Natural Product-Derived Phytochemicals for Influenza A Virus (H1N1) Prevention and Treatment.

Influenza A (H1N1) viruses are prone to antigenic mutations and are more variable than other influenza viruses. Therefore, they have caused continuous harm to human public health since the pandemic in 2009 and in recent times. Influenza A (H1N1) can be prevented and treated in various ways, such as direct inhibition of the virus and regulation of human immunity. Among antiviral drugs, the use of natural products in treating influenza has a long history, and natural medicine has been widely considered the focus of development programs for new, safe anti-influenza drugs. In this paper, we focus on influenza A (H1N1) and summarize the natural product-derived phytochemicals for influenza A virus (H1N1) prevention and treatment, including marine natural products, flavonoids, alkaloids, terpenoids and their derivatives, phenols and their derivatives, polysaccharides, and derivatives of natural products for prevention and treatment of influenza A (H1N1) virus. We further discuss the toxicity and antiviral mechanism against influenza A (H1N1) as well as the druggability of natural products. We hope that this review will facilitate the study of the role of natural products against influenza A (H1N1) activity and provide a promising alternative for further anti-influenza A drug development.

Number of positive lymph nodes and lymph node ratio predict recurrence and survival in hypopharyngeal cancer based on SEER database and validation of real-world data.

PURPOSE: This study investigated the impacts of the number of positive lymph nodes (NPLN) and lymph node ratio (LN ratio) for patients with hypopharyngeal squamous cell carcinoma (HPSCC) based on SEER database, which were validated in the real-world data of China. METHODS: A total of 520 patients from SEER database were analyzed. Then 195 patients with pathologically stage III or IV HPSCC in our center were retrospectively studied. RESULTS: In the SEER database, NPLN ≥ 3 was found in 36.9% of patients. Multivariate analysis revealed that LN ratio ≥ 0.138 was significant with poorer overall survival (OS) (hazard ratio [HR] = 1.525, p = 0.001) and cancer-specific survival (CSS) (HR = 1.697, p < 0.001), so was the NPLN ≥ 3 (HR = 1.388, p = 0.013; HR = 1.479, p = 0.008). Patients with NPLN ≥ 3 were found in 103 (52.8%) in our center. Multivariate analysis confirmed a significant association regarding OS (p = 0.005) or CSS (p = 0.003) between patients with LN ratio ≥ 0.138 or not. In addition, disease recurrence rate differed significantly between the patients with NPLN ≥ 3 (27.2%) and NPLN < 3 (14.1%, p = 0.026). Moreover, postoperative chemoradiotherapy (CCRT) was significantly associated with better prognosis in patients with NPLN ≥ 3. CONCLUSION: In the SEER database, NPLN ≥ 3 and LN ratio ≥ 0.138 were independent poor prognostic factors for patients with HPSCC. Whereas identifying worldwide cut-off values for LN ratio is difficult and surgeon-dependent. In our cohort, adjuvant CCRT was beneficial for OS in patients with NPLN ≥ 3.

Metabolic Syndrome and Tendon Disease: A Comprehensive Review.

Metabolic syndrome (MS) is a multifaceted pathological condition characterized by the atypical accumulation of various metabolic components such as central obesity or excess weight, hyperlipidemia, low-density lipoprotein (LDL), hypertension, and insulin resistance. Recently, MS has been recognized as a notable contributor to heart and circulatory diseases. In addition, with increasing research, the impact of MS on tendon repair and disease has gradually emerged. Recent studies have investigated the relationship between tendon healing and diseases such as diabetes, dyslipidemia, obesity, and other metabolic disorders. However, diabetes mellitus (DM), hypercholesterolemia, obesity, and various metabolic disorders often coexist and together constitute MS. At present, insulin resistance is considered the major pathological mechanism underlying MS, central obesity is regarded as the predominant factor responsible for it, and dyslipidemia and other metabolic diseases are known as secondary contributors to MS. This review aims to evaluate the current literature regarding the impact of various pathological conditions in MS on tendon recovery and illness, and to present a comprehensive overview of the effects of MS on tendon recovery and diseases, along with the accompanying molecular mechanisms.

Palbociclib inhibits the progression of head and neck cancer and improves the Cetuximab response under specific condition in vitro and in vivo.

BACKGROUND: In head and neck squamous cell carcinoma (HNSCC) with human papillomavirus (HPV)-negative, deregulation of cell cycle is partly due to inactivation of p16INK4 and overexpression of cyclin D1. Here we investigated the in vitro and in vivo effects of the CDK4/6 inhibitor Palbociclib alone or combined with EGFR inhibitor Cetuximab in HNSCC. METHODS AND RESULTS: CCK-8, soft agar assay, colony formation assay, wound healing assay and transwell assay, ß-galactosidase assay, western blotting, and cell-derived xenografts were used to investigated the in vitro and in vivo activity of drugs. Cell viability and colony formation decreased in a dose-dependent manner in Tu686, AMC-HN8, and Fadu cells under Palbociclib treatment. Palbociclib remarkably inhibited migration, invasion and the expression MMP-9 in HNSCC cells. Palbociclib also induced senescence. Palbociclib caused the dephosphorylation of RB but increased the cyclin D1 level in a dose-dependent manner. Moreover, combination with Cetuximab could significantly prevent the induction of cyclin D1 and activation of EGFR signals from Palbociclib treatment. Nevertheless, only within the range of certain concentrations, a synergistic inhibitory effect on cell growth was observed when combined with Palbociclib and Cetuximab. Although the synergistic effect in Palbociclib/Cetuximab combined therapy was comparable to that in traditional chemotherapeutic regimens (cisplatin/Cetuximab) in Fadu tumor xenograft, the combination therapy was less active than Cetuximab monotherapy in Tu686 tumor xenograft. CONCLUSION: In HPV-negative HNSCC, CDK4/6 inhibitor shows promising anti-tumor effects, which exhibits a synergistic effect when combined with EGFR inhibitor only in specific drug concentration and mouse model.

New evidence for fractional pressure ratio prediction by pulsatility index from transcranial Doppler in patients with symptomatic cerebrovascular stenosis disease.

Background: The pulsatility index (PI) derived from transcranial Doppler (TCD) assessment may represent the cerebral resistance and altered cerebral blood flow. The purpose of this study was to assess the performance of the TCD PI in correlation with wire-based fractional pressure ratio (FPR). Methods: This study included 33 patients with symptomatic atherosclerotic lesions of the extracranial and intracranial large arteries, specifically the internal carotid artery, middle cerebral artery (MCA), vertebral artery (VA) V4 segment, and basilar artery (BA), all of which exhibited luminal stenosis ranging from 50% to 70%. TCD was performed prior to angiography in order to determine the flow distal to the lesion. We performed cerebrovascular angiography with a pressure wire to measure the FPR of vessels with stenotic lesions. Bland-Altman analysis and ordinal least square (OLS) linear regression were used to quantify the correlation between PI and FPR. Results: A total of 42 TCD data points were analyzed. At the TCD locations distal to the lesions, the correlation coefficients were no less than 0.90%, with almost all P values <0.001, which indicated very strong positive correlations; the exception to this was the distal TCD for MCA segment lesions (r=0.897; P=0.015) and VA V4 segment (r=0.964; P=0.036). The Bland-Altman plot demonstrated a small difference (0.003) between the distal TCD PI and the FPR, with an acceptable 95% confidence interval [95% confidence interval (CI): 0.06-0.12]. Conclusions: The PI obtained through TCD assessment distal to the stenotic lesion exhibited a correlation with the FPR computed using pressure wire measurements.

EasyGraph: A multifunctional, cross-platform, and effective library for interdisciplinary network analysis.

Networks are powerful tools for representing the relationships and interactions between entities in various disciplines. However, existing network analysis tools and packages either lack powerful functionality or are not scalable for large networks. In this descriptor, we present EasyGraph, an open-source network analysis library that supports several network data formats and powerful network mining algorithms. EasyGraph provides excellent operating efficiency through a hybrid Python/C++ implementation and multiprocessing optimization. It is applicable to various disciplines and can handle large-scale networks. We demonstrate the effectiveness and efficiency of EasyGraph by applying crucial metrics and algorithms to random and real-world networks in domains such as physics, chemistry, and biology. The results demonstrate that EasyGraph improves the network analysis efficiency for users and reduces the difficulty of conducting large-scale network analysis. Overall, it is a comprehensive and efficient open-source tool for interdisciplinary network analysis.

Metal artifacts reduction in kV-CT images with polymetallic dentures and complex metals based on MV-CBCT images in radiotherapy.

This paper proposes a metal artifact reduction method of using MV-CBCT images to correct metal artifacts in kV-CT images, especially for the complex metal artifacts caused by multi-metal interaction of patients with head and neck tumors. The different tissue regions are segmented in the MV-CBCT images to obtain template images and the metal region is segmented in the kV-CT images. Forward projection is performed to get sinogram of the template images, kV-CT images and metal region images. Artifact images can be reconstructed through those sonograms. Corrected images is generated by subtracting the artifact images from the original kV-CT images. After the first correction, the template images are generated again and brought into the previous step for iteration to get better correction result. CT data set of 7 patients are used in this study, compared with linear interpolation metal artifact (LIMAR) and normalized metal artifact reduction method, mean relative error of CT value is reduced by 50.5% and 63.3%, noise is reduced by 56.2% and 58.9%. The Identifiability Score of the tooth, upper/lower jaw, tongue, lips, masseter muscle and cavity in the corrected images by the proposed method have significantly improved (P < 0.05) than original images. The artifacts correction method proposed in this paper can effectively remove the metal artifacts in the images and greatly improve the CT value accuracy, especially in the case of multi-metal and complex metal implantation.

A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification.

Sleep staging is crucial for diagnosing sleep-related disorders. The heavy and time-consuming task of manual staging can be released by automatic techniques. However, the automatic staging model would have a relatively poor performance when working on unseen new data due to individual differences. In this research, a developed LSTM-Ladder-Network (LLN) model is proposed for automatic sleep stage classification. Several features are extracted for each epoch and combined with the following epochs to form a cross-epoch vector. The long short-term memory (LSTM) network is added into the basic ladder network (LN) to learn the sequential information of adjacent epochs. The developed model is implemented based on a transductive learning scheme to avoid the issue of accuracy loss caused by individual differences. In this process, the labeled data pre-trains the encoder, and the unlabeled data re- fine the model parameters by minimizing the reconstruction loss. The proposed model is evaluated on the data from public database and hospital. Comparison experiments were conducted where the developed LLN model achieved rather satisfied performance while dealing with the unseen new data. The obtained results demonstrate the effectiveness of the proposed approach in addressing individual differences. This can improve the quality of automatic sleep staging when assessed on different individuals and has strong application potential as a computer aided approach for sleep staging.

Impacts of respiratory fluctuations on cerebral circulation: a machine-learning-integrated 0-1D multiscale hemodynamic model.

Objective. This study aims to accurately identify the effects of respiration on the hemodynamics of the human cardiovascular system, especially the cerebral circulation.Approach: we have developed a machine learning (ML)-integrated zero-one-dimensional (0-1D) multiscale hemodynamic model combining a lumped-parameter 0D model for the peripheral vascular bed and a one-dimensional (1D) hemodynamic model for the vascular network.In vivomeasurement data of 21 patients were retrieved and partitioned into 8000 data samples in which respiratory fluctuation (RF) of intrathoracic pressure (ITP) was fitted by the Fourier series. ML-based classification and regression algorithms were used to examine the influencing factors and variation trends of the key parameters in the ITP equations and the mean arterial pressure. These parameters were employed as the initial conditions of the 0-1D model to calculate the radial artery blood pressure and the vertebral artery blood flow volume (VAFV).Main results: during stable spontaneous respiration, the VAFV can be augmented at the inhalation endpoints by approximately 0.1 ml s-1for infants and 0.5 ml s-1for adolescents or adults, compared to those without RF effects. It is verified that deep respiration can further increase the ranges up to 0.25 ml s-1and 1 ml s-1, respectively.Significance. This study reveals that reasonable adjustment of respiratory patterns, i.e. in deep breathing, enhances the VAFV and promotes cerebral circulation.

Occurrence of Tomato leaf curl New Delhi virus in tomato (Lycopersicon esculentum) in China.

Tomato leaf curl New Delhi virus (ToLCNDV), a member of the genus Begomovirus in the family Geminiviridae is naturally transmitted by the whitefly Bemisia tabaci (order Hemiptera, family Aleyrodidae) in a circulative and persistent manner (Moriones et al. 2017). ToLCNDV has occurred in Bangladesh, India, Indonesia, Iran, Italy, Malaysia, Pakistan, Sri Lanka, Spain, Thailand and Tunisia (Moriones et al. 2017). To date, The primary cultivated host of ToLCNDV has been identified as tomato (Lycopersicon esculentum), but the virus is also known to infect 43 other plant species from a range of families including Cucurbitaceae, Euphorbiaceae, Solanaceae, Malvaceae and Fabaceae (Zaidi et al. 2017). In August 2021, virus-like symptoms including leaf deformation and curing were observed on tomato (Lycopersicon esculentum) in a greenhouse of about 0.5 hectares in Zhejiang Province, China. To identify viral agents potentially associated with this disease, an Oxford Nanopore cDNA library from a symptomatic sample was generated and sequenced. Total RNA was extracted using RNAiso Plus (TaKaRa, Tokyo, Japan). Libraries were constructed using Oxford Nanopore PCR-cDNA Sequencing Kit (SQK-PCS109; Oxford Nanopore Technologies, Oxford, UK), as recommended. Approximately 8.7 million reads were obtained from the Oxford MinION platform. After removing the adapters and low-quality reads, the clean reads were subjected to BLASTn analysis against the nt database. Approximately 797 and 168 reads produced high nt identities to the genome of ToLCNDV DNA-A (GeneBank Accession No. U15015.2) and ToLCNDV DNA-B (GeneBank Accession No. U15017.2) respectively. We designed 6 primer pairs (Table S1) to obtain the sequence of ToLCNDV Zhejiang (ToLCNDV-ZJ) isolate DNA-A and DNA-B. Briefly, total DNA from ToLCNDV-infected tomato was extracted using standard cetyl trimethylammonium bromide method. Segments of ToLCNDV DNA-A and DNA-B were amplified using high-fidelity DNA polymerase KOD-Plus-Neo (Toyobo, Osaka, Japan). PCR products were cloned into the pLB vector (Tiangen, Beijing, China) and Sanger sequenced. The obtained sequences were assembled into complete sequences of ToLCNDV-ZJ DNA-A (2,739 nt, GeneBank Accession No. OP356207) and DNA-B (2,693 nt, GeneBank Accession No. OP356208). Pairwise sequence comparison revealed that the ToLCNDV -ZJ shared the highest nt sequence identities of 98.7% and 98.4% with the genome segments of New Delhi isolate (genome A: HM159454) and India:Delhi:Cucumis:2012 isolate (genome B: KC545813) respectively. Furthermore, we performed PCR detection on 10 collected samples using the primer pair P1F and P1R. All eight symptomatic plants showing upward leaf curling and leaf distortion tested positive for ToLCNDV infection, whereas two asymptomatic plants were ToLCNDV free. To our knowledge, this is the first report of ToLCNDV infecting tomato in China, and with the widespread presence of B. tabaci in green houses, ToLCNDV may be a potential threat to the cultivation of tomato in China. In addition, ToLCNDV is an exceptional Old World bipartite begomovirus. In China, monopartite DNA satellite-associated begomoviruses with mostly narrow geographical ranges predominate, and are widespread (Li et al., 2022). The occurrence of ToLCNDV in China, which indicates that the success of this virus would become an emerging threat to vegetable and fiber crops.

A Novel Strategy for Excellent Piezocatalytic Activity in Lead-Free BaTiO3-Based Materials via Manipulating the Multiphase Coexistence.

Piezocatalysis is regarded as a fascinating technology for water remediation and possible disease treatment. A high piezoelectric coefficient (d33) is one of the most important parameters to determine piezocatalytic performance, which can be manipulated via phase boundary design. Herein, a novel strategy for excellent piezocatalytic activity in lead-free BaTiO3-based materials via manipulating the multiphase coexistence is proposed. The piezocatalyst of 0.82Ba(Ti0.89Sn0.11)O3-0.18(Ba0.7Ca0.3)TiO3 (0.82BTS-0.18BCT) with multiphase coexistence is prepared, and a large d33 can be obtained. As a result, 0.82BTS-0.18BCT exhibits excellent piezocatalytic performance for the degradation of Rhodamine B (RhB). Furthermore, the removal rate of RhB could reach more than 90% after vibration for 30 min, and the reaction rate constant (k) could reach 0.0706 min-1, which is much superior to that of most other representative perovskite-structured piezoelectric materials. Excellent piezocatalytic performance can be attributed to the strong local ferro-/piezoelectric response induced by the multiphase coexistence, as confirmed by the in situ piezoresponse force microscopy (PFM). Finally, the piezocatalytic degradation mechanism is analyzed systemically and proposed. This work not only provides a high-efficiency piezocatalyst but also sheds light on developing efficient BT-based piezocatalysts by manipulating the multiphase coexistence.

Induction chemotherapy of modified docetaxel, cisplatin, 5-fluorouracil for laryngeal preservation in locally advanced hypopharyngeal squamous cell carcinoma.

BACKGROUND: Previous studies have investigated the value of induction chemotherapy (IC) in organ preservation strategies for head and neck cancers. This study evaluated the effectiveness of sequential IC with radiotherapy as a laryngeal preservation strategy for locally advanced hypopharyngeal carcinoma (LAHSCC). METHODS: One hundred and forty-two consecutive patients with LAHSCC were retrospectively analyzed who received three IC regimens from 2015 to 2019. RESULTS: In the TP (docetaxel plus cisplatin), TPF (TP plus 5-fluorouracil), and TPX (TP plus capecitabine) IC groups, there were 51, 29, and 62 patients, respectively. The primary tumor objective response rates were 51%, 55.2%, and 71%, and the 3-year survival rates with preserved larynx were 36.6%, 31.8%, and 51.2%, respectively (p = 0.03). There was no difference in overall survival and the adverse events were tolerable. CONCLUSIONS: The TPX regimen displayed good efficacy and safety, indicating its potential as a therapeutic IC regimen for LAHSCC.

Design of ultra-thin underwater acoustic metasurface for broadband low-frequency diffuse reflection by deep neural networks.

Underwater acoustic metasurfaces have broad application prospects for the stealth of underwater objects. However, problems such as a narrow operating frequency band, poor operating performance, and considerable thickness at low frequencies remain. In this study a reverse design method for ultra-thin underwater acoustic metasurfaces for low-frequency broadband is proposed using a tandem fully connected deep neural network. The tandem neural network consists of a pre-trained forward neural network and a reverse neural network, based on which a set of elements with flat phase variation and an almost equal phase shift interval in the range of 700-1150 Hz is designed. A diffuse underwater acoustic metasurface with 60 elements was designed, showing that the energy loss of the metasurface in the echo direction was greater than 10 dB. Our work opens a novel pathway for realising low-frequency wideband underwater acoustic devices, which will enable various applications in the future.

A machine learning strategy for fast prediction of cardiac function based on peripheral pulse wave.

OBJECTIVE: Pulse wave has been considered as a message carrier in the cardiovascular system (CVS), capable of inferring CVS conditions while diagnosing cardiovascular diseases (CVDs). Clarification and prediction of cardiovascular function by means of powerful feature-abstraction capability of machine learning method based on pulse wave is of great clinical significance in health monitoring and CVDs diagnosis, which remains poorly studied. METHODS: Here we propose a machine learning (ML)-based strategy aiming to achieve a fast and accurate prediction of three cardiovascular function parameters based on a 412-subject database of pulse waves. We proposed and optimized an ML-based model with multi-layered, fully connected network while building up two high-quality pulse wave datasets comprising a healthy-subject group and a CVD-subject group to predict arterial compliance (AC), total peripheral resistance (TPR), and stroke volume (SV), which are essential messengers in monitoring CVS conditions. RESULTS: Our ML model is validated through consistency analysis of the ML-predicted three cardiovascular function parameters with clinical measurements and is proven through error analysis to have capability of achieving a high-accurate prediction on TPR and SV for both healthy-subject group (accuracy: 85.3%, 86.9%) and CVD-subject group (accuracy: 88.3%, 89.2%). DISCUSSION: The independent sample t-test proved that our subject groups could represent the typical physiological characteristics of the corresponding population. While we have more subjects in our datasets rather than previous studies after strict data screening, the proposed ML-based strategy needs to be further improved to achieve a disease-specific prediction of heart failure and other CVDs through training with larger datasets and clinical measurements. CONCLUSION: Our study points to the feasibility and potential of the pulse wave-based prediction of physiological and pathological CVS conditions in clinical application.

Increased response to TPF chemotherapy promotes immune escape in hypopharyngeal squamous cell carcinoma.

Background: There is an urgent need to identify which patients would benefit from TPF chemotherapy in hypopharyngeal squamous cell carcinoma (HPSCC) and to explore new combinations to improve the treatment effect. Materials and methods: Gene-expression profiles in 15 TPF-sensitive patients were compared to 13 resistant patients. Immunohistochemistry (IHC) was performed to detect CD8+ T cells in 28 samples. Patient-Derived Tumor Xenograft (PDX) model and IHC were used to verify markers that optimize treatment for HPSCC. Results: Through RNA sequencing 188 genes were up-regulated in TPF chemotherapy-resistant (CR) tissues were involved in T cell activation, while 60 down-regulated genes were involved in glycolysis. Gene set enrichment analysis (GSEA) showed that chemotherapy-sensitive (CS) group upregulation of the pathways of glycolysis, while immune response was downregulated. CIBERSORT, MCP-counter, and IHC proved that most immune cells including CD8+ T cells in the CR significantly higher than that in CS group. Among the 16 up-regulated genes in CS had close associations, the most significant negative correlation between the gene level and CD8+ T cells existed in SEC61G. SEC61G was related to glycolysis, which was transcriptionally regulated by E2F1, and participated in antigen degradation through ubiquitin-dependent protein catabolic process. Palbociclib, combined with Cetuximab decreased the tumor burden and significantly suppressed the expression of E2F1 and SEC61G while activating MHC-I in PDX model. Conclusion: Enhanced glycolysis promoted immune escape, but increased response to TPF chemotherapy. SEC61G was the center of the molecular network and targeting the E2F1/SEC61G pathway increased the expression level of MHC-I.

Deep learning-based hemodynamic prediction of carotid artery stenosis before and after surgical treatments.

Hemodynamic prediction of carotid artery stenosis (CAS) is of great clinical significance in the diagnosis, prevention, and treatment prognosis of ischemic strokes. While computational fluid dynamics (CFD) is recognized as a useful tool, it shows a crucial issue that the high computational costs are usually required for real-time simulations of complex blood flows. Given the powerful feature-extraction capabilities, the deep learning (DL) methodology has a high potential to implement the mapping of anatomic geometries and CFD-driven flow fields, which enables accomplishing fast and accurate hemodynamic prediction for clinical applications. Based on a brain/neck CT angiography database of 280 subjects, image based three-dimensional CFD models of CAS were constructed through blood vessel extraction, computational domain meshing and setting of the pulsatile flow boundary conditions; a series of CFD simulations were undertaken. A DL strategy was proposed and accomplished in terms of point cloud datasets and a DL network with dual sampling-analysis channels. This enables multimode mapping to construct the image-based geometries of CAS while predicting CFD-based hemodynamics based on training and testing datasets. The CFD simulation was validated with the mass flow rates at two outlets reasonably agreed with the published results. Comprehensive analysis and error evaluation revealed that the DL strategy enables uncovering the association between transient blood flow characteristics and artery cavity geometric information before and after surgical treatments of CAS. Compared with other methods, our DL-based model trained with more clinical data can reduce the computational cost by 7,200 times, while still demonstrating good accuracy (error<12.5%) and flow visualization in predicting the two hemodynamic parameters. In addition, the DL-based predictions were in good agreement with CFD simulations in terms of mean velocity in the stenotic region for both the preoperative and postoperative datasets. This study points to the capability and significance of the DL-based fast and accurate hemodynamic prediction of preoperative and postoperative CAS. For accomplishing real-time monitoring of surgical treatments, further improvements in the prediction accuracy and flexibility may be conducted by utilizing larger datasets with specific real surgical events such as stent intervention, adopting personalized boundary conditions, and optimizing the DL network.

Development of a random forest model for hypotension prediction after anesthesia induction for cardiac surgery.

BACKGROUND: Hypotension after the induction of anesthesia is known to be associated with various adverse events. The involvement of a series of factors makes the prediction of hypotension during anesthesia quite challenging. AIM: To explore the ability and effectiveness of a random forest (RF) model in the prediction of post-induction hypotension (PIH) in patients undergoing cardiac surgery. METHODS: Patient information was obtained from the electronic health records of the Second Affiliated Hospital of Hainan Medical University. The study included patients, ≥ 18 years of age, who underwent cardiac surgery from December 2007 to January 2018. An RF algorithm, which is a supervised machine learning technique, was employed to predict PIH. Model performance was assessed by the area under the curve (AUC) of the receiver operating characteristic. Mean decrease in the Gini index was used to rank various features based on their importance. RESULTS: Of the 3030 patients included in the study, 1578 (52.1%) experienced hypotension after the induction of anesthesia. The RF model performed effectively, with an AUC of 0.843 (0.808-0.877) and identified mean blood pressure as the most important predictor of PIH after anesthesia. Age and body mass index also had a significant impact. CONCLUSION: The generated RF model had high discrimination ability for the identification of individuals at high risk for a hypotensive event during cardiac surgery. The study results highlighted that machine learning tools confer unique advantages for the prediction of adverse post-anesthesia events.

Development and Validation of a Prognostic Nomogram for Hypopharyngeal Carcinoma.

Hypopharyngeal squamous-cell carcinoma (HSCC) is a relatively rare head and neck cancer, with great variation in patient outcomes. This study aimed to develop a prognostic nomogram for patients with HSCC. From the Surveillance, Epidemiology, and End Results (SEER) database, we retrieved the clinical data of 2198 patients diagnosed with HSCC between 2010 and 2016. The patients were randomly assigned at a 4:1 ratio to the training set or the validation set. An external validation was performed by a set of 233 patients with locally advanced HSCC treated at our center. A Cox proportional hazards regression model was used to assess the relationship between each variable and overall survival (OS). Cox multivariate regression analysis was performed, and the results were used to develop a prognostic nomogram. The calibration curve and concordance index (C-index) were used to evaluate the accuracy of the prognostic nomogram. With a median overall follow-up time of 41 months (interquartile range: 20 to 61), the median OS for the entire cohort of SEER database was 24 months. The 3-year and 5-year OS rates were 41.3% and 32.5%, respectively. The Cox multivariate regression analysis of the training set showed that age, marital status, race, T stage, N stage, M stage, TNM stage, local treatment, and chemotherapy were correlated with OS. The nomogram showed a superior C-index over TNM stage (training set: 0.718 vs 0.627; validation set: 0.708 vs 0.598; external validation set: 0.709 vs 0.597), and the calibration curve showed a high level of concordance between the predicted OS and the actual OS. The nomogram provides a relatively accurate and applicable prediction of the survival outcome of patients with HSCC.

Radiotherapy versus partial laryngectomy in the management of early glottic cancer with anterior commissure involvement: A propensity score matched study with 256 patients.

OBJECTIVES: The study was intended to compare the outcomes for T1-T2N0M0 glottic squamous cell carcinoma with anterior commissure involvement who had undergone partial laryngectomy (PL) or radiotherapy (RT). MATERIALS AND METHODS: We retrospectively analyzed 256 patients who were treated by RT (n = 70) or PL (n = 186). Patients received prophylactic irradiation of the neck in RT group whereas PL was not associated with lymphadenectomy. Propensity score matching (PSM) was used to eliminate the baseline variations. RESULTS: The average age of the RT group (67 years) was significantly higher than that of the PL (59 years). Local recurrence was noted in 14 patients of the RT group and 22 of the PL. While regional recurrence was noted in only 1 patient of the RT group and 23 of the PL. After PSM, the 5-year overall survival (82.8% vs. 83.9%, p = 0.302), 5-year cancer-specific survival (88.3% vs. 89.7%, p = 0.793), 5-year local relapse-free survival (79.3% vs. 84.5%, p = 0.127) were not significantly different between two groups. However, 5-year regional relapse-free survival in the RT group was significantly better than that in the PL (100% vs. 87.1%, p = 0.014). In the PL group, infection, granuloma, laryngeal stenosis, chylous leakage, and pharyngeal fistula were reported in six, 11, 12, one, and two patients, respectively. CONCLUSIONS: RT resulted in comparable rates of survival, local control, and larynx preservation compared to PL. However, RT was associated with higher regional control rate. The complication rates were extremely low in RT group.

Management of orbital invasion in sinonasal squamous cell carcinoma: 15 years' experience.

BACKGROUND: This study was intended to review our management strategy for sinonasal squamous cell carcinomas (SNSCCs) with orbital invasion and to explore the role of radiotherapy in orbital preservation. METHODS: We retrospectively analyzed 93 SNSCC patients with orbital invasion who underwent radiotherapy with or without surgery over the past 15 years. The degree of orbital invasion was classified into 3 grades. RESULTS: Eighty-eight patients presented with T4 tumors and 36 had grade III orbital invasion. Seventy-two patients received surgery plus radiation and 67 received platinum-based chemotherapy. The median follow-up for surviving patients was 60 months. Five-year overall survival (OS) for the whole group was 57.4%. The patients treated with surgery plus radiation had a 5-year survival rate of 62.2% and orbital preservation was feasible in 90.3% of cases. Twenty-one patients with SNSCCs that extended into the extraocular muscles or eye globe also underwent orbital preservation. Five-year locoregional relapse-free survival (LRFS) was 69.5% for patients treated with orbital preservation and 57.1% for those treated with orbital exenteration, indicating no statistical difference. Five-year survival, 5-year progression-free survival (PFS), and 5-year distant metastasis-free survival (DMFS) were similar between groups. Grade III orbital invasion was independently associated with shorter OS, LRFS, PFS, and DMFS. CONCLUSION: Orbital invasion in grade III was associated with the worst survival outcomes. Invasion of either the extraocular muscles or eye globe is not a contraindication for eye-sparing surgery. Preoperative chemoradiation continues to offer hope to patients with a strong desire to preserve their eyes.