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The expanding global population and the use of conventional agrochemical pesticides have led to the loss of crop yield and food shortages. Excessive pesticide used in agriculture risks life forms by contaminating soil and water resources, necessitating the use of nano agrochemicals. This article focuses on synthesis moiety and use of nanopesticides for enhanced stability, controlled release mechanisms, improved efficacy, and reduced pesticide residue levels. The current literature survey offered regulatory frameworks for commercial deployment of nanopesticides and evaluated societal and environmental impacts. Various physicochemical and biological processes, especially microorganisms and advanced oxidation techniques are important in treating pesticide residues through degradation mechanisms. Agricultural waste could be converted into nanofibers for sustainable composites production, new nanocatalysts, such as N-doped TiO2 and bimetallic nanoparticles for advancing pesticide degradation. Microbial and enzyme methods have been listed as emerging nanobiotechnology tools in achieving a significant reduction of chlorpyrifos and dimethomorph for the management of pesticide residues in agriculture. Moreover, cutting-edge biotechnological alternatives to conventional pesticides are advocated for promoting a transition towards more sustainable pest control methodologies. Application of nanopesticides could be critical in addressing environmental concern due to its increased mobility, prolonged persistence and ecosystem toxicity. Green synthesis of nanopesticides offers solutions to environmental risks associated and using genetic engineering techniques may induce pest and disease resistance for agricultural sustainability. Production of nanopesticides from biological sources is necessary to develop and implement comprehensive strategies to uphold agricultural productivity while safeguarding environmental integrity.

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Deep learning (DL) models for medical image classification frequently struggle to generalize to data from outside institutions. Additional clinical data are also rarely collected to comprehensively assess and understand model performance amongst subgroups. Following the development of a single-center model to identify the lung sliding artifact on lung ultrasound (LUS), we pursued a validation strategy using external LUS data. As annotated LUS data are relatively scarce-compared to other medical imaging data-we adopted a novel technique to optimize the use of limited external data to improve model generalizability. Externally acquired LUS data from three tertiary care centers, totaling 641 clips from 238 patients, were used to assess the baseline generalizability of our lung sliding model. We then employed our novel Threshold-Aware Accumulative Fine-Tuning (TAAFT) method to fine-tune the baseline model and determine the minimum amount of data required to achieve predefined performance goals. A subgroup analysis was also performed and Grad-CAM++ explanations were examined. The final model was fine-tuned on one-third of the external dataset to achieve 0.917 sensitivity, 0.817 specificity, and 0.920 area under the receiver operator characteristic curve (AUC) on the external validation dataset, exceeding our predefined performance goals. Subgroup analyses identified LUS characteristics that most greatly challenged the model's performance. Grad-CAM++ saliency maps highlighted clinically relevant regions on M-mode images. We report a multicenter study that exploits limited available external data to improve the generalizability and performance of our lung sliding model while identifying poorly performing subgroups to inform future iterative improvements. This approach may contribute to efficiencies for DL researchers working with smaller quantities of external validation data.

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BACKGROUND: Primary endpoint measures in clinical trials are typically measures of disease severity, with patient-reported outcome measures (PROMs) relegated as secondary endpoints. However, validation of some PROMs may be more rigorous than that of disease severity measures, which could provide support for a primary role for PROMs. OBJECTIVES: This study reports on 24 peer reviewed journal articles that used the Dermatology Life Quality Index (DLQI) as primary outcome, derived from a systematic review of randomized controlled trials (RCTs) utlizing DLQI, covering all diseases and interventions. METHODS: The study protocol was prospectively published on the PROSPERO database, and the study followed PRISMA guidelines. Searches were made using MEDLINE, The Cochrane Library, Embase, Web of Science, Scopus, CINAHL (EBSCO) and PsycINFO databases and records were combined into an Endnote database. Records were filtered for duplicates and selected based on study inclusion/exclusion criteria. Full-text articles were sourced and data were extracted by two reviewers into a bespoke REDCap database, with a third reviewer adjudicating disagreements. The Jadad scoring method was used to determine risk of bias. RESULTS: Of the 3220 publications retrieved from online searching, 457 articles met the eligibility criteria and included 198 587 patients. DLQI scores were used as primary outcomes in 24 (5.3%) of these studies comprising 15 different diseases and 3436 patients. Most study interventions (17 of 24 studies, 68%) were systemic drugs, with biologics (liraglutide, alefacept, secukinumab, ustekinumab, adalimumab) accounting for 5 of 25 pharmacological interventions (20%). Topical treatments comprised 32% (8 studies), whereas nonpharmacological interventions (n = 8) were 24% of the total interventions (N = 33). Three studies used nontraditional medicines. Eight studies were multicentred (33.3%), with trials conducted in at least 14 different countries, and four studies (16.7%) were conducted in multiple countries. The Jadad risk of bias scale showed that bias was uncertain or low, as 87.5% of studies had Jadad scores of ≥ 3. CONCLUSIONS: This study provides evidence for use of the DLQI as a primary outcome in clinical trials. Researchers and clinicians can use this data to inform decisions about further use of the DLQI as a primary outcome.

Measuring the quality of life (QoL) of people with skin diseases during controlled studies is normally done by groups of researchers and clinicians. To determine how much a skin disease affects a person's QoL, information on the patient and the severity of their skin condition is collected using laboratory measurements, and/or looking at the skin. Asking patients to self-report the impact of their skin condition using questionnaires they have completed themselves has usually been of secondary importance, even though these questionnaires can often be much more reliable. However, patient-reported outcomes are now being used more often as primary measures in controlled studies. Self-report measures can provide information on how effective treatment is, which can help government agencies to approve new products and justify claims made by drug companies. This study reports on 24 academic studies that used the Dermatology Life Quality Index (DLQI) (a type of self-report measure for dermatology patients) as a primary tool of measurement in controlled trials for a range of different skin diseases and treatments. Our study findings are important, as researchers and clinicians can use this data to help make decisions regarding use of the DLQI.

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BACKGROUND: Over 29 years of clinical application, the Dermatology Life Quality Index (DLQI) has remained the most used patient-reported outcome (PRO) in dermatology due to its robustness, simplicity and ease of use. OBJECTIVES: To generate further evidence of the DLQI's utility in randomized controlled trials (RCTs) and to cover all diseases and interventions. METHODS: The methodology followed PRISMA guidelines and included seven bibliographical databases, searching articles published from 1 January 1994 until 16 November 2021. Articles were reviewed independently by two assessors, and an adjudicator resolved any opinion differences. RESULTS: Of 3220 screened publications, 454 articles meeting the eligibility criteria for inclusion, describing research on 198 190 patients, were analysed. DLQI scores were primary endpoints in 24 (5.3%) of studies. Most studies were of psoriasis (54.1%), although 69 different diseases were studied. Most study drugs were systemic (85.1%), with biologics comprising 55.9% of all pharmacological interventions. Topical treatments comprised 17.0% of total pharmacological interventions. Nonpharmacological interventions, mainly laser therapy and ultraviolet radiation treatment, comprised 12.2% of the total number of interventions. The majority of studies (63.7%) were multicentric, with trials conducted in at least 42 different countries; 40.2% were conducted in multiple countries. The minimal clinically importance difference (MCID) was reported in the analysis of 15.0% of studies, but only 1.3% considered full score meaning banding of the DLQI. Forty-seven (10.4%) of the studies investigated statistical correlation of the DLQI with clinical severity assessment or other PRO/quality of life tools; and 61-86% of studies had within-group scores differences greater than the MCID in 'active treatment arms'. The Jadad risk-of-bias scale showed that bias was generally low, as 91.8% of the studies had Jadad scores of ≥ 3; only 0.4% of studies showed a high risk of bias from randomization. Thirteen per cent had a high risk of bias from blinding and 10.1% had a high risk of bias from unknown outcomes of all participants in the studies. In 18.5% of the studies the authors declared that they followed an intention-to-treat protocol; imputation for missing DLQI data was used in 34.4% of studies. CONCLUSIONS: This systematic review provides a wealth of evidence of the use of the DLQI in clinical trials to inform researchers' and -clinicians' decisions for its further use. Recommendations are also made for improving the reporting of data from future RCTs using the DLQI.

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Carbon dioxide (CO2) emissions from the combustion of fossil fuels and coal are primary contributors of greenhouse gases leading to global climate change and warming. The toxicity of heavy metals and metalloids in the environment threatens ecological functionality, diversity and global human life. The ability of microalgae to thrive in harsh environments such as industrial wastewater, polluted lakes, and contaminated seawaters presents new, environmentally friendly, and less expensive CO2 remediation solutions. Numerous microalgal species grown in wastewater for industrial purposes may absorb and convert nitrogen, phosphorus, and organic matter into proteins, oil, and carbohydrates. In any multi-faceted micro-ecological system, the role of bacteria and their interactions with microalgae can be harnessed appropriately to enhance microalgae performance in either wastewater treatment or algal production systems. This algal-bacterial energy nexus review focuses on examining the processes used in the capture, storage, and biological fixation of CO2 by various microalgal species, as well as the optimized production of microalgae in open and closed cultivation systems. Microalgal production depends on different biotic and abiotic variables to ultimately deliver a high yield of microalgal biomass.

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The bioremediation of soils contaminated with petroleum hydrocarbons (PHCs) has emerged as a promising approach, with its effectiveness contingent upon various types of PHCs, i.e., crude oil, diesel, gasoline, and other petroleum products. Strategies like genetically modified microorganisms, nanotechnology, and bioaugmentation hold potential for enhancing remediation of polycyclic aromatic hydrocarbon (PAH) contamination. The effectiveness of bioremediation relies on factors such as metabolite toxicity, microbial competition, and environmental conditions. Aerobic degradation involves enzymatic oxidative reactions, while bacterial anaerobic degradation employs reductive reactions with alternative electron acceptors. Algae employ monooxygenase and dioxygenase enzymes, breaking down PAHs through biodegradation and bioaccumulation, yielding hydroxylated and dihydroxylated intermediates. Fungi contribute via mycoremediation, using co-metabolism and monooxygenase enzymes to produce CO2 and oxidized products. Ligninolytic fungi transform PAHs into water-soluble compounds, while non-ligninolytic fungi oxidize PAHs into arene oxides and phenols. Certain fungi produce biosurfactants enhancing degradation of less soluble, high molecular-weight PAHs. Successful bioremediation offers sustainable solutions to mitigate petroleum spills and environmental impacts. Monitoring and assessing strategy effectiveness are vital for optimizing biodegradation in petroleum-contaminated soils. This review presents insights and challenges in bioremediation, focusing on arable land safety and ecotoxicological concerns.

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Good quality water and arable land are required for both domestic and agricultural uses. Increasing population leads to urbanization and industrialization increasing the need to share these resources and creating threats to the food supply. Higher meat consumption requires mitigation strategies to protect food and mitigate economic crises, especially in developing nations. The production of food crops for energy purposes and lower yield due to climate change increase food prices as well as have a negative impact on the economy. Thus, an alternative food source is required featuring high forage components to reduce grazing periods and to prevent rangeland degradation. Halophytes can tolerate high salinity and can be easily grown for fodder in coastal areas where fodder is a problem. Varied climate conditions offer opportunities to grow suitable halophytes for specific purposes. One important feature is their use as fodder. To reduce food shortages, saline areas could be used to grow nutritive and productive halophytic forage. Wild plants have undesirable metabolites produced in harsh conditions which may be harmful for ruminant health. Halophytes have moderate amounts of these metabolites which are nontoxic. Halophytes can be grown without intruding on agricultural lands and freshwater resources and could promote livestock production which may improve the socio-economic conditions of poor farmers in a sustainable and ecofriendly manner.

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OBJECTIVE: To assign clinical meanings to the Family Reported Outcome Measure (FROM-16) scores through the development of score bands using the anchor-based approach. DESIGN AND SETTING: A cross-sectional online study recruited participants through UK-based patient support groups, research support platforms (HealthWise Wales, Autism Research Centre-Cambridge University database, Join Dementia Research) and through social service departments in Wales. PARTICIPANTS: Family members/partners (aged ≥18 years) of patients with different health conditions. INTERVENTION: Family members/partners of patients completed the FROM-16 questionnaire and a Global Question (GQ). MAIN OUTCOME MEASURE: Various FROM-16 band sets were devised as a result of mapping of mean, median and mode of the GQ scores to FROM-16 total score, and receiver operating characteristic-area under the curve cut-off values. The band set with the best agreement with GQ based on weighted kappa was selected. RESULTS: A total of 4413 family members/partners (male=1533, 34.7%; female=2858, 64.8%; Prefer not to say=16, 0.4%; other=6, 0.14%) of people with a health condition (male=1994, 45.2%; female=2400, 54.4%; Prefer not to say=12, 0.3%; other=7, 0.16%) completed the online survey: mean FROM-16 score=15.02 (range 0-32, SD=8.08), mean GQ score=2.32 (range 0-4, SD=1.08). The proposed FROM-16 score bandings are: 0-1=no effect on the quality of life of family member; 2-8=small effect on family member; 9-16=moderate effect on family member; 17-25=very large effect on family member; 26-32=extremely large effect on family member (weighted kappa=0.60). CONCLUSION: The FROM-16 score descriptor bands provide new information to clinicians about interpreting scores and score changes, allowing better-informed treatment decisions for patients and their families. The score banding of FROM-16, along with a short administration time, demonstrates its potential to support holistic clinical practice.

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OBJECTIVES: To evaluate the accuracy of a bedside, real-time deployment of a deep learning (DL) model capable of distinguishing between normal (A line pattern) and abnormal (B line pattern) lung parenchyma on lung ultrasound (LUS) in critically ill patients. DESIGN: Prospective, observational study evaluating the performance of a previously trained LUS DL model. Enrolled patients received a LUS examination with simultaneous DL model predictions using a portable device. Clip-level model predictions were analyzed and compared with blinded expert review for A versus B line pattern. Four prediction thresholding approaches were applied to maximize model sensitivity and specificity at bedside. SETTING: Academic ICU. PATIENTS: One-hundred critically ill patients admitted to ICU, receiving oxygen therapy, and eligible for respiratory imaging were included. Patients who were unstable or could not undergo an LUS examination were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 100 unique ICU patients (400 clips) were enrolled from two tertiary-care sites. Fifty-six patients were mechanically ventilated. When compared with gold standard expert annotation, the real-time inference yielded an accuracy of 95%, sensitivity of 93%, and specificity of 96% for identification of the B line pattern. Varying prediction thresholds showed that real-time modification of sensitivity and specificity according to clinical priorities is possible. CONCLUSIONS: A previously validated DL classification model performs equally well in real-time at the bedside when platformed on a portable device. As the first study to test the feasibility and performance of a DL classification model for LUS in a dedicated ICU environment, our results justify further inquiry into the impact of employing real-time automation of medical imaging into the care of the critically ill.

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Introduction: Skin diseases affect patients at any age, but as each period in life is different, tools used to assess quality of life impairment should be adjusted according to the particular age group. Adolescence is a unique time, when young individuals go through many changes, making them especially vulnerable to stress. Aim: Translation and validation of a Polish language version of the Teenagers Quality of Life questionnaire (T-QoL) questionnaire. Material and methods: T-QoL was translated following international guidelines. A group of 34 dermatological patients, aged 12-19 years old, with various skin diseases were given the T-QoL as well as the CDLQI or DLQI to complete. They were also asked to complete the T-QoL questionnaire for the second time after 3-5 days. Statistical analysis of the results was performed. Results: The Polish version of T-QoL is internally consistent (Cronbach α 0.893 for the whole questionnaire). Moreover, it presents very good convergent validity (ICC = 0.864). No statistically significant differences between each question were noticed between the first and second time of completing the form. T-QoL scores correlated significantly with DLQI (p = 0.008, r = 0.636) and CDLQI (p < 0.001, r = 0.777) scores. Conclusions: The Polish version of the T-QoL questionnaire is a reliable instrument with adequate convergent validity, consistency and reproducibility. It can be successfully used to measure quality of life impairment among teenagers.

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Ewing sarcoma is one of the rare, highly malignant neuroectodermal tumors frequently involving bones. Primary orbital Ewing sarcoma is extremely uncommon. We report a rare case of a 5-year-old boy who presented to us with a painless, slow-growing mass above the medial canthus of the left eye, the clinical appearance of which was masquerading as an internal angular dermoid. The child was subsequently diagnosed to have primary orbital Ewing sarcoma. Primary orbital Ewing sarcoma is a rare tumor with poor prognosis, poses diagnostic challenges, and demands a high index of clinical suspicion.

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In the past, many studies have been conducted on the optimization of reinforced concrete (RC) structures. These studies have demonstrated the effectiveness of different optimization techniques to obtain an economical design. However, the use of optimization techniques to an obtain economical design is not so practical due to the difficulty in applying most of the optimization techniques to achieve an optimal solution. The RC beam is one of the most common structural elements encountered by a practising design engineer. The current study is designed to highlight the potential of the Solver tool in MS Excel as an easy-to-use option for optimizing the design of simply supported RC beams. A user-friendly interface was developed in a spreadsheet in which beam design parameters from a typical design can be entered and an economical design can be obtained using the Evolutionary Algorithm available in the MS Excel Solver tool. To demonstrate the effectiveness of the developed optimization tool, three examples obtained from the literature have been optimized. The results showed that up to 24% economical solution can be obtained by keeping the same material strengths that were assumed in the original design. However, if material strength is also considered as a variable, up to 44% of the economical solution can be obtained. A parametric study was also conducted to investigate the effect of different design variables on the economical design of simply supported RC beams and to derive useful rules of thumb for their design and proportioning, with the objective of cost minimization. The results of the parametric study suggest that the grade of the reinforcing steel is one of the most influential factors that affect the cost of simply supported RC beams. Practicing engineers can use the trends derived from this research to further refine their optimal designs.

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A complex assembly of lipids including fatty acids, cholesterol, and ceramides is vital to the integrity of the mammalian epidermal barrier. The formation of this barrier requires oxidation of the substrate fatty acid, linoleic acid (LA), which is initiated by the enzyme 12R-lipoxygenase (LOX). In the epidermis, unoxidized LA is primarily found in long-chain acylceramides termed esterified omega-hydroxy sphingosine (EOS)/phytosphingosine/hydroxysphingosine (collectively EOx). The precise structure and localization of LOX-oxidized EOx in the human epidermis is unknown, as is their regulation in diseases such as psoriasis, one of the most common inflammatory diseases affecting the skin. Here, using precursor LC/MS/MS, we characterized multiple intermediates of EOx, including 9-HODE, 9,10-epoxy-13-HOME, and 9,10,13-TriHOME, in healthy human epidermis likely to be formed via the epidermal LOX pathways. The top layers of the skin contained more LA, 9-HODE, and 9,10,13-TriHOME EOSs, whereas 9,10-epoxy-13-HOME EOS was more prevalent deeper in the stratum corneum. In psoriatic lesions, levels of native EOx and free HODEs and HOMEs were significantly elevated, whereas oxidized species were generally reduced. A transcriptional network analysis of human psoriatic lesions identified significantly elevated expression of the entire biosynthetic/metabolic pathway for oxygenated ceramides, suggesting a regulatory function for EOx lipids in reconstituting epidermal integrity. The role of these new lipids in progression or resolution of psoriasis is currently unknown. We also discovered the central coordinated role of the zinc finger protein transcription factor, ZIC1, in driving the phenotype of this disease. In summary, long-chain oxygenated ceramide metabolism is dysregulated at the lipidomic level in psoriasis, likely driven by the transcriptional differences also observed, and we identified ZIC1 as a potential regulatory target for future therapeutic interventions.

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OBJECTIVE: This study aimed to measure the impact of COVID-19 on the quality of life (QoL) of survivors and their partners and family members. DESIGN AND SETTING: A prospective cross-sectional global online survey using social media. PARTICIPANTS: Patients with COVID-19 and partners or family members (age ≥18 years). INTERVENTION: Online survey from June to August 2020. MAIN OUTCOME MEASURE: The EuroQol group five dimensions three level (EQ-5D-3L) to measure the QoL of survivors of COVID-19, and the Family Reported Outcome Measure (FROM-16) to assess the impact on their partner/family member's QoL. RESULTS: The survey was completed by 735 COVID-19 survivors (mean age=48 years; females=563) at a mean of 12.8 weeks after diagnosis and by 571 partners and 164 family members (n=735; mean age=47 years; females=246) from Europe (50.6%), North America (38.5%) and rest of the world (10.9%). The EQ-5D mean score for COVID-19 survivors was 8.65 (SD=1.9, median=9; range=6-14). 81.1% (596/735) reported pain and discomfort, 79.5% (584/735) problems with usual activities, 68.7% (505/735) anxiety and depression and 56.2% (413/735) problems with mobility. Hospitalised survivors (20.1%, n=148) and survivors with existing health conditions (30.9%, n=227) reported significantly more problems with mobility and usual activities (p<0.05), with hospitalised also experiencing more impact on self-care (p≤0.001). Among 735 partners and family members, the mean FROM-16 score (maximum score=highest impact =32) was 15 (median=15, range=0-32). 93.6% (688/735) reported being worried, 81.7% (601/735) frustrated, 78.4% (676/735) sad, 83.3% (612/735) reported impact on their family activities, 68.9% (507/735) on sleep and 68.1% (500/735) on their sex life. CONCLUSION: COVID-19 survivors reported a major persisting impact on their physical and psychosocial health. The lives of their partners and other family members were also severely affected. There is a need for a holistic support system sensitive to the needs of COVID-19 survivors and their family members who experience a major 'secondary burden'.

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Chronic diseases have long-term consequences and can affect individuals' life course. The aim of this study was to create the Polish language version of a questionnaire estimating the impact of the disease on important life decisions-the major life changing decision profile (MLCDP). The translation of the MLCDP followed international guidelines. The created Polish language version of the questionnaire was administered to 32 nephrology and dermatology ward inpatients. To assess its properties, statistical analysis of the results obtained was conducted. The Polish language version of the MLCDP demonstrated very good internal consistency with a Cronbach α coefficient of 0.84. The questionnaire presented excellent test-retest reliability, established with a coefficient ICC of 0.97. The Polish language version of MLCDP has shown high internal consistency and reproducibility, and can be used effectively to assess the cumulative impact of the disease by indicating the number of major life decisions affected by chronic disease.

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Chronic diseases not only have a direct influence on patients' quality of life, but can also affect the life of family members. The aim of this study was to create the Polish language version of a questionnaire estimating impact of disease on quality of family life: the Family Reported Outcome Measure - 16 (FROM-16). A standard forward and backward translation procedure was used to convert the original English version of FROM-16 into the Polish language. Creation of the Polish version was performed in a group of 30 patients' family members. The Polish language version of FROM-16 showed very good internal consistency reliability, the Cronbach α coefficient was 0.89. Reproducibility level was established with an intraclass correlation coefficient of 0.98. The Polish language version of FROM-16 can potentially be used as a tool to assess quality of life of patients' family members.

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Atopic dermatitis is the most prevalent chronic inflammatory skin condition globally. The burden of atopic dermatitis on children and adults is extensive and there is also significant impact on the lives of patient caregivers and family members. It is important to be able to measure this impact to inform clinical decisions and to plan appropriate patient and carer support. The current impact of atopic dermatitis on children and adults can be measured using several different quality of life questionnaires: the most frequently used are the Dermatology Quality of Life (DLQI), Children's Dermatology Quality of Life and Infants Dermatology Quality of Life. The impact on partners and family can be measured using several atopic dermatitis specific questionnaires or the Family DLQI or the generic Family Reported Outcome Measure, FROM-16.

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