Deadly Disease Research Articles

UNC93B1: a novel immune-related prognostic biomarker in breast cancer.

Breast cancer (BRCA) is a prevalent and deadly disease among women. This study investigated the role of UNC93B1, a gene associated with immune function, in BRCA prognosis and immune infiltration. Differentially expressed mRNA (DEmRNA) data related to the prognosis and immunity of BRCA patients were obtained from TCGA, GTE, GEO, and ImmPort databases. The Kruskal-Wallis test was used to identify clinicopathological parameters associated with UNC93B1 expression. Univariate and multivariate COX regression analyses were performed to assess the impact of UNC93B1 expression and clinicopathological parameters on patient survival. We analyzed the target genes' relevant functions and signaling pathways through enrichment analysis. Furthermore, the relationship between UNC93B1 expression and tumor immune infiltration was examined using ssGSEA and Spearman correlation analysis. The findings demonstrated that high expression of UNC93B1 was associated with poorer prognosis in BRCA patients. UNC93B1 was also linked to race, N stage, pathological stage, and overall survival in BRCA patients and emerged as an independent prognostic factor. Functional enrichment analysis indicated significant enrichment of UNC93B1 in oncogenic and immune-related pathways. Moreover, UNC93B1 expression displayed significant associations with tumor immune cells and immune checkpoints according to ssGSEA and Spearman correlation analysis. Knockdown of UNC93B1 expression in BRCA cell lines (MDA-MB-231, SK-BR-3) suppresses their proliferation, invasion, and other phenotypes. These results suggest that UNC93B1 may be an immunologically relevant diagnostic and prognostic biomarker for BRCA.

Genome-wide analysis of codon usage bias in Ascovirus: Insights into viral evolution and host adaptation.

Genome-wide analysis of codon usage bias in Ascovirus: Insights into viral evolution and host adaptation.

RECi-PE (REducing CT in Pulmonary Embolism Diagnosis): an emergency department quality intervention.

Pulmonary embolism (PE) is a potentially deadly disease and a diagnostic challenge in emergency departments (EDs). Established strategies exist for risk stratification and test stewardship for CT pulmonary angiography (CTPA). However, implementation of best practices has proven challenging, and rising CTPA utilisation increases costs, radiation exposure and ED crowding. We created a multimodal quality intervention to reduce excess CTPA studies and increase the use of d-dimer assays prior to CTPA. Balance measures included the rate of positive CTPA studies and ED returns within 72 hours of discharge. This was an observational, pre-post interventional design at three EDs. The intervention included an institutional PE diagnostic guideline, educational sessions, an electronic clinical decision support tool and monthly feedback to individual providers. Consecutive patient data were analysed 1 year pre and 1 year post an intervention on 21 November 2021. Analyses used Pearson χ2, logistic regression generalised linear models and XmR statistical process control (SPC). The study included 307 441 patient encounters, with 35 066 PE evaluations. CTPA utilisation decreased from 6.0% to 5.1% (p<0.01) of all patient encounters, and d-dimer use preceding CTPA increased from 36.6% to 56.3% (p<0.01). For both primary measures, SPC charts showed statistically significant special cause variation compared with the pre-intervention data. There was no significant change in the rate of positive CTPA studies (9.3% vs 10.4%, p=0.14) or 72-hour ED returns (3.0 vs 3.1%, p=0.6). A multimodal intervention was associated with reduced CTPA utilisation and increased use of d-dimer as the initial test in PE diagnosis, without any negative associated impact on balance measures. This strategy could be reproduced and implemented at other institutions looking to change practice.

TRNA-Derived Small RNA Accelerates Tumorigenesis through Crosstalk with Tumor-Associated Macrophages, and Downregulation with Cell Membrane-Modified Polymer Nanoparticles Enables Treatment Response.

Accumulating evidence has shown that tRNA-derived small RNAs (tsRNAs) play pivotal roles in the progression of the majority of malignancies. The tumor microenvironment (TME) is important for hepatocellular carcinoma (HCC) progression. However, how tsRNAs exert their effects through the TME to drive hepatocarcinogenesis is unclear. We revealed that tsr_019759, a tsRNA, was significantly upregulated in HCC, and it promoted HCC growth and metastasis via inhibiting TNFSF15 expression and activating the JAK2/STAT3 signal pathway. Moreover, tsr_019759 could impede the exocrine secretion of TNFSF15, thereby inducing tumor-associated macrophage (TAM) polarization toward the M2 type through inhibiting the DR3/NF-κB signaling pathway. Additionally, M2 TAMs further facilitated HCC development through increasing EGF secretion and activating the EGFR/JAK2/STAT3 signaling pathway. Furthermore, a type of delivery system targeting inhibition of tsr_019759 loaded in HCC cancer cell membrane (CCM)-packed polyethylenimine (PEI)-modified poly lactic-co-glycolic acid (PLGA) nanoparticles, namely, in-tsr/PEI/PLGA@CCM, was constructed. These nanocomposites effectively arrested HCC progression by blocking the reciprocal crosstalk between HCC cells and M2 TAMs in both subcutaneous xenograft and orthotopic tumor mouse models. Taken together, this study highlights the potential molecular mechanisms of tsr_019759 accelerating HCC progression through boosting the interaction with M2 TAMs in the TME. Moreover, in-tsr/PEI/PLGA@CCM may be a promising treatment strategy for this deadly disease.

Meningitis caused by N. meningitidis: How to prevent this “younger generation killer”?

Neisseria meningitidis is a gram-negative bacterium that inhabits the mucosal surface of the nasopharynx in approximately 10% of healthy persons. It stands out as a leading etiology of meningitis, particularly among children, adolescents, and young adults. Meningococcal infections account for an estimated 1.2 million cases annually worldwide, with a death toll exceeding 135,000. These infections are most prevalent in the “meningitis belt” of sub-Saharan Africa and have historically occurred in cyclic patterns in China. Chemoprophylaxis using antibiotics like rifampicin, ciprofloxacin, and ceftriaxone is effective in eliminating bacterial carriage and preventing disease spread. Vaccination represents another crucial preventive measure. This review provides an overview of meningococcal meningitis, emphasizing the importance of early diagnosis, chemoprophylaxis with antibiotics like ceftriaxone, and vaccination as key strategies to combat this deadly disease, particularly among vulnerable populations like infants, adolescents, and young adults.

Dictyosteliumdiscoideum–Mycobacterium marinum infection model: a powerful high-throughput screening platform for anti-infective compounds

Tuberculosis is among the world’s deadliest diseases, causing approximately 2 million deaths annually. The urgent need for new antitubercular drugs has been intensified by the rise of drug-resistant strains. Despite recent advancements, most hits identified through traditional target-based screening approaches exhibit limited efficacy in vivo. Consequently, there is a growing demand for whole-cell-based approaches that utilize host-pathogen systems directly. The Dictyostelium discoideum–Mycobacterium marinum host–pathogen system is a well-established and powerful alternative model system for studying mycobacterial infections. In this article, we present a phenotypic host–pathogen assay protocol that monitors M. marinum during infection of the amoeba D. discoideum. This assay is characterized by its scalability for high-throughput screening, robustness, and ease of manipulation, making it an effective system for compound screening. Notably, this system provides dual readouts: bacterial load via a bioluminescent M. marinum strain and host survival and growth via a fluorescent D. discoideum strain, enabling further host characterization by quantifying growth inhibition and potential cytotoxicity. Finally, the assay was benchmarked against selected antibiotics and anti-infectives, and IC50s and MIC values were calculated where applicable, demonstrating its ability to differentiate between antibiotics and anti-infective compounds.

Incidence, Symptomology, Morpho-molecular Characterization of Agroathelia rolfsii (Sclerotium rolfsii Sacc.): The Causal Agent of Basal Rot in Chabaud Carnation

Background: Basal rot or sclerotium rot is one of the most serious and deadly disease in wide range of crops, including carnations. In carnations, it causes significant damage and economic loss. Methods: The Agroathelia rolfsii, basionym: Sclerotium rolfsii Sacc., the causal agent of basal rot in Chabaud carnation was ioslated from diseased plant parts collected from the Horticultural Research Farm, Assam Agricultural University, Jorhat, in 2023-2024 consequently, the study on the disease incidence (%), symptoms and morphomolecular characterization of the pathogen was carried out. Result: The incidence of basal rot was recorded the maximum in April (25.78%). The symptoms first appeared in the basal region, just above the ground, which gradually progressed upward over time. Colonizing white mycelia were conspicuous, producing white smooth fruiting bodies that turned brown, resembling mustard seed grains. The disease caused constriction at the infected point, resulting in decaying of the tissue and collapse of the plant eventually. The culture exhibited compact, whitish, cottony mycelia with sclerotia grown over time. Additionally, the DNA sequence of fungal isolate was submitted to NCBI, with an accession No. PP 203038. The fungal isolate had 92.99% similarity with A. rolfsii and a phylogenetic tree was constructed according to its nearest species with a bootstrap value.

Ash trees evolve defences against deadly fungal disease

Ash trees evolve defences against deadly fungal disease

Expression and Prognostic Implication of the Nuclear Receptors Farnesoid X Receptor and Pregnane X Receptor in Human Cholangiocarcinoma

Background/AimCumulative evidence reveals the contribution of nuclear receptors in the development and progression of cancers. The present study aimed to investigate the expression of two nuclear receptors, farnesoid X receptor (FXR) and pregnane X receptor (PXR), in cholangiocarcinoma (CCA) tissues and the correlation of their expression with clinicopathological features.Materials and MethodsFXR and PXR expression was evaluated in 111 resected CCA patient samples using immunohistochemistry, and the association of its expression with clinicopathological parameters was analyzed. The effectiveness of the expression of these nuclear receptors in predicting patients’ outcomes was also assessed.ResultsFXR and PXR positivity was noted in all examined samples, with their expression predominantly localized in the cytoplasm. Patients with intraductal papillary neoplasm of the bile duct had significantly lower FXR expression (p=0.042). Elevated FXR expression was also significantly associated with lymph node metastasis (p=0.006) and advanced tumor stage (p=0.007). The results of the log-rank test analysis showed that the survival time of the patients was not associated with the expression of these two nuclear receptors. However, the CCA patients presenting low FXR/PXR expression tended to have a longer overall survival (p=0.125).ConclusionFXR may contribute to the progression of CCA to more advanced stages. The prognostic significance of FXR and PXR expression appears relevant in CCA. These nuclear receptors may have a function in the prediction and treatment of this deadly disease.

PREDICTIVE MODELING FOR LUNG CANCER PROGNOSIS USING DEEP LEARNING

Lung cancer is among the deadliest diseases, with a total of around 18.4 percent of all deaths associated with cancer all over the world. Early detection improves the survival rates, but conventional methods of diagnosis, e.g., chest X-rays and CT scans, are also highly disadvantaged. Such methods are also very expensive, in addition to being dependent on expertise; they also expose patients to radiation. To address these issues, the proposed study examines the application of deep learning methods, specifically, convolutional neural networks (CNNs), in building a learning model that would be able to classify the severity of lung cancer. Projected to be a hybrid between medical imaging and patient health records, the model has a goal to improve the precision of prognosis and differentiation. The model can be used to accurately diagnose patients undergoing treatment due to the considerable performance it achieves through rigorous testing with advanced deep learning architectures, such as DenseNet and ResNet, where it has superseded conventional diagnostic techniques. It has a staggering 99 percent accuracy in the classification of the severity, with high-risk cases having a recall rate of 97 percent, showing it has the potential for early detection. Although the results look encouraging, there are still challenges, e.g., imbalance of the data and complexity of interpreting the models. This study confirms the potential of deep learning to change the diagnosis of lung cancer, providing an opportunity to intervene with patients earlier and achieve improved outcomes. At the same time, these techniques still have to be perfected and refined, and further research is necessary to achieve that goal.

Effectiveness of Desmanthus virgatus Leaf Ethyl Acetate Extract and Antiviral Drugs as Antirabies Based on In Silico Study

Rabies is a deadly viral disease that has no effective therapy after clinical symptoms appear. This study aims to evaluate the antirabies potential of the dominant compounds in the ethyl acetate extract of Desmanthus virgatus leaves, as well as several antiviral drugs, through an in silico approach. The extract was obtained through maceration and partitioning methods using ethyl acetate solvent, then analyzed using LC-MS, which identified 182 secondary metabolite compounds, and ten dominant compounds were selected for further analysis. These compounds, along with seven antiviral drugs, were docked against the rabies virus glycoprotein (PDB ID: 6LGX) using AutoDockTools 4.2.6 software. The docking results were analyzed based on the values of binding affinity, inhibition constant (Ki), and interaction with active amino acid residues. Quercitrin and quercimeritrin were the dominant flavonoid glycosides in the ethyl acetate extract of D. virgatus leaves that showed binding affinity values of -8.45 kcal/mol and -8.10 kcal/mol, respectively. In addition, bictegravir and tegobuvir showed binding affinity values of -9.17 kcal/mol and -9.05 kcal/mol, respectively. Four compounds indicated potential as antirabies drugs. Pharmacokinetic feasibility tests using Lipinski parameters showed that most of the dominant compounds violated one or more parameters, especially the number of hydrogen bond donors/acceptors and molecular weight. However, such violations were also found in some antiviral drugs that have been used, such as remdesivir and darunavir. These results suggest that D. virgatus leaf extracts contain compounds with promising potential antirabies activity and deserve further investigation through in vitro and in vivo tests.

Trends in the Incidence of Ovarian Cancer Among Premenopausal and Postmenopausal Women in the United States, 2001 to 2021

Ovarian cancer remains the deadliest and leading cause of gynecological cancer-associated mortality in the US. The aim of this study was to characterize the trends in the incidence of ovarian cancer between premenopausal and postmenopausal women to inform future targeted interventions. This population-based cross-sectional study analyzed data from the US Cancer Statistics (USCS) database, which covered the whole of the US population between 2001 and 2021. Joinpoint regression was used to compute the average annual percentage change (APC) with 95% confidence interval (CI) and age-standardized incidence rates per 1,000,000 population. The results showed that the IR of ovarian cancer declined between 2001 and 2021. Postmenopausal women had greater decreases in the IR of ovarian cancer compared to premenopausal women who showed a small decline. When stratified by race/ethnicity, non-Hispanic American Indian/Alaska Native women aged 20-49 years experienced an increase in the IR of ovarian cancer (APC = 2.4; 95% CI 0.9 to 4.1) compared to other racial/ethnic groups which showed a decline. Joinpoint trend analyses identified one inflection point in localized ovarian cancer incidence trends among all three age groups: an initial decline from 2001 to 2011 among women 20-49 years old and 65+ years old, and from 2001 to 2012 among women 50-64 years old, followed by an upward trend thereafter to 2021. Similarly, there was one inflection point in the IR of ovarian cancer for the clear cell and endometrioid types among women aged 20-49 years old. The IR of ovarian cancer in the US declined significantly among postmenopausal compared to premenopausal women, for whom the IR of ovarian cancer decreased only slightly. Although encouraging, these findings show a need for continued efforts to improve early detection and prevention strategies to mitigate the burden of this deadly disease.

A Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting model to predict the epidemic trends of scrub typhus in China

Scrub typhus is a deadly infectious disease that is frequently underdiagnosed. Forecasting the emergence of infectious diseases using epidemiological models has emerged as a crucial instrument for comprehending the dynamics of their occurrence. This research aimed to investigate epidemic traits and create a predictive model for scrub typhus in mainland China, employing the Seasonal Autoregressive Integrated Moving Average (SARIMA) time series method. Monthly records of scrub typhus cases were gathered from the China Center for Disease Control and Prevention, covering the timeframe from 2006 to 2019. From 2006 to 2018, a total of 142849 scrub typhus cases were reported in China, the females’ morbidity was higher than the males’ one (P < 0.001). The ideal model was SARIMA (1, 0, 2) (1, 1, 1) 12 with its residual being white noise (P > 0.05). This method forecasted scrub typhus cases between January and December 2019, with the predicted values for 2019 falling within the 95% confidence range. The research indicates that the SARIMA model accurately simulated the epidemiological patterns of scrub typhus across mainland China. Utilizing the SARIMA model is a practical approach for tracking scrub typhus cases in mainland China.

Super-enhancers orchestrate transcriptional dysregulation and metabolic reprogramming in uveal melanoma

Uveal melanoma (UM) is the most common intraocular malignancy in adults and frequently metastasizes. Somatic mutations and chromatin aberrations have been implicated in the pathogenesis of this deadly disease. Despite rapid progress in elucidating the genetic landscape of UM, the epigenetic architecture underlying UM pathogenesis remains incompletely understood. Here, we describe a super-enhancer-mediated epigenetic pipeline through genome-scale histone acetylation and transcriptional profiling. We first characterized the active landscape of super-enhancer profiles in UM via chromatin immunoprecipitation sequencing (ChIP-seq). We identified master transcription factors specifically driven by UM-specific super-enhancers, and our pipeline identified transcription factor AP-2 alpha (TFAP2A), which is highly associated with metabolism and oncogenesis, as the top essential regulator in UM. TFAP2A occupied predicted super-enhancers associated with the oncogene Solute Carrier Family 7 member 8 (SLC7A8) in UM, thereby elucidating a mechanism for regulating oncogene expression. Collectively, our data illustrate the potential for epigenetic targeting of super-enhancer-mediated oncogene dependencies in UM, highlighting an epigenetic vulnerability that can be exploited for precision therapy.

Insights Into Cockayne Syndrome Type B: What Underlies Its Pathogenesis?

Cockayne Syndrome (CS) is an autosomal recessive disorder arising from mutations in either of two disease-associated genes, ERCC6 or ERCC8. CS patients exhibit cutaneous photosensitivity, neuropathological abnormalities, severe growth retardation, a distinctive facial appearance with pronounced sunken eyes, musculoskeletal anomalies, sensory impairment, and dental decay. Approximately 70% of all CS cases carry ERCC6 mutations; therefore, this review will focus solely on Cockayne Syndrome complementation group B (CS-B). CS-B exhibits several hallmarks of aging, including genomic instability, epigenetic modifications, loss of proteostasis, and mitochondrial failure. CS-B is proposed to result from the accumulation of DNA damage and the resulting transcription impairment. However, the main pathophysiological mechanisms underlying the severe cellular impairments observed in CS-B remain unclear. Here, we review the current literature to elucidate ERCC6-related mechanisms, highlighting the key and emerging pathological mechanisms underlying CS-B, as well as their putative interactions. Considering the mechanisms that heavily rely on ERCC6, we propose that CS-B pathogenesis arises from a combination of DNA damage accumulation, transcriptional dysregulation, and mitochondrial dysfunction. Furthermore, we argue that these molecular features influence each other, rather than acting as isolated mechanisms. This suggests that the crosstalk between mechanisms is a key factor for CS-B pathogenesis. Although efforts have been made to unveil CS-B pathogenesis, research is still lacking, hindering progress in understanding this deadly disease. Future work will prove crucial to determine the main contributor to CS-B pathogenesis and identify new interactions between CS-B-affected mechanisms.

Desmoplastic Small Round Cell Tumors and the Role of Androgen Receptors.

Desmoplastic small round cell tumor (DSRCT) is an aggressive soft-tissue sarcoma driven by the EWSR1::WT1 fusion protein resulting from a chromosomal translocation between the EWSR1 (Ewing sarcoma breakpoint region 1) gene on chromosome 22 and the WT1 (Wilms tumor 1) gene on chromosome 11. This disease typically occurs in post-pubertal adolescent and young adult males, which suggests it may be hormonally driven through the androgen receptor (AR) pathway. Over the years, various groups have established a relationship between AR and DSRCT. Profiling studies have noted a high expression of AR in DSRCT. Fine et al. showed that combined androgen blockade led to a clinical benefit in three (all male) of six patients with stable disease or at least a minor response lasting three months. The AR pathway is relevant not only in prostate cancer but has been discovered to be oncogenic in salivary gland cancers, melanoma, and breast cancer. Though numerous AR-directed therapies are available to treat prostate cancer, AR has not been extensively evaluated as a therapeutic target in DSRCT. Preclinical studies revealed that AR stimulation increased cell proliferation. Conversely, single-agent targeting of the pathway delayed tumor growth in xenograft models. Pharmacodynamic analysis showed that AR inhibition activates the PI3K/Akt/mTOR pathway, and recent epigenetic analysis of AR binding showed that it may interact with EWSR1::WT1 and the forkhead protein family of transcription factors that regulate development and cellular differentiation. A deeper understanding of the impact of AR on the epigenetic landscape and signaling pathway crosstalk of DSRCT promises to expand the therapeutic arsenal of agents available to combat this deadly disease.

Next-generation cancer therapeutics: unveiling the potential of liposome-based nanoparticles through bioinformatics.

Cancer remains one of the most deadly diseases in the world, requiring constant growth and improvements in therapeutic strategies. Traditional cancer treatments, such as chemotherapy, radiotherapy, and surgery, have limitations like off-target release, toxicity, and inefficient drug delivery. This study explains the role of bioinformatics and AI in optimizing and analyzing liposomal formulations for innovative and better cancer therapy. Molecular docking (MD), molecular dynamics simulations, and machine learning models are the computational techniques that can help to design stable liposomal carriers for drugs, predict receptor-ligand interactions, and can improve drug release efficiency. Improved liposome nanoparticles (LNPs) surface functionalization, the discovery of tumor-specific biomarkers, and the improvement of receptor-ligand interactions for accurate drug targeting are all made possible by bioinformatics tools and methodologies. Moreover, AI-assisted predictions and in silico modeling can speed up drug discovery and processing while eliminating the experimental expenditures and time. In the present review, we conducted MD studies to complement the discussed literature. MD was performed between cyclic RGD peptides (liposomal ligands) and the GPR116 receptor in triple-negative breast cancer, and between folic acid (liposomal ligand) and the Axl tyrosine kinase receptor for lung cancer, revealing strong and stable interactions and highlighting the amino acid residues involved. Notwithstanding current obstacles, computational tools have shown notable progress in nanomedicine, exploring more options for more individualized and effective cancer therapies. The combination of AI, machine learning, and multi-omics techniques to improve therapeutic efficacy and reduce side effects is asubstantialkey to the future of LNP-based cancer treatment.

Prevalence and associated factors of malaria among febrile patients at two sites with different transmission intensities, Northwest Ethiopia

Prevalence and associated factors of malaria among febrile patients at two sites with different transmission intensities, Northwest Ethiopia

Viral Hemorrhagic Fever: A Literature Review

Viral Hemorrhagic Fever (VHFs) is a diverse group of systemic diseases mediated by RNA viruses with significant morbidity and mortality rates and represents a major public health concern caused by four families of viruses- Arenaviridae, Bunyaviridae, Filoviridae, and Flaviviridae. It can harm the walls of small blood vessels, making them leak, and it can prevent blood from clotting. VHFs are a disease that is classified into a variety of deadly viral diseases characterized by severe internal or external hemorrhage or bleeding into the skin. Fever, malaise, muscle soreness, vomiting, and shock are common clinical signs of viral hemorrhagic fever, though they might vary depending on the type. Internal bleeding that results is typically not fatal, but the illness itself may be. Viral hemorrhagic fevers (VHFs) represent a group of severe, systemic feverish diseases. This review aims to shed light on viral hemorrhagic fevers in terms of their causes, symptoms, transmission methods, prevention, and available treatment, to raise awareness about their danger and enhance preventive efforts to combat their spread. Hemorrhagic fever is a serious disease that affects humans and causes a high mortality rate due to its pathogenicity. These viruses infect insects or rodents, so the focus is on staying away from rodents or insects that carry the virus. Therefore, it is necessary to adhere to the procedures of Islam and prepare. These procedures allow for preparation for the future. disease outbreaks and preparation reduce the impact of diseases on humans. Scientific research is still ongoing to develop more effective vaccines and treatments that may contribute to reducing the negative effects of these viruses.

Music-Medium as a Sensitisation Tool in the Fight Against the Covid-19 in Southwest Nigeria

This paper examines the contributions of the effective use of music-medium as a tool for sensitising the people of southwest Nigeria on the fast spread of the deadly Corona Virus Disease - 2019 (COVID-19) and the precautionary measures put in place. We examine two selected campaign-music by Lagos and Èkìtì States governments respectively to create awareness. The study adopted qualitative descriptive research design with the use of textual, verbal content analysis. The study is premised on Critical Theory and Cultural Studies as adequately adopted for analysis and discussion on optimising music medium as a sensitising tool against COVID-19 within the purview of this paper. Findings revealed that the campaign-music by Lagos State is affluent in nature as handled by a popular musician, Evang. Ṣèyí Lewis (Alápáńlá), while that of Èkìtì State had more of pan-African campaigners, anchored by the Èkìtì State Troup of Arts and Culture, who through wordings and messages of the songs, cultures, pass information of sensitisation to the people on how to combat COVID-19. The selected songs were rendered in Yorùbá language of the southwest Nigeria.