Memory impairment in Amyloidß-status Alzheimer's disease is associated with a reduction in CA1 and dentate gyrus volume: In vivo MRI at 7T.

INTRODUCTION: In Alzheimer's disease (AD), early diagnosis facilitates treatment options and leads to beneficial outcomes for patients, their carers and the healthcare system. The neuropsychological battery of the Uniform Data Set (UDSNB3.0) assesses cognition in ageing and dementia, by measuring scores across different cognitive domains such as attention, memory, processing speed, executive function and language. However, its neuroanatomical correlates have not been investigated using 7 Tesla MRI (7T MRI). METHODS: We used 7T MRI to investigate the correlations between hippocampal subfield volumes and the UDSNB3.0 in 24 individuals with Amyloidß-status AD and 18 age-matched controls, with respective age ranges of 60 (42-76) and 62 (52-79) years. AD participants with a Medial Temporal Atrophy scale of higher than 2 on 3T MRI were excluded from the study. RESULTS: A significant difference in the entire hippocampal volume was observed in the AD group compared to healthy controls (HC), primarily influenced by CA1, the largest hippocampal subfield. Notably, no significant difference in whole brain volume between the groups implied that hippocampal volume loss was not merely reflective of overall brain atrophy. UDSNB3.0 cognitive scores showed significant differences between AD and HC, particularly in Memory, Language, and Visuospatial domains. The volume of the Dentate Gyrus (DG) showed a significant association with the Memory and Executive domain scores in AD patients as assessed by the UDSNB3.0.. The data also suggested a non-significant trend for CA1 volume associated with UDSNB3.0 Memory, Executive, and Language domain scores in AD. In a reassessment focusing on hippocampal subfields and MoCA memory subdomains in AD, associations were observed between the DG and Cued, Uncued, and Recognition Memory subscores, whereas CA1 and Tail showed associations only with Cued memory. DISCUSSION: This study reveals differences in the hippocampal volumes measured using 7T MRI, between individuals with early symptomatic AD compared with healthy controls. This highlights the potential of 7T MRI as a valuable tool for early AD diagnosis and the real-time monitoring of AD progression and treatment efficacy. CLINICALTRIALS: GOV: ID NCT04992975 (Clinicaltrial.gov 2023).

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).

Mesothelioma in the pleura, pericardium and peritoneum: Recommendations from the International Collaboration on Cancer Reporting (ICCR).

AIMS: Mesothelioma is a rare malignancy of the serosal membranes that is commonly related to exposure to asbestos. Despite extensive research and clinical trials, prognosis to date remains poor. Consistent, comprehensive and reproducible pathology reporting form the basis of all future interventions for an individual patient, but also ensures that meaningful data are collected to identify predictive and prognostic markers. METHODS AND RESULTS: This article details the International Collaboration on Cancer Reporting (ICCR) process and the development of the international consensus mesothelioma reporting data set. It describes the 'core' and 'non-core' elements to be included in pathology reports for mesothelioma of all sites, inclusive of clinical, macroscopic, microscopic and ancillary testing considerations. An international expert panel consisting of pathologists and a medical oncologist produced a set of data items for biopsy and resection specimens based on a critical review and discussion of current evidence, and in light of the changes in the 2021 WHO Classification of Tumours. The commentary focuses particularly upon new entities such as mesothelioma in situ and provides background on relevant and essential ancillary testing as well as implementation of the new requirement for tumour grading. CONCLUSION: We recommend widespread and consistent implementation of this data set, which will facilitate accurate reporting and enhance the consistency of data collection, improve the comparison of epidemiological data, support retrospective research and ultimately help to improve clinical outcomes. To this end, all data sets are freely available worldwide on the ICCR website (www.iccr-cancer.org/data-sets).

A dedicated structured data set for reporting of invasive carcinoma of the breast in the setting of neoadjuvant therapy: recommendations from the International Collaboration on Cancer Reporting (ICCR).

AIMS: The International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations, is an initiative aimed at providing a unified international approach to reporting cancer. ICCR recently published new data sets for the reporting of invasive breast carcinoma, surgically removed lymph nodes for breast tumours and ductal carcinoma in situ, variants of lobular carcinoma in situ and low-grade lesions. The data set in this paper addresses the neoadjuvant setting. The aim is to promote high-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment that can be used for subsequent management decisions for each patient. METHODS: The ICCR convened expert panels of breast pathologists with a representative surgeon and oncologist to critically review and discuss current evidence. Feedback from the international public consultation was critical in the development of this data set. RESULTS: The expert panel concluded that a dedicated data set was required for reporting of breast specimens post-neoadjuvant therapy with inclusion of data elements specific to the neoadjuvant setting as core or non-core elements. This data set proposes a practical approach for handling and reporting breast resection specimens following neoadjuvant therapy. The comments for each data element clarify terminology, discuss available evidence and highlight areas with limited evidence that need further study. This data set overlaps with, and should be used in conjunction with, the data sets for the reporting of invasive breast carcinoma and surgically removed lymph nodes from patients with breast tumours, as appropriate. Key issues specific to the neoadjuvant setting are included in this paper. The entire data set is freely available on the ICCR website. CONCLUSIONS: High-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment are critical for subsequent management decisions for each patient.

Recommendations of the SUFU/AUGS/ICS Female Stress Urinary Incontinence Surgical Publication Working Group: A common standard minimum data set for the literature.

INTRODUCTION AND OBJECTIVES: Relevant, meaningful, and achievable data points are critical in objectively assessing quality, utility, and outcomes in female stress urinary incontinence (SUI) surgery. A minimum data set female SUI surgery studies was proposed by the first American Urological Association guidelines on the surgical management of female SUI in 1997, but recommendation adherence has been suboptimal. The Female Stress Urinary Incontinence Surgical Publication Working Group (WG) was created from members of several prominent organizations to formulate a recommended standard of study structure, description, and minimum outcome data set to be utilized in designing and publishing future SUI studies. The goal of this WG was to create a body of evidence better able to assess the outcomes of female SUI surgery. METHODS: The WG reviewed the minimum data set proposed in the 1997 AUA SUI Guideline document, and other relevant literature. The body of literature was examined in the context of the profound changes in the field over the past 25 years. Through a DELPHI process, a standard study structure and minimum data set were generated. Care was taken to balance the value of several meaningful and relevant data points against the burden of creating an excessively difficult or restrictive standard that would disincentivize widespread adoption and negatively impact manuscript production and acceptance. RESULTS: The WG outlined standardization in four major areas: (1) study design, (2) pretreatment demographics and characterization of the study population, (3) intraoperative events, and (4) posttreatment evaluation, and complications. Forty-two items were evaluated and graded as: STANDARD-must be included; ADDITIONAL-may be included for a specific study and is inclusive of the Standard items; OPTIMAL-may be included for a comprehensive study and is inclusive of the Standard and Additional items; UNNECESSARY/LEGACY-not relevant. CONCLUSIONS: A reasonable, achievable, and clinically meaningful minimum data set has been constructed. A structured framework will allow future surgical interventions for female SUI to be objectively scrutinized and compared in a clinically significant manner. Ultimately, such a data set, if adopted by the academic community, will enhance the quality of the scientific literature, and ultimately improve short and long-term outcomes for female patients undergoing surgery to correct SUI.

Impact of moderate-to-high-suicide-intent in major depressive disorder: a retrospective cohort study on patient characteristics and healthcare resource utilisation in England.

BACKGROUND: Major depressive disorder (MDD) is a disabling mental illness that can affect all aspects of daily life and is a leading cause of healthcare resource utilisation (HCRU). AIMS: We aimed to characterise patients with MDD with moderate-to-high-suicide-intent, compare their HCRU to patients with MDD without moderate-to-high-suicide-intent, and better understand their patient pathways. METHODS: This retrospective cohort study used data collected from primary care electronic health records from Clinical Practice Research Datalink (CPRD), linked to Hospital Episode Statistics, Mental Health Services Data Set, and Office for National Statistics in England. Adults diagnosed with ≥ 1 MDD diagnosis between 04/2007 and 11/2015 were categorised by suicide intent. RESULTS: 307,476 patients with MDD were included (294,259 patients without moderate-to-high-suicide-intent and 13,217 with moderate-to-high-suicide-intent). Patients with MDD with moderate-to-high-suicide-intent were younger on average (39.0 vs. 44.8 years) and included a lower percentage of females (58% vs. 65%) compared to patients without moderate-to-high-suicide-intent. HCRU was greater among patients with moderate-to-high-suicide-intent than patients without moderate-to-high-suicide-intent during the first follow-up year for general practitioner consultations (38.5 vs. 29.4), psychiatric outpatient visits (1.5 vs. 0.1), psychiatrist visits (3.6 vs. 0.3), emergency visits (1.5 vs. 0.3), and hospitalisations (86% vs. 26%). Overall, 56% of patients with moderate-to-high-suicide-intent had an antidepressant prescription within 30 days from the initial moderate-to-high-suicide-intent. CONCLUSIONS: Patients with MDD and moderate-to-high-suicide-intent were younger, included more males and incurred greater HCRU than those without moderate-to-high-suicide-intent. These results suggest a greater need for effective medical care and appropriate treatments for patients with moderate-to-high-suicide-intent, which could help reduce associated symptoms, mortality, and HCRU.

Designing a core data set for benign hysterectomy registration system and its implementation in a referral teaching hospital in Northwest Iran.

BACKGROUND AND AIMS: Although minimally invasive hysterectomy offers advantages, abdominal hysterectomy remains the predominant surgical method. Creating a standardized dataset and establishing a hysterectomy registry system present opportunities for early interventions in reducing volume and selecting benign hysterectomy methods. This research aims to develop a dataset for designing benign hysterectomy registration system. METHODS: Between April and September 2020, a qualitative study was carried out to create a data set for enrolling patients who were candidate for hysterectomy. At this stage, the research team conducted an information needs assessment, relevant data element identification, registry software development, and field testing; Subsequently, a web-based application was designed. In June 2023the registry software was evaluated using data extracted from medical records of patients admitted at Al-Zahra Hospital in Tabriz, Iran. RESULTS: During two months, 40 patients with benign hysterectomy were successfully registered. The final dataset for the hysterectomy patient registry comprise 11 main groups, 27 subclasses, and a total of 91 Data elements. Mandatory data and essential reports were defined. Furthermore, a web-based registry system designed and evaluated based on data set and various scenarios. CONCLUSION: Creating a hysterectomy registration system is the initial stride toward identifying and registering hysterectomy candidate patients. this system capture information about the procedure techniques, and associated complications. In Iran, this registry can serve as a valuable resource for assessing the quality of care delivered and the distribution of clinical measures.

Establishing Quality Indicators and Implementation Priorities for Post-Stroke Aphasia Services Through End-User Involvement.

BACKGROUND: Currently, there are no agreed quality standards for post-stroke aphasia services. Therefore, it is unknown if care reflects best practices or meets the expectations of people living with aphasia. We aimed to (1) shortlist, (2) operationalise and (3) prioritise best practice recommendations for post-stroke aphasia care. METHODS: Three phases of research were conducted. In Phase 1, recommendations with strong evidence and/or known to be important to people with lived experience of aphasia were identified. People with lived experience and health professionals rated the importance of each recommendation through a two-round e-Delphi exercise. Recommendations were then ranked for importance and feasibility and analysed using a graph theory-based voting system. In Phase 2, shortlisted recommendations from Phase 1 were converted into quality indicators for appraisal and voting in consensus meetings. In Phase 3, priorities for implementation were established by people with lived experience and health professionals following discussion and anonymous voting. FINDINGS: In Phase 1, 23 best practice recommendations were identified and rated by people with lived experience (n = 26) and health professionals (n = 81). Ten recommendations were shortlisted. In Phase 2, people with lived experience (n = 4) and health professionals (n = 17) reached a consensus on 11 quality indicators, relating to assessment (n = 2), information provision (n = 3), communication partner training (n = 3), goal setting (n = 1), person and family-centred care (n = 1) and provision of treatment (n = 1). In Phase 3, people with lived experience (n = 5) and health professionals (n = 7) identified three implementation priorities: assessment of aphasia, provision of aphasia-friendly information and provision of therapy. INTERPRETATION: Our 11 quality indicators and 3 implementation priorities are the first step to enabling systematic, efficient and person-centred measurement and quality improvement in post-stroke aphasia services. Quality indicators will be embedded in routine data collection systems, and strategies will be developed to address implementation priorities. PATIENT AND PUBLIC CONTRIBUTION: Protocol development was informed by our previous research, which explored the perspectives of 23 people living with aphasia about best practice aphasia services. Individuals with lived experience of aphasia participated as expert panel members in our three consensus meetings. We received support from consumer advisory networks associated with the Centre for Research Excellence in Aphasia Rehabilitation and Recovery and the Queensland Aphasia Research Centre.

The first national pediatric immune thrombocytopenia registry in Iran: research protocol and preliminary study results.

BACKGROUND: Disease registries are comprehensive databases that record detailed information on patients diagnosed with specific conditions, providing valuable insights into their diagnosis, treatment, and outcomes. This study aims to describe the pilot phase of the national pediatric Immune Thrombocytopenia(ITP) registry (NPITP) in Iran, serving as the inaugural interpretive report. METHODS: This patient-centered software system was implemented as a national program across multiple pediatric centers in Iran. Several focus groups were conducted to establish a minimum data set (MDS) comprising six main classes, 14 sub-classes, and 187 data elements. Following expert consensus on the final data set, a web-based software tool was developed by the dedicated IT team, accessible online and offline via https://disreg.sbmu.ac.ir/q/ITP.html . The registry included children aged between two months and 18 years with a platelet count below 100 × 109/L, based on predefined inclusion criteria. RESULTS: Within a four-month period, a total of 60 ITP patients were registered, including 41 (68.3%) newly diagnosed cases, 68 (13.6%) persistent cases, and 14 (23.3%) with chronic ITP. The mean age of the registered patients was 55.93 ± 9.72 months. The most frequently observed bleeding symptoms were petechiae (68.3%), purpura (51.6%), and ecchymosis (13.3%). Among the newly diagnosed patients, 20 (33.3%) received intravenous immunoglobulin (IVIG), 17 (28.3%) were treated with prednisolone, and 17 (28.3%) received combined IVIG and steroid therapy. Of all patients, 40 (66.7%) demonstrated a complete response to treatment, while 16 (26.7%) exhibited a partial response. Four patients (6.7%) remained unresponsive to therapy. Treatment-related complications, such as Cushing's syndrome, edema, weight gain, hirsutism, and mood disorders, were reported in 10 patients (16.6%). However, the majority of patients (81.7%) did not experience therapy-related complications. CONCLUSION: The pilot phase of the NPITP registry successfully implemented a web-based software tool for data collection, aiming to enhance the quality of care, facilitate clinical research, and support health service planning in the future.

Determining the minimum data set of geriatric assessment at the Iran primary health care referral system: shifting from fragmentation to integration care for older people.

BACKGROUND: Geriatric assessment (GA) is a multidimensional process that disrupts the primary health care (PHC) referral system. Accessing consistent data is central to the provision of integrated geriatric care across multiple healthcare settings. However, due to poor-quality data and documentation of GA, developing an agreed minimum data set (MDS) is required. Therefore, this study aimed to develop a GA-MDS in the PHC referral system to improve data quality, data exchange, and continuum of care to address the multifaceted necessities of older people. METHODS: In our study, the items to be included within GA-MDS were determined in a three-stepwise process. First, an exploratory literature search was done to determine the related items. Then, we used a two-round Delphi survey to obtain an agreement view on items to be contained within GA-MDS. Finally, the validity of the GA-MDS content was evaluated. RESULTS: Sixty specialists from different health geriatric care disciplines scored data items. After, the Delphi phase from the 230 selected items, 35 items were removed by calculating the content validity index (CVI), content validity ratio (CVR), and other statistical measures. Finally, GA-MDS was prepared with 195 items and four sections including administrative data, clinical, physiological, and psychological assessments. CONCLUSIONS: The development of GA-MDS can serve as a platform to inform the geriatric referral system, standardize the GA process, and streamline their referral to specialized levels of care. We hope GA-MDS supports clinicians, researchers, and policymakers by providing aggregated data to inform medical practice and enhance patient-centered outcomes.

Transforming Digital Phenotyping Raw Data Into Actionable Biomarkers, Quality Metrics, and Data Visualizations Using Cortex Software Package: Tutorial.

As digital phenotyping, the capture of active and passive data from consumer devices such as smartphones, becomes more common, the need to properly process the data and derive replicable features from it has become paramount. Cortex is an open-source data processing pipeline for digital phenotyping data, optimized for use with the mindLAMP apps, which is used by nearly 100 research teams across the world. Cortex is designed to help teams (1) assess digital phenotyping data quality in real time, (2) derive replicable clinical features from the data, and (3) enable easy-to-share data visualizations. Cortex offers many options to work with digital phenotyping data, although some common approaches are likely of value to all teams using it. This paper highlights the reasoning, code, and example steps necessary to fully work with digital phenotyping data in a streamlined manner. Covering how to work with the data, assess its quality, derive features, and visualize findings, this paper is designed to offer the reader the knowledge and skills to apply toward analyzing any digital phenotyping data set. More specifically, the paper will teach the reader the ins and outs of the Cortex Python package. This includes background information on its interaction with the mindLAMP platform, some basic commands to learn what data can be pulled and how, and more advanced use of the package mixed with basic Python with the goal of creating a correlation matrix. After the tutorial, different use cases of Cortex are discussed, along with limitations. Toward highlighting clinical applications, this paper also provides 3 easy ways to implement examples of Cortex use in real-world settings. By understanding how to work with digital phenotyping data and providing ready-to-deploy code with Cortex, the paper aims to show how the new field of digital phenotyping can be both accessible to all and rigorous in methodology.

Lane Attribute Classification Based on Fine-Grained Description.

As an indispensable part of the vehicle environment perception task, road traffic marking detection plays a vital role in correctly understanding the current traffic situation. However, the existing traffic marking detection algorithms still have some limitations. Taking lane detection as an example, the current detection methods mainly focus on the location information detection of lane lines, and they only judge the overall attribute of each detected lane line instance, thus lacking more fine-grained dynamic detection of lane line attributes. In order to meet the needs of intelligent vehicles for the dynamic attribute detection of lane lines and more perfect road environment information in urban road environment, this paper constructs a fine-grained attribute detection method for lane lines, which uses pixel-level attribute sequence points to describe the complete attribute distribution of lane lines and then matches the detection results of the lane lines. Realizing the attribute judgment of different segment positions of lane instances is called the fine-grained attribute detection of lane lines (Lane-FGA). In addition, in view of the lack of annotation information in the current open-source lane data set, this paper constructs a lane data set with both lane instance information and fine-grained attribute information by combining manual annotation and intelligent annotation. At the same time, a cyclic iterative attribute inference algorithm is designed to solve the difficult problem of lane attribute labeling in areas without visual cues such as occlusion and damage. In the end, the average accuracy of the proposed algorithm reaches 97% on various types of lane attribute detection.

Medical needs during the Kumamoto heavy rain 2020: analysis from emergency medical teams' responses.

BACKGROUND: Rainfall-induced floods represented 70% of the disasters in Japan from 1985 to 2018 and caused various health problems. To improve preparedness and preventive measures, more information is needed on the health problems caused by heavy rain. However, it has proven challenging to collect health data surrounding disasters due to various inhibiting factors such as environmental hazards and logistical constraints. In response to the Kumamoto Heavy Rain 2020, Emergency Medical Teams (EMTs) used J-SPEED (Japan-Surveillance in Post Extreme Emergencies and Disasters) as a daily reporting tool, collecting patient data and sending it to an EMTCC (EMT Coordination Cell) during the response. We performed a descriptive epidemiological analysis using J-SPEED data to better understand the health problems arising from the Kumamoto Heavy Rain 2020 in Japan. METHODS: During the Kumamoto Heavy Rain 2020 from July 5 to July 31, 2020, 79 EMTs used the J-SPEED form to submit daily reports to the EMTCC on the number and types of health problems they treated. We analyzed the 207 daily reports, categorizing the data by age, gender, and time period. RESULTS: Among the 816 reported consultations, women accounted for 51% and men accounted for 49%. The majority of patients were elderly (62.1%), followed by adults (32.8%), and children (5%). The most common health issues included treatment interruption (12.4%), hypertension (12.0%), wounds (10.8%), minor trauma (9.6%), and disaster-related stress symptoms (7.4%). Consultations followed six phases during the disaster response, with the highest occurrence during the hyperacute and acute phases. Directly disaster-related events comprised 13.9% of consultations, indirectly related events comprised 52.0%, and unrelated events comprised 34.0%. As the response phases progressed, the proportions of directly and indirectly related events decreased while that of unrelated events increased. CONCLUSION: By harnessing data captured by J-SPEED, this research demonstrates the feasibility of collecting, quantifying, and analyzing data using a uniform format. Comparison of the present findings with those of two previous analyses of J-SPEED data from other disaster scenarios that varied in time, location, and/or disaster type showcases the potential to use analysis of past experiences to advancing knowledge on disaster medicine and disaster public health.

Retention of American Indian and Alaska Native participants in the National Alzheimer's Coordinating Center Uniform Data Set.

INTRODUCTION: The number of American Indian and Alaska Native (AI/AN) elders is expected to double by 2060. Thus it is imperative to retain AI/AN participants in longitudinal research studies to identify novel risk factors and potential targets for intervention for Alzheimer's disease and related dementias in these communities. METHODS: The National Alzheimer's Coordinating Center houses uniformly collected longitudinal data from the network of National Institute on Aging (NIA)-funded Alzheimer's Disease Research Centers (ADRCs). We used logistic regression to quantify participant retention at 43 ADRCs, comparing self-identified AI/AN participants to non-Hispanic White (NHW) participants, adjusting for potential confounding factors including baseline diagnosis, age, sex, education, and smoking. RESULTS: The odds of AI/AN participant retention at the first follow-up visit were significantly lower than those for NHW participants (adjusted odds ratio [aOR]: 0.599; 95%: 0.46-0.78; p < 0.001). DISCUSSION: These results suggest the need for improved strategies to retain AI/AN participants, perhaps including improved researcher-community relationships and community engagement and education. HIGHLIGHTS: American Indian and Alaska Native (AI/AN) research participants were retained to the first follow-up appointment at lower rates than non-Hispanic White (NHW) participants. AI/AN participants are retained at lower rates than NHW participants for long-term follow-up. The majority of AI/AN participants were not retained to the second follow-up visit.

Individualized digitally designed surgical template for guided soft tissue surgery in cases with severe gingival enlargement: A clinical application in hereditary gingival fibromatosis.

AIM: The purpose of this study was to present the use of computer-assisted periodontal surgery utilizing a novel surgical guide for cases with severe gingival enlargement through a clinical application in a patient with hereditary gingival fibromatosis. MATERIALS AND METHODS: The treatment plan included nonsurgical periodontal therapy, surgical periodontal treatment, and regular periodontal maintenance before the initiation of orthodontic treatment. Due to the increased soft tissue thickness, a surgical guide with a novel design was fabricated to facilitate the periodontal surgery since most of the patient's teeth were malpositioned and underexposed due to fibromatosis. For this purpose, the patient's intraoral scan was merged with a CBCT image in order to plan surgical excisions based on the anatomy of the teeth and the bone contour. RESULTS: The customized surgical guide facilitated the gingivectomy by controlling not only the shape of the initial incisions but also their orientation toward the level of the cementoenamel junction, improving the efficiency of the clinical time compared with freehand surgery and assisting in the verification of the final soft tissue shape, based on the treatment plan. CONCLUSION: Digital technology through the superimposition of multiple data sets can assist in the diagnosis and multidisciplinary management of cases with gingival fibromatosis. The proposed design of the surgical guide can facilitate soft tissue surgery based on the digital treatment plan, leading to more predictable management of the soft tissue, especially in patients with severe gingival enlargement, as in cases with hereditary gingival fibromatosis or drug-induced gingival overgrowth.

Comparative assessment of soil quality dynamics using SQI modelling approach: a study in rice bowl of West Bengal, India.

The study attempted to evaluate the agricultural soil quality using the Soil Quality Index (SQI) model in two Community Development Blocks, Ausgram-II and Memari-II of Purba Bardhaman District. Total 104 soil samples were collected (0-20 cm depth) from each Block to analyse 13 parameters (bulk density, soil porosity, soil aggregate stability, water holding capacity, infiltration rate, available nitrogen, available phosphorous, available potassium, soil pH, soil organic carbon, electrical conductivity, soil respiration and microbial biomass carbon) in this study. The Integrated Quality Index (IQI) was applied using the weighted additive approach and non-linear scoring technique to retain the Minimum Data Set (MDS). Principal Component Analysis (PCA) identified that SAS, BD, available K, pH, available N, and available P were the key contributing parameters to SQI in Ausgram-II. In contrast, WHC, SR, available N, pH, and SAS contributed the most to SQI in Memari-II. Results revealed that Ausgram-II (0.97) is notably higher SQI than Memari-II (0.69). In Ausgram-II, 99.72% of agricultural lands showed very high SQI (Grade I), whereas, in Memari-II, 49.95% of lands exhibited a moderate SQI (Grade III) and 49.90% showed a high SQI (Grade II). Sustainable Yield Index (SYI), Sensitivity Index (SI) and Efficiency Ratio (ER) were used to validate the SQIs. A positive correlation was observed between SQI and paddy ( R2 = 0.82 & 0.72) and potato yield (R2 = 0.71 & 0.78) in Ausgram-II and Memari-II Block, respectively. This study could evaluate the agricultural soil quality and provide insights for decision-making in fertiliser management practices to promote agricultural sustainability.

Impacts of land use and management methods on soil quality dynamics in central highlands of Ethiopia.

Land degradation often results in poor soil quality in many parts of Ethiopia, including the study area. To address this issue and promote sustainable land management practices, various land use and management methods (LUMMs) have been implemented. However, little information is available regarding how these management practices influence overall soil quality dynamics of the study area. This study aimed at evaluating soil quality dynamics in the Urago micro-watershed, central highlands of Ethiopia, under major LUMMs: barren land (BL), grassland (GL), established farm boundary (EFB), restored degraded land (RDL), and stone-supported soil bund (SSB). Forty-five disturbed and fifteen undisturbed soil samples were collected from the ploughed soil layer (0-20 cm) of each LUMM and analysed for selected physicochemical properties to be used as indicators of soil quality. Principal component analysis and multiple correlation were used to select the minimum data set (MDS) to evaluate the overall soil quality index (SQI). The MDS included SOC, clay content, exchangeable Mg2+, and available P, which could replace other indicators for assessing the overall soil quality dynamics of the study watershed. The result showed notable variations in particle-size fractions, soil organic carbon (SOC), total nitrogen (TN), available P (av. P), and exchangeable Na+, K+, and Mg2+ levels among the LUMMs. RDL had higher sand and silt contents than SSB, whereas SSB had higher clay content compared to RDL, GL, and BL. GL, RDL, and EFB showed significantly higher levels of SOC, TN, and av. P, respectively, compared to other LUMMs. The obtained SQI showed that GL had the highest score (0.847), followed by SSB (0.703), RDL (0.701), EFB (0.644), and BL (0.628). This underscores the significance of stone-supported soil bund and restored degraded land as an efficient management method to enhance soil quality and agro-ecosystem through conserving soil and encouraging sustainable farming practices.

Dental age estimation: development and testing of a reference data set for Qatari children, adolescents, and young adults aged between 5 and 25 years.

The purpose of this study is to establish and test a reference data set of dental development of Qatari subjects aged between 5 and 25 years. Radiographs of individuals aged between 5 and 25 years were re-used to establish a reference data set (RDS). A scheme comprising 8 tooth development stages (TDS) was used to assess all the teeth on the left side of the maxilla and mandible. The accuracy of dental age estimation (DAE) was tested with a separate sample of radiographs - the validation sample (VS) comprised 50 females and 50 males of known chronological age (CA). Dental panoramic tomographs (DPT) of 1,597 Qataris were assessed. The summary data for the individual TDS comprising the number (n-tds), mean ( x ¯ -tds), standard deviation (sd-tds), 0th%-ile (the minimum), 25th%-ile, 50th%-ile (the median), 75th%-ile, and 100th%-ile (the maximum) were used to estimate the age of the VS subjects using the simple average method (SAM). There is a significant difference in dental age of 4.8 months in the female group when compared to the CA. The difference in the male group is 4.5 months. This shows similar differences to assessments of other ancestral or ethnic groups.

Integration and segregation manifolds in the brain ensure cognitive flexibility during tasks and rest.

Adapting to a constantly changing environment requires the human brain to flexibly switch among many demanding cognitive tasks, processing both specialized and integrated information associated with the activity in functional networks over time. In this study, we investigated the nature of the temporal alternation between segregated and integrated states in the brain during rest and six cognitive tasks using functional MRI. We employed a deep autoencoder to explore the 2D latent space associated with the segregated and integrated states. Our results show that the integrated state occupies less space in the latent space manifold compared to the segregated states. Moreover, the integrated state is characterized by lower entropy of occupancy than the segregated state, suggesting that integration plays a consolidating role, while segregation may serve as cognitive expertness. Comparing rest and the tasks, we found that rest exhibits higher entropy of occupancy, indicating a more random wandering of the mind compared to the expected focus during task performance. Our study demonstrates that both transient, short-lived integrated and segregated states are present during rest and task performance, flexibly switching between them, with integration serving as information compression and segregation related to information specialization.

Multidisciplinary recommendations for essential baseline functional and laboratory tests to facilitate early diagnosis and management of immune-related adverse events among cancer patients.

Immune checkpoint inhibitors (ICIs) have fundamentally changed the treatment landscape of various cancers. While ICI treatments result in improved survival, quality of life and are cost-effective, the majority of patients experience at least one immune-related adverse event (irAE). Many of these side effects cause little discomfort or are asymptomatic; however, irAEs can affect any organ and are potentially life-threatening. Consequently, early diagnosis and appropriate treatment of irAEs are critical for optimizing long-term outcomes and quality of life in affected patients. Some irAEs are diagnosed according to typical symptoms, others by abnormal findings from diagnostic tests. While there are various guidelines addressing the management of irAEs, recommendations for the early recognition of irAEs as well as the optimal extent and frequency of laboratory tests are mostly lacking. In clinical practice, blood sampling is usually performed before each ICI administration (i.e., every 2-3 weeks), often for several months, representing a burden for patients as well as health care systems. In this report, we propose essential laboratory and functional tests to improve the early detection and management of irAEs and in cancer patients treated with ICIs. These multidisciplinary expert recommendations regarding essential laboratory and functional tests can be used to identify possible irAEs at an early time point, initiate appropriate interventions to improve patient outcomes, and reduce the burden of blood sampling during ICI treatment.