BACKGROUND: Trauma can result in systemic inflammation that leads to organ dysfunction, but the impact on the brain, particularly following extracranial insults, has been largely overlooked.
METHODS: Building upon our prior findings, we aimed to understand the impact of systemic inflammation on neuroinflammatory gene transcripts in eight brain regions in rats exposed to (1) blast overpressure exposure [BOP], (2) cutaneous thermal injury [BU], (3) complex extremity injury, 3 hours (h) of tourniquet-induced ischemia, and hind limb amputation [CEI+tI+HLA], (4) BOP+BU or (5) BOP+CEI and delayed HLA [BOP+CEI+dHLA] at 6, 24, and 168 h post-injury (hpi).
RESULTS: Globally, the number and magnitude of differentially expressed genes (DEGs) correlated with injury severity, systemic inflammation markers, and end-organ damage, driven by several chemokines/cytokines (Csf3, Cxcr2, Il16, and Tgfb2), neurosteroids/prostaglandins (Cyp19a1, Ptger2, and Ptger3), and markers of neurodegeneration (Gfap, Grin2b, and Homer1). Regional neuroinflammatory activity was least impacted following BOP. Non-blast trauma (in the BU and CEI+tI+HLA groups) contributed to an earlier, robust and diverse neuroinflammatory response across brain regions (up to 2-50-fold greater than that in the BOP group), while combined trauma (in the BOP+CEI+dHLA group) significantly advanced neuroinflammation in all regions except for the cerebellum. In contrast, BOP+BU resulted in differential activity of several critical neuroinflammatory-neurodegenerative markers compared to BU. t-SNE plots of DEGs demonstrated that the onset, extent, and duration of the inflammatory response are brain region dependent. Regardless of injury type, the thalamus and hypothalamus, which are critical for maintaining homeostasis, had the most DEGs. Our results indicate that neuroinflammation in all groups progressively increased or remained at peak levels over the study duration, while markers of end-organ dysfunction decreased or otherwise resolved.
CONCLUSIONS: Collectively, these findings emphasize the brain\'s sensitivity to mediators of systemic inflammation and provide an example of immune-brain crosstalk. Follow-on molecular and behavioral investigations are warranted to understand the short- to long-term pathophysiological consequences on the brain, particularly the mechanism of blood-brain barrier breakdown, immune cell penetration-activation, and microglial activation.

Bacterial Leaf Blight (Xanthomonas oryzae pv. oryzae) and blast (Magnaporthe oryzae) are the major biotic stresses around the rice-growing zones of the world. The development of resistant varieties through Marker Assisted Backcross Breeding is the utmost economical and eco-friendly method for achieving stable yield. Amongst the resistance genes recognized, Xa21 and Pi54 possess broad-spectrum resistance to many Xoo and blast strains around the world. In the present study, we have effectively introgressed a Bacterial Blight resistance gene (Xa21) and a blast resistance gene (Pi54) into susceptible variety ADT43 from RP-Bio-Patho-2 coupled with phenotypic selection for agronomic, cooking quality and grain traits through MABC. MABC was sustained till BC2F2 generation with specific markers pTA248 for Xa21 and Pi54MAS for Pi54 resistance genes. A set of SSR markers for parental polymorphism were utilized for maximum regaining of recurrent parent genome in each backcrossing. \"Positive plants\" from BC2F1 were selfed to generate BC2F2 and the homozygous lines for bacterial leaf blight and blast resistance genes were identified for further assessment.

BACKGROUND: A molecular approach for the identification of unknown species by the using mitochondrial cox1 gene is an effective and reliable as compared with morphological-based identification. Hirudinaria manillensis referred to as Asian Buffalo Leech, is found in South Asia and traditionally used as medicine owing to its medicinal properties.
RESULTS: The study aimed to isolate and identify the leech species using cox1 gene sequencing and their phylogenetic relationships. The nucleotide sequences of cytochrome c oxidase subunit I (cox1) mitochondrial genes were analyzed for species identification and the phylogenetic relationship of crucial therapeutic leech Hirudinaria manillensis. The isolated DNA from the leech sample was amplified with cox1 gene-specific primers. BLAST results with the H. manillensis sequence showed 89.24% homology with H. manillensis and phylogenetic tree analysis revealed the genetic relationship with other GenBank submitted sequences.
CONCLUSIONS: The present study concluded that the cox1 gene could be an effective way to identify the leech H. manillensis and provided sufficient phylogenetic information to distinguish H. manillensis indicating a significant mtDNA-based approach to species identification.

Rice, a critical staple on a global scale, faces escalating challenges in yield preservation due to the rising prevalence of abiotic and biotic stressors, exacerbated by frequent climatic fluctuations in recent years. Moreover, the scorching climate prevalent in the rice-growing regions of South China poses obstacles to the cultivation of good-quality, heavy-grain varieties. Addressing this dilemma requires the development of resilient varieties capable of withstanding multiple stress factors. To achieve this objective, our study employed the broad-spectrum blast-resistant line Digu, the brown planthopper (BPH)-resistant line ASD7, and the heavy-grain backbone restorer lines Fuhui838 (FH838) and Shuhui527 (SH527) as parental materials for hybridization and multiple crossings. The incorporation of molecular markers facilitated the rapid pyramiding of six target genes (Pi5, Pita, Pid2, Pid3, Bph2, and Wxb ). Through a comprehensive evaluation encompassing blast resistance, BPH resistance, cold tolerance, grain appearance, and quality, alongside agronomic trait selection, a promising restorer line, Guihui5501 (GH5501), was successfully developed. It demonstrated broad-spectrum resistance to blast, exhibiting a resistance frequency of 77.33% against 75 artificially inoculated isolates, moderate resistance to BPH (3.78 grade), strong cold tolerance during the seedling stage (1.80 grade), and characteristics of heavy grains (1,000-grain weight reaching 35.64 g) with good grain quality. The primary rice quality parameters for GH5501, with the exception of alkali spreading value, either met or exceeded the second-grade national standard for premium edible rice varieties, signifying a significant advancement in the production of good-quality heavy-grain varieties in the southern rice-growing regions. Utilizing GH5501, a hybrid combination named Nayou5501, characterized by high yield, good quality, and resistance to multiple stresses, was bred and received approval as a rice variety in Guangxi in 2021. Furthermore, genomic analysis with gene chips revealed that GH5501 possessed an additional 20 exceptional alleles, such as NRT1.1B for efficient nitrogen utilization, SKC1 for salt tolerance, and STV11 for resistance to rice stripe virus. Consequently, the restorer line GH5501 could serve as a valuable resource for the subsequent breeding of high-yielding, good-quality, and stress-tolerant hybrid rice varieties.

BACKGROUND: Precise evaluation of fungal conidia production may facilitate studies on resistance mechanisms and plant breeding for disease resistance. In this study, hyperspectral imaging (HSI) was used to quantify the sporulation of Magnaporthe oryzae on the leaves of rice cultivars grown under controlled conditions. Three rice genotypes (CO 39, Nipponbare, IR64) differing in susceptibility to blast were inoculated with M. oryzae isolates Guy 11 and Li1497. Spectral information (450-850 nm, 140 wavebands) of typical leaf blast symptoms was recorded before and after induction of sporulation of the pathogen.
RESULTS: M. oryzae produced more conidia on the highly susceptible genotype than on the moderately susceptible genotype, whereas the resistant genotype resulted in no sporulation. Changes in reflectance spectra recorded before and after induction of sporulation were significantly higher in genotype CO 39 than in Nipponbare. The spectral angle mapper algorithm for supervised classification allowed for the classification of blast symptom subareas and the quantification of lesion areas with M. oryzae sporulation. The correlation between the area under the difference spectrum (viz. spectral difference without and with sporulation) and the number of conidia per lesion and the number of conidia per lesion area was positive and count-based differences in rice - M. oryzae interaction could be reproduced in the spectral data.
CONCLUSIONS: HSI provided a precise and objective method of assessing M. oryzae conidia production on infected rice plants, revealing differences that could not be detected visually.

The field of viral genomic studies has experienced an unprecedented increase in data volume. New strains of known viruses are constantly being added to the GenBank database and so are completely new species with little or no resemblance to our databases of sequences. In addition to this, metagenomic techniques have the potential to further increase the number and rate of sequenced genomes. Besides, it is important to consider that viruses have a set of unique features that often break down molecular biology dogmas, e.g., the flux of information from RNA to DNA in retroviruses and the use of RNA molecules as genomes. As a result, extracting meaningful information from viral genomes remains a challenge and standard methods for comparing the unknown and our databases of characterized sequences may need adaptations. Thus, several bioinformatic approaches and tools have been created to address the challenge of analyzing viral data. This chapter offers descriptions and protocols of some of the most important bioinformatic techniques for comparative analysis of viruses. The authors also provide comments and discussion on how viruses\' unique features can affect standard analyses and how to overcome some of the major sources of problems. Protocols and topics emphasize online tools (which are more accessible to users) and give the real experience of what most bioinformaticians do in day-by-day work with command-line pipelines. The topics discussed include (1) clustering related genomes, (2) whole genome multiple sequence alignments for small RNA viruses, (3) protein alignment for marker genes and species affiliation, (4) variant calling and annotation, and (5) virome analyses and pathogen identification.

UNASSIGNED: Acute leukemia (AL) is a life-threatening malignant disease that occurs in the bone marrow and blood, and is classified as either acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). Diagnosing AL warrants testing methods, such as flow cytometry, which require trained professionals, time, and money. We aimed to develop a model that can classify peripheral blood images of 12 cell types, including pathological cells associated with AL, using artificial intelligence.
UNASSIGNED: We acquired 42,386 single-cell images of peripheral blood slides from 282 patients (82 with AML, 40 with ALL, and 160 with immature granulocytes).
UNASSIGNED: The performance of EfficientNet-V2 (B2) using the original image size exhibited the greatest accuracy (accuracy, 0.8779; precision, 0.7221; recall, 0.7225; and F1 score, 0.7210). The next-best accuracy was achieved by EfficientNet-V1 (B1), with a 256 × 256 pixels image. F1 score was the greatest for EfficientNet-V1 (B1) with the original image size. EfficientNet-V1 (B1) and EfficientNet-V2 (B2) were used to develop an ensemble model, and the accuracy (0.8858) and F1 score (0.7361) were improved. The classification performance of the developed ensemble model for the 12 cell types was good, with an area under the receiver operating characteristic curve above 0.9, and F1 scores for myeloblasts and lymphoblasts of 0.8873 and 0.8006, respectively.
UNASSIGNED: The performance of the developed ensemble model for the 12 cell classifications was satisfactory, particularly for myeloblasts and lymphoblasts. We believe that the application of our model will benefit healthcare settings where the rapid and accurate diagnosis of AL is difficult.

Mild traumatic brain injury (mTBI) has emerged as a potential risk factor for the development of neurodegenerative conditions such as Alzheimer\'s disease and chronic traumatic encephalopathy. Blast mTBI, caused by exposure to a pressure wave from an explosion, is predominantly experienced by military personnel and has increased in prevalence and severity in recent decades. Yet the underlying pathology of blast mTBI is largely unknown. We examined the expression and localization of AQP4 in human post-mortem frontal cortex and observed distinct laminar differences in AQP4 expression following blast exposure. We also observed similar laminar changes in AQP4 expression and localization and delayed impairment of glymphatic function that emerged 28 days following blast injury in a mouse model of repetitive blast mTBI. In a cohort of veterans with blast mTBI, we observed that blast exposure was associated with an increased burden of frontal cortical MRI-visible perivascular spaces, a putative neuroimaging marker of glymphatic perivascular dysfunction. These findings suggest that changes in AQP4 and delayed glymphatic impairment following blast injury may render the post-traumatic brain vulnerable to post-concussive symptoms and chronic neurodegeneration.

Large-scale flank collapses are one of the main hazards associated with the evolution of volcanic islands. Precisely dating such events is critical to evaluate the frequency of destabilization episodes and further assess the triggering mechanism(s) associated with internal and/or external factors, such as volcano dynamics, regional tectonics, and global paleoclimatic changes. Here, we constrain the age of a pumice-rich pyroclastic deposit exposed on the eastern flank of Flores Island (Azores), which we interpret as a co-blast deposit generated by a major flank collapse that destroyed the whole western flank of the former volcanic edifice. Twelve single-grain 40Ar/39Ar analyses, performed on 250-500 µm anorthoclase feldspars (mean K/Ca close to 5) with our high-sensitivity multi-collector NGX mass spectrometer, provide a robust weighted mean age of 1.32 ± 0.01 Ma for this eruption. This new age is consistent with previous K/Ar data bracketing the flank collapse between 1.30 ± 0.04 and 1.18 ± 0.09 Ma, and indicates that this event occurred at the end of the main construction phase of the volcano. The explosion produced pumice-rich layers preceded by a lahar as attested by a polygenetic mudflow deposit underlying the dated deposit. From the geochemistry of lavas erupted just before and after the collapse, we speculate upon the possible role of magmatic processes on flank destabilization. We propose a first hypothesis where differentiation in a shallow magma reservoir could have favored edifice inflation, ground shaking, and flank failure, triggering a decompression-induced violent eruption. Overall, our study shows that high-sensitivity mass spectrometers have now reached analytical performances allowing to measure precisely and accurately ages on relatively small and moderately K-rich single feldspars, which is of the utmost importance for dating heterogeneous blasts and tephra deposits that may have been induced by large-scale flank collapses during the late Quaternary.

BACKGROUND: The species of genus Ageratum (family Asteraceae) are distributed in various parts of the world. Ageratum conyzoides and A. houstonianum are the most commonly occurring species in India. These species are quite similar in their morphology thus creating a challenge in identification during the field survey and taxonomic validation. The accurate identification of the species is highly significant especially when those are of medicinal interest. To overcome the barriers in morphological based identification, DNA barcoding has been employed during the present investigation.
RESULTS: Morphological and DNA barcodes matK and ITS genes, were employed to differentiate between Ageratum conyzoides and A. houstonianum. The obtained matK and ITS gene sequences were submitted to GenBank and BOLD system to obtain accession numbers. The DNA sequences were aligned with database sequences using BLAST and phylogenetic trees were constructed through neighbor-joining algorithm in MEGA 11 software. The distinguish features of A. conyzoides include ovate to elliptic-oblong leaves with a cuneate base and inflorescence heads forming domed to flat-topped clusters. However, A. houstonianum has triangular to ovate leaves with a cordate to truncate base, cymose clusters in the inflorescence and stipulate glandular involucre bracts. The matK gene has shown the highest identity percentages (100%) for A. houstonianum and 99.87% for A. conyzoides. The phylogenetic tree analysis has demonstrated a close association of A. conyzoides and A. houstonianum with their respective species, supported by bootstrap values in the matK and ITS trees.
CONCLUSIONS: This study revealed that morphological and molecular data can be successfully utilized in the identification of A. conyzoides and A. houstonianum. The matK and ITS barcodes provide promising results in the identification of Ageratum species, with their phylogeny supporting classification within the family asteraceae.