Miracle-dz/UniFAR-FTUs huggingface dataset:
The psychophysiological response during post-traumatic stress disorder treatment with modular motion-assisted memory desensitisation and reconsolidation (3MDR)

ABSTRACT Background: Psychophysiological changes are part of post-traumatic stress disorder (PTSD) symptomatology and can signal emotional engagement during psychological treatment. Objectives: The aim of this study was to explore psychophysiological responses during multi‐modular motion‐assisted memory desensitization and reconsolidation (3MDR) therapy. Increased self-reported distress, substantially increased heart rate (HR) and breathing rate (BR) were expected at the start of therapy and predicted to improve over time. Since physical exercise demands during therapy were low, any large HR or BR responses were considered part of the psychophysiological response. Methods: This study used pooled data collected during a randomized controlled trial of 3MDR, which demonstrated significant improvement as measured by the Clinician Administered PTSD Scale. Whilst attending therapy, HR and BR data, subjective units of distress (SUD) score and phrases to describe feelings whilst exposed to trauma-related images were collected continuously from 37 UK male military veterans with PTSD. Results: HR and BR were significantly increased throughout all sessions (p < .01 for both). Whilst HR was raised slightly remaining on average below 100 beats/minute, BR was increased substantially with average values between 40 and 50 breaths/minute. SUD scores were very high during therapy which concurred with the many negative feelings experienced during therapy sessions. Across the course of the treatment, SUD scores (p < .01) and negative feelings were reduced (p < .001), and positive feelings have increased (p < .01) significantly, reflecting improvements in clinicians assessed PTSD symptoms. Across therapy sessions, HR (p = .888) and BR (p = .466) responses did not change. Conclusions: The strong psychophysiological response alongside high levels of self-reported distress and negative feelings is interpreted as high emotional engagement during therapy. A novel finding was the very significant BR increase throughout recorded sessions. Future PTSD research should include BR response to therapy and explore breathing control as a treatment target.
Central Pain in Parkinson's Disease: Behavioral and Cognitive Characteristics

Introduction Pain is a major nonmotor symptom of Parkinson's disease (PD), and central parkinsonian pain is the core feature of the putative Park pain subtype of PD. This study aimed to explore the cognitive and behavioral profile of PD patients with central parkinsonian pain. Material and Methods. A structured interview was used to identify and characterize pain in a cohort of 260 consecutive PD patients. The Ford classification of pain was applied. The Dementia Rating Scale-2 (DRS-2) and the Impulse Control Disorders in Parkinson's Disease Short Form (QUIP-S) were administered, and patients' smoking habits were recorded. The Unified Parkinson's Disease Rating Scale (UPDRS) was used to assess motor and nonmotor symptoms in off and on conditions. Results One hundred and eighty-eight patients (68%) reported pain; and in 41 (22%) of them, the pain was classified as central parkinsonian pain. PD patients with central parkinsonian pain had better cognitive performance in DRS-2 Initiation/Perseveration and Conceptualization subscales but reported more other compulsive behaviors (e.g., hobbyism, punding, and walkabout) and had more current smoking habits than those without pain or with non-central parkinsonian pain. Multiple logistic regression analyses revealed that the DRS-2 Conceptualization subscale, other compulsive behaviors, and smoking habits remained statistically associated with central parkinsonian pain even when other significant covariates were considered. Only patients with pain, regardless of type, had a gambling disorder. Discussion. The study results provide further evidence that pain revealed that patients with central parkinsonian pain are more likely to present compulsive or addictive behaviors, despite having more preserved cognitive performance. Patients with central parkinsonian pain appear to have a distinct phenotype of PD.
Taxonomy of Vincetoxicum s.str. (Asclepiadoideae, Apocynaceae) from southern Asia including three new species and resurrected names

Abstract This paper presents a taxonomic study of genus Vincetoxicum s.str. from southern Asia. Eleven regional endemic species are recognized on the basis of herbarium studies and fieldwork. Three new species are described: V. lenifoliumsp. nov. (endemic to Pakistan), V. stewartianumsp. nov. (endemic to India), and V. subcanescenssp. nov. (endemic to Pakistan, Kashmir and Tibet). Three species names, V. cabulicum, V. glaucum and V. kenouriense, previously treated as synonyms of V. glaucum, V. canescens and V. hirundinaria, respectively, are resurrected. A neotype is designated for the Afghani endemic V. cabulicum. A lectotype is chosen from the syntypes of V. glaucum. We resolve the long-standing taxonomic problems in three species complexes: V. arnottianum, V. luridum, V. sakesarense, and V. stocksii; V. glaucum, V. canescens and V. cabulicum; and V. hirundinaria and V. kenouriense. Geo-taxonomic distinctions of southern Asian taxa are highlighted by excluding from henceforth the long misrecognized western Eurasian taxa V. canescens and V. hirundinaria. Furthermore, a detailed account of the genus including illustrations of whole plants, leaves and corona, distribution maps, a taxonomic key, morphological descriptions, synonymy, notes, and information on phenology, distribution and habitats is provided. Finally, provisional conservation assessments are provided, which indicate that V. cardiostephanum and V. sakesarense are critically endangered.
Abnormal proinflammatory and stressor environmental with increased the regulatory cellular IGF-1/PAPP-A/STC and Wnt-1/β-Catenin canonical pathway in placenta of women with Chronic venous Disease during Pregnancy

Lower limbs venous insufficiency refers to a wide variety of venous disorders grouped by the term of chronic venous disease (CVD). Hemodynamic and hormonal changes related to pregnancy period, may promote the development of CVD affecting approximately 1 in 3 women. It has been shown that the presence of this condition is associated with damage and placental suffering. Thus, taking IGF-1/PAPP-A/STC-2, inflammatory cytokines production, PI3K/Akt and Wnt/ β-catenin pathways as a part of the alterations that occurs in the placenta due to CVD, the aim of this study will be to examine the main components of these pathways. Genic and protein expression of PAPP-A, STC-2, IGF-1, IRS-4 Wnt-1, β-catenin, c-myc, Cyclin D1, IL-4/IL-6 and PI3K/Akt/mTOR pathway will be analysed through RT-qPCR and immunohistochemical techniques in women with CVD (n=62) and pregnant women without this condition (HC) (n=52). PAPP-A, IGF-1, IL-4, IL-6, IRS-4, PI3K, Akt, mTOR, Wnt-1, β-catenin, c-myc and Cyclin D1 expression were found to be increased in women with CVD, whereas STC-2 were decreased in this group, compared to non-affected women. Our study has demonstrated that IGF-1/PAPP-A/STC-2 axis, PI3K/Akt and Wnt/β-catenin pathways, along with c-myc, Cyclin D1 and inflammatory cytokines are altered in placenta women with CVD. These results extent the knowledge that CVD is associated to a placenta damage with abnormal tissue environment and cellular regulation.
The Effect of Rhythmic Breathing on the Severity of Sternotomy Pain after Coronary Artery Bypass Graft Surgery: A Randomized Controlled Clinical Trial

Background Moderate-to-severe pain is reported in up to 75% of the patients in the first 48 hours after cardiac surgery. Evidence suggests that distraction is an effective nursing intervention for controlling short-term and transient pain. Distraction can be achieved by various techniques, including progressive muscle relaxation, meditation, and rhythmic breathing (RB). The present research aimed at evaluating the impacts of RB on the severity of sternotomy pain after Coronary Artery Bypass Graft (CABG). Methods This randomized, controlled clinical trial was conducted on 60 patients after CABG surgery at the open-heart surgery Intensive Care Unit (ICU) of Kowsar Hospital, affiliated to Semnan University of Medical Sciences in Semnan, Iran. The patients were selected through convenience sampling and randomly assigned to two groups, including (1) intervention or RB and (2) control groups. RB was performed in the intervention group every 12 hours (9 a.m. and 9 p.m.) for three consecutive days after the surgery. The control group received only routine care for pain control (opioid analgesics) with no additional interventions. The severity of pain was measured every day in both groups of patients before and after the interventions using the Visual Analog Scale (VAS). Results The mean postintervention pain scores were significantly different from the mean preintervention scores in the intervention group (p < 0.05). The changes in the mean pain score in the intervention group were also significantly different from the corresponding changes in the controls (p < 0.05). Conclusion Based on the results, the severity of pain after the intervention was significantly lower in the RB group compared to the control. RB was found to be an effective technique for reducing the patients' pain and is therefore recommended as a post-CABG pain control technique. Iranian Registry of Clinical Trials: this trial is clinically registered with IRCT20120109008665N7, registered 3 September 2018.
Effect of Electroacupuncture on Bladder Dysfunction via Regulation of MLC and MLCK Phosphorylation in a Rat Model of Type 2 Diabetes Mellitus

Previous studies observed have reported that electroacupuncture (EA) is effective in relieving diabetic bladder dysfunction (DBD); however, little is known about the mechanism. Therefore, we explored the effects and mechanisms of EA on DBD in streptozotocin–high-fat diet- (STZ–HFD-) induced diabetic rats. The Sprague-Dawley male rats were divided randomly into four groups: normal group, diabetes mellitus group (DM group), DM with EA treatment group (EA group), and DM with sham EA treatment group (sham EA group). After 8 weeks of EA treatment, the body weight, serum glucose, bladder weight, and cystometrogram were evaluated. The bladder wall thickness was examined by abdominal ultrasound imaging. After the transabdominal ultrasound measurements, hematoxylin-eosin (HE) staining was used to observe the bladder mucosa layer. The bladder detrusor smooth muscle cells (SMCs) and fibroblasts were observed under transmission electron microscopy (TEM). The phospho-myosin light chain (p-MLC), phospho-myosin light chain kinase (p-MLCK), and phospho-myosin phosphatase target subunit 1 (p-MYPT1) levels in the bladder were examined using Western blot. The bladder weight, serum glucose, bladder wall thickness, volume threshold for micturition, and postvoid residual (PVR) volume in the diabetic rats were significantly higher than those in the control animals. EA treatment significantly reduced the bladder weight, bladder wall thickness, volume threshold for micturition, and PVR volume in diabetic rats. EA caused a significant increase in the MLC dephosphorylation and MLCK phosphorylation levels in the group compared to the sham EA and model groups. EA reduced the infiltration of inflammatory cells in the bladder mucosa layer of diabetic rats. In addition, EA repaired the damaged bladder detrusor muscle of diabetic rats by reducing mitochondrial damage of the SMCs and fibroblasts. Therefore, EA could reduce the bladder hypertrophy to ameliorate DBD by reversing the impairment in the mucosa layer and detrusor SMCs, which might be mainly mediated by the regulation of p-MLC and p-MLCK levels.
Prediction of lymphovascular space invasion in patients with endometrial cancer

Objective: Predict the presence of lymphovascular space invasion (LVSI), using uterine factors such as tumor diameter (TD), grade, and depth of myometrial invasion (MMI). Develop a predictive model that could serve as a marker of LVSI in women with endometrial cancer (EC). Methods: Data from 888 patients with endometrioid EC who were treated between January 2009 and December 2018 were reviewed. The patients' data were retrieved from six institutions. We assessed the differences in the clinicopathological characteristics between patients with and without LVSI. We performed logistic regression analysis to determine which clinicopathological characteristics were the risk factors for positive LVSI status and to estimate the odds ratio (OR) for each covariate. Using the risk factors and OR identified through this process, we created a model that could predict LVSI and analyzed it further using receiver operating characteristic curve analysis. Results: In multivariate logistic regression analysis, tumor size (P = 0.027), percentage of MMI (P < 0.001), and presence of cervical stromal invasion (P = 0.002) were identified as the risk factors for LVSI. Based on the results of multivariate logistic regression analysis, we developed a simplified LVSI prediction model for clinical use. We defined the “LVSI index” as “TD×%MMI×tumor grade×cervical stromal involvement. ” The area under curve was 0.839 (95% CI= 0.809-0.869; sensitivity, 74.1%; specificity, 80.5%; negative predictive value, 47.3%; positive predictive value, 8.6%; P < 0.001), and the optimal cut-off value was 200. Conclusion: Using the modified risk index of LVSI, it is possible to predict the presence of LVSI in women with endometrioid endometrial cancer. Our prediction model may be an appropriate tool for integration into the clinical decision-making process when assessed either preoperatively or intraoperatively.
Unpacking the impact of the COVID-19 pandemic: identifying structural domains

ABSTRACT Background: The novel coronavirus-19 (COVID-19) pandemic is a collective crisis that imposed an abrupt and unprecedented impact on college students, as universities were closed with little warning. Paired with the challenges associated with physical distancing (e.g. economic stress, job loss, food insecurity, housing challenges) and the simultaneous need to balance continued and new academic demands, impact will be wide-ranging. It is critical to determine the structure of the impact of this heterogeneous stressor (e.g. health concerns, pandemic worry, financial concerns) for prevention and intervention planning. Objective: Through an existing recruitment pipeline we were in a unique position to study the wide-ranging reach of this pandemic in a cohort of students for whom their university experiences were like no other cohort in history. Method: Data were collected from students who were in their third year of college during the onset of the pandemic; of the N = 1,899 in the cohort who were invited to participate in this COVID-related survey, 897 (47.2%) completed measures of impact between May and July of 2020. Results: A series of confirmatory and exploratory models were fit to examine the structure of the pandemic-related domains. Following estimation of a single-factor model, a correlated five factors model, as well as two second-order factor structures, the five correlated factors (exposure, worry, housing/food instability, social media, substance use) model was found to represent the data most appropriately, while producing an interpretable solution. Conclusions: These measurement model analyses set the stage for future research to examine how these correlated factors impact psychiatric, substance, and academic outcomes in this vulnerable population.
Machine learning for medical imaging‐based COVID‐19 detection and diagnosis

The novel coronavirus disease 2019 (COVID‐19) is considered to be a significant health challenge worldwide because of its rapid human‐to‐human transmission, leading to a rise in the number of infected people and deaths. The detection of COVID‐19 at the earliest stage is therefore of paramount importance for controlling the pandemic spread and reducing the mortality rate. The real‐time reverse transcription‐polymerase chain reaction, the primary method of diagnosis for coronavirus infection, has a relatively high false negative rate while detecting early stage disease. Meanwhile, the manifestations of COVID‐19, as seen through medical imaging methods such as computed tomography (CT), radiograph (X‐ray), and ultrasound imaging, show individual characteristics that differ from those of healthy cases or other types of pneumonia. Machine learning (ML) applications for COVID‐19 diagnosis, detection, and the assessment of disease severity based on medical imaging have gained considerable attention. Herein, we review the recent progress of ML in COVID‐19 detection with a particular focus on ML models using CT and X‐ray images published in high‐ranking journals, including a discussion of the predominant features of medical imaging in patients with COVID‐19. Deep Learning algorithms, particularly convolutional neural networks, have been utilized widely for image segmentation and classification to identify patients with COVID‐19 and many ML modules have achieved remarkable predictive results using datasets with limited sample sizes.
An ounce of prevention is worth a pound of cure: considerations for pharmacists delivering the National Diabetes Prevention Program

Prediabetes is highly prevalent in the United States affecting over 88 million adults. In 2010, the Centers for Disease Control and Prevention (CDC) established the National Diabetes Prevention Program (NDPP), an intensive lifestyle program consisting of a 16-lesson curriculum focused on diet, exercise, and behavior modification, with the ultimate goal to reduce progression from prediabetes to diabetes. Despite tens of millions of adults potentially qualifying to participate in the program, the uptake of the NDPP has been exceedingly low. As a result, the CDC has focused its efforts on engaging with local health departments and community partners, including community pharmacies, across the United States to scale-up enrollment in the NDPP. In this commentary we discuss factors affecting implementation of the NDPP in community pharmacies and other settings where pharmacists practice, including training, space, personnel, recruitment and enrollment, retention, and sustainability.
High-dimensional central limit theorems for a class of particle systems

We consider a class of particle systems that generalizes the eigenvalues of a class of matrix-valued processes, of which the empirical measures converge to deterministic measures as the dimension goes to infinity. In this paper, we obtain central limit theorems (CLTs) to characterize the fluctuations of the empirical measures around the limit measures by using stochastic calculus. As applications, CLTs for Dyson’s Brownian motion and the eigenvalues of Wishart process are recovered under slightly more general initial conditions, and a CLT for the eigenvalues of a symmetric matrixvalued Ornstein-Uhlenbeck process is obtained.
From Isolation to Containment: Perceived Fear of Infectivity and Protective Behavioral Changes during the COVID-19 Vaccination Campaign

In the ongoing COVID-19 pandemic, maintenance of protective behavior is a continued challenge in the effort to contain the spread of the virus. A cross-sectional study via an internet questionnaire was utilized to elucidate changes in compliance to protective behavior among the Israeli population (n = 1120), after the beginning of the vaccination campaign. Comparison was made between individuals who were previously infected with the virus, those who received one dose of inoculation with the vaccine, and individuals that were neither infected or vaccinated. The study results indicate that those who were previously infected with the COVID-19 virus were less careful about mask wearing (18.8%) and social distancing (29.7%), as compared to the other examined groups (regarding mask wearing, 8.2% and 11.6% respectively, and with regard to social distancing 12.8% and 19.2%), and may require targeted risk communication campaigns to address this population. Furthermore, the study revealed that those that were non-Jewish (as compared to Jewish study counterparts) or that were older (19+) were more vigilant in their protective behavior (29.6% vs. 11.2% respectively for social distancing and 29.6% vs. 11.1% respectively for mask wearing). Despite a successful initial vaccination campaign in Israel, public health officials need to engage all members of the public to unremittingly observe compliance to directed health guidelines, to ensure that the results of previous governmental efforts in fighting the pandemic (such as lockdowns) will be effectively sustained, and the road to containment will be hastened.
Diagnostic Value of the CSF α-Synuclein Real-Time Quaking-Induced Conversion Assay at the Prodromal MCI Stage of Dementia With Lewy Bodies

Objective To investigate whether the CSF α-synuclein (α-syn) real-time quaking-induced conversion (RT-QuIC) assay accurately identifies patients with mild cognitive impairment (MCI) due to probable Lewy body (LB) disease. Methods We applied α-syn RT-QuIC to 289 CSF samples obtained from 2 independent cohorts, including 81 patients with probable MCI-LB (age 70.7 ± 6.6 years, 13.6% female, Mini-Mental State Examination [MMSE] score 26.1 ± 2.4), 120 with probable MCI due to Alzheimer disease (AD) (age 68.6 ± 7.4 years, 45.8% female, MMSE score 25.5 ± 2.8), and 30 with unspecified MCI (age 65.4 ± 9.3 years, 30.0% female, MMSE score 27.0 ± 3.0). Fifty-eight individuals with no cognitive decline or evidence of neurodegenerative disease and 121 individuals lacking brain α-syn deposits at the neuropathologic examination were used as controls. Results RT-QuIC identified patients with MCI-LB against cognitively unimpaired controls with 95% sensitivity, 97% specificity, and 96% accuracy and showed 98% specificity in neuropathologic controls. The accuracy of the test for MCI-LB was consistent between the 2 cohorts (97.3% vs 93.7%). Thirteen percent of patients with MCI-AD also had a positive test; of note, 44% of them developed 1 core or supportive clinical feature of dementia with Lewy bodies (DLB) at follow-up, suggesting an underlying LB copathology. Conclusions These findings indicate that CSF α-syn RT-QuIC is a robust biomarker for prodromal DLB. Further studies are needed to fully explore the added value of the assay to the current research criteria for MCI-LB. Classification of Evidence This study provides Class III evidence that CSF α-syn RT-QuIC accurately identifies patients with MCI-LB.
Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.