An effective colorectal polyp classification for histopathological images based on supervised contrastive learning.

Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic variants is crucial. This study introduces a cutting-edge computer-aided diagnosis system optimized for this task. Our system employs advanced Supervised Contrastive learning to ensure precise classification of colon histopathology images. Significantly, we have integrated the Big Transfer model, which has gained prominence for its exemplary adaptability to visual tasks in medical imaging. Our novel approach discerns between in-class and out-of-class images, thereby elevating its discriminatory power for polyp subtypes. We validated our system using two datasets: a specially curated one and the publicly accessible UniToPatho dataset. The results reveal that our model markedly surpasses traditional deep convolutional neural networks, registering classification accuracies of 87.1% and 70.3% for the custom and UniToPatho datasets, respectively. Such results emphasize the transformative potential of our model in polyp classification endeavors.

Phase I study of sapanisertib (CB-228/TAK-228/MLN0128) in combination with ziv-aflibercept in patients with advanced solid tumors.

BACKGROUND: Sapanisertib is a potent ATP-competitive, dual inhibitor of mTORC1/2. Ziv-aflibercept is a recombinant fusion protein comprising human VEGF receptor extracellular domains fused to human immunoglobulin G1. HIF-1α inhibition in combination with anti-angiogenic therapy is a promising anti-tumor strategy. This Phase 1 dose-escalation/expansion study assessed safety/ tolerability of sapanisertib in combination with ziv-aflibercept in advanced solid tumors. METHODS: Fifty-five patients with heavily pre-treated advanced metastatic solid tumors resistant or refractory to standard treatment received treatment on a range of dose levels. RESULTS: Fifty-five patients were enrolled and treated across a range of dose levels. Forty were female (73%), median age was 62 (range: 21-79), and ECOG PS was 0 (9, 16%) or 1 (46, 84%). Most common tumor types included ovarian (8), colorectal (8), sarcoma (8), breast (3), cervical (4), and endometrial (4). Median number of prior lines of therapy was 4 (range 2-11). Sapanisertib 4 mg orally 3 days on and 4 days off plus 3 mg/kg ziv-aflibercept IV every 2 weeks on a 28-day cycle was defined as the maximum tolerated dose. Most frequent treatment-related grade ≥2 adverse events included hypertension, fatigue, anorexia, hypertriglyceridemia, diarrhea, nausea, mucositis, and serum lipase increase. There were no grade 5 events. In patients with evaluable disease (n = 50), 37 patients (74%) achieved stable disease (SD) as best response, two patients (4%) achieved a confirmed partial response (PR); disease control rate (DCR) (CR + SD + PR) was 78%. CONCLUSION: The combination of sapanisertib and ziv-aflibercept was generally tolerable and demonstrated anti-tumor activity in heavily pre-treated patients with advanced malignancies.

Transfer Learning for P300 Brain-Computer Interfaces by Joint Alignment of Feature Vectors.

This article presents a new transfer learning method named group learning, that jointly aligns multiple domains (many-to-many) and an extension named fast alignment that aligns any further domain to previously aligned group of domains (many-to-one). The proposed group alignment algorithm (GALIA) is evaluated on brain-computer interface (BCI) data and optimal hyper-parameter values of the algorithm are studied for classification performance and computational cost. Six publicly available P300 databases comprising 333 sessions from 177 subjects are used. As compared to the conventional subject-specific train/test pipeline, both group learning and fast alignment significantly improve the classification accuracy except for the database with clinical subjects (average improvement: 2.12±1.88%). GALIA utilizes cyclic approximate joint diagonalization (AJD) to find a set of linear transformations, one for each domain, jointly aligning the feature vectors of all domains. Group learning achieves a many-to-many transfer learning without compromising the classification performance on non-clinical BCI data. Fast alignment further extends the group learning for any unseen domains, allowing a many-to-one transfer learning with the same properties. The former method creates a single machine learning model using data from previous subjects and/or sessions, whereas the latter exploits the trained model for an unseen domain requiring no further training of the classifier.

Surgical outcomes of intraabdominal versus vaginal approach for uterine manipulation during total laparoscopic hysterectomy.

Uterine manipulation is essential for moving the uterus and proper anatomical dissection without complications during total laparoscopic hysterectomy (TLH). Although many different uterine manipulators (UM) have been designed in the last few decades, there is still no "optimal UM" that is universally safe, efficient, and cost-effective. This study aimed to compare myoma screw (MS) and UM with regard to surgical outcomes and cost-effectiveness in patients who underwent TLH. In the current study, we describe an operation technique that uses a MS instead of a uterine manipulator during TLH and discuss the surgical outcomes of this method. The use of MS resulted in significantly shorter operation time with respect to UM for uterine manipulation during TLH regarding benign indications, with affordable costs. The use of MS is a safe and cost-effective alternative to the use of UM during TLH.

Safety, tolerability, and clinical activity of selinexor in combination with pembrolizumab in treatment of metastatic non-small cell lung cancer.

BACKGROUND: In lung cancer, overexpression of nuclear export proteins can result in inactivation of critical tumor suppressor proteins and cell-cycle regulators. Selective suppression of nuclear export proteins has immunomodulatory activities. Here, clinical safety and early efficacy data are presented on the combination of pembrolizumab and an oral selective nuclear export inhibitor, selinexor, for the treatment of metastatic non-small cell lung cancer (mNSCLC). METHODS: The primary objective of this prospective investigator-initiated study was to determine the safety and tolerability of selinexor in combination with pembrolizumab in patients with mNSCLC. Secondary objectives included determination of objective tumor response rate, disease control rate, and progression-free survival duration. RESULTS: A total of 17 patients were included in the final analysis. Fifteen (88%) received more than two lines of prior systemic therapy and 10 (59%) had prior exposure to anti-PD-1/programmed death-ligand 1 (PD-L1) therapy. The median age was 67.5 years. Ten patients had grade ≥3 adverse events related to selinexor treatment. Responses to treatment occurred in patients who did and did not undergo previous anti-PD-1/PD-L1 therapy and in patients with activating driver mutations. The median overall survival and progression-free survival were 11.4 months (95% CI, 3.4-19.8 months) and 3.0 months (95% CI, 1.7-5.7 months), respectively. The overall response rate was 18% and the 6-month disease control rate was 24%. CONCLUSIONS: Selinexor in combination with pembrolizumab demonstrated promising antitumor activity in patients with mNSCLC, including those who had previously received anti-PD-1/PD-L1 therapy. The therapy-related toxic effects were consistent with the prior safety data for both drugs, and no overlapping toxic effects were observed. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02419495. PLAIN LANGUAGE SUMMARY: New strategies to prevent or reverse resistance to immune checkpoint inhibitors are under investigation. Selective inhibitors of nuclear export proteins, such as selinexor, can induce restoration of tumor-suppressing pathways and induce potent immunomodulatory activities. This article contains the clinical safety and early efficacy data on the combination of pembrolizumab and selinexor in treatment of metastatic non-small cell lung cancer.

Phase 1b study of combined selinexor and eribulin for the treatment of advanced solid tumors and triple-negative breast cancer.

BACKGROUND: Selinexor (KPT-330) is a potent inhibitor of exportin 1 (XPO1), in turn inhibiting tumor growth. Selinexor enhances the antitumor efficacy of eribulin in triple-negative breast cancer (TNBC) in vitro and in vivo. Given the unmet medical need in TNBC and sarcoma, the authors explored the safety and efficacy of this combination. METHODS: The authors conducted a phase 1b trial of combined selinexor and eribulin using a 3 + 3 dose-escalation design in patients who had advanced solid tumors and in those who had TNBC in a dose-expansion cohort. RESULTS: Patients with TNBC (N = 19), sarcoma (N = 9), and other cancers (N = 3) were enrolled in the dose-escalation cohort (N = 10) and in the dose-expansion cohort (N = 21). The median number lines of prior therapy received was four (range, from one to seven prior lines). The most common treatment-related adverse events for selinexor were nausea (77%), leukopenia (77%), anemia (68%), neutropenia (68%), and fatigue (48%). One dose-limiting toxicity occurred at the first dose level with prolonged grade 3 neutropenia. The recommended phase 2 dose was 80 mg of selinexor orally once per week and 1 mg/m2 eribulin on days 1 and 8 intravenously every 3 weeks. The objective response rate (ORR) was 10% in three patients. In the dose-escalation cohort, the ORR was 10%, whereas six patients with had stable disease. In the TNBC dose-expansion cohort (n = 18), ORR was 11%, and there were two confirmed partial responses with durations of 10.8 and 19.1 months (ongoing). CONCLUSIONS: Selinexor and eribulin had an acceptable toxicity profile and modest overall efficacy with durable responses in select patients. PLAIN LANGUAGE SUMMARY: Effective therapies for advanced, triple-negative breast cancer and sarcoma represent an unmet need. Exportin 1 is associated with the transport of cancer-related proteins. Preclinical studies have demonstrated tumor growth inhibition and enhanced tumor sensitivity in patients who receive selinexor combined with eribulin. In this phase 1b study, the authors evaluated the safety profile and clinical activity of the combination of selinexor, a potent oral inhibitor of exportin 1, and eribulin in patients with advanced cancers enriched for triple-negative breast cancer or sarcoma. The combination was well tolerated; most adverse events were mild or moderate, reversible, and managed with dose modifications or growth factor support. The combination of selinexor and eribulin produced an antitumor response, particularly in some patients with triple-negative breast cancer. This work lays the foundation for prospective investigations of the role of selinexor and eribulin in the treatment of triple-negative breast cancer.

Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization.

BACKGROUND AND OBJECTIVE: Early detection of colon adenomatous polyps is critically important because correct detection of it significantly reduces the potential of developing colon cancers in the future. The key challenge in the detection of adenomatous polyps is differentiating it from its visually similar counterpart, non-adenomatous tissues. Currently, it solely depends on the experience of the pathologist. To assist the pathologists, the objective of this work is to provide a novel non-knowledge-based Clinical Decision Support System (CDSS) for improved detection of adenomatous polyps on colon histopathology images. METHODS: The domain shift problem arises when the train and test data are coming from different distributions of diverse settings and unequal color levels. This problem, which can be tackled by stain normalization techniques, restricts the machine learning models to attain higher classification accuracies. In this work, the proposed method integrates stain normalization techniques with ensemble of competitively accurate, scalable and robust variants of CNNs, ConvNexts. The improvement is empirically analyzed for five widely employed stain normalization techniques. The classification performance of the proposed method is evaluated on three datasets comprising more than 10k colon histopathology images. RESULTS: The comprehensive experiments demonstrate that the proposed method outperforms the state-of-the-art deep convolutional neural network based models by attaining 95% classification accuracy on the curated dataset, and 91.1% and 90% on EBHI and UniToPatho public datasets, respectively. CONCLUSIONS: These results show that the proposed method can accurately classify colon adenomatous polyps on histopathology images. It retains remarkable performance scores even for different datasets coming from different distributions. This indicates that the model has a notable generalization ability.

Safety and Efficacy of Immune Checkpoint Inhibitors in Patients with Cancer and Viral Hepatitis: The MD Anderson Cancer Center Experience.

BACKGROUND: Despite the clinical benefit of immune checkpoint inhibitors (ICIs), patients with a viral hepatitis have been excluded from clinical trials because of safety concerns. The purpose of this study was to determine the incidence rate of adverse events (AEs) in patients with viral hepatitis who received ICIs for cancer treatment. MATERIALS AND METHODS: We conducted a retrospective study in patients with cancer and concurrent hepatitis B or C, who had undergone treatment with ICI at MD Anderson Cancer Center from January 1, 2010 to December 31, 2019. RESULTS: Of the 1076 patients screened, we identified 33 with concurrent hepatitis. All 10 patients with HBV underwent concomitant antiviral therapy during ICI treatment. Sixteen of the 23 patients with HCV received it before the initiation of ICI. The median follow-up time was 33 months (95% CI, 23-45) and the median duration of ICI therapy was 3 months (IQR, 1.9-6.6). Of the 33 patients, 12 (39%) experienced irAEs (immune-related adverse events) of any grade, with 2 (6%) having grade 3 or higher. None of the patients developed hepatitis toxicities. CONCLUSION: ICIs may be a therapeutic option with an acceptable safety profile in patients with cancer and advanced liver disease.

Selinexor in combination with weekly paclitaxel in patients with metastatic solid tumors: Results of an open label, single-center, multi-arm phase 1b study with expansion phase in ovarian cancer.

OBJECTIVE: Selinexor is a first-in-class, oral selective inhibitor of nuclear export (SINE) compound which blocks Exportin-1 (XPO1). Our objective was to determine maximum tolerated dose (MTD) and recommended phase II dose (RP2D) of selinexor and weekly paclitaxel. METHODS: This was an open label, single-center, multi-arm phase 1b study utilizing a "3 + 3" design and a "basket-type" expansion in recurrent solid tumors. Selinexor (60 mg or 80 mg twice weekly orally) and weekly paclitaxel (80 mg IV 2 week on, 1 week off) were one of 13 parallel arms. Efficacy was evaluated using RECIST version 1.1. RESULTS: All 35 patients treated were evaluable for toxicity and 31 (88%) were evaluable for response. Patient diagnoses included platinum-resistant/refractory ovarian (n = 28), breast (n = 4), prostate (n = 2), and cervical (n = 1) cancer. Patients had a median of four prior therapies (range 1-10), and 47% had a prior taxane in the recurrent setting. There were no DLTs and 60 mg was chosen as the RP2D due to long-term tolerability. Ninety-seven percent of patients had at least one treatment-emergent adverse event (TEAE), and the most common grade ≥ 3 TEAE were neutropenia (46%), anemia (31%), and nausea (21%). Among 24 evaluable patients with ovarian cancer, response rate was 17%, CBR was 58%, and median PFS was 6.8 months (95% CI 3.7, not reached (NR)). CONCLUSIONS: Oral selinexor in combination with weekly paclitaxel demonstrated promising clinical activity with manageable toxicity. This combination should be considered for further exploration in a randomized study, especially in ovarian malignancies.

Histopathology image classification: highlighting the gap between manual analysis and AI automation.

The field of histopathological image analysis has evolved significantly with the advent of digital pathology, leading to the development of automated models capable of classifying tissues and structures within diverse pathological images. Artificial intelligence algorithms, such as convolutional neural networks, have shown remarkable capabilities in pathology image analysis tasks, including tumor identification, metastasis detection, and patient prognosis assessment. However, traditional manual analysis methods have generally shown low accuracy in diagnosing colorectal cancer using histopathological images. This study investigates the use of AI in image classification and image analytics using histopathological images using the histogram of oriented gradients method. The study develops an AI-based architecture for image classification using histopathological images, aiming to achieve high performance with less complexity through specific parameters and layers. In this study, we investigate the complicated state of histopathological image classification, explicitly focusing on categorizing nine distinct tissue types. Our research used open-source multi-centered image datasets that included records of 100.000 non-overlapping images from 86 patients for training and 7180 non-overlapping images from 50 patients for testing. The study compares two distinct approaches, training artificial intelligence-based algorithms and manual machine learning models, to automate tissue classification. This research comprises two primary classification tasks: binary classification, distinguishing between normal and tumor tissues, and multi-classification, encompassing nine tissue types, including adipose, background, debris, stroma, lymphocytes, mucus, smooth muscle, normal colon mucosa, and tumor. Our findings show that artificial intelligence-based systems can achieve 0.91 and 0.97 accuracy in binary and multi-class classifications. In comparison, the histogram of directed gradient features and the Random Forest classifier achieved accuracy rates of 0.75 and 0.44 in binary and multi-class classifications, respectively. Our artificial intelligence-based methods are generalizable, allowing them to be integrated into histopathology diagnostics procedures and improve diagnostic accuracy and efficiency. The CNN model outperforms existing machine learning techniques, demonstrating its potential to improve the precision and effectiveness of histopathology image analysis. This research emphasizes the importance of maintaining data consistency and applying normalization methods during the data preparation stage for analysis. It particularly highlights the potential of artificial intelligence to assess histopathological images.

Role of Abdominal and Pelvic CT Scans in Diagnosis of Patients with Immunotherapy-Induced Colitis.

Introduction: Colitis is one of the most common immune-related adverse events in patients receiving immune checkpoint inhibitors. Although radiographic changes on computed tomography (CT), such as mild diffuse bowel thickening, mesenteric fat stranding, and mucosal enhancement, have been reported, the utility of CT in diagnosis of patients with suspected immune-related colitis is not well documented. The aim of this retrospective study was to determine the value of CT scans in diagnosis of immunotherapy-induced colitis. Methods: CT scans of the abdomen and pelvis of 34 patients receiving immunotherapy who had a clinical diagnosis of immunotherapy-induced colitis and 19 patients receiving immunotherapy without clinical symptoms of colitis (controls) were evaluated. Segments of the colon (rectum, sigmoid, descending, transverse, ascending, and cecum) were assessed independently by two abdominal imaging specialists, blinded to the clinical diagnosis. Each segment was assessed for radiographic signs such as mucosal enhancement, wall thickening, distension, and periserosal fat stranding. The presence of any of the signs was considered radiographic evidence of colitis. Results: CT findings suggestive of colitis was seen in 20 of 34 patients with symptoms of colitis and in 5 of 19 patients without symptoms of colitis. The sensitivity, specificity, positive predictive value, and negative predictive value for colitis on CT were 58.8%, 73.7%, 80%, and 50%, respectively. Conclusions: We found that CT had a low sensitivity, specificity, and negative predictive value for the diagnosis of immunotherapy-induced colitis. We therefore conclude that CT has a limited role in the diagnosis of patients with suspected uncomplicated immune-related colitis.

Detection of Movement Intention in EEG-Based Brain-Computer Interfaces Using Fourier-Based Synchrosqueezing Transform.

Patients with motor impairments need caregivers' help to initiate the operation of brain-computer interfaces (BCI). This study aims to identify and characterize movement intention using multichannel electroencephalography (EEG) signals as a means to initiate BCI systems without extra accessories/methodologies. We propose to discriminate the resting and motor imagery (MI) states with high accuracy using Fourier-based synchrosqueezing transform (FSST) as a feature extractor. FSST has been investigated and compared with other popular approaches in 28 healthy subjects for a total of 6657 trials. The accuracy and f-measure values were obtained as 99.8% and 0.99, respectively, when FSST was used as the feature extractor and singular value decomposition (SVD) as the feature selection method and support vector machines as the classifier. Moreover, this study investigated the use of data that contain certain amount of noise without any preprocessing in addition to the clean counterparts. Furthermore, the statistical analysis of EEG channels with the best discrimination (of resting and MI states) characteristics demonstrated that F4-Fz-C3-Cz-C4-Pz channels and several statistical features had statistical significance levels, [Formula: see text], less than 0.05. This study showed that the preparation of the movement can be detected in real-time employing FSST-SVD combination and several channels with minimal pre-processing effort.

The effects of Coronavirus disease-2019 (COVID-19) pandemic on routine antenatal care visits and complications of pregnancy.

OBJECTIVE: Routine follow-up of pregnancy is a comprehensive care process starting from planning of pregnancy that involves rational and careful use of medical, psychological, and social support. In this study, our objective was to compare the adherence rate to routine antenatal follow-up program during the COVID-19 pandemic with that of previous years among pregnant women, in an effort to shed light on health policies to be developed similar events in the future. METHODS: This retrospective cross-sectional study was carried out between March 11, 2019, when isolation measures were initiated in the context of precautionary steps taken in Turkey against the COVID-19 pandemic, and June 1, 2020, when the "normalization" was initiated. RESULTS: During the study period in 2020, the proportion of cesarean sections were higher, 61.1%, as compared to previous years (p=0.27). The stillbirths were numerically lower (1.2%, p=0.77), but the rate of spontaneous abortions was significantly higher (19.6%, p=0.009). The number of follow-up visits per pregnancy was lower than in previous years (3.8, p=0.02), although the proportion of patients visiting the outpatient units for regular controls to the overall patient group increased as compared to previous years (52.0%). CONCLUSION: During the flare-up of the COVID-19 pandemic (i.e. between March and June 2020), the rate of obstetric/neonatal morbidity and mortality except spontaneous abortion was not significantly higher as compared to the corresponding period in previous years. However, considering the potential increase in the risk of obstetric complications during a pandemic, specialized management programs targeting basic pregnancy follow-up services should be developed.

The level of depression, anxiety, and sleep quality in pregnancy during coronavirus disease 2019 pandemic.

AIM: We aimed to evaluate the mental health and sleep quality of pregnant women in different trimesters during coronavirus disease 2019 (COVID-19) pandemic and investigate the effect of quarantine and new lifestyle changes that come into our lives with pandemic with on this subject. METHODS: It was conducted on pregnant women (n = 149) who attended routine pregnancy prenatal visit during their pregnancy weeks. The data were collected using sociodemographic and clinical data form, Pittsburgh Sleep Quality Index (PSQI) to evaluate sleep quality, Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) to evaluate maternal depression and anxiety. RESULTS: A significant correlation was observed between the week of gestation and depression, anxiety, and defective sleep scores (p < 0.001). A moderate positive correlation was found between the week of gestation and depression (r: 0.628). A high level of positive correlation was found between the week of gestation and defective sleep quality and anxiety scores (r: 0.858, r: 0.754). A statistically significant increase in depression, anxiety, and defective sleep quality was found in the group staying in home quarantine (p = 0.002). CONCLUSION: This study showed that the COVID-19 pandemic can cause depression, anxiety, and serious sleep disorders in pregnant women. The depression and anxiety scores of pregnant women in home quarantine were also found to be higher than the group not in quarantine. As the week of gestation progresses, mental health symptoms worsen and sleep quality deteriorates.

The effects of Coronavirus disease-2019 (COVID-19) pandemic on routine antenatal care visits and complications of pregnancy

SUMMARY OBJECTIVE: Routine follow-up of pregnancy is a comprehensive care process starting from planning of pregnancy that involves rational and careful use of medical, psychological, and social support. In this study, our objective was to compare the adherence rate to routine antenatal follow-up program during the COVID-19 pandemic with that of previous years among pregnant women, in an effort to shed light on health policies to be developed similar events in the future. METHODS: This retrospective cross-sectional study was carried out between March 11, 2019, when isolation measures were initiated in the context of precautionary steps taken in Turkey against the COVID-19 pandemic, and June 1, 2020, when the "normalization" was initiated. RESULTS: During the study period in 2020, the proportion of cesarean sections were higher, 61.1%, as compared to previous years (p=0.27). The stillbirths were numerically lower (1.2%, p=0.77), but the rate of spontaneous abortions was significantly higher (19.6%, p=0.009). The number of follow-up visits per pregnancy was lower than in previous years (3.8, p=0.02), although the proportion of patients visiting the outpatient units for regular controls to the overall patient group increased as compared to previous years (52.0%). CONCLUSION: During the flare-up of the COVID-19 pandemic (i.e. between March and June 2020), the rate of obstetric/neonatal morbidity and mortality except spontaneous abortion was not significantly higher as compared to the corresponding period in previous years. However, considering the potential increase in the risk of obstetric complications during a pandemic, specialized management programs targeting basic pregnancy follow-up services should be developed.

Metformin reduces ovarian ischemia reperfusion injury in rats by improving oxidative/nitrosative stress.

OBJECTIVE: To assess the preventive role of metformin on rat ovarian ischemia reperfusion injury. MATERIALS AND METHODS: Forty rats were divided equally into five groups; Group 1: sham, Group 2: surgical control with 3-hr torsion and detorsion, Group 3: 50 mg/kg p.o. metformin 30 min before 3-hr torsion, Group 4; metformin just after detorsion, Group 5; metformin 30 min before torsion and just after detorsion. Bilateral ovaries and blood sample were obtained seven days after detorsion for biochemical and histopathological evaluation. RESULTS: Ovarian tissue total anti-oxidant status (TAS) levels were significantly increased in group 4 when compared to group 1, 2 and 3 (all p < 0.01). In addition, there was a significant decrease in tissue oxidative stress index (OSI) level in group 4 with respect to group 2 (p < 0.01). Moreover, serum levels of OSI were significantly higher in group 2 with respect to group 1 and 5 (both p < 0.05). Similarly, there was significant increase in serum levels of peroxynitrite in group 2 as compared to serum levels in group 3 and 5 (p < 0.01 and 0.05, respectively). Furthermore, there were significant decrease in histopathological scores metformin and sham groups when compared to rats in the control group (Group 2). CONCLUSION: Metformin reduces ischemia reperfusion injury in rat torsion detorsion model by improving histopathological and biochemical findings including TAS, OSI and peroxynitrite.

Pembrolizumab in Patients with Advanced Metastatic Germ Cell Tumors.

LESSONS LEARNED: Advanced germ cell tumors are aggressive and associated with poor prognosis. Pembrolizumab was overall well tolerated in 12 heavily pretreated patients. Three patients had radiographic stable disease that lasted for 10.9 months, 5.5 months, and 4.5 months, respectively. Published data of immunotherapeutic agents in patients with advanced germ cell tumors are confirmed. The limited antitumor activity of immunotherapy in germ cell tumors is, at least partially, attributed to tumor biology (low tumor mutational burden; low PD-1 expression) and other poor-risk features. Tumor profiling to understand the mechanisms of resistance to pembrolizumab and innovative clinical trials that may include immunotherapy are warranted. BACKGROUND: Advanced germ cell tumors are associated with poor prognosis. We investigated the role of pembrolizumab in patients with advanced germ cell tumors. METHODS: We analyzed a prespecified cohort of an open-label, phase II clinical trial in which patients with advanced germ cell tumors were treated with pembrolizumab (200 mg) intravenously every 21 days. The endpoints of the study were the non-progression rate (NPR) at 27 weeks, safety, and tolerability. An NPR >20% was considered successful and worthy of further pursuit. RESULTS: From August 2016 to February 2018, 12 patients (10 men, 2 women) were treated (median age, 35 years [range, 22-63 years]; median number of prior systemic therapies, 3.5 [range, 2-7]; median number of metastatic sites, 3 [range, 2-8]). Overall, pembrolizumab was well tolerated. One patient experienced both grade 1 immune-related skin rash and grade 3 immune-related pneumonitis. No patient died from toxicity. Three patients had radiographic stable disease that lasted for 10.9 months, 5.5 months, and 4.5 months, respectively. No objective response was noted. The median progression-free survival was 2.4 months (95% confidence interval [CI], 1.5-4.5 months), and the median overall survival was 10.6 months (95% CI, 4.6-27.1 months). The 27-week NPR was 9.0% (95% CI, 0.23-41.2%). CONCLUSION: Overall, pembrolizumab was safe and had limited antitumor activity in these patients. In the advanced, metastatic setting, tumor profiling to understand the mechanisms of resistance to immunotherapy and innovative clinical trials to identify efficacious combination regimens rather than off-label use of pembrolizumab are warranted.

The effect of human papilloma virus vaccination on embryo yield and clinical in vitro fertilisation outcomes: a matched retrospective cohort study.

The effects of HPV vaccination on embryo yield and pregnancy outcomes in IVF cycles with fresh embryo transfer (ET) were investigated. First, embryo yielding rates (EYR) in 2795 cycles with and without HPV vaccination were compared by retrospective cohort study design. EYR of HPV vaccinated and non-vaccinated patients were not significantly different (OR, 1.66; 95% CI, 0.76-3.63). Second, ET outcomes were compared for 155 HPV vaccine + cycles and 465 HPV vaccine - cycles after matching for ages and cycle attempt number. The differences in the number of retrieved oocytes (10.2 ± 6.1, 11.2 ± 6.7; p = .161), mature (MII) oocytes (8.7 ± 5.7, 9.8 ± 6.3; p = .088), two pronuclear zygotes (2PN) (5.4 ± 4.1, 6.1 ± 4.6; p = .110) and fertilisation rates (0.62 ± 0.23, 0.62 ± 0.23; p = .539) were insignificant between the two groups. Moreover, positive (OR, 0.74; 95% CI, 0.47-1.16), clinical (0.60; 0.36-1.01) and the ongoing pregnancy (0.55; 0.30-1.01) rates were lower in the HPV vaccinated group but the difference was not statistically significant.IMPACT STATEMENTWhat is already known on this subject? There are recent case studies that report premature ovarian insufficiency (POI) following a post-vaccination autoimmune response against the HPV vaccine. These studies suggest that the possible trigger for the immune reaction might be the immunogen content of the vaccine. However, the number of clinical studies investigating the effects of the HPV vaccine on reproductive function and in vitro fertilisation outcomes is limited.What do the results of this study add? In contrast to the case reports suggesting impaired reproductive and ovarian functions in HPV vaccinated patients, this study finds that in IVF patients HPV vaccinated and non-vaccinated women have similar EYR, MII, 2PN, oocyte counts, fertilisation rates, positive, clinical and ongoing pregnancy rates.What are the implications of these findings for clinical practice and/or further research? The results suggest the HPV vaccine does not have a negative impact on embryo yielding rates oocyte counts and fertilisation rates, positive, clinical and ongoing pregnancy rates in IVF treatments. Hence, they can be safely used for primary prevention against cervical cancer.

Melatonin attenuates ovarian ischemia reperfusion injury in rats by decreasing oxidative stress index and peroxynitrite

Background/aim: To evaluate the protective effect of melatonin on ovarian ischemia reperfusion injury in a rat model. Materials and methods: Forty-eight rats were separated equally into 6 groups. Group 1: sham; Group 2: surgical control with 3-h bilateral ovarian torsion and detorsion; Group 3: intraperitoneal 5% ethanol (1 mL) just after detorsion (as melatonin was dissolved in ethanol); Group 4: 10 mg/kg intraperitoneal melatonin 30 min before 3-h torsion; Group 5:10 mg/kg intraperitoneal melatonin just after detorsion; Group 6:10 mg/kg intraperitoneal melatonin 30 min before torsion and just after detorsion. Both ovaries and blood samples were obtained 7 days after detorsion for histopathological and biochemical analysis. Results: In Group 1, serum levels of total oxidant status (TOS) (µmol H2O2 equivalent/g wet tissue)were significantly lower than in Group2 (P = 0.0023), while tissue TOS levels were lower than in Group 3 (P = 0.0030). Similarly, serum and tissue levels of peroxynitrite in Group 6were significantly lower than those ofGroup 2 (P = 0.0023 and P = 0.040, respectively). Moreover, serum oxidative stress index (OSI) (arbitrary unit) levels were significantly increased in Group 2 when compared to groups 1 and 6 (P = 0.0023 and P= 0.0016, respectively) and in Group 3 with respect to groups 1, 4, 5, and 6 (P = 0.0023, P = 0.0026, P = 0.0008, and P = 0.0011, respectively). Furthermore, there was a significant decrease in histopathological scores including follicular degeneration, vascular congestion, hemorrhage, and inflammation in the melatonin and sham groups in comparison with control groups. Additionally, primordial follicle count was significantly higher in Group 6 than in Group 2 (P = 0.0002). Conclusion: Melatonin attenuates ischemia reperfusion damage in a rat torsion/detorsion model by improving histopathological and biochemical findings including OSI and peroxynitrite.