Synthesis and Characterization of Naproxen Intercalated Zinc Oxide Stacked Nanosheets for Enhanced Hepatoprotective Potential.

Liver diseases pose a significant global health burden, with limited therapeutic options for chronic cases. Zinc oxide (ZnO) nanomaterials have emerged as promising candidates for hepatoprotection due to their antioxidant, anti-inflammatory, and regenerative properties. However, their potential remains hampered by insufficient drug loading and controlled release. The current study explores the intercalation of Naproxen (Nx), a potent anti-inflammatory and analgesic drug, within ZnO stacked nanosheets (SNSs) to address these limitations. Herein, an easy and solution-based synthesis of novel Nx intercalated ZnO SNSs was established. The obtained Nx intercalated ZnO SNSs were encapsulated with poly(vinyl acetate) (PVA) to make them biocompatible. The synthesized biocomposite was characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR), which confirm the successful synthesis and intercalation of Nx within the ZnO SNSs. The obtained outcomes showed that the configuration of ZnO nanosheets was altered when Nx was introduced, resulting in a more organized stacking pattern. An in vivo investigation of mice liver cells unveiled that the Nx intercalated ZnO SNss had increased hepatoprotective properties. The study's results provide valuable insights into using Nx intercalated ZnO SNss for targeted drug delivery and improved treatment effectiveness, particularly for liver-related illnesses.

Revision Lumbar Spine Surgeries: An Early Career Neurosurgery Experience.

BACKGROUND: The aims and ambitions of a surgeon in the early years of his professional career are to make a good reputation by providing excellent patient outcomes and avoiding complex and difficult surgeries. Revision lumbar spine surgeries (RLSSs) pose a significant challenge in terms of surgical management, as the moribund anatomy increases the risk of complications, adding to an unlikely outcome. OBJECTIVE: We conducted this study to determine the clinical indications and outcomes of RLSSs performed by an early career neurosurgeon. MATERIALS AND METHODS: This cross-sectional study was conducted after approval from the hospital's ethical committee, and data was collected in late December of 2022 and early January 2023, from retrospective records for a single early career neurosurgeon. A form was filled with each patient's data, such as age, gender, time since surgery, indication for surgery, operative findings, types of surgery performed, etc. All variables were noted for the patient and were further categorized, based on the clinical records, into many sub-categories. RESULTS: Almost 400 lumbar spine surgeries were performed by the surgeon, and about 45 (11.25%) were revision surgeries, and the full record was available for 42 surgeries. These patients' ages ranged from 22 to 70 years, and the mean age was about 46.74±13.29 SD. The common symptoms leading to revision surgeries were numbness and pain in 17 (40.5%) patients each; common per-operative findings were recurrent disc in eight patients (19%), infection in nine patients (21.4%), and fibrosis/adhesions in 16 (38.1%); most common surgeries performed were diskectomy in 11 (26.2%) and diskectomy plus release of adhesions in 12 (28.6%); complications occurred in 14 (33%), and good to excellent outcomes was recorded in 29 (69%) cases.  Conclusion: RLSSs are difficult compared to first-time lumbar spine surgeries, and the moribund anatomy predisposes to complications, and better shall be dealt with great care and, at the minimum, shall be embarked upon as a team.

Recent advances in genome editing strategies for balancing growth and defence in sugarcane (Saccharum officinarum).

Sugarcane (Saccharum officinarum ) has gained more attention worldwide in recent decades because of its importance as a bioenergy resource and in producing table sugar. However, the production capabilities of conventional varieties are being challenged by the changing climates, which struggle to meet the escalating demands of the growing global population. Genome editing has emerged as a pivotal field that offers groundbreaking solutions in agriculture and beyond. It includes inserting, removing or replacing DNA in an organism's genome. Various approaches are employed to enhance crop yields and resilience in harsh climates. These techniques include zinc finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN) and clustered regularly interspaced short palindromic repeats/associated protein (CRISPR/Cas). Among these, CRISPR/Cas is one of the most promising and rapidly advancing fields. With the help of these techniques, several crops like rice (Oryza sativa ), tomato (Solanum lycopersicum ), maize (Zea mays ), barley (Hordeum vulgare ) and sugarcane have been improved to be resistant to viral diseases. This review describes recent advances in genome editing with a particular focus on sugarcane and focuses on the advantages and limitations of these approaches while also considering the regulatory and ethical implications across different countries. It also offers insights into future prospects and the application of these approaches in agriculture.

Performance enhancement of short-term wind speed forecasting model using Realtime data.

The ever-increasing demand for electricity has presented a grave threat to traditional energy sources, which are finite, rapidly depleting, and have a detrimental environmental impact. These shortcomings of conventional energy resources have caused the globe to switch from traditional to renewable energy sources. Wind power significantly contributes to carbon-free energy because it is widely accessible, inexpensive, and produces no harmful emissions. Better and more efficient renewable wind power production relies on accurate wind speed predictions. Accurate short-term wind speed forecasting is essential for effectively handling unsteady wind power generation and ensuring that wind turbines operate safely. The significant stochastic nature of the wind speed and its dynamic unpredictability makes it difficult to forecast. This paper develops a hybrid model, L-LG-S, for precise short-term wind speed forecasting to address problems in wind speed forecasting. In this research, state-of-the-art machine learning and deep learning algorithms employed in wind speed forecasting are compared with the proposed approach. The effectiveness of the proposed hybrid model is tested using real-world wind speed data from a wind turbine located in the city of Karachi, Pakistan. Moreover, the mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) are used as accuracy evaluation indices. Experimental results show that the proposed model outperforms the state-of-the-art legacy models in terms of accuracy for short-term wind speed in training, validation and test predictions by 98% respectively.

An evaluation of computational methods for aggregate data meta-analyses of diagnostic test accuracy studies.

BACKGROUND: A Generalized Linear Mixed Model (GLMM) is recommended to meta-analyze diagnostic test accuracy studies (DTAs) based on aggregate or individual participant data. Since a GLMM does not have a closed-form likelihood function or parameter solutions, computational methods are conventionally used to approximate the likelihoods and obtain parameter estimates. The most commonly used computational methods are the Iteratively Reweighted Least Squares (IRLS), the Laplace approximation (LA), and the Adaptive Gauss-Hermite quadrature (AGHQ). Despite being widely used, it has not been clear how these computational methods compare and perform in the context of an aggregate data meta-analysis (ADMA) of DTAs. METHODS: We compared and evaluated the performance of three commonly used computational methods for GLMM - the IRLS, the LA, and the AGHQ, via a comprehensive simulation study and real-life data examples, in the context of an ADMA of DTAs. By varying several parameters in our simulations, we assessed the performance of the three methods in terms of bias, root mean squared error, confidence interval (CI) width, coverage of the 95% CI, convergence rate, and computational speed. RESULTS: For most of the scenarios, especially when the meta-analytic data were not sparse (i.e., there were no or negligible studies with perfect diagnosis), the three computational methods were comparable for the estimation of sensitivity and specificity. However, the LA had the largest bias and root mean squared error for pooled sensitivity and specificity when the meta-analytic data were sparse. Moreover, the AGHQ took a longer computational time to converge relative to the other two methods, although it had the best convergence rate. CONCLUSIONS: We recommend practitioners and researchers carefully choose an appropriate computational algorithm when fitting a GLMM to an ADMA of DTAs. We do not recommend the LA for sparse meta-analytic data sets. However, either the AGHQ or the IRLS can be used regardless of the characteristics of the meta-analytic data.

Arrhythmias and Device Therapies in Cardiac Amyloidosis.

Cardiac amyloidosis is caused by amyloid fibrils that deposit in the myocardial interstitium, causing restrictive cardiomyopathy and eventually death. The electromechanical, inflammatory, and autonomic changes due to amyloid deposition result in arrhythmias. Atrial fibrillation is by far the most common arrhythmia. The rate control strategy is generally poorly tolerated due to restrictive filling physiology and heart rate dependance, favoring adoption of the rhythm control strategy. Anticoagulation for stroke prophylaxis is warranted, irrespective of CHA2DS2-VASc score in patients with a favorable bleeding profile; data on left appendage closure devices are still insufficient. Ventricular arrhythmias are also not uncommon, and the role of implantable cardioverter-defibrillator in cardiac amyloidosis is controversial. There is no evidence of improvement in outcomes when used for primary prevention in these patients. Bradyarrhythmia is most commonly associated with sudden cardiac death in cardiac amyloidosis. Pacemaker implantation can help provide symptomatic relief but does not confer mortality benefit.

Silver-infused TiO2 nanowires and unveiling their potential for superior wastewater dye remediations.

Silver infused ultrathin TiO2 nanowires (NWs) were synthesized via a single step solvothermal approach. The crystallinity, structure, and morphology were determined to understand the physicochemical nature of the nanocomposites. The catalytic efficiency of the newly synthesized nanocatalysts was tested for the textile waste treatment taking methylene blue (MB) as model pollutant under solar light irradiations. Nearly 96% photodegradation efficiency for MB was achieved within 20 min. Furthermore, the recyclability of the photocatalyst was also studied, and the material remained stable and effective up to four consecutive runs. RESEARCH HIGHLIGHTS: Precise size-controlled synthesis of Ag-incorporated titania nanowires (ATNWs) Controlled aspect ratios, with tunable lengths and diameters (100-3 nm) via precursor and surfactant optimization Demonstrated ATNWs' efficiency in degrading toxic dye, methylene blue (MB) 96% photodegradation efficiency for MB achieved within 20 min using 3 nm thick annealed TiO2 NWs Recyclability efficiency of photocatalyst, which remained stable and effective for up to four consecutive runs.

Video dataset of sheep activity for animal behavioral analysis via deep learning.

A primary dataset capturing five distinct types of sheep activities in realistic settings was constructed at various resolutions and viewing angles, targeting the expansion of the domain knowledge for non-contact virtual fencing approaches. The present dataset can be used to develop non-invasive approaches for sheep activity detection, which can be proven useful for farming activities including, but not limited to, sheep counting, virtual fencing, behavior detection for health status, and effective sheep breeding. Sheep activity classes include grazing, running, sitting, standing, and walking. The activities of individuals, as well as herds of sheep, were recorded at different resolutions and angles to provide a dataset of diverse characteristics, as summarized in Table 1. Overall, a total of 149,327 frames from 417 videos (the equivalent of 59 minutes of footage) are presented with a balanced set for each activity class, which can be utilized for robust non-invasive detection models based on computer vision techniques. Despite a decent existence of noise within the original data (e.g., segments with no sheep present, multiple sheep in single frames, multiple activities by one or more sheep in single as well as multiple frames, segments with sheep alongside other non-sheep objects), we provide original videos and the original videos' frames (with videos and frames containing humans omitted for privacy reasons). The present dataset includes diverse sheep activity characteristics and can be useful for robust detection and recognition models, as well as advanced activity detection models as a function of time for the applications.

Low profile high gain RHCP antenna for L-Band and S-Band using rectangular ring metasurface with backlobe suppression.

In this reported work a single feed, miniaturized, dual layer, and low profile antenna is presented for 1.575GHz frequency band. The proposed antenna offers high gain, lower noise bandwidth, with better sensitivity and range. The ground choke technique is used for back lobe suppression. The prototype is fabricated on FR 4 substrate using manual fabrication technique. This offers an inexpensive and readily available fabrication. Therefore, fabricated antenna is small size, low cost, easily fabricated and tested for satellite communication. The antenna comprises of two layers, containing a patch radiator and a Metasurface layer with 3x3 rectangular ring resonators. The layers are separated using foam with a 12mm width. The proposed prototype is radiating at 1.575GHz and 2.33GHz with an overall dimension of 85.6 x 68.4 x 15.204 mm. The developed antenna provides a gain of 5.9 dBi. The simulated results are verified using VNA and anechoic chamber testing. Moreover, the developed antenna has been successfully tested for L-Band Satellite communication in real time scenario without any LNA. Higher Gain due to Metasurface increase the efficiency of the system. The promising results indicate the aptness of the developed antenna for real-world applications of L-Band and S-Band.

Melatonin as a master regulatory hormone for genetic responses to biotic and abiotic stresses in model plant Arabidopsis thaliana: a comprehensive review.

Melatonin is a naturally occurring biologically active amine produced by plants, animals and microbes. This review explores the biosynthesis of melatonin in plants, with a particular focus on its diverse roles in Arabidopsis thaliana , a model species. Melatonin affects abiotic and biotic stress resistance in A. thaliana . Exogenous and endogenous melatonin is addressed in association with various conditions, including cold stress, high light stress, intense heat and infection with Botrytis cinerea or Pseudomonas , as well as in seed germination and lateral root formation. Furthermore, melatonin confers stress resistance in Arabidopsis by initiating the antioxidant system, remedying photosynthesis suppression, regulating transcription factors involved with stress resistance (CBF, DREB, ZAT, CAMTA, WRKY33, MYC2, TGA) and other stress-related hormones (abscisic acid, auxin, ethylene, jasmonic acid and salicylic acid). This article additionally addresses other precursors, metabolic components, expression of genes (COR , CBF , SNAT , ASMT , PIN , PR1 , PDF1.2 and HSFA ) and proteins (JAZ, NPR1) associated with melatonin and reducing both biological and environmental stressors. Furthermore, the future perspective of melatonin rich agri-crops is explored to enhance plant tolerance to abiotic and biotic stresses, maximise crop productivity and enhance nutritional worth, which may help improve food security.

Emerging Horizons in the Diagnosis of Pancreatic Cancer: The Role of Circulating microRNAs as Early Detection Biomarkers for Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a poor prognosis, primarily due to a late diagnosis. Recent studies have focused on identifying non-invasive biomarkers for early detection, with microRNAs (miRNAs) emerging as promising candidates. This systematic review aims to evaluate the potential of circulating miRNAs as biomarkers for the early detection of PDAC, analyzing their diagnostic accuracy, specificity, and sensitivity. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search across PubMed, Embase, and the Cochrane Library was conducted. Studies published from January 2013 to October 2023 focusing on miRNA biomarkers for early PDAC detection were included. Data synthesis was performed through a narrative approach due to the heterogeneity of the studies. Nine studies met the inclusion criteria. Key findings include the elevated levels of specific miRNAs, such as miR-18a, miR-106a, and miR-25, in early-stage PDAC patients compared to controls. The integration of miRNA profiles with traditional biomarkers like CA19-9 showed improved diagnostic performance. However, challenges in the standardization of miRNA evaluation methodologies were noted. Circulating miRNAs demonstrate significant potential as non-invasive biomarkers for early PDAC detection. Despite promising results, further research and standardization are necessary for clinical application.

Patient and Therapist Perceptions of a Publicly Funded Internet-Based Cognitive Behavioral Therapy (iCBT) Program for Ontario Adults During the COVID-19 Pandemic: Qualitative Study.

BACKGROUND: To address the anticipated rise in mental health symptoms experienced at the population level during the COVID-19 pandemic, the Ontario government provided 2 therapist-assisted internet-delivered cognitive behavioral therapy (iCBT) programs to adults free of charge at the point of service. OBJECTIVE: The study aims to explore the facilitators of and barriers to implementing iCBT at the population level in Ontario, Canada, from the perspective of patients and therapists to better understand how therapist-assisted iCBT programs can be effectively implemented at the population level and inform strategies for enhancing service delivery and integration into the health care system. METHODS: Using a convenience sampling methodology, semistructured interviews were conducted with 10 therapists who delivered iCBT and 20 patients who received iCBT through either of the publicly funded programs to explore their perspectives of the program. Interview data were analyzed using inductive thematic analysis to generate themes. RESULTS: Six salient themes were identified. Facilitators included the therapist-assisted nature of the program; the ease of registration and the lack of cost; and the feasibility of completing the psychoeducational modules given the online and self-paced nature of the program. Barriers included challenges with the online remote modality for developing the therapeutic alliance; the program's generalized nature, which limited customization to individual needs; and a lack of formal integration between the iCBT program and the health care system. CONCLUSIONS: Although the program was generally well-received by patients and therapists due to its accessibility and feasibility, the digital format of the program presented both benefits and unique challenges. Strategies for improving the quality of service delivery include opportunities for synchronous communication between therapists and patients, options for increased customization, and the formal integration of iCBT into a broader stepped-care model that centralizes patient referrals between care providers and promotes continuity of care.

Incidence of infection in carpal tunnel surgery with and without the use of local antibiotics.

Objectives: To compare the infection rate in patients who underwent carpal tunnel surgery with and without instilling local antibiotics into the surgical wound. METHODS: The retrospective cohort study was conducted at the Department of Surgery, Unit of Neurosurgery, Government Naseer Ullah Babar Memorial Hospital, Peshawar, Pakistan, and comprised data from July 2019 to July 2021 related to non-diabetic patients without any comorbidity who had undergone fresh carpal tunnel surgery. The cases had been operated by two surgeons having a different approach to preventing infection in carpal tunnel surgery cases. The surgeon in group A did not use any local antibiotics after completing the surgery, while the surgeon in group B instilled local gentamicin in the open wound for 3 minutes after completing the nerve release. All patients were put on oral antibiotics for a period of 5 days after the procedure in both the cohorts, and were assessed fortnightly for any infection and removal of stitches. Demographics of the patients, use of antibiotics and the occurrence of infection were recorded on a proforma. Data was analysed using SPSS 20. RESULTS: Of the 177 patients operated during the period, 13(7.3%) were discarded owing to missing data. Of the 164(92.7%) patients analysed, 138(84.14%) were females and 26(15.85%) were males. The overall mean age was 32.46±8.97 years. The total surgeries conducted were 176; 96(54.54%) in group A and 80(45.45%) in group B. Infections were found in 3(1.7%) patients; all in group A (p=0.160). CONCLUSIONS: Although not statistically significant, instillation of local antibiotics may play a role in preventing surgical site infections in carpal tunnel surgery cases.

Evaluating the effectiveness of decomposed Halstead Metrics in software fault prediction.

The occurrence of faults in software systems represents an inevitable predicament. Testing is the most common means to detect such faults; however, exhaustive testing is not feasible for any nontrivial system. Software fault prediction (SFP), which identifies software components that are more prone to errors, seeks to supplement the testing process. Thus, testing efforts can be focused on such modules. Various approaches exist for SFP, with machine learning (ML) emerging as the prevailing methodology. ML-based SFP relies on a wide range of metrics, ranging from file-level and class-level to method-level and even line-level metrics. More granularized metrics are expected to possess a higher degree of micro-level coverage of the code. The Halstead metric suite offers coverage at the line level and has been extensively employed across diverse domains such as fault prediction, quality assessment, and similarity approximation for the past three decades. In this article, we propose to decompose Halstead base metrics and evaluate their fault prediction capability. The Halstead base metrics consist of operators and operands. In the context of the Java language, we partition operators into five distinct categories, i.e., assignment operators, arithmetic operators, logical operators, relational operators, and all other types of operators. Similarly, operands are classified into two classes: constants and variables. For the purpose of empirical evaluation, two experiments were designed. In the first experiment, the Halstead base metrics were used along with McCabe, Lines of Code (LoC), and Halstead-derived metrics as predictors. In the second experiment, decomposed Halstead base metrics were used along with McCabe, LoC, and Halstead-derived metrics. Five public datasets were selected for the experiments. The ML classifiers used included logistic regression, naïve Bayes, decision tree, multilayer perceptron, random forest, and support vector machines. The ML classifiers' effectiveness was assessed through metrics such as accuracy, F-measure, and AUC. Accuracy saw an enhancement from 0.82 to 0.97, while F-measure exhibited improvement from 0.81 to 0.99. Correspondingly, the AUC value advanced from 0.79 to 0.99. These findings highlight the superior performance of decomposed Halstead metrics, as opposed to the original Halstead base metrics, in predicting faults across all datasets.

Harmonizing Medicine and Surgery in the Pursuit of Boolean Remission: A Rheumatological Magnum Opus.

Rheumatic diseases encompass a diverse group of musculoskeletal conditions that often lead to inflammation, pain, and significant limitations in patients' lives. While traditional treatment approaches have primarily centered on medications to control symptoms, recent developments have introduced the concept of Boolean remission. Boolean remission offers a comprehensive evaluation of disease activity by considering clinical, biochemical, and patient-reported outcomes. This narrative review explores the multifaceted landscape of Boolean remission in the context of rheumatic diseases, with a focus on rheumatoid arthritis (RA), as it remains a substantial clinical challenge. The review outlines the definition, criteria, historical context, and development of Boolean remission, shedding light on its emergence as a more patient-centered and stringent treatment goal. The role of pharmacological interventions, including immunomodulators and biologics, in achieving Boolean remission is discussed, emphasizing the significance of treatment protocols that encompass regular monitoring, medication adjustment, shared decision-making, and patient education. Surgical interventions, such as joint replacements and synovectomies, complement medication-based strategies when joint damage becomes severe, with adherence to surgical protocols ensuring sustained Boolean remission. The integration of medicine and surgery through integrated care models and interdisciplinary teams is examined as a critical aspect of optimizing patient outcomes. Boolean remission's broader impact on healthcare policies and clinical trial endpoints is explored, underscoring its growing significance in rheumatic disease management. The review concludes by looking toward the future, where emerging technologies, biomarkers, and personalized medicine approaches hold promise in refining Boolean remission criteria and making it a more attainable and impactful treatment goal. Policy implications suggest the integration of Boolean remission into healthcare quality metrics, incentivizing healthcare providers to prioritize this rigorous standard of care. Boolean remission represents a pivotal shift in the holistic and patient-centered management of rheumatic diseases, offering hope for improved patient outcomes and enhanced quality of life in this challenging clinical landscape.

Epithelioid hepatic angiomyolipoma in pregnancy: A case report.

INTRODUCTION AND IMPORTANCE: Epithelioid hepatic angiomyolipoma (HAML) is a rare benign tumor predominantly found in women. Its occurrence during pregnancy is extremely rare. Accurate diagnosis of HAML is challenging due to its radiological resemblance to other hepatic neoplasms. We present a case of epithelioid HAML in a pregnant patient, highlighting the diagnostic and management challenges encountered. CASE PRESENTATION: A 24-year-old pregnant female, in her fifth month of pregnancy, presented with right hypochondrium pain and nausea. Radiological imaging suggested the possibility of a hepatic adenoma. The patient opted to continue the pregnancy with regular monitoring of the mass as well as fetal health. After delivering a healthy baby, the patient underwent successful mass excision and cholecystectomy. Histopathology of the liver mass confirmed the diagnosis of epithelioid HAML. CLINICAL DISCUSSION: Epithelioid HAML is a rare tumor often misdiagnosed. It is more aggressive and frequently associated with tuberous sclerosis complex (TSC) compared to other subtypes. The diagnosis of HAML can be challenging due to its resemblance to Hepatocellular Carcinoma and other hepatic neoplasms on radiological imaging. Immunohistochemistry plays a crucial role in confirming the diagnosis. Surgical excision is the recommended treatment, with complete removal to minimize the risk of recurrence. CONCLUSION: This case report highlights the rarity of epithelioid HAML during pregnancy and emphasizes the importance of a multidisciplinary approach in managing hepatic neoplasms. Close monitoring is crucial, considering the potential risks to the mother and fetus. Accurate diagnosis through histopathological evaluation, immunohistochemistry and a multidisciplinary approach are essential for appropriate management.

Calcifying Nested Stromal-Epithelial Tumor: An Extremely Rare Hepatic Tumor.

Calcifying nested stromal-epithelial tumor is a rare hepatic malignancy with approximately 50 cases reported in the literature. Its clinical presentation is nonspecific, and the diagnosis is mainly based on histology which shows nests of spindle and epithelioid cells along with a desmoplastic myofibroblastic stroma containing variable calcification and ossification. In this report, we present a case of a 24-year-old woman with a history of abdominal pain, distension, and dyspepsia. She had a palpable liver with normal liver function test results. Serum alpha-fetoprotein levels were within normal range, and serologies for hepatitis B and C virus remained negative. Radiological investigations (magnetic resonance imaging and computed tomography) showed a large, right hepatic lobe mass with tumor invasion into the right posterior portal vein, but the 2 modalities could not characterize the lesion. Finally, an ultrasound-guided biopsy of the liver lesion provided the diagnosis of calcifying nested stromal-epithelial tumor. The tumor was resected successfully.

Donor Safety First: Postoperative Hepatectomy Outcomes in Living Liver Donors.

BACKGROUND: Living donor liver transplantation (LDLT) has become a popular treatment option because some countries lack a deceased organ program and the growing demand for liver transplants. Although postoperative outcomes are similar to deceased donor liver transplants, there is still an element of risk to the donor. The Clavien-Dindo classification system has been used to standardize reporting across different institutions and surgeons to categorize surgical outcomes. METHODS: Between January 1, 2022, and December 31, 2022, 207 living donors underwent hepatectomies at our center. All donors underwent a 3-step process of mandatory screening. Postsurgical complications were classified using the Clavien-Dindo classification. RESULTS: A total of 207 donor hepatectomies for LDLT were performed during our study period. Most donors (92.8%) were aged between 18 and 39 years. The most common type of graft used was a right lobe without the middle hepatic vein (82.6%). Most donors (91.7%) experienced an intraoperative blood loss of ≤500 mL. A total of 140 patients had an ordinary postoperative course. Grade 1 complications were observed in 16.9%, grade 2 in 12.1%, and grade 3 in 3.4% of the remaining patients. No grade 4 or grade 5 (patient death) complications were observed in this cohort. CONCLUSIONS: Living donor liver transplantation remains the most practiced liver transplant surgery in Pakistan. Our findings highlight the safety of the LDLT program with minimal risk of significant complications. The study also underscores the importance of careful screening and monitoring of living donors and the need for standardized reporting of surgical outcomes using the Clavien-Dindo classification system.