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Population-based cohort studies are essential for understanding the pathological basis of dementia in older populations. Previous studies have shown that limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) increases with age, but there have been only a few studies, which have investigated this entity in a population-based setting. Here we studied the frequency of LATE-NC and its associations with other brain pathologies and cognition in a population aged ≥ 85 years. The population-based Vantaa 85+ study cohort includes all 601 individuals aged ≥85 years who were living in Vantaa, Finland in 1991. A neuropathological examination was performed on 304 subjects (50.5%) and LATE-NC staging was possible in 295 of those. Dementia status and Mini-Mental State Examination (MMSE) scores were defined in the baseline study and three follow-ups (1994–99). The LATE-NC stages were determined based on TDP-43 immunohistochemistry, according to recently updated recommendations. Arteriolosclerosis was digitally assessed by calculating the average sclerotic index of five random small arterioles in amygdala and hippocampal regions, and frontal white matter. The association of LATE-NC with arteriolosclerosis and previously determined neuropathological variables including Alzheimer's disease neuropathologic change (ADNC), Lewy-related pathology (LRP), hippocampal sclerosis (HS) and cerebral amyloid angiopathy (CAA), and cognitive variables were analysed by Fisher's exact test, linear and logistic regression (univariate and multivariate) models. LATE-NC was found in 189 of 295 subjects (64.1%). Stage 2 was the most common (28.5%) and stage 3 the second most common (12.9%), whereas stages 1a, 1b and 1c were less common (9.5%, 5.1% and 8.1%, respectively). Stages 1a (P < 0.01), 2 (P < 0.001) and 3 (P < 0.001) were significantly associated with dementia and lower MMSE scores. LATE-NC was associated with ADNC (P < 0.001), HS (P < 0.001), diffuse neocortical LRP (P < 0.002), and arteriolosclerosis in amygdala (P < 0.02). In most cases LATE-NC occurred in combination alongside other neuropathological changes. There were only six subjects with dementia who had LATE-NC without high levels of ADNC or LRP (2% of the cohort, 3% of the cases with dementia), and five of these had HS. In all multivariate models, LATE-NC was among the strongest independent predictors of dementia. When LATE-NC and ADNC were assessed in a multivariate model without other dementia-associated pathologies, the attributable risk was higher for LATE-NC than ADNC (24.2% versus 18.6%). This population-based study provides evidence that LATE-NC is very common and one of the most significant determinants of dementia in the general late-life aged population. [ABSTRACT FROM AUTHOR]

The benefits of AI in pathology are demonstrated by the growing potential of diagnostic accuracy and efficiency in tissue segmentation, cancer detection and grading. In this scoping review, we studied how artificial intelligence (AI) technologies have been developed for usage in pathology. In the study, a literature search on databases and publisher portals PubMed, ScienceDirect, ProQuest, and CINAHL was conducted to collect peer-reviewed studies published between 2019 and 2023. Then after a thorough database search, 57 articles covering the topic were included out of 19 185 potential ones and were categorised into groups by their main purposes, such as pre-processing, segmentation, analysis, and prediction. The findings demonstrate that AI technologies like deep learning and convolutional neural networks (CNNs) enhance medical imaging for tissue segmentation and cancer detection by reducing human error and variability. [ABSTRACT FROM AUTHOR]

Over the past three decades, there has been an increase in the severity of fungal infections, affecting several individuals and claiming the lives of more than 1.6 million people every year. Species of Candida are one of the causatives of invasive fungal infections, and the extensive use of antifungals for their treatment has led to the emergence of drug resistance in these species, highlighting the need for the exploration of effective and cost-effective therapeutics. Drug repurposing is an important solution for alternative therapeutics. There are many studies where antifungal indications of any existing drug have been analyzed with an aim to establish new antimycotic therapeutics in a short time and with a lower budget. In this review, efforts are made to compile the literature on repurposed drugs against clinical isolates of Candida and fungal pathogens to better illustrate drug repurposing's role in the treatment of candidiasis. [ABSTRACT FROM AUTHOR]

Widespread usage of antifungals has led to the development of antifungal resistance, causing a change in the epidemiology of the responsible agents from albicans to non-Candida albicans species. Pharmaceutical repurposing is an alternate strategy that has provided a cost-effective method to address the increasing resistance to antifungal medications. The objective of this work was to examine the antifungal properties of Alexidine dihydrochloride (AXD) and Hexachlorophene (HCP) against a non-Albicans Candida model, C. glabrata. The lowest inhibitory doses of AXD and HCP against C. glabrata were determined by in vitro methods to be 0.69-1.03 µM and 14.75-19.66 µM, respectively. The minimum doses of AXD and HCP that caused fungicidal effects were defined as 1.375 µM and 61.44 µM, respectively. Three proteins involved in crucial physiological pathways, namely cell wall production (Kre1p, Kre2p, Ecm33p), membrane calcium channel (Mid1p, Ecm7p), and ergosterol biosynthesis (Erg5p), were chosen as potential targets for the medications due to their functions in survival and disease development. SWISS MODEL was used to create the 3D structures of predicted targets of C. glabrata. The quality of these structures was assessed using Ramachandran plot statistics. AXD and HCP were analyzed by docking software AutoDock Vina against these targets. The findings of computational investigations have shown that both medicines exhibit interaction affinities with all the selected protein types. The binding energy profiles of AXD and HCP showed that Mid1p had the lowest binding energies at -10.1 kcal/mol and -9.2 kcal/mol, respectively. Kre2p had binding energies of -7.9 kcal/mol and -7.1 kcal/mol, respectively. Erg5p had binding energies of -6.6 kcal/mol and -6.2 kcal/mol, respectively. Ecm7p had binding energies of -6.6 kcal/mol and -6.1 kcal/mol, respectively. Recm7p had binding energies of -4.8 kcal/mol and -7.7 kcal/mol, respectively. These results suggest that these genes are likely targets of the two drugs in C. glabrata. [ABSTRACT FROM AUTHOR]

The emergence of non-albicans Candida as a potential causative agent of candidiasis following Candida albicans is occurring globally. It is known that phenolic cresols, thymol, and carvacrol have anti-Candida characteristics. However, there are few papers that disclose the mechanism of action, which is characterized by a damaged cell wall and ergosterol synthesis, as well as calcium-induced death in C. albicans. This work utilized in-silico docking analysis to examine the molecular targets of thymol and carvacrol in Candida glabrata. The results were then validated in vitro by antifungal susceptibility testing and growth curve analysis. The study incorporated C. glabrata deletion mutants for the target proteins to gain understanding of the function of these proteins in the antifungal effects of the two monoterpenoids. After conducting molecular docking and in silico toxicity evaluations, thymol and carvacrol were chosen for in vitro investigations. Experimental tests conducted in a laboratory setting have shown that both phytocompounds exhibit strong binding affinity towards cell wall synthesis proteins (Kre1p, Kre2p, Ecm33p), calcium channel proteins (Mid1p, Ecm7p), and proteins involved in the ergosterol synthesis pathway (Erg5p). These proteins are likely to be the specific targets for the anti-Candida properties of the two isomeric monoterpenoids in C. glabrata. Minimum inhibitory concentration (MIC50) values for thymol and carvacrol range from 50 µg/ml to 75 µg/ml. The wild-type strains exhibit a minimum fungicidal concentration of 100 µg/ml for thymol and 125 µg/ml for carvacrol. The results underscore the significance of these proteins in the fungal reaction to thymol and carvacrol and also indicate a promising opportunity for the development of novel antifungal treatment methods utilizing these proteins. [ABSTRACT FROM AUTHOR]

Objective: To determine presence of inflammatory markers i.e. hyper-ferritinemia, elevated lactate dehydrogenase, and liver enzymes in dengue fever and their correlation with different classes of dengue severity, defined by new WHO classification. Study Design: Cross-sectional Analytical study. Setting: Medical Department of Dr. Ruth KM Pfau Civil Hospital Karachi. Period: October 2022 to March 2023. Methods: Conducted in confirmed cases of Dengue fever, after consent all patients were categorized in three i.e. D-W, D+W and SDF groups. Results: 120 patients were included in study. 24 suffered from Severe Dengue Fever (SDF) whereas 28 were in Dengue without warning signs (D-W) group and 68 were in Dengue with warning signs (D+W) group. We found a significant association between liver enzymes (SGPT and SGOT) and dengue severity. SGOT was significantly increased in cases with SDF as compared to D-W and D+W cases (p-value = 0.002). Similarly, ferritin was significantly increased in SDF cases compared to non-severe cohort (p-value <0.001). Using the area under the curve (AUC) of ROC curve, ferritin level (cutoff value of 800), produced a sensitivity of 75% for severe dengue fever. Mean length of stay in patients with non-severe dengue group was 3.63 days vs. 4.3 days in those with SDF (P value 0.002). Conclusion: As dengue is becoming a huge burden especially in developing countries, need to take proper measures to establish disease severity and according to severity resource allocation is cornerstone. Significant higher ferritin levels in severe dengue fever than other dengue groups, observed in our study, making serum ferritin a surrogate marker for dengue to predict the severity of dengue fever. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To assess eosinopenia and neutrophil to lymphocyte ratio in patients admitted with COVID-19 infection and correlate with pneumonia severity. METHODOLOGY: This prospective observational study was conducted at Covid HDU of Dr. Ruth KM Pfau Civil Hospital, Karachi, from October - December 2021. Data was collected using convenience sampling. The inclusion criteria were patients between 18-70 years with symptoms suggestive of COVID-19 and positive RT-PCR. Patients with negative RT-PCR with alternate diagnosis, history of using a corticosteroid, pancreatic or esophageal malignancy, and recent burn were excluded. Data analysis was done using SPSS version 23. RESULTS: Out of 141 patients, 66(46%) were classified as non-severe covid and 75(53.9%) as severe covid pneumonia. A significant association between eosinopenia and COVID severity was observed. The NLR was significantly increased in severe COVID patients compared to non-severe patients. Similarly, eosinophil was decreased considerably in severe covid compared to non-severe patients (p-value<0.05). The area under the eosinopenia ROC curve is 0.71 and 0.69 on days 7 and 3, respectively. Thus, eosinopenia on day 7 was fair in predicting severe COVID-19 pneumonia compared with increased NLR, which was poor in predicting severe COVID-19. Using the area under the ROC curve, an eosinophil count cutoff of <100 cells/mm3 produced a sensitivity of 75% for severe COVID-19 pneumonia. CONCLUSION: Eosinopenia and elevated NLR were found with increased frequency in patients with severe COVID-19 pneumonia; however, persistent eosinopenia was a better marker than NLR in predicting COVID-19 infection severity. [ABSTRACT FROM AUTHOR]

Breast cancer is the most prevalent neoplasia among women, with early and accurate diagnosis critical for effective treatment. In clinical practice, however, the subjective nature of histological grading of infiltrating ductal adenocarcinoma of the breast (DAC-NOS) often leads to inconsistencies among pathologists, posing a significant challenge to achieving optimal patient outcomes. Our study aimed to address this reproducibility problem by leveraging artificial intelligence (AI). We trained a deep-learning model using a convolutional neural network-based algorithm (CNN-bA) on 100 whole slide images (WSIs) of DAC-NOS from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Our model demonstrated high precision, sensitivity, and F1 score across different grading components in about 17.5 h with 19,000 iterations. However, the agreement between the model's grading and that of general pathologists varied, showing the highest agreement for the mitotic count score. These findings suggest that AI has the potential to enhance the accuracy and reproducibility of breast cancer grading, warranting further refinement and validation of this approach. [ABSTRACT FROM AUTHOR]

Objective: To determine correlation of HbA1c with serum iron and transferrin saturation in non-diabetic patients with iron deficiency. Methods: This cross-sectional comparative study was conducted at Dr Ruth KM Pfau Civil Hospital Karachi from 15th September 2021 to 14th March 2022, on non-diabetic patients based on fasting blood sugar (FBS) of <100 mg/dl. Patients were divided into two groups. Group one included patients having iron deficiency anemia (ID), whereas group two included same number of age and sex matched healthy subjects taken as controls, without ID. Blood sample was taken for HbA1c, CBC, serum iron and total iron binding capacity. Transferrin saturation (TSAT) was calculated. Comparison of quantitative variables with ID and non-ID group was done by Student's t-test. Correlation of HbA1c with iron &TSAT was done in both groups using Kendal tau-b test, as data was not normally distributed. Results: Out of 230 patients, 83 (36.1%) were males while 147(63.9%) were females. Mean age of patients was 43.7±13.28 years. Mean HbA1c level was significantly high in ID group (5.89±0.43) as compared to non-ID group (5.52±0.50) with a p-value <.001. The HbA1c levels correlated negatively with hemoglobin, serum iron levels and transferrin saturation with a p-value <.001. Conclusion: Low serum Iron and TSAT was related to elevation in HbA1c value. Iron deficiency needs to be corrected before HbA1c interpretation. [ABSTRACT FROM AUTHOR]

In this paper, we report a fast, linear wide-range hybrid flexible sensor based on a novel composite of strontium titanate (SrTiO3) and poly 3,4 ethylenedioxythiophene polystyrene sulfonate (PEDOT: PSS) as a sensing layer. Inter-digitate electrodes (IDEs) were printed for humidity monitoring (finger: 250 µm; spacing: 140 µm; length: 8 mm) whilst a meander-based pattern was printed for the temperature measurement (meander thickness: 180 µm; spacing: 400 µm) on each side of the PET substrate using silver ink. Moreover, active layers with different concentration ratios were coated on the electrodes using a spray coating technique. The as-developed sensor showed an excellent performance, with a humidity measurement range of (10–90% RH) and temperature measurement range of (25–90 °C) with a fast response (humidity: 5 s; temperature: 4.2 s) and recovery time (humidity: 8 s; temperature: 4.4 s). The reliability of the sensor during mechanical bending of up to 5.5 mm was validated with a reliable performance. The sensor was also used in real-world applications to measure human respiration. For this, a suggested sensor-based autonomous wireless node was included in a 3D-printed mask. The manufactured sensor was an excellent contender for wearable and environmental applications because of its exceptional performance, which allowed for the simultaneous measurement of both quantities by a single sensing device. [ABSTRACT FROM AUTHOR]