Application of small animal ultrasound imaging technology for identification of polycystic ovary syndrome in a mouse model.

BACKGROUND AND AIMS: Polycystic ovary syndrome (PCOS) is a hormonal disorder common among women of reproductive age, characterized by irregular menstrual periods, elevated levels of androgens, and polycystic ovaries, leading to various symptoms and complications such as infertility, metabolic issues, and increased risk of diabetes and heart disease. This study aimed to compare traditional histological methods and ultrasound imaging for consistency in identifying PCOS in a mouse model. The shortest time to construct the PCOS model using letrozole was determined. METHODS: Female C57/BL mice were randomly divided into three groups: Group A received normal saline and a regular diet; Group B received 1 mg/kg/day of letrozole with a regular diet; and Group C received 1 mg/kg/day of letrozole with a high-fat diet. All mice were administered letrozole by intragastric gavage daily for five weeks. The traditional identification method included measuring body weight, examining vaginal smears, monitoring the estrous cycle, measuring serum androgen levels, and performing H&E staining of ovarian tissues. The PCOS model was evaluated using ultrasound imaging to identify and monitor follicles. The significance of the difference between the traditional identification method and the ultrasonic method was calculated using the nonparametric McNemar test, and consistency between the two methods was assessed with the kappa-coefficient test. On this basis, the ultrasound imaging technology was used to monitor the model-making process for 2, 3 and 4 weeks, and to monitor the parameters of the ovary and follicles to judge the shortest time that gavage letrozole caused the appearance of vesicular follicles in the mouse ovary. RESULTS: The traditional identification method showed no PCOS phenotype in group A mice, while groups B and C showed multiple ovarian cystic follicles, indicating successful model induction. The ultrasound imaging results were consistent with the traditional method, showing no PCOS in group A and multiple cystic follicles in groups B and C. The McNemar test revealed no significant difference between the traditional and ultrasonic identification methods. The kappa-coefficient test assessed consistency, yielding a value of 0.903, indicating strong agreement between the methods. The ovarian area, diameter, and the number and diameter of cystic follicles were not significantly changed at two weeks in the letrozole group compared with the control group. At three weeks, there were significant increases in the number and in the diameter of vesicular follicles compared with control cells. At four weeks, the number and diameter, the maximum cross-sectional area and diameter of the ovary were significantly increased compared with the control group. CONCLUSIONS: The ultrasound and traditional methods provide consistent results for identifying PCOS in a mouse model. Construction of the PCOS model by letrozole gavage takes at least three weeks.

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples.

Multiplexed imaging technologies have made it possible to interrogate complex tissue microenvironments at sub-cellular resolution within their native spatial context. However, proper quantification of this complexity requires the ability to easily and accurately segment cells into their sub-cellular compartments. Within the supervised learning paradigm, deep learning-based segmentation methods demonstrating human level performance have emerged. However, limited work has been done in developing such generalist methods within the unsupervised context. Here we present an easy-to-use unsupervised segmentation (UNSEG) method that achieves deep learning level performance without requiring any training data via leveraging a Bayesian-like framework, and nucleus and cell membrane markers. We show that UNSEG is internally consistent and better at generalizing to the complexity of tissue morphology than current deep learning methods, allowing it to unambiguously identify the cytoplasmic compartment of a cell, and localize molecules to their correct sub-cellular compartment. We also introduce a perturbed watershed algorithm for stably and automatically segmenting a cluster of cell nuclei into individual nuclei that increases the accuracy of classical watershed. Finally, we demonstrate the efficacy of UNSEG on a high-quality annotated gastrointestinal tissue dataset we have generated, on publicly available datasets, and in a range of practical scenarios.

IDH1 Inhibition Potentiates Chemotherapy Efficacy in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is associated with a 5-year overall survival rate of just 13%, and development of chemotherapy resistance is nearly universal. PDAC cells overexpress wild-type isocitrate dehydrogenase 1 (IDH1) that can enable them to overcome metabolic stress, suggesting it could represent a therapeutic target in PDAC. Here, we found that anti-IDH1 therapy enhanced the efficacy of conventional chemotherapeutics. Chemotherapy treatment induced reactive oxygen species (ROS) and increased tricarboxylic acid cycle activity in PDAC cells, along with the induction of wild-type IDH1 expression as a key resistance factor. IDH1 facilitated PDAC survival following chemotherapy treatment by supporting mitochondrial function and antioxidant defense to neutralize ROS through the generation of α-ketoglutarate and NADPH, respectively. Pharmacologic inhibition of wild-type IDH1 with ivosidenib synergized with conventional chemotherapeutics in vitro and potentiated the efficacy of subtherapeutic doses of these drugs in vivo in murine PDAC models. This promising treatment approach is translatable through available and safe oral inhibitors and provides the basis of an open and accruing clinical trial testing this combination (NCT05209074). Significance: Targeting IDH1 improves sensitivity to chemotherapy by suppressing mitochondrial function and inducing oxidative stress, supporting the potential of the combination as an effective strategy for treating pancreatic cancer.

Design and evaluation of a deep learning-based automatic segmentation of maxillary and mandibular substructures using a 3D U-Net.

Background: Current segmentation approaches for radiation treatment planning in head and neck cancer patients (HNCP) typically consider the entire mandible as an organ at risk, whereas segmentation of the maxilla remains uncommon. Accurate risk assessment for osteoradionecrosis (ORN) or implant-based dental rehabilitation after radiation therapy may require a nuanced analysis of dose distribution in specific mandibular and maxillary segments. Manual segmentation is time-consuming and inconsistent, and there is no definition of jaw subsections. Materials and methods: The mandible and maxilla were divided into 12 substructures. The model was developed from 82 computed tomography (CT) scans of HNCP and adopts an encoder-decoder three-dimensional (3D) U-Net structure. The efficiency and accuracy of the automated method were compared against manual segmentation on an additional set of 20 independent CT scans. The evaluation metrics used were the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and surface DSC (sDSC). Results: Automated segmentations were performed in a median of 86 s, compared to manual segmentations, which took a median of 53.5 min. The median DSC per substructure ranged from 0.81 to 0.91, and the median HD95 ranged from 1.61 to 4.22. The number of artifacts did not affect these scores. The maxillary substructures showed lower metrics than the mandibular substructures. Conclusions: The jaw substructure segmentation demonstrated high accuracy, time efficiency, and promising results in CT scans with and without metal artifacts. This novel model could provide further investigation into dose relationships with ORN or dental implant failure in normal tissue complication prediction models.

Decoding contextual influences on auditory perception from primary auditory cortex.

Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus - a tritone pair - to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair's perception: either as an ascending or a descending step in pitch. We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-class-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch-class representations and taking their distance in the circular Shepard tone space predicts the opposite of the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch-class and pitch-class-direction cells, aligned with the neurophysiological responses. Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples.

Multiplexed imaging technologies have made it possible to interrogate complex tumor microenvironments at sub-cellular resolution within their native spatial context. However, proper quantification of this complexity requires the ability to easily and accurately segment cells into their sub-cellular compartments. Within the supervised learning paradigm, deep learning based segmentation methods demonstrating human level performance have emerged. Here we present an unsupervised segmentation (UNSEG) method that achieves deep learning level performance without requiring any training data. UNSEG leverages a Bayesian-like framework and the specificity of nucleus and cell membrane markers to construct an a posteriori probability estimate of each pixel belonging to the nucleus, cell membrane, or background. It uses this estimate to segment each cell into its nuclear and cell-membrane compartments. We show that UNSEG is more internally consistent and better at generalizing to the complexity of tissue samples than current deep learning methods. This allows UNSEG to unambiguously identify the cytoplasmic compartment of a cell, which we employ to demonstrate its use in an example biological scenario. Within the UNSEG framework, we also introduce a new perturbed watershed algorithm capable of stably and accurately segmenting a cell nuclei cluster into individual cell nuclei. Perturbed watershed can also be used as a standalone algorithm that researchers can incorporate within their supervised or unsupervised learning approaches to replace classical watershed. Finally, as part of developing UNSEG, we have generated a high-quality annotated gastrointestinal tissue dataset, which we anticipate will be useful for the broader research community. Segmentation, despite its long antecedents, remains a challenging problem, particularly in the context of tissue samples. UNSEG, an easy-to-use algorithm, provides an unsupervised approach to overcome this bottleneck, and as we discuss, can help improve deep learning based segmentation methods by providing a bridge between unsupervised and supervised learning paradigms.

Discoloration of stretched colored elastomeric modules : An in vivo study.

BACKGROUND: As the demands on esthetic orthodontic devices continue to increase, discoloration of colored elastomeric modules is still a concern for patients and orthodontics. Thus, we performed an in vivo study evaluating discoloration of stretched colored elastomeric modules (i.e., white, gray, and pink). MATERIALS AND METHODS: In all, 90 elastomeric modules of three different colors (white, gray and pink; 30 elastics from each color) were placed around brackets. The elastomeric modules were distributed and arranged randomly in the patients' four dental quadrants, and were removed after 1, 2, and 4 weeks. Color measurements were made before and after insertion into each patient's mouth. Digital images were taken with the camera of a mobile phone (iPhone X, Cupertino, CA, USA), and the variations in color were characterized using the Commission Internationale de l'Eclairage (CIE) color space system (L*a*b*) offered by Photoshop (Adobe, San Jose, CA, USA). Analysis of variance (ANOVA) and least significant difference (LSD) tests were used for statistical analyses. RESULTS: The white elastomeric modules were most prone to discoloration, followed by the pink and then finally by the gray colored modules. The amount of discoloration resulting from a random diet practiced by the patients increased gradually (but was not significant) for all elastomeric modules studied and reach a peak after 2 weeks for the white and gray elastomeric modules, while discoloration of the pink elastomeric modules plateaued after 1 week. CONCLUSION: Colored elastomeric modules (e.g., white, gray, and pink) discolor to variable degrees over time. Thus, patients should be advised that the consumption of food and drinks may result in discoloration of the elastomeric modules.

The Arabic Fonseca Anamnestic Index: Psychometric properties and use for screening temporomandibular disorders in prospective orthodontic patients.

OBJECTIVE: This study aimed to develop/evaluate the psychometric properties of the Arabic Fonseca Anamnestic Index (FAI-A) and estimate the prevalence of TMDs in prospective orthodontic patients. METHODS: The FAI-A was derived by forward-backward translation/cross-cultural adaption of the English FAI. Psychometric assessment of the FAI-A was performed with 308 orthodontic patients. Reliability was established via internal consistency and test-retest techniques, whereas, validity was verified by construct and convergent validity. RESULTS: Cronbach's alpha value for the FAI-A was 0.77, and the intraclass correlation coefficient was 0.99. For construct validity, the distribution of eigenvalues indicated that three items (mouth opening difficulty, jaw movement difficulty, and jaw fatigue) accounted for 60.5% of the total variance observed. For convergent validity, the FAI-A items were significantly correlated to the global question. CONCLUSION: The FAI-A showed good reliability/validity and may be useful for screening TMDs. About 17% of prospective orthodontic patients presented with moderate-to-severe TMD symptoms.

Recommendations for Early and Comprehensive Management of Type 2 Diabetes and Its Related Cardio-Renal Complications.

Type 2 diabetes (T2D) is a global health problem accompanied by an elevated risk of complications, the most common being cardiac and renal diseases. In Lebanon, the prevalence of T2D is estimated at 8-13%. Local medical practice generally suffers from clinical inertia, with gaps in the yearly assessment of clinical manifestations and suboptimal screening for major complications. The joint statement presented here, endorsed by five Lebanese scientific medical societies, aims at providing physicians in Lebanon with a tool for early, effective, and comprehensive care of patients with T2D. Findings from major randomized clinical trials of antidiabetic medications with cardio-renal benefits are presented, together with recommendations from international medical societies. Optimal care should be multidisciplinary and should include a multifactorial risk assessment, lifestyle modifications, and a regular evaluation of risks, including the risks for cardiovascular (CV) and renal complications. With international guidelines supporting a shift in T2D management from glucose-lowering agents to disease-modifying drugs, the present statement recommends treatment initiation with metformin, followed by the addition of sodium-glucose cotransporter 2 inhibitors or glucagon-like peptide-1 receptor agonists due to their CV and renal protection properties, whenever possible. In addition to the selection of the most appropriate pharmacological therapy, efforts should be made to provide continuous education to patients about their disease, with the aim to achieve a patient-centered approach and to foster self-management and adherence to the medical plan. Increasing the level of patient engagement is expected to be associated with favorable health outcomes. Finally, this statement recommends setting an achievable individualized management plan and conducting regular follow-ups to monitor the patients' glycemic status and assess their risks every 3-6 months.

Bilateral orbital myositis in a patient with rheumatoid arthritis on treatment with tofacitinib: a report and review of literature.

Orbital myositis is a rare inflammatory condition affecting the extraocular muscles of the eyes. It has also been linked to systemic autoimmune diseases. We present a case of orbital myositis in a 57-year-old male undergoing treatment for rheumatoid arthritis (RA) with tofacitinib, a Janus kinase inhibitor (JAK). Prompt administration of intravenous steroids led to rapid symptom improvement. To date, only six published cases have documented the association between RA and orbital myositis. This is the first description of orbital myositis occurring during treatment with the anti-inflammatory drug tofacitinib, an increasingly used disease-modifying anti-rheumatic drug (DMARD). We review the literature and emphasize the importance of ongoing vigilance regarding adverse events linked to tofacitinib.

CBCT based study to analyze and classify root canal morphology of maxillary molars - A retrospective study.

OBJECTIVE: The study aims to evaluate maxillary molars' root and root canal morphology among the Saudi population using Cone-Beam Computed Tomography scanning (CBCT). SUBJECTS AND METHODS: Retrospectively, the CBCT scans of 483 Saudi nationals were evaluated to identify the number of roots and root canals in maxillary first and second molars. The records were tabulated and classified according to Vertucci and a new system for root and canal classification given by Ahmed and Dummer. Fisher's exact test was used to analyze the data statistically. To check for symmetry, comparisons were made between all the maxillary first molars (MFM's) and maxillary second molars (MSM's) on opposing quadrants. Inter Observer variability was seen using Cohen's Kappa test. RESULTS: MFM's presented with three roots with Type II Vertucci canal configuration (VC) commonly seen among them. MSM's had more variations in the number of roots and canals, although three roots and Type I VC were predominantly seen. When comparing the two genders statistically significant difference was observed in both maxillary molars at a 5% level using Fisher's exact test. Three roots with four canals (3R4C) were predominantly observed in the MFM's (85.6%) and three roots with three canals (3R3C) identified in 51.95% were more common than 3R4C (43.55%) in MSM's. Both the maxillary molars bilaterally, exhibited a high percentage of symmetry in root and canal configurations. CONCLUSIONS: Identification of root canal morphology of molars would reduce the chances of root canal failures by making sure all canals are obturated. This study provides supplemental information about the root canals of maxillary molars in a Saudi Arabian subpopulation.

Yield, carbon stock, and price dynamics of agroforestry tree species in district Mardan, Khyber Pakhtunkhwa, Pakistan.

A socio-economic study was conducted in district Mardan of the Khyber Pakhtunkhwa (KP) province of Pakistan to get a comprehensive knowledge of the agroforestry tree species grown on the farmlands, their yield, and carbon stock. For yield and carbon stock estimation, data were collected from 59 sample plots by measuring the diameter, height, volume, and biomass of selected agroforestry tree species through D-tape and Haga altimeter. A total of 59 sample plots were inventoried using 2.5 percent sampling intensity. Each sample plot has an area of 0.5 ha, where each tree with a Diameter at Breast Height (DBH) ≥ 5 cm was inventoried. The calculated amount of volume of each tree species was then converted to biomass by multiplying it by the density of wood and the Biomass Expansion Factor (BEF). Total yield and C stock for the selected agroforestry tree species were 11535.2 metric tons and 2102.2 metric tons, respectively. Populus euroamericana is classified as the main tree with 28% growing stock prior to Morus alba by 21%, while Melia azedarach, Eucalyptus camaldulensis, Dalbergia sissoo, Acacia nilotica, Salix tetrasperma, and Bombax ceiba consist of 15%, 12%, 8%, 6%,7% and 3% growing stock respectively. Among the species found in different sampling plots the yield of Populus euroamericana was found to be 4747.5 metric tons and it was followed by the species Morus alba found at 2027.3 metric tons. Similarly, the volume for Melia azedarach, Eucalyptus camaldulensis, Dalbergia sissoo, Salix spp, Boombox ceiba, and Acacia nilotica was 1532.2 tons,1503 ton,745.7,203.5ton, 555.4ton and 220.5ton, respectively. The carbon stock for Populus euroamericana was calculated as 777.8 ton/ha, while for Eucalyptus camaldulensis, Melia azedarach, Morus alba, Dalbergia sissoo, Acacia nilotica, Salix species, and Bombax ceiba it was calculated as 312.3ton/ha, 272.1ton/ha, 363ton/ha, 245.1ton/ha, 51.4ton/ha, 27.3ton/ha and 53.2ton/ha, respectively. The questionnaire survey conducted for price dynamics showed that the majority of respondents purchase timber from the market for construction. But they use farm trees with low-quality city construction. They dislike using local timber in the conventional building as timber from farm trees is liable to insect attack. Rs. 50,000-100000, (33.33%) of daily sales was concluded from 50% of the trader while (16.7%) of the traders have their sales between Rs.150,000-200,000. Therefore, it is concluded by the authors that both provincial and federal government should promote agroforestry in Pakistan through different incentives because it has the potential to cope with dilemma of deforestation of natural forests and improve the livelihood of local peoples. It is strongly recommended that special projects just like the Ten Billion Tree Afforestation Project (T-BTTP) should be launched for agroforestry plantation and promotion in the country to sustain the ecological harmony and uplift the socio-economic condition of the peoples of Pakistan.

Environmental sustainability assessment of softwood and hardwood seedlings production in forest nurseries: A case study from Pakistan.

This article describes the environmental impacts of producing a single seedling in forest nurseries of selected districts (i.e., Haripur, Abbottabad, and Mansehra) of Hazara Division of Khyber Pakhtunkhwa, Pakistan using the life cycle assessment (LCA) approach. This study was based on the cradle-to-gate approach which begins with the pre-nursery stage and progresses toward the main nursery before transplanting seedlings into the plantation site. Data or life cycle inventory (LCI) of seedling production were collected through questionnaire surveys and personal meetings with forest nurseries managers and workers regarding consumption of different inputs such as electricity, diesel, fertilizers, herbicides, and polyethylene bags, organic manure, and water consumption. The SimaPro software version 8.5 and the CML2000 v2.05 environmental model was applied to perform life cycle impact assessment (LCIA) for a single seedling production in forest nurseries in the study area. In line with the objectives of the study, primary data regarding inputs and outputs of the nurseries were collected from 35 nurseries in the study area by using a random questionnaire method. In addition, secondary data were taken from online databases such as Eco-invent v.3.2 CORRIM and peer-reviewed published literature. For this study, a functional unit of a single seedling was considered. Production weighted average data were modeled in the latest environmental modeling software i.e., SimaPro v.8.5 for ten US-EPA most wanted environmental impacts, such as global warming potential (GWP), abiotic depletion (AD), eutrophication potential (EP), acidification potential (AP), freshwater aquatic eco-toxicity (FAE), marine water eco-toxicity (MWE), terrestrial eco-toxicity (TE), ozone layer depletion (OLD), photochemical oxidation (PO), and human toxicity (HT). The results showed that the highest environmental impact posed by a single seedling was marine aquatic eco-toxicity (11.31360 kg 1,4-DB eq), followed by global warming potential (0.02945 kg CO2 eq) and (0.01227 kg 1,4-DB eq) human toxicity. The primary reason for these environmental burdens was the use of synthetic fertilizers in forest nurseries and the consumption of fossil fuels in nursery mechanization and transportation activities. The total cumulative energy demand for a single seedling was (0.800 MJ) with more than 90% contribution from fossil fuel energy resources such as petrol and diesel. It is therefore highly recommended to use renewable energy resources and organic fertilizers instead of chemical fertilizers in forest nurseries to avoid and minimize greenhouse gas emissions (GHS) and other toxic emissions in the study area.

A Review on SAPO-34 Zeolite Materials for CO2 Capture and Conversion.

Among several known zeolites, silicoaluminophosphate (SAPO)-34 zeolite exhibits a distinct chemical structure, unique pore size distribution, and chemical, thermal, and ion exchange capabilities, which have recently attracted considerable research attention. Global carbon dioxide (CO2 ) emissions are a serious environmental issue. Current atmospheric CO2 level exceeds 414 parts per million (ppm), which greatly influences humans, fauna, flora, and the ecosystem as a whole. Zeolites play a vital role in CO2 removal, recycling, and utilization. This review summarizes the properties of the SAPO-34 zeolite and its role in CO2 capture and separation from air and natural gas. In addition, due to their high thermal stability and catalytic nature, CO2 conversions into valuable products over single metal, bi-metallic, and tri-metallic catalysts and their oxides supported on SAPO-34 were also summarized. Considering these accomplishments, substantial problems related to SAPO-34 are discussed, and future recommendations are offered in detail to predict how SAPO-34 could be employed for greenhouse gas mitigation.

Patient information - is it ever enough? A prospective audit of information provision for orthognathic treatment at the Queen Victoria Hospital (QVH), East Grinstead.

Appropriate patient information is essential to improving patient experience. This prospective audit looked at compliance with the Queen Victoria Hospital (QVH) orthognathic information patient protocol and patient opinion regarding information provision. A total of 77 patients participated, with 75 reporting that they received sufficient information to make an informed decision. Prior to attending the MDT, 69 patients had read the information leaflet, although only 37 had accessed the British Orthodontic Society (BOS) online resource. Despite a general trend in the use of online resources, patients do not necessarily choose to access information online. During the development of electronic information resources, we need to explore how to utilise new technology to continue improving patient experience during the consent process.

SARS CoV-2 infection in a patient with sickle cell disease - Atypical presentation.

Severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) infection causes the disease known as coronavirus disease that started in Wuhan (China) in December 2019, leading to the current COVID-19 pandemic. The common presenting symptoms include fever, dry cough, shortness-of-breath, while sore throat, diarrhea, and abdominal and chest pain are the least. The atypical presentation of SARS CoV-2 infection poses a challenge for family physicians to screen and manage such patients for COVID-19 and specifically those at high risk with underlying disease such a sickle cell disease. Herein, we report a case of SARS CoV-2 infection in a known patient of sickle cell disease (SCD) with an atypical presentation, in whom the course of the disease was mild to moderate, uncomplicated, and the patient had an uneventful recovery. Primary care physicians should be vigilant to screen and manage such patients with established protocols, especially in the ongoing COVID-19 pandemic.

Highly Efficient Permeation and Separation of Gases with Metal-Organic Frameworks Confined in Polymeric Nanochannels.

This work demonstrates the confinement of porous metal-organic framework (HKUST-1) on the surface and walls of track-etched nanochannel in polyethylene terephthalate (np-PET) membrane using a liquid-phase epitaxy (LPE) technique. The composite membrane (HKUST-1/np-PET) exhibits defect-free MOF growth continuity, strong attachment of MOF to the support, and a high degree of flexibility. The high flexibility and the strong confinement of the MOF in composite membrane results from (i) the flexible np-PET support, (ii) coordination attachment between HKUST-1 and the support, and (iii) the growth of HKUST-1 crystal in nanoconfined geometries. The MOF has a preferred growth orientation with a window size of 3.5 Å, resulting in a clear cut-off of CO2 from natural gas and olefins. The experimental results and DFT calculations show that the restricted diffusion of gases only takes place through the nanoporous MOF confined in the np-PET substrate. This research thereby provides a new perspective to grow other porous MOFs in artificially prepared nanochannels for the realization of continuous, flexible, and defect-free membranes for various applications.

Impact of weather conditions on incidence and mortality of COVID-19 pandemic in Africa.

OBJECTIVE: The weather-related conditions change the ecosystem and pose a threat to social, economic and environmental development. It creates unprecedented or unanticipated human health problems in various places or times of the year. Africa is the world's second largest and most populous continent and has relatively changeable weather conditions. The present study aims to investigate the impact of weather conditions, heat and humidity on the incidence and mortality of COVID-19 pandemic in various regions of Africa. MATERIALS AND METHODS: In this study, 16 highly populated countries from North, South, East, West, and Central African regions were selected. The data on COVID-19 pandemic including daily new cases and new deaths were recorded from World Health Organization. The daily temperature and humidity figures were obtained from the weather web "Time and Date". The daily cases, deaths, temperature and humidity were recorded from the date of appearance of first case of "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)" in the African region, from Feb 14 to August 2, 2020. RESULTS: In African countries, the daily basis mean temperature from Feb 14, 2020 to August 2, 2020 was 26.16±0.12°C, and humidity was 57.41±0.38%. The overall results revealed a significant inverse correlation between humidity and the number of cases (r= -0.192, p<0.001) and deaths (r= -0.213, p<0.001). Similarly, a significant inverse correlation was found between temperature and the number of cases (r= -0.25, p<0.001) and deaths (r=-0.18, p<0.001). Furthermore, the regression results showed that with 1% increase in humidity the number of cases and deaths was significantly reduced by 3.6% and 3.7% respectively. Congruently, with 1°C increase in temperature, the number of cases and deaths was also significantly reduced by 15.1% and 10.5%, respectively. CONCLUSIONS: Increase in relative humidity and temperature was associated with a decrease in the number of daily cases and deaths due to COVID-19 pandemic in various African countries. The study findings on weather events and COVID-19 pandemic have an impact at African regional levels to project the incidence and mortality trends with regional weather events which will enhance public health readiness and assist in planning to fight against this pandemic.

Can plant-derived phytochemicals provide symptom relief for hair loss? A critical review.

It is known that hair growth disorders and hair loss can cause personal distress and affect well-being. Whilst clinical conditions remain a target for medical research, current research on hair follicle biology and hair growth control mechanisms also provides opportunities for a range of non-medical and cosmetic interventions that have a modulating effect on the scalp and follicle function. Furthermore, an improvement of the hair fibre characteristics (cuticle structure, cortex size and integrity) could add to the overall positive visual effect of the hair array. Since phytochemicals are a popular choice because of their traditional appeal, this review provides a critical evaluation of the available evidence of their activity for hair benefit, excluding data obtained from animal tests, and offers recommendations on improving study validity and the robustness of data collection in pre-clinical and clinical studies.

La perte des cheveux ou les troubles de la croissance sont connus pour engendrer une grande détresse et affecter le bien-être des individus. Bien que les maladies soient la cible principale de la recherche médicale, de récentes découvertes sur la biologie du follicule pileux et les mécanismes de contrôle de la pousse de cheveux pourraient donner lieu à des interventions non-médicales ou cosmétiques afin d'impacter le cuir chevelu et le follicule. De plus, améliorer les caractéristiques de la fibre capillaire (structure des cuticules, taille et intégrité du cortex) pourrait contribuer à embellir l'apparence de la masse capillaire. Les phytoingrédients sont populaires car traditionnellement utilisés dans les cosmétiques, et cette revue présente une évaluation critique de leurs bénéfices pour les cheveux, en excluant les données issues de tests sur les animaux. Des recommandations afin d'améliorer la collecte de données et la validité des études pré-cliniques et cliniques sont aussi présentées dans cette revue.

Effects of non-surgical rapid maxillary expansion on nasal structures and breathing: A systematic review.

OBJECTIVE: This systematic review aims to determine the effects of non-surgical rapid maxillary expansion (RME) on breathing and upper airway structures. MATERIALS AND METHODS: An electronic search of the scientific literature from January 2005 to June 2016 was done using Web of Science, Dentistry & Oral Sciences Source and PubMed databases. A combination of search terms "rapid maxillary expansion", "nasal", "airway" and "breathing" were used. Studies that involved surgical or combined RME-surgical treatments and patients with craniofacial anomalies were excluded. RESULTS: The initial screening yielded a total of 183 articles. After evaluation of the titles, abstracts and accessing the full text, a total of 20 articles fulfilled both inclusion/exclusion criteria and possessed adequate evidence to be incorporated into this review. CONCLUSIONS: Non-surgical RME was found to improve breathing, increase nasal cavity geometry and decrease nasal airway resistance in children and adolescents.