Concurrent Preimplantation Genetic Testing and Competence Assessment of Human Embryos by Transcriptome Sequencing.

Preimplantation genetic testing (PGT) can minimize the risk of birth defects. However, the accuracy and applicability of routine PGT is confounded by uneven genome coverage and high allele drop-out rate from existing single-cell whole genome amplification methods. Here, a method to diagnose genetic mutations and concurrently evaluate embryo competence by leveraging the abundant mRNA transcript copies present in trophectoderm cells is developed. The feasibility of the method is confirmed with 19 donated blastocysts. Next, the method is applied to 82 embryos from 26 families with monogenic defects for simultaneous mutation detection and competence assessment. The accuracy rate of direct mutation detection is up to 95%, which is significantly higher than DNA-based method. Meanwhile, this approach correctly predicted seven out of eight (87.5%) embryos that failed to implant. Of six embryos that are predicted to implant successfully, four met such expectations (66.7%). Notably, this method is superior at conditions for mutation detection that are challenging when using DNA-based PGT, such as when detecting pathogenic genes with a high de novo rate, multiple pseudogenes, or an abnormal expansion of CAG trinucleotide repeats. Taken together, this study establishes the feasibility of an RNA-based PGT that is also informative for assessing implantation competence.

Follicular Dendritic Cell Sarcoma of the Parotid Gland: A Case Report and Review of Literature.

Follicular dendritic cell sarcoma of the parotid gland is an extremely rare tumor, with only six cases reported in the literature. A 51-year-old female had a 3.0 cm tumor resected from the right parotid gland. The tumor exhibited solid sheets, whorls, fascicular pattern, and syncytium appearance with an indistinct cell border. The lymphocytic infiltrate was sprinkled throughout the neoplasm, with focal prominent perivascular cuffing. Immunohistochemically, it was positive for follicular dendritic cell markers CD21, CD23, and CD35. We aim to enhance the understanding of this neoplasm and alert pathologists to this rare entity in this region to avoid misdiagnosis.

Ultrasound versus palpation-guided corticosteroid injection for de Quervain disease: A randomized controlled trial.

INTRODUCTION: Corticosteroid injection effectively treats de Quervain disease, and due to the high prevalence of the intracompartmental septum in the first extensor compartment, ultrasound guidance improves injection accuracy. OBJECTIVE: To compare the effectiveness, adverse events, and the recurrence rate between ultrasound-guided and palpation-guided injection in patients with de Quervain disease. DESIGN: Prospective, single-blind, randomized controlled trial. SETTING: Rehabilitation department of a private teaching hospital. PARTICIPANTS: We enrolled 49 patients, ≥20 years of age, clinically diagnosed with de Quervain disease based on their medical history and physical examination. INTERVENTIONS: Patients were randomized into two groups: ultrasound-guided and palpation-guided injection. Both groups received a mixture of 10 mg triamcinolone acetonide (10 mg/1 mL) and 0.3 mL 1% lidocaine. MAIN OUTCOME MEASURES: The primary outcome measure was the Quick Disabilities of the Arm, Shoulder and Hand (QuickDASH) score at 1 week. The secondary outcome measures were visual analog scale for pain (pain VAS) score, patient satisfaction, and adverse events or complications from the interventions at 1 week, 3 months, and 6 months. RESULTS: Both groups showed improvement over time in QuickDASH scores and pain VAS (p < .001); however, no statistically significant differences were noted between the groups for either QuickDASH scores (p = .22) or pain VAS (p = .30). In addition, no statistically significant differences were found between the groups in terms of patient satisfaction (p = .76) and adverse events (p = .47, .33, .58) at the 1-week, 3-month, and 6-month follow-ups. CONCLUSIONS: Both ultrasound-guided and palpation-guided injections effectively treated de Quervain disease. During a 6-month follow-up, there were no statistically significant differences between the groups in pain relief, upper limb function, or patient satisfaction. However, the palpation-guided group showed a tendency for more recurrence and skin side effects.

Caffeic acid phenethyl ester suppresses the expression of androgen receptor variant 7 via inhibition of CDK1 and AKT.

Androgen receptor (AR) splice variant 7 (AR-V7) is capable to enter nucleus and activate downstream signaling without ligand. AR-V7 assists the tumor growth, cancer metastasis, cancer stemness, and the evolvement of therapy-resistant prostate cancer (PCa). We discovered that caffeic acid phenethyl ester (CAPE) can repress the expression and downstream signaling of AR-V7 in PCa cells. CAPE blocked the gene transcription, nuclear localization, and protein abundance of AR-V7. CAPE inhibited the expression of U2AF65, SF2 and hnRNPF, which were splicing factors for AR-V7 intron. Additionally, CAPE decreased protein stability of AR-V7 and enhanced the proteosome-degradation of AR-V7. We observed that CDK1 and AKT regulated the expression and stability of AR-V7 via phosphorylation of Ser81 and Ser213, respectively. CAPE decreased the expression of CDK1 and AKT. Overexpression of CDK1 restored the abundance of AR-V7 in CAPE-treated PCa cells. Overexpression of AR-V7, AKT or CDK1 rescued the proliferation of PCa cells under CAPE treatment. Intraperitoneal injection of 10 mg/kg CAPE retarded the growth of 22Rv1 xenografts in nude mice and suppressed the protein levels of AR-V7, CDK1 and AKT in 22Rv1 xenografts. Our study provided the rationale of applying CAPE for inhibition of AR-V7 in prostate tumors.

Perineural invasion is a poor prognostic factor for sinonasal squamous cell carcinoma.

OBJECTIVES: In this study, our primary objective is to elucidate the correlation between sinonasal squamous cell carcinoma (SCC) and perineural invasion (PNI), a topic that has received limited attention in prior literature. Furthermore, we have undertaken an examination of various other clinicopathological factors. MATERIALS AND METHODS: We retrospectively reviewed the medical records of patients aged ≥ 20 years with newly diagnosed sinonasal cancer and received treatment and care at a tertiary medical center. We excluded patients who did not have an SCC diagnosis, those who underwent palliative surgery, and individuals with insufficient follow-up data at the study endpoint. Ultimately, a total of 49 eligible participants were included in our further analysis. RESULTS: PNI and advanced T staging were associated with increased risk of local recurrence (LR). Furthermore, PNI was significantly associated with an adverse prognosis in terms of LR-free survival. Participants with PNI had significantly worse overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS). Patients with LR had significantly worse OS, DFS, and DSS. CONCLUSION: PNI is associated with an elevated risk of LR and reduced OS, DFS, and DSS in patients with sinonasal SCC. These findings can facilitate the formulation of more targeted and effective treatment strategies for sinonasal SCC in clinical practice.

Efficacy of Combination Therapy (Hydrodilatation and Subdeltoid Bursa Injection With Corticosteroid, Mobilization, and Physical Therapy) vs Physical Therapy Alone for Treating Frozen Shoulder: A Randomized Single-Blind Controlled Trial, Phase I.

OBJECTIVE: To compare the efficacy of combination therapy (hydrodilatation and subdeltoid bursa injection with corticosteroid, mobilization, and physical therapy [PT]) with that of PT alone for treating frozen shoulder. DESIGN: A prospective, 2-arm parallel, single-blinded, randomized controlled trial. SETTING: Rehabilitation clinic of a private academic hospital. PARTICIPANTS: Patients (n=70) with frozen shoulder (freezing stage). INTERVENTIONS: Participants (n=35) in the combination group underwent hydrodilatation and subdeltoid bursa injection with corticosteroid twice, mobilization, and usual-care PT for 8 weeks; participants (n=35) in the PT group received only the usual-care PT for 8 weeks. MAIN OUTCOME MEASURES: The Shoulder Pain and Disability Index (SPADI) was the primary outcome measure. The secondary outcome measures were pain scores on a visual analog scale, range of motion (ROM), the Shoulder Disability Questionnaire (SDQ), quality of life (evaluated using the 36-item Short-Form Health Survey [SF-36]), and self-assessment of the treatment effect. RESULTS: Compared with the PT group, the combination group had significantly better pain (during activity), SPADI, SDQ, active and passive ROM, and self-assessment scores (all P<.001) as well as scores on some parts of the SF-36 (physical function and bodily pain, P<.05). Between-group differences were significant at the 1-, 2-, 4-, and 6-month follow-ups. CONCLUSIONS: A combination of hydrodilatation (with corticosteroid), bursal corticosteroid injection, and joint mobilization with PT was superior to PT alone for treating frozen shoulder, and the effects persisted for at least 6 months.

New Histopathologic Risk Model for Early T-stage Oral Squamous Cell Carcinoma: Focusing on a Modified Worst Pattern of Invasion System and a New Tumor Budding Score.

Oral squamous cell carcinoma (OSCC) is treated based on the TNM staging. However, early T-stage OSCC still exhibits substantial nodal metastasis and death rates. Recent literature highlights the independent prognostic value of worst pattern of invasion (WPOI) and tumor budding in OSCC. Nevertheless, WPOI-5 is uncommon in early T-stage OSCC, and the definitions of tumor budding and WPOI-4 overlap. Moreover, WPOI assessment is subjective, and tumor budding evaluation varies across studies. To address these limitations, we aimed to develop a modified WPOI system and a novel tumor budding scoring system that assesses single cells and high-density tumor budding. We also evaluated a new histopathologic risk model for early T-stage OSCC. The study cohort comprised 37 pT1 and 64 pT2 OSCCs. The modified WPOI demonstrated superior interobserver agreement compared with the original system (κ value: 0.98 vs. 0.53). In the multivariate analysis, modified WPOI and tumor budding score were independent prognostic factors for nodal metastasis and disease-free survival, while modified WPOI predicted disease-specific survival. By integrating these factors, our risk model stratified the patients into 3 groups. Notably, the intermediate-risk and high-risk groups exhibited significantly higher rates of nodal metastasis, recurrence, and tumor-related death. Conversely, none in the low-risk group had nodal metastasis or succumbed to the disease. Our model offered simplified scoring and potentially improved prognostic predictions. In conclusion, we've developed a modified WPOI system, a new tumor budding scoring system, and a reliable risk model that classifies early T-stage OSCC patients into distinct risk groups with significant prognostic differences.

Sleep, physical activity and panic attacks: A two-year prospective cohort study using smartwatches, deep learning and an explainable artificial intelligence model.

BACKGROUND: Sleep and physical activity suggestions for panic disorder (PD) are critical but less surveyed. This two-year prospective cohort study aims to predict panic attacks (PA), state anxiety (SA), trait anxiety (TA) and panic disorder severity (PDS) in the upcoming week. METHODS: We enrolled 114 PD patients from one general hospital. Data were collected using the DSM-5, the MINI, clinical app questionnaires (BDI, BAI, PDSS-SR, STAI) and wearable devices recording daily sleep, physical activity and heart rate from 16 June 2020 to 10 June 2022. Our teams applied RNN, LSTM, GRU deep learning and SHAP explainable methods to analyse the data. RESULTS: The 7-day prediction accuracies for PA, SA, TA, and PDS were 92.8 %, 83.6 %, 87.2 %, and 75.6 % from the LSTM model. Using the SHAP explainable model, higher initial BDI or BAI score and comorbidities with depressive disorder, generalized anxiety disorder or agoraphobia predict a higher chance of PA. However, PA decreased under the following conditions: daily average heart rate, 72-87 bpm; maximum heart rate, 100-145 bpm; resting heart rate, 55-60 bpm; daily climbing of more than nine floors; total sleep duration between 6 h 23 min and 10 h 50 min; deep sleep, >50 min; and awake duration, <53 min. LIMITATIONS: Moderate sample size and self-report questionnaires were the limitations. CONCLUSIONS: Deep learning predicts recurrent PA and various anxiety domains with 75.6-92.8 % accuracy. Recurrent PA decreases under adequate daily sleep and physical activity.

Clinical practice and outcomes of preimplantation genetic testing for CMT1A using a novel direct detection method.

Background: Charcot-Marie-Tooth type 1A (CMT1A), the most frequent type of Charcot-Marie-Tooth disease, is mainly caused by a 1.4-Mb duplication containing the PMP22 gene. There is no effective treatment other than general supportive care and symptomatic treatment. Preimplantation genetic testing for monogenic defects (PGT-M) is an alternative approach for obtaining healthy babies. Methods: A new technology and analysis method based on next-generation sequencing (NGS) was developed to detect duplication mutations directly. Simultaneously, aneuploidy and linkage analyses were performed to achieve a comprehensive and accurate embryo diagnosis. Results: Eight couples were recruited in this study; PMP22 duplication was validated in seven couples, and PMP22 splicing mutation was found in one. Forty-five embryos from 12 PGT cycles were successfully detected using this novel method. The direct detection results for all embryos were consistent with the linkage analyses, suggesting a 100 % accuracy rate, and the aneuploidy rate of the biopsied blastocysts was 33.3 %. Eventually, 18 of the 45 diagnosed embryos were deemed suitable for transfer. Four healthy babies from three families were delivered and their genetic status confirmed by amniocentesis. Additionally, there were no adverse effects of anesthesia or increased pregnancy complications during PGT-M in female patients with CMT1A. Conclusions: This study provided a simple, reliable, and efficient method that can directly detect PMP22 mutations based on NGS data and does not require positive family members. A clinical workflow for CMT1A interruption in the offspring before embryo implantation is also summarized.

Time-on-task effects on human pupillary and saccadic metrics after theta burst transcranial magnetic stimulation over the frontal eye field.

Pupil size undergoes constant changes primarily influenced by ambient luminance. These changes are referred to as the pupillary light reflex (PLR), where the pupil transiently constricts in response to light. PLR kinematics provides valuable insights into autonomic nervous system function and have significant clinical applications. Recent research indicates that attention plays a role in modulating the PLR, and the circuit involving the frontal eye field (FEF) and superior colliculus is causally involved in controlling this pupillary modulation. However, there is limited research exploring the role of the human FEF in these pupillary responses, and its impact on PLR metrics remains unexplored. Additionally, although the protocol of continuous theta-burst stimulation (cTBS) is well-established, the period of disruption after cTBS is yet to be examined in pupillary responses. Our study aimed to investigate the effects of FEF cTBS on pupillary and saccadic metrics in relation to time spent performing a task (referred to as time-on-task). We presented a bright stimulus to induce the PLR in visual- and memory-delay saccade tasks following cTBS over the right FEF or vertex. FEF cTBS, compared to vertex cTBS, resulted in decreased baseline pupil size, peak constriction velocities, and amplitude. Furthermore, the time-on-task effects on baseline pupil size, peak amplitude, and peak time differed between the two stimulation conditions. In contrast, the time-on-task effects on saccadic metrics were less pronounced between the two conditions. In summary, our study provides the first evidence that FEF cTBS affects human PLR metrics and that these effects are modulated by time-on-task.

Transfer learning with CNNs for efficient prostate cancer and BPH detection in transrectal ultrasound images.

Early detection of prostate cancer (PCa) and benign prostatic hyperplasia (BPH) is crucial for maintaining the health and well-being of aging male populations. This study aims to evaluate the performance of transfer learning with convolutional neural networks (CNNs) for efficient classification of PCa and BPH in transrectal ultrasound (TRUS) images. A retrospective experimental design was employed in this study, with 1380 TRUS images for PCa and 1530 for BPH. Seven state-of-the-art deep learning (DL) methods were employed as classifiers with transfer learning applied to popular CNN architectures. Performance indices, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), Kappa value, and Hindex (Youden's index), were used to assess the feasibility and efficacy of the CNN methods. The CNN methods with transfer learning demonstrated a high classification performance for TRUS images, with all accuracy, specificity, sensitivity, PPV, NPV, Kappa, and Hindex values surpassing 0.9400. The optimal accuracy, sensitivity, and specificity reached 0.9987, 0.9980, and 0.9980, respectively, as evaluated using twofold cross-validation. The investigated CNN methods with transfer learning showcased their efficiency and ability for the classification of PCa and BPH in TRUS images. Notably, the EfficientNetV2 with transfer learning displayed a high degree of effectiveness in distinguishing between PCa and BPH, making it a promising tool for future diagnostic applications.

Feasibility of predicting maximal oxygen uptake by using the efficiency factor in healthy men.

Conventionally, efficiency is indirectly estimated through a respiratory gas analyser (oxygen, carbon dioxide), which is a complex and rather costly calculation method that is difficult to perform in many situations. Therefore, the present study proposed a modified definition of efficiency, called the efficiency factor (EF) (i.e., the ratio of work to the corresponding exercise intensity), and evaluated the relation between the EF and maximal oxygen uptake ([Formula: see text]), as well as compared the prediction models established based on the EF. The heart rate (maximal heart rate: 186 ± 6 beats min-1), rating of perceived exertion (19 ± 1), and [Formula: see text] (39.0 ± 7.1 mL kg-1 min-1) of 150 healthy men (age: 20 ± 2 years; height: 175.0 ± 6.0 cm; weight: 73.6 ± 10.7 kg; body mass index [BMI]: 24.0 ± 3.0 kg m-2; percent body fat [PBF]: 17.0 ± 5.7%) were measured during the cardiopulmonary exercise test (CPET). Through multiple linear regression analysis, we established the BMI model using age and BMI as parameters. Additionally, we created the PBF modelHRR utilizing weight, PBF, and heart rate reserve (HRR) and developed PBF modelEF6 and PBF modelEF7 by incorporating EF6 from the exercise stage 6 and EF7 from the exercise stage 7 during the CPET, respectively. EF6 (r = 0.32, p = 0.001) and EF7 (r = 0.31, p = 0.002) were significantly related to [Formula: see text]. Among the models, the PBF modelEF6 showed the highest accuracy, which could explain 62.6% of the variance in the [Formula: see text] at with a standard error of estimate (SEE) of 4.39 mL kg-1 min-1 (%SEE = 11.25%, p < 0.001). These results indicated that the EF is a significant predictor of [Formula: see text], and compared to the other models, the PBF modelEF6 is the best model for estimating [Formula: see text].

Fusion extracted features from deep learning for identification of multiple positioning errors in dental panoramic imaging.

BACKGROUND: Dental panoramic imaging plays a pivotal role in dentistry for diagnosis and treatment planning. However, correctly positioning patients can be challenging for technicians due to the complexity of the imaging equipment and variations in patient anatomy, leading to positioning errors. These errors can compromise image quality and potentially result in misdiagnoses. OBJECTIVE: This research aims to develop and validate a deep learning model capable of accurately and efficiently identifying multiple positioning errors in dental panoramic imaging. METHODS AND MATERIALS: This retrospective study used 552 panoramic images selected from a hospital Picture Archiving and Communication System (PACS). We defined six types of errors (E1-E6) namely, (1) slumped position, (2) chin tipped low, (3) open lip, (4) head turned to one side, (5) head tilted to one side, and (6) tongue against the palate. First, six Convolutional Neural Network (CNN) models were employed to extract image features, which were then fused using transfer learning. Next, a Support Vector Machine (SVM) was applied to create a classifier for multiple positioning errors, using the fused image features. Finally, the classifier performance was evaluated using 3 indices of precision, recall rate, and accuracy. RESULTS: Experimental results show that the fusion of image features with six binary SVM classifiers yielded high accuracy, recall rates, and precision. Specifically, the classifier achieved an accuracy of 0.832 for identifying multiple positioning errors. CONCLUSIONS: This study demonstrates that six SVM classifiers effectively identify multiple positioning errors in dental panoramic imaging. The fusion of extracted image features and the employment of SVM classifiers improve diagnostic precision, suggesting potential enhancements in dental imaging efficiency and diagnostic accuracy. Future research should consider larger datasets and explore real-time clinical application.

A novel embryo biopsy morphological analysis and genetic integrality criterion system significantly improves the outcome of preimplantation genetic testing.

PURPOSE: While efforts have been made to establish blastocyst grading systems in the past decades, little research has examined the quality of biopsy specimens. This study is the first to correlate the morphology of biopsied trophectoderm (TE) cells to their quality and subsequent genetic testing results of preimplantation genetic testing (PGT), through an innovative Morphological Analysis and Genetic Integrality Criterion (MAGIC) system. METHODS: Biopsied TE cells were first evaluated according to the MAGIC procedure, followed by whole-genome amplification (WGA) and library construction, and then sequenced using the Illumina X Ten Platform. Copy number variation (CNV) and allele drop-out (ADO) rates as well as test failure rates were compared and analyzed. RESULTS: Our data explores the relationship between TE cell morphology and its quality and final genetic testing outcome, which is established based on the MAGIC system. MAGIC guarantees that only high- or good-quality TE cells are used for genetic testing to generate excellent data uniformity and lower ADO rates. Low-quality cells containing biopsied TE cell mass are responsible for the "background noise" of CNV analysis. CONCLUSION: The MAGIC application has effectively decreased the false-positive mosaicism, hence to ensure the stability and veracity of detection results, to avoid misdiagnoses, and to improve accuracy, as well as to avoid re-biopsy procedures. The study also contributes to understand how the IVF laboratory and the molecular biology laboratory depend on each other to achieve good-quality PGT results, which are clinically relevant for the patients.

Tgfbr1 regulates lateral plate mesoderm and endoderm reorganization during the trunk to tail transition.

During the trunk to tail transition the mammalian embryo builds the outlets for the intestinal and urogenital tracts, lays down the primordia for the hindlimb and external genitalia, and switches from the epiblast/primitive streak to the tailbud as the driver of axial extension. Genetic and molecular data indicate that Tgfbr1 is a key regulator of the trunk to tail transition. Tgfbr1 has been shown to control the switch of the neuro mesodermal-competent cells from the epiblast to the chordo-neural hinge to generate the tail bud. We now show that Tgfbr1 signaling also controls the remodeling of the lateral plate mesoderm (LPM) and of the embryonic endoderm associated with the trunk to tail transition. In the absence of Tgfbr1 the two LPM layers do not converge at the end of the trunk, extending instead as separate layers enclosing the celomic cavity until the caudal embryonic extremity, and failing to activate markers of primordia for the hindlimb and external genitalia. However, this extended LPM, does not exhibit the molecular signatures characteristic of this tissue in the trunk. The vascular remodeling involving the dorsal aorta and the umbilical artery leading to the connection between embryonic and extraembryonic circulation was also affected in the Tgfbr1 mutant embryos. Similar alterations in the LPM and vascular system were also observed in Isl1 null mutants, indicating that this factor acts in the regulatory cascade downstream of Tgfbr1 in LPM-derived tissues. In addition, in the absence of Tgfbr1 the embryonic endoderm fails to expand to form the endodermal cloaca and to extend posteriorly to generate the tail gut. We present evidence suggesting that the remodeling activity of Tgfbr1 in the LPM and endoderm results from the control of the posterior primitive streak fate after its regression during the trunk to tail transition. Our data, together with previously reported observations, place Tgfbr1 at the top of the regulatory processes controlling the trunk to tail transition.

Application of the PGT-M strategy using single sperm and/or affected embryos as probands for linkage analysis in males with hereditary tumor syndromes without family history.

Hereditary tumor syndromes have garnered substantial attention due to their adverse effects on both the physical and psychological health of patients, as well as the elevated risk of transmission to subsequent generations. This has prompted a growing interest in exploring preimplantation genetic testing (PGT) as a treatment option to mitigate and eliminate these impacts. Several studies have demonstrated that de novo variants have become a great cause of many hereditary tumor syndromes, which introduce certain difficulties to PGT. In the absence of adequate genetic linkage information (parents and offspring), haplotype construction seems unrealizable. In the study, researchers used single sperm or affected embryos as proband to perform single-nucleotide polymorphism linkage analysis for cases with de novo variants. For complicated variants, the strategy that sperm combined with embryo detection will increase accuracy while avoiding the limitations and potential failures of using a single detection material. The study recruited 11 couples with male de novo carriers, including 3 tumor types and 4 genes. To date, 4 couples have been clinically confirmed as pregnant and three healthy babies have been born. The results of amniocentesis or umbilical cord blood verification were consistent with the results of PGT-M. The study aims to introduce the application of the PGT-M strategy in hereditary tumor syndromes.

Classification of Color Fundus Photographs Using Fusion Extracted Features and Customized CNN Models.

This study focuses on overcoming challenges in classifying eye diseases using color fundus photographs by leveraging deep learning techniques, aiming to enhance early detection and diagnosis accuracy. We utilized a dataset of 6392 color fundus photographs across eight disease categories, which was later augmented to 17,766 images. Five well-known convolutional neural networks (CNNs)-efficientnetb0, mobilenetv2, shufflenet, resnet50, and resnet101-and a custom-built CNN were integrated and trained on this dataset. Image sizes were standardized, and model performance was evaluated via accuracy, Kappa coefficient, and precision metrics. Shufflenet and efficientnetb0demonstrated strong performances, while our custom 17-layer CNN outperformed all with an accuracy of 0.930 and a Kappa coefficient of 0.920. Furthermore, we found that the fusion of image features with classical machine learning classifiers increased the performance, with Logistic Regression showcasing the best results. Our study highlights the potential of AI and deep learning models in accurately classifying eye diseases and demonstrates the efficacy of custom-built models and the fusion of deep learning and classical methods. Future work should focus on validating these methods across larger datasets and assessing their real-world applicability.

Palisading Adenocarcinoma: A Morphologically Unique Salivary Gland Tumor With a Neuroendocrine-like Appearance and a Predilection for the Sublingual Glands of Women.

Adenocarcinoma, not otherwise specified (NOS) is a heterogenous group of salivary gland tumors that likely contains distinct tumors that have not yet been characterized. Indeed, in recent years, cases previously diagnosed as adenocarcinoma, NOS have been recategorized into novel tumor designations such as secretory carcinoma, microsecretory adenocarcinoma, and sclerosing microcystic adenocarcinoma. We sought to describe a distinctive, hitherto-undescribed salivary gland tumor encountered in the authors' practices. Cases were pulled from the surgical pathology archives of the authors' institutions. Histologic, immunohistochemical, and clinical findings were tabulated, and targeted next-generation sequencing was performed on all cases. Nine cases were identified, arising in 8 women and 1 man ranging from 45 to 74 years (mean, 56.7 y). Seven tumors (78%) arose in the sublingual gland, while 2 (22%) arose in the submandibular gland. The cases shared a distinctive morphologic appearance. They were biphasic, with ducts scattered among a predominant polygonal cell with round nuclei, prominent nucleoli, and pale eosinophilic cytoplasm. These cells were arranged as trabeculae and palisaded as pseudorosettes around hyalinized stroma and vessels, resembling a neuroendocrine tumor. Four of the cases were well-circumscribed, while the remaining 5 showed infiltrative growth including perineural invasion in 2 (22%) and lymphovascular invasion in 1 (11%). Mitotic rates were low (mean, 2.2/10 HPFs); necrosis was absent. By immunohistochemistry, the predominant cell type was strongly positive for CD56 (9 of 9) and variably positive for pan-cytokeratin (AE1/AE3) (7 of 9) with patchy S100 (4 of 9), but negative for synaptophysin (0 of 9) and chromogranin (0 of 9), while the ducts were strongly positive for pan-cytokeratin (AE1/AE3) (9 of 9) and CK5/6 (7 of 7). Next-generation sequencing did not reveal any fusions or obvious driver mutations. All cases were resected surgically, with external beam radiation also done in 1 case. Follow-up was available in 8 cases; there were no metastases or recurrences after 4 to 160 months (mean, 53.1 mo). A dual population of scattered ducts with a predominance of CD56-positive neuroendocrine-like cells characterizes a unique salivary gland tumor which is often encountered in the sublingual glands of women, for which we propose the term "palisading adenocarcinoma." Although the tumor was biphasic and had a neuroendocrine-like appearance, it lacked convincing immunohistochemical evidence of myoepithelial or neuroendocrine differentiation. Although a subset showed unequivocally invasive growth, this tumor appears to behave in an indolent manner. Moving forward, recognition of palisading adenocarcinoma and its separation from other salivary adenocarcinomas, NOS will facilitate a better understanding of the characteristics of this previously unrecognized tumor.

BayesESS: A tool for quantifying the impact of parametric priors in Bayesian analysis.

Bayesian inference has become an attractive choice for scientists seeking to incorporate prior knowledge into their modeling framework. While the R community has been an important contributor in facilitating Bayesian statistical analyses, software to evaluate the impact of prior knowledge to such modeling framework has been lacking. In this article, we present BayesESS, a comprehensive, free, and open source R package for quantifying the impact of parametric priors in Bayesian analysis. We also introduce an accompanying web-based application for estimating and visualizing Bayesian effective sample size for purposes of conducting or planning Bayesian analyses.