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Purpose of Review Increasing environmental problems demand mitigation solutions to fulfill sustainability development goals. Microalgae offer possibility of valorizing the CO 2 and wastewater-derived nutrients to produce numerous industrial bioproducts. However, developing self-sustained systems for the complete valorization of algal biomass into valuable biobased products is challenging. Currently, sustainable algal processing faces several challenges including costly cultivation, difficult harvesting, and incomplete biomass valorization. This review assessed the prospects of emerging technologies focusing on the integrated approaches for sustainable algal biorefinery development ensuring the sustainability of environment-water-energy nexus. Recent Findings Evaluation of various upstream, midstream, and downstream processing technologies provided insights into the processing issues. In upstream processing, high-rate algal ponds and integrated carbon capture and transformation technologies offer waste valorization into eco-friendly algal production. A brief comparison of harvesting technologies mainly focusing on chemical and biological flocculation has shown that integrating physical and biological harvesting methods are more reliable and efficient. Overview of downstream processing has indicated that biomass processing in a cascading manner offers the complete biomass valorization in a zero-waste paradigm. Summary Assessment of cultivation-to-production technologies highlighted that “zero-waste” algal biorefinery has the potential to become reality by integrating the industry 4.0 and phenomics approaches with eco-friendly cultivation, harvesting, and processing technologies. Hybrid methods based on integrated cascading processing offer complete biomass valorization in a circular bioeconomy paradigm. Graphical Abstract

The cultivation of Plectonema terebrans BERC10 in wastewater and integrating the wastewater-derived biomass followed by its processing for multiple products in a biorefinery could help in achieving environmental sustainability and cost effectiveness. This study evaluated the resource recovery potential of the cyanobacterium Plectonema terebrans BERC10 from urban wastewater followed by the cascading processing of the biomass into multiple bioproducts. The annual biomass productivity ranged from 0.035–0.064 gL−1d−1 and contained 40–46% lipids and 20–38% protein. The cascading processing of the biomass resulted in multiple products, including 53 mgg−1 of high-value pigments and high-quality biodiesel in accordance with American and European standards. The pigment-free and de-fatted residual biomass was used as a sole feedstock (30–70 gL−1) to produce enzymes and mycoproteins via fungal fermentation employing Aspergillus niger and Aspergillus oryzae. Interestingly, A. oryzae produced 28 UmL−1 of α-amylase and the final residues were mycoproteins after 96 h. Furthermore, the strain removed 80–90% of total phosphorous, 90–99% of total nitrogen, and significantly lowered the COD, BOD, and TDS of urban wastewater. The data demonstrated that P. terebrans has substantial potential for resource recovery and could become a candidate for a wastewater-derived algal biorefinery.

Purpose of Review Growing algae in wastewater offers carbon-neutral biomass production and pollutant removal. However, practical applications of wastewater-grown algal biomass have social acceptability issues in the food and feed industries due to unexpected threats (such as human/animal pathogens and toxins) associated with the wastewater-grown biomass. Therefore, considering the substantial pollutant removal potential of microalgae and the abundance of wastewater as a growth media, alternative bioprocessing routes of the wastewater-grown biomass should be developed. This review highlights some non-food and non-feed applications of wastewater-grown algae biomass. Recent Findings Wastewater-grown algal biomass contains high amounts of carbohydrates, proteins, and lipids depending upon the composition of wastewater and algal species grown. These three significant metabolites are precursors to bioenergy and biomaterial products such as bioethanol, biogas, and bioplastics. Hydrolysis of the wastewater-grown algal biomass can be easily improved to enhance the microbial fermentation yields to produce bioethanol and biobutanol. Fresh algal biomass, residual biomass, or both can be used as feedstocks in anaerobic digestion/co-digestion to produce biogas. Depending upon the selected species, wastewater-grown algal biomass can also produce biopolymers whose productivity depends on growth conditions, wastewater composition, and biopolymer synthesis method. Enzymatic, eco-friendly chemicals and mechanical approaches used to prepare biopolymers from algal biomass should be optimized for higher yields of biopolymers. Summary Although wastewater-grown biomass has acceptability issues, it offers certain environmental benefits, including atmospheric carbon capture, phycoremediation of pollutants, and water recycling. This manuscript highlights the recent progress and emerging trends of wastewater-grown algal biomass as a feedstock with potential applications for fermentation, anaerobic digestion, and bioprocessing to produce clean energy and bioplastics. Graphical Abstract

Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM), lung cancer (LC), tuberculosis (TB), and COVID-19 etc. The diagnosis of LGDs is performed by using different medical imaging such as X-rays, CT scans, and MRI. However, LGDs contain similar symptoms such as fever, cough, and sore throat, making it challenging for radiologists to classify these LGDs. If LGDs are not diagnosed at their initial phase, they may produce severe complications or even death. An automated classifier is required for the classification of LGDs. Thus, this study aims to propose a novel model named lung diseases classification network (LGD_Net) based on the combination of a capsule network (CapsNet) with the extreme learning machine (ELM) for the classification of five different LGDs such as PNEUM, LC, TB, COVID-19 omicron (COO), and normal (NOR) using CT scans. The LGD_Net model is trained and tested on the five publicly available benchmark datasets. The datasets contain an imbalanced distribution of images; therefore, a borderline SMOTE (BL_SMT) approach is applied to handle this problem. Additionally, the affine transformation methods are used to enhance LGD datasets. The performance of the LGD_Net is compared with four CNN-based baseline models such as Vgg-19 (D 1 ), ResNet-101 (D 2 ), Inception-v3 (D 3 ), and DenseNet-169 (D 4 ). The LGD_Net model achieves an accuracy of 99.71% in classifying LGDs using CT scans. While the other models such as D 1 , D 2 , D 3 , and D 4 attains an accuracy of 91.21%, 94.39%, 93.96%, and 93.82%, respectively. The findings demonstrate that the LGD_Net model works significantly as compared to D 1 , D 2 , D 3 , and D 4 as well as state-of-the-art (SOTA). Thus, this study concludes that the LGD_Net model provides significant assistance to radiologists in classifying several LGDs.

Background Pharmacy service is an essential part of a healthcare system. The profession of pharmacy is well recognized and is practiced to its full potential in developed countries however, it is underutilized in developing countries such as Pakistan. The recognition of pharmacist’s role as healthcare professional is limited. This study aimed to document pharmacists’ attitude towards their role in Pakistan’s healthcare system, their experience with doctors and their perceptions towards involvement in medicines management. Methods A 4-month cross-sectional survey (Jan – Apr 18) was conducted targeting pharmacists practising in 26 tertiary care hospitals across Pakistan using a developed and validated questionnaire in both Urdu/English languages. Chi square (χ 2 ) test was used to report any associations between independent variables, i.e., education, type of hospital and work experience and, dependent variables, i.e., pharmacists’ attitudes, experience, and perception. A p -value of ≤0.01 with value of Cramer’s V ≥ 0.3 was considered cut-off for establishing statistical significance. The study was approved by ethical committee and local hospital committees. Results Three hundred ninety-six questionnaires were returned out of 500, i.e., response rate = 87.9%. Most participants (92.2%) interacted with doctors at least once daily. Most interactions were related to drug availability inquiry (72.5%). Most pharmacists (91.4%) mentioned that pharmacy duties are mostly clinical in nature. 93.4% of the respondents indicated that pharmacists are reliable source of information regarding general medicines. Furthermore, 87.4% reasoned inadequate training for not being able to discuss issues of clinical nature with doctors. Conclusion Pharmacists were willing to perform their duties and provide healthcare benefits to patients however, they seemed sceptical of advanced clinical pharmacy roles such as intervening in prescriptions and medication therapy, consultations and prescribing. There is a need to increase awareness regarding pharmacist’s role. Therefore, it would be helpful if trainings and seminars are conducted on the importance of clinical pharmacy to improve the pharmacy services in Pakistan’s healthcare system.

Although mobile shopping is a new norm after the pandemic, its proliferation is still not very mature in developing nations. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this research employs the SEM technique to examine the effect of mobile shopping frequency and repurchase intent among 198 young mobile shopping consumers in Pakistan. Our findings suggest that purchase frequency is a key variable in consumer behavior and plays a significant role in building mobile shopping repurchase intentions. Findings further suggest that effort expectancy, unlike the performance expectancy, also strongly affects the relationship between purchase frequency and repurchase intention as an intervening mechanism, while a strong interaction effect from the social influence is also noted. This research offers insightful implications for researchers and marketers in the realm of e-commerce and mobile shopping domains.

Background Pakistan is a lower-middle-income country with a high burden of injuries. Karachi, its most populated city, lacks a trauma care system due to which trauma patients do not receive the required care. We conducted an assessment of the existing facilities for trauma care in Karachi. Methods Twenty-two tertiary and secondary hospitals from public and private sectors across Karachi were assessed. The Guidelines for Essential Trauma Care (GETC) tool was used to collect information about the availability of skills, knowledge, and equipment at these facilities. Results Among tertiary hospitals ( n  = 7), private sector hospitals had a better median (IQR) score, 90.4 (81.8–93.1), as compared to the public sector hospitals, 44.1 (29.3–75.8). Among secondary hospitals ( n  = 15), private sector hospitals had a better median (IQR) score, 70.3 (67.8–77.7), as compared to the public sector hospitals, 39.7 (21.9–53.3). Discussion This study identifies considerable deficiencies in trauma care in Karachi and provides objective data that can guide urgently needed reforms tailored to this city’s needs. On a systems level, it delineates the need for a regulatory framework to define trauma care levels and designate selected hospitals across the city accordingly. Using these data, improvement in trauma care systems can be achieved through collaboration and partnership between public and private stakeholders.