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IntroductionThere has been recent introduction of novel lithotripters and high-power lasers for stone disintegration. With miniaturization of PCNL, there is need of effective disintegration and faster stone-clearance. This study aimed to evaluate efficiency of Trilogy™ and Thulium fibre laser (TFL) in mini-percutaneous nephrolithotomy (mini-PCNL).MethodsThis is prospective study comparing efficiency and outcomes of Trilogy™ and TFL in mini-PCNL between January 2019 and February 2020. Primary objective was to compare stone fragmentation rates, with secondary objectives beings stone-free rates and complications.ResultsThere were 60 mini-PCNL with suction using either Trilogy™ or TFL energy source. Mean stone size and density were 27.60 ± 10.17 mm, 22.04 ± 9.69 mm (p = 0.05) and 1172.9 ± 313.5HU, 1308.9 ± 333.9HU (p = 0.10) for Trilogy™ and TFL, respectively. Using 3D doctor imaging software from CT images, mean stone volumes were 3718.9 ± 3038.7mm3 for Trilogy™ and 3425.9 ± 3096.1mm3 for TFL(p = 0.77). Using probe-activation time or lasing time, stone-fragmentation rate was 5.98 ± 4.25mm3/sec for Trilogy™ and 3.95 ± 1.00mm3/sec for TFL(p = 0.015). Treatment time (puncture to complete clearance) was 32.48 ± 15.39 min for Trilogy™ and 28.63 ± 18.56 min for TFL(p = 0.38). Haemoglobin drop was 1.19 ± 0.76gm/dl for Trilogy™ and 0.99 ± 0.74gm/dl for TFL (p = 0.30). Trilogy™ arm had 96.6% complete clearance and TFL had 76.6% in TFL at 48 h. One patient in Trilogy™ arm required auxiliary RIRS for residual stone. Both arms had complete stone clearance at 1 month follow-up. Trilogy™ arm had 3 Clavien–Dindo grade-II complications while TFL had 2 Clavien–Dindo grade-II complications (UTI requiring antibiotics). There was no blood transfusion in either of arm.ConclusionTrilogy™ had significantly better stone fragmentation rate than TFL in managing renal stones. However, stone-free rates and complications were comparable for Trilogy™ and TFL.

PurposeTo report safety and efficacy of mini-PCNL with suction attached to sheath combined with high-power Thulium Fibre laser (TFL). The secondary aim was to evaluate optimal laser settings for maximum stone dusting.Materials and methodsProspective, single arm study was conducted from June 2019–December 2019 using miniPCNL with suction and TFL in 54 patients with renal stones < 3 cm. Stone fragments for each laser setting were independently retrieved and segregated according to size(< 1 mm,1-3 mm, > 3 mm) and weighed. Xray/CT scan imaging was performed in all patients within 48 h and 30 days to assess stone clearance. Optimal laser settings were evaluated for maximum dusting.ResultsMean stone size was 18.32 ± 6.37 mm, volume was 2337.75 ± 1996.84mm3 and stone density was 1300.55 ± 435.32 HU. Total operative time was 39.85 ± 20.52 min, laser time was 10.08 ± 7.41 min and stone fragmentation rate was 5.02 ± 3.93 mm3/s. The procedure was completely tubeless in 37.04%, nephrostomy tube in 37.04% and DJ stent placed in 25.92%. Postoperatively, three patients had urinary infection (Clavien 2). Complete stone clearance at 48 h was achieved in 35 (64.8%) cases. 19 patients (35.2%) who had residual fragments at 48 h, had 100% clearance at one month on CT/Xray KUB.ConclusionsMiniPCNL using a nephrostomy sheath with suction along with high power Thulium Fibre Laser is safe and effective modality for lithotripsy. An initial laser setting of 0.2 J and 125–200 Hz was optimal for maximum dusting and simultaneous aspiration. Randomized comparative studies with other energy sources are being considered.

PurposeUrinary tract infection (UTI) is the most common bacterial infection among infectious complications in kidney transplant recipients (KTR). After transplantation, infections can result from surgical complications, donor-derived infections, pre-existing recipient infections, and nosocomial infections. Post-transplant infection is still a major cause of morbidity, mortality, graft dysfunction and rejection. In this paper, we aimed to review a few compelling questions in kidney transplantation (KTX).MethodsTo identify relevant clinical questions regarding KTX and UTI a meeting was conducted among physicians involved in the KT program in our hospital. After discussion, several clinically relevant questions related to UTI after KTX. The 5 first rated in importance were judged generalizable to other clinical settings and selected for the purposes of this review.ResultsNearly half of the patients present in the first three months of transplant with UTI. The most common uropathogens in post-transplant UTIs are Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis. Risk factors for UTI include female sex, advanced age, recurrent UTI before transplant, prolonged urethral catheterization, delayed graft function, and cadaveric kidney transplant.ConclusionThe incidence of post-transplant UTI is similar in both developed and developing countries. E.coli is the most common pathogen in most of studies. Cadaveric donor and post-dialysis transplantation are defined as independent risk factors for post-transplant UTI. Further studies are still required to identify risk factors after kidney transplantation and UTI’s importance for graft function and patient outcome.

Objective: To understand the cardioprotective effect of Moringa oleifera (MO) seed powder using isoproterenol induced cardiotoxicity in albino rats of wistar strain. Materials and Methods: Hydroalcoholic extract of MO (HAMO) seeds was prepared by soxhlet method and used for the study. After phytochemical analysis, the extract was evaluated for in vivo study. Six rats were grouped. Group 1 as vehicle, group 2 as disease control, group 3 as standard, group 4 and 5 as low and high dose of hydroalcoholic extract of MO (200mg/kg, 400mg/kg) respectively. ECG parameters, cardiac markers and oxidative stress were assessed. Results: 4% yield was obtained. ST segment elevation and increased heart rate by Isoproterenol was treated by hydroalcoholic extract of MO seeds. CK-MB, LDH levels were also restored in treatment groups as compared to disease control. The endogenous antioxidant enzymes catalase and GSH activity increased in treatment groups whereas lipid peroxidation was decreased significantly. The HAMO (400mg/kg) showed better cardioprotective activity as equivalent to Terminalia arjuna tablets which was used as standard. In histology findings, HAMO (400mg/kg) showed decrease in necrosis as compared to disease control. Conclusion: The HAMO (400mg/kg) has proven to attenuate cardiotoxicity induced by Isoproterenol, confirmed by ECG, cardiac markers and histopathological findings.

Every year, the Western Ghats region experiences devastating landslide disasters that are closely linked to the region’s wealth and growth, resulting in the loss of lives and damage to private and public property. Thus, it is important to identify the highly vulnerable places to minimize these losses. The major objective of this present research is to create a reliable landslide susceptibility map for the Gaganbawada region of Western Ghats. Support vector machine (SVM) is the machine learning based algorithm used to demarcate landslide susceptibility zones using a holistic approach of remote sensing and geographical information system. At first, the landslide inventory map is produced using Google Earth images and field studies. A total of 170 landslide (85) and non-landslide (85) points are used for the training and testing dataset, with a ratio of 70% and 30%, respectively. Secondly, 15 landslide influencing factors are selected. The predictive capabilities of the influencing factors are assessed using the information gain ratio and Pearson correlation coefficient to choose the optimal subset of influencing factors. Subsequently, a landslide susceptibility map is produced using the radial basis function kernel of the SVM model. As per the result, 23% of Gaganbawada’s land area is in the high and very high landslip susceptibility zone, and 50% is in the low zone. The susceptibility map represents that only 8% of the land area is in the very high zone, on the other hand, 70.5% of historical landslides have been recorded. The resulting model is validated using the receiver operating characteristic (ROC), and several statistical evaluation matrices. According to the ROC evaluation result, the SVM model has an area under the curve (AUC) value of 0.88, showing that the present machine learning based model has acceptable prediction effectiveness and landslide susceptibility map result is reliable and effective for implementation.

Introduction: COVID-19 pandemic is associated with secondary opportunistic fungal infections. These have an aggressive course with a high mortality rate. We present our experience of seven cases of post-COVID-19 fungal pyelonephritis. Methods: An observational study over a period of 8 months of May to December 2021 was carried out at our tertiary care hospital, including all patients with features of fungal pyelonephritis in post-COVID-19 setting. The patient demographics, details of previous COVID-19 infection, details of present admission and management were collected. The endpoints were either discharge from the hospital or death. Results: Seven patients were included. Mean age of presentation was 42 years (range: 20-63 years, standard deviation ± 14.2). Male-to-female ratio was 6:1. One patient was diabetic. Two patients were asymptomatic, one had mild infection, and four patients had severe COVID-19 infection as per National Institute of Health criteria. In the present admission, all patients had symptomatic pyelonephritis with laboratory parameters showing elevated D dimer, C reactive protein, and total leukocyte counts. In all seven patients, ultrasound of kidney ureter bladder region showed bulky kidney, color Doppler showed main renal arterial thrombosis in two patients, segmental arterial thrombosis in another patient. Computed tomography scan was suggestive of changes of pyelonephritis in all patients with multiple renal hypodense areas. All patients required nephrectomy with biopsy suggestive of changes of necrotizing fungal inflammation. Three patients expired. Conclusion: Management of post-COVID-19 fungal pyelonephritis should be aggressive and suspicious laboratory and imaging findings should be treated by early nephrectomy.

Being considered among the most fatal neurological conditions, Creutzfeldt-Jakob disease is a transmissible spongiform encephalopathy characterized by its unknown etiology and rapidly progressive neurodegenerative symptoms that often lead to a mean survival of 6 to 12 months. The accumulation of the prionic protein causes brain matter degeneration, which leads to a set of clinical findings that include rapidly progressive dementia, myoclonus, tremors, cerebellar ataxia, and extrapyramidal signs. This clinical presentation is non-specific, which makes CJD a very difficult condition to diagnose, due to the low level of clinical suspicion. However, combining this clinical presentation with neuroimaging, a lumbar puncture and an encephalogram will help us make the correct diagnosis. We present the case of a 57-year-old male presenting to the Emergency department with complaint of personality change and intermittent memory loss. The patient's physical exam was significant for resting pill roll tremor, bilateral cogwheel rigidity, dysmetria, and shuffling gait. Magnetic resonance imaging of his brain showed symmetric bilateral diffusion signal abnormality involving the cortex, bilateral caudate heads and putamina. Continuous electroencephalogram revealed multiple bifrontal delta discharges with triphasic morphology. Lumbar puncture was significant for presence of 14–3-3 protein in cerebrospinal fluid. The multiple examinations performed in conjunction with the previous findings supported the diagnosis of acute encephalopathy secondary to sporadic CJD.

Purpose This study aims to uncover recent research trends and primary focal points associated with the use of drones in the application of fertilizers and pesticides within the agricultural sector. The research seeks to explore the global impact of agricultural drones, highlighting their benefits in reshaping traditional farming practices and promoting sustainable agriculture. Methodology A bibliometric analysis was conducted, reviewing 46 academic publications from 2015. This comprehensive review aggregated findings related to the use of drones in fertilizers and pesticides applications, focusing on the advancements, benefits, and future potential of drone technology in modern agriculture. Results The integration of drones in agriculture has shown a notable reduction in pesticide usage, ranging from 30 to 65% compared to conventional methods like knapsack spraying. Additionally, the application of pesticides and fertilizers via drones has led to crop yield increases of 3.6% to 9.7%, thereby enhancing food production. Drones have also demonstrated effectiveness in pest control, with rates between 63.7% and 94.94%, reducing the reliance on chemical pesticides. Furthermore, drones contribute to significant water conservation, with potential reductions in water usage by up to 90%. The ability to cover 2 to 6 hectares per hour enables rapid response to agricultural challenges, improving pest and disease management. Conclusions Drones offer substantial benefits in modern agriculture, promoting eco-friendly practices, enhancing efficiency, and contributing to sustainable food production. The future of agricultural drone technology lies in enhancing capabilities such as extended flight durations, increased payload capacities, and integrating artificial intelligence for data-driven decision-making. These advancements are likely to encourage the widespread adoption of drones, fostering sustainable, efficient, and environmentally friendly agricultural practices on a global scale.

PurposeSingle-use disposable digital flexible ureterorenoscope has become an attractive option to reusable scope with many advantages. Currently available single-use digital fURS have outer shaft diameter above 9 Fr which requires large access sheath insertion and sometimes double J stent placement. Recently, 7.5 Fr single-use digital fURS is introduced in market by Pusen. Objective of this study is to compare two Pusen single-use scopes in the clinical setting: 7.5 Fr Uscope PU3033A and 9.5 Fr Uscope PU3022A.Methods30 patients, having renal stones < 2 cm, planned for RIRS were prospectively randomized to two groups: group 1 had 15 patients in which 7.5 Fr Uscope PU3033A and group 2 had 15 patients in which 9.5 Fr Uscope PU3022A was used. The various pre-operative, intra-operative, and post-operative parameters at 1 month along with complications were evaluated for both the scopes by a single surgical team.ResultsPre-operative parameters including stone characteristics were comparable in both the groups. Three patients in group 2 needed ureteric dilatation prior to 11/13 access sheath insertion, while 10/12 Fr access sheath was placed in all patients in group 1 without manipulation (p = 0.06). Intra-operative vision was comparable in both scopes with an empty working channel and with laser. Hazy vision while lasing in two and one patient in group 1 and group 2, respectively (p = 0.54). In group 1, one had fever and UTI, while in group 2, one had fever post-operatively.Conclusion7.5 Fr Uscope PU3033A could be introduced with smaller access sheath. The vision, deflection, maneuverability is comparable to 9.5 Fr Uscope PU3022a.

PurposeWith the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network and by reducing the latency of transmitted data. The communications in IIoT and Industry 4.0 requires handshaking of multiple technologies for supporting heterogeneous networks and diverse protocols. IIoT applications may gather and analyse sensor data, allowing operators to monitor and manage production systems, resulting in considerable performance gains in automated processes. All IIoT applications are responsible for generating a vast set of data based on diverse characteristics. To obtain an optimum throughput in an IIoT environment requires efficiently processing of IIoT applications over communication channels. Because computing resources in the IIoT are limited, equitable resource allocation with the least amount of delay is the need of the IIoT applications. Although some existing scheduling strategies address delay concerns, faster transmission of data and optimal throughput should also be addressed along with the handling of transmission delay. Hence, this study aims to focus on a fair mechanism to handle throughput, transmission delay and faster transmission of data. The proposed work provides a link-scheduling algorithm termed as delay-aware resource allocation that allocates computing resources to computational-sensitive tasks by reducing overall latency and by increasing the overall throughput of the network. First of all, a multi-hop delay model is developed with multistep delay prediction using AI-federated neural network long–short-term memory (LSTM), which serves as a foundation for future design. Then, link-scheduling algorithm is designed for data routing in an efficient manner. The extensive experimental results reveal that the average end-to-end delay by considering processing, propagation, queueing and transmission delays is minimized with the proposed strategy. Experiments show that advances in machine learning have led to developing a smart, collaborative link scheduling algorithm for fairness-driven resource allocation with minimal delay and optimal throughput. The prediction performance of AI-federated LSTM is compared with the existing approaches and it outperforms over other techniques by achieving 98.2% accuracy.Design/methodology/approachWith an increase of IoT devices, the demand for more IoT gateways has increased, which increases the cost of network infrastructure. As a result, the proposed system uses low-cost intermediate gateways in this study. Each gateway may use a different communication technology for data transmission within an IoT network. As a result, gateways are heterogeneous, with hardware support limited to the technologies associated with the wireless sensor networks. Data communication fairness at each gateway is achieved in an IoT network by considering dynamic IoT traffic and link-scheduling problems to achieve effective resource allocation in an IoT network. The two-phased solution is provided to solve these problems for improved data communication in heterogeneous networks achieving fairness. In the first phase, traffic is predicted using the LSTM network model to predict the dynamic traffic. In the second phase, efficient link selection per technology and link scheduling are achieved based on predicted load, the distance between gateways, link capacity and time required as per different technologies supported such as Bluetooth, Wi-Fi and Zigbee. It enhances data transmission fairness for all gateways, resulting in more data transmission achieving maximum throughput. Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation.FindingsOur proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. It also shows that AI- and IoT-federated devices can communicate seamlessly over IoT networks in Industry 4.0.Originality/valueThe concept is a part of the original research work and can be adopted by Industry 4.0 for easy and seamless connectivity of AI and IoT-federated devices.