Late recovery of phrenic nerve palsy in a neonate: A case report

Hyperextension of the neck at birth can injure the phrenic nerve and/or brachial plexus usually at the point where the phrenic nerve crosses the brachial plexus. We present a case of the preterm baby, who had Erb’s palsy and diaphragmatic paralysis since birth after breech delivery. Persistent respiratory distress and chest X-ray gave a clue to diagnosis, which was confirmed on ultrasound. The baby recovered on the conservative approach at 2 months of life without surgical plication. This study describes that late spontaneous recovery up to 2 months is possible in a newborn with respiratory distress due to phrenic nerve palsy

Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd.

Recent technological developments allow us to measure the status of dozens of proteins in individual cells. This opens the way to understand the heterogeneity of complex multi-signaling networks across cells and cell types, with important implications to understand and treat diseases such as cancer. These technologies are, however, limited to proteins for which antibodies are available and are fairly costly, making predictions of new markers and of existing markers under new conditions a valuable alternative. To assess our capacity to make such predictions and boost further methodological development, we organized the Single Cell Signaling in Breast Cancer DREAM challenge. We used a mass cytometry dataset, covering 36 markers in over 4,000 conditions totaling 80 million single cells across 67 breast cancer cell lines. Through four increasingly difficult subchallenges, the participants predicted missing markers, new conditions, and the time-course response of single cells to stimuli in the presence and absence of kinase inhibitors. The challenge results show that despite the stochastic nature of signal transduction in single cells, the signaling events are tightly controlled and machine learning methods can accurately predict new experimental data

Posteromedial varus fatigue fragment (PVFF) in severe varus knee osteoarthritis phenotype: incidence, surgical implications, and management

Purpose: Severe varus knee osteoarthritis (OA) alters weight-bearing mechanics, leading to progressive stress concentration on the posteromedial tibial plateau. In select cases, this results in the development of a Posteromedial Varus Fatigue Fragment (PVFF), a chronic stress-related fracture that remains ununited and influences knee stability, surgical planning, and implant selection. This study aims to evaluate the incidence, radiographic detectability, and intraoperative significance of PVFF in patients undergoing total knee arthroplasty (TKA). Methods: A retrospective analysis was conducted of 856 consecutive TKA cases performed by a single surgeon. Preoperative radiographs, intraoperative findings, and surgical modifications were assessed to determine the incidence and implications of PVFF. Correlation with varus severity and absence of ACL was done. Results: PVFF was detected intraoperatively in 17 of 856 cases (1.99%), but only 9 (53%) were visible on pre-op imaging.” All PVFF cases exhibited varus alignment exceeding 15° and complete ACL deficiency. Intraoperatively, fragment removal resulted in an increased medial flexion gap, impacting gap balancing and necessitating adjustments in implant selection, including the use of tibial stems or augments in select cases. Conclusion: PVFF is an underrecognized structural lesion for precision in severe varus knee OA, affecting tibial fixation, load distribution, and medial knee stability. Its presence requires careful intraoperative assessment, as fragment removal can alter gap balancing. Improved preoperative recognition and surgical planning are essential to optimize TKA outcomes in patients. Further prospective studies and biomechanical analyses are needed to better understand PVFF’s long-term clinical implications and refine surgical strategies

Augmented Intelligence in Joint Replacement Surgery: How can artificial intelligence (AI) bridge the gap between the man and the machine?

AbstractRobot-assisted arthroplasty is likely to grow exponentially in the years to come. While most surgeons recognize their superiority in refining alignment and improving component positioning accuracy, the universal adaptability of robots remains slow due to certain technological and behavioural gaps. Endoprosthesis robots currently suffer from increased reaction time, lack of natural adaptation to the surgeon's abilities, and unavailability and inapplicability in different surgical contexts. As humans and machines have to move forward into the next phase of their relationship, robots enabled with artificial intelligence (AI) may become more advanced and an alternative to overcome existing challenges like cost, training, and improve performance based on feedback provided by surgeons. Augmented intelligence is perhaps a more apt word than artificial, as it reflects more human-machine fusion and several areas are already proactively adopting the terminology. Arthroplasty robots can benefit from AI by using computer vision models, applying sensors, and integrating feedback and loop execution. All of this would help achieve a technical superiority to the surgeon alone. This brief perspective on how humans and machines are likely to benefit from the integration of AI outlines the technical side of this enablement.</jats:p

A Knowledge and Practices study of health hazards among animal handlers in zoological gardens

Background- Close association with animals makes zookeepers a high risk group for suffering from various zoonotic diseases. Thus, it is important that they are able to protect themselves from these diseases and injuries through prevention awareness. Objective- To study the knowledge, attitude and practices regarding health hazards among animal handlers in zoological gardens. Materials and Methods- A questionnaire based cross-sectional study conducted in the National Zoological Park, New Delhi, India involving all 66 employees, including 49 who were directly involved in taking care of animals. Result- About 86% of the total participants perceived a risk of suffering from disease or injury due to animal handling. Allergies, tuberculosis and bird flu were commonly perceived risks from animal handling. Majority (69.7%) suggested isolation of animals with infectious diseases. About 65% and 37% were vaccinated for tetanus and rabies respectively. Headache (83.3%), itching (80.3%) and vomiting (77.3%) were the most commonly stated symptoms of zoonotic diseases. While handling animals 59.2% had at least once got injured, after which they were mostly taken to the doctor (79.3%). Only 24.5% had attended training program on zoonotic diseases. Conclusion- There were many lacunae in the knowledge and practices of animal handlers regarding prevention, control and treatment of zoonotic disease and injuries due to animal handling. Training sessions for prevention of zoonotic diseases and injuries are absent. It is important that these issues are addressed promptly and adequately. Also, such study must be conducted in other zoos as situation analysis activity to plan training programmes. DOI: http://dx.doi.org/10.3126/ijosh.v4i1.914