated that the administration of Parabacteroides merdae ATCC 43,184 and N-acetyl-D-mannosamine provided notable relief from colitis symptoms. In summary, our study underscores the potential of an integrative approach to identify novel therapeutic avenues for UC, paving the way for future targeted interventions.

Genetic improvement of Egyptian cotton (Gossypium barbadense L.) for high yield and fiber quality properties under semi arid conditions.

Between 2016 and 2018, the Agriculture Research Center's Sakha Agriculture Research Station conducted two rounds of pedigree selection on a segregating population of cotton (Gossypium barbadense L.) using the F2, F3, and F4 generations resulting from crossing Giza 94 and Suvin. In 2016, the top 5% of plants from the F2 population were selected based on specific criteria. The superior families from the F3 generation were then selected to produce the F4 families in 2017, which were grown in the 2018 summer season in single plant progeny rows and bulk experiments with a randomized complete block design of three replications. Over time, most traits showed increased mean values in the population, with the F2 generation having higher Genotypic Coefficient of Variance (GCV) and Phenotypic Coefficient of Variance (PCV) values compared to the succeeding generations for the studied traits. The magnitude of GCV and PCV in the F3 and F4 generations was similar, indicating that genotype had played a greater role than the environment. Moreover, the mean values of heritability in the broad sense increased from generation to generation. Selection criteria I2, I4, and I5 were effective in improving most of the yield and its component traits, while selection criterion I1 was efficient in improving earliness traits. Most of the yield and its component traits showed a positive and significant correlation with each other, highlighting their importance in cotton yield. This suggests that selecting to improveone or more of these traits would improve the others. Families number 9, 13, 19, 20, and 21 were the best genotypes for relevant yield characters, surpassing the better parent, check variety, and giving the best values for most characters. Therefore, the breeder could continue to use these families in further generations as breeding genotypes to develop varieties with high yields and its components.

Integrative analysis unveils ECM signatures and pathways driving hepatocellular carcinoma progression: A multi-omics approach and prognostic model development.

Liver hepatocellular carcinoma (LIHC) is a highly lethal form of cancer that is among the deadliest cancer types globally. In terms of cancer-related mortality rates, liver cancer ranks among the top three, underscoring the severity of this disease. Insufficient analysis has been conducted to fully understand the potential value of the extracellular matrix (ECM) in immune infiltration and the prognostic stratification of LIHC, despite its recognised importance in the development of this disease. The scRNA-seq data of GSE149614 was used to conduct single-cell analysis on 10 LIHC samples. CellChat scores were calculated for seven cell populations in the descending cohort to investigate cellular communication, while PROGENy scores were calculated to determine tumour-associated pathway scores in different cell populations. The pathway analysis using GO and KEGG revealed the enrichment of ECM-associated genes in the pathway, highlighting the potential role of the ECM in LIHC development. By utilizing the TCGA-LIHC cohort, an ECM-based prognostic model for LIHC was developed using Lasso regression. Immune infiltration scores were calculated using two methods, and the performance of the ECM-related risk score was evaluated using an independent cohort from the CheckMate study. To determine the precise expression of ECM-associated risk genes in LIHC, we evaluated hepatocellular carcinoma cell lines using a range of assays, including Western blotting, invasion assays and Transwell assays. Using single-cell transcriptome analysis, we annotated the spatially-specific distribution of major immune cell types in single-cell samples of LIHC. The main cell types identified and annotated included hepatocytes, T cells, myeloid cells, epithelial cells, fibroblasts, endothelial cells and B cells. The utilisation of cellchat and PROGENy analyses enabled the investigation and unveiling of signalling interactions, protein functionalities and the prominent influential pathways facilitated by the primary immune cell types within the LIHC. Numerous tumour pathways, including PI2K, EGFR and TGFb, demonstrated a close correlation with the involvement of ECM in LIHC. Moreover, an evaluation was conducted to assess the primary ECM-related functional changes and biological pathway enrichment in LIHC. Differential genes associated with ECM were identified and utilised to create prognostic models. The prognostic stratification value of these models for LIHC patients was confirmed through validation in multiple databases. Furthermore, through immune infiltration analysis, it was discovered that ECM might be linked to the irregular expression and regulation of numerous immune cells. Additionally, histone acetylation was mapped against gene mutation frequencies and differential expression profiles. The prognostic stratification efficacy of the ECM prediction model constructed in the context of PD-1 inhibitor therapy was also examined, and it exhibited strong stratification performance. Cellular experiments, including Western blotting, invasion and Transwell assays, revealed that ECM-associated risk genes have a promoting effect on the development of LIHC. The creation of biomarkers for LIHC using ECM-related genes unveiled substantial correlations with immune microenvironmental infiltration and functional mutations in various tumour pathways. This enlightens us to the possibility that the influence of ECM on tumours may extend beyond simply promoting the fibrotic process and the stromal composition of tumours.

Optimizing antigen selection for the development of tuberculosis vaccines.

Tuberculosis (TB) remains a prevalent global infectious disease caused by genetically closely related tubercle bacilli in Mycobacterium tuberculosis complex (MTBC). For a century, the Bacillus Calmette-Guérin (BCG) vaccine has been the primary preventive measure against TB. While it effectively protects against extrapulmonary forms of pediatric TB, it lacks consistent efficacy in providing protection against pulmonary TB in adults. Consequently, the exploration and development of novel TB vaccines, capable of providing broad protection to populations, have consistently constituted a prominent area of interest in medical research. This article presents a concise overview of the novel TB vaccines currently undergoing clinical trials, discussing their classification, protective efficacy, immunogenicity, advantages, and limitations. In vaccine development, the careful selection of antigens that can induce strong and diverse specific immune responses is essential. Therefore, we have summarized the molecular characteristics, biological function, immunogenicity, and relevant studies associated with the chosen antigens for TB vaccines. These insights gained from vaccines and immunogenic proteins will inform the development of novel mycobacterial vaccines, particularly mRNA vaccines, for effective TB control.

Simultaneous brain and neck time-of-flight MRA using spiral multiband with localized quadratic encoding.

PURPOSE: To develop a method that achieves simultaneous brain and neck time-of-flight (ToF) magnetic resonance angiography (MRA) within feasible scan timeframes. METHODS: Localized quadratic (LQ) encoding is efficient for both signal-to-noise ratio (SNR) and in-flow enhancement. We proposed a spiral multiband LQ method to enable simultaneous intracranial and carotid ToF-MRA within a single scan. To address the venous signal contamination that becomes a challenge with multiband (MB) ToF, tilt-optimized non-saturated excitation (TONE) and partial-Fourier slice selection (PFSS) were further introduced in the LQ framework to mitigate the venous signal and improve artery contrast. A sequential spiral MB and LQ reconstruction pipeline was employed to obtain the brain-and-neck image volumes. RESULTS: The proposed MB method was able to achieve simultaneous brain and neck ToF-MRA within a 2:50-min scan. The complementarily boosted SNR-efficiency by MB and LQ acquisitions allows for the increased spatial coverage without increase in scan time or noticeable compromise in SNR. The incorporation of both TONE and PFSS effectively alleviated the venous contamination with improved small vessel sensitivity. Selection of scan parameters such as the LQ factor and flip angle reflected the trade-off among SNR, blood contrast, and venous suppression. CONCLUSIONS: A novel MB spiral LQ approach was proposed to enable fast intracranial and carotid ToF-MRA with minimized venous corruption. The method has shown promise in MRA applications where large spatial coverage is necessary.

The drivers of intraspecific trait variation and their implications for future tree productivity and survival.

Forests are facing unprecedented levels of stress from pest and disease outbreaks, disturbance, fragmentation, development, and a changing climate. These selective agents act to alter forest composition from regional to cellular levels. Thus, a central challenge for understanding how forests will be impacted by future change is how to integrate across scales of biology. Phenotype, or an observable trait, is the product of an individual's genes (G) and the environment in which an organism lives (E). To date, researchers have detailed how environment drives variation in tree phenotypes over long time periods (e.g., long-term ecological research sites [LTERs]) and across large spatial scales (e.g., flux network). In parallel, researchers have discovered the genes and pathways that govern phenotypes, finding high degrees of genetic control and signatures of local adaptation in many plant traits. However, the research in these two areas remain largely independent of each other, hindering our ability to generate accurate predictions of plant response to environment, an increasingly urgent need given threats to forest systems. I present the importance of both genes and environment in determining tree responses to climate stress. I highlight why the difference between G versus E in driving variation is critical for our understanding of climate responses, then propose means of accelerating research that examines G and E simultaneously by leveraging existing long-term, large-scale phenotypic data sets from ecological networks and adding newly affordable sequence (-omics) data to both drill down to find the genes and alleles influencing phenotypes and scale up to find how patterns of demography and local adaptation may influence future response to change.

Shaping immunity: The influence of natural selection on population immune diversity.

Humans exhibit considerable variability in their immune responses to the same immune challenges. Such variation is widespread and affects individual and population-level susceptibility to infectious diseases and immune disorders. Although the factors influencing immune response diversity are partially understood, what mechanisms lead to the wide range of immune traits in healthy individuals remain largely unexplained. Here, we discuss the role that natural selection has played in driving phenotypic differences in immune responses across populations and present-day susceptibility to immune-related disorders. Further, we touch on future directions in the field of immunogenomics, highlighting the value of expanding this work to human populations globally, the utility of modeling the immune response as a dynamic process, and the importance of considering the potential polygenic nature of natural selection. Identifying loci acted upon by evolution may further pinpoint variants critically involved in disease etiology, and designing studies to capture these effects will enrich our understanding of the genetic contributions to immunity and immune dysregulation.

An enriched approach to combining high-dimensional genomic and low-dimensional phenotypic data.

We describe an approach for combining and analyzing high-dimensional genomic and low-dimensional phenotypic data. The approach leverages a scheme of weights applied to the variables instead of observations and, hence, permits incorporation of the information provided by the low dimensional data source. It can also be incorporated into commonly used downstream techniques, such as random forest or penalized regression. Finally, the simulated lupus studies involving genetic and clinical data are used to illustrate the overall idea and show that the proposed enriched penalized method can select significant genetic variables while keeping several important clinical variables in the final model.

Comparison of different screening methods for the selection of Ascochyta blight disease on chickpea (Cicer arietinum L.) genotypes.

Chickpea (Cicer arietinum L.) is the second most important edible food grain legume, widely grown all over the world. However, the cultivation and production of chickpea are mainly affected by the Ascochyta blight (AB) disease, which causes losses of up to 100% in areas with high humidity and warm temperature conditions. Various screening methods are used in the selection of chickpea genotypes for resistance to AB disease. These methods are natural field condition (NFC), artificial epidemic field condition (AEC), marker-assisted selection (MAS), and real-time PCR (RT-PCR). The study was conducted with 88 chickpea test genotypes between the 2014 and 2016 growing seasons. The results of the screening were used to sort the genotypes into three categories: susceptible (S), moderately resistant (MR), and resistant (R). Using MAS screening, 13, 21, and 54 chickpea genotypes were identified as S, MR, and R, respectively. For RT-PCR screening, 39 genotypes were S, 31 genotypes were MR, and 18 genotypes were R. In the AEC method for NFC screening, 7, 17, and 64 genotypes were S, MR, and R, while 74 and 6 genotypes were S and MR, and 8 genotypes were R-AB disease. As a result of screening chickpea genotypes for AB disease, it was determined that the most effective method was artificial inoculation (AEC) under field conditions. In the study, Azkan, ICC3996, Tüb-19, and Tüb-82 were determined as resistant within all methods for Pathotype 1.

Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients' response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.

Post-transplant cyclophosphamide or cell selection in haploidentical allogeneic hematopoietic cell transplantation?

BACKGROUND: One major limitation for broader applicability of allogeneic hematopoietic cell transplantation (allo-HCT) in the past was the lack of HLA-matched histocompatible donors. Preclinical mouse studies using T-cell depleted haploidentical grafts led to an increased interest in the use of ex vivo T-cell depleted (TCD) haploidentical allo-HCT. TCD grafts through negative (T-cell depletion) or positive (CD34+ cell selection) techniques have been investigated to reduce the risk of graft-versus-host disease (GVHD) given the known implications of alloreactive T cells. A more practical approach to deplete alloreactive T cells in vivo using high doses of cyclophosphamide after allografting has proved to be feasible in overcoming the HLA barrier. Such approach has extended allo-HCT feasibility to patients for whom donors could not be found in the past. Nowadays, haploidentical donors represent a common donor source for patients in need of an allo-HCT. The broad application of haploidentical donors became possible by understanding the importance of depleting alloreactive donor T cells to facilitate engraftment and reduce incidence and severity of GVHD. These techniques involve ex vivo graft manipulation or in vivo utilization of pharmacologic agents, notably post-transplant cyclophosphamide (PTCy). DISCUSSION: While acknowledging that no randomized controlled prospective studies have been yet conducted comparing TCD versus PTCy in haploidentical allo-HCT recipients, there are two advantages that would favor the PTCy, namely ease of application and lower cost. However, emerging data on adverse events associated with PTCy including, but not limited to cardiac associated toxicities or increased incidence of post-allograft infections, and others, are important to recognize.

Magnetic nanoparticle-mediated enrichment technology combined with microfluidic single cell separation technology: A technology for efficient separation and degradation of functional bacteria in single cell liquid phase.

Although there are many microorganisms in nature, the limitations of isolation and cultivation conditions have restricted the development of artificial enhanced remediation technology using functional microbial communities. In this study, an integrated technology of Magnetic Nanoparticle-mediated Enrichment (MME) and Microfluidic Single Cell separation (MSC) that breaks through the bottleneck of traditional separation and cultivation techniques and can efficiently obtain more in situ functional microorganisms from the environment was developed. MME technology was first used to enrich rapidly growing active bacteria in the environment. Subsequently, MSC technology was applied to isolate and incubate functional bacterial communities in situ and validate the degradation ability of individual bacteria. As a result, this study has changed the order of traditional pure culture methods, which are first selected and then cultured, and provided a new method for obtaining non-culturable functional microorganisms.