Tumor-related denervation pseudohypertrophy of the tongue: A clinical entity in disguise!

Isolated hypoglossal nerve palsy in the base of tongue carcinomas is seldom noticed. The clinical signs are subtle in early stageand can often be overlooked. There may be slight tongue deviation to the affected side, and the tongue feels soft and edematouson careful palpation. There may be associated enlargement of the affected side of the tongue known as “pseudo hypertrophy” dueto denervation of its motor supply. Contrast-enhanced magnetic resonance imaging is the gold standard of diagnosis which showsdiffuse fatty changes in the affected half of tongue with the preservation of architecture. Clinicians need to be aware of this clinicalentity to distinguish it from actual tumor invasion

Fertility-Sparing Approaches in Atypical Endometrial Hyperplasia and Endometrial Cancer Patients: Current Evidence and Future Directions

Endometrial cancer (EC) is the fourth most common cancer in women in developed countries. Although it is usually diagnosed in postmenopausal women, its incidence has increased in young women, as well in recent decades, with an estimated rate of 4% in those under 40 years of age. Factors involved in this increase, particularly in resource-rich countries, include delayed childbearing and the rise in obesity. The new molecular classification of EC should help to personalize treatment, through appropriate candidate selection. With the currently available evidence, the use of oral progestin either alone or in combination with other drugs such as metformin, levonorgest-relreleasing intrauterine devices and hysteroscopic resection, seems to be feasible and safe in women with early-stage EC limited to the endometrium. However, there is a lack of high-quality evidence of the efficacy and safety of conservative management in EC. Randomized clinical trials in younger women and obese patients are currently underway

Fertility-Sparing Approaches in Atypical Endometrial Hyperplasia and Endometrial Cancer Patients : Current Evidence and Future Directions

Endometrial cancer (EC) is the fourth most common cancer in women in developed countries. Although it is usually diagnosed in postmenopausal women, its incidence has increased in young women, as well in recent decades, with an estimated rate of 4% in those under 40 years of age. Factors involved in this increase, particularly in resource-rich countries, include delayed childbearing and the rise in obesity. The new molecular classification of EC should help to personalize treatment, through appropriate candidate selection. With the currently available evidence, the use of oral progestin either alone or in combination with other drugs such as metformin, levonorgestrel-releasing intrauterine devices and hysteroscopic resection, seems to be feasible and safe in women with early-stage EC limited to the endometrium. However, there is a lack of high-quality evidence of the efficacy and safety of conservative management in EC. Randomized clinical trials in younger women and obese patients are currently underway

Frozen Section Evaluation in Head and Neck Oncosurgery: An Initial Experience in a Tertiary Cancer Center

Objective: Frozen section evaluation is routinely used by oncosurgeons across specialties for rapid assessment of the presence of tumor in any tissue and its most common use is in surgical margins. Today, the use of intraoperative frozen-section evaluation of surgical margins is an accepted and frequent practice in head and neck oncology. This study aims to determine the efficacy and accuracy of frozen sections in head and neck cancer patients and compare the results with the respective paraffin sections and also to analyze the reasons for any disparity between them. Material and Method: A retrospective study was conducted to evaluate efficacy and accuracy of frozen section in head and neck cancer of 265 patients, treated at a tertiary cancer centre hospital between January 2013 to December 2014. Results: Out of 265 cases, it was found that 12.6% of these sections showed true positivity, 6.3% false positivity, 2.9% false negativity and 78.2% true negativity. The study also shows a sensitivity of 82.05% and specificity of 96.46%. Conclusion: Our study shows that intraoperative frozen section reports are specific and highly sensitive. We recommend a minimum of 3-4 sections, optimum cryostat temperature, good section thickness and quality staining for a good concordance rate

Evolutionary Dynamics of Large Systems

Several socially and economically important real-world systems comprise large numbers of interacting constituent entities. Examples include the World Wide Web and Online Social Networks (OSNs). Developing the capability to forecast the macroscopic behavior of such systems based on the microscopic interactions of the constituent parts is of considerable economic importance. Previous researchers have investigated phenomenological forecasting models in such contexts as the spread of diseases in the real world and the diffusion of innovations in the OSNs. The previous forecasting models work well in predicting future states of a system that are at equilibrium or near equilibrium. However, forecasting non-equilibrium states– such as the transient emergence of hotspots in web traffic–remains a challenging problem. In this thesis we investigate a hypothesis, rooted in Ludwing Boltzmann’s celebrated Htheorem, that the evolutionary dynamics of a large system–such as the World Wide Web–is driven by the system’s innate tendency to evolve towards a state of maximum entropy. Whereas closed systems may be expected to evolve towards a state of maximum entropy, most real-world systems are not closed. However, the stipulation that if a system is closed then it should asymptotically approach a state of maximum entropy provides a strong constraint on the inverse problem of formulating the microscopic interaction rules that give rise to the observed macroscopic behavior. We make the constraint stronger by insisting that, if closed, a system should evolve monotonically towards a state of maximum entropy and formulate microscopic interaction rules consistent with the stronger constraint. We test the microscopic interaction rules that we formulate by applying them to two real world phenomena: the flow of web traffic in the gaming forums on Reddit and the spread of Covid-19 virus. We show that our hypothesis leads to a statistically significant improvement over the existing models in predicting the traffic flow in gaming forums on Reddit. Our interaction rules are also able to qualitatively reproduce the heterogeneity in the number of COVID-19 cases across the cities around the globe. The above experiments provide supporting evidence for our hypothesis, suggesting that our approach is worthy of further investigation. In addition to the above stochastic model, we also study a deterministic model of attention flow over a network and establish sufficient conditions that, when met, signal imminent parabolic accretion of attention at a node

Autonomy, AI Perception and Safety : A Safety Evaluation Framework for AI Perception Models Used In Agricultural Autonomous Vehicles

Autonomous vehicle technology has seen rapid development thanks to advances in artificial intelligence. Among the various sectors, agriculture is one sector that is testing the potential of autonomous vehicle robots to meet the growing demands of society. Cutting or "Mowing" grass is one potential application that can be automated with AI-driven vehicles on large farms to increase efficiency. However, the increasing reliance on artificial intelligence models for decision-making, such as for navigation, raises the question of how safe these models are and how we can assess the safety of such algorithms. As the safety of AI is still an open challenge, very little research has addressed this problem, and even less in the field of agriculture. The aim of this work is to develop a framework for evaluating the safety of AI perception models used in autonomous vehicle robots in agriculture. The proposed methodology evaluates safety in three main stages: sub-system level, system-level, and post-deployment, along with a preliminary stage for defining boundaries. The feasibility of the framework was also tested on an AI perception system present in a prototype autonomous mowing vehicle to identify areas of safety concern. Autonom fordonsteknologi har haft en snabb utveckling tack vare framstegen inom konstgjord intelligens. Bland de olika sektorerna är jordbruk en sektor som testar potentialen för autonoma fordonsrobotar för att möta samhällets växande krav. Skär eller "Mowing" gräs är en potentiell applikation som kan automatiseras med AI-drivna fordon på stora gårdar för att öka effektiviteten. Det ökande beroendet av modeller för konstgjord intelligens för beslutsfattande, till exempel för navigering, väcker emellertid frågan om hur säkra dessa modeller är och hur vi kan bedöma säkerheten för sådana algoritmer. Eftersom AI: s säkerhet fortfarande är en öppen utmaning har mycket lite forskning tagit upp detta problem och ännu mindre inom jordbruksområdet. Syftet med detta arbete är att utveckla en ram för utvärdering av säkerheten för AI-uppfattningsmodeller som används i autonoma fordonsrobotar i jordbruket. Den föreslagna metodologin utvärderar säkerheten i tre huvudsteg: delsystemnivå, systemnivå och efterutplacering, tillsammans med ett preliminärt steg för att definiera gränser. Ramens genomförbarhet testades också på ett AI-uppfattningssystem som finns i ett prototyp autonomt klippfordon för att identifiera områden med säkerhetsproblem

Autonomy, AI Perception and Safety : A Safety Evaluation Framework for AI Perception Models Used In Agricultural Autonomous Vehicles

Autonomous vehicle technology has seen rapid development thanks to advances in artificial intelligence. Among the various sectors, agriculture is one sector that is testing the potential of autonomous vehicle robots to meet the growing demands of society. Cutting or "Mowing" grass is one potential application that can be automated with AI-driven vehicles on large farms to increase efficiency. However, the increasing reliance on artificial intelligence models for decision-making, such as for navigation, raises the question of how safe these models are and how we can assess the safety of such algorithms. As the safety of AI is still an open challenge, very little research has addressed this problem, and even less in the field of agriculture. The aim of this work is to develop a framework for evaluating the safety of AI perception models used in autonomous vehicle robots in agriculture. The proposed methodology evaluates safety in three main stages: sub-system level, system-level, and post-deployment, along with a preliminary stage for defining boundaries. The feasibility of the framework was also tested on an AI perception system present in a prototype autonomous mowing vehicle to identify areas of safety concern. Autonom fordonsteknologi har haft en snabb utveckling tack vare framstegen inom konstgjord intelligens. Bland de olika sektorerna är jordbruk en sektor som testar potentialen för autonoma fordonsrobotar för att möta samhällets växande krav. Skär eller "Mowing" gräs är en potentiell applikation som kan automatiseras med AI-drivna fordon på stora gårdar för att öka effektiviteten. Det ökande beroendet av modeller för konstgjord intelligens för beslutsfattande, till exempel för navigering, väcker emellertid frågan om hur säkra dessa modeller är och hur vi kan bedöma säkerheten för sådana algoritmer. Eftersom AI: s säkerhet fortfarande är en öppen utmaning har mycket lite forskning tagit upp detta problem och ännu mindre inom jordbruksområdet. Syftet med detta arbete är att utveckla en ram för utvärdering av säkerheten för AI-uppfattningsmodeller som används i autonoma fordonsrobotar i jordbruket. Den föreslagna metodologin utvärderar säkerheten i tre huvudsteg: delsystemnivå, systemnivå och efterutplacering, tillsammans med ett preliminärt steg för att definiera gränser. Ramens genomförbarhet testades också på ett AI-uppfattningssystem som finns i ett prototyp autonomt klippfordon för att identifiera områden med säkerhetsproblem

Predicting donor-related factors for high platelet yield donations by classification and regression tree analysis

Introduction: Collecting high-dose (HD) or double-dose (DD) apheresis platelets units from a single collection offers significant benefit by improving inventory logistics and minimizing the cost per unit produced. Platelet collection yield by apheresis is primarily influenced by donor factors, but the cell separator used also affects the collection yield. Objectives: To predict the cutoff in donor factors resulting in HD and DD platelet collections between Trima/Spectra Optia and MCS+ apheresis equipment using Classification and Regression Trees (CART) analysis. Methods: High platelet yield collections (target ≥ 4.5 × 1011 platelets) using MCS+, Trima Accel and Spectra Optia were included. Endpoints were ≥ 6 × 1011 platelets for DD and ≥ 4.5 to < 6 × 1011 for HD collections. The CART, a tree building technique, was used to predict the donor factors resulting in high-yield platelet collections in Trima/Spectra Optia and MCS+ equipment by R programming. Results: Out of 1,102 donations, the DDs represented 60% and the HDs, 31%. The Trima/Spectra Optia predicted higher success rates when the donor platelet count was set at ≥ 205 × 103/µl and ≥ 237 × 103/µl for HD and DD collections. The MCS+ predicted better success when the donor platelet count was ≥ 286 × 103/µl for HD and ≥ 384 × 103/µl for DD collections. Increased donor weight helped counter the effects of lower donor platelet counts only for HD collections in both the equipment. Conclusions: The donor platelet count and weight formed the strongest criteria for predicting high platelet yield donations. Success rates for collecting DD and HD products were higher in the Trima/Spectra Optia, as they require lower donor platelet count and body weight than the MCS+

Utility of squash smear cytology in fiber-optic bronchoscopic biopsies

Background: Fiber-optic bronchoscopic biopsies yield very small bits of tissue, leading to high false negativity in lung cancer diagnosis, after paraffin embedding. Aim: The aim of the present study is to assess the diagnostic efficacy of squash smear cytology of fiber-optic bronchoscopic biopsies and to compare this with standard paraffin embedded sections and sputum cytology. Materials and Methods: A total of 100 suspected cases of lung cancer were subjected to fiber-optic bronchoscopic biopsies. Multiple biopsies from each were divided into two portions. One portion was processed routinely and paraffin sections made. Squash smears were made from the other and stained by Papanicolaou method. The diagnostic efficiency of two methods was compared. A positive diagnosis of cancer by any of the diagnostic modalities initially or during 6 months follow-up was taken as the gold standard. Results: Out of 100 cases, 91 cases proved to be cancer. The pick-up rate was 0.77 for squash cytology, 0.55 for tissue sections, and 0.31 for sputum cytology. The pick-up was higher for endo-bronchial tumors by all methods. The agreement between squash cytology and tissue sections was 100% for small cell carcinoma and adenocarcinoma and 88% for squamous cell carcinoma. Conclusion: Squash smear cytology has better pick-up rate than paraffin embedding in fiber-optic bronchoscopic biopsies and should be the preferred method when only one or few bits are available