Early Diagnosis Research Articles

HdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning.

Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of β-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis. In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited significant differences between the diseased and control groups. Following the identification of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint NK cell subset with the most robust communication effects. Subsequently, three machine learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model was then designed based on these characterized genes. Additionally, a protein-protein interaction (PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was conducted to classify AD subtypes based on the model genes, followed by the analysis of immune infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized to explore the correlation between model genes and immune cells, as well as inflammatory factors. We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a high association with AD. The nomogram based on these genes provides practical assistance in diagnosing and predicting patients' outcomes. The interconnected genes screened through PPI are intricately linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment of an immune environment in AD patients is closely intertwined with the heightened expression of model genes. This study has not only established a valuable diagnostic model for AD patients but has also delved deeply into the pivotal role of model genes in shaping the immune environment of individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management strategies.

Exosomes in the Diagnosis of Neuropsychiatric Diseases: A Review

Exosomes are 30–150 nm small extracellular vesicles (sEVs) which are highly stable and encapsulated by a phospholipid bilayer. Exosomes contain proteins, lipids, RNAs (mRNAs, microRNAs/miRNAs, long non-coding RNAs/lncRNAs), and DNA of their parent cell. In pathological conditions, the composition of exosomes is altered, making exosomes a potential source of biomarkers for disease diagnosis. Exosomes can cross the blood–brain barrier (BBB), which is an advantage for using exosomes in the diagnosis of central nervous system (CNS) diseases. Neuropsychiatric diseases belong to the CNS diseases, and many potential diagnostic markers have been identified for neuropsychiatric diseases. Here, we review the potential diagnostic markers of exosomes in neuropsychiatric diseases and discuss the potential application of exosomal biomarkers in the early and accurate diagnosis of these diseases. Additionally, we outline the limitations and future directions of exosomes in the diagnosis of neuropsychiatric diseases.

Plant Disease Detection Using Deep Learning-Based Convolutional Neural Networks With Transfer Learning Algorithms

Plant diseases can have significant impacts on agricultural production, leading to significant losses in yield and quality. Early detection and diagnosis of crop diseases is essential for effective control and management. In this study, We present a novel approach for the automated detection of plant diseases using deep learning-based Convolutional Neural Networks (CNNs) coupled with Transfer Learning algorithms. Our study focuses on developing a robust and adaptable system capable of accurately identifying plant diseases from image data. By leveraging a comprehensive dataset comprising diverse plant species and disease types, our goal is to train the model to achieve high accuracy and real-time detection capabilities. The potential significance of this research lies in its potential to significantly improve agricultural practices by offering farmers a valuable tool for prompt disease diagnosis and management, ultimately leading to increased crop yields and sustainable farming practices. Keywords: CNN, Deep Learning, Plant Diseases detection, Disease Diagnosis, Agriculture.

Theranostic Potential of Bacteriophages against Oral Squamous Cell Carcinoma.

Oral Squamous Cell Carcinoma (OSCC) is a widespread and challenging disease that accounts for 94% of cancers of the oral cavity worldwide. Bacteriophages (phages) have shown promise as a potential theranostic agent for the treatment of OSCC. It may offer advantages in overcoming the challenges of conventional methods. Modern high-throughput pyrosequencing techniques confirm the presence of specific bacterial strains associated with OSCC. Bio-panning and filamentous phages facilitate visualization of the peptide on surfaces and show high affinity in OSCC cells. The peptide has the potential to bind integrin (αvβ6), aid in diagnosis, and inhibit the proliferation of OSCC cells. Mimotopes of tumor-associated antigens show cytotoxic and immune responses against cancer cells. Biomarker-based approaches such as transferrin enable early OSCC diagnosis. A modified temperate phage introduces CRISPR-Cas3 to target antimicrobial-resistant bacteria associated with OSCC. The research findings highlight the evolving field of phage diagnostics and therapy and represent a new avenue for non-invasive, targeted approaches to the detection and treatment of OSCC. However, extensive clinical research is required to validate the efficacy of phages in innovative cancer theranostic strategies.

Sodium signal intensity of CSF using 1H-guided 23Na-MRI as a potential noninvasive biomarker in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by cognitive decline and mnestic deficits. The pathophysiology of AD is not fully understood, which renders the development of accurate tools for early diagnosis and effective therapies exceedingly difficult. In this study, we investigated the use of 23Na-MRI to measure the relative sodium signal intensities (rSSIs) in CSF in patients with AD and healthy controls. We prospectively recruited 11 patients with biomarker-diagnosed early-stage AD, as well as 12 cognitively healthy age-matched controls. All participants underwent 23Na-MRI to measure rSSI. Statistical analyses were performed to compare CSF sodium signal intensities between groups and to evaluate the specificity and sensitivity of the rSSI in the diagnosis of AD. RSSIs in CSF were significantly higher in AD patients (mean=68.6%±7.7%) compared to healthy controls (mean=56.9%±5.5%) (p<.001). There was also a significant negative correlation between rSSI in CSF and hippocampus and amygdala volumes (r=-.54 and -.49, p<.05) as well as a positive correlation with total CSF volumes (r=.81, p<.05). Receiver operating characteristic analysis showed high diagnostic accuracy for rSSI in discriminating between AD patients and healthy controls (area under the curve=.94). Our study provides evidence that rSSI in CSF is increased in AD patients in comparison to healthy controls. rSSI may serve as a potential marker for early detection and monitoring of disease progression. Larger, longitudinal studies are needed to confirm our findings and to investigate the association between rSSI in CSF and the severity of cognitive impairment.

A Rapid and Robust DNA Extraction Method for PCR-Based Diagnosis of V. cholerae

Cholera, caused by _V. cholerae_, needs rapid diagnosis because of its threat for rapid spread. Recent molecular diagnosis by PCR assay is more advantageous than the conventional methods. The bottleneck in PCR diagnosis lies in the delay in template DNA extraction of _V. cholerae_, which is the basic requirement. This study describes a simple, less expensive, and rapid template DNA extraction method to lessen the total time for PCR diagnosis of _V. cholerae._ To obtain template DNA, our method involves boiling of _V. cholerae_ suspension in distilled water (takes 18-24 hours) instead of boiling the suspension in broth medium, which is a lengthy process (takes 72 hours). The validation of our template DNA was conducted using 40 _V. cholerae_ O1 strains that were confirmed previously, and its usefulness was checked on 20 clinical strains of _V. cholerae_ O1 isolated from acute diarrhea patients; results were compared with those of conventional template DNA. The analysis of our template DNA in simplex and quadruplex PCR assays revealed the presence of _ctxA_, _tcpA _(El Tor), _rfb _(O1), _ToxR_, _ctxB_, _zot_, _ace,rst _, and _OmpW _genes in _V. cholerae _O1. The comparison of the results of PCR assays using the template DNA from both sources showed equal results and matched correctly. The sensitivity of our template DNA was 1.5x103 CFU per assay. Our template DNA extraction method is simple, less expensive, and rapid, and it can be employed for early diagnosis of _V. cholerae_ during outbreaks, in research laboratories, and in hospital setups where infrastructures are available.

Sleep-Disordered Breathing and Associated Comorbidities among Preschool-Aged Children with Down Syndrome

Children with Down syndrome (DS) are at high risk of sleep-disordered breathing (SDB). The American Academy of Pediatrics recommends a polysomnogram (PSG) in children with DS prior to the age of 4. This retrospective study examined the frequency of SDB, gas exchange abnormalities, co-morbidities, and surgical management in children with DS aged 2–4 years old at Seattle Children’s Hospital from 2015–2021. A total of 153 children underwent PSG, with 75 meeting the inclusion criteria. The mean age was 3.03 years (SD 0.805), 56% were male, and 54.7% were Caucasian. Comorbidities included (n, %): cardiac (43, 57.3%), dysphagia or aspiration (24, 32.0%), prematurity (17, 22.7%), pulmonary (16, 21.3%), immune dysfunction (2, 2.7%), and hypothyroidism (23, 30.7%). PSG parameter data collected included (mean, SD): obstructive AHI (7.9, 9.4) and central AHI (2.4, 2.4). In total, 94.7% met the criteria for pediatric OSA, 9.5% met the criteria for central apnea, and 9.5% met the criteria for hypoventilation. Only one child met the criteria for hypoxemia. Overall, 60% had surgical intervention, with 88.9% of these being adenotonsillectomy. There was no statistically significant difference in the frequency of OSA at different ages. Children aged 2–4 years with DS have a high frequency of OSA. The most commonly encountered co-morbidities were cardiac and swallowing dysfunction. Among those with OSA, more than half underwent surgical intervention, with improvements in their obstructive apnea hypopnea index, total apnea hypopnea index, oxygen saturation nadir, oxygen desaturation index, total arousal index, and total sleep duration. This highlights the importance of early diagnosis and appropriate treatment. Our study also suggests that adenotonsillar hypertrophy is still a large contributor to upper airway obstruction in this age group.

Impact of the difference in diagnostic criteria for adolescent polycystic ovary syndrome excluding polycystic ovarian morphology.

Exclusion of polycystic ovarian morphology (PCOM) from the diagnostic criteria for adolescent polycystic ovary syndrome (PCOS) has been proposed. We analyzed the profiles of adolescent women with suspected PCOS based on the Japan Society of Obstetrics and Gynecology (JSOG) diagnostic and Rotterdam criteria, excluding those with PCOM. Thirteen- to twenty-one-year-old women with suspected or confirmed diagnosis of PCOS according to the JSOG and Rotterdam criteria were included in this study. Patient characteristics such as hormone levels and body mass index (BMI) were compared between the groups. Correlations between BMI and testosterone, and BMI and time to diagnosis were also analyzed. Twenty-nine patients were diagnosed with adolescent PCOS according to the JSOG criteria, and 11 patients according to the Rotterdam criteria after excluding the patients fulfilling the PCOM criteria. Serum testosterone levels were significantly higher in adolescents diagnosed with PCOS using the Rotterdam criteria than in those diagnosed using the JSOG criteria (p < 0.001). The obese group had significantly higher testosterone levels and a longer time from menarche to PCOS diagnosis. A positive correlation was observed between BMI and testosterone levels (r = 0.318, p = 0.014). Although adolescents with PCOS diagnosed using the Rotterdam criteria exhibited higher testosterone levels, which is a typical characteristic of this condition, the JSOG criteria may be useful for the early diagnosis of adolescent PCOS, including suspected cases. The differences between the two criteria may reflect the natural history of PCOS and its different reproductive and metabolic phenotypes.

Skin Cancer Segmentation using CNN

This groundbreaking research introduces a comprehensive strategy for advancing medical image segmentation, merging two pivotal concepts to significantly enhance both the accuracy and efficiency of the segmentation process. The first component of our approach involves the integration of polar transformations as a preprocessing step applied to the original dataset. This transformative technique is designed to address the challenges associated with segmenting single structures of elliptical shape in medical images, such as organs (e.g., heart and kidneys), skin lesions, polyps, and various abnormalities. By centering the polar transformation on the object's focal point, a reduction in dimensionality is achieved, coupled with a distinct separation of segmentation and localization tasks. Two distinct methodologies for selecting an optimal polar origin are proposed: one involving estimation through a segmentation neural network trained on non-polar images, and the other employing a dedicated neural network trained to pre dict the optimal origin. The second key element of our approach is around the integration of the DoubleU-Net architecture, a powerful encoder-decoder model specifically designed for the task of semantic image segmentation. DoubleU- Net is a group of two U-Net architectures, each with a specific purpose. The initial U-Net is pre-trained on VGG-19 as the encoder and uses features learned from ImageNet to provide efficient information transfer. In order to store more semantic information and content, a second U-Net was added to the base to enhance the capabilities of the network. Join Atrous Spatial Pyramid Pooling (ASPP) to develop network data extraction content. The combination of DoubleU-Net architecture and joint transformation as a step forward shows good segmentation performance in different clinical tasks, including liver segmentation, polyp detection vision, skin segmentation, and epicardial fat tissue segmentation. It shows that various medical projects, including various diagnostic methods such as colonoscopy, dermoscopy, microscopy, have a positive impact on the plan. More importantly, the method performs well in difficult cases, such as the segmentation of small and flat polyps in CVC-ClinicDB and the 2015 subset of the MICCAI Automated Polyp Detection dataset. The results demonstrate the accuracy and generality of the combination, making it the best way to evaluate medical images in context; Our study has revealed a new method of skin cancer diagnosis that combines the power of deep learning with innovation. Advanced technology. The combination of dual U-Net architecture and polar coordinate transformation not only improves the accuracy of classification of lesions but also improves the robustness of the model to changes in image features. This study contributes to the development of computer-aided diagnostic systems for early diagnosis. Experimental results show that our method provides good accuracy, sensitivity, and specificity in detecting malignant and benign tumors. Additionally, we are conducting ablation studies to determine the contribution of each presentation and treatment of skin cancer to ultimately benefit patients and determine these benefits. We also apply the transformation of the joint as the first step to improve the discrimination ability of the model. This mechanical change effectively reduces the impact caused by changes in wound size, shape, and direction by displaying the original image of the polar system. By standardizing the representation of skin diseases, polar transformation improves the model's ability to generalize across different data sets and improves overall performance.

Dealing with the Unexpected: Stercoral Perforation – A Surgical Conundrum

Stercoral colon perforation is a rare surgical emergency primarily linked to chronic constipation and advanced age. Diagnosis is challenging and requires established criteria and imaging. Urgent surgery is the modality of choice, typically involving Hartmann's procedure. Mortality rates can be as high as 60%, emphasising the need for early diagnosis and intervention. We presented a case of a 71-year-old bedridden female with a history of stroke, diabetes, and hypertension presenting with abdominal pain, fever and diarrhoea. Initial evaluation indicated dehydration, sepsis, and abdominal tenderness. An urgent imaging revealed a suspected rectal perforation, prompting emergency surgery. Intraoperatively, stercoral perforation due to impacted hard faeces was identified. Despite prompt and intensive treatment, the patient's condition deteriorated, ultimately resulting in her demise. Stercoral colon perforation is a critical condition requiring rapid diagnosis. Symptoms include abdominal distension, tenderness, cramps, fever, and anorectal pain. Healthcare providers should consider the possibility of stercoral perforation in individuals exhibiting these symptoms alongside a background of persistent constipation. Treatment involves peritoneal lavage and surgery. Early recognition is vital for proper management and improved outcomes.

Characterization of acute-on-chronic liver diseases: A multicenter prospective cohort study

BACKGROUND Acute-on-chronic liver disease (AoCLD) accounts for the majority of patients hospitalized in the Department of Hepatology or Infectious Diseases. AIM To explore the characterization of AoCLD to provide theoretical guidance for the accurate diagnosis and prognosis of AoCLD. METHODS Patients with AoCLD from the Chinese Acute-on-Chronic Liver Failure (ACLF) study cohort were included in this study. The clinical characteristics and outcomes, and the 90-d survival rate associated with each clinical type of AoCLD were analyzed, using the Kaplan-Meier method and the log-rank test. RESULTS A total of 3375 patients with AoCLD were enrolled, including 1679 (49.7%) patients with liver cirrhosis acute decompensation (LC-AD), 850 (25.2%) patients with ACLF, 577 (17.1%) patients with chronic hepatitis acute exacerbation (CHAE), and 269 (8.0%) patients with liver cirrhosis active phase (LC-A). The most common cause of chronic liver disease (CLD) was HBV infection (71.4%). The most common precipitants of AoCLD was bacterial infection (22.8%). The 90-d mortality rates of each clinical subtype of AoCLD were 43.4% (232/535) for type-C ACLF, 36.0% (36/100) for type-B ACLF, 27.0% (58/215) for type-A ACLF, 9.0% (151/1679) for LC-AD, 3.0% (8/269) for LC-A, and 1.2% (7/577) for CHAE. CONCLUSION HBV infection is the main cause of CLD, and bacterial infection is the main precipitant of AoCLD. The most common clinical type of AoCLD is LC-AD. Early diagnosis and timely intervention are needed to reduce the mortality of patients with LC-AD or ACLF.

Bronchiectatic Actinomycosis with Osseous Metaplasia Masquerading as Lung Cancer.

Bronchial involvement in pulmonary actinomycosis is rare and has been reported in the literature rarely. However, these reports describe endobronchial actinomycosis secondary to foreign body aspiration (for example, a fish bone). Our case did not have any history or clinical evidence suggesting foreign body aspiration, which makes it even more rare. A 55-year-old woman presented with complaints of on and off haemoptysis and cough for three weeks. In view of the haemoptysis and consolidation seen on imaging, a bronchoalveolar lavage was done and sent for cytological assessment. Few atypical cells with nuclear hyperchromasia and prominent nucleoli were noted. In view of the persistent haemoptysis, worsening symptoms, and non-resolution of the consolidation despite antibiotics, and the finding of atypical cells, segmental resection was done. A final diagnosis of bronchiectatic actinomycosis with osseous metaplasia was given. The patient was started on prolonged antibiotics with good response and recovery. Other risk factors associated with pulmonary actinomycosis include alcoholism, diabetes, haematological diseases, human immunodeficiency viral infection, use of immunosuppressants, and rarely chronic lung diseases, such as bronchiectasis. Our case had this rare association of bronchiectasis with bronchial actinomycosis. Bronchiectatic actinomycosis is a rare infection and it can mimic several lung disorders like unresolving pneumonia, pulmonary tuberculosis, foreign body, and even lung tumours. The pathologists and clinicians should be aware of this entity and thus help in the early diagnosis and better management of patients with this disease.

Global modified Delphi consensus on diagnosis, phenotypes, and treatment of SCN8A-related epilepsy and/or neurodevelopmental disorders.

We aimed to develop consensus for diagnosis/management of SCN8A-related disorders. Utilizing a modified Delphi process, a global cohort of experienced clinicians and caregivers provided input on diagnosis, phenotypes, treatment, and management of SCN8A-related disorders. A Core Panel (13 clinicians, one researcher, six caregivers), divided into three subgroups (diagnosis/phenotypes, treatment, comorbidities/prognosis), performed a literature review and developed questions for the modified Delphi process. Twenty-eight expert clinicians, one researcher, and 13 caregivers from 16 countries participated in the subsequent three survey rounds. We defined consensus as follows: strong consensus, ≥80% fully agree; moderate consensus, ≥80% fully/partially agree, <10% disagree; and modest consensus, 67%-79% fully/partially agree, <10% disagree. Early diagnosis is important for long-term clinical outcomes in SCN8A-related disorders. There are five phenotypes: three with early seizure onset (severe developmental and epileptic encephalopathy [DEE], mild/moderate DEE, self-limited (familial) infantile epilepsy [SeL(F)IE]) and two with later/no seizure onset (neurodevelopmental delay with generalized epilepsy [NDDwGE], NDD without epilepsy [NDDwoE]). Caregivers represented six patients with severe DEE, five mild/moderate DEE, one NDDwGE, and one NDDwoE. Phenotypes vary by age at seizures/developmental delay onset, seizure type, electroencephalographic/magnetic resonance imaging findings, and first-line treatment. Gain of function (GOF) versus loss of function (LOF) is valuable for informing treatment. Sodium channel blockers are optimal first-line treatment for GOF, severe DEE, mild/moderate DEE, and SeL(F)IE; levetiracetam is relatively contraindicated in GOF patients. First-line treatment for NDDwGE is valproate, ethosuximide, or lamotrigine; sodium channel blockers are relatively contraindicated in LOF patients. This is the first-ever global consensus for the diagnosis and treatment of SCN8A-related disorders. This consensus will reduce knowledge gaps in disease recognition and inform preferred treatment across this heterogeneous disorder. Consensus of this type allows more clinicians to provide evidence-based care and empowers SCN8A families to advocate for their children.

Clinical and haematological parameters in malaria caused by different plasmodium species in children

Background: Malaria is a disease of global importance and affects more than ninety countries in both the tropical and subtropical regions. Clinical and haematological parameters vary with type of malaria, although data relating to different species of malaria in children is limited. This study aims to understand the clinical and haematological profile of malaria and to correlate these with different malarial species among children. Methods: This is a descriptive cross-sectional study involving 130 proven malaria cases done over 18 months from October 2014 to April 2016. A detailed history and clinical examination along with haematological parameters were analysed and correlated with different types of malaria. Results: Among 130 children, 97 children were vivax positive, 4 were falciparum and 27 were mixed malaria. Fever was present in all, whilst other symptoms were chills and rigors (86.15%), vomiting (39.52%), headache (19%), pain abdomen (6.84%), myalgia (4.56%) and convulsions (1.52%). Clinical signs were pallor (29.64%), icterus (0.76%), splenomegaly (65.36%), hepatomegaly (23.56%) and hepatosplenomegaly (21.28%).75% of children with falciparum malaria had splenomegaly and pallor whereas hepatomegaly was observed in 34% of mixed malaria cases. Haematological parameters observed were anaemia (47.6%), severe anaemia (2%), leucocytosis (11.5%), leukopenia (39.2%), thrombocytopenia (87%) and severe thrombocytopenia (30%). Severe thrombocytopenia was seen with vivax malaria (70%). No mortality was noted in the studied population. Conclusions: Fever and splenomegaly are important clinical features, whereas anaemia and thrombocytopenia are the most noted haematological parameters in malaria. The parameters vary with different species of malaria knowledge of clinical and haematological parameters aid us in early diagnosis and prompt initiation of treatment and prevention of associated complications.

The potential diagnostic value of serum pentraxin-3 in hepatocellular carcinoma in Egyptian patients

Background and aimHepatocellular carcinoma (HCC) is considered one of the most common cancers in the world and one of the principal causes of cancer-linked deaths. Therefore, identification of new biomarkers for diagnosis, especially early diagnosis of HCC, is very important. Pentraxin 3 (PTX3) is possibly involved in cancer development, and as regard to liver diseases, plasma PTX3 was implicated to be associated with HCC occurrence. Therefore, this study will determine the serum PTX3 levels in patients with cirrhosis and HCC and to assess the potential diagnostic value in HCC in Egyptian patients.ResultsPentraxin 3 was significantly higher in HCC patients than in cirrhotic patients (p < 0.001); also, serum PTX3 was significantly correlated with number, size of focal lesions, the presence of portal vein thrombosis, and BCLC staging (p < 0.001).ConclusionThe significant increased levels of serum pentraxin 3 in HCC may support its use as an early marker for HCC, either alone or in combination with serum alpha-fetoprotein (AFP), allowing early diagnosis and prompt intervention.

What Are the Reliable Plasma Biomarkers for Mild Cognitive Impairment? A Clinical 4D Proteomics Study and Validation

Objective. At present, Alzheimer’s disease (AD) lacks effective treatment means, and early diagnosis and intervention are the keys to treatment. Therefore, for mild cognitive impairment (MCI) and AD patients, blood sample analysis using the 4D nonstandard (label-free) proteomic in-depth quantitative analysis, looking for specific protein marker expression differences, is important. These marker levels change as AD progresses, and the analysis of these biomarkers changes with this method, which has the potential to show the degree of disease progression and can be used for the diagnosis and preventive treatment of MCI and AD. Materials and Methods. Patients were recruited according to the inclusion and exclusion criteria and divided into three groups according to scale scores. Elderly patients diagnosed with AD were selected as the AD group (n = 9). Patients diagnosed with MCI were classified into the MCI group (n = 10). Cognitively healthy elderly patients were included in the normal cognition control group (n = 10). Patients’ blood samples were used for 4D label-free proteomic in-depth quantitative analysis to identify potential blood biomarkers. The sample size of each group was expanded (n = 30), and the selected biomarkers were verified by enzyme-linked immunosorbent assay (ELISA) to verify the accuracy of the proteomic prediction. Results. Six specific blood markers, namely, APOE, MMP9, UBR5, PLA2G7, STAT5B, and S100A8, were detected by 4D label-free proteomic quantitative analysis. These markers showed a statistically significant upregulation trend in the MCI and AD groups compared with the normal cognition control group (P&lt;0.05). ELISA results showed that the levels of these six proteins in the MCI group were significantly higher than those in the normal cognition control group, and the levels of these six proteins in the AD group were significantly higher than those in the MCI group (P&lt;0.05). Conclusion. The plasma levels of APOE, MMP9, UBR5, PLA2G7, STAT5B, and S100A8 in cognitively healthy elderly patients and patients with MCI and AD were significantly different and, more importantly, showed a trend of increasing expression. These results indicate that these six human plasma markers have important diagnostic and therapeutic potential in the identification of cognitive impairment and have value for in-depth research and clinical application.

Characteristics of children with autism spectrum disorder in pediatric rehabilitation at a referral hospital in Peru.

Motivation for the study. Despite the prevalence of ASD, research in the field of Physical Medicine and Rehabilitation is scarce in Peru. Main findings. Of 120 children with a previous diagnosis of ASD, only 9.8% received inclusive education. The median age at diagnosis was 3.83 years. We also found that 78.4% had no disability certificate and 77.5% had incomplete psychological evaluation. The median time since the last physical, occupational, and speech therapy sessions was 3 months, 8 months, and 3.5 months, respectively. Implications. These findings highlight the need to enhance early diagnosis, inclusive education, and evaluation and subsequent certification of disability, as well as to establish more timely interventions. Autism spectrum disorder (ASD) is characterized by developmental disorders, difficulties in social interaction and communication, and restrictive and repetitive patterns of behavior. Despite its high prevalence, few studies have been conducted in rehabilitation settings. This study aimed to describe the characteristics of children with ASD from the Pediatric Rehabilitation Service of the Rebagliati Hospital (SRP-HNERM). Cross-sectional descriptive study. We reviewed the medical records of children under 14 years of age previously diagnosed with ASD from the SRP-HNERM during 2022. A total of 120 children with ASD were evaluated. The median age was 5 years. Most received regular education, but it was inclusive only for 9.8%. The mean age at diagnosis was 3.83 years. We found that 78.4% had no disability certificate and 77.5% of the participants had incomplete psychological evaluation. The median time since the last physical, occupational and speech therapy sessions was 3, 8 and 3.5 months respectively. The mean age at diagnosis of ASD was older than three years, and more than 75% of the patients had neither a disability certificate nor a complete psychological evaluation. The median time since the last rehabilitation therapy sessions was three months or more. Our findings highlight the need to improve early diagnosis, inclusive education and evaluation and subsequent certification of disability, as well as to establish timely interventions.

The protocol for an observational Australian cohort study of CADASIL: The AusCADASIL study

IntroductionCerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a rare genetic condition with a broad phenotypic presentation. This study aims to establish the first Australian cohort of individuals affected by CADASIL (AusCADASIL) and examine its clinical features and longitudinal course, and to investigate neuroimaging and blood biomarkers to assist in early diagnosis and identify disease progression. MethodsParticipants will be recruited from six study centres across Australia for an observational study of CADASIL. We aim to recruit 150 participants with diagnosed CADASIL, family history of CADASIL or suspected CADASIL symptoms, and 150 cognitively normal NOTCH3 negative individuals as controls. Participants will complete: 1) online questionnaires on medical and family history, mental health, and wellbeing; 2) neuropsychological evaluation; 3) neurological examination and brain MRI; 4) ocular examination and 5) blood sample donation. Participants will have annual follow-up for 4 years to assess their progression and will be asked to invite a study partner to corroborate their self-reported cognitive and functional abilities.Primary outcomes include cognitive function and neuroimaging abnormalities. Secondary outcomes include investigation of genetics and blood and ocular biomarkers. Data from the cohort will contribute to an international consortium, and cohort participants will be invited to access future treatment/health intervention trials. DiscussionAusCADASIL will be the first study of an Australian cohort of individuals with CADASIL. The study will identify common pathogenic variants in this cohort, and characterise the pattern of clinical presentation and longitudinal progression, including imaging features, blood and ocular biomarkers and cognitive profile.

Infertility risk assessment with ultrasound in congenital adrenal hyperplasia male patients.

Testicular adrenal rest tumor (TART) is a prevalent complication associated with congenital adrenal hyperplasia (CAH), culminating in gonadal dysfunction and infertility. Early hormonal intervention is preventive, but excessive glucocorticoid poses risks. Developing reliable methods for early TART diagnosis and monitoring is crucial. The present study aims to formulate a scoring system to identify high-risk infertility through analysis of TART ultrasound features. Grayscale and power Doppler ultrasound were employed in this retrospective study to evaluate testicular lesions in male CAH patients. Lesion assessment encompassed parameters such as range, echogenicity, and blood flow, and these were subsequently correlated with semen parameters. Results of 49 semen analyzes from 35 patients demonstrated a notable inverse correlation between lesion scores and both sperm concentration (rs = - 0.83, P < 0.001) and progressive motility (rs = - 0.56, P < 0.001). The ROC curve areas for evaluating oligospermia and asthenozoospermia were calculated as 0.94 and 0.72, respectively. Establishing a lesion score threshold of 6 revealed a sensitivity of 75.00% and specificity of 93.94% for oligospermia and a sensitivity of 53.85% and specificity of 100.00% for asthenozoospermia. These findings underscore the potential utility of incorporating ultrasound into routine CAH patient management, facilitating timely interventions to preserve male fertility.

Screening for lung cancer using thin-slice low-dose computed tomography in southwestern China: a population-based real-world study.

Lung cancer is one of the most common malignant tumors threatening human life and health. At present, low-dose computed tomography (LDCT) screening for the high-risk population to achieve early diagnosis and treatment of lung cancer has become the first choice recommended by many authoritative international medical organizations. To further optimize the lung cancer screening method, we conducted a real-world study of LDCT lung cancer screening in a large sample of a healthy physical examination population, comparing differences in lung nodules and lung cancer detection between thin and thick-slice LDCT scanning. A total of 29 296 subjects who underwent low-dose thick-slice CT scanning (5 mm thickness) from January 2015 to December 2015 and 28 058 subjects who underwent low-dose thin-slice CT scanning (1 mm thickness) from January 2018 to December 2018 in West China Hospital were included. The positive detection rate, detection rate of lung cancer, pathological stage of lung cancer, and mortality rate of lung cancer were analyzed and compared between the two groups. The positive rate of LDCT screening in the thin-slice scanning group was significantly higher than that in the thick-slice scanning group (20.1% vs. 14.4%, p < 0.001). In addition, the lung cancer detection rate in the thin-slice LDCT screening positive group was significantly higher than that in the thick-slice scanning group (78.0% vs. 52.9%, p < 0.001). The screening positive rate of low-dose thin-slice CT scanning is higher and more early-stage lung cancer (IA1 stage) can be detected in the screen-positive group.