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Neuroimaging is a powerful tool to investigate potential associations between chronic pain and brain structure. However, the proliferation of studies across diverse chronic pain syndromes and heterogeneous results challenges data integration and interpretation. We conducted a preregistered anatomical likelihood estimate meta-analysis on structural magnetic imaging studies comparing patients with chronic pain and healthy controls. Specifically, we investigated a broad range of measures of brain structure as well as specific alterations in gray matter and cortical thickness. A total of 7849 abstracts of experiments published between January 1, 1990, and April 26, 2021, were identified from 8 databases and evaluated by 2 independent reviewers. Overall, 103 experiments with a total of 5075 participants met the preregistered inclusion criteria. After correction for multiple comparisons using the gold-standard family-wise error correction ( P < 0.05), no significant differences associated with chronic pain were found. However, exploratory analyses using threshold-free cluster enhancement revealed several spatially distributed clusters showing structural alterations in chronic pain. Most of the clusters coincided with regions implicated in nociceptive processing including the amygdala, thalamus, hippocampus, insula, anterior cingulate cortex, and inferior frontal gyrus. Taken together, these results suggest that chronic pain is associated with subtle, spatially distributed alterations of brain structure.

Background: In Cerebral Vascular Disease when one or more arteries are thrombosed it results in Cerebral Venous Sinus Thrombosis (CVST) and affects in all ages. This condition is very challenging as it is not diagnosed early due to diverse signs and symptoms and involvement of extensive collateral circulation. Superior sagittal sinus is a large sinus which is commonly affected. Usually, patient comes with clinical presentation of headache with papilledema, to focal deficit, seizures and coma. Aim: To investigate the efficacy of Physiotherapy Rehabilitation for Hemiparesis following Cerebral Venous Sinus Thrombosis. Presentation of Case: A 18-year-old male patient presented with a history of severe headache, weakness in his right arm and leg, dizziness upon rising from bed, and a unilateral headache. On investigation CT scan and MRI brain was done. The physiotherapy has started from 2 days after admission in AVBRH. Discussion: In the cases of cerebral venous sinus thrombosis the management of hemiparesis is shown to enhance the ADL and quality of life of patients. Conclusion: The rehabilitation protocol planned will help in improving the range of motion and ADL of patient when started as early as possible.

Despite the increase in assisted reproductive technologies, the high rates of infertility and pregnancy complications are a major concern to infertility specialists worldwide. Infertility may be attributed to pregnancy complications like thrombophilia, preeclampsia and fibrin-induced recurrent pregnancy loss (RPL). Renin-angiotensin-aldosterone system (RAAS) directly or indirectly causes preeclampsia and thrombophilia through the fibrinolytic pathway that ultimately leads to RPL or infertility. The underlying mechanisms of this interaction are still unclear. The present comprehensive review is intended to demonstrate the role and interaction of RAAS and fibrinolytic pathways in pregnancy complications. How this interaction can induce pregnancy complications, and ultimately infertility, is also discussed in the light of current evidence. This study also presents common markers that link RAAS and fibrinolytic processes in developing thrombophilia, preeclampsia and RPL. The common link in these pathways is ACE gene I/D polymorphism. Apart from ACE, PAI-1, VIIa, XIIa, AT1R, AT1AA, and TF are common molecules that can delineate the underlying causes of pregnancy complications and infertility.

Heterogeneity in physician practice within nursing homes (NHs) may explain variations in quality. However, data on physician practice organization in NHs are hard to obtain. We characterized NH physician practice using two claims-based measures: (a) concentration of NH care among physicians (measured by Herfindahl–Hirschman index of visits); and (b) physician NH practice specialization (measured by the proportion of a physician’s visits to NHs). We examined the relationship between the measures and NH administrator perceptions of physician practice reported in the Shaping Long-Term Care in America (SLTCA) Survey. All 2011 Part B claims from 13,718 physicians who treated Medicare fee-for-service patients in 2,095 NHs in the SLTCA survey were analyzed. The median Herfindahl–Hirschman index was 0.44 (interquartile range [IQR] 0.28-0.70), and the median specialization was 38.1% (IQR 19.9% to 60.9%). NHs with higher physician specialization reported more frequent physician participation in care coordination activities. Claims-based measures could inform the study of NH physician practice.

BackgroundWild-type transthyretin amyloidosis (ATTRwt) is an underdiagnosed and potentially fatal disease. Interestingly, ATTRwt deposits have been found to deposit in the ligamentum flavum (LF) of patients with lumbar spinal stenosis prior to the development of systemic and cardiac amyloidosis. In order to study this phenomenon and its possible relationship with LF thickening and systemic amyloidosis, a precise method of quantifying amyloid deposits in histological slides of LF is critical. However, such a method is currently unavailable. Here, we present a machine learning quantification method with Trainable Weka Segmentation (TWS) to assess amyloid deposition in histological slides of LF.MethodsImages of ligamentum flavum specimens stained with Congo red are obtained from spinal stenosis patients undergoing laminectomies and confirmed to be positive for ATTRwt. Amyloid deposits in these specimens are classified and quantified by TWS through training the algorithm via user-directed annotations on images of LF. TWS can also be automated through exposure to a set of training images with user-directed annotations, and then application to a set of new images without additional annotations. Additional methods of color thresholding and manual segmentation are also used on these images for comparison to TWS.ResultsWe develop the use of TWS in images of LF and demonstrate its potential for automated quantification. TWS is strongly correlated with manual segmentation in the training set of images with user-directed annotations (R = 0.98; p = 0.0033) as well as in the application set of images where TWS was automated (R = 0.94; p = 0.016). Color thresholding was weakly correlated with manual segmentation in the training set of images (R = 0.78; p = 0.12) and in the application set of images (R = 0.65; p = 0.23).ConclusionTWS machine learning closely correlates with the gold standard comparator of manual segmentation and outperforms the color thresholding method. This novel machine learning method to quantify amyloid deposition in histological slides of ligamentum flavum is a precise, objective, accessible, high throughput, and powerful tool that will hopefully pave the way towards future research and clinical applications.

Characterizing a reliable, pain-related neural signature is critical for translational applications. Many prior fMRI studies have examined acute pain-related brain activation in healthy participants. However, synthesizing these data to identify convergent patterns of activation can be challenging due to the heterogeneity of experimental designs and samples. To address this challenge, we conducted a comprehensive meta-analysis of fMRI studies of stimulus-induced pain in healthy participants. Following pre-registration, two independent reviewers evaluated 4,927 abstracts returned from a search of 8 databases, with 222 fMRI experiments meeting inclusion criteria. We analyzed these experiments using Activation Likelihood Estimation with rigorous type I error control (voxel height p < 0.001, cluster p < 0.05 FWE-corrected) and found a convergent, largely bilateral pattern of pain-related activation in the secondary somatosensory cortex, insula, midcingulate cortex, and thalamus. Notably, these regions were consistently recruited regardless of stimulation technique, location of induction, and participant sex. These findings suggest a highly-conserved core set of pain-related brain areas, encouraging applications as a biomarker for novel therapeutics targeting acute pain.HIGHLIGHTSPain stimulation recruits a core set of pain-related brain regions.This core set includes thalamus, SII, insula and mid-cingulate cortex.These regions were recruited regardless of stimulus modality and stimulus location.

Characterizing a reliable, pain-related neural signature is critical for translational applications. Many prior fMRI studies have examined acute nociceptive pain-related brain activation in healthy participants. However, synthesizing these data to identify convergent patterns of activation can be challenging due to the heterogeneity of experimental designs and samples. To address this challenge, we conducted a comprehensive meta-analysis of fMRI studies of stimulus-induced pain in healthy participants. Following pre-registration, two independent reviewers evaluated 4,927 abstracts returned from a search of 8 databases, with 222 fMRI experiments meeting inclusion criteria. We analyzed these experiments using Activation Likelihood Estimation with rigorous type I error control (voxel height p < 0.001, cluster p < 0.05 FWE-corrected) and found a convergent, largely bilateral pattern of pain-related activation in the secondary somatosensory cortex, insula, midcingulate cortex, and thalamus. Notably, these regions were consistently recruited regardless of stimulation technique, location of induction, and participant sex. These findings suggest a highly-conserved core set of pain-related brain areas, encouraging applications as a biomarker for novel therapeutics targeting acute nociceptive pain.

This meta-analysis assesses differential brain responses to noxious stimuli in patients with chronic pain using functional magnetic resonance imaging while adhering to current best practices for neuroimaging meta-analyses., Key Points Question Do the brains of patients with chronic pain respond differently to noxious stimuli? Findings This systematic review and meta-analysis of 37 experiments from 29 unique articles including 944 participants found that patients with chronic pain were not associated with significant differential responses to noxious stimuli that induce pain compared with healthy controls. Meaning Chronic pain does not appear to be associated with consistent marked alterations in the brain’s response to noxious stimuli., Importance Functional neuroimaging is a valuable tool for understanding how patients with chronic pain respond to painful stimuli. However, past studies have reported heterogenous results, highlighting opportunities for a quantitative meta-analysis to integrate existing data and delineate consistent associations across studies. Objective To identify differential brain responses to noxious stimuli in patients with chronic pain using functional magnetic resonance imaging (fMRI) while adhering to current best practices for neuroimaging meta-analyses. Data Sources All fMRI experiments published from January 1, 1990, to May 28, 2019, were identified in a literature search of PubMed/MEDLINE, EMBASE, Web of Science, Cochrane Library, PsycINFO, and SCOPUS. Study Selection Experiments comparing brain responses to noxious stimuli in fMRI between patients and controls were selected if they reported whole-brain results, included at least 10 patients and 10 healthy control participants, and used adequate statistical thresholding (voxel-height P

Terrorism is evolving rapidly, and with the technological advancements new threats are emerging from the ‘World of Terror'. Now, it has become crucial than ever to evaluate and channelise our capabilities to curb terrorism. This article evaluates the basics of human behaviour and how it can be tactically used against terrorism. The author has also addressed an important question often raised among the terrorism research community — ‘Who becomes a terrorist?'.

Advancements in the computing realm have assisted the Architecture, Engineering, and Construction (AEC) industry to progress significantly by automating several design tasks and activities. Building Information Modelling (BIM) authoring tools have played a significant role in automating design tasks and reducing the efforts required by the designer in redundant, repetitive or production-oriented activities. This paper explores one such approach that, with the help of BIM authoring tool and its Application Programming Interface (API), reduces the efforts expended on formwork design for concrete structures. The paper utilises the concept of using BIM data as input to compute the quantity of formwork, and generate visualisations and schedule of formwork. The developed approach first takes data input from semantic BIM to the API environment for computation and design of formwork systems, which is then placed within the BIM model, to generate visualisation and prepare schedules. The research work utilises a structural concrete wall as an example to demonstrate the presented approach. The approach will be influential in streamlining the formwork design process in the BIM environment and reducing efforts required by the designer and the planning engineer. Since the formwork elements are generated as 3-Dimensional (3D) solids and smart BIM elements, the generated model of formwork can be used for resolving clashes, scheduling, and resource planning.