Factors associated with the timely diagnosis of malaria and the utilization of types of healthcare facilities: a retrospective study in the Republic of Korea.

Objectives: This study aimed to analyze trends in the timely diagnosis of malaria cases over the past 10 years in relation to the utilization of different types of healthcare facilities. Methods: The study included 3,697 confirmed and suspected cases of malaria reported between January 1, 2013, and December 31, 2022, in the national integrative disease and healthcare management system. Some cases lacking a case report or with information missing from the case report were excluded from the analysis. A generalized linear model with a Poisson distribution was constructed to estimate rate ratios and 95% confidence intervals adjusted for other variables, such as distance. Results: When cases involving diagnosis >5 days after symptom onset in confirmed patients (5DD) were examined according to the type of healthcare facility, the rate ratio of 5DD cases was found to be higher for public health facilities than for tertiary hospitals. Specifically, the rate ratio was higher when the diagnosis was established at a tertiary hospital, even after a participant had visited primary or secondary hospitals. In an analysis adjusted for the distance to each participant's healthcare facility, the results did not differ substantially from the results of the crude analysis. Conclusion: It is imperative to improve the diagnostic capabilities of public facilities and raise awareness of malaria at primary healthcare facilities for effective prevention and control.

Radiographic Outcomes in Paediatric Bronchiectasis and Factors Associated with Reversibility.

RATIONALE: Conventionally considered irreversible, bronchiectasis reversibility in children has been demonstrated in small studies. However, the factors associated with radiographic reversibility in bronchiectasis have yet to be defined. OBJECTIVES: In a large cohort of children with bronchiectasis, we aimed to determine (a) if and to what extent bronchiectasis is reversible and (b) factors associated with radiographic chest high resolution computed tomography (cHRCT) resolution. METHODS: We identified children with bronchiectasis who had a repeat multidetector HRCT between 2010-2021. We excluded those with cystic fibrosis, surgical pulmonary resection, traction bronchiectasis only, or lobar opacification. MAIN RESULTS: cHRCT scans were scored using the modified Reiff-score (MRS) with a paediatric correction. Resolution was defined as absence of abnormal broncho-arterial ratio (>0.8) on the second cHRCT. We included 142 children (median age=5years: IQR 2.6-7.4), Inter- and intra-rater agreement in MRSs was excellent (weighted kappa=0.83-0.86 and 0.95 respectively). Radiographically resolution was documented in 57/142 (40.1%), improved in 56/142 (39.4%), unchanged/worse in 29/142 (20.4%). Pseudomonas aeruginosa (PsA) was absolutely associated with non-resolution. On multivariable regression, in those without PsA cultured, younger age-at-diagnosis (risk ratio (RR)=0.94, 95%CI 0.88-0.99) lower MRS (RR=0.89, 95% CI 0.82-0.97) and lower annual exacerbation rate requiring intravenous antibiotics (RR=0.60, 95%CI 0.37-0.98) increased the likelihood of radiographic resolution. CONCLUSIONS: This first large cohort confirms bronchiectasis in children is often reversible with appropriate management. Younger aged children and those with lesser radiographic severity at diagnosis were most likely to achieve radiographic reversibility whilst those with PsA infection were least likely.

Early diagnosis in ATTRv amyloidosis, how early is enough? How early is possible?

Hereditary transthyretin amyloidosis (ATTRv amyloidosis) is a rare, progressive, and debilitating genetic disorder characterized by the deposition of abnormal transthyretin (TTR) protein aggregates in various tissues, leading to organ dysfunction. Early diagnosis of ATTRv amyloidosis is critical for starting timely interventions and improving patient outcomes. This review explores the concepts of "how early is enough" and "how early is possible" in the context of diagnosing ATTRv amyloidosis, highlighting the challenges and opportunities for early recognition.

Beyond imagination: Sorting out and treating psychosis in the context of autism spectrum disorder.

In the last decades, growing caseness for Autism Spectrum Disorder (ASD) has been observed, owing to the diagnostic accretion of low-impairment forms, over and above other possible causes. Unrecognized ASD is likely to be mislabeled as a psychotic disorder (PD), as people in the spectrum may show 'pseudopsychotic' symptoms, resembling both negative and positive symptoms. On the other hand, PDs are likely to be overlooked when they arise in people with ASD, due to the 'diagnostic overshadowing' of new-onset conditions by lifelong core autistic symptoms. The three available metanalyses on the occurrence of psychosis in adults with ASD convergently reported a rate of PDs that is at least ten times higher than in the general population. Therefore, the lack of literature addressing risk factors, outcomes, and treatment options for psychosis in the context of ASD is utterly concerning. The present review aims to summarize up-to-date knowledge of PDs with comorbid ASD in terms of clinical features, course, and treatment.

Advancing fetal ultrasound diagnostics: Innovative methodologies for improved accuracy in detecting down syndrome.

This research work explores the integration of medical and information technology, particularly focusing on the use of data analytics and deep learning techniques in medical image processing. Specifically, it addresses the diagnosis and prediction of fetal conditions, including Down Syndrome (DS), through the analysis of ultrasound images. Despite existing methods in image segmentation, feature extraction, and classification, there is a pressing need to enhance diagnostic accuracy. Our research delves into a comprehensive literature review and presents advanced methodologies, incorporating sophisticated deep learning architectures and data augmentation techniques to improve fetal diagnosis. Moreover, the study emphasizes the clinical significance of accurate diagnostics, detailing the training and validation process of the AI model, ensuring ethical considerations, and highlighting the potential of the model in real-world clinical settings. By pushing the boundaries of current diagnostic capabilities and emphasizing rigorous clinical validation, this research work aims to contribute significantly to medical imaging and pave the way for more precise and reliable fetal health assessments.

Timely Pulmonary Tuberculosis Diagnosis Based on the Epidemiological Disease Spectrum: Population-Based Prospective Cohort Study in the Republic of Korea.

BACKGROUND: Timely pulmonary tuberculosis (PTB) diagnosis is a global health priority for interrupting transmission and optimizing treatment outcomes. The traditional dichotomous time-divided approach for addressing time delays in diagnosis has limited clinical application because the time delay significantly varies depending on each community in question. OBJECTIVE: We aimed to reevaluate the diagnosis time delay based on the PTB disease spectrum using a novel scoring system that was applied at the national level in the Republic of Korea. METHODS: The Pulmonary Tuberculosis Spectrum Score (PTBSS) was developed based on previously published proposals related to the disease spectrum, and its validity was assessed by examining both all-cause and PTB-related mortality. In our analysis, we integrated the PTBSS into the Korea Tuberculosis Cohort Registry. We evaluated various time delays, including patient, health care, and overall delays, and their system-associated variables in line with each PTBSS. Furthermore, we reclassified the scores into distinct categories of mild (PTBSS=0-1), moderate (PBTBSS=2-3), and severe (PBTBSS=4-6) using a multivariate regression approach. RESULTS: Among the 14,031 Korean patients with active PTB whose data were analyzed from 2018 to 2020, 37% (n=5191), 38% (n=5328), and 25% (n=3512) were classified as having a mild, moderate, and severe disease status, respectively, according to the PTBSS. This classification can therefore reflect the disease spectrum of PTB by considering the correlation of the score with mortality. The time delay patterns differed according to the PTBSS. In health care delays according to the PTBSS, greater PTB disease progression was associated with a shorter diagnosis period, since the condition is microbiologically easy to diagnose. However, with respect to patient delays, the change in elapsed time showed a U-shaped pattern as PTB progressed. This means that a remarkable patient delay in the real-world setting might occur at both apical ends of the spectrum (ie, in both mild and severe cases of PTB). Independent risk factors for a severe PTB pattern were age (adjusted odds ratio 1.014) and male sex (adjusted odds ratio 1.422), whereas no significant risk factor was found for mild PTB. CONCLUSIONS: Timely PTB diagnosis should be accomplished. This can be improved with use of the PTBSS, a simple and intuitive scoring system, which can be more helpful in clinical and public health applications compared to the traditional dichotomous time-only approach.

Relationship between health checkups and cancer screenings of wives and health checkups of their husbands: A cross-sectional study in Japan.

Objectives: This study investigated the relationship between health checkups, cervical cancer screenings, and breast cancer screenings (collectively referred to as wellness examinations) of wives and health checkups of their husbands. We aimed to develop strategies to encourage wellness examinations among married individuals in Japan. Methods: This study used the 2019 Comprehensive Survey of Living Conditions, focusing on married couples aged 40-64. We analyzed the percentage of wives undergoing wellness examinations, grouped based on whether their husbands had undergone health checkups. Subsequently, multivariable modified Poisson regression analysis was performed considering sociodemographic and health-related factors. All analyses considered medical insurance of wives because wellness examination methods varied depending on medical insurance type. Results: The sample comprised 40,560 couples undergoing health checkups, 39,870 undergoing cervical cancer screening, and 39,895 undergoing breast cancer screening. Regardless of the medical insurance type of the wife, a significant positive association was observed between the wellness examination of wives and the health checkup of husbands across all age groups. After adjusting for covariates, prevalence ratios (95% confidence intervals) for wives whose husbands underwent health checkups were 2.24 (2.09-2.40) for national health insurance, 1.18 (1.16-1.21) for employee insurance (employee), and 1.53 (1.44-1.63) for employee insurance (family) for health checkups. Similar trends were observed in cervical and breast cancer screening. Conclusions: Wellness examinations of wives were associated with those of their husbands, suggesting that couples often share similar health-seeking behaviors. Hence, targeted interventions are important for couples who do not undergo wellness examinations.

Predicting early gastric cancer risk using machine learning: A population-based retrospective study.

Background: Early detection and treatment are crucial for reducing gastrointestinal tumour-related mortality. The diagnostic efficiency of the most commonly used diagnostic markers for gastric cancer (GC) is not very high. A single laboratory test cannot meet the requirements of early screening, and machine learning methods are needed to aid the early diagnosis of GC by combining multiple indicators. Methods: Based on the XGBoost algorithm, a new model was developed to distinguish between GC and precancerous lesions in newly admitted patients between 2018 and 2023 using multiple laboratory tests. We evaluated the ability of the prediction score derived from this model to predict early GC. In addition, we investigated the efficacy of the model in correctly screening for GC given negative protein tumour marker results. Results: The XHGC20 model constructed using the XGBoost algorithm could distinguish GC from precancerous disease well (area under the receiver operating characteristic curve [AUC] = 0.901), with a sensitivity, specificity and cut-off value of 0.830, 0.806 and 0.265, respectively. The prediction score was very effective in the diagnosis of early GC. When the cut-off value was 0.27, and the AUC was 0.888, the sensitivity and specificity were 0.797 and 0.807, respectively. The model was also effective at evaluating GC given negative conventional markers (AUC = 0.970), with the sensitivity and specificity of 0.941 and 0.906, respectively, which helped to reduce the rate of missed diagnoses. Conclusions: The XHGC20 model established by the XGBoost algorithm integrates information from 20 clinical laboratory tests and can aid in the early screening of GC, providing a useful new method for auxiliary laboratory diagnosis.

Recent advances in functional nucleic acid decorated nanomaterials for cancer imaging and therapy.

Nanomaterials possess unusual physicochemical properties including unique optical, magnetic, electronic properties, and large surface-to-volume ratio. However, nanomaterials face some challenges when they were applied in the field of biomedicine. For example, some nanomaterials suffer from the limitations such as poor selectivity and biocompatibility, low stability, and solubility. To address the above-mentioned obstacles, functional nucleic acid has been widely served as a powerful and versatile ligand for modifying nanomaterials because of their unique characteristics, such as ease of modification, excellent biocompatibility, high stability, predictable intermolecular interaction and recognition ability. The functionally integrating functional nucleic acid with nanomaterials has produced various kinds of nanocomposites and recent advances in applications of functional nucleic acid decorated nanomaterials for cancer imaging and therapy were summarized in this review. Further, we offer an insight into the future challenges and perspectives of functional nucleic acid decorated nanomaterials.

Celiac Disease-Related Enamel Defects: A Systematic Review.

INTRODUCTION: This systematic review aims to elucidate the intricate correlation between celiac disease (CD) and dental enamel defects (DED), exploring pathophysiological mechanisms, oral health implications, and a dentist's role in early diagnosis. MATERIALS AND METHODS: Following PRISMA guidelines, a comprehensive search from 1 January 2013 to 1 January 2024 across PubMed, Cochrane Library, Scopus, and Web of Science identified 153 publications. After exclusions, 18 studies met the inclusion criteria for qualitative analysis. Inclusion criteria involved study types (RCTs, RCCTs, case series), human participants, English language, and full-text available. RESULTS: The search yielded 153 publications, with 18 studies meeting the inclusion criteria for qualitative analysis. Notable findings include a high prevalence of DED in CD patients, ranging from 50 to 94.1%. Symmetrical and chronological defects, according to Aine's classification, were predominant, and significant associations were observed between CD severity and enamel defect extent. CONCLUSIONS: The early recognition of oral lesions, particularly through Aine's classification, may signal potential CD even in the absence of gastrointestinal symptoms. Correlations between CD and dental health conditions like molar incisor hypomineralization (MIH) emphasize the dentist's crucial role in early diagnosis. Collaboration between dentists and gastroenterologists is essential for effective monitoring and management. This review consolidates current knowledge, laying the groundwork for future research and promoting interdisciplinary collaboration for improved CD-related oral health outcomes. Further large-scale prospective research is recommended to deepen our understanding of these issues.

Role of Hematological Parameters in the Early Diagnosis of Neonatal Sepsis.

The major cause of neonatal mortality and morbidity is bacterial sepsis. Blood culture is the most reliable method in neonatal sepsis. This study was conducted to study the usefulness of hematological parameters in the early diagnosis of neonatal sepsis and to assess the most sensitive and specific variables in diagnosing neonatal sepsis. This prospective study was conducted in a tertiary care hospital from January 2017 to January 2018. Peripheral blood smears were prepared from patients with clinical suspicion of sepsis or predisposing perinatal factors for sepsis and stained with Field's stain and examined. The hematological findings were analyzed according to the hematologic scoring system of Rodwell. It was found that immature PMN count, I: M ratio, and I: T ratio had the highest sensitivity (92.06%, 87.30%, and 74.60%, respectively) while I: M ratio, I: T ratio, and degenerative changes in PMN had the highest specificity (97.50%, 96.50%, and 94.0%, respectively) in the prediction of sepsis.

Características epidemiológicas, clínicas y funcionales de los pacientes mayores de 75 años ingresados en un hospital terciario durante la primera ola pandémica por SARS-CoV-2 / Epidemiological, clinical, and functional characteristics of patients older than 75 years admitted to a tertiary hospital during the first wave of the SARS-CoV-2 pandemic

Fundamento: Analizar las características epidemiológicas, clínicas y funcionales de los pacientes ingresados en el Hospital Universitario de Navarra por infección por SARS-CoV-2, así como los factores predictores de mortalidad, durante la primera ola de la pandemia provocada por este virus. Metodología: Estudio observacional y retrospectivo de todos los pacientes hospitalizados mayores de 75 años entre marzo y noviembre de 2020. Se ha obtenido información sobre múltiples variables, entre las que cabe destacar los síndromes geriátricos previos y que han aparecido durante la hospitalización, o los antecedentes médicos considerados relevantes en la infección por SARS-CoV-2. Se ha realizado un análisis descriptivo de los datos, comparaciones según diversos factores de interés y análisis multivariable para analizar los factores asociados a la mortalidad. Resultados: Se obtuvieron datos de un total de 426 pacientes cuya edad media fue de 83,2 años (52,6% varones). El 34,7% fallecieron en el hospital y el 4,5% antes de un mes tras el alta hospitalaria. Los factores relacionados con la mortalidad fueron: peor situación funcional basal, enfermedad renal crónica y fiebre o disnea como formas de presentación. Los síntomas típicos más frecuentes fueron: fiebre, disnea, tos, astenia e hiporexia. Hasta el 42,1% presentaron delirium como síntoma de inicio atípico. Se objetivó un deterioro funcional que no se recuperó al mes de seguimiento (índice de Barthel basal 81,12; 70,08 al alta; 75,55 al mes). Conclusiones: La infección por SARS-CoV-2 ha provocado elevadas tasas de mortalidad en las personas mayores. En este grupo etario, es frecuente la forma de presentación atípica de esta enfermedad y el deterioro funcional durante la hospitalización. En el presente estudio se ha identificado un peor estado funcional previo como predictor de mortalidad. Son necesarios más estudios que evalúen el impacto que la enfermedad y la hospitalización tienen en el paciente mayor...(AU)

Background: The objective of the present study is to analyze the epidemiological, clinical and functional characteristics of patients admitted to the University Hospital of Navarra due to SARS-CoV-2 infection, as well as the predictors of mortality, during the first wave of the pandemic caused by this virus. Methodology: An observational, retrospective study was performed, including all hospitalized patients older than 75 years. Information has been obtained on multiple variables, among which it is worth mentioning previous geriatric syndromes or those that have appeared during hospitalization, or past medical history considered relevant in SARS-CoV-2 infection. A descriptive analysis of the data, comparisons according to various factors of interest and multivariate analysis to analyze factors associated with mortality were carried out. Results: Data have been obtained from a total of 426 patients with a mean age of 83.2 years (52.6% men). 34.7% died in hospital and 4.5% within 1 month after hospital discharge. The factors related to mortality were: worse baseline functional status, chronic kidney disease, and fever or dyspnea as forms of presentation. The most frequent typical symptoms were: fever, dyspnea, cough, asthenia and hyporexia. Up to 42.1% presented delirium as a symptom of atypical onset. We observed a functional deterioration that was not recover after a month of follow-up (baseline Barthel index 81.12; 70.08 at discharge; 75.55 after a month). Conclusions: SARS-CoV-2 infection has caused high mortality rates in older adults. In this age group, the atypical presentation of this disease and functional deterioration during hospitalization are frequent. In the present study, a worse previous functional status has been identified as a predictor of mortality. More studies are needed to evaluate the impact that the disease and hospitalization have on the older patient...(AU)

Clinical suspicion, diagnosis and management of cardiac amyloidosis: update document and executive summary.

In recent years, the interest in cardiac amyloidosis has grown exponentially. However, there is a need to improve our understanding of amyloidosis in order to optimise early detection systems. Therefore, it is crucial to incorporate solutions to improve the suspicion, diagnosis and follow-up of cardiac amyloidosis. In this sense, we designed a tool following the different phases to reach the diagnosis of cardiac amyloidosis, as well as an optimal follow-up: a) clinical suspicion, where the importance of the "red flags" to suspect it and activate the diagnostic process is highlighted; 2) diagnosis, where the diagnostic algorithm is mainly outlined; and 3) follow-up of confirmed patients. This is a practical resource that will be of great use to all professionals caring for patients with suspected or confirmed cardiac amyloidosis, to improve its early detection, as well as to optimise its accurate diagnosis and optimal follow-up.

Synaptic vesicle glycoprotein 2 A in serum is an ideal biomarker for early diagnosis of Alzheimer's disease.

BACKGROUND: Previous studies have demonstrated that early intervention was the best plan to inhibit the progression of Alzheimer's disease (AD), which relied on the discovery of early diagnostic biomarkers. In this study, synaptic vesicle glycoprotein 2 A (SV2A) was examined to improve the early diagnostic efficiency in AD. METHODS: In this study, biomarker testing was performed through the single-molecule array (Simoa). A total of 121 subjects including cognitively unimpaired controls, amnestic mild cognitive impairment (aMCI), AD and other types of dementia underwent cerebrospinal fluid (CSF) SV2A testing; 430 subjects including health controls, aMCI, AD and other types of dementia underwent serum SV2A, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL) and p-tau217 testing; 92 subjects including aMCI and AD underwent both CSF SV2A and serum SV2A testing; 115 cognitively unimpaired subjects including APOE ε4 carriers and APOE ε4 non-carriers were tested for serum SV2A, GFAP, NfL and p-tau217. Then, the efficacy of SV2A for the early diagnosis of AD and its ability to identify those at high risk of AD from a cognitively unimpaired population were further analyzed. RESULTS: Both CSF and serum SV2A significantly and positively correlated with cognitive performance in patients with AD, and their levels gradually decreased with the progression of AD. Serum SV2A demonstrated excellent diagnostic efficacy for aMCI, with a sensitivity of 97.8%, which was significantly higher than those of NfL, GFAP, and p-tau217. The SV2A-positive rates ranged from 92.86 to 100% in aMCI cases that were negative for the above three biomarkers. Importantly, of all the biomarkers tested, serum SV2A had the highest positivity rate (81.82%) in individuals at risk for AD. CONCLUSIONS: Serum SV2A was demonstrated to be a novel and ideal biomarker for the early diagnosis of AD, which can effectively distinguish those at high risk of AD in cognitively unimpaired populations.

Partnering Early to Provide for Infants At Risk of Cerebral Palsy (PEPI ARC): protocol for a feasibility study of a regional hub for early detection of cerebral palsy in Aotearoa New Zealand.

Introduction: Cerebral palsy (CP) can now be diagnosed in infants with identified CP risk factors as early as three months of age; however, many barriers prevent equitable access to early detection pathways. The "Partnering Early to Provide for Infants At Risk of Cerebral Palsy" feasibility study (PEPI ARC) seeks to trial a new approach to decrease inequitable health service in Aotearoa New Zealand for high-risk infants and their families. PEPI ARC incorporates face-to-face clinics, an in-person and virtual Hub, and the use of telehealth to enable flexible access to CP assessments and support for health professionals in early CP detection. Methods and analysis: A non-randomised feasibility study was conducted from a tertiary Neonatal Intensive Care Unit (NICU) in Wellington and included seven regional referral centres, servicing nearly 30% of the total population in New Zealand (NZ). The families of infants with a high risk of neurodevelopmental impairment and health professionals interacting with the Hub were invited to participate. Mixed methods were used to evaluate the (i) equitable implementation of an early detection pathway, (ii) acceptability, (iii) demand among families and health professionals, (iv) efficacy in relation to reducing the age of receipt of CP diagnosis, and (v) the experiences around communication and information sharing. Ethics and dissemination: The NZ Health and Disability Ethics Committee approved this study (HDEC: 2022 FULL 13434). The findings will be disseminated in peer-reviewed journals, in conference presentations, and via professional networks. Clinical trial registration: Australian New Zealand Clinical Trials Registry: ACTRN12623000600640.

Study on exosomes for identifying bipolar disorder in early stage: A cross-sectional and validation study protocol.

BACKGROUND: The difficulty is remained to accurately distinguish bipolar disorder (BD) from major depressive disorder (MDD) in early stage, with a delayed diagnosis for 5-10 years. BD patients are often treated with antidepressants systematically due to being diagnosed with MDD, affecting the disease course and clinical outcomes. The current study aims to explore the role of plasma exosomes as biomarker to distinguish BD from MDD in early stage. METHODS: Two stages are included. The first stage is a cross-sectional study, comparing the concentrations of plasma exosome microRNA and related proteins among BD group, MDD group, and healthy controls (HC) group (n = 40 respectively), to identify target biomarkers preliminarily. The "Latent Class Analysis" and "Receiver Operating Characteristic" analysis will be performed to determine the optimal concentration range for each biomarker. The second stage is to validate target markers in subjects, coming from an ongoing study focusing on patients with a first depressive episode. All target biomarkers will be test in plasma samples reserved at the initial stage to detect whether the diagnosis indicated by biomarker level is consistent with the diagnosis by DSM-5. Furthermore, the correlation between specific biomarkers and the manic episode, suicidal ideation, and adverse reactions will also be observed. DISCUSSION: Exosome-derived microRNA and related proteins have potential in serving as a good medium for exploring mental disorders because it can pass through the blood-brain barrier bidirectionally and convey a large amount of information stably. Improving the early diagnosis of BD would help implement appropriate intervention strategy as early as possible and significantly reduce the burden of disease.

Early identification of patients at risk for iron-deficiency anemia using deep learning techniques.

OBJECTIVES: Iron-deficiency anemia (IDA) is a common health problem worldwide, and up to 10% of adult patients with incidental IDA may have gastrointestinal cancer. A diagnosis of IDA can be established through a combination of laboratory tests, but it is often underrecognized until a patient becomes symptomatic. Based on advances in machine learning, we hypothesized that we could reduce the time to diagnosis by developing an IDA prediction model. Our goal was to develop 3 neural networks by using retrospective longitudinal outpatient laboratory data to predict the risk of IDA 3 to 6 months before traditional diagnosis. METHODS: We analyzed retrospective outpatient electronic health record data between 2009 and 2020 from an academic medical center in northern Texas. We included laboratory features from 30,603 patients to develop 3 types of neural networks: artificial neural networks, long short-term memory cells, and gated recurrent units. The classifiers were trained using the Adam Optimizer across 200 random training-validation splits. We calculated accuracy, area under the receiving operating characteristic curve, sensitivity, and specificity in the testing split. RESULTS: Although all models demonstrated comparable performance, the gated recurrent unit model outperformed the other 2, achieving an accuracy of 0.83, an area under the receiving operating characteristic curve of 0.89, a sensitivity of 0.75, and a specificity of 0.85 across 200 epochs. CONCLUSIONS: Our results showcase the feasibility of employing deep learning techniques for early prediction of IDA in the outpatient setting based on sequences of laboratory data, offering a substantial lead time for clinical intervention.

Single cell glycan-linkages profiling for hepatocellular carcinoma early diagnosis using lanthanide encoded bacteriophage MS2 based ICP-MS.

Early diagnosis is paramount for enhancing survival rates and prognosis in the context of malignant diseases. Hepatocellular carcinoma (HCC), the second leading cause of cancer-related deaths worldwide, poses significant challenges for its early detection. In this study, we present an innovative approach which contributed to the early diagnosis of HCC. By lanthanide encoding signal amplification to map glycan-linkages at the single-cell level, the minute quantities of "soft" glycan-linkages on single cell surface were converted into "hard" elemental tags through the use of an MS2 signal amplifier. Harnessing the power of lanthanides encoded within MS2, we achieve nearly three orders of magnitude signal amplification. These encoded tags are subsequently quantified using single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS). Linear discriminant analysis (LDA) identifies seven specific glycan-linkages (α-2,3-Sia, α-Gal, α-1,2-Fuc, α-1,6-Fuc, α-2,6-Sia, α-GalNAc, and Gal-ß-1,3-GalNAc) as biomarkers. Our methodology is initially validated at the cellular level with 100% accuracy in discriminating between hepatic carcinoma HepG2 cells and their normal HL7702 cells. We apply this approach to quantify and classify glycan-linkages on the surfaces of 55 clinical surgical HCC specimens. Leveraging these seven glycan-linkages as biomarkers, we achieve precise differentiation between 8 normal hepatic specimens, 40 early HCC specimens, and 7 colorectal metastasis HCC specimens. This pioneering work represents the first instance of employing single-cell glycan-linkages as biomarkers promising for the early diagnosis of HCC with a remarkable 100% predictive accuracy rate, which holds immense potential for enhancing the feasibility and precision of HCC diagnosis in clinical practice.

Masqueraded sebaceous gland carcinoma of the lower eyelid in a young pregnant patient.

The purpose of this case report is to present misdiagnosed sebaceous gland carcinoma of the lower eyelid with rapid growth in a young woman during pregnancy. Eyelid sebaceous gland carcinoma is a relatively rare tumor and a disease primarily of older patients. It occurs more commonly in oriental populations and with a predilection for the upper eyelid. Early diagnosis and appropriate treatment may help improve disease control and patient survival.