bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthetic Biology: The New Era
Authors: Samudra Guha  , Joyeeta Talukdar  , Abhibrato Karmakar  , Sandeep Goswami  , Arun Kumar  , Ruby Dhar  , Karmakar Subhradip 
Published: April 2022

Synthetic biology is an emerging discipline of science, at the intersection of biology, engineering, and chemistry that involves redesigning organisms to have new phenotypes and customized abilities. While synthetic biology seems to have originated from genetic engineering, over the years, it has matured as well as diverged from it. It involves not just the transfer of genes from one or cell to another creating some variants, it also involves the assembly of an altogether novel organism or cell created part by part by the assembly of individual components of the desired function in a logical fashion. In this minireview, we will explore this new discipline and its possible applications and future promises to serve the humanity
The Impact of Job Enrichment on Job Satisfaction of Local Government Workers in Temeke Municipal Council of Tanzania
Authors: Wilfred Uronu Lameck  
Published: April 2022

This study examines the impact of job enrichment on employee job satisfaction of local government workers in Tanzania. Specifically, the study examines how job characteristics, job meaningfulness, job responsibilities, and knowledge about job results impact employee job satisfaction. The target population of the study is 4000 employees of Temeke Municipal Council in Tanzania from which a sample of 396 respondents were drawn using a stratified simple random sampling technique. Temeke Municipal Council was selected since it is one of the biggest municipalities where the workers are highly dissatisfied due to the big workload and the pressure from the central bureaucracy, but it is not clear to what extent job enrichment is affecting job satisfaction. The data were collected through a self-administered questionnaire with closed-ended questions and analyzed quantitatively using descriptive statistics and regression analysis with the aid of STATA software. The findings show that job enrichment impacts positively on employees' job satisfaction because all the variables of job enrichments show a strong positive and statistically significant relationship with job satisfaction. This study recommends that job satisfaction among employees of the organizations could be increased through enriching their jobs focusing on job characteristics, job meaningfulness, job responsibilities, and knowledge about job results.
Keywords: Job Enrichment, Job Satisfaction, Local Government Workers, Tanzania
Changing Dynamics of Gender Inequality in the Context of COVID-19 Pandemic in India
Authors: Debahuti Brahmachari  
Published: April 2022

With the second-largest nation in terms of population, India has been one of the most affected countries by the COVID-19 pandemic. One of the repercussions of the ongoing pandemic can be noticed in terms of the widened deeply embedded gender inequalities in India. The post-recovery period would be immensely complex. The fear that the world is witnessing is the amplification of the existing gender gap or inequality. The pandemic has once again proven that the ill effects have a differential impact on both the sexes. Hence, an attempt through this research has been made to understand the changing dynamics of gender inequality in India due to the impact of COVID-19. The main objective of the paper is to find out the devastating impact of COVID-19 on the socio-economic structures that enhance the existing gender inequality, and how far it has impacted the deeply embedded gender inequalities. In this regard, qualitative research methods with descriptive analysis have been used. The literature and narratives available related to various dimensions of gender inequality have been reviewed to understand the differential impacts of the pandemic on women. The need to have an engendering governance outlook has been highlighted. No public health approach should neglect the gendered impact of such a crisis. The research tries to sum up with proactive strategy recommendations that the state should embark upon both as long-term and short-term goals.
Keywords: COVID-19, Pandemic, Gender, Women, Governance, Equality
Respectful Conduct in Public School Community in Sri Lanka: Exploring the Policy and Program Framework
Authors: Visakesa Chandrasekaram  
Published: April 2022

In organizational development literature, ‘Respectful conduct’ refers to acceptable standards of behavior rejecting violence, discrimination, bullying, or harassment. In a workplace setting, respectful conduct is ensured by introducing policies on behavioral standards, remedies to address policy breaches, and programs to build staff capacities to implement such policies. A growing body of evidence demonstrates that disrespectful conduct is a common problem in public schools in Sri Lanka, and the school system is poorly equipped to address the issue. Clarifying the existing laws concerning respectful conduct, this article explores policy reforms, remedial pathways, and program mechanisms to solve the problem. The key research question posed in this article is ‘what policy and program initiatives are required to ensure respectful conduct in schools under the existing legal setting in Sri Lanka?’ This research aims to identify gaps in existing policy and program frameworks and propose policy measures to fill the gaps based on the international best practices. The methodology adopted in this study includes a survey of local and international literature on the problem of institutional level disrespectful conduct and appropriate solutions. This study also consists of a policy review conducted by collating the instruments currently being applied in the public school system. Based on the analysis, this study proposes several components of a policy framework, including remedial pathways supplemented by a program mechanism to implement such policies in public schools in Sri Lanka.
Keywords: Discrimination, Harassment, Bullying, Violence, Respect, Schools, Policies, Programs
Risk Evaluation on Security Personnel Managing Illegal Detainees in a Makeshift Covid-19 Low Risk Quarantine and Treatment Centre
Authors: Rusli Mohammad Farhan , Abd Rahman Anita , Moideen Mohd Arshil , Erlendawati Mohd Anuar  , Mahabot Fuad Ridha , Wan Mustapha Wan Mohd Harith , Abd Samad@Mahmood Md Anuar 
Published: April 2022

Background: The COVID-19 pandemic situation in Malaysia has resulted in a whole country approach where a newly built makeshift low risk Covid-19 treatment centre was chosen to house all COVID-19 positive illegal immigrants. In view of the desperate situation the detained illegal immigrants were in as the risks of them behaving aggressively, taking hostage, running away and escaping from the treatment centre were high this is the first time ever other governmental, non-governmental and security agencies worked alongside healthcare personnel in a biological hazard treatment centre while the clinical management was of no different than any other clinical setup in the country.
Methodology: This is a semi-quantitative and integrated type of hazard identification, risk assessment and risk control (HIRARC) approach where it incorporates risk rating and severity rating to cover four elements, which are people, property, environment, and reputation. Total scores range from 1 to 25 and was further categorized into low, medium and high risk in a color-coded representation. The assessment was done for two weeks from 27th May 2020 till 11th June 2020.
Result & Discussion: Four types of occupational and security hazards identified were physical, biological, psychological and ergonomics hazards. this evaluation serves as a good planning tool in optimizing the risk mitigation measures among security personnel working in a biological hazardous environment. Physical hazards with possible violence and riot scored the highest risk while ergonomic issues had the lowest rating.
Conclusion: The mapping combination of existing hazard, risk rating and control was able to facilitate organization to prioritise future planning. With the fluidity of the COVID-19 pandemic, periodical evaluation is recommended to meet dynamic changes such as demands for frontliner manpower strength, the number of existing detainee patients in ward and the evolution of the COVID-19 infection itself to maintain safety and security for all.
Differentiation of lumbar disc herniation and lumbar spinal stenosis using natural language processing–based machine learning based on positive symptoms
Authors: Ren GuanRui , Yu Kun , Xie ZhiYang , Liu Lei , Wang PeiYang , Zhang Wei , Wang YunTao , Wu XiaoTao 
Published: April 2022

OBJECTIVE
The purpose of this study was to develop natural language processing (NLP)–based machine learning algorithms to automatically differentiate lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) based on positive symptoms in free-text admission notes. The secondary purpose was to compare the performance of the deep learning algorithm with the ensemble model on the current task.

METHODS
In total, 1921 patients whose principal diagnosis was LDH or LSS between June 2013 and June 2020 at Zhongda Hospital, affiliated with Southeast University, were retrospectively analyzed. The data set was randomly divided into a training set and testing set at a 7:3 ratio. Long Short-Term Memory (LSTM) and extreme gradient boosting (XGBoost) models were developed in this study. NLP algorithms were assessed on the testing set by the following metrics: receiver operating characteristic (ROC) curve, area under the curve (AUC), accuracy score, recall score, F1 score, and precision score.

RESULTS
In the testing set, the LSTM model achieved an AUC of 0.8487, accuracy score of 0.7818, recall score of 0.9045, F1 score of 0.8108, and precision score of 0.7347. In comparison, the XGBoost model achieved an AUC of 0.7565, accuracy score of 0.6961, recall score of 0.7387, F1 score of 0.7153, and precision score of 0.6934.

CONCLUSIONS
NLP-based machine learning algorithms were a promising auxiliary to the electronic health record in spine disease diagnosis. LSTM, the deep learning model, showed better capacity compared with the widely used ensemble model, XGBoost, in differentiation of LDH and LSS using positive symptoms. This study presents a proof of concept for the application of NLP in prediagnosis of spine disease.
A novel surgical planning system using an AI model to optimize planning of pedicle screw trajectories with highest bone mineral density and strongest pull-out force
Authors: Ma Chi , Zou Da , Qi Huan , Li Chentian , Zhang Cheng , Yang Kedi , Zhu Feng , Li Weishi , Lu William W. 
Published: April 2022

OBJECTIVE
The purpose of this study was to evaluate the ability of a novel artificial intelligence (AI) model in identifying optimized transpedicular screw trajectories with higher bone mineral density (BMD) as well as higher pull-out force (POF) in osteoporotic patients.

METHODS
An innovative pedicle screw trajectory planning system called Bone’s Trajectory was developed using a 3D graphic search and an AI-based finite element analysis model. The preoperative CT scans of 21 elderly osteoporotic patients were analyzed retrospectively. The AI model automatically calculated the number of alternative transpedicular trajectories, the trajectory BMD, and the estimated POF of L3–5. The highest BMD and highest POF of optimized trajectories were recorded and compared with AO standard trajectories.

RESULTS
The average patient age and average BMD of the vertebral bodies were 69.6 ± 7.8 years and 55.9 ± 17.1 mg/ml, respectively. On both sides of L3–5, the optimized trajectories showed significantly higher BMD and POF than the AO standard trajectories (p < 0.05). On average, the POF of optimized trajectory screws showed at least a 2.0-fold increase compared with AO trajectory screws.

CONCLUSIONS
The novel AI model performs well in enabling the selection of optimized transpedicular trajectories with higher BMD and POF than the AO standard trajectories.
Boosting phase-contrast MRI performance in idiopathic normal pressure hydrocephalus diagnostics by means of machine learning approach
Authors: Vlasák Aleš , Gerla Václav , Skalický Petr , Mládek Arnošt , Sedlák Vojtěch , Vrána Jiří , Whitley Helen , Lhotská Lenka , Beneš Vladimír , Beneš Vladimír , Bradáč Ondřej 
Published: April 2022

OBJECTIVE
Phase-contrast MRI allows detailed measurements of various parameters of CSF motion. This examination is technically demanding and machine dependent. The literature on this topic is ambiguous. Machine learning (ML) approaches have already been successfully utilized in medical research, but none have yet been applied to enhance the results of CSF flowmetry. The aim of this study was to evaluate the possible contribution of ML algorithms in enhancing the utilization and results of MRI flowmetry in idiopathic normal pressure hydrocephalus (iNPH) diagnostics.

METHODS
The study cohort consisted of 30 iNPH patients and 15 healthy controls examined on one MRI machine. All major phase-contrast parameters were inspected: peak positive, peak negative, and average velocities; peak amplitude; positive, negative, and average flow rates; and aqueductal area. The authors applied ML algorithms to 85 complex features calculated from a phase-contrast study.

RESULTS
The most distinctive parameters with p < 0.005 were the peak negative velocity, peak amplitude, and negative flow. From the ML algorithms, the Adaptive Boosting classifier showed the highest specificity and best discrimination potential overall, with 80.4% ± 2.9% accuracy, 72.0% ± 5.6% sensitivity, 84.7% ± 3.8% specificity, and 0.812 ± 0.047 area under the receiver operating characteristic curve (AUC). The highest sensitivity was 85.7% ± 5.6%, reached by the Gaussian Naive Bayes model, and the best AUC was 0.854 ± 0.028 by the Extra Trees classifier.

CONCLUSIONS
Feature extraction algorithms combined with ML approaches simplify the utilization of phase-contrast MRI. The highest-performing ML algorithm was Adaptive Boosting, which showed good calibration and discrimination on the testing data, with 80.4% accuracy, 72.0% sensitivity, 84.7% specificity, and 0.812 AUC. Phase-contrast MRI boosted by the ML approach can help to determine shunt-responsive iNPH patients.
Machine learning to predict passenger mortality and hospital length of stay following motor vehicle collision
Authors: Kolcun John Paul G. , Covello Brian , Gernsback Joanna E. , Cajigas Iahn , Jagid Jonathan R. 
Published: April 2022

OBJECTIVE
Motor vehicle collisions (MVCs) account for 1.35 million deaths and cost $518 billion US dollars each year worldwide, disproportionately affecting young patients and low-income nations. The ability to successfully anticipate clinical outcomes will help physicians form effective management strategies and counsel families with greater accuracy. The authors aimed to train several classifiers, including a neural network model, to accurately predict MVC outcomes.

METHODS
A prospectively maintained database at a single institution’s level I trauma center was queried to identify all patients involved in MVCs over a 20-year period, generating a final study sample of 16,287 patients from 1998 to 2017. Patients were categorized by in-hospital mortality (during admission) and length of stay (LOS), if admitted. All models included age (years), Glasgow Coma Scale (GCS) score, and Injury Severity Score (ISS). The in-hospital mortality and hospital LOS models further included time to admission.

RESULTS
After comparing a variety of machine learning classifiers, a neural network most effectively predicted the target features. In isolated testing phases, the neural network models returned reliable, highly accurate predictions: the in-hospital mortality model performed with 92% sensitivity, 90% specificity, and a 0.98 area under the receiver operating characteristic curve (AUROC), and the LOS model performed with 2.23 days mean absolute error after optimization.

CONCLUSIONS
The neural network models in this study predicted mortality and hospital LOS with high accuracy from the relatively few clinical variables available in real time. Multicenter prospective validation is ultimately required to assess the generalizability of these findings. These next steps are currently in preparation.
Resection of petroclival clear cell meningioma by the anterior transpetrosal approach: diagnosis of rare pathology and improvement of preoperative hearing disturbance
Authors: Matsushima Ken , Kohno Michihiro , Nakajima Nobuyuki , Ichimasu Norio , Onodera Sho , Akimoto Jiro 
Published: April 2022

Clear cell meningioma is a rare histological variant of meningioma, which often recurs aggressively. This video demonstrates a patient with a petroclival clear cell meningioma, which was resected completely through the anterior transpetrosal approach. The absence of intratumoral spotty signal voids on preoperative susceptibility-weighted imaging (SWI) suggested that the tumor was a meningioma rather than a schwannoma, although typical imaging features of meningioma were not observed. After surgery, the patient’s preoperative hearing disturbance improved from class D to class A, which the authors had sometimes experienced in cerebellopontine angle meningioma surgeries. Careful observation over a 2.5-year period revealed no tumor recurrence, without additional treatment.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21219
Combined petrosal approach for resection of a large left petroclival meningioma
Authors: Paglia Francesco , Giammattei Lorenzo , di Russo Paolo , Froelich Sebastien 
Published: April 2022

Petroclival meningiomas represent the most complex lesions in skull base surgery, being closely related to critical neurovascular structures. The combined petrosal approach allows a wide exposure of the petroclival region and provides multiple angles of attack, limiting brain retraction.
The authors present the case of a 54-year-old man with a large left petroclival meningioma responsible for headaches, dysphagia, and trigeminal neuralgia. The lesion was resected using a combined petrosal approach. A progressive improvement of the preoperative symptoms was observed. Postoperative MRI showed a near-total resection of the tumor, along with reexpansion of the brainstem.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21226
Right posterior petrosectomy for resection of petroclival meningioma
Authors: Vakharia Kunal V. , Naylor Ryan M. , Hasegawa Hirotaka , Nassiri Ashley M. , Driscoll Colin L. W. , Link Michael J. 
Published: April 2022

Petroclival meningiomas, which arise from the upper two-thirds of the clivus and are medial to the trigeminal nerve, carry significant surgical risk. Patients whose operations are tailored to maximize tumor resection while minimizing neurological morbidity have favorable outcomes. Subtotally resected tumors can be subsequently considered for radiosurgery in an attempt to limit recurrence. Here the authors report the case of a 40-year-old woman with postpartum trigeminal neuropathy secondary to a petroclival meningioma. The patient underwent an aggressive subtotal resection via a posterior petrosal approach with preservation of neurological function followed by adjuvant radiosurgery.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21227
Endoscopic endonasal transpetroclival approach for recurrent bilateral petroclival meningioma
Authors: Shinya Yuki , Shin Masahiro , Hasegawa Hirotaka , Koizumi Satoshi , Kin Taichi , Kondo Kenji , Saito Nobuhito 
Published: April 2022

The authors performed an endoscopic endonasal transpetroclival approach for recurrent bilateral petroclival meningioma, with the aim of sufficient tumor resection with cranial nerve functional preservation. The tumor was sufficiently removed with excellent postoperative course. Petroclival meningioma, especially located in the medial region with dural attachment of the clivus, is considered a good indication for this approach. Recurrent tumors after radiotherapy often have strong adhesion to the brainstem and basilar artery; therefore, careful assessment of whether or not tumor detachment is possible is essential. The endoscopic endonasal transpetroclival approach is an acceptable, less-invasive treatment for petroclival tumors.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21229
Microsurgical resection of a large petroclival meningioma via translabyrinthine approach combined with middle fossa craniotomy
Authors: Keleş Abdullah , Armstrong Stephanie Alyse , Sayyahmelli Sima , Gürbüz Mehmet Sabri , Başkaya Mustafa Kemal 
Published: April 2022

Petroclival meningiomas arise from the upper two-thirds of the clivus at the petroclival junction and are reached via various approaches. As petroclival meningiomas expand, they displace the brainstem and basilar artery toward the contralateral side. Because of their proximity to critical structures and deep skull base location, surgical treatment is challenging. Although several approaches have been introduced, their rationales vary. Herein, the authors demonstrate microsurgical resection of a large petroclival meningioma via a translabyrinthine approach combined with middle fossa craniotomy. For each approach, the pros and cons should be carefully evaluated based on the patient’s presentation and lesion characteristics.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21253
Modified Dolenc-Kawase anterior petrous rhomboid approach for petroclival meningioma: surgical nuances and complication avoidance
Authors: Suri Ashish , Sharma Ravi , Katiyar Varidh , Raheja Amol 
Published: April 2022

Resection of petroclival meningiomas has remained challenging because of the critical neurovascular structures that lie in the vicinity, and thus various surgical corridors have been explored over time to figure out the optimum approach. In this video, the authors have highlighted the operative nuances of the modified Dolenc-Kawase (MDK) anterior petrous rhomboid approach. This approach gives access to the prepontine area, Dorello’s canal, anterior petrous apex, and upper two-thirds of the clivus with better angulation and surgical flexibility. It is a versatile approach for petroclival lesions that are not extending laterally and inferiorly to the internal auditory canal.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21256
Endoscopic-assisted combined transcrusal anterior petrosal approach for resection of large petroclival meningioma: operative video and nuances of technique
Authors: Tayebi Meybodi Ali , Liu James K. 
Published: April 2022

In this illustrative video, the authors demonstrate an endoscopic-assisted combined transcrusal anterior petrosal approach for resection of a large petroclival meningioma with significant brainstem compression involving Meckel’s cave. This unique petrosal variant provides increased petroclival exposure that can potentially preserve hearing by combining a transcrusal labyrinthectomy with anterior petrosectomy (Kawase’s approach). The advantages include multidirectional angles of attack to the brainstem and petroclival region without cerebellar retraction. Endoscopic assistance allows expanded visualization into deep surgical corridors. The surgery was performed in a two-stage fashion, and a near-total resection was achieved with cranial nerve and hearing preservation. The operative nuances are demonstrated.
The video can be found here: https://stream.cadmore.media/r10.3171/2022.1.FOCVID21257