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Background: Linezolid-resistant Enterococcus faecium (LRE) is a global priority pathogen. Thirteen LRE were reported from clinical specimens between November 2021 and April 2023 at two laboratories in Karachi, Pakistan. We aimed to investigate the strain types and genes associated with linezolid resistance among these isolates. Whole genome sequencing (WGS) was performed and analyzed by multilocus sequence typing (MLST). The presence of linezolid resistance genes was identified using ResFinder v4.1.11 and the LRE-finder tool. Results: Twelve isolates belonged to clonal complex 17 (CC17); ST80 (n = 10), ST612 (n = 1) and ST1380 (n = 1). Six isolates showed the presence of optrA gene and G2576T mutations in the 23S rRNA gene, while six showed poxtA and cfr(D) genes. One isolate showed the combination of optrA, cfr(D) and poxtA genes. Conclusion: Our findings show the circulation of CC17 sequence types with a known outbreak potential and we identified molecular mechanisms of resistance that were not previously reported from Pakistan. [ABSTRACT FROM AUTHOR]

Background: The provision of dental care in Pakistan is limited, with less than 5% of the population having access to qualified dental practitioners. The lack of contextually relevant local dental guidelines further adds to the problem. We developed clinical practice guidelines (CPGs) and referral pathways to improve primary care for common oral diseases. Methods: Using the GRADE-ADOLOPMENT approach, recommendations from source guidelines (developed in Europe and the United States) were adopted (retained as is or with minor changes), adapted (modified according to the local context), or excluded (omitted due to lack of local relevance). The guidelines included diseases such as periodontitis, dental pain, intraoral swelling, and oral cavity malignancies. The end result was a set of locally relevant CPGs, which were then used to formulate referral pathways, with the incorporated suggestions being based on a thorough evidence review process. Results: We included four recommendations, three of which were adopted with minor modifications to the referral pathway. These changes focused on assessing potentially malignant oral conditions and counseling for risk factors. No content changes were needed for the CPGs of the other two disorders. We developed referral pathways for three specific oral conditions, detailing primary care physicians' roles in diagnosis, initial treatment, and timely referral. Conclusion: Contextually relevant dental CPGs and referral pathways can improve patient outcomes in Pakistan. Our study produced four additional recommendations focused on risk factor counselling and mitigation, which could potentially reduce the burden of oral malignancies in our local population. [ABSTRACT FROM AUTHOR]

Background: Burnout, characterized by emotional exhaustion (EX), depersonalization (DP), and a reduced sense of personal efficacy (PF) among medical and nursing students can lead to suicidal ideation, lack of empathy, and dropouts. Previous studies have used over-simplified definitions of burnout that fail to capture its complexity. We describe the prevalence of burnout profiles and its risk factors among medical and nursing students. Methods: A cross sectional study was conducted at a tertiary care University Hospital in Pakistan. The Maslach Burnout Inventory (MBI) survey was disseminated via SurveyMonkey over a period of 4 months (November 2019 to February 2020) to 482 Medical and 441 nursing students. The MBI tool measures the dimensions of EX, DP, and PF to describe seven burnout profiles. Multivariable regression was used to identify predictors of burnout. Results: The response rate was 92% in nursing and 87.3% in medical students. The prevalence of burnout in medical and nursing students was 16.9% and 6.7% respectively (p<0.001), with 55.7% (n = 427) suffering from at least one burnout profile. Only 32.5% (n = 250) students felt engaged, (42.3% medical, 22.7% nursing students, p<0.001). The most common profile was ineffective (32.5%, n = 250), characterized by a reduced sense of personal efficacy (35.6% medical, 29.4% nursing students; p = 0.065). Medical students were at higher risk of burnout compared to nursing students (OR = 2.49 [1.42, 4.38]; p<0.001) with highest risk observed in year 4 (OR = 2.47 [1.02, 5.99]; p = 0.046). Other risk factors for burnout included occasional drug use (OR = 1.83 [1.21, 8.49]; p = 0.017) and living in a hostel (OR = 1.64 [1.01,2.67]; p = 0.233). Conclusion and relevance: Two-thirds of our participants experienced at least one dimension of burnout with the highest prevalence of a reduced sense of PF. Drivers of burnout unique to a lower-middle-income country need to be understood for effective interventions. Faculty training on principles of student evaluation and feedback may be beneficial. [ABSTRACT FROM AUTHOR]

Background: Advances in molecular imaging strategies have had an effect on precise diagnosis and treatment. Research has been intensified to develop more effective and versatile radiopharmaceuticals to uplift diagnostic efficiency and, consequently, the treatment. Purpose: To label the flutamide (FLUT) coupled with diethylenetriamine pentaacetate (DTPA) with technetium-99 m (99mTc) and to evaluate its binding efficiency with rhabdomyosarcoma (RMS) cancer cells. Material and methods: Radiolabeling of FLUT with 185 MBq freshly eluted 99mTcO4−1 was carried out via DTPA bifunctional chelating agent using stannous chloride reducing agent at pH 5. The labeled compound was assessed for its purity using chromatography analysis, stability in saline and blood serum, AND charge using paper electrophoresis. Normal biodistribution was studied using a mouse model, while binding affinity with RMS cancer cells was studied using an internalization assay. The in vivo accumulation of RMS cancer cells in a rabbit model was monitored using a SPECT gamma camera. Results: Radiolabeling reaction displayed a pharmaceutical yield of 97% and a stability assay showed >95% intact radiopharmaceutical up to 6 h in saline and blood serum. In vitro internalization studies showed the potential of [99mTc]DTPA-FLUT to enter into cancer cells. This biodistribution study showed rapid blood clearance and minimum uptake by body organs, and scintigraphy displayed the [99mTc]DTPA-FLUT uptake by lesion, induced by RMS cancer cell lines in rabbit. Conclusion: Stable, newly developed [99mTc]DTPA-FLUT seeks its way to internalize into RMS cancer cells, indicating it could be a potential candidate for the diagnosis of RMS cancer. [ABSTRACT FROM AUTHOR]

The present study demonstrates laser bending which is a flexible and (external) tool-free method for bending and shaping of metallic components. The numerical and experimental analysis of the bending behaviors of Ti-6Al-4V titanium alloy sheets has been done under the constant line energy concept. Numerical simulations using Abaqus examine the transient temperature fields, thermal stress, strain, and deformation characteristics. To validate the numerical calculations and observe the effects of process parameters such as laser powers and scanning speeds on the bending capability, the experimental analysis has been conducted and compared with the numerical simulations. In addition, the influence of laser irradiation on the surface morphology of the laser-scanned specimens has been observed by scanning electron microscope (SEM). The findings show that higher line energy causes significant enhancement in bending deformation. The maximum numerical and experimental bending angles of 0.91° and 0.88° have been observed at the line energy of 15 J/mm, respectively. The average percentage deviation of 5.24% has been observed between the numerical and experimental results at the line energy of 15 J/mm. Moreover, melting, thermal oxidation, and crack propagations have been observed during the SEM analysis at high laser power. The numerical simulation and experimental outcomes are helpful for the selection of optimum process conditions in the laser bending method of Ti-6Al-4V sheets. [ABSTRACT FROM AUTHOR]

Implementing lean manufacturing practices in the systematic layout planning (SLP) process for improving facility layouts in various industries is essential. This approach enhances material handling processes and effectively manages space utilization. An efficient plant employing systematic layout planning leads to improved resource utilization and facilitates the integration of lean manufacturing techniques such as value stream mapping, 5 S, Ohno's 7 wastes, and cellular manufacturing. This research article presents a case study on a steel processing plant in Dubai with an area of 160 m × 160 m, where systematic layout planning and lean manufacturing techniques were applied. The factors considered included space and material flow optimization, incorporating layout alternatives based on systematic layout planning principles along with lean manufacturing techniques. The study revealed a 34% reduction in material flow and an efficient overall space utilization improvement of 26%. Additionally, cost analysis validation was conducted. [ABSTRACT FROM AUTHOR]

Background: Patients with traumatic brain injury (TBI) constitute a highly heterogeneous population, with varying risks for New-onset Psychiatric Disorders (NPDs). The objectives of this study were to identify TBI phenotypes and determine how NPDs differ among these phenotypes. Methods: Hospitalized TBI patients from 2003 to 2019 were obtained from the provincial trauma registry. Propensity score matching was conducted to balance covariates among patients with TBI and controls. To uncover heterogeneity in TBI, latent class analysis (LCA)-based clustering was applied. LCA was conducted separately for two TBI cohorts: those with and without pre-injury psychiatric conditions The effect of classes on NPDs was assessed using log binomial regression models. Results: A total of 3,453 patients with TBI and 13,112 controls were included in the analysis. In a conditional regression involving propensity matched patients with TBI and controls, TBI was significantly associated with the development of NPD-A (OR: 2.78; 95% CI: 2.49–3.09), as well as NPD-P (OR: 2.36; 95% CI: 2.07–2.70). Eight distinct latent classes were identified which differed in the incidence of NPDs. Four classes displayed a 53% (RR:1.53; 95% CI: 1.31–1.78), 48% (RR:1.48; 95% CI: 1.26–1.74), 28% (RR:1.28; 95% CI: 1.08–1.54), and 20% (RR: 1.20, 95%CI: 1.03–1.39), increased NPD risk. Conclusion: TBI is a significant predictor of NPDs. There are clinically distinguishable phenotypes with different patterns of NPD risk among patients with TBI. Identifying individuals with respect to their phenotype may improve risk stratification of patients with TBI and promote early intervention for psychiatric care in this vulnerable population. [ABSTRACT FROM AUTHOR]

This paper presents the design and isolation enhancement of a filtering MIMO antenna with a radiation null for out-of-band suppressions suited for 5G sub-6 GHz communications. The MIMO antenna offers -10 dB impedance bandwidth functionality at the most prominent partial spectrum of the 5G NR n78 band for enabling wireless applications in base stations, ranging from 3.4 GHz to 3.61 GHz. To mitigate the redundancy of an RF filter and to achieve a strong filtering response, a radiation null is produced in the gain with four identical rectangular slots, which results in a significant gain drop of more than 8 dBi at the stopband. The geometrical design also allows 30 percent size reduction of single element. Subsequently, a closely spaced (0.11λ0) two-port MIMO antenna is implemented and with the utilization of the proposed rectangular shaped hollow stub parasitic element, the interelement isolation is significantly improved by more than 8 dB over the operational frequency range while retaining the filtering without any additional RF structure. The design simplification, peak gain of 5.4 dBi, near ideal response of diversity gain, ECC less than 0.03, congruency between simulated and measured results, and stable parameters make it a valuable choice for 3.5 GHz sub-6 GHz communications. [ABSTRACT FROM AUTHOR]

In this study, we address the critical need for enhanced situational awareness and victim detection capabilities in Search and Rescue (SAR) operations amidst disasters. Traditional unmanned ground vehicles (UGVs) often struggle in such chaotic environments due to their limited manoeuvrability and the challenge of distinguishing victims from debris. Recognising these gaps, our research introduces a novel technological framework that integrates advanced gesture-recognition with cutting-edge deep learning for camerabased victim identification, specifically designed to empower UGVs in disaster scenarios. At the core of our methodology is the development and implementation of the Meerkat Optimization Algorithm--Stacked Convolutional Neural Network--Bi--Long Short Term Memory--Gated Recurrent Unit (MOASConv-Bi-LSTM-GRU) model, which sets a new benchmark for hand gesture detection with its remarkable performance metrics: accuracy, precision, recall, and F1-score all approximately 0.9866. This model enables intuitive, real-time control of UGVs through hand gestures, allowing for precise navigation in confined and obstacle-ridden spaces, which is vital for effective SAR operations. Furthermore, we leverage the capabilities of the latest YOLOv8 deep learning model, trained on specialised datasets to accurately detect human victims under a wide range of challenging conditions, such as varying occlusions, lighting, and perspectives. Our comprehensive testing in simulated emergency scenarios validates the effectiveness of our integrated approach. The system demonstrated exceptional proficiency in navigating through obstructions and rapidly locating victims, even in environments with visual impairments like smoke, clutter, and poor lighting. Our study not only highlights the critical gaps in current SAR response capabilities but also offers a pioneering solution through a synergistic blend of gesture-based control, deep learning, and purposebuilt robotics. The key findings underscore the potential of our integrated technological framework to significantly enhance UGV performance in disaster scenarios, thereby optimising life-saving outcomes when time is of the essence. This research paves the way for future advancements in SAR technology, with the promise of more efficient and reliable rescue operations in the face of disaster. [ABSTRACT FROM AUTHOR]

The Asian region of earth has a rich agriculture system that provides extensive opportunities to boost pharmaceutical and nutritional research to address the use of food crops for health benefits and potential clinical applications. The traditionally cropped green leaf vegetable indigenously known as Bathu and botanically known as Chenopodium album (C. album) is traditionally used as a sedative, blood purifier, hepatoprotectant, diuretic, and antiscorbutic laxative. In this study, we investigated the anti-infection potential, anti-diabetic potential, and mineral composition of indigenously cultivated C. album plant extracts. Methanol and n-hexane solvents were used to extract phytochemicals at different extraction conditions. The maximum yield of 12.72 ± 0.36 g/100 g extract was obtained in methanol with 200 rpm shaking, 200 mL solvent, and an 8 h extraction period. Under the same conditions, n-hexane gave 2.09 ± 0.29 g/100 g extract. Good alpha-amylase inhibition efficiency was shown by the n-hexane extracts, while the methanol extracts showed good urease inhibition potential. The H6 extract had the lowest IC50 (8.16 ± 0.2 ug/mL) as compared to the standard acarbose (9.27 ± 0.6 ug/mL). Similarly, the M6 extract revealed a significant urease inhibitory potential, i.e., IC50 of 18.77 ± 0.6 ug/mL, which was close to the standard thiourea (IC50: 19.09 ± 0.7 ug/mL). Regarding the antibacterial study, the M6 extract showed 16.55 ± 0.57 mm ZOI against E. coli and 15.54 ± 0.55 mm in the case of S. aureus, as compared to the standard ciprofloxacin, which showed 26.08 ± 0.73 mm, and penicillin, which showed 21.12 ± 0.81 mm ZOI. Mineral profiling was investigated by ICP-OES, which showed significant amounts of Mg and Fe in all extracts. Our findings tend to show that systematic harvesting and utilization of this vegetable crop could be recommended as an alternative nutritional therapy in the management of internal infections and diabetes. [ABSTRACT FROM AUTHOR]

This study compares the fatigue crack growth (FCG) behavior of Ti6Al4V parts fabricated by laser powder bed melting (LPBF) with four build directions (0°, 30°, 60°, and 90°) and two heat treatments and analyzed the effect of build direction and microstructure on FCG. The results show that the build direction has a significant effect on the FCG rate. Particularly, specimens with 90° build direction have the best FCG resistance while the 0° specimens have the worst. Furthermore, the fragile deposition layer boundary is the main cause of the crack deflection. The microstructure shows that the columnar β grains have less effect on FCG. The increase in resistance to FCG after heat treatment is attributed to the lath‐like α grains consuming the energy for FCG. As compared to needle‐like α′ grains, the lath‐like α grains are more likely to initiate intergranular fracture and secondary cracking, leading to rugged crack tip paths. Highlights: The effect of build direction on FCG of LPBF‐Ti6Al4V part is significant.The heat‐treated lath‐like α grains have better resistance to FCG.Cracks tend to expand in the direction of parallel deposition layers.Secondary cracking is related to build direction and microstructure. [ABSTRACT FROM AUTHOR]

In recent years, climate policy has experienced several episodes of crest and trough in the US, which has induced profound uncertainty. This climate policy uncertainty (CPU) may exert economic, social, and environmental impacts. Therefore, using the environmental Kuznets curve (EKC) framework, this study targets to probe whether CPU affects sectoral carbon dioxide emissions (COE) in the US. We make use of advanced econometric procedures such as the novel SOR unit root test (to probe the order of integration of the entire dataset) and the novel Fourier ARDL approach (to retrieve the long- and short-run estimates). The findings delineate that the EKC holds for the industrial, electric power, commercial, and residential sectors. In addition, CPU escalates COE in the residential, commercial, and electric power sectors in both the long- and short-run. Parallel to this, CPU affects industrial COE neither in the short-run nor in the long-run. Keeping in view the key findings, we propose a set of sector-specific policy implications to curb COE. [ABSTRACT FROM AUTHOR]