Riphah Journal of Allied Health Sciences

From Analyzers to Algorithms: Artificial Intelligence and the Future of Laboratory Medicine

Mohammad Sohail — Tue, 02 Jun 2026 00:00:00 +0000

Environmental Antibiotic Resistance in Resource-Limited Settings: Sources, Mechanisms and Sustainable Mitigation Strategies; A Review

Maryam Arif, Nazia Jamil, Rida Batool — Fri, 19 Jun 2026 00:00:00 +0000

Antibiotic resistance has grown to be a major global health concern, and environmental systems are being recognized as significant reservoirs and transmission pathways for antibiotic-resistance genes (ARGs). In particular, resistant bacteria, mobile genetic elements, and co-selective pollutants congregate in wastewater systems, which promotes the persistence and spread of resistance. Recent studies on the existence, diffusion mechanisms, and co-selection of ARGs in wastewater systems, both globally and in Pakistan, are compiled in this review. The role of non-antibiotic contaminants in resistance maintenance, horizontal gene transfer channels, and methodological differences between DNA-based resistome methods and culture-based surveillance are highlighted. Additionally, the effectiveness of both new, low-cost, nature-based mitigation techniques and traditional treatment methods is critically assessed. The evidence examined indicates that while conventional disinfection can reduce ARG loads to some degree, its effectiveness varies and is occasionally insufficient in practical situations. However, nature-based and hybrid treatment approaches show promising elimination efficiency and practical in resource-constrained environments such as Pakistan. Quantitative modeling of ARG elimination, reliable monitoring systems, and long-term field-scale validation of mitigating devices are still severely constrained. This research highlights the need for comprehensive, One-Health-oriented surveillance and the creation of predictive and economical treatment options to successfully manage antibiotic resistance in wastewater systems.

Precision-Driven Advancements in Cancer Treatment: A Review of Emerging Therapies and Personalized Approaches

Aswad Khan, Ayesha Maqbool, Alina Shehzadi — Wed, 10 Jun 2026 00:00:00 +0000

Cancer remains a significant global health challenge despite advances in research and treatment. In 2023 alone, statistics documented nearly 19.3 million new diagnoses and 10 million fatalities. While conventional therapies like surgery, chemotherapy, and radiation have demonstrably improved survival outcomes, they often result in systemic side effects, particularly in advanced malignancies. In recent years, the field of oncology has placed more focus on specific molecular and cellular mechanisms that trigger tumor growth. Several treatments, such as targeted therapy and immunotherapy, have evolved from these advancements and work to enhance immune-mediated tumor recognition and destruction while limiting the amount of damage to normal tissue. Furthermore, using drugs like rosiglitazone and MEK inhibitors to cause cancer cells to transdifferentiate into benign adipocyte-like cells represents a novel approach to non-lethal cancer control. Chimeric antigen receptor (CAR) T-cell therapy has demonstrated significant clinical success in treating blood malignancies. In contrast, oncolytic therapy uses genetically modified viruses to infect and kill cancerous cells and stimulate antitumor immunity. Non-invasive technologies like histotripsy use focused ultrasound waves to mechanically disrupt cancerous cells. This review study summarizes the latest innovative developments in oncology by incorporating all of the most recent promising techniques currently available. A new era in cancer care is being signaled by these developments, which not only assist patients in responding better to cancer treatment but also enhance their quality of life. More technological and scientific advancements will be required to give patients new, creative cancer control methods that are more precise and less toxic.

In silico analysis of glucose transporter-1 (GLUT1) protein involved in pancreatic ductal adenocarcinoma

Wed, 10 Jun 2026 00:00:00 +0000

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and therapy resistant cancers worldwide and is typically diagnosed late in the course of the disease. One of the most characteristic PDAC metabolic changes is the significant upregulation of glucose transporter 1 (GLUT1/SLC2A1) that leads to excessive glucose uptake to support aerobic glycolysis, to maintain proliferation under hypoxic conditions and to confer chemoresistance.

Methods: In the present study, comprehensive in silico approaches are used to identify and characterize the GLUT1 protein.

Results: The active site residues Tyr292, Gln282, Asn288, Asn411, Asn415 and Trp412 are strictly conserved across the species (91.7–100% conservation) and this suggests that GLUT1 is an evolutionarily conserved therapeutic target.

Conclusion: The study highlights the GLUT1 protein structure and its conservation analysis through in-silico online tools such as ERRAT, Verify 3D, PROCHECK, Ramachandran plot and ESPript.

Key words: GLUT1, conservation analysis, 3D structure.

The Phenotypic profiling and blaTEM gene detection in multidrug resistant gram-negative bacteria isolated from hostel sanitary area

Wardah Attique, Muteeba Illyas, Irham Ihsanullah, Saba Riaz — Thu, 18 Jun 2026 00:00:00 +0000

Background: Antimicrobial resistance (AMR) is a major health concern across the world, with Gram-negative bacteria account for failing the therapeutic options available. Environmental reservoirs, such as sink drains in high-occupancy hostels have been recognized as the neglected hotspots for multidrug-resistant bacteria, has become an imminent health peril because it is associated with biofilm-mediated persistence and transmission of antimicrobial resistance.

Objective: This study aimed to investigate the phenotypic resistance patterns and detect bla_TEM gene among the Gram-negative strains from the drainage system of hostel sanitary areas.

Methodology: The 80 swab samples were collected and cultured on a selective media to specifically isolate 50 resistant strains followed by performing antibiotic susceptibility testing using Kirby-Bauer disk diffusion method. PCR was conducted to confirm the presence of the bla_TEM gene.

Results: Biochemical profiling identified various species with Escherichia coli and Acinetobacter spp. (18% each) were the most common, followed by Pseudomonas spp. and Salmonella spp. (12% each). While Enterobacter spp. and Stenotrophomonas spp. constituted 10% of isolates. Proteus spp. and Shigella spp. were identified as 8% and 6% respectively. The less frequently found organisms were Serratia spp. and Aeromonas spp. Antibiotic susceptibility testing revealed all isolates were resistant to ampicillin, with varying levels of resistance against CZC (98%), CIP (94%), ZOX (88%), CTX (82%), MEM (72%), CN (72%) and TBZ (68%), PCR analysis confirmed the presence of the bla_TEM gene in 54% (95% CI: 40.4%–67.0%) of the resistant isolates.

Conclusion: In conclusion, the findings indicate that the hostel sanitary drainage system serves as a potential reservoir for MDR Gram-negative bacteria, many of which harbor the bla_TEM gene. This underscores the urgent need for improved sanitation practices, regular microbial surveillance, strict infection control measures, and rational antibiotic usage to reduce the risk of resistant pathogen transmission in communal living environments.

Key words: Antimicrobial resistance, sink drains, biofilm, lactamase, Kirby-Bauer disk diffusion, and bla_TEM gene

Biotin-Minoxidil Conjugated Copper Oxide Nanoparticles for Antimicrobial Protection and Hair Regeneration

Aliza Mukhtar, Laraib Tabassum, Tuba Fiaz, Kaneez Fatima, Mehreen Fatima — Tue, 23 Jun 2026 00:00:00 +0000

Background: Nanobiotechnology has greatly improved targeted drug delivery by facilitating localized therapeutic effects with customized nanocomposites.

Objectives: This research focused on synthesizing and characterizing a biotin-minoxidil-linked copper oxide (CuO) nanocomposite and assessing its dual capabilities for hair regeneration and antimicrobial activity.

Methodology: CuO nanoparticles were synthesized by chemical co-precipitation. Afterward, biotin and minoxidil were coupled to nanoparticles using PEG, glutaraldehyde, and EDC. The obtained nanocomposite was extensively characterized using UV-Vis spectrophotometry and Fourier Transform Infrared (FTIR) spectroscopy. The well-diffusion method and culture-based assays were used to evaluate antimicrobial efficacy. The in vivo promotion of hair growth was assessed in albino mice with shaved dorsal areas.

Results: The biotin-minoxidil-linked CuO nanocomposite demonstrated strong antimicrobial activity against the evaluated microbial strains and markedly improved hair regrowth rate in the mouse model compared with the control groups. Hair regrowth was observed after topical application of 100 µL of a nanocomposite containing 5% minoxidil for approximately 21 days.

Conclusion: The addition of biotin and minoxidil provided specific therapeutic advantages for hair growth while also enhancing the copper oxide core's natural biological characteristics. This nanocomposite shows great promise as a multifunctional tool for managing scalp health, integrating antimicrobial properties with effective hair growth promotion.

Identification Of Bacterial Isolates and Antimicrobial Susceptibility Pattern Among Patients Diagnosed with Surgical Site Infections

Tue, 23 Jun 2026 00:00:00 +0000

Background: Despite the use of prophylactic antibiotics and preventive measures, surgical site infections (SSIs) continue to be a common postoperative complication, attributed mostly to increasing antimicrobial resistance.

Objective: To investigate the bacterial profile and antimicrobial susceptibility patterns of isolates from patients diagnosed with SSIs at Jinnah Hospital, Lahore, Pakistan.

Methodology: A cross-sectional study design was used for sampling, and 65 surgical wound samples were collected from admitted patients. All specimens (Pus and wound swabs) were collected for bacterial isolation, identification, and antimicrobial testing using standard microbiological techniques. SPSS software was used for statistical analysis, and a P value (<0.05) was considered statistically significant.

Results: This research found that SSIs were found in 24 (37%) of patients who belonged to the 16-30 years of age group. More males, 41(63%), were affected as compared to females. SSIs were more common in the lower extremities 43 (66%). The majority of patients, 30(46%) were diagnosed with double microbial infections at SSIs. More males, 14 (22%) developed SSIs due to E. coli (P<0.05), and double microbial infection was also common in males (P < 0.05). MRSA was found resistant to antimicrobial drugs, while S. aureus was found sensitive to antimicrobial drugs. (P value<0.05).

Conclusion: In our study, SSIs were found prevalent in the lower extremities and mostly due to double microbial infections. E. coli was found to cause SSIs in males.

Gender-Based Analysis of Anemia Prevalence and Hematological Indices in Individuals with Beta Thalassemia Trait

Wed, 03 Jun 2026 00:00:00 +0000

Background: Beta thalassemia trait (BTT) is the heterozygous condition involving a mutation in the HBB gene, characterized by hypochromic, microcytic anemia. Although hematological features of beta thalassemia trait are well-described, gender-specific variations in these features, influenced by many physiological factors, remain less explored.

Objective: This study aims to identify the role of gender in defining anemia and hematological indices in BTT individuals.

Methodology: This cross-sectional study, involving 200 individuals (84 males and 116 females) was conducted at the Department of Hematology, Noor Thalassemia Foundation, Lahore. Blood samples were taken, and a hemogram was performed, and repeated hemoglobin analysis using HPLC was done for confirmation of BTT. WHO guidelines were taken in consideration while defining anemia in both genders and in different age groups. The number of males and females in different age groups and the number of anemic individuals in different age groups were noted and presented as frequency (n) and percentage (%). Chi-square and odds ratios with 95%CI were used to test the association between gender and anemia status. Independent sample t-test was used to compare the hematological indices (Hb, RBC, HCT, MCV, MCH, MCHC) between males and females.

Results: The overall prevalence of anemia in our study population was 62%. Anemia prevalence was relatively higher in females (68.9%) than males (52.3%). Hemoglobin concentration was significantly lower in females (9.75±1.40 g/dL), than in males (11.35±2.12 g/dL), p<0.001. In the same way, females had statistically lower hematocrit (32.95±4.66%) than males (38.13±6.89%), p<0.001.

Conclusion: Anemia is not the defining feature of beta thalassemia trait, as a substantial number of BTT individuals were non-anemic. The diagnosis should not rely on anemia alone; rather, it must involve comprehensive evaluation based on red cell indices and hemoglobin fractions.

Segmentation of Charcot’s Neuropathy (Diabetic Foot) Using Medical Images and Artificial Intelligence

Mon, 15 Jun 2026 00:00:00 +0000

Background: Charcot neuroarthropathy (CN) is a diabetes-associated neuropathic condition that can cause progressive bone and joint destruction. The scarcity of annotated radiographs limits the development and evaluation of deep learning models for radiographic image segmentation.

Objectives: This study developed and evaluated a generative adversarial network (GAN)-augmented deep learning framework for segmentation of the affected bone/joint region in Charcot foot radiographs.

Methodology: Twenty plain radiographs from four patients with CN stages 0-2 were included. Fourteen original radiographs were used to train SinGAN-Seg, which generated 560 synthetic radiographs with corresponding segmentation masks. Synthetic-image similarity was assessed using single-image Fréchet Inception Distance (SIFID) and Inception Score (IS). Six U-Net-based segmentation architectures were trained using the synthetic dataset. Of the 560 synthetic image–mask pairs, 504 (90%) were used for training, and 56 (10%) were reserved for testing. Segmentation performance was evaluated using the intersection over union (IoU).

Results: The SIFID values ranged from 77.56 to 125.81 for images generated from reference image A and from 139.92 to 196.91 for images generated from reference image B. Across the evaluated architectures, mean IoU values ranged from 0.642 to 0.757 on the held-out synthetic test images. R2U-Net obtained the highest observed mean IoU (0.757); however, no formal statistical comparison was performed, and this result should be interpreted cautiously.

Conclusion: GAN-generated image–mask pairs enabled preliminary training and evaluation of U-Net-based models for segmenting the annotated affected bone/joint region in Charcot foot radiographs. Larger patient-level, externally validated datasets are needed before conclusions can be made regarding diagnostic accuracy, clinical reliability, or generalizability.

Building a framework for an effective work life balance environment for hospital staff: Evidence from Lebanese healthcare facilities

Roy Moarbes, Carolyn Msheik — Wed, 10 Jun 2026 00:00:00 +0000

Background: Quality of work life is one of the main factors that influence healthcare workers' performance, satisfaction, and retention. Lebanon is experiencing a shortage of the healthcare workforce, and the increasing competition for qualified professionals makes it very important to have supportive work environments.

Objective: To build a framework for an effective work-life balance environment for hospital staff.

Methodology: To carry out this quantitative research, cross-sectional surveys were conducted between May and June 2021 and 2022 consecutively. A bilingual structured questionnaire was used to collect data from 300 healthcare staff members of Lebanese healthcare facilities using convenience sampling. The questionnaire items were derived from well-known work-life balance models. Descriptive statistics were used to analyse the data. Also, standard ethical procedures related to voluntary participation and anonymity were ensured.

Results: Data from the survey of 300 healthcare professionals in Lebanon showed that the work-life balance environment is quite inadequate. The mean overall work-life balance score was 19.06 ± 7.48 out of 39, representing approximately 49% of the optimal score, indicating substantial work-life imbalance. Organizational benefits and work-life balance dimensions received low mean scores, whereas managerial support was comparatively higher. Significant associations were observed between work-life balance dimensions and age (p < 0.022), educational level (p < 0.007), and years of professional experience (p < 0.005). Approximately 66% of participants reported sacrificing personal activities because of work, and more than 60% indicated an intention to change employment if the opportunity arose. Apart from only limited organizational support measures, there were also weak flexibility policies and high levels of stress and personal-life conflict. Although management support was somewhat positive, the overall work-life balance score was just about half of the optimal level, with numerous staff members feeling tired and having turnover intention. The study points out that there is a need for stronger work-life balance policies at the institutional level as well as practical implementation frameworks that will result in better staff welfare and higher retention rates.

Conclusion: Medical organizations should consider it as a top priority for the provision of high-quality care and the work-life balance of their employees. Several studies have shown that the conditions of the workplace have a substantial impact on the health of the employees, care quality, and thus the ability of staff to have an effective work-life balance.

Retrospective Analysis of Dyslipidemia In Type 2 Diabetes Mellitus Patients With Hypertension In Lahore, Pakistan

Waqas Ahmad, Nosheen Mushtaq, Muhammad Awais Nayyar, Shahzad Ahmad — Mon, 15 Jun 2026 00:00:00 +0000

Background: Type 2 Diabetes Mellitus (T2DM) is a common health problem in the world. According to the Global Diabetes League report, the number of individuals affected by diabetes was 416 million in 2015, projected to increase to 650 million by 2045. Hypertension is a major cause of heart disease and mortality, often accompanied by risk factors such as dyslipidemia, contributing to atherosclerosis in hypertensive individuals.

Objectives: The objective of this work was to examine the pattern of lipid profiles and associated risk factors in local patients with both T2DM and hypertension.

Methodology: A comparative and analytical study was conducted on a sample of 230 males and females aged between 30 and 65 years, diagnosed with T2DM and hypertension. The work was done in the biochemistry section of Lahore University of Biological & Applied Sciences (UBAS), from October 2022 to April 2023. Participants meeting the inclusion criteria were selected, and their blood samples and medical histories were obtained with their informed consent. Blood samples were analyzed, and data analysis was performed using SPSS 22.

Results: The study findings showed that Type 2 diabetes mellitus was more prevalent in males (54%) compared to females (46%), with an average age of 49.64 years. The mean HbA1c level was 8.06, while the average cholesterol level (in mg/dL) was approximately 209.91, and the average triglyceride (TG) level (in mg/dL) was around 213.89 in diabetic patient’s p-value < 0.0001.

Conclusion: Diabetic dyslipidemia significantly contributes to morbidity. The duration of diabetes is concerned with a higher frequency of dyslipidemia, believed to be a significant risk factor for heart disease. In this study, elevated levels of total serum cholesterol, LDL-C, and low levels of HDL-C were observed. We recommend regular lipid profile examinations for patients and emphasize the importance of effective management of glucose and lipid levels in case of abnormalities

Evaluating the appropriateness of ChatGPT in providing dietary advice: An evidence-based approach

Ayesha Saeed, Maliha Amanat, Ayesha Ishfaq Ali — Thu, 18 Jun 2026 00:00:00 +0000

Background: ChatGPT, a generative artificial intelligence chatbot developed by OpenAI, is being increasingly used to obtain health and nutrition information. Limited research has evaluated the appropriateness and validity of dietary advice.

Objective: This study aimed to evaluate the appropriateness of the dietary advice provided by ChatGPT in alignment with international clinical guidelines for the management of seven specific non-communicable diseases, and its appropriateness in managing complex cases.

Methodology: Cross-sectional descriptive research was conducted in December 2025-January 2026. Seven NCD’s were selected: obesity, dyslipidemia, non-alcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), arterial hypertension, sarcopenia, and chronic kidney disease (CKD). For each disease, prompts were given to ChatGPT version 5.0 in independent sessions. Responses were then compared with international practice guidelines. Two experienced dietitians independently assessed each response using a structured evaluation framework. Any discrepancies between the dietitians were reviewed and finalised by a third reviewer, who made the final decision. In addition, a complex case scenario involving T2DM, obesity, and CKD was used to evaluate ChatGPT’s ability to integrate recommendations from different clinical nutrition guidelines. Frequencies and percentages were calculated using SPSS v. 26.

Results: ChatGPT generally provided appropriate advice for individual diseases, dyslipidemia (88.8%), arterial hypertension (83.3%), obesity (93.8%), T2DM (94.1%), NAFLD (95.8%), and sarcopenia (94.4%). However, for CKD, 70% responses were appropriate, and six key recommendations were missing. ChatGPT demonstrated strong clinical reasoning when managing complex scenarios. AI maintained safe boundaries by explicitly stating it is not a medical professional and strongly advising users to seek highly individualized care from a registered renal dietitian.

Conclusion: ChatGPT provided largely appropriate and safe dietary advice, with good performance in both single-disease and complex clinical scenarios, though greater caution is needed in conditions requiring highly specific restrictions such as CKD.

Association of Lifestyle Factors with Menstrual Irregularities Among Female University Students

Wed, 24 Jun 2026 00:00:00 +0000

Background: Menstrual irregularities are a prevalent concern among females of reproductive age, often causing anxiety, and potentially impacting their physical, psychological and social health along with the quality of life. The global prevalence of irregular menstrual cycle is reported to range between 14% and 35%, depending on the geographical region and diagnostic criteria.

Aim and Objective: While recent studies have examined physical activity, smoking, nutrition and sleep in relation to menstrual health, there is limited research on how they all together influence menstrual irregularities in female university students in Pakistan. Studying these factors together could offer a more extensive understanding of lifestyle patterns related to menstrual health.

To determine the association between lifestyle factors and menstrual irregularities among female university students aged 18 to 26 years, a descriptive cross-sectional research design was employed.

Methodology: This research was conducted at Ibadat International University Islamabad comprising of a sample size of (n=350) using a random sampling technique. Two tools were used, such as the “lifestyle pattern associated with menstrual irregularities questionnaire” and “sleep quality scale”.

Results: A high prevalence of menstrual irregularities was observed among female students, with dysmenorrhea and premenstrual syndrome being the most common. Significant associations were found between menstrual irregularities and BMI, dietary frequency, sleep duration, and dietary habits (p<0.05). Chi-square analysis identified irregular breakfast intake (p=0.0001) and difficulty sleeping during menstruation (p=0.008) as the strongest risk factors

Conclusion: The finding of this study concluded that menstrual irregularities were associated with a variety of lifestyle patterns. Furthermore, there was a statistically significant correlation between multiple menstrual irregularities and sleep, body mass index and skipping breakfast and dinner. University should put in place health education programs to increase awareness of how lifestyle factors. affect menstrual health. It is important to encourage the female to follow the balanced diet, practice regular exercise and obtain adequate sleep. Promoting good sleep pattern and frequent exercise can help to promote the hormonal balance and reduce premenstrual syndrome symptoms. To better understand the underlying cause of menstrual irregularities, future research should use longitudinal design and explore other factors of stress and hormonal level.