anthonyyazdaniml/gliner-biomed-curated-corpus huggingface dataset:
The prevalence of longstanding chronic diseases has increased worldwide, along with the average age of the population. As a result, an increasing number of people is affected by two or more chronic conditions simultaneously, and healthcare systems are facing the challenge of treating multimorbid patients effectively. Current therapeutic strategies are suited to manage each chronic condition separately, without considering the whole clinical condition of the patient. This approach may lead to suboptimal clinical outcomes and system inefficiencies (e.g. redundant diagnostic tests and inadequate drug prescriptions). We develop a novel methodology based on the joint implementation of data reduction and clustering algorithms to identify patterns of chronic diseases that are likely to co-occur in multichronic patients. We analyse data from a large adult population of multichronic patients living in Tuscany (Italy) in 2019 which was stratified by sex and age classes. Results demonstrate that (i) cardio-metabolic, endocrine, and neuro-degenerative diseases represent a stable pattern of multimorbidity, and (ii) disease prevalence and clustering vary across ages and between women and men. Identifying the most common multichronic profiles can help tailor medical protocols to patients' needs and reduce costs. Furthermore, analysing temporal patterns of disease can refine risk predictions for evolutive chronic conditions.
The US Food and Drug Administration (FDA) regulations permit additive-containing RBCs to be stored for up to 42 days prior to transfusion. However, RBCs progressively develop abnormalities during storage. The efficacy of older stored blood, i.e., effective oxygen delivery, has not been established in rigorous controlled studies. Due to pragmatic reasons, a large clinical trial that randomizes patients to "old" blood may not be feasible.

Every subject will have 2 phlebotomy visits at Stony Brook University Hospital. Subjects randomized to the 7- and 42-day old groups will have 2 units of blood removed at Week 0 and another 2 units removed at Week 5. However, the remaining 28-day group will have 2 units of blood removed at Week 2 and only 1 unit of blood removed at Week 5. During week 6, each subjects will have 3 study visits: 1) On Monday, a VO2 max test; 2) On Wednesday, a transfusion with 2 units of autologous RBCs (each over 1 hour), followed by a VO2 max test 2 hours later; 3) On Friday, a VO2 max test will be done in order to calculate a delta VO2 max (Friday minus Monday results).
Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for the diagnosis and prognosis of neurodegenerative pathologies such as Alzheimer's disease or multiple sclerosis. However, its use in individualized assessments is currently discouraged due to a series of technical and biological issues. In this work, we present a deep learning pipeline for segmentation-based brain atrophy quantification that improves upon the automated labels of the reference method from which it learns. This goal is achieved through tissue similarity regularization that exploits the a priori knowledge that scans from the same subject made within a short interval must have similar tissue volumes. To train the presented pipeline, we use unlabeled pairs of T1-weighted MRI scans having a tissue similarity prior, and generate the target brain tissue segmentations in a fully automated manner using the fsl_anat pipeline implemented in the FMRIB Software Library (FSL). Tissue similarity regularization is enforced during training through a weighted loss term that penalizes tissue volume differences between short-interval scan pairs from the same subject. In inference, the pipeline performs end-to-end skull stripping and brain tissue segmentation from a single T1-weighted MRI scan in its native space, i.e., without performing image interpolation. For longitudinal evaluation, each image is independently segmented first, and then measures of change are computed. We evaluate the presented pipeline in two different MRI datasets, MIRIAD and ADNI1, which have longitudinal and short-interval imaging from healthy controls (HC) and Alzheimer's disease (AD) subjects. In short-interval scan pairs, tissue similarity regularization reduces the quantification error and improves the consistency of measured tissue volumes. In the longitudinal case, the proposed pipeline shows reduced variability of atrophy measures and higher effect sizes of differences in annualized rates between HC and AD subjects. Our pipeline obtains a Cohen's d effect size of d=2.07 on the MIRIAD dataset, an increase from the reference pipeline used to train it (d=1.01), and higher than that of SIENA (d=1.73), a well-known state-of-the-art approach. In the ADNI1 dataset, the proposed pipeline improves its effect size (d=1.37) with respect to the reference pipeline (d=0.80) and surpasses SIENA (d=1.33). The proposed data-driven deep learning regularization reduces the biases and systematic errors learned from the reference segmentation method, which is used to generate the training targets. Improving the accuracy and reliability of atrophy quantification methods is essential to unlock brain atrophy as a diagnostic and prognostic marker in neurodegenerative pathologies.
Supporting Addiction Affected Families Effectively is a contextually adapted version of the 5-Step Method, a psychosocial intervention based on the principles of the Stress-Strain-Coping-Support model. The intervention is manualised, and is delivered by lay counsellors over 5 sessions at a weekly basis. The 5 steps (covered in the 5 steps) include: 1) Exploring stresses and strains, 2) Providing relevant information, 3) Exploring and discussing coping behaviours, 4) Exploring and enhancing social support, and 5) Exploring additional needs, and further sources of help. The intervention is delivered in settings based on convenience of the participant: which might be a place outside the home (e.g. field office, neighbour's home), or the participant's home.
OBJECTIVES: Giant cell hepatitis is an important diagnostic consideration in early childhood, especially for patients who present with jaundice. Different diseases may play a role in their etiology. In this study, we presented pediatric patients in our center diagnosed with giant cell hepatitis.
MATERIALS AND METHODS: Liver biopsies performed in our hospital between January 2010 and December 2023 were retrospectively evaluated, and biopsies with histological giant cell formation were included in the study. Demographic, clinical, and histopathological characteristics of the patients were obtained from the medical records.
RESULTS: Our study included 31 cases of giant cell hepatitis. Twenty-four (90.3%) of the patients were male, and the median age was 4 months (range, 1-148 mo). The most common clinical findings were jaundice (93.5%). Among the 31 patients, idiopathic giant cell hepatitis was observed in 13 cases (41.9%), and etiology was elucidated in 18 patients. The most common diagnoses in these patients were progressive familial intrahepatic cholestasis, biliary atresia, and autoimmune hepatitis (22.6%, 19.4%, and 9.7%, respectively). The most common accompanying histopathologic findings were canalicular cholestasis (87.1%), lobular cholestasis (54.8%), and pericellular fibrosis (35.5%). Liver transplant was required in 10 patients (32.3%). Nine patients (29%) died from various reasons. Although follow-up of 13 patients (41.9%) are ongoing, 9 patients (29%) are no longer being followed.
CONCLUSIONS: Few studies in the pediatric age group on giant cell hepatitis have been conducted in the literature. Similar to our series, etiology could not be specified in most of the patients in these reports. Additional research is needed to improve our understanding of the disease process, uncover any other potential causes, and create specific treatment options.
PURPOSE:To obtain a dental dense molded article having excellent strength, transparency, etc., by irradiating a dental photopolymerization type resin with light rays while applying a gas pressure using a device equipped with a pressurizing means by gas pressure and a visible light irradiation device. CONSTITUTION:In polymerizing and curing a dental photopolymerization type resin by light irradiation, light irradiation is carried out while simultaneously pressurizing by gas pressure to give a molded article free from foams. In a device wherein a photopolymerization type resin polymerizer 5 is equipped with an air compressor or gas bomb 1 and a lamp 4 (e.g. xenon lamp fluorescent lighting), a resin sheet 6 is placed on a gypsum model 7, a pressure contact sheet 9 (e.g. one made of silicone rubber) is sandwiched by a holding part 10, a pressurizing valve 3 is opened and then a resin is irradiated with light rays by the lamp 4 for 5 minutes to give a base made of resin. When a resin is successively laminated, air or oxygen is introduced under pressure and preferably photopolymerization is done.
Multiple prognostic scores have been developed to predict morbidity and mortality in patients with spontaneous intracerebral hemorrhage(sICH). Since the advent of machine learning(ML), different ML models have also been developed for sICH prognostication. There is however a need to verify the validity of these ML models in diverse patient populations. We aim to create machine learning models for prognostication purposes in the Qatari population. By incorporating inpatient variables into model development, we aim to leverage more information. 1501 consecutive patients with acute sICH admitted to Hamad General Hospital(HGH) between 2013 and 2023 were included. We trained, evaluated, and compared several ML models to predict 90-day mortality and functional outcomes. For our dataset, we randomly selected 80% patients for model training and 20% for validation and used k-fold cross validation to train our models. The ML workflow included imbalanced class correction and dimensionality reduction in order to evaluate the effect of each. Evaluation metrics such as sensitivity, specificity, F-1 score were calculated for each prognostic model. Mean age was 50.8(SD 13.1) years and 1257(83.7%) were male. Median ICH volume was 7.5 ml(IQR 12.6). 222(14.8%) died while 897(59.7%) achieved good functional outcome at 90 days. For 90-day mortality, random forest(RF) achieved highest AUC(0.906) whereas for 90-day functional outcomes, logistic regression(LR) achieved highest AUC(0.888). Ensembling provided similar results to the best performing models, namely RF and LR, obtaining an AUC of 0.904 for mortality and 0.883 for functional outcomes. Random Forest achieved the highest AUC for 90-day mortality, and LR achieved the highest AUC for 90-day functional outcomes. Comparing ML models, there is minimal difference between their performance. By creating an ensemble of our best performing individual models we maintained maximum accuracy and decreased variance of functional outcome and mortality prediction when compared with individual models.
The reference group (Group 3), per IHS guidelines and current standard of care at participating IHS facilities, receives usual care (ie, screening recommendation and a FIT kit at a clinic visit). The FIT kit used is the Polymedco OC FIT-CHECK® OC-Light test, which is a single collection test that meets USPSTF's guidelines.
In every group on day 1, two volunteers will be injected. On day 3 the remaining four volunteers of the group will be injected. Injections in subsequent volunteers are always spaced at least one hour apart in any group. Injection of subsequent (groups of) volunteers will only commence if the previous injection was shown to be safe. Three different doses of PfSPZ will be administered: a dose of 2,500 PfSPZ Challenge (Group 1); a dose of 10,000 PfSPZ Challenge (Group 2) if not all volunteers become thick smear positive (TS+) in Group 1; and a dose of 25,000 PfSPZ Challenge (Group 3) if there is not 100% TS+ in Group 2. If all volunteers in Group 1 (2,500 PfSPZ Challenge) become thick smear positive, then Group 2a will receive 1,000 PfSPZ Challenge. If all volunteers in Group 2a become TS+, the volunteers in Group 3a will receive 500 PfSPZ Challenge. If all volunteers in Group 2 (10,000 PfSPZ Challenge) become TS+, Group 3b will receive 5,000 PfSPZ. If less than 100% of volunteers in Group 2a (1,000 PfSPZ Challenge) become TS+ then Group 3c will receive 1,750 PfSPZ Challenge.

The clinical, biological, parasitological and immunological data of these groups' volunteers will be compared. Volunteers and the investigator will not be blinded, but the laboratory personnel will be blinded.
Rapid diagnostics of any gene mutations related to organ loss is highly demanded now-a days to consume time as well to reduce cost. Currently, Surface enhanced Raman spectroscopy (SERS) is evolved to be a rapid investigating tool to screen gene mutations down to single molecule sensing with regard to the design and development of substrates used for sensing. The current research focuses on particular towards direct detection of deafness mutations associated with single and dual sites related to GJB2 gene. SERS Sensor construction is achieved with plasmonic silver nanoarrays on Si (SNA/Si) substrate by effortless wet chemical methods (Reaction time: 35 s; Concentration: 20 mM). The fabricated SNA/Si facilitates direct sensing of the deafness mutations of GJB2 gene in single as well dual sites with the enhancement of plasmonic hotspots. Normal DNA DMF-33 (GGGGGG) as well as Mutant DNA at single site DMF-9 (GGGGG) were validated by their guanine fingerprint Raman bands intensity quenching for mutant DNA DMF-9 at 1366 cm-1 and 1595 cm-1 respectively. Likewise, double mutations in DMF-19 are substitutional from G to A, portrayed highly intense fingerprint of Adenine Raman bands at 739 cm-1, 1432 cm-1, 1572 cm-1 in comparison to normal DNA (DMF-33). The findings were well analyzed with Raman mapping data which carries almost 625 scans for each DNA sample. The fabricated sensor exhibited the highest sensitivity towards DNA detection down to 0.1 pg/μL with utmost reproducibility. The current study aims to bring in creation of library files for deafness mutations to facilitate clinical diagnostics in a simple and rapid approach.
Disclosed is a composition for inhibiting the differentiation of adipocytes comprising, as an active component, an Ulmus davidiana var. japonica root cortex extract which can help to prevent obesity or reduce body weight by having the ability to inhibit differentiation of adipocytes by using the Ulmus davidiana var. japonica root cortex extract as a main component, or a compound isolated from the same. The present invention provides a method for manufacturing the composition for inhibiting the differentiation of adipocytes comprising the following steps: (a) washing and cutting the collected Ulmus davidiana var. japonica root cortex; (b) immersing and extracting the cut Ulmus davidiana var. japonica root cortex; and (c) separating the solid content after the active component is extracted.
INTRODUCTION: Heterotopic ossification (HO) in the knee after tibial intramedullary nailing (IMN) has yet to be thoroughly investigated. Our aim was to assess frequency and associated factors for HO in the knee after tibial IMN.
METHODS: This is a retrospective review at a single level 1 urban trauma center of 213 patients who underwent reamed tibial IMN. Plain radiographs were reviewed postoperatively and on final follow-up (≥6 weeks). Chart review was performed for surgical approach (suprapatellar versus infrapatellar), demographics, injury characteristics, and clinical follow-up. The primary outcome was frequency of HO.
RESULTS: HO on final follow-up (mean: 41.43 weeks) was recorded in 15% cases. Postsurgical retroinfrapatellar reaming debris (odds ratio [OR], 4.73), Injury Severity Score (OR, 1.05), intensive care unit admission (OR, 2.89), chest injury (OR, 3.4), and ipsilateral retrograde femoral IMN (OR, 5.08) showed a notable association with HO development. No association was observed in HO formation between surgical approach, knee pain, or range-of-motion deficits.
DISCUSSION: Radiographic evidence of HO in the knee after reamed tibial IMN is not uncommon and is associated with retained reaming debris, Injury Severity Score, chest injury, intensive care unit admission, and ipsilateral retrograde femoral nailing. No differences were noted in HO formation between approaches. HO was not associated with knee pain or range-of-motion deficits.
The invention aims to disclose a terramycin injection and a preparation method thereof. The terramycin injection comprises the following components of, in every 100 mL, 10-50 g of terramycin, 10-60 g of an organic solvent, 0.1 g-1 g of an anti-oxidant, and the balance being injection water. Compared with a conventional terramycin injection, the terramycin injection provided by the invention has high bioavailability, good curative effect and definite therapeutic effect. Clinic experiments show that the curative effect of the terramycin injection is 3-5 times that of a common terramycin injection. The terramycin injection has stable property, and can keep relatively high biological activity for a long time. The product is simple and easy to prepare, and can be used for industrial large-scale production. The object of the invention is realized.
Patients with posttraumatic, idiopathic, and postinflammatory cause of smell loss; patients age between 18 and 50 years. Odor threshold better than 1.
Approximately 10 to 15% of patients with breast cancer will have a local recurrence after initial conservative treatment or mastectomy. Total mastectomy has historically been the standard treatment for local recurrence. However, the question of reirradiation may arise as part of a second conservative treatment in conjunction with segmentectomy or in the case of chest wall recurrence to improve local control. Different modalities are available: brachytherapy, external beam radiotherapy with or without hyperthermia. Although the carcinologic results are encouraging, this complex situation requires rigorous patient selection and technical requirements to achieve the best local control and limit toxicity events. This article presents a review of the literature on the different indications and techniques for reirradiation of ipsilateral recurrent breast cancer, with the aim of providing decision support in clinical practice.
Riboflavin is recovered in the form of a precipitate of a reduction product of riboflavin from large volumes of solutions of the type commonly encountered in its commercial production by the addition to such solutions, preferably in the presence of an inert gas, of a soluble reducing agent having an E DEG  which is less negative than -0.15 volt to produce in said solution an Eh corresponding to a value between +0.050 and -0.400 volt.  Reducing agents mentioned include titanium trichloride, stannous chloride, sodium dithionite, hypovanadous sulphate, hypovanadous chloride, chromous chloride and chromous sulphate.  In carrying out the invention, the solution containing the riboflavin is first filtered, then treated with the desired reducing agent, preferably at a temperature between 20-30 DEG C. in the appropriate amount to give an Eh which lies within the range set out above. The insoluble reduced form of riboflavin precipitates and is allowed to stand before being separated from the solution.  A preferred method of separation is by the process described in Specification 621,468.  Examples are given of conditions of precipitation and separation of the insoluble reduced riboflavin. In the separation process referred to above it is stated to be an advantage if the precipitation is effected in the presence of a non-absorbent type of finely divided diatomaceous earth. Specification 621,469 is referred to.
OBJECTIVES: We aimed to develop a multi-modality model to predict axillary lymph node (ALN) metastasis by combining clinical predictors with radiomic features from magnetic resonance imaging (MRI) and mammography (MMG) in breast cancer. This model might potentially eliminate unnecessary axillary surgery in cases without ALN metastasis, thereby minimizing surgery-related complications.
METHODS: We retrospectively enrolled 485 breast cancer patients from two hospitals and extracted radiomics features from tumor and lymph node regions on MRI and MMG images. After feature selection, three random forest models were built using the retained features, respectively. Significant clinical factors were integrated with these radiomics models to construct a multi-modality model. The multi-modality model was compared to radiologists' diagnoses on axillary ultrasound and MRI. It was also used to assist radiologists in making a secondary diagnosis on MRI.
RESULTS: The multi-modality model showed superior performance with AUCs of 0.964 in the training cohort, 0.916 in the internal validation cohort, and 0.892 in the external validation cohort. It surpassed single-modality models and radiologists' ALN diagnosis on MRI and axillary ultrasound in all validation cohorts. Additionally, the multi-modality model improved radiologists' MRI-based ALN diagnostic ability, increasing the average accuracy from 70.70 to 78.16% for radiologist A and from 75.42 to 81.38% for radiologist B.
CONCLUSION: The multi-modality model can predict ALN metastasis of breast cancer accurately. Moreover, the artificial intelligence (AI) model also assisted the radiologists to improve their diagnostic ability on MRI.
CLINICAL RELEVANCE STATEMENT: The multi-modality model based on both MRI and mammography images allows preoperative prediction of axillary lymph node metastasis in breast cancer patients. With the assistance of the model, the diagnostic efficacy of radiologists can be further improved.
KEY POINTS: • We developed a novel multi-modality model that combines MRI and mammography radiomics with clinical factors to accurately predict axillary lymph node (ALN) metastasis, which has not been previously reported. • Our multi-modality model outperformed both the radiologists' ALN diagnosis based on MRI and axillary ultrasound, as well as single-modality radiomics models based on MRI or mammography. • The multi-modality model can serve as a potential decision support tool to improve the radiologists' ALN diagnosis on MRI.
PURPOSE:To provide the title bath agent to be used by fitting at a shower mouth, faucet or shower head, designed to dissolve the perfume, etc., therein into water or warm water at a moderate rate, containing a nonionic surfactant with specified HLB. CONSTITUTION:The objective solid bath agent (pref. of tablet shape) containing pref. 0.1-10 (esp. 2-5)wt.% of a nonionic surfactant 2-20 in HLB [pref. a glyceryl fatty acid ester containing in the molecule polyoxyethylene chain (POE), fatty acid ester, alkyl ether, alkylphenyl ether or castor oil]. When used by fitting at the above-mentioned sites, the present bath agent will be dissolved at a moderate rate and the various ingredients such as coloring matter and perfume will be transferred into water or warm water homogeneously. Furthermore, alteration of the kind or amount of the surfactant will freely control the dissolving time for the ingredients.
Caregivers will participate in 6 30-minute skills sessions. A clinical psychologist will deliver all of the sessions. The main intervention goal is to provide dyads with resiliency skills to reduce emotional distress and prevent chronic distress.