{ "cells": [ { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "from core.s3_utils import S3Handler" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": [ "s3_handler = S3Handler()\n", "from config import get_settings\n", "settings = get_settings()" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Files in bucket 'sehas3.bucket1' with prefix '':\n", "No files found\n" ] }, { "data": { "text/plain": [ "[]" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s3_handler.list_files(settings.AWS_BUCKET_NAME)" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Failed to download string data: An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist.\n" ] }, { "ename": "NoSuchKey", "evalue": "An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist.", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNoSuchKey\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[63], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mjson\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m metadata_content \u001b[38;5;241m=\u001b[39m \u001b[43ms3_handler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_string_from_s3\u001b[49m\u001b[43m(\u001b[49m\u001b[43msettings\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mAWS_BUCKET_NAME\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpubmed_metadata/metadata.json\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m metadata_content \u001b[38;5;241m=\u001b[39m json\u001b[38;5;241m.\u001b[39mloads(metadata_content)\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mlen\u001b[39m(metadata_content)\n", "File \u001b[0;32m~/Documents/fakkerai/sehatech/core/s3_utils.py:192\u001b[0m, in \u001b[0;36mS3Handler.download_string_from_s3\u001b[0;34m(self, bucket_name, s3_key)\u001b[0m\n\u001b[1;32m 181\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 182\u001b[0m \u001b[38;5;124;03mDownload a string object from S3 and return it.\u001b[39;00m\n\u001b[1;32m 183\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[38;5;124;03m str: The content of the object as a string.\u001b[39;00m\n\u001b[1;32m 190\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 191\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 192\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43ms3_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_object\u001b[49m\u001b[43m(\u001b[49m\u001b[43mBucket\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbucket_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mKey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43ms3_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 193\u001b[0m content \u001b[38;5;241m=\u001b[39m response[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBody\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mread()\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 194\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDownloaded content from s3://\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mbucket_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00ms3_key\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n", "File \u001b[0;32m~/Documents/fakkerai/sehatech/pinecone-env/lib/python3.11/site-packages/botocore/client.py:569\u001b[0m, in \u001b[0;36mClientCreator._create_api_method.._api_call\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 565\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 566\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpy_operation_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m() only accepts keyword arguments.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 567\u001b[0m )\n\u001b[1;32m 568\u001b[0m \u001b[38;5;66;03m# The \"self\" in this scope is referring to the BaseClient.\u001b[39;00m\n\u001b[0;32m--> 569\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_api_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/Documents/fakkerai/sehatech/pinecone-env/lib/python3.11/site-packages/botocore/client.py:1023\u001b[0m, in \u001b[0;36mBaseClient._make_api_call\u001b[0;34m(self, operation_name, api_params)\u001b[0m\n\u001b[1;32m 1019\u001b[0m error_code \u001b[38;5;241m=\u001b[39m error_info\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mQueryErrorCode\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m error_info\u001b[38;5;241m.\u001b[39mget(\n\u001b[1;32m 1020\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCode\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1021\u001b[0m )\n\u001b[1;32m 1022\u001b[0m error_class \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexceptions\u001b[38;5;241m.\u001b[39mfrom_code(error_code)\n\u001b[0;32m-> 1023\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m error_class(parsed_response, operation_name)\n\u001b[1;32m 1024\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1025\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m parsed_response\n", "\u001b[0;31mNoSuchKey\u001b[0m: An error occurred (NoSuchKey) when calling the GetObject operation: The specified key does not exist." ] } ], "source": [ "import json\n", "metadata_content = s3_handler.download_string_from_s3(settings.AWS_BUCKET_NAME, \"pubmed_metadata/metadata.json\")\n", "metadata_content = json.loads(metadata_content)\n", "\n", "len(metadata_content)\n" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'pmc_id': 'PMC8419487',\n", " 'title': 'No Title Available',\n", " 'abstract': 'ZnS materials have been widely used in fluorescence biosensors to characterize different types of stem cells due to their excellent fluorescence effect. In this study, ZnS was prepared by vulcanizing nano-Zn particles synthesized using a DC arc plasma. The composition and structure of the ZnS materials were studied by X-ray diffraction (XRD), and their functional group information and optical properties were investigated by using IR spectrophotometry and UV-vis spectrophotometry. It has been found that the synthesized materials consist of Zn, cubic ZnS, and hexagonal ZnS according to the vulcanization parameters. Crystalline ZnS was gradually transformed from a cubic to a hexagonal structure, and the cycling properties first increase, then decrease with increasing sulfurization temperature. There is an optimal curing temperature giving the best cycling performance and specific capacity: the material sulfurized thereat mainly consists of cubic ',\n", " 'authors': ['Ren, Y.',\n", " 'Zhou, H.',\n", " 'Wang, X.',\n", " 'Liu, Q. W.',\n", " 'Hou, X. D.',\n", " 'Zhang, G. F.'],\n", " 'keywords': [],\n", " 'doi': 'N/A',\n", " 'source': 'downloaded_pdfs/PMC8419487/PMC8419487/SCI2021-7067146.nxml',\n", " 'publication_date': '2021'}]" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metadata_content" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "No files found in bucket 'sehas3.bucket1' with prefix ''\n", "\n", "Successfully deleted 0 files\n" ] }, { "data": { "text/plain": [ "(0, [])" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "s3_handler.delete_all_files(settings.AWS_BUCKET_NAME)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/larawehbe/Documents/fakkerai/sehatech/venv/lib/python3.13/site-packages/pinecone/data/index.py:1: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from tqdm.autonotebook import tqdm\n" ] } ], "source": [ "import pinecone\n", "pc = pinecone.Pinecone(settings.PINECONE_API_KEY)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "index = pc.Index(settings.INDEX_NAME)\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'matches': [], 'namespace': 'default', 'usage': {'read_units': 1}}" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "index.query(namespace=\"default\", top_k=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### temp : remove when tested" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import PyPDF2" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from PyPDF2 import PdfReader" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "pdf = PdfReader(\"WJR-9-27.pdf\")\n", "info = pdf.metadata\n", "\n" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "text = \"\".join(page.extract_text() for page in pdf.pages)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Matteo Bauckneht, Roberta Piva, Gianmario Sambuceti, Francesco Grossi, Silvia Morbelli EDITORIAL\n", "27 February 28, 2017 |Volume 9 |Issue 2| WJR|www.wjgnet.comEvaluation of response to immune checkpoint inhibitors: Is \n", "there a role for positron emission tomography?\n", "Matteo Bauckneht, Roberta Piva, Gianmario Sambuceti, \n", "Silvia Morbelli, Nuclear Medicine Unit, IRCCS San Martino-\n", "IST, University of Genoa, 16132 Genoa, Italy\n", "Francesco Grossi, Lung Cancer Unit, IRCCS San Martino-IST, \n", "University of Genoa, 16132 Genoa, Italy\n", "Author contributions: Morbelli S conceived and designed \n", "the study; Bauckneht M and Morbelli S drafted the manuscript; \n", "Bauckneht M and Piva R prepared the tables and figures; \n", "Sambuceti G and Grossi F critically revised the manuscript; all \n", "the authors approved the final version of the paper.\n", "Conflict-of-interest statement: The authors have no conflicts of \n", "interest related to this publication to disclose.\n", "Open-Access: This article is an open-access article which was \n", "selected by an in-house editor and fully peer-reviewed by external \n", "reviewers. It is distributed in accordance with the Creative Commons \n", "Attribution Non Commercial (CC BY-NC 4.0) license, which \n", "permits others to distribute, remix, adapt, build upon this work non-\n", "commercially, and license their derivative works on different terms, \n", "provided the original work is properly cited and the use is non-\n", "commercial. See: http://creativecommons.org/licenses/by-nc/4.0/\n", "Manuscript source: Invited manuscript\n", "Correspondence to: Silvia Morbelli, MD, PhD, Nuclear \n", "Medicine Unit, IRCCS San Martino-IST, University of Genoa, \n", "Largo R. Benzi 10, 16132 Genova, \n", "Italy. silviadaniela.morbelli@hsanmartino.i t \n", "Telephone: +39-010-5552026\n", "Fax: +39-010-5556911\n", "Received: August 20, 2016 \n", "Peer-review started: August 23, 2016 \n", "First decision: October 21, 2016\n", "Revised: November 2, 2016 \n", "Accepted: November 27, 2016\n", "Article in press: November 29, 2016\n", "Published online: February 28, 2017\n", "Abstract\n", "Strategies targeting intracellular negative regulators such as immune checkpoint inhibitors (ICPIs) have \n", "demonstrated significant antitumor activity across a \n", "wide range of solid tumors. In the clinical practice, the \n", "radiological effect of immunotherapeutic agents has \n", "raised several more relevant and complex challenges for \n", "the determination of their imaging-based response at \n", "single patient level. Accordingly, it has been suggested \n", "that the conventional Response Evaluation Criteria in \n", "Solid Tumors assessment alone, based on dimensional \n", "evaluation provided by computed tomography (CT), \n", "tends to underestimate the benefit of ICPIs at least in \n", "a subset of patients, supporting the need of immune-\n", "related response criteria. Different from CT, very few \n", "data are available for the evaluation of immunotherapy \n", "by means of 18F-fluoro-2-deoxy-D-glucose positron \n", "emission tomography (FDG-PET). Moreover, since \n", "the antineoplastic activity of ICPIs is highly related \n", "to the activation of T cells against cancer cells, FDG \n", "accumulation might cause false-positive findings. Yet, \n", "discrimination between benign and malignant processes \n", "represents a huge challenge for FDG-PET in this clinical \n", "setting. Consequently, it might be of high interest to test \n", "the complex and variegated response to ICPIs by means \n", "of PET and thus it is worthwhile to ask if a similar \n", "introduction of immune-related PET-based criteria could \n", "be proposed in the future. Finally, PET might offer a new \n", "insight into the biology and pathophysiology of ICPIs \n", "thanks to a growing number of non-invasive immune-\n", "diagnostic approaches based on non-FDG tracers.\n", "Key words: Immune checkpoint inhibitors; Positron \n", "emission tomography; Computed tomography; 18F-fluoro-\n", "2-deoxy-D-glucose; Non-18F-fluoro-2-deoxy-D-glucose \n", "tracers\n", "© The Author(s) 2017. Published by Baishideng Publishing \n", "Group Inc. All rights reserved.\n", "Core tip: In the clinical practice, the radiological \n", "interpretation of immunotherapy effects represents \n", "a huge challenge at single patient level. However, \n", "although the computed tomography-based response World Journal of \n", "Radiology WJR\n", "Submit a Manuscript: http://www.wjgnet.com/esps/\n", "DOI: 10.4329/wjr.v9.i2.27World J Radiol 2017 February 28; 9(2): 27-33\n", "ISSN 1949-8470 (online)28 February 28, 2017 |Volume 9 |Issue 2| WJR|www.wjgnet.comBauckneht M et al. Immune checkpoint inhibitors and PET\n", "evaluation for immune checkpoint inhibitors (ICPIs) is \n", "feasible thanks to the introduction of immune-related \n", "response criteria, very few data are available for the \n", "potential role of 18F-fluoro-2-deoxy-D-glucose positron \n", "emission tomography (FDG-PET). Due to the intrinsic \n", "nature of FDG accumulation pathophysiology, it might \n", "be central to test the complex and variegated response \n", "to ICPIs by means of PET. Finally, PET might offer a new \n", "insight into the biology of ICPIs thanks to a growing \n", "number of non-invasive immune-diagnostic approaches \n", "based on non-FDG tracers.\n", "Bauckneht M, Piva R, Sambuceti G, Grossi F, Morbelli S. \n", "Evaluation of response to immune checkpoint inhibitors: Is \n", "there a role for positron emission tomography? World J Radiol \n", "2017; 9(2): 27-33 Available from: URL: http://www.wjgnet.\n", "com/ 1949-8470 /full/v9/i2/27.htm DOI: http://dx.doi.org/10.4329/\n", "wjr.v9.i2.27\n", "TEXT\n", "The function of the immune system is characterized by \n", "multiple checkpoints aiming to avoid its over-activation \n", "against healthy cells (self-tolerance)[1]. Cancer cells may \n", "take advantage of these checkpoints to escape detection \n", "by the immune system. Some of these checkpoints such \n", "as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) \n", "and programmed cell death protein 1 (PD-1) have been \n", "extensively studied as t argets in the frame of the so-\n", "called cancer immunotherapy[1]. CTLA-4 counteracts \n", "the activity of the T cell co-stimulatory receptor CD28 \n", "and actively delivers inhibitory signals to the T cell[2]. \n", "PD-1 has two ligands, PD1 ligand 1 (PDL1) and PDL2, \n", "and its inhibitory effect is accomplished through a dual \n", "mechanism of promoting apoptosis in antigen specific \n", "T-cells in lymph nodes while simultaneously reducing \n", "apoptosis in regulatory T cells (suppressor T cells)[3]. In \n", "the last few years, the blockade of immune checkpoints \n", "has disclosed the potential of the antitumor immune \n", "response in a fashion that is transforming human cancer \n", "therapeutics. CTLA4 antibodies such as ipilimumab \n", "and tremelimumab have been tested in the last ten \n", "years in different types of cancer , starting with patients \n", "with advanced melanoma[4]. Ipilimumab was the first \n", "therapy to demonstrate a survival benefit for patients \n", "with metastatic melanoma. In a study by Hodi et al[5], \n", "ipilimumab significantly improved overall survival in \n", "patients with previously treated metastatic melanoma \n", "and the drug was approved by the United States Food \n", "and Drug Administration (FDA) for the treatment of \n", "advanced melanoma in 2011[5]. Similarly, nivolumab, \n", "a humanized anti-PD-1 monoclonal antibody, has \n", "demonstrated durable responses in several phase III \n", "trials and has received FDA approval in specific clinical \n", "settings in patients with melanoma, renal cell cancer , \n", "Hodgkin’s lymphoma, bladder cancer, and non-small \n", "cell lung cancer (NSCLC)[6-9]. Figure 1 summarizes the mechanisms of action of the two FDA approved immune \n", "checkpoint inhibitors (ICPIs) .\n", "Evaluation of response to ICPIs \n", "Historically, the Response Evaluation Criteria in Solid \n", "Tumors (RECIST) has been validated and used to eva -\n", "luate antitumor responses to chemotherapeutic agents[10] \n", "(Table 1 for a more detailed description). These criteria \n", "are based on dimensional evaluation and rely on the \n", "fact that the cytotoxic effect of chemotherapeutic agents \n", "tends to translate into measurable effects in terms of \n", "tumor shrinkage from baseline. Furthermore, published \n", "studies indicated that achieving a response according to \n", "RECIST criteria is predictive of remission and improved \n", "survival in specific settings[11]. Conversely, both RECIST \n", "and their revised 1.1 version assumed that an early \n", "increase in tumor growth and/or the appearance of \n", "new lesions correspond to progressive disease (PD), \n", "testifying drug failure and indicating the need of ongoing \n", "treatment cessation[10].\n", "Some exceptions for the use of these criteria have \n", "been already suggested in patients treated with target \n", "therapies such as tyrosine kinase inhibitors as in this \n", "group of patients the lack of tumor shrinkage in the \n", "presence of a stable disease has been identified as a \n", "potential surrogate end point for improved clinical out -\n", "come[12]. However , in the clinical practice, the radiolo -\n", "gical effect of immunotherapeutic agents has raised \n", "several more relevant and complex challenges for \n", "the determination of their imaging-based response at \n", "single patient level[13]. In published studies, while some \n", "patients have responded to ICPIs with the expected \n", "tumor shrinkage (chemo-like response) or with a \n", "stable disease (target therapy-like response), other \n", "distinct immune-related patterns of response have been \n", "identified. In particular , an initial increase in tumor size, \n", "development of new lesions and then a delayed objective \n", "response were also observed in patients treated with \n", "immunotherapeutic agents[13]. Specifically, in some \n", "patients, the initial increase in total tumor burden was \n", "proven to be due to inflammatory cell infiltrates by \n", "means of biopsy. In these patients the initial pseudo-\n", "progression was followed by a decrease in tumor burden \n", "or even disease regression. \n", "As RECIST criteria were not suitable to catch \n", "these atypical responses, the so-called immune-\n", "related response criteria (irRC) have been proposed to \n", "provide more rigorous characterization of all patterns \n", "of response observed in the phase II development \n", "program for ipilimumab in melanoma[13-15] (Table 1). \n", "The main differences between RECIST 1.1 and irRC \n", "rely on the fact that, according to irRC, appearance of \n", "new lesions (PD according to the RECIST criteria) will \n", "only result in progressive disease in case of a significant \n", "(≥ 25%) increase in total tumor burden with respect \n", "to baseline. Moreover, different from conventional \n", "criteria, if irRC-based PD is evident, it requires further \n", "confirmation after one month with the aim of capturing 29 February 28, 2017 |Volume 9 |Issue 2| WJR|www.wjgnet.comdelayed response.\n", "Recent ly, Hodi et al[16] evaluated atypical response \n", "patterns and reported the overall survival data in \n", "correlation with irRC and RECIST criteria in the context \n", "of a retrospective analysis of 327 melanoma patients \n", "treated wit h the PD-1 inhibitor pembrolizumab. This \n", "study indicated that the conventional RECIST asses sment \n", "alone tends to underestimate the benefit of PD-1 inhibi -\n", "tor therapy in a subset of patients, supporting a need of \n", "immune-related response evaluation[16]. IrRC are thus \n", "increasingly proposed, but they have not been validated \n", "yet in the context of clinical trials and most trials \n", "involving ICPIs continue to use RECIST 1.1 to obtain \n", "standardized endpoints for regulatory approvals[15]. \n", "However, although the irRC seem better than \n", "RECIST , the former has some limitations. The irRC use \n", "the bidimensional measurements in line with WHO \n", "criteria that are now rarely used in clinical trials and \n", "replaced by the unidimensional measurement of the larger axis of target lesions (RECIST 1.0 and 1.1). The \n", "bidimensional measurements introduce a greater vari -\n", "ability than unidimensional measurements and make it \n", "difficult to compare the responses with studies using the \n", "RECIST criteria.\n", "Is there a role for 18F-fluoro-2-deoxy-D-glucose positron \n", "emission tomography in the evaluation of ICPIs?\n", "While optimal CT-based response criteria for ICPIs \n", "are in the path of their identification, very few data \n", "are available for the evaluation of immunotherapy by \n", "means of 18F-fluoro-2-deoxy-D-glucose positron emi s-\n", "sion tomography (18F-FDG-PET), one of the most used \n", "imaging techniques in oncology. 18F-FDG-PET is currently \n", "the most widely used molecular imaging mod ality in \n", "the clinical practice for staging and restaging of several \n", "cancers. 18F-FDG-PET is clinically indicated before and \n", "after treatment in patients with Hod gkin’s lymphoma \n", "and NSCLC and it is used in patients with melanoma for \n", "Figure 1 Schematic representation of mechanism of action of nivolumab and ipilimumab, two Food and Drug Administration approved immune \n", "checkpoint inhibitors. To prevent autoimmunity, numerous checkpoint pathways regulate the activation of T cells at multiple steps (process known as peripheral \n", "tolerance). Central in this process are the cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed death 1 (PD-1) immune checkpoints pathways. \n", "CTLA-4 is potentially able to stop autoreactive T cells at the initial stage of naive T-cell activation, typically in lymph nodes, while PD-1 regulates previously activated \n", "T cells at the later stages of an immune response in peripheral tissues. The binding between T-cell receptor (TCR), which is expressed on T cell surface, with major \n", "histocompatibility complex (MHC) expressed on antigen presenting cells (APCs) provides specificity to T-cell activation. However, T cell activation requires more than \n", "one stimulatory signal. Among them a central role is played by the binding between B7 molecules (APC) with CD28 (T-Cell). CTLA-4 is a CD28 homolog which does \n", "not produce a stimulatory signal but inhibits TCR-MHC binding and thus the T-Cell activation. Different from T-cells in which the amount of CTLA-4 is low, T-Regs \n", "highly express CTLA-4. In these cells CTLA-4 might play a role in their suppressive functions. PD-1 is a member of the B7/CD38 family of protein, which is able to \n", "bind with two different ligands: Programmed death ligand 1 (PD-L1) and programmed death ligand 2 (PD-L2). PD-1 activation in a T-cell prevents the phosphorylation \n", "of key TCR signaling intermediates and thus T-cell activation, resulting in suboptimal control of infections and cancers. Therefore, even though they act at different \n", "phases of T-cell activation, the negative effect of PD-1 and CTLA-4 on T-cell activity is similar. Moreover, different from CTLA-4, PD-1 expression is not specific in \n", "T-cells, but can be observed also in B-cells and myeloid cells. The rationale for immune checkpoint inhibition (represented in red) for cancer treatment is that CTLA-4 \n", "and PD1 pathways are strictly related to cancer survival and thus targeting these molecules or their ligands with monoclonal antibodies permits to impact on cancer \n", "growth. Therefore, even if the exact mechanism of action of these monoclonal antibodies in the antitumor response remains unclear, research data suggest that it is at \n", "least partially related to an activation and proliferation of T-cells regardless of TCR specificity (due to the inhibition of the inhibitory activity of these checkpoints), which \n", "enhances the anti-cancer immune reaction. T Reg\n", "Antigen\n", "presenting cellCancer cell\n", "T cellB7\n", "B7\n", "B7\n", "B7\n", "B7\n", "B7\n", "B7\n", "B7MHCCTLA-4\n", "TCR\n", "IPILMUMABNIVOLUMAB\n", "CD28\n", "CD28\n", "CD28\n", "CTLA-4 CTLA-4PD-1\n", "PD-1\n", "PD-1PD-L1\n", "PD-L1\n", "PD-L1MHCMHCBauckneht M et al. Immune checkpoint inhibitors and PET30 February 28, 2017 |Volume 9 |Issue 2| WJR|www.wjgnet.comspecific clinical indications[17-19]. The use of 18F-FDG-PET \n", "in post-treatment settings is based on the assumption \n", "that tumor size changes are only the final step in a \n", "sequence of complex metabolic and functional processes \n", "during and after treatment[20]. Two different types \n", "of criteria have been proposed for the identification \n", "of 18F-FDG-PET-based response in solid tumors: The \n", "European Organization for Research and Treatment of \n", "Cancer (EORTC) and the PET Response Criteria in Solid \n", "Tumors (PERCIST) criteria[21,22] (Table 1). Both criteria \n", "target the most metabolically active part of patient’s \n", "tumor burden, which is regarded as the most viable and \n", "aggressive disease site. In both cases, the so-called \n", "standardized uptake value (SUV) is measured at baseline \n", "and after treatment. However , they differ for some rele -\n", "vant aspects. The EORTC criteria were published in 1999 \n", "and are based on the evaluation of a lesion-specific \n", "region of interest (ROI) chosen as the most 18F-FDG-avid \n", "at baseline and followed in the after-treatment scans[22]. \n", "The PERCIST criteria were proposed in 2009 by Wahl \n", "et al[21] and rely on the use of a 1 cm3 ROI on the most \n", "18F-FDG-avid part of the single most metabolically active \n", "lesion at each PET/CT scan (which is not necessarily \n", "located in the same lesion in all scans). \n", "Relatively few papers have compared the two methods in solid tumors and good agreement, similar \n", "responses and survival outcomes have been highlighted \n", "in the available studies[23]. However, for the EORTC \n", "criteria, no recommendations on the number of target \n", "lesions or on whether computing SUV max or average \n", "SUV for response calculation are given while the \n", "PERCIST criteria recommend the use of lean body mass \n", "for SUV normalization (SUL). In this framework, some \n", "studies have demonstrated a higher accuracy with \n", "respect to RECIST for both metabolic response based \n", "criteria in patients treated with target therapies such as \n", "erlotinib. This finding is due to the relative lower tumor \n", "shrinkage characterizing this type of treatment[24]. \n", "Similarly, an 18F-FDG-PET-based five-point scale (5-PS), \n", "the so-called Deauville criteria, has been demonstrated \n", "to be superior to CT-based response by scoring images \n", "in the assessment of response at the middle and end of \n", "treatment in HD patients[18]. Again these findings testify \n", "that functional changes always precede morphological \n", "changes in the course of pathological processes. In \n", "this regard it might be of interest to test the complex \n", "and variegated response to ICPIs by means of PET-\n", "based criteria. In fact, on one hand, functional imaging \n", "may capture different features of treatment with ICPIs \n", "in terms of entity and time course of response. On Category PERCIST EORTC 1999 RECIST 1.1 irRC\n", " Target lesions The hottest single tumor lesion (SUL \n", "peak) at baseline\n", "18F-FDG PET The most 18F-FDG-avid \n", "lesions (SUV BSA). Number \n", "of lesions not specifiedMaximum, 5 Maximum, 15 lesions\n", " New lesion Results in progressive disease at first \n", "appearanceResults in progressive disease \n", "at first appearanceResults in progressive \n", "disease at first \n", "appearanceUp to 10 new visceral and 5 cutaneous \n", "lesions may be added to the sum of \n", "the products of the two largest \n", "perpendicular diameters of \n", "all index lesions at \n", "any time point\n", " Complete \n", " responseCMR: Complete resolution of 18F-FDG \n", "uptake within the \n", "target lesion (< mean liver activity and \n", "indistinguishable from \n", "background/blood pool and no new \n", "18F-FDG-avid lesions)CMR: Complete absence of \n", "18F-FDG uptake Disappearance of all target and nontarget lesions\n", " Nodes must regress to < 10 mm short axis \n", " No new lesions\n", " Confirmation required\n", " Partial response PMR: A reduction of a minimum of \n", "30% in the target tumor 18F-\n", "FDG SUL peakPMR: A decrease in SUV > \n", "25%≥ 30% decrease in \n", "tumor burden compared \n", "to baseline \n", "Confirmation required≥ 50% decrease in tumor burden \n", "compared with baseline1\n", "Confirmation required\n", " Progressive \n", " diseasePMD: A 30% increase in 18F-FDG SUL \n", "peak or advent of new 18F-FDG-avid \n", "lesionsPMD: An increase in SUV > \n", "25% or appearance of new \n", "lesions≥ 20% + 5 mm absolute \n", "increase in tumor \n", "burden compared\n", "with nadir\n", "Appearance of new \n", "lesions or progression of \n", "nontarget lesions≥ 25% increase in tumor burden \n", "compared with baseline,\n", "nadir or reset baseline1\n", "New lesions added to tumor burden\n", "Confirmation required\n", " Stable disease SMD: Disease other than CMR, PMR \n", "or PMDSMD: Increase in SUV by < \n", "25% or decrease in SUV by < \n", "15% Neither partial response nor progressive diseaseTable 1 Key features of positron emission tomography Response Criteria in Solid Tumors, European Organization for Research and \n", "Treatment of Cancer 1999, Response Evaluation Criteria in Solid Tumors 1.1 and immune related Response Criteria \n", "1If an increase in tumor burden is observed at the first scheduled assessment, the baseline is reset to the value observed at the first assessment. PERCIST: PET \n", "Response Criteria in Solid Tumors; EORTC: European Organization for Research and Treatment of Cancer; RECIST: Response Evaluation Criteria in Solid \n", "Tumors; irRC: Immune related Response Criteria; CMR: Complete metabolic response; PMR: Partial metabolic response; PMD: Progressive metabolic disease; \n", "SMD: Stable metabolic disease; SUL: SUV normalized to lean body mass; SUV BSA: SUV normalized for body surface area; SUV: Standardized uptake value.Bauckneht M et al. Immune checkpoint inhibitors and PET31 February 28, 2017 |Volume 9 |Issue 2| WJR|www.wjgnet.comthe other hand, it has been reported that the initial \n", "increase in tumor size, later followed by tumor volume \n", "reduction in part of the patients treated with ICPIs, is \n", "due to inflammatory cell infiltrates. Accordingly, given \n", "the well-known high metabolic activity characterizing \n", "inflammatory cells, this feature may also hamper the \n", "evaluation of 18F-FDG-PET-based response to ICPIs. \n", "Sachpekidis et al[20] evaluated the role of 18F-FDG-\n", "PET/CT after two cycles of ipilimumab in predicting the \n", "final response to therapy in 22 patients with metastatic \n", "melanoma. They evaluated response to treatment by \n", "means of the EORTC criteria and found that 18F-FDG-\n", "PET/CT after two cycles of ipilimumab is predictive of \n", "the final treatment outcome in patients with progressive \n", "metabolic disease (PMD) and stable metabolic disease \n", "(SMD)[20]. However, two patients were initially falsely \n", "classified as early SMD, but they later demonstrated \n", "new metastatic lesions, “upgrading” them to late PMD. \n", "Similarly, early evaluation by means of 18F-FDG-PET \n", "did not identify responders to treatment as the two \n", "patients eventually characterized with PMR were initially \n", "classified with early PMD due to new lesions[20]. In fact, \n", "both RECIST 1.1 and PET-based criteria consider the \n", "identification of new (metabolically active) lesions as \n", "progressive disease. Therefore, presently proposed \n", "PET-based metabolic criteria suffer from at least one \n", "of the same limitations that ha ve resulted in the under -\n", "estimation of response to treatment with ICPIs by \n", "means of RECIST 1.1. Similarly, in the phase 2 study \n", "by Younes et al[9], nivolumab resulted in frequent res -\n", "ponses in patients with classical Hodgkin’s lymphoma \n", "after failure of ASCT and brentuximab vedotin. Most of \n", "these responses were maintained through the reported \n", "follow-up period with an acceptable safety profile. In \n", "this study 18F-FDG-PET was performed at baseline and \n", "at weeks 17 and 25. A negative 18F-FDG-PET scan, \n", "visually assessed by an independent radiological review \n", "committee (IRRC), was required for confirmation \n", "of complete remission. The study demonstrated a \n", "general reduction of tumor burden. Yet, discordance \n", "in complete remission between IRRC and investigator \n", "assessments was largely based on the interpretation \n", "of 18F-FDG-PET scans and standardized uptake values \n", "were not collected as part of this study. The vast \n", "majority of other available data on the potential utility \n", "of 18F-FDG-PET afte r ICPIs are case reports more \n", "often describing underlying challenges of monitoring \n", "radiologic response in these patients and showing \n", "18F-FDG-PET features of inflammatory reactions. PET-\n", "highlighted autoimmune pancolitis, splenic sarcoidosis-\n", "like lesion and exacerbation of sarcoidosis as a potential \n", "confounder in the assessment of tumor response in \n", "a melanoma patient treated with ipilimumab have all \n", "been described[25-27]. Similarly, K oo et al[26] illustrated a \n", "series of inflammatory reactions with avid FDG uptake \n", "in patients treated with ipilimumab, including those with \n", "thyroiditis, hypophysitis, granulomatous inflammation in \n", "the lymph nodes and skin, and enterocolitis. \n", "Accordingly, the potential and challenges of 18F-FDG-PET imaging in the evaluation of patients treated with \n", "ICPIs still need to be clarified and deeply addressed. \n", "Given the relatively greater experience of CT-based \n", "evaluation in this setting and the fact that irRC CT-\n", "based criteria seem to better in capturing response to \n", "ICPIs, it is worthwhile to ask if a similar modification of \n", "PET-based criteria could be proposed in the future.\n", "Potential new PET-based approaches to evaluate the \n", "effect of ICPIs\n", "As mentioned above, due to its intrinsic nature, 18F-FDG-\n", "PET displays not only cancer cell’s metabolic activity but \n", "also inflammation. Since the antineoplastic activity of \n", "ICPIs is highly related to the activation of T cells against \n", "cancer cells, 18F-FDG accumulation might cause false-\n", "positive findings. Yet, discrimination between benign \n", "and malignant processes represents a huge challenge \n", "for 18F-FDG-PET in this clinical setting. Together with the \n", "need of the clinicians to discriminate between responders \n", "and non-responders, allowing individual therapy \n", "optimization and avoiding adverse effects brought \n", "about by ineffective therapy, several studies have been \n", "recently conducted to explore the possible role of non-\n", "FDG radiotracers in the field of ICPIs. These studies, \n", "mainly performed with labeled monoclonal antibodies, \n", "open the new era of the so-called “Immuno-PET”. \n", "Accordingly, in 2014, Higashikawa et al[28] developed \n", "a molecular imaging probe that is able to evaluate \n", "CTLA-4 expression prior to CTLA-4 targeting in cancer . \n", "This 64Cu labeled radiotracer is basically composed \n", "of DOTA protein together with a CTLA-4 specific \n", "antibody and is able to display CTLA-4 expression \n", "in vivo . Similarly, specific experimental radiotracers \n", "were proposed for the visualization of PD-1 and PD-L1 \n", "cellular expression[29-32]. Maute et al[29] measured PD-L1 \n", "expression by radiolabeling a PD-L1 high affinity protein \n", "(HAC) with 64Cu and tested its feasibility in a living \n", "mouse, while Hettich et al[30] developed two 64Cu labeled \n", "immunoPET tracers for imaging of both PD-1 and PD-L1. \n", "Also one SPECT study with radiolabeled anti-murine \n", "PD-L1 in mice has been conducted[32]. More recently, a \n", "89Zr labeled CD3 PET imaging agent was proposed by \n", "Larimer et al[33]. CD3 is a part of the TCR complex that \n", "serves as a global T lymphocyte marker . By serving as \n", "a marker of total T-cell infiltration, CD3 may represent \n", "a more direct approach than pre-treatment biopsy \n", "or genetic screening to monitoring tumor immune \n", "response, by directly examining active recruitment of \n", "T cells responsible for cancer cell death. In this study \n", "the authors showed that CD3 PET imaging revealed \n", "two distinct groups of mice, stratified by PET signal \n", "intensity. While high-CD3 PET uptake was correlated \n", "with subsequent reduced tumor volume, low uptake was \n", "predictive of suboptimal response. Altogether these non-\n", "invasive approaches allow simultaneous imaging of the \n", "entire cancer mass and associated metastases, which \n", "may differ from the primary tumor in CTLA-4, PD-1 or \n", "PD-L1 expression status. Immune imaging can be used \n", "for repeated assessment of the same tumor at different Bauckneht M et al. Immune checkpoint inhibitors and PET32 February 28, 2017 |Volume 9 |Issue 2| WJR|www.wjgnet.comtime points ( e.g., before and after treatment), thereby \n", "yielding a richer set of diagnostic information that would \n", "be difficult or impossible to achieve with traditional \n", "approaches. Furthermore, although further investigations \n", "are needed before their potential introduction in the \n", "clinical setting, these non-invasive immune-diagnostic \n", "approaches might yield novel insights into the biology \n", "and pathophysiological importance of ICPIs as cancer \n", "therapeutics. \n", "REFERENCES\n", "1 Pardoll DM . The blockade of immune checkpoints in cancer \n", "immunotherapy. Nat Rev Cancer 2012; 12: 252-264 [PMID: \n", "22437870 DOI: 10.1038/nrc3239]\n", "2 Walunas TL , Lenschow DJ, Bakker CY , Linsley PS, Freeman GJ, \n", "Green JM, Thompson CB, Bluestone JA. CTLA-4 can function as \n", "a negative regulator of T cell activation. Immunity 1994; 1: 405-413 \n", "[PMID: 7882171]\n", "3 Francisco LM , Sage PT, Sharpe AH. The PD-1 pathway in \n", "tolerance and autoimmunity. Immunol Rev 2010; 236: 219-242 \n", "[PMID: 20636820 DOI: 10.1111/j.1600]\n", "4 O’Day SJ , Hamid O, Urba WJ. 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Cancer Res 2016; 76: 472-479 [PMID: \n", "26554829 DOI: 10.1158/0008-5472.CAN-15-2141]\n", "33 Larimer BM , Wehrenberg-Klee E, Caraballo A, Mahmood U. \n", "Quantitative CD3 PET Imaging Predicts Tumor Growth Response \n", "to Anti-CTLA-4 Therapy. J Nucl Med 2016; 57: 1607-1611 [PMID: \n", "27230929 DOI: 10.2967/jnumed.116.173930]\n", "P- Reviewer : Morris DLL, Palumbo B S- Editor : Ji FF \n", "L- Editor : Wang TQ E- Editor : Wu HLBauckneht M et al. Immune checkpoint inhibitors and PET\n", " © 2017 Baishideng Publishing Group Inc . All rights reserved.Published by Baishideng Publishing Group Inc\n", "8226 Regency Drive, Pleasanton, CA 94588, USA\n", "Telephone: +1-925-223-8242\n", "Fax: +1-925-223-8243\n", "E-mail: bpgoffice@wjgnet.com\n", "Help Desk: http://www.wjgnet.com/esps/helpdesk.aspx\n", "http://www.wjgnet.com\n", "\n" ] } ], "source": [ "print(text)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "import xml.etree.ElementTree as ET\n", "tree = ET.parse(\"ijms-24-05988.nxml\")" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": [ "root = tree.getroot()\n", "body_elements = root.findall(\".//body//p\")\n" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'acute myeloid leukemia'" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "root.findall(\".//kwd\")[0].text" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Variation in Lipid Species Profiles among Leukemic Cells Significantly Impacts Their Sensitivity to the Drug Targeting of Lipid Metabolism and the Prognosis of AML Patients'" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "root.find(\".//article-title\").text" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Several studies have linked bad prognoses of acute myeloid leukemia (AML) to the ability of leukemic cells to reprogram their metabolism and, in particular, their lipid metabolism. In this context, we performed “in-depth” characterization of fatty acids (FAs) and lipid species in leukemic cell lines and in plasma from AML patients. We firstly showed that leukemic cell lines harbored significant differences in their lipid profiles at steady state, and that under nutrient stress, they developed common mechanisms of protection that led to variation in the same lipid species; this highlights that the remodeling of lipid species is a major and shared mechanism of adaptation to stress in leukemic cells. We also showed that sensitivity to etomoxir, which blocks fatty acid oxidation (FAO), was dependent on the initial lipid profile of cell lines, suggesting that only a particular “lipidic phenotype” is sensitive to the drug targeting of FAO. We then showed that the lipid profiles of plasma samples from AML patients were significantly correlated with the prognosis of patients. In particular, we highlighted the impact of phosphocholine and phosphatidyl-choline metabolism on patients’ survival. In conclusion, our data show that balance between lipid species is a phenotypic marker of the diversity of leukemic cells that significantly influences their proliferation and resistance to stress, and thereby, the prognosis of AML patients.'" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "root.find(\".//abstract/p\").text " ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "\n", "content = \"\\n\".join([p.text for p in body_elements if p.text]) if body_elements else \"No Content Available\"\n" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "School nutrition is an important key modifier in terms of child and adolescent nutrient intake. A poor diet early in life can lead to a multitude of immediate and long-term health problems. Changes to the dietary information given in the school setting as well as changes to the food programs offered have the potential to promote adherence to a healthy diet, which can lead to lifelong health benefits.\n", "The present Special Issue includes two multicomponent school-based nutrition interventions to increase fruit (F) and vegetable (V) intake in children [\n", "Both multicomponent school-based interventions in the present Special Issue used the well-known theory of planned behavior as one of their theoretical models. More specifically, attitude, subjective norms, and perceived behavioral control can predict behavioral intentions. This approach has effectively predicted and changed diet-related behaviors and intentions in youth [\n", "The Dutch “Kokkerelli learning street” program combined the classroom with experiential learning strategies. Using this program, Hahnraths et al. also examined FV preferences, knowledge, attitudes, and intention to consume FV short term (directly after the intervention) and after 3 months [\n", "Both of the school-based nutrition interventions included in the Special Issue aimed to change F and V intake in children aged approximately 7–10 years old. Preference is the main factor associated with F and V in children, whereas Vs are not an innate preferred food. However, participation in the 3-year intervention had a stronger effect on changing FV intake than change in FV preference among primary school children [\n", "Overall, these intervention studies [\n", "It is noteworthy that the 3-year intervention “Nutri-skolica” was not fully implemented due to the COVID-19 pandemic. On the same note, the next study in the Special Issue examines the changes due to COVID-19 regarding the implementation of emergency school meals and pandemic electronic benefits in an urban setting. Cadenhead et al. presented qualitative data on facilitators and barriers to using the available emergency school meals and the P-EBT [\n", "Through the Hunger-Free Kids Act of 2010, the US Department of Agriculture (USDA) established policies to improve the nutritional quality of food and beverages served to US children through federal food assistance programs and it made changes in the Child and Adult Care Food Program (CAFP). In this Special Issue, Dave et al. assess what changes in children’s dietary behaviors occurred as a result of the new CACFP meal pattern requirements [\n", "The Smart Snacks rule was part of the implementation of the 2010 Act, which allows the USDA to regulate foods and beverages sold in schools outside of the school meal programs. For example, energy drinks are not permitted in schools, and a study using data from the School Nutrition and Meal Cost Study reported 84% compliance in middle schools in the United States [\n", "The National School Lunch Program (NSLP) and the School Breakfast Program have to follow specific nutrition requirements consistent with the Dietary Guidelines for Americans. Eating school breakfast and school lunch every day was associated with modestly healthier dietary intakes in US schoolchildren [\n", "Taken together, the studies presented in this Special Issue highlight the relevance of the role of schools in children’s nutrition. The school environment represents a unique opportunity to positively impact the nutrition of children considering they can consume a significant percentage of their daily intake there. Similarly, a recent systematic review concluded that FV interventions provide a promising avenue by which children’s consumption can be improved. Future interventions should place more focus on vegetable intake [\n" ] } ], "source": [ "print(content)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "pinecone-env", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.10" } }, "nbformat": 4, "nbformat_minor": 2 }