Neurostatistical imaging for diagnosing dementia: translational approach from laboratory neuroscience to clinical routine.
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ABSTRACT:
SUBMITTER: Imabayashi E
PROVIDER: S-EPMC5562589 | biostudies-other | 2014 Oct
REPOSITORIES: biostudies-other
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Project description:ImportancePrevious studies have shown that uniform pathologic review of all splenectomy surgical specimens reveals new clinically actionable diagnoses only in a minority of cases.ObjectiveTo examine whether the aggregate of clinical, laboratory, imaging, and pathologic preoperative data is associated with a clinically beneficial pathologic study for routine splenectomy surgical specimens.Design, setting, and participantsThis single-center retrospective cohort study included all patients who underwent splenectomy from January 1, 2013, through December 31, 2018, at a single center. Clinical, imaging, and pathologic data were extracted from the institution's electronic medical records system. Data analysis was conducted from June to November 2020.ExposuresUndergoing splenectomy for trauma or diagnostic or therapeutic indications.Main outcomes and measuresSpleen pathology study resulting in a new medical diagnosis or change in medical management.ResultsOverall, 90 patients (53 [59%] men) with a median (range) age of 59 (19-90) years underwent splenectomy for therapeutic purposes in 41 patients (45%), trauma in 24 patients (27%), diagnostic purposes in 15 patients (17%), and combined therapeutic and diagnostic purposes in 9 patients (10%). In 14 patients (15%) a new malignant neoplasm was found, and in 8 patients (9%), a new nonneoplastic medical condition was diagnosed. A new pathologic diagnosis resulted in change in medical management in 16 patients (18%). In patients without a prior diagnosis of cancer, 41 of 56 pathology biopsies (73%) were found to be normal whereas in 7 biopsies (13%), a new diagnosis of a hematologic malignant neoplasm was revealed (P < .001). Patients with clinical splenomegaly were significantly more likely to have a new pathologic diagnosis of cancer compared with patients without splenomegaly (15 of 26 [58%] vs 4 of 64 [7%]; P < .001). In 39 of 43 patients (91%) with normal presurgery imaging studies, normal spleen pathology was revealed, whereas in 14 of 17 patients (82%) with abnormal imaging studies, a new hematological malignant neoplasm was diagnosed following pathologic review of the spleen specimen (P < .001). Patients with gross abnormalities on macroscopic examination had a significantly increased likelihood of a hematological cancer diagnosis (17 of 40 [43%]) and a solid cancer diagnosis (4 [10%]) compared with patients with grossly normal specimens (4 of 49 [8%]; P < .001).Conclusions and relevanceIn this cohort study, routine pathologic review of spleen specimens was clinically beneficial in patients with splenomegaly, abnormal imaging results, a prior diagnosis of cancer, and with grossly abnormal spleens.
| S-EPMC8369355 | biostudies-literature
Project description:ObjectiveSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged as a global pandemic in early 2020 with rapidly evolving approaches to diagnosing the clinical illness called coronavirus disease (COVID-19). The primary objective of this scoping review is to synthesize current research of the diagnostic accuracy of history, physical examination, routine laboratory tests, real-time reverse transcription-polymerase chain reaction (rRT-PCR), immunology tests, and computed tomography (CT) for the emergency department (ED) diagnosis of COVID-19. Secondary objectives included a synopsis of diagnostic biases likely with current COVID-19 research as well as corresponding implications of false-negative and false-positive results for clinicians and investigators.MethodsA Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review (PRISMA-ScR)-adherent synthesis of COVID-19 diagnostic accuracy through May 5, 2020, was conducted. The search strategy was designed by a medical librarian and included studies indexed by PubMed and Embase since January 2020.ResultsA total of 1,907 citations were screened for relevance. Patients without COVID-19 are rarely reported, so specificity and likelihood ratios were generally unavailable. Fever is the most common finding, while hyposmia and hypogeusia appear useful to rule in COVID-19. Cough is not consistently present. Lymphopenia is the mostly commonly reported laboratory abnormality and occurs in over 50% of COVID-19 patients. rRT-PCR is currently considered the COVID-19 criterion standard for most diagnostic studies, but a single test sensitivity ranges from 60% to 78%. Multiple reasons for false-negatives rRT-PCR exist, including sample site tested and disease stage during which sample was obtained. CT may increase COVID-19 sensitivity in conjunction with rRT-PCR, but guidelines for imaging patients most likely to benefit are emerging. IgM and IgG serology levels are undetectable in the first week of COVID-19, but sensitivity (range = 82% to 100%) and specificity (range = 87% to 100%) are promising. Whether detectable COVID-19 antibodies correspond to immunity remains unanswered. Current studies do not adhere to accepted diagnostic accuracy reporting standards and likely report significantly biased results if the same tests were to be applied to general ED populations with suspected COVID-19.ConclusionsWith the exception of fever and disorders of smell/taste, history and physical examination findings are unhelpful to distinguish COVID-19 from other infectious conditions that mimic SARS-CoV-2 like influenza. Routine laboratory tests are also nondiagnostic, although lymphopenia is a common finding and other abnormalities may predict severe disease. Although rRT-PCR is the current criterion standard, more inclusive consensus-based criteria will likely emerge because of the high false-negative rate of PCR tests. The role of serology and CT in ED assessments remains undefined.
| S-EPMC7323136 | biostudies-literature
Project description:Tremor is the most common movement disorder worldwide, but diagnosis is challenging. In 2018, the task force on tremor of the International Parkinson and Movement Disorder Society published a consensus statement that proposes a tremor classification along two independent axes: a clinical tremor syndrome and its underlying aetiology. In line with this statement, we here propose a stepwise diagnostic approach that leads to the correct clinical and aetiological classification of upper limb tremor. We also describe the typical clinical signs of each clinical tremor syndrome. A key feature of our algorithm is the distinction between isolated and combined tremor syndromes, in which tremor is accompanied by bradykinesia, cerebellar signs, dystonia, peripheral neuropathy or brainstem signs. This distinction subsequently informs the selection of appropriate diagnostic tests, such as neurophysiology, laboratory testing, structural and dopaminergic imaging and genetic testing. We highlight treatable metabolic causes of tremor, as well as drugs and toxins that can provoke tremor. The stepwise approach facilitates appropriate diagnostic testing and avoids unnecessary investigations. We expect that the approach offered in this article will reduce diagnostic uncertainty and increase the diagnostic yield in patients with tremor.
| S-EPMC7402459 | biostudies-literature
Project description:Described is a design for easy-to-construct apparatus that measures movement of flying insects suitable for the undergraduate teaching laboratory. The system does not require the purchase of specialized scientific equipment or software. The apparatus can be constructed and operated without advanced knowledge in electronics or programming. The goal of this apparatus was to expand upon previous research detecting insect flight in response to radiation. We improved upon the quantification and resolution of flight across differing intensities of white light. All of this was achieved using low-cost and commonly available materials and open-source software to collect and analyze data. The only substantial prerequisites for this design are a PC with a 3.5 mm microphone input and an understanding of basic electrical connections. The apparatus was validated with comparative physiological data from two different species of butterfly.
| S-EPMC7491750 | biostudies-literature
Project description:Real-time PCR has revolutionized the way clinical microbiology laboratories diagnose many human microbial infections. This testing method combines PCR chemistry with fluorescent probe detection of amplified product in the same reaction vessel. In general, both PCR and amplified product detection are completed in an hour or less, which is considerably faster than conventional PCR detection methods. Real-time PCR assays provide sensitivity and specificity equivalent to that of conventional PCR combined with Southern blot analysis, and since amplification and detection steps are performed in the same closed vessel, the risk of releasing amplified nucleic acids into the environment is negligible. The combination of excellent sensitivity and specificity, low contamination risk, and speed has made real-time PCR technology an appealing alternative to culture- or immunoassay-based testing methods for diagnosing many infectious diseases. This review focuses on the application of real-time PCR in the clinical microbiology laboratory.
| S-EPMC1360278 | biostudies-literature
Project description:Several prediction models have been proposed for preoperative risk stratification for mortality. However, few studies have investigated postoperative risk factors, which have a significant influence on survival after surgery. This study aimed to develop prediction models using routine immediate postoperative laboratory values for predicting postoperative mortality. Two tertiary hospital databases were used in this research: one for model development and another for external validation of the resulting models. The following algorithms were utilized for model development: LASSO logistic regression, random forest, deep neural network, and XGBoost. We built the models on the lab values from immediate postoperative blood tests and compared them with the SASA scoring system to demonstrate their efficacy. There were 3817 patients who had immediate postoperative blood test values. All models trained on immediate postoperative lab values outperformed the SASA model. Furthermore, the developed random forest model had the best AUROC of 0.82 and AUPRC of 0.13, and the phosphorus level contributed the most to the random forest model. Machine learning models trained on routine immediate postoperative laboratory values outperformed previously published approaches in predicting 30-day postoperative mortality, indicating that they may be beneficial in identifying patients at increased risk of postoperative death.
| S-EPMC8706001 | biostudies-literature
Project description:BACKGROUND:"Nanomedicine" is the application of purposely designed nano-scale materials for improved therapeutic and diagnostic outcomes, which cannot be otherwise achieved using conventional delivery approaches. While "translation" in drug development commonly encompasses the steps from discovery to human clinical trials, a different set of translational steps is required in nanomedicine. Although significant development effort has been focused on nanomedicine, the translation from laboratory formulations up to large scale production has been one of the major challenges to the success of such nano-therapeutics. In particular, scale-up significantly alters momentum and mass transfer rates, which leads to different regimes for the formation of nanomedicines. Therefore, unlike the conventional definition of translational medicine, a key component of "bench-to-bedside" translational research in nanomedicine is the scale-up of the synthesis and processing of the nano-formulation to achieve precise control of the nanoscale properties. This consistency requires reproducibility of size, polydispersity and drug efficacy. METHODS:Here we demonstrate that Flash NanoPrecipitation (FNP) offers a scalable and continuous technique to scale up the production rate of nanoparticles from a laboratory scale to a pilot scale. FNP is a continuous, stabilizer-directed rapid precipitation process. Lumefantrine, an anti-malaria drug, was chosen as a representative drug that was processed into 200 nm nanoparticles with enhanced bioavailability and dissolution kinetics. Three scales of mixers, including a small-scale confined impinging jet mixer, a mid-scale multi-inlet vortex mixer (MIVM) and a large-scale multi-inlet vortex mixer, were utilized in the formulation. The production rate of nanoparticles was varied from a few milligrams in a laboratory batch mode to around 1 kg/day in a continuous large-scale mode, with the size and polydispersity similar at all scales. RESULTS:Nanoparticles of 200 nm were made at all three scales of mixers by operating at equivalent Reynolds numbers (dynamic similarity) in each mixer. Powder X-ray diffraction and differential scanning calorimetry demonstrated that the drugs were encapsulated in an amorphous form across all production rates. Next, scalable and continuous spray drying was applied to obtain dried powders for long-term storage stability. For dissolution kinetics, spray dried samples produced by the large-scale MIVM showed 100% release in less than 2 h in both fasted and fed state intestinal fluids, similar to small-batch low-temperature lyophilization. CONCLUSIONS:These results validate the successful translation of a nanoparticle formulation from the discovery scale to the clinical scale. Coupling nanoparticle production using FNP processing with spray drying offers a continuous nanofabrication platform to scale up nanoparticle synthesis and processing into solid dosage forms.
| S-EPMC6570894 | biostudies-other
Project description:The neural basis of decision-making has been elusive and involves the coordinated activity of multiple brain structures. This NeuroView, by the International Brain Laboratory (IBL), discusses their efforts to develop a standardized mouse decision-making behavior, to make coordinated measurements of neural activity across the mouse brain, and to use theory and analyses to uncover the neural computations that support decision-making.
| S-EPMC5752703 | biostudies-literature
Project description:Over the past few decades, several radiotracers have been developed for neuroimaging applications, especially in PET. Because of their low steric hindrance, PET radionuclides can be used to label molecules that are small enough to cross the blood brain barrier, without modifying their biological properties. As the use of 11C is limited by its short physical half-life (20 min), there has been an increasing focus on developing tracers labeled with 18F for clinical use. The first such tracers allowed cerebral blood flow and glucose metabolism to be measured, and the development of molecular imaging has since enabled to focus more closely on specific targets such as receptors, neurotransmitter transporters, and other proteins. Hence, PET and SPECT biomarkers have become indispensable for innovative clinical research. Currently, the treatment options for a number of pathologies, notably neurodegenerative diseases, remain only supportive and symptomatic. Treatments that slow down or reverse disease progression are therefore the subject of numerous studies, in which molecular imaging is proving to be a powerful tool. PET and SPECT biomarkers already make it possible to diagnose several neurological diseases in vivo and at preclinical stages, yielding topographic, and quantitative data about the target. As a result, they can be used for assessing patients' eligibility for new treatments, or for treatment follow-up. The aim of the present review was to map major innovative radiotracers used in neuroscience, and explain their contribution to clinical research. We categorized them according to their target: dopaminergic, cholinergic or serotoninergic systems, β-amyloid plaques, tau protein, neuroinflammation, glutamate or GABA receptors, or α-synuclein. Most neurological disorders, and indeed mental disorders, involve the dysfunction of one or more of these targets. Combinations of molecular imaging biomarkers can afford us a better understanding of the mechanisms underlying disease development over time, and contribute to early detection/screening, diagnosis, therapy delivery/monitoring, and treatment follow-up in both research and clinical settings.
| S-EPMC6890558 | biostudies-literature
Project description:Translational research in neuroscience is increasingly focusing on the analysis of multi-modal data, in order to account for the biological complexity of suspected disease mechanisms. Recent advances in machine learning have the potential to substantially advance such translational research through the simultaneous analysis of different data modalities. This review focuses on one of such approaches, the so-called "multi-task learning" (MTL), and describes its potential utility for multi-modal data analyses in neuroscience. We summarize the methodological development of MTL starting from conventional machine learning, and present several scenarios that appear particularly suitable for its application. For these scenarios, we highlight different types of MTL algorithms, discuss emerging technological adaptations, and provide a step-by-step guide for readers to apply the MTL approach in their own studies. With its ability to simultaneously analyze multiple data modalities, MTL may become an important element of the analytics repertoire used in future neuroscience research and beyond.
| S-EPMC9714033 | biostudies-literature