Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging.

Single-molecule localization microscopy in a typical wide-field setup has been widely used for investigating subcellular structures with super resolution; however, field-dependent aberrations restrict the field of view (FOV) to only tens of micrometers. Here, we present a deep-learning method for precise localization of spatially variant point emitters (FD-DeepLoc) over a large FOV covering the full chip of a modern sCMOS camera. Using a graphic processing unit-based vectorial point spread function (PSF) fitter, we can fast and accurately model the spatially variant PSF of a high numerical aperture objective in the entire FOV. Combined with deformable mirror-based optimal PSF engineering, we demonstrate high-accuracy three-dimensional single-molecule localization microscopy over a volume of ~180 × 180 × 5 µm3, allowing us to image mitochondria and nuclear pore complexes in entire cells in a single imaging cycle without hardware scanning; a 100-fold increase in throughput compared to the state of the art.

Highly Reactive Graphene Dispersant and Its Effective Reinforcement for Phase Change Coatings.

High efficient dispersant that meanwhile possesses additional functions is highly desirable for the fabrication of graphene-based composite. In this paper, a new reactive dispersant, multi-silanols grafted naphthalenediamine (MSiND), is synthesized, which shows superiority compared with conventional dispersants. It can not only stabilize graphene in water at a high concentration of up to 16 mg mL-1 , but also simultaneously be applicable for ethanol medium, in which the graphene concentration can be as high as 12 mg mL-1 at the weight ratio of 1:1 (MSiND:graphene). The dispersion is compatible with multi-matrixes and affinity to various substrates. In addition, MSiND exhibits excellent reactivity due to the existence of high-density silanol groups. Tough graphene coatings are constructed on glass slides and non-woven fabric simply by direct painting and dip-coating. Moreover, with the assistance of MSiND, graphene-doped phase-change coatings on hydrophobic non-woven fabric (e.g., functional mask) are prepared via the spray method. The composite coatings show enhanced mechanical strength and excellent energy storage performance, exhibiting great potential in heat preservation and thermotherapy.

Phenotypic and genotypic analysis of 11 fetal cases with Bardet-Biedl syndrome.

OBJECTIVE: To present the prenatal sonographic features and genomic spectrum of pregnancies with fetal Bardet-Biedl syndrome (BBS). METHODS: This was a retrospective study of 11 cases with BBS diagnosed by prenatal ultrasound and confirmed by genetic testing. Clinical and laboratory data were collected and reviewed for these cases, including maternal demographics, prenatal sonographic findings, molecular testing sequencing results, and pregnancy outcomes. RESULTS: All cases had unremarkable first-trimester ultrasound scans without reporting limb malformations. All had second-trimester abnormal ultrasounds: postaxial polydactyly in nine cases (9/11), renal abnormalities in seven (7/11), reduced amniotic fluid volume in two (2/11), central nervous system anomalies in two (2/11), and ascites in three (3/11). Ten fetuses presented with at least two-system anomalies, and one (Case 11) presented with only postaxial polydactyly. Variants were detected in five genes, including BBS2, ARL6/BBS3, BBS7, CEP290/BBS14 and IFT74/BBS22. Ten pregnancies were terminated in the second trimester, while one continued to term. CONCLUSION: Enlarged hyperechogenic kidneys and postaxial polydactyly are the two most common sonographic features of fetal BBS. Prenatal diagnosis of BBS can be done with ultrasound and genetic testing although the diagnosis may be made in the second trimester.

Pain Sensitivity and Acute Postoperative Pain in Patients Undergoing Abdominal Surgery: The Mediating Roles of Pain Self-Efficacy and Pain Catastrophizing.

BACKGROUND: Inadequately managed postoperative pain remains a common issue. Examining factors like pain sensitivity, pain catastrophizing, and pain self-efficacy can help improve postoperative pain management. While these factors have been identified as potential predictors of acute postoperative pain, their effects have been inconsistent. Few studies have explored the interactions between these factors. AIM: To investigate the influence of preoperative pain sensitivity, pain catastrophizing, and pain self-efficacy on acute postoperative pain in abdominal surgery patients and to determine the mediating roles of pain catastrophizing and pain self-efficacy in the relationship between pain sensitivity and acute postoperative pain, as per the gate control theory. METHODS: A total of 246 patients were enrolled in this study. General information was collected before surgery, and the Pain Sensitivity Questionnaire (PSQ), Pain Catastrophizing Scale (PCS), and Pain Self-Efficacy Questionnaire (PSEQ) were administered. After surgery, patients' average pain scores over the 24 hours were reported using the Numerical Rating Scale (NRS). Correlation analyses and a structural equation model were used to examine the relationships among these variables. RESULTS: NRS scores over 3 during the 24 hours post-surgery were reported by 21.54% of patients. Postoperative acute pain was found to be associated with pain sensitivity (rs = 0.463, p < .001), pain catastrophizing (rs = 0.328, p < .001), and pain self-efficacy (rs = -0.558, p < .001). A direct effect on postoperative acute pain was exerted by pain sensitivity (effect = 0.250, p = .001), along with indirect effects through: (A) pain catastrophizing (effect = 0.028, p = .001); (B) pain self-efficacy (effect = 0.132, p = .001); and (C) the chain mediation of pain self-efficacy and pain catastrophizing (effect = 0.021, p = .008). CONCLUSIONS: The severity of postoperative acute pain can be predicted by pain self-efficacy and pain catastrophizing, and the connection between moderate pain sensitivity and postoperative acute pain severity is mediated by them. Therefore, intervention programs aimed at boosting pain self-efficacy and reducing pain catastrophizing can enhance postoperative pain outcomes for abdominal surgery patients.

Fetal Phenotype of CHARGE Syndrome with a Molecular Confirmation: A Series of 13 Cases.

INTRODUCTION: CHARGE syndrome is an autosomal dominant genetic disorder with known pattern of features. The aim of the study was to present the fetal features of CHARGE syndrome to gain awareness that the antenatal characteristics can be very nonspecific. CASE PRESENTATION: This was a retrospective study of 13 cases with CHARGE syndrome diagnosed by prenatal or postnatal genetic testing and physical examination. Two (15.4%; 2/13) had normal ultrasound scans during pregnancy. One (7.7%; 1/13) with first-trimester cystic hygroma presented intrauterine fetal demise at 16 weeks gestation. The remaining 10 (76.9%; 10/13) cases had abnormal ultrasound features in utero; among these, 1 had an increased nuchal translucency in the first trimester, 5 had second-trimester abnormal ultrasounds including micrognathia, cardiac defects, and facial defects, and 4 third-trimester abnormal ultrasounds including micrognathia, isolated fetal growth restriction, and polyhydramnios. Among the 11 cases with abnormal prenatal ultrasound scans, no fetus could reach the diagnostic criteria of CHARGE syndrome if only based on the results of ultrasound. However, the diagnosis was made in all cases when CHD7 defects were detected. DISCUSSION/CONCLUSION: The CHARGE syndrome presents non-specific abnormal ultrasound markers in utero. Exome sequencing in the genetic workup will aid in prenatal diagnosis of this syndrome.

Visual Detection of Road Cracks for Autonomous Vehicles Based on Deep Learning.

Detecting road cracks is essential for inspecting and assessing the integrity of concrete pavement structures. Traditional image-based methods often require complex preprocessing to extract crack features, making them challenging when dealing with noisy concrete surfaces in diverse real-world scenarios, such as autonomous vehicle road detection. This study introduces an image-based crack detection approach that combines a Random Forest machine learning classifier with a deep convolutional neural network (CNN) to address these challenges. Three state-of-the-art models, namely MobileNet, InceptionV3, and Xception, were employed and trained using a dataset of 30,000 images to build an effective CNN. A systematic comparison of validation accuracy across various base learning rates identified a base learning rate of 0.001 as optimal, achieving a maximum validation accuracy of 99.97%. This optimal learning rate was then applied in the subsequent testing phase. The robustness and flexibility of the trained models were evaluated using 6,000 test photos, each with a resolution of 224 × 224 pixels, which were not part of the training or validation sets. The outstanding results, boasting a remarkable 99.95% accuracy, 99.95% precision, 99.94% recall, and a matching 99.94% F1 Score, unequivocally affirm the efficacy of the proposed technique in precisely identifying road fractures in photographs taken on real concrete surfaces.

Development of a nomogram for predicting acute pain among patients after abdominal surgery: A prospective observational study.

AIMS: To develop a nomogram to provide a screening tool for recognising patients at risk of post-operative pain undergoing abdominal operations. BACKGROUND: Risk prediction models for acute post-operative pain can allow initiating prevention strategies, which are valuable for post-operative pain management and recovery. Despite the increasing number of studies on risk factors, there were inconsistent findings across different studies. In addition, few studies have comprehensively explored predictors of post-operative acute pain and built prediction models. DESIGN: A prospective observational study. METHODS: A total of 352 patients undergoing abdominal operations from June 2022 to December 2022 participated in this investigation. A nomogram was developed for predicting the probability of acute pain after abdominal surgery according to the results of binary logistic regression. The nomogram's predictive performance was assessed by discrimination and calibration. Internal validation was performed via Bootstrap with 1000 re-samplings. RESULTS: A total of 139 patients experienced acute post-operative pain following abdominal surgery, with an incidence of 39.49%. Age <60, marital status (unmarried, divorced, or widowed), consumption of intraoperative remifentanil >2 mg, indwelling of drainage tubes, poor quality sleep, high pain catastrophizing, low pain self-efficacy, and PCIA not used were predictors of inadequate pain control in patients after abdominal surgery. Using these variables, we developed a nomogram model. All tested indicators showed that the model has reliable discrimination and calibration. CONCLUSIONS: This study established an online dynamic predictive model that can offer an individualised risk assessment of acute pain after abdominal surgery. Our model had good differentiation and calibration and was verified internally as a useful tool for risk assessment. RELEVANCE TO CLINICAL PRACTICE: The constructed nomogram model could be a practical tool for predicting the risk of experiencing acute post-operative pain in patients undergoing abdominal operations, which would be helpful to realise personalised management and prevention strategies for post-operative pain. REPORTING METHOD: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were adopted in this study. PATIENT OR PUBLIC CONTRIBUTION: Before the surgery, research group members visited the patients who met the inclusion criteria and explained the purpose and scope of the study to them. After informed consent, they completed the questionnaire. The patients' pain scores (VAS) were regularly assessed and documented by the bedside nurse for the first 3 days following surgery. Other information was obtained from medical records.

Prenatal Diagnosis of Oral Teratoma by Ultrasound.

A pregnant woman had a normal second-trimester anatomic survey at 22 weeks gestation. She was revealed to have a fetal oral mass with polyhydramnios and invisible stomach bubble by ultrasound at 28 weeks. A 50 mm × 36 mm × 42 mm, solid mass was found in the fetal mouth, filling the entire oral cavity. Fetal magnetic resonance imaging showed a homogeneous solid mass in the oral cavity compressing the hypopharynx. At 33 weeks, preterm labor occurred because of the continuation of increased amniotic fluid volume, and a female infant was vaginally delivered. The infant died shortly after tracheal intubation attempt failed. Autopsy confirmed the prenatal sonographic finding. The final pathologic diagnosis was oral immature teratoma. Our study indicates that although oral teratomas are rare, they are readily apparent at prenatal sonographic examinations. Respiratory compromise is the frequent complication of oral teratomas, which is associated with high perinatal mortality.

Prenatal diagnosis of autosomal recessive Noonan syndrome associated with biallelic LZTR1 variants presented with thick nuchal translucency and cardiac abnormalities.

Noonan syndrome (NS) is a common clinical variable disease characterized by a number of features, mainly including congenital heart defects, short stature, and a variable degree of developmental delay. This disorder is transmitted mostly in an autosomal dominant manner and is genetically heterogeneous. We report three prenatal cases of LZTR1-related recessive NS. One case had a recurrent cystic hygroma at 13 weeks gestation and the pregnancy was terminated. Two cases had an increased nuchal translucency at 12 weeks' gestation, but a normal second trimester ultrasound; both presented with hypertrophic cardiomyopathy in the third trimester. The two infants were diagnosed with NS after birth. All of the three cases had invasive genetic investigations during pregnancy, and trio exome sequencing revealed biallelic likely pathogenic or pathogenic LZTR1 variants in the fetuses. All parents were LZTR1 variant carriers. Our report further strengthens the association of LZTR1 with an autosomal recessive form of NS. The affected fetuses are more likely to have cardiac anomalies. Clarification of molecular diagnosis has important implications in these families because they carry a 25% recurrence risk.

Hypermethylation of thymosin ß4 predicts a poor prognosis for patients with acute-on-chronic hepatitis B liver failure.

BACKGROUND: It has been demonstrated that thymosin ß4 (Tß4) could inflect the severity of acute-on-chronic hepatitis B liver failure (ACHBLF), but the relationship between its methylation status and the prognosis of liver failure is not clear. This study aimed to determine Tß4 promoter methylation status in patients with ACHBLF and to evaluate its prognostic value. METHODS: The study recruited 115 patients with ACHBLF, 80 with acute-on-chronic hepatitis B pre-liver failure (pre-ACHBLF), and 86 with chronic hepatitis B (CHB). In addition, there were 36 healthy controls (HCs) from the Department of Hepatology, Qilu Hospital of Shandong University. The 115 patients with ACHBLF were divided into three subgroups: 33 with early stage ACHBLF (E-ACHBLF), 42 with mid-stage ACHBLF (M-ACHBLF), and 40 with advanced stage ACHBLF (A-ACHBLF). Tß4 promoter methylation status in peripheral blood mononuclear cells (PBMCs) was measured by methylation-specific polymerase chain reaction, and mRNA was detected by quantitative real-time polymerase chain reaction. RESULTS: Methylation frequency of Tß4 was significantly higher in patients with ACHBLF than in those with pre-ACHBLF, CHB or HCs. However, expression of Tß4 mRNA showed the opposite trend. In patients with ACHBLF, Tß4 promoter methylation status correlated negatively with mRNA levels. The 3-month mortality of ACHBLF in the methylated group was significantly higher than that in the unmethylated group. Also, Tß4 promoter methylation frequency was lower in survivors than in non-survivors. When used to predict the 1-, 2-, and 3-month incidence of ACHBLF, Tß4 methylation status was better than the model for end-stage liver disease (MELD) score. The predictive value of Tß4 methylation was higher than that of MELD score for the mortality of patients with E-ACHBLF and M-ACHBLF, but not for A-ACHBLF. CONCLUSIONS: Tß4 methylation might be an important early marker for predicting disease incidence and prognosis in patients with ACHBLF.

Prediction of hyperkalemia in ESRD patients by identification of multiple leads and multiple features on ECG.

BACKGROUND: Patients with end-stage renal disease (ESRD) especially those undergoing dialysis have a high prevalence of hyperkalemia, which must be detected and treated immediately. But the initial symptoms of hyperkalemia are insidious, and traditional laboratory serum potassium concentration testing takes time. Therefore, rapid and real-time measurement of serum potassium is urgently needed. In this study, different machine learning methods were used to make rapid predictions of different degrees of hyperkalemia by analyzing the ECG. METHODS: A total of 1024 datasets of ECG and serum potassium concentrations were analyzed from December 2020 to December 2021. The data were scaled into training and test sets. Different machine learning models (LR, SVM, CNN, XGB, Adaboost) were built for dichotomous prediction of hyperkalemia by analyzing 48 features of chest leads V2-V5. The performance of the models was also evaluated and compared using sensitivity, specificity, accuracy, accuracy, F1 score and AUC. RESULTS: We constructed different machine models to predict hyperkalemia using LR and four other common machine-learning methods. The AUCs of the different models ranged from 0.740 (0.661, 0.810) to 0.931 (0.912,0.953) when different serum potassium concentrations were used as the diagnostic threshold for hyperkalemia, respectively. As the diagnostic threshold of hyperkalemia was raised, the sensitivity, specificity, accuracy and precision of the model decreased to various degrees. And AUC also performed less well than when predicting mild hyperkalemia. CONCLUSION: Noninvasive and rapid prediction of hyperkalemia can be achieved by analyzing specific waveforms on the ECG by machine learning methods. But overall, XGB had a higher AUC in mild hyperkalemia, but SVM performed better in predicting more severe hyperkalemia.

Influence of Ultra-High-Pressure Pretreatment Method on Chemical Constituents, Antioxidant and Cytoprotective Activities of Free, Esterified, and Bound Phenolics from Anneslea Fragrans Wall. Leaves.

Anneslea fragrans Wall., an edible and medicinal plant, is traditionally used to treat liver and gastrointestinal diseases. This paper aimed to investigate the influence of ultra-high pressure (UHP) pretreatment on the phenolics profiling, antioxidant, and cytoprotective activities of free (FP), esterified (EP), and bound (BP) phenolics from A. fragrans leaves. A total of 32 compounds were characterized and quantified. The davidigenin (44.46 and 113.37 mg/g extract) was the highest in A. fragrans leaves. The vitexin (9), afzelin (10), coreopsin (15), and davidigenin (28) were analyzed with MS2 fragment pathways. Results showed that UHP treated A. fragrans leaves had higher total phenolic (TPC) and total flavonoid (TFC) contents of FP, EP, and BP fractions than those in the raw leaves. Moreover, UHP pretreated A. fragrans leaves had higher scavenging activities on DPPH+• and ABTS+•, and inhibitory effects on the intracellular ROS generation in H2O2-induced HepG2 cells. UFP showed the highest inhibition of ROS production among the samples. Therefore, UHP pretreatment method might be used as an effective strategy for elevating the availabilities of A. fragrans leaves to develop functional foods.

Electrothermal Desolvation-Enhanced Dielectric Barrier Discharge Plasma-Induced Vapor Generation for Sensitive Determination of Antimony by Atomic Fluorescence Spectrometry.

A novel simple electrothermal desolvation-enhanced dielectric barrier discharge plasma-induced vapor generation (ETD-DBD-PIVG) method has been developed for sensitive Sb determination by atomic fluorescence spectrometry (AFS). In our proposed ETD-DBD-PIVG, 20 µL sample solution was dried first; then, the resulting solution residue was directly converted into molecular volatile species efficiently through the interactions with hydrogen-doped DBD plasma; and finally, it was transported to AFS for detection. It was found that the desolvation process could greatly enhance Sb vapor generation, and the Sb fluorescence signal intensity is almost independent of its speciation, where comparable sensitivity is achieved for Sb(III) and Sb(V), enabling efficient total Sb detection without pre-reduction. Influencing parameters were evaluated in detail, including heating time, discharge gap, solution pH, and flow rates of argon and hydrogen, as well as coexisting ion interference. Under optimized conditions, the limit of detection was calculated as 0.86 µg L-1 (17.2 pg) for Sb. The accuracy of the proposed method was validated by the analysis of certified reference materials of simulated natural water samples and several river water samples. Compared with conventional hydride generation, the new ETD-DBD-PIVG offers an alternative green vapor generation technique with several advantages: (1) it eliminates the use of a sample flow system (e.g., no use of any syringe or peristaltic pump); instead, 20 µL of a sample is directly pipetted onto the glass plate for analysis; (2) it greatly simplifies the sample pretreatment steps as no pre-reduction process is needed; (3) it is sensitive and suitable for volume-limited sample analysis: efficient Sb vapor generation without chemical reducing reagents in ETD-DBD-PIVG enables Sb detection with an absolute limit at the picogram level. All the results demonstrate that the proposed method provides a simple, green, and sensitive method for Sb determination and it can also be extended to other elements such as Cd and As.

Localization of the WD repeat-containing protein 5 to the Virion Assembly Compartment Facilitates Human Cytomegalovirus Assembly.

We previously reported that human cytomegalovirus (HCMV) utilizes the cellular protein WD repeat-containing protein 5 (WDR5) to facilitate capsid nuclear egress. Here, we further show that HCMV infection results in WDR5 localization in a juxtanuclear region, and that its localization to this cellular site is associated with viral replication and late viral gene expression. Furthermore, WDR5 accumulated in the virion assembly compartment (vAC) and co-localized with vAC markers of gamma-tubulin (γ-tubulin), early endosomes, and viral vAC marker proteins pp65, pp28, and glycoprotein B (gB). WDR5 co-immunoprecipitated with multiple virion proteins, including MCP, pp150, pp65, pIRS1, and pTRS1, which may explain WDR5 accumulation in the vAC during infection. WDR5 fractionated with virions either in the presence or absence of Triton X-100 and was present in purified viral particles, suggesting that WDR5 was incorporated into HCMV virions. Thus, WDR5 localized to the vAC and was incorporated into virions, raising the possibility that in addition to capsid nuclear egress, WDR5 could also participate in cytoplasmic HCMV virion morphogenesis.Importance Human cytomegalovirus (HCMV) has a large (∼235-kb) genome that contains over 170 ORFs and exploits numerous cellular factors to facilitate its replication. In the late phase of HCMV infection cytoplasmic membranes are reorganized to establish the virion assembly compartment (vAC), which has been shown to necessary for efficient assembly of progeny virions. We previously reported that WDR5 facilitates HCMV nuclear egress. Here, we show that WDR5 is localized to the vAC and incorporated into virions, perhaps contributing to efficient virion maturation. Thus, findings in this study identified a potential role for WDR5 in HCMV assembly in the cytoplasmic phase of virion morphogenesis.

ResNet-based image inpainting method for enhancing the imaging speed of single molecule localization microscopy.

Single molecule localization microscopy (SMLM) is a mainstream method in the field of super-resolution fluorescence microscopy that can achieve a spatial resolution of 20∼30 nm through a simple optical system. SMLM usually requires thousands of raw images to reconstruct a super-resolution image, and thus suffers from a slow imaging speed. Recently, several methods based on image inpainting have been developed to enhance the imaging speed of SMLM. However, these image inpainting methods may also produce erroneous local features (or called image artifacts), for example, incorrectly joined or split filaments. In this study, we use the ResNet generator, a network with strong local feature extraction capability, to replace the popularly-used U-Net generator to minimize the image artifact problem in current image inpainting methods, and develop an image inpainting method called DI-STORM. We validate our method using both simulated and experimental data, and demonstrate that DI-STORM has the best acceleration capability and produces the least artifacts in the repaired images, as compared with VDSR (the simplest CNN-based image inpainting method in SMLM) and ANNA-PALM (the best GAN-based image inpainting method in SMLM). We believe that DI-STORM could facilitate the application of deep learning-based image inpainting methods for SMLM.

Pushing the colorimetry camera-based fluorescence microscopy to low light imaging by denoising and dye combination.

Colorimetry camera-based fluorescence microscopy (CCFM) is a single-frame imaging method for observing multiple biological events simultaneously. Compared with the traditional multi-color fluorescence microscopy methods based on sequential excitation or spectral splitting, the CCFM method simplifies multi-color fluorescence imaging experiments, while keeping a high spatial resolution. However, when the level of the detected fluorescence signal decreases, the image quality, the demosaicking algorithm precision, and the discrimination of fluorescence channels on the colorimetry camera will also decrease. Thus, CCFM has a poor color resolution under a low signal level. For example, the crosstalk will be higher than 10% when the signal is less than 100 photons/pixel. To solve this problem, we developed a new algorithm that combines sCMOS noise correction with demosaicking, and a dye selection method based on the spectral response characteristics of the colorimetry camera. By combining the above two strategies, low crosstalk can be obtained with 4 ∼ 6 fold fewer fluorescence photons, and low light single-frame four-color fluorescence imaging was successfully performed on fixed cos-7 cells. This study expands the power of the CCFM method, and provides a simple and efficient way for various bioimaging applications in low-light conditions.

Real-time image resolution measurement for single molecule localization microscopy.

Recent advancements in single molecule localization microscopy (SMLM) have demonstrated outstanding potential applications in high-throughput and high-content screening imaging. One major limitation to such applications is to find a way to optimize imaging throughput without scarifying image quality, especially the homogeneity in image resolution, during the imaging of hundreds of field-of-views (FOVs) in heterogeneous samples. Here we introduce a real-time image resolution measurement method for SMLM to solve this problem. This method is under the heuristic framework of overall image resolution that counts on localization precision and localization density. Rather than estimating the mean localization density after completing the entire SMLM process, this method uses the spatial Poisson process to model the random activation of molecules and thus determines the localization density in real-time. We demonstrate that the method is valid in real-time resolution measurement and is effective in guaranteeing homogeneous image resolution across multiple representative FOVs with optimized imaging throughput.

Single-shot multi-color fluorescence microscopy via a colorimetry camera.

Multi-color fluorescence microscopy presents highly detailed biological samples interactively. However, current multi-color methods suffer from an intricate optical setup, complicated image analysis, or a long acquisition time. To address these issues, here we develop a simple multi-color method based on a customized colorimetry camera to enable the detection of multiple structures from single-shot acquisition. The unfiltered channel (W pixels) and color channels (R, G, B, and NIR pixels) in this customized camera simultaneously provide a broad detection wavelength range and high detection sensitivity. We built a simple optical setup by replacing the monochrome camera in a basic fluorescence microscopy system with a colorimetry camera, and developed effective image analysis procedures to reconstruct a multi-color image from a single frame of a raw image. We demonstrated single-shot four-color wide-field fluorescence imaging on fixed cos-7 cells with < 5% cross talk, which is comparable to the best reported values. Our method greatly simplifies both the optical system and image analysis in the widely used method of multi-color fluorescence microscopy, thus offering an effective and easy way to study multiple objects at the same time.

Prenatal diagnosis of Coffin-Siris syndrome: What are the fetal features?

OBJECTIVE: To present both our center's and previously reported experience of prenatal diagnosis of Coffin-Siris syndrome (CSS) with regard to the laboratory testing and fetal features of this syndrome. METHODS: This was a retrospective study of eight pregnancies with fetal CSS identified by prenatal or postnatal genetic testing. Clinical and laboratory data were collected and reviewed for these cases, including maternal demographics, prenatal sonographic findings, chromosomal microarray and exome sequencing (ES) results, and pregnancy outcomes. RESULTS: A total of eight cases of fetal CSS based on molecular testing were detected. Two cases presented with an increased nuchal translucency (NT) in the first trimester. The remaining six were identified at the second trimester scan. Agenesis of the corpus callosum (ACC) was the most common sonographic finding, accounting for 5/7 (71.4%) cases in which a second trimester sonogram was performed: four had ACC as an isolated finding, and one had additional features of cerebellar hypoplasia and left congenital diaphragmatic hernia. CONCLUSION: CSS should be included in the differential diagnosis when ACC is found by prenatal ultrasound. Both chromosomal microarray and ES should be options when counseling patients with a structurally anomalous fetus.

Prenatal isolated clubfoot increases the risk for clinically significant exome sequencing results.

OBJECTIVE: To examine the diagnostic yield of exome sequencing (ES) in singleton pregnancies with isolated fetal clubfoot. METHODS: Clinical data from singleton pregnancies with a sonographic diagnosis of isolated clubfoot and ES results between 2018 and 2021 were retrospectively obtained from a single referral medical center. The recorded data include maternal age, gestational age at sonographic diagnosis, the indication for genetic testing, ES results, and pregnancy outcomes. RESULTS: During the study period, 38 fetuses were prenatally diagnosed with isolated clubfoot by ultrasound and underwent ES after the copy number variant analysis was non-diagnostic. Through the trio-ES analysis, pathogenic or likely pathogenic variants were detected in 4 of 38 (10.5%) with the following genes: BRPF1, ANKRD17, FLNA, and KIF1A. All are de novo with three of autosomal dominant inheritance and one of X-linked recessive inheritance. CONCLUSION: Sonographic diagnosis of clubfoot, even isolated, increases the risk for monogenic syndromes. Exome sequencing should be an option for genetic investigation for such pregnancies.