Search Results (28)

Introduction: Pathogenic variants in the OFD1 gene are linked to a spectrum of syndromes that exhibit partial clinical overlap. Hemizygous loss-of-function variants are considered lethal in males, while heterozygous loss-of-function variants generally result in oro-facial-digital syndrome type 1. A reported phenotype, Simpson–Golabi–Behmel syndrome type 2, was published once but remains controversial, with many specialists questioning its validity and arguing about its continued listing in the OMIM database. Methods: To investigate the genetic and phenotypic characteristics of the patients, we performed clinical exome sequencing, family-based genetic analysis, X-inactivation studies, electron microscopy, and detailed clinical assessments. Results: Three patients from unrelated families carrying loss-of-function variants in the OFD1 gene were identified, emphasizing the diverse phenotypic spectrum of OFD1-associated disorders. The first patient, a female with a heterozygous frameshift variant p.(Gln398LeufsTer2), was diagnosed with oro-facial-digital syndrome type 1. The second patient, a male with a heterozygous nonsense variant p.(Gln892Ter), presented with features resembling Simpson–Golabi–Behmel syndrome type 2, as previously reported under this diagnosis. The third patient, a male with another heterozygous nonsense variant p.(Glu879Ter), exhibited isolated primary ciliary dyskinesia without any syndromic features. Conclusions: This study contributes to the growing body of evidence on the expanding phenotypic spectrum of OFD1-associated disorders. It underscores the need for further investigation into the molecular mechanisms underlying the diverse presentations and the necessity of re-evaluating diagnostic classifications for conditions such as SGBS2 in the context of variants in the OFD1 gene. Full article

Many techniques adopted by annual crop growers, addressing challenges such as disease, are not viable for perennial systems. Groundcover vegetation can be employed as a natural method for increasing soil health and perennial plant performance; however, cover crop species may differ in the plant–soil feedback effects that modulate the rhizosphere. To investigate the relationship between cover crop identity and soil microbial composition and to determine potential impacts of cover crop species on pathogen occurrence in perennial systems, we characterized the fungal communities in soil sampled from nine cover crop species used for under-vine groundcover at three separate Okanagan vineyards. Soil characteristics, particularly available phosphorus levels, varied significantly among sites, with SuRDC at 39.9 ppm, Covert at 140.1 ppm, and Kalala at 276.2 ppm. Of 1876 fungal species, SuRDC showed lower richness and diversity. A random forest model classified samples by site with 98.4% accuracy (p < 0.001), but cover crop classification was minimal (2.4% accuracy). Phacelia had significantly lower variance in Shannon’s (p = $2.35\times {10}^{-7}$) and Simpson’s diversity (p = $3.59\times {10}^{-12}$). Crescendo ladino clover had simpler fungal networks than buckwheat, with a negative correlation between fungal species count and co-occurrence affinity across cover crops (p < 0.001). We found that within sites, soil fungal communities did not vary greatly in composition and measures of community structure, regardless of cover crop identity. Nectriaceae were abundant across all samples, suggesting that cover crops may recruit certain fungal pathogens. Soil fungal communities were distinct across sites, indicating that site-specific conditions may play a larger role in shaping soil fungal communities in BC vineyards than cover crop–microbe interactions and that cover crops do not have consistent short-term (<1 year) effects on soil fungi across sites. Altogether, this research encourages careful consideration of both groundcover species and site-specific conditions when using cover crops in perennial agriculture. Full article

Background: Our aim was to investigate the predictability of postoperative meningioma resection status based on clinical features. Methods: We examined 23 clinical features to assess their effectiveness in distinguishing gross total resections (GTR) from subtotal resections (STR). We analyzed whether GTR/STR cases are better predictable if the classification is based on the Simpson grading or the postoperative operative tumor volume (POTV). Results: Using a study cohort comprising a total of 157 patients, multivariate models for the preoperative prediction of GTR/STR outcome in relation to Simpson grading and POTV were developed and subsequently compared. Including only two clinical features, our models showed a notable discriminatory power in predicting postoperative resection status. Our final model, a straightforward decision tree applicable in daily clinical practice, achieved a mean AUC of 0.885, a mean accuracy of 0.866, a mean sensitivity of 0.889, and a mean specificity of 0.772 based on independent test data. Conclusions: Such models can be a valuable tool both for surgical planning and for early planning of postoperative treatment, e.g., for additional radiotherapy/radiosurgery, potentially required in case of subtotal resections. Full article

Background: The brain and the intestinal microbiota are highly interconnected and especially vulnerable to disruptions in early life. Emerging evidence indicates that psychosocial adversity detrimentally impacts the intestinal microbiota, affecting both physical and mental health. This study aims to investigate the gut microbiome in young children in the immediate aftermath of maltreatment exposure. Methods: Maltreatment exposure was assessed in 88 children (ages 3–7) using the Maternal Interview for the Classification of Maltreatment [MICM]. Children were allocated to three groups according to the number of experienced maltreatment categories: no maltreatment, low maltreatment, and high maltreatment exposures. Stool samples were collected and analyzed by 16S rRNA sequencing. Results: Children subjected to high maltreatment exposure exhibited lower alpha diversity in comparison to those with both no and low maltreatment exposure (Simpson Index, Tukey post hoc, p = 0.059 and p = 0.007, respectively). No significant distinctions in beta diversity were identified. High maltreatment exposure was associated with the enrichment of several genera from the class Clostridia (Clostridium, Intestinibacter, Howardella and Butyrivibrio) and the depletion of the genus Phocaeicola (class Bacteriodia). Conclusions: Severe maltreatment exposure is associated with alterations in the gut microbiota of young children. Longitudinal trajectories of intestinal microbiota composition in the context of maltreatment may reveal important insights related to psychiatric and somatic health outcomes. Full article

Vegetation biodiversity in mountainous regions is controlled by altitudinal gradients and their corresponding microclimate. Higher temperatures, shorter snow cover periods, and high variability in the precipitation regime might lead to changes in vegetation distribution in mountains all over the world. In this study, we evaluate vegetation distribution along an altitudinal gradient (1334–1667 m.a.s.l.) in the Zao Mountains, northeastern Japan, by means of alpha diversity indices, including species richness, the Shannon index, and the Simpson index. In order to assess vegetation species and their characteristics along the mountain slope selected, fourteen 50 m × 50 m plots were selected at different altitudes and scanned with RGB cameras attached to Unmanned Aerial Vehicles (UAVs). Image analysis revealed the presence of 12 dominant tree and shrub species of which the number of individuals and heights were validated with fieldwork ground truth data. The results showed a significant variability in species richness along the altitudinal gradient. Species richness ranged from 7 to 11 out of a total of 12 species. Notably, species such as Fagus crenata, despite their low individual numbers, dominated the canopy area. In contrast, shrub species like Quercus crispula and Acer tschonoskii had high individual numbers but covered smaller canopy areas. Tree height correlated well with canopy areas, both representing tree size, which has a strong relationship with species diversity indices. Species such as F. crenata, Q. crispula, Cornus controversa, and others have an established range of altitudinal distribution. At high altitudes (1524–1653 m), the average shrubs’ height is less than 4 m, and the presence of Abies mariesii is negligible because of high mortality rates caused by a severe bark beetle attack. These results highlight the complex interactions between species abundance, canopy area, and altitude, providing valuable insights into vegetation distribution in mountainous regions. However, species diversity indices vary slightly and show some unusually low values without a clear pattern. Overall, these indices are higher at lower altitudes, peak at mid-elevations, and decrease at higher elevations in the study area. Vegetation diversity indices did not show a clear downward trend with altitude but depicted a vegetation composition at different altitudes as controlled by their surrounding environment. Finally, UAVs showed their significant potential for conducting large-scale vegetation surveys reliably and in a short time, with low costs and low manpower. Full article

Quantitative classification and ordination are instrumental in improving our understanding of plant community patterns and facilitating effective conservation efforts in national mountain ecosystems worldwide. However, there has been a lack of relevant research focused on arid and semi-arid mountain ecosystems. This study aims to address this gap by investigating the Ningxia Helan Mountain National Nature Reserve (located in Northwest China). We conducted a comprehensive study on the patterns of plant communities and their association with environmental factors across a broad elevation range from 1200 m a.s.l. to 2600 m a.s.l. Our findings revealed the presence of 121 angiosperm species across 41 families, with vegetation classified into six distinct groups through two-way indicator species analysis (TWINSPAN) along the elevational gradient. Notably, the communities of Ulmus, Prunus, and Stipa in the middle elevation range exhibited the highest Shannon–Wiener (SW) and Simpson (SN) diversity indices, and these indices followed a single-peak pattern with increasing elevation. Canonical correspondence analysis (CCA) further revealed six distinct yet interrelated plant communities, revealing elevation (ELE) and the biological aridity index (BK) as the most influential environmental factors influencing plant communities’ distribution. This understanding is critically important for biodiversity conservation and the management of ecosystems in arid and semi-arid mountain ecosystems. Full article

Biodiversity is a characteristic of ecosystems that plays a crucial role in the study of their evolution, and to estimate it, the species of all plants need to be determined. In this study, we used Unmanned Aerial Vehicles to gather RGB images of mid-to-high-altitude ecosystems in the Zao mountains (Japan). All the data-collection missions took place in autumn so the plants present distinctive seasonal coloration. Patches from single trees and bushes were manually extracted from the collected orthomosaics. Subsequently, Deep Learning image-classification networks were used to automatically determine the species of each tree or bush and estimate biodiversity. Both Convolutional Neural Networks (CNNs) and Transformer-based models were considered (ResNet, RegNet, ConvNeXt, and SwinTransformer). To measure and estimate biodiversity, we relied on the Gini–Simpson Index, the Shannon–Wiener Index, and Species Richness. We present two separate scenarios for evaluating the readiness of the technology for practical use: the first scenario uses a subset of the data with five species and a testing set that has a very similar percentage of each species to those present in the training set. The models studied reach very high performances with over 99 Accuracy and 98 F₁ Score (the harmonic mean of Precision and Recall) for image classification and biodiversity estimates under 1% error. The second scenario uses the full dataset with nine species and large variations in class balance between the training and testing datasets, which is often the case in practical use situations. The results in this case remained fairly high for Accuracy at 90.64% but dropped to 51.77% for F₁ Score. The relatively low F₁ Score value is partly due to a small number of misclassifications having a disproportionate impact in the final measure, but still, the large difference between the Accuracy and F₁ Score highlights the complexity of finely evaluating the classification results of Deep Learning Networks. Even in this very challenging scenario, the biodiversity estimation remained with relatively small (6–14%) errors for the most detailed indices, showcasing the readiness of the technology for practical use. Full article

This study aimed to investigate the effect of an essential oil/fumaric combination, mannan-oligosaccharide, galactooligosaccharide, and a mannan-oligosaccharide/galactooligosaccharide combination on the dry matter disappearance (DMD), gas production, greenhouse gasses, volatile fatty acid, and microbial community of a total mixed ration using a 24 h in vitro batch culture technique. The study design was a completely randomized design with four treatments as follows: a control treatment without any additives, the control treatment supplemented with galactooligosaccharide at 3% (Gos treatment), a galactooligosaccharide and mannan-oligosaccharide mixture at 1:1 at 3% (Gosmos treatment), or an essential oil blend (200 μL/g feed) and fumaric acid at 3% combination (Eofumaric treatment). The Gosmos treatment had the highest (p < 0.05) DMD (63.8%) and the numerical lowest acetate–propionate ratio (p = 0.207), which was 36.9% higher compared to the control. The lowest Shannon index, Simpson’s index, and all the diversity indices were recorded for the Eofumaric treatment, while the other treatments had similar Shannon index, Simpson’s index, and diversity index. The Z-score differential abundance between the Eofumaric and the control indicated that the inclusion of the Eofumaric treatment differentially increased the abundance of Patescibacteria, Synergistota, Chloroflexi, Actinobacteriota, Firmicutes, and Euryarchaeota while Verrucomicrobiota, WPS-2, Fibrobacterota, and Spirochaetota were decreased. The Random Forest Classification showed that the lower relative abundance of Fibrobacterota, Spirochaetota, and Elusimicrobiota and the higher relative abundance of Firmicutes and Chloroflexi were most impactful in explaining the microbial community data. Overall, the essential oil blend showed great potential as a methane gas mitigation strategy by modifying rumen fermentation through changes in the microbial community dynamics. Full article

Taxonomic classification using metabarcoding is a commonly used method in microbiological studies of environmental samples and during monitoring of biotechnological processes. However, it is difficult to compare results from different laboratories, due to the variety of bioinformatics tools that have been developed and used for data analysis. This problem is compounded by different choices regarding which variable region of the 16S rRNA gene and which database is used for taxonomic identification. Therefore, this study employed the DADA2 algorithm to optimize the preprocessing of raw data obtained from the sequencing of activated sludge samples, using simultaneous analysis of three frequently used regions of 16S rRNA (V1–V3, V3–V4, V4–V5). Additionally, the study evaluated which variable region and which of the frequently used microbial databases for taxonomic classification (Greengenes2, Silva, RefSeq) more accurately classify OTUs into taxa. Adjusting the values of selected parameters of the DADA2 algorithm, we obtained the highest possible numbers of OTUs for each region. Regarding biodiversity within regions, the V3–V4 region had the highest Simpson and Shannon indexes, and the Chao1 index was similar to that of the V1–V3 region. Beta-biodiversity analysis revealed statistically significant differences between regions. When comparing databases for each of the regions studied, the highest numbers of taxonomic groups were obtained using the SILVA database. These results suggest that standardization of metabarcoding of short amplicons may be possible. Full article

The essential oils of Juniperus are highly beneficial medicinally. The present study aimed to assess the chemodiversity and bioactivity of Juniperus formosana, Juniperus przewalskii, Juniperus convallium, Juniperus tibetica, Juniperus komarovii, and Juniperus sabina essential oils from the Qinghai-Tibet Plateau. The results revealed 92 components in six essential oils: α-pinene (2.71–17.31%), sabinene (4.91–19.83%), and sylvestrene (1.84–8.58%) were the main components. Twelve components were firstly reported in Juniperus oils, indicating that the geographical location and climatic conditions of the Qinghai-Tibet Plateau produced the unique characteristics of Juniperus essential oils. The chemodiversity of Juniperus essential oils varied greatly, with J. sabina having the most recognized components (64) and the highest chemodiversity (Shannon–Wiener index of 3.07, Simpson’s diversity index of 0.91, and Pielou evenness of 0.74). According to the chemodiversity of essential oils, the six plants were decided into the α-pinene chemotype (J. formosana), hedycaryol chemotype (J. przewalskii, J. komarovii, J. convallium, J. tibetica), and sabinene chemotype (J. sabina). PCA, HCA and OPLS-DA showed that J. formosana and J. sabina were distantly related to other plants, which provides a chemical basis for the classification of Juniperus plants. Furthermore, bioactivity tests exhibited certain antioxidant and antibacterial effects in six Juniperus oils. And the bioactivities of J. convallium, J. tibetica, and J. komarovvii were measured for the first time, broadening the range of applications of Juniperus. Correlation analysis of components and bioactivities showed that δ-amorphene, β-udesmol, α-muurolol, and 2-nonanone performed well in the determination of antioxidant activity, and α-pinene, camphene, β-myrcene, as well as (E)-thujone, had strong inhibitory effects on pathogenic bacteria, providing a theoretical basis for further research on these components. Full article

Meningiomas have the highest incidence among brain tumors. In contrast to benign tumors that constitute the majority of this tumor entity, the treatment of aggressive meningiomas (WHO Grade 2 and 3) is more challenging, requiring gross total removal of the tumor and the affected dura and adjuvant radiotherapy. Sometimes the location and/or the configuration of the tumor do not favor radical surgical resection without endangering the patient’s clinical condition after surgery and pharmacological therapy has, until now, not been proven to be a reliable alternative. Discussion: In this narrative review, we discuss the current literature with respect to the management of meningiomas, discussing the importance of the grade of resection in the overall prognosis of the patient and in the planning of adjuvant therapy. Conclusions: According to the location and size of the tumor, radical resection should be taken into consideration. In patients with aggressive meningiomas, adjuvant radiotherapy should be performed after surgery. In cases of skull base meningiomas, a maximal, though safe, resection should take place before adjuvant therapy. An interdisciplinary approach is beneficial for patients with primary or recurrent meningioma. Full article

Background: There is currently no consensus in the field regarding whether a frontal or lateral approach is superior for microsurgical resection of olfactory groove meningiomas (OGM). Due to the lack of uniformity in classifying lesions and inherent differences in reporting outcomes after varying operative approaches, the best practice for approaching these lesions is yet to be determined. Objective: This study aimed to assess various surgical approaches undertaken for OGMs, investigate procedural aspects influencing the extent of resection, and analyze the respective complication rate associated with each approach. We performed a comprehensive literature review of presenting signs and symptoms in OGM patients, their surgical management, and the reported surgical outcomes. To address the lack of uniform data reporting across studies and to take more recent translational studies into account, we developed a new classification system for OGMs that can remedy the existing deficiencies in comparability of reporting. Methods: We conducted a PRISMA-guided literature search for surgical reports on OGMs published in the MRI era using broad search terms such as ‘olfactory groove meningioma’ and ‘surgery’, which yielded 20,672 results. After title screening and removal of duplicates, we assessed 871 studies on the specific surgical management of olfactory groove meningiomas. Following the application of exclusion criteria and abstract screening, a set of 27 studies was chosen for the final analysis of a pooled cohort of these reported patient outcomes. Results: The final twenty-seven studies included in our in-depth analysis identified a total of 1016 individual patients who underwent open microsurgical resection of OGMs. The approaches used included: pterional/unilateral, bifrontal with variations, and anterior interhemispheric approaches. Across all studies, gross total resection (Simpson Grades I or II) was achieved in 91.4% of cases, and subtotal resection (Grades III and IV) was reported in 8.6% of cases. A cumulative twenty-seven percent of surgical OGM patients sustained some form of complications. Minor issues accounted for 22.2% (CSF leak, seizures, infection, transient cranial nerve palsies, hydrocephalus), whereas major issues comprised 4.7% (hemorrhage, ischemic infarct, malignant cerebral edema). We then examined the correlation between these complications and the surgical approach chosen. Among pooled cohort of 426 patients who underwent unilateral approaches, 14% experienced minor complications, and 2.1% experienced major complications. For the mixed cohort of 410 patients who underwent bifrontal approaches, 24.6% experienced minor complications, and 7% experienced major complications. Conclusions: Unilateral approaches appear to have lower complication rates for the resection of OGMs compared to bilateral approaches. However, the extent of resection is not uniformly reported, making it difficult to identify differences. The use of an improved preoperative classification and scoring system can help establish a more coherent system to select the most suitable approach and to uniformly report surgical outcomes, such as EOR and complication rates specific to a given OGM and its surgical approach. Full article

The coast of the Red Sea in Jeddah City is home to a unique microbial community that has adapted to extreme environmental conditions. Therefore, it is essential to characterize the microbial community in this unique microbiome to predict how environmental changes will affect it. The aim of this study was to conduct metagenomic sequencing of 16S rRNA and ITS rRNA genes for the taxonomic classification of the microbial community in soil samples associated with the halophytic plants Tamarix aphylla and Halopeplis perfoliata. Fifteen soil samples were collected in triplicate to enhance robustness and minimize sampling bias. Firstly, to identify novel microbial candidates, the gDNAs were isolated from the saline soil samples surrounding each plant, and then bacterial 16S (V3–V4) and fungal ITS1 regions were sequenced utilizing a high-throughput approach (next-generation sequencing; NGS) on an Illumina MiSeq platform. Quality assessment of the constructed amplicon libraries was conducted using Agilent Bioanalyzer and fluorometric quantification methods. The raw data were processed and analyzed using the Pipeline (Nova Lifetech, Singapore) for bioinformatics analysis. Based on the total number of readings, it was determined that the phylum Actinobacteriota was the most prevalent in the soil samples examined, followed by the phylum Proteobacteria. Based on ITS rRNA gene analysis, the alpha and beta fungal diversity in the studied soil samples revealed that the fungal population is structured into various groups according to the crust (c) and/or rhizosphere (r) plant parts. Fungal communities in the soil samples indicated that Ascomycota and Basidiomycota were the two most abundant phyla based on the total amount of sequence reads. Secondly, heat-map analysis of the diversity indices showed that the bacterial alpha diversity, as measured by Shannon, Simpson, and InvSimpson, was associated with soil crust (Hc and Tc enclosing H. perfoliata and T. aphylla, respectively) and that the soil rhizosphere (Hr and Tr) was strongly correlated with bacterial beta diversity. Finally, fungal-associated Tc and Hc samples clustered together, according to observations made using the Fisher and Chao1 methods, and Hr and Tr samples clustered together according to Shannon, Simpson, and InvSimpson analyses. As a result of the soil investigation, potential agents that have been identified could lead to innovative agricultural, medical, and industrial applications. Full article

This study aimed to identify the oral microbial signature of Kazakh female rheumatoid arthritis (RA) patients. A total of 75 female patients who met the American College of Rheumatology 2010 classification criteria for RA and 114 healthy volunteers were included in the study. Amplicons of the 16S rRNA gene were sequenced to analyze the microbial composition. We identified significant differences in bacterial diversity and abundance between the RA and control groups, as measured by Shannon (p value = 0.0205) and Simpson (p value = 0.00152) indices. The oral samples from RA patients had higher bacterial diversity than those from non-RA volunteers. The RA samples had a higher relative abundance of Prevotellaceae and Leptotrichiaceae, but a lower content of butyrate and propionate-producing bacteria compared to the control group. The samples from patients in remission had a higher abundance of Treponema sp. and Absconditabacteriales (SR1), whereas those with low disease activity had higher levels of Porphyromonas and those with high RA activity had higher levels of Staphylococcus. A positive correlation was found between the taxa Prevotella_9 and serum levels of antibodies to cyclic citrullinated peptide (ACPA) and rheumatoid factor (RF). The predicted functional pattern of the ACPA+/RF− and ACPA+/RF+ seropositive groups was characterized by increased ascorbate metabolism, degradation of glycosaminoglycans, and reduced biodegradation of xenobiotics. These findings suggest that the functional pattern of the microflora should be considered when selecting a therapeutic strategy for RA in order to provide a personalized approach. Full article

Left ventricular ejection fraction (LVEF) is a key parameter in evaluating left ventricular (LV) function using echocardiography (Echo), but its manual measurement by the modified biplane Simpson (MBS) method is time consuming and operator dependent. We investigated the feasibility of a server-based, commercially available and ready-to use-artificial intelligence (AI) application based on convolutional neural network methods that integrate fully automatic view selection and measurement of LVEF from an entire Echo exam into a single workflow. We prospectively enrolled 1083 consecutive patients who had been referred to Echo for diagnostic or therapeutic purposes. LVEF was measured independently using MBS and AI. Test–retest variability was assessed in 40 patients. The reliability, repeatability, and time efficiency of LVEF measurements were compared between the two methods. Overall, 889 Echos were analyzed by cardiologists with the MBS method and by the AI. Over the study period of 10 weeks, the feasibility of both automatic view classification and seamlessly measured LVEF rose to 81% without user involvement. LVEF, LV end-diastolic and end-systolic volumes correlated strongly between MBS and AI (R = 0.87, 0.89 and 0.93, p < 0.001 for all) with a mean bias of +4.5% EF, −12 mL and −11 mL, respectively, due to impaired image quality and the extent of LV function. Repeatability and reliability of LVEF measurement (n = 40, test–retest) by AI was excellent compared to MBS (coefficient of variation: 3.2% vs. 5.9%), although the median analysis time of the AI was longer than that of the operator-dependent MBS method (258 s vs. 171 s). This AI has succeeded in identifying apical LV views and measuring EF in one workflow with comparable results to the MBS method and shows excellent reproducibility. It offers realistic perspectives for fully automated AI-based measurement of LVEF in routine clinical settings. Full article