Environmental policy stringency, ICT, and technological innovation for achieving sustainable development: Assessing the importance of governance and infrastructure.

Achieving sustainable development goals (SDGs) has garnered significant attention from academia and policymakers worldwide. In this study, we examine the impact of ICT, technological innovation (TI), and environmental policy stringency (EPS) on SDI, considering the moderating role of governance quality (GQI) and transport infrastructure (TIS). A comprehensive dataset of 17 advanced nations is utilized from 1996 to 2021. To capture the dynamic and extreme marginal impacts of these policy instruments on SDG attainment, we employ the advanced technique of Feasible Generalized Least Square (FGLS). The results demonstrate that ICT has a positive and significant effect on SDGs, particularly when combined with high levels of governance quality (GOV) and transport infrastructure (TIS). Likewise, TI has a positive impact on SDGs, especially in the presence of strong governance. Furthermore, EPS exhibits a positive association with SDGs. The findings also reveal that while governance hurts SDGs, this effect diminishes when combined with higher levels of ICT, TI, and EPS, and when TIS positively moderates the relationships. The robustness estimations using DOLS and PCSE methods validate the FGLS findings. These results underscore the importance of ICT, TI, and EPS in advancing sustainable development. Moreover, they highlight the significance of good governance and robust transport infrastructure in maximizing the positive effects of these factors. These findings hold implications for policymakers and stakeholders involved in promoting sustainable development.

Sculpting conducting nanopore size and shape through de novo protein design.

Transmembrane ß-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane ß-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.

An Update on Current Trend in Sample Preparation Automation in Bioanalysis: strategies, Challenges and Future Direction.

Automation in sample preparation improves accuracy, productivity, and precision in bioanalysis. Moreover, it reduces resource consumption for repetitive procedures. Automated sample analysis allows uninterrupted handling of large volumes of biological samples originating from preclinical and clinical studies. Automation significantly helps in management of complex testing methods where generation of large volumes of data is required for process monitoring. Compared to traditional sample preparation processes, automated procedures reduce associated expenses and manual error, facilitate laboratory transfers, enhance data quality, and better protect the health of analysts. Automated sample preparation techniques based on robotics potentially increase the throughput of bioanalytical laboratories. Robotic liquid handler, an automated sample preparation system built on a robotic technique ensures optimal laboratory output while saving expensive solvents, manpower, and time. Nowadays, most of the traditional extraction processes are being automated using several formats of online techniques. This review covered most of the automated sample preparation techniques reported till date, which accelerated and simplified the sample preparation procedure for bioanalytical sample analysis. This article critically analyzed different developmental aspects of automated sample preparation techniques based on robotics as well as conventional sample preparation methods that are accelerated using automated technologies.

Development of 2400-2450 MHz Frequency Band RF Energy Harvesting System for Low-Power Device Operation.

Recently, there has been an increasing fascination for employing radio frequency (RF) energy harvesting techniques to energize various low-power devices by harnessing the ambient RF energy in the surroundings. This work outlines a novel advancement in RF energy harvesting (RFEH) technology, intending to power portable gadgets with minimal operating power demands. A high-gain receiver microstrip patch antenna was designed and tested to capture ambient RF residue, operating at 2450 MHz. Similarly, a two-stage Dickson voltage booster was developed and employed with the RFEH to transform the received RF signals into useful DC voltage signals. Additionally, an LC series circuit was utilized to ensure impedance matching between the antenna and rectifier, facilitating the extraction of maximum power from the developed prototype. The findings indicate that the developed rectifier attained a peak power conversion efficiency (PCE) of 64% when operating at an input power level of 0 dBm. During experimentation, the voltage booster demonstrated its capability to rectify a minimum input AC signal of only 50 mV, yielding a corresponding 180 mV output DC signal. Moreover, the maximum power of 4.60 µW was achieved when subjected to an input AC signal of 1500 mV with a load resistance of 470 kΩ. Finally, the devised RFEH was also tested in an open environment, receiving signals from Wi-Fi modems positioned at varying distances for evaluation.

Long-term medical and quality of life outcomes among voluntary liver donors.

BACKGROUND: Long-term medical and quality of life (QOL) outcomes in voluntary liver donors remain under investigated. The objective of the current study was to report long-term medical outcomes and re-evaluate QOL in living liver donors. METHODS: This was a single-center retrospective cohort study of donors who underwent donor hepatectomy between 2012 and 2018. We investigated long-term outcomes in 7 domains. These include medical problems, surgical procedures, work-related issues, pregnancy outcomes, psychiatric interventions, willingness to donate again, and long-term mortality. QOL was evaluated using short-form 36. RESULTS: The median follow-up time was 61.4 months (53.3-83.7). Among 698 donors, 80 (11.5%) experienced medical problems, 4 (0.6%) had work-related issues, and 20 (2.9%) needed psychiatric assistance. Surgery was performed in 49 donors (7%), and females were more likely to have undergone incisional hernia repair (5.8% vs 1.9%, P = .006). There were 79 postdonation pregnancies including 41 normal vaginal deliveries (51.9%), 35 cesarean sections (44.3%), and 3 miscarriages (3.8%). Willingness to donate again was reported by 658 donors (94.3%). Donors whose recipients were alive were more likely to donate again (95.5% vs 90.5%, P = .01). There were 3 deaths (0.4%) in the long-term. The mean physical composite score at initial and follow-up evaluation was 86.7 ± 13.9 and 76.5 ± 20.9 (P = .001), and the mean mental composite score at initial and follow-up evaluation was 92.1 ± 13.5 and 80.7 ± 16 (P = .001). CONCLUSION: The overall long-term outlook in living liver donors is promising. QOL parameters might deteriorate over time and frequent re-evaluation might be considered.

Haemophagocytic lymphohistiocytosis secondary to Epstein-Barr and cytomegalovirus coinfection.

Haemophagocytic lymphohistiocytosis (HLH) is a rare and life-threatening disorder caused by uncontrolled activation of the immune system, leading to phagocytosis of blood cells and cytokine storm. HLH can manifest in childhood due to a genetic mutation, but in adults HLH arises secondary to viral infections, autoimmune diseases or neoplastic processes. The most common viral infections associated with HLH are Epstein-Barr virus (EBV) and cytomegalovirus (CMV). EBV and CMV coinfection associated with HLH, however, is exceedingly rare. We present a case of HLH secondary to EBV and CMV coinfection in a young adult who presented with recurrent intermittent high-grade fevers and epistaxis. This case illustrates the importance of considering HLH in patients with idiopathic fevers and to consider all the potential aetiologies for HLH to ensure proper treatment.

Genetic substructure and host-specific natural selection trend across vaccine-candidate ORF-2 capsid protein of hepatitis-E virus.

Hepatitis E virus is a primary cause of acute hepatitis worldwide. The present study attempts to assess the genetic variability and evolutionary divergence among HEV genotypes. A vaccine promising capsid-protein coding ORF-2 gene sequences of HEV was evaluated using phylogenetics, model-based population genetic methods and principal component analysis. The analyses unveiled nine distinct clusters as subpopulations for six HEV genotypes. HEV-3 genotype samples stratified into four different subgroups, while HEV-4 stratified into three additional subclusters. Rabbit-infectious HEV-3ra samples constitute a distinct cluster. Pairwise analysis identified marked genetic distinction of HEV-4c and HEV-4i subgenotypes compared to other genotypes. Numerous admixed, inter and intragenotype recombinant strains were detected. The MEME method identified several ORF-2 codon sites under positive selection. Some selection signatures lead to amino acid substitutions within ORF-2, resulting in altered physicochemical features. Moreover, a pattern of host-specific adaptive signatures was identified among HEV genotypes. The analyses conclusively depict that recombination and episodic positive selection events have shaped the observed genetic diversity among different HEV genotypes. The significant genetic diversity and stratification of HEV-3 and HEV-4 genotypes into subgroups, as identified in the current study, are noteworthy and may have implications for the efficacy of anti-HEV vaccines.

Empirical phenotyping and genome-wide association study reveal the association of panicle architecture with yield in Chenopodium quinoa.

Chenopodium quinoa manifests adaptability to grow under varying agro-climatic scenarios. Assessing quinoa germplasm's phenotypic and genetic variability is a prerequisite for introducing it as a potential candidate in cropping systems. Adaptability is the basic outcome of ecological genomics of crop plants. Adaptive variation predicted with a genome-wide association study provides a valuable basis for marker-assisted breeding. Hence, a panel of 72 quinoa plants was phenotyped for agro morphological attributes and association-mapping for distinct imperative agronomic traits. Inter simple sequence repeat (ISSR) markers were employed to assess genetic relatedness and population structure. Heatmap analysis showed three genotypes were early maturing, and six genotypes were attributed for highest yield. The SD-121-07 exhibited highest yield per plant possessing green, glomerulate shaped, compact density panicle with less leaves. However, SJrecm-03 yielded less exhibiting pink, intermediate shape, intermediate density panicles with less leaves. The phenotyping revealed strong correlation of panicle architecture with yield in quinoa. A genome-wide association study unraveled the associations between ISSR makers and agro-morphological traits. Mixed linear modes analysis yielded nine markers associated with eight traits at p ≤ 0.01. Moreover, ISSR markers significantly associated with panicle shape and leafiness were also associated with yield per plant. These findings contribute to the provision of authenticity for marker-assisted selection that ultimately would support quinoa breeding programs.

Discovery and development of COVID-19 vaccines and therapeutics: nonclinical perspectives.

The development and regulatory review of BNT162b2, a COVID-19 vaccine, and PaxlovidTM (nirmatrelvir tablets/ritonavir tablets), a COVID-19 therapeutic, are benchmarks for accelerated innovation during a global pandemic. Rapid choice of the SARS-CoV-2 spike protein and main protease (Mpro) as targets for the vaccine and therapeutic, respectively, leveraged the available knowledge of the biology of SARS-CoV-2 and related viruses. The nonclinical immunogenicity and safety of BNT162b2 was rigorously assessed. Likewise, a comprehensive nonclinical safety assessment was conducted for the therapeutic candidates, lufotrelvir (PF-07304814) and nirmatrelvir (PF-07321332). The development and regulatory review of BNT162b2 and Paxlovid was enabled through close collaboration of the pharmaceutical industry with regulatory agencies and public health organizations. This experience highlights approaches that could be adopted for pandemic preparedness including risk-based investment strategies, conduct of activities in parallel that normally are conducted sequentially, quick kill decisions, simultaneous evaluation of multiple candidates, and use of flexible, established vaccine platforms.

Rural households' livelihood adaptation strategies in the face of changing climate: A case study from Pakistan.

Rural and agricultural communities' adaptation to climate change has gained significant attention owing to many countries' vulnerability to climate change risks. A similar trend has been witnessed in South Asia, a highly climate-vulnerable region, where research has grown dramatically considering the agriculture sector's vulnerability to climate-induced disasters. However, little attention has been paid to the adaptation of the livelihoods of rural households. This research, therefore, takes the case of Pakistan to explore livelihood adaptation strategies of rural households to climate change and investigate the factors that expedite or halt the adoption of livelihood diversification strategies. A multistage sampling design is used in this research, where 480 rural households from the Punjab province of Pakistan were selected and interviewed using stratified and random sampling approaches. A multivariate probit (MVP) regression model is employed to analyze the factors affecting households' adoption of livelihood adaptation strategies. The results show that besides adaptation of agronomic operations (agricultural adaptation strategies), rural households in the study area employed a wide range of strategies to adapt their livelihoods to climate change. These strategies include poultry and livestock farming, value addition of farm produce, trading of animals and farm commodities, small businesses (shops, etc.), daily wage labor, horticultural crop farming, and non-farming jobs. The estimates of the MVP model revealed that respondents' education, household size, income, access to a credit facility, access to farm advisory services, and access to climate forecasts have significantly influenced the choice of livelihood adaptation strategies. Based on these findings, this research recommends that the authorities should make efforts to improve farmers' understanding of the adaptation of climate change risks and educate them to adopt multiple livelihood options to improve the resilience of their livelihoods to climate-induced risks. This research has important policy implications for other countries with similar socio-economic features.

Technological Advancement and Trend in Selective Bioanalytical Sample Extraction through State of the Art 3-D Printing Techniques Aiming 'Sorbent Customization as per need'.

The inherent complexity of biological matrices and presence of several interfering substances in biological samples make them unsuitable for direct analysis. An effective sample preparation technique assists in analyte enrichment, improving selectivity and sensitivity of bioanalytical method. Because of several key benefits of employing 3D printed sorbent in sample extraction, it has recently gained popularity across a variety of industries. Applications for 3D printing in the field of bioanalytical research have grown recently, particularly in the areas of miniaturization, (bio)sensing, sample preparation, and separation sciences. Due to the high expense of the solid phase microextraction cartridge, researcher approaches in-lab production of sorbent material for the extraction of analyte from biological samples. Owing to its distinct advantages such as low costs, automation capabilities, capacity to produce products in a variety of shapes, and reduction of tedious steps of sample preparation, 3D printed sorbents are gaining increased attention in the field of bioanalysis. It is also reported to offer high selectivity and assist in achieving a much lower limit of detection. In this review, we have discussed current advancements in different types of 3D printed sorbents, production methods, and their applications in the field of bioanalytical sample preparation.

Reconstruction of soft tissue defects of hand: A systematic approach.

Background and Objective: A thorough insight into the management of hand injuries can shape the approach of a surgeon in order to achieve optimal outcomes for the patients. The aim of this study was to share our experience in reconstruction of the hand and establishing an algorithm for classification and treatment of hand injuries. Methods: This is a descriptive cross sectional study and was conducted from January 2020 to August 2022 at Burns and Plastic Surgery center, Peshawar. Data was collected from medical records about the patient demographics, mechanism of injury and type of procedures done. Defect size was classified into small (<5cm), medium (5cm to 10 cm) and large (>10cm). The defect site and size was cross tabulated against the method of soft tissue reconstruction in order to make the algorithm for reconstruction of hand injuries. Data was analyzed using SPSS. Results: The study population included 41 (75.9%) male and 13 (24.1%) female patients, mean age 31.56±14.1. Machine injuries (33.3%) and electric burns (24.1%) were the most common cause of hand soft tissue defects. The most commonly performed flap was Posterior introsseous artery (PIA) flap, followed by First dorsal metacarpal artery (FDMA) flap. Flap necrosis was observed in three cases (5.6%). Conclusion: This treatment algorithm for coverage of soft tissue defects in hand injuries will help with the decision making process of hand reconstruction and has didactic value for novice surgeons. It will also form the foundation for further work on this aspect of hand injuries.

Enhancing specimen collection skills for dried blood spots through an immersive virtual learning environment: a cross-sectional study.

OBJECTIVE: The quality of dried blood spot (DBS) specimens impacts newborn screening (NBS) results, hence proper training is crucial for DBS specimen collection. To address this, a training module for Allied Health Professionals (AHPs) and nurses was created on Moodle, a virtual learning environment (VLE). The purpose of this research was to determine the feasibility and effectiveness of this module. METHODOLOGY: Participants were trained on-site (March to December 2019), through online training sessions (January to June 2020), and the two training strategies were compared. Data analysis included the total number of participants, cost-effectiveness, trainer engagement, and the number of unacceptable samples collected by nurses/AHPs trained by the two strategies. RESULTS: A total of 55 nurses/AHPs were trained on-site, while 79 nurses/AHPs completed the online module and received certificates through online VLE-based training. The trainer engagement and cost were more for onsite training. After online training, the specimen rejection rate was reduced from 0.84% (44 rejected out of 5220 total specimens collected) to 0.38% (15/3920). CONCLUSIONS: This study shows that using VLE-based DBS specimen collection training is feasible and effective for training nurses and AHPs.

Synthesis and analysis of silica nanocarriers for pectinase immobilization: Enhancing enzymatic stability for continuous industrial applications.

Pectinolytic enzymes are among the important group of industrial enzymes that have wide applications in different food industries. In this study, pectinase-based silica nanocarriers were synthesized using co-precipitation and cross-linking techniques. The resulting silica nanoparticles were investigated using scanning electron microscopy (SEM), energy-dispersive electron microscopy (EDEX), and X-ray diffraction (XRD) for determination of its morphology, elemental composition, and crystalline pattern. Under the optimal immobilization conditions like 1.5 % glutaraldehyde, 3000 IU/mg pectinase concentration, 90 min immobilization time and 40 °C immobilization temperature, pectinase showed maximum immobilization yield. The immobilization of pectinase onto the silica nanocarriers led to enhanced catalytic characteristics, displaying higher enzymatic activity across various temperature and pH levels compared to soluble pectinase. Moreover, the immobilization substantially improved the temperature stability of pectinase, exhibiting 100 % of its initial activity even after 120 h of pre-incubation at 50 °C. Additionally, the silica nanocarrier pectinase retained 100 % of its original activity even after being reused 10 times in a single batch of reactions. These findings indicate that the immobilization of silica nanocarriers effectively enhances pectinase's industrial capabilities, making it economically feasible for industrial use and an efficient system for various biotechnological applications.

RF energy harvesters for wireless sensors, state of the art, future prospects and challenges: a review.

The power consumption of portable gadgets, implantable medical devices (IMDs) and wireless sensor nodes (WSNs) has reduced significantly with the ongoing progression in low-power electronics and the swift advancement in nano and microfabrication. Energy harvesting techniques that extract and convert ambient energy into electrical power have been favored to operate such low-power devices as an alternative to batteries. Due to the expanded availability of radio frequency (RF) energy residue in the surroundings, radio frequency energy harvesters (RFEHs) for low-power devices have garnered notable attention in recent times. This work establishes a review study of RFEHs developed for the utilization of low-power devices. From the modest single band to the complex multiband circuitry, the work reviews state of the art of required circuitry for RFEH that contains a receiving antenna, impedance matching circuit, and an AC-DC rectifier. Furthermore, the advantages and disadvantages associated with various circuit architectures are comprehensively discussed. Moreover, the reported receiving antenna, impedance matching circuit, and an AC-DC rectifier are also compared to draw conclusions towards their implementations in RFEHs for sensors and biomedical devices applications.

Green Synthesis of Low-Glycemic Amylose-Lipid Nanocomposites by High-Speed Homogenization and Formulation into Hydrogel.

In this research, we focused on the production of amylose-lipid nanocomposite material (ALN) through a green synthesis technique utilizing high-speed homogenization. Our aim was to investigate this novel material's distinctive physicochemical features and its potential applications as a low-glycemic gelling and functional food ingredient. The study begins with the formulation of the amylose-lipid nanomaterial from starch and fatty acid complexes, including stearic, palmitic, and lauric acids. Structural analysis reveals the presence of ester carbonyl functionalities, solid matrix structures, partial crystallinities, and remarkable thermal stability within the ALN. Notably, the ALN exhibits a significantly low glycemic index (GI, 40%) and elevated resistance starch (RS) values. The research extends to the formulation of ALN into nanocomposite hydrogels, enabling the evaluation of its anthocyanin absorption capacity. This analysis provides valuable insights into the rheological properties and viscoelastic behavior of the resulting hydrogels. Furthermore, the study investigates anthocyanin encapsulation and retention by ALN-based hydrogels, with a particular focus on the influence of pH and physical cross-link networks on the uptake capacity presenting stearic-acid (SA) hydrogel with the best absorption capacity. In conclusion, the green-synthesized (ALN) shows remarkable functional and structural properties. The produced ALN-based hydrogels are promising materials for a variety of applications, such as medicine administration, food packaging, and other industrial purposes.

Mucoid degeneration of the anterior cruciate ligament corrected with autograft reconstruction.

The anterior cruciate ligament (ACL) is the most frequently injured knee ligament, typically in non-contact athletic injuries in young adults. Mucoid degeneration of the ACL (ACL-MD) is an uncommon ACL pathology in which glycosaminoglycans deposition within the collagenous bundles leads to hypertrophy, loss of full knee flexion and knee pain without instability. ACL-MD usually presents in individuals over 40 years with sudden-onset knee pain after minimal trauma or as an incidental MRI finding. ACL-MD is rarely described in young adults. We present a case of ACL-MD in a previously healthy adult in his early 20s who presented with 3-month recalcitrant dull left knee pain and limited range of motion after 'stepping funny' with slight twisting. This case highlights the need to critically reflect on the anatomical structures when presented with musculoskeletal pathologies and to consider the unique presentation of musculoskeletal disease in atypical age groups.

Reconnoitering NGOs strategies to strengthen disaster risk communication (DRC) in Pakistan: A conventional content analysis approach.

Risk communication is crucial since individuals need to understand how they are at risk and what proper steps to deal with flood events. Sharing information with the public opens the door for two-way communication about risks, wherein you learn about people's perspectives and work together to find ways to mitigate the risks. Beyond government scope, relief organizations play a big part in advising individuals about the likelihood of catastrophic events as they possess the commonalities that define community engagement. In numerous accounts of devastating events, the failure of risk management groups to coordinate their efforts and the public's mistrust of relief agencies are highlighted. One possible explanation for this skepticism could be relief organizations' failures in communicating risks. In addition, individuals' lack of skills and experience with catastrophes has left rural residents unprepared, which is why relief agencies need to raise their efforts or measures to communicate with people about possible risks. If these measures are uncovered, it could improve public communication and provide information for formulating recommendations to prevent fatalities. This study identifies the strategies used by relief organizations in enhancing disaster risk communication across four severely affected districts in Khyber Pakhtunkhwa, Pakistan. The qualitative research used semi-structured interviews with 50 participants from relief organizations, local institutions, and affected households. We employed qualitative content analysis and NVivo software to analyze the data. The findings of this study highlighted some significant strategies that relief organizations adopted in this line of work: the administration of educational and information transmission, managing obstacles in communication, and managing inter-organizational communications. The findings validate the potential for relief organizations to become change agents, facilitate communication between the public and relief organizations, and ultimately strengthen community resilience and reduce disaster risks as part of local responses.

Non-contrast CT synthesis using patch-based cycle-consistent generative adversarial network (Cycle-GAN) for radiomics and deep learning in the era of COVID-19.

Handcrafted and deep learning (DL) radiomics are popular techniques used to develop computed tomography (CT) imaging-based artificial intelligence models for COVID-19 research. However, contrast heterogeneity from real-world datasets may impair model performance. Contrast-homogenous datasets present a potential solution. We developed a 3D patch-based cycle-consistent generative adversarial network (cycle-GAN) to synthesize non-contrast images from contrast CTs, as a data homogenization tool. We used a multi-centre dataset of 2078 scans from 1,650 patients with COVID-19. Few studies have previously evaluated GAN-generated images with handcrafted radiomics, DL and human assessment tasks. We evaluated the performance of our cycle-GAN with these three approaches. In a modified Turing-test, human experts identified synthetic vs acquired images, with a false positive rate of 67% and Fleiss' Kappa 0.06, attesting to the photorealism of the synthetic images. However, on testing performance of machine learning classifiers with radiomic features, performance decreased with use of synthetic images. Marked percentage difference was noted in feature values between pre- and post-GAN non-contrast images. With DL classification, deterioration in performance was observed with synthetic images. Our results show that whilst GANs can produce images sufficient to pass human assessment, caution is advised before GAN-synthesized images are used in medical imaging applications.

PEGylated Graphene Oxide as a Nanodrug Delivery Vehicle for Podophyllotoxin (GO/PEG/PTOX) and In Vitro α-Amylase/α-Glucosidase Inhibition Activities.

This study aims to develop a nanodrug delivery system containing podophyllotoxin (PTOX), a known anticancer drug, loaded on graphene oxide (GO). The system's ability to inhibit α-amylase and α-glucosidase enzymes was also investigated. PTOX was isolated from Podophyllum hexandrum roots with a yield of 2.3%. GO, prepared by Hummer's method, was converted into GO-COOH and surface-mobilized using polyethylene glycol (PEG) (1:1) in an aqueous medium to obtain GO-PEG. PTOX was loaded on GO-PEG in a facile manner with a 25% loading ratio. All the samples were characterized using FT-IR spectroscopy, UV/visible spectroscopy, and scanning electron microscopy (SEM). In FT-IR spectral data, GO-PEG-PTOX exhibited a reduction in acidic functionalities and there was an appearance of the ester linkage of PTOX with GO. The UV/visible measurements suggested an increase of absorbance in 290-350 nm regions for GO-PEG, suggesting the successful drug loading on its surface (25%). GO-PEG-PTOX exhibited a rough, aggregated, and scattered type of pattern in SEM with distinct edges and binding of PTOX on its surface. GO-PEG-PTOX remained potent in inhibiting both α-amylase and α-glucosidase with IC50 values of 7 and 5 mg/mL, closer to the IC50 of pure PTOX (5 and 4.5 mg/mL), respectively. Owing to the 25% loading ratio and 50% release within 48 h, our results are much more promising. Additionally, the molecular docking studies confirmed four types of interactions between the active centers of enzymes and PTOX, thus supporting the experimental results. In conclusion, the PTOX-loaded GO nanocomposites are promising α-amylase- and α-glucosidase-inhibitory agents when applied in vitro and have been reported for the first time.