BACKGROUND

Down syndrome or trisomy 21, the most common chromosomal disorder, results from the presence of a third copy of chromosome 21 and manifests as mild to moderate intellectual disability, growth retardation, congenital heart defects, gastrointestinal abnormalities, and characteristic facial features. Several methods have been used to screen for Down syndrome in the prenatal period, such as ultrasound, biomarkers, cell-free DNA testing, and combinations of these tests. A positive result from one or more of these screening tests signals the need for confirmatory karyotyping to clinch the diagnosis. Ultrasound between 11 to 14 weeks of gestation can evaluate nuchal translucency (NT) to screen for Down syndrome. During the second trimester, a triple or quadruple test can also be performed alone or in addition to NT to quantify Down syndrome risk. In limited resource settings however, only the measurement of NT via ultrasound can be performed since biomarker tests are either unavailable or inaccessible. While the diagnostic performance of NT measurement alone has been investigated in several observational studies, there is no consensus on its performance as a sole test to screen for Down syndrome.

To determine the diagnostic performance of NT during prenatal first-trimester ultrasound as a screening test for Down syndrome.

We performed a systematic search on the PubMed, ProQuest, and Cochrane Library databases for recent systematic reviews and meta-analyses that addressed the objective. The existing reviews found were then independently appraised by the two reviewers with the AMSTAR-2 checklist. To update the existing reviews, a systematic search was done in the same databases to identify additional primary diagnostic studies, which were appraised using the QUADAS-2 tool. Random-effects univariate meta-analysis and summary receiving operator curve (HSROC) analysis for the outcomes were performed using Review Manager version 5.4 and R version 4.2.2, respectively. Subgroup analysis was performed by stratifying the baseline risk of mothers for fetal anomaly as low- or high-risk. Highrisk mothers were defined as women with risk factors such as advanced age, positive serum screen, presence of other ultrasound anomalies, and history of previous fetus with anomaly.

We found 22 cohort studies (n=225,846) of women at low-risk for fetal anomaly. The pooled sensitivity was 67.8% (95% CI: 61.4%-73.6%, I2=70.4%) and specificity was 96.3% (95% CI: 95.5%-96.9%, I2=96.7%). For low-risk women, the overall certainty of evidence was low, due to different modes of verification and heterogeneity not completely explained by variability in baseline risk or cut-points. Seven studies (n=9,197) were on high-risk women. The pooled sensitivity was 62.2% (95% CI: 54.1%-69.7%, I2=38.8%) and specificity was 96.5% (95% CI: 93.6%-98.1%, I2=95.5%). For women at high-risk, the evidence was rated as moderate due to differential verification.

Our analysis showed that NT measured through first-trimester ultrasound is specific for Down syndrome but has low sensitivity. Despite this, it is a useful screening test for Down syndrome in low-resource settings where other strategies may not be available or accessible. Furthermore, interpretation of NT results must take into consideration its limited sensitivity as this may lead to missed cases.

INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings. Machine learning (ML) models have strengths in disease prediction and early diagnosis. We explored the use of ML with oximetry, demographic and anthropometric data to diagnose OSA. METHODS: A total of 2,996 patients were included for modelling and divided into test and training sets. Seven commonly used supervised learning algorithms were trained with the data. Sensitivity (recall), specificity, positive predictive value (PPV) (precision), negative predictive value, area under the receiver operating characteristic curve (AUC) and F1 measure were reported for each model. RESULTS: In the best performing four-class model (neural network model predicting no, mild, moderate or severe OSA), a prediction of moderate and/or severe disease had a combined PPV of 94%; one out of 335 patients had no OSA and 19 had mild OSA. In the best performing two-class model (logistic regression model predicting no-mild vs. moderate-severe OSA), the PPV for moderate-severe OSA was 92%; two out of 350 patients had no OSA and 26 had mild OSA. CONCLUSION Our study showed that the prediction of moderate-severe OSA in a tertiary setting with an ML approach is a viable option to facilitate early identification of OSA. Prospective studies with home-based oximeters and analysis of other oximetry variables are the next steps towards formal implementation.
Humans ; Oximetry/methods* ; Sleep Apnea, Obstructive/diagnosis* ; Male ; Female ; Middle Aged ; Machine Learning ; Polysomnography ; Adult ; Anthropometry ; ROC Curve ; Aged ; Algorithms ; Predictive Value of Tests ; Sensitivity and Specificity ; Neural Networks, Computer ; Demography

INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback of patients for further management. Artificial intelligence (AI) has been viewed as a potential solution to augment the shortage of radiologists after hours. We explored the efficacy of an AI solution in the detection of appendicular and pelvic fractures for adult radiographs performed after hours at a general hospital ED in Singapore, and estimated the potential monetary and non-monetary benefits. METHODS: One hundred and fifty anonymised abnormal radiographs were retrospectively collected and fed through an AI fracture detection solution. The radiographs were re-read by two radiologist reviewers and their consensus was established as the reference standard. Cases were stratified based on the concordance between the AI solution and the reviewers' findings. Discordant cases were further analysed based on the nature of the discrepancy into overcall and undercall subgroups. Statistical analysis was performed to evaluate the accuracy, sensitivity and inter-rater reliability of the AI solution. RESULTS: Ninety-two examinations were included in the final study radiograph set. The AI solution had a sensitivity of 98.9%, an accuracy of 85.9% and an almost perfect agreement with the reference standard. CONCLUSION An AI fracture detection solution has similar sensitivity to human radiologists in the detection of fractures on ED appendicular and pelvic radiographs. Its implementation offers significant potential measurable cost, manpower and time savings.
Humans ; Singapore ; Emergency Service, Hospital ; Fractures, Bone/diagnostic imaging* ; Artificial Intelligence ; Retrospective Studies ; Adult ; Male ; Female ; Cost Savings ; Middle Aged ; Pelvic Bones/diagnostic imaging* ; Reproducibility of Results ; Aged ; Sensitivity and Specificity ; Radiography

INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers age, sex and cardiac troponin I (TnI) results to risk-stratify patients for type 1 myocardial infarction. METHOD: Patients aged ≥25 years who presented to the emergency department (ED) of Singapore General Hospital with symptoms suggestive of acute coronary syndrome with no diagnostic 12-lead electrocardiogram (ECG) changes were included. Participants had serial ECGs and high-sensitivity troponin assays performed at 0, 2 and 7 hours. The primary outcome was the adjudicated diagnosis of type 1 myocardial infarction at 30 days. We compared the performance of MI3 in predicting the primary outcome with the European Society of Cardiology (ESC) 0/2-hour algorithm as well as the 99th percentile upper reference limit (URL) for TnI. RESULTS: There were 1351 patients included (66.7% male, mean age 56 years), 902 (66.8%) of whom had only 0-hour troponin results and 449 (33.2%) with serial (both 0 and 2-hour) troponin results available. MI3 ruled out type 1 myocardial infarction with a higher sensitivity (98.9, 95% confidence interval [CI] 93.4-99.9%) and similar negative predictive value (NPV) 99.8% (95% CI 98.6-100%) as compared to the ESC strategy. The 99th percentile cut-off strategy had the lowest sensitivity, specificity, positive predictive value and NPV. CONCLUSION The MI3 algorithm was accurate in risk stratifying ED patients for myocardial infarction. The 99th percentile URL cut-off was the least accurate in ruling in and out myocardial infarction compared to the other strategies.
Humans ; Male ; Female ; Emergency Service, Hospital ; Middle Aged ; Electrocardiography ; Machine Learning ; Singapore ; Chest Pain/blood* ; Troponin I/blood* ; Myocardial Infarction/blood* ; Risk Assessment/methods* ; Aged ; Algorithms ; Acute Coronary Syndrome/blood* ; Adult ; Sensitivity and Specificity

As important biocatalysts, nitrilases can efficiently convert nitrile groups into acids and ammonia in a mild and eco-friendly manner, being widely used in the synthesis of important pharmaceutical intermediates. Early studies reported that nitrilases only had the hydrolysis activity of catalyzing the formation of corresponding carboxylic acid products from nitriles, showing catalytic specificity. However, recent studies have shown that some nitrilases exhibit the hydration activity for catalyzing the formation of amides from nitriles, showing catalytic promiscuity. The catalytic promiscuity of nitrilases has dual effects. On the one hand, the presence of amide by-products increases the difficulties and costs of subsequent separation and purification of carboxylic acid products. On the other hand, however, if the catalytic reaction pathways of nitrilases can be precisely regulated to reshape enzyme functions, the reactions catalyzed by nitrilases can be broadened to provide new ideas for the biosynthesis of high-value amides, which is crucial for the development of artificial enzymes and biocatalysis. This review summarized the research progress in the catalytic promiscuity of nitrilases and discussed the key regulatory factors that may affect the catalytic promiscuity of nitrilases from the evolutionary origin, catalytic domains, and catalytic mechanisms, hoping to provide reference and inspiration for the application of nitrilases in biocatalysis.
Aminohydrolases/chemistry* ; Biocatalysis ; Nitriles/chemistry* ; Substrate Specificity ; Catalytic Domain ; Catalysis

To screen and identify a chitosanase with high stability, we cloned the chitosanase gene from Bacillus atrophaeus with a high protease yield from the barren saline-alkali soil and expressed this gene in Escherichia coli. The expressed chitosanase of B. atrophaeus (BA-CSN) was purified by nickel-affinity column chromatography. The properties including optimal temperature, optimal pH, substrate specificity, and kinetic parameters of BA-CSN were characterized. The results showed that BA-CSN had the molecular weight of 31.13 kDa, the optimal temperature of 55 ℃, the optimal pH 5.5, and good stability at temperatures below 45 ℃ and pH 4.0-9.0. BA-CSN also had good stability within 4 h of pH 3.0 and 10.0, be activated by K⁺, Na⁺, Mn²⁺, Ca²⁺, Mg²⁺, and Co²⁺, (especially by Mn²⁺), and be inhibited by Fe³⁺, Cu²⁺, and Ag⁺. BA-CSN showcased the highest relative activity in the hydrolysis of colloidal chitosan, and it had good hydrolysis ability for colloidal chitin. Under the optimal catalytic conditions, BA-CSN demonstrated the Michaelis constant K_m and maximum reaction rate V_max of 9.94 mg/mL and 26.624 μmoL/(mL·min), respectively, for colloidal chitosan. In short, BA-CSN has strong tolerance to acids and alkali, possessing broad industrial application prospects.
Bacillus/genetics* ; Hydrogen-Ion Concentration ; Escherichia coli/metabolism* ; Glycoside Hydrolases/biosynthesis* ; Substrate Specificity ; Enzyme Stability ; Chitosan/metabolism* ; Temperature ; Kinetics ; Cloning, Molecular ; Bacterial Proteins/biosynthesis* ; Recombinant Proteins/genetics*

This study aims to establish an antibody detection method for porcine deltacoronavirus (PDCoV). The recombinant proteins PDCoV-N1 and PDCoV-N2 were expressed via the prokaryotic plasmid pColdII harboring the N gene sequence of the PDCoV strain CH/XJYN/2016. The reactivity and specificity of PDCoV-N1 and PDCoV-N2 with anti-PEDV sera were analyzed after the recombinant proteins were analyzed by SDS-PAGE and purified by the Ni-NTA Superflow Cartridge. Meanwhile, Western blotting and indirect immunofluorescence assay were carried out separately to validate the recombinant proteins PDCoV-N1 and PDCoV-N2. Finally, we established an indirect ELISA method based on the recombinant protein PDCoV-N2 after optimizing the conditions and tested the sensitivity, specificity, and reproducibility of the method. Then, the established method was employed to examine 102 clinical serum samples. The recombinant protein PDCoV-N2 showed low cross-reactivity with anti-PEDV sera. The optimal conditions of the indirect ELISA method based on PDCoV-N2 were as follows: the antigen coating concentration of 1.25 μg/mL and coating at 37 ℃ for 1 h; blocking by BSA overnight at 4 ℃; serum sample dilution at 1:50 and incubation at 37 ℃ for 1 h; secondary antibody dilution at 1:80 000 and incubation at 37 ℃ for 1 h; color development with TMB chromogenic solution at 37 ℃ for 10 min. The S/P value ≥ 0.45, ≤0.38, and between 0.45 and 0.38 indicated that the test sample was positive, negative, and suspicious, respectively. The testing results of the antisera against porcine epidemic diarrhea virus (PEDV), porcine circovirus 2 (PCV2), transmissible gastroenteritis virus (TGEV), foot-and-mouth disease virus (FMDV), and African swine fever virus (ASFV) showed that the S/P values were all less than 0.38. The testing results of the 800-fold diluted anti-PDCoV sera were still positive. The results of the inter- and intra-batch tests showed that the coefficients of variation of this method were less than 10%. Clinical serum sample test results showed the coincidence rate between this method and neutralization test was 94.12%. In this study, an ELISA method for the detection of anti-PDCoV antibodies was successfully established based on the truncated N protein of PDCoV. This method is sensitive, specific, stable, and reproducible, serving as a new method for the clinical diagnosis of PDCoV.
Animals ; Enzyme-Linked Immunosorbent Assay/methods* ; Swine ; Antibodies, Viral/blood* ; Recombinant Proteins/genetics* ; Deltacoronavirus/isolation & purification* ; Coronavirus Infections/virology* ; Swine Diseases/diagnosis* ; Coronavirus Nucleocapsid Proteins ; Sensitivity and Specificity

Hemoglobin A1c (HbA1c) has a unique structure that makes monoclonal antibody (mAb) preparation challenging. This study aims to develop a method for preparing HbA1c mAbs and establish a fluorescent immunochromatographic assay (FICA) for rapid detection of HbA1c. Three glycosylated peptides were synthesized and used to prepare complete antigens, which were identified by dot enzyme-linked immunosorbent assay (Dot-ELISA) and ultraviolet absorption spectroscopy. The complete antigens and natural HbA1c were used for cross-immunization of mice, and the optimal complete antigen was selected. The mouse with the highest serum titer was chosen for mAb preparation. The purity and specificity of the mAbs were verified, and a FICA method was developed. The optimal complete antigen, with a titer of 1:512 000, was successfully prepared and selected. Fusion with splenocytes resulted in four specific HbA1c antibodies (purity > 90%). The best antibody exhibited a binding constant (Ka) of 1.67×10¹⁰ L/mol with the antigen. Based on this antibody, a FICA method was successfully established, capable of producing results within 15 min. The method demonstrated a good linear range (3%-13% HbA1c, y=0.071 3x+0.005 6, R²=0.993 7), recovery rates of 98%-102%, precision < 10.00%, and no nonspecific reactions. Clinical testing of 210 samples showed positive agreement of 96.36%, negative agreement of 97.00%, and overall agreement of 96.68%. The receiver operating characteristic (ROC) curve analysis yielded an area under curve (AUC) of 0.980 9 [95% confidence interval (CI): 0.961 0-1.000 0], with high consistency verified in multicenter studies. We successfully developed a key technique for preparing HbA1c monoclonal antibodies and established a FICA method for rapid detection of HbA1c. It will provide an efficient and convenient detection method for the early diagnosis and long-term management of diabetes and its complications.
Antibodies, Monoclonal/biosynthesis* ; Animals ; Mice ; Glycated Hemoglobin/immunology* ; Mice, Inbred BALB C ; Humans ; Antibody Specificity ; Chromatography, Affinity/methods* ; Enzyme-Linked Immunosorbent Assay/methods* ; Female

Ochratoxin A (OTA) is ubiquitous in the food and feed fields. It has strong hepatotoxicity and nephrotoxicity, seriously threatening the health of humans and animals. Enzymatic degradation of mycotoxins is considered to be a promising method to control mycotoxin contaminations. In this study, a new ochratoxin A amidohydrolase from Microbulbifer thermotolerans (MiADH) was obtained. After heterologous expression in Escherichia coli and purification, the recombinant protein was studied regarding the hydrolysis activity, hydrolysis products, enzymatic properties, and substrate binding mode. MiADH can degrade OTA into ochratoxin α (OTα) and phenylalanine, demonstrating a detoxifying ability. It demonstrated the best performance at 70 ℃ and pH 8.0, and Cu²⁺ had the strongest inhibitory effect on the activity of MiADH. MiADH with good thermal stability exhibited huge potential for industrial application. Rational design guided by three-dimensional structural models and substrate docking analysis revealed the important amino acids affecting substrate binding and obtained multiple mutants with improved activity. Among these mutants, V324A had the highest activity, which was 4.2-fold that of the wild type. The identification of MiADH enriches the ochratoxin A degradation enzyme library and provides a new candidate enzyme for the biological detoxification of ochratoxin A in the food and feed industry.
Amidohydrolases/chemistry* ; Ochratoxins/metabolism* ; Substrate Specificity ; Escherichia coli/metabolism* ; Recombinant Proteins/metabolism* ; Actinomycetales/genetics*

Protein tyrosine phosphatases (PTPs, EC 3.1.3.48) are key regulators of cellular processes, with the catalytic activity attributed to the conserved motif (H/V)CX₅R(S/T), where cysteine and arginine residues are critical. Previous studies revealed that alternative splicing of extracellular phosphatase mRNA precursors in Metarhizium anisopliae generated two distinct transcripts, with the longer sequence containing a novel HCPTPMLS motif resembling PTP signatures but lacking the arginine residue. To identify the novel signature motif and characterize its enzymatic properties, we heterologously expressed and purified both proteins in Pichia pastoris and comprehensively characterized their enzymatic properties. The protein containing the HCPTPMLS motif (designated as L-protein) exhibited the highest activity at pH 5.5 and a strong preference for pTyr substrates. Its phosphatase activity was inhibited by Ag⁺, Zn²⁺, Cu²⁺, molybdate, and tungstate, but enhanced by Ca²⁺ and EDTA. AcP101 (lacking HCPTPMLS) showed the maximal activity at pH 6.5 and a strong preference toward pNPP (P < 0.05), with the activity inhibited by NaF and tartrate, but enhanced by Mg²⁺ and Mn²⁺. Functional analysis confirmed that the L-protein retained the PTP activity despite the absence of arginine in its signature motif, while AcP101 functioned as an acid phosphatase. This study provides the first functional validation of an arginine-deficient PTP motif, expanding the definition of PTP signature motifs and offering new insights for phosphatase classification.
Metarhizium/genetics* ; Protein Tyrosine Phosphatases/chemistry* ; Amino Acid Motifs ; Recombinant Proteins/biosynthesis* ; Amino Acid Sequence ; Pichia/metabolism* ; Fungal Proteins/chemistry* ; Substrate Specificity ; Saccharomycetales