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Multiaxial involvement in neurological cases poses a diagnostic challenge even to the astute clinician. We present the case of a young man with multiple cranial nerve palsies, brain stem involvement, and subacutely progressive polyradiculoneuropathy. In addition, he had unexplained intractable vomiting, lymphadenopathy, and splenomegaly. These atypical features prompted us to evaluate for a secondary or systemic cause of polyneuropathy. Evaluation with neuroimaging and bone marrow examination revealed the underlying cause to be pre-T-cell acute lymphoblastic leukemia (pre-T-ALL). While acute lymphoblastic leukemia (ALL) is known to cause central nervous system involvement, such extensive multiaxial involvement as the first presentation in an adult is extremely rare. In this report, we describe the diagnostic approach to such a case and review the literature.

Abstract The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status from clinical notes in the Epic electronic health records system. The primary outcome was the classification of infant feeding status from clinical notes using Medical Subject Headings (MeSH) terms. Annotation of notes was completed using TeamTat to uniquely classify clinical notes according to infant feeding status. We trained 6 machine learning models to classify infant feeding status: logistic regression, random forest, XGBoost gradient descent, k-nearest neighbors, and support-vector classifier. Model comparison was evaluated based on overall accuracy, precision, recall, and F1 score. Our modeling corpus included an even number of clinical notes that was a balanced sample across each class. We manually reviewed 999 notes that represented 746 mother-infant dyads with a mean gestational age of 38.9 weeks and a mean maternal age of 26.6 years. The most frequent feeding status classification present for this study was exclusive breastfeeding [n = 183 (18.3%)], followed by exclusive formula bottle feeding [n = 146 (14.6%)], and exclusive feeding of expressed mother’s milk [n = 102 (10.2%)], with mixed feeding being the least frequent [n = 23 (2.3%)]. Our final analysis evaluated the classification of clinical notes as breast, formula/bottle, and missing. The machine learning models were trained on these three classes after performing balancing and down sampling. The XGBoost model outperformed all others by achieving an accuracy of 90.1%, a macro-averaged precision of 90.3%, a macro-averaged recall of 90.1%, and a macro-averaged F1 score of 90.1%. Our results demonstrate that natural language processing can be applied to clinical notes stored in the electronic health records to classify infant feeding status. Early identification of breastfeeding status using NLP on unstructured electronic health records data can be used to inform precision public health interventions focused on improving lactation support for postpartum patients.

Abstract Background Reaching hard to reach populations is key to reduce health inequities. Despite targeted interventions, status of crucial public health indicators like neonatal and maternal mortality is still far from optimal. Complex interplay of social determinants can influence both communities and health care workers to effectively access each other. We argue that culturally sensitive and contextually relevant healthcare provision has potential to increase health care utilization by the vulnerable communities living in remote areas. Methods The study is an exploratory case study using rapid ethnographic techniques to understand the interplay of social determinants in hard to reach areas of Odisha state, India. We used in-depth interviews, focus group discussion, participatory action research and key informant interviews as tools for data collection. The analysis of data has been guided by thematic analysis approach. Results We found that there are further layers within the designated hard to reach areas and those can be designated as-i) extremely remote ii) remote and iii) reachable areas. Degree of geographic difficulties and cultural dynamics are deciding the ‘perceived’ isolation and interaction with health care providers in hard to reach areas. This ultimately leads to impacting the utilization of the facilities. At extremely remote areas, felt health needs are mainly fulfilled by traditional healers and ethno-medical practices. In reachable areas, people are more prone to seek care from the public health facilities because of easy accessibility and outreach. Being in middle people in remote areas, diversify health care seeking depending upon social (e.g. patient’s gender) economic (e.g. avoid catastrophic expenditure) and health system (timely availability of health human resources, language barriers) factors. Conclusion Our research highlights the need to value and appreciate different worldviews, beliefs and practices, and their understanding of and engagement with the pluralistic health care system around them. Other than pursuing the ‘mainstreaming’ of a standardized health system model across hard to reach areas, strategies need to be adaptive as per local factors. To handle that existing policies need revision with a focus on culturally sensitive and contextual care provision.

ABSTRACT Regulatory small RNAs (sRNAs) play large-scale and essential roles in many cellular processes across all domains of life. Microbial sRNAs have been extensively studied in model organisms, but very little is known about the dynamics of sRNA synthesis and their roles in the natural environment. In this study, we discovered hundreds of intergenic (itsRNAs) and antisense (asRNAs) sRNAs expressed in an extremophilic microbial community inhabiting halite nodules (salt rocks) in the Atacama Desert. For this, we built SnapT, a new sRNA annotation pipeline that can be applied to any microbial community. We found asRNAs with expression levels negatively correlated with that of their overlapping putative target and itsRNAs that were conserved and significantly differentially expressed between 2 sampling time points. We demonstrated that we could perform target prediction and correlate expression levels between sRNAs and predicted target mRNAs at the community level. Functions of putative mRNA targets reflected the environmental challenges members of the halite communities were subjected to, including osmotic adjustments to a major rain event and competition for nutrients. IMPORTANCE Microorganisms in the natural world are found in communities, communicating and interacting with each other; therefore, it is essential that microbial regulatory mechanisms, such as gene regulation affected by small RNAs (sRNAs), be investigated at the community level. This work demonstrates that metatranscriptomic field experiments can link environmental variation with changes in RNA pools and have the potential to provide new insights into environmental sensing and responses in natural microbial communities through noncoding RNA-mediated gene regulation.

Systemic lupus erythematosus (SLE) can present with varied neurological manifestations in children. Guillain–Barre syndrome (GBS) as a presenting feature of SLE is quite rare in children. We report a 9-year-old girl who presented with acute motor axonal polyradiculoneuropathy and noticed to have features of SLE. She was initially treated with intravenous immunoglobulins and corticosteroids with partial response. After starting rituximab, she showed dramatic recovery, proving the role of rituximab in GBS refractory to first-line medications in SLE. She remained in remission after 12 months of follow-up.

Continuous brachial plexus nerve block catheters are commonly inserted for postoperative analgesia after upper extremity surgery. Modifications of the insertion technique have been described to improve the safety of placing an infraclavicular brachial plexus catheter. Rarely, these catheters may become damaged or entrapped, complicating their removal. We describe a case of infraclavicular brachial plexus catheter entrapment related to differences in arm positioning during catheter placement and removal. Written authorization to obtain, use, and disclose information and images was obtained from the patient.