Consanguinity and Occurrence of Monogenic Diseases in a Single Tertiary Centre in Riyadh, Saudi Arabia: A 2 Years Cross-Sectional Study.

Background: Consanguinity, or the practice of marrying close relatives, is a common cultural tradition in Saudi Arabia, with rates among the highest in the world. This practice has significant implications for the prevalence and distribution of major single genetic defects and chromosomal abnormalities within the Saudi population. Methods: Herein, using the BESTCare electronic medical record system (designed to streamline hospital operations, enhance patient care, and improve the overall efficiency of healthcare services; bestcare.ezcaretech.com) in a single tertiary centre, King Abdullah Specialized Children Hospital (KASCH) in Riyadh, Saudi Arabia, we performed a cross-sectional study for all patients referred to the hospital from the 1st January 2020 until 1st January 2022. Results: The present study, which included 1100 individuals, found a high prevalence of consanguinity (64%) and a significant proportion of third-degree relatives (69%). The mean age of participants was 12.24 years, and the diagnostic rate using advanced molecular genetics techniques was 45%, with whole exome sequencing (WES) being the most common method (43%). The study also noted a significant delay in diagnosis for more than a year in 16% of cases, with a common neurodevelopmental phenotype (18%). Conclusion: In conclusion, we revealed the prevalence of consanguineous marriages in the KASCH hospital in Riyadh, Saudi Arabia. We also highlighted the most frequently referred phenotype. These findings are consistent with previous research on the prevalence and impact of consanguinity on rare genetic disorders.

Quality Assessment of Periapical Radiographs Taken by Dental Assistants Using the Recent Faculty of General Dental Practice (FGDP) Guidelines.

BACKGROUND: Periapical radiographs play a pivotal role in dentistry, offering invaluable insights essential for various dental procedures. OBJECTIVE: This study aims to systematically assess the quality of intraoral periapical (IOPA) radiographs evaluating adherence to the recent guidelines established by the Faculty of General Dental Practice (FGDP). METHODS: A cross-sectional study was conducted at the University College of Dentistry (UCD), employing a non-probability consecutive sampling technique to acquire a calculated sample of 300 IOPA radiographs from the operative, oral surgery, and oral radiology departments. Two senior faculty members evaluated the radiographs according to the recent two-tier grading system outlined in the FGDP guidelines. RESULTS: The study revealed that 197 (65.67%) of the assessed radiographs were diagnostically acceptable, while 103 (34.33%) were deemed diagnostically unacceptable. Contrast problems emerged as the most prevalent issue, accounting for 85 (28.3%) of the cases. Other common problems included incorrect film positioning in 66 (22%), incorrect vertical cone angulation in 37 (12.3%), incorrect horizontal cone angulation in 11 (3.7%), and incorrect processing in 15 (5%) of the IOPA radiographs. CONCLUSION: This study revealed that approximately two-thirds of the IOPA radiographs were deemed diagnostically acceptable. However, contrast issues emerged as the predominant concern affecting image quality. These findings highlight the critical importance of continuous quality improvement initiatives in radiographic practices to enhance diagnostic precision and ensure optimal patient care.

A novel CLRN2 variant: expanding the mutation spectrum and its critical role in isolated hearing impairment.

BACKGROUND: Biallelic variants in the CLRN2 gene have been reported to cause autosomal recessive profound hearing impairment in humans. CLRN2 belongs to the clarin gene family that encodes a tetraspan protein that contains a cytosolic N-terminus, multiple helical transmembrane domains, and an endoplasmic reticulum membrane retention signal, TKGH, in the C-terminus. The encoded protein may be important in development and homeostasis of the inner ear and retina. METHODS: Here, we present a consanguineous family suffering from autosomal recessive non-syndromic profound hearing impairment (HI). We employed state of the art Whole exome sequencing (WES), Sanger sequencing followed by routine bioinformatics filtration steps and homology modeling to elucidate the effect of mutation at the protein level. RESULTS: ES followed by Sanger sequencing revealed a novel homozygous nonsense variant in the CLRN2 gene [c.414 C > A; p.Cys138*]. Furthermore, insilico protein modeling of the wildtype and mutated version of the CLRN2 protein revealed large-scale changes that predict to compromise the routine normal function of the protein. CONCLUSION: Our finding further extends the mutations spectrum of CLRN2 gene and confirms its important role in hearing homeostasis and with developmental disorder in humans.

Elucidating the clinical and genetic spectrum of inositol polyphosphate phosphatase INPP4A-related neurodevelopmental disorder.

PURPOSE: Biallelic INPP4A variants have recently been associated with severe neurodevelopmental disease in single case reports. Here, we expand and elucidate the clinical-genetic spectrum and provide a pathomechanistic explanation for genotype-phenotype correlations. METHODS: Clinical and genomic investigations of 30 individuals were undertaken alongside molecular and in silico modelling and translation reinitiation studies. RESULTS: We characterize a clinically variable disorder with cardinal features including global developmental delay, severe-profound intellectual disability, microcephaly, limb weakness, cerebellar signs and short stature. A more severe presentation associated with biallelic INPP4A variants downstream of exon 4 has additional features of (ponto)cerebellar hypoplasia, reduced cerebral volume, peripheral spasticity, contractures, intractable seizures and cortical visual impairment. Our studies identify the likely pathomechanism of this genotype-phenotype correlation entailing translational reinitiation in exon 4 resulting in an N-terminal truncated INPP4A protein retaining partial functionality, associated with less severe disease. We also identified identical reinitiation site conservation in Inpp4a-/- mouse models displaying similar genotype-phenotype correlation. Additionally, we show fibroblasts from a single affected individual exhibit disrupted endocytic trafficking pathways, indicating the potential biological basis of the condition. CONCLUSION: Our studies comprehensively characterise INPP4A-related neurodevelopmental disorder and suggest genotype-specific clinical assessment guidelines. We propose the potential mechanistic basis of observed genotype-phenotype correlations entails exon 4 translation reinitiation.

Polluting industries: Does green industrial policy encourage green innovation? Chinese perspective evidence.

This study investigates the efficacy of green industrial policies in stimulating green innovation within China's polluting industries, over the period 2011-2022. Focusing on 30 provinces, we assess the dynamic relationship between green industrial policy implementation and innovation in environmentally detrimental sectors. Employing Difference-in-Differences (DID) and Propensity Score Matching DID (PSM-DID) models, we analyze comprehensive provincial-level data to quantify the impact of policy measures on green technological advancements. The results reveal a significant positive correlation between green industrial policies and the rate of green innovation, particularly in regions with higher pollution levels. These findings suggest that well-structured green industrial policies can serve as effective catalysts for fostering sustainable technological innovations in polluting industries. Policy implications highlight the necessity of targeted, region-specific approaches to maximize the potential of green industrial policies in promoting environmental sustainability and economic growth.

The genetic cause of neurodevelopmental disorders in 30 consanguineous families.

Objective: This study aims to clinically and genetically assess 30 unrelated consanguineous Pakistani families from various ethnic backgrounds, all exhibiting features of neurodevelopmental disorders (NDDs). Methods: We conducted clinical, genetic, biochemical, and molecular analyses on 30 consanguineous families with NDDs enrolled from various regions of Pakistan. The likely molecular causes of primary microcephaly and NDDs were identified. Detailed clinical investigations and molecular diagnoses were performed using whole exome sequencing (WES) of the proband, followed by Sanger sequencing for validation and segregation in the available family members of the affected families. Results: WES identified likely disease-causing homozygous variants in 30 unrelated consanguineous families. Six families presented newly described variants in known NDD-related genes: ABAT (c.1439 T > G; p.Phe480Cys) [OMIM613163], SLC12A6 (c.2865_2865insT; p.Glu955Asnfs*5) [OMIM 218000], SHANK3 (c.1305-3_1,305-2delTT; p.Gln29-_Gly305del) [OMIM 606232], BCKDK (c.356_356insC; p.Gly119Alafs*24) [OMIM 614923], DDHD2 (c.2065G > T; p.Asp689Tyr) [OMIM 615033], ERCC2 (c.1255G > A; p.Glu419Lys) [OMIM 610756]. Additionally, 12 families had previously reported disease-causing variants associated with different types of NDDs: ATRX (c.109C > T; p.Arg37*) [OMIM 309580], GPR56 [ADGRG1] (c.1423C > T; p.Arg475*) [OMIM 606854], NAGLU (c.1694G > A; p.Arg565Gln) [OMIM 252920], DOLK (c.3G > A; p.Met1Ile) [OMIM 610768], GPT2 (c.815C > T; p.Ser272Leu) [OMIM 616281], DYNC1I2 (c.607 + 1G > A; p.?) [OMIM 618492], FBXL3 (c.885delT; p.Leu295Phefs25*) [OMIM 606220], LINGO1 (c.869G > A; p.Arg290His) [OMIM 618103], and ASPM (c.3978G > A; Trp1326*, c.9557C > G; p.Ser3186*, c.6994C > T; p.Arg2332*) [OMIM 608716]. All the identified variants showed segregation compatible with autosomal recessive inheritance. Conclusion: In the present study, we observed a high frequency of ASPM variants in the genetic analysis of 30 consanguineous families exhibiting features of NDDs, particularly those associated with autosomal recessive primary microcephaly. These findings contribute to studies on genotype-phenotype correlation, genetic counseling for families, and a deeper understanding of human brain function and development.

Accounting for regression to the mean under the bivariate t-distribution.

Regression to the mean occurs when an unusual observation is followed by a more typical outcome closer to the population mean. In pre- and post-intervention studies, treatment is administered to subjects with initial measurements located in the tail of a distribution, and a paired sample t-test can be utilized to assess the effectiveness of the intervention. The observed change in the pre-post means is the sum of regression to the mean and treatment effects, and ignoring regression to the mean could lead to erroneous conclusions about the effectiveness of the treatment effect. In this study, formulae for regression to the mean are derived, and maximum likelihood estimation is employed to numerically estimate the regression to the mean effect when the test statistic follows the bivariate t-distribution based on a baseline criterion or a cut-off point. The pre-post degrees of freedom could be equal but also unequal such as when there is missing data. Additionally, we illustrate how regression to the mean is influenced by cut-off points, mixing angles which are related to correlation, and degrees of freedom. A simulation study is conducted to assess the statistical properties of unbiasedness, consistency, and asymptotic normality of the regression to the mean estimator. Moreover, the proposed methods are compared with an existing one assuming bivariate normality. The p-values are compared when regression to the mean is either ignored or accounted for to gauge the statistical significance of the paired t-test. The proposed method is applied to real data concerning schizophrenia patients, and the observed conditional mean difference called the total effect is decomposed into the regression to the mean and treatment effects.

Generative Artificial Intelligence: Enhancing Patient Education in Cardiovascular Imaging.

Cardiovascular disease (CVD) is a major cause of mortality worldwide, especially in resource-limited countries with limited access to healthcare resources. Early detection and accurate imaging are vital for managing CVD, emphasizing the significance of patient education. Generative artificial intelligence (AI), including algorithms to synthesize text, speech, images, and combinations thereof given a specific scenario or prompt, offers promising solutions for enhancing patient education. By combining vision and language models, generative AI enables personalized multimedia content generation through natural language interactions, benefiting patient education in cardiovascular imaging. Simulations, chat-based interactions, and voice-based interfaces can enhance accessibility, especially in resource-limited settings. Despite its potential benefits, implementing generative AI in resource-limited countries faces challenges like data quality, infrastructure limitations, and ethical considerations. Addressing these issues is crucial for successful adoption. Ethical challenges related to data privacy and accuracy must also be overcome to ensure better patient understanding, treatment adherence, and improved healthcare outcomes. Continued research, innovation, and collaboration in generative AI have the potential to revolutionize patient education. This can empower patients to make informed decisions about their cardiovascular health, ultimately improving healthcare outcomes in resource-limited settings.

Adversarial Training Based Domain Adaptation of Skin Cancer Images.

Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were performed using two different domain adaptation architectures. The domain adversarial neural network with two gradient reversal layers and VGG13 as a feature extractor achieved the highest accuracy and F1 score of 0.7567 and 0.75, respectively, representing an 18.47% improvement in accuracy over the baseline model.

Biallelic HMGXB4 loss-of-function variant causes intellectual disability, developmental delay, and dysmorphic features.

Background: HMGXB4 (additionally known as HMG2L1) is a non-histone DNA-binding protein that contains a single HMG-box domain. HMGXB4 was originally described in Xenopus where it was seen to negatively regulate the Wnt/ß-catenin signaling pathway. Materials and methods: In this study, we conducted a genetic and clinical evaluation of a single family with three affected individuals suffering from intellectual disability (ID), global developmental delay (GDD) and dysmorphic facial features.Whole genome sequencing (WGS) and Sanger sequencing were performed on the affected individuals' DNA to identify genetic variations. Additionally, a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to assess gene expression in both the affected and unaffected individuals in the family. Result: WGS identified a homozygous frameshift variant c.1193_1196del p. (Lys398Argfs × 25) in exon 5 of the HMGXB4 gene (OMIM 604702), which completely segregated the disease phenotype in the family. Furthermore, RT-qPCR revealed a substantial decrease in the HMGXB4 gene expression in the affected individuals as compared to the unaffected individuals of the family. Conclusions: The current study is the first evidence linking a genetic variant in the HMGXB4 gene to ID, GDD, and dysmorphic facial features. Therefore, it is possible that HMGXB4 contributes significantly to developmental milestones and may be responsible for neurodevelopmental disorders in humans.

Delineating the Disease Boundaries: Homozygous CDC14A Variants Underlying Nonsyndromic Hearing Loss and Hearing Impairment Infertile Male Syndrome.

Background: Hereditary hearing loss is a genetically heterogeneous neurosensory disorder that affects many people. Deafness and infertility can coexist in some cases, creating the hearing impairment infertile male syndrome. There are several known molecular mechanisms that can cause deafness either on its own or in conjunction with infertility. Methods and Results: Here, we represent two consanguineous families (A, B), both families had clinical evidence of deafness, and family B also had infertility, so we referred to them as having nonsyndromic hearing loss (NSHL) and hearing impairment infertile male syndrome (HIIMS), respectively. These families' genetic makeup was examined using an Affymetrix GeneChip 250K Nsp array followed by Sanger sequencing. In family A, we identified a novel homozygous stop gain variant [NM_003672.4; c.1000C>T; p.(Gln334*)] and a homozygous missense variant [NM_003672.4; c.684C>A; p.(Asn228Lys)] in family B in CDC14A gene (MIM#603504). In animal models, the CDC14A gene causes both hearing loss and infertility; in addition, it also causes NSHL and HIIMS in humans. Conclusions: Our study on the CDC14A gene has identified two novel variants, crucial for delineating disease boundaries. Variants in exon 10 and upstream cause HIIMS, and those in exon 11 and downstream are linked exclusively to hearing impairment. This precision enhances diagnostics and offers potential for targeted interventions, marking a significant advancement in understanding the genetic basis of these conditions.

Effect of biochar amendment on bacterial community and their role in nutrient acquisition in spinach (Spinacia oleracea L.) grown under elevated CO2.

Global climate change is anticipated to shift the soil bacterial community structure and plant nutrient utilization. The use of biochar amendment can positively influence soil bacterial community structure, soil properties, and nutrient use efficiency of crops. However, little is known about the underlying mechanism and response of bacterial community structure to biochar amendment, and its role in nutrient enhancement in soil and plants under elevated CO2. Herein, the effect of biochar amendment (0, 0.5, 1.5%) on soil bacterial community structure, spinach growth, physiology, and soil and plant nutrient status were investigated under two CO2 concentrations (400 and 600 µmol mol-1). Findings showed that biochar application 1.5% (B.2.E) significantly increased the abundance of the bacterial community responsible for growth and nutrient uptake i.e. Firmicutes (42.25%) Bacteroidetes (10.46%), and Gemmatimonadetes (125.75%) as compared to respective control (CK.E) but interestingly abundance of proteobacteria decreased (9.18%) under elevated CO2. Furthermore, the soil available N, P, and K showed a significant increase in higher biochar-amended treatments under elevated CO2. Spinach plants exhibited a notable enhancement in growth and photosynthetic pigments when exposed to elevated CO2 levels and biochar, as compared to ambient CO2 conditions. However, there was variability observed in the leaf gas exchange attributes. Elevated CO2 reduced spinach roots and leaves nutrient concentration. In contrast, the biochar amendment (B2.E) enhanced root and shoot Zinc (494.99%-155.33%), magnesium (261.15%-183.37%), manganese (80.04%-152.86%), potassium (576.24%-355.17%), calcium (261.88%-165.65%), copper (325.42%-282.53%) and iron (717.63%-177.90%) concentration by influencing plant physiology and bacterial community. These findings provide insights into the interaction between plant and bacterial community under future agroecosystems in response to the addition of biochar contributing to a deeper understanding of ecological dynamics.

Pioneers of progress: Documenting the legacy of underrepresented radiologists.

PURPOSE: This study aims to illuminate the enduring contributions of underrepresented pioneers in radiology, emphasizing their resilience, innovations, and the significant barriers they overcame. By weaving their achievements into the broader narrative of medical science, this research highlights the critical role of diversity and progress in the evolution of radiology. HISTORICAL EXPLORATION: This narrative review chronicles the significant contributions of underrepresented radiologists from the early 20th century to the present. By synthesizing historical data, biographical sketches, and contemporary medical literature, we highlight the pivotal roles these pioneers have played in advancing radiology. Their groundbreaking work not only enhanced medical imaging technologies and practices but also championed the cause of diversity and inclusion within the field. These stories of perseverance and innovation underscore the ongoing need for an inclusive approach in the medical community, reflecting on how diversity has shaped and will continue to influence the evolution of radiology. FINDINGS AND CONCLUSION: The study identifies several pivotal figures, such as Marcus F. Wheatland, the first known African American radiologist, and Ivy O. Roach Brooks, the first woman to lead a radiology department at a major U.S. hospital. It explores their wide-ranging contributions from clinical practice and education to leadership and advocacy for diversity within the medical profession. The legacies of these radiologists illuminate not just their individual accomplishments but also reflect the broader struggle for equality and representation in the medical field. Their determination and excellence have paved the way for future generations, significantly enhancing the inclusivity and diversity of the radiology field. CLINICAL RELEVANCE AND APPLICATION: Understanding the contributions of these underrepresented radiologists enriches the field's perspective on diversity, equity, and inclusion. Highlighting these pioneers underscores the importance of mentorship, representation, and advocacy in creating an environment where all talented individuals can thrive. Insights from this historical analysis are crucial for shaping future policies and practices in radiology and medical education, ensuring the continuation of these trailblazers' inspiring legacy.

Variants of NAV3, a neuronal morphogenesis protein, cause intellectual disability, developmental delay, and microcephaly.

Microtubule associated proteins (MAPs) are widely expressed in the central nervous system, and have established roles in cell proliferation, myelination, neurite formation, axon specification, outgrowth, dendrite, and synapse formation. We report eleven individuals from seven families harboring predicted pathogenic biallelic, de novo, and heterozygous variants in the NAV3 gene, which encodes the microtubule positive tip protein neuron navigator 3 (NAV3). All affected individuals have intellectual disability (ID), microcephaly, skeletal deformities, ocular anomalies, and behavioral issues. In mouse brain, Nav3 is expressed throughout the nervous system, with more prominent signatures in postmitotic, excitatory, inhibiting, and sensory neurons. When overexpressed in HEK293T and COS7 cells, pathogenic variants impaired NAV3 ability to stabilize microtubules. Further, knocking-down nav3 in zebrafish led to severe morphological defects, microcephaly, impaired neuronal growth, and behavioral impairment, which were rescued with co-injection of WT NAV3 mRNA and not by transcripts encoding the pathogenic variants. Our findings establish the role of NAV3 in neurodevelopmental disorders, and reveal its involvement in neuronal morphogenesis, and neuromuscular responses.

Estimation of Prediction Intervals for Performance Assessment of Building Using Machine Learning.

This study utilizes artificial neural networks (ANN) to estimate prediction intervals (PI) for seismic performance assessment of buildings subjected to long-term ground motion. To address the uncertainty quantification in structural health monitoring (SHM), the quality-driven lower upper bound estimation (QD-LUBE) has been opted for global probabilistic assessment of damage at local and global levels, unlike traditional methods. A distribution-free machine learning model has been adopted for enhanced reliability in quantifying uncertainty and ensuring robustness in post-earthquake probabilistic assessments and early warning systems. The distribution-free machine learning model is capable of quantifying uncertainty with high accuracy as compared to previous methods such as the bootstrap method, etc. This research demonstrates the efficacy of the QD-LUBE method in complex seismic risk assessment scenarios, thereby contributing significant enhancement in building resilience and disaster management strategies. This study also validates the findings through fragility curve analysis, offering comprehensive insights into structural damage assessment and mitigation strategies.

Exploring sustainable healthcare: Innovations in health economics, social policy, and management.

The healthcare sector faces several challenges, such as rising costs, rising demand, and the need for sustainability. A new area of healthcare has emerged due to these problems, focusing on long-term improvements in management, social policy, and health economics. This research explores the cutting edge of healthcare, concentrating on long-term advancements in management, social policy, and health economics. To better understand the problems affecting the healthcare sector and to pinpoint the areas where sustainable solutions are most required, a survey of 2000 healthcare professionals and policymakers was performed. The data were analyzed using structural equation modeling (SEM), and a thorough sustainable healthcare model was created. According to the survey's findings, the healthcare sector now faces three significant challenges: growing prices, increased demand, and the need for sustainability. According to the respondents, the three main areas where sustainable innovations are most required are management, social policy, and health economics. These conclusions were supported by the (SEM) analysis, which also showed that sustainable practices in these fields significantly impact the sustainability of the healthcare system. These findings lead this research to conclude that to guarantee the accessibility and affordability of healthcare for everyone, a move towards sustainable practices in health economics, social policy, and management is needed. Cooperation between healthcare providers, policymakers, and other stakeholders is required to create creative solutions that support sustainability in the healthcare sector. This study offers a thorough framework for sustainable healthcare that may act as a guide for further research and the formulation of new regulations.

Mutated neuron navigator 3 as a candidate gene for a rare neurodevelopmental disorder.

BACKGROUND: Neuron navigator 3 (NAV3) is characterized as one of the neuron navigator family (NAV1, NAV2, NAV3) proteins predominantly expressed in the nervous system. The NAV3-encoded protein comprises a conserved AAA and coiled-coil domains characteristic of ATPases, which are associated with different cellular activities. METHODS: We describe a Saudi proband presenting a complex recessive neurodevelopmental disorder (NDD). Whole exome sequencing (WES) followed by Sanger sequencing, 3D protein modeling and RT-qPCR was performed. RESULTS: WES revealed a bi-allelic frameshift variant (c.2604_2605delAG; p.Val870SerfsTer12) in exon 12 of the NAV3 gene. Furthermore, RT-qPCR revealed a significant decrease in the NAV3 mRNA expression in the patient sample, and 3D protein modeling revealed disruption of the overall secondary structure. CONCLUSION: For the time, we associate a bi-allelic variant in the NAV3 gene causing NDD in humans.

Efficient Photocatalytic Partial Oxidation of Aromatic Alcohols by Using ZnIn2S4 under Green Conditions.

The ternary chalcogenide ZnIn2S4 (ZIS) has been synthesized by a simple hydrothermal method in which the carcinogen thiacetamide, universally used as a precursor, has been, for the first time, replaced successfully with the harmless thiourea. ZIS has been used as photocatalyst for the partial oxidation of different aromatic alcohols to their corresponding aldehyde in water solution, under ambient conditions and simulated solar light irradiation. The photocatalytic performance of ZnIn2S4 was better than TiO2 P25. In the presence of ZIS for 4-methoxybenzyl alcohol, piperonyl alcohol, and benzyl alcohol, a selectivity towards the corresponding aldehyde of 99 % for a conversion of 46 %, 75 % for a conversion of 81 %, and 87 % for a conversion of 25 %, respectively, was obtained. For the same alcohols a selectivity of 19 % for a conversion of 41 %, 19 % for a conversion of 13 %, and 16 % for a conversion of 26 %, was observed in the presence of TiO2 P25.