Synergistic enhancement of maize crop yield and nutrient assimilation via zinc oxide nanoparticles and phosphorus fertilization.

BACKGROUND: Low recovery of conventional fertilizers remains a significant bottleneck for maize production globally. In particular, with phosphate fertilization, zinc (Zn) is prone to precipitation in soil, reducing recovery of both phosphorus (P) and Zn by maize. RESULTS: The present study was designed to investigate the synergistic effect of zinc oxide (ZnO) nanoparticles (NPs) and P on maize crop growth, yield, and nutrient uptake under ZnO seed coating and foliar application in a randomized complete block design. However, plants were subjected to two ZnO NPs levels (0.5 and 12 kg ha-1) amended with two P levels (45 and 90 kg ha-1). ZnO NPs, especially in the form of foliar application, with a P dose of 90 Kg ha-1 significantly (P < 0.05) improved maize crop growth, yield, and nutrient uptake compared with control. In comparison with the control group, plants grown in these conditions absorbed higher levels of Zn and P. Zn uptake rose to 16.34 g ha-1, 137.88 g ha-1, and 166.89 g ha-1 in roots, grains, and stover respectively, and P uptake increased to 0.80 mg kg-1, 10.066 mg kg-1, and 12.17 mg kg-1 respectively. Additionally, seed emergence rate, plant height, and cob length increased by up to 2%, 1177 cm2, and 3.3 cm respectively compared with control. Furthermore, Zn use efficiency was increased up to 38.55% in ZnO NPs foliar application. CONCLUSIONS: Application of ZnO NPs at 0.5 kg ha-1 in the form of foliar application with 90 kg ha-1 P dose produced a more pronounced increment in the parameters studied than ZnO NPs seed coating did. © 2024 Society of Chemical Industry.

Design of smart citrus picking model based on Mask RCNN and adaptive threshold segmentation.

Smart agriculture is steadily progressing towards automation and heightened efficacy. The rapid ascent of deep learning technology provides a robust foundation for this trajectory. Leveraging computer vision and the depths of deep learning techniques enables real-time monitoring and management within agriculture, facilitating swift detection of plant growth and autonomous assessment of ripeness. In response to the demands of smart agriculture, this exposition delves into automated citrus harvesting, presenting an ATT-MRCNN target detection model that seamlessly integrates channel attention and spatial attention mechanisms for discerning and identifying citrus images. This framework commences by subjecting diverse citrus image classifications to Mask Region-based CNN's (Mask RCNN's) discerning scrutiny, enhancing the model's efficacy through the incorporation of attention mechanisms. During the model's training phase, transfer learning is utilized to expand data performance and optimize training efficiency, culminating in parameter initialization. Empirical results notably demonstrate that this method achieves a recognition rate surpassing the 95% threshold across the three sensory recognition tasks. This provides invaluable algorithmic support and essential guidance for the imminent era of intelligent harvesting.

Investigating the Antibacterial and Anti-inflammatory Potential of Polyol-Synthesized Silver Nanoparticles.

Silver nanoparticles (Ag-NPs) were synthesized by using the polyol method. The structural and morphological characteristics of Ag-NPs were studied by using X-ray diffraction (XRD) and field-emission scanning electron microscopy (FE-SEM). The XRD analysis revealed the formation of single-phase polycrystalline Ag-NPs with an average crystallite size and lattice constant of ∼23 nm and 4.07 Å, respectively, while the FE-SEM shows the formation of a uniform and spherical morphology. Energy-dispersive X-ray spectroscopy confirmed the formation of single-phase Ag-NPs, and no extra elements were detected. A strong absorption peak at ∼427 nm was observed in the UV-vis spectrum, which reflects the surface plasmon resonance (SPR) behavior characteristic of Ag-NPs with a spherical morphology. Fourier-transform infrared (FTIR) spectra also supported the XRD and EDX results with regard to the purity of the prepared Ag-NPs. Anti-inflammatory activity was tested using HRBCs membrane stabilization and heat-induced hemolysis assays. The antibacterial activity of Ag-NPs was evaluated against four different types of pathogenic bacteria by using the disc diffusion method (DDM). The Gram-negative bacterial strains used in this study are Escherichia coli (E. coli), Klebsiella, Shigella, and Salmonella. The analysis suggested that the antibacterial activities of Ag-NPs have an influential role in inhibiting the growth of the tested Gram-negative bacteria, and thus Ag-NPs can find a potential application in the pharmaceutical industry.

Image synthesis of apparel stitching defects using deep convolutional generative adversarial networks.

In industrial manufacturing, the detection of stitching defects in fabric has become a pivotal stage in ensuring product quality. Deep learning-based fabric defect detection models have demonstrated remarkable accuracy, but they often require a vast amount of training data. Unfortunately, practical production lines typically lack a sufficient quantity of apparel stitching defect images due to limited research-industry collaboration and privacy concerns. To address this challenge, this study introduces an innovative approach based on DCGAN (Deep Convolutional Generative Adversarial Network), enabling the automatic generation of stitching defects in fabric. The evaluation encompasses both quantitative and qualitative assessments, supported by extensive comparative experiments. For validation of results, ten industrial experts marked 80% accuracy of the generated images. Moreover, Fréchet Inception Distance also inferred promising results. The outcomes, marked by high accuracy rate, underscore the effectiveness of proposed defect generation model. It demonstrates the ability to produce realistic stitching defective data, bridging the gap caused by data scarcity in practical industrial settings.

Clinical Manifestation, Transmission, Pathogenesis, and Diagnosis of Monkeypox Virus: A Comprehensive Review.

Monkeypox virus is a double-stranded DNA virus species that causes disease in humans and mammals. It is a zoonotic virus belongs the genus Orthopoxviral, the family of Poxviridae, associated with the smallpox virus in many aspects. The first human case of monkeypox was reported throughout the Democratic Republic of Congo in 1970. In April 2022, several cases were recorded in widespread regions of Africa, the Northern and western hemispheres. The current review spotlights taxonomic classification, clinical presentations during infection, and the pathogenicity of the monkeypox virus in humans. Furthermore, the current review also highlights different diagnostics used for virus detection.

The global emergence of Chikungunya infection: An integrated view.

Chikungunya virus (CHIKV) is one of the emerging viruses around the globe. It belongs to the family Togaviridae and genus Alphavirus and is an arthropod borne virus that transmits by the bite of an infected mosquito, mainly through Aedes aegypti and Aedes albopcitus. It is a spherical, enveloped virus with positive single stranded RNA genome. It was first discovered during 1952-53 in Tanganyika, after which outbreaks were documented in many regions of the world. CHIKV has two transmission cycles; an enzootic sylvatic cycle and an urban cycle. CHIKV genome contains 11,900 nucleotides and two open reading frames and shows great sequence variability. Molecular mechanisms of virus host-cell interactions and the pathogenesis of disease are not fully understood. The disease involves three phases; acute, post-acute and chronic with symptoms including high-grade fever, arthralgia, macupapular rashes and headache. There is no licensed vaccine or specific treatment for CHIKV infection. This lack of specific interventions combined with difficulties in making a precise diagnosis together make the disease difficult to manage. In this review we aim to present the current knowledge of global epidemiology, transmission, structure, various aspects of diagnosis as well as highlight potential antiviral drugs and vaccines against CHIKV.

Type 2 diabetes prevalence in Pakistan: what is driving this? Clues from subgroup analysis of normal weight individuals in diabetes prevalence survey of Pakistan.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a global health tissue. We determined factors relating to the likelihood of developing T2DM in normal BMI individuals. METHODOLOGY: This was a cross-sectional community-based representative survey, of people aged ≥20 years in Pakistan, using HBA1c as the screening tool. The prevalence of T2DM/prediabetes in people having normal BMI together with associated risk factors was estimated. RESULTS: Of 6824 normal BMI individuals, there was still a high prevalence of T2DM 14.92% and in underweight at 10.14% (overall prevalence 16.96%). Corresponding rates for prediabetes for the normal BMI category: 9.79% and underweight 8.99%. Multivariate logistic regression modeling for normal BMI individuals, showed a significantly increased risk of T2DM with increasing age (odds ratio [OR] 2.1, 3.3, 4.5 and 4.8, P < 0.001 for 31-40, 41-50, 51-60 and 61 years and above respectively, compared to age decade 20-30 years). Similarly, there was a significantly high risk of T2DM with lower education level [OR for no vs graduate 2.4, 95% confidence interval (CI) 1.5-3.8]. There was a significantly increased risk of T2DM in individuals having a positive family history [OR 4.3 (95% CI 7.0-11.5)]. Overall the influence of overweight/obese on T2DM occurrence (20% increased risk) was much less than in other regions of the world. CONCLUSION: There are higher than expected rates of T2DM/prediabetes in Pakistani ethnicity normal BMI individuals. Targeted screening of older individuals with historical lack of educational opportunity, with a family history of T2DM even if of normal BMI may result in a significant benefit in the Pakistan population.

Using Thypro 39 Scale For Predicting The Quality Of Life In Hypothyroid Patients At Lady Reading Hospital.

BACKGROUND: Thyroid disorders are the second most common of the endocrine diseases. With regards to Hypothyroidism, it has a slow indolent course over the years, before its diagnosis. Most of the patient, on adequate treatment with biochemical euthyroid status, have generalised symptoms that affect their quality of life. Several tools to assess quality of life in thyroid disorders have been validated and recommended for use for those patients in clinical follow ups. ThyPRO 39 is one of a recently developed thyroid-specific quality of life (QoL) questionnaires applicable to patients with benign thyroid disorders (BTD). The purpose of this study was to predict the thyroid-related quality of life (QoL) instrument ThyPRO 39 in patients with Hypothyroidism, who were rendered euthyroid with thyroid replacement therapy prior to the administration of study tool and to assess the internal reliability of this scale in our population. METHODS: A sample of 52 patients undergoing maintenance treatment for Hypothyroidism who visited the outpatient Endocrinology clinics at Lady Reading Hospital was studied. They were interviewed for their baseline demographic details and details on ThyPRO 39 questionnaire were recorded after a written informed consent. The data was entered and analysed using SPSS 25. The Internal reliability of the ThyPRO 39 scale was assessed for multi-item scales using Cronbach's alpha coefficient. RESULTS: The ThyPRO 39 scale demonstrated good response across the whole range of QoL aspects in patients with hypothyroidism. Internal reliability for ThyPRO 39 scale was satisfactory. Cronbach's Alpha in our study was 0.928, which was comparable to the results of other studies. CONCLUSIONS: We suggest implementing this measurement tool as a patient-reported outcome in clinical studies in our indigenous population and further more to utilise it as a screening tool for QoL in clinical management of Hypothyroidism in our routine medical consultations.

Expert Opinion: Use of sodium glucose co-transporter type-2 inhibitors in South Asian population -The Pakistan perspective.

Sodium-glucose co-transporter type 2 inhibitors (SGLT 2- i)are increasingly being used in the management of type 2 diabetes mellitus (T2DM). With the novel insulinindependent glycosuric action, these agents help to attain glycaemic goals by lowering HbA1c and fasting blood glucose. In addition, these agents improve metabolic control in diabetes and ameliorate comorbidities like obesity and hyper tension. Beneficial effec ts on cardiovascular outcomes have been a key attraction for physicians. These agents are used alone or in combination with oral antidiabetic agents and insulin to attain glycaemic and metabolic targets. A major disadvantagewith these agents is the increased risk for genital andurinary infections. When used in appropriate settings, there is no additional increased risk of hypoglycaemia or volume depletion with these agents. Available evidence suggests good efficacy and safety of these agents in diabetes management. The easy and convenient oncedaily dosing should be customized according to patient needs and glycaemic profiles.

Diabetes Prevalence Survey of Pakistan (DPS-PAK): prevalence of type 2 diabetes mellitus and prediabetes using HbA1c: a population-based survey from Pakistan.

OBJECTIVES: We conducted a Pakistan-wide community-based survey on the prevalence of type 2 diabetes using glycated haemoglobin (HbA1c) as the screening test. The aim was to estimate diabetes prevalence across different demographic groups as well as all regions of Pakistan. DESIGN, SETTINGS AND PARTICIPANTS: Multistaged stratified cluster sampling was used for the representative selection of people aged ≥20 years, residing in 378 sampled clusters of 16 randomly selected districts, in this cross-sectional study. Eligible participants had blood drawn for HbA1c analyses at field clinics near to their homes. The oral glucose tolerance test (OGTT) was conducted on a subsample of the participants. Overall and stratified prevalence of type 2 diabetes and its association with risk factors were estimated using logistic regression models. MAIN OUTCOME MEASURES: Prevalence of prediabetes and type 2 diabetes. RESULTS: Of 18 856 eligible participants the prevalence of prediabetes was 10.91% (95% CI 10.46 to 11.36, n=2057) and type 2 diabetes was 16.98% (95% CI 16.44 to 17.51, n=3201). Overall, the mean HbA1c level was 5.62% (SD 1.96), and among newly diagnosed was 8.56% (SD 2.08). The prevalence was highest in age 51-60 years (26.03%, p<0.001), no formal education (17.66%, p<0.001), class III obese (35.09%, p<0.001), family history (31.29%, p<0.001) and female (17.80%, p=0.009). On multivariate analysis, there was a significant association between type 2 diabetes and older age, increase in body mass index and central obesity, positive family history, and having hypertension and an inverse relation with education as a categorical variable. On a subsample (n=1027), summary statistics for diagnosis of diabetes on HbA1c showed a sensitivity of 84.7%, specificity of 87.2% and area under the receiver operating characteristic curve 0.86, compared with OGTT. CONCLUSIONS: The prevalence of type 2 diabetes and prediabetes is much higher than previously thought in Pakistan. Comprehensive strategies need to be developed to incorporate screening, prevention and treatment of type 2 diabetes at a community level.

Naked Eye DNA detection: synthesis, characterization and DNA binding studies of a novel azo-guanidine.

A novel class of azo-guanidine compounds is introduced in this article. The novel compound 2-(2-hydroxyphenyl)-1-(phenylamino)-3-(phenylimino)guanidine (AG) was synthesized and well characterized by using different analytical instrumental techniques like elemental analysis, FTIR, (1)H and (13)C NMR, UV-Visible spectroscopy and cyclic voltammetry. The new compound was found interacting with DNA and shows clear color change in the solution. The AG-DNA complex was qualitatively and quantitatively characterized with UV-Visible spectroscopy and cyclic voltammetry. Electrostatic mode of interaction, clear color change and moderate binding constant (K(b)=10(4)) indicate its potential use as DNA staining agent.

Costs attributable to healthcare-acquired infection in hospitalized adults and a comparison of economic methods.

BACKGROUND: Hospitals will increasingly bear the costs for healthcare-acquired conditions such as infection. Our goals were to estimate the costs attributable to healthcare-acquired infection (HAI) and conduct a sensitivity analysis comparing analytic methods. METHODS: A random sample of high-risk adults hospitalized in the year 2000 was selected. Measurements included total and variable medical costs, length of stay (LOS), HAI site, APACHE III score, antimicrobial resistance, and mortality. Medical costs were measured from the hospital perspective. Analytic methods included ordinary least squares linear regression and median quantile regression, Winsorizing, propensity score case matching, attributable LOS multiplied by mean daily cost, semi-log transformation, and generalized linear modeling. Three-state proportional hazards modeling was also used for LOS estimation. Attributable mortality was estimated using logistic regression. RESULTS: Among 1253 patients, 159 (12.7%) developed HAI. Using different methods, attributable total costs ranged between $9310 to $21,013, variable costs were $1581 to $6824, LOS was 5.9 to 9.6 days, and attributable mortality was 6.1%. The semi-log transformation regression indicated that HAI doubles hospital cost. The totals for 159 patients were $1.48 to $3.34 million in medical cost and $5.27 million for premature death. Excess LOS totaled 844 to 1373 hospital days. CONCLUSIONS: Costs for HAI were considerable from hospital and societal perspectives. This suggests that HAI prevention expenditures would be balanced by savings in medical costs, lives saved and available hospital days that could be used by overcrowded hospitals to enhance available services. Our results obtained by applying different economic methods to a single detailed dataset may inform future cost analyses.

Hospital and societal costs of antimicrobial-resistant infections in a Chicago teaching hospital: implications for antibiotic stewardship.

BACKGROUND: Organisms resistant to antimicrobials continue to emerge and spread. This study was performed to measure the medical and societal cost attributable to antimicrobial-resistant infection (ARI). METHODS: A sample of high-risk hospitalized adult patients was selected. Measurements included ARI, total cost, duration of stay, comorbidities, acute pathophysiology, Acute Physiology and Chronic Health Evaluation III score, intensive care unit stay, surgery, health care-acquired infection, and mortality. Hospital services used and outcomes were abstracted from electronic and written medical records. Medical costs were measured from the hospital perspective. A sensitivity analysis including 3 study designs was conducted. Regression was used to adjust for potential confounding in the random sample and in the sample expanded with additional patients with ARI. Propensity scores were used to select matched control subjects for each patient with ARI for a comparison of mean cost for patients with and without ARI. RESULTS: In a sample of 1391 patients, 188 (13.5%) had ARI. The medical costs attributable to ARI ranged from $18,588 to $29,069 per patient in the sensitivity analysis. Excess duration of hospital stay was 6.4-12.7 days, and attributable mortality was 6.5%. The societal costs were $10.7-$15.0 million. Using the lowest estimates from the sensitivity analysis resulted in a total cost of $13.35 million in 2008 dollars in this patient cohort. CONCLUSIONS: The attributable medical and societal costs of ARI are considerable. Data from this analysis could form the basis for a more comprehensive evaluation of the cost of resistance and the potential economic benefits of prevention programs.

Characteristics of patient care management problems identified in emergency department morbidity and mortality investigations during 15 years.

STUDY OBJECTIVE: We describe cases referred for physician review because of concern about quality of patient care and identify factors that contributed to patient care management problems. METHODS: We performed a retrospective review of 636 cases investigated by an emergency department physician review committee at an urban public teaching hospital over a 15-year period. At referral, cases were initially investigated and analyzed, and specific patient care management problems were noted. Two independent physicians subsequently classified problems into 1 or more of 4 major categories according to the phase of work in which each occurred (diagnosis, treatment, disposition, and public health) and identified contributing factors that likely affected outcome (patient factors, triage, clinical tasks, teamwork, and system). Primary outcome measures were death and disability. Secondary outcome measures included specific life-threatening events and adverse events. Patient outcomes were compared with the expected outcome with ideal care and the likely outcome of no care. RESULTS: Physician reviewers identified multiple problems and contributing factors in the majority of cases (92%). The diagnostic process was the leading phase of work in which problems were observed (71%). Three leading contributing factors were identified: clinical tasks (99%), patient factors (61%), and teamwork (61%). Despite imperfections in care, half of all patients received some benefit from their medical care compared with the likely outcome with no care. CONCLUSION: These reviews suggest that physicians would be especially interested in strategies to improve the diagnostic process and clinical tasks, address patient factors, and develop more effective medical teams. Our investigation allowed us to demonstrate the practical application of a framework for case analysis. We discuss the limitations of retrospective cases analyses and recommend future directions in safety research.