Development of maximum relevant prior feature ensemble (MRPFE) index to characterize future drought using global climate models.

Drought is one of the foremost outcomes of global warming and global climate change. It is a serious threat to humans and other living beings. To reduce the adverse impact of drought, mitigation strategies as well as sound projections of extreme events are essential. This research aims to strengthen the robustness of anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop a new drought index, named Maximum Relevant Prior Feature Ensemble index that is based on the newly proposed weighting scheme, called weighted ensemble (WE). In the application, this study considers 32 randomly scattered grid points within the Tibetan Plateau region and 18 GCMs of Coupled Model Intercomparison Project Phase 6 (CMIP6) of precipitation. In this study, the comparative inferences of the WE scheme are made with the traditional simple model averaging (SMA). To investigate the trend and long-term probability of various classes, this research employs Markov chain steady states probability, Mann-Kendall trend test, and Sen's Slope estimator. The outcomes of this research are twofold. Firstly, the comparative inference shows that the proposed weighting scheme has greater efficiency than SMA to conflate GCMs. Secondly, the research indicates that the Tibetan Plateau is projected to experience "moderate drought (MD)" in the twenty-first century.

Serological markers of transfusion transmissible infections and ABO blood groups in Najran, Saudi Arabia.

OBJECTIVES: To ascertain the prevalence of transfusion transmissible infections (TTIs) across diverse donor groups in the Najran province. Additionally, to establish a potential association between the development of TTI and the donors' blood group, as determined by the ABO/Rh blood grouping system. METHODS: Blood donation data of 4120 donors, spanning from January to December 2020, were retrospectively reviewed. The blood were screened for TTI markers, including hepatitis B surface antigen (HBsAg), anti-hepatitis B core (anti-HBc), anti-hepatitis C virus (anti-HCV), anti-human immunodeficiency viruses 1 and 2 (anti-HIV1&2), anti-human T-lymphotropic virus types 1 and 2 (anti-HTLV-1&2), and syphilis antigen. RESULTS: Positive TTI markers were detected in 10.9% of the donors. The most detected TTI marker was anti-HBc (8.9%), followed by HBsAg (0.7%). Other markers were individually detected in <1% of the donors. Anti-HBc-positive was significantly elevated among non-Saudi blood donors. There was an association between age groups and anti-HCV (p=0.002), anti-HTLV (p=0.004) and syphilis antigen (p=0.02) markers positivity. The AB positive blood group exhibited the most positivity for TTI markers, followed by O positive blood group. Similarly, association was found between ABO group and HBsAg (p=0.01), anti-HBc (p=0.001), and anti-HCV (p<0.001) markers positivity. CONCLUSION: Emphasis on implementing robust screening measures for donated blood is underscored by this study. There is the need for future study to extensively evaluate TTI status to enhance our understanding of the trend in TTI.

Exploring conformational landscapes and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variant complexes with the ACE2 receptor using AlphaFold2-based structural ensembles and molecular dynamics simulations.

In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles evolution and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamics (MD) simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and MD simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and MD simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.

Cardiotoxicity in Cancer Patients: The Prevalence, Risk Factors, and Cardioprotective Measures in a Cancer Centre in Saudi Arabia.

BACKGROUND: Chemotherapy-related cardiotoxicity can exhibit several patterns of functional, structural, and vascular complications. This study aims to identify the patterns and the factors associated with cardiotoxicity in cancer patients. METHOD: A retrospective cross-sectional analysis of 96 adult cancer patients undergoing anticancer therapy was investigated at King Khalid Hospital in Najran, Saudi Arabia, from May 2022 to April 2023. The data on patient and cancer characteristics, treatment, and outcomes were collected and analyzed. Factors associated with cardiotoxicity were investigated through univariate analyses using odds ratio (OR) and 95% confidence interval (CI). RESULTS:  Among the 96 cancer patients in the study, cardiotoxicity occurred in 12 individuals (12.5%). The mean age was 57.0 ± 13.3 years (range: 32-81 years), with 32 (33.3%) being above 65 years. The most common comorbidities were diabetes (n=48; 50%), followed by hypertension (n=32; 33.3%), and dyslipidemia (n=20; 20.8%). The most common cancers were gastrointestinal cancer (n=32; 33.3%), followed by breast cancer (n=22; 22.9%) and lymphoma (n=14; 14.6%). Females were disproportionately affected (64.6%), with 57.3% of them in the metastatic stage. The majority of patients (90.6%) had normal ejection fraction before chemotherapy initiation. In univariate analysis, current smoking (OR: 7.00; 95%CI: 1.94-25.25, p= 0.003), history of percutaneous cardiac intervention (OR: 40.24; 95%CI: 1.80-896.26, p= 0.019), diabetes (OR: 6.05; 95%CI: 1.24-29.32, p= 0.025), renal failure (OR: 8.20; 95%CI: 0.91-74.88, p= 0.046), dyslipidemia (OR: 5.00; 95 CI: 1.38-18.32, p=0.012), anthracycline use (OR: 18.33; 95%CI: 4.36-126.55, p <0.001), trastuzumab use (OR: 25.00; 95%CI: 6.25-129.86, p < 0.001), and increased chemotherapy cycles number (> 10 cycles) (OR: 73.00; 95%CI: 8.56- 622.36, p < 0.001) were associated with cardiotoxicity. Additionally, beta-blocker use was associated with lower rates of cardiotoxicity (OR: 0.17; 95%CI: 0.036-0.84, p= 0.029). CONCLUSIONS: The incidence of cardiotoxicity among cancer patients treated with chemotherapy is modest, difficult to predict, and independent of baseline cardiac systolic functions. Factors associated with cardiotoxicity include smoking, history of percutaneous cardiac intervention, diabetes, renal failure, dyslipidemia, anthracycline or trastuzumab use, and increased chemotherapy cycle numbers. A combination of various anticancer drugs and chemotherapy may dramatically raise the risk of cardiotoxicity in cancer patients. As a result, patients receiving high-risk cardiotoxic drugs should be monitored with caution to avoid drug-related cardiotoxicity. Furthermore, proactive treatment techniques aiming at reducing the possible cardiotoxic effects of anticancer therapy are critical.

Evaluation of the Relationship Between Smartphone Addiction and Lower Back Pain and Neck Pain Among Medical Students at Al-Baha University.

Introduction In recent years, the increased use of smartphones has adversely affected students, leading to issues like musculoskeletal pain. Therefore, our objective was to assess the correlation between smartphone addiction and neck and lower back pain. Methodology An observational cross-sectional study was conducted at Al-Baha University, Al-Baha, Saudi Arabia. The Smartphone Addiction Scale Short Version (SAS-SV) was used to measure the level of smartphone addiction while the Nordic Musculoskeletal Questionnaire (NMQ) was utilized to evaluate musculoskeletal pain. Results Smartphone addiction was prevalent in 72% of the participants (n = 293). Significantly, lower back pain was associated with smartphone addiction (p-value = 0.004). However, none of the demographic characteristics were associated with neck or lower back pain (p-value > 0.05). Students in clinical years had a higher risk of neck pain than those in an internship (p-value = 0.048). Conclusion Almost two-thirds of the students were addicted to smartphones, with a significant association with lower back pain. Students addicted to their smartphones had a higher risk of developing lower back pain, while clinical-year students had a higher risk of developing neck pain. It's important to raise awareness about the health and safety dangers linked to smartphones and other devices.

Integration of a Randomized Sequence Scanning Approach in AlphaFold2 and Local Frustration Profiling of Conformational States Enable Interpretable Atomistic Characterization of Conformational Ensembles and Detection of Hidden Allosteric States in the ABL1 Protein Kinase.

Despite the success of AlphaFold methods in predicting single protein structures, these methods showed intrinsic limitations in the characterization of multiple functional conformations of allosteric proteins. The recent NMR-based structural determination of the unbound ABL kinase in the active state and discovery of the inactive low-populated functional conformations that are unique for ABL kinase present an ideal challenge for the AlphaFold2 approaches. In the current study, we employ several adaptations of the AlphaFold2 methodology to predict protein conformational ensembles and allosteric states of the ABL kinase including randomized alanine sequence scanning combined with the multiple sequence alignment subsampling proposed in this study. We show that the proposed new AlphaFold2 adaptation combined with local frustration profiling of conformational states enables accurate prediction of the protein kinase structures and conformational ensembles, also offering a robust approach for interpretable characterization of the AlphaFold2 predictions and detection of hidden allosteric states. We found that the large high frustration residue clusters are uniquely characteristic of the low-populated, fully inactive ABL form and can define energetically frustrated cracking sites of conformational transitions, presenting difficult targets for AlphaFold2. The results of this study uncovered previously unappreciated fundamental connections between local frustration profiles of the functional allosteric states and the ability of AlphaFold2 methods to predict protein structural ensembles of the active and inactive states. This study showed that integration of the randomized sequence scanning adaptation of AlphaFold2 with a robust landscape-based analysis allows for interpretable atomistic predictions and characterization of protein conformational ensembles, providing a physical basis for the successes and limitations of current AlphaFold2 methods in detecting functional allosteric states that play a significant role in protein kinase regulation.

Revitalizing oral cancer research: Crispr-Cas9 technology the promise of genetic editing.

This review presents an in-depth analysis of the immense potential of CRISPR-Cas9 technology in revolutionizing oral cancer research. It underscores the inherent limitations of conventional treatments while emphasizing the pressing need for groundbreaking approaches. The unparalleled capability of CRISPR-Cas9 to precisely target and modify specific genes involved in cancer progression heralds a new era in therapeutic intervention. Employing genome-wide CRISPR screens, vulnerabilities in oral cancer cells can be identified, thereby unravelling promising targets for therapeutic interventions. In the realm of oral cancer, the disruptive power of CRISPR-Cas9 manifests through its capacity to perturb genes that are intricately associated with drug resistance, consequently augmenting the efficacy of chemotherapy. To address the challenges that arise, this review diligently examines pertinent issues such as off-target effects, efficient delivery mechanisms, and the ethical considerations surrounding germline editing. Through precise gene editing, facilitated by CRISPR/Cas9, it becomes possible to overcome drug resistance by rectifying mutations, thereby enhancing the efficacy of personalized treatment strategies. This review delves into the prospects of CRISPR-Cas9, illuminating its potential applications in the domains of medicine, agriculture, and biotechnology. It is paramount to emphasize the necessity of ongoing research endeavors and the imperative to develop targeted therapies tailored specifically for oral cancer. By embracing this comprehensive overview, we can pave the way for ground-breaking treatments that instill renewed hope for enhanced outcomes in individuals afflicted by oral cancer.

Tranexamic acid as a therapeutic option for melasma management: meta-analysis and systematic review of randomized controlled trials.

Purpose: This study aimed to evaluate the efficacy of tranexamic acid (TXA) in treating melasma through a meta-analysis and systematic review of randomized controlled trials (RCTs). The study focused on identifying associated adverse effects and comparing TXA's effectiveness with other melasma treatments.Materials and methods: Following PROSPERO and PRISMA guidelines, an extensive electronic search was conducted across four databases for RCTs on TXA use in melasma. Inclusion criteria encompassed full-text English articles with specific outcome measures, while studies with high bias risk or non-English publications were excluded. Data were extracted from 22 relevant studies and analyzed using the RevMan software, with heterogeneity identified using I² statistics and forest plots.Results: A total of 22 studies with 1280 patients were included. TXA was administered orally, topically, or via injection, with treatment durations ranging from 8 weeks to nearly 2 years. TXA significantly reduced melasma severity, evidenced by reductions in MASI, mMASI, MI, and hemi-MASI scores. Oral TXA showed the most substantial decrease in MASI scores, followed by injections and topical applications. However, studies exhibited high heterogeneity, particularly in combined treatments. Adverse effects included gastrointestinal discomfort, skin irritation, and menstrual irregularities.Conclusions: TXA is effective in treating melasma, either alone or combined with other treatments. Despite significant reductions in melasma severity, further research is necessary to standardize TXA administration methods and address long-term effects. The high heterogeneity observed suggests a need for more consistent treatment protocols.

Prediction of Conformational Ensembles and Structural Effects of State-Switching Allosteric Mutants in the Protein Kinases Using Comparative Analysis of AlphaFold2 Adaptations with Sequence Masking and Shallow Subsampling.

Despite the success of AlphaFold2 approaches in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and have been challenged to accurately capture of the effects of single point mutations that induced significant structural changes. We systematically examined several implementations of AlphaFold2 methods to predict conformational ensembles for state-switching mutants of the ABL kinase. The results revealed that a combination of randomized alanine sequence masking with shallow multiple sequence alignment subsampling can significantly expand the conformational diversity of the predicted structural ensembles and capture shifts in populations of the active and inactive ABL states. Consistent with the NMR experiments, the predicted conformational ensembles for M309L/L320I and M309L/H415P ABL mutants that perturb the regulatory spine networks featured the increased population of the fully closed inactive state. On the other hand, the predicted conformational ensembles for the G269E/M309L/T334I and M309L/L320I/T334I triple ABL mutants that share activating T334I gate-keeper substitution are dominated by the active ABL form. The proposed adaptation of AlphaFold can reproduce the experimentally observed mutation-induced redistributions in the relative populations of the active and inactive ABL states and capture the effects of regulatory mutations on allosteric structural rearrangements of the kinase domain. The ensemble-based network analysis complemented AlphaFold predictions by revealing allosteric mediating centers that often directly correspond to state-switching mutational sites or reside in their immediate local structural proximity, which may explain the global effect of regulatory mutations on structural changes between the ABL states. This study suggested that attention-based learning of long-range dependencies between sequence positions in homologous folds and deciphering patterns of allosteric interactions may further augment the predictive abilities of AlphaFold methods for modeling of alternative protein sates, conformational ensembles and mutation-induced structural transformations.

Statistical analysis plan for the replacing protein via enteral nutrition in a stepwise approach in critically ill patients (REPLENISH) randomized clinical trial.

BACKGROUND: The optimal amount and timing of protein intake in critically ill patients are unknown. REPLENISH (Replacing Protein via Enteral Nutrition in a Stepwise Approach in Critically Ill Patients) trial evaluates whether supplemental enteral protein added to standard enteral nutrition to achieve a high amount of enteral protein given from ICU day five until ICU discharge or ICU day 90 as compared to no supplemental enteral protein to achieve a moderate amount of enteral protein would reduce all-cause 90-day mortality in adult critically ill mechanically ventilated patients. METHODS: In this multicenter randomized trial, critically ill patients will be randomized to receive supplemental enteral protein (1.2 g/kg/day) added to standard enteral nutrition to achieve a high amount of enteral protein (range of 2-2.4 g/kg/day) or no supplemental enteral protein to achieve a moderate amount of enteral protein (0.8-1.2 g/kg/day). The primary outcome is 90-day all-cause mortality; other outcomes include functional and health-related quality-of-life assessments at 90 days. The study sample size of 2502 patients will have 80% power to detect a 5% absolute risk reduction in 90-day mortality from 30 to 25%. Consistent with international guidelines, this statistical analysis plan specifies the methods for evaluating primary and secondary outcomes and subgroups. Applying this statistical analysis plan to the REPLENISH trial will facilitate unbiased analyses of clinical data. CONCLUSION: Ethics approval was obtained from the institutional review board, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia (RC19/414/R). Approvals were also obtained from the institutional review boards of each participating institution. Our findings will be disseminated in an international peer-reviewed journal and presented at relevant conferences and meetings. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04475666 . Registered on July 17, 2020.

AlphaFold2 Predictions of Conformational Ensembles and Atomistic Simulations of the SARS-CoV-2 Spike XBB Lineages Reveal Epistatic Couplings between Convergent Mutational Hotspots that Control ACE2 Affinity.

In this study, we combined AlphaFold-based atomistic structural modeling, microsecond molecular simulations, mutational profiling, and network analysis to characterize binding mechanisms of the SARS-CoV-2 spike protein with the host receptor ACE2 for a series of Omicron XBB variants including XBB.1.5, XBB.1.5+L455F, XBB.1.5+F456L, and XBB.1.5+L455F+F456L. AlphaFold-based structural and dynamic modeling of SARS-CoV-2 Spike XBB lineages can accurately predict the experimental structures and characterize conformational ensembles of the spike protein complexes with the ACE2. Microsecond molecular dynamics simulations identified important differences in the conformational landscapes and equilibrium ensembles of the XBB variants, suggesting that combining AlphaFold predictions of multiple conformations with molecular dynamics simulations can provide a complementary approach for the characterization of functional protein states and binding mechanisms. Using the ensemble-based mutational profiling of protein residues and physics-based rigorous calculations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of the Q493 hotspot in the synchronization of epistatic couplings between L455F and F456L mutations, providing a quantitative insight into the energetic determinants underlying binding differences between XBB lineages. We also proposed a network-based perturbation approach for mutational profiling of allosteric communications and uncovered the important relationships between allosteric centers mediating long-range communication and binding hotspots of epistatic couplings. The results of this study support a mechanism in which the binding mechanisms of the XBB variants may be determined by epistatic effects between convergent evolutionary hotspots that control ACE2 binding.

Unmet Needs and Strategies to Promote Patient Engagement in the Arab World: Experts' Opinion.

BACKGROUND: The significance of patient engagement (PE) is widely acknowledged as a crucial element in fostering positive health outcomes, elevating care quality, and streamlining healthcare systems. Despite its recognized advantages, the level of patient engagement in Arab nations remains suboptimal. METHODS: A high-level assembly was convened in Dubai with 11 distinguished patient advocates from diverse Arab countries. Their collective aim was to dissect the obstacles hindering patient engagement in the Arab world and propose pragmatic strategies to surmount them. First, a series of five open-ended, comprehensive questions were posed and thoroughly deliberated upon. Second, the barriers to patient engagement within the experts' respective communities were debated. A qualitative thematic analysis was conducted and two reports were generated by two independent researchers from the original meeting recordings. RESULTS: This paper highlights the importance of patient engagement in advancing healthcare and categorizes barriers to patient engagement as patient-related, provider-related, or system/government-related. The experts identified the primary gaps in patient engagement and proposed strategies to promote it, with a primary focus on motivating both patients and providers toward shared decision-making. CONCLUSIONS: This paper amalgamates the insights and recommendations distilled from the expert gathering, juxtaposing them within the broader context of existing literature on patient engagement. Offering a comprehensive viewpoint, this article delves into the challenges and opportunities intrinsic to bolstering patient engagement in the Arab world. Moreover, it spotlights invaluable tools often overlooked within Arab countries. The practical insights provided here can serve as a roadmap for administrators and decision-makers, providing guidance to enhance patient engagement on both a national and institutional scale.

A support vector machine based drought index for regional drought analysis.

The increased global warming has increased the likelihood of recurrent drought hazards. Potential links between the frequency of extreme weather events and global warming have been suggested by earlier research. The spatial variability of meteorological factors over short distances can cause distortions in conclusions or limit the scope of drought analysis in a particular region when extreme values predominate. Therefore, it is challenging to make trustworthy judgments regarding the spatiotemporal characteristics of regional drought. This study aims to improve the quality and accuracy of regional drought characterization and the process of continuous monitoring. The new drought indicator presented in this study is called the Support Vector Machine based drought index (SVM-DI). It is created by adding different weights to an SVM-based X-bar chart that is displayed with regional precipitation aggregate data. The SVM-DI application site is located in Pakistan's northern area. Using the Pearson correlation coefficient for pairwise comparison, the study compares the SVM-DI and the Regional Standard Precipitation Index (RSPI). Interestingly, compared to RSPI, SVM-DI shows more pronounced regional characteristics in its correlations with other meteorological stations, with a significantly lower Coefficient of Variation. These results confirm that SVM-DI is a useful tool for regional drought analysis. The SVM-DI methodology offers a unique way to reduce the impact of extreme values and outliers when aggregating regional precipitation data.

Ensemble-Based Mutational Profiling and Network Analysis of the SARS-CoV-2 Spike Omicron XBB Lineages for Interactions with the ACE2 Receptor and Antibodies: Cooperation of Binding Hotspots in Mediating Epistatic Couplings Underlies Binding Mechanism and Immune Escape.

In this study, we performed a computational study of binding mechanisms for the SARS-CoV-2 spike Omicron XBB lineages with the host cell receptor ACE2 and a panel of diverse class one antibodies. The central objective of this investigation was to examine the molecular factors underlying epistatic couplings among convergent evolution hotspots that enable optimal balancing of ACE2 binding and antibody evasion for Omicron variants BA.1, BA2, BA.3, BA.4/BA.5, BQ.1.1, XBB.1, XBB.1.5, and XBB.1.5 + L455F/F456L. By combining evolutionary analysis, molecular dynamics simulations, and ensemble-based mutational scanning of spike protein residues in complexes with ACE2, we identified structural stability and binding affinity hotspots that are consistent with the results of biochemical studies. In agreement with the results of deep mutational scanning experiments, our quantitative analysis correctly reproduced strong and variant-specific epistatic effects in the XBB.1.5 and BA.2 variants. It was shown that Y453W and F456L mutations can enhance ACE2 binding when coupled with Q493 in XBB.1.5, while these mutations become destabilized when coupled with the R493 position in the BA.2 variant. The results provided a molecular rationale of the epistatic mechanism in Omicron variants, showing a central role of the Q493/R493 hotspot in modulating epistatic couplings between convergent mutational sites L455F and F456L in XBB lineages. The results of mutational scanning and binding analysis of the Omicron XBB spike variants with ACE2 receptors and a panel of class one antibodies provide a quantitative rationale for the experimental evidence that epistatic interactions of the physically proximal binding hotspots Y501, R498, Q493, L455F, and F456L can determine strong ACE2 binding, while convergent mutational sites F456L and F486P are instrumental in mediating broad antibody resistance. The study supports a mechanism in which the impact on ACE2 binding affinity is mediated through a small group of universal binding hotspots, while the effect of immune evasion could be more variant-dependent and modulated by convergent mutational sites in the conformationally adaptable spike regions.

Folliculotropic mycosis fungoides associated with follicular mucinosis: A case report and mini review.

Key Clinical Message: F-MF is a rare non-classic variant of MF. In the case of hair loss, this should be a diagnostic consideration. The essence of the diagnosis of F-MF is a careful medical history, physical examination, and a combination of immunohistological and molecular analyses (Cureus. 2022; 14:e21231, Ann Saudi Med. 2012; 32:283, Oman Med J. 2012; 27:134, Int J Dermatol. 2016; 55:1396, Saudi Med J. 2018; 39:994 and Case Rep Oncol. 2018; 11:436). Abstract: Mycosis fungoides (MF) is a primary cutaneous T-cell lymphoma with multiple subtypes. Follicular MF (F-MF) is a non-classic variant of MF. Histological features entail folliculotropism and damage of the epithelium lining of the hair follicles with or without mucin deposition. A 52-year-old male patient complained of recurrent skin lesions on the scalp over 8 months. The lesions appeared suddenly, enlarged over time, and became itchy. A skin punch biopsy was performed. Histological features included mucin deposits in the epithelium of the hair follicles and dense, predominantly perifollicular atypical lymphocytes infiltrating the follicular epithelium. The lymphoid cells were composed of CD3-positive T cells (CD4/CD8-positive T cells) with a shift in favor of the former. The case was diagnosed as F-MF on an immunohistological basis. The diagnosis of F-MF is often difficult for dermatologists and dermatopathologists alike. Not only clinicopathological correlations but also immunohistochemical and molecular analysis are required.

Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations.

In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles and binding mechanisms of convergent evolution for the SARS-CoV-2 Spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron Spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamic simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron Spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and molecular dynamics simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and molecular dynamics simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.

Pattern of Virtual Consultations in the Kingdom of Saudi Arabia: An Epidemiological Nationwide Study.

BACKGROUND: In the Kingdom of Saudi Arabia (KSA), little is known about the adoption of virtual consultations (VCs), with most studies being survey-based leading to varying results. This study aims to utilise secondary collected data on the use of both kinds of VCs currently available, and to epidemiologically describe the adoption of these consultations. METHODS: This retrospective study analysed data provided by the Ministry of Health between January 1st 2021 and June 30th 2022. For both the home-based and the hospital-based consultations, variables included the age and sex of patients, date of consultation, duration in minutes, closure status for the appointment and the governorate in which the patient is residing. A heat map was drawn to present patterns of utilisation across the country. RESULTS: The total number of VCs for both types were 1,008,228. For both types, females were higher adopters (54.73%). Of the total number of consultations, 751,156 were hospital-based. Of these consultations, family medicine consultations were the most common (20.42%), followed by internal medicine. Maternity follow-up clinics were higher in home-based clinics. The proportion of patient no-shows was high overall (48.30%). Utilisation was high in urban governorates, and low in rural ones. CONCLUSION: Findings have several implications on health policy. It provides further evidence of the importance of family medicine, where it was the most common speciality even in hospital-based settings. The high variability in the adoption of consultations across rural and urban areas as well as the extremely high number of patient-no-shows warrants further investigation.

Analysis of dermoscopy images of multi-class for early detection of skin lesions by hybrid systems based on integrating features of CNN models.

Skin cancer is one of the most fatal skin lesions, capable of leading to fatality if not detected in its early stages. The characteristics of skin lesions are similar in many of the early stages of skin lesions. The AI in categorizing diverse types of skin lesions significantly contributes to and helps dermatologists to preserve patients' lives. This study introduces a novel approach that capitalizes on the strengths of hybrid systems of Convolutional Neural Network (CNN) models to extract intricate features from dermoscopy images with Random Forest (Rf) and Feed Forward Neural Networks (FFNN) networks, leading to the development of hybrid systems that have superior capabilities early detection of all types of skin lesions. By integrating multiple CNN features, the proposed methods aim to improve the robustness and discriminatory capabilities of the AI system. The dermoscopy images were optimized for the ISIC2019 dataset. Then, the area of the lesions was segmented and isolated from the rest of the image by a Gradient Vector Flow (GVF) algorithm. The first strategy for dermoscopy image analysis for early diagnosis of skin lesions is by the CNN-RF and CNN-FFNN hybrid models. CNN models (DenseNet121, MobileNet, and VGG19) receive a region of interest (skin lesions) and produce highly representative feature maps for each lesion. The second strategy to analyze the area of skin lesions and diagnose their type by means of CNN-RF and CNN-FFNN hybrid models based on the features of the combined CNN models. Hybrid models based on combined CNN features have achieved promising results for diagnosing dermoscopy images of the ISIC 2019 dataset and distinguishing skin cancers from other skin lesions. The Dense-Net121-MobileNet-RF hybrid model achieved an AUC of 95.7%, an accuracy of 97.7%, a precision of 93.65%, a sensitivity of 91.93%, and a specificity of 99.49%.

Comparative phenotypic and genotypic analysis of community-acquired and hospital-acquired intra-abdominal infections among liver transplanted patients.

AIM: During liver transplantation, both hospital-acquired (HA) and community-acquired (CA) intra-abdominal infections (IAIs) are involved causing life-threatening diseases. Therefore, comparative studies of aerobic and facultative anaerobic HA-IAIs and CA-IAIs after liver transplantation surgery are necessary. METHODS AND RESULTS: The species of detected isolates (310) from intra-abdominal fluid were identified and classified into hospital-acquired intra-abdominal infections (HA-IAIs) and community-acquired intra-abdominal infections (CA-IAIs). Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii were the most commonly detected species. The resistant phenotypes were commonly detected among the HA-IAIs; however, the virulent phenotypes were the predominant strains of CA-IAIs. Regrettably, the resistance profiles were shocking, indicating the inefficacy of monotherapy in treating these isolates. Therefore, we confirmed the use of empirical combination therapies of amikacin and meropenem for treating all IAIs (FICI ≤ 0.5). Unfortunately, the high diversity and low clonality of all identified HA and CA-IAIs were announced with D-value in the range of 0.992-1. CONCLUSION: This diversity proves that there are infinite numbers of infection sources inside and outside healthcare centers.

The incorporation of sumac seed powder (Rhus coriaria L.) into the diet of quail breeders as a novel feed additive.

A total of 150 adult quails, aged 8 wk, were divided into 5 groups to study the effect of sumac seed powder on reproductive and productive parameters, egg quality, digestive enzymes, and quail breeders' blood profiles. Dietary supplements containing sumac powder were formulated as follows: group 1 (G1) (control, only basal diet); group 2 (G2) (basal diet + 1 g sumac powder/kg diet); group 3 (G3) (basal diet + 2 g sumac powder/kg diet); group 4 (G4) (basal diet + 3 g sumac powder/kg diet); and group 5 (G5) (basal diet + 4 g sumac powder/kg diet). The feed conversion ratio was significantly higher at all levels of sumac powder (P < 0.05) compared to the control group (G1). Overall, during the study (8-16 wk), quail-fed 3 g sumac powder/kg diet (G4) showed no significant increase (P > 0.05) in the feed intake compared to the control group. Sumac powder supplementation significantly (P < 0.05) increased egg number, egg weight, egg mass, fertility, and hatchability. While supplementing with sumac powder did not impact other egg quality parameters, it did significantly (P < 0.05) increase yolk percentage, Haugh unit, and unit surface shell weight. Furthermore, when compared to the control group (G1), birds given 2, 3, or 4 g of sumac powder/kg diet showed a significant improvement (P < 0.05) in hematological parameters such as red blood cells, white blood cells, and hemoglobin, as well as a decrease in glucose levels. Feeding quail with a 3 g sumac powder/kg diet (G4) resulted in significantly (P < 0.05) higher globulin levels and improved albumin/globulin ratio compared to other treatments and control (G1). Sumac powder intake significantly (P < 0.05) reduced plasma lipid profile, liver enzymes (aspartate aminotransferase, and alanine aminotransferase), and kidney functions (creatinine, and urea). Furthermore, the supplementation of sumac powder resulted in a substantial increase (P < 0.05) in the levels of amylase, lipase, and protease. Sumac powder administration also significantly (P < 0.05) improves immunity by boosting IgM, IgG, IgA, and lysozyme levels in quail breeders' plasma. Supplementing with sumac powder, on the other hand, increased levels of reduced glutathione, total antioxidant capacity, catalase, and superoxide dismutase. The results of the current study indicated that the addition of 1, 2, 3, and 4 g of sumac powder to the diet of Japanese quail breeders led to improvements in egg quality, digestive enzymes, reproductive and productive performances, and most blood hematological and biochemical parameters.