Comparison of Aroma and Taste Profiles of Kiwi Wine Fermented with/without Peel by Combining Intelligent Sensory, Gas Chromatography-Mass Spectrometry, and Proton Nuclear Magnetic Resonance.

Kiwi wine (KW) is tipically made by fermenting juice from peeled kiwifruit, resulting in the disposal of peel and pomace as by-products. However, the peel contains various beneficial compounds, like phenols and flavonoids. Since the peel is edible and rich in these compounds, incorporating it into the fermentation process of KW presents a potential solution to minimize by-product waste. This study compared the aroma and taste profiles of KW from peeled (PKW) and unpeeled (UKW) kiwifruits by combining intelligent sensory technology, GC-MS, and 1H-NMR. Focusing on aroma profiles, 75 volatile organic compounds (VOCs) were identified in KW fermented with peel, and 73 VOCs in KW without peel, with 62 VOCs common to both. Among these compounds, rose oxide, D-citronellol, and bornylene were more abundant in UKW, while hexyl acetate, isoamyl acetate, and 2,4,5-trichlorobenzene were significantly higher in PKW. For taste profiles, E-tongue analysis revealed differences in the taste profiles of KW from the two sources. A total of 74 molecules were characterized using 1H-NMR. UKW exhibited significantly higher levels of tartrate, galactarate, N-acetylserotonin, 4-hydroxy-3-methoxymandelate, fumarate, and N-acetylglycine, along with a significantly lower level of oxypurinol compared to PKW. This study seeks to develop the theoretical understanding of the fermentation of kiwifruit with peel in sight of the utilization of the whole fruit for KW production, to increase the economic value of kiwifruit production.

Research progress of ectopic thyroid cancer in thyroglossal duct cyst: A case report and literature review.

RATIONALE: Thyroglossal duct carcinoma, a rare clinical condition characterized by ectopic thyroid adenocarcinoma within thyroglossal duct cysts (TGDCs), typically confirmed through intraoperative rapid pathology, this condition generally has a favorable prognosis. Nevertheless, comprehensive treatment guidelines across all disease stages are lacking, the purpose of this study is to report 1 case of the disease and propose the treatment plan for each stage of the disease. PATIENT CONCERNS: A patient presented with thyroid swelling, classified as C-TIRADS 4A following a physical examination. Preoperative thyroid puncture identified papillary thyroid carcinoma, and genetic testing revealed a BRAF gene exon 15-point mutation. Ancillary tests showed a slightly decreased thyroid stimulating hormone (TSH) level (0.172) with no other significant abnormalities. DIAGNOSES: Preoperative fine-needle aspiration cytology (FNAC) confirmed right-side thyroid cancer. Intraoperative exploration uncovered a TGDC and intraoperative rapid pathology confirmed thyroglossal duct carcinoma. INTERVENTIONS: A Sistrunk operation and ipsilateral thyroidectomy were performed. OUTCOMES: Postoperative recovery was satisfactory. LESSONS: Thyroglossal duct carcinoma is a rare disease affecting the neck. Due to limited clinical cases and the favorable prognosis associated with this condition, there is currently no established set of diagnostic and treatment guidelines. According to tumor size, lymph node metastasis, thyroid status and other factors, the corresponding treatment methods were established for each stage of thyroglossal duct cancer, which laid the foundation for the subsequent treatment development of this disease.

Biological functions and therapeutic potential of SRY related high mobility group box 5 in human cancer.

Cancer is a heavy human burden worldwide, with high morbidity and mortality. Identification of novel cancer diagnostic and prognostic biomarkers is important for developing cancer treatment strategies and reducing mortality. Transcription factors, including SRY associated high mobility group box (SOX) proteins, are thought to be involved in the regulation of specific biological processes. There is growing evidence that SOX transcription factors play an important role in cancer progression, including tumorigenesis, changes in the tumor microenvironment, and metastasis. SOX5 is a member of SOX Group D of Sox family. SOX5 is expressed in various tissues of human body and participates in various physiological and pathological processes and various cellular processes. However, the abnormal expression of SOX5 is associated with cancer of various systems, and the abnormal expression of SOX5 acts as a tumor promoter to promote cancer cell viability, proliferation, invasion, migration and EMT through multiple mechanisms. In addition, the expression pattern of SOX5 is closely related to cancer type, stage and adverse clinical outcome. Therefore, SOX5 is considered as a potential biomarker for cancer diagnosis and prognosis. In this review, the expression of SOX5 in various human cancers, the mechanism of action and potential clinical significance of SOX5 in tumor, and the therapeutic significance of Sox5 targeting in cancer were reviewed. In order to provide a new theoretical basis for cancer clinical molecular diagnosis, molecular targeted therapy and scientific research.

timsTOF HT Improves Protein Identification and Quantitative Reproducibility for Deep Unbiased Plasma Protein Biomarker Discovery.

Mass spectrometry (MS) is a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide-ranging plasma protein concentrations, along with technical and biological variabilities, present significant challenges for deep and reproducible protein quantitation. Here, we evaluated the qualitative and quantitative performance of timsTOF HT and timsTOF Pro 2 mass spectrometers for analysis of neat plasma samples (unfractionated) and plasma samples processed using the Proteograph Product Suite (Proteograph) that enables robust deep proteomics sampling prior to mass spectrometry. Samples were evaluated across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV < 20%) with timsTOF HT compared to Pro 2. Additionally, approximately 4.5 fold more plasma peptide precursors were detected by both timsTOF HT and timsTOF Pro 2 in the Proteograph analyzed plasma vs neat plasma. In an exploratory analysis of 20 late-stage lung cancer and 20 control plasma samples with the Proteograph, which were expected to exhibit distinct proteomes, an approximate 50% increase in total and statistically significant plasma peptide precursors (q < 0.05) was observed with timsTOF HT compared to Pro 2. Our data demonstrate the superior performance of timsTOF HT for identifying and quantifying differences between biologically diverse samples, allowing for improved disease biomarker discovery in large cohort studies. Moreover, researchers can leverage data sets from this study to optimize their liquid chromatography-mass spectrometry (LC-MS) workflows for plasma protein profiling and biomarker discovery. (ProteomeXchange identifier: PXD047854 and PXD047839).

Risk of COVID-19 death for people with a pre-existing cancer diagnosis prior to COVID-19-vaccination: A systematic review and meta-analysis.

While previous reviews found a positive association between pre-existing cancer diagnosis and COVID-19-related death, most early studies did not distinguish long-term cancer survivors from those recently diagnosed/treated, nor adjust for important confounders including age. We aimed to consolidate higher-quality evidence on risk of COVID-19-related death for people with recent/active cancer (compared to people without) in the pre-COVID-19-vaccination period. We searched the WHO COVID-19 Global Research Database (20 December 2021), and Medline and Embase (10 May 2023). We included studies adjusting for age and sex, and providing details of cancer status. Risk-of-bias assessment was based on the Newcastle-Ottawa Scale. Pooled adjusted odds or risk ratios (aORs, aRRs) or hazard ratios (aHRs) and 95% confidence intervals (95% CIs) were calculated using generic inverse-variance random-effects models. Random-effects meta-regressions were used to assess associations between effect estimates and time since cancer diagnosis/treatment. Of 23 773 unique title/abstract records, 39 studies were eligible for inclusion (2 low, 17 moderate, 20 high risk of bias). Risk of COVID-19-related death was higher for people with active or recently diagnosed/treated cancer (general population: aOR = 1.48, 95% CI: 1.36-1.61, I2 = 0; people with COVID-19: aOR = 1.58, 95% CI: 1.41-1.77, I2 = 0.58; inpatients with COVID-19: aOR = 1.66, 95% CI: 1.34-2.06, I2 = 0.98). Risks were more elevated for lung (general population: aOR = 3.4, 95% CI: 2.4-4.7) and hematological cancers (general population: aOR = 2.13, 95% CI: 1.68-2.68, I2 = 0.43), and for metastatic cancers. Meta-regression suggested risk of COVID-19-related death decreased with time since diagnosis/treatment, for example, for any/solid cancers, fitted aOR = 1.55 (95% CI: 1.37-1.75) at 1 year and aOR = 0.98 (95% CI: 0.80-1.20) at 5 years post-cancer diagnosis/treatment. In conclusion, before COVID-19-vaccination, risk of COVID-19-related death was higher for people with recent cancer, with risk depending on cancer type and time since diagnosis/treatment.

A deep learning model, NAFNet, predicts adverse pathology and recurrence in prostate cancer using MRIs.

We aimed to apply a potent deep learning network, NAFNet, to predict adverse pathology events and biochemical recurrence-free survival (bRFS) based on pre-treatment MRI imaging. 514 prostate cancer patients from six tertiary hospitals throughout China from 2017 and 2021 were included. A total of 367 patients from Fudan University Shanghai Cancer Center with whole-mount histopathology of radical prostatectomy specimens were assigned to the internal set, and cancer lesions were delineated with whole-mount pathology as the reference. The external test set included 147 patients with BCR data from five other institutes. The prediction model (NAFNet-classifier) and integrated nomogram (DL-nomogram) were constructed based on NAFNet. We then compared DL-nomogram with radiology score (PI-RADS), and clinical score (Cancer of the Prostate Risk Assessment score (CAPRA)). After training and validation in the internal set, ROC curves in the external test set showed that NAFNet-classifier alone outperformed ResNet50 in predicting adverse pathology. The DL-nomogram, including the NAFNet-classifier, clinical T stage and biopsy results, showed the highest AUC (0.915, 95% CI: 0.871-0.959) and accuracy (0.850) compared with the PI-RADS and CAPRA scores. Additionally, the DL-nomogram outperformed the CAPRA score with a higher C-index (0.732, P < 0.001) in predicting bRFS. Based on this newly-developed deep learning network, NAFNet, our DL-nomogram could accurately predict adverse pathology and poor prognosis, providing a potential AI tools in medical imaging risk stratification.

HDAC1: An Essential and Conserved Member of the Diverse Zn2+-Dependent HDAC Family Driven by Divergent Selection Pressure.

Zn2+-dependent histone deacetylases (HDACs) are enzymes that regulate gene expression by removing acetyl groups from histone proteins. These enzymes are essential in all living systems, playing key roles in cancer treatment and as potential pesticide targets. Previous phylogenetic analyses of HDAC in certain species have been published. However, their classification and evolutionary origins across biological kingdoms remain unclear, which limits our understanding of them. In this study, we collected the HDAC sequences from 1451 organisms and performed analyses. The HDACs are found to diverge into three classes and seven subclasses under divergent selection pressure. Most subclasses show species specificity, indicating that HDACs have evolved with high plasticity and diversification to adapt to different environmental conditions in different species. In contrast, HDAC1 and HDAC3, belonging to the oldest class, are conserved and crucial in major kingdoms of life, especially HDAC1. These findings lay the groundwork for the future application of HDACs.

A model for predicting lymph node metastasis of thyroid carcinoma: a multimodality convolutional neural network study.

Background: Early preoperative evaluation of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) is critical for further surgical treatment. However, insufficient accuracy in predicting LNM status for PTC based on ultrasound images is a problem that needs to be urgently resolved. This study aimed to clarify the role of convolutional neural networks (CNNs) in predicting LNM for PTC based on multimodality ultrasound. Methods: In this study, the data of 308 patients who were clinically diagnosed with PTC and had confirmed LNM status via postoperative pathology at Beijing Tiantan Hospital, Capital Medical University, from August 2018 to April 2022 were incorporated into CNN algorithm development and evaluation. Of these patients, 80% were randomly included into the training set and 20% into the test set. The ultrasound examination of cervical LNM was performed to assess possible metastasis. Residual network 50 (Resnet50) was employed for feature extraction from the B-mode and contrast-enhanced ultrasound (CEUS) images. For each case, all of features were extracted from B-mode ultrasound images and CEUS images separately, and the ultrasound examination data of cervical LNM information were concatenated together to produce a final multimodality LNM prediction. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the predictive model. Heatmaps were further developed for visualizing the attention region of the images of the best-working model. Results: Of the 308 patients with PTC included in the analysis, 158 (51.3%) were diagnosed as LNM and 150 (48.7%) as non-LNM. In the test set, when a triple-modality method (i.e., B-mode image, CEUS image, and ultrasound examination of cervical LNM) was used, accuracy was maximized at 80.65% (AUC =0.831; sensitivity =80.65%; specificity =82.26%), which showed an expected increased performance over B-mode alone (accuracy =69.00%; AUC =0.720; sensitivity =70.00%; specificity =73.00%) and a dual-modality method (B-mode image plus CEUS image: accuracy =75.81%; AUC =0.742; sensitivity =74.19%; specificity =77.42%). The heatmaps of our triple-modality model demonstrated a possible focus area and revealed the model's flaws. Conclusions: The PTC lymph node prediction model based on the triple-modality features significantly outperformed all the other feature configurations. This deep learning model mimics the workflow of a human expert and leverages multimodal data from patients with PTC, thus further supporting clinical decision-making.

Tumor suppressor miR-520a inhibits cell growth by negatively regulating PI3K/AKT signaling pathway in acute myeloid leukemia.

BACKGROUND: Short regulatory RNAs, called microRNAs (miRNAs), have been found to possess regulatory functions in cancer and, as such, have recently been evaluated for their therapeutic role against various human malignancies. OBJECTIVES: The present work aimed to investigate whether miR-520a can play a therapeutic role in the treatment of human acute myeloid leukemia. MATERIAL AND METHODS: Human myeloid leukemia cell lines (Kasumi-1, Kasumi-3, Kasumi-6, BDCM, and K562) and a normal myeloid cell line (NCI-H5N6) were used for the study. Cell lines were subjected to real-time quantitative polymerase chain reaction (RT-qPCR), evaluation of cell viability and proliferation by MTT assay and colony formation assays. Dual acridine orange (AO)/ethidium bromide (EB) staining was applied for transfected K562 cells with miR-negative control (NC) or miR-520a mimics, and annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) dual staining and flow cytometry were performed to analyze cancer cell apoptosis followed by western blot. RESULTS: Cancerous cell lines exhibited lower gene expression of miR-520a, and its overexpression significantly reduced (p < 0.05) the proliferation and viability of cancer cells. Cancer cells demonstrated the induction of Bax/Bcl-2-mediated apoptosis following miR-520a overexpression. The miR-520a was shown to target the PI3K/AKT signaling pathway in human acute myeloid leukemia to exercise its regulatory role in cancer. CONCLUSIONS: The study showed that miR-520a actively regulated cell proliferation in acute myeloid leukemia and illustrated the mechanism by which it exerts its regulatory role, emphasizing the possibility of targeting miR-520a as an efficient therapeutic strategy against human acute myeloid leukemia.

High-Performance Artificial Ligament Made from Helical Polyester Fibers Wrapped with Aligned Carbon Nanotube Sheets.

Repairing high-load connective tissues, such as ligaments, by surgically implanting artificial grafts after injury is challenging because they lack biointegration with host bones for stable interfaces. Herein, a high-performance helical composite fiber (HCF) ligament by wrapping aligned carbon nanotube (CNT) sheets around polyester fibers is proposed. Anterior cruciate ligament (ACL) reconstruction surgery shows that HCF grafts could induce effective bone regeneration, thus allowing the narrowing of bone tunnel defects. Such repair of the bone tunnel is in strong contrast to the tunnel enlargement of more than 50% for commercial artificial ligaments made from bare polyester fibers. Rats reconstructed with this HCF ligament show normal jumping, walking, and running without limping. This work allows bone regeneration in vivo through a one-step surgery without seeding cells or transforming growth factors, thereby opening an avenue for high-performance artificial tissues.

Polyphyllin VII induces autophagy-dependent ferroptosis in human gastric cancer through targeting T-lymphokine-activated killer cell-originated protein kinase.

T-lymphokine-activated killer cell-originated protein kinase (TOPK) is a serine-threonine kinase that is overexpressed in gastric cancer (GC) and promotes tumor progression. Polyphyllin VII (PPVII), a pennogenin isolated from the rhizomes of Paris polyphylla, shows anticancer effects. Here, we explored the antitumor activity and mechanism of PPVII in GC. Ferroptosis was detected by transmission electron microscope, malondialdehyde, and iron determination assays. Autophagy and its upstream signaling pathway were detected by Western blot, and gene alterations. The binding of PPVII and TOPK was examined through microscale thermophoresis and drug affinity responsive target stability assays. An in vivo mouse model was performed to evaluate the therapeutic of PPVII. PPVII inhibits GC by inducing autophagy-mediated ferroptosis. PPVII promotes the degradation of ferritin heavy chain 1, which is responsible for autophagy-mediated ferroptosis. PPVII activates the Unc-51-like autophagy-activating kinase 1 (ULK1) upstream of autophagy. PPVII inhibits the activity of TOPK, thereby weakening the inhibition of downstream ULK1. PPVII stabilizes the dimer of the inactive form of TOPK by direct binding. PPVII inhibits tumor growth without causing obvious toxicity in vivo. Collectively, this study suggests that PPVII is a potential agent for the treatment of GC by targeting TOPK to activate autophagy-mediated ferroptosis.

Preoperative prediction of extrathyroidal extension: radiomics signature based on multimodal ultrasound to papillary thyroid carcinoma.

BACKGROUND: There is a recognized need for additional approaches to improve the accuracy of extrathyroidal extension (ETE) diagnosis in papillary thyroid carcinoma (PTC) before surgery. Up to now, multimodal ultrasound has been widely applied in disease diagnosis. We investigated the value of radiomic features extracted from multimodal ultrasound in the preoperative prediction of ETE. METHODS: We retrospectively pathologically confirmed PTC lesions in 235 patients from January 2019 to April 2022 in our hospital, including 45 ETE lesions and 205 non-ETE lesions. MaZda software was employed to obtain radiomics parameters in multimodal sonography. The most valuable radiomics features were selected by the Fisher coefficient, mutual information, probability of classification error and average correlation coefficient methods (F + MI + PA) in combination with the least absolute shrinkage and selection operator (LASSO) method. Finally, the multimodal model was developed by incorporating the clinical records and radiomics features through fivefold cross-validation with a linear support vector machine algorithm. The predictive performance was evaluated by sensitivity, specificity, accuracy, F1 scores and the area under the receiver operating characteristic curve (AUC) in the training and test sets. RESULTS: A total of 5972 radiomics features were extracted from multimodal sonography, and the 13 most valuable radiomics features were selected from the training set using the F + MI + PA method combined with LASSO regression. The multimodal prediction model yielded AUCs of 0.911 (95% CI 0.866-0.957) and 0.716 (95% CI 0.522-0.910) in the cross-validation and test sets, respectively. The multimodal model and radiomics model showed good discrimination between ETE and non-ETE lesions. CONCLUSION: Radiomics features based on multimodal ultrasonography could play a promising role in detecting ETE before surgery.

LSD-YOLOv5: A Steel Strip Surface Defect Detection Algorithm Based on Lightweight Network and Enhanced Feature Fusion Mode.

In the field of metallurgy, the timely and accurate detection of surface defects on metallic materials is a crucial quality control task. However, current defect detection approaches face challenges with large model parameters and low detection rates. To address these issues, this paper proposes a lightweight recognition model for surface damage on steel strips, named LSD-YOLOv5. First, we design a shallow feature enhancement module to replace the first Conv structure in the backbone network. Second, the Coordinate Attention mechanism is introduced into the MobileNetV2 bottleneck structure to maintain the lightweight nature of the model. Then, we propose a smaller bidirectional feature pyramid network (BiFPN-S) and combine it with Concat operation for efficient bidirectional cross-scale connectivity and weighted feature fusion. Finally, the Soft-DIoU-NMS algorithm is employed to enhance the recognition efficiency in scenarios where targets overlap. Compared with the original YOLOv5s, the LSD-YOLOv5 model achieves a reduction of 61.5% in model parameters and a 28.7% improvement in detection speed, while improving recognition accuracy by 2.4%. This demonstrates that the model achieves an optimal balance between detection accuracy and speed, while maintaining a lightweight structure.

What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?

The present study aimed to explore the potential of artificial intelligence (AI) methodology based on magnetic resonance (MR) images to aid in the management of prostate cancer (PCa). To this end, we reviewed and summarized the studies comparing the diagnostic and predictive performance for PCa between AI and common clinical assessment methods based on MR images and/or clinical characteristics, thereby investigating whether AI methods are generally superior to common clinical assessment methods for the diagnosis and prediction fields of PCa. First, we found that, in the included studies of the present study, AI methods were generally equal to or better than the clinical assessment methods for the risk assessment of PCa, such as risk stratification of prostate lesions and the prediction of therapeutic outcomes or PCa progression. In particular, for the diagnosis of clinically significant PCa, the AI methods achieved a higher summary receiver operator characteristic curve (SROC-AUC) than that of the clinical assessment methods (0.87 vs. 0.82). For the prediction of adverse pathology, the AI methods also achieved a higher SROC-AUC than that of the clinical assessment methods (0.86 vs. 0.75). Second, as revealed by the radiomics quality score (RQS), the studies included in the present study presented a relatively high total average RQS of 15.2 (11.0-20.0). Further, the scores of the individual RQS elements implied that the AI models in these studies were constructed with relatively perfect and standard radiomics processes, but the exact generalizability and clinical practicality of the AI models should be further validated using higher levels of evidence, such as prospective studies and open-testing datasets.

Sculponeatin A promotes the ETS1-SYVN1 interaction to induce SLC7A11/xCT-dependent ferroptosis in breast cancer.

BACKGROUND: E26 transformation specificity-1 (ETS1) is a transcription factor that is overexpressed in breast cancer (BC) and promotes tumor progression. Sculponeatin A (stA), a new diterpenoid extracted from Isodon sculponeatus, has no reported antitumor mechanism. PURPOSE: Here, we explored the antitumor activity of stA in BC and further clarified its mechanism. METHODS: Ferroptosis was detected by flow cytometric, glutathione, malondialdehyde, and iron determination assays. The effect of stA on the upstream signaling pathway of ferroptosis was detected by Western blot, gene expression, gene alterations and other approaches. The binding of stA and ETS1 was examined through a microscale thermophoresis assay and a drug affinity responsive target stability assay. An in vivo mouse model experiment was performed to evaluate the therapeutic and potential mechanism of stA. RESULTS: stA exhibits therapeutic potential in BC by inducing SLC7A11/xCT-dependent ferroptosis. stA decreases the expression of ETS1, which is responsible for xCT-dependent ferroptosis in BC. stA inhibits the transcriptional expression of xCT by directly binding to the ETS domain of the ETS1 protein. In addition, stA promotes proteasomal degradation of ETS1 by triggering ubiquitin ligase synoviolin 1 (SYVN1)-mediated ubiquitination. The K318 site of ETS1 mediates ubiquitination of ETS1 by SYVN1. In a mouse model, stA inhibits tumor growth without causing obvious toxicity. CONCLUSION: Taken together, the results confirm that stA promotes the ETS1-SYVN1 interaction to induce ferroptosis in BC mediated by ETS1 degradation. stA is expected to be used in research of candidate drugs for BC and drug design based on ETS1 degradation.

Pre-operative erector spinae plane block should be considered a viable option for laparoscopic colectomies.

BACKGROUND: The Erector Spinae Plane (ESP) block is a recent development in the field of regional anaesthesia and has been increasingly explored for abdominal surgeries to reduce opioid use and improve pain control. Colorectal cancer is the commonest cancer in multi-ethnic Singapore and requires surgery for curative treatment. ESP is a promising alternative in colorectal surgeries, but few studies have evaluated its efficacy in such surgeries. Therefore, this study aims to evaluate the use of ESP blocks in laparoscopic colorectal surgeries to establish its safety and efficacy in this field. METHODS: A prospective two-armed interventional cohort study comparing T8-T10 ESP blocks with conventional multimodal intravenous analgesia for laparoscopic colectomies was conducted in a single institution in Singapore. The decision for doing an ESP block versus conventional multimodal intravenous analgesia was made by a consensus between the attending surgeon and anesthesiologist. Outcomes measured were total intra-operative opioid consumption, post-operative pain control and patient outcome. Post-operative pain control was measured by pain score, analgesia use, and amount of opioids consumed. Patient outcome was determined by presence of ileus. RESULTS: A total of 146 patients were included, of which 30 patients received an ESP block. Overall, the ESP group had a significantly lower median opioid usage both intra-operatively and post-operatively (p = 0.031). Fewer patients required patient-controlled analgesia and rescue analgesia post-operatively for pain control (p < 0.001) amongst the ESP group. Pain scores were similar and post-operative ileus was absent in both groups. Multivariate analysis found that the ESP block had an independent effect on reducing intra-opioid consumption (p = 0.014). Multivariate analysis of post-operative opioid use and pain scores did not yield statistically significant results. CONCLUSIONS: The ESP block was an effective alternative regional anaesthesia for colorectal surgery that reduced intra-operative and post-operative opioid use while attaining satisfactory pain control.

Application of decision tree algorithms to predict central lymph node metastasis in well-differentiated papillary thyroid carcinoma based on multimodal ultrasound parameters: a retrospective study.

Background: Prophylactic central neck dissection (pCND) in patients with well-differentiated primary papillary thyroid carcinoma (PTC) has become controversial. Several attempts have been made to predict central compartment lymph node metastasis (CLNM) based on clinical and conventional ultrasonic parameters. This study aimed to develop a decision tree (DT) model for predicting the risk of CLNM in patients with PTC based on clinical and preoperative multimodal ultrasound (US) characteristics. Methods: A total of 148 PTC nodules confirmed by surgical pathology at Beijing Tiantan Hospital were retrospectively analyzed. All nodules underwent multimodal US examinations preoperatively from January 2020 to September 2021. Correlation analysis of CLNM with clinical characteristics as well as multimodal US parameters of PTC lesions based on gray-scale US, color Doppler flow imaging (CDFI), superb microvascular imaging (SMI), contrast-enhanced ultrasound (CEUS), and shear wave elastography (SWE) technology was carried out. Finally, the chi-squared automatic interaction detector (CHAID) with a 10-fold cross-validation was used to establish DTs for CLNM prediction. The area under the curve was calculated to compare the predictive performance. Results: Univariate analysis indicated that CLNM was positively correlated with thyroglobulin level, maximum size, taller-than-wide, the number of microcalcifications greater than or equal to 5, contact capsule, abnormal cervical lymph node on conventional US, noncentripetal perfusion, delayed clearance, the average shear wave velocity (SWV mean), and the SWV ratio (P<0.05). The multimodal US DT based on taller-than-wide, contact capsule, abnormal cervical lymph node on conventional US, and centripetal enhancement as independent variables showed good discrimination: the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve were 80.0%, 76.7%, 78.4%, and 0.837 [95% confidence interval (CI): 0.771-0.902]. There was a significant difference between the multimodal and conventional US DTs (P=0.009). Conclusions: Our results indicated that the DT based on the preoperative multimodal US characteristics of PTCs has a reasonable predictive ability for CLNM and can be conveniently used for clinical decision-making of individualized treatment in patients with well-differentiated PTC.

Significance of FNAC, BRAF mutation, and intraoperative frozen section in surgical decision-making of thyroid nodules.

BACKGROUND: A preoperative method is desired to discriminate benign from malignant thyroid nodules. This retrospective study evaluated the diagnostic performance of BRAF (B-Raf proto-oncogene) mutation (BRAFV600E ) positivity and fine-needle aspiration cytology (FNAC) relative to intraoperative frozen section pathology. METHODS: Patients underwent preoperative FNAC of thyroid nodules. Cytology specimens were classified according to the Bethesda System for Reporting Thyroid Cytopathology (BSRTC), and analyzed for BRAFV600E using an amplification-refractory mutation system (ARMS). Thyroid tissue was surgically removed and frozen sections processed for histology. The sensitivities and specificities of each analysis were compared, alone and in combination. RESULTS: Among 346 patients, 333/358 FNACs (93%) showed malignant nodules; 322 (93%) patients received a pathological diagnosis of papillary thyroid carcinoma (PTC). The sensitivity and specificity of BSRTC VI for malignancy was the highest among the BSRTC categories. Compared with FNAC, the BRAFV600E analysis had significantly higher sensitivity and specificity. The diagnostic efficacy of frozen section pathology was significantly higher than that of either BSRTC category or BRAFV600E analysis alone. Combining methods variably improved diagnostic performance. BRAFV600E was not associated with capsule infiltration, neurovascular infiltration, mono- or multifocal PTC, lymph node metastasis, or clinical stage. CONCLUSION: The diagnostic performance of preoperative BRAFV600E determination was better than that of the BSRTC-FNAC category; combining both improved sensitivity and specificity. Patients with positive malignancy scores from both should be recommended for surgery; those with negative scores require close monitoring. Surgical treatment should include comprehensive intraoperative frozen section assessment. BRAF mutations cannot indicate aggressive treatment.

One-year review of real-time artificial intelligence (AI)-aided endoscopy performance.

BACKGROUND: Colonoscopies have long been the gold standard for detection of pre-malignant neoplastic lesions of the colon. Our previous study tried real-time artificial intelligence (AI)-aided colonoscopy over a three-month period and found significant improvements in collective and individual endoscopist's adenoma detection rates compared to baseline. As an expansion, this study evaluates the 1-year performance of AI-aided colonoscopy in the same institution. METHODS: A prospective cohort study was conducted in a single institution in Singapore. The AI software used was GI Genius™ Intelligent Endoscopy Module, US-DG-2000309 © 2021 Medtronic. Between July 2021 and June 2022, polypectomy rates in non-AI-aided colonoscopies and AI-aided colonoscopies were calculated and compared. Some of the AI-aided colonoscopies were recorded and video reviewed. A "hit" was defined as a sustained detection of an area by the AI. If a polypectomy was performed for a "hit," its histology was reviewed. Additional calculations for polyp detection rate (PDR), adenoma detection rate (ADR), and adenoma detection per colonoscopy (ADPC) were performed. Cost analysis was performed to determine cost effectiveness of subscription to the AI program. RESULTS: 2433 AI-aided colonoscopies were performed between July 2021 and June 2022 and compared against 1770 non-AI-aided colonoscopies. AI-aided colonoscopies yielded significantly higher rates of polypectomies (33.6%) as compared with non-AI-aided colonoscopies (28.4%) (p < 0.001). Among the AI-aided colonoscopies, 1050 were reviewed and a final 843 were included for additional analysis. The polypectomy to "hit" ratio was 57.4%, PDR = 45.6%, ADR = 32.4%, and ADPC = 2.08. Histological review showed that 25 polyps (3.13%) were sessile-serrated adenomas. Cost analysis found that the increased polypectomy rates in AI-aided colonoscopes led to an increase in revenue, which covered the subscription cost with an excess of USD 20,000. CONCLUSION: AI-aided colonoscopy is a cost effective means of improving colonoscopy quality and may help advance colorectal cancer screening in Singapore.