Case report: New insights into persistent chronic pelvic pain syndrome with comorbid somatic symptom disorder

Chronic pelvic pain syndrome (CPPS) is generally defined as pain in the pelvic area that persisted for 3–6 months or longer. The pain can be constant or episodic and functionally disabling. Any dysfunction of the central nervous system can lead to central sensitization, which enhances and maintains pain as well as other symptoms that are mediated by the central nervous system. It occurs in subgroups of nearly every chronic pain condition and is characterized by multifocal pain and co-occurring somatic symptoms. Somatic symptom disorder (SSD) is defined as a condition in which having one or more somatic symptoms, such as excessive worries, pressure, and catastrophic events. These symptoms can be very disruptive to a patient’s life and can cause significant distress. SSD cases with severe symptoms frequently undergo repeated medical investigations and the symptoms often lead patients to seek emergency medical treatment and consult with specialists repeatedly, which is a source of frustration for patients and clinicians. Here we report a case that Asian female with persistent CPPS with comorbid SSD, who got in trouble for up to 8 years. This case reminds clinicians to pay excessive attention to the diagnosis of CPPS with comorbid SSD after recovery from acute COVID-19, with hope of raising awareness in the identification of SSD and present new insight into appropriate treatment for each woman who suffers from it

An Intelligent Method for Pork Freshness Identification Based on EfficientNet Model

A method for measuring pork freshness based on images and the EfficientNet framework was established. A total of 2 500 images of pork with different freshness were collected as original dataset and processed by image enhancement to construct a new dataset of 60 000 images. First, EfficientNet was trained with the CIFAR-10 dataset to determine the basic structure and initial weights of the model. Then, the model was trained and improved using the constructed dataset to make the model suitable for five classification problems. Finally, the established model was tested, verified, and compared with the current mainstream convolutional neural network (CNN) models of Alexnet, VGG16 and ResNet50. The results showed that the average correct recognition rate of the EfficientNet model was as high as 98.62%, which was significantly better than that of the Alexnet, VGG16 and ResNet50 models. The correct recognition rate of the EfficientNetB2 model was 99.22%, and the training time was only 157 min. The comprehensive performance of the EfficientNetB2 model was the best, making it the most suitable method for pork freshness identification. In order to improve its generalization ability, the optimizer algorithm of the EfficientNetB2 model was improved, and the performances of stochastic gradient descent (SGD), adaptive moment estimation (Adam), root mean square propagation (RMSProp) and rectified adaptive moment estimation (RAdam) were compared. The results showed that the RAdam optimizer failed to further improve the accuracy of the model but instead helped to improve its generalization capability, which will of practical significance for engineering applications

Spatial variation in grain-size population of surface sediments from northern Bering Sea and western Arctic Ocean: implications for provenance and depositional mechanisms

In general, sediments in nature comprise populations of various diameters. Accurate information regarding the sources and depositional mechanisms of the populations can be obtained through their temporal and spatial comparisons. In this study, the grain size distribution of surface sediments from the Bering Sea and western Arctic Ocean were fitted and partitioned into populations using a log-normal distribution function. The spatial variations in the populations indicate differences in their sources and deposition mechanisms. The sediments on most of the Bering Sea Shelf originated from the Yukon River, and were transported westward by waves and currents. However, the presence of a coarser population outside Anadyr Bay was the result of Anadyr River transport. Additionally, a northward transport trend of fine suspended particles was observed on the west side of the Bering Sea Shelf. The sediments in Hope Valley in the south Chukchi Sea also originated from the Yukon River. The coarser population on the central Chukchi Sea Shelf originated from coast of Alaska to the east, not the Yukon River, and was transported by sea ice and bottom brine water. The populations of sediments from the Chukchi Basin and the base of the Chukchi Sea Slope are the result of sea ice and eddy action. Surface sediments from the western high Arctic Ocean predominantly comprised five populations, and two unique populations with mode diameters of 50–90 μm and 200–400 μm, respectively, were ubiquitous in the glacial and interglacial sediments. It was difficult to distinguish whether these two populations originated from sea ice or icebergs. Therefore, caution should be exercised when using either the > 63 μm or > 250 μm fractions in sediments as a proxy index for iceberg and ice sheet variation in the high Arctic Ocean

A bibliometric analysis and visualization of normal pressure hydrocephalus

BackgroundNormal pressure hydrocephalus (NPH) has drawn an increasing amount of attention over the last 20 years. At present, there is a shortage of intuitive analysis on the trends in development, key contributors, and research hotspots topics in the NPH field. This study aims to analyze the evolution of NPH research, evaluate publications both qualitatively and quantitatively, and summarize the current research hotspots.MethodsA bibliometric analysis was conducted on data retrieved from the Web of Science Core Collection (WoSCC) database between 2003 and 2023. Quantitative assessments were conducted using bibliometric analysis tools such as VOSviewer and CiteSpace software.ResultsA total of 2,248 articles published between 2003 and 2023 were retrieved. During this period, the number of publications steadily increased. The United States was the largest contributor. The University of Gothenburg led among institutions conducting relevant research. Eide P. K. was the most prolific author. The Journal of Neurosurgery is the leading journal on NPH. According to the analysis of the co-occurrence of keywords and co-cited references, the primary research directions identified were pathophysiology, precise diagnosis, and individualized treatment. Recent research hotspots have mainly focused on epidemiology, the glymphatic system, and CSF biomarkers.ConclusionThe comprehensive bibliometric analysis of NPH offers insights into the main research directions, highlights key countries, contributors, and journals, and identifies significant research hotspots. This information serves as a valuable reference for scholars to further study NPH

Low Serum Magnesium Level Is Associated with Microalbuminuria in Chinese Diabetic Patients

Whether serum magnesium deficiency is independently associated with the prevalence of microalbuminuria is still unclear. The objective of the present study was to elucidate the association between serum magnesium and microalbuminuria in diabetic patients. A cross-sectional study was conducted in 1829 diabetic subjects (aged ≥ 40 years) from Shanghai, China. Subjects were divided into three groups according to serum magnesium tertiles. A first-voided early-morning spot urine sample was obtained for urinary albumin-creatinine ratio (UACR) measurement. Microalbuminuria was defined as 30 mg/g ≤ UACR < 300 mg/g. Overall, 208 (11.37%) of the study population had microalbuminuria, with similar proportions in both genders (). The prevalence of microalbuminuria in tertile 1 of serum magnesium was higher than the prevalence in tertile 2 and tertile 3 (15.98%, 9.72%, and 8.46%, resp.; for trend <0.0001). After adjustment for age, sex, BMI, blood pressure, lipidaemic profile, HbA1c, eGFR, history of cardiovascular disease, HOMA-IR, antihypertensive and antidiabetic medication, and diabetes duration, we found that, compared with the subjects in tertile 3 of serum magnesium, those in tertile 1 had 1.85 times more likeliness to have microalbuminuria. We concluded that low serum magnesium level was significantly associated with the prevalence of microalbuminuria in middle-aged and elderly Chinese

Drug-Tolerant Cancer Cells Show Reduced Tumor-Initiating Capacity: Depletion of CD44+ Cells and Evidence for Epigenetic Mechanisms

Cancer stem cells (CSCs) possess high tumor-initiating capacity and have been reported to be resistant to therapeutics. Vice versa, therapy-resistant cancer cells seem to manifest CSC phenotypes and properties. It has been generally assumed that drug-resistant cancer cells may all be CSCs although the generality of this assumption is unknown. Here, we chronically treated Du145 prostate cancer cells with etoposide, paclitaxel and some experimental drugs (i.e., staurosporine and 2 paclitaxel analogs), which led to populations of drug-tolerant cells (DTCs). Surprisingly, these DTCs, when implanted either subcutaneously or orthotopically into NOD/SCID mice, exhibited much reduced tumorigenicity or were even non-tumorigenic. Drug-tolerant DLD1 colon cancer cells selected by a similar chronic selection protocol also displayed reduced tumorigenicity whereas drug-tolerant UC14 bladder cancer cells demonstrated either increased or decreased tumor-regenerating capacity. Drug-tolerant Du145 cells demonstrated low proliferative and clonogenic potential and were virtually devoid of CD44+ cells. Prospective knockdown of CD44 in Du145 cells inhibited cell proliferation and tumor regeneration, whereas restoration of CD44 expression in drug-tolerant Du145 cells increased cell proliferation and partially increased tumorigenicity. Interestingly, drug-tolerant Du145 cells showed both increases and decreases in many “stemness” genes. Finally, evidence was provided that chronic drug exposure generated DTCs via epigenetic mechanisms involving molecules such as CD44 and KDM5A. Our results thus reveal that 1) not all DTCs are necessarily CSCs; 2) conventional chemotherapeutic drugs such as taxol and etoposide may directly target CD44+ tumor-initiating cells; and 3) DTCs generated via chronic drug selection involve epigenetic mechanisms

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submit- Avenue, Silver Spring, Maryland 20993; 22Glycoscience Research Laboratory, Genos, Borongajska cesta 83h, 10 000 Zagreb, Croatia; 23Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacˇ ic´ a 1, 10 000 Zagreb, Croatia; 24Department of Chemistry, Georgia State University, 100 Piedmont Avenue, Atlanta, Georgia 30303; 25glyXera GmbH, Brenneckestrasse 20 * ZENIT / 39120 Magdeburg, Germany; 26Health Products and Foods Branch, Health Canada, AL 2201E, 251 Sir Frederick Banting Driveway, Ottawa, Ontario, K1A 0K9 Canada; 27Graduate School of Advanced Sciences of Matter, Hiroshima University, 1-3-1 Kagamiyama Higashi-Hiroshima 739–8530 Japan; 28ImmunoGen, 830 Winter Street, Waltham, Massachusetts 02451; 29Department of Medical Physiology, Jagiellonian University Medical College, ul. Michalowskiego 12, 31–126 Krakow, Poland; 30Department of Pathology, Johns Hopkins University, 400 N. Broadway Street Baltimore, Maryland 21287; 31Mass Spec Core Facility, KBI Biopharma, 1101 Hamlin Road Durham, North Carolina 27704; 32Division of Mass Spectrometry, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongwon-gu, Cheongju Chungbuk, 363–883 Korea (South); 33Advanced Therapy Products Research Division, Korea National Institute of Food and Drug Safety, 187 Osongsaengmyeong 2-ro Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 363–700, Korea (South); 34Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 35Ludger Limited, Culham Science Centre, Abingdon, Oxfordshire, OX14 3EB, United Kingdom; 36Biomolecular Discovery and Design Research Centre and ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, North Ryde, Australia; 37Proteomics, Central European Institute for Technology, Masaryk University, Kamenice 5, A26, 625 00 BRNO, Czech Republic; 38Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany; 39Department of Biomolecular Sciences, Max Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany; 40AstraZeneca, Granta Park, Cambridgeshire, CB21 6GH United Kingdom; 41Merck, 2015 Galloping Hill Rd, Kenilworth, New Jersey 07033; 42Analytical R&D, MilliporeSigma, 2909 Laclede Ave. St. Louis, Missouri 63103; 43MS Bioworks, LLC, 3950 Varsity Drive Ann Arbor, Michigan 48108; 44MSD, Molenstraat 110, 5342 CC Oss, The Netherlands; 45Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5–1 Higashiyama, Myodaiji, Okazaki 444–8787 Japan; 46Graduate School of Pharmaceutical Sciences, Nagoya City University, 3–1 Tanabe-dori, Mizuhoku, Nagoya 467–8603 Japan; 47Medical & Biological Laboratories Co., Ltd, 2-22-8 Chikusa, Chikusa-ku, Nagoya 464–0858 Japan; 48National Institute for Biological Standards and Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire EN6 3QG United Kingdom; 49Division of Biological Chemistry & Biologicals, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158–8501 Japan; 50New England Biolabs, Inc., 240 County Road, Ipswich, Massachusetts 01938; 51New York University, 100 Washington Square East New York City, New York 10003; 52Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom; 53GlycoScience Group, The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland; 54Department of Chemistry, North Carolina State University, 2620 Yarborough Drive Raleigh, North Carolina 27695; 55Pantheon, 201 College Road East Princeton, New Jersey 08540; 56Pfizer Inc., 1 Burtt Road Andover, Massachusetts 01810; 57Proteodynamics, ZI La Varenne 20–22 rue Henri et Gilberte Goudier 63200 RIOM, France; 58ProZyme, Inc., 3832 Bay Center Place Hayward, California 94545; 59Koichi Tanaka Mass Spectrometry Research Laboratory, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho Nakagyo-ku, Kyoto, 604 8511 Japan; 60Children’s GMP LLC, St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, Tennessee 38105; 61Sumitomo Bakelite Co., Ltd., 1–5 Muromati 1-Chome, Nishiku, Kobe, 651–2241 Japan; 62Synthon Biopharmaceuticals, Microweg 22 P.O. Box 7071, 6503 GN Nijmegen, The Netherlands; 63Takeda Pharmaceuticals International Co., 40 Landsdowne Street Cambridge, Massachusetts 02139; 64Department of Chemistry and Biochemistry, Texas Tech University, 2500 Broadway, Lubbock, Texas 79409; 65Thermo Fisher Scientific, 1214 Oakmead Parkway Sunnyvale, California 94085; 66United States Pharmacopeia India Pvt. Ltd. IKP Knowledge Park, Genome Valley, Shamirpet, Turkapally Village, Medchal District, Hyderabad 500 101 Telangana, India; 67Alberta Glycomics Centre, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 68Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 69Department of Chemistry, University of California, One Shields Ave, Davis, California 95616; 70Horva´ th Csaba Memorial Laboratory for Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Egyetem ter 1, Hungary; 71Translational Glycomics Research Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Egyetem ut 10, Hungary; 72Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way Newark, Delaware 19711; 73Proteomics Core Facility, University of Gothenburg, Medicinaregatan 1G SE 41390 Gothenburg, Sweden; 74Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Institute of Biomedicine, Sahlgrenska Academy, Medicinaregatan 9A, Box 440, 405 30, Gothenburg, Sweden; 75Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy at the University of Gothenburg, Bruna Straket 16, 41345 Gothenburg, Sweden; 76Department of Chemistry, University of Hamburg, Martin Luther King Pl. 6 20146 Hamburg, Germany; 77Department of Chemistry, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2; 78Laboratory of Mass Spectrometry of Interactions and Systems, University of Strasbourg, UMR Unistra-CNRS 7140, France; 79Natural and Medical Sciences Institute, University of Tu¨ bingen, Markwiesenstrae 55, 72770 Reutlingen, Germany; 80Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands; 81Division of Bioanalytical Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; 82Department of Chemistry, Waters Corporation, 34 Maple Street Milford, Massachusetts 01757; 83Zoetis, 333 Portage St. Kalamazoo, Michigan 49007 Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license. Received July 24, 2019, and in revised form, August 26, 2019 Published, MCP Papers in Press, October 7, 2019, DOI 10.1074/mcp.RA119.001677 ER: NISTmAb Glycosylation Interlaboratory Study 12 Molecular & Cellular Proteomics 19.1 Downloaded from https://www.mcponline.org by guest on January 20, 2020 ted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide communityderived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods. Molecular & Cellular Proteomics 19: 11–30, 2020. DOI: 10.1074/mcp.RA119.001677.L

Modeling the Simultaneous Effects of Particle Size and Porosity in Simulating Geo-Materials

The particle discrete element method (PDEM) is widely used to simulate rock and soil materials to obtain stress and strain. However, there are three shortcomings: (1) Single sphere or ellipsoids directly replace the soil particles; (2) it treats the diameters of spheres or ellipsoids as the soil particle size; (3) the overlapping particle volume is not deducted in calculating the porosity. Hence, it is difficult for the simulation of the geological body to agree with reality. This research found a rotation calculation model and a pixel counting method to make joint soil particles more accurately simulate geological materials to solve the three shortcomings. The model successfully obtained the gradation curve and porosity of the simulated geological body with joint particles. This research will further enrich and broaden the application prospects of PDEM and provide a reference for scientific research and engineering fields in geological engineering, geotechnical engineering, and petroleum engineering